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The Future of Metabolic Phenotyping: Using data bandwidth to maximize N, analytical flexibility and reproducibility
Sponsored by:
John Lighton, PhDSable Systems International
Andy HentonInsideScientific
Jennifer A. Teske, PhDUniversity of Arizona
InsideScientific is an online educational environment designed for life science researchers. Our goal is to aid in
the sharing and distribution of scientific information regarding innovative technologies, protocols, research
tools and laboratory services.
The Future of Metabolic Phenotyping: Using data bandwidth to maximize N, analytical flexibility and reproducibility
John Lighton, PhD
President & Chief Scientist, Sable Systems International
Copyright 2015 InsideScientific & Sable Systems International. All Rights Reserved.
Some history…
• I’m a comparative physiologist
• Ph.D. 1987, UCLA under George Bartholomew
• Respiratory physiology & energetics
• Attracted to extreme technical challenges
• > 80 papers using diverse metabolic measurement methods
• Founded Sable Systems International in 1987
• “By Scientists, For Scientists”
“John Lighton has probably done more to
modernize and consolidate the field of
whole-animal respirometry than any single
person. And now he has written a book that
explains all.”
– Theodore Garland, UCR
Technical Challenges?
Designed for Research
“…a precision of 0.3 ppm was obtained…”
(against a background of 209,400 ppm)
Application of a Differential Fuel-Cell Analyzer for Measuring
Atmospheric Oxygen Variations
BRITTON B. STEPHENS
Earth Observing Laboratory, National Center for Atmospheric Research, Boulder, Colorado
The Challenge… from the biomedical community
1. Make a higher throughput metabolic phenotyping system… (faster)
2. Using the techniques you’ve learned
3. Without cage seals & desiccants
4. With better accuracy, resolution & repeatability
5. While reducing animal stress
6. While increasing animal safetyand…
7. With expert technical support!
METABOLIC SCREENING
Our growing global user base…
Back to Basics
• VO2 = FR(ΔO2)/(1 - FiO2)
• What limits data resolution & bandwidth?
- Cage time constant (TC) = cage volume / FR
- E.g. 5 L / 0.5 L min-1 = 10 minutes
- Require ~5 TC for equilibrium
• To reduce TC, we must increase FR
• But that reduces ΔO2 !
• Usual ΔO2 target is ~0.5%, limiting > of FR
• Rethinking needed! Here come 6 rethinkings…
FRi FRe
RETHINK (1)
“ In order to detect relevant changes in metabolism of a small mammal, the analyzers should be able to detect changes in Vol%O2 or Vol%CO2 at a relative precision of 0.01% ”
– Meyer, Reitmeyer & Tschöp, 2015
Sophisticated analyzers can resolve 0.0001% - a new standard is available
Specifically designed for cutting-edge flow-through respirometry- allows much higher flow rates
Appropriate scientific gas analyzer technology
Fuel cell technology, when applied properly, is the clear leader in low noise, high resolution & speed
15 second dwell time – can reduce further if needed
Shows extraction of cage 4 excurrent O2
data from a 4-cage multiplexed system
Incurrent O2
measurement
• High analyzer resolution allows higher FR
• This << Time Constant of chamber
• High analyzer speed << cycle time (animal 1 to animal 1 in a multiplexed system ~ 2 minutes!)
• Now, finally, cycle time can be less than chamber TC – even with shorter TC!
RETHINK (2)
Result: drastic temporal & data resolution improvement= HIGHER BANDWIDTH
RETHINK (3)
• Desiccant systems are unreliable, unnecessary & slow down gas analysis
• Simple physics: Dalton’s Law of Partial Pressures allows desiccant elimination
IFF water vapor pressure & barometric pressure are measured with high resolution
• Developed WVP analyzer for my research that can resolve 1 Drosophila easily
Effect of Barometric PressureIncurrent O2 is constant, yet measured
incurrent O2 is variable!
Data courtesy of Vanderbilt MMPC
Does mathematical WV dilution comp. actually work?
After WV Dilution Correction(eqn. in Lighton, 2008)
After WV Dilution and BP Correction
Hell yes
Data courtesy of Vanderbilt MMPC
After WV Dilution Correction After WV Dilution and BP Correction
The result of mathematical WV compensation…
The speed penalties, reliability problems & inefficiencies of desiccators, including chemical, thermal and permeable-membrane ARE NOW ELIMINATED
BONUS: Extra data channel of whole-animal water flux rates!
• Collect ALL raw data from ALL analyzers, flow generators, cage sensors (intake, body mass, position) every second, making no changes to the data
• Create agnostic Deep Data Field -- High Bandwidth and continuous recording of all raw data
• NO pre-set decisions from the scientist necessary for routine data acquisition
RETHINK (4)
Result: Data analysis is uniquely flexible
Light Field Camera = Raw Light Data
Light Field Camera = Raw Light Data
Light Field Camera = Raw Light Data
Legacy Systems…
PROMETHION
You’ve Got Data
LEGACY:16 cages x 5 min x 20 variables/animal = 320 var (max!)/300 sec= ~1 variable/second
PROMETHION:1 measurement/sec from all analyzers & sensors in 16-cage system = 350-450 variables/second
RETHINK (5)
• All data transfer is digital
• Mission-critical, high speed error-correcting network optimizes simplicity, reliability and…
RESOLUTION!
• Exclusively Pull Mode = high FR!, Bedding OK
• No seals to leak, minimum dead volume
• Lowest possible stress, best animal welfare
• Best reproducibility
RETHINK (6)
What about acclimation…?
Body mass increases from start of run
EE remains similar; factorial scope approx. 2
Activity pattern remains similar
Data: 21 gram C57BL/6J transferred straight from communal housing into Promethioncage…
Wait…That Didn’t Look Right?
Typical Legacy Resolution…
Source: Advertising brochure
• 5 minute cycle time
• REE? AEE?• Note correlation
quality between activity and VO2
• Note super-unity RER during scotophase
Promethion Resolution
• Clean activity data (1 cm beam spacing)
• Excellent correlation between activity & EE
• Unambiguous active & resting EE
• Realistic RQs
Tight correlation between EE and activity -Fast response from high bandwidth
Excellent resolution of resting EE (CV ~2-3% with no averaging)
Excellent resolution of active EE quantifies precise energetic cost of activity; factorial scope approx. 2
Accurate RQs (measure WV & correct mathematically)
I don’t recognize the data…?
combination of fast cycle time & fast TC unique to Promethion
How to Use the Resolution
• This example: Promethion-C, 1 sample/sec from all cages in the system
• Superb temporal & data resolution
…e.g., determine cost of transport
Correlate distance run on wheel and energy expended while running
measure of coordination & musculoskeletal condition
Usually requires a treadmill… Lighton & Gillespie, 1987
• Very repeatable• Tighter regression
than with most treadmill runs
• No stress for animals orpersonnel
• Time-efficient
But not with Promethion
Continuous Measurement – Promethion-C
METABOLIC RATE SAMPLED AT 1 Hz…120x - 2700x faster than multiplexed systems
Vs. Legacy “Continuous”
METABOLIC RATE SAMPLED AT 0.016 Hz… 60x slower than Promethion-C
Vs. “Continuous”… Analyzing the same Gas Stream
Red = legacy systemBlue = Promethion-C
system
ACTH & Cortisol spike? BAT?
Detail of EE in body mass habitat
• Cool-Down Period Lasts ~15 Min
• Variable Low Activity Duration Correlates with Low EE
• ANY Movement is Detectable in Habitat
• EE Rises PRIOR to Activity (Leaving Habitat)
Productivity
How is high bandwidth related to productivity?
Increase data resolution & replicability
Increase analytical flexibility & publishability for researchers
Decrease re-runs, repeats, re-bookings, wasted time & funds
Perfect for labs and high-demand MP cores
Support & training by Ph.D.-level personnel
Our emphasis – not on us, but on YOU AND YOUR SCIENCE!
Quantifying components of total energy expenditure (TEE): integrating data across multiple platforms
Jennifer A. Teske, PhD
Assistant Professor,University of Arizona,
Department of Nutritional Sciences
Copyright 2015 J. Teske, InsideScientific & Sable Systems International. All Rights Reserved.
44
Promethion-C Indirect calorimetry, Sable Systems Int’l EEG/EMG by telemetry, Data Sciences International
Infrared physical activity sensors, Sable Systems Int’l
Integrating equipment to quantify TEE:
45
Promethion-C Indirect calorimetry, Sable Systems Int’l EEG/EMG by telemetry, Data Sciences International
Infrared physical activity sensors, Sable Systems Int’l
Integrating equipment to quantify TEE:
Components of total energy expenditure
Energy expenditure during…
• REM sleep: calories during REM sleep
• Non-REM sleep: calories during NREM sleep
• Rest:1. Metabolic rate during the early light cycle when not moving based on IR-beam sensors
2. Calories when wake and not moving based on IR-beam sensors
• Physical activity: sum of calories when moving based on IR-beam sensors
OR
Quantifying components of energy expenditure
47
Time Stamp Physical Kcal/hr Sleep/wake Temperature Activity counts EE due to EE due to EE due to EE due to
Activity (m/s) stage (Celsius) (Counts/min) PA Rest/QW NREM REM
10:54:20 AM 0.00266 3.340 active wake 37.60 18 3.340
10:54:21 AM 0.00172 3.338 active wake 37.60 18 3.338
10:54:22 AM 0.00272 3.342 active wake 37.58 18 3.342
10:54:23 AM 0.00274 3.351 active wake 37.57 18 3.351
10:54:24 AM 0.00248 3.359 active wake 37.65 18 3.359
10:55:10 AM 0.00000 2.715 active wake 37.50 0 2.715
10:55:11 AM 0.00000 2.723 active wake 37.59 0 2.723
10:55:12 AM 0.00000 2.732 active wake 37.62 0 2.732
10:55:13 AM 0.00000 2.744 active wake 37.63 0 2.744
10:55:14 AM 0.00000 2.756 active wake 37.57 0 2.756
10:52:20 AM 0.00000 2.377 quiet wake 36.66 0 2.805
10:52:21 AM 0.00000 2.375 quiet wake 36.65 0 2.805
10:52:22 AM 0.00000 2.373 quiet wake 36.66 0 2.805
10:52:23 AM 0.00000 2.371 quiet wake 36.66 0 2.805
10:52:24 AM 0.00000 2.369 quiet wake 36.65 0 2.805
12:10:10 PM 0.00000 2.404 NREM sleep 37.48 0 2.404
12:10:11 PM 0.00000 2.399 NREM sleep 37.48 0 2.399
12:10:12 PM 0.00000 2.393 NREM sleep 37.47 0 2.393
12:10:13 PM 0.00000 2.386 NREM sleep 37.47 0 2.386
12:10:14 PM 0.00000 2.379 NREM sleep 37.47 0 2.379
12:06:20 PM 0.00000 2.440 REM sleep 37.46 0 2.440
12:06:21 PM 0.00000 2.440 REM sleep 37.47 0 2.440
12:06:22 PM 0.00000 2.441 REM sleep 37.46 0 2.441
12:06:23 PM 0.00000 2.441 REM sleep 37.46 0 2.441
12:06:24 PM 0.00000 2.442 REM sleep 37.46 0 2.442
EE: energy expenditure, QW: quiet wake, NREM: non-rapid eye movement sleep, REM: rapid eye movement sleep
48
Time Stamp Physical Kcal/hr Sleep/wake Temperature Activity counts EE due to EE due to EE due to EE due to
Activity (m/s) stage (Celsius) (Counts/min) PA Rest/QW NREM REM
10:54:20 AM 0.00266 3.340 active wake 37.60 18 3.340
10:54:21 AM 0.00172 3.338 active wake 37.60 18 3.338
10:54:22 AM 0.00272 3.342 active wake 37.58 18 3.342
10:54:23 AM 0.00274 3.351 active wake 37.57 18 3.351
10:54:24 AM 0.00248 3.359 active wake 37.65 18 3.359
10:55:10 AM 0.00000 2.715 active wake 37.50 0 2.715
10:55:11 AM 0.00000 2.723 active wake 37.59 0 2.723
10:55:12 AM 0.00000 2.732 active wake 37.62 0 2.732
10:55:13 AM 0.00000 2.744 active wake 37.63 0 2.744
10:55:14 AM 0.00000 2.756 active wake 37.57 0 2.756
10:52:20 AM 0.00000 2.377 quiet wake 36.66 0 2.805
10:52:21 AM 0.00000 2.375 quiet wake 36.65 0 2.805
10:52:22 AM 0.00000 2.373 quiet wake 36.66 0 2.805
10:52:23 AM 0.00000 2.371 quiet wake 36.66 0 2.805
10:52:24 AM 0.00000 2.369 quiet wake 36.65 0 2.805
12:10:10 PM 0.00000 2.404 NREM sleep 37.48 0 2.404
12:10:11 PM 0.00000 2.399 NREM sleep 37.48 0 2.399
12:10:12 PM 0.00000 2.393 NREM sleep 37.47 0 2.393
12:10:13 PM 0.00000 2.386 NREM sleep 37.47 0 2.386
12:10:14 PM 0.00000 2.379 NREM sleep 37.47 0 2.379
12:06:20 PM 0.00000 2.440 REM sleep 37.46 0 2.440
12:06:21 PM 0.00000 2.440 REM sleep 37.47 0 2.440
12:06:22 PM 0.00000 2.441 REM sleep 37.46 0 2.441
12:06:23 PM 0.00000 2.441 REM sleep 37.46 0 2.441
12:06:24 PM 0.00000 2.442 REM sleep 37.46 0 2.442
Quantifying components of energy expenditure
• Score 15-s epochs of EEG and EMG for the appropriate sleep-wake state (active wake, quiet wake, NREM sleep, or REM sleep)
• Align physical activity (from Sable infrared sensors), energy expenditure (from Sable Promethion-C) and sleep/wake (scored from DSI)
• May include temperature and subjective activity counts data from DSI
EE due to PA
EE: energy expenditure, QW: quiet wake, NREM: non-rapid eye movement sleep, REM: rapid eye movement sleep
49
Time Stamp Physical Kcal/hr Sleep/wake Temperature Activity counts EE due to EE due to EE due to EE due to
Activity (m/s) stage (Celsius) (Counts/min) PA Rest/QW NREM REM
10:54:20 AM 0.00266 3.340 active wake 37.60 18 3.340
10:54:21 AM 0.00172 3.338 active wake 37.60 18 3.338
10:54:22 AM 0.00272 3.342 active wake 37.58 18 3.342
10:54:23 AM 0.00274 3.351 active wake 37.57 18 3.351
10:54:24 AM 0.00248 3.359 active wake 37.65 18 3.359
10:55:10 AM 0.00000 2.715 active wake 37.50 0 2.715
10:55:11 AM 0.00000 2.723 active wake 37.59 0 2.723
10:55:12 AM 0.00000 2.732 active wake 37.62 0 2.732
10:55:13 AM 0.00000 2.744 active wake 37.63 0 2.744
10:55:14 AM 0.00000 2.756 active wake 37.57 0 2.756
10:52:20 AM 0.00000 2.377 quiet wake 36.66 0 2.805
10:52:21 AM 0.00000 2.375 quiet wake 36.65 0 2.805
10:52:22 AM 0.00000 2.373 quiet wake 36.66 0 2.805
10:52:23 AM 0.00000 2.371 quiet wake 36.66 0 2.805
10:52:24 AM 0.00000 2.369 quiet wake 36.65 0 2.805
12:10:10 PM 0.00000 2.404 NREM sleep 37.48 0 2.404
12:10:11 PM 0.00000 2.399 NREM sleep 37.48 0 2.399
12:10:12 PM 0.00000 2.393 NREM sleep 37.47 0 2.393
12:10:13 PM 0.00000 2.386 NREM sleep 37.47 0 2.386
12:10:14 PM 0.00000 2.379 NREM sleep 37.47 0 2.379
12:06:20 PM 0.00000 2.440 REM sleep 37.46 0 2.440
12:06:21 PM 0.00000 2.440 REM sleep 37.47 0 2.440
12:06:22 PM 0.00000 2.441 REM sleep 37.46 0 2.441
12:06:23 PM 0.00000 2.441 REM sleep 37.46 0 2.441
12:06:24 PM 0.00000 2.442 REM sleep 37.46 0 2.442
Quantifying components of energy expenditureEE due to Rest/QW
• Multiple ways to calculate
• Traditional: Metabolic rate during the early light cycle
• Promethion-C:
• Metabolic rate during the early light cycle when not moving based on IR-beam sensors
• Calories when wakeand not moving based on IR-beam sensors
EE: energy expenditure, QW: quiet wake, NREM: non-rapid eye movement sleep, REM: rapid eye movement sleep
50
Time Stamp Physical Kcal/hr Sleep/wake Temperature Activity counts EE due to EE due to EE due to EE due to
Activity (m/s) stage (Celsius) (Counts/min) PA Rest/QW NREM REM
10:54:20 AM 0.00266 3.340 active wake 37.60 18 3.340
10:54:21 AM 0.00172 3.338 active wake 37.60 18 3.338
10:54:22 AM 0.00272 3.342 active wake 37.58 18 3.342
10:54:23 AM 0.00274 3.351 active wake 37.57 18 3.351
10:54:24 AM 0.00248 3.359 active wake 37.65 18 3.359
10:55:10 AM 0.00000 2.715 active wake 37.50 0 2.715
10:55:11 AM 0.00000 2.723 active wake 37.59 0 2.723
10:55:12 AM 0.00000 2.732 active wake 37.62 0 2.732
10:55:13 AM 0.00000 2.744 active wake 37.63 0 2.744
10:55:14 AM 0.00000 2.756 active wake 37.57 0 2.756
10:52:20 AM 0.00000 2.377 quiet wake 36.66 0 2.805
10:52:21 AM 0.00000 2.375 quiet wake 36.65 0 2.805
10:52:22 AM 0.00000 2.373 quiet wake 36.66 0 2.805
10:52:23 AM 0.00000 2.371 quiet wake 36.66 0 2.805
10:52:24 AM 0.00000 2.369 quiet wake 36.65 0 2.805
12:10:10 PM 0.00000 2.404 NREM sleep 37.48 0 2.404
12:10:11 PM 0.00000 2.399 NREM sleep 37.48 0 2.399
12:10:12 PM 0.00000 2.393 NREM sleep 37.47 0 2.393
12:10:13 PM 0.00000 2.386 NREM sleep 37.47 0 2.386
12:10:14 PM 0.00000 2.379 NREM sleep 37.47 0 2.379
12:06:20 PM 0.00000 2.440 REM sleep 37.46 0 2.440
12:06:21 PM 0.00000 2.440 REM sleep 37.47 0 2.440
12:06:22 PM 0.00000 2.441 REM sleep 37.46 0 2.441
12:06:23 PM 0.00000 2.441 REM sleep 37.46 0 2.441
12:06:24 PM 0.00000 2.442 REM sleep 37.46 0 2.442
Quantifying components of energy expenditure
• Calories when in NREM sleep based on scored EEG/EMG from DSI and no movement based on IR-beam sensors from Sable Promethion-C.
EE due to NREM sleep
EE: energy expenditure, QW: quiet wake, NREM: non-rapid eye movement sleep, REM: rapid eye movement sleep
51
Time Stamp Physical Kcal/hr Sleep/wake Temperature Activity counts EE due to EE due to EE due to EE due to
Activity (m/s) stage (Celsius) (Counts/min) PA Rest/QW NREM REM
10:54:20 AM 0.00266 3.340 active wake 37.60 18 3.340
10:54:21 AM 0.00172 3.338 active wake 37.60 18 3.338
10:54:22 AM 0.00272 3.342 active wake 37.58 18 3.342
10:54:23 AM 0.00274 3.351 active wake 37.57 18 3.351
10:54:24 AM 0.00248 3.359 active wake 37.65 18 3.359
10:55:10 AM 0.00000 2.715 active wake 37.50 0 2.715
10:55:11 AM 0.00000 2.723 active wake 37.59 0 2.723
10:55:12 AM 0.00000 2.732 active wake 37.62 0 2.732
10:55:13 AM 0.00000 2.744 active wake 37.63 0 2.744
10:55:14 AM 0.00000 2.756 active wake 37.57 0 2.756
10:52:20 AM 0.00000 2.377 quiet wake 36.66 0 2.805
10:52:21 AM 0.00000 2.375 quiet wake 36.65 0 2.805
10:52:22 AM 0.00000 2.373 quiet wake 36.66 0 2.805
10:52:23 AM 0.00000 2.371 quiet wake 36.66 0 2.805
10:52:24 AM 0.00000 2.369 quiet wake 36.65 0 2.805
12:10:10 PM 0.00000 2.404 NREM sleep 37.48 0 2.404
12:10:11 PM 0.00000 2.399 NREM sleep 37.48 0 2.399
12:10:12 PM 0.00000 2.393 NREM sleep 37.47 0 2.393
12:10:13 PM 0.00000 2.386 NREM sleep 37.47 0 2.386
12:10:14 PM 0.00000 2.379 NREM sleep 37.47 0 2.379
12:06:20 PM 0.00000 2.440 REM sleep 37.46 0 2.440
12:06:21 PM 0.00000 2.440 REM sleep 37.47 0 2.440
12:06:22 PM 0.00000 2.441 REM sleep 37.46 0 2.441
12:06:23 PM 0.00000 2.441 REM sleep 37.46 0 2.441
12:06:24 PM 0.00000 2.442 REM sleep 37.46 0 2.442
Quantifying components of energy expenditure
• Calories when in REM sleep based on scored EEG/EMG from DSI and no movement based on IR-beam sensors from Sable Promethion-C.
EE due to REM sleep
EE: energy expenditure, QW: quiet wake, NREM: non-rapid eye movement sleep, REM: rapid eye movement sleep
Sleep ad libitum
(control)
Male
Sprague-
Dawley
rats
Sleep deprived
(8h/d for 9d)
Validation that exposure to pre-recorded environmental noise reduces sleep
52Mavanji, Teske, Kotz, Billington. 2013. Obesity. Partial sleep deprivation by environmental noise increases food intake and body weight in obesity-resistant rats.21(7):1396-405. Data represented as mean +/- S.E.M, N = 8/group. *P<0.01, **P<0.001 as compared to respective baseline. NREM: non-rapid eye movement sleep, REM:
rapid eye movement sleep
0
15
30
45
60
75
Sleep/wake stage% tim
e in
sle
ep
/wa
ke
sta
ge
s
**
*
**
Undisturbed (control (C))
Partial sleep deprivation
Wake REM SWS
Does acute sleep deprivation affect TEE?
NREMREMWake
0
15
30
45
60
75
Sleep/wake stage% tim
e in
sle
ep
/wa
ke
sta
ge
s
**
*
**
Undisturbed (control (C))
Partial sleep deprivation
Wake REM SWSNREMREMWake
Sleep ad libitum
(control)
Male
Sprague-
Dawley
rats
Sleep deprived
(8h/d for 9d)
Validation that exposure to pre-recorded environmental noise reduces sleep
53Mavanji, Teske, Kotz, Billington. 2013. Obesity. Partial sleep deprivation by environmental noise increases food intake and body weight in obesity-resistant rats.21(7):1396-405. Data represented as mean +/- S.E.M, N = 8/group. *P<0.01, **P<0.001 as compared to respective baseline. NREM: non-rapid eye movement sleep, REM:
rapid eye movement sleep
Does acute sleep deprivation affect Total EE?
Does exposure to environmental noise affect energy expenditure?
Study Design: effect of acute environmental noise on energy expenditure
54Data represented as mean +/- S.E.M, N = 7/group. *P<0.05.
• 10-d acclimation to Sable food and water containers
• 3-day acclimation in Sable Promethion-C chambers
• 2500mL/min flow rate
• Food and water ad libitum
• 12-h noise exposure on day 5
• 36-h recovery phase after noise exposure
Study Design: effect of acute environmental noise on energy expenditure
55Data represented as mean +/- S.E.M, N = 7/group. *P<0.05. SD: sleep deprivation
• 12-h noise exposure causes significantly greater weight gain
• Weight gain remained elevated after noise exposure
0
3
6
9
12
Treatment
24h b
ody w
eig
ht gain
(g
)
*
sleep ad lib
SD recoverysleep ad lib
-4
-3
-2
-1
0
1
2
Sleep Treatment (24 h)
Change in
24h E
E (
kcal)
ad lib SD recover
**
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
Treatment
Ch
an
ge
in E
E (kca
ls)
light & dark cycle
ad lib SD recover
*
*
*
*
A B C
RecoverSDAd lib
Treatment
Study Design: effect of acute environmental noise on energy expenditure
56Data represented as mean +/- S.E.M, N = 7/group. *P<0.05. SD: sleep deprivation
0
3
6
9
12
Treatment24h b
ody w
eig
ht gain
(g
)
*
sleep ad lib
SD recoverysleep ad lib
-4
-3
-2
-1
0
1
2
Sleep Treatment (24 h)
Change in
24h E
E (
kcal)
ad lib SD recover
**
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
Treatment
Ch
an
ge
in E
E (kca
ls)
light & dark cycle
ad lib SD recover
*
*
*
*
A B C
• 12-h noise exposure causes significantly greater weight gain
• Weight gain remained elevated after noise exposure
• Reduced total energy expenditure during and after noise exposure
0
3
6
9
12
Treatment
24h b
ody w
eig
ht gain
(g
)
*
sleep ad lib
SD recoverysleep ad lib
-4
-3
-2
-1
0
1
2
Sleep Treatment (24 h)
Change in
24h E
E (
kcal)
ad lib SD recover
**
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
Treatment
Ch
an
ge
in E
E (kca
ls)
light & dark cycle
ad lib SD recover
*
*
*
*
A B C
RecoverSDAd lib
TreatmentRecoverSDAd lib
Treatment
57
Acute sleep deprivation reduces energy expenditure during sleep
Data represented as mean +/- S.E.M, N = 7/group. *P<0.05. SD: sleep deprivation
58
Acute sleep deprivation reduces energy expenditure during rest and physical activity
Data represented as mean +/- S.E.M, N = 7/group. *P<0.05. SD: sleep deprivation
• DSI EMG leads implanted in neck musculature
• 1Energy expenditure during rest: when awake but no movement based on Sable IR-beams andDSI EMG activity counts
• 2Energy expenditure during reset: when awake but no movement based on IR-beams only.
EE
du
e to
re
st1
EE
du
e to
re
st2
How does central orexin A increase total EE?
SLEEP, Vol. 38, No. 9, 2015 1367 Orexin-A in the VLPO Modulates Behavior—Mavanji et al.
well characterized. These results show that local injection of
orexin-A in the VLPO produces a behavioral profile similar
to that observed after orexin-A injection into other wake-
promoting nuclei. Microinjection of orexin-A in the VLPO
enhances wakefulness, SPA, SPA-induced energy expenditure
and total energy expenditure without any feeding effect. Fur-
thermore, we showed that blockade of both orexin receptors
in the VLPO reduces orexin-A stimulated wakefulness and
SPA, while blockade of OX2R alone partially reduced orexin-
A stimulated SPA. Together these data suggest that the VLPO
may be a critical site of convergence for orexin-A mediation of
vigilance states and energy balance regulation.
The VLPO contains both orexin receptor subtypes,34,35 and
there are reciprocal connections with orexinergic nuclei and the
VLPO.32,36–38,40–42,59 Neuroanatomical and functional39,44 data
indicate that the VLPO promotes sleep, at least partially, by
inhibiting orexin neurons. This suggests that orexin can inhibit
sleep-promoting neurons in the VLPO to maintain wakeful-
ness and also that the VLPO may modulate orexin-A stimu-
lated behavior in a push-pull relationship29,60 similar to that of
other arousal-promoting centers such as the tuberomammil-
lary nucleus.61 In addition, locally in the VLPO, orexin affects
galaninergic/GABAergic interneurons.42,62
Our work and that of others suggest that orexin-A increases
SPA and elevates energy expenditure in a dose-dependent and
cumulative manner, which promotes obesity resistance.14,23,63,64
Here, we observed significantly greater SPA, SPA-induced en-
ergy expenditure and total energy expenditure in response to
orexin-A in the VLPO during the 0–2 h post-injection time
period. One novelty of this finding lies in the time-locked rela-
tionship between SPA and energy expenditure in both orexin-
A-treated and non-treated rats. This can be seen from the
matching of long intervals of SPA with peaks of total energy
expenditure and from the decline in total energy expenditure
towards that of resting metabolic rate during times of low SPA.
This is the first demonstration that orexin-A in the VLPO stim-
ulates SPA-related energy expenditure, and that increases in
whole body energy expenditure after orexin-A administration
in the VLPO are directly coupled to SPA-induced energy ex-
penditure.56,64 Together these data imply that pharmacological
interventions to enhance orexin activity in the VLPO may be
effective in combating obesity by increasing physical activity.
In contrast to the effect of orexin-A on vigilance states, SPA,
and energy expenditure, VLPO administration of orexin-A
failed to augment either acute or 24-h food intake. Orexin-
A administered in the VLPO did not increase food intake,
which is in agreement with previous findings that orexin-A
Figure 6—Study 5. Orexin-A in the ventrolateral preoptic area (VLPO)
has no effect on (A) acute (e.g. 0–1, 0–2 or 0–4 h post-injection) or (B)
chronic food intake (e.g. 0–24 h post-injection). n = 18. Data represented
as mean ± SEM. Note different scaling on y-axes.
0.0
0.5
1.0
1.5
2.0
2.5
Dose of orexin-A (pmol)
Fo
od
in
take
(g
)
0–1 h 0–2 h 0–4 h
15.6
31.2
62.5012
5
A B
015
.631
.262
.5 125
0
5
10
15
20
25
Dose of orexin-A (pmol)
Fo
od
in
take
(g
)
0–24 h
Figure 7—Study 6. Representative examples of the time course of spontaneous physical activity (SPA, right y-axis in red) and total energy expenditure
(TEE, left y-axis in blue) after injection of (A) vehicle-artificial cerebrospinal fluid or (B) orexin-A, beginning 2-h post-injection. Microinjection of orexin-A into
the ventrolateral preoptic area (VLPO) significantly increases (C) distance traveled, (D) TEE and (E) SPA-induced energy expenditure relative to vehicle
injection. n = 4. Data represented as mean ± SEM. Brackets indicate bars that are significantly different from each other (*P < 0.05) in panels C D, and E.
Note different scaling on the y-axes.
0
1
2
3
4
5
6
0.00
0.02
0.04
0.06
0.08
0.10
Time (min)
TE
E (
kca
l/h
)
TE
E (
kca
l/h
)
acsf
Dis
tan
ce
travele
d (m
/s)
Dis
tan
ce
travele
d (m
/s)
30 60 90 1200
0
1
2
3
4
5
6
0.00
0.02
0.04
0.06
0.08
0.10
Time (min)
Orexin-A
30 60 90 1200
A B
DC E
0 125 0 125
0
20
40
60
80
Dose of orexin-A (pmol)
0–1
h D
ista
nc
e
trav
ele
d (
m)
0–1 h 0–2 hTime (h):
Dose:
*
*
0 125 0 125
0
2
4
6
8
Dose of orexin-A (pmol)
0–1
h T
ota
l En
erg
y
Ex
pe
nd
itu
re (
kca
l/h
)
0–1 h 0–2 hTime (h):
Dose:
*
*
0 125 0 125
0
1
2
3
4
5
6
Dose of orexin-A (pmol)
0–
2 h
PA
En
erg
y
Ex
pe
nd
itu
re (
kca
l/h
)
0–1 h 0–2 hTime (h):
Dose:
*
*
59
Mavanji, Perez-Leighton, Kotz, Billington,
Parthasarathy, Sinton, Teske, JA. Promotion of
wakefulness and energy expenditure by orexin A
in the ventrolateral preoptic area. Sleep. 38(9):
1361-1370. Data represented as mean +/- S.E.M,
Brackets indicate bars that are significantly
different from each other (P < 0.05) N = 4.
0 62.5
0
5
10
15
20
25
Dose orexin A (pmol / 0.5 uL)
Dis
tan
ce
tra
ve
led
(cm
)
*
0
0
1
2
3
Dose orexin A (pmol / 0.5 uL)
To
tal e
ne
rgy
exp
en
ditu
re (kca
l/h
) *
0 62.5
0
20
40
60
80
100
Dose orexin A (pmol / 0.5 uL)
Tim
e in
activ
e w
ake
(%
)
*
0 62.5
0
15
30
45
60
Dose orexin A (pmol / 0.5 uL)
Tim
e in
NR
EM
sle
ep
(%
)
*
0 62.5
0
5
10
15
20
Dose orexin A (pmol / 0.5 uL)
Tim
e in
RE
M s
lee
p (%
)
*
0 62.5
0.0
0.5
1.0
1.5
2.0
2.5
Dose orexin A (pmol / 0.5 uL)
0-1
h P
A-r
ela
ted
en
erg
y
exp
en
ditu
re (kca
l/h
)
*
0 62.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
Dose orexin A (pmol / 0.5 uL)
0-1
h re
stin
g m
eta
bo
lic
rate
(kca
l/h)
*
0 62.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
Dose orexin A (pmol / 0.5 uL)
0-1
h N
RE
M m
eta
bo
lic
rate
(kca
l/h)
*
0 62.5
0.0
0.5
1.0
1.5
2.0
2.5
Dose orexin A (pmol / 0.5 uL)
0-1
h R
EM
me
tab
olic
ra
te (kca
l/h)
0 62.5
0.0
0.2
0.4
0.6
0.8
Dose orexin A (pmol / 0.5 uL)
0-1
h R
estin
g E
ne
rgy
Exp
en
ditu
re (kca
l/h
) *
EE: energy expenditure, NREM: non-rapid eye movement sleep, REM: rapid eye movement sleep
Does orexin A increase components of Total energy expenditure?
Orexin A increases several components of total EE
60
0 62.5
0
5
10
15
20
25
Dose orexin A (pmol / 0.5 uL)
Dis
tan
ce
tra
ve
led
(cm
)
*
0
0
1
2
3
Dose orexin A (pmol / 0.5 uL)
To
tal e
ne
rgy
exp
en
ditu
re (kca
l/h) *
0 62.5
0
20
40
60
80
100
Dose orexin A (pmol / 0.5 uL)
Tim
e in
activ
e w
ake
(%
)
*
0 62.5
0
15
30
45
60
Dose orexin A (pmol / 0.5 uL)
Tim
e in
NR
EM
sle
ep
(%
)
*
0 62.5
0
5
10
15
20
Dose orexin A (pmol / 0.5 uL)
Tim
e in
RE
M s
lee
p (%
)
*
0 62.5
0.0
0.5
1.0
1.5
2.0
2.5
Dose orexin A (pmol / 0.5 uL)
PA
-re
late
d e
ne
rgy
exp
en
ditu
re (kca
l/h
)
*
0 62.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
Dose orexin A (pmol / 0.5 uL)
Re
stin
g m
eta
bo
lic
rate
(kca
l/h)
*
0 62.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
Dose orexin A (pmol / 0.5 uL)
NR
EM
me
tab
olic
ra
te (kca
l/h
)
*
0 62.5
0.0
0.5
1.0
1.5
2.0
2.5
Dose orexin A (pmol / 0.5 uL)
RE
M m
eta
bo
lic
rate
(kca
l/h)
0 62.5
0.0
0.2
0.4
0.6
0.8
Dose orexin A (pmol / 0.5 uL)
Re
stin
g E
ne
rgy
Exp
en
ditu
re (
kca
l)
*• Energy expenditure
during physical activity: when awake and moving based on Sable IR-beams
• Energy expenditure during rest (when awake but no movement based on Sable IR-beams andDSI EMG activity counts): total and resting metabolic rate
0 62.5
0
5
10
15
20
25
Dose orexin A (pmol / 0.5 uL)
Dis
tan
ce
tra
ve
led
(cm
)
*
0
0
1
2
3
Dose orexin A (pmol / 0.5 uL)
To
tal e
ne
rgy
exp
en
ditu
re (kca
l/h) *
0 62.5
0
20
40
60
80
100
Dose orexin A (pmol / 0.5 uL)
Tim
e in
activ
e w
ake
(%
)
*
0 62.5
0
15
30
45
60
Dose orexin A (pmol / 0.5 uL)
Tim
e in
NR
EM
sle
ep
(%
)
*
0 62.5
0
5
10
15
20
Dose orexin A (pmol / 0.5 uL)
Tim
e in
RE
M s
lee
p (%
)
*
0 62.5
0.0
0.5
1.0
1.5
2.0
2.5
Dose orexin A (pmol / 0.5 uL)
PA
-re
late
d e
ne
rgy
exp
en
ditu
re (kca
l/h
)*
0 62.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
Dose orexin A (pmol / 0.5 uL)
Re
stin
g m
eta
bo
lic
rate
(kca
l/h)
*
0 62.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
Dose orexin A (pmol / 0.5 uL)
NR
EM
me
tab
olic
ra
te (kca
l/h
)
*
0 62.5
0.0
0.5
1.0
1.5
2.0
2.5
Dose orexin A (pmol / 0.5 uL)
RE
M m
eta
bo
lic
rate
(kca
l/h)
0 62.5
0.0
0.2
0.4
0.6
0.8
Dose orexin A (pmol / 0.5 uL)
Re
stin
g E
ne
rgy
Exp
en
ditu
re (
kca
l)
*
0 62.5
0
5
10
15
20
25
Dose orexin A (pmol / 0.5 uL)
Dis
tan
ce
tra
ve
led
(cm
)
*
0
0
1
2
3
Dose orexin A (pmol / 0.5 uL)
To
tal e
ne
rgy
exp
en
ditu
re (kca
l/h) *
0 62.5
0
20
40
60
80
100
Dose orexin A (pmol / 0.5 uL)
Tim
e in
activ
e w
ake
(%
)
*
0 62.5
0
15
30
45
60
Dose orexin A (pmol / 0.5 uL)
Tim
e in
NR
EM
sle
ep
(%
)
*
0 62.5
0
5
10
15
20
Dose orexin A (pmol / 0.5 uL)
Tim
e in
RE
M s
lee
p (%
)
*
0 62.5
0.0
0.5
1.0
1.5
2.0
2.5
Dose orexin A (pmol / 0.5 uL)
PA
-re
late
d e
ne
rgy
exp
en
ditu
re (kca
l/h
)
*
0 62.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
Dose orexin A (pmol / 0.5 uL)
Re
stin
g m
eta
bo
lic
rate
(kca
l/h)
*
0 62.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
Dose orexin A (pmol / 0.5 uL)
NR
EM
me
tab
olic
ra
te (kca
l/h
)
*
0 62.5
0.0
0.5
1.0
1.5
2.0
2.5
Dose orexin A (pmol / 0.5 uL)
RE
M m
eta
bo
lic
rate
(kca
l/h)
0 62.5
0.0
0.2
0.4
0.6
0.8
Dose orexin A (pmol / 0.5 uL)
Re
stin
g E
ne
rgy
Exp
en
ditu
re (
kca
l)
*
Does chronic sleep deprivation reduce physical activity-related EE to favor weight gain?
61
1d 2d 3d 4d 5d 6d 7d 8d 9d
Orexin Aresponse
test
Orexin Aresponse
test
Sleep deprivation by environmental noise (8h/d for 9d)
N= 7-8 per study. 62.5 or 125pmol/0.5 μL (American Peptide, Sunnyvale, CA). 1Data Sciences International, 2Promethion-Continuous, Sable Systems International
Chronic sleep deprivation
1. Time spent1 in wake, NREM and REM sleep
2. Distance traveled2
3. Total energy expenditure2
4. Energy expenditure during physical activity2
Endpoints for Studies:
before after0
20
40
60
80
Acute SD
D ti
me
in w
ake
(%
)
before after0
20
40
60
80
Chronic SD
D ti
me
in
wa
ke
(%
) *
before after0.0
0.2
0.4
0.6
0.8
Acute SD
D to
tal E
E (kca
l/h)
before after-0.5
0.0
0.5
1.0
1.5
2.0
Acute SD
D E
E d
ue
to p
hysic
al
activity
(kca
l/h) *
before after0.0
0.2
0.4
0.6
0.8
1.0
Chronic SD
D to
tal E
E (kca
l/h) *
before after0.0
0.5
1.0
1.5
2.0
Chronic SD
D E
E d
ue
to p
hysic
al
activ
ity (kca
l/h)
*
A. B. C. D.
E. F. G. H.
before after-100
-80
-60
-40
-20
0
Acute SD
D ti
me
in s
lee
p (%
)
before after-80
-60
-40
-20
0
Chronic SD
D ti
me
in s
lee
p (%
)
*
The response to orexin A was attenuated after sleep deprivation
62EE = energy expenditure. *p < .05 as compared to 0 dose of orexin A. Data represent mean ± SEM. N = 7-8/group.
Dose OXA (pmol)
• Before sleep deprivation: Validated that orexin-A in the ventrolateral preoptic area increases wake time, total EE and the EE due to physical activity and reduces sleep time.
Dose OXA (pmol)Dose OXA (pmol) Dose OXA (pmol)
Before
After
63
University of Arizona
Christopher M. Sinton, Ph.D. Jennifer Barbee, M.A. Giuliano Sciani, B.A. Martina Sepulveda
Minneapolis VA Health Care System
Charles J. Billington, MD.Catherine M. Kotz, Ph.D. Vijay Mavanji, Ph.D. Martha Grace, B.A.
Universidad Andres Bello, Santiago, Chile
Claudio E. Perez-Leighton, Ph.D.
Funding:
Department of Veterans Affairs RR&D (F7212W to J.Teske)
United States Department of Agriculture (ARZT-1360220-H23-150 J.Teske)
Minnesota Obesity Center NIH/NIDDK NORC (P30-DK050456)
1
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