PHYSIOLOGICAL CONSEQUENCES OF CIRCADIAN DISRUPTION BY NIGHTTIME LIGHT
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PHYSIOLOGICAL CONSEQUENCES OF CIRCADIAN DISRUPTION BY NIGHTTIME LIGHT EXPOSURE DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Laura K. Fonken Graduate Program in Neuroscience The Ohio State University 2013 Dissertation Committee: Dr. Randy J. Nelson, Advisor Dr. A. Courtney DeVries Dr. Jonathan P. Godbout Dr. Dana M. McTigue
Transcript of PHYSIOLOGICAL CONSEQUENCES OF CIRCADIAN DISRUPTION BY NIGHTTIME LIGHT
PHYSIOLOGICAL CONSEQUENCES OF CIRCADIAN DISRUPTION BY
NIGHTTIME LIGHT EXPOSURE
DISSERTATION
Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy
in the Graduate School of The Ohio State University
By
Laura K. Fonken
Graduate Program in Neuroscience
The Ohio State University
2013
Dissertation Committee:
Dr. Randy J. Nelson, Advisor
Dr. A. Courtney DeVries
Dr. Jonathan P. Godbout
Dr. Dana M. McTigue
Copyright by
Laura K. Fonken
2013
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ABSTRACT
For more than 3 billion years, life outside the highest latitudes has evolved under
brightly illuminated days and dark nights. Most organisms have developed endogenously
driven circadian rhythms which are synchronized to this light/dark cycle. In recent years,
daily light schedules have become artificial and irregular due to the use of electric
lighting. In this dissertation, I propose that exposure to light at night (LAN) disrupts the
circadian system altering metabolic, immunological, and behavioral functions.
The global increase in the prevalence of obesity and metabolic disorders coincides
with increases in exposure to LAN and shift work. Therefore, my first experiments
examined whether exposure to LAN affects metabolism. Mice exposed to dimly lit (5
lux) as compared to dark nights increased body mass and reduced glucose processing
without changing caloric intake or activity. Exposure to dim light at night diminished the
daily rhythm in food intake and restricting food access to the dark phase prevented
weight gain in mice exposed to dimly lit nights (Chapter 2). Furthermore, metabolic
changes associated with exposure to LAN are not permanent; placing mice back in dark
nights partially reversed increases in body mass caused by exposure to dim light at night
(Chapter 3). In Chapters 4 & 5, I investigated the interactions among LAN and more
traditional risk factors for obesity such as high fat diet and lethargy.
Because light is the most potent synchronizing factor for the circadian system and
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disruption in clock genes is associated with significant changes in metabolism, I next
investigated the effects of exposure to LAN on the circadian system (Chapter 6).
Exposure to dimly lit nights attenuated core circadian clock rhythms in both the master
circadian pacemaker and peripheral tissues.
In addition to altering metabolism, exposure to LAN is implicated as a
contributing factor to several diseases involving dysregulation of the immune system.
This led to experiments examining the effects of acute exposure to dim LAN on recovery
following cardiac arrest (Chapter 7). Exposure to dimly lit as compared to dark nights
following global ischemia increased hippocampal inflammation, neuronal cell death, and
mortality. Selectively inhibiting inflammation and altering the spectrum of nighttime
light to which mice were exposed reduced damage among mice exposed to dim LAN.
In the experiments described above, I worked with nocturnal mice in order to
assess the effects of nighttime light exposure independent of changes in sleep
architecture. However, the secretion patterns of many hormones and immune parameters
are different in nocturnal and diurnal species. In the final set of experiments, I
demonstrated that diurnal Nile Grass rats (Arvicanthus Niloticus) exposed to dim LAN
increased immunological measures (Chapter 8) and altered hippocampal connectivity in
addition to changing cognitive and affective behaviors (Chapter 9). Taken together,
these studies indicate that exposure to ecologically relevant levels of dim LAN attenuate
core circadian clock mechanisms in rodents resulting in physiological and behavioral
consequences.
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DEDICATION
To my family – for their love, encouragement, and support.
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ACKNOWLEDGEMENTS
First and foremost, I thank my advisor Dr. Randy Nelson for his superb
mentorship. Randy has provided me with abundant opportunities and resources, as well
as much of his own time over the past five years. Randy is a truly dedicated and
supportive mentor who has given me both excellent scientific advice and savvy insight
into what one needs to do to become a successful researcher.
I am grateful for all of the wonderful people with whom I have had the
opportunity to work in the Nelson and DeVries labs. I thank James Walton, Dr. Joanna
Workman, Dr. Kate Weil, and John Morris for their fantastic guidance and patience in
teaching me skills ranging all the way from how to work a pipette to performing
immunohistochemistry and PCR. Dr. Zachary Weil has been an excellent mentor and
friend over the past few years. I thank Zach for his valuable advice and support.
Furthermore, I am grateful to Joanna Workman, Tracy Bedrosian, and Taryn Aubrecht
for their help, advice, and friendship both inside and outside the lab. My lab experience
would not have been the same without the “executive broads,” our international travel
adventures, or the occasional stealth trip to Easton! I thank Greg Norman, Brant Jarrett,
Shannon Chen, Jeremy Borniger, Tomoko Ikeno, Adam Hinzey, Katie Stuller, and Jackie
Thomas for assisting me and for making the Nelson and DeVries labs such a great place
to work. I am also indebted to all of the undergraduate volunteers that helped make this
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work possible including: Rebecca Lieberman, O. Hecmarie Meléndez-Fernández, Emily
Kitsmiller, Dan McCarthy, Heather Michaels, Brittany Jones, Jordan Grier, Amanda
Grunenwald, Natalie Hood, Brian Klein, Kristopher Gaier, Zachary McHenry, and
Joseph Ferraro. I would like to thank Ning Zhang as well, for her remarkable surgical
skills and friendly attitude.
I have had a lot of help from other faculty members and students, both at Ohio
State and other institutions. First, I want to thank Nathaniel Thomas and Dr. Catherine
Cornwell for introducing me to behavioral neuroscience at Syracuse University. I am
grateful to Dr. Courtney DeVries for serving on my candidacy and dissertation
committees, and for her outstanding mentorship on several experiments. Dr. DeVries is a
great role model for any aspiring female scientist and she has provided me with excellent
advice over the years. I also thank Drs. Dana McTigue and Jonathan Godbout for
providing me with insightful feedback while serving on my candidacy and dissertation
committees. I am grateful to Dr. Laura Smale, Dr. Phillip Popovich, Dr. Andrew Gaudet,
Dr. Qinghua Sun, Dr. Sanjay Rajagopalan, Dr. Xiaohua Xu, and Dr. Cuiqing Lui for
providing me the opportunity to collaborate on very interesting projects. Thank you to
Holly Brothers, Roxanne Kaercher, Ashley Fenn, Puneet Sodhi, and Jodie Hall for being
great friends and always having helpful scientific advice. Special thanks to Andrew
Gaudet for being incredibly supportive, and willing to help me in the lab at all hours of
the day and night.
Finally I would like to thank my family. I am very grateful to my parents, Carol
and David Fonken, for providing me with so many opportunities, tireless encouragement,
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and support. I can trace my initial interest in science to conversations I had with my dad
while walking the dog. Dad has an incredible knowledge of many scientific topics, and
the ability to make all science seem both accessible and exciting! I also thank Erin and
Brian for being the best siblings I can imagine and always giving me love, support, and
advice.
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VITA
May 21, 1986 .................................................Born – Austin, TX, USA
2004................................................................L.C. Anderson High School
2008................................................................ B.S. Biology and Psychology, Syracuse
University
2009-present ..................................................Graduate Research Fellow, Department of
Neuroscience, The Ohio State University
PUBLICATIONS
1. Bedrosian, T.A., Herring, K.L., Walton, J.C., Fonken, L.K., Weil, Z.M., &
Nelson, R.J. (2013). Possible feedback control of pineal melatonin secretion.
Neuroscience Letters (In press).
2. Fonken, L.K., Weil, Z.M., & Nelson, R.J. (2013). Dark nights reverse metabolic
disruption caused by dim light at night. Obesity, (In press).
3. Fonken, L.K. & Nelson, R.J. (2013). Dim light at night increases depressive-like
responses in male C3H/HeNHsd mice. Behavioural Brain Research, 243 (3): 74-
78.
4. Fonken, L.K., Kitsmiller, E., Smale, L., & Nelson, R.J. (2012). Dim nighttime
light impairs cognition and provokes depressive-like responses in a diurnal
rodent. Journal of Biological Rhythms, 27 (4): 319-27.
5. Fonken, L.K., Bedrosian, T.A., Michaels, H., Weil, Z.M., & Nelson, R.J. (2012).
Short photoperiods attenuate central responses to an inflammogen. Brain,
Behavior, and Immunity, 26 (4): 617-22.
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6. Bedrosian, T.A., Fonken, L.K., Demas, G.E., & Nelson, R.J. (2012). Photoperiod-
dependent effects of neuronal nitric oxide synthase inhibition on aggression in
Phodopus sungorus. Hormones and Behavior, 61 (2): 176-80.
7. Fonken, L.K., Haim, A., & Nelson, R.J. (2012). Dim light at night increases
immune function in grass rats, a diurnal rodent. Chronobiology International, 29
(1): 26-34.
8. Fonken, L.K. & Nelson, R.J. (2011). Illuminating the deleterious effects of light
at night. F1000 Med Report, 3: 18.
9. Workman, J.L., Fonken, L.K., Gusfa, J., Kassouf, K., & Nelson, R.J. (2011). Post-
weaning environmental enrichment reduces negative affective responses and
interacts with behavioral testing to alter nNOS expression. Pharmacology,
Biochemistry and Behavior, 100 (1): 25-32.
10. Fonken, L.K., Xu, X., Weil, Z.M., Chen, G., Sun, Q., Rajagopalan, S., & Nelson,
R.J. (2011). Inhalation of fine particulates alters hippocampal neuronal
morphology. Molecular Psychiatry, 16 (10): 973.
11. Fonken, L.K., Xu, X., Weil, Z.M., Chen, G., Sun, Q., Rajagopalan, S., & Nelson,
R.J. (2011). Air pollution impairs cognition, provokes depressive-like behaviors,
and alters hippocampal cytokine expression and morphology. Molecular
Psychiatry, 16 (10): 987-995.
12. Fenn, A.M.*, Fonken, L.K.*, & Nelson, R.J. (2011). Sustained melatonin
treatment blocks body mass, pelage, reproductive and fever responses to short day
lengths in female Siberian hamsters. Journal of Pineal Research, 51: 180-186.
*equal contributors
13. Bedrosian, T.A., Fonken, L.K., Walton, J.C., Haim, A., & Nelson, R.J. (2011).
Dim light at night provokes depression-like behaviors and reduces CA1 dendritic
spine density in female hamsters. Psychoneuroendocrinology. 36: 1062-1069.
14. Bedrosian, T.A., Fonken, L.K., Walton, J.C., & Nelson, R.J. (2011). Chronic
exposure to dim light at night suppresses immune responses in Siberian hamsters.
Biology Letters, 7 (3): 468-471.
15. Fonken, L.K., Morris, J.S., & Nelson, R.J. (2011). Early life experiences affect
adult delayed-type hypersensitivity in short- and long-photoperiods.
Chronobiology International, 28 (2): 101-108.
16. Fonken, L.K., Workman, J.L., Walton, J.C., Weil, Z.M., Morris, J.S., Haim, A., &
Nelson, R.J. (2010). Light at night increases body mass by shifting the time of
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food intake. Proceedings of the National Academy of Sciences, 107 (43): 18664-
18669.
17. Thomas, N.R., Fonken, L.K., LeBlanc, M., & Cornwell, C.A. (2010). Maternal
separation alters social odor preference development in infant mice (Mus
musculus). Journal of Comparative Psychology, 124 (3): 295-301.
18. Workman, J.L., DeWitt, S.J., Fonken, L.K., & Nelson, R.J. (2010). Environmental
enrichment enhances delayed-type hypersensitivity in both short- and long-day
Siberian hamsters. Physiology and Behavior, 99 (5): 638-643.
19. Fonken, L.K., Finy, M.S., Walton, J.C., Weil, Z.M., Workman, J.L., Ross, J., &
Nelson, R.J. (2009). Influence of light at night on murine anxiety- and depressive-
like responses. Behavioural Brain Research, 205 (2): 349-354.
FIELDS OF STUDY
Major Field: Neuroscience
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TABLE OF CONTENTS
Page
Abstract ............................................................................................................................... ii
Dedication .......................................................................................................................... iv
Acknowledgements ..............................................................................................................v
Vita ................................................................................................................................... viii
List of Tables ................................................................................................................... xiii
List of Figures .................................................................................................................. xiv
Chapters:
1. The “Skinny” on Light at Night, Circadian Clocks, and Metabolism ............................1
2. Light at Night Increases Body Mass through Altered Timing of Food Intake .............29
3. Dark Nights Reverse Metabolic Changes Caused by Dim Light at Night ...................49
4. Dim Light at Nigh Exaggerates Weight Gain and Inflammation Associated with a
High Fat Diet..........................................................................................................66
5. Exercise Attenuates the Metabolic Effects of Dim Light at Night ...............................83
6. Dim Light at Night Disrupts Molecular Circadian Rhythms ........................................94
7. Dim Light at Night Affects Cardiac Arrest Outcome .................................................112
8. Dim Light at Night Elevates Inflammatory Responses in Diurnal Grass Rats ...........140
9. Dim Light at Night Impairs Cognition and Provokes Depressive-like Responses in
Grass Rats ............................................................................................................161
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Page
Conclusions ......................................................................................................................178
List of References ............................................................................................................188
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LIST OF TABLES
Table Page
2.1 Food intake in food restricted mice exposed to dimly lit or dark nights………...44
3.1 Experimental design……………………………………………………………...54
8.1 Tissue masses in Nile grass rats exposed to dimly lit or dark nights…………...157
9.1 Hippocampal neuron characteristics in grass rats exposed to dark or dimly lit
nights....................................................................................................................174
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LIST OF FIGURES
Figure Page
2.1. Light at night affects body mass and glucose tolerance ............................................45
2.2. Activity is comparable between mice exposed to dimly lit and dark nights .............47
2.3. Time of food intake but not corticosterone is altered by dim light at night...............48
2.4. Resticting feeding to the dark phase prevents dim light at night induced body mass
gain .........................................................................................................................49
3.1. Return to dark nights affects body mass after exposure to dim light at night ...........63
3.2. Dim light at night affects fat mass and composition..................................................64
3.3. Dark nights reverse changes in feeding behavior and glucose processing ................65
4.1. Light at night exaggerates weight gain on a high fat diet ..........................................79
4.2. High fat diet and light at night alter timing of food intake ........................................80
4.3. High fat diet and light at night increase adipose inflammation .................................81
4.4. Hypothalamic inflammation is elevated by high fat diet but not exposure to dim light
at night ...................................................................................................................82
5.1. Voluntary exercise prevents weight gain induced by dim light at night....................92
5.2. Dim light at night disrupts daily wheel running patterns in a subset of mice ............93
6.1. Mice exposed to dim light at night alter somatic measures .....................................107
6.2. Dim light at night attenuates clock gene expression ................................................108
6.3. Dim light at night suppresses Rev-Erb expression in peripheral tissue ...................109
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Figure Page
6.4. Clock protein expression is reduced in the SCN of mice exposed to dimly lit
nights ....................................................................................................................110
7.1. Ambient lighting in cardiac intensive care unit patient rooms ................................131
7.2. Cardiac arrest and cardiopulmonary resuscitation surgical parameters ...................132
7.3. Dim light at night impairs cardiac arrest recovery...................................................133
7.4. Corticosterone concentrations in the 24 h following cardiac arrest .........................134
7.5. Cytokine expression is elevated in the hippocampus and microglia of mice exposed
to dim light at night following cardiac arrest .......................................................135
7.6. Selective inhibition of specific cytokines attenuates inflammation and neuronal cell
death following cardiac arrest and exposure to dim light at night .......................137
7.7. Manipulation of lighting wavelength minimizes light at night induced damage
following cardiac arrest........................................................................................138
8.1. Nile grass rats exposed to dimly lit nights elevate corticosterone concentrations and
delayed-type hypersensitivity swelling response .................................................158
8.2. Rats exposed to light at night enhance humoral immune function and plasma
bactericidal capacity.............................................................................................159
8.3. Grass rats exposed to dark and dimly lit nights have comparable activity ..............160
9.1. Grass rats exposed to dim light at night show impairments in learning and
memory ................................................................................................................175
9.2. Exposure to dim light at night increases depressive-like responses in grass rats ....176
9.3. Exposure to dim light at night alters hippocampal morphology in grass rats ..........177
1
CHAPTER 1
THE “SKINNY” ON LIGHT AT NIGHT, CIRCADIAN CLOCKS, AND
METABOLISM
Over the course of the 20th
century the prevalence of obesity and metabolic
disorders rapidly increased worldwide. By the year 2000 the number of adults with
excess adiposity surpassed those who were underweight for the first time in evolutionary
history (Caballero, 2007). The growth in obesity has been exponential in recent decades
particularly for the highest weight categories. From 2000 to 2005 the number of
individuals qualifying as morbidly obese (BMI over 50) increased by 75% in the United
States (Sturm, 2007). Obesity is a pathogenic condition defined by the accumulation of
excess adipose tissue and is associated with serious health complications including
diabetes, cardiovascular disease, hypertension, asthma, and reproductive dysfunction
(Guh et al., 2009). Obesity reduces quality of life, results in significant health related
complications, and more than doubles healthcare costs. In addition to typical obesogenic
factors such as high calorie diet and sedentary lifestyles contributing to obesity, other
environmental factors are likely involved in the development and maintenance of this
condition (Symonds, Sebert, & Budge, 2011).
2
Unprecedented transitions in human lifestyle occurred during the past century,
such as advances in travel and communication, greater urbanization, and the eradication
of multiple diseases (Engineering, 2000). One environmental change that had a mostly
unappreciated, yet dramatic, effect on human lifestyle was the widespread adoption of
electric lighting. Electric lights have provided many societal advances. Brightening the
night has shed the negative stigma of nighttime as a time solely for crime, sickness, and
death (Ekirch, 2005). The use of electric light at night played a large role in the industrial
revolution allowing for the creation of shift work. Furthermore, electric lighting has given
individuals the freedom to function on a self-selected sleep/wake schedule. Because the
invention of electric lighting occurred prior to an understanding of circadian biology,
little concern was given to the potential effects exposure to unnatural light schedules may
have on human health. It is becoming apparent, however, that there are significant
physiological repercussions associated with exposure to light at night (Fonken & Nelson,
2011; Navara & Nelson, 2007). In a sense, shift workers, who are exposed to high levels
of light at night in the workplace, have served as society‟s „canaries in the coal mine‟ for
maladaptive consequences of nighttime light exposure. Epidemiological evidence from
shift workers demonstrates that prolonged exposure to light at night increases the risk of
developing cancer (Stevens, 2009b), sleep disturbances (Kohyama, 2009), mood
disorders (Driesen, Jansen, Kant, Mohren, & van Amelsvoort, 2010), metabolic
dysfunction (B. H. Karlsson, Knutsson, Lindahl, & Alfredsson, 2003; Knutsson, 2003;
Obayashi et al., 2013; Parkes, 2002; Puttonen, Viitasalo, & Harma, 2011; van
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Amelsvoort, Schouten, & Kok, 1999), and cognitive impairments (K. Cho, 2001; Vetter,
Juda, & Roenneberg, 2012).
The reason that exposure to electric lights likely affects physiology is because
many organism have developed endogenously driven 24 h rhythms, termed circadian
rhythms, that are most potently synchronized by light information. The rotation of the
Earth about its axis produces a highly consistent cycle of light and dark that varies
latitudinally and on a seasonal basis. For more than 3 billion years, life on Earth has
evolved under bright days and dark nights. In order to optimally time physiological,
behavioral, and metabolic functions many organisms developed circadian rhythms.
Circadian rhythms allow organisms to anticipate predictable daily events such as food
availability and rest. Here I propose that increases in exposure to light at night during the
20th
century and concomitant changes in lifestyle are associated with alterations in
metabolism. In this introductory chapter, I will first provide an introduction to the
circadian system, with a specific emphasis on the effects of light on circadian rhythms.
Next I address interactions between the circadian system and metabolism. Animal models
have provided a vast amount of knowledge about the effects of circadian rhythm
disruption on metabolism, as well as the effects of disrupted metabolism on the circadian
system. Finally, I will tie in current experimental and epidemiological work associating
exposure to light at night and metabolism.
2. Circadian clock work
Most organisms, from unicellular cyanobacterium, to fruit flies and humans, have
developed an endogenous timekeeping system that synchronizes physiological and
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behavioral processes to the external solar cycle (Bell-Pedersen et al., 2005). Biological
clocks have the ability to both coordinate interactions among animals (e.g., knowing the
time of day can help animals avoid predation or engage in mating) and synchronize
internal physiological and biochemical processes within an individual (e.g., rhythmic
hormone release in anticipation of food availability and sleep). Circadian rhythms are
defined specifically as internally driven oscillation that meet several characteristics
including: (1) the period of the rhythm is about 24 h in the absence of environmental
cues, (2) rhythms are buffered against changes in environment such as temperature
fluctuations and behavioral feedback, and (3) rhythms can shift under the influence of
certain factors but entrainment is limited to a specific range (Dunlap, Loros, &
DeCoursey, 2004).
One common example of a circadian rhythm in mammals is the presence of a
sleep/wake cycle. In diurnal species, such as humans, sleep typically occurs during the
dark portion of the day, whereas nocturnal animals, such as house mice (Mus musculus),
generally sleep during the light. The propensity for sleep and activity is influenced by
endogenously controlled rhythmic hormone release. For example, cortisol secretion
spikes in the early morning directly prior to awakening in humans and then drops
throughout the day, reaching its nadir around the time of sleep onset (S. L. Bailey &
Heitkemper, 2001). Overall, circadian rhythms exist in many facets of physiology and the
importance of the circadian system is clearly demonstrated by considering pathogenic
conditions that result from altering circadian physiology (Takahashi, Hong, Ko, &
McDearmon, 2008). Circadian rhythm disruptions contribute to a wide range of disorders
5
including cognitive impairments, mood disturbances, and increased risk of
cardiometabolic disorders (Zee, Attarian, & Videnovic, 2013). In order to understand
why these pathogenic conditions arise from disruption of the circadian clock it is first
important to understand where circadian oscillations originate.
2.1. The suprachiasmatic nucleus is the master circadian oscillator
The suprachiasmatic nuclei (SCN) of the hypothalamus comprise the master
circadian clock in mammals, at the top of a hierarchy of independent self sustaining
oscillators. The SCN is located in the anterior hypothalamus directly above the optic
chiasm and is composed of approximately 50,000 densely packed small neurons in
humans and 10-20,000 neurons in rodents (Dunlap, Loros, & DeCoursey, 2004). There
are several lines of evidence confirming that the SCN is the master circadian oscillator in
mammals: (1) SCN lesions abolish circadian rhythms (Stephan & Zucker, 1972), (2)
electrical and chemical stimulation of the SCN induce phase shifts (Michel et al., 2013;
Rusak & Groos, 1982), (3) transplanting an SCN into an animal whose own SCN has
been ablated restores circadian activity (R. Silver, LeSauter, Tresco, & Lehman, 1996),
and (4) individual neurons dissociated from the SCN display long term self-sustaining
oscillations (Welsh, Logothetis, Meister, & Reppert, 1995). Cellular synchrony within the
SCN is established through multiple mechanisms such as sodium dependent action
potentials (Yamaguchi et al., 2003) and humoral signals (R. Silver, LeSauter, Tresco, &
Lehman, 1996).
2.2. Molecular mechanisms of the circadian clock
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The circadian clock in mammals is driven by an autoregulatory feedback loop of
transcriptional activators and repressors (reviewed in (Mohawk, Green, & Takahashi,
2012; Reppert & Weaver, 2002). CLOCK and BMAL1 form heterodimers that induce
expression of Period (Per1, Per2, and Per3) and Cryptochrome (Cry1 and Cry2) through
E-box enhancers (Gekakis et al., 1998). PER and CRY proteins accumulate in the
cytoplasm throughout the circadian day. Upon reaching a critical amount, PER and CRY
form a complex that translocates back to the nucleus to associate with CLOCK and
BMAL and repress their own transcription (Mohawk, Green, & Takahashi, 2012; Reppert
& Weaver, 2002). This process takes approximately 24 h to complete a full cycle. In
addition to the primary feedback loop, other regulatory loops influence the circadian
clockwork. For example, the CLOCK:BMAL1 heterodimer also activates transcription of
retinoic acid-related orphan nuclear receptors, Rev-erbα and Rora, which have feedback
effects primarily on Bmal1 (Preitner et al., 2002).
Core clock components are defined as genes with protein products that are
essential for the generation and regulation of circadian rhythms (Takahashi, 2004).
Ablation of the core clock genes Clock, Bmal1 (Bunger et al., 2000), Per1, Per2 (Bae et
al., 2001), Cry1, and Cry2 (van der Horst et al., 1999) all disrupt circadian physiology
(see Table 1 in (Ko & Takahashi, 2006). The line between what constitutes a core clock
gene is constantly evolving. Rev-Erb and Per3 were not initially considered critical for
maintaining clock function; however, the importance of these genes for circadian
regulation is now widely accepted (H. Cho et al., 2012; Pendergast, Niswender, &
Yamazaki, 2012).
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2.3. Additional clocks persist outside the SCN
In multicellular organisms, circadian oscillators are present in most if not all
tissues. The SCN serves as the master circadian clock at the top of a hierarchically
organized system (Mohawk, Green, & Takahashi, 2012). Tissue specific clocks contain
the molecular machinery necessary for self sustaining oscillations (King et al., 1997) and
have virtually the same molecular makeup as circadian oscillators in the SCN. Peripheral
clocks are entrained by the SCN through both neural and hormonal signals (Guo, Brewer,
Champhekar, Harris, & Bittman, 2005; McNamara et al., 2001; Reddy et al., 2007), as
well as local factors such as nutritional signals (Vollmers et al., 2009). Peripheral clocks
do not appear to communicate with each other but they are coupled to the SCN (A. C. Liu
et al., 2007). Ablation of the SCN in vivo has profound effects on peripheral oscillators
(Akhtar et al., 2002) and peripheral oscillators show more rapid dampening of circadian
rhythms in vitro (Balsalobre, Damiola, & Schibler, 1998). Whereas SCN rhythms can
persist for more than one month in vitro, peripheral rhythms are not as robust and
diminish within two to seven cycles (Yamazaki et al., 2000).
2.4. Light entrains the circadian system
In most organisms, the circadian system functions at approximately but not
exactly 24 h. Therefore, circadian clocks require external input to entrain them to the
environment (Golombek & Rosenstein, 2010). Light is the most potent synchronizing
factor for the circadian system. Light information travels directly from intrinsically
photo-sensitive melanopsin containing retinal ganglion cells (ipRGCs), through the
retinohypothalmic tract, to the SCN (Hattar, Liao, Takao, Berson, & Yau, 2002). Within
8
the SCN, light induces rapid changes in cellular activity that have been extensively
characterized by examining the expression of immediate early genes (Rusak, Robertson,
Wisden, & Hunt, 1990).
At the molecular level, exposure to light results in rapid induction of Per1
(Albrecht, Sun, Eichele, & Lee, 1997; Shigeyoshi et al., 1997). A pulse of light during the
night can phase advance or delay the circadian clock depending on the strength and time
of the light signal (Miyake et al., 2000). For example, light at dawn advances the clock
through advancing the onset of the Per1 rhythm and acutely increasing mRNA
transcription, whereas light at dusk delays the clock through delaying the offset of Per2
(Schwartz, Tavakoli-Nezhad, Lambert, Weaver, & de la Iglesia, 2012). The SCN can
rapidly adjust to light shifts, whereas peripheral tissues shift more slowly and in different
ways (Yamazaki et al., 2000). Although light is the most potent signal for the mammalian
circadian system, other factors such as food availability and locomotor activity can
feedback and influence circadian clock function (Fuller, Lu, & Saper, 2008; Mistlberger
& Antle, 2011). These types of stimuli can leave SCN rhythms intact, specifically
altering clock gene expression in peripheral tissues (Damiola et al., 2000; Vollmers et al.,
2009).
Multiple characteristics of the circadian system are conserved between rodents
and humans. In humans, specifically-timed light pulses can also shift the circadian clock
(Czeisler et al., 1989; Smith, Revell, & Eastman, 2009). Moreover, both humans and
rodents are most responsive to 460 nm nighttime light exposure (Brainard, Richardson,
Petterborg, & Reiter, 1982; Ruger et al., 2013). Longer wavelengths of lighting, such as
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red light, do not activate the melanopsin containing retinal ganglion cells that project to
the SCN and therefore minimally influence the circadian system (Brainard et al., 2008;
Figueiro & Rea, 2010).
Exposure to constant dim light or total darkness results in a free-running circadian
system. This knowledge has been used to test the effects of different factors, such as
melatonin, on synchronizing circadian activity (Redman, Armstrong, & Ng, 1983). In
contrast, the effects of dim and bright light at night on the circadian system are less well
documented. In Chapter 2 of this dissertation I demonstrate that exposure to constant
light alters activity rhythms and flattens circadian rhythms in glucocorticoids (Coomans
et al., 2013; Fonken et al., 2010), two principle outputs of the circadian system.
There is evidence that very dim levels of light at night can influence circadian
rhythms in both rodents and humans (Evans, Elliott, & Gorman, 2005; Jasser, Hanifin,
Rollag, & Brainard, 2006). However, the effects of physiologically relevant levels of
light exposure on the circadian system are not well characterized. Therefore, in this
dissertation I evaluate the effects of chronic exposure to dim light at night (~5 lux) on the
murine circadian system. The level of dim light used in my studies is ecologically
relevant and comparable to levels of light pollution found in urban areas (Gaston, Davies,
Bennie, & Hopkins, 2012; Kloog, Haim, & Portnov, 2009) and sleeping environments
(Obayashi et al., 2013). In Chapter 5, I document that exposure to chronic low levels of
light at night alters circadian clock genes in both the SCN and peripheral tissue (Fonken,
L.K., Aubrecht, T.G., Meléndez-Fernández, O.H., Weil, Z.M., & Nelson, R.J., unpublished
observations). Exposure to dim light at night specifically attenuates the rhythm in Per1
10
and Per2 gene and protein expression in the SCN around the light/dark transition.
Furthermore, expression of Bmal1, Per1, Per2, Cry1, Cry2, and Rev-Erb are all
suppressed in the liver. Nocturnal light may affect the liver through both autonomic and
hormonal pathways (Cailotto et al., 2009). The changes in clock gene expression
associated with exposure to dim light at night do not result in disruption of either the
glucocorticoid rhythm or locomotor activity rhythm (Chapter 2). Similar changes in
circadian clock function are also apparent in the SCN of hamsters exposed to low levels
of light at night (Bedrosian, T.A., Galan, A., Vaughn, C.A., Weil, Z.M., & Nelson, R.J.,
unpublished observations). Hamsters exposed to dim light suppress PER1 and PER2
protein rhythms in the SCN independent of changes in activity rhythm. Overall, these
results indicate that exposure to levels of nighttime lighting that are commonly found in
urban settings can affect the circadian system.
3. The circadian system regulates metabolism and vice versa
Approximately 10% of the mammalian transcriptome displays circadian
regulation (K. L. Eckel-Mahan et al., 2012; Panda et al., 2002; Storch et al., 2002).
Among the rhythmic genes identified, many have a specific role in coordinating nutrient
metabolism (K. Eckel-Mahan & Sassone-Corsi, 2009). For example, there is circadian
expression of glucose transporters and the glucagon receptor (Panda et al., 2002),
multiple enzymes involved in the metabolism of sugars and the biosynthesis of
cholesterols display circadian oscillation (la Fleur, Kalsbeek, Wortel, Fekkes, & Buijs,
2001; Panda et al., 2002), and PCG-1α, an essential activator of gluconeogensis, has a
key role in regulating circadian rhythms (C. Liu, Li, Liu, Borjigin, & Lin, 2007).
11
Metabolically related hormones such as glucagon, insulin, ghrelin, leptin, and
corticosterone also oscillate in a circadian fashion (Kalsbeek et al., 2001; Ruiter et al.,
2003; Sinha et al., 1996). There is rhythmic expression of orexigenic signals including
neuropeptide Y, galanin, and pre-opiomelanocortin within the hypothalamus, an area
critical for coordinating metabolic signals (Jhanwar-Uniyal, Beck, Burlet, & Leibowitz,
1990; B. Xu, Kalra, Farmerie, & Kalra, 1999). Moreover, neuroanatomical organization
provides evidence of interactions between metabolism and the circadian system;
hypothalamic nuclei such as the paraventricular nucleus receive direct neuronal input
from the SCN (reviewed in (Kalra et al., 1999).
3.1. Knocking out the circadian clock and obesity
In addition to fluctuations in metabolic processes suggesting an association
between the circadian and metabolic systems, disrupting the clock network through
genetic manipulations has provided insight into the role of the circadian system in
maintaining metabolic homeostasis. Mice harboring mutations in various components of
the circadian clock are susceptible to obesity and metabolic syndrome. Turek and
colleagues were the first to report that Clock mutant mice on a BALB/c and C57BL/6J
background are susceptible to diet induced obesity. Clock mutants show marked changes
in circadian rhythmicity, as well as disruptions in diurnal food intake and increased body
mass (Turek et al., 2005). This phenotype may partially result from changes in endocrine
regulation as serum leptin, glucose, cholesterol, and triglyceride levels are all increased in
Clock mutants compared to wild type mice. Deletion of Clock on an ICR background also
results in metabolic alterations. In contrast to Clock deletion in a BALB/c and C57BL/6J
12
background, ICR Clock deficient mice are protected against weight gain due to
impairments in dietary fat absorption (Oishi et al., 2006).
Disruption of other core circadian clock genes similarly affects metabolism. Mice
deficient in Bmal1 alter insulin and glucose secretion (Marcheva et al., 2010) and
rescuing Bmal1 in the central nervous system restores activity rhythms but not changes in
metabolism (McDearmon et al., 2006). Mutation of Cry1 produces symptoms of diabetes
mellitus in mice (Okano, Akashi, Hayasaka, & Nakajima, 2009). Furthermore, mice
deficient in mPer1/2/3 increased weight gain on a high fat diet (Dallmann & Weaver,
2010) and single disruption of the Per2 gene alters glucose homeostasis (Carvas et al.,
2012).
Loss of clock function in peripheral tissues also affects metabolism. Deletion of
pancreatic Clock or Bmal1 reduces glucose and insulin processing abilities, independent
of changes in activity or feeding rhythms in mice (Marcheva et al., 2010). Mice with
liver-specific deletion of Bmal1 exhibit hypoglycemia during the fasting phase,
exaggerated glucose clearance, and loss of rhythmic expression of hepatic glucose
regulatory genes (Kornmann, Schaad, Bujard, Takahashi, & Schibler, 2007; Lamia,
Storch, & Weitz, 2008). Changes in glucose processing with liver specific Bmal1 deletion
occur independently of alterations in feeding behavior or locomotor activity, indicating a
primary defect in metabolic responses (Lamia, Storch, & Weitz, 2008). In contrast,
deletion of Bmal1 in adipocytes alters daily feeding rhythms and results in obesity
(Paschos et al., 2012). Finally, Bmal1 deletion in the central nervous system produces
13
deficits in locomotor activity entrainment by periodic feeding, reductions in food intake,
and subsequent loss of body weight (Mieda & Sakurai, 2011).
Alterations in secondary clock genes are also associated with metabolic changes
in mice. Modulation of Per3 may be responsible for weight gain in Per1/2/3-/- mice, as
single deletion of Per3 results in significant weight gain (Dallmann & Weaver, 2010).
Mice lacking the VIP-VPAC2 pathway, which plays an important role in SCN
communication (Reppert & Weaver, 2001), dampen feeding rhythms and show
reductions in metabolic rate (Bechtold, Brown, Luckman, & Piggins, 2008). Furthermore,
mice lacking Nocturnin, a gene involved in the posttranscriptional regulation of rhythmic
gene expression (Baggs & Green, 2003), remain lean on a high fat diet. This appears to
be due to either changes in lipid uptake or utilization as genes important for lipid
pathways lose rhythmicity in Nocturnin-/- mice (Douris et al., 2011; Green et al., 2007).
Recently, Rev-Erb has been implicated in the modulation of both metabolism and the
circadian system (Yin et al., 2007). Dual deletion of Reb-Erbα and Rev-Erbβ disrupts
gene networks involved in lipid metabolism (H. Cho et al., 2012) and markedly affects
circadian rhythms. Rev-Erb likely regulates hepatic lipid homeostasis through the
recruitment of histone deacetylase 3 (Feng et al., 2011). Treatment with a Rev-Erb
agonist increases energy expenditure and promotes weight loss in mice fed a high fat diet
(Solt et al., 2012).
Associations between changes in clock genes and metabolism are also apparent in
humans. Body mass index correlates with clock gene expression in peripheral adipose
tissue depots (Zanquetta et al., 2012). Per2 expression levels in visceral adipose tissue
14
inversely correlate with waist circumference (Gomez-Abellan, Hernandez-Morante,
Lujan, Madrid, & Garaulet, 2008) and Bmal, Per2, and Cry1 levels negatively correlate
with total cholesterol and LDL concentrations. The methylation pattern of difference
CpG sites of Clock, Bmal, and Per1, are significantly associated with metabolic
parameters including body mass index, adiposity, and metabolic syndrome score
(Milagro et al., 2012). Moreover, a common clock polymorphism is coupled to the
presence of metabolic syndrome in humans (E. M. Scott, Carter, & Grant, 2008).
3.2. Metabolism and the circadian clock are reciprocally related
The relationship between the circadian system and metabolism appears to be bi-
directional. In addition to circadian system disruptions causing obesity, metabolic
abnormalities alter circadian rhythms. For example, in humans, metabolically related
diseases such as obesity and anorexia nervosa are associated with altered hormone and
body temperature rhythms (Ferrari, Fraschini, & Brambilla, 1990). Daily rhythms in
glucose and insulin sensitivity are apparent in non-obese but not obese subjects (Lee,
Ader, Bray, & Bergman, 1992). Moreover, obese women display significantly lower
wrist temperature and a more flattened temperature rhythm compared to normal-weight
control women (Corbalan-Tutau et al., 2011).
An intriguing interaction between high fat diets and clock genes has been
discovered. Placing mice on a high fat diet lengthens the circadian period of activity and
attenuates the diurnal pattern of feeding (Kohsaka et al., 2007; Stucchi et al., 2012). Mice
fed a high fat diet dampen circadian rhythms in clock gene expression, specifically in
peripheral metabolically related tissues. These changes appear to occur rapidly, as liver
15
rhythms are phase advanced 5 h, within one week of initiating a high fat diet (Pendergast
et al., 2013). Furthermore, mice fed a high fat diet show a slower rate of re-entrainment
of behavioral and physiological rhythms after a 6 h phase shift (Mendoza, Pevet, &
Challet, 2008).
Modulation of leptin in mice and rats provides further support for the hypothesis
that disrupting metabolism affects the circadian system. Zucker obese rats, a widely used
obesity model produced by a single mutation in the gene encoding the leptin receptor
(Phillips et al., 1996), exhibit phase advanced circadian rhythms and an attenuated
amplitude of body temperature, activity, and sleep (Mistlberger, Lukman, & Nadeau,
1998; Murakami, Horwitz, & Fuller, 1995). Zucker rats increase daytime food
consumption when compared to lean controls (Becker & Grinker, 1977; Wangsness,
Dilettuso, & Martin, 1978) and preventing food intake during the light phase ameliorates
weight gain in obese rats (Mistlberger, Lukman, & Nadeau, 1998). Furthermore, db/db
mice, which lack the leptin receptor, show changes in the diurnal rhythms of multiple
metabolically related hormones (Roesler, Helgason, Gulka, & Khandelwal, 1985) and
clock genes in peripheral tissues (Su et al., 2012). ob/ob leptin deficient mice attenuate
rhythms in activity, heat production, and clock gene expression (Dauncey & Brown,
1987). Disruptions in circadian rhythms, however, may occur prior to the onset of obesity
in ob/ob mice (Ando et al., 2011).
Other obesity models display similar changes in circadian rhythms. Rats with
ventromedial hypothalamic lesions become obese and alter the daily pattern of food
intake and circadian gene expression (Balagura & Devenport, 1970). KK-Ay mice, a
16
mouse model of obesity and type II diabetes, attenuate clock gene rhythms in adipose
tissue and the liver (Ando et al., 2005; Hashinaga et al., 2012). Moreover, a subset of
Volcano mice are naturally susceptible to obesity and display phase advanced activity-
onset and attenuated locomotor activity rhythms compared to non-obese Volcano mice
(Carmona-Alcocer et al., 2012). Of note, one common feature in many of the obesity
models discussed above is that rodents shift diurnal rhythms in food intake.
3.3. You are what when you eat?
Food is an entraining signal for the circadian system. Restricting feeding to
certain times of day can lead to anticipatory increases in wakefulness, locomotor activity,
body temperature, and glucocorticoid secretion (Krieger, 1974). Food entrainable
oscillators appear dependent on extra-SCN signaling and likely involve the dorsomedial
hypothalamus (Gooley, Schomer, & Saper, 2006). Indeed, while the SCN remains phase
locked to light/dark cues, restricting feeding to certain times of day rapidly entrains
circadian rhythms in the liver (Stokkan, Yamazaki, Tei, Sakaki, & Menaker, 2001). In the
absence of light cues, however, restricted feeding is capable of affecting the SCN. For
example, in mice made arrhythmic by constant light exposure, restricted feeding rescues
both activity rhythms and Per2 rhythms in the SCN (Lamont, Diaz, Barry-Shaw, Stewart,
& Amir, 2005).
Timing of food intake is now recognized as a critical factor in energy acquisition,
storage, and expenditure. Mice fed a high fat diet only during the 12 h light (resting)
phase gain significantly more weight than mice fed only during the dark (active) phase
(Arble, Bass, Laposky, Vitaterna, & Turek, 2009). This change in body mass may be
17
dependent on leptin signaling (Arble, Vitaterna, & Turek, 2011). Importantly, in this
model total daily caloric intake and activity do not differ between groups, indicating
changes in body mass can occur independently of changes in energy intake (Arble, Bass,
Laposky, Vitaterna, & Turek, 2009). A more thorough examination of metabolic
characteristics in food restricted mice revealed light-phase fed mice exhibit a higher
respiratory exchange ratio (indicating decreased reliance on fat oxidation), tissue-specific
alterations in metabolically-related genes and circadian clock genes, changes in the
diurnal variations in humoral factors (i.e. corticosterone), and increased weight gain
within 9 days of restricting feeding (Bray et al., 2012). In the study by Bray and
coauthors, mice did show changes in food intake; mice fed during the light phase had
increases in food intake as well as a larger meal on presentation of food (Bray et al.,
2012). The time of day at which dietary fat is consumed also influences multiple
cardiometric parameters (Bray et al., 2010). Consumption of a high fat meal at the end, as
compared to the beginning of the active phase, leads to features of metabolic syndrome
including increased weight gain, elevated adiposity, reductions in glucose processing,
hyperinsulemia, hyperleptinemia, and hypertrigluceridemia (Bray et al., 2010).
As discussed above, multiple obesity models show increases in rest-phase food
intake. This has led to recent research assessing whether preventing rest-phase feeding
can ameliorate weight gain. Mice fed a high fat diet that are food restricted to either 4
(Sherman et al., 2012) or 8 (Hatori et al., 2012) h per day during the active phase are
protected against diet induced obesity. Food restricted mice consume equivalent calories
as mice with ad libitum food access and yet are buffered against obesity, inflammation,
18
hepatic steatosis, hypercholesterolemia, and hyperinsulinemia. Changes in metabolism in
food restricted mice are associated with improved intracellular signaling and nutrient
utilization as well as greater circadian clock oscillations (Hatori et al., 2012; Sherman et
al., 2012). Similarly, restricting food access to the 14 h dark phase reduces weight gain in
Zucker obese rats (Mistlberger, Lukman, & Nadeau, 1998).
Accumulating epidemiological and experimental evidence in humans, supports
the hypothesis that when energy intake occurs is important in determining energy
utilization. Timing of food intake predicts body mass index in humans, even when
controlling for variables such as sleep timing and duration. People who consume more
food after 2000 h tend to have higher body mass index (Baron, Reid, Horn, & Zee, 2013;
Baron, Reid, Kern, & Zee, 2011). Moreover, weight loss therapy is more effective for
individuals who eat early as compared to late eaters (Garaulet et al., 2013). Short duration
sleepers also have increased risk for obesity, weight gain over time, and higher body fat
composition (Weiss et al., 2010). Controlling for factors such as preference for fatty food,
skipping breakfast, snacking, and eating out only partially accounts for the effects of
short duration sleep on obesity, suggesting that changes in metabolic homeostasis at
different times of day may partially account for different body weight regulation
(Nishiura, Noguchi, & Hashimoto, 2010). Indeed, people with Night Eating Syndrome, a
disorder characterized by evening hyperphasia and nocturnal awakenings accompanied
by food intake (Allison et al., 2010), show alterations in metabolically related hormones
and are more likely to be obese (Birketvedt et al., 1999; Goel et al., 2009).
4. Exposure to light at night and obesity
19
Given the well established role of light in modulating the circadian system, and
the relationship between circadian and metabolic functions, it is not surprising that
exposure to light at unnatural times affects metabolism. Increases in nocturnal
illumination parallel increases in obesity and metabolic syndrome worldwide. Here I
propose that exposure to light at night may be contributing to increasing rates of obesity.
In this section I will discuss evidence from animal models and epidemiological studies
implicating exposure to light at night in the growing obesity epidemic.
4.1. Light at night and obesity: evidence from animal models
Exposure to continuous light, non-24 h light schedules, and dim light at night are
all associated with metabolic changes in rodents. First, exposure to constant light
desynchronizes circadian activity in rodents (Coomans et al., 2013). In Chapter 2 of this
dissertation I describe the effects of exposure to constant light on metabolism in mice.
Swiss Webster mice exposed to constant light as compared to a standard light/dark cycle
show increases in body mass and reductions in glucose processing without altering total
daily activity or food intake (Fonken et al., 2010). C57/Bl/6J mice show similar
metabolic changes in constant light, with immediate body weight gain upon placement in
constant light and reductions in insulin sensitivity. Following 4 weeks of exposure to
constant light, mice lack a circadian rhythm in both food intake and energy expenditure.
These changes are associated with reductions in circadian rhythm amplitude as measured
by in vivo electrophysiological recordings of the SCN (Coomans et al., 2013). Rats also
change metabolism with continuous light exposure. Rats exposed to constant light
20
increase visceral adiposity and demonstrate higher feed efficiency than rats exposed to
either a standard light/dark cycle or constant dim light (Wideman & Murphy, 2009).
One limitation to studying the effects of constant light exposure on metabolism is
that the circadian system either free-runs or becomes arrhythmic under constant light
conditions (Fonken et al., 2010; Lamont, Diaz, Barry-Shaw, Stewart, & Amir, 2005).
Furthermore, with the exception of high latitudes, exposure to constant light in natural
settings is rare. For this reason, in Chapters 2-6 of this dissertation I evaluate the effects
of exposure to ecologically relevant levels of dim nighttime light (~5 lux) exposure on
metabolic function. Mice exposed to dimly lit, as compared to dark nights, impair glucose
processing, increase white adipose tissue, and elevate body mass gain (Chapter 2,
(Fonken et al., 2010)). Changes in metabolism occur independently of changes in total
daily food intake or locomotor activity. However, mice exposed to dim light at night shift
timing of food intake, consuming more during the light phase. Much as other obesity
models, restricting food intake to the dark phase prevents weight gain in mice exposed to
dim light at night.
Metabolic changes associated with exposure to dim light at night are not
permanent; placing mice back in dark nights partially reverses increases in body mass
caused by dim light at night exposure (Chapter 3 (Fonken, Weil, & Nelson, 2013)).
Moreover, exposure to dim light at night interacts with more traditional obesogenic risk
factors to affect weight gain. Exposure to dim nights exaggerates weight gain on a high
fat diet, increasing peripheral but not hypothalamic inflammation (Chapter 4). Increases
in weight gain associated with exposure to light at night are also reduced by providing a
21
running wheel for voluntary exercise (Chapter 5). Providing mice a running wheel in
dim light at night prevents increases in weight gain without restoring feeding rhythms.
Models of circadian desynchrony provide further support for an association
between exposure to altered light schedules and changes in metabolism. Placing mice in a
20 h light/dark cycles incongruous with their endogenous ~24 h circadian period,
accelerates weight gain and alters metabolically related hormones (Karatsoreos, Bhagat,
Bloss, Morrison, & McEwen, 2011). Circadian desynchrony in mouse models of shift
work, demonstrate altered light or activity patterns, can disrupt liver transcriptome
rhythms (Barclay et al., 2012), flatten glucose rhythms, increase abdominal fat (Salgado-
Delgado, Angeles-Castellanos, Saderi, Buijs, & Escobar, 2010), and cause reductions in
body mass when shift work is combined with other environmental challenges (Preuss et
al., 2008). Notably, preventing daytime food intake may rescue metabolic changes in
mice undergoing a shift work paradigm (Salgado-Delgado, Angeles-Castellanos, Saderi,
Buijs, & Escobar, 2010).
4.2. Exposure to light at night and obesity: Evidence in humans
Multiple epidemiological studies in shift working populations have linked
exposure to light at night to altered metabolism (X. S. Wang, Armstrong, Cairns, Key, &
Travis, 2011). Health care personnel that work night, as compared to day shifts, show
elevated risk for metabolic syndrome (Pietroiusti et al., 2010). Shift work is associated
with increased blood pressure, cholesterol, obesity, and hypertriglyceridemia in males
(Ha & Park, 2005; B. Karlsson, Knutsson, & Lindahl, 2001) and increased risk for
obesity, hypertension, and hypertriglyceridemia in females (B. Karlsson, Knutsson, &
22
Lindahl, 2001). A study of offshore personnel either chronically working day shifts or
transitioning between day and nights shifts, demonstrated that the number of years of
shift work is positively associated with body mass index in the day/night workers. In
contrast, age is the greatest predictor for body mass index in the day shift population
(Parkes, 2002). This suggests that chronic exposure to light at night can affect body mass
index to a more appreciable extent than typical predictors of body mass, such as age.
Several other studies indicate that working rotating shift schedules as compared to day
schedules increases risk for developing metabolic syndrome (De Bacquer et al., 2009;
Esquirol et al., 2009; Lin, Hsiao, & Chen, 2009a, , 2009b; Sookoian et al., 2007).
Importantly, the effects of shift work on metabolism may be long lasting as former shift
workers show increases in obesity (Puttonen, Viitasalo, & Harma, 2011). Changes in
metabolic signals may contribute to increased body mass in shift workers. For example,
brief behavioral and endogenous circadian misalignment in a controlled laboratory setting
alters leptin, insulin, and cortisol secretion and elevates blood pressure (Scheer, Hilton,
Mantzoros, & Shea, 2009). Moreover, forced desynchrony can produce postprandial
glucose responses comparable to a prediabetic state (Scheer, Hilton, Mantzoros, & Shea,
2009).
In industrialized economies, approximately 20% of the population are shift
workers (Monk, 2000; Rajaratnam & Arendt, 2001). However, exposure to light at night
occurs beyond the scope of shift work. Over 99% of the population in US and Europe
experiences nighttime light exposure (Cinzano, Falchi, & Elvidge, 2001). Associations
between exposure to light at night and increases in body mass index are also apparent
23
outside the shift working population. A recent study by Obayashi et al reported that
increased light exposure in an uncontrolled home setting is associated with obesity and
other metabolic consequences. People with nocturnal light levels above 3 lux display
significantly higher body weight, elevated body mass index, increased waist
circumference, and elevated triglyceride and low-density lipoprotein cholesterol levels
(Obayashi et al., 2013). Moreover, a large scale epidemiological study demonstrated that
“social jetlag” is associated with increased BMI, even when controlling for factors such
as sleep duration (Roenneberg, Allebrandt, Merrow, & Vetter, 2012).
One final piece of evidence linking exposure to light at night and obesity comes
from a population where nighttime light exposure is minimal, the Amish. The Old Order
Amish abstain from using public power, and therefore, are not exposed to common
sources of light at night such as televisions, computers, and electric lights (S. Scott &
Pellman, 1990). The prevalence of obesity among the Amish is far lower than the general
population in the United States (Tremblay, Esliger, Copeland, Barnes, & Bassett, 2008).
Lower obesity rates among the Amish are for the most part attributed to changes in
activity and diet (Esliger et al., 2010; Tremblay, Esliger, Copeland, Barnes, & Bassett,
2008). However, other environmental factors are likely involved in limiting disease rates
among the Amish. For example, the Amish also suffer disproportionately lower rates of
breast and prostate cancer (Westman et al., 2010). Controlling for known carcinogenic
variables such as tobacco use does not completely account for the disparate rates of
cancer. Importantly, exposure to light at night is associated with increased risk for
24
developing both breast and prostate cancer (Kloog, Haim, Stevens, Barachana, &
Portnov, 2008; Kloog, Haim, Stevens, & Portnov, 2009).
4. Conclusions
In this introduction, I specifically focused on how light at night may influence
metabolism through disruption of the circadian clock genes. There are, however, several
additional pathways through which light can affect metabolism, including disruptions in
melatonin production, alterations in glucocorticoids, and sleep disturbances (Reiter, Tan,
Korkmaz, & Ma, 2011). Exposure to sufficient levels and duration of nighttime lighting
can suppress pineal melatonin secretion (Brainard, Rollag, & Hanifin, 1997). Melatonin
is an endogenously synthesized molecule that is secreted by the pineal gland during the
night in both nocturnal and diurnal mammals (Reiter, 1991). Melatonin has recently been
reported to have anti-obesity effects (Mantele et al., 2012; Tan, Manchester, Fuentes-
Broto, Paredes, & Reiter, 2011). Although there is compelling evidence that suppression
of melatonin secretion can contribute to weight gain, I specifically did not focus on
melatonin for several reasons: (1) pineal melatonin suppression requires high and
sustained levels of nighttime light exposure (Brainard, Rollag, & Hanifin, 1997), (2)
nighttime light exposure below the threshold for melatonin suppression is associated with
changes in metabolism (Obayashi et al., 2013), and (3) multiple strains of laboratory mice
that lack pineal melatonin demonstrate changes in metabolism with nighttime light
exposure (Coomans et al., 2013; Fonken et al., 2010). Additionally, I did not focus on the
effects of exposure to light at night on sleep or glucocorticoids because nighttime light
25
exposure affects metabolism in mice independently of changes in sleep architecture or
corticosterone release.
Chapters 2-7 of this dissertation are all conducted in nocturnal laboratory mice.
A nocturnal rodent was selected for the studies in order to separate the effects of
exposure to light at night from sleep disruption. Indeed, exposure to dimly lit nights does
not interrupt sleep in Swiss Webster mice (Borniger, J., Weil, Z.M., & Nelson, R.J.,
unpublished observations). However, both circadian influences on behavior and the
masking effects of light are very different in diurnal as compared to nocturnal species (R.
Cohen, Kronfeld-Schor, Ramanathan, Baumgras, & Smale, 2010; Shuboni, Cramm, Yan,
Nunez, & Smale, 2012). Rhythmic release of multiple hormones also occurs 180° degrees
out of phase between diurnal and nocturnal rodents. Thus, in the final two chapters of this
dissertation (Chapters 8 & 9), I consider the physiological implications of exposing
diurnal Nile grass rats (Arvicanthis niloticus) to dim light at night. Grass rats exposed to
dimly lit as compared to dark nights, enhance cell-mediated immune function as
measured by delayed-type hypersensitivity, elevate antibody production following
inoculation with keyhole lymphocyte hemocyanin, and increase bactericidal capacity
(Chapter 8 (Fonken, Haim, & Nelson, 2011)). Furthermore, Grass rats exposed to dim
light at night display cognitive impairments in a Barnes maze test and increases in
depressive-like behavior (Chapter 9 (Fonken, Haim, & Nelson, 2011)). Changes in
cognitive and affective responses are associated with altered hippocampal connectivity in
grass rats exposed to dimly lit as compared to dark nights. In contrast to nocturnal rodents
exposed to dim light at night (Fonken et al., 2010), grass rats chronically exposed to
26
dimly lit nights elevate corticosterone concentrations compared to rats exposed to dark
nights.
One important population that is often neglected when considering light at night is
patients in hospitals. Although multiple epidemiological studies have been conducted on
nurses, there are no studies on the affects of light at night on the patients with whom they
work. Many in-patients are already at high risk of increased inflammation and disrupted
physiology, which may be exacerbated by light at night. For example, the circadian
system regulates multiple immune related functions (Lange, Dimitrov, & Born, 2010).
Antigen presentation, toll-like receptor function, cytokine gene expression, and
lymphocyte proliferation all occur in a circadian pattern (Arjona & Sarkar, 2006; A. C.
Silver, Arjona, Walker, & Fikrig, 2012). Furthermore, circadian clock proteins directly
regulate the expression of pro-inflammatory cytokines (Narasimamurthy et al., 2012).
Immune cells such as natural killer cells, macrophages, dendritic cells, and B cells
possess molecular clock mechanisms necessary for self-sustaining oscillations (Arjona &
Sarkar, 2005; Keller et al., 2009; A. C. Silver, Arjona, Hughes, Nitabach, & Fikrig,
2012). Because recent research has demonstrated that light at night may detrimentally
affect the immune system (Bedrosian, Fonken, Walton, & Nelson, 2011a) in Chapter 7
of this dissertation I investigate the effects of exposure to light at night on recovery from
global cerebral ischemia.
Most permanent damage to the central nervous system that occurs post-ischemia
is mediated by endogenous secondary processes, typically involving inflammation. The
delay in damage following cerebral ischemia suggests that the immediate post-recovery
27
environment may affect the trajectory of recovery. Because the circadian system is
controlled by an endogenous biological clock, and physiological processes such as
inflammation become dysregulated in disruptive lighting conditions, I hypothesized that
cardiac arrest outcome may be negatively affected by light at night. In agreement with the
hypothesis, mice exposed to dim light at night in the week following a cardiac arrest and
cardiopulmonary resuscitation procedure increase mortality compared to mice exposed to
dark nights. Moreover, mice exposed to dim light at night increase hippocampal cell
death, microglia activation, and pro-inflammatory cytokine expression. Selectively
inhibiting IL-1β or TNFα ameliorate damage in mice exposed to dim light at night,
suggesting increases in inflammation are critical for light-associated damage. Restricting
the wavelength of the nighttime light exposure to ~640 nm also reduces
neuroinflammation and eliminates the detrimental effects of light at night on CA
outcome. These findings implicate the involvement of the circadian system in dim light at
night-associated damage.
Modern society now functions on a 24 h schedule. Although there are many
economic and other societal benefits to such a schedule, there is converging evidence
from epidemiological and experimental work that light at night has unintended,
maladaptive consequences. In many ways, this field of study is just beginning; further
characterization of the biological and psychological effects of light at night is needed
along with effective interventions to ameliorate the unintended negative effects of light at
night on health.
28
Overall, preventing the general population from excessive exposure to light at
night can be achieved with relatively low-cost manipulations, such as using curtains to
block out street lights, turning off hallway lights, and removing all light sources,
including televisions and computers, from bedrooms. However, these methods do not
prevent the social jet lag that many of us experience and exposure to light at night is often
unavoidable in shift-working populations. To that end, there are studies currently
comparing visual aids that may alleviate some of the maladaptive effects of exposure to
light at night in shift workers. Specifically, manipulation of wavelength may prove
effective in blocking out some of the light-induced physiological changes.
29
CHAPTER 2
LIGHT AT NIGHT INCREASES BODY MASS THROUGH ALTERED TIMING
OF FOOD INTAKE
During the past two decades obesity has shifted from a US-centered epidemic to a
global issue. Although well-documented factors such as caloric intake, dietary choices,
and lack of exercise are known to contribute to the prevalence of obesity and metabolic
disorders, additional environmental factors are now considered critical in the
development and maintenance of obesity (Hill, Wyatt, Reed, & Peters, 2003). The
increase of light at night (LAN) during the 20th
century coincides with increasing rates of
obesity and metabolic disorders throughout the world. Artificial lighting allows people to
extend daytime activities into the night, but as a consequence produces significant
environmental light pollution caused by light straying into the atmosphere and
brightening the nighttime sky.
Circadian regulation of energy homeostasis is controlled by an endogenous
biological clock, located in the suprachiasmatic nuclei (SCN) of the hypothalamus that
are synchronized by photic information that travels directly from light-sensitive ganglion
cells in the retina to the SCN, thereby entraining individuals‟ physiology and behavior to
30
the external day-night cycle (Golombek & Rosenstein, 2010). Importantly, light is the
most potent entraining signal for the circadian clock, although other factors such as food
consumption influence clock signaling (Fuller, Lu, & Saper, 2008). To promote optimal
adaptive functioning, the circadian clock prepares individuals for predictable events such
as food availability and sleep. Shift work disrupts clock function and is linked to
circadian and metabolic consequences including sleep disturbances (Kohyama, 2009),
elevated body mass index (BMI) (Parkes, 2002; van Amelsvoort, Schouten, & Kok,
1999), altered plasma lipid metabolism and adiposity (B. H. Karlsson, Knutsson, Lindahl,
& Alfredsson, 2003), and increased risk for cardiovascular disease (Ha & Park, 2005).
Multiple studies suggest a link between the molecular circadian clock and
metabolism (for review see (Bray & Young, 2007). Mice harboring a mutation in their
clock genes are susceptible to obesity and metabolic syndrome (Turek et al., 2005).
Clock mutants show profound changes in circadian rhythmicity, as well as disrupted
diurnal food intake and increased body mass. Serum leptin, glucose, cholesterol, and
triglyceride levels are also increased in Clock mutants compared to wild type mice. Mice
lacking the VIP-VPAC2 pathway which plays an important role in SCN communication
(Reppert & Weaver, 2001) have metabolic abnormalities similar to those in Clock mutant
mice (Bechtold, Brown, Luckman, & Piggins, 2008). Furthermore, consumption of a
high-fat diet alters circadian rhythmicity and the cycling of circadian clock genes in mice
(Kohsaka et al., 2007).
Because multiple studies have linked disruption of the molecular circadian clock
and metabolic disorders (Bechtold, Brown, Luckman, & Piggins, 2008; Rudic et al.,
31
2004; Turek et al., 2005), I hypothesized that exposure to light at night alters circadian
organization and affects metabolic parameters. I investigated the possibility of a direct
link between altered light cycles and metabolic disorder by housing mice in either a
standard light/dark cycle (LD; 16 h light at ~150 lux/8 h dark at ~0 lux), a light/dim light
cycle (dLAN; 16h light at ~150 lux/ 8h dim light at ~5 lux), or 24 h of continuous
lighting (LL; constant ~150 lux) and assessed metabolic parameters. I included a dLAN
group in addition to LL because mice in constant lighting have no temporal cue to
distinguish time of day, and their biological clocks free-run. The dLAN group may more
directly model environmental light pollution experienced in industrialized nations;
however, I predicted circadian alterations in daily activity would not be as profound in a
dLAN environment. By including the LL group, this study not only focused on the
effects of light pollution, but also on the effects of a desynchronized circadian system on
metabolism. I hypothesized that mice housed in dLAN and LL conditions would alter
metabolic parameters compared to mice housed in LD. More specifically, I hypothesized
that housing mice in dLAN and LL would result in reduced glucose tolerance and
increased body mass in comparison to LD-housed mice. I also hypothesized that mice
housed in LL and dLAN would alter stress levels as evaluated by circulating
corticosterone and that LL would induce locomotor arrhythmicity indicative of circadian
disruption.
Methods
Animals
32
Eighty male Swiss Webster mice (~8 weeks of age) were obtained from Charles
River Labs (Kingston, NY) for use in these studies. The mice were individually housed in
propylene cages (30 x 15 x 14 cm) at an ambient temperature of 22 ±2°C and provided
food (D12450B: 10% kcal% fat, 70% kcal% carbohydrate, 20% kcal protein; Research
Diets Inc., New Brunswick, NJ, USA) and water ad libutum. Upon arrival, all mice were
maintained under a 16:8 light/dark (lights on at 23:00 Eastern Standard Time [EST] ~130
lux) cycle for one week to allow them to entrain to local conditions and recover from the
effects of shipping. A 16:8 light dark cycle was used rather than 12:12 to avoid providing
a seasonally ambiguous signal. Because Swiss Websters are an outbred species and may
retain some responsiveness to photoperiod, mice might interpret a 12:12 light cycle as
either a long or short photoperiod, and thus impose higher variability in phenotype
(Nelson, 1990). All experimental procedures in this dissertation were approved by The
Ohio State University Institutional Animal Care and Use Committee, and animals were
maintained in accordance with the recommendations of the National Institutes of Health
and the Guide for the Care and Use of Laboratory Animals.
Experiment 1
Following the habituation period, mice were pseudo-randomly assigned to one of
three groups (n=10/group); mice were housed in either a standard light/dark cycle,
constant light, or a light/dim light cycle. Mice were weighed during group assignment to
establish that all groups had a similar baseline body mass. All mice weighing >35 grams
were excluded from the experiments. After group assignment, the LL mice were placed
in a constant light room (LL) where they were exposed to a constant amount of
33
continuous light (~150 lux). The dLAN mice were placed in a room with a 16:8 light/dim
cycle; during the light period they were exposed to ~150 lux of light and during the dim
period they were exposed to ~5 lux of light at cage level.
Food intake was measured daily immediately before the onset of the dark period
(15:00 EST) throughout the study and body mass was measured weekly. After 6 weeks in
light conditions food intake was measure twice daily, at the onset of the dark period
(15:00 EST) and onset of the light period (23:00 EST) in order to quantify timing of food
consumption (expressed as percentage: 100 x consumption light/(consumption light +
consumption dark)). Home cage activity was monitored during the 5th
and 6th
weeks in
light conditions; each room was monitored for 4 consecutive days including a weekend.
At week 4 mice underwent an intra-peritoneal glucose tolerance test (GTT). After 8
weeks in light conditions mice were killed by cervical dislocation at one of two time
points, either directly after the onset of darkness (between 15:00 and 17:00 EST) or
during the middle of the light phase (5:00 to 7:00 EST), in order to collect blood samples
at the peak and nadir of locomotor activity. Epididymal fat pads were also collected as an
index of white adipose tissue.
Experiment 2
Following the habituation period, mice were pseudo-randomly assigned a number
and divided into one of six groups (n=8-9/group); mice were housed in either LD or
dLAN and had either 24 h/day food access (FA; food weighed twice daily at 9:00 and
19:00 EST), food access during the dark phase (FD; food in: 9:00 EST, food out: 19:00
EST), or food access during the light phase (FL; food in 19:00 EST, food out: 9:00 EST).
34
After 7 weeks in light conditions mice underwent a series of three retro-orbital blood
collections with at least 48 h between collection points to assess serum corticosterone
concentrations. After 8 weeks in light conditions mice were killed by cervical dislocation
at one of two time points, either directly after the onset of darkness (10:00-12:00 EST) or
during the middle of the light phase (23:00-1:00 EST). Epididymal fat pads were
collected. All entrances into the animal rooms and collections after lights off were made
under dim red illumination.
Glucose tolerance test
The glucose tolerance test was given after four weeks in experimental light
conditions. Mice were administered a 1.5 g/kg body mass intra-peritoneal glucose bolus
at 10:00 EST after an 18 h fast. Blood samples of ~5 µL were collected via
submandibular bleed before injection, and at 15, 30, 60, 90, and 120 min following
injection. Blood glucose was immediately measured with the Contour blood glucose
monitoring system and corresponding test strips (Bayer HealthCare, Mishawaka, IN).
Activity analyses
Locomotor activity was tracked in 8 mice per group using OPTO M3 animal
activity monitors (Columbus Instruments, Columbus, OH) that continuously compile data
using MDI software system. Results from locomotor activity were used to determine
whether lack of physical activity or altered rhythmicity may have affected metabolism
(Laposky, Bass, Kohsaka, & Turek, 2008).
Blood collection and hormone analyses
35
Blood samples were then allowed to clot, had the clot removed, and were
centrifuged at 4°C for 30 min at 3300 g. Serum aliquots were aspirated and stored in
sealable polypropylene microcentrifuge tubes at -80°C for subsequent analysis. Total
serum corticosterone concentrations, for mice, was determined in duplicate in an assay
using an ICN Diagnostics 125
I double antibody kit (Costa Mesa, CA USA). The high and
low limits of detectability of the assay were 1200 and 3 ng/ml, respectively. The intra-
assay coefficient of variation was 7.00% for experiment 1 and 16.83% for experiment 2.
Statistical analyses
Hormone concentrations, total daily food consumption and total daily activity
were analyzed using a one-way analysis of variance (ANOVA). Following a significant
F score, multiple comparisons were conducted with Tukey‟s HSD tests. Glucose
tolerance test results were analyzed with a repeated measures ANOVA with lighting
condition as the within-subject factor and time as the between subject variable. A
repeated measures ANOVA was also used to analyze change in body mass over time.
Following a significant result on repeated measures ANOVA, single time point
comparisons were made using Student‟s t-tests. The above statistical analyses were
conducted with StatView software (v. 5.0.1, Cary, NC). Fourier analysis was used to
determine whether locomotor activity was rhythmic and followed 24 h periodicity using
Clocklab software from Actimetrics (Wilmette, IL). Mice were considered rhythmic
when the highest peak occurred at ~1 cycle per day with an absolute power of at least
0.005 mV/Hz as previously described (Kriegsfeld et al., 2008). Nonlinear regression
analysis was used in GraphPad Prism software (v. 4 La Jolla, CA). In all cases,
36
differences between group means and correlation coefficients were considered
statistically significant if p ≤ 0.05.
Results
Body mass
Body mass was differentially affected by light condition over the 8 experimental
weeks (F24,192 = 3.457; p < 0.0001; Fig. 1a). A significant increase in body mass among
LL and dLAM mice, relative to the LD control group, was evident beginning one week
after onset of light treatment and continuing throughout the 8 week study (F2,24 = 4.441,
10.187, 12.660, 12.232, 6.561, 4.568, 4.293 respectively, p ≤ 0.01). The elevated body
mass among LL and dLAN groups was due to increased body mass gain (F2,24 = 4.291; p
< 0.05; Fig 1b), rather than initial differences in body mass among groups. Furthermore,
epididymal fat pad mass was significantly greater at the end of the study in mice with
light at night suggesting increased body mass reflected increases in white adipose tissue
(F2,24 = 4.767; p < 0.05; Fig. 1b) .
Glucose tolerance test
After four weeks in experimental light conditions, LL and dLAN mice displayed
impaired glucose tolerance during an intra-peritoneal glucose tolerance test (GTT).
Injection of glucose increased blood glucose levels in all groups following an 18 hour fast
(F5,23 = 151.015; p < 0.0001; Fig. 1c). LL and dLAN mice failed to recover glucose
levels as rapidly as the LD group (F10,115 = 2.514; p < 0.01). dLAN mice significantly
elevated glucose levels after 60 min and glucose levels remained elevated after 90 and
120 min in dLAN and LL mice compared to the LD group (post hoc; p < 0.05).
37
Furthermore, final glucose levels in the GTT positively correlated with body mass (R =
0.5236; p < 0.05; Fig. 1d).
Locomotor Activity
In contrast to the LD and dLAN groups, which displayed the typical circadian
rhythm in locomotor activity, as measured in the home cage via an infrared beam
crossing system, the LL mice were arrhythmic (7 out of 8 arrhythmic as measured by
Fourier analysis; Fig. 2a-c). However, total daily locomotor activity was similar for all
groups (F2,153= 0.0002; p > 0.95; Fig. 2d).
Glucocorticoids
Corticosterone was decreased in the LL (p < 0.05; Fig. 3a), but not dLAN mice;
these results suggest that changes in glucocorticoid concentrations were not necessary for
altered metabolism.
Energy Intake
Total 24 h food consumption did not differ between groups (F2,24 = 0.107; p >
0.85). Although no differences in total food consumption and home cage locomotor
activity were detected between groups, feeding behavior was altered in the dLAN group
(F1,38 = 29.315; p ≤ 0.05; Fig. 3b). The dLAN mice consumed 55.5% of their food during
the light phase as compared to 36.5% in LD mice, indicating that mice exposed to LAN
ate more food during the day, rather than at night. LL mice were not considered in this
comparison because they had no temporal signal to distinguish the light and dark phase.
Furthermore, correlation analyses confirmed that percentage of daytime food
38
consumption was positively related to final body mass and final glucose levels in the
GTT (R = 0.5058 and R = 0.6066 respectively; p < 0.01; Fig. 3c/d).
Timed feeding
Because altered timing of food consumption may mediate changes in body mass
in the dLAN mice, I performed an additional experiment with mice housed in either LD
or dLAN with either continuous access to food (FA) or with food availability limited to
either the light (FL) or dark (FD) phase, respectively. Timed feeding affected body and
epididymal fat pad mass gain (F2,44 = 5.392 and 4.372 respectively; p < 0.05; Fig. 4a/b).
Within dLAN mice limiting food access to the dark phase prevented weight and fat gain
(weight: t14=1.940, fat: t14=2.526, p≤0.05). dLAN-FD mice gained an equivalent amount
of weight and fat as LD-FD mice and LD mice with 24h food access (weight: t14=-.250,
t14=-1.176 fat: t14=-.076, t14=-1.004; p > 0.05). Furthermore, FL mice increased body and
fat pad masses (post hoc, p < 0.05); this increase was not dependent on light/dark cycle
and LD- and dLAN-FL had comparable weight gain. There was no effect of light on
corticosterone concentrations at the 6 time points measured (p > 0.05). However, timed
feeding altered corticosterone concentrations at ZT 16 (F2,24 = 15.316; p < 0.05; Fig. 4c),
such that timed feeding during the dark phase increased corticosterone concentrations
(post hoc, p < 0.05). Food consumption changed over time such that consumption
decreased throughout the study (F6,258=664.474; p < 0.05; Table 1). Furthermore, there
was an interaction between timed feeding and food consumption over time (F12,258 =
98.051; p < 0.05), with timed feeding groups initially consuming more than mice with
food access all the time.
39
Discussion
Swiss-Webster mice were housed in either standard light/dark cycles, 24 h of
continuous lighting, or in light/dim cycles. A significant increase in body mass among
LL and dLAN mice, relative to the LD control group, was evident beginning one week
after onset of light treatment and continuing throughout the 8-week study. After four
weeks, LL and dLAN mice displayed impaired glucose tolerance during an intra-
peritoneal glucose tolerance test; the mice with dLAN failed to recover glucose levels as
effectively as the LD group. Increased body mass and reduced glucose tolerance are
indicative of a pre-diabetic-like state (Kahn, Hull, & Utzschneider, 2006). Thus, as little
as 5 lux of light exposure during the typical dark period is sufficient to increase body
mass and compromise glucose regulation.
Total daily locomotor activity, as measured in the home cage via an infrared beam
crossing system, was similar for all groups. However, in contrast to the LD and dLAN
groups, that displayed the typical circadian rhythm in locomotor activity, the LL mice
were arrhythmic. Although no differences in total daily food consumption were detected
between groups, feeding behavior was altered in the dLAN group. The dLAN mice
consumed 55.5% of their food during the light phase as compared to 36.5% in LD mice,
indicating that mice exposed to dLAN ate more food during the day, rather than at night.
LL mice were not considered in this comparison because they had no temporal signal to
distinguish the light and dark phase. Again, total 24 h consumption did not differ among
groups, but food intake is substantially higher at night among nocturnal rodents (Zucker,
1971) and altered timing of food consumption has been associated with metabolic
40
syndrome in other animal models (Arble, Bass, Laposky, Vitaterna, & Turek, 2009;
Turek et al., 2005). Correlation analyses confirmed that percentage of daytime food
consumption was positively related to final body mass and final glucose levels in the
GTT.
To establish whether the altered timing of food intake contributed to the increased
weight gain, I performed an additional study with a timed feeding schedule. Because
mice housed in LL would likely entrain to the time of food access, they were omitted
from the food access iteration (Mistlberger, 2009). Mice were housed in either LD or
dLAN with either 24 h ad libitum access to food, food access only during the light phase,
or food access only during the dark/dim phase. Restricting food availability to the dark
phase prevented weight and fat gain among dLAN mice. dLAN-FD mice gained an
equivalent amount of weight and fat as LD-FD mice and LD mice with no food
restriction. This further suggests that altered timing of food consumption in the dLAN
mice leads to increased body mass gain. As previously reported for rats and mice, FL
mice increased body mass; this increase was not dependent on light/dark cycle and LD-
and dLAN-FL had comparable weight gain. Mice with limited access to food displayed
an initial spike in consumption that decreased over time. When food access was limited
to the light phase, mice displayed an increased elevation in food consumption during
week one; however, mice with access to food limited to the dark phase consumed more
food in subsequent weeks. Again, overall food intake for the study was comparable
among all groups suggesting that the timing of food intake is a critical factor mediating
increased weight gain.
41
Alterations in light cycles are typically considered to be stressful; the results of
previous research on the effects of LAN on glucocorticoid concentrations, however, are
equivocal (Abilio, Freitas, Dolnikoff, Castrucci, & Frussa-Filho, 1999; Fonken et al.,
2009). Because high glucocorticoid concentrations can alter metabolism resulting in
obesity I measured circulating glucocorticoids (Dallman et al., 2004). Contrary to my
predictions, corticosterone was decreased in the LL, but not dLAN mice, which suggests
that changes in glucocorticoid concentrations were unnecessary for altered metabolism.
The decreased corticosterone concentrations in the LL mice likely reflect masking of the
glucocorticoid rhythm. Glucocorticoid concentrations were affected by food restriction.
Mice with food access during the dark phase had elevated peak glucocorticoid
concentrations. There were no differences in glucocorticoid concentrations between
dLAN and LD mice that were on the FA or FL feeding schedules.
These results establish that night-time illumination at a level as low as 5 lux is
sufficient to uncouple timing of food consumption and locomotor activity resulting in
metabolic abnormalities. dLAN mice display desynchrony between internal metabolic
activity and food intake, as demonstrated by altered timing of food consumption; this
may be the primary factor leading to increased weight gain. Similarly, in LL mice the
arrhythmic home cage activity suggests that there may be desynchrony between food
intake and metabolic parameters leading to increased weight gain by a similar but distinct
mechanism. Mice exposed to LAN may have disrupted melatonin signaling leading to a
misalignment of food intake and activity resulting in altered fuel metabolism. Melatonin
concentrations have been relatively unexplored in Swiss-Webster mice, however, retinal
42
melatonin levels were undetectable in one previous study in common with melatonin
values in common strains of laboratory mice such as C57Bl/6 (Tosini & Menaker, 1998).
Although previous research failed to detect melatonin in many strains of mice (Goto,
Oshima, Tomita, & Ebihara, 1989), more recent studies report attenuated, but rhythmic,
melatonin expression in strains such as C57Bl/6 which were previously thought void of
melatonin (Kennaway, Voultsios, Varcoe, & Moyer, 2002). Melatonin rhythmicity, rather
than absolute quantities of nightly melatonin secretion, plays a crucial role in metabolic
function (Korkmaz, Topal, Tan, & Reiter, 2009). For example blunted nighttime
melatonin rhythms due to LL increased visceral adiposity in rats (Wideman & Murphy,
2009) and daily administration of melatonin suppressed abdominal fat and plasma leptin
levels (Rasmussen, Boldt, Wilkinson, Yellon, & Matsumoto, 1999). Furthermore,
melatonin influences clock gene expression in peripheral tissues such as the heart
(Zeman, Szantoova, Stebelova, Mravec, & Herichova, 2009) and may similarly modulate
clock gene expression in peripheral tissue involved in metabolism.
Mice exposed to LAN may also have disrupted clock expression leading to altered
metabolism. The SCN are the primary pacemaker at the top of a hierarchy of temporal
regulatory systems wherein multiple peripheral tissues contain molecular machinery
necessary for self-sustaining circadian oscillation (Kohsaka & Bass, 2007). In addition to
becoming obese, mice fed a high fat diet have disrupted mClock expression in the liver
(Kohsaka et al., 2007) and mice with mutations in clock genes have altered energy
homeostasis (Turek et al., 2005). Moreover, mice with mutations in either Clock or Bmal1
show impaired glucose tolerance, reduced insulin secretion, and defects in the
43
proliferation and size of pancreatic islets (Marcheva et al., 2010). Several models of
obesity have reported attenuated amplitude of circadian clock gene expression and
changes in the phase and daily rhythm of clock genes may cause obesity (Barnea, Madar,
& Froy, 2009).
Metabolism and the circadian clock are intrinsically related (K. Eckel-Mahan &
Sassone-Corsi, 2009) with desynchrony of feeding and activity causing metabolic
alterations (Arble, Bass, Laposky, Vitaterna, & Turek, 2009; Salgado-Delgado, Angeles-
Castellanos, Saderi, Buijs, & Escobar, 2010). In humans even brief circadian
misalignment results in adverse metabolic and cardiovascular consequences (Scheer,
Hilton, Mantzoros, & Shea, 2009). The seemingly innocuous environmental light
manipulation used in this study that changed feeding behavior resulting in obesity may
have important implications for humans. Patients with night-eating syndrome are obese
and appear to display circadian rhythm disruption (Benca et al., 2009; Stunkard, Grace, &
Wolff, 1955). More generally, prolonged computer use and television viewing have been
identified as risk factors for obesity, diabetes, and metabolic disorders (Fung et al., 2000).
For the most part, researchers considering this correlation have focused on the lack of
physical activity associated with television and computer use; however the results from
the current study suggest that exposure to nighttime lighting and the resulting changes in
the daily pattern of food intake and activity may also be contributing factors.
44
Mean ± SEM daily food intake (g)
Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7
LD-FA 4.7 ± 0.2 4.5 ± 0.1 4.2 ± 0.1 4.0 ± 0.1 3.9 ± 0.1 3.4 ± 0.1 3.7 ± 0.2
LD-FD 5.1 ± 0.2 4.6 ± 0.1 4.2 ± 0.2 4.3 ± 0.2 4.1 ± 0.1 3.7 ± 0.1 3.8 ± 0.1
LD-FL 5.7 ± 0.2 4.9 ± 0.1 4.1 ± 0.2 3.8 ± 0.1 3.8 ± 0.1 3.8 ± 0.1 3.8 ± 0.1
DM-FA 4.7 ± 0.1 4.6 ± 0.1 4.5 ± 0.2 4.1 ± 0.1 3.8 ± 0.1 3.6 ± 0.2 3.8 ± 0.2
DM-FD 5.4 ± 0.2 4.5 ± 0.2 4.2 ± 0.1 4.2 ± 0.1 4.0 ± 0.1 4.2 ± 0.1 4.0 ± 0.1
DM-FL 5.8 ± 0.3 4.8 ± 0.1 4.3 ± 0.1 3.9 ± 0.1 3.7 ± 0.2 3.7 ± 0.2 3.5 ± 0.2
...... Table 2.1. Food intake in food restricted mice exposed to dimly lit or dark nights.
44
45
Figures
0 30 60 90 120
0
100
200
300
400
LDdLANLL
+
* *
Time (min)
Glu
co
se (
% b
aseli
ne)
0 1 2 3 4 5 6 7 825
30
35
40
45
LDdLAN
*
***
*
**
LL
&
Weeks
Bo
dy m
ass (
g)
LD dLAN LL0
4
8
12*
*
Bo
dy m
ass g
ain
(g
)
LD dLAN LL0
1
2
3
.06 *
Ep
idid
ym
al
fat
(g)
32 34 36 38 40 42 44 46 48
100
200
300
400
500
R=0.5236p=0.0036
Body mass (g)
Fin
al
glu
co
se (
mg
/dl)
A
C
B
D
Figure 2.1. Light at night affects body mass and glucose tolerance.
Body mass, fat pad mass, and glucose tolerance in mice exposed dark or lit nights. (A)
Mice with light at night elevated body mass beginning one week after placement in light
conditions and continuing throughout the remainder of the study. (B) Body mass gain and
epididymal fat pad mass differed among groups at the conclusion of the study suggesting
increases in body mass may be due to changes in body fat composition (C) Mice exposed
to either dim or bright light at night had reduced glucose tolerance; dLAN and LL mice
failed to recover blood glucose as rapidly as LD mice (D) Furthermore, body mass at the
time of the glucose tolerance test positively correlated with final blood glucose levels.
*p≤0.05 when LD differs from both groups, &p≤0.05 between all groups.
46
Figure 2.2. Activity is comparable between mice exposed to dimly lit and dark nights.
Representative activity records from mice held in (A) a standard light/dark cycle (B) a
light/dim cycle and (C) constant lighting. Homecage locomotor activity was measured in
an infrared beam crossing system and is shown in a double plotted actogram. LL mice
became arrhythmic in constant light, however dLAN mice maintained rhythmicity. (D)
All mice had equivalent total 24 h activity (p>0.05).
47
LD dLAN LL0
25
50
75
100
125Light
Dark/Dim
*
Seru
m c
ort
ico
ste
ron
e
(n
g/m
l)
20 30 40 50 60 70 80 9030
35
40
45
50
R=0.5058p=0.006
% Daytime consumption
Fin
al
bo
dy m
ass (
g)
LD dLAN LL0
10
20
30
40
50
60
70
80
*
*
% D
ayti
me f
oo
d
co
nsu
mp
tio
n20 30 40 50 60 70 80 90
100
200
300
400
500R=0.6066p=0.0005
% Daytime consumptionF
inal
glu
co
se (
mg
/dl)
A
C D
B
Figure 2.3. Time of food intake but not corticosterone is altered by dim light at night.
(A) Serum corticosterone concentrations were reduced in the LL but not dLAN mice at
the two time points measured suggesting that glucocorticoids did not mediate the changes
in body mass (*p≤0.05 from LL and dLAN). (B) Mice exposed to bright and dim light at
night ate more food during the light phase than in the dark phase which is atypical in
nocturnal animals (*p≤0.05). (C) Body mass and (D) blood glucose levels are associated
with percentage of daytime food consumption.
48
FA FD FL FA FD FL30
35
40
45
LD dLAN
#
†
Bo
dy m
ass g
ain
(g
)
0 4 8 12 16 20 240
50
100
150
200
250
300 FA
FD
FL
*
LD
Time (hrs)
Seru
m c
ort
ico
ste
ron
e (
ng
/mL
)
FA FD FL FA FD FL0
1
2
3#
†
Ep
idid
ym
al
fat
(g)
0 4 8 12 16 20 240
50
100
150
200
250
300*dLAN
Time (hrs)
A B
C
Figure 2.4. Restricting feeding to the dark phase prevents dim light at night induced
body mass gain.
Body mass gain and epididymal fat pad mass differed between groups at the conclusion
of the study (A) Total body mass gain and (B) epididymal fat pad mass (*p≤0.05 when
group differs from LD, †p≤0.05 when FD differs from both). Timed feeding during the
dark in mice with light at night prevented increased weight gain and elevated epididymal
fat pad mass. (C) Serum corticosterone concentrations are altered by timed feeding.
Feeding mice during the dark resulted in increased corticosterone concentrations at
Zeitgeber Time (ZT) 16 irrespective of light condition (*p≤0.05 FD differs from FA and
FL).
49
CHAPTER 3
DARK NIGHTS REVERSE METABOLIC CHANGES CAUSED BY DIM LIGHT
AT NIGHT
Metabolic disorders are increasing in prevalence worldwide and represent a major
global health threat. The metabolic syndrome is categorized by the development of
several metabolic abnormalities that increase the risk of coronary artery disease, stroke,
and diabetes. Hypercaloric food intake and physical lethargy are known to underlie the
development of metabolic syndrome and obesity. However, additional nontraditional
factors are likely involved. The increasing prevalence of metabolic disorders coincides
with increasing exposure to light at night (Fonken & Nelson, 2011; Reiter, Tan,
Korkmaz, & Ma, 2011; Wyse, Selman, Page, Coogan, & Hazlerigg, 2011). Recent
epidemiological and experimental studies implicate the introduction of artificial light in
the development of metabolic syndrome (Maury, Ramsey, & Bass, 2010). Indeed, shift-
workers who experience high levels of light at night are at increased risk for
cardiovascular disease (Ha & Park, 2005; Knutsson, 2003) and elevated body mass index
(Parkes, 2002). Even brief behavioral and circadian misalignment alters metabolic
homeostasis in humans, resulting in hyperglycemia, hyperinsulinemia, and postprandial
50
glucose levels comparable to a pre-diabetic state (Scheer, Hilton, Mantzoros, & Shea,
2009). Moreover, in rodent models exposure to light at night produces changes in
metabolism (Fonken et al., 2010; Vinogradova, Anisimov, Bukalev, Semenchenko, &
Zabezhinski, 2009; Wideman & Murphy, 2009).
Metabolic processes fluctuate throughout the day. The suprachiasmatic nuclei
(SCN) of the hypothalamus comprise the master circadian clock in mammals and control
physiological and behavioral circadian rhythms. Photic input to the SCN is the dominant
cue for entraining the circadian clock. Light travels directly from intrinsically
photosensitive retinal ganglion cells (ipRGCs) to the SCN via the retino-hypothalamic
tract (RHT). Prior to the wide-spread adoption of electric lighting the circadian system
was principally synchronized to the solar cycle. In contrast, modern light exposure occurs
in a variety of patterns. Because of the importance of light in synchronizing the circadian
system, exposure to aberrant light schedules disrupt circadian activity. Disruption in the
clock gene network is linked to changes in sleep, body mass, locomotor activity, and food
intake. Homozygous Clock mutant mice have significant increases in energy intake and
body weight, and total arrhythmicity when housed in constant darkness (Turek et al.,
2005). These mutants also showed dyslipidemia, hyperglycemia, and hypoinsulinemia-
all markers of metabolic dysregulation (Turek et al., 2005). Manipulation of other genes
in the clock gene family similarly cause metabolic abnormalities (Marcheva et al., 2010).
Interactions between metabolism and the circadian system appear to be reciprocal as diet
induced obesity alters the period of the central clock and dampens diurnal rhythm in
locomotor activity (K. Eckel-Mahan & Sassone-Corsi, 2009; Kohsaka et al., 2007). Both
51
short and long duration exposure to light at night or constant light also produce symptoms
of metabolic syndrome (Fonken et al., 2010; Vinogradova, 2007; Vinogradova,
Anisimov, Bukalev, Semenchenko, & Zabezhinski, 2009).
Although the SCN is the dominant brain region involved in driving circadian
activity, peripheral clock mechanisms are present throughout the body. Metabolic tissues
such as liver, adipose, pancreas, and muscle all display independent rhythmic clock gene
expression. The SCN principally regulates peripheral clock activity through neural and
endocrine signaling pathways (Guo, Brewer, Champhekar, Harris, & Bittman, 2005;
McNamara et al., 2001). Extra-SCN clock activity occurs in a tissue-specific manner
which enables organs to cope with local physiological demands and respond to local
factors. Multiple signals related to feeding and fasting entrain clock activity in metabolic
tissue. Environmental cues that occur at aberrant times may lead to asynchronous activity
within or between tissues which can lead to organ dysfunction (Vollmers et al., 2009).
For example, changes in peripheral clock function contribute to symptoms of metabolic
syndrome such as body weight gain and reduced glucose tolerance (Carvas et al., 2012;
Kennaway, Owens, Voultsios, Boden, & Varcoe, 2007; Lamia, Storch, & Weitz, 2008).
We previously reported that constant light (LL) and a bright/dim light cycles
(dLAN) alter metabolic parameters in mice (Fonken et al., 2010). Mice housed in LL and
dLAN increase body mass and white adipose tissue, impair glucose processing, and alter
food intake patterns compared to mice housed in LD. dLAN mice consume more food
during the light period than at night which is atypical in nocturnal rodents (Fonken et al.,
2010). Altered timing of food intake could be the mechanism by which light at night
52
induces weight gain as it has previously been shown to induce metabolic disorder (Arble,
Bass, Laposky, Vitaterna, & Turek, 2009) and uncouple central and peripheral clock gene
expression (Damiola et al., 2000). The goal of the present experiment was to determine
whether or not changes in metabolism dissipate after removal of the aberrant light
schedule. Studies in shift-workers offer contrasting views about whether removing
circadian disruption can produce a return to baseline state. For example, current shift-
workers increase systemic markers of inflammation, but former shift workers do not
differ from day shift controls (Puttonen, Viitasalo, & Harma, 2011). However, former
shift workers have increased risk for obesity (Puttonen, Viitasalo, & Harma, 2011). Thus,
I tested whether metabolic disruption that occurs with light at night is an enduring effect
following placement back in a standard light dark cycle. Mice were housed under dim
light at night for 4 weeks and then transferred back to a standard light dark cycle.
Placement back into dark nights ameliorated the effects of exposure to dim light at night.
This suggests that changes in metabolism that occur with nighttime light exposure are not
necessarily permanent.
Methods
Animals
Sixty male Swiss-Webster mice (~8 weeks of age) from Charles River Kingston
were used in this study. Nocturnal rodents were used in this study to investigate the
effects of nighttime light exposure independent of sleep disruption. The mice were
individually housed in propylene cages (dimensions: 27.8 x 7.5 x 13 cm) at an ambient
temperature of 22 ±2°C and provided with Harlan Teklad 8640 food (Madison, WI) and
53
filtered tap water ad libitum. All mice appeared healthy throughout the study and showed
no signs of sickness behavior.
Mice were assigned to one of four groups: (1) a control group that remained in
standard light-dark conditions [14h light (150 lux): 10h dark (0 lux); LD/LD] for the 8
weeks study, (2) a group housed in dim light at night for 8 weeks [14h light (150 lux):
10h dim (5 lux); dLAN/dLAN], (3) a group housed in LD for 4 weeks, then 4 weeks of
dLAN (LD/dLAN), and (4) a group housed in dLAN for 4 weeks then 4 weeks of LD
(dLAN/LD). All mice were housed in LD for one week to entrain to the local light-dark
cycle and recover from the effects of shipping prior to entering the study. On day 1 of the
experiment mice were weighed and transferred from an LD room to a cabinet with either
an LD or dLAN light cycle. Body mass was measured weekly and glucose tolerance was
evaluated after 7 weeks in experimental conditions. After 6 weeks in lighting conditions
timing of food intake was measured for 4 consecutive days. At the conclusions of the
study mice were anesthetized with isoflurane vapors and rapidly decapitated. Epididymal
fat pads of mice that underwent the glucose tolerance test were collected and weighed
and then flash frozen for qPCR analyses.
54
Table 3.1. Experimental design for Chapter 3.
Quantitative PCR (qPCR)
The mRNA levels of MAC1, IL6, and TNFα were assayed in epididymal fat pads
as an index of peripheral inflammation (Reed et al., 2010). A small portion of the distal
epididymal fat pad was collected and flash frozen at the conclusion of the study. Total
RNA was extracted using a homogenizer (Ultra-Turrax T8, IKAWorks, Wilmington, NC)
and an RNeasy Mini Kit (Qiagen, Austin, TX). RNA was reverse transcribed into cDNA
with M-MLV Reverse Transcriptase enzyme (Invitrogen, Carlsbad, CA) according to the
manufacturer‟s protocol. Gene expression for MAC1 was determined using inventoried
primer and probe assays (Applied Biosystems, Foster City, CA) on an ABI 7500 Fast
Real Time PCR System using Taqman® Universal PCR Master Mix. The universal two-
step RT-PCR cycling conditions used were: 50 °C for 2 min, 95 °C for 10 min, followed
by 40 cycles of 95 °C for 15 s and 60 °C for 1 min. Relative gene expression of
55
individual samples run in duplicate was calculated by comparison to a relative standard
curve and standardized by comparison to 18S rRNA signal.
Intra-peritoneal glucose tolerance test (GTT)
After 7 weeks in experimental light conditions a subset of each group of mice was
administered an intra-peritoneal glucose bolus (1.5 g/kg body mass) after an 18 h fast.
Blood samples of 5 µL were collected via submandibular bleed before injection and at
15, 30, 60, 120, and 180 min following injection. Blood glucose was measured
immediately with a Contour blood glucose monitoring system and corresponding test
strips (Bayer HealthCare, Mishawaka, IN).
Statistical analyses
Body mass and glucose tolerance test were compared between groups using
repeated measures analysis of variance (ANOVA). Body mass gain, fat pad mass, gene
expression, and food intake comparisons were analyzed using one-way ANOVA.
Following a significant F score, multiple comparisons were conducted with Tukey‟s HSD
tests. The above statistical analyses were conducted with StatView software (v. 5.0.1,
Cary, NC). In all cases, differences between group means were considered statistically
significant if p ≤ 0.05.
Results
Body mass
Body mass was significantly affected by light conditions over the 8 experimental
weeks (F21,336 = 3.537; p < 0.0001; Fig. 1A). After 4 weeks in their respective lighting
conditions, and prior to the light schedule transfer, significant differences in weight gain
56
were observed (F3,50 = 3.710; p < 0.05). Both groups that were initially housed under
dLAN showed elevated body mass gain compared to those housed in standard lighting
conditions (post hoc analyses; p < 0.05; Fig 1B). Directly following collection of week 4
body weights mice in the dLAN/LD and LD/dLAN groups were transferred to the new
light schedules. After 3 weeks of the new lighting schedules body mass gain was also
significantly affected by lighting conditions (F3,50 = 3.906 from beginning of study; Fig
1C; F3,50 = 8.862 from transfer; Fig. 1D; p < 0.05 respectively). LD/dLAN and
dLAN/dLAN mice gained significantly more weight throughout the study as compared to
LD/LD mice (post hoc; p < 0.05; Fig 1C). dLAN/LD mice did not differ from any group
with respect to weight gain when evaluating the entire 7 week period. When evaluating
body mass gain following the transfer however, dLAN/LD mice significantly reduced
weigh gain compared to dLAN/dLAN and LD/dLAN mice (post hoc; p < 0.05; Fig 1D).
Relative epididymal fat pad mass (corrected for total body mass), a representative
measure of white adipose tissue, significantly differed by the conclusion of the study
(F3,31 = 4.089; p < 0.05; Fig. 2A). Mice that were housed with dLAN for the entirety of
the study showed significantly elevated relative epididymal fat pad mass as compared to
LD/LD and dLAN/LD mice. LD/dLAN mice also had significantly elevated fat pad mass
as compared to LD/LD mice (post hoc; p < 0.05). These results are particularly important
because they suggest that increases in body mass among dLAN mice reflect increases in
white adipose tissue (Rogers & Webb, 1980). Furthermore, these results demonstrate that
a switch back to a standard light dark cycle after 4 weeks of housing in dLAN allows
57
restoration of fat levels to those of LD/LD mice. Lighting conditions did not affect paired
testes, epididymides, spleen, or adrenal mass (p > 0.05 in each case).
Gene expression
MAC1 mRNA expression in epididymal fat pads was significantly affected by
lighting conditions (F3,31 = 2.948; p < 0.05; Fig. 2B). dLAN/dLAN mice elevated MAC1
expression as compared to both LD/LD and dLAN/LD mice (post hoc; p < 0.05). In
contrast, expression of IL6 and TNFα in the fat pads did not significantly differ between
groups (data not shown, p > 0.05).
Glucose tolerance test
Three weeks after the transfer to the new lighting schedules (7 experimental
weeks) mice underwent a GTT. Injection of glucose led to a rapid increase in blood
glucose levels in all groups (F5,155 = 267.514; p < 0.0001; Fig 3A). Furthermore, there
was a significant interaction between lighting conditions and blood glucose levels over
time (F15,155 = 2.427; p < 0.005), such that dLAN/dLAN mice failed to recover glucose
levels as effectively as all other groups. Single time point comparisons revealed that
glucose levels were significantly elevated in dLAN/dLAN mice as compared to LD/LD
mice at T60 and as compared to all other groups at T120 and T180 (F3,31 = 3.285, 4.879,
4.622, respectively; p < 0.05). These results suggest that dysregulation in glucose
processing is secondary to increased weight gain as the LD/dLAN groups does not yet
show impairments in glucose tolerance. Furthermore, the improvement in glucose
processing in the dLAN/LD group suggests that impairments in glucose regulation are
reversible among dLAN mice by a transfer back to standard lighting conditions.
58
Energy intake
Total 24 h food intake did not differ among groups (p > 0.05). There was a main
effect of light cycle on timing of food intake (F3,31 = 3.912; p < 0.05; Fig. 3B);
dLAN/dLAN and LD/dLAN mice consumed significantly more of their food during the
light phase as compared LD/LD mice (post hoc; p < 0.05). LD/dLAN also consumed
significantly more food during the light phase than dLAN/LD mice (post hoc; p < 0.05).
Discussion
The goal of the current study was to determine whether mice returned to dark
nights after dLAN exposure recover metabolic function. This study replicates previous
results demonstrating that mice housed with dim light at night develop symptoms of
metabolic syndrome (Fonken et al., 2010). As expected, both groups of mice housed in
dLAN for the initial segment of the experiment (dLAN/dLAN and dLAN/LD)
significantly increased body mass gain compared to LD mice. Half of the dLAN mice
(dLAN/LD) were then transferred to LD and vice versa (LD/dLAN). Following the
transfer dLAN/dLAN and LD/dLAN mice gained significantly more weight than LD/LD
and dLAN/LD mice. At the conclusion of the study dLAN/LD mice did not differ from
either LD/LD or dLAN/dLAN mice with respect to body mass gain. The intermediary
results of the dLAN/LD mice may reflect an inability to completely recover body mass
after the 4 week exposure to LAN. This would indicate permanent changes in metabolism
occur after nighttime light exposure. Former shift workers show symptoms of metabolic
dysfunction after return to a day shift schedule which indicates that this may be the case
in humans (Puttonen, Viitasalo, & Harma, 2011). However, in the study on shift workers
59
there was no specified duration of time workers were on the non-shifting schedule. An
alternative explanation to the findings is that 3 weeks in LD may be insufficient to
completely recover body mass to LD levels. For example, recovery of other metabolic
markers can occur prior to reduction in body mass (Poudyal, Panchal, Ward, Waanders,
& Brown, 2012). Food intake patterns, epididymal fat pad mass, as well as the GTT
results support the latter hypothesis.
In agreement with previous findings, dLAN/dLAN mice shifted the timing of
food intake compared to LD/LD controls without changing the amount consumed.
dLAN/dLAN mice ate a significantly higher percentage of food during the light phase
which is atypical for nocturnal rodents and may contribute to weight gain. Consuming
higher amounts of food during the light phase is associated with increased weight gain in
rodents (Arble, Bass, Laposky, Vitaterna, & Turek, 2009). Moreover, restricting food
intake to the dark phase can prevent weight gain in mice fed a high fat diet (Hatori et al.,
2012; Sherman et al., 2012). Three weeks after dLAN/LD mice were moved back to LD,
food intake no longer differed from LD/LD controls. In contrast, LD/dLAN mice shifted
food intake to the light phase, with similar levels of daytime consumption as
dLAN/dLAN mice. These results suggest that 3 weeks of dLAN is sufficient to induce
altered timing of food intake.
Reduced glucose tolerance is a key symptom of metabolic syndrome (Kahn, Hull,
& Utzschneider, 2006). Here I show that impaired glucose clearance abilities associated
with dLAN are recovered by 3 weeks of exposure to LD. After 7 weeks in lighting
conditions mice underwent a glucose tolerance test. dLAN/dLAN mice showed
60
significantly reduced glucose tolerance compared to all other groups. Importantly, the
dLAN/LD group was comparable to LD/LD controls in the GTT. This suggests that
dLAN/LD mice recover glucose processing abilities. Although dLAN/LD mice did not
show a complete reduction in body mass, the GTT results suggest that metabolic function
is restored.
Increases in body mass in dLAN are associated with increased white adipose
tissue (Fonken et al., 2010). dLAN/dLAN mice displayed significantly elevated
epididymal fat pad masses compared to LD/LD mice indicating increases in body mass in
dLAN are due to increased fat depots. At the conclusion of the study, dLAN/LD mice
had significantly reduced white adipose tissue compared to dLAN/dLAN mice.
Furthermore, LD/dLAN mice had intermediary fat pad mass compared to the LD/LD and
dLAN/dLAN groups. Elevated fat mass is associated with widespread chronic low-grade
inflammation in peripheral metabolic tissue which led us to evaluate levels of
macrophage expression in the epididymal fat pads (Marceau et al., 1999; Plomgaard et
al., 2005). dLAN/dLAN mice significantly elevated expression of MAC1, a marker for
macrophages, in the epididymal fat pads. This indicates that there is increased
macrophage infiltration into peripheral fat tissue. Peripheral inflammation can lead to
disrupted insulin and leptin signaling further propagating fat accumulation (Hotamisligil,
2006). LD/dLAN mice had intermediary level of MAC1 expression compared to LD/LD
and dLAN/dLAN mice whereas dLAN/LD mice had comparable MAC1 expression to
LD/LD controls. This suggests that increases in peripheral inflammation are associated
metabolic dysfunction following exposure to dLAN.
61
This study also provides important insight into the time-course of development of
metabolic syndrome in dLAN. For example, altered timing of feeding likely precede
changes in glucose clearance as LD/dLAN mice did not differ in the GTT compared to
LD/LD controls although they already showed a pattern of food intake similar to
dLAN/dLAN mice. As discussed above, timing of food intake is a critical factor in the
development of metabolic disease (Arble, Bass, Laposky, Vitaterna, & Turek, 2009;
Hatori et al., 2012) and light at night likely elevates body mass gain through altering time
of food intake (Fonken et al., 2010). Additionally, changes in weight gain appear to occur
prior to the development of glucose intolerance because LD/dLAN mice show elevated
weight gain but do not have impairments in the GTT. This would be consistent with other
models of obesity in which adipose tissue releases factors (such as non-esterified fatty
acids, glycerol, pro-inflammatory cytokines, etc.) that can contribute to the development
of insulin resistance and β-cell dysfunction (Kahn, Hull, & Utzschneider, 2006).
Overall, these results demonstrate that re-exposure to dark nights ameliorates
metabolic disruption caused by dim light at night. dLAN appears as an innocuous
environmental manipulation, which may be why it was overlooked as a significant risk
factor for health and disease for many years. However, because of the profound affect
light has on the circadian system and upon downstream outputs such as hormone
secretion, dLAN likely exerts a significant effect on many physiological processes. The
circadian clock and metabolic pathways are intrinsically linked (Dallmann, Viola,
Tarokh, Cajochen, & Brown, 2012; K. Eckel-Mahan & Sassone-Corsi, 2009) with
desynchrony of feeding and activity causing metabolic alterations (Arble, Bass, Laposky,
62
Vitaterna, & Turek, 2009; Salgado-Delgado, Angeles-Castellanos, Saderi, Buijs, &
Escobar, 2010). In humans even brief circadian misalignment results in adverse
metabolic and cardiovascular consequences (Scheer, Hilton, Mantzoros, & Shea, 2009).
The findings presented here suggest that exposure to nighttime lighting and the resulting
changes in the daily pattern of food intake may be contributing factors in the current
obesity epidemic. If these results apply to humans, then humans who experience weight
gain in response to exposure to dim light at night may be able to help manage body
weight by adjusting when they eat or by using low cost light blocking interventions such
as sleep masks.
63
Figures
0 1 2 3 4 5 6 730
33
36
39
42
45
LD/LDdLAN/dLANdLAN/LDLD/dLAN
Weeks
Bo
dy m
ass (
g)
LD/L
D
dLAN/d
LAN
LD/d
LAN
dLAN/L
D0
2
4
6
8
10
A A
B
B
Bo
dy m
ass g
ain
befo
re t
ran
sft
er
(g-g
)
LD/L
D
dLAN/d
LAN
LD/d
LAN
dLAN/L
D0
2
4
6
8
10
12
A
B
ABB
Fin
al
bo
dy m
ass
gain
(g
-g)
LD/L
D
dLAN/d
LAN
LD/d
LAN
dLAN/L
D0
1
2
3
4
5
B
B
A AB
od
y m
ass g
ain
fro
m t
ran
sfe
r (g
-g)
A B
C D
Figure 3.1. Return to dark nights affects body mass after exposure to dim light at night.
Body mass was differentially affected by the lighting conditions throughout the study.
(A) Weekly body mass for mice over the course of the study. (B) Body mass gain after 4
weeks of lighting conditions and prior to the transfer. (C) Body mass gain at the
conclusion of the study. (D) Body mass gain from the point of the transfer at
experimental week 4 (different letters denote differences between groups, p≤0.05).
64
LD/L
D
dLAN/d
LAN
LD/d
LAN
dLAN/L
D0
1
2
3
4
5
6
A
BBC
ACR
ela
tive e
pid
idym
al
fat
mass (
% b
od
y m
ass)
LD/L
D
dLAN/d
LAN
LD/d
LAN
dLAN/L
D0.0
0.3
0.6
0.9
1.2
1.5
1.8
A
A
B
AB
Rela
tive M
AC
1 m
RN
A
exp
ressio
n i
n f
at
A B
Figure 3.2. Dim light at night affects fat mass and composition.
dLAN increased relative fat pad mass and macrophage gene expression in fat pads. (A)
Relative epididymal fat pad mass at the conclusion of the study. (B) Relative MAC1
mRNA expression from epididymal fat pads (different letters denote differences between
groups, p≤0.05).
65
0 30 60 90 120 150 1800
100
200
300
400
500
600LD/LDdLAN/dLANLD/dLANdLAN/LD
†
*
*
Time
Glu
co
se
(m
g/d
L)
LD/L
D
dLAN/d
LAN
LD/d
LAN
dLAN/L
D0
10
20
30
40
50
60
70
A
BCC
AB
% D
ay
tim
e c
on
su
mp
tio
n
A B
Figure 3.3. Dark nights reverse changes in feeding behavior and glucose processing
(A) Glucose tolerance was evaluated after 7 weeks in lighting conditions (*indicates
LD/LD and dLAN/dLAN differ, †indicates dLAN/dLAN differs from LD/LD,
LD/dLAN, and dLAN/LD). (B) Percentage of food consumed during the light phase
(different letters denote differences between groups, p≤0.05).
66
CHAPTER 4
DIM LIGHT AT NIGHT EXAGGERATES WEIGHT GAIN AND
INFLAMMATION ASSOCIATED WITH A HIGH FAT DIET
Obesity is a significant public health problem that reduces quality of life,
increases mortality risk, and is a financial burden on society (Y. Wang, Beydoun, Liang,
Caballero, & Kumanyika, 2008). Once termed a disease of western societies it is now
clear that prevalence rates are increasing on a global scale (WHO, 2000). Health
problems associated with obesity are replacing concerns such as under nutrition and
infectious disease as the most significant contributors to global ill health (Antipatis &
Gill, 2001). Although well-documented factors such as dietary choices and lethargy are
known to contribute to the prevalence of obesity and metabolic disorders, additional
environmental factors are now considered critical in the development and maintenance of
obesity (Hill, Wyatt, Reed, & Peters, 2003).
The worldwide increase in obesity and metabolic disorders correlates with
increased exposure to artificial light at night (LAN) during the 20th
century.
Approximately 99% of the US and Europe currently experiences light pollution that alters
the natural cycle of light and dark (Navara & Nelson, 2007). Artificial lighting allows
67
people to extend daytime activities into the night and engage in countercyclical night
time shift work. This type of aberrant light exposure can disrupt the circadian system
because light is the most potent entraining signal for the mammalian biological clock
(Reppert & Weaver, 2002). Many homeostatic processes are regulated by the circadian
system including metabolism (Lowrey & Takahashi, 2004). For example, there are 24-
hour variations in the expression of genes involved in gluconeogenesis, lipogenesis, and
lipid catabolism, among others (Oishi et al., 2003; Yang et al., 2006). Disruption of both
primary and secondary clock genes cause profound changes in metabolism (Marcheva et
al., 2010; Paschos et al., 2012; Solt et al., 2012; Turek et al., 2005). Similarly, shifting the
timing of food intake can alter weight gain independently of changes in total caloric
intake (Hatori et al., 2012; Sherman et al., 2012). Even brief circadian misalignment can
results in adverse metabolic and cardiovascular consequences in humans (Scheer, Hilton,
Mantzoros, & Shea, 2009).
Communication between the circadian clock and metabolic system appears bi-
directional as diet induced obesity is associated with behavioral and molecular circadian
rhythm disturbances (Hsieh et al., 2010; Kohsaka et al., 2007). I have previously
demonstrated that mice exposed to dim light at night (dLAN) significantly increase body
mass and reduced glucose processing compared with mice in a standard light-dark cycle
(LD), despite equivalent caloric intake and total daily activity. Nocturnal rodents
typically eat substantially more food at night; however, dLAN mice consume more than
half of their food during the light phase. Restricting food intake to the active phase in
dLAN mice prevents body mass gain. These results suggest that low levels of light at
68
night disrupt the timing of food intake and other metabolic signals, leading to excess
weight gain (Fonken, Kitsmiller, Smale, & Nelson, 2012; Fonken et al., 2010).
In addition to altering metabolism, disruption of circadian clock through activities such
as shift work has serious health consequences including increased risk for cancer
(Stevens, 2009a), tissue damage (Tunez et al., 2003), heart disease (Morris, Yang, &
Scheer, 2012), and stroke (Vyas et al., 2012). A feature common to all of these
pathologies is elevated inflammation. Inflammation is integrally associated with obesity,
likely contributing to both the development and maintenance of metabolic syndrome
(Hotamisligil, 2006). Elevated expression of tumor necrosis factor-α (TNF-α) in adipose
tissue of obese mice was the first indication of inflammatory dysregulation in obesity
(Hotamisligil, Shargill, & Spiegelman, 1993). Elevated fat mass is associated with
widespread chronic low-grade inflammation in adipose tissue, liver, and skeletal muscle
(Marceau et al., 1999; Plomgaard et al., 2005). This inflammatory response is
characterized by increased levels of circulating pro-inflammatory cytokines, as well as
infiltration of the tissue by immune cells such as macrophages, neutrophils, and
eosinophils (Weisberg et al., 2003; H. Xu et al., 2003). Peripheral inflammation leads to
disruption in insulin signaling further propagating fat accumulation. Peripheral
inflammation described above is both a cause and consequence of obesity.
In contrast to the peripheral response, accumulating evidence suggests that
hypothalamic inflammation resulting from a high fat diet (HFD) may occur prior to
development of obesity through central leptin and insulin resistance. Acute glucose
overload significantly increases NF-κB activity in the hypothalamus, but not peripheral
69
tissue (Zhang et al., 2008). Furthermore, hypothalamic insulin resistance occurs prior to
insulin resistance in peripheral tissue (Purkayastha et al., 2010). Whereas peripheral
inflammation can take weeks to develop after beginning a HFD (Kim et al., 2008),
changes in hypothalamic inflammation can occur within hours of consuming high fat
food (Thaler et al., 2012).
In developed and developing countries exposure to LAN and high fat diets often
occur in tandem and may contribute to the increasing obesity epidemic. Thus, I
hypothesized that dLAN would exagerate metabolic dysfunction produced by a HFD in
mice. Because dLAN is associated with changes in immune function (Bedrosian, Fonken,
Walton, & Nelson, 2011b; Fonken, Haim, & Nelson, 2011), I also investigated whether
dLAN works through a similar mechanism as HFD producing additional increases in
peripheral and hypothalamic inflammation. Overall, I hypothesized that these two
variables would synergistically affect metabolism through a similar mechanism.
Methods
Animals
Fifty four male Swiss–Webster mice (~8 wk of age) were obtained from Charles
River Laboratories for use in this study. The mice were housed individually in propylene
cages (30 x 15 x 14 cm) at an ambient temperature of 22 ± 2 °C and provided with
filtered tap water ad libitum. Mice were housed in a standard light/dark cycle [14h light
(150 lux): 10h dark (0 lux); LD] and provided basic rodent diet (chow; Harlan Teklad
8640, Madison, WI, USA) for one week after arrival at our facility. After the one week
acclimation period, mice were randomly assigned a number and placed in one of four
70
groups (n=13-14 per group); mice were housed in either LD or dim light at night [14h
light (150 lux): 10h dim (5 lux); dLAN] and received either a high fat diet (HFD;
Research Diets D12451, New Brunswick, NJ, USA) or chow. On day 1 of the experiment
mice were weighed and transferred from an LD room to a cabinet with either an LD or
dLAN light cycle. At this time mice were also either maintained on chow or switched to a
HFD for the duration of the study. Body mass was measured weekly at ~ZT8 and timing
of food intake was measured twice daily at the onset of the light (ZT 0) and dark (ZT 14)
phase, respectively, for 4 consecutive days during the final experimental week. The
percentage of food consumed during the light phase was calculated for each day and
averaged for each mouse to generate a single percentage value. At the conclusion of the
study 6-7 mice per group were used for quantitative PCR (qPCR) and the remaining mice
per group were used for immunohistochemistry.
qPCR
Between ZT 8 and 10 mice were brought into a procedure room, anesthetized with
isoflurane vapors, a blood sample was collected from the retro-orbital sinus, and mice
were rapidly decapitated. Brains were removed, placed in RNAlater overnight and then
the hypothalamus was dissected. Epididymal fat pads and liver were removed, weighed,
and flash frozen. Total RNA was extracted from hypothalamic, fat, and liver tissue using
a homogenizer (Ultra-Turrax T8, IKAWorks, Wilmington, NC) and an RNeasy Mini Kit
(Qiagen, Austin, TX) according to manufacturer instructions. For fat extractions an
additional chloroform separation step was added prior to using the kit to prevent excess
fat from clogging the spin columns. RNA was then reverse transcribed into cDNA with
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M-MLV Reverse Transcriptase enzyme (Invitrogen, Carlsbad, CA). Gene expression for
MAC1, TNFα, and POMC were determined using inventoried primer and probe assays
(Applied Biosystems, Foster City, CA) on an ABI 7500 Fast Real Time PCR System
using Taqman® Universal PCR Master Mix. The universal two-step RT-PCR cycling
conditions used were: 50 °C for 2 min, 95 °C for 10 min, followed by 40 cycles of 95 °C
for 15 s and 60 °C for 1 min. Relative gene expression of individual samples run in
duplicate was calculated by comparison to a relative standard curve and standardized by
comparison to 18S rRNA signal.
Immunohistochemistry
A subset of mice was used to assess histological evidence of microglia infiltration
to the hypothalamus. Between ZT 8 and 10 mice were deeply anesthetized with
isoflurane vapors, a blood sample was collected from the retro-orbital sinus, and mice
were given a sodium pentobarbital overdose. Mice were then perfused transcardially with
ice-cold 0.1M PBS followed by 50 mL of 4% paraformaldehyde. Brains were removed,
post-fixed overnight, cyroprotected in 30% sucrose, and frozen in isopentane with dry
ice. Brains were stored at -80°C and then sectioned on a cryostat at 40 μm into
cryoprotectant. Sections were stored at -20°C until further processing. The sections were
rinsed in phosphate buffered saline (PBS) and blocked with 4% BSA in PBS + Triton-X
(TX) for 1 h with constant agitation. Sections were incubated overnight with primary
rabbit-anti-Iba-1 (Wako Chemicals, Richmond, VA) diluted 1:1000 in PBS + TX. After
PBS rinses the sections were subsequently incubated for 1 h at room temperature with
biotinylated goat-anti-rabbit 1:1000 in PBS + TX (Vector Laboratories, Burligame, CA,
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USA). Sections were then quenched for 20 min in methanol containing 0.3% hydrogen
peroxide. After washing with PBS, sections were incubated for 1 hour with avidin-biotin
complex (ABC Elite kit, Vector laboratories). After rinses, the sections were developed
in diaminobenzidine for 2 min (Sigma, D4168). Sections were mounted on gel-coated
slides, dehydrated, and coverslipped with Permount. Images were captured on a Nikon
E800 microscope at 20X and analyzed using Image J software (NIH) to determine
immunoreactive regions. Both sides of bilateral structures were counted in duplicate per
animal.
Statistical Analyses
Comparisons between groups were conducted using a two-way analysis of
variance (ANOVA) with lighting condition and diet as the between subject factors.
Change in body mass over time was analyzed using a repeated measures ANOVA.
Following a significant F score, multiple comparisons were conducted with Tukey‟s HSD
test. The above statistical analyses were conducted with StatView software (v.5.0.1,
Cary, NC). In all cases, differences between group means were considered statistically
significant if p ≤ 0.05.
Results
Somatic measures
To determine whether dLAN exacerbates diet induced weight gain, mice were
exposed to either dLAN or LD while fed HFD or chow. There was an overall increase in
body mass over the 4 experimental weeks (F4,196 = 367.202; p < 0.0001). Both lighting
and dietary conditions affected body mass over time (Light: F4,196 = 15.525, Diet: F4,196 =
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150.178; p < 0.0001; Fig. 1A). Average body mass was comparable between all groups at
the start of the study (p > 0.05), but within 1 week of experimental onset both dLAN and
HFD elevated body mass (Light: F1,49 = 17.250, Diet: F1,49 = 50.218; p < 0.0001).
Furthermore, at the conclusion of the study relative body mass gain was increased among
both dLAN and HFD groups ( Light: F1,49 = 15.779; Diet: F1,49 = 136.447; p < 0.001; Fig.
1B). Increases in body mass likely reflected increases in fat mass as both dLAN and HFD
increased relative epididymal fat pad mass, a reliable index of overall adiposity (Light:
F1,21 = 9.785, Diet: F1,21 = 103.282; p < 0.01; Fig. 1C). Moreover, both dLAN and HFD
increased blood glucose levels (Light F1,49 = 4.148, Diet: F1,49 = 5.214; p < 0.05; Fig.
1A). There were no interactions between lighting condition and diet with respect to body
mass, fat pad mass, or blood glucose levels.
Food Intake
Despite increases in body mass among mice housed with dLAN, there were no
differences in total daily food intake between lighting conditions (p > 0.05; Fig. 2A).
Mice fed a high fat diet decreased food intake compared to the mice fed standard chow
(F1,49 = 32.860; P<.0001; Fig. 2A). Decreased food intake among HFD mice was
expected because the high fat food is much more calorie dense than standard chow.
Although there were no differences in total food intake, dLAN and HFD both altered
timing of food intake. dLAN mice increased daytime food intake as compared to mice
exposed to dark nights (Light: F1,49 = 42.649; p < 0.0001, Fig. 2B). High daytime food
intake is atypical for nocturnal rodents and changes in timing of food intake have
previously been associated with changes in metabolism (Arble, Bass, Laposky, Vitaterna,
74
& Turek, 2009; Sherman et al., 2012; Tsai et al., 2012). HFD also caused a shift toward
daytime food intake which has previously been described in (Kohsaka et al., 2007) (Diet:
F1,49 = 5.509; p < 0.05).
Peripheral Inflammation
In metabolically related peripheral tissues (i.e., white adipose tissue (WAT), liver,
and pancreas) obesity promotes a state of chronic low-level inflammation. This in turn
contributes to insulin resistance, further propagating metabolic syndrome (Hotamisligil,
2006; Myers, Leibel, Seeley, & Schwartz, 2010). For this reason, I evaluated the
expression of pro-inflammatory cytokines in both white adipose tissue (WAT) and liver.
dLAN and HFD both elevated gene expression of MAC1, a marker for macrophages, in
WAT (Light: F1,20 = 9.304, Diet: F1,20 = 25.442; p < 0.01; Fig. 3A). Additionally, dLAN
and a HFD elevated expression of the pro-inflammatory cytokine TNFα in WAT (Light:
F1,20 = 4.649, Diet: F1,20 = 4.979; p < 0.05; Fig. 3B). There were no differences in TNFα
or MAC1 gene expression in the liver (data not shown). This is consistent with previous
research as it is not uncommon for changes in peripheral inflammation to take > 4 weeks
to develop in response to HFD (Kim et al., 2008).
Hypothalamic Inflammation
Previous research indicates that hypothalamic inflammation may occur with a
HFD prior to the onset of inflammation in peripheral tissue and contribute to obesity
development (Thaler et al., 2012). Because light at night is associated with changes in
immune function (Bedrosian, Fonken, Walton, & Nelson, 2011b; Fonken, Haim, &
Nelson, 2011), I hypothesized that hypothalamic inflammation may also be contributing
75
to changes in weight gain in dLAN mice. Consistent with previous reports (De Souza et
al., 2005; Thaler et al., 2012; Zhang et al., 2008), HFD elevated hypothalamic TNFα
expression relative to standard chow (F1,21 = 4.433; p < 0.05; Fig. 4A). However, no
differences in MAC1 expression were apparent between light or dietary conditions (p >
0.05). This may reflect the distribution of hypothalamic microglia; with
immunohistochemistry I established that the concentration of Iba1 positive cells was
elevated in the arcuate nucleus of the hypothalamus in mice fed a HFD (F1,22 = 9.612; p <
0.01; Fig 3C,E,F), but not other hypothalamic nuclei such as the DMH (p > 0.05; Fig.
3D). There was no main effect of dLAN or interaction between lighting condition and
diet with respect to Iba1 immunoreactivity. However, there was a simple effect of
lighting condition within mice fed chow diet, such that dLAN increased the number of
Iba1 positive cells within the chow group (F1,12 = 4.855; p < 0.05). Neither diet nor
lighting condition affected POMC gene expression (data not shown, p > 0.05).
Discussion
I hypothesized that housing mice in dLAN would exaggerate metabolic changes
induced by a HFD. Moreover, I predicted that dLAN and HFD would both result in
elevated peripheral inflammation and upregulated inflammatory responses in the
hypothalamus, indicating the manipulations worked through a similar mechanism.
Although dLAN and HFD increased weight gain and peripheral inflammation, results in
the central nervous system were less clear. dLAN did not alter hypothalamic TNFα,
MAC1, or POMC gene expression. As anticipated, microglia staining was increased in
the arcuate nucleus of mice fed a high fat diet. However, dLAN only resulted in increased
76
microglia staining among mice fed the chow diet. Lack of hypothalamic inflammation
among both dLAN groups suggests dLAN induces weigh gain through an alternative
mechanism.
Both diet and lighting condition elevated body mass over the course of the study.
Body mass was elevated by dLAN and HFD within the first week of experimental
conditions. Among HFD mice, dLAN potentiated increases in body and fat pad mass
compared to LD demonstrating that changes in environmental lighting can exacerbate the
adverse affects of a HFD. HFD and dLAN also both altered timing of food intake. As
previously reported, dLAN mice increase daytime food intake (Fonken et al., 2010).
Whereas LD mice consume the majority of their food during the dark phase (~70%),
dLAN mice show no preference for nighttime food intake. Daytime food intake is
atypical for nocturnal rodents and is associated with the development of metabolic
syndrome in animal models (Arble, Bass, Laposky, Vitaterna, & Turek, 2009). In
addition to dLAN shifting the daily pattern of food intake, HFD also caused subtle
changes in timing of food intake. Previous work demonstrates that blocking access to
food during the light phase can prevent increases in weight gain due to a HFD or dLAN
(Fonken et al., 2010; Hatori et al., 2012; Sherman et al., 2012; Tsai et al., 2012). This
suggests that weight gain due to both manipulations may partially result from the shift in
timing of food intake.
Light at night is associated with changes in immune function in rodents
(Bedrosian, Fonken, Walton, & Nelson, 2011b; Fonken, Haim, & Nelson, 2011). The
effects of light at night on metabolic inflammation have not been previously
77
characterized. Here, I report that dLAN increases inflammation in white adipose tissue.
Both TNFα and MAC1 gene expression were upregulated by dLAN and HFD. Elevated
MAC1 expression is indicative of increased macrophage infiltration into fat tissue and
has previously been described in models of obesity (Weisberg et al., 2003). Macrophage
infiltration can increase pro-inflammatory cytokine release and result in the widespread,
chronic, low-grade peripheral inflammation typical of high fat accumulation (Marceau et
al., 1999; Plomgaard et al., 2005). The development of peripheral inflammation, although
it propagates obesity through disrupting insulin and leptin signaling (Kim et al., 2008)
generally follows the onset of obesity suggesting it is not the primary mechanism driving
weight gain.
In contrast, hypothalamic inflammation may precede and contribute to the
development of obesity as changes in the hypothalamic milieu are apparent within 24 h of
the induction of high fat feeding (Thaler et al., 2012). Therefore, I hypothesized that
hypothalamic inflammation may contribute to changes in weight gain in dLAN mice.
Although HFD elevated hypothalamic TNFα expression relative to standard chow, there
were no differences in TNFα expression between lighting conditions. Moreover, no
differences in MAC1 expression were apparent between light or dietary conditions. Lack
of significant changes in hypothalamic expression of MAC1 may be due to the specificity
of the changes in hypothalamic inflammation. For example, there is a regionally specific
enrichment of IKKβ and NF-κB in the mediobasal hypothalamus (includes the arcuate)
that becomes potently upregulated with HFD (Zhang et al., 2008). This suggests elevated
inflammation in the arcuate nucleus may be masked by the lack of change in
78
inflammation in other hypothalamic nuclei. In support of this hypothesis, the
concentration of Iba1 positive cells was elevated in the arcuate of mice fed a HFD, but
not in the dorsal medial hypothalamus. Although dLAN did not affect Iba1 positive cells
among HFD mice, dLAN increased the number of Iba1 positive cells within the chow
group. This suggests that hypothalamic inflammation is not essential for weight gain in
dLAN as dLAN-HFD mice elevated weight gain compared to LD-HFD mice without
increasing hypothalamic microglia. Continued elevation of CNS inflammatory responses
combined with a long term HFD leads to gliosis and damage to proopiomelanocortin
neurons (Parton et al., 2007). However, neither diet nor lighting condition affected
POMC gene expression.
These results indicate that dLAN exacerbates weight gain and peripheral
inflammation associated with HFD. Lack of elevated hypothalamic inflammation among
dLAN mice suggests central inflammation is not the primary mechanism for light
induced weight gain. Overall, these results have important implications for industrial
societies in which nighttime light exposure and poor diet often co-occur. Further
understanding of the mechanisms through which LAN contributes to inflammation and
obesity is important for characterizing and treating metabolic disorders.
79
Figures
Figure 4.1. Light at night exaggerates weight gain on a high fat diet.
Body mass and fat pad mass were elevated by dLAN and HFD. (A) Body mass
throughout the experiment. (B) Final body mass gain expressed as a percentage from
baseline body mass. (C) Epididymal fat pad mass corrected for final body mass. (D)
Blood glucose levels at the conclusion of the study. (* p < 0.05 between lighting
conditions, † p < 0.05 between dietary conditions).
80
Figure 4.2. High fat diet and light at night alter timing of food intake.
Total daily food intake was comparable between lighting conditions; however, dLAN
mice consumed a higher percentage of food during the light phase. (A) Total daily food
intake. (B) Relative daytime food intake. (* p < 0.05 between lighting conditions, † p <
0.05 between dietary conditions).
81
Figure 4.3. High fat diet and light at night increase adipose inflammation.
Both dLAN and HFD increased inflammatory gene expression in white adipose tissue.
(A) Relative MAC1 and (B) TNFα gene expression in epididymal fat. (* p < 0.05
between lighting conditions, † p < 0.05 between dietary conditions).
82
Figure 4.4. Hypothalamic inflammation is elevated by high fat diet but not exposure to
dim light at night.
Hypothalamic inflammation is elevated by HFD but not dLAN. (A) Relative TNFα and
(B) MAC1 gene expression in the hypothalamus. Iba1 staining in the (C) arcuate and (D)
dorsomedial nuclei of the hypothalamus. Representative photomicrographs captured at
20X from the arcuate nucleus of (E) an LD-chow mouse and (F) an LD-HFD mouse.
83
CHAPTER 5
EXERCISE ATTENUATES THE METABOLIC EFFECTS OF DIM LIGHT AT
NIGHT
Over the course of the 20th
century body mass rapidly increased worldwide. By
the year 2000 the number of adults with excess weight surpassed those who were
underweight for the first time in human history. This excess adiposity is recognized as
one of the world‟s leading health threats because obesity increases the risk of developing
type II diabetes, cardiovascular disease, hypertension, and cancer (Caballero, 2007). The
rapid growth in adiposity during the 20th
century correlates with significant changes in
human environment and lifestyle. In addition to changes in activity levels and dietary
choices, a less appreciated environmental perturbation has been the shift in timing of
daily activities. The invention of electric lighting ~150 years ago has enabled humans to
illuminate their homes, hospitals, factories, and night skies and engage in activities such
as countercyclical shift work (Navara & Nelson, 2007). Widespread adoption of electric
lights occurred well before an understanding of circadian biology, and without any
consideration of the negative biological consequences that artificial light at night (LAN)
may have on physiology and behavior.
84
Circadian regulation of energy homeostasis is organized by an endogenous
biological clock located in the suprachiasmatic nuclei (SCN) of the hypothalamus. The
circadian clock is entrained by light information that travels directly from light-sensitive
ganglion cells in the retina to the SCN, thereby synchronizing individuals‟ physiology
and behavior to the external day-night cycle (Golombek & Rosenstein, 2010; Reppert &
Weaver, 2002). Because light is the primary signal for the circadian clock, exposure to
light at aberrant times can disrupt clock function (Navara & Nelson, 2007).
Many studies suggest a direct link between the molecular circadian clock and
metabolism (Bray & Young, 2007). Mice harboring a mutation in the core circadian gene
Clock are susceptible to obesity and metabolic syndrome (Turek et al., 2005). Clock
mutants show dramatic changes in circadian rhythmicity, as well as altered timing of food
intake and increased body mass. Serum leptin, glucose, cholesterol, and triglyceride
levels are increased in Clock mutants compared to wild type (WT) mice. Mice with
mutations in other clock related genes including Bmal1, Per1, Per2, Vipr2, and Rev-erbα
display similar metabolic outcomes (Bechtold, Brown, Luckman, & Piggins, 2008;
Carvas et al., 2012; Delezie et al., 2012; Marcheva et al., 2010). Even single tissue clock
gene disruptions can result in metabolic disturbances (Marcheva et al., 2010; Paschos et
al., 2012). Thus, it seems reasonable to propose that disrupted circadian clock function
has the potential to derange normal metabolism.
Mice housed in dim LAN (dLAN) elevate body mass and reduce glucose
tolerance independent of changes in total daily food intake or home cage locomotor
activity (Fonken et al., 2010). dLAN mice increase the percentage of food consumed
85
during the light phase as compared to mice housed in dark nights; restricting food intake
to the dark phase ameliorates weight gain among dLAN mice (Fonken et al., 2010).
Daytime food intake is associated with weight gain and metabolic disruption in mice in
other contexts (Arble, Bass, Laposky, Vitaterna, & Turek, 2009; Bray et al., 2012).
Furthermore, the relationship between the circadian clock and metabolism appears to be
bi-directional as diet induced obesity can dampen circadian rhythms (Kohsaka et al.,
2007).
As mentioned, light is the dominant entraining factor for the circadian system;
however, non-photic stimuli such as food intake and exercise can alter circadian rhythms
(Fuller, Lu, & Saper, 2008; Mistlberger & Antle, 2011). Activity is both a behavioral
output of the circadian system and an important feedback factor that can modulate
rhythms (Edgar & Dement, 1991; Mistlberger, 1991; Reebs & Stcoeur, 1994). In constant
dark conditions, timed wheel access entrains circadian rhythms in mice (Edgar &
Dement, 1991). Moreover, scheduled access to a running wheel can strengthen circadian
rhythms in mice with disrupted clock function (Power, Hughes, Samuels, & Piggins,
2010). Even under a standard light-dark cycle, ad lib access to wheels can strengthen the
power of circadian rhythms in wild type mice (Schroeder et al., 2012).
In addition to strengthening circadian rhythms, it is well established that exercise
prevents weight gain (Patterson & Levin, 2008). Therefore, I hypothesized providing
mice a running wheel for voluntary exercise would buffer against the effects of LAN on
metabolism. Specifically, I hypothesized that mice exposed to LAN would increase body
mass and alter feeding rhythms, indicating circadian system disruption. I predicted that
86
providing mice running wheels would strengthen circadian entrainment preventing
altered timing of food intake and LAN-induced weight gain.
Materials and Methods
Animals
Forty male Swiss-Webster mice (~8 weeks of age) were obtained from Charles
River Laboratories. The mice were individually housed in propylene cages (dimensions:
33 x 19 x 14 cm) at an ambient temperature of 22 ± 2° C and provided with Harlan
Teklad 8640 food (Madison, WI) and filtered tap water ad libitum. Upon arrival, mice
were maintained in a standard 14:10 light (150 lux) /dark (0 lux) cycle (LD; lights on at
2:00 EST) for one week in order to habituate to local lighting conditions and recover
from the effects of shipping. After this period mice were randomly assigned a group,
weighed, and transferred to either a cabinet with LD or dim light at night [dLAN; 14:10
light (150 lux) /dim (5 lux) light cycle]. Within each lighting condition mice received
either a locked wheel or a low-profile running wheel (running surface of 15.5 cm
diameter) for voluntary exercise (Med Associates, St. Albans, VT). Wheel running was
constantly monitored using a wireless interface hub system which transmitted the data to
a computer. Locked wheels were provided to control for the presence of a novel object in
the cage. Mice were weighed every week at Zeitgeber Time (ZT) 9.
After 3 weeks in experimental conditions, food was weighed twice daily,
immediately before the onset of the dark phase (ZT 14) and immediately after the onset
of the light phase (ZT 0). Average food intake for the light and dark phases over three
days was used to quantify percentage of daytime food intake. At the conclusion of the
87
study mice were individually brought into a procedure room, anesthetized with isoflurane
vapors, and rapidly decapitated between ZT 9 and 11; a blood sample was then collected
and epididymal fat pads were removed and weighed.
Statistical analyses
One dLAN mouse with a running wheel was removed from statistical
comparisons because it did not use the wheel and one mouse was removed from the
locked wheel LD group for demonstrating sickness behaviors. Effects of lighting
condition and wheel access on body mass gain, fat pad mass, and percentage of daytime
food intake were analyzed using two-way analysis of variance (ANOVA). A repeated
measures ANOVA was used to assess change in body mass over time. Following a
significant F score, multiple comparisons were conducted with Tukey‟s HSD test. The
above statistical analyses were performed with StatView software (v.5.0.1, Cary, NC).
Running wheel activity was analyzed and actograms were generated using ClockLab
Software (Coulbourn Instruments, Boston, MA). An animal was considered rhythmic
when the highest peak occurred at ~1 cycle/24 h, with an absolute power of at least 0.005
mV/Hz (Kriegsfeld, et al., 2008). In all cases, differences between group means were
considered statistically significant if p ≤ 0.05.
Results
Somatic measures
Over the course of the study, body mass was elevated among all groups (F4,136 =
82.814; p < 0.0001); however, light at night potentiated increases in body mass, whereas
access to a running wheel limited weight gain (Body mass over time: F4,136 = 4.275 and
88
4.659 respectively, Final body mass gain: F1, 34= 7.711 and 8.203 respectively; p <0.01;
Fig. 1A/B). Final body mass gain did not differ between mice exposed to dLAN with a
running wheel and mice housed in dark nights with either a running or locked wheel (post
hoc; p < 0.05). There were no interactions of the two variables on weight gain. Both light
and access to a running wheel also affected final fat pad mass (F1,33 = 7.505 and 3.791;
Fig. 1C); such that dLAN increased fat pad mass and presence of a running wheel
reduced fat pad mass. In agreement with previous results, mice housed in dLAN
increased percentage of food consumed during the light phase (F1,34 = 14.345; p < 0.001;
Fig. 1D). In contrast to the hypothesis, wheel running also increased the percentage of
food consumed during the light phase (F1,34 = 5.265; p < 0.05; Fig. 1D).
Daily running wheel activity
Total daily wheel running did not differ between mice in the LD and dLAN
conditions (F1,17 = 0.144; p > 0.1; data not shown). All mice in LD showed a dominant
rhythm of 0.042 (or 1 cycle per 24 hours) (Fig. 2A). In contrast, only 5 of the 9 dLAN-
mice demonstrated a dominant 24 hour wheel running rhythm (Fig. 1B).
Discussion
The goal of this study was to assess the effects of voluntary exercise on changes
in body mass and food intake associated with exposure to dLAN in male Swiss Webster
mice. I hypothesized that enhanced activity by means of optional wheel running would
prevent body mass gain in mice exposed to dLAN. Specifically, I predicted that voluntary
exercise would strengthen circadian organization in mice exposed to dLAN, preventing
increased daytime food intake. Here I report that exercise availability limits weight gain
89
in mice housed under dLAN. In contrast to the hypothesis, reduced body mass occurred
independently of re-establishing nighttime food intake; mice with running wheel access
increased food intake during the light phase. Furthermore, although all mice maintained
under dark nights had a dominant 24 hour activity rhythm, a subset of the dLAN mice
showed disrupted patterns of wheel running.
These results confirm and extend previous findings (Coomans et al., 2013;
Fonken, Kitsmiller, Smale, & Nelson, 2012; Fonken et al., 2010); mice exposed to LAN
without access to wheel running elevated body mass gain over the course of the study.
Consistent with the hypothesis, access to a running wheel reduced weight gain among
mice exposed to dLAN. Final body mass gain was comparable between dLAN mice with
a running wheel and both groups of LD mice. Furthermore, whereas dLAN increased
relative epididymal fat pad mass, an index of overall adiposity, housing mice with a
running wheel reduced fat pad mass. These results indicate that weight gain induced by
dLAN is susceptible to traditional weight loss interventions, i.e. increased exercise.
As in previous studies, dLAN mice ate more food during the light phase
compared to mice exposed to dark nights (Fonken et al., 2010). Eating during the light
part of the day is atypical for nocturnal rodents and is associated with changes in
metabolism (Arble, Bass, Laposky, Vitaterna, & Turek, 2009; Bray et al., 2012).
Moreover, restricting food intake to the dark phase prevents weight gain in models of
obesity (Fonken et al., 2010; Hatori et al., 2012; Mistlberger, Lukman, & Nadeau, 1998;
Sherman et al., 2012). Voluntary wheel running has previously been associated with
increasing the power of ambulatory activity rhythms with greater activity specifically
90
during the dark phase in mice housed in standard lighting conditions (Schroeder et al.,
2012). Thus, I predicted that access to a running wheel would prevent the shift towards
daytime food intake in dLAN mice. Contrary to my prediction, presence of a running
wheel increased daytime food intake irrespective of lighting condition. These results
differ from rats; rats with either voluntary wheel running or forced exercise consume
more calories during the active phase (Oudot, Larue-Achagiotis, Anton, & Verger, 1996).
To my knowledge the effects of voluntary wheel running on the daily pattern of food
intake in mice has not been investigated. However, mice with access to running wheels
have fewer, but larger, daily meals (Atalayer & Rowland, 2011).
Total daily wheel running did not differ between mice exposed to dark or dimly
illuminated nights. These findings are consistent with previous research demonstrating
that exposure to dLAN does not affect the amount of activity in either an open field or
home cage (Fonken et al., 2009; Fonken et al., 2010). Circadian rhythms of home cage
locomotor activity remain intact in mice exposed to dLAN and comparable to activity
patterns in mice exposed to dark nights (Fonken et al., 2010). In the present study,
however, wheel running activity was disrupted in several dLAN mice. All mice exposed
to dark nights displayed a dominant 24 h rhythm in wheel running compared to 5 of 9
mice exposed to dLAN. Although I have previously asserted that dLAN does not affect
sleep architecture or activity patterns, the existence of running activity during the so-
called inactive periods suggests that dim light may shift circadian activity when paired
with optional wheel running. Future studies should address sleep quantity and quality in
mice exposed to LAN. Disparate results between wheel running and home cage activity
91
could reflect the different forms of behavior that the two systems monitor (Novak,
Burghardt, & Levine, 2012). Home cage activity occurs for multiple reasons including
grooming, feeding, or locomotor activity, whereas running wheels only monitor
voluntary running. Overall, these results suggest that voluntary exercise prevents weight
gain induced by dLAN without rescuing circadian rhythm disruptions.
92
Figures
0 1 2 3 430
32
34
36
38
40LD-Sed
dLAN-Sed
LD-Ex
dLAN-Ex*
***
Weeks
Bo
dy m
ass (
g)
LD dLAN0
4
8
12
16 Sed
Ex
*
Bo
dy m
ass g
ain
(% b
aseli
ne)
LD dLAN0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5†
% E
pid
idym
al
fat
pad
mass
LD dLAN0
10
20
30
40
50
60
†
% D
ayti
me f
oo
d i
nta
ke
A B
C D
Figure 5.1. Voluntary exercise prevents weight gain induced by dim light at night.
(A) Body mass over the course of the study. (B) Body mass gain expressed relative to
baseline body mass. (C) Epididymal fat pad mass expressed relative to final body mass.
(D) Percentage of food consumed during the light phase. All data are presented as mean ±
SEM. *indicates dLAN-Sed differs from all other groups, †indicates main effect of
lighting condition
93
Figure 5.2. Dim light at night disrupts daily wheel running patterns in a subset of mice.
Representative actograph from a mouse housed in either (A) dark or (B) dim nights.
94
CHAPTER 6
DIM LIGHT AT NIGHT DISRUPTS MOLECULAR CIRCADIAN RHYTHMS
For >3 billion years, life outside of the highest latitudes has evolved under bright
days and dark nights. Most organisms have developed endogenously driven circadian
rhythms which are synchronized to this daily light/dark cycle. With the widespread
adoption of electric lighting ~150 years ago, humans began brightly illuminating their
nocturnal environments. Exposure to light at night is now pervasive in modern society
and typically considered a mild environmental perturbation. However, the use of light at
night (LAN) began prior to a deep appreciation of the importance of circadian rhythms
for normal biological functions (Fonken & Nelson, 2011; Gerstner, 2012).
Recent evidence suggests that exposure to unnatural light cycles increases the risk for
cancer (Stevens, 2009b), sleep disturbances (Kohyama, 2009), and mood disorders
(Driesen, Jansen, Kant, Mohren, & van Amelsvoort, 2010). Furthermore, exposure to
light at night is increasingly associated with changes in metabolism. Shift workers who
experience sustained nighttime illumination are at increased risk for cardiovascular
disease and elevated body mass index (Ha & Park, 2005; Knutsson, 2003; Parkes, 2002;
van Amelsvoort, Schouten, & Kok, 1999). Increases in nighttime light exposure at home
95
are associated with increased body mass, waist circumference and triglyceride levels, and
poor cholesterol balance (Obayashi et al., 2013). Even brief exposure to altered light and
food schedules can result in adverse metabolic and cardiovascular consequences (Scheer,
Hilton, Mantzoros, & Shea, 2009). Moreover, I have reported that mice chronically
exposed to dimly illuminated, as opposed to dark, nights elevate body mass
independently of changes in total daily activity or caloric intake (Fonken, Kitsmiller,
Smale, & Nelson, 2012; Fonken et al., 2010). Mice exposed to dim nights shift the timing
of food intake toward the light phase and restricting food access to the dark phase
prevents dLAN-associate body mass gain. The mechanism by which light at night
induces these changes is not fully understood.
Here I propose that light alters metabolic homeostasis in mammals by disrupting
the circadian system. As mentioned, light is the most potent synchronizing factor for the
circadian system. Light information travels directly from intrinsically photosensitive
ganglion cells in the retina to the master circadian clock located in the suprachiasmatic
nuclei (SCN) of the hypothalamus (S. K. Chen, Badea, & Hattar, 2011). Pacemaker
neurons within the SCN thereby drive the circadian clock with an autoregulatory
transcriptional-translational feedback loop of transcription activators and repressors
(Albrecht, 2002). Although the SCN are the primary pacemakers in mammals, most if not
all central and peripheral tissues contain the molecular machinery necessary for self
sustaining circadian oscillation (Mohawk, Green, & Takahashi, 2012). The master clock
converts external light/dark information to neural and endocrine signals that synchronize
96
peripheral clocks (Guo, Brewer, Champhekar, Harris, & Bittman, 2005; McNamara et al.,
2001).
Exposure to a pulse of light during the night can phase advance or delay the
circadian clock depending on the strength and time of the light signal (Miyake et al.,
2000). Exposure to constant light can alter activity rhythms and ablate circadian rhythms
in glucocorticoids, two principle outputs of the circadian system (Coomans et al., 2013;
Fonken et al., 2010). Moreover, specifically timed nighttime light pulses can be used to
ablate the circadian system (Ruby et al., 2008). Because disruption in circadian clock
genes are associated with significant changes in metabolism (Bechtold, Brown, Luckman,
& Piggins, 2008; Carvas et al., 2012; Delezie et al., 2012; Marcheva et al., 2010; Paschos
et al., 2012), I hypothesized that exposure to light at night alters metabolism through
disrupting the circadian system. To assess the effects of light at night on the circadian
clock I exposed mice to either total darkness or dim light (5 lux) during the night and
then characterized the expression of several circadian clock genes and proteins in the
SCN, hippocampus, liver, and adipose tissue. Five lux of nighttime light exposure was
selected because (1) it is approximately five times bright than maximal moonlight (2) it is
comparable to levels of light pollution found in urban areas (Kloog, Haim, & Portnov,
2009) and sleeping environments (Obayashi et al., 2013), yet (3) it is highly distinct from
daytime light levels.
Methods
Animals
97
One hundred and twenty male Swiss Webster mice (~8 weeks of age) were
obtained from Charles River for use in this study. Mice were individually housed in
propylene cages (dimensions: 33 x 19 x 14cm) at an ambient temperature of 23 ±2°C and
provided with Harlan Teklad 8640 food (Madison, WI) and filtered tap water ad libitum.
All mice were maintained in a standard light dark cycle (LD; 14:10 light (~150 lux)/dark
(0 lux)) for one week following arrival. After the 1 week acclimation period mice were
randomly assigned a group and transferred to a cabinet with either LD or a light/dim light
cycle (14:10 light (~150 lux)/dim light (5 lux)). Daytime lighting was provided with
white LEDs on the walls of the cabinets and dim light was administered with a flexible
strip of cool white LEDs wrapped around the rack on which the mouse cages were
placed. The lighting intensity was measured inside the home cage and was highly
consistent between cages. Mice were also assigned to 1 of 6 tissue collection time points
(Zeitgeber Time (ZT) 2, 6, 10, 14, 18, 22). Mice were weighed at the start of the
experimental light treatment and weekly throughout the study. After 3 weeks in lighting
conditions food was weighed twice daily for four days to determine the timing of food
intake. Four weeks after placement in light conditions blood and tissue were collected for
either quantitative PCR (qPCR) or immunohistochemical analyses (n=5 per
group/use/time point).
Quantitative PCR
Mice were anesthetized with isofluorane vapors and rapidly decapitated.
Peripheral tissue was dissected out, immediately weighed on a fine balance, and flash
frozen. Weighed tissues include liver, spleen, pancreas, white adipose tissue (epididymal
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and inguinal), brown adipose tissue, adrenals, heart, and skeletal muscle. Brains were
collected, placed in RNAlater, and after > 24 h the hypothalamus and hippocampus were
dissected out for PCR. Total RNA was extracted from liver, white adipose, hippocampal,
and hypothalamic tissues using a homogenizer (Ultra-Turrax T8, IKAWorks,
Wilmington, NC) and an RNeasy Mini Kit following the manufacturers protocol (Qiagen,
Austin, TX). For fat extractions an additional chloroform step was added following
homogenization and prior to the use of the Mini Kit. RNA concentration and purity were
measured on an ND-1000 spectrophotometer (Fischer Scientific, PLACE). RNA
concentrations were equalized with sterile water and RNA was reverse transcribed into
cDNA with M-MLV Reverse Transcriptase enzyme (Invitrogen, Carlsbad, CA)
according to the manufacturer‟s protocol. Gene expression for Clock, Bmal1, Per1, Per2,
Cry1, Cry2 and Rev-erbα were determined using inventoried primer and probe assays
(Applied Biosystems, Foster City, CA) on an ABI 7500 Fast Real Time PCR System
using Taqman® Universal PCR Master Mix. The universal two-step RT-PCR cycling
conditions used were: 50 °C for 2 min, 95 °C for 10 min, followed by 40 cycles of 95 °C
for 15 s and 60 °C for 1 min. Relative gene expression of individual samples run in
duplicate was calculated by comparison to a relative standard curve and standardized by
comparison to 18S rRNA signal.
Immonohistochemistry
Mice were given a lethal dose of sodium pentobarbital and perfused transcardially
with ice-cold 0.1M PBS followed by 4% paraformaldehyde. Brains were removed, post-
fixed overnight, cyroprotected in 30% sucrose, and frozen with dry ice. Brains were
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serially sectioned at 40 μm into cryoprotectant and stored at -20°C. Sets of tissue
collected at 240 μm intervals were used for immunohistochemical detection of BMAL,
CLOCK, PER1, and PER2 using antibodies generously provided by David Weaver
(LeSauter et al., 2012). Sections were rinsed in PBS, blocked for 1 h in 4% bovine serum
albumin in 0.1 M PBS + 0.3% TX, and then incubated overnight at room temperature
with primary antibody at 1:5000. The following day sections were rinsed and incubated
for 1 h with biotinylated goat anti-rabbit at 1:1000 (Vector Laboratories, Burligame, CA).
Endogenous peroxidase activity was quenched with 3% H2O2 in methanol for 20 min and
then the signal was amplified with avidin-biotin complex (Vectastain Elite ABC kit,
Vector Laboratories) and tissue was developed using DAB. Tissue was then mounted
onto gel coated slides, dehydrated through a series of graded ethanol washes, cleared with
xylene, and coverslipped using Permount. Images of sections containing the SCN were
captured at 20X using a Nikon E800 microscope. The number of immonoreactive cells in
the SCN was counted in ImageJ (NIH) by a condition blind observer and averaged across
section and sides of the bilateral structure to obtain one value per each mouse.
Statistical analyses
Body mass was analyzed using a repeated-measures analysis of variance
(ANOVA) with time as the within subject factor and lighting condition as the between
subject factor. Comparisons between lighting conditions with respect to weight gain,
tissue masses, and percentage of daytime food intake were conducted using a one-way
ANOVA. Blood glucose concentrations, qPCR results, and IHC results were analyzed
using a two-way ANOVA with lighting condition and time as the between subjects
100
factors. Following a significant F score, multiple comparisons were conducted with
Tukey‟s HSD test. All statistical analyses were performed using StatView software
(v.5.0.1, Cary, NC). In all cases, differences between group means were considered
statistically significant if p ≤ 0.05.
Results
Exposure to dim light at night increases body mass
Body mass increased among both groups over the course of the study (F3,354 =
304.187; p < 0.0001); however, mice exposed to dim light at night significantly elevated
body mass compared to mice housed in dark nights (F3,354 = 15.820; p < 0.0001; Fig 1A).
Overall, mice exposed to dim light at night had a greater body mass gain at the
conclusion of the study compared to mice exposed to dark nights (F1,118 = 15.476; p <
0.001; Fig 1B). There were no differences in spleen, liver, pancreas, BAT, adrenal, or
heart masses between groups (p > 0.05 in all cases). Epididymal fat pad mass was
elevated among mice exposed to dim light at night ( F1,58 = 7.520; p < 0.01; Fig 1D)
suggesting increases in body mass may reflect increases in white adipose tissue.
Light at night attenuates nocturnal feeding behavior
Despite increases in body mass among mice exposed to dLAN, there were no
differences in total daily food intake between groups (p > 0.05; Fig S1). In agreement
with previous results (Fonken, Kitsmiller, Smale, & Nelson, 2012; Fonken et al., 2010),
exposure to light at night increased the percentage of food consumed during the light
phase (F1,118 = 16.595; p < 0.0001; Fig 1D). Mice displayed a diurnal variation in blood
101
glucose levels (F5,106 = 14.023; p < 0.0001; Fig 1E) with no differences between lighting
conditions (p > 0.05).
Clock gene expression is disrupted by nighttime light exposure
To test the hypothesis that nighttime light exposure affects core clock gene
expression, I analyzed the diurnal expression of transcripts encoding Clock, Bmal1, Per1,
Per2, Cry1, and Cry2 in the hypothalamus, hippocampus, fat, and liver every 4 h after 4
weeks of exposure to dim or dark nights. All of the core clock genes assessed in the
hypothalamus displayed diurnal variation (p < 0.05; Fig. 2A). Expression of Clock, Bmal,
and Cry1 were unaffected by lighting conditions, however, rhythmic expression of Per1,
Per2, and Cry2 were all attenuated by exposure to dim light as compared to dark nights
(p < 0.05; Fig 2A). Specifically, gene expression of Per2 and Cry1 was significantly
reduced at ZT18, 6 hours after lights off, and Per1 expression was reduced at both ZT6
and ZT14.
In order to determine whether the effects of nighttime light exposure in the brain
are specific to the master circadian clock I examined core clock gene expression in the
hippocampus, a brain region known to show robust circadian oscillations. There was
clear cycling of Clock, Bmal1, Per1, Per2, Cry1, and Cry2 in the hippocampus of mice
exposed to both dark and dim nights (p < 0.001; Fig 2B). Overall, lighting condition had
no effect on hippocampal clock gene expression (p > 0.05). This suggests that within the
brain, changes in clock gene expression provoked by exposure to light at night may be
regionally specific.
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Recent work has demonstrated the importance of tissue specific clocks in
regulating metabolism (e.g., Marcheva et al., 2010). Thus, I investigated the effects of
nighttime light exposure on core clock gene expression in peripheral white adipose and
liver tissues. All of the clock genes analyzed except for Clock displayed rhythmic
variation in white adipose tissue and there was no effect of nighttime light exposure on
mRNA expression levels (p > 0.05; Fig 2C). In contrast, rhythmic expression of Bmal1,
Per1, Per2, Cry1, and Cry2 were all attenuated in the liver of mice exposed to dim nights
(p < 0.05; Fig 2D). Taken together, these results reveal that exposure to low levels of
light at night produce both tissue- and gene-specific changes in the expression levels of
several core circadian clock genes.
To further explore the effects of light at night on clock transcriptional networks I
studied the 24 h pattern of expression of Rev-Erb mRNA in hypothalamic, hippocampal,
WAT, and liver tissues. Rev-Erb is a nuclear receptor that has prominent functions for
both circadian oscillations and metabolic homeostasis (reviewed in Ribberger and
Albrecht, 2012). Diurnal rhythmicity in Rev-Erb expression was observed in all tissues
evaluated (p < 0.05; Fig 3). However, exposure to dim light at night reduced Rev-Erb
expression levels during the light phase in both the WAT and liver (p < 0.05). Decreased
Rev-Erb expression was specific to the periphery as there were no changes in
hypothalamic or hippocampal Rev-Erb mRNA levels.
Core clock protein expression in the suprachiasmatic nucleus
In order to fully characterize changes in circadian clock function within the SCN
after nighttime light exposure I evaluated clock protein expression every 4 h in mice
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housed under dark or dimly lit nights for 4 weeks. Rhythmic CLOCK and BMAL protein
expression was observed within the SCN with no effect of nighttime light exposure (Fig
4A/B). Expression levels of both PER1 and PER2 were altered by exposure to dim light
as compared to dark nights (p < 0.05; Fig 4C/D). Whereas mice exposed to dark nights
had rhythmic expression of PER1, mice exposed to dim light at night showed no diurnal
variation in PER1. Specifically, the peak in PER1 expression at ZT10 was abolished by
exposure to dim light at night. PER2 expression was also suppressed in mice exposed to
dim light at night at ZT14. These results confirm gene expression findings demonstrating
dim light at night specifically targets hypothalamic Per1 and Per2.
Discussion
Exposure to electric light at night can lead to disruptions in metabolic energy
homeostasis in rodents and humans (Ha & Park, 2005; Knutsson, 2003; Obayashi et al.,
2013; Parkes, 2002; van Amelsvoort, Schouten, & Kok, 1999). However, it remains
unclear how environmental lighting affects metabolism. Thus, I exposed mice to dim
light at night and investigated changes in body mass and the circadian system. Here I
establish that exposure to ecologically relevant levels of dim light during the night
attenuate circadian clock gene and protein rhythms, change feeding behavior, and lead to
weight gain. These observations indicate that exposure to dim light at night, a
commonplace and innocuous seeming environmental manipulation, can influence the
circadian system and metabolism.
Mice exposed to dim light at night showed rapid and sustained body mass
elevations. Increases in body mass may reflect increases in white adipose tissue as
104
epididymal fat pad mass was elevated among mice exposed to dim nights. Although total
daily caloric intake was comparable between groups, mice exposed to light at night
consumed more food during the light period and less during the dark period than mice
housed in dark nights. Disorganization in the feeding rhythm may contribute to increased
body weight. Indeed, altered timing of food intake can cause weight gain and restricting
feeding to specific hours prevents development of obesity (Arble, Bass, Laposky,
Vitaterna, & Turek, 2009; Bray et al., 2010; Hatori et al., 2012; Sherman et al., 2012).
Furthermore, mice fed a high fat diet disrupt daily feeding patterns and attenuate
circadian clock gene rhythms in peripheral tissue (Kohsaka et al., 2007).
Genetic models indicate a close association between the molecular events
underlying metabolism and those involved in the generation of circadian rhythms. For
example, Clock mutant mice become overweight on a high fat diet and develop
symptoms characteristic of metabolic syndrome (Turek et al., 2005). Mice with mutations
in other clock related genes including Bmal1, Per1, Per2, Vipr2, and Rev-erbα display
similar metabolic outcomes (Bechtold, Brown, Luckman, & Piggins, 2008; Carvas et al.,
2012; Delezie et al., 2012; Marcheva et al., 2010). These studies indicate alterations in
core clock transcription factors within both the central clock and peripheral tissues alter
metabolism. Importantly, these results suggest that changes in the circadian clock genes
can be induced with exposure to ecologically relevant levels of dim light at night. Mice
exposed to dim light at night suppress Per1 and Per2 expression at both the gene and
protein level in the SCN. Importantly, there were no differences in clock gene expression
105
in the hippocampus, suggesting changes in central clock gene expression provoked by
exposure to light at night are regionally specific.
In addition to altering clock gene expression in the hypothalamus, exposure to
dim as opposed to dark nights attenuated the rhythm in all but one of the core circadian
clock genes assessed in the liver. Peripheral clocks are entrained by neural and endocrine
signaling from the SCN (Guo, Brewer, Champhekar, Harris, & Bittman, 2005;
McNamara et al., 2001), as well as local factors such as nutritional signals (Vollmers et
al., 2009). Recent work highlights the importance of peripheral clocks in regulating
metabolism as single tissue clock gene deletions in the liver or fat can result in metabolic
disturbances (Lamia, Storch, & Weitz, 2008; Marcheva et al., 2010; Paschos et al., 2012).
In addition to disruption in core clock mechanisms, mice exposed to dim light at
night attenuated Rev-Erb expression in the liver and adipose tissue. Although previously
considered an accessory feedback loop, REV-ERBs are increasingly demonstrated to be
essential for circadian clock function and regulation of rhythmic metabolism. Mice
deficient in both isoforms of REV-ERB show circadian rhythm adjustments and
pronounced changes in metabolically related functions (Bugge et al., 2012; H. Cho et al.,
2012).
Here I provide an extensive characterization of expression of circadian clock
genes and proteins in both the master circadian oscillator in the brain and tissue specific
clocks in mice exposed to light at night. Overall, these findings indicate that exposure to
light at night attenuates core circadian clock mechanisms in the SCN at both the gene and
protein level. Moreover, circadian clock function is disrupted in metabolically relevant
106
peripheral tissue (i.e., white adipose tissue and liver) by nighttime light exposure. These
changes in circadian clock function are associated with alterations in feeding behavior
and increased weight gain. These finding are significant because they provide evidence
for how mild changes in environmental lighting can alter circadian and metabolic
function. Exposure to light at night is pervasive in modern society and typically
considered a harmless environmental perturbation; however, these results demonstrate
nighttime light exposure alters homeostatic functions. Detailed analysis of temporal
changes induced by nighttime light exposure may provide insight into the onset and
progression of obesity and metabolic syndrome and other disorders involving sleep and
circadian disruption.
107
Figures
1 2 3 432
34
36
38
LD
dLAN
**
*B
od
y m
ass
LD dLAN0
5
10
15 *
Bo
dy m
ass g
ain
(% b
aseli
ne)
LD dLAN0
1
2
*
Ep
idid
ym
al
fat
pad
mass (
g)
LD dLAN0
10
20
30
40
50
*
Perc
en
t d
ayti
me
foo
d i
nta
ke
0 12 24
100
150
200
250LD
dLAN
Blo
od
glu
co
se (
mg
/dl)
A
E
C
B
D
Figure 6.1. Mice exposed to dim light at night alter somatic measures.
(A) Overall body mass (B) body mass gain and (C) epididymal fat pad mass were
increased in mice exposed to dimly lit as compared to dark nights. (D) Mice exposed to
dim light at night altered timing of food intake consuming more during the light phase
than mice exposed to dark nights. (E) Blood glucose was rhythmic and did not differ
between groups. All data are presented as (mean ± SEM). *indicates dLAN differs from
LD.
108
0.4
1.2
0
2
0.0
1.5
**
0.00
1.25
*
0.0
1.5
0
2 *
0.0
3.5
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0.0
3.5
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0.0
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*
0 12 24
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0 12 24
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1
2
Clock Bmal Per1 Per2 Cry1 Cry2
Liv
er
WA
TH
ipp
oca
mp
us
Hyp
oth
ala
mu
s
Re
lati
ve
mR
NA
ex
pre
ss
ion
A
B
C
D
Figure 6.2. Dim light at night attenuates clock gene expression.
(A) Hypothalamic, (B) hippocampal, (C) white adipose, and (D) liver tissues were collected at 4 h intervals from mice
exposed to dark (black lines) or dimly lit (dotted lines) nights and Clock, Bmal1, Per1, Per2, Cry1, and Cry2 mRNA
expression were quantified. Values are relative to a standard curve and normalized to 18S. * dLAN differs from LD
108
109
0
1
0.0
0.5
0 12 24
0.0
3.5
*
0 12 24
0.0
1.2
*
*
Re
lativ
e R
ev-
Erb
mR
NA
exp
ress
ion
WAT Liver
Hypothalamus Hippocampus
Figure 6.3. Dim light at night suppresses Rev-Erb expression in peripheral tissue.
Rev-Erb gene expression was quantified in the (A) hypothalamus (B) hippocampus, (C)
white adipose tissue, and (D) liver. Values are expressed as relative abundance (mean ±
SEM) after normalization to 18S *indicates dLAN differs from LD.
110
Figure 6.4. Clock protein expression is reduced in the SCN of mice exposed to dimly lit
nights.
111
(A) PER1, (B) PER2, (C) CLOCK, and (D) BMAL immunoreactivity were analyzed in
hypothalamic tissue collected every 4 h from mice exposed to either dark (black lines) or
dimly lit (dotted lines) nights for 4 weeks. Images of sections containing the SCN were
captured at 20X and the number of immonoreactive cells was counted and averaged
across section and sides of the bilateral structure. Data are presented as (mean ± SEM).
*indicates dLAN differs from LD.
112
CHAPTER 7
LIGHT AT NIGHT AFFECTS CARDIAC ARREST OUTCOME
Global ischemia produces high levels of central nervous system (CNS) damage
that profoundly affect patient survival and long-term cognitive and psychological
recovery. Minimizing this CNS injury to improve patient outcome is an important goal of
current research. Importantly, the majority of damage to the CNS produced by cerebral
ischemia is mediated by endogenous secondary processes (Krause, Kumar, White, Aust,
& Wiegenstein, 1986; Saito, Suyama, Nishida, Sei, & Basile, 1996). Excitotoxicity,
inflammation, and apoptosis develop in the days following injury and extensively
contributing to outcome (Eltzschig & Eckle, 2011; Kirino, 1982; Nitatori et al., 1995;
Weil, Norman, DeVries, & Nelson, 2008). The delay in CNS damage following injury
provides a potential therapeutic window for influencing recovery. This suggests changes
in environment may affect neural damage that develops post-ischemia.
One inconsistent environmental factor in hospitals is nighttime light exposure.
Hospital intensive care units have variable levels of lighting during both day and night
(Fig. 1; (Dunn, Anderson, & Hill, 2010)). These disruptive lighting conditions may
influence patient recovery because light is the most potent entraining signal for the
113
mammalian circadian clock (suprachiasmatic nuclei; SCN). Extrinsic light information
travels directly from the intrinsically photosensitive retina ganglion cells (ipRGCs) to the
SCN via the retinohypothalamic tract (Hattar, Liao, Takao, Berson, & Yau, 2002)
synchronizing daily physiological rhythms to the external light-dark cycle (Reppert &
Weaver, 2002). Aberrant light exposure can disrupt the circadian system creating
desynchrony between internal rhythms and the external environment.
Circadian rhythms are important for many homeostatic functions including those
associated with the immune system (Lange, Dimitrov, & Born, 2010). There are circadian
components to many immunological processes including antigen presentation, toll-like
receptor function, cytokine production, and lymphocyte proliferation (Arjona & Sarkar,
2006; A. C. Silver, Arjona, Walker, & Fikrig, 2012) and many immune cells such as
natural killer cells, macrophages, dendritic cells, and B cells possess molecular clock
mechanisms necessary for self-sustaining oscillations (Arjona & Sarkar, 2005; Keller et
al., 2009; A. C. Silver, Arjona, Hughes, Nitabach, & Fikrig, 2012). This reciprocal
relationship between the circadian system and immune function has led to multiple
studies evaluating the effects of chronic circadian disruption on human physiology. Shift-
workers, who are chronically exposed to LAN, are at increased risk for several
inflammatory disorders including heart disease (Ha & Park, 2005), cancer (Davis &
Mirick, 2006; Schernhammer et al., 2001), disrupted rhythmicity of neuroendocrine
function (such as corticotrophin releasing hormone, glucocorticoids, and prolactin)
(Claustrat, Valatx, Harthe, & Brun, 2008; Persengiev, Kanchev, & Vezenkova, 1991),
metabolic disorders and diabetes, as well as mood disorders (Dumont & Beaulieu, 2007).
114
Indeed, shift workers display several altered immune parameters, including elevated C-
reactive protein and increased leukocyte count (Puttonen, Viitasalo, & Harma, 2011).
Importantly, circadian disruption dysregulates inflammatory responses independently of
sleep loss or stress (Castanon-Cervantes et al., 2010). In healthy individuals, circadian
misalignment can be rapidly induced with aberrant lighting schedules, resulting in
adverse metabolic and cardiovascular consequences (Scheer, Hilton, Mantzoros, & Shea,
2009).
Cardiac arrest has both seasonal and circadian (i.e., time of day) patterns of
incidence and recovery (M. C. Cohen, Rohtla, Lavery, Muller, & Mittleman, 1997;
Spencer, Goldberg, Becker, & Gore, 1998; Weil et al., 2009), implicating light in altering
the physiological response to cerebral ischemia. Moreover, disruption of the core clock
gene Per2, impairs recovery following myocardial ischemia (Eckle et al., 2012). Light
exposure may be particularly salient to CA-induced neuroinflammation. Although several
mechanisms contribute to damage following ischemic injury, including energetic failure,
excitotoxicity, and oxidative damage (reviewed in (Eltzschig & Eckle, 2011; Weil,
Norman, DeVries, & Nelson, 2008), manipulation of inflammatory responses are
considered a prime target for improving recovery. Following CA an inflammatory
response is triggered by activation of microglia and astrocytes with a corresponding
upregulation of pro-inflammatory cytokines (Stoll, Jander, & Schroeter, 1998). IL-1β and
TNFα are pro-inflammatory cytokines that are upregulated within hours following global
ischemia (Saito, Suyama, Nishida, Sei, & Basile, 1996) and exacerbate injury. Therefore,
if dim light at night promotes inflammation, then it could be a critical factor for
115
consideration in cardiac arrest outcome. I hypothesized that light exposure at night would
potentiate injury following cardiac arrest. Consistent with my hypotheses, light at night
following CA enhanced acute cytokine responses, increased neuronal death, and resulted
in higher short-term mortality. Moreover, the effects of light at night were ameliorated
through inhibition of cytokines and manipulation of the light source.
Methods
Animals
8-week old male Swiss Webster mice (~30g; Charles River, Kingston, NY) were
housed in a temperature- and humidity-controlled vivarium and provided ad libitum
access to food and water. Mice were left unmanipulated for 1 week to recover from the
effects of shipping and adjust to a 14:10 light/dark (LD) cycle prior to experimental
manipulations.
Cardiac arrest and cardiopulmonary resuscitation procedure
Mice were anesthetized with 3% isoflurane in air, intubated, and maintained
thereafter on 1.5% isoflurane. Mice were ventilated a tidal volume of 150 µL at a
respiratory rate of 160 breaths/min. A temperature probe was inserted in the temporalis
muscle on the left side of the head as an indicator of brain temperature (correlation
between brain and temporalis muscle temp r2 = 0.942) (Neigh, Kofler et al., 2004). A
second probe monitored rectal temperature. A PE10 catheter was placed into the right
jugular vein for epinephrine (EPI) and potassium chloride (KCl) administration. Blood
pressure was monitored through a cannula inserted into the right femoral artery and
connected to a blood pressure transducer (Columbus, Instruments). Mice were stabilized
116
for 10 min and blood pressure and temperature recorded at 1 min intervals (Fig. 2).
Following the 10 min acclimation, body and tail (but not head) temperature were lowered
by circulating cold water through a coil system beneath the mouse to induce peripheral
hypothermia restricting damage to the CNS during the CA/CPR procedure. CA was
induced with an injection of KCL (50 μl, 0.5 M, 4°C) into the jugular catheter and the
mouse was disconnected from the ventilator. Once a body temperature of 27°C was
reached after approximately 4 min of arrest slow re-warming via a heat lamp and thermal
blanket began. After 7 min 45 sec of arrest mice were reattached to the ventilator and 100
% oxygen at a tidal volume of 150 µL and a respiratory rate of 160 breaths/min was
ventilated. After 8 min of arrest CPR was initiated with an injection of EPI (16 µg in 0.6
cc saline, 37°C) into the jugular catheter and chest compressions (300/min); 0.5 µg
injections of EPI were administered until the mouse resuscitated (with a maximal dose of
32 µg). Mice were maintained on 100% oxygen for 25 min after return of spontaneous
circulation and catheters were removed and incisions sutured.
Tissue collection and staining
One week following CA mice were individually brought into a procedure room,
anesthetized with isoflurane vapors and a blood sample was collected via the retro-orbital
sinus. Mice then received a lethal injection of sodium pentobarbital and were perfused
transcardially with ice-cold 0.1M PBS followed by 50 µL of 4% paraformaldehyde.
Brains were post-fixed overnight, cryoprotected in 30% sucrose, frozen on crushed dry
ice, and stored at -80ºC. Fourteen µm brain sections were sliced at -22ºC using a cryostat
and thaw mounted onto Super Frost Plus slides (Fisher, Hampton, NH). Sections were
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stored at -20ºC until stained with Fluoro-Jade C (FJ-C) or Iba1 using procedures already
established in our lab (Weil et al., 2009). Fluoro-Jade C. Cell death was quantified by
labeling degenerating neurons with the fluorescein derivative FJ-C (Millipore, Temecula,
CA). Mounted sections were thoroughly dried on a slide warmer, immersed in a basic
ethanol solution (80% EtOH with 1% NaOH) and rinsed with 70% ethanol followed by
water. Slides were placed in a 0.06% potassium permanganate solution for 10 min and
rinsed twice. Sections were simultaneously incubated in FJ-C (0.0001% in a 1% acetic
acid solution) and counterstained with DAPI (Sigma, St. Louis). Slides were rinsed 3X,
aspirated, completely dried, cleared in xylene for 1 min, and coverslipped with DPX
(Sigma). FJ positive cells were counted in the CA1, CA3, and DG of both hippocampal
hemispheres by a condition blind experimenter using a Nikon E800 microscope at 200X
magnification. Microglia. Microglia were visualized using a Iba1 directed antibody.
Slides were dried, rinsed in phosphate buffered saline (PBS), and blocked with bovine
serum albumin (BSA). Slides were incubated at room temperature for 24 h with rabbit
anti-Iba1 antibody (Wako, Richmond, VA) diluted 1:1000 in PBS containing 0.1%
Triton-X and BSA. Slides were rinsed and incubated with biotinylated goat anti-rabbit
secondary antibody (1:1000; Vector Labs, Burlingame, CA) for 1 h. Sections were
quenched in H2O2 in methanol, rinsed, and treated with Elite ABC reagent for 60 min
(Vector). Sections were rinsed, developed with DAB (Vector), rinsed, dehydrated,
cleared, and coverslipped. Photomicrographs of the hippocampus were taken with a
Nikon E800 microscope at 20X and images were assessed using Image J software (NIH)
to determine immunoreactive regions.
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Cytokine expression
A separate cohort of mice that underwent CA or SHAM was used for detection of
hippocampal cytokine gene expression using RT-PCR. Mice were brought individually
into a procedure room, anesthetized with isoflurane vapors, blood was drawn via the
retro-orbital sinus, and mice were rapidly decapitated. Brains were removed, divided
sagittally along the midline, and hippocampi extracted and immersed in RNALater
stabilizing solution RT-PCR. From hippocampi stored in RNALater, total RNA was
extracted using a homogenizer (Ultra-Turrax T8, IKAWorks, Wilmington, NC) and an
RNeasy Mini Kit (Qiagen). RNA was reverse transcribed into cDNA with M-MLV
Reverse Transcriptase enzyme (Invitrogen) according to the manufacturer‟s protocol.
Pro-inflammatory cytokine expression for IL-1β, IL-6, and TNFα was determined using
inventoried primer and probe assays (Applied Biosystems, Foster City, CA) on an ABI
7500 Fast Real Time PCR System using Taqman® Universal PCR Master Mix. The
universal two-step RT-PCR cycling conditions used were: 50 °C for 2 min, 95 °C for 10
min, followed by 40 cycles of 95 °C for 15 s and 60 °C for 1 min. Relative gene
expression of individual samples run in duplicate was calculated by comparison to a
relative standard curve and standardized by comparison to 18S rRNA signal.
Microglial isolation and RNA extraction
A separate cohort of mice that underwent CA or SHAM procedures was used for
microglial cytokine analysis. Microglia were extracted following a previously reported
protocol (Wynne, Henry, Huang, Cleland, & Godbout, 2010). Briefly, 24 h after surgery
and one night of either dLAN or LD mice were anesthetized with isoflurane vapors,
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blood was drawn via the retro-orbital sinus and mice were rapidly decapitated. Brains
were removed and placed in ice-cold Hank‟s Balanced Salt Solution (HBSS). Brains
were transferred to a sterile flow hood and crushed through a 70 µm nylon cell strainer.
The resulting homogenate was transferred to a 15 mL tube, topped off with additional
HBSS and centrifuged for 7 min at 600g at 15°C. Supernatant was discarded and cell
pellets re-suspended in 70% isotonic Percoll (GE Healthcare, Uppsala, Sweden). A
discontinuous Percoll gradient was created by applying layers of 70%, 50%, 35%, and
0% isotonic Percoll (bottom to top). Percoll gradient was centrifuged for 30m at 2000g at
15°C and microglia were extracted from the interphase layer between the 70% and 50%
Percoll. Microglia were then washed and RNA immediately extracted using a Sonicator
(Microson XL2000, Misonix Inc., Farmingdale, NY) and an RNAeasy Micro Kit
(Qiagen, Valencia CA). RNA was reverse transcribed into cDNA and processed as
described above (in Real-time (RT) PCR).
Administration of cytokine inhibitors
An indwelling cannula was inserted into the left lateral ventricle (cannula
position: +0.02 posterior and -0.95 lateral to bregma, extending 2.75 mm below the skull;
Plastics One, Roanoke, VA) of anesthetized mice using a stereotaxic apparatus three days
prior to CA or SHAM surgeries (Neigh et al., 2009). One hour following CA mice
received a 2 μL injection of either a vehicle solution (artificial cerebral spinal fluid,
aCSF), a monoclonal TNF antibody (Infliximab. IFX), an IL1 receptor antagonist (IL1-
ra), or an IL6 neutralizing antibody (IL6na) based on pre-assigned group and were then
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placed back in their respective lighting conditions. Cannula placement was verified on
Iba1 stained tissue.
Corticosterone radioimmunoassay
Within 30 min of collection, blood samples were centrifuged at 3000g for 30 min
at 4°C. Plasma was collected and stored at -80°C until assayed. The samples were
assayed using and I125
corticosterone kit (MP Biomedicals, Solon, OH). The standard
curve was run in triplicate and samples in duplicate. All samples within an experiment
were run in a single assay.
Statistical Analyses
Statistical comparisons among groups were conducted using ANOVA. In the case
of significant differences (p<0.05), a post-hoc Tukey‟s test was conducted. When
conditions of normality or equal variance were not met, the data were log transformed.
Above statistical tests will be conducted using StatView Software v. 5.0.1. Survival plots
were analyzed using Kaplan-Meier survival analysis. Differences were considered
statistically significant when p < 0.05.
Results
Hospital lighting levels
In order to assess typical lighting environments for patients recovering in hospital
settings, HOBO light loggers (Onset, Bourne, MA) were placed in patient rooms at The
Ohio State University Wexner Medical Center Hospital. Significant nighttime light
intrusions were observed in all units monitored, including the intensive care, post-
surgical, and cardiac intensive care units (Fig. 1; representative patient lighting). Patients
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experienced light levels as high as 100 lux several times each night between the hours of
11PM and 6AM. After confirming nighttime light disruptions in patient rooms, I used a
mouse model of CA to determine whether exposure to dim light at night influences
recovery following global cerebral ischemia.
Dim light at night increases mortality and hippocampal damage following CA
Eight week old Swiss Webster mice were acclimated to a standard light dark
cycle [14h light (150 lux): 10h dark (0 lux); LD] and then underwent a CA or SHAM
procedure (Fig. 2; surgical measures). I used nocturnal mice to avoid the confound of
sleep disruption. Following the procedure mice either remained in LD cycle or were
transferred to a bright-dim light cycle [14h light (150 lux): 10h dim light (5 lux); dLAN].
As anticipated, there was 100% survival in both SHAM groups. In contrast, CA
significantly reduced survival compared to the SHAM procedure (p < 0.05; Fig 3a).
Among the CA mice, mortality in the dLAN group was four-fold higher than in the LD
group suggesting that modest changes in the recovery environment markedly affect
cardiac arrest survival.
The reduced survival rate of mice exposed to dLAN may reflect increased
neuroinflammation and hippocampal cell death. One week following CA or SHAM
procedures mice were anesthetized and perfused transcardially with ice cold saline
followed by 4% paraformaldehyde. Brains were cryoprotected, frozen, sectioned, and
processed for Fluoro-JadeC, a marker for degenerating neurons. The Fluoro-JadeC
labeled tissue was used to evaluate cell death in the hippocampus, a brain region
particularly vulnerable to ischemic damage (Nikonenko, Radenovic, Andjus, & Skibo,
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2009). As expected, cell death was uniformly low among SHAM mice (Fig. 3b-d), and
significantly elevated among mice subjected to CA (p < 0.05; Fig. 3b,e,f). Moreover,
mice exposed to dLAN had significantly more cell death in the hippocampus one week
after CA compared with mice exposed to dark nights (p < 0.05; Fig. 3b-f). Hippocampal
cell death is a reliable proxy for overall recovery after global ischemia as increased
hippocampal damage is associated with elevated mortality and memory deficits, as well
as impaired affective responses (M. Fujioka et al., 2000; Langdon, Granter-Button, &
Corbett, 2008; Neigh, Glasper et al., 2004; Neigh, Kofler et al., 2004; Zola-Morgan,
Squire, & Amaral, 1986). Investigation of corticosterone concentration at 6 h intervals
following CA did not reveal any significant differences between the CA-dLAN and CA-
LD groups during the first 24 h of recovery (p > 0.05; Fig. 4).
Dim light at night alters acute inflammatory status
The inflammatory response following global ischemia is an important factor in
recovery. Thus, I investigated whether dLAN alters the expression of pro-inflammatory
cytokines following CA. Brain tissue was collected 24 h after CA or SHAM procedures,
i.e., after only a single night of post-ischemic dLAN or LD. The brains were rapidly
removed and placed in RNA later. The following day, hippocampi were dissected out and
used for quantitative real time PCR (q-PCR) analyses of pro-inflammatory cytokines. As
expected, TNFα, IL1β, and IL6 gene expression were elevated among CA compared to
SHAM mice (p < 0.05; Fig 5a-c). Moreover, exposure to a single night of dLAN after CA
was sufficient to upregulate expression of TNFα and IL1β, compared to mice exposed to
a dark night (p < 0.05; Fig. 5a,b). The increase in pro-inflammatory cytokine expression
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may occur very early after placement back in lighting conditions. Indeed, a difference in
post-CA TNFα expression was apparent after as little as 4 h of total darkness versus dim
light (p < 0.05; Fig. 5d). There were no differences in hippocampal cytokine gene
expression between dLAN and LD mice that underwent the SHAM procedure (p > 0.05).
In sum, acute upregulation of inflammatory markers among CA mice housed in dLAN
may contribute to the increased hippocampal neuronal death and mortality observed in
this group.
Microglia are the resident immune cells in CNS and perturbations of the
microenvironment can induce microglial activation, resulting in altered morphology and
secretion of pro-inflammatory mediators (Graeber, 2010; Nimmerjahn, Kirchhoff, &
Helmchen, 2005). Therefore, I hypothesized that microglia increase cytokine expression
24 h after CA in dLAN mice, contributing to the overall elevation in inflammatory status
in the dLAN-CA group. Microglia were extracted from whole brain tissue using a Percoll
gradient 24 h after CA or SHAM procedures (a single night of dLAN or LD lighting
conditions). mRNA was extracted immediately following microglial isolation and pro-
inflammatory cytokine expression was evaluated. IL-1β and TNF-α mRNA expression
were significantly higher in microglia isolated from CA mice as compared to SHAM
mice (p < 0.05; Fig. 5e,f). Furthermore, exposure to a single night of dLAN after CA
elevated microglial IL-1β and IL-6 mRNA relative to LD (p < 0.05; Fig 5f,g). These
results suggest that microglia may be partially responsible for the pro-inflammatory bias
observed among mice that were housed in dLAN after CA.
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We also examined whether altered circulating glucocorticoid concentrations could
be contributing to the impaired recovery after CA because elevated corticosterone has
previously been associated with increased CA-induced neuroinflammation and neuronal
death (Neigh et al., 2009). However, altered corticosteroid responses do not appear to
underlie the differences in ischemic outcome between the CA-LD and CA-dLAN groups;
there were no differences in corticosterone concentrations between CA or SHAM groups
at 24h (p > 0.05; Fig. 5h).
Inhibition of selective cytokines ameliorates light induced damage
Although several mechanisms contribute to damage following ischemic injury,
including energetic failure, excitotoxicity, and oxidative stress (reviewed in (Weil,
Norman, DeVries, & Nelson, 2008), manipulation of inflammatory responses are
considered a prime target for prevention of damage. Following ischemic brain damage
both selective targeting of specific cytokines and non-selective (e.g., minocycline)
inhibition of pro-inflammatory cytokines ameliorate damage improving recovery and
behavioral outcomes (Craft & DeVries, 2006; Karelina et al., 2009; Mizushima et al.,
2002; Neigh et al., 2009). Because the results indicate that IL-1β, TNF-α, and IL-6
mRNA expression are greater among CA-dLAN mice compared to CA-LD mice, I
hypothesized that selective inhibition of these pro-inflammatory cytokines would
improve outcome following CA-dLAN. Three days prior to the CA procedure, mice were
implanted with a cannula directed at the lateral ventricle. Two hours following CA, mice
were administered a single 2μL ICV injection of either vehicle (artificial cerebrospinal
fluid; aCSF), mouse IL6 neutralizing antibody (IL6-na), TNF monoclonal antibody
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(infliximab; IFX), or recombinant mouse IL-1 receptor antagonist (IL1-ra). Hippocampal
cell death was evaluated using Fluoro-JadeC as described above. IL1-ra and IFX
decreased hippocampal cell death compared to aCSF treatment among CA-dLAN mice (p
< 0.05; Fig. 6b), producing levels of neuronal death that were similar to CA-LD mice
treated with the vehicle (p>0.05). In contrast, treatment with IL6-na did not ameliorate
hippocampal neuronal damage associated with CA-dLAN.
A similar pattern was apparent for microglial activation, which is often used as an
index of neuroinflammation (Amantea, Nappi, Bernardi, Bagetta, & Corasaniti, 2009).
Brain tissue was labeled with Iba-1, an antibody directed against microglia; increased
Iba-1 surface area suggests microglial activation (Donnelly, Gensel, Ankeny, van
Rooijen, & Popovich, 2009). Significantly greater microglial activation in the CA1, CA2,
and CA3 subfields of the hippocampus was apparent among the CA-dLAN mice treated
with the vehicle (aCSF) relative to the CA-LD mice treated with the vehicle (p < 0.05;
Fig. 6c-i). Furthermore, treatment of CA-dLAN mice with IL1-ra or IFX reduced
microglia activation in the CA1, CA2, and CA3 (p < 0.05; Fig. 6c-i) relative to the CA-
dLAN mice treated with vehicle. Iba1 expression in CA-dLAN mice treated with IL1-ra
or IFX did not differ from CA-LD mice treated with the vehicle in any of the
hippocampal subfields quantified. In contrast, CA-dLAN mice treated with IL6-na had
levels of microglial activation in the CA1 that were comparable to CA-dLAN mice
treated with the vehicle, while levels of microglial activation in the CA2 and CA3 regions
were intermediate between vehicle treated CA-dLAN and CA-LD mice. Thus, inhibiting
IL-1 and TNF-α signaling in CA-dLAN mice normalized the microglial and
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neurodegenerative responses. Furthermore, the results suggest IL1 and TNFα cytokine
pathways may be more involved than IL6 in inducing hippocampal damage.
Alternative spectra of lighting minimize light induced damage
The circadian system is not equally responsive to all wavelengths of lighting. The
intrinsically photosensitive retinal ganglion cells (ipRGCs) that project to the master
circadian pacemaker in the SCN contain melanopsin and are most responsive to the blue
region of the visible light spectrum ranging from 450 to 485 nm. These wavelengths are
present in broad spectrum white light such as natural sunlight and the majority of indoor
lighting. Longer wavelengths of lighting, such as red light, do not activate ipRGCs and
therefore minimally influence the circadian system (Brainard et al., 2008; Figueiro &
Rea, 2010). Thus, I hypothesized that the circadian system is involved in dLAN induced
damage following CA with ipRGCs communicating the light information. To test this
hypothesis I examined whether mice exposed to red light at night would more closely
resemble the LD phenotype than the dLAN phenotype. Following CA, mice were placed
in LD, dLAN [14 h light (150 lux): 10 h dim light (5 lux; 6500K cool white light-
containing blue wavelengths)] or a bright-dim red light cycle [rLAN; 14 h light (150 lux):
10 h dim red (5 lux; 636 nm)]. Tissue was collected either seven days later for analysis of
neuronal damage (assessed by Fluoro-JadeC) and microglial activation (via Iba-1) or
after 24 h for evaluation of pro-inflammatory cytokine expression.
Unlike full spectrum light at night, dim red light at night did not increase
mortality following CA. There were no differences in mortality between CA mice
exposed to rLAN versus LD (p > 0.05; Fig. 7a). As in the first experiment, CA-dLAN
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increased hippocampal cell death compared to CA-LD (p < 0.05; Fig. 7b,d-f). In contrast,
rLAN did not exacerbate ischemic cell death. Hippocampal neuronal damage among CA-
rLAN mice resembled that of CA-LD mice (p > 0.05) and there was significantly less
damage among rLAN mice compared to dLAN mice following CA (p < 0.05; Fig. 7b,d-
f). I similarly replicated the findings that CA-dLAN mice exhibited increased microglia
activation in multiple hippocampal subfields compared to CA-LD conspecifics (p < 0.05;
Fig. 7c,g-i), whereas rLAN did not increase post-ischemic microglia activation relative to
CA-LD (p > 0.05; Fig. 7c,g-i).
Because the previous results indicate that light at night affects recovery by
altering acute changes in the inflammatory response I evaluated hippocampal pro-
inflammatory cytokine expression 24 h after CA and a single night of dark, dim white
light or dim red light. Again, dLAN mice elevated hippocampal TNFα and IL6
expression compared to LD mice 24 h post-ischemia (p < 0.05; Fig. 7j,l). Red light did
not elevate pro-inflammatory cytokine expression compared to LD controls (p > 0.10);
dLAN mice had significantly elevated TNFα, IL6 and IL1β expression compared to
rLAN mice (p < 0.05; Fig 7j-l). These results indicate that standard indoor lighting could
potentiate neuroinflammation and neuronal damage following CA, whereas alternative
lighting using wavelengths greater than ~600 nm are not likely to produce the same
detrimental biological responses.
Discussion
Cardiovascular disease is the leading causes of death in the US (CDC, 2009). The
survival rate for cardiac arrest is very low, and the majority of patients who survive live
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with extensive physical, cognitive, and affective disabilities (Elliott, Rodgers, & Brett,
2011; Keuper, Dieker, Brouwer, & Verheugt, 2007; Lim, Alexander, LaFleche, Schnyer,
& Verfaellie, 2004). However, the results presented in this dissertation indicate that
adjusting environmental lighting could prove to be an inexpensive and effective way to
improve patient outcome in cardiac intensive care units. Because of patient safety
concerns and the need for monitoring, hospital ICU rooms are rarely completely dark and
it is not uncommon for patients to be exposed to bright lights (100 lux) several times per
night (Figure 1; (Dunn, Anderson, & Hill, 2010)). Indeed, even patients whose eyelids
are closed may be affected by the light intrusion (Robinson, Bayliss, & Fielder, 1991).
Here I show that exposing mice to as little as 5 lux of dim light at night after resuscitation
from CA exacerbates neuroinflammation and neuronal damage, and increases short-term
mortality four-fold relative to mice that are maintained in a consistent light-dark cycle.
The effects on neuronal damage and mortality appear to be mediated by increased
neuroinflammation among CA mice exposed to dLAN. Indeed, TNF-α mRNA expression
in the hippocampus is elevated as early as 4 h after exposure to dLAN, and by 24 h the
CA-dLAN group has significantly greater TNF-α, IL-1β, and IL-6 mRNA expression
compared to the CA-LD group (Fig. 2). These pro-inflammatory cytokines are known to
contribute to damage after cerebral ischemia (Betz, Schielke, & Yang, 1996; Hurn et al.,
2007). Thus, early changes in the inflammatory response caused by light at night may
alter the trajectory of recovery resulting in higher mortality and increased neuronal
damage characterized after one week.
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Inhibition of TNF-α, IL-1, or IL-6 signaling among CA-dLAN mice produced 7-
day survival rates that approximated or exceeded the survival rate for the CA-LD group
(Fig. 3a), although only treatment with IL-1ra or IFX significantly reduced microglial
activation and neuronal damage relative to the CA-dLAN mice. Thus, two bodies of
evidence point to a role of increased inflammatory responses in mediating elevated
neuronal damage among the CA-dLAN mice: (1) both proinflammatory cytokine gene
expression and neuronal damage were elevated after exposure to dLAN relative to LD
and (2) treatment with IL1ra or IFX prevented the exacerbation of neuronal damage and
microglial activation observed among vehicle treated CA-dLAN mice.
Although pharmacological intervention clearly reduced the detrimental effects of
dLAN on CA-induced microglial activation, neuronal damage, and short-term mortality,
a far simpler approach to improving CA outcome is to modify the physical qualities of
the nighttime light to prevent increased neuroinflammation. For example, night time red
light of the same illuminance as the dim white light did not exacerbate CA-induced
neuronal damage or microglial activation in mice. Indeed, the CA-rLAN mice did not
differ significantly from CA-LD mice in either of these measures (Fig. 3). These data are
consistent with studies reporting that red light at night does not affect other aspects of
physiology and behavior in humans or other animals to the same extent as broad
spectrum white light that contains blue wavelengths (Figueiro, Wood, Plitnick, & Rea,
2011). The effects of night time light are likely mediated by the suprachiasmatic nucleus
or “master circadian clock”, which receives input from melanopsin containing ipRGCs in
the retina. The ipRCGs are activated by blue light (~480nm, found in outdoor and most
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indoor lighting, especially fluorescent lights), but are unaffected by long wavelength
light, such as red light. The minimal influence of red light compared to white light on CA
recovery suggests that light recognition by the circadian system is involved in dim white
light induced exacerbation of CA damage. Importantly, exposure to dim light at night is
an equally potent facilitator of inflammation in diurnal rodents (Fonken, Haim, & Nelson,
2011).
In sum, the mouse data presented here suggest that exposure to light at night, a
common occurrence in hospital rooms, increases short-term mortality and compromises
recovery from cerebral ischemia by exacerbating neuroinflammation. Using red lights at
night in hospital rooms or having patients wear goggles that filter lower wave length light
could be inexpensive solutions that allow visibility without priming the immune system
of the patients. If the effects of white light at night are replicated in cardiovascular
patients, then these results could have important implications for the design of lighting in
clinical settings and could apply to a broad number of conditions and medical procedures
that involve ischemia and inflammation, such as stroke, cardiovascular artery bypass
graft, sickle cell disease, sleep apnea, and organ transplant.
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Figures
Figure 7.1. Ambient lighting in cardiac intensive care unit patient rooms.
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CASHAM
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Figure 7.2. Cardiac arrest and cardiopulmonary resuscitation surgical parameters.
Mean arterial blood pressure, temporalis temperature, and core body temperature across
the CA/CPR procedure.
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Figure 7.3. Dim light at night impairs cardiac arrest recovery.
(A) dLAN increases short-term mortality following CA in a rodent model. (B-F) dLAN
exacerbates CA induced hippocampal cell death as indicated by Fluoro-JadeC staining.
Representative Fluoro-JadeC stained sections from the CA1 of (C) LD-SH (D) dLAN-SH
(E) LD-CA and (F) dLAN-CA mice one week following the CA procedure.
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0 6 12 18 240
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Figure 7.4. Corticosterone concentrations in the 24 h following cardiac arrest.
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Figure 7.5. Cytokine expression is elevated in the hippocampus and microglia of mice
exposed to dim light at night following cardiac arrest.
136
Hippocampal (A) TNFα, (B) IL1β, and (C) IL6 gene expression are upregulated 24 h
following CA and placement in dLAN. (D) TNF-α expression is elevated as early as 6
hours post-CA and only 4 hours of dLAN. Microglial (E) TNFα, (F) IL1β, and (G) IL6
gene expression are also altered 24 h following CA and placement in dLAN. (h) Serum
corticosterone concentrations are unaffected by light at night.
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Figure 7.6. Selective inhibition of specific cytokines attenuates inflammation and
neuronal cell death following cardiac arrest and exposure to dim light at night.
(A) Percent survival following CA and treatment with different cytokine inhibitors. (B)
Neuronal damage in the hippocampus as indicated by Fluoro-JadeC staining. (C)
Proportional area of Iba1 staining in the CA1. Representative photomicrographs from the
CA1 of mice treated with (D) LD-Veh (E) dLAN-Veh (F) dLAN-IL1ra (G) dLAN-IL6ab
(H) dLAN-IFX. (I) Proportional area of Iba1 staining throughout the hippocampus.
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Figure 7.7. Manipulation of lighting wavelength minimizes light at night induced
damage following CA.
(A) Percent survival following CA and placement in LD, dLAN, or rLAN. (B) Neuronal
damage in the hippocampus as indicated by Fluoro-JadeC staining. (C) Proportional area
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of Iba1 staining in the CA1. Representative photomicrographs of Flourojade staining
from the CA1 of (D) LD (E) dLAN and (F) rLAN mice. Representative
photomicrographs of Iba1 staining from the CA1 of (G) LD (H) dLAN and (I) rLAN
mice. (J) Proportional area of Iba1 staining throughout the hippocampus. Compared to
LD controls (K) TNFα, (L) IL1β, and (M) IL6 gene expression are elevated 24 h
following CA and placement in dLAN but not rLAN (*dLAN significantly differs from
both rLAN and LD, #dLAN
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CHAPTER 8
DIM LIGHT AT NIGHT ELEVATES INFLAMMATORY RESPONSES IN NILE
GRASS RATS, A DIURNAL RODENT
Most organisms possess an endogenous biological clock that is synchronized by a
very reliable exogenous cue: the daily cycle of light and dark produced by the rotation of
the Earth about its axis. This biological clock is adaptive as it helps to maintain both daily
and seasonal rhythms that allow animals to anticipate changes in the external
environment (Hut & Beersma, 2011). The natural light-dark cycle, however, is now
disrupted for many humans and nonhuman animals. With the advent of electric lights,
light exposure is no longer limited to the natural pattern. Instead of aligning the circadian
system with a stable cyclical factor, individuals currently experience a variety of lighting
schedules. This divergence from the natural environment is not without repercussions.
Disruptive lighting affects many physiological and behavioral functions (Fonken &
Nelson, 2011; Navara & Nelson, 2007). For example, individuals exposed to altered light
cycles are at increased risk for heart disease (Ha & Park, 2005), cancer (Davis & Mirick,
2006; Kloog, Portnov, Rennert, & Haim, 2011; Schernhammer et al., 2001), sleep
disturbances (Deboer, Detari, & Meijer, 2007; Kohyama, 2009), circadian rhythm
141
dysfunctions (Borugian, Gallagher, Friesen, Switzer, & Aronson, 2005), disrupted
rhythmicity of neuroendocrine function (Claustrat, Valatx, Harthe, & Brun, 2008;
Persengiev, Kanchev, & Vezenkova, 1991), mood disorders (Dumont & Beaulieu, 2007;
Fonken et al., 2009), metabolic dysfunction (Fonken et al., 2010; Reiter, Tan, Korkmaz,
& Ma, 2011), and reproductive dysfunction (Fiske, 1941; Thomas, Oommen, &
Ashadevi, 2001). One common factor for many of these pathologies is altered immune
function.
Circadian timing in mammals is organized by a hierarchy of oscillating tissues, at
the top of which are the suprachiasmatic nuclei (SCN) of the hypothalamus (Reppert &
Weaver, 2002). Light information is the primary entraining cue for this master circadian
clock. Light travels from the external environment through the intrinsically
photosensitive retinal ganglion cells (ipRGCs) to the SCN. The SCN then influences
downstream “slave” oscillators via the autonomic nervous system and control of the
sleep-wake cycle. SCN driven sympathetic innervation of the pineal gland regulates the
release of melatonin; nighttime sympathetic neural stimulation leads to the production of
melatonin from its precursor serotonin in the pineal gland. This nocturnal melatonin
signal provides time of day information to cells throughout the body and is the most
reliable peripheral marker of central clock activity (Blask, 2009). Nocturnal lighting, if
sufficiently bright, disrupts the synthesis of melatonin (Brainard et al., 1985; Brainard,
Richardson, Petterborg, & Reiter, 1982; Dauchy et al., 2010). Importantly, modulation of
both the circadian system and melatonin alters immunological measures.
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Multiple immune markers such as interleukin 2 (IL2), IL10, IL6, IL1β, tumor
necrosis factor alpha (TNFα), interferon gamma (IFNγ), and chemokine receptor 2
(CCR2) are expressed in a circadian pattern (Lundkvist, Robertson, Mhlanga, Rottenberg,
& Kristensson, 1998; Young et al., 1995). Disruption of the circadian system through jet-
lag, genetic mutations, or light exposure, changes the normal pattern of immune
parameters. For example, mice with a loss of function mutation in the clock gene Period
2 (Per2) have irregular production of IL10 and IFNγ in response to lipopolysaccharide
(LPS) injection (Arjona & Sarkar, 2006). Mice deficient in Bmal1, another critical clock
component, show early signs of aging such as sarcopenia, cataracts, organ shrinkage and
elevated reactive oxygen species (ROS) in the kidney and spleen. The lifespans of Bmal1
deficient mice are also reduced (Kondratov, Kondratova, Gorbacheva, Vykhovanets, &
Antoch, 2006). Cry 1 and 2 knockout mice have exacerbated cytokine and joint swelling
after arthritic induction (Hashiramoto et al., 2010). Furthermore, using a phase advancing
chronic jet-lag (CJL) protocol causes persistent hypothermia and reduced survival
following LPS administration in mice, and macrophages extracted from these mice have
increased cytokine response to LPS (Castanon-Cervantes et al., 2010).
The nighttime increase in pineal melatonin production and secretion correlates
with reduced innate immune responses (Markus, Ferreira, Fernandes, & Cecon, 2007).
NF-κB, a pleiotropic transcription factor involved in the regulation of genes encoding for
immune related enzymes, displays daily variation (Cecon, Fernandes, Pinato, Ferreira, &
Markus, 2010; Z. Chen, Gardi, Kushikata, Fang, & Krueger, 1999). NF-κB induces
multiple pro-inflammatory cytokines, inducible nitric oxide synthase (iNOS), and
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cyclooxygenase-2 (COX-2). Melatonin blocks NF-κB nuclear translocation in leukocytes
and endothelial cells, suppressing immune gene transcription activity (Gilad et al., 1998;
Tamura, Cecon, Monteiro, Silva, & Markus, 2009). Darkness induced suppression in NF-
κB transcription is blocked by propranolol (a drug that inhibits melatonin production in
addition to altering catecholaminergic function). In vitro work has further supported the
role of melatonin in NF-κB signaling as melatonin reduces NF-κB in cultured pineal
glands (Cecon, Fernandes, Pinato, Ferreira, & Markus, 2010). In a rat model of diabetes
increased expression of NF-κB and pro-inflammatory cytokines including TNFα and IL6
were reduced with melatonin treatment (Negi, Kumar, & Sharma, 2011). Melatonin also
impairs capacity for rolling and adhesion among leukocytes (Lotufo, Lopes, Dubocovich,
Farsky, & Markus, 2001). Furthermore, communication between the circadian and
immune system is bidirectional with multiple studies characterizing an immune-pineal
axis (Couto-Moraes, Palermo-Neto, & Markus, 2009; Lopes, Mariano, & Markus, 2001;
Markus, Ferreira, Fernandes, & Cecon, 2007). For example, administration of LPS
inhibits norephinephrine (NE) induced N-acetylserotonin (NAS) production resulting in
decreased nocturnal melatonin production (da Silveira Cruz-Machado et al., 2010).
Taken together, these studies suggest that nighttime lighting may affect immune
function through disruption of the circadian system and suppression of melatonin.
Recently our lab demonstrated that Siberian hamsters (Phodopus sungorus) exposed to
dim nighttime lighting (dLAN) reduce immunological capabilities (Bedrosian, Fonken,
Walton, & Nelson, 2011a). Housing female Siberian hamsters under dLAN for 4 weeks
reduces delayed-type hypersensitivity responses, decreases bactericidal capacity of blood,
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and prevents fever-associated reductions in locomotor activity. Because Siberian
hamsters are nocturnal, and in the laboratory are typically exposed to light at night during
their active period, I asked whether light at night would evoke similar responses in a
diurnal species. Thus, I investigated the effects of nighttime light exposure on immune
parameters in Nile grass rats (Arvicanthis niloticus), a diurnal rodent species. Male grass
rats were exposed to either a standard light- dark cycle or dim light at night for 3 weeks
and then tested for delayed type hypersensitivity, bacteria killing capacity, and antibody
production.
Methods
Animals
Male grass rats (Arvicanthis niloticus) used in this study were bred in the Nelson
lab colony at the Ohio State University from a wild stock obtained by Dr. Laura Smale,
Michigan State University, from the Masai Mara reserve in Kenya. Grass rats were bred
under a light-dark (LD) cycle (14:10 light (~150 lux) /dark (0 lux); lights illuminated at
7:00 Eastern Standard Time [EST]) and all animals were provided food (ProLab RMH
2000, LabDiet) and water ad libitum. Experimental grass rats were weaned between 21
and 24 days of age and housed with same sex siblings in polypropylene cages (40 cm x
20 cm x 20 cm) with straw bedding. Colony rooms were maintained at a temperature of
20 ± 4º C and a relative humidity of 50% ± 10%. At approximately 3 months of age grass
rats were singly housed, randomly assigned a number, and were either maintained in LD
(n=9) or placed in dLAN (n=9; 14:10 light (~150 lux)/ dim (~5 lux); lights illuminated at
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7:00 EST) for the remainder of the study. Immunological testing began after 3 weeks in
the lighting conditions.
Delayed-type hypersensitivity (DTH)
DTH is a cell mediated response that provides information about the primary
immune reaction to invading pathogens. After 3 weeks in lighting conditions grass rats
were assessed for DTH response to the chemical antigen 2,4-dinitro-1-fluorobenzene
(DNFB; Sigma, St. Louis, MO). Grass rats were individually brought into a procedure
room between 14:00 and 15:00 EST, lightly anesthetized with isoflurane vapors,
weighed, and a blood sample was collected from the retro-orbital sinus for use in the
bacteria killing and corticosterone assays (see below). Following blood collection a 1 x 2
cm patch of fur was shaved on the dorsum and 25 μl of DNFB in a 0.5% solution (wt/vol)
of 4:1 acetone to olive oil (prepared fresh daily) was applied to the dorsal skin in the
same location on two consecutive days. To obtain a baseline measurement, both right and
left pinna were measured during sensitization with a constant loading dial micrometer
(Mitutoyo, America Corp., Aurora, IL, USA). Grass rats were then left undisturbed for 1
week, after which they were again anesthetized, pinna thickness measured, and
challenged on the surface of the right pinna with 20 µl of 0.2% (wt/vol) DNFB in 4:1
acetone to olive oil. Left pinna was treated with the vehicle solution and both pinnae were
measured every 24 h for 7 days. Pinna swelling values obtained on each day were
expressed as a percentage of baseline thickness. All measurements occurred between
14:00 and 15:00 EST. DTH is an in vivo measure of cell mediated immune responses that
is characterized by swelling at the site of DNFB challenge. Swelling of the right pinna is
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due to infiltration of leukocytes into the epidermis and dermis (Vadas, Miller, Gamble, &
Whitelaw, 1975). This immune measure was previously validated; pinna swelling is
positively correlated to the intensity of the immune reaction (Phanuphak, Moorhead, &
Claman, 1974).
Keyhole limpet hemocyanin (KLH)
Two weeks following the conclusion of DTH measures humoral immune function
was assessed by injecting grass rats with 140 µg KLH suspended in 0.2 mL sterile saline.
KLH is a respiratory protein from the giant keyhole limpet (Megathura crenulata) that
produces a robust antigenic response without inducing fever or a long-term inflammatory
response. KLH production has not previously been assessed in grass rats, therefore, this
dose was determined based on other arvicoline rodents and resulted in similar patterns of
plasma immunoglobulin G (IgG) production (Klein & Nelson, 1999; Weil, Martin, &
Nelson, 2006). Blood was drawn from the retro-orbital sinus at the time of injection and
5, 10, and 15 days post injection in order to capture peak immunoglobulin production
(Demas, Chefer, Talan, & Nelson, 1997). All blood sampling occurred between 14:00
and 15:00 EST. Blood samples were centrifuged at 4° C for 30 min at 3.3 g and plasma
was pulled off and stored in microcentrifuge tubes at -80° C.
KLH ELISA
Plasma concentrations of anti-KLH IgG were determined using an enzyme-linked
immunosorbent assay (ELISA) as previously described (Demas, Chefer, Talan, &
Nelson, 1997). Plates were coated overnight with dialyzed KLH antigen, washed, and
blocked the subsequent night with a milk blocking buffer. Plates were then washed and
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150 µL of plasma diluted 1:80 in PBS+Tween was added in duplicated to the wells.
Following a 3 h incubation plates were again washed and incubated for 1.5 h with a
secondary antibody (alkaline phosphatase-conjugated anti-mouse IgG). Plates were then
treated with the enzyme substrate (p-nitrophenyl phosphate) before determining the
optical density of each well with a plate reader (Benchmark Microplate Reader, Biorad,
Hercules, CA) and 405 nm wavelength filter. To minimize intra-assay variability optical
density was averaged over duplicate wells and expressed as a percentage of the plate-
positive control value for statistical analyses.
Bactericidal capacity of blood plasma
Blood samples collected directly prior to DTH sensitization were used in this
assay. Blood was centrifuged at 3300 g for 30 min at 4° C and plasma was pulled off and
stored at -80° C. Plasma samples were diluted 1:20 in L-glutamine CO2-independent
media (Gibco, Carlsbad, CA, USA). A standard number of colony-forming units (CFUs)
of Escherichia coli (Epower 0483E7, Fisher Scientific) were added to each sample and
samples were incubated for 30min at 37° C. Using sterile techniques 75 μL of each
sample was plated in duplicate on tryptic soy agar plate. Two positive controls of diluted
bacteria alone and two negative controls of CO2-independent media were also plated.
Plates were inverted and incubated overnight and total CFUs were counted and expressed
as a percent of the positive control.
Radioimmunoassay Procedure (RIA)
Blood samples were collected for RIA of corticosterone from the retro-orbital
sinus of grass rats on the first day of DTH sensitization. Blood samples were centrifuged
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at 4° C for 30 min at 3.3g and plasma was pulled off and stored in sealable polypropylene
microcentrifuge tubes at -80° C until assayed. Total plasma corticosterone concentrations
were determined in duplicate using an ICN Diagnostics 125
I double antibody kit (Costa
Mesa, CA, USA). The high and low limits of detectability of the assay were 1200 and 3
ng/ml, respectively. The intra-assay coefficient of variation was 11%. All procedures
followed the manufacturer guidelines.
Activity analyses
A separate cohort of grass rats were implanted intraperitoneally (i.p.; under sterile
conditions) with telemeters (PDT-4000; Minimitter, Bend, OR) while under isoflurane
anesthesia. Surgical wounds were treated topically with Betadine (Sigma Chemical, St.
Louis, MO) to discourage infection, and grass rats were injected (i.p.) with buprenorphine
(0.1mg/kg; Sigma Chemical) in sterile saline to alleviate pain during recovery. Following
surgery, grass rats were placed in a clean cage, which was placed on a receiver
(Minimitter) connected to a computer. Receivers collated emitted body temperature and
movement activity frequencies continuously over 30 min intervals and converted them to
raw data based on pre-programmed calibration curves for each transmitter.
Data analyses
Tissue weight, body mass, and total surviving CFU‟s were compared between
lighting conditions using a one-way analysis of variance (ANOVA). Delayed-type
hypersensitivity swelling and anti-KLH were analyzed with a repeated measures
ANOVA with lighting condition as the between-subject factor and time as the within
subject variable. Following a significant result on repeated measures ANOVA, single
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time point comparisons were made. Plasma corticosterone concentrations were analyzed
using a one tailed t- test based on a priori hypotheses (Keppel & Wickens, 2004). Fourier
analysis was used to determine whether locomotor activity was rhythmic and followed 24
h periodicity using Clocklab software from Actimetrics (Wilmette, IL). Grass rats were
considered rhythmic when the highest peak occurred at ~1 cycle per day with an absolute
power of at least 0.005 mV/Hz as previously described (Kriegsfeld et al., 2008). FFT
power values for 0.083 cycles per day were compared between lighting conditions by one
way ANOVA. Percentage of daytime activity and total daily activity were also analyzed
by one way ANOVA. Nonlinear regression analysis was used in GraphPad Prism
software (v. 4 La Jolla, CA). In all cases, differences between group means and
correlation coefficients were considered statistically significant if p ≤ 0.05.
Results
Reproductive and somatic measures
There were no differences in body, reproductive tissue, adrenal, spleen, or thymus
mass between groups (p > 0.05; Table 1).
Circadian activity pattern
There were no differences between grass rats housed with dLAN and those in LD
with respect to circadian pattern in activity, total daily activity, or percentage of activity
occurring during the light phase (p>0.05; Fig. 1).
Plasma corticosterone concentrations
Samples for corticosterone analysis were collected directly prior to DTH
sensitization. Plasma corticosterone concentrations were elevated among grass grass rats
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exposed to dLAN as compared to those exposed to dark nights (t16 = 1.815; p ≤ 0.05; Fig.
2a).
DTH swelling responses
One dLAN grass rat did not develop a swelling response and was excluded from
comparisons. The remaining grass rats all exhibited robust swelling of the right pinna
over the measurement period (F5,75 = 19.58, p ≤ 0.05; Fig. 2b). There was a main effect of
lighting condition, such that grass rats exposed to dLAN had significantly elevated
swelling of the right pinna as compared to conspecifics housed with dark nights (F5,75 =
4.30, p ≤ 0.05). dLAN grass rats had greater swelling on days 2 and 3 post challenge than
grass rats exposed to dark nights (F1,15 = 5.62 and 5.19, respectively, p ≤ 0.05).
Furthermore, there was a positive association between plasma corticosterone
concentrations and pinna swelling on days 2, 3, and 5 post challenge (r2 = 0.327, 0.219,
0.391, p ≤ 0.05; day 2 shown; Fig. 2c).
KLH antibody production
Two grass rats, one per group, produced no antibody in response to the KLH
injection and were excluded from the analyses. Grass rats significantly elevated antibody
production following KLH injection (F3,42 = 105.60, p ≤ 0.05). There was an interaction
between light condition and time (F3,42 = 5.21, p ≤ 0.05), such that grass rats exposed to
dLAN increased anti-KLH IgG production 10 and 15 days following injection (F1,14 =
13.11, 7.67, p ≤ 0.05; Fig. 3a).
Bacteria colony killing
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Grass rats housed with dLAN decreased the percentage of surviving CFUs
compared to grass rats housed in standard LD conditions (F1,16 = 8.155, p ≤ 0.05; Fig.
3b).
Discussion
Light at night influenced immune function in male Nile grass rats. Rats exposed
to dLAN elevated bacteriacidal capacity, and humoral and cell-mediated immune
responses. Increased immune activity occurred independently of overt changes in
circadian locomotor activity. dLAN grass rats increased plasma corticosterone
concentrations during the active phase after three weeks in lighting conditions which may
have affected immunological measures. These results contrast with previously reported
results in nocturnal rodents undergoing similar experimental nighttime light exposure.
The results suggest that male and female, as well as diurnal and nocturnal, rodents may
respond differently to the effects of nighttime light exposure.
Rats exposed to dLAN increased pinna swelling compared to LD rats in response
to the antigen DNFB. DTH is a measure of cell-mediated immunity that demonstrates
primary somatic immune response to an invading pathogen. Pinna swelling is caused by
increased infiltration of macrophages and lymphocytes into the epidermis and dermis
(Vadas, Miller, Gamble, & Whitelaw, 1975) and has previously been positively
correlated to the intensity of the immune reaction (Phanuphak, Moorhead, & Claman,
1974). Functionally, elevated swelling in DTH testing is indicative of increased
resistance to viruses, bacteria, and fungi (Bilbo et al., 2002).
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Increased pinna swelling in dLAN grass rats contrasts with previously reported
results in which swelling was suppressed in Siberian hamsters exposed to light at night
(Bedrosian, Fonken, Walton, & Nelson, 2011a). DTH responses may vary over the
course of the day. In the previous study, Siberian hamsters underwent DTH testing during
the light phase when they are generally inactive. In the present study DTH testing also
occurred during the light phase, however, grass rats are diurnal and active at this time.
Other factors that vary in a circadian pattern such as immune cells and hormones may
contribute to the equivocal t-cell mediated results (Bollinger, Bollinger, Naujoks, Lange,
& Solbach, 2010). For example, exposure to dLAN elevates glucocorticoid
concentrations in grass rats but not Siberian hamsters (Bedrosian, Fonken, Walton, Haim,
& Nelson, 2011a). Furthermore, glucocorticoid concentration can alter diurnal rhythms in
T-cell mediated inflammatory responses, an effect which may be partially mediated by
melatonin. Adrenalectomy abolishes the diurnal rhythm in BCG inflammation; however,
the rhythm can be recovered with exogenous administration of melatonin (Lopes,
Mariano, & Markus, 2001). In the previous study in Siberian hamsters (6) DTH was also
assessed in female Siberian hamsters as compared to male grass rats in the current
experiments. Although female Siberian hamsters were ovariectomized, varying levels of
sex steroids may have contributed to divergent results (Kanda & Watanabe, 2005).
Overall, assessing DTH responses during the active phase in this study is more
ecologically relevant because it is more likely that grass rats would encounter a pathogen
while awake and interacting with the external environment.
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Exposure to light at night suppresses melatonin production in both rodents and
humans (Brainard et al., 1985; Brainard, Richardson, Petterborg, & Reiter, 1982; Dauchy
et al., 2010). Even very low levels of light exposure can alter melatonin concentrations in
rodents (Evans, Elliott, & Gorman, 2007). Although I did not measure melatonin
concentrations in this study, it is likely that they were decreased with exposure to light at
night. It is unlikely, however, that changes in DTH response reflect suppression of
melatonin among dLAN rats. Melatonin is positively associated with DTH responses in
diurnal and nocturnal rodent species (Drazen & Nelson, 2001; Haldar & Singh, 2001).
Glucocorticoids both increase and suppress DTH responses depending on the type
and duration of the stressor (Dhabhar, 2002; Dhabhar & McEwen, 1999). Typically,
acute stress increases DTH, whereas chronic stress suppresses DTH reactions, indicating
that changes in DTH are in some cases related to altered glucocorticoid concentrations
(Dhabhar & McEwen, 1999). During acute stress, blood leukocytes redistribute to the
skin, mucosal linings, lung, liver, and lymph nodes, key areas in preventing breaching of
immune defenses. In this study the positive association between corticosterone
concentrations and pinna swelling suggests that the two may be related. It is possible that
a long-term stressor such as light at night induces a state of functional glucocorticoid
resistance. Previous work has demonstrated that psychosocial stressors can cause splenic
macrophages to become resistant to the suppressive effects of glucocorticoid hormones
(Avitsur, Stark, Dhabhar, Padgett, & Sheridan, 2002; Avitsur, Stark, & Sheridan, 2001;
M. T. Bailey, Avitsur, Engler, Padgett, & Sheridan, 2004). Alternatively, the elevation in
glucocorticoids among dLAN rats may be sufficiently low to exert an atypical effect on
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DTH swelling. Glucocorticoids exert a U-shaped influence on multiple factors; for
example, basal or low stress levels of corticosterone enhance glucose utilization,
hippocampal synaptic excitability, hippocampal-dependent learning, and cerebral
perfusion rate whereas higher physiological levels of corticosterone exert opposite effects
(Sapolsky, 2004). Moreover, melatonin and glucocorticoids interact in modulating
immunological processes. Acute and chronic stress increase plasma melatonin
concentrations in rodents (Couto-Moraes, Palermo-Neto, & Markus, 2009; Dagnino-
Subiabre et al., 2006). This may be a compensatory mechanism as melatonin protects
against some effects of chronic stress (Brotto, Gorzalka, & LaMarre, 2001). This
interaction has important implications for this study because it suggests that
glucocorticoids may increase melatonin concentrations partially compensating for the
light induced suppression in melatonin.
Rats exposed to dLAN enhanced antibody production following injection with
KLH. Anti-KLH production is a general indicator of B cell activity. Previous studies
have reported no differences in anti-KLH production or enhanced production in
melatonin treated rodents (Demas, Chefer, Talan, & Nelson, 1997; Drazen & Nelson,
2001). Furthermore, primary and secondary antibody production is decreased in mice
treated with propranolol (Maestroni, Conti, & Pierpaoli, 1986). Thus, differences in
antibody production between dLAN and LD rats may be independent of putative changes
in melatonin. Elevated concentrations of glucocorticoids following social defeat are
associated with enhanced lymphocyte release of IFNγ and IL6. However, changes in anti-
KLH production are not apparent (Merlot, Moze, Dantzer, & Neveu, 2004). Furthermore,
155
in another model of social defeat elevated glucocorticoid concentrations were associated
with impairment in antiviral immunological memory (de Groot, Boersma, Scholten, &
Koolhaas, 2002). Again this indicates that changes in anti-KLH production may occur
independently of changes in corticosteroids. Alternatively, light at night may be an
atypical stressor affecting the glucocorticoid system in a different manner than other
chronic stressors.
Bactericidal capacity was enhanced in dLAN rats as compared to those housed in
standard lighting conditions. Bacteria killing is a low-cost nonspecific immune response
predominately mediated by plasma proteins (L. B. Martin, 2nd, Weil, & Nelson, 2007).
Plasma bactericidal capacity increases with immune challenge and represents an
enhanced ability to clear a bacterial infection (Weinrauch, Abad, Liang, Lowry, & Weiss,
1998). Elevated glucocorticoids concentrations have been associated with enhanced
bactericidal capacity in spleen cells from mice that underwent social disruption stress (M.
T. Bailey, Engler, Powell, Padgett, & Sheridan, 2007). Melatonin, however, generally
enhances bactericidal capacity (Terron et al., 2009).
Overall, nighttime light exposure increased immunocompetence in grass rats
exposed to light at night. Light at night may exert its effects through changes in the
hypothalamic-pituitary adrenal axis as corticosteroid concentrations were elevated among
dLAN rats. It is widely accepted that stress affects immune responses, with chronic
stress generally exerting an immunosuppressive effect. The role of glucocorticoids in
immunological processes are complex however (Sorrells, Caso, Munhoz, & Sapolsky,
2009); depending on the type of stress, glucocorticoids can have opposite effects. Light at
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night may also disrupt circadian processes leading to changes in immune function.
Although gross changes in locomotor activity were not apparent, disruption of the
circadian system at the molecular level may have occurred. Previous work has indicated
disruption of clock function can lead to exacerbated immune activity (Arjona & Sarkar,
2006; Castanon-Cervantes et al., 2010; Hashiramoto et al., 2010). Melatonin can also be
directly produced by immune cells (Pontes, Cardoso, Carneiro-Sampaio, & Markus,
2006). Importantly, this study did not evaluate all aspects of immune function; it is
possible that other arms of the immune system could be differentially affected by
nighttime light exposure (L. B. Martin, 2nd, Weil, & Nelson, 2007).
Enhanced immune responses are not always favorable. Immunological processes
are energetically costly and a delegation of energy to immune responses in unnecessary
situations can reduce fitness (L. B. Martin, Weil, & Nelson, 2008). Moreover,
enhancement of the immune response in cases such as allergic asthma is detrimental
(Wills-Karp, 1999). Because of the contrasting results obtained in this study and another
study conducted in a nocturnal rodent species, further research on the effects of light at
night on immune function are warranted. Nighttime light exposure is currently
experienced by over 99% of the population of the US and Europe. Light pollution has
significant ecological consequences for animals living in urban and suburban areas and
may contribute to species loss (Navara & Nelson, 2007). It is important to understand the
physiological implications of this exposure in order to work toward preventing
ecologically related complications.
157
Tables
LD dLAN
Body mass (g) 93.02 +/- 6.47 93.55 +/- 6.66
Epididymides (mg) 447 +/- 19 474 +/- 29
Epididymal fat (mg) 2108 +/- 315 2230 +/- 370
Testes (mg) 1779 +/- 67 1713 +/- 48
Adrenal (mg) 66 +/- 8 62 +/- 6
Thymus (mg) 112 +/- 20 110 +/- 21
Spleen (mg) 142 +/- 9 148 +/- 12
Table 8.1. Tissue masses in Nile grass rats exposed to dimly lit or dark nights
158
Figures
LD dLAN0
100
200
300
400
500
600
700
*C
ort
ico
ste
ron
e
co
ncen
trati
on
(n
g/m
L)
0 1 2 3 4 5
0
20
40
60
80
100
120 LD
dLAN* *
Days after challenge
% S
we
llin
g
0 200 400 600 800 10000
50
100
150
200
r2=0.327p=0.013
Corticosterone (ng/mL)
Pin
na s
well
ing
A B
C
Figure 8.1. Nile grass rats exposed to dimly nights elevate corticosterone concentrations
and delayed-type hypersensitivity swelling responses.
Rats exposed to dim light at night (A) elevated plasma corticosterone concentrations
compared to rats with dark night. (B) Dim light rats exhibited increased pinna swelling 2
and 3 days following challenge with the antigen 2,4-dinitro-1-fluorobenzene. (C) There
was an association between peak pinna swelling and corticosterone concentrations 2 days
after challenge. Data are presented as mean ± SEM. *p ≤ 0.05.
159
0 5 10 15
0
25
50
75
100
125
LDdLAN
**
Days Post Innoculation
An
ti-K
LH
Ig
G
LD dLAN0
5
10
15
20
25
30
35
40
45
*
Bacte
rial
co
lon
ies
(% o
f p
osit
ive c
on
tro
l)
A B
Figure 8.2. Rats exposed to light at night enhance humoral immune function and plasma
bactericidal capacity.
(A) Anti-KLH IgG responses were elevated in dLAN rats 10 and 15 days following
innoculation. (B) Plasma obtained from dLAN grass rats caused fewer surviving bacterial
colonies. Data are presented as mean ± SEM. *p ≤ 0.05.
160
Figure 8.3. Grass rats exposed to dark and dimly lit nights have comparable activity.
Representative actograph of a grass rat housed in (A) dark or (B) dimly lit nights.
161
CHAPTER 9
DIM NIGHTTIME LIGHT IMPAIRS COGNITION AND PROVOKES
DEPRESSIVE-LIKE RESPONSES IN A DIURNAL RODENT
Biological rhythms are highly adaptive, aligning individuals to daily fluctuations
in the external environment, as well as synchronizing internal homeostatic processes. The
master mammalian circadian clock is located in the suprachiasmatic nuclei (SCN) and
regulates timing of subordinate oscillators throughout the central nervous system and
periphery. External lighting is important in synchronizing the circadian system and
maintaining daily temporal organization. Prior to the widespread adoption of electric
lighting, individuals‟ biological clocks were entrained to a consistent pattern of light and
dark; in contrast, modern light exists in several temporal patterns. Moreover, shift-work,
trans-meridian travel, and inconsistent sleep schedules have rapidly increased during the
past century. Because the change in nighttime lighting has occurred so rapidly in terms of
evolutionary history, it is likely that significant physiological and ecological
perturbations have resulted. For example, disruption of the circadian system results in
adverse health conditions such as heart disease (Ha & Park, 2005), cancer (Davis &
162
Mirick, 2006; Schernhammer et al., 2001), and metabolic dysfunction (Reiter, Tan,
Korkmaz, & Ma, 2011).
Circadian disruption and light at night are implicated in impaired cognition. Rats
housed in constant illumination perform poorly in the Morris water maze (A. Fujioka et
al., 2011; Ling et al., 2009; Ma et al., 2007). Constant light causes tau
hyperphosphorylation, increased expression of endoplasmic reticulum (ER) stress-related
proteins, thinner synapses, and increased superoxide dismutase and monoamine oxidase
(Ling et al., 2009). Similarly, rats housed in constant light display impaired spatial
learning in the Morris water maze with accompanying changes in long-term depression in
the CA1 area of the hippocampus (Ma et al., 2007). Constant light also impairs learning
and memory in mice, which may be related to decreased neurogenesis (A. Fujioka et al.,
2011). Furthermore, mice undergoing experimental jet lag decrease neurogenesis and
have prolonged deficits in learning and memory as evaluated in a conditioned place
preference task (Gibson, Wang, Tjho, Khattar, & Kriegsfeld, 2010).
In addition to influencing learning and memory, circadian disruption changes
mood (Monteleone, Martiadis, & Maj, 2010). Seasonal lighting, abnormalities in the
circadian clock (Benedetti et al., 2008), and sleep disorders are associated with
depression (Bunney & Bunney, 2000). Constant light alters anxiety and depressive-like
behaviors in mice (Fonken et al., 2009; Martynhak et al., 2011). Furthermore, Siberian
hamsters exposed to dim light during the dark phase increase depressive-like responses
and have reduced spine density in the CA1 area of the hippocampus (Bedrosian, Fonken,
Walton, Haim, & Nelson, 2011a).
163
In all of these studies, only nocturnal rodents were used. Both circadian influences
on behavior and masking effects of light are very different in nocturnal and diurnal
species. Thus, in the present experiment, I examined behavioral and brain responses of
diurnal male Nile grass rats to dim light at night (dLAN).
Methods
Animals
Male grass rats (Arvicanthis niloticus) used in this study were bred at The Ohio
State University from a wild stock obtained from LS. Grass rats were bred under a
standard light-dark (LD) cycle (14:10 light (~150 lux) /dark (0 lux)). All animals were
provided food (ProLab RMH 2000, LabDiet) and filtered tap water ad libitum.
Experimental grass rats were weaned between 21 and 24 days of age and housed with
same sex siblings in polypropylene cages (40 cm x 20 cm x 20 cm) with straw bedding.
Colony rooms were maintained at a temperature of 20 ± 4º C and a relative humidity of
50% ± 10%.
At 10 weeks of age grass rats were singly housed, randomly assigned a number,
and either maintained in LD or placed in dLAN (14:10 light (~150 lux)/ dim (~5 lux)).
Blood samples were collected at Zeitgeber Time (ZT) 6 via retro-orbital bleed after two
weeks for corticosterone analysis and one week later grass rats underwent behavioral
testing to assess cognitive and affective behaviors. Testing occurred in the following
order: Barnes maze, sucrose anhedonia, and forced swim test. The sucrose anhedonia test
occurred between ZT 8-13; all other tests were conducted between ZT 1-ZT 6.
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Retro orbital blood samples (~0.20 ml) were collected from grass rats
anesthetized with isoflurane vapors for RIA of corticosterone concentrations, prior to the
onset of behavioral testing. Blood samples were centrifuged at 4°C for 30 min at 3.3 g
and plasma aliquots were aspirated and stored in sealable polypropylene microcentrifuge
tubes at -80°C until assayed for corticosterone concentrations using a radioimmunoassay
(RIA). Total plasma corticosterone concentrations for grass rats were determined in
duplicate in an assay using an ICN Diagnostics 125
I double antibody kit (Costa Mesa, CA,
USA). The high and low limits of detectability of the assay were ~1000 and 5 ng/ml,
respectively. All procedures followed those described by the manufacturer guidelines.
Behavioral testing
Barnes maze. The Barnes maze is a brightly lit arena with 18 evenly spaced
holes, one leading to dark box and the others blocked off with black inserts (Sunyer,
2007). On the first day animals were acclimated to the maze; a bright light and loud fan
were turned on as they were guided from the center of the maze to the target hole. After
entering, the bright light and fan were turned off and the grass rat were left undisturbed
for 30 sec. Animals then underwent four days of training consisting of 3, 90 sec trials
separated by 10 min intervals in the home cage. One day after the last training trial
animals were given a 60 sec probe trial in which the escape box was blocked off. Latency
to find the target hole and number of errors were scored during all trials. Sucrose
Anhedonia. Consumption of a 2% sucrose solution between ZT 8 and ZT 13, was
recorded in all grass rats to measure sucrose anhedonia (Willner, Muscat, & Papp, 1992).
Before presentation of the sucrose solution, grass rats were administered water in
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modified water bottles for three consecutive days, to control for novelty of the bottles.
The bottles were weighed before and after the 5 h sample time; the next day animals were
provided a choice between a 2% sucrose solution and water. Sucrose consumption was
normalized to water consumption. Forced Swim Test. To assess depressive-like
responses, grass rats were placed in ~17 cm water (22 ±1°C), within an opaque,
cylindrical tank (diameter = 24 cm, height = 53 cm). Swimming behavior was videotaped
for 5 min and scored by a condition-blind observer with the Observer software (Noldus
Corp, Leesburg, VA, USA). Latency to float and time spent floating served as dependent
measures; both are used in rodents, including grass rats, to assess depressive-like
response (Ashkenazy-Frolinger, Kronfeld-Schor, Juetten, & Einat, 2010; Porsolt, Bertin,
& Jalfre, 1977).
Hippocampal Morphology
Grass rats were killed between ZT 3 and ZT 5. and brains were removed, and
processed for Golgi impregnation using the FD Rapid GolgiStain™ Kit (FD
NeuroTechnologies Inc., Ellicott City, MD) according to the manufacturer„s instructions.
Brains were sliced at 100μm, thaw mounted onto gelatin coated slides counterstained
with cresyl violet (Sigma), dehydrated, and coverslipped. Brains were assessed for
hippocampal cell morphology and spine density in the dentate gyrus (DG), CA1, and
CA3 using a Nikon E800 brightfield microscope. Tracings were done with Neurolucida
software (MicroBrightField, Burlington, VT, USA) at a magnification of 200× for
neuronal morphology and 1000× for spine density. Six representative neurons were
selected per area, per animal. Whole cell traces were analyzed using NeuroExplorer
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software, for cell body size and perimeter, and dendritic length (MicroBrightField,
Burlington, VT). Sholl analysis defines dendritic complexity by the number of dendritic
branch points at fixed intervals from the cell bodies (Sholl, 1956) and was conducted on
apical and basilar dendrites. From each neuron >20 µm were selected in the apical and
basilar areas respectively (except in the DG where granule cells lack bidirectional
projections). All spine segments selected were at least 50 µm distal to the cell body.
Spine density (spines per 1 μm) was calculated for each trace and averaged per cell, per
area, and per animal.
Statistical Analyses
Comparisons for behavior analyses and hormone concentrations were conducted
using a one-way ANOVA. Neuronal characteristics and spine densities were averaged
per animal and then analyzed using a one-way ANOVA. Sholl analyses were also
averaged per animal and then analyzed using a repeated measures ANOVA with lighting
condition as the between subject factor and distance from the cell body as the with-in
subject factor. For each Barnes maze session (1–4) latencies and error rates, respectively,
were averaged per session for each grass rat; data were subject to repeated-measures
ANOVA (lighting condition as the between subject factor and session as the with-in
subject factor). Fourier analysis was used to determine whether locomotor activity was
rhythmic and followed 24 h periodicity using Clocklab software from Actimetrics
(Wilmette, IL). Grass rats were considered rhythmic when the highest peak occurred at
~1 cycle per day with an absolute power of at least 0.005 mV/Hz as previously described
(Kriegsfeld et al., 2008). FFT power values for 0.083 cycles per day were compared
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between lighting conditions by one way ANOVA. Percentage of daytime activity and
total daily activity were also analyzed by one way ANOVA. The above statistical
analyses were conducted with StatView software (v. 5.0.1, Cary, NC). Nonlinear
regression analysis was used in GraphPad Prism software (v. 4 La Jolla, CA). In all
cases, differences between group means were considered statistically significant if p ≤
0.05.
Results
Somatic Measures
There were no differences in body or reproductive tissue mass (p > 0.05; data not
shown).
Learning and Memory
Grass rats exposed to dLAN decreased learning abilities in the Barnes maze.
dLAN grass rats had an increased latency to reach the target hole and a higher error rate
as compared to grass rats housed under dark nights. There was a main effect of lighting
condition, such that dLAN increased latency to reach the target hole over the course of
training trials (F1,42 = 6.064, p < 0.05; Fig. 1A). Post-hoc analysis revealed dLAN
increased latency to reach the target hole on days 2 and 4 of the training trials (p < 0.05).
Furthermore, there was a main effect of lighting condition with respect to error rate; grass
rats housed under dLAN increased errors over the course of training trials (F1,42 = 8.184,
p < 0.05; Fig. 1B). On day two of the training trials dLAN grass rats showed increased
error rate compared to grass rats housed under standard LD conditions (p < 0.05).
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Twenty-four hours after the final training session, memory retention was assessed
with a probe trial. During the probe trial the target box was removed and behavior on the
maze was recorded for 60 sec. dLAN grass rats spent a lower percentage of time
investigating the target hole compared to LD grass rats; these data indicate decreased
memory retention (F1,14 = 7.084, p < 0.05; Fig. 1C). Our lab has previously found no
differences in spontaneous locomotor activity between grass rats housed under dLAN and
LD in a 5 min brightly lit open field task (unpublished observations). This indicates
Barnes maze differences are due to changes in learning and memory and not differences
in motivation when exposed to a brightly lit open space.
Affective Responses
Depressive-like responses were evaluated using a sucrose anhedonia and forced
swim task. Grass rats exposed to dLAN increased depressive-like responses in the
sucrose anhedonia test. One grass rat was excluded from analyses because of a leaky
water bottle. dLAN grass rats reduced consumption of a sucrose solution demonstrating
an anhedonic-like response (F1,15 = 4.711, p < 0.05; Fig. 2A).
Grass rats exposed to dLAN also increased behavioral despair in the forced swim
task. dLAN grass rats reduced latency to first float indicating they more rapidly reach a
state of behavioral despair (F1,16 = 4.774; p<0.05; Fig. 2B). No differences, however,
were observed between groups with respect to float duration which is the primary
depressive-like response evaluated in the forced swim test (p > 0.10).
Corticosterone Concentrations
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Grass rats displayed elevated corticosterone concentrations 2 weeks after
placement in dLAN compared to LD (F1,16 = 4.521, p < 0.05; Fig. 2D).
Hippocampal Neuronal Morphology
Exposure to dLAN is associated with changes in neuronal morphology in the CA1
and DG regions of the hippocampus. Rats housed under dLAN reduced dendritic length
in the DG and CA1 basilar dendrites (F1,11 = 4.875, 7.357 respectively, p < 0.05; Fig 3).
Furthermore, there was a positive association between dendritic length in the dentate
gyrus and sucrose consumption in the sucrose anhedonia test (r = 0.455, p = .016; Fig,
3C). Groups did not differ with respect to spine density, cell body area, or cell body
perimeter in any area (Table 1).
Discussion
This study investigated the effect of dim nighttime light exposure on depressive-
like responses and learning and memory in Nile grass rats, a diurnal rodent. Here I show
that exposing grass rats to light at night impaired their spatial learning and memory as
evaluated by the Barnes maze (Sunyer, 2007). Animals were trained to find a target hole
on the maze over the course of 4 days and then evaluated in a probe trial. During the
training trials, dLAN impaired performance as compared to LD. dLAN increased the
latency for grass rats to reach the target hole and increased the number of visits to
incorrect holes. Spatial memory was similarly impaired by dLAN. Twenty-four hours
after the final training session, memory retention was assessed with a probe trial. dLAN
decreased the percentage of time spent investigating the target hole, indicating decreased
memory retention.
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These results confirm and extend previous findings (A. Fujioka et al., 2011; Ling
et al., 2009; Ma et al., 2007) indicating that housing nocturnal rodents under light at night
impairs spatial learning and memory. The results demonstrate that nighttime light
exposure also impairs spatial learning and memory in diurnal rodents. Furthermore,
previous studies have used 24 h lighting of the same intensity while in this study grass
rats were exposed to a distinctly darker phase. Grass rats exsposed to dark or dimly lit
nights display maintain a diurnal activity pattern and have equivalent levels of total daily
locomotor activity and similar locomotor activity rhythms (Fonken, Haim, & Nelson,
2011; McElhinny, Smale, & Holekamp, 1997). Constant lighting conditions used in
previous studies can result in an arrhythmic activity rhythm (Cambras, Castejon, & Diez-
Noguera, 2011). These results demonstrate that cognitive impairments occur in animals
with light at night in the absence of disruption in locomotor activity rhythm.
The effects of light at night on other cognitive functions remain unspecified
(Castro et al., 2005). It is possible that nighttime light exposure specifically targets
hippocampal dependent learning and memory through disruption of circadian processes
(Ruby et al., 2008). Alternatively, dLAN may represent a mild chronic stressor producing
deficits in learning and memory via reduced neurogenesis, changes in hippocampal
architecture, or both processes (A. Fujioka et al., 2011; Gould & Gross, 2002; McEwen
& Sapolsky, 1995). Studies in nocturnal rodents have reported glucocorticoid
concentrations to be both elevated or unaffected by nighttime light exposure (Abilio,
Freitas, Dolnikoff, Castrucci, & Frussa-Filho, 1999; Fonken et al., 2009; Fonken et al.,
2010; Van der Meer, Van Loo, & Baumans, 2004). Grass rats housed under dLAN
171
elevated plasma corticosterone concentrations. dLAN may be a stronger stressor to
diurnal as compared to nocturnal rodents. Circulating glucocorticoid concentrations are
predictive of hippocampal atrophy and memory deficits in both humans and rodents
(Bodnoff et al., 1995; Lupien et al., 1998). Because corticosterone concentrations were
only measured at a single time point however, conclusions drawn from the results must
be constrained.
Grass rats exposed to dLAN increased depressive-like responses in a sucrose
preference test. dLAN reduced consumption of a sucrose solution in the sucrose
anhedonia test. LD rats consumed a higher percentage of sucrose than water, whereas
dLAN grass rats showed no preference for the sucrose solution. This implies that the
sucrose solution had diminished hedonic valence for grass rats exposed to dLAN which
models a key feature of human depression (Willner, Muscat, & Papp, 1992). Results in
the forced swim test were equivocal. Increased floating time in the forced swim test is
considered “behavioral despair” because rodents putatively stop searching for an escape
mechanism (Porsolt, Bertin, & Jalfre, 1977). There were no differences in total floating
time in the forced swim test between LD and dLAN grass rats, but grass rat housed under
dLAN reduced latency to first float. The forced swim test has not been extensively used
in grass rats, although one study reported increases in floating duration in grass rats
housed in short photoperiods (Ashkenazy-Frolinger, Kronfeld-Schor, Juetten, & Einat,
2010). Grass rats are poor swimmers, which suggests the forced swim test may not be a
reliable behavioral measure (Duplantier & Ba, 2001).
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The depressive-like phenotype of the dLAN grass rats is consistent with my
predictions based on depressive disorders related to both stress (Willner, 1997) and
circadian dysfunction (Turek, 2007). Furthermore, nighttime light exposure increases
depressive-like responses in nocturnal rodents (Bedrosian, Fonken, Walton, Haim, &
Nelson, 2011b). Light at night may increase depressive-like responses through changes in
hippocampal circuitry. dLAN decreased dendritic length in DG and CA1 basilar
dendrites. Furthermore, there was a positive association between dendritic length in the
dentate gyrus and sucrose consumption in the sucrose anhedonia test. The hippocampus
is a critical structure in the pathophysiology of depressive disorders. Depression is
associated with changes in glucocorticoids and hippocampal atrophy (Sapolsky, 2000;
Sheline, Wang, Gado, Csernansky, & Vannier, 1996). Moreover, changes in hippocampal
morphology are associated with chronic stress and depressive-like responses in rodents
(Hajszan et al., 2009; Magarinos et al., 2011; Magarinos, McEwen, Flugge, & Fuchs,
1996).
In summary, these results suggest that exposure to dim nighttime lighting can
alter hippocampal neuronal morphology, impair learning and memory, and increase
depressive-like responses in a diurnal rodent. Opportunities for exposure to light at night
have rapidly increased during the past century. The present results suggest that this
exposure may have accompanying maladaptive effects. Finding an appropriate model to
test whether changes in environmental lighting are related to mood disorders is critical.
Many animal models are potentially confounded by the use of nocturnal rodents that may
not experience the same form of disruption as diurnal animals when exposed to light at
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night. The responses to light at night seen in the present study are comparable to those
described in previous reports using nocturnal rodents (e.g., Bedrosian et al., 2011a),
which increases confidence that nocturnal rodents are appropriate subjects of study of this
issue. In addition, these results raise questions about the use of rodent vivaria that have
windows in the doors of animal rooms and continuous lighting in the halls.
174
Tables
Table 9.1. Characteristics of hippocampal neurons in grass rats exposed to dark or dimly
lit nights.
Characteristics of neurons in the CA1, CA3, and DG of the hippocampus of grass rats
exposed to dark or dimly lit nights. Represented as mean ± SEM micrometers; AD =
apical dendrite; BD = basilar dendrite.
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Figures
1 2 3 40
25
50
75
100LD
dLAN
*
*
Days
La
ten
cy
(s
ec)
1 2 3 40
5
10
15
20
25
*
Days
# E
rro
rs
LD dLAN0
5
10
15
20
25
30
35
*
% v
isit
s t
o c
orr
ec
t h
ole
A B
C
Figure 9.1. Grass rats exposed to dim light at night show impairments in learning and
memory.
Dim light at night impaired spatial learning and memory in the Barnes maze. (A) Latency
to reach the target hole in the Barnes maze by day (average of 3 trials). (B) Number of
visits to false holes by session. (C) Relative visits to the target hole versus false holes
during the probe trial.
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500 650 800 950 1100 1250 14000
20
40
60
80
100
R=0.45p=0.02
Dendritic length
% S
ucro
se c
on
su
med
LD dLAN0
25
50
75
100
*%
Su
cro
se c
on
su
med
LD dLAN0
10
20
30
40
50
60
*
Late
ncy t
o f
loat
(sec)
A B
C
LD dLAN0
100
200
300
400
500
600*
Co
rtic
oste
ron
e
co
ncen
trati
on
(n
g/m
L)
D
Figure 9.2. Exposure to dim light at night increases depressive-like responses in grass
rats.
(A) Amount of sucrose solution versus total liquid consumed in a sucrose anhedonia task.
(B) Latency to first float the forced swim test. (C) Correlation between percentage of
sucrose consumed and dendritic length in the dentate gyrus of the hippocampus. (D)
Corticosterone concentrations after two weeks in lighting conditions. Data are expressed
as mean ± standard error of the mean (SEM). *p<0.05 between groups.
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Figure 9.3. Exposure to dim light at night alters hippocampal morphology in grass rats.
(A) Total dendritic length was reduced in CA1 basilar dendrites and (B) in the dentate
gyrus (DG). (C) Representative tracing from the CA1 of an LD grass rat (black)
compared to a dLAN grass rat (red). (D) Representative tracing from the DG of an LD
grass rat (black) and dLAN grass rat (red). Data are expressed as mean ± SEM. *p<0.05
between groups.
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CONCLUSIONS
Exposure to light at night is generally considered an innocuous environmental
manipulation. The perceived harmlessness of nocturnal illumination likely persists
because the invention and widespread adoption of the electric lighting occurred prior to
an understanding of circadian biology. The goal of this dissertation was to determine the
physiological consequence of exposing nocturnal (Swiss Webster mice) and diurnal (Nile
grass rats) rodents to ecologically relevant levels of dim (~5 lux) light at night. In this
dissertation, I demonstrate that exposure to light at night has significant metabolic,
immunological, and behavioral repercussions.
Summary
The global increase in the prevalence of obesity and metabolic disorders coincides
with the increase of exposure to light at night and shift work. Circadian regulation of
energy homeostasis is controlled by an endogenous biological clock that is synchronized
by light information (Reppert & Weaver, 2002). To promote optimal adaptive
functioning, the circadian clock prepares individuals for predictable events such as food
availability and sleep, and disruption of clock function causes circadian and metabolic
disturbances (Green, Takahashi, & Bass, 2008). To determine whether a causal
relationship exists between nighttime light exposure and obesity I examined the effects of
exposure to light at night on body mass in male mice (Chapter 2). Mice exposed to dim
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light at night or continuous lighting increase body mass and impair glucose processing as
compared to mice exposed to dark nights. Changes in body mass occur independently of
changes in total daily food intake or activity. However, mice attenuate the daily pattern in
food intake, eating more during the rest phase than mice exposed to dark nights. Blocking
daytime food intake in mice with light at night prevents weight gain. Furthermore,
placing mice back in dark nights following exposure to 4 weeks of dim light at night
prevents changes in glucose tolerance and partially restores body mass (Chapter 3).
In industrialized societies, exposure to light at night and more typical obesogenic
factors such as a high fat diet and sedentary lifestyle, often occur in tandem and may
contribute to the increasing obesity epidemic. Thus, I examined the effects of a high fat
diet and exercise availability on dim light at night associated weight gain in Chapters 4
and 5, respectively. Dim light at night exaggerates weight gain in mice fed a high fat diet
(Chapter 4). Moreover, both high fat feeding and dim light at night increase daytime
food intake and elevate peripheral inflammation. Exposure to a high fat diet but not dim
light at night elevates hypothalamic inflammation suggesting that these two factors may
work through different physiological mechanisms to affect weight regulation. As
anticipated, access to a functional running wheel prevents body mass gain in mice
exposed to dim light at night (Chapter 5). Voluntary exercise suppresses weight gain in
mice exposed to dimly lit nights without rescuing changes to the circadian system;
increases in daytime food intake induced by exposure to dim light at night are not
diminished by exercise availability. Furthermore, exposure to light at night disrupts
wheel running behavior in a subset of mice exposed to dim light at night.
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Because changes in circadian clock mechanisms affect metabolism (Kornmann,
Schaad, Bujard, Takahashi, & Schibler, 2007; Lamia, Storch, & Weitz, 2008; Marcheva
et al., 2010; Oishi et al., 2006; Paschos et al., 2012; Turek et al., 2005) and exposure to
light at night affects circadian rhythms (Albrecht, Sun, Eichele, & Lee, 1997; Schwartz,
Tavakoli-Nezhad, Lambert, Weaver, & de la Iglesia, 2012; Shigeyoshi et al., 1997), in
Chapter 6, I investigated the effects of exposure to light at night on both central and
peripheral core circadian clock mechanisms. Mice exposed to dim light at night attenuate
core circadian clock rhythms in the SCN at both the gene and protein levels. Circadian
clock rhythms are also perturbed in the liver of mice exposed to dimly lit as compared to
dark nights.
In addition to affecting metabolism, circadian system disruptions are linked to
alterations in immune function. For example, many of the pathologies associated with
exposure to light at night such as cancer (Stevens, 2009b), obesity (X. S. Wang,
Armstrong, Cairns, Key, & Travis, 2011), and mood disorders (Driesen, Jansen, Kant,
Mohren, & van Amelsvoort, 2010) involve changes in inflammation. Moreover, multiple
immune related parameters show circadian oscillations (Lange, Dimitrov, & Born, 2010)
(Arjona & Sarkar, 2006; Narasimamurthy et al., 2012; A. C. Silver, Arjona, Walker, &
Fikrig, 2012) (Arjona & Sarkar, 2005; Keller et al., 2009; A. C. Silver, Arjona, Hughes,
Nitabach, & Fikrig, 2012). Therefore, Chapter 7 of this dissertation addressed the effects
of exposure to light at night on recovery from cardiac arrest in mice. Following either a
cardiac arrest or a sham procedure, mice were exposed to dark or dimly lit nights. Mice
exposed to dimly illuminated as compared to dark nights elevate mortality in the week
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following cardiac arrest. Furthermore, mice exposed to dim light at night post-cardiac
arrest increase neuroinflammation and hippocampal cell death. Dim light at night likely
affects cardiac arrest recovery by elevating inflammation; selective inhibition of IL-1β or
TNFα ameliorates the effects of dim light at night on cardiac arrest recovery.
Additionally, restricting the wavelength of the nighttime light exposure to ~640 nm
eliminates the detrimental effects of nighttime light exposure on cardiac arrest outcome.
The experiments described in the first 7 chapters of this dissertation were
conducted using nocturnal rodents in order to examine the effects of nighttime light
exposure without disrupting sleep. However, in diurnal species many hormones and
immune parameters vary with secretion patterns 180º out of phase to those of nocturnal
rodents. Furthermore, light can have very different effects on activity and masking in
diurnal versus nocturnal rodents. Thus, in the final two chapters of this dissertation
(Chapters 8 and 9) I investigated the effects of nighttime light on behavior, hippocampal
connectivity, and immune related parameters, in grass rats. Rats exposed to dim light at
night increase delayed-type hypersensitivity pinna swelling which is consistent with
enhanced cell-mediated immune function. Similarly, rats exposed to dimly lit as
compared to dark nights increase antibody production following inoculation with keyhole
lymphocyte hemocyanin (KLH) and increase bactericidal capacity. In contrast to
nocturnal rodents, daytime corticosterone concentrations are elevated in grass rats
exposed to nighttime lighting.
In addition to influencing immune function, three behavioral effects are apparent
in grass rats exposed to dim light at night: (1) decreased preference for a sucrose solution,
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(2) increased latency to float in a forced swim test, and (3) impaired learning and memory
in the Barnes maze. Light at night also reduces dendritic length in dentate gyrus and
basilar CA1 dendrites. In agreement with findings in nocturnal rodents (Fonken et al.,
2010), nighttime light exposure does not disrupt the pattern of circadian locomotor
activity in grass rats.
Mechanisms
There are several mechanisms by which nighttime light exposure can affect
physiology. In this dissertation, I specifically focused on how light at night may influence
metabolism through disruption of the circadian system. Exposure to unnatural light at
night can also affect physiological processes through melatonin suppression, alterations
in glucocorticoids, and changes in sleep architecture.
Melatonin is an endogenously synthesized molecule that is secreted by the pineal
gland during the night in both nocturnal and diurnal mammals (Reiter, 1991). Melatonin
secretion is potently inhibited by exposure to sufficient levels and durations of nighttime
lighting in both rodents and humans (Brainard, Rollag, & Hanifin, 1997). For example,
exposing humans to one hour of 45 lux of nighttime light exposure decreases plasma
melatonin by ~60% (Brainard, Richardson, Petterborg, & Reiter, 1982). Similar to
circadian clock gene disruption, suppressing melatonin secretion is associated with
increased risk for developing cancer (Blask, 2009; Blask et al., 2005), obesity (Mantele et
al., 2012; Tan, Manchester, Fuentes-Broto, Paredes, & Reiter, 2011), and mood disorders
(Srinivasan, De Berardis, Shillcutt, & Brzezinski, 2012). Although there is compelling
evidence that suppression of melatonin secretion can contribute to weight gain, I
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specifically did not focus on melatonin for several reasons: (1) pineal melatonin
suppression requires high and sustained levels of nighttime light exposure (Brainard,
Rollag, & Hanifin, 1997), (2) nighttime light exposure below the threshold for melatonin
suppression is associated with changes in metabolism (Obayashi et al., 2013), and (3)
multiple strains of laboratory mice that lack pineal melatonin demonstrate changes in
metabolism with nighttime light exposure (Coomans et al., 2013; Fonken et al., 2010).
Diurnal variations in other hormones may be disrupted by exposure to light at
night. Glucocorticoids are of particular interest in the context of nighttime light exposure
because (1) light at night may be interpreted as a stressor (Ma et al., 2007) and (2)
glucocorticoids are a primary output of, and feedback signal for the circadian system
(Kiessling, Eichele, & Oster, 2010; Sage et al., 2004). Importantly, I did not focus on
glucocorticoids as a primary mechanism for physiological changes associated with
nighttime light exposure because exposure to light at night appears to affect
glucocorticoid secretion in only a subset of mammals. For example, Nile grass rats show
elevations in serum corticosterone concentrations after chronic exposure to dim light at
night, but mice do not (Fonken, Haim, & Nelson, 2011; Fonken et al., 2010). Despite
disparate effects of light at night on glucocorticoids, Swiss Webster mice and Nile grass
rats show similar changes in physiology and behavior following exposure to light at night
(Fonken et al., 2009; Fonken, Kitsmiller, Smale, & Nelson, 2012; Fonken & Nelson,
2013). This suggests that alterations in glucocorticoids are not critical for dim light at
night-associated changes.
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Finally, exposure to light at night may affect metabolism through disturbing sleep
architecture. Sleep disruptions can profoundly affect physiology and contribute to
multiple pathological conditions including metabolic syndrome (Mullington, Haack,
Toth, Serrador, & Meier-Ewert, 2009; Spiegel, Tasali, Leproult, & Van Cauter, 2009). In
order to dissociated the effects of nighttime light exposure from sleep disruptions I
specifically worked with nocturnal Swiss Webster mice in the majority of the studies in
this dissertation. These studies indicate that light at night causes changes in metabolism
independently of sleep disruptions. However, due to the synergistic effects of light at
night and disrupted sleep on metabolism, future research should address whether these
variables act through similar mechanisms to affect metabolism.
Overall, it is difficult to tease apart which mechanism is the greatest contributing
force to the negative effects of nighttime light exposure. Melatonin suppression, circadian
disruption, changes in the HPA axis, and sleep disturbances likely all contribute to the
deleterious outcomes associated with exposure to light at night.
Implications
Over 99% of the population in the US and Europe is exposed to light at night
(Cinzano, Falchi, & Elvidge, 2001). In addition to experiencing urban light pollution,
many people bring light into their homes by turning on electric lights after sunset,
watching TV late into the night, or using computers directly prior to bed. It is estimated
that two-thirds of the population experience this form of “social jet lag” (Roenneberg,
Allebrandt, Merrow, & Vetter, 2012). Moreover, shift workers make up approximately
20% of the populations and are exposed to high and prolonged levels of light at night.
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It is also important to note that exposure to light at night is not just a human issue.
Many plant and animal species are affected by nighttime light exposure, as lighting from
infrastructure strays into the atmosphere creating a general nighttime glow termed “light
pollution” (Navara & Nelson, 2007). The results presented in this dissertation suggest
that unnatural exposure to light at night may have significant ecological implications.
Indeed, exposure to light at night is known to affect mating (Dominoni, Quetting, &
Partecke, 2013; Kempenaers, Borgstrom, Loes, Schlicht, & Valcu, 2010), foraging and
predation (Davies, Bennie, & Gaston, 2012; Dwyer, Bearhop, Campbell, & Bryant, 2012;
Rydell, 1992; Stone, Jones, & Harris, 2009), and migration in multiple species (Z. Wang
et al., 2011).
Prevention and Interventions
Preventing the general population from excessive exposure to light at night can be
achieved with relatively low-cost manipulations, such as using curtains to block out street
lights, turning off hallway lights, and removing all light sources, including televisions
and computers, from bedrooms. Furthermore, adhering to a consistent schedule and
avoiding rapid phase shifts can minimizing “social jet lag” (Roenneberg, Allebrandt,
Merrow, & Vetter, 2012).
In shift-working populations, avoiding phase shifts and nighttime light exposure
is often unavoidable. However, not all nocturnal illumination equally affects the circadian
system. The intrinsically photosensitive retinal ganglion cells that project to the SCN are
most responsive to the blue region of the visible spectrum (ranging from 450 to 485 nm)
with longer wavelengths of lighting minimally influencing the circadian system (Brainard
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et al., 1985; Brainard, Richardson, Petterborg, & Reiter, 1982). Manipulation of lighting
wavelength may prove effective in blocking out light-induced physiological changes. To
that end, ongoing research is investigating the effectiveness of preventing exposure to
blue wavelength light with specially designed goggles and light fixtures.
Future Directions
Future studies should confirm the importance of the circadian system in mediating
light at night-associated physiological changes. This could be accomplished by several
means including (1) examining the effects of exposure to red light at night, (2) using a
mouse strain lacking ipRGCs such as Opn4aDTA/aDTA
mice (LeGates et al., 2012), or (3) by
ablating ipRGCs with saporin conjugated to a melanopsin polyclonal antibody (Ingham,
Gunhan, Fuller, & Fuller, 2009). Additionally, these studies should particularly focus on
potential interventions to limit deleterious changes associated with exposure to light at
night.
Because the research presented in this dissertation may have important
implications for human health, future studies should directly investigate the effects of
exposure to light at night on humans. First, conducting comparative work in the Amish,
who are minimally exposed to light at night, may provide insight into some of the
unintended consequences of exposure to light at night. For example, Amish have reduced
risk compared to the general population for developing breast cancer and metabolic
syndrome, two conditions associated with exposure to light at night (Fonken & Nelson,
2011). Second, the effects of nighttime light exposure on patient recovery should be
evaluated. This could be achieved by introducing altered light fixtures into hospital and
187
retroactively monitoring variables such as length of patients stay. Finally, the effects of
dim light at night on human physiology should be investigated in a controlled laboratory
setting. Exposing people to a single night, or week, of dim light at night and monitoring
various circadian and metabolic outputs may highlight the mechanism by which exposure
to electril light at night influences human health
188
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