Self-assembly of amyloid-ßpeptides in the presence of metalions and interacting molecules  – a detour of amyloid building blocks 

 Cecilia Mörman

Cecilia Mörm

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Doctoral Thesis in Biophysics at Stockholm University, Sweden 2020

Department of Biochemistry and Biophysics

ISBN 978-91-7911-188-5

Cecilia Mörman (former Wallin)received her MSc. in Biochemistry in2015 from Stockholm University andcontinued with a PhD in the lab ofAstrid Gräslund at StockholmUniversity. Cecilia’s research ismainly about amyloid-formingproteins.

Self-assembly of amyloid-β peptides in thepresence of metal ions and interacting molecules– a detour of amyloid building blocksCecilia Mörman

Academic dissertation for the Degree of Doctor of Philosophy in Biophysics at StockholmUniversity to be publicly defended on Thursday 3 September 2020 at 10.00 in Magnélisalen,Kemiska övningslaboratoriet, Svante Arrhenius väg 16 B.

AbstractMisfolding of proteins into amyloid structures is implicated as a pathological feature in several neurodegenerativediseases and the molecular causes are still unclear. One typical characteristic of Alzheimer’s disease is self-assemblyand accumulation of soluble amyloid-β (Aβ) peptides into insoluble fibrils and plaques. One way to provide fundamentalknowledge about the underlying fibrillization processes is to perturb the aggregation by varying the experimentalconditions. Two main aspects are included in this thesis work: interactions with the Aβ peptide, and modulation of the Aβpeptide aggregation kinetics. The interplay between the Aβ peptide and three different types of aggregation modulatorswas studied mainly in vitro by biophysical techniques such as NMR, circular dichroism, and fluorescence spectroscopy.

Metal ions, such as Ag(I), Cu(II), Hg(II), and Zn(II), at sub-stoichiometric concentrations with specific binding tomonomeric Aβ peptides modulate and attenuate the Aβ self-assembly process. The bound (metal:Aβ) state removes Aβmonomers from the monomeric pool of amyloid building blocks used for fibril formation. In contrast, designed peptideconstructs with cell-penetrating properties do not interact with monomeric Aβ, but exhibit an inhibitory effect on the Aβoligomerization and fibrillization in vitro and in cells, via interactions with multimeric Aβ structures. The designed peptideconstructs rescue Aβ-induced neurotoxicity and target both intracellular and extracellular Aβ. Full-length and native Tauprotein, another protein implicated in Alzheimer’s disease, prevents the Aβ peptide fibrillization. The Aβ fibrillizationprocess is not prevented by Tau interactions with the Aβ monomeric species, but rather with fibrils and oligomeric speciesof Aβ.

Here we showed that the Aβ peptide interacts with various metal ions and molecules, both at the monomeric stage and aslarger assemblies, with resulting perturbation of the Aβ aggregation kinetics. The interactions and aggregation modulatorscan be used to learn more about the underlying fibrillization processes and for the development of potential therapeuticstrategies.

Keywords: biophysics, Alzheimer’s disease, protein aggregation, amyloid formation, amyloid-β peptide, aggregationkinetics, interactions, metal ions, designed peptide constructs, Tau protein, NMR, circular dichroism, fluorescencespectroscopy.

Stockholm 2020http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-181495

ISBN 978-91-7911-188-5ISBN 978-91-7911-189-2

Department of Biochemistry and Biophysics

Stockholm University, 106 91 Stockholm

SELF-ASSEMBLY OF AMYLOID-ß PEPTIDES IN THE PRESENCE OFMETAL IONS AND INTERACTING MOLECULES  

Cecilia Mörman

Self-assembly of amyloid-ßpeptides in the presence ofmetal ions and interactingmolecules  

– a detour of amyloid building blocks  

Cecilia Mörman

©Cecilia Mörman, Stockholm University 2020 ISBN print 978-91-7911-188-5ISBN PDF 978-91-7911-189-2 Cover image: “11 arrows” by Cecilia Mörman.Aß amyloid aggregation is a heterogeneous process with several potential aggregation pathways, heresymbolized by nine grey arrows (seven arrows are visible). These aggregation pathways may be disrupted to takea detour (pink arrows) by molecular interactions from aggregation modulators (pink).PDB ID 2MPZ, software’s PEP-FOLD3 and PyMOL. Printed in Sweden by Universitetsservice US-AB, Stockholm 2020

”Energy and persistenceconquer all things”Benjamin Franklin    This thesis is dedicatedto everyone fighting againstAlzheimer’s disease

List of papers

Cecilia Mörman conducted most of the thesis work and articles under former

name, Cecilia Wallin. This thesis is based on the following papers (I-VII):

I. Metal ion coordination delays amyloid-β peptide self-assembly by

forming an aggregation-inert complex.

Wallin C, Jarvet J, Biverstål H, Wärmländer S, Danielsson J,

Gräslund A, Abelein A., 2020. Journal of Biological Chemistry,

295(21), pp.7224-7234. doi: 10.1074/jbc.RA120.012738.

II. Characterization of Mn(II) ion binding to the amyloid-β peptide in

Alzheimer’s disease.

Wallin C, Kulkarni YS, Abelein A, Jarvet J, Liao Q, Strodel B,

Olsson L, Luo J, Abrahams JP, Sholts SB, Roos PM, Kamerlin SC,

Gräslund A, Wärmländer SK., 2016. Journal of Trace Elements in

Medicine and Biology, 38, pp.183–193. doi:

10.1016/j.jtemb.2016.03.009.

III. Mercury and Alzheimer’s Disease: Hg(II) Ions Display Specific

Binding to the Amyloid-β Peptide and Hinder Its Fibrillization.

Wallin C, Friedemann M, Sholts SB, Noormägi A, Svantesson T,

Jarvet J, Roos PM, Palumaa P, Gräslund A, Wärmländer SKTS.,

2019. Biomolecules, 10(1), pp.44. doi: 10.3390/biom10010044.

IV. Specific Binding of Cu(II) Ions to Amyloid-Beta Peptides Bound to

Aggregation-Inhibiting Molecules or SDS Micelles Creates

Complexes that Generate Radical Oxygen Species.

Tiiman A, Luo J, Wallin C, Olsson L, Lindgren J, Jarvet J, Roos P,

Sholts SB, Rahimipour S, Abrahams JP, Karlström AE, Gräslund A,

Wärmländer SK., 2016. Journal of Alzheimer’s Disease, 54(3),

pp.971–982. doi: 10.3233/JAD-160427.

V. Alzheimer’s disease and cigarette smoke components: effects of

nicotine, PAHs, and Cd(II), Cr(III), Pb(II), Pb(IV) ions on amyloid-

β peptide aggregation.

Wallin C, Sholts SB, Österlund N, Luo J, Jarvet J, Roos PM, Ilag L,

Gräslund A, Wärmländer SKTS., 2017. Scientific Reports, 7(1),

pp.14423. doi: 10.1038/s41598-017-13759-5.

VI. Designed Cell-Penetrating Peptide Inhibitors of Amyloid-beta

Aggregation and Cytotoxicity.

Henning-Knechtel A, Kumar S, Wallin C, Król S, Wärmländer

SKTS, Jarvet J, Esposito G, Kirmizialtin S, Gräslund A, Hamilton

AD, Magzoub M., 2020. Cell Reports Physical Science, 1(2),

pp.100014. doi: 10.1016/j.xcrp.2020.100014.

VII. The Neuronal Tau Protein Blocks in Vitro Fibrillation of the

Amyloid-β (Aβ) Peptide at the Oligomeric Stage.

Wallin C, Hiruma Y, Wärmländer SKTS, Huvent I, Jarvet J,

Abrahams JP, Gräslund A, Lippens G, Luo J., 2018. Journal of the

American Chemical Society, 140(26), pp.8138–8146. doi:

10.1021/jacs.7b13623.

The papers will be referred to as Paper I-VII in the thesis. All papers are

reprinted with permission from the publishers.

List of additional papers

– not included in the thesis

VIII. ATP impedes the inhibitory effect of Hsp90 on Aβ40 fibrillation.

Wang H, Lallemang M, Hermann B, Wallin C, Loch R, Balzer B,

Hugel T, Luo J. Submitted manuscript.

IX. Big dynorphin is a neuroprotector against amyloid-β peptide

aggregation and cell toxicity.

Gallego-Villarejo L, Suades-Sala A, Wallin C, Król S, Enrich

Bengoa J, José Gomara M, Haro I, J. Muñoz F, Wärmlander S,

Gräslund A, Perálvarez-Marín A. Submitted manuscript.

X. Studies on citrullinated LL-37: detection in human airways,

antibacterial effects and biophysical properties.

Al-Adwani S, Wallin C, Balhuizen MD, Veldhuizen EJA, Coorens

M, Landreh M, Végvári Á, Smith ME, Qvarfordt I, Lindén A,

Gräslund A, Agerberth B, Bergman P., 2020. Scientific Reports,

10(1), pp.2376. Original article.

XI. Metal binding to the amyloid-β peptides in the presence of

biomembranes: potential mechanisms of cell toxicity.

Wärmländer SKTS, Österlund N, Wallin C, Wu J, Luo J, Tiiman A,

Jarvet J, Gräslund A., 2019. Journal of Biological Inorganic

Chemistry, 24(8), pp.1189-1196. Mini-review.

XII. Pro-Inflammatory S100A9 Protein Aggregation Promoted by

NCAM1 Peptide Constructs.

Pansieri J, Ostojić L, Iashchishyn IA, Magzoub M, Wallin C,

Wärmländer SKTS, Gräslund A, Nguyen Ngoc M, Smirnovas V,

Svedružić Ž, Morozova-Roche LA., 2019. ACS Chemical Biology,

14(7), pp.1410-1417. Original article.

XIII. Copper ions induce dityrosine-linked dimers in human but not in

murine islet amyloid polypeptide (IAPP/amylin).

Dong X, Svantesson T, Sholts SB, Wallin C, Jarvet J, Gräslund A,

Wärmländer SKTS., 2019. Biochemical and Biophysical Research

Communications, 510(4):520-524, pp.520–524. Original article.

XIV. Co-aggregation of pro-inflammatory S100A9 with α-synuclein in

Parkinson’s disease: ex vivo and in vitro studies.

Horvath I, Iashchishyn IA, Moskalenko RA, Wang C, Wärmländer

SKTS, Wallin C, Gräslund A, Kovacs GG, Morozova-Roche LA.,

2018. Journal of Neuroinflammation, 15(1), pp.172. Original

article.

XV. Amyloid-β Peptide Interactions with Amphiphilic Surfactants:

Electrostatic and Hydrophobic Effects.

Österlund N, Kulkarni YS, Misiaszek AD, Wallin C, Krüger DM,

Liao Q, Mashayekhy Rad F, Jarvet J, Strodel B, Wärmländer SKTS,

Ilag LL, Kamerlin SCL, Gräslund A., 2018. ACS Chemical

Neuroscience, 9(7), pp.1680–1692. Original article.

XVI. Mechanism of Peptide Binding and Cleavage by the Human

Mitochondrial Peptidase Neurolysin.

Teixeira PF, Masuyer G, Pinho CM, Branca RMM, Kmiec B,

Wallin C, Wärmländer SKTS, Berntsson RP, Ankarcrona M,

Gräslund A, Lehtiö J, Stenmark P, Glaser E., 2018. Journal of

Molecular Biology, 430(3), pp.348–362. Original article.

XVII. The Amyloid-β Peptide in Amyloid Formation Processes:

Interactions with Blood Proteins and Naturally Occurring Metal

Ions.

Wallin C, Luo J, Jarvet J, Wärmländer SKTS, Gräslund A., 2017.

Israel Journal of Chemistry, 57(7), pp.674–685. Review.

XVIII. Ancient water bottle use and polycyclic aromatic hydrocarbon

(PAH) exposure among California Indians: a prehistoric health risk

assessment.

Sholts SB, Smith K, Wallin C, Ahmed TM, Wärmländer SKTS.,

2017. Environmental Health: A Global Access Science Source,

16(1), pp.61. Original article.

XIX. Self-Assembled Cyclic d,l-α-Peptides as Generic Conformational

Inhibitors of the α-Synuclein Aggregation and Toxicity: In Vitro and

Mechanistic Studies.

Chemerovski-Glikman M, Rozentur-Shkop E, Richman M, Grupi A,

Getler A, Cohen HY, Shaked H, Wallin C, Wärmländer SK, Haas

E, Gräslund A, Chill JH, Rahimipour S., 2016. Chemistry - A

European Journal, 22(40), pp.14236–14246. Original article.

Abbreviations

Aβ Amyloid-β peptide

AβPP Amyloid precursor protein

ACH Amyloid cascade hypothesis

AFM Atomic Force Microscopy

ALS Amyotrophic lateral sclerosis

AMPs Antimicrobial peptides

CAC Critical aggregation concentration

CD Circular dichroism

CFs Curvilinear fibrils (protofibrils)

CNS Central nervous system

CPMG Carr-Purcell-Meiboom-Gill

CPP Cell-penetrating peptide

Cryo-EM Cryo electron microscopy

CSF Cerebrospinal fluid

gOs Globular amyloid oligomers

GuHCl Guanidine hydrochloric acid

DMSO Dimethyl sulfoxide

DTNB 5,5-dithio-bis-(2-nitrobenzoic acid)

FCS Fluorescence correlation spectroscopy

HFIP Hexafluoroisopropanol

HSQC Heteronuclear single quantum coherence

IAPP Islet amyloid polypeptide

IDP Intrinsically disordered protein

iPSC Induced pluripotent stem cells

LLPS Liquid-liquid phase separation

LTP Long-term potentiation

MAP Microtubule-associated protein

MCI Mild cognitive impairment

MRI Magnetic resonance imaging

NCAM Neural cell adhesion molecule

NFT Neurofibrillary tangles

NMR Nuclear magnetic resonance

PAH Polycyclic hydrocarbons

PET Positron emission tomography

PFG Pulse-field gradient

pFTAA Pentameric formyl thiophene acetic acid

PrP Prion protein

PTM Post-translational modifications

RF Rigid fibrils

RH Hydrodynamic radius

ROS Reactive oxygen species

SEC Size exclusion chromatography

SOD Superoxide dismutase

SPM Scanning Probe Microscopy

TEM Transmission Electron Microscopy

TTR Transthyretin

ThS Thioflavin S

ThT Thioflavin T

Contents

List of papers ............................................................................................................... i

List of additional papers – not included in the thesis ............................................... iii

Abbreviations .............................................................................................................. v

Contents ................................................................................................................... vii

1. Introduction ............................................................................................................. 1

2. Background ............................................................................................................. 2

2.1 Association and dissociation of biomolecules ................................................................. 3

2.2 Misfolding protein diseases ............................................................................................. 3

2.3 Neurodegeneration .......................................................................................................... 5

2.3.1 Alzheimer’s disease – general description.................................................................... 5

2.3.2 Alzheimer’s disease – biochemical and molecular description .................................... 6

2.4 The Aβ peptide – Introduction to the system ................................................................... 7

2.5 Amyloid and fibril formation .......................................................................................... 9

2.5.1 The cross-β structure .................................................................................................. 10

2.5.2 Aggregation versus amyloid fibrillization .................................................................. 11

2.5.3 Amyloid formation from monomers via intermediate structures ................................ 11

2.5.4 Are amyloid-forming proteins toxic? ......................................................................... 12

2.5.5 Amyloid fibrillization kinetics ................................................................................... 13

2.5.6 Modulation of protein aggregation ............................................................................. 17

2.6 What this thesis is about ................................................................................................ 17

2.7 Aim ............................................................................................................................... 18

3. Materials and Experimental techniques ................................................................ 19

3.1 Sample preparation........................................................................................................ 19

3.1.1 Sample preparation for aggregation kinetics experiments .......................................... 20

3.2 Spectroscopy ................................................................................................................. 22

3.2.1 Circular dichroism ...................................................................................................... 22

3.2.2 Fluorescence............................................................................................................... 23

3.2.3 UV/Vis spectroscopy.................................................................................................. 26

3.2.4 Nuclear magnetic resonance ....................................................................................... 26

3.3 Atomic Force Microscopy ............................................................................................. 29

4. Metal ions as protein aggregation modulators ...................................................... 30

4.1 Metal-binding properties of Aβ peptide (Paper I-V) ..................................................... 32

4.1.1 Binding mode and aggregation ................................................................................... 32

4.1.2 Metal ion binding in membrane-mimetics .................................................................. 34

4.2 Metal-Aβ complexes are unable for incorporation into fibril ends (Paper I) ................. 34

4.2.1 Ag(I) ions attenuate Aβ fibrillization by interfering with fibril-end elongation ......... 35

4.2.2 Fibril growth attenuation originates from Aβ peptides bound in metal complexes .... 35

4.2.3 Model: Metal ion perturbation of the fibrillization process ........................................ 37

4.3 Formation of reactive oxygen species by metal:Aβ complexes (Paper IV) ................... 38

4.4 Outlook ......................................................................................................................... 38

5. Small molecules and peptide construct interactions with Aβ peptide assemblies . 40

5.1 Hydrophobic compounds found in cigarette smoke (Paper V) ...................................... 40

5.2 Designed peptide constructs (Paper VI) ........................................................................ 40

6. Two interacting proteins implicated in Alzheimer’s disease – Aβ and Tau .......... 45

6.1 Full-length native Tau protein prevents Aβ fibrillization (Paper VII) ........................... 47

6.2 Outlook ......................................................................................................................... 48

7. Concluding remarks and future perspectives ........................................................ 49

7.1 Outlook ......................................................................................................................... 50

8. Populärvetenskaplig sammanfattning .......................................................................

9. Acknowledgements ...................................................................................................

10. References ...............................................................................................................

1

1. Introduction

“Everything should be made as simple as possible, but not simpler” was

once proposed by Albert Einstein. Is that true for solving the riddle of

Alzheimer’s disease – by finding all the chemical puzzle pieces underlying

progression of disease? One strategy to find out the answer is by usage of

molecular biology in combination with interdisciplinary collaboration with

more complex models. Alzheimer’s disease is a relatively new disease, first

described by Alois Alzheimer in 1907 (1). Followed by the “boom” of

molecular biology development, about 30 years of molecular insights into the

disease have been provided. The amyloid cascade hypothesis (ACH) with self-

assembly/misfolding of amyloid-β (Aβ) peptides was first postulated in the

1990’s (2). Since then an enormous amount of intensive studies and clinical

trials with potential drug candidates including passive immunization strategies

have been executed – but so far, no strong results of disease modifying

treatments have been developed (3–8). The need for therapeutic interventions

and prevention strategies is high as well as development of effective

biomarkers for early disease detection.

Knowledge and molecular descriptions of the pathology in terms of

amyloids and protein misfolding are still subject to notable improvements.

This thesis is built on the foundation of the ACH, focusing on the Aβ peptide

and its interaction partners using biophysical techniques. Prevention of

Alzheimer’s disease is a complex problem – what does studies about a small

peptide provide? It provides a small piece of a complicated problem, following

the strategy of targeting a complicated problem simply by disentangle it in

series of soluble and simple questions/solutions. Nevertheless, studies of the

Aβ peptide are not simple, and the challenges motivate scientists all over the

world.

The small piece of a complex problem is here presented as the detour of

amyloid building blocks, from the French word of détour, to perturb the

building blocks of amyloids via molecular interactions for a temporary

detained state before entering its way back to the amyloidogenic path.

However, the physiological relevance/benefits for Alzheimer’s disease

patients lie in future work. The anticipation is to provide insights into a 40 or

42 fragment peptide (one protein out of 100,000 proteins in a human cell) –

one protein that is of high importance for underlying molecular processes in

Alzheimer’s disease.

“A trophy carries dust. Memories last forever.” Mary Lou Retton

2

2. Background

The definition of rest from physics is by simple means something static that

does not change over time. In opposite, from the physiological perspective

even at rest thousands of molecular processes are running constantly. It is not

always the same ones, rather constant interchangeable processes, adapting to

the needs of the current environment. A eukaryotic cell consists of about 70%

of water, but nevertheless, the environment inside a cell is typically extremely

crowded. All is tightly organized, controlled and regulated to keep

homeostasis of a 80-400 mg/l concentrated soup of macrobiomolecules (9).

One type of biomolecules within a cell is proteins and are the most abundant

molecules other than water in biology in general (10). An average human male

body consists of about 16% of proteins. Proteins are not only limited to

“luxurious” proteins such as myosin and actin that build muscles, other

proteins maintain essential functions such as being involved in signaling,

adaptive systems, communication, energy factories, enzymes, stability and

integrity, processing of food in the digestive tract, storage, clearance,

membrane builders, defense systems, and so forth.

Proteins are beautiful structures with intriguing properties. Structure lies

within the order of the amino acids, and structure and function are tightly

intertwined. Without a proper fold the function of the protein may be

compromised. Cells are optimized to have a certain concentration of

molecules that are needed at certain times, with fast adaptation to new

stimulations/stress by external conditions. Once the systems responsible for

keeping everything in order are not functioning properly, the protein

concentration may be increased with undesirable protein accumulation.

“No one succeeds alone” is also applicable to the protein world, several

functional proteins consist of multimer structures, or requires cooperation in

tandem for work performance. Many chemical processes rely on interactions

between two or more biomolecules. In other words, it is not only limited to

proper structure and fold/function, also interactions and dynamics are

essential. A second layer of complexity comes with the thermodynamic

characteristics and affinity of those interactions and the response of such an

interaction. The dynamics of protein-protein or protein-molecule interactions

in cellular systems are complex. How does it work and how is it controlled –

to avoid unwanted association and dissociation?

“There are many hypotheses in science which are wrong. That’s perfectly

all right; they’re the aperture to finding out what’s right. Science is a self-

correcting process. To be accepted, new ideas must survive the most

rigorous standards of evidence and scrutiny.” Carl Sagan

3

2.1 Association and dissociation of biomolecules

Association and dissociation are two fundamental processes underlying

chemical reactions. Interactions and chemical processes are essential for life

– as life is known today – where systems drive for equilibrium. On the other

hand, in the scenario of total equilibrium where Gibbs free energy is zero and

no work is performed – then life does not exist. Energy barriers, gradients,

different milieus within defined compartments are giving rise to systems with

dynamic equilibria, utilizing chemical processes striving for equilibria with

equal rates of reactions forward and backwards. The equilibria may be shifted

with increased concentration of products if the reactant concentrations are

increased, according to Le Chatelier’s principle.

One of the strongest interactions without covalent binding in biological

systems is the one of biotin (vitamin B7/vitamin H) and avidin (a glycoprotein

in egg white), an interaction also utilized in molecular biology methods. This

interaction is in the order of a KD of 1.3x10-15 M and the association rate is

fast (11). The example of biotin-avidin is extraordinary, many biological

complexes forms with an association rate of <103 M-1s-1 to >109 M-1s-1 (12)

corresponding to a KD value of approximately 10-4 to10-7 M.

In a complex system such as the interior of a living cell, proteins need to

find the appropriate interacting partner among many others. Some interactions

are weak and non-specific, while other interactions are stronger and specific.

Specific, electrostatic- and hydrophobic interactions are all important. The cell

has several safeguards to keep order among all possible interactions such as

quality control systems, concentration-dependences, crowded environment,

association and dissociation rates, turnover rates (degradation) and regulated

expression/transcription/translation as well as an advanced system with feed-

back loops (13). In summary, association and dissociation of biomolecules are

essential to perform work and for life itself. What happens when processes

and systems fail to keep the balance of interactions and what are the

consequences? If not regulated it could lead to uncontrolled accumulation,

aggregation and protein misfolding (13). This will be discussed in more detail

in the next section.

2.2 Misfolding protein diseases

Many peptides and proteins share a common tendency to misfold from their

native state and self-assembly towards formation of aberrant aggregates not

applicable for proteolysis. This statement is true not only for proteins in

‘misfolding protein diseases’, but most proteins aggregate under conditions

close to extreme boundaries. Initiation of misfolding – loss of native protein

folds to incorrect folds – may originate from several causes such as inherited

genetic mutations, post-translational modification (PTMs), thermal changes,

4

translational errors, and high protein concentration (14). Protein

concentrations above the critical aggregation concentration (CAC) are

vulnerable for aggregation, and the CAC is not a static measure but rather

dependent on and influenced by environmental and experimental factors. The

fibrillization process is basically a non-equilibrium process, as the final

products are not reversible back to the initial state.

More than 30 different aggregating and amyloidogenic proteins are

associated with contribution to a broad range of human diseases. Notably,

these proteins are also expressed under normal physiological conditions,

indicating both normal and aberrant behavior. Some of the proteins are

intrinsically disordered proteins (IDPs) (15), while others are folded in their

native state. Several aggregating/misfolding proteins in this category of

proteins are disease-specific but overlap between different diseases occur.

Both IDPs and IDP-like proteins such as the Aβ peptide, Tau and α-synuclein

implicated in Alzheimer’s and Parkinson’s disease, as well as natively folded

proteins such as superoxide dismutase (SOD), lysozyme and transthyretin

(TTR) may undergo the paths of misfolding. Insulin and islet amyloid

polypeptide/amylin (IAPP) are two other protein examples related to diabetes

mellitus. “The mad cow” disease, Creutzfeldt-Jakobs disease, and Kuru

involve protein misfolding of the prion protein (PrP) – a protein that in the

native state is partially folded with unfolded regions. Up to date there is only

one disease-modifying drug available to treat TTR amyloidosis named

Tafamidis with mechanisms and mode of action described (16). There are

several well-written reviews about misfolding proteins (17–21).

Folding and unfolding of proteins are complex processes, where the

instructions of the fold lie within the amino acid sequence. Unfolded proteins

are especially vulnerable to misfolding (22, 23). One fundamental question is

what the “seed” of protein misfolding underlying pathology is, in other words

the factors initiating directed misfolding. Misfolding of proteins into stable

aggregates may follow different pathways involving on-pathway or off-

pathway structures and intermediates. Up to date the exact mechanisms of

misfolding and intermediate structures simultaneously present are not yet

elucidated. Observations from several different proteins suggest an initial

point of water-soluble monomeric structures, natively disordered or unfolded,

and a final state with insoluble and elongated stable aggregates in equilibrium

with a few percent monomeric species. The conversion from the initial state

towards the final, stable state is subject to substantial studies, and the

metastable intermediate structures have gained a large interest during the past

years because of their potential importance for disease development. This

“intermediate state” remains a black box with little information behind the

structures and precise properties. The intermediate states are heterogenous and

transient, which makes those structures a challenge to study. Recent studies

attempted to stabilize low molecular intermediate states such as dimers,

trimers, hexamers, heptamers, and octamers (24–27), by innovative

5

methodology, but the biological relevance, how they are formed, and how they

proceed along the fibrillization pathway remain elusive.

Protein misfolding is not only part of diseases, misfolded protein species

may form without any deleterious consequences. The cell has several safety

systems (28), one of them being chaperone proteins. One category of

chaperones are ATP-dependent heat shock proteins, such as Hsp70 and Hsp90

(29), that are induced during cellular stress. Other examples are the BRICHOS

domain (8, 30–32), clusterin (33, 34), and DNAJB6 (35), to name a few. As

many things, these protective systems are not improving by advanced ages,

and unnecessary stress in the upper age range should be avoided.

2.3 Neurodegeneration

Protein misfolding is a phenomenon not only limited to certain tissues,

several misfolding protein diseases, or proteinopathies, are systemic and

target the nervous system. Alzheimer’s disease, Parkinson’s disease,

amyotrophic lateral sclerosis (ALS), Huntington’s disease, and Creutzfeldt-

Jakob disease are a few examples of central nervous system (CNS)

degeneration (36). Neurodegenerative diseases involve aggregate and plaque

formation within the CNS and are irreversible and often severe, present as a

global contemporary problem both on the individual level and for the society.

Although neurodegenerative disorders differ in symptoms and progression,

some common denominators exist. They are all slowly progressive and

neuronal death and cellular inclusions are common findings. Proteins causing

amyloidosis are known to interact with different cellular constituents and

molecules (37–41).

Studying misfolding and aggregation kinetics of amyloidogenic proteins

have gained an increased interest since the recognition of this process being

part in Alzheimer’s disease and other neurodegenerative diseases.

2.3.1 Alzheimer’s disease – general description

Few things scare as much as losing memory. Alzheimer’s disease is the

most prevalent type of dementia characterized by neuronal atrophy, loss of

synaptic activity and memory impairment with a global prevalence of nearly

24-40 million people with increasing numbers (42, 43). The disease is often

mentioned as one disease, but late onset Alzheimer’s disease is rather a

trajectory of a multifaceted disease with different symptoms and progression

rates. Advanced age is one of the major risk factors (44), despite this,

Alzheimer’s disease is not part of normal ageing (45, 46). About a few

percentages of all cases are familial cases with known genetic defects with

pathogenic mutations (47, 48), whereas the rest of the cases are considered

sporadic cases. The APOε4 allele is more frequently present in both familial

6

and sporadic cases and it causes an increased risk of developing Alzheimer’s

disease by 3-4 or >10 times for one or two copies, respectively (49, 50). On

the opposite, one mutation recognized as the Icelandic mutation in the Aβ

amyloid precursor protein (AβPP) is described as protective (51, 52).

From the clinical perspective, mild cognitive impairment (MCI) and

Alzheimer’s disease are often diagnosed by memory deficiency evaluation

tests and laboratory tests. There are not yet any disease-modifying treatments

available, only about five (53) symptomatic treatments such as cholinesterase

inhibitors (54) and memantine (55). On the histopathological level, senile

plaques and neurofibrillary tangles (NFTs) are two typical features of the

disease. However, presence of senile plaques is not only limited to

Alzheimer’s disease but also to other diseases as well as in asymptomatic

people (56, 57). Instead a stronger correlation between NFTs has been noticed

in sporadic cases of Alzheimer’s disease (58). Accumulation of Aβ usually

occurs in grey matter, from the neocortex to the hippocampal area and further

brain areas (59).

2.3.2 Alzheimer’s disease – biochemical and molecular description

The Aβ peptide is the major constituent of senile plaques, whereas NFTs

or paired helical filaments consist of aggregated and hyperphosphorylated Tau

proteins. Other components of senile plaques beside Aβ peptides are other

proteins, nucleic acids, lipids and metal ions (40). Part of the laboratory test

diagnosis of Alzheimer’s disease involves increased total Tau and

phosphorylated Tau protein and changed Aβ42/Aβ40 ratio in cerebrospinal

fluids (CSF) (60, 61). The Aβ40 isoform is normally more abundant compared

to the Aβ42 variant. In Alzheimer’s disease the Aβ42 concentration decreases

compared to healthy individuals. At advanced stages the neuronal atrophy in

brains of patients is visible by structural and functional magnetic resonance

imaging (MRI), and senile plaques and NFTs are observed by

radiopharmaceuticals in positron emission tomography (PET) imaging and by

histologic markers (62). In recent years PET imaging has been shown to be an

accurate but costly tool for diagnosing patients and for following disease

progression (57, 63). Low Aβ42 levels is one typical marker for pre-clinical

stages (60). Biomarkers in CSF and blood are also used (60, 64, 65), and new

biomarkers are under constant search and development for diagnostic

certainty, such as p-Tau181 (66, 67). A decrease of the acetylcholine levels in

the brain is a common feature of the patient.

Overall, the molecular and cellular mechanisms underlying Alzheimer’s

disease are not yet known (68), but the ACH points at accumulation and

aggregation of the Aβ peptide as a primary cause or as a secondary

consequence (2, 20). Beyond the presence of Aβ peptides as the major

building block of senile plaques, a link towards the precursor protein of Aβ

with described inherently genetic mutations with associated increased risk for

7

Alzheimer’s disease are further supported by Down syndrome/Trisomi-21 (an

extra copy of chromosome 21) with similar cognitive decline at young age as

Alzheimer’s disease patients. Interestingly, like the old saying of “sleep helps

the brain clean itself”, the CSF flow during sleep contributes to a decrease in

local Aβ concentrations (69). In Alzheimer’s disease patients, biochemical

changes occur already decade(s) before onset of symptoms related to disease

pathology (70). Elucidating the molecular events preceding symptoms of the

pathology is therefore of high importance to be able to target the disease on

an early stage (71, 72). Apart from the ACH, several other hypotheses in the

field of Alzheimer’s disease have been postulated (73–75). The Tau

hypothesis (76–78) postulates hyperphosphorylation and aggregation of Tau

proteins as contributions to the pathology. Inflammation and oxidative stress

are two other major aspects of the disease, both at early stages and during

progression. In some part also related is the metal hypothesis of Alzheimer’s

disease (79, 80) originated from observed metal dyshomeostasis and senile

plaques enriched of endogenous metal ions such as copper, iron, zinc and

calcium (~mM concentration). The molecular interplay between the ACH and

loss of function and/or gain of toxicity from aggregated Tau protein (81) and

if the two proteins act in concert is still under debate (2, 76). Alzheimer’s

disease is often described with an extracellular location of senile plaques and

Tau protein NFTs with an intracellular location, however an equilibrium of

intracellular and extracellular Aβ has been proposed and observed (82, 83), as

well as propagation/spread of Tau protein (84, 85).

2.4 The Aβ peptide – Introduction to the system

The Aβ peptide, derived from two consecutive enzymatic cleavages of a

transmembrane glycoprotein named AβPP mainly located in the plasma

membrane, has been exposed to intensive research since the first description

in 1984 by Glenner and Wong (86). The Aβ peptide comes in several isoforms

ranging from 37-43 residues long, with the 40 and 42 isoforms being the most

abundant ones (87). The AβPP is constitutively and ubiquitously expressed in

neurons especially, and the Aβ peptide is not the only fragment released by

enzymatic cleavages. Potential pathways and resulting fragments are

illustrated in Figure 1. The Aβ peptide is subject to proteolysis by degrading

enzymes such as neprilysin and insulin-degrading enzyme (88). A large

proportion of released Aβ peptides are secreted to the extracellular space, but

intracellular uptake via endocytic vesicles occur. The amphipathic Aβ peptide

is predominantly present as random coil (89) or polyproline II-helical

conformation in water solution (90), determined by circular dichroism (CD)

spectroscopy and NMR chemical shifts typical for a random coil structure. In

membrane-mimicking environments the Aβ peptide adopts α-helical

secondary structures (91).

8

Figure 1. Precursor protein of the Aβ peptide – AβPP. (A) Processing of AβPP by enzymatic

cleavages by α- or β-secretase followed by γ-secretase yields the non-amyloidogenic or

amyloidogenic pathways. The Aβ peptide is released from the AβPP protein via the

amyloidogenic pathway. In (B) is the primary sequence of the Aβ peptide shown, together with

a few fundamental properties.

The native functions of AβPP and the Aβ peptide are not fully understood

but the AβPP gene family is evolutionary conserved in vertebrates (92).

Knock-outs of AβPP and the AβPP-related proteins are reported as lethal (93).

A possible role in neural growth and during development is suggested as well

as cell adhesion functioning (88, 93–97). AβPP interacts with divalent metal

ions such as copper and zinc (79, 98), and the expression levels are adopted to

meet the available metal ion concentration (99–104). In addition, AβPP also

takes part in cell adhesion and in synaptogenesis (93). The Aβ peptide is not

only associated with pathology, at low concentration it is also present during

healthy conditions. It has been proposed to be part of memory formation,

communication between neurons, long-term potentiation (LTP) in

9

hippocampus, cell survival, and synaptic processes (94–96, 105). The

neurotropic features of Aβ also includes metal chelating- and antioxidant

properties (94). To conclude, both AβPP and Aβ are reported to be important

for the neuronal function, but exactly why and how it is regulated remains to

be clarified.

The properties of the Aβ peptide contribute to a variety of possible

interaction probabilities with different molecules (40, 99, 106). The strongest

interaction measured is the one between two identical Aβ peptides (107). Two

hydrophobic segments in the primary sequence of the Aβ peptides enable both

interaction with biological membranes and inter- and intramolecular self-

interactions. Under physiological conditions the Aβ peptide concentration is

in the nanomolar range with a saturation concentration in the µmolar range

(96, 108). The N-terminal part of the Aβ peptide is hydrophilic and has three

histidine residues. Histidine residues are often involved in coordinating metal

ions via the nitrogen in the imidazole ring. The N-terminal segment is a

flexible part of the Aβ peptide, also shown as not being part of the cross-β

structure within some fibril structures (109). Despite not being incorporated

into the fibril core, the N-terminal part is suggested to be important for the

amyloid aggregation formation (110). One aspect of importance is

coordination of redox-active metal ions able to generate free radicals and

oxidative stress (111).

2.5 Amyloid and fibril formation

Self-assembly and polymerization processes (polymer from the Greek

word of polus, meaning “many, much”) are both biologically relevant, and

only sometimes associated with disease. Formation of stable and homogenous

structures as building blocks of the cytoskeleton by polymerization of

microtubules and actin is necessary to keep the architecture and functioning

of a cell. Other examples are biofilm formation in bacteria and biosynthesis of

stabilizing molecules such as cellulose and lignin in cell walls viable for plant

cells. The story of the term amyloid started already in 1842 by Matthias

Schleiden who named starch for “amyloid” (from the latin word amulum), and

in 1854 by Rudolph Virchow who studied cerebral corpora amylacea from

brain tissues (112) and named the structures “amyloid” after the Latin word

for starch. Later, it was established the structures in the brain tissues consisted

mainly of protein material.

Amyloid, amyloid-like and fibril formation via self-assembly processes are

both functional and pathological (113–115). Storage of hormones (116), stress

granules, biofilm formation (114), spider silk (115, 117), artificial scaffold

proteins, and chorion proteins constituting fish and insect egg shells (113), are

a few examples of beneficial aggregation properties. Amyloid formation is not

10

only selective for proteins in misfolding protein diseases, nearly “all” proteins

despite lack of sequence homology can aggregate and form amyloid structures

in vitro – it is only a question of experimental conditions. The steps from

monomeric and soluble protein species into insoluble amyloids are not

understood in molecular detail but the field is moving forward (17, 53, 118,

119). In terms of linear aggregation, the increase of insoluble amyloid

materials may originate from two processes; increased concentration of

aggregate number and/or increased concentration of fibril mass (119).

2.5.1 The cross-β structure

The amyloid motif consists of an insoluble and stable cross-β structure (17)

(Figure 2).The cross-β includes β-sheets structures aligned in parallel and

packed as repeating units perpendicular to the fibril axis to an elongated fibril

(120), and is characteristically recognized with a typical birefringence pattern

in polarized light (apple green) once stained with Congo red (121). There are

several protein fibrils with cross-β structures and filaments presented and

visualized by different methodologies, such as fiber diffraction, X-ray

crystallography, cryo electron microscopy (cryo-EM) and solid-state NMR

(122–129).

Figure 2. Aβ amyloid and Tau paired helical filament structures. (A) Cross-β structure of

Aβ42 fibril from solid-state NMR studies, PDB ID 2NAO (124). (B) Amyloid Aβ40 fibril NMR

structure from an Alzheimer’s disease patient, PDB ID 2M4J (128). (C) Cross-section of an in

vitro formed Aβ fibril determined by cryo-EM, PDB ID 5AEF (123). (D) Aβ42 fibril from solid-

state NMR studies with two hydrophobic cores of dimer structures, PDB ID 5KK3 (129). (E)

Structure of paired helical Tau filaments determined by cryo-EM, PDB ID 5O3L (127).

11

Mature amyloid fibrils usually have a diameter in the range of 2-20 nm and

lengths to several micrometer (121). Interestingly, all structures are not

identical. Differences exist between different protein isoforms, mutations,

variable experimental conditions, in vitro vs samples from patients, and

differences between different patients (128). The polymorphic behavior with

different inter-residue interactions may reflect the heterogeneous aggregation

pattern of these proteins, easily perturbed by changes in the reaction volume.

In general, Aβ fibril structures have a hydrophobic core stabilized by strong

inter-strand backbone hydrogen bonds and intramolecular hydrogen bonds.

Other interactions contribute to the amyloid fibril as well, such as side chain

interactions, electrostatic interactions, van der Waals interactions, pi-stacking

and hydrophobic interactions (121).

2.5.2 Aggregation versus amyloid fibrillization

The self-assembly and amyloid formation processes are chemical reactions

like crystallization of solutes, forming new aggregates by nucleation or

fragmentation processes. The amyloid-state is often referred to as an

additional phase with high thermodynamic stability, distinguishable from the

crystalline and glass transition state. A sample of amyloid fibrils is easily

described as gel-like. The reaction and the rate of the self-assembly reaction

is dependent on solubility and concentration, and supersaturated conditions

are usually used in in vitro kinetics studies. Co-precipitates, such as salts,

detergents, membranes, etc. also affect the amyloid formation (130–133). It is

important to distinguish aggregation from amyloid fibril formation. Amyloid

fibril formation results in crystalline, stable amyloid structures, whereas

aggregation in general can include fibrillization, precipitation and formation

of amorphous aggregates. Proteins able to form amyloid structures both in

vitro and in vivo can also under certain conditions, such as very rapid

association, form amorphous aggregates, a process dependent on co-

precipitants. Eventually amorphous aggregates may form amyloid fibrils over

time. On the contrary, in the absence of any trace metal ions or buffer (ionic

strength), amyloid formation is seldom present (134). Precipitation of proteins

by salt additions is not surprising since the solubility of proteins is limited

under certain ionic strengths, and this phenomenon is extensively used in

practice to “salt out” proteins during i.e. protein purification. Liquid-liquid

phase separation (LLPS) has obtained an increased research interest in terms

of amyloid and neurodegeneration with interesting features both in vitro and

in cells (135–137).

2.5.3 Amyloid formation from monomers via intermediate structures

The aggregation and self-assembly of the Aβ peptide are usually described

as a nucleation-dependent process with distinct amyloid on-pathway or off-

12

pathway intermediates. Whereas the characteristics of the structures at the

start and the end of the amyloid fibrillization pathway are well described (89,

138–140), the intermediate states are poorly defined. The definition of the

intermediate structures varies greatly in literature in terms of the

characteristics (size, structure, formation) and names. Oligomers and

protofibrils are the most common terms. Low-molecular weight oligomers

and high-molecular weight oligomers are sub-groups often used, based on the

molecular mass. Globular amyloid oligomers (gOs), highly curvilinear

fibrils/protofibrils (CFs), and rigid fibrils (RF) are other commonly used

nomenclature (141). Usage of different definitions and variable nomenclatures

by different research groups is a limitation of the research field. In this thesis

oligomers are referred to having a size of 2-100 monomers, whereas

protofibrils are larger than oligomers but smaller than long (micrometer,

diameter of 5-15 nm) fibrils. Despite the large interest of amyloid oligomeric

structures and a few ones (stabilized in vitro) structurally described (24–27,

142), the transition process from oligomeric species into protofibrils and

fibrils is scarcely well known. In one study oligomers with fibrillar structures

(fragments of fibrils?) correlated with Alzheimer’s disease, whereas

oligomers with non-fibrillar structures did not (143).

2.5.4 Are amyloid-forming proteins toxic?

Mechanistic details of amyloid toxicity are still scarce but many attempts

to link amyloid formation to cytotoxicity (41, 144) and to capture the toxic

response of amyloids in vivo have extensively been tried. Transgenic mice for

modeling Alzheimer’s disease are often not suitable/optimal to capture human

pathology (59, 145–147). However, innovative model systems such as

induced pluripotent stem cells (iPSCs) as 3D models derived from fibroblast

donations from patients and controls differentiated to the cell type of interest

with preserved age are under development (148–152). Early formed pre-

fibrillar aggregates are suggested as the most toxic species (145, 153, 154),

whereas fibril surfaces function as catalytic sites for new aggregates.

In terms of cytotoxicity for any toxicant or toxin, the origin of the observed

effects may be considered as gain-of-toxicity or loss-of-function. Both

induced toxicity (155, 156) and loss of function have been hypothesized (157,

158). The mechanisms of toxicity may also be specific or non-specific. The

physiological function of native Aβ peptides is not yet well known (section

2.4), but Aβ has been proposed as an endogenous antimicrobial peptide

(AMP) in comparison with the human cathelicidin LL-37 (159–163). The

AMP properties of the Aβ peptide is a shared feature with α-synuclein

associated with Parkinson’s disease (164). Cytotoxicity in relation to the Aβ

peptide is a complex question, especially when considering all secondary

effects (165, 166). Several toxicity paths connected to Aβ aggregation and

amyloid formation studied in several model systems have been proposed (17,

13

59, 145, 167, 168). Both interference and disruption of vital cellular functions

and induced toxicity have been suggested. More precise suggestions involve

mitochondrial dysfunction, interference with calcium homeostasis, perturbed

cell membrane integrity, affected lipid and membrane composition, disruption

of synaptic plasticity, inhibition of LTP, dysfunctional interactions with

neuronal receptors and other proteins, excitotoxicity, pore formation,

oxidative stress via reactive oxygen species (ROS) formation, inflammation,

lipid peroxidation, and induced apoptosis (24, 25, 88, 146, 166, 169–178). The

Aβ peptide toxicity is also dependent on several other factors according to a

few studies, such as APOε4, cholesterol, mitochondrial network and clusterin

(145, 179–186).

The toxic origins of amyloid formation described in the previous section

are under debate and widely discussed (154). Toxicity studies are complex,

and the dose makes the poison as according to Paracelsus. Toxicity

determination of potential toxic species should be used with caution, as

different end-points of toxicity in different studies are often used, and

overexpression and physiologically irrelevant (high) concentrations of the

proposed toxicant to induce measurable end-points might not reflect

pathological relevant events. On the other hand, detailed studies of antibodies

in clinical trials showed an in vivo effect reflected in oligomeric species in

vitro (187).

Oligomeric structures with β-barrel pore-resembling structures have been

described as well as larger assemblies with different properties (24–26, 115,

174). A large extent of the focus lies on oligomers with β-structures, whereas

the β-content has not been correlated to toxicity (171) and early oligomeric

structures have also been proposed to consist of α-structures (188). An

interesting aspect discussed in a review of Eisele and Duyckaert is potential

effects due to diffusion and spread of soluble oligomers versus insoluble

oligomers, where the insoluble and diffusible oligomeric fraction may be the

harmful one (59). Protein aggregation overload is another aspect of

uncontrolled events with accompanying cell toxicity (81). Further, upstream

effects of Tau protein by gingipains originated from the bacterium

Porphyromonas gingivalis is another subject of interest in Alzheimer’s

disease (189).

2.5.5 Amyloid fibrillization kinetics

The fundamental processes underlying polymerization/fibrillization and

filamentous growth are a combination of contributing processes (Figure 3)

such as nucleation processes (primary and secondary), fragmentation, growth

processes and dissociation processes (121, 190). Fragmentation of existing

fibrils may be introduced to the system by shaking or stirring conditions, or

simple from brittle fibrils breaking apart. Further, fragmentation is one of the

main processes underlying growth of prion amyloid aggregates (191). Primary

14

nucleation describes a simple polymerization process, where nuclei of two or

more monomers are formed with a higher association rate compared to the

dissociation rate. In contrast, the dominating process underlying Aβ peptide

fibrillization is related to monomer-dependent secondary nucleation process

(192, 193). Secondary nucleation includes catalysis of new aggregates via the

surface of existing fibrils or other surfaces (194). How the surface contributes

to facilitated nucleation remains to be elucidated in full detail, but a role as a

template or simply as a convenient meeting point for monomers has been

suggested. The dissociation processes are usually described as negligible at

the end of the fibrillization reaction, with an irreversible fibril state. The

processes leading to an increase of fibril mass concentration during

aggregation are mainly attributed to elongation processes (190). Growth of

the Aβ fibril mass by addition of soluble and unstructured Aβ monomers to

existing fibril ends is proposed by a dock-and-lock event, where soluble

monomers binds to the fibril end and adopt to the conformation required for

incorporation into the fibril in a two-step process (195–199).

To obtain more information about the aggregation/fibrillization of proteins

one strategy is to measure aggregate mass concentration as a function of time

(119). The outcome and quality of such an experiment and resulting data is

Figure 3. Aggregation kinetics experiments. (A) Macroscopic, bulk experiments following a

phenomenological sigmoidal behavior. Amyloid formation can be measured by a reporter dye

recognizing amyloid structures. The lag phase is followed by the growth- and the saturation

phase. During the lag phase the detection limit of small multimers and initial growth is not

sensitive enough to capture those events. (B) Microscopic rate processes are distinguishably

from the bulk experiments by global fit analysis with an integrated rate law (119, 192, 200).

15

highly dependent on the starting point/material, and it is crucial to control the

starting material as careful and as accurate as possible. Different suitable

techniques are available, and different methods (at least two) for validation of

the results are recommended. The chosen technique should report linearly of

the aggregate/fibril mass for proper investigation (201). Circular dichroism

(CD) and amyloid-reporting fluorescent dyes (such as Thioflavin T (ThT)

(202, 203) and pentameric formyl thiophene acetic acid (pFTAA) (204)) are

two biophysical methods commonly used to measure amyloid formation as a

function of time. ThT should not be confused with related Thioflavin S (ThS)

molecules often used to stain biological materials for amyloid.

Here I will focus on the usage of amyloid dyes for monitoring the

fibrillization and to follow the aggregate mass concentration over time. A fast

and simple amyloid kinetics analysis consists of phenomenological models

such as sigmoidal curve fitting of bulk experiments with ThT/pFTAA

fluorescence intensity measured over time to obtain phenomenological

parameters. This type of analysis gives information of the evaluated kinetic

curves for parameters that describe the curves as such, like aggregation

halftime τ½, aggregation lag time, maximum growth rate, and end-point

fluorescence intensity – but it gives no further information about the

mechanisms behind the observations. A typical resulting sigmoidal kinetic

trace shows a reasonable stable lag phase, but below the detection limit many

molecular reactions are taking place (205). The lag phase is not only a

“transportation phase”. Several molecular events are taking place not captured

by typical bulk ThT/pFTAA fluorescence experiments. Single molecule

techniques may be more successful. It was recently reported that about 60

monomers in an Aβ multimer was necessary for ThT-activity detected in

fluorescence correlation spectroscopy (FCS) experiments (206). In recent years

several mathematical models have been developed to describe the protein

aggregation/fibrillization kinetics in mechanistic detail (119, 192, 193, 207–

209) facilitating usage of bulk experiments to obtain information about the

microscopic rate processes of primary (kn) and secondary nucleation (k2),

elongation (k+) and fragmentation (k-) (Figure 3 and 4). These models use rate

laws to describe the chemical processes underlying fibrillization, and by

taking all necessary events (reasonable number of events – still a simplified

model of the observable) into account such as the concentrations of the

reactants and products, an integrated rate law, or the Master equation, can be

derived (118, 121, 193). Perturbation of the system by varying the

experimental conditions such as concentration or by modulators gives a tool

to study and elucidate the mechanisms behind the fibrillization process. Rome

was not built in one day, likewise mechanistic information about protein

fibrillization is not performed in one hand turn. With the limitations of a

model, especially with the corresponding simplifications for a complex

process such as protein aggregation, the quality and quantity of the data is

extremely important, as well as a careful global fit analysis. On the other hand,

16

if successful, the global fit analysis allows determination of the microscopic

rate constants giving rise to fibrillization as well as physical properties of the

system (201).

Figure 4. Fit of microscopic rate constants for the processes of primary nucleation (kn),

secondary nucleation (k2), and elongation (k+) from the influence of an aggregation inhibitor

visualized as the nucleation dependence. The fit/modeling of the kinetic equations was

performed in Amylofit online software (201).

Even more mechanistic information about the monomer-dependence and

the reaction order of the fibrillization/nucleation process can be obtained using

the scaling component and the mechanisms behind explaining the observables

(119). The scaling component, γ, is obtained by a double logarithmic plot of

τ½ versus the initial monomeric concentration, where a linear relationship

reveals a slope equivalent to the γ-value. The scaling component is related to

the reaction orders (201) and connects the macroscopic behavior observed in

bulk experiments to the microscopic processes and helps the choice of suitable

models for a deeper analysis of the data (121, 201).

The Aβ peptide aggregation behavior in bulk fluorescence experiments

differs depending on the length of the peptide. Compared to the Aβ40 peptide,

Aβ42 is the more aggregation-prone one and only a tenth of the concentration

is needed for fibrillization compared to the Aβ40 variant. On the microscopic

level, for both peptide isoforms, the dominating processes underlying

fibrillization are secondary nucleation processes. There is a large body of

studies investigating the scaling component for the Aβ40 and Aβ42 peptides

(190, 192) and it is slightly different. However, the differences (bulk) have

also been described as reduced rate constants in general for Aβ40, and Aβ42 is

not dependent on the monomer concentration for secondary nucleation

processes to the same extent as Aβ40 (192). The dissociation rate of monomers

from protofibrils, a slow process, have been reported to be very similar for the

both Aβ peptide isoforms (210). Co-incubational studies with both Aβ40 and

that Aβ42 have also been performed (61, 192, 211).

17

2.5.6 Modulation of protein aggregation

Many factors affect the Aβ fibrillization processes. Variation of the

experimental conditions such as pH, ionic strength, temperature, viscosity,

molecular crowders, lipids, membrane mimetics, type of experimental tubes,

small molecules, shaking conditions, other proteins, organic compounds, and

Aβ local concentration may influence the aggregation. In a recent paper the

influence of CSF on the Aβ aggregation kinetics was showed (212). The net

negative charge of Aβ contributes to electrostatic repulsion between

monomers which in turn make the peptides less aggregation-prone (213).

Modulation of the fibrillization by organic or inorganic compounds (214, 215)

such as curcumin (216), EGCG (217), metal ions (218), lipids (219), many

organic compounds as metal chelators (220, 221), other FDA-approved drugs

(222), β-sheet breakers (223), molecular tweezers, or Pt-based compounds

(224, 225) has been extensively studied (39). Modulation of the Aβ amyloid

aggregation kinetics by other proteins, such as chaperones, has also been

studied (30, 31, 34, 35, 118, 226), as well as co-aggregation of two different

amyloidogenic proteins (192, 227–232). The aggregation modulation can take

place at different stages of the process, by induction of off-pathway structures

or by interactions with monomers or with nuclei (kinetic intermediates) and

fibrils. Interactions with monomers influence the available pool of

aggregation-competent units. Coating of fibrillar surfaces by other proteins,

such as the BRICHOS domain, efficiently attenuate secondary nucleation

processes (31). Amyloid aggregation is partly driven by hydrophobic

interactions. Small perturbations of the system may give rise to large effects

in bulk experiments. Modulation of the aggregation kinetics both gives a tool

for therapeutic strategies and a tool to gain more knowledge about the

underlying fibrillization system by perturbing it. Noteworthy, assumptions

based on whether the modulator concentration is decreased (consumed) over

the aggregation time or not needs to be considered. Dual effects, such as

observed changed aggregation kinetics in vitro and improved cognitive

functions in clinical trials, should not be ignored.

2.6 What this thesis is about

An increased understanding of the underlying processes of protein

misfolding is central for medicine, material sciences and life sciences. This

work is mainly built on pure biophysical strategies to understand Aβ

aggregation and the interactions underlying the aggregation processes – how

soluble peptide monomers aggregate into highly ordered structures and how

this process can be modulated to take a detour from the fibrillization pathway

by perturbational effects by metal ions and interacting molecules (Figure 5).

18

Copper-, zinc, and iron ion interactions with the Aβ peptide are not new to

the field, rather the opposite – the Aβ peptide has been suggested to act as a

weak metal chelator. Here we studied about 27 different metal ions to gain

more information about the metal binding. In chapter 5 innovative peptide

constructs were used to perturb the Aβ fibrillization, and the biophysical in

vitro studies were moved into cell studies as well. In the last part, chapter 6,

the interplay between two proteins implicated in Alzheimer’s disease (Aβ and

Tau) was studied in vitro to provide new information about an interaction

previously suggested from cellular and animal model studies. The choice of

aggregation modulators was based on curiosity, the grade of modulating

effects, and from ideas based on potential biological implications. We were

both inspired by molecules with relationships to biological systems/diseases

and of modulators providing information of amyloid aggregation per se.

Figure 5. Overview of the thesis. The thesis consists of two main topics, molecular interactions

with monomeric Aβ peptides and modulation of the Aβ peptide aggregation behavior. These

two topics are both separated and intertwined.

2.7 Aim

Enormous efforts are put into research about misfolding protein diseases

from several perspectives and interdisciplinary fields, but the biochemistry

about these molecular processes are not yet elucidated. This thesis aims to

contribute with further insights into the underlying Aβ peptide fibrillization

processes probed by metal ions, designed peptide constructs and Tau protein.

The overall aim is to understand the Aβ peptide’s molecular properties and

interactions and how these interactions affect the Aβ’s aggregation behavior.

“It isn’t the mountains ahead to climb that wear you out; it’s the pebble in your

shoe.” Muhammed Ali

19

3. Materials and Experimental techniques

The heart of a scientific paper is often referred to the methodology – a

paper/conclusion is not better than the weakest link. In this section commonly

used biophysical techniques to study conformational changes, interactions and

other perturbations included in this thesis work are briefly described.

3.1 Sample preparation

One important difference between ‘normal’ and amyloid aggregation prone

proteins such as the Aβ peptide is that they instantly start to self-assemble during

physiological conditions at concentrations frequently used for biophysical

measurements. These features together with heterogenous mixtures of protein

assemblies make it a challenge to study Aβ aggregation in a reproducible way,

especially to understand the kinetics of amyloidogenesis and to characterize the

kinetic intermediates. In order to study how Tau protein, designed peptide

constructs, and metal ions affect the Aβ peptide and the aggregation kinetics the

Aβ composition/aggregation state must be well distinguished in the experimental

setup. A sample of Aβ peptides in buffer solution is a heterogeneous mixture with

a stochastic nature of aggregation, especially at concentrations reaching the lower

range for the critical CAC, and during the aggregation a distribution of many

different structures eventually forming stable amyloid fibrils is present. In this

section sample preparation is presented as protein sample preparation for

experiments with already expressed and purified proteins. Optimization and good

quality protein expression systems for amyloidogenic proteins are not part of this

thesis, but in literature are several examples of such (233–235).

One strategy for reproducible experiments is to take control over the initial

state of the system as far as possible. This can be achieved by various approaches,

such as additional protein purification to remove pre-formed aggregates (130).

One approach is schematically presented in Figure 6. To begin with, buffers, co-

precipitants and reagents need to be filtered before any use in experiments. In

addition, unnecessary air-water interfaces and low-binding surfaces are avoided

by using degassed buffers (130). Low-adhesive and metal-free tubes are

recommended for the protein samples. Commercially available proteins are often

offered both as recombinant proteins and as synthetic proteins. The cost may be

higher for the recombinant proteins but are more accurate in terms of amino acid

“Great things are not done by impulse, but by a series of small things brought

together.” Vincent van Gogh

“In theory, there is no difference between theory and practice. But in practice,

there is”. Manfred Eigen

20

composition and length. Important to keep in mind are the batch variation

possibilities. The choice of buffer may vary depending on the experimental setup

and the technique, further considerations involve suitable pH range, non-

significant metal ion-buffer interactions, and compatibility with the method.

Usage of a metal chelator for studies in the absence of metal ions is recommended

due to the strong effect of metal ions on the aggregation kinetics. Notably, when

metal ion interactions are the focus of the study, the metal ion solution may also

be sensitive to buffer conditions and pH. Due to the aggregation propensity of Aβ

peptides, lyophilized peptide powders are preferably dissolved at high pH (10 mM

NaOH) or in an organic solvent such as Hexafluoroisopropanol (HFIP), Dimethyl

sulfoxide (DMSO), or Guanidine hydrochloric acid (GuHCl). Organic solvents

need to be removed before kinetic experiments, by gel filtration or evaporation,

but low concentrations of DMSO (a few v/v %) may be used in kinetics

experiments without any significant effects on the bulk experiment. Sonication of

the protein in an ice-water bath for a couple of minutes (at least ~3 minutes)

reduces the amount of pre-existing aggregates. Protein samples for experiments

extra sensitive of the presence of pre-existing aggregates, such as aggregation

kinetic experiments, need to be purified one step further.

3.1.1 Sample preparation for aggregation kinetics experiments

In this section a generally used approach is briefly presented (Figure 6). The

purpose of this step is to remove pre-formed aggregates to obtain good-quality

samples for aggregation kinetics experiments:

- A high purity recombinant protein sample with a ~2 mg/ml concentration is dissolved

in 6 M GuHCl and applied with a disposable syringe to a pre-equilibrated gel filtration

column with a suitable running buffer for size exclusion chromatography (SEC) (i. e

Superdex 75 10/300GL).

- One column volume takes about 50 minutes (0.5 ml/min flow-rate), with sufficient

separation for one peak with aggregated peptides and one peak corresponding to

principally monomeric peptides (marked with a dashed circle in the chromatogram in

Figure 6). The aliquots of purified proteins (filtrate) should directly be put on ice if

the gel filtration is performed in room temperature.

- The Aβ peptide has one Y10 residue, that may be used for protein concentration

determination by absorbance spectroscopy with an extinction coefficient of 1424 M-

1cm-1. The apparent “free” protein concentration with several different equilibrium

may affect the measured value. Once the concentration of the monomeric aliquots is

measured, the sample can be used directly for kinetic experiments (preferable). Long

storage times, i.e. to the next day or several days, may be done at +4 °C or -20 °C,

respectively, but the quality of the sample may be compromised.

This step in the sample preparation for aggregation kinetics experiments takes

time and with the cost of protein losses. However, this step is highly valuable in

21

Figure 6. Aβ sample preparation to avoid/reduce the number of pre-formed aggregates in

monomeric Aβ samples for NMR and fibrillization kinetics experiments. The pre-formed

aggregates and monomeric peptide visualized in the figure are derived from the protein data

bank with PDB ID 2BEG, 2M4J, 5AEF, and 2M9S. The images are not to scale. The fluorescence

correlation spectroscopy (FCS) results are subject for future publication (Mörman, Jarvet).

order to be able to control the initial state before an aggregation kinetic

experiments starts, for more reproducible and accurate measurements. A

significant proportion of aggregated peptides in the sample is clearly removed by

the SEC procedure. We measured the ThT-activity by FCS of samples obtained

at different time points during the SEC (Figure 6). The running buffer did not

contain any detectable ThT-active structures. A sample from the “aggregated

22

peak”, the peak prior the “monomeric peak”, did however show a high number of

fluorescence intensity fluctuations (counts) corresponding to the presence of

aggregates. In contrast, measurements of the “monomeric peak” did not show as

many fluorescence intensity fluctuations, but interestingly still some counts

indicative of a few structural assemblies with ThT-activity were present. Previous

studies reported the smallest unit of Aβ multimers with ThT-activity as an

aggregate of around 60 monomers (206). A CD spectrum of the “monomeric

peak” shows typical random coil secondary structures, which is in line with most

of the peptides being unstructured (Figure 6). However, the monomeric sample

obtained after the SEC is in equilibrium with multimers with a few structures that

are still ThT-active.

A common tool to distinguish between primary and secondary nucleation

processes (see section 2.5.5) is to add pre-formed seeds to the reaction volume

with monomeric protein and different concentrations of an aggregation modulator

at time zero. One way to generate seeds for seeding experiments include

suspension of fibrils and sonication for a few minutes in an ice bath. Regarding

the concentration of fibrils, one common way is to estimate the seed concentration

based on the initial monomeric concentration. One important aspect regarding

seeds is to avoid usage of old seeds. The concentration of seeds can be varied

depending on the questions to be addressed. A low seeds concentration is useful

to be able to conclude which one of the primary or secondary nucleation processes

that is the dominating process, whereas a high seeds concentration (giving a

concave shape instead of a sigmoidal curve) can be used for direct estimation of

the elongation rate constant. The concentrations can vary between different

experimental setups. For seeding experiments, it is important to use one stock

solution of seeds that are distributed to all different conditions on the same plate

for a fair comparison. Since the kinetics are faster in the presence of seeds, it is

usually a good idea to measure data points more frequently. Different techniques

to monitor aggregation kinetics are further presented in section 3.2.1 and 3.2.2.2.

3.2 Spectroscopy

Spectroscopy is the study of interactions between electromagnetic radiation

and matter. Here some of the methods used in the thesis are briefly described.

3.2.1 Circular dichroism

The secondary and tertiary structure is an important feature of a protein, and

for aggregation-prone amyloidogenic proteins with a transition from one

conformation to another such information is crucial. Information about the

secondary structure content is easily obtained from circular dichroism (CD)

spectroscopy. CD is a fast and practical optical method. It is an ideal technique to

23

measure structural changes upon interactions, denaturing conditions, and changes

in pH, temperature, salt concentration, and more.

Many biomolecules are optically active. CD utilizes the property of chirality

both regarding the molecule and to circularly polarized light. Chiral molecules

interact and absorb left- and right circular polarized light to different extents. The

ΔA=AL-AR difference spectrum consist of a pattern of characteristic structural

features with both positive and negative bands possible. ΔA is often expressed as

ellipticity, [θ]. For historical reasons θ=32.98ΔA. CD data is often presented as

mean residual molar ellipticity ([θ]MRME) with units of deg cm2/dmol for a direct

comparison of different samples regardless of concentration or size (236). For

protein studies the far-UV region from ~180 to 260 nm is commonly used with

the origin of the CD signal mainly by the peptide bond (237). The π-π* and n-π*

transitions give typical bands at 190 and 210-220 nm, respectively (238). Typical

CD spectra of secondary structures (random coil and β-structures) in proteins are

shown in Figure 6. Spectral changes for longer wavelengths around 260-320 nm

also occur for side chains of aromatic residues and disulphide bonds. Comparison

with known structural spectra can easily be performed by using online software

to calculate the percentage of i.e. α-helical content (239). The α-helical content is

also easily derived by Eq. 1 (240).

𝛂 − 𝐡𝐞𝐥𝐢𝐜𝐚𝐥 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 [%] = (𝛉𝟐𝟐𝟐 𝐧𝐦,𝐫𝐚𝐧𝐝𝐨𝐦 𝐜𝐨𝐢𝐥 − 𝛉𝟐𝟐𝟐 𝐧𝐦,𝐨𝐛𝐬𝐞𝐫𝐯𝐞𝐝

𝛉𝟐𝟐𝟐 𝐧𝐦,𝐫𝐚𝐧𝐝𝐨𝐦 𝐜𝐨𝐢𝐥 − 𝛉𝟐𝟐𝟐 𝐧𝐦,𝛂−𝐡𝐞𝐥𝐢𝐱) ∗ 𝟏𝟎𝟎 (Eq. 1)

where (θ222 nm, random coil) is the average ellipticity for random coil structures in values of 3900

deg cm2/dmol and the average ellipticity for α-helices is -35700 deg cm2/dmol (θ222 nm, α-helix).

3.2.2 Fluorescence

A common phenomenon used in a wide range of applications is fluorescence.

Fluorescence is one type of luminescence, another example of luminescence is

bioluminescence (sea-fire, luciferase in fireflies). Fluorescence is the name of the

relaxation process back to the singlet ground state (S0) from an excited electronic

state (often S1) via emission of a photon. The excited state is reached by

absorption (excitation, 10-15 s) and internal conversion of a photon matching the

energy between two energy levels. A fluorophore is a molecule/substance and

chemical sensor with the property of absorbing light at a certain energy

(wavelength) and emit a photon (fluorescence), often with a conjugated π-system.

In protein chemistry, the aromatic residues tryptophan, tyrosine and phenylalanine

are present as intrinsic fluorophores. Tryptophan and tyrosine are the ones mostly

used for biochemical experiments. Extrinsic fluorophores may also be used, by

labeling the protein of interest at a suitable place. Fluorescence measurements of

a fluorophore is highly sensitive and specific, detecting only the fluorescence of

interest, despite a potential large number of molecules absorbing light at the

excitation wavelength. In addition, the fluorophore is sensitive to the local

24

environment, providing a tool for studying protein conformation, folding,

misfolding, ligand binding, detection of localization etc. The quantum yield is the

ratio of the number of emitted photons and the number of absorbed photons by

the fluorophore, and it is temperature-dependent.

3.2.2.1 Interactions studies

Relaxation as fluorescence is a spontaneous emission, competing with other

processes (non-radiative). One of the competing processes is fluorescence

quenching evolved from collision of the fluorophore, energy transfer,

rearrangements, excited state or ground state reactions, or complex formation. The

Aβ peptide has one tyrosine residue, Y10, and the intrinsic fluorescence may be

used to study interactions with the Aβ peptide. Copper ions, Cu2+, are known

fluorescence quenchers (241) and the Cu2+-dependent quenching can be used to

study the interaction of the Aβ peptide with copper ions. The mechanism behind

the fluorescence quenching of copper ions is not yet fully understood. The degree

of Y10 fluorescence quenching upon titration with copper ions can be plotted

against the [Cu], revealing a titration curve amenable for curve fitting with Eq. 2

for a 1:1 binding model (242) to determine the dissociation constant of the Cu:Aβ

complex. In addition, studies of competitive binding with other metal ions without

fluorescence quenching properties are also possible.

𝐈 = 𝐈𝟎 +𝐈∞−𝐈𝟎

𝟐∙[𝐀𝛃]∙ (𝐊𝐃

𝐚𝐩𝐩+ [𝐂𝐮] + [𝐀𝛃] − √(𝐊𝐃

𝐚𝐩𝐩+ [𝐂𝐮] + [𝐀𝛃])

𝟐− 𝟒 ∙ [𝐂𝐮] ∙ [𝐀𝛃]) (Eq. 2)

where I∞ is the intensity upon saturation of Cu2+ ions, I0 the initial intensity in the absence

of Cu2+ ions, and KD is the apparent dissociation constant.

3.2.2.2 Fibrillization studies

The fluorescence phenomenon is utilized in amyloid aggregation kinetics

experiments with extrinsic fluorophores recognizing amyloid structures.

Commonly used dyes as probes for amyloid material are Congo red, Thioflavin S

(ThS), Thioflavin T (ThT) (202, 203, 243, 244), and the luminescent conjugated

oligothiophene pentameric formyl thiophene acetic acid (pFTAA) (204). ThT (λex

440 nm and λem around 480 nm) is a benzothiazole salt, a planar aromatic dye

molecule that is highly flexible in solution where no fluorescence is detected due

to relaxation processes of rotation. Once bound to amyloid material, the C-C bond

is not as flexible anymore, and perhaps in combination with an increased

hydrophobic environment, the fluorescence quantum yield increases to a high

extent with emission at around 480 nm due to a bathochromic shift of the

absorbance (245). Another probe, not as commonly used yet as ThT, is the

pFTAA molecule (204) (λex 480 nm and λem around 520 nm) recognizing amyloid

material, also with resulting emission fluorescence intensity changes from a

restricted conformation upon binding to amyloid material (246). A comparison

between ThT and pFTAA is shown in Figure 7. A similar binding site for pFTAA

as for Congo red has been reported (246). In Paper I (supporting information,

25

Figure S2) the pFTAA influence on the Aβ aggregation kinetics was monitored,

revealing no significant effect by the probe itself. However, another study

reported changed fibril properties in the presence of higher concentrations of

pFTAA (247).

Figure 7. Comparison of Thioflavin T (ThT) and pentameric formyl thiophene acetic acid

(pFTAA) in fibrillization kinetics experiments. 5 μM Aβ42 in 10 mM MOPS buffer pH 7.2

supplemented with 10 μM ThT or 0.3 μM pFTAA were used. The molecular structures for ThT

(blue) and pFTAA (green) are shown in the right panel.

Both ThT and pFTAA may be used as probes to follow the amount of fibril

mass formed over time. Such kinetics curves can be analyzed with

phenomenological models, such as sigmoidal curve fitting, with Eq. 3 (248, 249).

𝐅(𝐭) = 𝐅𝟎 +𝐀

𝟏+𝐞𝐱𝐩 [𝐫𝐦𝐚𝐱(𝛕½−𝐭)] (Eq. 3)

where F0 is the fluorescence baseline, A the amplitude of the kinetic curve, rmax is the growth

rate in h-1 and the aggregation halftime is denoted τ½ in units of h.

A more robust analysis of bulk experiments with parameters of biological

meaning may be performed by a Master equation, an integrated rate law

describing the evolution of fibril mass concentration by involved reaction rates

(201, 207) (theoretical description of the approach is presented in section 2.5.5).

This approach provides a tool to elucidate mechanistic information from

aggregation kinetic curves. Back in time, Copernicus once said “Mathematics is

written for mathematicians”, and luckily an online software with a user-friendly

interface was developed by the lab of Knowles, Cambridge, UK (201). The Master

equation is described as below, Eq. 4 (18, 118, 192, 193, 200, 207, 208, 250).

𝐌(𝐭)

𝐌(∞)= 𝟏 − (

𝑩+ + 𝑪+

𝑩+ + 𝑪+ 𝒆𝜿𝒕 𝑩− + 𝑪+ 𝒆𝜿𝒕

𝑩− + 𝑪+)

𝒌∞𝟐

𝜿𝒌∞𝒆−𝒌∞𝒕 (Eq. 4)

where 𝜅 = √2𝑘2𝑘+𝑚(0)𝑛2+1 (or 𝑘2 = 𝑘− when n2=0) secondary nucleation

𝜆 = √2𝑘𝑛𝑘+𝑚(0)𝑛𝑐 primary nucleation

𝐵± =(𝑘∞±�̃�∞)

(2𝜅) , 𝐶± = ±

𝜆2

(2𝜅2) ,

𝑘∞ = √2𝜅2/[𝑛2(𝑛2 + 1)] + 2𝜆2/𝑛𝑐 , �̃�∞ = √𝑘∞2 − 4 𝐶+ 𝐶− 𝜅2

26

3.2.3 UV/Vis spectroscopy

Many biomolecules do not absorb light in the visible region but absorb light in

the UV region. This property is utilized for protein concentration determination,

by aromatic residues (Trp, Tyr) around 280 nm, DNA at 260 nm and peptide

bonds at around 214 nm. Some molecules, like ThT described in section 3.2.2.2

commonly used for detection of amyloidogenic material, they do absorb light in

the visible region and this property is useful for accurate concentration

determination. Formation of H2O2 was measured in Paper IV by a biochemical

assay using 5,5-dithio-bis-(2-nitrobenzoic acid) (DTNB) and UV/Vis spectroscopy.

3.2.4 Nuclear magnetic resonance

Nuclear magnetic resonance (NMR) spectroscopy is an excellent method to

study biomolecules in liquid solution alike the natural environment with a broad

range of applications such as for structural information, substance identification,

inter- and intramolecular interactions, and one of the strengths of the method – to

study dynamic processes (251) at equilibrium at several different timescales

(Figure 8). Another strength of the method is the possibility to study weak inter-

molecular interactions. NMR provides high resolution information at the atomic

level with the cost of low sensitivity due to a low energy difference between the

ground state and the first excited state – connected to disadvantages of high

amounts of materials needed and size limitation towards larger proteins, with low

tumbling rate leading to line broadening and spectral overlaps. In NMR spectra,

depending on the population/exchange rates, it might not be only one single

conformation observed rather a weighted average from all observables.

An atomic nucleus with a spin ≠ to zero has properties like a small magnet and

can be perturbed by radiofrequency pulses in a strong, external magnetic field.

This phenomenon is utilized in NMR spectroscopy, by perturbing the system in

equilibrium towards an excited state and study the relaxation back to equilibrium.

Relevant nuclei in protein samples with a spin quantum number of ½ includes 1H, 15N, 13C, and 31P. The natural abundances of 15N and 13C nuclei are low, requiring

isotopically labeled samples for reasonable experimental times and detection. One

further advantage with isotopically labeled proteins in terms of interaction studies

is when the protein of interest can be labeled whereas the other protein/chemical

is invisible in the spectrum to avoid signals from both. Atomic nuclei are sensitive

to the chemical environment, and the chemical shifts and the amplitude of the

signal resonances compared to a reference spectrum give information about

structural changes, ligand-binding, exchange processes etc. As an example, a 1D

or 2D NMR spectrum of a folded protein is rather dispersed, with nuclei with

several different local and chemical environments, whereas an unfolded protein

shows resonance signals with shifts very much alike. In other words, the chemical

shifts of a protein provide a fingerprint spectrum of that particular protein under

those experimental conditions. The resonance signals of the corresponding

27

residues can be assigned by measuring standard triple resonance backbone

assignment experiments, such as HNCBCA and HN(co)CBCA. For the Aβ peptide

there are several assignments already published (89, 91, 252, 253).

Figure 8. NMR timescales and molecular events. CPMG Carr-Purcell-Meiboom-Gill, NOE Nuclear

Overhauser effect, PRE Paramagnetic relaxation enhancement, RDC Residual dipolar coupling.

Conformational changes and ligand-binding can be studied by NMR using

chemical shift perturbation. As one example, a titration series of a ligand onto a 15N-labeled protein sample can be used and the chemical shift difference, Δδ, can

be quantified by Eq. 5 (254, 255). The magnitude of the chemical shift differences

Δδ does not always correspond with the strength of the effect (binding etc.).

∆𝛅 = (((∆𝛅𝐍

𝟓)

𝟐+ (∆𝛅𝐇)𝟐) /𝟐)

½

(Eq. 5)

For an increased understanding of the equilibria of protein dynamics or ligand-

binding kinetics in solution, information about the chemical exchange processes

may be helpful (256). The exchange between two (or more) chemical

states/environments are easily detected in the NMR spectrum by the rate relative

to the frequency difference between an observable (257) such as the resulting

chemical shift difference. The exchange rate (kex) between the states provides

kinetic information, whereas the lifetime of such a state, the population (p),

provides information about the thermodynamics of the dynamic process. Slow

exchange (kex < Δω) relative to the NMR timescale with equally populated states

stateA and stateB gives rise to two peaks (signal resonances) with the same

intensity. With a faster, intermediate exchange rate (kex ~ Δω), the two states result

in a broad peak in the middle of the former two peaks at slow exchange. In the

fast exchange regime (kex > Δω), the exchange between the two states results in

one narrow peak in the middle.

Upon induced changes of nuclei’s chemical environment, such as ligand-

binding, the signal resonances of the affected nuclei may lose signal intensity due

to line broadening by paramagnetic effects or by chemical exchange. The loss of

signal to “an invisible state” (258) can be further studied by relaxation dispersion

experiments if the exchange occur on the ms-μs timescale, by gathering

28

information about the minor invisible state (stateB) from the kinetics of the

properties of the major stateA. Compared to 2D heteronuclear single quantum

coherence (HSQC) experiments where the monomeric major state, the unbound

“free” state, is observed, Carr-Purcell-Meiboom-Gill (CPMG) relaxation

dispersion experiments (259–261) provide information about the minor populated

state, which can be the bound state when chemical exchange effects are present

on the intermediate-fast NMR timescale (261–263). In some of my papers the

bound state corresponds to the invisible state in 2D HSQC spectra, observed as

loss of signal. The “invisible state”, the bound state, was studied by following the

free, visible state by relaxation dispersion.

In Paper 1 the chemical exchange between a metal:Aβ40 bound complex and

“free” Aβ40 was measured, assuming a two-state process. Pseudo 3D 15N-CPMG

relaxation dispersion experiments were measured with a pulse scheme by Carr-

Purcell-Meiboom-Gill with 11 different CPMG frequency delays between the

refocusing 180° pulses. In Paper 1 one external magnetic field was used, but

usage of two different external fields would have been optimal to determine the

sign of Δδ. The transverse relaxation rates, R2, for each residue were calculated

by Eq. 6.

𝐑𝟐𝐨𝐛𝐬 =

𝟏

𝐓𝐂𝐏∙ 𝐥𝐧 (

𝐈𝟎

𝐈) (Eq. 6)

where TCP is the mixing time and I is the intensity of the peaks for each CPMG frequency

delay with the reference spectrum TCP = 0 ms. CPMG-relaxation dispersion is observable in a

narrow time-window.

In my studies with Aβ and metal ions, typically N-terminal residues gave rise

to relaxation dispersion profiles. Affected residues do not automatically mean that

they are directly involved (ligand) in the metal coordination, rather that the

chemical environment around the nuclei are changed – perhaps due to metal

coordination, or the outer shell of the coordination or structural changes. The

relaxation dispersion data were further analysed with a two-state exchange model,

thoroughly described in previous work by Axel Abelein (131, 264, 265) to obtain

information about the following parameters: pB, kex, Δδ, and 𝑅20. The

concentration- and temperature dependence was also measured.

Translational diffusion of a protein can be measured by NMR spectroscopy.

By using the inhomogeneity in the applied magnetic field, by a magnetic field

gradient pulse, it is possible to evaluate how nuclei diffuse in the tube and from

peak intensity changes determine a diffusion coefficient. Pulse-field gradient

(PFG) diffusion experiments regarding the Aβ peptide provides information to

determine the translational diffusion coefficient, Dt, that can further be used to

estimate the hydrodynamic radius (RH) via the Stokes-Einstein equation (266,

267) in Eq. 7. The approximation of RH here is determined as the radius of a

spherical molecule.

29

𝐃𝐭 =𝐤𝐁𝐓

𝟔𝛑𝛈𝐑𝐇 (Eq.7)

where kB is the Boltzmann constant, η is the viscosity, and T is the temperature.

3.3 Atomic Force Microscopy

Microscopy is to see the invisible by the naked eye with magnification, both

with visible light (optical microscopy), as well as with instrumental techniques

utilizing other wavelengths (electron microscopy) or a probe to scan the surface

of interest (scanning probe microscopy (SPM)). Atomic force microscopy (AFM)

is one type of SPM. AFM utilizes the principle of measuring the force between a

probe and the sample to gain information, such as 3D imaging topography, charge

distribution, mechanical properties, electrochemical and magnetic properties, and

spectral properties (IR/Raman). In the amyloid field AFM is commonly used to

study the topographical properties of amyloid fibrils and aggregates/oligomers at

high resolution (268), monomer-monomer interactions (269–271) and protein

perturbation of lipid bilayers (272, 273). The measurements can be performed

both in air and in liquid. One limitation of the AFM method is the sample

preparation that includes drying of the samples onto the surface. Measurements

in air on dried samples might not reflect the sample in solution. However,

advances of the technique into “nanoscale” and even high-speed AFM providing

a tool to directly study amyloid formation in real time (274) facilitate studies of

amyloid formation. In this thesis AFM is mainly used to study the morphology of

the amyloid end-products after aggregation kinetics measurements (Figure 9), for

verification of fibril structures in the reaction volume. Such measurements can be

performed on mica surfaces, a surface that is slightly negatively charged. In

contact mode the surface is scanned at low speed with a constant

setpoint/height/force mode. The image resolution and quality are dependent on

the parameters set to adjust the feedback response. One disadvantage with contact

mode is the risk of damaging either the tip or the surface. In tapping mode the tip

on the cantilever vibrate (resonance frequency) and the cantilever is in a dynamic

range between a contact and non-contact mode.

Figure 9. Topographical AFM image of Aβ40 fibrils recorded in tapping mode in air on a

mica surface to visualize the fibril morphology. The scale bar corresponds to 1 μm, data to be

published (Mörman, Luo).

30

4. Metal ions as protein aggregation

modulators

Metal ions – a large family of ions with both common and distinctive

properties. 80% of the periodic table consists of metals and with several

oxidation states the possible variation of metal ions results in many different

ions. From a biological perspective, metal ions are essential and participate in

biological reactions (275), or used for stability reasons necessary for life-

sustaining processes. Specificity of a metal to a metal binding site is reached

by thermodynamics and kinetics. Billions of years ago the first cells utilized

metal ions abundantly present in their environment, mainly Fe2+ and Mg2+

(276). During evolution other metal ions became available also suitable for

participating as co-factors in proteins, with an induced pressure for the cellular

systems to adapt to the new milieu with several utilizable metal ions (276).

About 50% of all proteins today utilize metal ions. In contrast, certain metal

ion concentrations are kept under strict control in biological and cellular

systems to avoid deficiency or toxic overload. Several d-block transition metal

ions are present in the human brain. The “free” metal ions concentrations are

very low intracellularly (for Zn2+ about 10-10-10-15 M and for Cu+ about 10-18

M (276)). But, increased transition metal ion levels (about 300 µM Zn ions

and 15 µM Cu ions) (100, 277, 278) are released in the synaptic cleft during

neuronal transmission – which is the same cellular compartment where the Aβ

peptide is released from its precursor protein. Notably, compromised cellular

synapse plasticity has been suggested to be involved in the Alzheimer’s

disease neuronal loss (155, 166, 278).

Metal dyshomeostasis is implicated in Alzheimer’s disease and in other

misfolding protein diseases, with impaired biomolecular functioning, ROS

formation, accumulation, elevated/changed concentrations, or mislocalization

of metal ions (56, 79, 104, 166, 167, 279–290). The data in the literature are

spread, sometimes with observed elevated/decreased metal ion concentrations

(288, 291–303). Several challenges lie in the attempt to use complex model

systems such as patients and healthy controls, with disperse disease

progression, not optimal diagnosis opportunities, usage of non-age matched

controls, and analytical methods and biomarkers with low sensitivity or high

detection limits. Estimation of environmental exposure of both endogenous

and contaminant metal ions is also a challenge, as the vulnerable time window

(304) of acute or chronic exposure to harmful/toxic or deficient metal levels

“For me too, the periodic table was a passion. ... As a boy, I stood in front of

the display for hours, thinking how wonderful it was that each of those metal

foils and jars of gas had its own distinct personality.” Freeman Dyson

31

may differ and might not be reflected by single measurements. There is

growing evidence supporting binding of metal ions to amyloid species,

specifically in the context of misfolding diseases (104, 218, 305–310) with or

without a link to other factors (311). It is not yet completely elucidated if metal

ion interactions with misfolding proteins in neurodegenerative diseases are a

cause, a consequence or only secondary effects from disease

progression/pathology (312). Correlation and causation are two important

concepts to distinguish. One wonders if metal ion interactions with

amyloidogenic proteins occur in healthy cells too, or only applies during

pathological conditions. Chelation-based therapeutic strategies for

neurodegenerative diseases such as Alzheimer’s disease have been tested and

are also under development (221, 286, 308, 313–315).

Metal ion interactions with the Aβ peptide (316) are indeed interesting and

ions of particular interest have been copper, zinc, calcium and iron – metal

ions that are abundantly sequestered in senile plaques (99, 299, 317, 318).

Copper, manganese and iron are also highlighted metal ions due to their redox

properties and possible induction of oxidative stress (111, 177, 242, 279, 319–

322). The Aβ peptide binds both Cu(II) and Cu(I) ions with different binding

modes, and the transition between those two binding modes are of interest for

an understanding of the molecular details of ROS formation (111, 177). The

Aβ peptide interacts with certain metal ions in the nano- to µM range, binding

metal ions at the N-terminus both as a monomer and as more structured

aggregates (99, 106).

Upon metal binding the net charge of the Aβ peptide is decreased which

may facilitate self-assembly processes. With fast self-association amorphous

aggregates can be induced instead of ordered amyloid structures. Discussions

about metal ion inducible effects on the Aβ peptide is much dependent on the

metal ion concentration versus the peptide concentration (323). When

metal<peptide, specific interactions may occur with one type of effect on the

aggregation, different from a metal>peptide situation where non-specific

interactions and electrostatic effects become more important. The metal-

ligand binding is easily described as a competition between the metal ion and

protons. The Aβ peptide lacks the typical metal binding cysteine residues

(polarizable atoms of thiolate and carboxylate), but three histidine residues

together with negatively charged residues in the N-terminus are typical metal

binding ligands under physiological conditions in the human Aβ peptide

variant. The histidine residues, as well as Asn and Gln, are polar, uncharged

and favorable for metal binding (276). The histidine residues with a pKa of ~6

are however sensitive to changes of pH close to physiological pH (324, 325).

In contrast, the murine Aβ peptide has only two histidine residues, together

with Y10 substituted to a phenylalanine and R5 to a glycine. Surprisingly, the

murine Aβ peptide display a higher affinity towards metal ions compared to

the human one (326). The origin of this effect has been suggested to be the

absence of a charged and somewhat bulky arginine residue. R5 in the wildtype

32

Aβ is not in the first coordination sphere, rather in the second one, but does

still affect the metal ion interaction.

Systematically studying metal ion interactions and modulation of the Aβ

self-assembly can provide important information for the understanding of

disease etiology (111, 312, 327). Pioneering work by Atwood and co-workers

studied several different metal ions incubated with Aβ and consequently

induced amounts of aggregates (328). However, information such as binding

and detailed mechanisms were not provided to explain the observed effects.

By studying the interaction in detail, pieces of information can possibly be put

together to connect the binding to the metal-modulated aggregation behavior

(307). Why certain metal ions bind to the Aβ peptide specifically and others

do not is another question to be addressed.

We studied about 27 different metal ions (Table 1) with molecular

resolution to understand the biophysical effects on the aggregation behavior,

where a pattern started to develop. Here we will discuss only a selection of

these 27 metal ions (Paper I-V): Ag(I), Cd(II), Cr(III), Cu(II), Hg(II), Mn(II),

Pb(II), Pb(IV), and Zn(II) ions. In addition to metal binding per se, metal ions

are convenient to work with to perturb the Aβ peptide aggregation kinetics

which allows further mechanistic insights into the aggregation and nucleation

mechanisms. To study the metal-induced effects on the Aβ aggregation

behavior, Ag(I) and Zn(II) were chosen as model ions and discussed in more

detail in section 4.2.

4.1 Metal-binding properties of Aβ peptide (Paper I-V)

4.1.1 Binding mode and aggregation

In Paper I-V a selection of metal ions was studied in terms of binding

specificity. The metal ion:Aβ40 binding was studied with high-resolution

NMR spectroscopy and molecular modeling simulations. One question

addressed was why certain metal ions bind to the Aβ peptide specifically,

while others do not. d-block transition metal ions are prominent protein

binders via coordination or electrostatic interactions (329). Metal specificity

is often thermodynamically controlled via ionic radii, coordination number,

Lewis acid type, and coordination geometry. Polarizability of the ligand and

metal also contributes (275). The Aβ peptide is intrinsically disordered and

hence flexible to adjust its structure for coordination of different metal ions

despite differences in sizes and charges. The binding mode is similar but not

exclusive between the metal ions, rather slightly different and the second

sphere coordination affects the specificity and hence the binding mode.

Following a similar concept, there is not only one binding mode per metal ion;

instead a collection of different but related populated binding modes with a

33

Table 1. Metal-binding properties of the Aβ peptide with fundamental features of 33 metal ions – 27 ions here

experimentally studied in the thesis. The affinity values (dissociation constant, KD) for the metal:Aβ complexes vary

depending on the experimental setup and the state of the sample. Here are the KD values estimated based on similar

experimental conditions. Metal ions marked in green display specific binding towards Aβ. (330) (331) (332) (111, 333) (322)(334, 335) (40) (334)

transient character are present. The imidazole group of histidine residues is on

the borderline (intermediate) between being a “hard” or a “soft” electron

donor, or base, according to the Pearson acid base concept (332, 336). From

the data in Table 1 the Aβ peptide is suggested to be on the borderline towards

a “soft” electron donor. None of the studied metal ions considered as “hard”

acids (Cr(III), K(I), Na(I), Ca(II) (337), Mg(II), Al(III)) interact specifically

with the Aβ peptide, but three different ions (Cu(I) (333), Ag(I), and Hg(II))

regarded as “soft” acids do (Paper I and III). Metal ions regarded as

intermediate acids that bind specifically to the Aβ peptide are Cu(II), Zn(II),

Ni(II), Co(II), Mn(II), and Fe(II) (322) (Table 1). One exception seems to be

Pb(II) (Paper V), as it is a “borderline/intermediate” acid but does not bind

specifically to the Aβ peptide. Based on these observations, the Aβ peptide

can interact with a variety of metal ions that lies in the intermediate/soft acid

region with different affinities. No binding towards trivalent ions were

observed, only nonspecific electrostatic interactions. Two monovalent, one

tetravalent, and nine divalent ions display specific binding towards the Aβ

* Yes for high metal ion concentrations (super stoichiometric), ** 1:1 ratio slower aggregation kinetics

34

peptide (Table 1), and eight of those ions studied here (with a moderate

binding affinity) modulate the Aβ fibrillization kinetics. Cu(II) ions bind, at

least to our current knowledge, definitely with the highest affinity towards the

Aβ peptide, following the Irving-Williams series which is based on high-spin

divalent ions and their corresponding ionic radii (ionic potential) and

compares the stability of the metal complexes (and the Jahn-Teller effect). In

biology, the intracellular concentrations of transition metal ions also follow

the pattern of the Irving-Williams series. The metal ions with highest affinity

towards bioligands are also kept at lowest concentrations via cellular

regulation of the concentrations – to avoid unwanted competition between

more weakly binding metal ions (276). The general assumption of the Aβ

peptide being a typical divalent metal ion binder has now been modified. In

summary, the Aβ histidine residues function as binding ligands for all

specifically interacting metal ions studied (Paper I-V).

4.1.2 Metal ion binding in membrane-mimetics

Copper and zinc ions in relation to the Aβ peptide have been studied to a

high extent by several groups (252, 265, 310, 333, 338–343). In Paper IV we

introduced metal binding effects when the Aβ40 peptide is in a membrane

mimicking environment. Liposomes modeling a biological membrane in

terms of lipids, curvature and size are not suitable for NMR experiments;

instead SDS micelles were used as a model system. In a lipid environment the

Aβ peptide adopts an α-helical secondary structure. Interestingly, the metal

binding properties of the Aβ peptide are not significantly affected by the

incorporation into the SDS micelles, explained by the free N-terminal part of

the peptide also in a micelle complex.

4.2 Metal-Aβ complexes are unable for incorporation

into fibril ends (Paper I)

A general feature of metal ions, displaying specific binding towards the Aβ

peptide in sub-stoichiometric concentrations relative the peptide

concentration, is the ability to interfere with the Aβ aggregation behavior. The

rate of amyloid formation is reduced, previously demonstrated with Aβ40 and

Zn(II) ions where the elongation rate constant is the one most affected

parameter without changing the overall aggregation mechanisms (265). In

Paper I we studied two different metal ions, Ag(I) and Zn(II) (265) to further

investigate the molecular mechanisms. Both ions bind specifically to the N-

terminal part of the Aβ peptide via three histidine residues as the main ligands.

First, the approach of using Ag(I) ions to perturb the Aβ fibrillization is

discussed, and secondly the Ag(I) results are compared to previously

35

published Zn(II) data (265) for a general description and a proposed model of

transition metal ion perturbation of Aβ fibrillization kinetics.

4.2.1 Ag(I) ions attenuate Aβ fibrillization by interfering with fibril-end

elongation

ThT is not suitable for measurements in the presence of Ag(I) ions.

Therefore pFTAA was used instead as a fluorescent probe for detection of

amyloid material in Paper I. Ag(I) ions attenuate the bulk Aβ fibrillization

kinetics in a concentration-dependent manner with similar amounts of

amyloid material reached after the reaction, confirmed with AFM imaging.

Bulk experiments only show the average behavior of the fibrillization reaction

and sigmoidal curve fitting of the kinetic traces does not tell what kind of

processes that underlie the observations. Previous studies reported affected Aβ

fibrillization kinetics in the presence of Zn(II) ions without any changes of the

dominating processes (265). To shed more light on the mechanistic details we

used our data sets for a global fit analysis (119, 133, 192, 200, 201, 208) to

describe the fibrillization reaction in terms of microscopic rate constants.

Further processing of our data provided insights about the elongation rate

constant, k+, as the one most affected by Ag(I) ions, even though the other rate

constants kn and k2 also contribute to the fibrillization – but probably to a lower

extent. This observation was supported by seeding experiments with fibrillary

material added at t=0. The presence of seeds provides many sites of fibril end

elongation and secondary nucleation to fibril surfaces – whereas the

contribution of primary nucleation is minimal. For a low seed concentration

elongation and secondary nucleation are dominant, whereas with a high

concentration of seeds the slope of the linear dependence of the initial

fluorescent intensity signal corresponds to the k+ multiplied with the

concentration of aggregates. The relative k+ both from non-seeded and seeded

experiments show a similar dependence on the presence of Ag(I) ions,

strongly indicating fibril end elongation as the processes most affected by

Ag(I) ions (Paper I). But, several questions still remain. How does Ag(I)

influence the fibrillization kinetics and what is the mechanisms behind this

observation? Does it originate from the monomeric metal binding or not?

Does the metal ion affect the peptides during the lag phase of aggregation, or

at later stages? Which conformational stage is the starting point of binding to

the metal ion or other peptides?

4.2.2 Fibril growth attenuation originates from Aβ peptides bound in

metal complexes

The kinetic model in the previous section does not provide

conformation/structural information. Instead NMR experiments were used to

36

compensate for the lack of structural data. In Paper I the Ag(I) binding to

Aβ40 was characterized in detail. The affinity for Ag(I) ions towards the Aβ

peptide is in the µM range, explored with a variety of techniques (NMR

HSQC, NMR diffusion, fluorescence). In contrast to all other metal ions

studied, except Pt(II) ions (Table 1), Ag(I) ions induce chemical shift

differences in addition to line broadening of the NMR signal (Paper I). This

binding was further characterized by NMR CPMG relaxation dispersion in

terms of structure and dynamics. The metal:Aβ binding was assumed to

behave as a two state process with a 1:1 binding mode, with a “free” state and

a metal-bound state (the bound state likely includes several different bound

populations, here encountered as the average one). From CPMG relaxation

dispersion experimental information was obtained about the metal-bound state

in terms of the exchange rate between the “free” and the bound state and the

population for each residue affected by the metal ion binding. Non-specific

residue information was also obtained in terms of Δδ and R2. The exchange

rate between the two states is on the millisecond timescale with ~10% of the

peptides as metal-bound. The chemical shift changes observed in HSQC

spectra correlate with the chemical shifts Δδ derived from the relaxation

dispersion experiments, which suggests that we studied the same process and

bound state with both experiments. This is an extension of previous Zn(II)

data (265), where no chemical shift changes from HSQC spectra are visible to

be compared to the ΔδZn, relaxdisp.

Binding and folding often comes together, and to further characterize the

binding PFG diffusion experiments were performed. From these experiments

the diffusion coefficient can be extracted, which in the presence of Ag(I) ions

increases, indicative of a metal:Aβ complex that diffuses faster than the apo-

Aβ. This behavior becomes clearer by using the Stokes-Einstein relationship

of the diffusion coefficient and the hydrodynamic radius. The hydrodynamic

radius is here based on the assumption of a sphere and is decreased to 16.3 Å

in the presence of Ag(I) compared to the apo-state of 17 Å (Paper I). In other

words, the Aβ peptide becomes more compact when coordinating a metal ion.

Based on our observations from detailed NMR data of the metal-bound

state – how come that just a minor fraction of the available population of Aβ

peptides give rise to a clear attenuation of the fibrillization kinetics? To be

able to answer this question we scrutinized all the data and calculated the

theoretical “free” monomeric concentration, m(0), for each Ag(I) ion

concentration for each sample in the fibrillization kinetics experiment based

on the affinity for the Ag(I):Aβ complex. The higher Ag(I) concentration, the

higher portion of peptides in the bound state → lower available Aβ

concentration. Hence a theoretical value of m(0) for each Ag(I) concentration

was obtained, and this information together with the experimental kinetics

curves (Paper I) were globally fitted. The results revealed a reasonable good

fit with a dissociation constant in the same range as the values determined with

other techniques. In other words, the Ag(I) ions redirect active Aβ monomers

37

towards a detour on the fibrillization pathway, where the Ag(I):Aβ complex

is not available for fibril incorporation. Are these observations only applicable

to Ag(I) ions alone, or does it apply for metal ions in general?

4.2.3 Model: Metal ion perturbation of the fibrillization process

In Paper I we propose a model of sub-stochiometric transition metal ion

perturbation on the Aβ fibrillization kinetics, where structural information of

the metal:Aβ complex is proven to be linked to the bulk aggregation kinetics

behavior explained by microscopically reduced elongation rates (Figure 10).

Figure 10. Proposed model of the effects on the Aβ peptide amyloid aggregation behavior by interactions with

sub-stoichiometric metal ion concentrations. Metal ions with a specific histidine-dependent interaction towards the

Aβ peptide attenuate the overall fibrillization. This effect originates from a dynamic metal ion interaction with

monomeric peptides, making the monomeric pool of peptides unavailable to be incorporated into the fibrils, described

by a reduced elongation rate. PDB ID 2M9S.

This model was developed by comparing the obtained Ag(I) ion data with

previous data on Zn(II) (265). The binding of Ag(I) and Zn(II) ions towards

the Aβ peptide is not identical but similar for induction of a putative fold and

interference with the monomeric Aβ peptide. The different capacities are

reflected in a lower concentration of Zn(II) needed for a bound population and

subsequent attenuated macroscopic and microscopic processes in the

fibrillization kinetics. Both ions present a monomeric interaction with an

impact on the later stages of the fibrillization pathway – reduced overall

fibrillization kinetics via reduced elongation rate. The differences in

retardation efficiency may originate from the differences of dissociation

constants, as well as other discrepancies (Table 1). To conclude, histidine-

coordinated metal ions can retard the overall Aβ fibrillization kinetics by

mainly interfering with the process of fibril end elongation originating from

an aggregation-inert metal:Aβ complex, while primary and secondary

nucleation processes are not as much affected.

38

4.3 Formation of reactive oxygen species by metal:Aβ

complexes (Paper IV)

Cells and organisms may be exposed to oxidative stress and several

protective systems have been evolved during the evolution to deal with ROS,

both as inductively/constitutively expressed proteins like SOD, catalase, and

glutathione peroxidases, and dietary supplied antioxidants such as vitamin C

and E. Oxidative stress is also used as a defense agent against foreign intruders

such as bacteria. However, compromised defense systems or overproduction

of oxidative stress in sensitive locations is an issue, especially for tissues as

sensitive as the brain. Oxidative stress has been implicated as one route of

toxicity in Alzheimer’s disease (344). The Aβ peptide, as many biomolecules,

is involved in oxidation/reduction reactions. Post-translational modifications

have also been reported following oxidative stress, such as histidine

modifications, phosphorylation of the serine residues, and crosslinking

between aromatic residues such as the reaction of forming a covalent

dityrosine crosslink between two adjacent Aβ peptides (345).

Cu(II) ions are redox-active, via redox-cycling with Cu(I) and the Haber-

Weiss reaction, and in Paper IV we tested the Cu(II)-facilitated hydrogen

peroxide formation over time in a biochemical assay in the absence and

presence of Aβ (346–348). Over time, samples of 3 µM Cu(II) ions in buffer

generated about 30 µM hydrogen peroxide. In the presence of Aβ the

formation of hydrogen peroxide was not altered – in other words, the Cu(II)-

binding properties of Aβ is not strong/long-lived enough to hinder hydrogen

peroxide formation. Neither was the generation of hydrogen peroxide

significantly affected by the presence of SDS micelles. The only experimental

conditions able to shift the generation of hydrogen peroxide were apo-SOD1

and the chelator EDTA. EDTA is a strong metal ion chelator. Despite the lack

of effect of Aβ in these experiments, the Cu(II)-binding Aβ peptides might be

of interest in terms of redirecting redox-active ions in close proximity to the

plasma membrane due to the membrane-binding properties. Noteworthy, the

murine Aβ peptide binds Cu(II) with higher affinity compared to the human

one, with less hydrogen peroxide formed for the murine peptide (326).

4.4 Outlook

Metal ions that display a specific binding to Aβ can be used as modulators

of the fibrillization process. In Paper I this strategy was addressed, and it

remains to be verified if it can be translated onto other amyloidogenic and

misfolding proteins as well, since several misfolding proteins implicated in

misfolding protein diseases display metal binding properties. Further careful

analysis of other relevant metal ions to be put into the model proposed in

39

Paper I is ongoing. Beyond metal ions, additional efforts to explain the

microscopic and macroscopic effects on both aggregation and fibrillization

kinetics are highly endorsed for other modulators too.

The metal binding to Aβ is different compared to metalloproteins where

the metal binding site is highly specific. Is there a secondary binding site

occupied at high metal ion concentrations accompanied with disruption of key

interactions needed for amyloid formation? Both intra- and intermolecular

exchange between the metal ion and the Aβ peptide is possible. In Paper I the

metal-bound populated state is determined to ~10% of the total Aβ peptide

population with an exchange rate on the millisecond time scale. The low

population, the relatively low Aβ concentration used (in terms of NMR

spectroscopy), together with a transient metal ion binding contribute to a

challenge to obtain a structure(s) of the metal bound state(s). Optimal

experimental conditions for stabilization of the bound state would be very

much appreciated in the field, such as forcing the bound population into a

more stable state.

The relation of the metal ion induced perturbation of fibrillization and

cytotoxicity is still an unsolved question. The findings from my in vitro thesis

work cannot tell anything about potential toxicity (170). Notably, misfolded

proteins with exposed hydrophobic patches can be toxic, independently of

metal ions, and sole metal ions are cytotoxic in a dose-dependent manner.

Whether toxicity by metal-induced protein structures is additive, synergistic

or antagonistic is dependent on the metal ion, and details still have to be

elucidated. Homeostasis of endogenous metal ions is tightly regulated but may

be disturbed by contaminants. Competition between endogenous metal ions

with metal ion contaminants may be biologically relevant. Formation of ROS

during the aggregation and potential toxic endpoints are further points of

interest.

One of the main questions in the field is about multimeric structures of Aβ

peptides, and how such structures proceed to larger and insoluble fibril

structures – or the other way around with fibril and fibril-like structures

anticipating oligomers as a source, or acting as catalytic sites for oligomeric

peptide formation. Related to metal ion chemistry, the roles of metal ions in

the growth or formation of such structures, regulation of metal balance and

AβPP processing, and the functionality of Aβ-degrading proteins, are

important questions to address. The relevance of metal binding towards the

Aβ peptide in health and disease remains to be elucidated. The relatively low

Aβ affinity for metal ions does not speak for a significant metal ion binding

role during physiological concentrations, in the presence of i.e. copper

proteins with substantial higher affinity for copper ions. On the other hand,

both metal ions (Cu and Zn) and Aβ concentrations are increased during

synaptic activity (100, 277, 278). Iron overload is as well an important issue

related to advanced age and Alzheimer’s disease (79, 288).

40

5. Small molecules and peptide construct

interactions with Aβ peptide assemblies

5.1 Hydrophobic compounds found in cigarette smoke

(Paper V)

Alzheimer’s disease is more abundant in a cigarette smoking sample

population compared to a non-smoking sample population (349). To study the

effects of cigarette compounds on the Aβ peptide from a molecular

perspective, we studied a selection of polycyclic hydrocarbons (PAHs) and

nicotine present in cigarettes and cigarette smoke in Paper V. All molecules

except nicotine promoted the Aβ aggregation kinetics under our experimental

conditions. Interestingly, no specific binding studied with 2D NMR HSQC

was found for these compounds, yet the aggregation kinetics were affected,

possibly by interactions with more ordered structures containing Aβ peptide

multimers. Such sizes of Aβ assemblies are invisible by solution NMR and

may explain the lack of observed specific interactions. To conclude, small

hydrophobic compounds found in cigarette smoke promote the Aβ

aggregation without a specific interaction with the monomeric Aβ peptide.

Hydrophobic and non-specific interactions and when/where on the

fibrillization pathway a detour from the original path is initiated need to be

further studied, and not only limited to molecules in cigarettes but also other

hydrophobic compounds are of interest.

5.2 Designed peptide constructs (Paper VI)

One therapeutic strategy used in clinical trials to combat Alzheimer’s

disease is to target misfolded Aβ peptides distinguishable from both Aβ

monomers and Aβ fibrils. The blood brain barrier is undoubtedly a hinder of

passive immunization therapeutics administered orally or intravenously, due

to the limitations of low bioavailability. One efficient strategy is to use drug

cargos attached to cell-penetrating peptides (CPPs) able to cross the blood

brain barrier for effective delivery into the brain. CPPs occur both

endogenously and as engineered peptides. The cell-penetrating abilities of

certain proteins were discovered in the 1980s and since then the field has

“Being a scientist is a special privilege: for it brings the opportunity to be

creative, the passionate quest for answers to nature's most precious secrets,

and the warm friendships of many valued colleagues.” Stanley B. Prusiner

41

evolved with an increased understanding and steps into clinical applications

(350). CPPs are non-toxic peptides in the size range of 5-30 amino acids long

and give rise to protein delivery via cellular uptake. The process can be both

energy-dependent and energy-independent (351). The cell-penetrating

properties open up an avenue of potential applications to deliver drugs of

various kind (352). This approach has also been utilized in amyloid research

(353).

Previous research studied prion protein (PrP) infected cells and inhibition

of the progression of prion infection by different proteins with cell-penetrating

properties (354, 355). The strategy was based on steric hindrance of the

pathologic conversion of normal PrPC to the so-called scrapie form PrPSc

evolved by the N-terminal part of the murine prion protein, mPrP1-28. This part

of the protein consists of a signal sequence (mPrP1-22) and a positively charged

hexapeptide (mPrP23-28). The mPrP23-28 motif has been reported to have a high

affinity towards the PrPSc version of PrP (356), possibly explaining the

observed behavior. Due to the cell-penetrating properties the mPrP1-28 peptide

was internalized inside the cells and able to effectively attenuate the prion

infection (357). Interestingly, another signal sequence for secretion from the

first 19 residues of another protein, the neural cell adhesion molecule – 1

(NCAM) conjugated with the hexapeptide from the PrP (mPrP23-28) was even

more efficient to inhibit prion infection. The signal sequence targeting for

secretion seems to be important for the observed effect, with properties of

hydrophobic segments compared to CPPs in general. The physiological

function of the native NCAM protein is related to adhesion mechanisms

between neurons, neuronal growth and neurite fasciculation, and located in

the plasma membrane. The NCAM protein does also potentially interact with

PrP and AβPP (358–360). Does this inhibitory effect on misfolding prion

progression also apply for other amyloidogenic protein processes? This

question was addressed in vitro and in cells in Paper VI.

Two different peptide constructs were studied in Paper VI, one identical

sequence from the previous study (357) called NCAM-PrP (MLRTKDLIWT

LFFLGTAVSKKRPKP-NH2), whereas a second one with the cationic

hexapeptide based on a part of the Aβ sequence (NCAM-Aβ) was also added

as a proof of principle peptide construct. In the scope of this thesis only the

NCAM-PrP variant is discussed. The NCAM-PrP peptide construct is

predominately unstructured in aqueous solution and forms α-helical secondary

structures in 30% HFIP (Paper VI) and in membrane mimetics such as SDS

micelles. The peptide construct is stable in pure water at low pH for several

weeks but incubated in buffer solution at physiological pH the NCAM-PrP

([μM]) starts to aggregate/precipitate.

In Paper VI the NCAM-PrP peptide construct efficiently disrupts the

typical sigmoidal ThT fluorescence curves of Aβ42 peptides in a ThT

aggregation kinetics assay. At a ratio of 0.5:1 (NCAM-PrP:Aβ) the ThT

kinetic trace shows an instant but small increase in ThT fluorescence that

42

levels out to a stable, low signal fluorescence intensity level. The low ThT

fluorescence intensity is indicative of a low level of ThT-active

aggregates/fibrils, and transmission electron microscopy (TEM) images

confirmed the absence of typical amyloid fibrils. These observations indicate

that the Aβ42 fibrillization is inhibited in the presence of the NCAM-PrP

peptide construct. The mechanism behind this effect was further investigated

with solution 1D and 2D HSQC NMR experiments. The impact of NCAM-

PrP on monomeric 15N-Aβ peptides was investigated and reported as non-

specific interactions; however, a gradual and uniform loss of signal was

observed in the spectra together with a clear precipitation visible by the naked

eye. To avoid precipitation and to constrain the 15N-Aβ peptides in a

monomeric state, the same experiment was repeated in SDS micelles

(unpublished data). Both monomeric 15N-Aβ peptides and NCAM-PrP

construct peptides adopt α-helical secondary structures located in SDS

micelles, however no immediate interaction was observed. We further

examined the impact of the NCAM-PrP peptide construct on 15N-Aβ peptides

over time (unpublished results). 15N-Aβ peptides were incubated in the

presence and absence of sub-stoichiometric concentrations of NCAM-PrP for

48 hours and a 1H-15N-HSQC spectrum was recorded before and after the

incubation. As expected, the sample of 15N-Aβ peptides alone started to

aggregate during the incubation proved by reduced signal resonance intensity.

Surprisingly, the 15N-Aβ sample supplemented and incubated with NCAM-

PrP showed a less pronounced signal loss compared to the sample without

(Figure 11). Taken together, these observations suggest a weak, if any,

interaction with monomeric 15N-Aβ species, and with non-identified

interactions with more ordered structures invisible by NMR. Another aspect

is potential dissociation of ordered structures to monomeric species as part of

the explanation of maintaining the 15N-Aβ sample monomeric to a higher

extent in the presence of NCAM-PrP, this is also supported by the

observations from the ThT assay and TEM imaging (Paper VI). The

inhibitory effect of NCAM-PrP on the Aβ42 fibrillization kinetics is hence not

solely explained by an interaction with monomeric Aβ species.

The Aβ-NCAM-PrP interaction and effects on the Aβ peptide aggregation

behavior were further investigated with ELISA and dot blot assays using

mono- and polyclonal antibodies recognizing oligomeric Aβ structures

(Paper VI). The signal of oligomers increased linearly when Aβ was

incubated over time in the absence of the NCAM-PrP, followed by a rapid

decrease currently proposed as a shift of the oligomeric population towards

fibrils. In contrast, Aβ incubated in the presence of equimolar concentrations

of NCAM-PrP decreased the signal of oligomeric structures by 35-50%. The

NCAM-PrP peptide construct thus interferes with the formation of oligomeric

Aβ species in this assay.

The inhibitory effects of Aβ fibrillization in vitro in a simple model system

is one isolated aspect, and effects in cellular systems is another one. The

43

Figure 11. Aβ and NCAM-PrP peptide construct interactions. (A) 2D NMR 1H-15N-HSQC

spectra of 20 μM 15N-Aβ40 before (dark blue) and after 48 hours incubation (light blue). Below

are the relative intensities plotted against the Aβ primary amino acid sequence shown. In (B)

the measurements in (A) were repeated but in the presence of 5 μM NCAM-PrP (dark blue) and

after 48 hours incubation (green). (C) ThT fibrillization kinetics experiments. 5 μM Aβ42

peptides were incubated in 10 mM MOPS buffer at physiological pH +37 °C supplemented with

10 μM ThT, in the presence and absence of 10% seeds and 5 μM NCAM-PrP peptide constructs.

NCAM-PrP construct peptide was also tested in N2a mouse neuroblastoma

cells (Paper VI). Interestingly, the NCAM-PrP peptide was able to rescue the

N2a cells completely from the Aβ42-induced toxicity in a cell viability assay

44

where the cells were supplemented with the two peptides simultaneously.

Cells were also exposed to fluorescently labeled peptides and studied in

confocal fluorescence microscopy imaging after 24 hours of incubation. The

peptides were co-localized in mitochondria and lysosomes, observations that

indicated internalization of both peptides and localization to similar sites in

the cell. In addition, cells were also pre-treated with Aβ peptides for 24 hours

followed by supplementation of NCAM-PrP peptide constructs. It turned out

that the NCAM-PrP peptides were able to target intracellular Aβ peptides,

visualized by confocal fluorescence microscopy imaging and cell viability

measurements (Paper VI). The NCAM-PrP concentration used together with

Aβ was also tested to distinguish any toxicity of the construct alone and the

cell viability for those samples were close to the background level. In

summary, the NCAM-PrP peptide construct rescued cells from Aβ-induced

neurotoxicity.

The designed peptide construct inhibits Aβ42 fibrillization (ThT assay and

TEM imaging), prevents formation of oligomeric species (ELISA and dot blot

assay) and rescues Aβ42-induced neurotoxicity and targets both intracellular

and extracellular Aβ42 (Paper VI). NMR experiments proposed that the

involved interactions between Aβ and NCAM-PrP does not originate from

monomeric Aβ peptides. So, if it is not monomeric interactions, what kind of

structural interaction lies behind the inhibitory effects of NCAM-PrP? To

enlighten this question seeding experiments were added to the cassette of ThT

kinetics experiments, for an attempt to identify secondary nucleation

pathways from primary nucleation processes. Pre-formed seeds at a high seed

concentration was added at time zero to monomeric Aβ42 peptides in the

presence of different concentrations of NCAM-PrP peptides (unpublished

results). In the absence of NCAM-PrP, the Aβ42 peptides seeded with pre-

formed aggregates reached the plateau phase before the samples in the absence

of seeds left the lag phase, indicative of dominating secondary nucleation

processes. Intriguingly, in the presence of NCAM-PrP the effect of pre-formed

seeds was abolished (Figure 11). In other words, despite an increased number

of fibril surfaces and fibril ends, the growth of aggregate mass is similar to the

conditions without seeds. These findings need to be further verified, but the

secondary nucleation processes may be hampered by NCAM-PrP, along with

potential additional processes.

In summary, the NCAM-PrP peptide construct with a hydrophobic signal

sequence + a polycationic sequence inhibits and detouring the Aβ aggregation

in vitro with reduced amounts of oligomers and fibrils, and attenuated

neurotoxicity effects in cellular model systems. The NCAM-PrP peptide

construct stabilized the Aβ peptide in a non-amyloid state, that may be a

promising approach for future therapeutic strategies. Obviously, further

development of the CPP-based peptide strategy is needed, and more

information about the interaction, optimization, D-variants, and other

sequence improvements are yet to come in ongoing projects.

45

6. Two interacting proteins implicated in

Alzheimer’s disease – Aβ and Tau

There are several hypotheses regarding Alzheimer’s disease, and two of them

are the amyloid cascade hypothesis and the Tau hypothesis (2, 76, 77, 361).

These two hypotheses occur both individually and combined. Common

denominators of Aβ and Tau are their properties of forming amyloid and

paired helical filament structures from disordered monomeric structures. The

Aβ peptide and Tau protein (362, 363) are two proteins with highly disperse

properties and functions (Figure 12). Tau protein is about ten times larger than

Aβ, with a net charge of +3 compared to -3 for the Aβ peptide under

physiological conditions. The physiological roles of the two proteins are

different. Detailed Aβ peptide information is presented in section 2.4. Tau

protein has a distinct native function of promoting axonal microtubule

assembly and microtubule stability and belongs to the microtubule-associated

protein (MAP) family (364). There are six isoforms of Tau, and the largest

one consists of 441 residues (365). Tau protein is highly unstructured with a

low content of secondary structures, but with regions exhibiting β-sheet

propensity (365). The affinity towards microtubules decreases upon

phosphorylation (362, 366) and is part of the equilibrium between association

and dissociation of microtubules. In Alzheimer’s disease, Tau proteins are

found hyperphosphorylated and aggregated into helical filaments (76). In

vitro, native Tau protein does not aggregate into ThT-active aggregates unless

incubated in the presence of negatively charged polyions such as heparin

(367).

Interplay between Aβ and Tau protein including co-existence and

combined pathological effects has been reported (76, 146, 368–382). It has

been proposed that Aβ amyloidosis induces or enhances Tau pathology (76,

146, 368–381), and Aβ toxicity has been described as Tau-dependent (368).

The combined pathological effects are partly seen as synergistic effects from

both Aβ and Tau (76, 146, 368–381). Aβ/AβPP may trigger Tau aggregation,

and Tau protein may trigger Aβ aggregation. Tau deficiency, Tau-/- models,

are not susceptible to Aβ toxicity (76, 146, 368–381). Transgenic mice

overexpressing both AβPP and presenilin-1 were reported with lower burden

of senile plaques when Tau was suppressed (368). If Aβ is mainly an

extracellular peptide and Tau is an intracellular microtubule-binding protein –

can these proteins make contact in vivo? However, both Aβ- and Tau

“Were always together, were one of a kind, three words describes us “partners

in crime”.” Unknown

46

Figure 12. Native Tau protein. (A) Tau protein belongs to the microtubule-associated protein

(MAP) family and stabilizes microtubules in the cell, Tau is here visualized in dark blue colour

from PDB ID 6CVN (383). (B) The longest isoform of Tau protein is 441 residues long and the

microtubule-binding domains are designated as R1, R2, R3, and R4 (363).

aggregates exhibit prion-like transmission properties for spreading from one

neuron to another, observed both in vitro and in patients (384–386). Therefore

the Aβ peptide is not only limited to the extracellular space, but is rather also

present in intracellular compartments (165). Under physiological conditions

the Aβ concentration in the human brain is low (nanomolar), but may be

higher in the μM range in specific cellular compartments (96, 108). The

physiological concentration of Tau protein is about 2 μM (387, 388). The in

vivo estimated concentrations and the ability for both proteins to propagate

from one cell to another actually provide reasonable opportunities for the two

proteins implicated in Alzheimer’s disease to physically meet. Paper VII

investigated the interplay between the Aβ40 peptide and native full-length Tau

protein on the molecular level in vitro and how Tau influences the aggregation

properties of the Aβ peptide.

47

6.1 Full-length native Tau protein prevents Aβ

fibrillization (Paper VII)

In Paper VII we studied the impact of Tau protein on the Aβ40 peptide

fibrillization. From our findings, a simple schematic model of interaction

stages during the Aβ fibrillization pathway is suggested and highlighted in

Figure 13. We monitored the fibrillization of Aβ40 with a ThT assay in the

presence of increasing concentrations of Tau proteins. Whereas the Aβ40

peptide sample shows a typical ThT fluorescence signal curve with a

sigmoidal shape, Tau protein prevents the Aβ fibrillization process in a

concentration-dependent manner observed as increased aggregation halftimes

and decreased fluorescence intensity at the end of the experimental time.

Based on these observations, Tau protein is proposed to prevent the Aβ

fibrillization processes. However, this analysis does not tell about the

underlying microscopic nucleation mechanisms, nor at what stage and how

the fibrillization is attenuated.

The ThT molecule used in the ThT assay does not recognize amorphous

aggregates and to investigate the structural state at the end of the Aβ

aggregation in the presence of Tau protein, TEM imaging was used.

Compared to the 10 µM Aβ alone sample that formed characteristic fibrils, in

samples with Aβ in the presence of 2.5 or 10 µM Tau proteins only non-

fibrillary structures were present. These findings hence validate the

observation from the ThT assay with less ThT-active structures in the presence

of Tau. For more detailed information, monomeric Aβ was studied with high-

resolution NMR spectroscopy. 2D NMR 1H-15N-HSQC spectra of 10 µM 15N-

Aβ in the absence and presence of equimolar concentration of Tau were

recorded before and after 15 hours of incubation. All samples showed

monomeric 15N-Aβ resonance signals with similar signal intensities for both

samples before the incubation started, and after the incubation the 15N-Aβ

sample without Tau protein lost all signals down to the noise level due to

aggregation into larger structures. In contrast, the sample co-incubated with

Tau protein still showed monomeric 15N-Aβ resonance signals, indicative of

remaining monomers in solution.

Based on these observations, it is relevant to propose that the key Tau

interaction explaining the attenuation of the Aβ fibrillization is not with

monomeric Aβ – rather with more ordered structures such as oligomers and

fibrils (Figure 13). To test this hypothesis, we performed fluorescence

polarization experiments to measure the affinity between Tau and Aβ

monomeric-, oligomeric-, and fibril structures. So called oligomeric structures

were generated by incubation of monomeric Aβ peptides at certain time

points. Interestingly, the fluorescence polarization experiments confirmed a

low affinity towards monomeric Aβ (KD >100 µM), but with higher affinity

for oligomeric species (KD of ~10 µM) and the highest affinity for fibrils (KD

of ~1 µM). Taken together, the higher affinity for larger structures (oligomers,

48

Figure 13. Full-length, native Tau protein prevents Aβ fibrillization. Tau influences the Aβ

fibrillization at several stages, with a range of fibrils > intermediate structures > monomeric

species, determined by various biophysical techniques.

fibrils) compared to monomers and an increased monomeric population in the

presence of Tau protein is indicative of Tau interference at several levels

related to the Aβ fibrillization: both by binding to the fibril surface preventing

formation of new aggregates on the surface or elongation to the fibril ends,

and by facilitating dissociation of Aβ oligomeric structures into monomers.

6.2 Outlook

Two interacting proteins very much entangled in Alzheimer’s disease are

intriguing and of interest for further investigation. Are the Aβ peptides and

Tau proteins partners in crime, or a result of dysregulated biochemical

processes? The clinical implications of such interactions remain to be

tested/verified, and multifaceted therapeutic interventions towards both Aβ

species and Tau protein are suggested. Detailed structural information of the

Tau-Aβ interaction coupled to biological/physiological conditions is highly

desirable. We first wish to investigate which domain of Tau protein is

responsible for the prevention and detouring of the Aβ fibrillization. A

working hypothesis interesting to investigate is if the absence of fibrillated Aβ

species inside cells might be related to the presence of native full-length Tau

protein.

49

7. Concluding remarks and future perspectives

A detour of amyloid building blocks can be achieved by perturbing the

fibrillization processes by interacting metal ions and molecules. The Aβ

peptide interacts with various ions and molecules, both at the monomeric stage

and as larger assemblies. In brief, based on our findings we specifically

conclude that:

- From a total of 33 metal ions (27 ions studied within this thesis), 12 metal ions

interact specifically with the Aβ peptide.

- Based on the observations and the Pearson acid-base concept (336), the Aβ

peptide interacts with intermediate-soft electron acceptors, both monovalent and

divalent metal ions. Notably, not all divalent metal ions interact specifically with

the Aβ peptide.

- Specific metal ion interactions to the Aβ40 peptide with an affinity high enough

modulate the Aβ peptide self-assembly. At high metal ion concentrations ionic

strength effects are present.

- A common interaction mechanism appears for monovalent Ag(I) and divalent

Zn(II) ions with Aβ peptides.

- The pool of available Aβ monomeric peptides is reduced once Ag(I) and Zn(II)

ions are bound to the Aβ peptide. This interaction results in an overall attenuating

effect of Aβ fibril formation linked to a reduction of the elongation rate.

- SDS-bound Aβ peptide binds Cu(II) ions and copper ions generate hydrogen

peroxide, implicated as a source of ROS and oxidative stress.

- Small hydrophobic compounds, PAHs, present in cigarette smoke promote the

Aβ amyloid aggregation kinetics.

- Designed CPP peptide constructs, NCAM-PrP peptides, comprised of a

hydrophobic signal sequence targeting for secretion and a polycationic

hexapeptide affect oligomeric structures of Aβ multimers, and inhibits Aβ42

fibrillization.

- In cells, NCAM-PrP peptides rescue Aβ42-induced neurotoxicity, and targets

both intracellular and extracellular Aβ42.

- Soluble, full-length, and non-phosphorylated Tau-441 protein prevents Aβ

aggregation. The Aβ fibrillization process is not prevented by Tau interaction

with Aβ monomeric species, but rather with fibrils and oligomeric species of Aβ.

“Always make a total effort, even when the odds are against you.”

Arnold Palmer – ”Athlete of the Decade” in the 1960s

“Spela bollen som den ligger och banan som den är” Regel 13 i golfboken

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7.1 Outlook

There are still many remaining questions. The Aβ amyloid aggregation

processes are heterogenous, and easily affected by external factors. The

interplay between metal ions and the Aβ peptide in relation to cytotoxicity,

mitochondrial dependence, competitive binding and more importantly, the

biological and pathological relevance, are a few areas of further possibly

investigation. Are these NMR and aggregation kinetics studies applicable to

other proteins as well?

The interactions and aggregation modulators can be used both to learn more

about the underlying fibrillization processes and for development of potential

and promising therapeutic strategies. CPP-based inhibitors of Aβ fibrillization

might be a promising therapeutic possibility. A body of different ions and

molecules (endogenous, exogenous, and disease-relevant ones) interacts with

the Aβ peptide and changes the aggregation processes on the microscopic

level. By studies of such interactions, clues about the aggregation mechanisms

can be obtained as fundaments for further studies to design better, sustainable,

and suitable aggregation modulating substances to therapeutically target

amyloid-forming proteins in diseases.

Is it an advantage with slow fibrillization or is fast fibrillization more

beneficial if translated into cellular systems? It is not a simple question with a

simple yes/no answer based on the behavior of aggregation in bulk

experiments. Slow aggregation may contribute to a longer time window with

Aβ peptides in an oligomeric state before the fibril state is reached, whereas

fast aggregation kinetics may contribute to aggregation of species not readily

available for aggregation in the first place. A decrease of aggregation-

competent units such as the monomer concentration, nuclei, certain oligomeric

structures, or available fibril surfaces will certainly affect the aggregation

kinetics for sure. On the other hand, the nucleation processes may be affected

directing the aggregation pathway to a different path.

To combat protein misfolding linked to the pathogenesis of

neurodegenerative diseases further steps still need to be taken, likely

facilitated with substantial resources and collaborations. Preventative actions

are important, long-term goals and ambitions may be crucial for successful

treatments in misfolding protein diseases. Detour and an escape from the

fibrillization pathway may be one step further.

51

8. Populärvetenskaplig sammanfattning

”Allt bör göras så enkelt som möjligt, men inte enklare” är ett citat myntat

av Albert Einstein. Projektet i den här avhandlingen använder ett enkelt

modellsystem för att studera komplexa processer underliggande Alzheimers

sjukdom enligt den så kallade amyloid-hypotesen.

Bakgrund

Människan består utav 37,2 biljoner (1012) celler, där varje cell är i

genomsnitt cirka 100 mikrometer = 0,0001 meter = 0,1 millimeter i diameter.

Om varje cell läggs på en enda lång rad så räcker detta band av celler till hela

93 varv runt jordklotet, motsvarande fem tur och returresor till månen.

Enskilda celler (n=1) kan ingående studeras med modern teknologi och

vetenskapen idag har gjort det allt mer vedertaget att studera enskilda

molekyler i laboratoriet. Ritningen för en människa finns tätt packad i en

lösenordskyddad kärna i varje cell som ett genom bestående av DNA. DNA

kodar för olika ”arbetsmyror”, även kallade proteiner, som behövs för att

sköta processer och händelser i en cell. Det finns på ett ungefär 20-25 000

gener som i sin tur kodar för cirka 100 000 olika proteiner. Ett protein, en

molekylär maskin, är en polymer av sammanlänkande aminosyror, vars

ordning och typ avgör proteinets struktur och dess funktion. Myosin och aktin

är två exempel på typiska proteiner i muskelvävnad som med generella termer

ofta associeras med protein i det vardagliga livet. Människokroppen består av

många olika sorters proteiner med livsviktiga funktioner såsom sockerupptag

(insulin), signalering (hormoner, signalsubstanser), energi-produktion i

cellens kraftverk (proteiner i mitokondrier) och cellskelett (aktin, keratin,

tubulin).

Hjärnan består av en mosaik av flera olika sorters celler. En av dessa

celltyper, neuroner, består av en cellkropp (soma), en lång axon för transport

av nervimpulser samt dendriter som samlar upp och delar vidare kemisk

information. Alzheimers sjukdom, en av de vanligaste demenssjukdomarna,

kännetecknas av att hjärnan förtvinar genom förstörelse av neuroner (se Figur

14). Förtvingen leder till en påverkan på vitala funktioner samt hjärnans

kommunikation mellan nervcellerna, för att slutgiltigt helt upphöra. Denna

neurodegenerering tros vara en följd eller orsak av aggregerade (”ihop-

kloggade”) proteiner. Aggregerade proteiner förlorar både sin naturliga

funktion och är svåra att bryta ned för cellen, samt klibbar ihop andra

52

livsnödvändiga system som i sin tur bidrar till ett tillstånd som inte är optimalt

för cellens överlevnad och livskvalité. Flera sjukdomar är associerade till

neurodegeneration, såsom Alzheimers sjukdom, Parkinsons sjukdom, ALS,

Huntingtons sjukdom, Creutzfeldt-Jakobs sjukdom (”galna kosjukan”) samt

”Skellefteå-sjukan”.

Proteiner som ofta förknippas med Alzheimers sjukdom är Aβ-peptiden

och Tau (se Figur 14). Aβ-peptiden består av både klibbiga och vattenlösliga

segment och dess naturliga funktion är ännu inte helt klarlagd. Enstaka och ett

fåtal Aβ-peptider är vattenlösliga, men vid start av dess aggregering via olika

mellantillstånd sjunker lösligheten tills dess att sluttillståndet av stabila och

olösliga aggregat har uppnåtts. Tau har däremot en tydlig funktion i att

stabilisera de protein som i sin tur stabiliserar cellens ryggrad/skelett. Både

Aβ och Tau tenderar att aggregera ihop till proteinaggregat vid sjukdom, både

var och en för sig samt i en ömsesidig process.

Figur 14. Typiska kännetecken för Alzheimers sjukdom inkluderar förtvinad hjärnvävnad,

celldöd och aggregat av Aβ-peptider och Tau protein. Tau hjälper till att stabilisera cellens

ryggrad och axon. I den här avhandlingen har Aβ-peptidens aggregationsförlopp (=processen

från enstaka och lösliga peptider till stabila fibriller/aggregat bestående av många peptider)

studerats i detalj.

53

Problemställning

För att beskriva och förhindra neurodegenerativa sjukdomar är det av

största vikt att förstå i detalj hur processen som bidrar till att proteiner

aggregerar fungerar, vilket är en del av den här avhandlingen. Här har ett (n=1)

protein studerats, den så kallade Aβ-peptiden. Aβ-peptiden har en stark

tendens att aggregera – det vill säga att under rätt betingelser så sker

aggregation och bildande av kemiskt stabila aggregat spontant.

Aggregationsförloppet i samband med olika mellantillstånd anses vara

sjukdomsförkallande (=amyloid-hypotesen). Arbetet har inriktats på att

studera olika interaktioner i relation till dess effekt på aggregationsförloppet.

Metodik

I provrör har molekylära interaktioner och aggregationsprocesser studerats

med hjälp av biofysiska metoder — spektroskopi och mikroskopi. För vissa

mätningar har även levande celler, neuroner, använts. Aβ-peptiden är en av

huvudaktörerna inom amyloid-hypotesen. Detaljstudier har utförts av Aβ-

peptidens interaktioner med andra molekyler (metalljoner, designade peptider

och Tau protein) och dess effekt på aggregationsförloppet.

Resultat och slutsatser

Aβ-peptiden påverkas i mångt och mycket av flera olika faktorer och

beroende på vilken typ av interaktion som föreligger kan effekten te sig olika

ut. Resultaten tyder på att enskilda Aβ-peptider (n=1) gärna binder svagt till

flera olika metalljoner. Den här typen av metallbindning påverkar Aβ-

peptiden så pass mycket att det totala aggregationsförloppet tar längre tid till

att fullborda aggregationen till olösliga och strukturerade aggregat. Dock får

inte alla sorters metalljoner ut den här effekten. Det som krävs är en specifik

bindning som är tillräckligt kraftfull och ger en veckningsform som kan leda

bort enskilda Aβ-peptider från det spontana aggregationsförloppet. Denna

process att Aβ-peptiden tar en omväg innan de hittar rätt i aggregationen

påverkar främst tillväxten av befintliga aggregat.

Till skillnad från metallbindning till enskilda Aβ-peptider så har andra

molekyler en annan typ av effekt för aggregat med många Aβ-peptider (n=~2-

100). Designade peptidsekvenser som har egenskaper för att kunna passera

från en cell till en annan kan även påverka Aβ-peptidens aggregationsförlopp.

Effekten kommer inte från en interaktion med enskilda Aβ-peptider, utan

snarare med multistrukturer av Aβ-peptider som kan variera i form och storlek

och även i ytegenskaper. Dessa designade peptidsekvenser samverkar med

dessa multistrukturer och förhindrar fortsatt aggregation till fullväxta aggregat

samt hindrar även toxiciteten hos dessa multistrukturaggregat.

Ett annat protein, Tau, påverkar också Aβ-peptidens aggregationsförlopp

genom att samverka med multistrukturer snare än med enskilda Aβ-peptider.

Tau förhindrar att Aβ-peptiden bildar strukturerade aggregat, samt bidrar till

54

en ökad fraktion enskilda Aβ-peptider från en aggregatlösning. Det är inte helt

klarlagt än, vad den upplösande effekten beror på, men den är tydlig.

Tre olika typer av modulatorer (=metalljoner, designade peptider och Tau)

av Aβ-peptidens aggregationsförlopp har studerats och de påverkar Aβ-

peptiden på olika aggregationsnivåer. Det modulatorerna har gemensamt är att

den framkallade störningen av aggregationsförloppet både kan användas för

att lära sig mer om de bakomliggande molekylära mekanismerna för

aggregation samt ge idéer på möjliga terapeutiska strategier.

55

9. Acknowledgements

If I would list everyone who has been important for and during this thesis

work, this section of the thesis would have been longer than the kappa itself.

Thereby I will keep it short and simple (without mutual order).

I wish to express my sincere gratitude to my supervisor Astrid Gräslund.

Thank you for infinite support, scientific guidance and patience. Thank you

for four and a half years of research joy and happy memories. Thank you for

being encouraging and a good role model, for accepting me as a PhD student,

for giving me freedom to suggest and pursue new ideas and research projects,

always having your door open for questions and discussions, and for letting

me take part of our global community with collaborators all over the world. It

has been an interesting journey.

I am grateful for financial support from foundations/organizations

making it possible to participate and to present our research on international

scientific conferences, summer school courses, and research visits. Thanks to

the Biophysical Society travel award, Klas-Bertil and Margareta

Augustinssons stipendiefond, the Jubilee donation, K & A Wallenberg

Foundation, the Nobel Foundation, the Paul Scherrer Institute, and the

Stockholm University Donation Scholarship.

My co-supervisor Andreas Barth, thank you for being incredibly

supportive for each stage of the PhD process. Thank you for all your help, for

being encouraging, for your guidance, and for inspiring me to learn more

about IR spectroscopy. For this I am enormously grateful.

Extra supervisors, Per Roos and Sebastian Wärmländer, thank you for

support, guidance, and for the opportunity to study these incredible interesting

research topics. Per, I highly appreciate your enthusiasm and for introducing

the field of neurodegeneration from the medical point of view to me, including

meetings with patients. Sebastian, thank you for providing many different

aspects of protein chemistry/methodology, and for the help to present our

research at conferences and to visit other laboratories of our collaborators.

I would like to acknowledge Axel Abelein, thank you for sharing your

knowledge and your enthusiasm about research so generously. It has been a

privilege to be part of our collaborative and joint research projects, and I have

learned so much during the process. I highly enjoyed working with our

projects. Thank you for excellent feedback and for help with the thesis work.

”In science, one should use all available resources to solve difficult problems.

One of our most powerful resources is the insight of our colleagues”. Peter Agre

56

I would like to express my gratitude to Jens Danielsson for your consistent,

skilful support and highly valuable input throughout the research projects.

Thank you for providing multiple perspectives and for encouraging me to

never leave no stone unturned to be able to interpret all the data obtained.

”Stick to the data” will for always be remembered.

I wish to show my deepest gratitude to Jinghui Luo, who I have had the

fortune to work together with on multiple projects. Thank you very much for

all support, scientific advices, and excellent supervision. I have learned very

much, all from basic knowledge to new and innovative methods and strategies

to study amyloid-related questions and beyond. I am incredibly grateful for

the opportunity to visit your lab and group in Switzerland for exciting research

projects and modern research facilities, we did accomplish a lot of work in

only two weeks!

Jüri Jarvet, thank you for always sharing your knowledge and for

providing straight answers to all my questions. There have been many

interesting discussions over the years. I am forever grateful for everything I

learned from you. Thank you for teaching me about FCS measurements.

Britt-Marie Olsson, thank you for being the kindest person, always being

so happy and friendly. I wish to address the importance of your assistance that

has been invaluable in this process. Thank you!

I would like to pay my special regards to Göran Eriksson, thank you for

all of your help and for sharing your knowledge and beautiful paintings. Thank

you for being both a good colleague and for your invaluable friendship.

Henrik Biverstål, thank you very much for all your help in the lab and for

insightful and enlightening discussions.

Sabrina Sholts, thank you very much for being so friendly, welcoming and

for accepting me as an internship student for a few weeks in your lab in

Washington DC. By far one of the best experiences, to work and to learn new

things in an American lab setting with questions concerning bones, metals,

ancient water bottles and health.

Furthermore, my warmest and deepest gratitude to everyone, who showed

an interest in our research, did ask questions on conferences/meetings,

questioned our work, supported us with constructive criticism, wrote

constructive review comments to improve our papers, and provided reality

checks for new perspectives. I am incredibly grateful for the opportunity of

being part of the chemical- and amyloid communities for a few years.

I would like to acknowledge all past and present lab members of the

Gräslund lab that I had the opportunity to meet and work with. Thank you

very much for all these years. Thanks to all members of DBB, including the

administrative and technical personnel who are invaluable for us working

in the lab. Thank you. I wish to pay my special regards to Ann-Britt Rönnell,

Alex Tuuling, Erik Sjölund and Matthew Bennett, and former employees

Haidi and Torbjörn Astlind, for your endless support and persistent help. I

57

would like to express my gratitude and appreciation to the academic crew at

DBB. It truly has been a wonderful/interesting time.

Ida Nyqvist and Johan Berg, what would I have done without you when

we were facing our first year as lab assistants? You made the teaching

responsibility highly enjoyable and you also inspired me with your technical

teaching skills and problem-solving approaches. As a plus, or really the most

important thing, the students were happy too. I also want to express my

gratitude towards Agneta Norén, the great course leader of the course. Thank

you - Teamwork makes dreamwork.

A sincere appreciation and deepest gratitude to our collaborators over the

years, with special thanks to Mazin Magzoub, Elzbieta Glaser, Pedro Teixeira,

Salma Al-Adwani, Peter Bergman, Anders Olofsson, Oleg Antzutkin, Lynn

Kamerlin, Birgit Strodel, Jan Pieter Abrahams, Yashraj Kulkarni, Qinghua

Liao, Ludmilla Morozova-Roche, Igor Iashchishyn, Jonathan Pansieri, Istvan

Horvath, Guy Lippens, Shai Rahimipour, Leopold Ilag, and Alex Perálvarez-

Marín.

Current and former colleagues, friends, and inspirers/motivators:

Alexandra Toth, Andreas Carlström, Ann Tiiman, Axel Leppert, Biao Fu, Britt-Marie

Sjöberg, Candan Ariöz, Carmela Vazquez Calvo, Cecilia Bergqvist, Cesare Baronio,

Chenge Li, Christian Brown, Christoph Loderer, Ghada Nouairia, Elin Roos, Ellinor

Haglund, Eloy Vallina, Emma Danelius, Fan Yang, Faraz Vosough – thank you for

all your help and wise advices, Fatemeh Madani – thank you for your help with lipid

vesicles preparations, Henry Ampah-Korsah, Hongzhi Wang, Huabing Wang,

Huixin Yu, Inna Rozman Grinberg, Jakob Dogan, James Cumming, Jan Aaseth,

Jean-Philippe Demers, Jinming Wu, Joan Patrick – thank you for always being so

friendly, smart, graceful, and for English language advices, Joanna Lachowicz, Jobst

Liebau, Johannes Björnerås, Lisa Lang, Magdalena Rzepka, Margareta Sahlin,

Matthiew Fielden, Maurizio Baldassarre, Médoune Sarr, Mikael Oliveberg,

Mingming Xu, Monica Nordberg, Nadejda Eremina, Nicklas Österlund, Ornella

Bimai, Pascal Meier, Paul Sumar, Philip Williamson, Pia Harryson, Pontus Petterson,

Riccardo Diamanti, Rolf Loch, Rosita Cappai, Sabeen Survery, Sarah Leeb, Seongil

Choi, Scott Ayton, Sofia Gama, Stefan Nordlund, Syed Razaul Haq, Sylwia Król,

Therese Grönlund – thank you for your endless enthusiasm, for your honesty and

good advices, Thibault Viennet, Tim Hofer, Vladana Vukojevic, Weihua Ye, Xin Mu

– thank you all very much. If I have forgotten anyone I apologize. I have had the

fortune to meet you and I will forever be grateful. Best wishes to you all.

I am grateful for my former neighbors Harold Shapiro and Max Tegmark,

and the cousin of my father, Stefan Rosén, for being a substantial inspiration

for me by their own academic pursuits.

I wish to acknowledge present and absent Family, Friends, Relatives,

Mormor , Mamma, Pappa, sister Lotta, my dear husband Martin and our

highly beloved cat companion Helga Tassimo Onatopp Mörman for your

endless support and great love – Mahalo, you all mean the most to me. You

are Everything. Aloha.

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59

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