t all 2005-07-15

Studies of Amyloid Nanostructure

Sumner Makin

Clare College

University of Cambridge

This dissertation is submitted for the degree of Doctor of Philosophy.

2

Preface

This dissertation is the result of my own work and includes nothing which is the

outcome of work done in collaboration except where specifically indicated in the text.

3

Acknowledgements

Thanks to my supervisor Louise Serpell for her active encouragement, guidance and

assistance throughout the project. Thusnelda Stromer for extensive discussions, her

patience in testing Clearer and helpful feedback.

I am very grateful for the assistance provided by our collaborators. Professor Atkins

for detailed discussions and access to facilities. Pawel Sikorski for his outstanding

help with data collection, discussions and substantive suggestions for Clearer. Gayatri

Chavali for her help with data collection, particularly the supply of a cryo-loop for

alignment. Jan Johansson for the supply of the KFFEAAAKKFFE peptide. James

Elliot for help with data analysis and Sam MacDonald for assistance with early data

collection.

Professor David Lomas and his group were invaluable; Didier Belorgey, Robin

Carrell, Damian Crowther, Mark Davies, Kerri Kinghorn, Meera Mallya, Elena

Miranda, Richard Page, Russell Phillips, Lynda Sharp and Alison Warrington for the

meetings, support and discussions.

Professor Randy Read and his group for providing a friendly environment, which was

conducive to work.

Brenda Sumner and Nick, Seth, Tristan and Gully Makin, for their love, support and

wonderfully critical reading.

4

Abstract

Amyloid fibril self-assembly, from a disparate group of soluble precursor peptides, is

central to the pathology of many diseases. Knowledge of the structure and formation

of these fibrils is critical to the understanding required for the rational design of drugs

capable of inhibiting fibrillogenesis and promoting disaggregation. Amyloidogenic

potential is thought to be an almost universal property of protein. It is therefore

desirable that the three-dimensional structure and architecture of amyloid be

understood. The insolubility and texture of the amyloid fibrils frustrate the usual

techniques of X-ray crystallography and solution nuclear magnetic resonance.

We have investigated the structure of amyloid fibrils formed from various peptides,

including islet amyloid polypeptide (type II diabetes) and designed peptides.

Computer programs have been written which enable structural analysis using data

from X-ray fibre diffraction, electron microscopy and electron diffraction. Our

twelve-residue, sequence-designed peptide forms fibrous nano-crystallites, which

diffract to high resolution (> 0.1 nm). Our analyses favour a hydrogen-bonded �-sheet

as the fundamental crystalline entity within these fibrils and show how the fibril is

held together. Fine structural details have been revealed, including salt-bridges and �-

� bonding between adjacent phenylalanine residues. Consequently, the data from

many different fibrils contributes to the understanding of the formation and structure

of the generic amyloid fibril.

5

Abbreviations

Å Angstroms

AA Amyloid A

AAAK Peptide with sequence KFFEAAAKKFFE

A� Amyloid beta peptide

AFM Atomic force microscopy

APP Amyloid precursor protein

apoSAA Apolipoprotein serum amyloid A

BSE Bovine spongiform encephalopathy

CD Circular dichroism

CJD Creutzfeldt-Jakob disease

CR Congo red

Cryo-EM Cryo electron microscopy

DQCSA Double quantum chemical shift anisotropy

DRAMA Dipolar decoupling at the magic angle

DRAWS Dipolar coupling in a windowless sequence

ED Electron diffraction

6

EM Electron microscopy

EPR Electron paramagnetic resonance

fpRFDR-CT Finite-pulse radio-frequency driven recoupling constant time

FT Fourier transform

FTIR Fourier transform infrared spectroscopy

H1 First predicted �-helical region, residues (109-122) of cellular prion

hCT Human calcitonin

HDX Hydrogen-deuterium exchange

HypF-N N-terminal domain of the bacterial hydrogenase maturation factor

HypF

IAPP Islet amyloid polypeptide (amylin)

IgLC Immunoglobulin light chain

JAI Java advanced imaging library

MAS Magic angle spinning

MS Mass spectrometry

MQNMR Multiple quantum nuclear magnetic resonance

NMR Nuclear magnetic resonance

PDB Protein data bank

7

PrP Prion protein

PrPC Prion protein, cellular form

PrPSc Prion protein, scrapie form

REDOR Rotational echo double resonance

RR Rotational resonance

SANS Small angle neutron scattering

SAXS Small angle X-ray scattering

SDSL Site directed spin labelling

SH3 Src-homology 3 domain

SSNMR Solid state nuclear magnetic resonance

STEM Scanning transmission electron microscopy

TEM Transmission electron microscopy

TTR Transthyretin

XD X-ray diffraction

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Contents

Preface ...................................................................................................................... 2

Acknowledgements ................................................................................................... 3

Abstract..................................................................................................................... 4

Abbreviations............................................................................................................ 5

Contents .................................................................................................................... 8

Table of Figures ...................................................................................................... 16

1 Introduction ..................................................................................................... 20

1.1 Biological Background............................................................................. 20

1.1.1 Definition of Amyloid ...................................................................... 20

1.1.2 Amyloid in Disease .......................................................................... 21

1.1.3 Alzheimer’s Disease Amyloid .......................................................... 26

1.1.4 Amyloid and Oligomer Toxicity....................................................... 27

1.1.5 Protein Folding and Misfolding ........................................................ 29

1.1.6 Natural Amyloid-Like Products........................................................ 30

1.1.7 Bionanotechnology Applications...................................................... 30

1.2 Current Understanding of Amyloid Structure ........................................... 31

1.2.1 Introduction...................................................................................... 31

9

1.2.2 Problems Associated with Studying Amyloid Structure.................... 33

1.3 Techniques Used to Examine Amyloid Structure ..................................... 33

1.3.1 The Use of Synthetic Peptides for Studies of Amyloid Structure ...... 33

1.3.2 X-ray Diffraction.............................................................................. 34

1.3.3 Electron Microscopy ........................................................................ 36

1.3.4 Electron Diffraction.......................................................................... 39

1.4 Other Techniques Used to Examine Amyloid Structure............................ 41

1.4.1 Fourier Transform Infra Red Spectroscopy....................................... 41

1.4.2 Atomic Force Microscopy ................................................................ 42

1.4.3 Neutron Scattering ........................................................................... 44

1.4.4 Hydrogen-Deuterium Exchange ....................................................... 45

1.4.5 Solid State Nuclear Magnetic Resonance.......................................... 46

1.4.6 Other Methods ................................................................................. 49

1.5 Electron Microscopy Theory.................................................................... 50

1.5.1 Beam Specimen Interaction.............................................................. 50

1.5.2 Imaging............................................................................................ 52

1.6 Diffraction Theory ................................................................................... 53

1.6.1 Introduction...................................................................................... 53

10

1.6.2 Fourier Transform ............................................................................ 53

1.6.3 Convolution Theorem....................................................................... 53

1.6.4 Sample Texture ................................................................................ 55

1.6.5 Ewald Sphere ................................................................................... 55

1.6.6 Problems .......................................................................................... 59

1.7 Experimental Methods for X-ray Fibre Diffraction................................... 60

1.7.1 Introduction...................................................................................... 60

1.7.2 Glass Capillary and Stretch Frame.................................................... 60

1.7.3 Magnetic Field ................................................................................. 61

1.7.4 Mat .................................................................................................. 62

2 Application for the Structural Analysis of Amyloid ......................................... 64

2.1 Abstract ................................................................................................... 64

2.2 Introduction ............................................................................................. 64

2.3 Preparation............................................................................................... 66

2.3.1 Format Conversion........................................................................... 66

2.3.2 Centring ........................................................................................... 66

2.3.3 Background Removal ....................................................................... 67

2.3.4 Contrast Enhancement...................................................................... 71

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2.4 Peak Measurement................................................................................... 72

2.4.1 Automated........................................................................................ 72

2.4.2 Manual............................................................................................. 73

2.5 Unit Cell Determination........................................................................... 74

2.5.1 Search .............................................................................................. 74

2.5.2 Spot Position Predictor..................................................................... 76

2.6 Simulation of Amyloid Fibre Diffraction Patterns .................................... 77

2.6.1 Sampling of Intensities in Reciprocal Space ..................................... 77

2.6.2 Reflection Shape .............................................................................. 80

2.6.3 Structure Factors .............................................................................. 81

2.6.4 Other Factors.................................................................................... 82

2.6.5 Optimisation..................................................................................... 83

2.6.6 Automation ...................................................................................... 84

2.6.7 Testing ............................................................................................. 84

2.7 Other Features.......................................................................................... 86

2.7.1 Introduction...................................................................................... 86

2.7.2 Fourier Space Operations ................................................................. 86

2.7.3 Determining the Repeat Distance from Micrographs ........................ 86

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2.7.4 General Features .............................................................................. 88

2.7.5 PDB Display and Manipulation ........................................................ 89

2.7.6 Image Mathematics .......................................................................... 90

2.8 Discussion ............................................................................................... 90

2.8.1 Comparison of Clearer with Other Programs .................................... 90

2.8.2 Application Use ............................................................................... 91

2.8.3 General Improvements ..................................................................... 92

2.8.4 Specific Improvements..................................................................... 93

2.9 Conclusion............................................................................................... 94

3 Characterisation of Islet Amyloid Polypeptide Fibrils ...................................... 95

3.1 Abstract ................................................................................................... 95

3.2 Introduction ............................................................................................. 95

3.3 Methods................................................................................................... 98

3.3.1 Peptide and Incubation ..................................................................... 98

3.3.2 Electron Microscopy ........................................................................ 98

3.3.3 Cryo Electron Microscopy................................................................ 98

3.3.4 Electron Diffraction.......................................................................... 99

3.3.5 X-ray Diffraction.............................................................................. 99

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3.4 Results ....................................................................................................100

3.4.1 Negative Stain Electron Microscopy................................................100

3.4.2 Platinum/Carbon Shadowed Electron Microscopy ...........................100

3.4.3 Cryo Electron Microscopy...............................................................101

3.4.4 Electron Diffraction.........................................................................103

3.4.5 X-ray Diffraction.............................................................................105

3.4.6 Structural Interpretation...................................................................108

3.5 Discussion ..............................................................................................109

3.5.1 General Fibril Morphology..............................................................109

3.5.2 Understanding of Structure Derived from Diffraction Data..............110

3.5.3 Hypothetical Modelling...................................................................111

3.5.4 Conclusion ......................................................................................112

4 Molecular Basis for Fibril Formation and Stability .........................................114

4.1 Abstract ..................................................................................................114

4.2 Introduction ............................................................................................114

4.3 Methods..................................................................................................116

4.3.1 Peptide and Incubation ....................................................................116

4.3.2 Electron Microscopy .......................................................................116

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4.3.4 X-ray Diffraction.............................................................................117

4.3.5 Structural Determination .................................................................117

4.4 Results ....................................................................................................118

4.4.1 Electron Microscopy .......................................................................118

4.4.2 X-ray Fibre Diffraction ...................................................................118


4.4.4 Indexing..........................................................................................120

4.4.5 Modelling........................................................................................122

4.5 Discussion ..............................................................................................129

4.5.1 The Role of Side-chains in Amyloid Formation and Structure .........129

4.5.2 Conclusion ......................................................................................131

5 Discussion ......................................................................................................133

5.1 Models of Amyloid Structure..................................................................133

5.1.1 Introduction.....................................................................................133

5.1.2 Largely Native Structures ................................................................133

5.1.3 Water-Filled Nanotube ....................................................................136

5.1.4 General �-Helices............................................................................138

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5.1.5 Cross-� Tubule................................................................................140

5.1.6 Conventional Cross-� Structure.......................................................141

5.2 Conclusion..............................................................................................155

6 Bibliography...................................................................................................157

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Table of Figures

Figure 1.1 The characteristic cross-� pattern 21

Figure 1.2 Schematic showing cleavage of A� from APP 27

Figure 1.3 Structural hierarchy in amyloid fibrils 32

Figure 1.4 Structure of transthyretin amyloid 35

Figure 1.5 Fibre diffraction patterns of A� (11-25) 36

Figure 1.6 Electron microscope images of A� (11-25) and A� (1-40) fibrils 39

Figure 1.7 Electron diffraction pattern from IAPP amyloid fibrils 41

Figure 1.8 Atomic force micrograph of Sup35 fibrils 44

Figure 1.9 Summary of NMR distance information for A� (10-35) 48

Figure 1.10 Diffraction geometry 56

Figure 1.11 Side view of the diffraction geometry showing circle traced out by a reflection 57

Figure 1.12 Side view of the diffraction geometry; the circle centred at the fibre axis does not intersect with the Ewald sphere 58

Figure 1.13 Side view of the diffraction geometry; the case in which no diffraction occurs 58

Figure 1.14 Unaligned A� (1-40) fibrils and stretch frame aligned A� (11-25) fibrils 60

Figure 1.15 Stretch frame used to align fibrils 61

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Figure 1.16 Orientation of fibres after alignment 63

Figure 2.1 Procedure for processing general fibre diffractograms 66

Figure 2.2 Centring of the diffraction pattern 67

Figure 2.3 Image histogram and cumulative frequency distribution 70

Figure 2.4 Circularly symmetric background reduction 70

Figure 2.5 Comparison of electron diffraction pattern with contrast-enhanced version 72

Figure 2.6 Screenshot of the automated peak finder 73

Figure 2.7 Manually measuring the resolution of a peak 74

Figure 2.8 Indexing of reflections and determination of the unit cell 76

Figure 2.9 Diffraction simulation window for MacOS X 77

Figure 2.10 Process by which simulated diffractograms are calculated 79

Figure 2.11 Reflection shapes for a true fibre and the general case 81

Figure 2.12 Simulated and empirical diffraction patterns for A� (11-25) fibrils 85

Figure 2.13 Simulated and empirical diffraction patterns for cellulose triacetate I 85

Figure 2.14 Graph relating visibility to length of box 85

Figure 2.15 Superposition of images 89

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Figure 3.1 Negative stain electron micrograph of IAPP amyloid fibrils 100

Figure 3.2 Platinum/carbon shadowed electron micrograph of mature IAPP amyloid fibrils 101

Figure 3.3 Cryo-electron micrographs of IAPP fibrils and Fourier transform 103

Figure 3.4 Electron diffraction patterns before and after dehydration 105

Figure 3.5 X-ray fibre diffraction patterns from IAPP fibrils 107

Figure 4.1 Negative stain electron micrographs of AAAK amyloid 118

Figure 4.2 X-ray fibre diffraction pattern from amyloid nanocrystals 119

Figure 4.3 Electron diffraction pattern from the fibrous nanocrystals 120

Figure 4.4 Comparison between simulated and observed diffraction patterns for incorrect model 125

Figure 4.5 Comparison between simulated and observed diffraction patterns for proposed model 126

Figure 4.6 Orientations of aromatic rings 127

Figure 4.7 Structure of amyloid nanocrystals 128

Figure 5.1 Pair of transthyretin molecules 135

Figure 5.2 Transthyretin amyloid fibrils 136

Figure 5.3 Perutz’s model of amyloid 138

Figure 5.4 Antiparallel �-helix 140

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Figure 5.5 Possible structure of A� (1-40) 141

Figure 5.6 Models of insulin fibrils 144

Chapter 1. Introduction

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1 Introduction

1.1 Biological Background

1.1.1 Definition of Amyloid

Rokitansky is generally credited with the first description of amyloid in 1842 as a

firm, greyish, “lardaceous-gelatinous” substance infiltrating the livers of patients with

syphilis and tuberculosis (Rokitansky 1846). In 1854, Rudolph Virchow gave amyloid

its name after noticing that it stained pale blue with iodine and sulphuric acid, similar

to corpora amylacea in brain tissue. He believed that it was similar to cellulose and

consequently amyloid means starch (amylase) like (Virchow 1854; Sipe and Cohen

2000). It is now known that this is due to associated proteoglycans and

glycosaminoglycans and that the core of amyloid is protein (Snow et al. 1987;

Kisilevsky and Snow 1988).

Amyloid fibrils are formed by the polymerisation of a normally soluble, non-toxic

protein into extracellular, insoluble aggregates with a large molecular weight.

Amyloid is defined by a series of empirical observations. Specific chemical staining

forms part of the definition. After staining with Congo red (CR), plaques composed of

the fibrils appear orange in tissue sections. An apple green birefringence pattern is

seen when the stained sample is viewed between crossed polarisers, (Puchtler et al.

1961; Puchtler and Sweat 1965). The birefringence is due to an ordered structure in

which dye binding sites are symmetry related (Carter and Chou 1998). Amyloid can

be extracted using a water purification method (Pras et al. 1968). Binding to the

histological benzothiazole dye thioflavine T results in a shift in fluorescence (LeVine

1993). Neither dye is completely specific but each empirical observation forms part of

the definition. The aggregates are rich in �-structure, with resistance to proteolysis

and even strong chemical denaturants. Circular dichroism (CD) and Fourier transform

infrared spectroscopy (FTIR) both show a high percentage of �-structure (Hilbich et

al. 1991). X-ray diffraction reveals a characteristic pattern, similar to that observed in

silk fibroin and described as cross-�. The cross-� pattern is comprised of two


21

reflections, a sharp one at 4.7 Å parallel to the direction of the fibre and a more

diffuse spot between 10 and 11 Å perpendicular to the fibre direction (Figure 1.1)

(Eanes and Glenner 1968). Electron microscopy (EM) reveals fibrils that are

unbranching, 70 to 120 Å in diameter and of indeterminate length (Cohen et al. 1982).

Figure 1.1. The X-ray fibre diffractogram of amyloid has a characteristic cross-� pattern, with

the 4.7 Å reflection along the same direction as the fibrils.

1.1.2 Amyloid in Disease

The diseases collectively known as the amyloidoses are characterised by the

deposition of extracellular amyloid fibrils. These are generally divided into five

subdivisions; systemic, hereditary, central nervous system, ocular and other localized

amyloidoses (Sipe and Cohen 2000). A substantial number of human and animal

amyloidoses have been described to date (Table 1.1 and Table 1.2, respectively).

Further examples continue to be found; amyloid deposits have been discovered in the

cell-free fraction of bronchoalveolar lavage fluid in patients with pulmonary alveolar

proteinosis (Gustafsson et al. 1999). Whilst amyloid is defined to be extracellular,

there are intracellular deposits thought to be otherwise of the same structural class.

X-ray beam

Bundle of fibres

Equ

ator

ial d

irect

ion

4.7 Å

10-11 Å


22

These include paired-helical filaments formed from tau in Alzheimer’s disease

(Grundke-Iqbal et al. 1986), Lewy bodies formed from �-synuclein in Parkinson’s

disease (Spillantini et al. 1998) and polyglutamine huntingtin deposits in

Huntington’s disease (Chen et al. 2002). Perhaps the correct nomenclature for such

material is amyloid-like. Nevertheless, the literature does not generally use such a

term (Perutz et al. 2002) and the distinction becomes impractical in the case of

amyloid formed from synthetic peptide fragments or proteins not normally associated

with disease.


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Table 1.1. Classification and nomenclature of the human amyloidoses, assembled from (Husby et al. 1994; Kelly 1996; Sunde et al. 1997; Xing and Higuchi

2002; Blumenthal 2004).

Amyloidogenic protein Precursor to Amyloidogenic Protein Syndrome

Immunoglobulin light chain (IgLC) or fragments of VL domain

Monoclonal immunoglobulin light chain (i.e. � or �)

AL amyloidosis: primary isolated or associated with multiple myeloma

AH Immunoglobulin heavy chain (�) AH amyloidosis: isolated

76-residue N-terminal fragment of amyloid A (AA)

Apolipoprotein serum amyloid A (apoSAA)

Secondary systemic amyloidosis: resulting from infections, chronic inflammation, tumours, familial Mediterranean fever, tumour necrosis factor receptor associated periodic syndrome, Muckle-Wells syndrome

Mutant transthyretin Mutant transthyretin Familial amyloid polyneuropathy I and II

Transthyretin (TTR) or its fragments Native transthyretin Senile systemic amyloidosis

�2-microglobulin �2-microglobulin Haemodialysis related amyloidosis: associated with chronic endstage renal failure

Approximately 90-residue apolipoprotein A-I N-terminal fragments

Apolipoprotein A-I variants Familial amyloid polyneuropathy III

Apolipoprotein A-II Apolipoprotein A-II Familial amyloidosis


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71-residue gelsolin fragment Gelsolin Familial amyloid polyneuropathy IV

Lysozyme or its fragments Lysozyme variants (not native) Hereditary non-neuropathic systemic amyloidosis (Ostertag-type)

110-residue cystatin C fragment Cystatin C Hereditary cerebral haemorrhage

Amyloid � peptide (A�) (39 to 43 residues)

Amyloid precursor protein (APP), native and variants

Alzheimer's disease, Down syndrome, hereditary or sporadic cerebral amyloidosis

Prion protein, scrapie form (PrPSc) (not cellular form, PrPC)

Prion precursors, native and variants Transmissible spongiform encephalopathies, including kuru, Creutzfeldt-Jakob Disease (CJD) and variant Creutzfeldt-Jakob Disease

Calcitonin or its fragments Procalcitonin Medullary thyroid carcinoma associated amyloidosis

Atrial natriuretic factor Atrial natriuretic factor Isolated atrial amyloidosis

Islet amyloid polypeptide (IAPP) Pro-islet amyloid polypeptide Type 2 diabetes, insulinoma

Insulin Insulin Injection localised amyloidosis, insulinoma

Prolactin Prolactin Aging pituitary prolactinoma

ABri BRI-L Familial British dementia


25


Keratoepithelin Keratoepithelin Keratoepithelin amyloidosis: lattice dystrophies of the cornea

Lactoferrin Lactoferrin Familial cornea amyloidosis

Lactadherin Lactadherin Aortic medial amyloidosis

Keratin Keratin Primary localised cutaneous amyloidosis

Fibrinogen �-chain variant fragments Fibrinogen �-chain variants Hereditary renal amyloidosis


26

Table 1.2. Classification and nomenclature of animal amyloidoses (Xing and Higuchi 2002).

Amyloid protein Precursor Syndrome

PrPSc Prion precursors

Transmissible spongiform encephalopathies, including scrapie (sheep and goat) and similar bovine (BSE), feline, mink, elk and mule deer diseases.

AA Apolipoprotein serum amyloid A Reactive AA amyloidosis (mouse)

Apolipoprotein A-II Apolipoprotein A-II Mouse senile amyloidosis

The amyloidoses are often cited as examples of post evolutionary disease (Csermely

2001; Dobson 2002). Modern medical practices are one cause of such disease. �2-

microglobulin accumulates during blood dialysis, which after several years, results in

skeletal deposition of amyloid (Gejyo et al. 1985; Gejyo et al. 1986). Cannibalism in

members of the Fore tribe in Papua New Guinea caused kuru. Bovine spongiform

encephalopathy appeared as a result of feeding cows with animal material,

demonstrating an infectious route for amyloidosis (Gajdusek 1988). Many

amyloidoses are diseases of old age and the incidence of such disease has grown as

life spans have increased over the last century. In addition to humans, a relationship

between aging and amyloidosis has been examined in mice, hamsters, cats, dogs,

cattle, ducks and horses (Blumenthal 2004).

1.1.3 Alzheimer’s Disease Amyloid

Alzheimer’s disease is the best-known amyloidosis. It is estimated to cost the US

economy some $100 billion annually (Ernst and Hay 1994). Alois Alzheimer, a

Bavarian neuropsychiatrist, first noted the disease. In November 1901, a patient

referred to as Auguste D. presented with an unknown brain disorder; the 1906 post-

mortem revealed lesions in the brain (Alzheimer 1907; Graeber and Mehraein 1999;

Gorman and Chakrabartty 2001). Some twenty years ago, the principal component of

these plaques was found to be amyloid formed from A� (Glenner and Wong 1984;


27

Masters et al. 1985). A� is a 4-kDa peptide cleaved from amyloid precursor protein

(APP) (Kang et al. 1987) by �-secretase (beta-site APP cleaving enzyme) followed by

�-secretase as shown in Figure 1.2. Most APP is degraded in the secretory pathway

before reaching the cell surface by �-secretase. A� is always present in healthy

subjects (Seubert et al. 1992) and is a result of normal proteolytic processing (Shoji et

al. 1992). The predominant A� species in vivo has forty residues, whilst A� (1-42) is

the major component of senile plaques and may nucleate amyloidogenesis (Jarrett et

al. 1993; Iwatsubo et al. 1994). All species of in vivo A� are able to cofibrilise

(Hasegawa et al. 1999). Alzheimer’s disease’s prominence among the amyloidoses

has resulted in substantial effort being expended in examining fibrils formed from A�

(Serpell 2000).

12345678901234567890123456789012345678901234567890 1 10 20 30 40

NH2 COOH

Extracellular Space Membrane Cytosol

VKMDAEFRHDSGYEVHHQKLVFFAEDVGSNKGAIIGLMVGGVVIATVIVITLVMLKK NL GQ VI X G F

NH2 COOH

40 42 43

�-Secretase �-Secretase �-Secretase

Swedish double mutation

Flemish mutation

Dutch mutation

Florida mutation

London mutations

Australia mutation

671 714

A�

APP

Figure 1.2. Schematic showing cleavage of A� from APP; the A� sequence is in bold type (Storey

and Cappai 1999; Burkoth et al. 2000). A dashed box indicates the transmembrane domain.

Vertical lines show the sites of secretase cleavage. Hydrophobic regions of A� are in blue.

1.1.4 Amyloid and Oligomer Toxicity

The amyloid hypothesis suggests that the formation and accumulation of amyloid is

central to disease pathology. Amyloid toxicity has been demonstrated on many

occasions (Kelly 1996; 1998b). Alzheimer's amyloid interacts with endothelial cells to

produce superoxide free radicals (Thomas et al. 1996; Hardy and Selkoe 2002) and is

responsible for the destruction of neurons (Lansbury 1999). Prion aggregates are

responsible for disease transmission in the transmissible spongiform encephalopathies


28

(Prusiner 1998). In other cases, it is the sheer quantity of amyloid; kilograms of this

material disrupt organs such as the liver or spleen (Tan and Pepys 1994; Pepys 1996).

The oligomer hypothesis takes the view that it is the oligomeric precursors to amyloid

which are primarily responsible for toxicity (Kirkitadze et al. 2002; Stefani and

Dobson 2003). Fibrils are clearly immobile which raises the question of how they can

effect change in nearby cells. One piece of evidence, apparently contrary to the

amyloid hypothesis, is that the degree of cognitive impairment shows poor correlation

with the quantity of amyloid deposited in the brain in Alzheimer’s disease (Morris et

al. 1996). Furthermore, studies using amyloid fibrils not associated with the

amyloidoses show that they can have a similar effect on cells as those made of

proteins linked to disease (Stefani and Dobson 2003). These include aggregates

formed from the src-homology 3 (SH3) domain of the phosphatidyl inositol-3-kinase

(Frederikse 2000) and the N-terminal domain of the bacterial hydrogenase maturation

factor HypF (HypF-N) (Chiti et al. 1999). The studies observed a series of well-

defined, pre-fibrillar species, which substantially impaired cultured cell viability.

Mature amyloid was not found to have any substantial effect on the cultures. This

implies that cytotoxicity is due to the supramolecular structure of pre-fibrillar

aggregates and not the amino acid sequence (Bucciantini et al. 2002). Alzheimer’s A�

oligomers have been studied in detail (Lambert et al. 1998; Hartley et al. 1999; Lin et

al. 1999; Walsh et al. 1999; Bhatia et al. 2000; Monji et al. 2000; Nilsberth et al.

2001; Walsh et al. 2002). Similar studies concerning familial amyloidotic

polyneuropathy (Sousa et al. 2001) and Parkinson’s disease (Conway et al. 2000b;

Goldberg and Lansbury 2000) have been conducted. These studies suggest that

oligomers may interact with cell membranes, leading to oxidative stress and increases

in free Ca2+ causing apoptosis or necrotic cell death.

It should not be concluded from the above studies that amyloid is unimportant. The

amyloid cascade hypothesis takes account of both oligomers and amyloid (Hardy and

Selkoe 2002). Neither should it be neglected that amyloid fibrils are large inactive

reservoirs of toxic species (Walsh et al. 2002). Contrarily, mature fibrils are a

potential sink for toxic agent. Any doubt as to harm caused by amyloid is removed in


29

those diseases in which amyloid forms the greater part of the diseased organ (Pepys

1996).

Once a link between amyloid and amyloidosis pathology has been established, the

fibril structure is more than intellectual curiosity. Understanding of the structure of

amyloid is necessary for the rational design of drugs to prevent aggregation and

promote disaggregation. One way in which such an agent can be devised is by using

peptide mimetics (Lashuel et al. 2000). Examples of agents have been conceived in

many cases (Kolstoe and Wood 2004), including IAPP (Kapurniotu et al. 2002;

Rijkers et al. 2002; Scrocchi et al. 2002) and A� (Tjernberg et al. 1996; Talaga 2001).

1.1.5 Protein Folding and Misfolding

Knowledge of amyloid structure also contributes to the understanding of protein

folding and misfolding. Amyloidogenic potential may be an almost universal property

of protein (Stefani and Dobson 2003). This important alternative protein-folding state

addresses fundamental aspects of biophysics. Indeed, a change in our understanding

of protein folding, previously established for soluble globular proteins, may be

required. Amyloid precursor proteins appear to be extremely diverse. There is

considerable variation in size and sequence (Fandrich and Dobson 2002) with

molecular masses varying from less than a single kilodalton to tens of kilodaltons.

Precursors do not share a common tertiary structure; they may even be unstructured or

�-helical. In spite of this, amyloid fibrils have a similar external morphology and

internal structure. The molecular basis of amyloid toxicity also seems to display

common features (Stefani and Dobson 2003).

Proteins not associated with disease have been shown to form fibrils in vitro. These

include SH3 (Guijarro et al. 1998), acylphosphatase (Chiti et al. 1999), cold shock

protein A (Alexandrescu and Rathgeb-Szabo 1999) and cold shock protein B (Gross

et al. 1999). Conditions for amyloid fibril formation include a low pH, lack of specific

ligands, high temperature and moderate concentrations of salts or co-solvents.

Although amyloid is very stable, there might be a significant activation energy barrier

to amyloidogenesis (Kusumoto et al. 1998). Mutations associated with hereditary


30

amyloidoses often destabilise the native state of the protein, thus reducing this barrier

(Kelly 1998a; Dobson 1999; Radford and Dobson 1999). Natural proteins in their

native states deploy several strategies to avoid intermolecular association of �-strands

(Richardson and Richardson 2002). Strategies include covering with helical or non-

repetitive structure, having no edges (�-barrel), a sharp bulge in the �-sheet or

prolines and charged residues. Statistical analysis of globular protein sequences shows

that nature disfavours both sequences of alternating polar and non-polar residues

(Broome and Hecht 2000) and clusters of several consecutive hydrophobic residues

(Schwartz et al. 2001). Most aggregation disease proteins are either secreted or

membrane bound, or a fragment of such a protein. Although the aggregated form may

have the lowest Gibbs energy (Gazit 2002a), the removal of the source of

unaggregated protein results in disaggregation (Pepys et al. 2002). It is therefore

important to know how these proteins adopt highly organised multi-molecular

structures that are not specifically encoded for in the sequence (Uversky 2002). This

is important in protein handling and production, where general protein aggregation is

a serious problem (Clark 1998).

1.1.6 Natural Amyloid-Like Products

Amyloid-like material is also a natural product (Kelly and Balch 2003), the earliest

example being the silk of the egg-stalk of the lacewing Chrysopa (Parker and Rudall

1957; Geddes et al. 1968). The cross-� structure is also found in mammalian ocular

lenses (Frederikse 2000) and it is hypothesised that fibrillar deposits of serum amyloid

A induce lysis of bacterial cells, thus protecting the host in chronic amyloid diseases

(Hirakura et al. 2002). Curli are highly aggregated amyloid-like fibres produced by

Escherichia coli and Salmonella (Chapman et al. 2002) and cross-� spider silk fibres

also have the characteristic features of amyloid (Li et al. 2001).

1.1.7 Bionanotechnology Applications

Finally, the emerging field of bionanotechnology offers industrial application for

amyloid (Zhang 2003; Waterhouse and Gerrard 2004). This requires a fundamental

understanding of the macromolecules, which are the elemental components from

which nanostructures are constructed. Nano-structural components require the


31

properties of structural compatibility and chemical complementarity. Amyloid

precursors satisfy this requirement, so investigation is needed to understand the

structure, assembly and dynamic behaviour of amyloid fibres (Mihara and Takahashi

2001; Zhang et al. 2002). By way of demonstration, a conducting nanowire was

constructed by using Sup35 amyloid as a natural scaffold to align gold particles

(Scheibel et al. 2003). Similarly, silver nanowires were also assembled; ionic silver

was reduced inside amyloid nanotubes formed from diphenylalanine (Reches and

Gazit 2003). A great many potential applications have been envisaged including using

fibrils in catalysis and electronics, as a plastic, a support for the growth of cells or a

therapy for treating humans and animals (Dobson and MacPhee 2004).

1.2 Current Understanding of Amyloid Structure

1.2.1 Introduction

The characteristic cross-� diffraction pattern gives insight into the basic structure of

amyloid. Peptides are in a �-strand conformation, with a distance of 6.9 Å between

adjacent pairs of residues along the direction of the chains (Figure 1.3). �-strands,

perpendicular to the direction of the fibre, are spaced 4.7 Å apart and laterally

associated to form a �-sheet ribbon. These �-sheets run along the direction of the fibre

and are stacked approximately 10 to 11 Å apart. The laminated �-sheets comprise the

protofilaments, which form the fibril (Figure 1.3). The ribbons may be twisted and the

protofilaments themselves intertwined (Lashuel et al. 2000). Protofilaments should be

distinguished from the pre-fibrillar intermediates known as protofibrils (Harper et al.

1997b; 1999; Walsh et al. 1999). Substantive evidence for protofilaments is provided

by electron microscopy. Helical reconstruction showed twisted structure for SH3 and

insulin fibrils (Jimenez et al. 1999; Jimenez et al. 2002). Similarly, intracellular

paired-helical filaments (Crowther 1991) have been shown to have a protofilament

substructure. Cross-sections of fibres analysed using single particle methods allowed

the number of protofilaments to be determined (Serpell et al. 2000b). In the case of

IAPP, the splitting of fibrils can be explained using protofilaments (Goldsbury et al.

1997), an electrolucent core may also be detected (Cohen et al. 1982; Serpell et al.

2000b).


32

70-120 Å

Single �-strand

�-sheets

Protofilament

Fibril

Two to six protofilaments

25-30 Å

4.7 Å

10-11 Å

6.9 Å

Figure 1.3. The structural hierarchy in amyloid. Fibrils are composed of protofilaments.

Protofilaments are built from laminated �-sheet ribbons.

Amyloid fibrils formed from the same precursor peptide may have different structures

at all levels of detail. Under the same experimental conditions, differing numbers and

organisations of protofilaments are observed, whilst the structure within the

protofilament appears to remain the same (Fraser et al. 1991b; Bauer et al. 1995;

Goldsbury et al. 1997; Jimenez et al. 1999; Bouchard et al. 2000; Jimenez et al.

2002). Several varieties of fibril may be present in a single electron micrograph. This

polymorphism was demonstrated in many types of in vitro amyloid, including A�,

calcitonin, IAPP, SH3 and insulin fibrils. Cryo-electron microscopy of insulin fibrils

combining helical reconstruction with single particle analysis revealed diverse low-

resolution three-dimensional fibrils containing two, four and six protofilaments.

Atomic force microscopy also revealed similar diversity in amyloid derived from A�

(Goldsbury et al. 2001) and �2-microglobulin (Kad et al. 2001; Kad et al. 2003).

Cryo-electron microscopy of ex vivo material from patients with hereditary non-

neuropathic, systemic amyloidosis demonstrated that spontaneous polymorphism is

also present in disease fibrils (Jimenez et al. 2001).

In the case that experimental conditions are changed, then both the arrangement of

protofilaments and their internal structure may differ. Polymorphism may be


33

attributed to staining conditions (Cohen et al. 1982), since ion concentration has been

shown to affect fibril conformation (Fraser et al. 1991b). Solid-state nuclear magnetic

resonance of fibrils formed from A� (11-25) and human calcitonin at various pHs

both showed structural diversity at the atomic level, whilst maintaining a cross-�

structure (Naito et al. 2004; Petkova et al. 2004).

1.2.2 Problems Associated with Studying Amyloid Structure

Structural studies of amyloid fibrils are impeded by a series of problems relating to

the characteristics of amyloid fibrils. They are neither three-dimensionally crystalline

nor soluble (Lansbury 1992; Kelly 1997), which prevents the use of conventional

techniques such as single-crystal X-ray crystallography and solution nuclear magnetic

resonance. Although amyloidogenesis resembles crystallisation (Jarrett and Lansbury

1993), single crystal formation has proved as difficult as for insoluble fibrous silk

proteins (Lotz et al. 1982). Disorder within the sample is a serious issue since it

reduces the amount of available information. Polymorphic structures also present

problems when attempting to compare data from X-ray diffraction and electron

microscopy (Diaz-Avalos et al. 2003a).

1.3 Techniques Used to Examine Amyloid Structure

1.3.1 The Use of Synthetic Peptides for Studies of Amyloid Structure

Structural examination requires as much order within the sample as possible. Ex vivo

material is rarely used, since synthetic samples can be grown in the conditions to

maximise orientational order. Additionally, synthetic peptides are more readily

available and purification is not required. Full-length peptides form amyloid that

appears to be less ordered than truncated versions. A� (11-25) amyloid fibrils have a

similar morphology and pH dependence as full-length A� (Fraser et al. 1991b) and

may form the core of fibrils formed from full-length A�. Similar results have been

shown for other A� fragments including A� (11-28), A� (13-28), A� (15-28) and A�

(29-42) (Castano et al. 1986; Gorevic et al. 1987; Halverson et al. 1990; Barrow and

Zagorski 1991; Fraser et al. 1991a; Barrow et al. 1992; Burdick et al. 1992; Fraser et

al. 1992b).


34

Other peptides, including human non-disease related peptides, such as SH3 and those

that are sequence designed are employed as amyloid precursors. These can be used to

investigate the generic nature of amyloidogenesis and the importance of side chain

interactions. Amyloid formed from proteins with four to six residues has all the

characteristics of fibrils formed from 100-residue peptides (de la Paz et al. 2002;

Reches et al. 2002; Tjernberg et al. 2002). The advantages of such an approach are a

far higher quality of experimental data, the fibrils being more amenable to alignment

and that it also allows the removal of disordered regions.

1.3.2 X-ray Diffraction

Much of the published information on protein structure is based on X-ray diffraction

data (XD). Detailed information at high resolution (approximately 1 to 3 Å) can be

obtained from the analysis of X-ray scattering patterns. Although single-crystal X-ray

crystallography is not possible, X-ray fibre diffraction has proved to be a very

powerful technique. The primary evidence for amyloid fibrils having a common core

structure composed of laminated, continuous �-sheets running along the fibre arises

from X-ray fibre diffraction (Eanes and Glenner 1968; Blake and Serpell 1996; Sunde

et al. 1997).

The cross-� pattern’s characteristic features were first described in diffraction from

the egg stalk of the lacewing Chrysopa (Geddes et al. 1968). The proposed structure

was formed from extended �-strands folded back on themselves, forming a �-sheet

25 Å wide. The �-ribbons described were flat and stacked face-to-face (Pauling and

Corey 1951). The same pattern was observed for amyloid formed from the Bence

Jones protein (Eanes and Glenner 1968).

Indexing of meridional diffraction signals suggested the presence of helical repeats.

Transthyretin amyloid was found to have a helical pitch of 115.5 Å, corresponding to

24 �-strands and a twist of 15 degrees per strand (Figure 1.4). A twisted �-pleated

sheet has been shown to have a lower free energy than an untwisted sheet (Chothia

1973). On this basis, a model of the core structure of the generic amyloid fibril was

built (Blake and Serpell 1996; Sunde et al. 1997).


35

Figure 1.4. The structure of transthyretin amyloid, based on X-ray diffraction data (Serpell et al.

1997).

Examination of peaks on the equator of X-ray diffraction patterns allows the number

and arrangement of protofilaments to be interpreted. A� (1-40) fibrils were modelled

using three to five tubular protofilaments, each built from a pair of �-sheets

(Malinchik et al. 1998). Small angle X-ray scattering (SAXS) studies on fibrils

formed from a wide variety of A� fragments arrived at similar models involving

hollow cylinders (Lu et al. 2003) or bundles thereof (Inouye et al. 1993). In one case

it was not possible to distinguish between an 86 Å diameter tubule or walls of cross-�

sheets 71 Å apart (Kirschner et al. 1987). Difficulties may also arise in the event of

polymorphism being present in the sample.

Much of the early work on amyloid used fibrils formed from A� fragments and

mutants thereof (Kirschner et al. 1987; Halverson et al. 1990; Fraser et al. 1992b;

Inouye et al. 1993; Fraser et al. 1994; Inouye and Kirschner 1996). A detailed

structure of A� (11-25) fibrils was built based on X-ray fibre diffraction data

(Sikorski et al. 2003). Diffraction patterns were recorded from the magnetically

aligned specimen using three mutually orthogonal beam directions, one of which was

parallel to the magnetic field. All three patterns were different, suggesting that the

fibrils are composed of crystallites with a preferred orientation. The A� (11-25)

peptide was in an extended �-strand conformation; these �-strands were then stacked

to form an antiparallel �-sheet. The pseudo-unit cell was monoclinic (� = 122°) with

dimensions a = 9.42 Å, b = 25 Å and c = 6.9 Å. There was therefore a slip along the

chain direction of 6.9 Å, which is twice the length of an amino acid unit in an

extended � conformation.

Other studies have postulated similar cross-� structures from X-ray data in the cases

of amyloid fibrils formed from short prion protein (PrP) fragments (Nguyen et al.


36

1995); the first predicted �-helical region, residues (109-122) of PrPC (H1) (Inouye

and Kirschner 1996); eleven-residue N-termini of the apoSAA family (Kirschner et

al. 1998) and IAPP (Makin and Serpell 2004b).

a

b

c

a

b

c

Figure 1.5. Fibre diffraction patterns from A� (11-25) fibrils (Sikorski et al. 2003). Images a and

b are perpendicular to the direction of preferred orientation, while image c is parallel to the fibre

axis.

1.3.3 Electron Microscopy

Transmission electron microscopy (TEM) is a form of microscopy in which the

properties of the specimen are measured in terms of the specimen’s interaction with a

beam of electrons. This beam is passed though lenses composed of electric and

magnetic fields allowing very high-resolution data to be obtained in a manner

analogous to the operation of a light microscope. Electron microscopy does not

require a crystalline sample and the result need not be implicitly averaged as with

neutron and X-ray diffraction experiments. Unfortunately, the contrast of micrographs

of many biological samples is poor and increasing the flux of the electron beam to

compensate results in damage to the specimen. Cryo electron microscopy (cryo-EM)

reduces the radiation damage by cooling the specimen using liquid nitrogen or

helium. Alternatively, the specimen may be stained with a material such as uranyl


37

acetate; however the image will be of the stain rather than the specimen itself; hence

little information about the interior of the fibril is revealed. Shadow electron

microscopy involves imaging heavy metal atoms that had previously been deposited

at an angle, delivering improved definition of vertical features. EM is a visual

technique, which allows the examination of a sample to confirm the presence of

ordered fibrils (Figure 1.6).

Much of the information about the number of protofilaments involved in the fibril

substructure is derived from EM (Kirschner et al. 1987; Fraser et al. 1991a; Fraser et

al. 1991b; Serpell et al. 1995; Goldsbury et al. 1997; Jimenez et al. 1999; Serpell et

al. 2000b; Jimenez et al. 2001; Jimenez et al. 2002). Groups of filamentous structures

wound around a common axis are sometimes observed, whilst cross-sections show

between three and six units composing the fibril. Single particle analysis combined

with helical reconstruction of micrographs has revealed low-resolution three-

dimensional structures of insulin fibrils with two, four or six protofilaments (Jimenez

et al. 2002). As discussed earlier, polymorphism may arise spontaneously or as a

result of the differing conditions for fibril formation.

Three-dimensional reconstruction of cryo-electron microscope images resulted in

low-resolution (≈25 Å) structures of protofilaments for amyloid formed from SH3

(Jimenez et al. 1999) and insulin (Jimenez et al. 2002). Ex vivo Asp67His lysozyme

and Leu60Arg apolipoprotein were also studied but structural variability and disorder

prevented reconstruction (Jimenez et al. 2001). A great diversity of helical fibrils was

observed. Single particle averaging and analysis was combined with helical

reconstruction, which dealt with the problem of variable pitch (Boettcher et al. 1996;

Jimenez 2000). The resulting structures showed how the protofilaments were arranged

around an electrolucent core. These structures implied possible arrangements of

strands within the protofilaments. The model suggested that protofilaments had the

same overall twist as the fibril itself. SH3 fibrils were composed of four

protofilaments with cross-section dimensions of 20 by 40 Å and a crossover repeat of

~600 Å. Insulin fibrils had a larger cross-section of 30 by 40 Å with crossover repeats

of between 355 and 900 Å depending on the number of protofilaments in the fibril.


38

Models of lysozyme fibrils, with a periodicity of ~3000 Å, were also constructed; a

six-protofilament model most closely matched the experimental results.

Images of fibrils composed of A� (11-25) compared to A� (1-42) showed that fibrils

formed from the shorter peptide were more consistently homogenous, straight and

uniform with higher contrast and better-defined edges (Serpell and Smith 2000).

Tjernberg found that making substitutions and deletions in the A� (14-23) peptide had

a significant effect on the morphology of the amyloid formed, however all A�

peptides longer than eleven residues formed fibrils of similar morphology (Tjernberg

et al. 1999). Structural elucidation of the protofilament has then proceeded by either

three-dimensional reconstruction (Jimenez et al. 1999) or direct visualisation (Serpell

and Smith 2000). Fourier transforms of regions of electron micrographs showed a

similar cross-� pattern to X-ray diffractograms and in the case of A� (11-25) fibrils,

striations 4.7 Å apart were visible. These striations perpendicular to the fibre axis

were clear after the application of translational averaging. They have been interpreted

as being stacks of �-strands. It was not known whether the fibril was twisted so the

fibre was cut into boxes containing a specified number of striations and boxes with

the same number of striations averaged along the fibre. Boxes containing six or

twelve striations gave qualitatively better results than those with four, eight or ten.

The core of the fibril also appeared to be electrolucent, which was consistent with

images of the cross-sections of cores that have been processed using single-particle

averaging techniques (Kirschner et al. 1987; Fraser et al. 1991a; Fraser et al. 1991b;

Serpell et al. 1995; Serpell et al. 2000b). Electron micrographs of A� (10-35) fibrils

showed a 1200 Å helical twist, allowing a model to be built (Lakdawala et al. 2002).

Scanning transmission electron microscopy (STEM) uses a smaller probe than TEM,

which scans across the image. It allows the mass per unit length of fibrils to be

determined by comparison with a standard, such as the tobacco mosaic virus. This

information can be combined with data from other techniques, especially nuclear

magnetic resonance, to build a model. A protofilament composed of a pair of �-sheets

was proposed for A� (1-40) fibrils (Antzutkin et al. 2000; Antzutkin 2004; Petkova et

al. 2004) and similar structures postulated for A� (10-35) and A� (1-42) fibrils


39

(Antzutkin et al. 2002). STEM complemented protease digestion, cryo-EM and mass

spectroscopy in the analysis of Ure2p, to build a model based on a cross-� core (Baxa

et al. 2003). In the study of a designed seventeen-residue peptide, STEM formed part

of a battery of techniques in conjunction with X-ray diffraction, TEM and nuclear

magnetic resonance (Kammerer et al. 2004). It can also be used simply as another

form of microscopy (Goldsbury et al. 2000a; Goldsbury et al. 2000b).

Figure 1.6. Electron microscope images showing the morphology of A� (11-25) and A� (1-40)

fibrils (Sikorski et al. 2003).

1.3.4 Electron Diffraction

Electron diffraction (ED) patterns are theoretically very similar to X-ray

diffractograms (Dyson 2004). A sample is illuminated with a beam of electrons and

the resulting diffraction pattern recorded using film or another detector. A sharp,

strong 4.7 Å reflection is normally very clear but little else can generally be seen.

Most examples of this type of pattern are from amyloid-like fibrils formed from �-

synuclein (Serpell et al. 2000a), paired-helical filaments (Berriman et al. 2003) and

polyglutamine fibrils (Perutz et al. 1994). In general fibre diffraction, high-resolution

reflections are spread over a greater volume in reciprocal space than those at lower

resolution, resulting in a lower relative intensity. If an electron beam is used, then the

relative intensity of high resolution reflections are further reduced owing to changes

in the structure factors. The structure factors for an electron beam are calculated from

the X-ray structure factors using the Mott formula, which involves division by the

distance from the origin in reciprocal space squared. Thus, the reflection intensity is


40

divided by a total factor proportional to the radius to the fourth power and hence some

reflections are much stronger than others. The incident electron beam also obscures

low angle data; it is very strong compared with the intensity of the reflections and

saturates the film, thereby preventing their recovery.

Electrons are charged and have a far stronger interaction with matter in comparison to

X-rays. Electron diffraction can therefore take advantage of a much lower beam width

than X-ray diffraction; hence a far smaller sample can be examined. This enabled

individual amyloid nanocrystals from a seven-residue peptide to be selected and the

diffraction patterns from single crystals recorded (Diaz-Avalos et al. 2003a; b). The

image area being diffracted from can be viewed in real space. Consequently, the

relative orientations of fibres and their diffraction patterns can be determined. Another

result of the strength of interaction is radiation damage; the microscope operator may

observe the diffraction pattern fading as the irradiated region is permanently damaged.

Long exposures increase the signal to noise ratio and reveal weak signals, whereas

short exposures ensure that the specimen remains intact.

Quantitative analysis of intensities is further impeded by the requirement for

calibration of the exposed film to establish the relationship between film transparency

and incident flux density. Other electron diffraction studies have used amyloid fibrils

formed from IAPP (Chapter 3) (Makin and Serpell 2004b), a twelve-residue sequence

designed peptide with sequence KFFEAAAKKFFE (see Chapter 4), scrapie prion

(Wille et al. 2002), Sup35 (King and Diaz-Avalos 2004) and the WW domain FBP28

(Ferguson et al. 2003).


41

4.7 Å

Figure 1.7. Electron diffraction pattern from IAPP amyloid fibrils (Chapter 3).

1.4 Other Techniques Used to Examine Amyloid Structure

1.4.1 Fourier Transform Infra Red Spectroscopy

A Michelson interferometer, with a movable mirror, has an interference pattern,

which is the Fourier transform of the spectrum of the source. In Fourier Transform

Infrared Spectroscopy (FTIR), this interference pattern is Fourier inverted to allow the

measurement of the absorbance spectrum of a sample (Jackson and Mantsch 1995).

Normal mode analysis of simple molecules allows the theoretical spectrum to be

calculated in these cases. The reverse of this process is not possible and different

structures may have indistinguishable absorption spectra.

Especially in conjunction with isotopic labelling (Anderson et al. 1996), FTIR is able

to distinguish between parallel and antiparallel arrangements and obtain detailed

information about the orientation of amide carbonyls. The amide I band, which is the

carbonyl stretching vibration of the amide group (1700 to 1600 cm-1), is sensitive to

�-structure. Evidence for antiparallel sheets involves splitting of the amide band into

low and high frequency bands due to strong inter-strand dipole coupling. Studies of

amyloid of various types observed a strong amide I band near 1630 cm-1 and a weaker

band near 1690 cm-1 (Hilbich et al. 1991; Fraser et al. 1992b; Conway et al. 2000a).

This spectrum was close to that simulated for Pauling’s cross-� structure (Krimm and

Bandekar 1986). Percentages of secondary structure were calculated by curve fitting


42

to the experimental spectrum. Unfortunately, another study showed that that the

position of bands should not be over-interpreted (Wilder et al. 1992), particularly

since amyloid might be regarded as being a separate class of structures. Therefore, the

presence of a low frequency amide band is a necessary but not sufficient condition for

the assignment of antiparallel �-structure (Lansbury 1992). Measurements on parallel

�-sheet protein showed that these amide I bands were not unique to antiparallel

structures (Khurana and Fink 2000). Booth used FTIR to show that there was some

residual helical and disordered fold in lysozyme fibrils (Booth et al. 1997); this more

flexible structure may surround the rigid core. FTIR provides the only support for the

�-sheets in full-length A� fibrils being in an antiparallel conformation (Halverson et

al. 1990; Hilbich et al. 1991). This was contradicted by solid-state nuclear magnetic

resonance studies, which were claimed to be more reliable, since the nuclear magnetic

resonance data was not based on purely empirical models (Yamada et al. 1998) or

normal mode calculations (Bandekar and Krimm 1988) that were based on

substantially simplified model systems (Antzutkin et al. 2000).

1.4.2 Atomic Force Microscopy

Atomic force microscopy (AFM) offers direct, high-resolution visualisation without

the requirement for averaging (Stine et al. 1996). The height of a solid probe over a

specimen surface is measured, with individual molecules examined in air or solution.

Physiological conditions are possible without the requirement for fixing or staining.

Time dependent aspects of the molecular interactions can be observed including the

molecular conformation and aggregation state.

In vitro assembly of amyloid, including fibrils and protofibrils, can be studied using

time lapse AFM. Thus, information about the directionality, growth rate and

morphology of individual protofibrils is obtained (Goldsbury et al. 1999). Atomic

resolution is not possible with biological samples, due to the end radii of available

tips, limiting this resolution to flat periodic structures, such as graphite. Fibrils imaged

using AFM appear larger than those in electron micrographs. Additionally, the tip-

sample interaction may also distort or destroy many soft biological samples. Tapping


43

rather than dragging the tip over the sample reduces but does not eliminate this effect

(Chamberlain et al. 2000).

Fibrils may be pre-assembled in a test tube, then absorbed on to a mica surface or

assembled on the surface. Different distributions of fibrils are formed in each case.

The cause is probably fibril immobilisation due to the constraining effect of the mica.

It is not known which better represents physiological conditions, since in vivo, there

are many surfaces, including cell membranes. Substantial work has been done on A�

(Harper et al. 1997a; Harper et al. 1997b; 1999) and amyloid formed from other

peptides, including IgLC (Ionescu-Zanetti et al. 1999), IAPP (Goldsbury et al. 1997)

and �2-microglobulin (Kad et al. 2001; Kad et al. 2003). The images showed that

growth was normally bi-directional (Blackley et al. 1999; Blackley et al. 2000) but

often blocked at one end. Protofibrils themselves were observed to be growing from

one end of a fibril (Goldsbury et al. 1999). Structural diversity and twisting

protofilament substructure were often observed (Kad et al. 2001).


44

1 �m

Figure 1.8. Atomic force micrograph of Sup35 fibrils (Stromer and Serpell, unpublished).

1.4.3 Neutron Scattering

Neutron diffraction (Bacon 1975) is similar to both electron diffraction and X-ray

diffraction. A beam of neutrons is fired at the sample and the scattering pattern

observed. Unlike electrons, neutrons have no charge and therefore do not interact with

the charges on the nuclei or electron clouds. Instead, neutrons have a nuclear

magnetic moment, resulting in an interaction with the nuclei of atoms making up the

specimen. This interaction makes it easier to detect light atoms, such as hydrogen, in

the presence of heavier ones, which would normally be expected to dominate the

interaction. Additionally, atoms with similar atomic numbers such as deuterium and

hydrogen, can be distinguished, allowing isotopic substitution for labelling purposes.

Radiation damage is largely eliminated, owing to the weak nature of the interaction.

Unfortunately, the technique is limited by the available neutron sources, which are

nuclear reactors and high-energy spallation sources.


45

Studies of micelle-like oligomers, involved in A� fibril formation, used curve fitting

of small angle neutron scattering (SANS) data to study a solution cooled to slow

fibrillogenesis (Yong et al. 2002). Spherocylindrical structures were modelled with

sizes consistent with the diffractogram. Likewise, A� (10-21) fibril formation was

monitored in the presence of zinc ions (Morgan et al. 2002a). X-ray and neutron

scattering studies showed that a crystallised human serum amyloid P component was

a pentameric species (Wood et al. 1988). Nuclear magnetic resonance and electron

microscopy studies of mature A� (10-35) fibrils were complemented by small angle

neutron scattering data (Burkoth et al. 2000).

1.4.4 Hydrogen-Deuterium Exchange

Hydrogens in a protein structure normally undergo rapid exchange with those in the

solvent. If the solvent contains deuterium, then this is exchanged into the protein, thus

increasing the protein’s mass. Determination of the quantity of incorporated

deuterium is normally accomplished using two-dimensional nuclear magnetic

resonance, mass spectrometry (MS) or FITR. The rate of exchange is dependent on

the protein structure and solvent accessibility. Therefore, by measuring protein

exchange, inferences about the protein dynamics can be made. Hydrogens bonded to

carbons do not, for the purposes of these experiments, exchange and those bonded to

heteroatoms on the side-chains generally exchange too rapidly to be detected.

Backbone amide hydrogen exchange rates can be measured, so information can be

gathered along the length of the backbone. All amino acids, except prolines, have

amide hydrogens. Proton exchange is much slower if the hydrogen is involved in a

hydrogen bond, as is the case in a �-sheet or �-helix. In contrast, solvent accessible

hydrogens will exchange very rapidly. Therefore, hydrogen-deuterium exchange

(HDX) does not provide a high-resolution three-dimensional structure but probes

structure at the resolution of a single residue (Li and Woodward 1999; Englander

2000). A problem is the loss of exchange information via back exchange during fibril

solubilisation.

Exchange protection in mature �2-microglobulin fibrils has been observed in a variety

of conditions, over large regions of the chain, including those in the native loops


46

(McParland et al. 2000; Hoshino et al. 2002; Yamaguchi et al. 2004). This suggested

a wide �-sheet or an ideal �-helix. This was also the case for cold shock protein A

fibrils, in which all amide protons were found to be protected from exchange

(Alexandrescu 2001). A study using A� (1-40) amyloid fibrils found that at least 50 %

of residues did not exchange even after a thousand hours of exposure (Kheterpal et al.

2000). These exchange times are not generally observed in globular proteins. Whilst

much of the protein exists in a highly protected, rigid core, a substantial proportion is

not involved in the protective �-sheet structure. In the case of A� (25-35) fibrils,

residues 28-35 formed this core (Ippel et al. 2002). Later studies on A� (1-40) fibrils

showed the N-terminus to be substantially better protected (> 50 %) than the C-

terminal segment (35 %) (Wang et al. 2003). Similarly, fibrils formed from lysozyme

had some residual helical and disordered fold present (Booth et al. 1997). Such

structures contradict the view that strong hydrogen bonding is present along the whole

length of the peptide.

1.4.5 Solid State Nuclear Magnetic Resonance

Nuclear magnetic resonance (NMR) is a well-established technique used to describe

the high-resolution structure of molecules. Nuclear spins are aligned by a large

magnetic field of the order of one Tesla. These spins are then perturbed by sequences

of radio frequency waves and the resulting electromagnetic output detected by means

of induction coils. Solution NMR is not possible due to amyloid being extremely

insoluble. Solid state NMR (SSNMR) refers to the use of NMR on condensed matter

that is neither liquid nor in solution (reviewed (McDowell and Schaefer 1996)).

Unfortunately, the spectral resolution of solid state NMR is orders of magnitude lower

than solution NMR. This line broadening, of the order of 10 kHz, is due to the

angularly dependent anisotropic interactions and dipole-dipole interactions between

nuclei in the solid. In liquids, these interactions are averaged out since the molecules

rotate rapidly and randomly. Chemical shift data can be obtained using magic angle

spinning (MAS). This can substantially reduce the line-width by spinning the solid

sample about an axis at 54.5˚ (the magic angle) to the external magnetic field

(Stejskal and Memory 1994). Relaxation measurements can be made by selectively

reintroducing weak dipolar recoupling.


47

If the angular speed is matched to a multiple of the chemical shift difference between

appropriate spins, then rotational resonance (RR) leads to recoupling. RR therefore

requires a substantial isotropic chemical shift difference in the homonuclear spin pair.

Techniques such as rotational echo double resonance (REDOR) (Gullion and Schaefer

1989) and dipolar decoupling at the magic angle (DRAMA) (Tycko and Dabbagh

1990) involve dephasing pairs of nuclei of the same isotope with no isotropic shift

difference. Dipolar recoupling in a windowless sequence (DRAWS) allows detection

of weak, dipolar-coupling interactions between spin ½ nuclei with substantial

chemical-shift anisotropies (Mehta et al. 1996; Gregory et al. 1997; Gregory et al.

1998). Constant-time finite-pulse radiofrequency-driven recoupling (fpRFDR-CT) is

also an example of a dipolar recoupling technique; it minimises distortions in the

experimental data due to pulse sequence imperfections (Ishii et al. 2001a).

In the case of amyloid, 13C labels are usually employed. Pulse sequences use the

direct dipolar interactions to allow the determination of distances between

strategically placed spin pairs (Figure 1.9). The dipolar interaction is inversely

proportional to the cube of the distance between the nuclei in the spin pair. It also

depends on the magnetic moments of the nuclei and the cosine of the angle between

the internuclear vector and the external magnetic field. More recently, multiple

quantum NMR (MQNMR) (Yen and Pines 1983) has been employed. Signals from

groups of coupled nuclear spins are detected; showing that labelled residues occur in

groups of a particular size. Measurement of internuclear distances using these

techniques is possible at up to 6 Å in favourable cases, with a standard error of

between 0.1 Å and 0.2 Å (Tycko 2000). Additionally, torsion angles and absolute

orientations of bonds and functional groups with respect to the external magnetic field

can be determined. Double quantum chemical shift anisotropy (DQCSA) and 2D

MAS exchange techniques both measure the relative orientations of a pair of 13C

tensors. These tensors depend on the orientations of the carbonyl groups and therefore

the torsion angles. Line widths indicate the degree of structural order.


48

5.7 4.9 5.1 5.7 4.9

5.6 5.1

11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35

5.1 5.1

5.2

5.5 5.8

Figure 1.9. Summary of NMR distance information for A� (10-35); this fits the model for a �-

strands being parallel and in register. No evidence for a �-turn is observed. (Data taken from

(Burkoth et al. 2000; Lynn and Meredith 2000).)

Most papers concerning SSNMR have reported on amyloid composed of truncated or

full-length A�. The exceptions were two early papers on two amyloidogenic

fragments, IAPP (20-29) (Griffiths et al. 1995) and hamster prion H1 (109-122)

(Heller et al. 1996). Both used rotational resonance to conclude that the structure was

composed of �-strands. Many studies concentrated on short truncated A� peptides and

found antiparallel �-strands in A� (34-42), A� (26-40), A� (26-43) and A� (16-22)

(Jarrett et al. 1994; Lansbury et al. 1995; Balbach et al. 2000). A cis linkage between

residues 37 and 38 was proposed (Spencer et al. 1991) but later concluded to be a

trans linkage (Costa et al. 1997). Parallel and in-register �-strands were found in a

series of DRAWS experiments on A� (10-35) (Benzinger et al. 1998; Gregory et al.

1998; Benzinger et al. 2000; Burkoth et al. 2000). Similarly, experiments using a

wide variety of NMR techniques on full-length A� revealed in-register parallel �-

sheets (Antzutkin et al. 2000; Balbach et al. 2002; Petkova et al. 2002; Antzutkin et

al. 2003). Line widths suggested a degree of structural disorder at the N-terminus.

Some non-� structure was found at residues 25, 26 and 29 (Antzutkin et al. 2003).

This may be necessary, since a fully extended �-strand is too wide to fit into the

diameter of fibres observed in micrographs and therefore there must be a turn

somewhere. The authors postulated the existence of a turn between �-sheets, though

this is not common in general protein structure.

Limitations on the distances measurable using SSNMR mean that it is often combined

with other techniques. Using the constraints established by SSNMR data, some


49

members of the ensemble of possible structures can be eliminated. STEM has been

used to obtain mass per unit length data so that a model may be constructed

(Antzutkin et al. 2000; Petkova et al. 2002). They did not however completely refute

the possibility of a �-helical structure. Whilst FTIR measurements generally indicated

antiparallel organisations of �-strands (Jarrett et al. 1994; Lansbury et al. 1995), they

were not consistent with later, more reliable NMR studies (see FTIR section). The

SSNMR investigation into A� (11-25) gave a pair of pH dependent structures,

different to that expected from X-ray studies under different conditions (Sikorski et

al. 2003; Petkova et al. 2004). This suggested that the �-strand packing is

environmentally dependent and the result may be explained by slippage along the

chain axis (Makin and Serpell 2004a).

1.4.6 Other Methods

Site directed spin labelling (SDSL) involves the use of electron paramagnetic

resonance (EPR) to determine structure at the level of the backbone fold in native-like

conditions. EPR uses the same principle as NMR but applied to unpaired electrons

rather than nuclei. Most stable molecules have closed shells without unpaired spins.

Unpaired spins are introduced by means of site specific labelling of engineered

cysteine residues with a sulphydryl-specific paramagnetic nitroxide compound. The

EPR spectrum depends on the structural microenvironment of the spin label including

its secondary structure, proximity to other spin labels and solvent accessibility. A

study of full-length A� fibrils found parallel in-register �-strands (Torok et al. 2002),

whilst a mostly native structure in a head-to-head, tail-to-tail arrangement was

proposed for amyloid formed from transthyretin (Serag et al. 2002).

Protease digestion leaves the cross-� core of the fibril. The technique was employed

to assign the �-turn position to be between residues 26 and 29 in A� (10-43) fibrils

(Hilbich et al. 1991). In the case of Ure2p it is disputed as to whether the fibrils are

amyloid at all. Although they have the characteristic birefringence pattern and

micrograph appearance, which in conjunction with mass spectrometry and protease

digestion suggest a cross-� structure (Baxa et al. 2003), other studies have used these


50

techniques to propose a structure is that largely native and therefore predominantly �-

helical (Bousset et al. 2004).

Selective mutation experiments have proved effective, including demonstrating the

effect of charge-charge interactions to stabilise �-sheet conformation (Fraser et al.

1994). Other studies have used amyloid formed from Sup35 mutated with cysteine

residues (Scheibel et al. 2001), rat IAPP with point mutations from human IAPP

(Green et al. 2003), A� (Serpell 2000), �2-microglobulin (Smith et al. 2003) and IgLC

(Hurle et al. 1994; Stevens et al. 1995). Finally, circular dichroism spectroscopy has

been applied to A� (10-43) and �-synuclein fibrils (Hilbich et al. 1991; Conway et al.

2000a) to describe the fibrils’ �-sheet content.

1.5 Electron Microscopy Theory

1.5.1 Beam Specimen Interaction

If electron microscopy is used to describe the structure of amyloid, it is necessary to

understand how the structure influences the image on the micrograph. As imaging

takes place using an electron beam, the interaction between the electron beam and the

specimen should be considered. The electrons in the column travel at speeds

comparable to the speed of light, hence relativistic quantum mechanics is required.

The requisite mathematical machinery requires the use of the Dirac equation.

Fortunately, the effect of spin can be neglected, as it represents only about 1 % of the

total interaction (Fujiwara 1961); meaning that a suitable first order approximation is

the Schrödinger equation, with relativistic corrections to the wavelength and electron

mass,

ψψψ EVmh

pf

=+∇− 22

2

2c

eVmm p

ef +=


51

epA meV

ceV

h

22

+��

��

�=λ

where me is the rest mass of the electron, � is the electron wave function, E is the total

energy of the electron, e is the charge on the electron, h is Planck’s constant, VA is the

accelerating voltage and Vp is the potential. Passing through a specimen changes the

potential in the Schrödinger equation and thus the wavelength of the electrons,

introducing a phase shift φ(x,y).

( ) ( )� ��

�

�

��

�

�−= dz

zyxyx

,,11

2,specimenvacuum λλ

πφ

( )( ) ( )( )� ��

�

�

��

�

�++�

�

��

� +−+��

��

�= dzmzyxVVec

zyxVVemeV

ceV

h esAsA

eAA ,,2

,,2

2 22πφ

Approximating this shows that passing through the specimen advances the phase by

( ) ( )��

��

�+= dzzyxV

cmeV

hem

yx se

Ae ,,12

, 2

πφ

where Vs(x, y, z) is the potential at a point (x, y, z) in the specimen, and the line

integral is parallel to the electron beam (Saxton 1980). This equation shows that by

finding the phase of the electron beam leaving the specimen, the projection of the

potential can be found. Once the projection is known, the potential at any point can be

calculated using the methods of three-dimensional reconstruction. The potential is

related to the charge density �s and permittivity of free space �0 by the Poisson

equation.

0

2

ερ s

sV −=∇


52

This is in contrast to X-ray diffraction, in which the scattering factors depend almost

entirely on the electron charge density; whereas electron scattering amplitudes are

also dependent on the nuclear charge.

1.5.2 Imaging

Let oψ be the object wave function, which is the wave function of the electrons

leaving the specimen and iψ the image wave function, that is, the wave function of

the electrons in the image plane.

The Fourier transforms of the image and object wave functions are related by the

wave function transfer function ( )kW (Teague 1983).

( ) ( ) ( )kkk oi W Ψ=Ψ

( ) ( )432

2exp kkk SCiDiW λπλ π+=

where λ is the electron wavelength, D is the defocus and SC is the spherical

aberration. Here 0>D is over focus. (There are also a number of envelope functions,

which are not shown here.) If the specimen is such that the phase of the object wave

function is small and the amplitude unity, then the weak phase object approximation

(Frank 1996) can be employed. This gives the result that the measured intensity is

twice the convolution of the phase of the object wave function with the inverse

Fourier transform of the imaginary part of the wave function transfer function,

[ ] ( )[ ] ( )432

22sinargFT2FT kk Soi CD λπλψψ π+= .

Within this approximation, the phase of the object wave function can be found simply

by dividing by

( )432

2sin2 kk SCD λπλ π+ ,

known as the contrast transfer function, in Fourier space.


53

1.6 Diffraction Theory

1.6.1 Introduction

Much of what is known about the three-dimensional structure of protein is from

diffraction studies. X-ray diffraction theory and fibre diffraction in particular are

covered in detail in many excellent books (Vainshtein 1966; Blundell and Johnson

1976; Fraser et al. 1976; Holmes and Blow 1980; Vibert and Squire 1987). This brief

summary illustrates how this theory relates to the included work.

The problem is the scattering of a beam of electrons from a sample. Formally, the

Huygens-Kirchhoff Integral should be solved. In the far field approximation, the

phase varies linearly across the aperture and Fraunhofer diffraction occurs. The three-

dimensional diffraction pattern is the three-dimensional Fourier transform of the

sample structure. The space in which the three-dimensional diffraction pattern exists

is known as reciprocal space.

1.6.2 Fourier Transform

Fourier transforms are written as capitals, hence the Fourier transform (FT) of a

function f(x) is written

( )[ ] ( ) ( )� � �∞

∞−

∞

∞−

∞

∞−

−== xxkx xk 3.2FT defFf iπ

Discrete Fourier transforms are used for computations in practice.

1.6.3 Convolution Theorem

The Fourier transform of the sample structure can be worked out by repeated

application of the convolution theorem. This theorem states that multiplication in real

space is equivalent to convolution in reciprocal space.

( )[ ] ( )[ ] ( ) ( )[ ]xxxx gfgf *FTFTFT =


54

The sample is composed of a series of crystallites at varying angles. These crystallites

can be thought of a being a small part of an infinitely large crystal. This crystal is

constructed from a lattice of parallelepiped shaped building blocks (unit cells). Points

on the lattice rlmn are defined by linear combinations of integer multiples of three

lattice vectors { }cba ,, .

cbar nmllmn ++=

These unit cells are themselves composed of identical symmetry related objects

known as the crystallographic asymmetric units. The space group defines the number

and orientation of asymmetric units. Mirror and inversion symmetries are not allowed

since proteins are chiral and only one type of enantiomer is allowed.

A real space sample can be represented by a series of multiplications and

convolutions. The Fourier transform of the unit cell is the molecular transform. The

Fourier transform of the lattice is another lattice. This reciprocal lattice has reciprocal

lattice vectors { }*** ,, cba calculated using

( )cbacba

××=

.* , ( )cba

acb×

×=.

* , ( )cbabac×

×=.

*

Points on the reciprocal lattice *r , with Miller indices [ ]lkh are defined thus

**** cbar lkhhkl ++=

Structure factors Fhkl are the values of the molecular transform at rhkl*.

The crystallites have a finite size, which is equivalent to multiplying an infinite crystal

by a cut-off function, such as a top hat function. Hence, by applying the convolution

theorem, the infinitely narrow spots are convolved with the Fourier transform of the

cut-off function. So the result is a lattice of spots of finite size. Next, the orientational

disorder is applied by convolving the lattice of spots with an angular function,

representing the distribution of crystallites. In the case of a true fibre, the crystallites


55

are randomly distributed about the fibre axis. As a result, the spots are convolved with

circles centred on the fibre axis and in planes perpendicular to this axis; the diffraction

produced is equivalent to a rotation photograph. Hence fibre diffraction patterns have

layers of reflections perpendicular to the fibre axis, known as layer lines.

1.6.4 Sample Texture

Texture is a description of the distribution of fibril orientations (Kocks et al. 1998). It

determines the shape of the reflection in reciprocal space and hence affects both the

shape and intensity of the signals on the diffractogram. In general, the texture can be

complicated (Detavernier et al. 2003), however amyloid fibrils are relatively simple.

In the case of a true fibre, there is a rotational degree of freedom about the fibre axis;

this results in a diffraction pattern with infinite cyclic symmetry about that axis. The

diffraction pattern’s symmetry is like that of a rotating single crystal experiment;

however there is also disorder in the orientations of individual fibrils about the mean.

Sample texture depends on the method of alignment, the precursor peptide and the

experimental conditions.

1.6.5 Ewald Sphere

The diffractograms observed by the detector are two-dimensional. Only points lying

on the surface of a sphere in reciprocal space satisfy the geometrical requirements for

diffraction to occur. Given the position of a lattice point, the corresponding position

of the reflection on the detector can be calculated (Figure 1.10).


56

Figure 1.10. The diffraction geometry, a sample lattice point (xlattice, ylattice, zlattice) in red and its

circle are shown, diffraction occurs where this circle intersects with the sphere. The resulting

signal on the detector plate has the coordinates (ximageplate, yimageplate).

To achieve this, the position of the reflection on the Ewald sphere must first be

determined. The constraint provided by the Ewald sphere is

( ) 22sphere

2sphere

2sphere 11 λλ =+++ zyx

In the case that the fibre axis is parallel to the y-axis then there are three possibilities.

If the circle intercepts with the Ewald sphere (Figure 1.11), then the condition is

2lattice

2lattice

2sphere

2sphere zxzx +=+ and latticesphere yy =

X-rays

Ewald sphere

Detector

x

z

y


57

These three equations can be solved to give:

( )2lattice

2lattice

2lattice2

1sphere zyxz ++−= λ

( )22lattice

2lattice

2lattice

2412

lattice2

latticesphere zyxzxx ++−+±= λ

Figure 1.11. Side view of the diffraction geometry shows the circle traced out by the reflection

(red) intersecting with the Ewald sphere at (xsphere, ysphere, zsphere) (green).

Alternatively, the circle may not intercept with the Ewald sphere, in which case the

angular disorder perpendicular to this circle is important in giving the circle a finite

thickness on the surface of a sphere (shown in red, Figure 1.12) and the equations are

as follows:

2lattice

2lattice

2lattice

2sphere

2sphere zyxzy ++=+ and 0sphere =x

( )2lattice

2lattice

2lattice2

1sphere zyxz ++−= λ

( ) ( )22lattice

2lattice

2lattice

2412

lattice2

lattice2

latticesphere zyxzyxy ++−++= λ

2lattice

2lattice zx +

y

z x

( )latticelatticelattice ,, zyx

( )imageplateimageplate, yx

( )spherespheresphere ,, zyx

latticey


58

Figure 1.12. The circle centred at the fibre axis (y-axis) does not intersect with the Ewald sphere.

Nevertheless diffraction may still occur since the diffraction circle has a finite thickness and is

represented by a two-dimensional circular surface on the surface of a sphere (red).

There is no intercept if 22lattice

2lattice

2lattice 4 λ>++ zyx (Figure 1.13).

Figure 1.13. The case in which no diffraction occurs. The radius of the sphere containing the

lattice point is greater than the diameter of the Ewald sphere.

y

z x


( )imageplateimageplate, yx

( )spherespheresphere ,, zyx

2lattice

2lattice

2lattice zyx ++

y

z x


2lattice

2lattice

2lattice zyx ++

λ2


59

Once the position on the Ewald sphere is known, the position of the spot on the image

plate can be calculated

1sphere

sphereimageplate +

=λ

λz

Dxx ,

1sphere

sphereimageplate +

=λ

λz

Dyy

1.6.6 Problems

Diffraction detectors only measure the intensity of the wave function, not its phase. In

single crystal X-ray diffraction, the integrated intensity of reflections is measured and

after the application of intensity correction factors, the amplitude of the structure

factors can be calculated.

In order to calculate the structure of the sample from its structure factors, both the

amplitude and phase of the structure factors are required. The absence of the phase

information is known as the phase problem. Crystallographers are able to solve this

problem using a variety of methods including molecular replacement, multiple

isomorphous replacement and anomalous dispersion. Neither is there a problem in

electron microscopy, in which phases can be experimentally determined under the

weak phase object approximation. Fibre diffraction structures are generally

determined by modelling a structure and then comparing the simulated diffractogram

with the observed pattern. The most prominent exceptions are the use of isomorphous

replacement to determine the structure of the tobacco mosaic virus TMV (Stubbs and

Diamond 1975) and molecular replacement in the case of the ribgrass mosaic virus

(Wang et al. 1997).

Overlapping reflections can also be a problem, further reducing the amount of

information available. Reflections may overlap due to angular disorder or the diffuse

nature of the signals. The choice of the Lorentz intensity correction factor also

depends substantially on the sample texture (Vainshtein 1966). These make

calculation of the intensity of individual reflections difficult or impossible.


60

1.7 Experimental Methods for X-ray Fibre Diffraction

1.7.1 Introduction

The quantity and quality of diffraction information is very dependent on the amount

of order in the sample (Lorenz and Holmes 1993). The general problem was first

considered in the case of tobacco mosaic virus fibrils (Bernal and Fankuchen 1941).

In the absence of alignment, the pattern is a series of concentric rings; if there is some

alignment, the reflections form arcs (Sunde et al. 1997) (Figure 1.14). Investigators

therefore wish to align fibrils with respect to one another, which may achieve a high

degree of orientation and a diffraction pattern with far more information (Sikorski et

al. 2003). The correct technique and maximum degree of orientation depends strongly

on the type of fibre.

Figure 1.14. Comparison of unaligned A� (1-40) amyloid fibrils (left) and stretch frame aligned

A� (11-25) fibrils (right). Arrows indicate the location of the 4.7 Å reflections.

1.7.2 Glass Capillary and Stretch Frame

Long fibres are likely to be very viscous and thus a stretch frame will yield the best

results. The frame can be used to mount a pair of glass capillaries. These capillaries

are sealed flat using melted wax and a droplet rests between the two (Figure 1.15).

The fibrils orient parallel to the capillaries as the drop dries over several hours

(Damas et al. 1995; Sunde et al. 1997) (Figure 1.16). A threaded arrangement allows


61

the capillaries to be separated gradually during drying, leading to some stretching of

the fibre sample, although the sample may break even without stretching.

Laterally aggregated samples can also be encouraged to align by drying them down to

form a disk. This can be obtained by drawing 2 to 3 cm of solution into a siliconized

capillary of 0.7 mm diameter and then allowing the solution to dry.

Figure 1.15. A stretch frame can be used to align fibrils. Inset shows sample suspended between

the waxed ends of two glass capillaries. The capillaries are attached to the stretch frame by

means of Plasticine.

1.7.3 Magnetic Field

Most filamentous macromolecular assemblies are oriented by magnetic fields

(Glucksman et al. 1986). Magnetic alignment is more appropriate for samples

composed of small crystallites, which are grown in a magnetic field. Alignment of

these samples can be achieved using a 2.4 Tesla permanent magnet (Hummingbird

Sample

Capillary Wax

Stretch frame

Plasticine


62

Instruments, Arlington, MA). The fibrils are oriented parallel to the direction of the

magnetic flux density vector (Figure 1.16). Bond resonance in certain side-chains

causes anisotropy in the diamagnetic susceptibility, resulting in a force on the fibrils

and thus a preferred orientation (Worcester 1978; Pauling 1979; Glucksman et al.

1986). The sample is prepared in the same manner as for a disk, with the sample

placed between the poles of the magnet and dried over several weeks. Kirschner first

used this to study A� and its fragments (Inouye et al. 1993). Magnetic alignment has

also proved very effective for the alignment of other amyloid fibrils (Inouye and

Kirschner 1997; Malinchik et al. 1998; Sikorski et al. 2003).

1.7.4 Mat

Alternatively, a thin flat film can be formed with the fibres aligned parallel to the

plane of the film (Figure 1.16). A larger volume of solution is required and the film

must be mounted such that the X-ray beam can be passed both in the plane of film and

perpendicular to that plane.

The mat can be produced by depositing solution on a glass slide, drying and detaching

the residue from the substrate. Whilst this method has been successfully applied in the

case of poly-amino acids (Fandrich and Dobson 2002), removing the mat from the

surface can be difficult if the mat is brittle, perhaps owing to short fibres. Parafilm

and Teflon can also be used as a substrate and the mat has been used for aligning

polymers, AA (Turnell et al. 1986) and polyglutamine fibrils (Perutz et al. 2002). To

avoid problems with lifting off the mat, a cryo-loop (Hampton) normally used to

freeze single crystals can be employed. The loop is immersed in the fibril solution and

then lifted out to dry, resulting in a film across the plane of the loop (Makin and

Serpell 2005).


63

Figure 1.16. Illustration of the orientation of fibres after alignment by stretch frame, cryo-loop

and magnetic field (from top to bottom). Block arrows indicate the X-ray beam directions.

Magnetic Field

Chapter 2. Application for the Structural Analysis of Amyloid

64

2 Application for the Structural Analysis of Amyloid

2.1 Abstract Amyloid has a characteristic cross-� structure. Structural studies of amyloid

necessarily reflect its characteristics. The examination of amyloid structure is

impeded by problems peculiar to amyloid. Existing applications, which are not

specific to amyloid diffraction, have difficulty with these issues and are unable to

exploit amyloidal features. We have therefore developed a suite of programs

specifically for the study of amyloid fibre diffraction patterns. It is also suitable for

many general fibre diffraction problems.

Our Java based application (Clearer), employs a series of libraries to process

experimental data, particularly X-ray and electron diffractograms. Components within

the suite aid and automate crucial elements in the sequence of analysis. Background

subtraction and contrast enhancement allow weak signals to be observed and then

peak profiling gives their resolutions. The indexing process is semi-automated, so the

user can obtain the unit cell. Finally, simulation of diffraction patterns ensures that

structures modelled using an external program can be tested and compared with the

experimental diffractogram. This allows the structure of amyloid to be examined in

detail.

2.2 Introduction The purpose of the application was to facilitate the process of examining amyloid

structure. Both portability and usability were intrinsic to the design; these made Java

(Sun Microsystems) the obvious choice of language. Rapid application development

and the Java Advanced Imaging library (JAI) enabled better use of development

resources. The aim was to be as user friendly as possible. Accordingly, the system

was built with a modern graphical user interface and without batch files, lists of

parameters or idiosyncratic user-interface metaphors. Sensible defaults and clear

language were also essential to help new users and enable rapid working.


65

Each component was developed in response to a specific practical requirement.

Development proceeded as a response to issues arising from the analysis of the

peptides described in Chapter 3 and Chapter 4. Feedback from users was crucial, both

in terms of demand for features and human-computer interaction issues.

We have benefited greatly from the availability of ancillary software. The underlying

image processing engine relies on the Java Advanced Imaging library, in which many

of its methods are available as C routines for speed. One-dimensional graphs are

displayed by JFreeChart. The molecular visualisation component allows protein data

bank (PDB) files to be viewed; this was based on an existing application (Jmol),

implemented with the assistance of Jmol developers.

The sequence of analysis for fibre diffraction patterns generally involves several

stages (Figure 2.1). First, the image is prepared for processing, including removing

the background. Secondly, the required data is extracted from the image. Finally, this

data is processed to reveal information about the structure of the sample.

Amyloid samples suffer from low crystallinity, small crystal size and lack of good

packing. A carefully chosen processing strategy is required to make best use of the

available data. Each stage is analysed in turn.


66

Figure 2.1. Flowchart showing the procedure for processing general fibre diffractograms. Based

on (Stubbs 1999).

2.3 Preparation

2.3.1 Format Conversion

A very wide variety of image formats are output by detectors and used by diffraction

processing programs. The range of formats in general use is even greater. Writing

input filters is time consuming and does not result in new structures. The CCP13

website lists some 22 types, before accounting for byte order and other nuances. We

therefore chose to limit the input to those available from the underlying library

including RAW, BMP, GIF, JPEG, PNG, PNM and TIFF. Marcvt (Marresearch,

Norderstedt), Fit2D (A. Hammersley, ESRF), Denzo (Otwinowski and Minor 1997)

and XCONV (CCP13) all offer the ability to convert the output of detectors into TIFF

files, which are compatible with most image processing applications.

2.3.2 Centring

The centre of the pixel array collected from the detector rarely matches the centre of

the beam. It is therefore necessary to realign the image so that systematic error does

not affect the following analysis. Figure 2.2 shows the component used for this

Structure Modelling

Image Analysis

Indexing

Image Processing

Format Conversion


67

purpose. On the right, traces along the x and y axes in the positive and negative

directions will line up once the image is properly centred. Pressing the calculate

button crudely calculates the optimum x and y shifts by comparing peak positions on

each of the traces. Alternatively, blue concentric rings are overlaid so the process can

be completed by eye.

Figure 2.2. The user can centre the diffraction pattern to prevent the introduction of systematic

error into the analysis.

2.3.3 Background Removal

The background is unwanted low frequency data, which is added to the diffraction

pattern. Reasons for its existence include detector-specific noise (fog) and white

radiation – the incident beam not being completely monochromatic. Additionally X-

ray scattering from air, the sample holder, amorphous material in the specimen such

as solvent and disordered polymer and components of the camera all contribute. The

background may show a high level of variation across the field and is a source of error


68

in intensity measurements. In the case of electron diffraction, the background is

particularly strong and weak spots may be obscured.

There are three types of methods to determine the background, experimental

measurement, simulation and estimation from the diffractogram. The diffraction

experiment can be repeated without the sample; this method does not account for

amorphous scattering from the sample and is time consuming, as it must be repeated

many times. Computational simulation is unreliable since a great many parameters

must be estimated to be input into the model, which may not correctly simulate the

amorphous scattering. Finally, the background can be estimated from the spaces

between reflections in the diffractogram. This estimation is difficult if layer lines

overlap, which is often a problem at larger radii. We implemented several methods of

estimation.

The simplest form of background estimation is to calculate the local mean, using a

box filter. Each pixel is replaced by the average of the pixels in a box centred on its

position. Since the background is low resolution, a large box is used and the

calculation may require a large number of calculations. It may be better to do the

calculation in Fourier space. A box filter is a convolution operation, so it is equivalent

to multiplication by a sinc function in reciprocal space. Alternatively, the box may be

replaced by a Gaussian, so the effects of the sharp box edges are avoided. This

method can also be used for background removal in electron micrographs.

In single crystal X-ray crystallography, the individual reflections are small; hence an

inclined plane is a suitable function for the local background (Rossmann 1979). Early

attempts employed a similar strategy, using a series of inclined planes or splines.

Unfortunately, amyloid’s angular disorder results in large reflections, many of which

may overlap. Therefore, a single, global function, interpolated from the gaps between

signals, may be more appropriate. One approximation is that the background varies

linearly with the polar angle, with the parameters determined using a set of

experimental and computationally derived values (Fraser et al. 1976). Alternatively,


69

the lower orders of two-dimensional cylinder function expansion can be calculated

using selected points between layer lines (Millane and Arnott 1985).

If the background is circular, other methods are appropriate. A polynomial fit to the

circularly averaged image is surprisingly effective. The beam stop must be excluded

and non-quadratic polynomials are prone to over fitting. We have developed a

statistical approach in which the image is divided into concentric circular annuli, each

one pixel thick. If an annulus contains a signal, its histogram (intensity frequency

distribution) will be the sum of two approximately normal distributions (Figure 2.3).

These are a tall, narrow Gaussian at low intensities from the background and a low,

wide distribution at higher intensities due to the reflection. The aim of the program is

to determine the mean of the background distribution. If the background distribution

has a roughly constant standard deviation, then it is only necessary to determine the

mean plus a constant offset. The algorithm finds the background intensity by

considering the cumulative frequency distribution and using a user supplied value for

the minimum percentage of the image that is background. A value of 50 % was found

to work well in most cases (Figure 2.4). Care should be taken not to introduce

artefacts by underestimating the percentage of any annulus occupied by the signal,

since this will result in overestimation of the background intensity at some

resolutions.


70

Cum

ulat

ive

Fre

que

ncy

Intensity

Fre

que

ncy

Intensity

Figure 2.3. Illustrations of the image histogram (left) and cumulative frequency distribution

(right). By analysing the cumulative frequency distribution, the background intensity can be

determined.

For the case that the background is not circularly symmetric, an iterative approach can

be used (Ivanova and Makowski 1998). Experimentation is required to determine the

correct number of iterations; too many can result in an estimation with many of the

foreground’s features present as artefacts.

Figure 2.4. Circularly symmetric background reduction on an electron diffraction pattern,

before (left) and after (right).


71

2.3.4 Contrast Enhancement

Weak spots appear to be obscured when displayed, both by the background and also

the range of intensities in the image. Changing the display’s minimum and maximum

intensity values, corresponding to black and white, can reveal these signals. Values

that reveal some signals will obscure others. We therefore seek a method of changing

the intensities such that the whole image can be surveyed (Figure 2.5). Electron

diffraction images are particularly affected, as discussed in Chapter 1.

The image is first divided into single pixel wide, concentric annuli; then, an

appropriate contrast stretch is performed on each annulus and the image reassembled.

The contrast stretch requires the selection of intensity values corresponding to black

and white. Three different methods were developed. The first simply used the

minimum and maximum values from the annulus. Secondly, the stretch used

minimum and maximum values from the corresponding annulus in the locally

averaged image. Finally, the image histogram of each annulus was analysed and the

distribution of intensities normalised such that all the annuli in the output had the

same means and standard deviations.

The best method depends on the noise level in the diffractogram and level of

enhancement required. The first gives the most aggressive enhancement of signals but

also increases the noise. This is particularly visible if there are no reflections at a

particular radius. Using a locally averaged image reduces the effect of high-frequency

noise by making the stretch aware of the annulus’ surroundings. The final method is

also less sensitive, since it largely eliminates the effects of outliers on the choice of

minimum and maximum values. More aggressive methods are also prone to

introducing artefacts such as the white bands visible in Figure 2.5. Random noise can

be reduced by locally averaging the image beforehand, although this also softens bona

fide reflections.


72

Figure 2.5. Comparison of original electron diffraction pattern (left) with contrast-enhanced

version (right). Spots barely visible in the original are clear in the enhanced image.

2.4 Peak Measurement

2.4.1 Automated

After viewing peaks, their d-spacings must be determined. Peak finding greatly

speeds up this process and delivers more accurate results, since measurements are

based on a large proportion of the reflection rather than simply the maximum point.

The user supplies the angular range to be studied, the expected peak width in pixels

and the diffraction settings and the process is as follows.

The diffractogram is divided into user-specified circular sectors (wedges) and one-

dimensional radial averages calculated for each. A local mean of the radial average

based on the expected peak width ensures that high frequency noise is not counted as

a peak. Approximate maxima are found by double differentiation, whilst checking for

clipping. Finally, the actual maximum is determined by fitting an inverted parabola to

the peak using the raw values centred on the approximate maximum. This generates a

list of peak radii from which their spacings and relative intensities are calculated

(Figure 2.6).


73

Figure 2.6. Screenshot of the automated peak finder. The radially averaged diffractogram, in this

case averaged over the full 360°, is shown on the left.

2.4.2 Manual

Following the peak finding measurements, it is wise to check the results visually

(Figure 2.7). The peak finder may be confused by salt or dust, or give incorrect results

if the user supplied expected peak width is very wrong. If the reflections are diffuse,

then a small signal may appear as a shoulder in a much larger peak. Interactive

resolution calculation and a zoom function allow rapid verification of the calculated

values and the peaks can be sorted into categories prior to finding the unit cell. Peak

measurements were tested by comparing results from other programs and back

calculating data from simulated diffractograms.


74

Figure 2.7. Manually measuring the d-spacing of a peak using a zoomed-in image.

2.5 Unit Cell Determination

2.5.1 Search

The first stage of modelling is to find the unit cell and thus index the reflections.

Powder diffraction programs often assign incorrect Miller indices to amyloid fibre

diffraction patterns, since they are unable to distinguish whether a reflection is

meridional or equatorial. They also generally require far sharper reflections than are

available for amyloid. The search space is very wide since there are six variables (a,

b, c, �, � and �). The use of prior information may limit the search. Other data, such as

electron diffraction, may show that the cell is orthorhombic. The cross-� pattern

implies that the a dimension will be a multiple of 4.7 Å and b will be a multiple of a

value between approximately 10 and 11 Å. The other dimension may be a multiple of

the length of an extended �-strand, calculated as the product of 3.5 Å and the number

of residues. Adjustment may be required if the cell is not orthorhombic. Most amyloid


75

models in the literature use an orthorhombic cell and monoclinic cells are rare

(Sikorski et al. 2003); therefore not all angles need necessarily be considered. The

volume of the unit cell must also be sufficient to contain a whole number of peptides,

which further restricts the allowed values.

The program is supplied with a list of d-spacings, broken into the categories of

equatorial, meridional and other, defined by reference to restrictions on Miller indices.

Whilst a more fine-grained system was supported by the underlying code, mock-ups

of these user interfaces proved to be overcomplicated.

Unfortunately, the indexing method may output spuriously large values for the Miller

indices, if the corresponding unit cell dimension is large. It is therefore sometimes

better to restrict initially the type of input d-spacing and only use equatorial

reflections, since they correspond to the largest cell dimensions. Once this is done, the

meridionals and off meridionals can be considered.

Improvement of the user supplied unit cell uses a grid search. Given a unit cell and set

of d-spacings with appropriate constraints, the peaks are indexed by a least absolute

error between calculated and observed values. The total error for this unit cell is

calculated by summing the lowest errors for each d-spacing. Then, the process is

repeated for all possible unit cells on a six-dimensional grid. The user determines the

search width and spacing of the points on the grid. Once the optimum unit cell is

selected, the search width in every direction is halved and the process repeated a user-

specified number of iterations. The result is a table, comparing the experimental and

calculated resolutions (Figure 2.8). This table can be saved as an HTML file to be

viewed in a web browser or pasted into another program. Comparison of calculated

and back-calculated results, both with and without random error, was used to test the

veracity of the method.


76

Figure 2.8. Indexing of reflections and determination of the unit cell is carried out using this

window. The user supplies the initial guess, how far the program should look for improved

values and the d-spacing of the experimental reflections. The component then finds the Miller

indices best matching the supplied unit cell and attempts to improve it.

2.5.2 Spot Position Predictor

After determination of the unit cell, a visual conformation of the correct values is

obtained by superimposing coloured crosses on to the empirical diffractogram. Whilst

some crosses will appear in empty regions of the pattern, perhaps due to systematic

absences, each reflection should have an accompanying marker.


77

2.6 Simulation of Amyloid Fibre Diffraction Patterns Amyloid diffraction data is of insufficient quality for the structure to be solved using

standard crystallographic methods. Verification of a proposed structure involves

comparison of observed and simulated diffraction patterns (Figure 2.9). Two windows

are present, one specific to fibre diffraction and another for more general use. In each

case, the same underlying routine is used.

Figure 2.9. Diffraction simulation window for MacOS X.

2.6.1 Sampling of Intensities in Reciprocal Space

The process works by tracing the diffracted beam back from the positions of the

pixels on the detector, to find the corresponding sample points on the Ewald sphere

(Figure 2.10). For each sample, the contribution from each reciprocal lattice point is

calculated, based on the shape and intensity of that lattice point. The effect of the

projection in real space is also considered. The shape of each of the reflections is

determined by the disorder in the sample and the crystallite size. The temperature,


78

Lorentz, polarisation and structure factors govern the intensity of each reciprocal

lattice point. Factors that remain constant over the whole diffractogram are ignored.


79

Angular D

isorder

Crysta

llite D

imensions

Molecular S

tructure

Lattice Vectors

Beam

Orie

ntation

Miller Indicies

Fibre A

xis

Wa

velength

Tempe

rature F

actor

Diffractogram

Reflectio

n Intensities

S

tructure F

actors

Correction F

actors

Reciprocal La

ttice Points

Spot S

hape

Location of S

amp

les

Intensity o

f Sam

ples

Ew

ald Sp

here

Projection F

rom S

phere

LP C

orrection

Figure 2.10. Flowchart showing the process by which simulated diffractograms are calculated.


80

The location of the sampling points (xsample, ysample, zsample) on the Ewald sphere is

given by:

2imageplate

2imageplate

2

imageplatesample

yxD

xx

++=

λ

2imageplate

2imageplate

2

imageplatesample

yxD

yy

++=

λ

λλ1

2imageplate

2imageplate

2sample −++

=yxD

Dz

where � is the wavelength of the incident beam, D is the distance between the image

plate and the sample and (ximageplate, yimageplate) is the position of the pixel on the

detector.

2.6.2 Reflection Shape

The shape of each reflection is determined by the region in reciprocal space swept out

by the distribution of crystallites. It is therefore dependent on the size of individual

crystallites and the angular disorder. The result is the convolution of a pair of

Gaussians expressed in polar coordinates due to the fibre orientation (Dupont et al.

1997) and another three-dimensional Gaussian from the size of the crystallite. The

convolution of a pair of Gaussians is another Gaussian. Amyloid fibres are generally

far more ordered along the direction of the fibre. The hydrogen bonding between �-

strands in this direction is more ordered than the packing between �-sheets. On this

basis, meridional reflections are likely to be sharper than equatorials. Angular

disorder is described by two parameters, � and �, as shown in Figure 2.11. We

distinguish between samples for which � = �, referred to as a true fibre and those

which have a preferred orientation in this direction. Whilst most amyloid fibrils

appear to be true fibres, diffraction patterns of A� (11-25) taken with the beam

parallel to the fibre axis show that this is not always the case (Sikorski et al. 2003)

(Figure 1.5).


81

Figure 2.11. Reflection shapes for a true fibre (left) and the general case (right). The vertical axis

is the fibre axis and the solid red dot represents the position of the spot before fibre disorder is

applied. The effect of crystallite size is not considered here.

2.6.3 Structure Factors

The unit cell contains a set of N atoms with coordinates ( ){ }iii zyx ,,atom =r and

atomic scattering factors ( )kjf . Atomic scattering factors can be approximated using

numerical solutions to Hartree-Fock functions (Cromer and Mann 1968) using

coefficients from XtalView (McRee and David 1999).

( ) 21.086.058.102.131.2221221219219 102.5106.51002.1101.2

Carbon ++++=−−−− ×−×−×−×− kkkkk eeeef

The resulting structure factor is therefore:

( ) ( )�=

=N

jhkljhkl ifF

1

*atom.2exp krk π

If electrons rather than X-rays are used, then the atomic scattering factor should be

changed to account for scattering from the nucleus, according to the Mott formula

(Mott and Massey 1965) based on the use of Poisson’s equation relating the potential

to the charge-density distribution,

θσ θσ

φσ


82

( ) ( )

�

��

� −=

2

Xray

2

22

electron

8

k

kk

fZ

h

emf eπ

using me the mass of the electron, e the charge on the electron, h Planck’s constant

and Z the atomic number. A table of neutron scattering factors is also provided but has

not been tested.

2.6.4 Other Factors

The polarisation factor for an unpolarised incident beam is

( )BP θ2cos1 221 +=

Bθ is the Bragg angle given by ( )λθ k21arcsin=B , therefore

( ) ( )4

812

211 λλ kk +−=P

In the analysis of integrated intensities from a single crystal, the Lorentz factor is due

to the diffracted flux being dependent on the angular velocity with which the crystal is

moved through the reflecting position (Cella et al. 1970). Here, the sampling process

takes care of the issue; however, it is still necessary to account for the volume of the

reflection in reciprocal space. The full three-dimensional integral can be

approximated using a portion of a spherical shell.

( ) ( )( ) ( ) ( )( )θθφ σθσθσσσ +−−−−+=

ffrr

Lcoscos

133 kk

In fact, constraints are necessary to prevent the introduction of negative numbers:

( ) ( )[ ] ( )( ) ( )( )[ ]πσθσθσσσ θθφ ,mincos0,maxcos0,max

133 +−−−−+

=ffrr

Lkk


83

fθ is the angle between the position vector of the reciprocal lattice point and the fibre

axis

rσ is the standard deviation of the radial distribution, calculated by convolution of the

appropriate distributions.

The atomic isotropic Gaussian Debye-Waller factor accounts for atoms not being in

their mean positions; the effect is to lower the intensity of higher resolution signals.

( )2exp2kTT BA −=

TB is the atomic temperature factor, typically between 20 and 50 Å2 for proteins.

Therefore,

Thklhkl LPAFI2=

Factors which are constant over the whole image are not calculated since only relative

intensity is considered important.

2.6.5 Optimisation

The process is very slow since every pixel on the image detector must be compared

with every reciprocal lattice point and the effect of that point calculated. Reducing the

number of pixels and reducing the number of lattice points will speed up the

simulation process. In many cases, the fibre diffraction pattern is quadrant symmetric;

this is checked since only a quarter of the calculation may be required. A general

picture of the diffractogram can be obtained without calculating every pixel; sampling

every other pixel reduces the number of pixels by a factor of four. The remaining

values can be calculated using bicubic interpolation. This allows the quality of the

output to be varied according to the user’s requirements. We can also reduce the

number of lattice points that need to be considered by each sample. Reciprocal space

can be divided into a series of spherical shells, in the manner of an onion. Shells are a


84

few radial standard deviations in thickness and each sample point need only consider

samples in the shell at the same resolution and the shells on either side.

2.6.6 Automation

The result of diffraction simulation is the calculated diffractogram. Building and

simulating diffraction from a large number of models is excessively time consuming.

Facilities to construct a series of models and determine their X-ray and electron

diffraction patterns are available but due to their complexity, not exposed through the

user interface. These facilities were heavily used in the study of amyloid nanocrystals

(Makin et al. 2005) (Chapter 4).

2.6.7 Testing

Testing was critical to ensure that the results were reliable. The structure of A� (11-

25) amyloid fibrils had previously been solved by X-ray fibre diffraction using

Cerius2 (Accelrys) (Sikorski et al. 2003). Therefore, A� (11-25) diffractograms were

used for testing purposes (Figure 2.12), although testing was not limited to this

peptide (Figure 2.13). Using the published model, the X-ray diffraction pattern was

simulated with the other settings chosen to best fit the experimental data. Good

agreement was demonstrated between the calculated and observed images.

Additionally, the simulation process was broken down into stages and each verified

using data calculated using other methods. Dr P. Sikorski provided particular

assistance in finding bugs in this component.


85

Figure 2.12. Comparison between the simulated (left) and observed (right) X-ray fibre diffraction

patterns, for amyloid formed from A� (11-25), using the model from (Sikorski et al. 2003).

Figure 2.13. Observed diffraction pattern with calculated top left quadrant, for a non-amyloid

sample - cellulose triacetate I (Sikorski et al. 2004).


86

2.7 Other Features

2.7.1 Introduction

Many other features are provided for the processing of diffractograms, in addition to

those which fit well in the process described earlier. Some facilities for the analysis of

electron micrograph data are also present. Furthermore, application programming

interfaces for general image processing allow for flexibility as necessary.

2.7.2 Fourier Space Operations

Fourier transforms are the basis of many other useful functions. The autocorrelation

function has peaks where the image repeats itself, which is useful in the analysis of

electron micrographs of single amyloid fibrils to look for repeat distances. Likewise,

the power spectrum, which is the intensity of the Fourier transform, is also used to

look for repeats. Often, the logarithm of power spectrum is more useful, owing to the

large range of intensities. Convolution can be calculated rapidly in Fourier space and

is employed in many aspects of electron micrograph processing including removal of

the background and the contrast transfer function. A Gaussian convolution filter

averages out local noise and can be used to calculate the low frequency components

of an image.

2.7.3 Determining the Repeat Distance from Micrographs

Repeat distances, in electron micrographs of fibres, can be established by calculating

the power spectrum of the micrograph. In the case of A� (11-25) fibrils, only a repeat

at 4.7 Å is clear and no low-resolution information is visible. An alternative strategy

was devised based on single particle averaging techniques (Serpell and Smith 2000)

and then extended. The fibril image was first straightened, then regions of the fibril

were boxed, the boxes aligned and the aligned boxes averaged. This resulting average

was stored and the process repeated for boxes of different lengths. If the length of a

box corresponded to the repeat distance, then the average image for that length should

have been clearer than for all the other lengths. In order to be objective, some measure

of the visibility of the fibril was required. A variety of different methods were tested

and the standard deviation of the image was found to give the best measure of the

visibility. A graph of the results (Figure 2.14) showed peaks every 4.7 Å


87

corresponding to the distance between �-strands (the Measured Fibril) curve; the steps

were due to the background statistics (the other curves). Unfortunately no peak was

substantially larger than the others, so better visibility measurements and

straightening algorithms are required.

0

2

4

6

8

10

12

14

0 50 100 150 200 250Length of Box (Å)

Vis

ibili

ty (A

rbitr

ary

Uni

ts)

Theoretical Background

Measured Fibril

Measured Background

Figure 2.14. Graph relating visibility to length of box. In this case, visibility was defined as the

standard deviation of the image intensities. The statistics used for the theoretical background

were fitted to the measured fibril rather than the measured background. Screenshot shows

averaged images; the striations in some images have greater contrast.


88

2.7.4 General Features

It is useful to be able to compare diffractograms; therefore crop, resize and rotation

transforms are required. Salt rings can prove a distraction, so there is the ability to

replace a specified annulus with the mean of its surrounding pixels. Horizontal and

vertical traces are used to obtain one-dimensional graphs of equatorial and meridional

reflections of fibre diffraction patterns. They are included in the diffractogram

centring component and the analysis of power spectra. Averaging the quadrants of a

fibre diffractogram reduces noise and the averaged quadrant can be inset into another

diffractogram for a visual comparison. The quadrants are symmetrical in the case that

the tilt angle is zero, Friedel’s law is obeyed and the fibre axis is horizontal or

vertical. Layers are useful when comparing diffractograms taken from different

samples. Images are given different colours and the layers superimposed as if they

were slides on top of one another; thus enabling two images to be viewed

simultaneously and the relative positions of spots compared (Figure 2.15).


89

Figure 2.15. The two images on the bottom left and right are added together to give the

superposition shown in the upper display. The colouring of the images is determined by the

positions of the coloured sliders in the centre of the window.

2.7.5 PDB Display and Manipulation

The goal is to determine the structure of the amyloid macromolecule and this

necessarily involves PDB files. Therefore, facilities are provided to open and display

these files. The Jmol application was modified, so that it acts as a component within

the application purely for molecular visualisation. Detailed editing of PDB files is

best done using modelling applications such as Insight II (Accelrys); however it is

helpful to include some operations. Renumbering is necessary, after manual or

automated editing of the PDB, to ensure all atoms are numbered correctly. Building a

fibre structure is helpful when visualising a result. It is necessary to fill the unit cell

using the asymmetric unit and the space group, prior to diffraction simulation, using

equipoint transformations to generate the other symmetry related objects.


90

2.7.6 Image Mathematics

Many functions are provided, mostly as public methods, rather than being exposed

through the user interface. Simple arithmetic is based on wrappers around the JAI

Library (Sun Microsystems) with corrections for bugs, such as handling complex

arithmetic correctly. Histograms and their standard deviations are useful in

understanding the statistics of the image. False colour applied to images such as

diffractograms gives a larger range of contrast than black to white and makes features

clearer.

2.8 Discussion

2.8.1 Comparison of Clearer with Other Programs

The purpose of our application is to facilitate and accelerate structural studies of

amyloid. As such, it complements those programs already used for amyloid fibre

diffraction analysis. Applications are offered by two of the collaborative computing

projects CCP4 and CCP13 and elsewhere. Outside of these projects, Fit2d (A.

Hammersley, ESRF) is the most prominent example. It is capable of one and two

dimensional data analysis, including powder and fibre diffraction and for the

calibration and correction of detector distortions.

CCP4 is the standard suite of programs for protein crystallography. Whilst they are

not specifically targeted at fibre diffraction studies, many of the programs have

proved useful; Mosflm was employed for the initial survey in the studies described in

Chapters 3 and 4.

CCP13 is a collection of separate programs written specifically for the analysis of

data from fibre diffraction. The programs share a common file format (BSL) and are

widely used for processing diffraction data from macromolecules and muscle tissue.

Some of them are now being rewritten in C# (Microsoft) and Java with a more unified

user interface. Linked Atom Least Squares (LALS) (Okada et al. 2003) is a CCP13

program for structure refinement. Atoms are constrained in such a way that the correct

intramolecular and intermolecular contacts are enforced and non-crystallographic


91

repeat geometry is maintained. The model is then refined to reduce the error between

experimental and calculated fibre diffraction intensities. The method was successfully

developed as for analysing X-ray diffraction data from �-poly-1-alanine (Arnott and

Wonacott 1966; Arnott et al. 1969). FX-PLOR is a patch (Denny et al. 1997), which

allows some versions of X-PLOR (Brunger et al. 1987) to be used with fibre

diffraction data. Hence, the facilities offered by X-PLOR, such as simulated annealing

and energy minimisation can be used for fibre structures.

Cerius2 (Accelrys) offers a very wide range of facilities for general simulation and

modelling. It was used for much of the early work on fibrous nanocrystals formed

from the peptide with sequence KFFEAAAKKFEE (AAAK) (Makin et al. 2005)

(Chapter 4). Much of Clearer was designed to offer improvements on Cerius2, whilst

still using other aspects of the program. Clearer’s fibre diffraction simulations offer

more detailed images both in terms of pixel size and number of pixels. The study of

amyloid nanocrystal structure also benefited from automated model building,

although Cerius does have a proprietary scripting language. Furthermore, Clearer is

available on all major operating systems. There is less apparent complexity whilst

maintaining a high degree of flexibility; including allowing a free choice of beam

direction, fibre axis and crystallite orientation, without the requirement for laborious,

complicated workarounds. Non-true fibres can be simulated and sets of parameters are

easily loaded and saved. Tests with new users showed that Clearer is relatively easy to

learn. Careful note was taken of user feedback and improvements have been

forthcoming. These include the simulation program having everything accessible from

a single summary window and the overall program not requiring any parameters or

input file formats to be learnt. Additionally, Clearer was designed specifically for

amyloid, including the use of sensible defaults, which are less likely to need

adjustment.

2.8.2 Application Use

Clearer has proved to be useful throughout our studies of amyloid structure. For IAPP

amyloid fibrils, both the electron and X-ray diffraction patterns benefited from

contrast enhancement. Equatorial and off-meridional signals not otherwise obvious


92

were revealed. Radial averaging of the unprocessed images showed that these signals

were not artefacts due to the enhancement process. Examination of these averages

allowed their resolutions to be recorded and their nature to be analysed. Clues in the

shape of the peak helped determine whether any given peak was either single

reflection or some combination of many signals.

Fibrous nanocrystals (Chapter 4) were more highly oriented than IAPP (Chapter 3), so

the resulting X-ray and electron diffraction data is of higher quality. Whilst Mosflm

was used for the initial survey, Clearer’s radial averaging and peak finder allowed

reflection resolutions to be found efficiently and accurately. With this information, the

unit cell was determined using an earlier version of the unit cell search program. The

earlier version used the same grid search technique but had less flexibility and no user

interface. Using this program proved to be substantially faster than the manual

methods we employed during the development process.

Electron diffractograms from AAAK (Chapter 4) were made considerably clearer

using the contrast enhancement tool developed specifically for the patterns from this

peptide. We were then able to view the whole image, with even very faint spots made

visible and the background effectively eliminated.

Our simulation program was developed for AAAK to satisfy the particular

requirements of that study, including the simulation of hundreds of models. Cerius2

was used for the modelling itself and Discover for the molecular dynamics.

2.8.3 General Improvements

Our investigations have revealed several broad areas for further development.

Improvements are planned to each stage of the examination and to the overall

program.

General developments will each improve the user experience. In addition to

automating individual stages, the results from any single component may be fed into

the next. Once implemented, the application then mirrors the required workflow in

addition to processing each separate task. Less intervention from the user is required


93

by default, only confirming steps, such as information from the peak finder being

automatically fed into the unit cell determination program.

Documentation is time consuming to produce and dates rapidly but is nonetheless

essential. As Clearer matures it should become more substantial as there are less

major changes in individual components. In the same way, user interface design is

crucial so that “it just works”; testing should be more formalised, including user

feedback and bug filing.

Individual calculations can be further optimised for speed, both in terms of removing

bottlenecks and parallelising routines. The latter being essential as multicore

processors, multiprocessor machines and techniques such as simultaneous

multithreading increase in prevalence.

2.8.4 Specific Improvements

Angular deconvolution of the fibre diffraction pattern has proved to be nontrivial,

including difficulties with the point spread function. Modelling of the pattern, such as

that provided by LSQINT (CCP13), specifically for amyloid, including overlapping

layer lines might prove a more fruitful approach.

A version of the unit cell determination program with greater sophistication would

incorporate heuristics specific to amyloid. These rules would result in less user

understanding being required and results being obtained more rapidly. Once an

approximate unit cell is known, the background removal program can be improved,

involving back calculation of the spot positions. The regions containing the spot

positions can be blanked out and the low frequency background calculated, with the

missing regions filled in using bicubic interpolation.

Next, the model building process can be improved. Although much of this stage is

beyond the scope of this application, automated adjustment of rotamers, interfacing

with other programs and a more quantitative approach to model building should prove

fruitful.


94

Finally, analysis of the equator of the X-ray fibre diffraction pattern has been

considered elsewhere (Kirschner et al. 1987; Inouye et al. 1993; Malinchik et al.

1998; Lu et al. 2003). These analyses were quite rudimentary since they used models

based on radial densities quite different to those of cylindrically averaged �-sheets or

bundles thereof. Compelling results have been obtained for other structures, in the

cylindrically symmetric (Oster and Riley 1952), bundles of cylinders (Burge 1959)

and general cases (Burge 1963). Building more complex models and then improving

them using methods such as simulated annealing may reveal much about the number

of protofilaments and their arrangements.

2.9 Conclusion Our application comprises a series of programs for the analysis of diffraction data

from amyloid and some general image processing. Component programs are provided

for each stage of the analysis process. Each program was developed in parallel with

the studies discussed in the other chapters. This concurrency ensured that each

component was specifically targeted to aid in the examination of amyloid structure.

The application enabled much of the analysis of X-ray and electron fibre diffraction

data from amyloid formed from IAPP and was crucial in the examination of the

detailed structure of amyloid nanocrystals formed from AAAK.

Chapter 3. Characterisation of Islet Amyloid Polypeptide Fibrils

95

3 Characterisation of Islet Amyloid Polypeptide Fibrils

3.1 Abstract Amyloid formed from the islet amyloid polypeptide (IAPP) is found in the pancreatic

islets of 90 % of type II diabetes patients on post mortem. We have used negative

stain, platinum/carbon shadowing and cryo electron microscopy, in conjunction with

X-ray and electron diffraction. Synchrotron diffraction data from synthetic fibrils,

aligned using a stretch frame, shows a well-oriented diffraction pattern. This cross-�

pattern is characteristic of amyloid and has discrete layer lines, which are clearly

visible at spacings of 4.7 Å. Electron diffraction reveals a very strong, sharp 4.7 Å

meridional reflection. The diffractogram was compared to a real space image obtained

by defocusing the diffraction beam, in order to show that the 4.7 Å signal is in the

same direction as the fibrils. A Fourier transform of a single fibre in the cryo-electron

micrograph also shows the 4.7 Å signal parallel to the fibril axis. Our evidence shows

that amyloid formed from IAPP has a structure built of laminated hydrogen-bonded �-

sheets.

3.2 Introduction IAPP is a 37-residue peptide, the deposition of which is associated with type 2

diabetes (Cooper et al. 1987; Hull et al. 2004). Approximately 100 years ago, post-

mortem studies found amyloid in the pancreatic islets of Langerhans (Opie 1901;

Weichselbaum and Stangl 1901). IAPP amyloid is deposited in 90 % of type 2 (non-

insulin dependent) diabetes cases in all ethnic groups (Westermark 1972; Clark et al.

1987; Clark et al. 1988; Westermark 1994; Kahn et al. 1999).

IAPP is normally cosecreted with insulin in beta cells (Clark et al. 1989; Sanke et al.

1991) and it may act as a hormone (Cooper et al. 1988). Whilst the peptide’s native,

monomeric structure is not known, its stable random coil structure in aqueous buffer

may indicate that the peptide is natively unfolded (Higham et al. 2000). IAPP is


96

formed by cleavage from pro-IAPP; it has an amidated C-terminus and a disulphide

bond between the cysteines at residues 2 and 7 (Goldsbury et al. 2000a).

Extracellular deposition of amyloid occurs between beta cells and islet capillaries.

Deposition in invaginations of the plasma membrane is likely to interfere with glucose

and hormone transport, insulin release and membrane signalling. The cytotoxicity of

the deposits (Lorenzo et al. 1994) may explain how amyloid formation and the

resulting death of beta cells results in the reduction of islet function observed in type 2

diabetes (Johnson et al. 1989; Clark et al. 1996; Butler et al. 2003).

Apple-green birefringence, characteristic of amyloid, is observed in ex vivo IAPP

fibril deposits after staining with Congo red and viewed between crossed polarisers

(Puchtler et al. 1961; Charge et al. 1995; Hull et al. 2004). In vitro fibril formation

proceeds via a process of nucleation and seeding (Kayed et al. 1999) and the kinetics

of this have been studied using a variety of truncated peptides (Westermark et al.

1990; Charge et al. 1995; Nilsson and Raleigh 1999).

Certain residues and groups of residues have particular importance for

amyloidogenesis (Moriarty and Raleigh 1999; Azriel and Gazit 2001). Whilst human,

cat, racoon, degu and macaque IAPP all form amyloid in vivo; rat, mouse, guinea pig

and hamster IAPP does not form fibrils, either in vivo or in vitro. Comparisons

between the structure and amyloid fibril-forming activity of truncated versions of the

peptides suggested that residues 20-29 were likely to be of importance to the

amyloidogenic properties of the molecule (Green et al. 2003). Amino acid residues

20-29 of the human IAPP molecule (SNNFGAILSS) have been suggested to be a

primary amyloidogenic domain (Westermark et al. 1990). Comparison to hamster

IAPP revealed a high degree of sequence divergence in this region. Investigation of

this region in cat IAPP found that the fragment formed amyloid and residues 25 and

26 are particularly important to amyloid formation (Betsholtz et al. 1990). Rat IAPP

differs from the human form by six residues in the central region between residues 18

and 29. Substitution of single residues by corresponding residues from the human

sequence allowed limited amyloidogenesis in three cases (R18H, L23F, V26I); multi-


97

residue substitution ensured a higher rate of amyloid formation (Green et al. 2003).

Residues 22-27 are also likely to be of importance owing to the region’s

amyloidogenic potential. An alanine scan of this region found that substitution of the

phenylalanine residue prevented amyloid formation (Azriel and Gazit 2001). These

conclusions are supported by a proline scan of the 20-29 residues. Substitution at any

of these locations inhibited fibril formation, with residues 22, 24 and 26-28 having the

most significant effect (Moriarty and Raleigh 1999). Additionally, IAPP (23-27),

IAPP (20-29) and IAPP (22-27) fibrils are toxic to pancreatic cells, unlike the soluble

forms (Tenidis et al. 2000).

The central region is not unique in its amyloidogenic potential; many other 5 to 20

residue fragments form amyloid, including IAPP (15-19) and IAPP (14-18)

pentapeptides (Mazor et al. 2002; Scrocchi et al. 2003). Other examples include the C

terminal region IAPP (30-37) (Nilsson and Raleigh 1999) and IAPP (8-20) (Jaikaran

et al. 2001). The role of each part of the sequence in the self-assembly process is not

fully understood; fibrils formed from truncated IAPP may have different

morphologies possibly modulated by the N-terminal region (Goldsbury et al. 1997;

Goldsbury et al. 2000a; Jaikaran et al. 2001). Fibrils formed in vitro from the full-

length peptide are therefore more likely to have the same morphology as in vivo

material than those formed from IAPP fragments. We have characterised the

molecular structure of these fibrils. Our study demonstrates that IAPP shares the same

cross-� structural organisation assigned to other amyloid fibrils. X-ray diffraction

reveals the �-sheet structure of bulk fibrils, whilst electron diffraction allows analysis

of the highly ordered, molecular arrangement of small bundles of fibres. Negative

stain and platinum/carbon shadowing shows the diversity and morphology of fibrils.

Cryo-electron micrographs enable the structure of single fibrils formed from full-

length IAPP to be examined.


98

3.3 Methods

3.3.1 Peptide and Incubation

IAPP (1-37) with the sequence NH3+-KCNTATCATQ RLANFLVHSS

NNFGAILSST NVGSNTY-NH2 was purchased from Peninsula Laboratories (St.

Helens, UK) and the lyophilised powder dissolved in filtered water to a concentration

of 20 mg/ml. The stock solution was incubated at room temperature until required.


The stock solution was diluted to 0.1 mg/ml in filtered water. A drop of solution was

placed on a 400 mesh copper pioloform (TAAB) carbon-coated, glow-discharged

grid. The grid was blotted and washed twice with filtered water. The grid was then

stained twice with 4 µl of 2 % uranyl acetate, blotted and left to dry, before being

examined with a Philips 208 electron microscope.

The stock solution diluted to 50 µg/ml in 25 % glycerol and water was sprayed onto

freshly cleaved mica and left to dry. This sample was platinum coated using 2 mm

platinum wire and then carbon coated using an Edwards coater. Replicas were floated

off onto 400 mesh copper grids and the platinum/carbon shadowed result examined

with a Philips 208 electron microscope operating at 80 kV.

3.3.3 Cryo Electron Microscopy

The solution was diluted to a concentration of 12.5 µg/ml using 22 µm filtered milliQ

distilled water. Holey carbon cryo-electron microscopy grids were prepared using 400

mesh copper grids (TAAB) and glow discharged for one minute. The solution was

applied onto the carbon coated, charged side of the grid, carefully blotted from the

underside and directly plunged into liquid ethane, cooled using liquid nitrogen. Grids

were stored in liquid nitrogen (Unwin 1995; Serpell and Smith 2000).

Frozen grids were examined using a Hitachi 2000 microscope operated at 200 kV

using a low dose mode and Gatan cryo stage at 103 K. Images were recorded on

Kodak film at 60 000 times magnification, with a defocus range between 6000 and

18 000 Å.


99

Micrographs were digitised using a Zeiss digitiser. Regions of interest were selected

from digitised images and Fourier transforms calculated using Ximdisp (Smith 1999).

The contrast transfer function was calculated from an amorphous region of the

micrograph using the MRC image-processing suite (Crowther et al. 1996). Defocus

correction was applied by filtering the measured intensity by the contrast transfer

function in Fourier space.


20 mg/ml solution was placed on holey carbon grids and plunged into liquid ethane as

for the cryo-EM (Serpell and Smith 2000). The Hitachi 2000 microscope in low dose

mode was switched from imaging to diffraction mode. Diffractograms were recorded

on Kodak film, camera length 1.6 m. The ice was then allowed to sublime overnight,

leaving dehydrated fibrils, which were then examined in the same way.

Micrographs were digitised with a pixel size of 7 µm using a Zeiss digitiser. The

resulting image data was examined using Ximdisp.


The fibrils were aligned using a stretch frame as described in Chapter 1, Section 1.7.2.

A 10 mg/ml droplet of solution was placed between two waxed capillary tubes and

allowed to dry at room temperature. During drying, the distance between capillary

tubes was slowly increased (Sunde et al. 1997). Patterns were collected using a

synchrotron beam (ESRF BL4 ID2.2) with a wavelength of 0.9515 Å on a

Marresearch image plate. A second set of diffractograms was recorded in-house using

a Rigaku rotating anode, CuK� X-ray source on a 345 mm Marresearch image plate.

The maximum sample to detector distance was 400 mm.

Diffraction patterns were examined using Mosflm (A. Leslie, Cambridge) run on a

Linux workstation and the resolutions of reflections noted.

All experimental data was provided by Dr L. Serpell.


100

3.4 Results

3.4.1 Negative Stain Electron Microscopy

Negative stain electron microscopy reveals fibrils approximately 100 Å in diameter.

They are long and unbranching, with a large radius of curvature (Figure 3.1). Their

morphology is similar to fibrils formed from synthetic truncated IAPP (Jaikaran et al.

2001). Polymorphic structures were observed, with species varying in both width and

shape. Some were smooth and others constructed of twisted filaments. One area of the

micrograph appeared to show a sheet of equally-spaced parallel filaments emerging

from the end of a fibril, with the appearance that the fibril was built from the curled

up sheet.

100 nm

Figure 3.1. Negative stain electron micrograph of IAPP amyloid fibrils. The insets show

magnified, higher-contrast regions of the image. Twisted fibrils with a repeat distance of 500 to

2000 Å show that the fibrils may be formed from protofilaments.

3.4.2 Platinum/Carbon Shadowed Electron Microscopy

Narrow filaments, with a minimum diameter of 50 Å, are seen on the same

micrograph as thicker fibres, with a width between 100 and 150 Å (Figure 3.2).


101

Fibrils appear slightly wider than with negative stain or cryo-electron microscopy,

owing to the shadowing. Whilst the narrow filaments were uniformly very smooth,

some of the thicker fibrils appear to be composed of two filaments coiled about one

another to form a helical structure. The pitch appeared to vary between 250 and

2000 Å. These thin, smooth filaments may be protofilaments. The measured diameters

are commensurate with previous studies based on negative stain and metal shadowing

electron microscopy (Goldsbury et al. 1997; Goldsbury et al. 2000a).

100 nm

Figure 3.2. Platinum/carbon shadowed electron micrograph of mature IAPP amyloid fibrils.

3.4.3 Cryo Electron Microscopy

Cryo-electron microscopy allows direct visualisation of single fibrils. The micrograph

is generated from the fibril itself, since there is no stain and therefore less probability

of distortion. Fibrils are closer to physiological conditions since they are frozen,

hydrated in vitreous ice. This is the same technique as previously applied to A� (11-

25). That study revealed striations 4.7 Å apart corresponding to the spacing between

�-strands (Serpell and Smith 2000).


102

We observe fairly straight, long, smooth, unbranching fibrils 45 to 50 Å diameter. The

morphology is similar to amyloid formed from truncated IAPP, A� (11-25) and other

peptides. Regions of interest each containing a single straight section of a fibril were

selected, padded and floated in a box filled with mean intensity and then the Fourier

transform calculated (Crowther et al. 1996) (Figure 3.3). A strong 4.7 Å along the

direction of the fibril is prominent in the transformed images. Thicker fibrils are seen

to be composed of several protofilaments. In this case, a Fourier transform shows the

4.7 Å meridional and an equatorial at approximately 10 Å, corresponding to the �-

sheet spacing. The absence of a 10 Å reflection in regions containing narrow

filaments is most likely due to small amount of ordered material within the beam

diameter since a single fibril contains only a few �-sheets.

Contrast transfer function correction was applied to the region of the micrograph with

the best Fourier transform. This contained a fibril with a diameter of 45 Å. The

defocus (7500 Å) was calculated from the power spectrum of the amorphous carbon

surrounding the fibril. The micrograph was corrected by assuming the weak object

scattering approximation and dividing the Fourier transform of the region by the

calculated contrast transfer function. This corrected image gives a strong layer line at

4.7 Å. Although striations are not visible in the real space micrograph, the presence of

a layer line reveals that there is a repeating unit along the length of the fibril.


103

Figure 3.3. Cryo-electron micrographs of IAPP fibrils are shown on the left. In the centre is a

magnified region of micrograph containing a single fibril. The right hand image shows the

intensity of the Fourier transform of the centre image after boxing and floating. The arrow

indicates the 4.7 Å signal. The apparent layer line at approximately 15 Å was not observed in any

other transform or diffractogram.


Low-resolution microscopy shows the field of view to be full of densely packed

fibrils with a clear preferred orientation (Figure 3.4 e). Electron diffraction of this area

shows a sharp arc in the same direction as the fibrils (Figure 3.4 a). Defocusing the

diffraction beam allows the diffraction region to be imaged (Figure 3.4 d & e). This

confirms that the 4.7 Å reflection is in the same direction as the fibrils.

Dehydrated fibrils have sharper reflections and higher orders (2.4 and 1.6 Å) with

greater intensities than the hydrated sample (Figure 3.4 b). This implies a larger order

parameter, owing to reduced Debye thermal broadening (Bonart et al. 1963).

Contrast enhancement and circular background subtraction reveal previously

unobserved, extremely faint reflections (Figure 3.4 c). Although standard contrast

stretches, combined with sufficient patience, would also have allowed individual

signals’ resolutions to be determined, this technique allows the complete

diffractogram to be examined. Reflection d-spacings were measured using peak


104

profiling (detailed in Chapter 2) of the image after background removal (Table 3.1).

The off-meridional reflections at 3.8 and 2 Å are hence revealed. These are

constituents of layer lines consistent with those measured using X-ray diffraction.

Unfortunately, the 9.5 Å equatorial reflection was not seen, since it would be inside

the saturated beam centre. Nevertheless, two other equatorials are observed at 5 and

2.8 Å.

Table 3.1. Electron diffraction signal spacings

Direction d-spacing (Å)

Meridional 4.7 2.4 1.6

Off meridional 3.8 2

Equatorial 4.8-5.2 (diffuse) 2.8


105

4.7 Å

1.6 Å

2.4 Å

2.8 Å

~5 Å

3.8 Å

2 Å 4.7 Å

4.7 Å

a

b

c

d

e

Figure 3.4. Electron diffraction patterns before and after dehydration (a & b). The diffractogram

from dehydrated fibrils has sharper reflections and higher order meridional reflections are

visible. Real space images show their corresponding fibril directions (d & e). The contrast-

enhanced version of b is shown in c, with off meridional and equatorial reflections now visible.


X-ray diffraction patterns show an oriented structure with discrete layer lines (Figure

3.5). Although layer lines may be seen in diffraction patterns from amyloid formed

from truncated peptides, they are rare in those taken from fibrils formed from full-

length precursors, since the bundles of fibrils are often too disordered (Inouye et al.

1993; Sunde et al. 1997).


106

The synchrotron pattern has the classic cross-� structure with a sharp 4.7 Å reflection

on the meridian and a diffuse reflection equatorial at 9.5 Å. Although much of the

diffractogram appears similar to that of A� (11-25) (Sikorski et al. 2003), there is no

evidence of a 9.4 Å layer line associated with an antiparallel structure. The 4.7 Å

corresponds to the interstrand spacing of �-strands in a �-sheet, whilst the 9.5 Å on

the equator represents the spacing between the �-sheets. All the equatorials are very

diffuse, making accurate measurement difficult. It was therefore necessary to develop

methods to improve the contrast of the diffractograms including background removal,

contrast enhancement and peak profiling. The resulting d-spacings are listed in Table

3.2. Some peaks appear to be composed of series of overlapping peaks, as is indicated

from the shape of the signal. In-house small angle data down to 40 Å reveals two

further diffuse equatorial reflections at around 23 and 38 Å.


107

2.4 Å

4.7 Å

3.4 & 3.7 Å

4.2 Å

9.5 Å

9.5 Å

38 Å

~5 Å

1.9 & 2.3 Å

Figure 3.5. Wide angle (top) and small angle (bottom) synchrotron X-ray fibre diffraction

patterns from stretch frame aligned IAPP amyloid fibrils. Layer lines are clearly visible with a

spacing of 4.7 Å but not of 9.4 Å.


108

Table 3.2. X-ray diffraction signal spacings

d-spacing

(Å)

Intensity

(%) Description

4.7 100 Sharp, meridional

2.37 9 Sharp, meridional

4.2 < 4 Diffuse, off meridional

3.7 2 Diffuse, off meridional

3.4 < 4 Diffuse, off meridional



38-40 < 4 Very diffuse, equatorial, low angle

20-23 < 4 Very diffuse, equatorial, low angle

15 19 Very diffuse, equatorial

11.2 < 4 Very diffuse, weak, equatorial

9.5 25 Diffuse, equatorial

4.8-5.3 18 Diffuse, equatorial

2 3 Background sample

3.4.6 Structural Interpretation

A combination of data from X-ray and electron diffraction and Fourier transforms of

cryo-electron micrographs has demonstrated that amyloid formed from IAPP has a

cross-� core structure. The distinct layer lines observed in the electron diffraction

patterns and cryo-electron microscopy Fourier transforms are perpendicular to fibre

axis from ED and clearly demonstrate that �-strands spaced 4.7 Å apart run

perpendicular to the fibre axis.

Analysis of the tables of reflections allows a likely unit cell to be inferred. The layer

line spacing gives one unit cell dimension as 4.7 Å in the direction of the fibre.


109

Equatorial indexing is difficult, owing to a limited number of diffuse reflections. Each

equatorial may be the result of overlapping peaks, which have not been individually

resolved. There are similar difficulties with off-meridionals, which are even more

diffuse. The strong 9.5 Å equatorial probably corresponds to the distance between �-

sheets. If the �-sheets are mutually antiparallel, so that adjacent �-strands are face-to-

face, then we expect a cell dimension of 19 Å. This fits many equatorials and off-

meridionals. The lamellar repeat is the distance corresponding to length of peptide

chain in extended �-conformation before �-turn. This is likely to be a multiple of half

of 6.9 Å, which is the distance between every other �-carbon in an extended �-strand.

If there are 10 residues between turns, then the repeat is 34.5 Å; alternatively if there

are 11 residues, then the cell length is 38 Å. We therefore propose that the unit cell

may be orthorhombic with a = 4.7 Å, b = 19 Å, c = 38 Å. In this case, with a unit cell

length of 38 Å, each protofilament is composed of four �-sheets. If the �-sheet

stacking distance is 9.5 Å, then this is commensurate with the diameter of narrow

filaments observed in the negative stain and cryo electron micrographs.

3.5 Discussion

3.5.1 General Fibril Morphology

Amyloid formed from synthetic IAPP has a variety of morphologies. Studies have

examined the overall structure and analysed the differing arrangements of the

protofilaments that constitute the fibril (Goldsbury et al. 1997). Micrographs show

that the most common morphology is two intertwined filaments with an average

diameter of 80 Å. These are formed by the left-handed coiling of protofilaments and

have an axial crossover repeat distance of 250 Å. Species with more than two

filaments form either twisted structures or ribbons. The twisted structures are thicker

versions of the intertwined protofilaments with a cable-like appearance and a variety

of diameters. The ribbons are formed from the laterally associated protofilaments.

Our negative-stain electron microscopy results are consistent with these

measurements. However our cryo-electron microscopy shows single fibres with a

width of 50 Å. We therefore wish to know whether these narrow filaments are indeed


110

protofilaments or an aberration due to absence of stain. In cryo-electron microscopy,

the fibres are fixed in vitreous ice and the observed structure may be the ordered,

densely packed core. Cryo-electron micrographs often have low contrast; hence, any

less ordered region in the structure may be lost amongst the amorphous material

surrounding it. The same observation has also been made in studies of paired helical

filaments (Berriman et al. 2003).

STEM measurements of the mass per unit length give a value of 1.0 kDa/Å

(Goldsbury et al. 1997). Each �-strand has a width of 4.7 Å, with the result that the

mass per strand width is 4.7 kDa. IAPP monomers have a molecular mass of 3.9 kDa;

therefore there are 1.2 monomers per strand width. Our data suggests that a

protofilament is composed of four laminated �-sheets, giving 0.3 monomers in each

strand. This implies that the IAPP molecule is extended over three �-strands and is

also commensurate with the protofilament width.

3.5.2 Understanding of Structure Derived from Diffraction Data

The cross-� diffraction pattern is as expected for amyloid and of similar appearance to

those patterns reported in other studies (Inouye et al. 1993). Discrete, off-meridional

signals are clearly visible on layer lines, due to high orientational order in the sample.

Diffuse equatorials are observed implying a low coherence length, a relatively small

number of �-sheets in each fibril and that the arrangement of fibrils with respect to

one another is disordered.

The proposed unit cell results imply a structure constructed from laterally associated,

hydrogen-bonded �-strands, which form four �-sheets. Each sheet is separated by

9.5 Å (half the b dimension), which is sufficient to allow the side-chains to pack

without overlapping. The 19 Å repeat implies that the �-sheets are mutually

antiparallel. Further, detailed modelling of the structure and its side-chains is

impractical since the reflections are diffuse in the equatorial direction to the point of

overlapping. Additionally, the angular disorder results in more overlapping of closely

spaced signals.


111

The X-ray and electron diffraction patterns both show layer lines at 4.7 Å. Neither a

signal at 9.4 Å, nor any other evidence of a layer line at this resolution is apparent. If

such a layer line was present, then the �-strands must be in an antiparallel

arrangement. Unfortunately, its absence does not directly imply a parallel

arrangement of strands within the �-sheet. Antiparallel strands have a 21 symmetry,

which results in systematic absences. Furthermore, the specific arrangement of strands

may extinguish the whole layer line or render it sufficiently weak as to be invisible in

our experiments. A mixture of parallel and antiparallel strands is also possible but

would break the crystallographic symmetry. Whilst the �-sheets themselves may be

parallel, the turn may be between sheets, in the manner suggested in models built for

A� (1-40) (Petkova et al. 2002) and �-synuclein (Der-Sarkissian et al. 2003), based

on SSNMR and SDSL, respectively. Although SSNMR data shows that IAPP (20-29)

fibrils are antiparallel (Griffiths et al. 1995), meridional profiles of X-ray fibre

diffractograms show no evidence of a 9.4 Å layer line (Sunde et al. 1997). Evidence

of antiparallel orientation from such a short peptide may not necessarily imply that

full-length IAPP should be the same. Whilst SSNMR studies of both A� (10-35) and

full-length A� both show a parallel structure (Benzinger et al. 1998; Antzutkin et al.

2000; Benzinger et al. 2000; Antzutkin et al. 2002; Balbach et al. 2002; Petkova et al.

2002; Antzutkin et al. 2003), SSNMR and X-ray diffraction studies on A� (11-25)

found an antiparallel structure (Sikorski et al. 2003; Petkova et al. 2004). A structure

formed from parallel, extended �-strands would have a diameter of 128 Å, far larger

than that observed in the electron microscope.

3.5.3 Hypothetical Modelling

Full-length IAPP has three fibrillogenic regions, each of which is independently

capable of adopting a �-sheet conformation and forming fibrils in vitro. IAPP (20-29)

is the most studied intrinsically amyloidogenic region (Glenner et al. 1988;

Westermark et al. 1990; Ashburn et al. 1993; Griffiths et al. 1995). IAPP (30-37) also

forms amyloid fibrils (Nilsson and Raleigh 1999), as does IAPP (8-20) (Jaikaran et al.

2001). Thus the full-length peptide has three �-strands, allowing both intramolecular

and intermolecular hydrogen bonding. These interactions may result in a folding

process that may be significantly more complex than that expected for other


112

amyloidogenic proteins (Griffiths et al. 1995; Serpell et al. 1997; Sunde et al. 1997).

Modelling of this process suggests that the peptide may fold into an “e” shape, with

both parallel and antiparallel arrangement of chains (Jaikaran and Clark 2001). The

three regions form the dense core of the protofilament, with an unfolded N-terminal

region forming the tail of the “e”. The C-terminus is sandwiched between the other

two strands. Such a shape requires two turns, a tight �-turn and wider curved region to

accommodate a greater radius of curvature. The role of the C-terminus has been

examined using an intrinsic fluorescent probe (Padrick and Miranker 2001). Spectral,

quenching and anisotropic properties of the final tyrosine indicated that the C-

terminus is extremely rigid and well packed. The presence of a fluorescence resonant

energy transfer pathway confirms that residue 37 is within approximately 11 Å of the

phenylalanines at residues 15 and 23. If the turns are in residues 17 to 19 and 28 to 29,

then the extended �-strand region covers approximately 10 residues. The distance

between corresponding �-carbons is 6.9 Å, implying a strand length of approximately

35 Å.

The three-strand model is commensurate with the STEM mass per unit length data

showing 1.2 monomers per strand width (4.7 Å), if there are four �-sheets per

protofilament (Goldsbury et al. 1997). A layer line at 9.4 Å is not expected since there

is no symmetric plane at this interval, the appropriate width of the true unit cell being

3 or 6 times 4.7 Å. This model has the hydrogen-bonded �-strands perpendicular to

the fibre axis necessary to fit the characteristic cross-� X-ray and electron diffraction

patterns. Four �-sheets is consistent with the unit cell dimensions which require an

even number of sheets, in order to have a whole number of cells in a filament. Both

the width and length of such an arrangement is accommodated if the protofilaments

are 40 to 50 Å in diameter. Although the data is commensurate with the model, its

quality is insufficient for a firm confirmation or disproof of the hypothesis.

3.5.4 Conclusion

Mature amyloid fibrils formed from full-length IAPP have been examined in detail.

We have successfully combined negative stain, platinum/carbon shadowed and cryo

electron microscopy with X-ray and electron diffraction to build a probable unit cell.


113

This result complements data from previous studies, including scanning transmission

electron microscopy and provides new insight into existing models. The fibrils have a

stable, highly ordered core structure, characteristic of the generic amyloid structure.

This core is a series of laminated �-sheet ribbons composed of ladders of tightly

packed, hydrogen-bonded �-strands; protofilaments based on this core structure are

intertwined to form mature amyloid fibrils.

Chapter 4. Molecular Basis for Fibril Formation and Stability

114

4 Molecular Basis for Fibril Formation and Stability

4.1 Abstract Amyloid fibrils are highly ordered aggregates, although sufficiently disordered to be

generally considered non-crystalline. Considerable effort has been expended to

increase the order parameter, to improve the diffraction patterns. We have produced

amyloid crystals, formed from a twelve-residue sequence-designed peptide. Electron

microscopy reveals that these microcrystalline structures are composed of nanofibres.

X-ray and electron diffractograms show diffraction to beyond 1 Å. This has allowed

us to determine a detailed structure for amyloid. The structure has a P212121 space

group in which antiparallel �-sheets are arranged in a cross-� manner, which is

characteristic of amyloid. Detailed modelling reveals the side-chain packing and thus

the importance of � bonding between aromatic side-chains. Component �-strands are

zipped together by stacks of intermeshed aromatic rings, which in conjunction with

salt bridges between pairs of charged residues, increase the stability of the structure.

These controlling interactions are commensurate with other authors’ work and are

likely to be of importance in understanding the self-assembly and stability of amyloid.

4.2 Introduction We examined a twelve-residue designed peptide with sequence KFFEAAAKKFFE,

henceforth referred to AAAK (Hosia et al. 2004). This sequence is near palindromic

and is composed of a four-residue motif (KFFE) at each end, with a hydrophobic

central region (AAAK), designed to prevent �-turn formation. The designed peptide

features many motifs found in amyloid precursors associated with the amyloidoses

(Table 4.1). The phenylalanine pair is found in A� and AA, which are associated with

Alzheimer’s disease and secondary systemic amyloidosis, respectively. The AAA and

AAAxK motifs are both present in �-synuclein (Parkinson’s disease). Although

amyloidogenic peptides do not share a common primary structure, they have a high

concentration of aromatic residues. These have been found to be important in the self-

assembly process of both amyloid (Gazit 2002b) and protein in general (Claessens


115

and Stoddart 1997; Gillard et al. 1997). Hence the structure determined herein offers

substantial insight into the generic amyloid structure.

Our peptide forms amyloid fibrils organised into three-dimensional fibrous

nanocrystals. This high degree of order has enabled the collection of high-resolution

X-ray and electron diffraction data. Thus, it has been possible to determine the fibril

structure, including the orientation of �-strands and obtain a detailed visualisation of

highly intermeshed side-chain arrangement.

Table 4.1. Similarities between the designed peptide and disease precursors.

Precursor Peptide Relevant Sequence Associated Syndrome

AAAK KFFEAAAKKFFE None

AA SFFSFLGEAFD Chronic inflammation amyloidosis

A� KLVFFAE Alzheimer's disease

�-synuclein AAAxK, AAA and

AYEMPSEEGYQDYE Parkinson's disease

�2-microglobulin DWSFYLLYYTEFT Dialysis related amyloidosis

ABri FAIRHF and FENKFAV British dementia

Calcitonin DFNKFT Medullary thyroid carcinoma

Gelsolin SFNNGDCCFILD Finnish inflammation amyloidosis

IAPP NFGAIL and NFLVHS Type II diabetes

Lactadherin NFGSVQFV Aortic medial amyloid

PrP PQGGYQQYN and VAGAAAAGAV Creutzfeldt-Jakob disease


116

4.3 Methods

4.3.1 Peptide and Incubation

The peptide, with sequence KFFEAAAKKFFE, was purchased from Interactiva

(Darmstadt, Germany) and purified by reversed-phase, high-pressure, liquid

chromatography using a C18 column and a linear gradient water/acetonitrile

supplemented with 0.1 % trifluoroacetic acid. The sample’s identity was verified

using electrospray ionisation mass spectrometry (Tjernberg et al. 2002; Hosia et al.

2004) and was provided by Dr J. Johansson. Amyloidogenesis was achieved by

incubation at 37 °C with shaking at 3 mM concentration in 50 mM phosphate buffer,

pH 7.0 for 7 days.


The incubated solution, diluted (1:10), was examined by transmission electron

microscopy. 4 µl aliquots were placed on carbon-coated, glow-discharged, copper

grids (400 mesh, TAAB) and excess solution withdrawn after 30 s. Grids were

washed with 4 µl filtered (200 nm) water and negatively stained with 2 % (w/v)

uranyl acetate. The stained grids were examined using a Philips 208 microscope,

operated at 80 kV.


Grids previously prepared for electron microscopy were examined using a Philips

EM400T microscope by electron diffraction. A grid was platinum coated and used for

calibration. Electron diffraction patterns were observed at an operating voltage of

100 kV and camera lengths of 295 to 2300 mm. Patterns were recorded on Kodak film

and real space images of the sampled areas examined. Films were scanned using an

Epson digitiser.

Electron diffraction patterns were analysed and processed using the Clearer image-

processing suite as described in Chapter 2. The background was removed and the

contrast enhanced.


117


Fibres were partially aligned using a stretch frame (Serpell et al. 1999; Makin and

Serpell 2005) and a cryo-loop. The cryo-loop (Hampton) (radius 0.25 mm) was

dipped in the sample of fibrous material. This formed a film, which was allowed to

dry, resulting in a thin mat of fibrous material at many orientations within the two-

dimensional plane of the loop (Chapter 1, Section 1.7.4).

Data collection was carried out in-house using a Rigaku rotating anode, CuK� X-ray

source and Marresearch image plate and at ESRF, France using a synchrotron beam

(BL4, ID2, wavelength = 0.99 Å). Images at several specimen-to-film distances were

collected.

Diffraction patterns were examined using Mosflm (A. Leslie, LMB Cambridge) run

on a Linux workstation and the d-spacings of reflections noted (Table 4.2). The

diffractogram was further processed using the Clearer image-processing suite

described earlier. The circularly symmetric background was removed using statistical

analysis of circular annuli. Peak positions were measured using Clearer’s peak finder

component, which examines radially-averaged circular sectors.

4.3.5 Structural Determination

The unit cell was determined using the d-spacings of signals measured from X-ray

diffraction patterns, which were then indexed. A grid search of possible orthorhombic

cells confirmed the result. Initial values were obtained using constraints from the

dimensions of the peptide and knowledge of the electron diffraction pattern. The unit

cell dimensions imply four chains. We built the model by first considering a single

chain, then an antiparallel pair and finally two pairs of chains. The initial single chain

in an idealised �-conformation was built using Insight II (Accelrys) run on an SGI

workstation. All other manual refinement of the model used Cerius 2 (Accelrys).


118

4.4 Results


Fibrous nanocrystals were revealed by electron microscopy (Figure 4.1). The crystals

were observed to have a diameter of 12 nm to 240 nm and a high aspect ratio. Higher

magnification images showed the crystals to be composed of packed fibrils running in

the same direction as the crystals. These fibres were marked by faint striations parallel

to the fibre axis. The distance between striations was measured as 50 Å by integration

along the fibre axis. The striations may correspond to protofilaments since they are

similar to measurements made on other fibrils (Sikorski et al. 2003).

1 �m

100 nm

Figure 4.1. Negative stain electron micrographs of AAAK amyloid. The left hand image shows

fibrous nanocrystals at low magnification. The fibrous content of the nanocrystals is shown on

the right, with striations spaced 50 Å apart parallel to the fibre axis.

4.4.2 X-ray Fibre Diffraction

High-resolution diffraction was observed to beyond 2 Å (Figure 4.2). The

characteristic cross-� pattern, with a weak 4.7 Å meridional, showed equatorial

reflections substantially sharper than usually expected of amyloid. This may be due to

increased order between �-sheets. Low angle data recorded down to 100 Å showed no


119

observable signals at resolutions lower than 24 Å (data not shown, collected by Prof

E. Atkins).

4.76 Å

10.7 Å

24.4 Å

Fibre axis

Figure 4.2. X-ray fibre diffraction pattern from amyloid nanocrystals using synchrotron

radiation.


Electron diffraction showed reflections beyond 1 Å (Figure 4.3). Layer lines were

observed at 9.5 Å and row lines at 6.9 Å. Defocusing the beam allowed the direct

image to be viewed and the observation made that the 4.7 Å reflections were along the

direction of the fibre. Tilting the sample did not reveal any other spots. No 10 to

11 Å reflection was observed owing to the crystal orientation. In conjunction with X-

ray diffraction, this pattern allowed the structure to be solved.

Electron diffraction involves dynamic and kinematic scattering and the film’s

response to electron flux density is not linear. This makes quantitative analysis of spot

intensities difficult. A more detailed model would have required significant collection


120

of extra data, including obtaining many sections through reciprocal space, by means

of tilted crystals.

4.76 Å

6.9 Å

c*

a*

Fibre axis

Figure 4.3. Electron diffraction pattern from the fibrous nanocrystals showing diffraction out to

0.9 Å. Electron beam is parallel to the [0 1 0] zone axis. Right hand image is the contrast

enhanced version.

4.4.4 Indexing

The unit cell was determined based on the sharp X-ray diffraction reflections,

information from the electron diffractogram and the dimensions of the peptide chains.

An orthorhombic cell was found with a = 9.52 Å, b = 21.3 Å, c = 48.1 Å and a

P212121 space group; where a is the fibre axis and hydrogen bonding direction, b the

�-sheet chain stacking direction and c the chain direction. This is as expected for an

antiparallel cross-� structure.

The normal to the specimen surface and the [0 1 0] zone axis are both parallel to the

electron beam direction; allowing us to conclude that b is orthogonal to the ac plane

and therefore the lattice vectors are mutually perpendicular. The strong meridional


121

4.76 Å signal corresponds to the spacing between �-strands; whilst the layer line in

the electron diffractogram at 9.52 Å implies an antiparallel arrangement and gives the

a unit cell dimension. A 9.3 Å meridional X-ray reflection is also present; the 9.52 Å

[1 0 0] signal is not expected or observed since this is a systematic absence if the

structure is antiparallel cross-�. On the equator, the strong signal at 10.7 Å is the

spacing between �-sheets, indexed to b = 21.3 Å. Even layer lines are observed to be

much stronger than their odd counterparts. These relative intensities can only be

achieved by having more than one pair of �-strands in the unit cell and confirms the

�-sheet spacing. A twelve-residue, extended �-strand measures approximately

6.9 × 12 ÷ 2 = 42 Å. The lowest angle reflection is observed at 24 Å. Semi-automated

fitting and search in conjunction with modelling found c equal to 48 Å; many possible

unit cells could be eliminated since they would cause substantial clashing between

side-chains.

The space group was found by modelling; nevertheless certain signals are

conspicuously absent in both the X-ray and electron diffraction data. No meridional at

9.52 Å [1 0 0] is observed or any other reflections of the form [2n+1 0 0]. On the

equator, neither 21.3 Å [0 1 0] nor 48 Å [0 0 1] (low angle data) are observed. This is

suggestive of a P212121 space group, which has systematic absences [h 0 0] [0 k 0]

[0 0 1] h, k, l = 2n. Comparison of the expected resolutions calculated using the above

unit cell and space group, and empirical values shows a strong fit (Table 4.2).


122

Table 4.2. Strong agreement is shown between observed and predicted resolutions. Wide-angle

reflections are omitted, owing to indexing becoming trivial at high resolution.

Miller Indices Measured d-spacing

(Å) h k l

Predicted d-spacing

(Å)

24.43 0 0 2 24.06

19.94 0 1 1 19.49

13.27 0 1 3 12.82

10.66 0 2 0 10.66

9.33 1 0 1 9.34

8.69 1 1 0 8.70

7.93 0 2 4 7.98

7.19 0 2 5 7.14

6.13 1 0 6 6.14

5.65 1 3 1 5.66

5.33 0 4 0 5.33

4.91 1 3 5 4.90

4.76 2 0 0 4.76

4.66 1 0 1 4.65

4.37 1 3 7 4.38

4.00 0 0 12 4.01

3.91 1 1 11 3.91

3.79 1 5 3 3.78

4.4.5 Modelling

Modelling taking several months attempted to replicate the electron diffraction by

manually adjusting combinations of the strands and adjusting the side-chains. The


123

presence of a 9.5 Å layer line in the electron diffraction data shows that the peptides

are in an antiparallel conformation. The electron diffraction patterns confirm that the

cell is orthorhombic; the a and c axes are clearly orthogonal, whilst the direction of b

is perpendicular to this plane. The strong, highly detailed pattern would only be

observed if the electron beam was parallel to that zone axis. The X-ray data implies a

chain stacking distance of 21.3 Å, indicating that there must be another pair of chains

in the unit cell. The orientation of this pair of chains can be determined from the

electron diffraction pattern in conjunction with stereochemical constraints.

The aromatic rings are heavily constrained by each other. Rings only fit side by side if

they are twisted, the angle of that twist being suggested by a large peak in the 9.5 Å

layer line. Each pair of adjacent phenylalanine residues has the same torsion angle,

which is equal and opposite to that of the pair at the opposite end of the peptide. There

is an apparent degeneracy in that it was not possible to determine the difference in the

electron diffraction pattern if all the aromatic rings were twisted by additional �

radians; indeed, it is conceivable that two species of fibre exist. By extension of this

principle, the other side-chains have the same orientation as the phenylalanine groups

in that half of the chain. We concluded that the only possible rotation of the second

pair of chains with respect to the first was a rotation by � about the a-axis. Only

rotation about the a-axis gave good intermeshing and the correct relative intensity

between odd and even layer lines. In this case the 9.5 Å layer line completely

disappears so an additional translation in the a-c plane is required to reintroduce it. In

the c direction, translations must be in units of 6.9 Å, which is the distance between

adjacent, �-carbon atoms. This is difficult, since there is now no partner for free ends;

interleaving the chains results in a wide ribbon and reduces aromatic interactions;

alternatively a sequential slip between chains gives a non-orthorhombic unit cell and

the 9.5 Å layer line is no longer orthogonal to the fibre axis. Hence, the translation

must be in the a-direction. A slip by 4.7/2 = 2.4 Å eliminates all 2 0 x layer lines,

whilst 4.7/4 = 1.2 Å gives approximately the correct relative intensity of odd and even

layer lines.


124

Unfortunately this approach failed since it was unable to replicate the experimental X-

ray pattern and whilst the simulated electron pattern had many features of the

experimental image, it was not convincing. Manual modelling had proved to be both

slow and ineffective, so a semi automated approach was developed.

Appropriate rotamers in a single chain were selected to avoid side-chain overlap.

Next, a pair of antiparallel chains was considered. Phenylalanine side-chains were

necessarily closely interlocked since the width of a benzene ring is greater than the

distance between the �-strands in a �-sheet. Careful attention was therefore required

to select the optimum set of phenylalanine rotamers.

Each phenylalanine has four possible rotamers; in a pair of chains there are eight

phenylalanine residues. This gives a total of 48 = 65 536 permutations. The aromatic

residues are concentrated into two blocks at either end of the chain. The blocks do not

interact and therefore they can be considered separately. Of the four residues in each

block, two are above the chain and two below, hence only 16 permutations need be

considered. The �-strands exist in a periodic structure, hence the analysis must take

account of interactions from both sides. Models were built for each case and

examined both by inspection and clash score using Molprobity (Lovell et al. 2003).

The constraints resulted in only one permutation being reasonable. Once the correct

permutation had been determined, a pair of antiparallel chains could be modelled.

The whole cell contains two pairs of antiparallel chains 10.7 Å apart in the �-sheet

stacking distance (b). We therefore wish to know the translation and rotation of the

second pair of chains relative to the first. Many models were built by hand and

diffraction patterns simulated using Cerius 2. This was very time consuming, so a

semi-automated approach was developed in which many hundreds of models were

built with many possible orientations and translations in the ac plane.

Stereochemically unlikely structures were eliminated by inspection. Simulated X-ray

and electron diffraction patterns were calculated using Clearer. These were compared

with experimental diffractograms (Figure 4.4); duplication of models ensured

consistency in evaluation. The absence of a 48 Å reflection in low-angle data


125

eliminated many models owing to their shift along the chain direction. Short listed

candidates were judged on the basis of having the most signals in common with the

experimental diffractograms of the correct relative intensity and the least non-

observed signals. Only one candidate fit the criteria well, having the best similarity

between calculated and observed diffraction patterns (Figure 4.5). Side-chains were

oriented by energy minimisation in Cerius 2 and molecular dynamics in Discover

(Accelrys).

Figure 4.4. Comparison between simulated (top left) and observed fibre diffraction patterns for

an incorrect model. A 48 Å reflection is seen innermost on the equator and the 9.4 Å layer line is

far too strong.


126

Figure 4.5. Comparison between observed and simulated X-ray diffraction patterns. The top left

hand quadrant shows the diffractogram calculated using the proposed model.

The final structure has a face-centred arrangement of chains with �-strands

perpendicular to the fibre axis. Hydrogen-bonded, antiparallel chains are organised

into long �-sheet ribbons, resembling previous structural models (Eanes and Glenner

1968; Sunde and Blake 1998; Jimenez et al. 1999; Sikorski et al. 2003). Chains in an

adjacent �-sheet are shifted in the chain direction by half the unit cell direction (c/2)

with respect to one another. This gives the repeating model a brick-like appearance.

The fibril structure can be generated from the repeating single chain after application

of the space group’s equipoint transformations.

The brick-like organisation of chains leads to a banding pattern when the model is

viewed down the b axis. This may explain the striations seen in the micrographs of


127

fibrils (Figure 4.1). There is sufficient room between the ends of the chains for

sodium or chloride ions, which have ionic radii of 0.95 Å and 1.7 Å respectively.

Amyloid formation and growth may be entropically driven due to the release of bound

water. The central hydrophobic region (AAAK) stabilises the extended �-strand, thus

reducing the energy required for self-assembly.

Examination of the final structure shows that the �-sheets are held together by side-

chain interactions (Figure 4.7). In each case, the N-terminus of any given chain is

surrounded by the C-termini of adjacent chains and vice versa. Aromatic interlocking

is a prominent feature, whilst avoiding aliphatic clashing. Aromatic rings between

strands in the �-sheet are mutually parallel but displaced so that they are off centre.

Between sheets, the rings are in a T-shaped arrangement. Both are highly stable, with

parallel displaced being the preferred orientation (Figure 4.6) (Sun and Bernstein

1996; McGaughey et al. 1998). Pairs of lysine and glutamic acids alternate along the

structure, which may be responsible for the antiparallel orientation of strands. At

neutral pH, the peptide has a net charge of unity. A net charge of +1 or -1 has been

shown to be necessary for fibrogenesis from de novo hexapeptides (de la Paz and

Serrano 2004).

Figure 4.6. Parallel displaced (left) and T-shaped (right) orientations of aromatic rings are

particularly stable.

This stable, interlocked structure has intermeshed side-chains resulting in a highly

ordered organisation; thus ensuring the crystalline nature of the material and the high-

quality diffraction pattern.


128

Figure 4.7. Proposed model for the structure of the amyloid nanocrystals. Insets containing more

than one strand are generated by the application of P212121 symmetry. Chains are coloured by

either residue type or chain (Humphrey et al. 1996). (a) An extended single �-strand with its

sequence, coloured by residue type (blue is basic, red is acidic and green is non-polar), viewed

down the a axis. (b) Four chains viewed down the b axis to show hydrogen bonding (light blue).

(c) Pair of chains, coloured by residue type; magnified region shows T-shaped aromatic

interaction between sheets. (d) Packing of chains within the crystals. Magnified region shows

both intersheet and interstrand interactions between phenylalanine side-chains. (e) Isosurface

representation of fibrillar structure, in which the fibre axis is vertical, showing close interlocking

of side-chains (Varshney et al. 1994). (f) Brick-like structure of crystal viewed down the a axis.

b

d

e

f

a

c

K F F E A A A K K F F E


129

4.5 Discussion

4.5.1 The Role of Side-chains in Amyloid Formation and Structure

Phenylalanine residues stabilise the structure by �-� intersheet interactions (Figure

4.7). This is not surprising since aromatic residues have a critical role in the self-

assembly of amyloid from many disease related peptides (Table 4.1) (Gazit 2002b).

Investigations to understand the effects of charge attraction and �-propensity on

tetrapeptides have demonstrated the importance of electrostatic interactions. They

showed that whilst the peptides KFFK and EFFE were not able to self-assemble, an

equimolar mixture and KFFE were both able to form amyloid (Tjernberg et al. 2002).

Hence, charge attraction is critical to amyloidogenesis.

Investigations into short truncated A� peptides have demonstrated the importance of

the phenylalanine pair. A� (17-21) with sequence LVFFA was shown to be of

particular significance in the process of plaque growth and maturation (Esler et al.

1996). Fibril assembly can be prevented by the addition of A� (15-20) (QKLVFF),

which binds to A� and appears to block further elongation. Similarly, A� (17-21)

(LVFFA) also inhibited amyloid formation (Findeis et al. 1999). On this basis,

LPFFD is a �-sheet breaker based on the A� (17-21) template. Alanine substitution

shows that Lys16, Leu17, and Phe20 are all critical to inhibitory activity (Tjernberg et

al. 1996). Tests using a rat-brain cell model found it not only reduced fibril formation

but also disassembled preformed fibrils in vitro and prevented neuronal cell death

(Soto et al. 1998). An unbiased screen for variants of A� with reduced

amyloidogenicity demonstrated the importance of Phe19 (Esler et al. 1996; Wurth et

al. 2002). Indeed, stacking of phenylalanine rings is observed in the X-ray structure of

A� (11-25) (Sikorski et al. 2003).

Analogous experiments to those involving A� used fragments of IAPP. IAPP (23-26)

(FGAIL), IAPP (15-19) (FLVHS) and IAPP (14-18) (NFLVH) are the shortest IAPP

fragments capable of forming amyloid (Azriel and Gazit 2001; Mazor et al. 2002).

Both IAPP (22-27) (NFGAIL) and IAPP (20–29) (SNNFGAILSS) also formed

amyloid and were cytotoxic, whilst GAIL remained soluble (Tenidis et al. 2000). An

alanine scan of NFGAIL showed that all substitutions could still form large


130

multimeric assemblies with the exception of Phe23 (Azriel and Gazit 2001).

Molecular simulation of NFGAIL showed aromatic rings cementing the

macromolecular assemblies due to their aromatic chemical character and restricted

conformational flexibility (Zanuy and Nussinov 2003; Zanuy et al. 2004). This was

confirmed using near-ultraviolet CD spectra, recorded just before aggregates were

observed. It showed two positive bands at 265 and 285 nm, indicating that formation

of the conformational population just prior to fibril formation was associated with

aromatic interactions.

High concentrations of phenylalanine residues are present in other prominent

amyloidogenic fragments of disease related proteins. Examination of the human

calcitonin (hCT) fragments hCT (15-19), hCT (16-19), hCT (15-18) and hCT (15-17)

found that aromatic nature seemed to be the only common property of the various

very-short, amyloid-forming peptides (Reches et al. 2002). SSNMR revealed �-�

interactions in these fibrils (Naito et al. 2004). Similar interactions were postulated in

the case of lactadherin (Haggqvist et al. 1999) and AA has four phenylalanine

residues including a pair (Westermark et al. 1992).

Later studies of �2-microglobulin fragments found no correlation between their

length, hydrophobicity, secondary structural propensity and ability to associate into

fibrils. In contrast, the presence of a relatively high content of aromatic side-chains

did correlate with amyloid formation, leading the authors to postulate that �-�

stacking was critical for amyloidogenesis (Jones et al. 2003). Sequences with a high

concentration of aromatic residues have also been found in PrP and Sup35.

Cumulatively, this evidence suggests that aromatic residues are likely to be critically

important in amyloidogenesis (Gazit 2002b).

Aromatic interactions are important in many areas of biology and chemistry (Gazit

2002b); Kevlar being a prominent example (McGaughey et al. 1998). Stacking of

aromatic rings provides stacking energy, order and directionality; thus driving and

stabilising structural assembly, whilst providing necessary selectivity. These non-

covalent interactions contribute to the packing of hydrophobic cores of protein, the


131

formation of tertiary structure, host-guest interactions, porphyrin aggregation in

solution and DNA base packing (Waters 2002). The characteristic thermal stability of

thermophilic proteins is aided by aromatic clusters in a T-shaped, orthogonal-packing

geometry in comparisons with mesophilic homologues (Kannan and Vishveshwara

2000). Congo red forms micelles due to parallel stacking of the aromatic rings (Stopa

et al. 1997). Its interaction with the phenylalanine residues may explain how it

inhibits fibril formation from certain proteins including A� (Klunk et al. 1989) and

IAPP (LeVine 1993).

Furthermore, aromatic interactions have been shown to be vital in many general self-

assembly processes (Claessens and Stoddart 1997; Gillard et al. 1997) and molecular

recognition (Shetty et al. 1996; McGaughey et al. 1998). Stable, well-ordered

nanotubes have been formed from assembly of diphenylalanine two-residue peptide,

with the order driven by aromatic interactions (Reches and Gazit 2003). Adjacent �-

strands were aligned during the spontaneous molecular self-assembly process by �

stacking to form polymeric tapes (Aggeli et al. 1997).

4.5.2 Conclusion

High-resolution diffraction patterns have, for the first time, enabled the determination

of the nanostructure of an amyloid fibril. Side-chain arrangements have been

revealed, allowing the detailed nature of the interactions between �-sheets to be

visualised.

The structure is composed of �-strands, laterally associated to form �-sheet ribbons,

which layer on top of one another to form a three-dimensional lattice. Charge pairing

and a phenylalanine zipper provide stability. The staggered arrangement creates a

highly stable, crystalline structure with the capacity to extend in all three dimensions.

π-stacking supplies an energetic contribution (Hunter 1993), which may drive the

self-assembly process. Side-chain interactions result in specific directionality, order

and orientation leading to a highly ordered, stable, cross-� structure, rather than

amorphous aggregate. Proteins have a unique side-chain arrangement that packs to

form the core of amyloid. Amyloidogenic protein appears to have many aromatic and


132

charged residues. It is these specific side-chain interactions that control self-assembly,

its rate, the resulting order and therefore stability. This structure shows intersheet and

interstrand side-chain interactions and emphasises their significance for

amyloidogenesis and cohesion within the superstructure.

Our proposed structure for AAAK amyloid nanocrystals was derived by a process of

modelling. The modelling process used data from electron microscopy, electron

diffraction and X-ray fibre diffraction in conjunction with stereochemical constraints

to establish the most likely configuration. We were not able to determine the phases

of the structure factors experimentally, so uniqueness cannot be shown, as would be

the case in single-crystal X-ray crystallography. Comparison of experimental and

simulated fibre diffraction patterns shows good agreement at low resolutions;

however there are some differences at higher resolutions, showing that improvement

is possible. The orientation of aromatic rings is fixed owing to their width and the fact

that there are sixteen in a unit cell, making only one rotamer possible. The

arrangement of other side chains is largely unconstrained and the orientations shown

in the models are due to energy minimisation and molecular dynamics. Whilst this is

the best model tested, we cannot completely rule out the possibility of other models.

Chapter 5. Discussion

133

5 Discussion

5.1 Models of Amyloid Structure

5.1.1 Introduction

Many models have been proposed for the structure of amyloid. Most of these are

either tubular or laminated �-sheets; the major exception being structures consisting

mainly of native structure (Inouye et al. 1998; Bousset et al. 2002; Serag et al. 2002).

Tubules can be built either from a cross-� structure (Kirschner et al. 1987; Inouye et

al. 1993; Lu et al. 2003) or a single �-sheet wrapped around a hollow core. In the

latter case, the shape can be either cylindrical, giving a nanotube or triangular

prismatic, resulting in a �-helix (Lazo and Downing 1998; Perutz et al. 2002; Wetzel

2002; Wille et al. 2002; Kishimoto et al. 2004).

5.1.2 Largely Native Structures

A largely native structure does not explain amyloid formed from precursor proteins

without a high �-sheet content but has been suggested in the cases of transthyretin and

Ure2p fibrils. There is some discussion as to whether Ure2p fibrils are amyloid. Some

studies implied a cross-� core (Baxa et al. 2003), whilst others suggested a structure

based on interaction between monomers (Bousset et al. 2002). Disagreements could

be attributed to different conditions; since, after heating, a cross-� structure was

postulated for Ure2p fibrils (Bousset et al. 2003).

Three transthyretin models have also been built in which the structure largely retains

its native structure. X-ray fibre diffraction reflection resolutions were measured and a

unit cell proposed that implied a structure composed of axially arrayed monomers

(Figure 5.2) (Inouye et al. 1998). Proximity information from site-directed spin-

labelling experiments lead to the suggestion of a head-to-head and tail-to-tail model

(Serag et al. 2002). In this model, the �-sheets present in native transthyretin interact,

resulting in an infinite �-sheet. The individual �-sheets are able to interact owing to a

substantial conformational change, which moves the terminal �-strand in native

transthyretin and thereby exposes the penultimate strand.


134

A crystal structure of a highly amyloidogenic triple-mutant of transthyretin revealed a

conformation in which there was a three-residue shift of one of the �-strands. This

conformation, referred to as a �-slip, creates a new packing arrangement in which the

molecules interact to form a double helical array of protein (Eneqvist et al. 2000).

Within the helix, a translation of 114.5 Å along the fibre axis results in superposition

of tetramers, similar to the meridional repeat of 115.5 Å found by fibre diffraction

(Blake and Serpell 1996). The diameter of the helix is 120 Å; close to the 130 Å

measured using electron microscopy (Serpell et al. 1995).

Largely native transthyretin structures (Figure 5.1) do not have simple �-sheet

stacking. The diffraction pattern for such structures is likely to be significantly more

complex than that observed for transthyretin fibrils. Native transthyretin has two �-

sheets, which are not parallel, so the �-strands in the fibril cannot be perpendicular to

the fibre axis. Neither has any meridional signal with a d-spacing of 29 Å been

detected (Blake and Serpell 1996; Inouye et al. 1998).

The largely native models may explain the features of individual amyloid fibrils but

do not aid the understanding of amyloid in general. Amyloid forms from precursor

peptides without a common secondary structure; so, the relatively small

conformational changes proposed in these models do not explain how such disparate

precursors form structures with the shared characteristics described in Chapter 1.


135

Figure 5.1. Pair of transthyretin molecules (1BMZ) (Peterson et al. 1998). Two four-stranded �-

sheets are present in each molecule forming a �-sandwich (Blake et al. 1978).


136

Figure 5.2. Transthyretin amyloid fibrils; four protofilaments are composed of arrays of

monomers (Inouye et al. 1998).

5.1.3 Water-Filled Nanotube

Perutz’s model for amyloid formed from polyglutamine, was described as being a

water-filled nanotube with an internal radius of 6 Å and an external radius of 16 Å,

with 20 residues per turn (Figure 5.3). The number of residues per turn might explain

the dependence of Huntington’s disease on the number of glutamine repeats (Perutz

and Windle 2001). A nanotube is a particularly appealing structure, similar to carbon

75 Å

40 Å

29 Å

23 Å


137

nanotubes and thus elegant in both its simplicity and symmetry. Nevertheless

“elegance is for tailors” (Boltzmann) so careful note must be made of the

experimental data.

Recently, both the nanotube and �-helix models have gained prominence, owing to

the observation of fibre diffraction patterns apparently without a 10 to 11 Å reflection.

Two possibilities were suggested for the existence of this signal in the case of A�.

This distance could have represented the packing between twisted amyloid

protofilaments or the protofilaments could be modelled as being double or triple

walled nanotubes (Perutz et al. 2002). In the polyglutamine amyloid pattern, an 8.3 Å

signal was present in the same direction at the 4.7 Å signal. The movement of the

reflection from its expected place could be explained by the texture of the sample,

since the experiment used a mat rather than a bundle of fibres. The reflection is at a

higher resolution than is usually expected for the spacing between �-sheets, owing to

the excellent packing made possible by the glutamine side-chains. Furthermore, the

observed diffraction pattern could be simulated using a conventional cross-� model

(Sikorski and Atkins 2005).

A nanotube may not necessarily explain amyloid’s resistance to enzymatic

degradation, particularly for the larger radius models, which were also postulated.

Although glutamines are not themselves hydrophobic, much of the side-chain is

hydrophobic, suggesting that the tube may not be water filled.


138

�

Figure 5.3. Views of Perutz’s model of amyloid, down the fibre axis (left) and from the side

(right) (Perutz et al. 2002).

5.1.4 General �-Helices

It has been suggested that the 10 to 11 Å reflection in the cross-� pattern was merely

an artefact due to dehydration (Kishimoto et al. 2004) and that a �-helix was a better

model (Jenkins and Pickersgill 2001; Wetzel 2002). �-helices are present in globular

protein structure, including pectate lyase C and E (Yoder et al. 1993; Lietzke et al.

1994) and the tailspike protein of Salmonella typhimurium phage 22 (Steinbacher et

al. 1994). In addition, a left-handed, parallel �-helix is present in the structure of

UDP-N-acetylglucosamine acyltransferase (Raetz and Roderick 1995).

A cylindrical antiparallel �-helix, somewhat similar to Perutz’s model, with a radius

of 10 Å, was proposed for amyloid, formed from the peptide with sequence

KLKLKLELELELG (Lazo and Downing 1997). Modelling was based on X-ray fibre

diffraction, electron microscopy and particularly circular dichroism spectra, using

information derived from the CD spectrum of pectate lyase E (Sieber et al. 1995).

This antiparallel model was further postulated for amyloid fibrils formed from

transthyretin, A� and immunoglobulin light chain (Figure 5.4) (Lazo and Downing

1998). A later study of the KLKLKLELELELG peptide using FTIR concluded that

the peptide did not form a parallel �-helix and was more likely to be an extended �-

strand (Khurana and Fink 2000).


139

�-helices in globular proteins are not identical to those proposed as amyloid models

since the former are almost completely filled with inward-facing side-chains rather

than water. Additionally, these helices are composed of stretches of straight �-strands

interspersed with sharp turns rich in glycine and proline residues, rather than a

continuous turn. Finally, amorphous aggregates of the P22 tail spike protein did not

show the same bands in circular dichroism spectra after staining with Congo red,

which were observed with amyloid fibrils; perhaps suggesting structural differences

between the �-helix and amyloid (Khurana et al. 2001).

Electron crystallography of scrapie prion fragments resulted in an averaged electron

density calculated using a p3 symmetry operation on a lattice of hexagonal units

(Wille et al. 2002). Projection maps of oligomers, presumed to be protofilaments and

thus cross-sections of amyloid fibrils were calculated. Calculation of the maps used a

model based on six left-handed parallel �-helices per hexagon. These projections were

then compared with the averaged image. Only models containing �-helices were said

to be capable of satisfying the electron density constraints.

A �-helix has also been proposed for full-length A� amyloid based on hydrogen

deuterium exchange studies and a proline scan (Kheterpal et al. 2000; Wetzel 2002;

Kheterpal et al. 2003a; Kheterpal et al. 2003b; Williams et al. 2004). The exchange

data shows that hydrogen bonding is present along substantial lengths of the peptide

chain. In globular protein, �-sheets are composed of exchange protected regions six to

eight residues in length, interspersed with shorter, unprotected regions. Hence the �-

sheets in amyloid fibrils are either very wide or form close-to-ideal �-helices.

NMR data is inconclusive, owing to the limitations on the length scales it is capable

of measuring. However a �-helix built from parallel in-register �-strands would have a

seam running down the fibril. If such a �-helix collapsed, then the structure would be

very similar to the conventional cross-� arrangement (Petkova et al. 2002). It is also

difficult to see how a three-sided �-helix could fit in the electron density

reconstructions obtained for SH3. No evidence for a �-helical model was obtained for

the IAPP fibrils and the AAAK structure is very different to that of a �-helix.


140

�

Figure 5.4. The antiparallel �-helix is composed of �-strands running antiparallel to one another;

side-chains emerge from the core structure (Lazo and Downing 1998).

5.1.5 Cross-� Tubule

Studies which reported a cross-� tubular structure were generally based on analyses of

the equatorial region of X-ray diffraction patterns. Amyloid fibrils formed from a

series of short A� fragments were modelled using a tube made of 5-6 crystallites, in

which each crystallite was made of less than six �-sheets (Inouye et al. 1993). In some

versions of this model, the crystallites appeared to be organised like the spokes of a

wheel, so a tubule may not necessarily be the best description.

An earlier study on amyloid, formed from A� (1-28), hypothesised that the fibrils

were hollow tubular structures with a mean radius of 43 Å. The data could also have

been modelled as a pair of cross-� walls, 71 Å apart (Kirschner et al. 1987). The

values were obtained by calculating transforms of step function models and

comparing them to a graph of the equator of X-ray diffraction pattern. Both these

studies also proposed more conventional cross-� models.

Examination of the signals of the equator of X-ray diffraction pattern and subsequent

modelling concluded that the A� (1-40) amyloid fibrils were composed of 3 to 5

protofilaments. Each protofilament was a 30 Å wide tubule with a wall composed of

tilted �-strands (Figure 5.4) (Malinchik et al. 1998).

Small angle X-ray and neutron scattering in combination with circular dichroism,

atomic force microscopy and electron microscopy on A� (16-22) amyloid found only

hollow cylindrical particles fit the data. The proposed structure had a radius of 260 Å

with walls 40 Å thick. It was composed of laminated �-sheets wrapped around a

hollow core with a pitch of 2140 Å (Lu et al. 2003). It is not known whether some of


141

these results may also be explained by considering protofilaments twisting about an

electrolucent core.

Each of these studies only considered a quite limited ensemble of possible models.

The selection of initial models to be tested and optimised appears to have greatly

influenced the results in each case. It may be that a wider choice of starting models

and more flexible adjustment of them would result in models similar to those

postulated using other techniques.

�

Figure 5.5. Possible structure of A� (1-40) in which four double walled, tubular protofilaments

constitute the fibril (Malinchik et al. 1998).

5.1.6 Conventional Cross-� Structure

The vast majority of studies have proposed conventional cross-� structures (see Table

5.1 and Table 5.2), although there is substantial diversity between models. The first

major amyloid model was of transthyretin fibrils (Blake and Serpell 1996) and later

extended to amyloid in general (Sunde et al. 1997). Some models have parallel and

others antiparallel organisations of �-strands, with increasing amphiphilicity shown to

change the alignment from antiparallel to parallel (Gordon et al. 2004). Full-length

A� and A� (10-35) both have hydrophobic regions, which are not distributed

symmetrically about the centre of the peptide (residues 17 to 21 and 29 to 40). A

parallel, in-register model will juxtapose these hydrophobic regions; unfortunately, it

will also juxtapose charged residues, which will require counter ions or interactions

between �-sheets to overcome the unfavourable electrostatic interactions. In contrast,

A� (16-22) and A� (34-42) both have central hydrophobic regions, so antiparallel


142

extended �-strands will both juxtapose the hydrophobic regions and minimise the

electrostatic energy. Both the suggested IAPP fibril model (Chapter 3) (Makin and

Serpell 2004b) and AAAK nanocrystal structure (Chapter 4) (Makin et al. 2005) fitted

well into the cross-� paradigm and appeared clearly to exclude the other models.

Of particular interest is the nature of any twist in the fibril and its constituent

protofilaments (Figure 5.6). The �-sheets within the protofilament may twist at the

same rate as the protofilaments twist about themselves, resulting in a twist of a few

degrees per strand (as found for insulin fibrils (Jimenez et al. 2002)). Alternatively,

the rates may be very different, which was proposed as a common core structure for

amyloid fibrils, with a twist of approximately 15° per stand (Sunde et al. 1997). The

key difference between these models is as to whether there is a region of the

protofilament that does not interact with any other protofilament. In the first case, the

cross-section rotates as a rigid unit along the helical structure; so all packing contacts

remain the same. This allows interacting regions to be in contact with one another

along the length of the fibril. By the same logic, non-interacting regions, including

large loops and folded domains, outside the cross-� core do not interfere with the

packing of protofilaments. The AAAK model does not feature any twist, owing to the

absence of any evidence in the diffraction or micrographic data. This may be due to

the helical repeat distance being sufficiently large for the corresponding reflection to

be lower than that of the beamstop; alternatively the curvature in the �-sheet may

limit the size of the nanocrystals (Diaz-Avalos et al. 2003a).

Many questions remain to be fully answered, at all levels of structural detail.

1. Which segments of the sequence form �-strands? Is there any non-� secondary

structure? If so, where and why?

2. What is the supramolecular organisation of �-sheets? Strands may be mutually

parallel, antiparallel or perhaps some mixture of the two, which may or may

not be regular. What factors, including sequence, determine this organisation?

3. Are the �-sheets laminated and how do the sheets interact with one another?


143

4. Why do fibrils stop growing in diameter?

5. What causes the conformational change leading to amyloidogenesis?

6. Do the �-sheets form any sort of tubular structure? If so, where are the bends

along the chain?

7. Does amyloid have a well-defined backbone and side-chain organisation or is

the translational order of the peptide backbone only approximate?

8. Is the disorder static or dynamic?

9. How can the structure be used to find how and why fibrils are formed and can

we interfere with this process? Which intermolecular and intramolecular

interactions control the stability of the fibre?

10. How do specific amyloid structures relate to amyloid structure in general?

Which aspects of the amyloid structure are sequence specific?

11. How does amyloidogenesis relate to the overall phenomenon of protein

misfolding?

12. How do the structures of the native or oligomeric precursors relate to the

mature fibril?


144

a b c

Figure 5.6. (a) Model of insulin fibril, comprising four protofilaments coloured red, green, orange

and cyan, each containing a pair of �-sheets. The transparent surface represents the

experimental EM density. (b) Model showing packing of a pair of protofilaments, the interacting

region of the protofilament is coloured purple. The protofilament twist matches that of the fibril

itself, so the interacting region remains in the core of the fibril. (c) Supercoiled protofilaments;

there is no correlation between the protofilament and fibril twist and the interacting region

rotates about the protofilament. Similar models may be constructed for other numbers of

protofilaments. (Jimenez et al. 2002) (Copyright 2002 National Academy of Sciences, U.S.A., used

with permission.)


145

Table 5.1. Summary of models postulated for the structure of amyloid using methods other than nuclear magnetic resonance.

Model Type of Amyloid Techniques Reference

86 Å diameter tubule or 71 Å apart walls of cross-� sheets. A� (1-28), A� (18-28), A� (18-28) mutant SAXS; XD; TEM (Kirschner et al.

1987)

Antiparallel �-strands A� (34-42) TEM; FTIR; XD (Halverson et al. 1990)

6 protofilaments Paired helical filaments TEM (reconstruction) (Crowther 1991)

Antiparallel �-strands A� (6-25) A� (22-35), A� (1-38), A� (1-40) XD; TEM (Fraser et al. 1991a)

Antiparallel �-strands A� (1-28), A� (19-28), A� (17-28), A� (15-28), A� (13-28), A� (11-28), A� (9-28) XD; TEM; FTIR (Fraser et al.

1991b)

Antiparallel �-strands, �-turn between Ser-26 and Gly-29 A� (10-43) TEM; FTIR; CD;

Protease digestion (Hilbich et al. 1991)

Cross-� A� (1-40) and mutants TEM; FTIR; XD (Fraser et al. 1992b)

Cross-� A� (11-28), A� (13-28), A� (15-28), A� (11-25) TEM; XD (Fraser et al.

1992a)


146


Hollow cylinder of 5-6 �-crystallites, each of ~5 �-sheets with ~6 residue strands

A� (19-28), A� (13-28), A� (12-28), A� (11-28), A� (9-28), A� (1-28), A� (1-38), A� (1-40), A� (6-25), A� (11-25), A� (34-42)

XD (Inouye et al. 1993)

Antiparallel �-strands A� (11-25) and mutants FTIR; XD; TEM (Fraser et al. 1994)

Polar zipper Polyglutamine CD; TEM; XD (Perutz et al. 1994)

Cross-�, twisted �-strands, 115.5 Å period TTR XD (Blake 1995)

Cross-� PrP (113-120), PrP (109-122), PrP (90-145) XD (Nguyen et al. 1995)

Four protofilaments, in square array TTR TEM (cross-sections) (Serpell et al. 1995)

Cross-�, twisted �-strands, 115.5 Å period TTR XD (Blake and Serpell 1996)

Quarter staggered �-sheets A� (11-28), H1 XD (Inouye and Kirschner 1996)

Cross-� with residual helical and disordered fold Lysozyme FTIR; HDX (Booth et al. 1997)


147


Twisted, probably not cylindrical protofilaments, polymorphic IAPP TEM; STEM (Goldsbury et al.

1997)

Cross-�, twisted �-strands, 115.5 Å period TTR variants, IgLC, IAPP (29-29), AA, lysozyme variant XD (Sunde et al. 1997)

Greek key motif with antiparallel C-termini �-strands A� (1-42) Model (Chaney et al.

1998)

Axially-arrayed, native monomers TTR XD (Inouye et al. 1998)

Cross-� Eleven-residue N-termini of apoSAA family XD; TEM (Kirschner et al. 1998)

Protofilaments are antiparallel �-helices, A� �-turn between Val-24 and Asn-27 TTR, A�, IgLC Model (Lazo and Downing

1998)

Antiparallel �-strands A� (1-42) Model (Mager 1998)

3-5, twisted, tubular protofilaments, ~460 Å period A� (1-40) XD; TEM (Malinchik et al.

1998)

Beaded structure, ~210 Å period A� (1-40) AFM (Blackley et al. 1999)

Antiparallel �-strands, �-turn between Gly-25 and Lys-28 A� (1-43) Model; Monte

Carlo simulations (George and Howlett 1999)


148


Double helix of 2 protofilaments, �-strand unclear, antiparallel shown SH3 Cryo-EM

(reconstruction) (Jimenez et al. 1999)

Antiparallel �-strands, �-turn between Gly-25 and Lys-28 A� (12-42) Model; Molecular

dynamics (Li et al. 1999)

�-hairpin or compact random coil Polyglutamine Model (Starikov et al. 1999)

Antiparallel �-strands, �-turn between Ile-32 and Gly-37 A� (14-23), A� (14-42) Model (Tjernberg et al.

1999)

Regular association of thin filaments (TTR), four protofilaments with left handed twist TTR (10-19), lysozyme, SH3 AFM (Chamberlain et al.

2000)

Antiparallel �-strands with twisted protofilaments �-synuclein TEM; AFM; CD;

FTIR (Conway et al. 2000a)

Twisted protofilaments IAPP AFM; STEM (Goldsbury et al. 2000a)

Polymorphic assemblies of twisted protofilaments A� (1-40) TEM; STEM (Goldsbury et al.

2000b)

Not all of sequence is hydrogen bonded A� (1-40) HDX (MS) (Kheterpal et al. 2000)


149


Not parallel �-helix, probably extended �-sheet

KLKLKLELELELG and ELELELELELELG FTIR (Khurana and Fink

2000)

Cylinder or tube of �-sheets, strands are in exact register A� (11-25) Cryo-EM (Serpell and Smith

2000)

5 to 6 protofilaments AA, IgLC, variant apolipoprotein A-I, variant lysozyme Single particle EM (Serpell et al.

2000b)

Parallel �-strands Sup35 fragment XD (Balbirnie et al. 2001)

N-terminal region not in �-sheet network A� (1-40) Proteolysis (Kheterpal et al. 2001)

Parallel �-strands SH3 FTIR (Zurdo et al. 2001)

Largely native structure Ure2p AFM; FTIR; Binding

(Bousset et al. 2002)

Most residues form rigid �-sheet core �2-microglobulin HDX (NMR) (Hoshino et al. 2002)

Helical cross-� protofilaments Insulin Cryo-EM (reconstruction)

(Jimenez et al. 2002)

Parallel, in-register �-strands, ~1200 Å period A� (10-35) Molecular

dynamics; TEM (Lakdawala et al. 2002)


150


Parallel �-strands with substantial fluctuations about a central core A� (10-35) Model; Molecular

dynamics (Morgan et al. 2002b)

Water-filled nanotube Polyglutamine XD; TEM (Perutz et al. 2002)

Mostly native, head to head, tail to tail arrangement TTR SDSL (Serag et al. 2002)

In-register, parallel �-strands A� (1-40) SDSL (Torok et al. 2002)

Parallel �-helix Amyloid in general Model (Wetzel 2002)

Left-handed parallel �-helix Scrapie prion fragments Electron crystallography (Wille et al. 2002)

Cross-� core Ure2p Digestion; Cryo-EM, STEM; MS

(Baxa et al. 2003)

Antiparallel �-strands, reverse turn A� (31-35) XD; EM (Bond et al. 2003)

Various cross-� models, unit cell found, P212121

GNNQQNY nanocrystals ED; Powder XD (Diaz-Avalos et al. 2003a)

Staggered cross-� Prion related XD (Inouye and Kirschner 2003)


151


Coiled tube of cross-� structure A� (16-22) SANS; SAXS; CD; AFM; TEM (Lu et al. 2003)

Antiparallel, monoclinic cross-� A� (11-25) XD (Sikorski et al. 2003)

C-terminus 30 % protected, N-terminus 50 % protected A� (1-40) HDX (MS) (Wang et al. 2003)

Largely native structure – fibrils are not amyloid Ure2p

CR; Proteolysis (MS, TEM, microsequencing)

(Bousset et al. 2004)

Left-handed parallel �-helix A� (15-36) Model (Guo et al. 2004)

�-helix (nanotube) Sup35 XD (Kishimoto et al. 2004)

Cross-� IAPP XD; ED; TEM (Makin and Serpell 2004b)

Parallel �-helix A� (1-40) Proline scan (Williams et al. 2004)

80 % of residues form distinct core �2-microglobulin HDX (NMR) (Yamaguchi et al. 2004)

Antiparallel Cross-� KFFEAAAKKFFE XD; ED; TEM (Makin et al. 2005)


152

Table 5.2. Models of amyloid fibrils derived from solid-state nuclear magnetic resonance data.


Not classic �-sheet, possible cis linkage between 37 and 38 A� (34-42) RR NMR (Spencer et al. 1991)

Antiparallel �-strands A� (26-40) A� (26-43) NMR; FTIR (Jarrett et al. 1994)

Highly pleated �-sheet, may be parallel IAPP (20-29) RR NMR (Griffiths et al. 1995)

Pleated antiparallel �-strands A� (34-42) RR NMR; FTIR (Lansbury et al. 1995)

Extended, primarily �-sheet like Hamster prion H1 (109-122) RR NMR (Heller et al. 1996)

Not classic �-sheet, trans linkage between 37 and 38 A� (34-42) Static echo RR NMR (Costa et al. 1997)

Antiparallel �-helix KLKLKLELELELG 13C MAS NMR; EM; CD (Lazo and Downing 1997)

Parallel, in-register �-strands A� (10-35) DRAWS NMR (Benzinger et al. 1998)

Parallel, in-register �-strands A� (10-35) DRAWS NMR (Gregory et al. 1998)

Parallel, in-register �-strands A� (1-40) MQNMR; STEM (Antzutkin et al. 2000)

Antiparallel �-strands A� (16-22) MQMNR, REDOR NMR (Balbach et al. 2000)

Parallel, in-register �-strands, no evidence for a turn A� (10-35) DRAWS NMR (Benzinger et al. 2000)


153


Parallel all �-sheets twisting along fibre axis A� (10-35) DRAWS NMR; EM; SANS (Burkoth et al. 2000)

�-strand backbone A� (16-22) fpRFDR-CT NMR (Ishii et al. 2001b)

Mixture of �-sheet and �-helical structure Mutant prion fragment 13C NMR (Laws et al. 2001)

Parallel, in-register �-strands A� (1-28) High resolution MAS NMR (Mikros et al. 2001)

Parallel, in-register �-strands A� (10-35) A� (1-42) MQNMR, dipolar recoupling NMR; STEM; EM

(Antzutkin et al. 2002)

Parallel �-strands A� (1-40) fpRFDR-CT NMR (Balbach et al. 2002)

Extended �-strand, may be parallel TTR (105-115) 13C 15N MAS, REDOR NMR (Jaroniec et al. 2002)

Parallel, in-register �-strands, disordered N-terminus A� (1-40) fpRFDR-CT, DQCSA NMR; STEM (Petkova et al. 2002)

Parallel in-register �-strands, non-� at residues 25, 26 and 29 A� (1-40) fpRFDR-CT, DQCSA, 2D

MAS exchange NMR (Antzutkin et al. 2003)

Parallel, folded �-sheets A� (1-40) mutant 13C 1H MAS NMR; SDSL; TEM; STEM; AFM (Antzutkin 2004)


154


Extended �-strand TTR (105-115) 13C 15N MAS NMR (Jaroniec et al. 2004)

Antiparallel, extended �-strand, out of register Designed seventeen-residue peptide

XD; TEM; STEM; REDOR NMR (Kammerer et al. 2004)

Antiparallel, �-strands, registry highly ordered, registry shift 1 or 3 depending on pH (7.4 or 2.4) A� (11-25)

15N-13C REDOR, fpRFDR-CT, 2D MAS exchange NMR

(Petkova et al. 2004)

Antiparallel, �-strands at pH 7.5 and 4.1. Mixture of parallel and antiparallel at pH 3.3. Random coil at C termini.

Human calcitonin 13C REDOR (Naito et al. 2004)


155

5.2 Conclusion We have designed and implemented a suite of software tools for the examination of

diffraction patterns from amyloid fibrils. Background reduction and contrast

enhancement components ensure that the best use is made of the available data. The

locations of signals can be accurately determined using automated peak measurement.

With this information, the unit cell determination program enables the testing and

improvement of potential unit cells. Finally, fibre diffraction patterns from models

can be simulated. In conjunction with other modelling programs, this allows the

determination of amyloid structure.

This application was used to analyse X-ray and electron diffraction data from amyloid

fibrils formed from full-length IAPP and AAAK. The IAPP amyloid study employed

this information in conjunction with cryo, negative stain and platinum/carbon

shadowing electron microscopy. The presence of layer lines showed that the structure

was highly ordered and contrast enhancement aided the measurement of the

diffraction reflections. These lead to the suggestion of an orthorhombic unit cell with

a = 4.7 Å, b = 19 Å and c = 38 Å. Using protofilament dimensions provided by the

electron micrographs and mass per unit length data from a previous study (Goldsbury

et al. 1997), a hypothetical model was constructed. In this model, the protofilament

was composed of four mutually antiparallel �-sheets. The IAPP peptide was spread

over three �-strands and perhaps formed an “e” shape (Jaikaran and Clark 2001).

Amyloid nanocrystals formed from AAAK were analysed in a similar manner. The

high quality of the resulting data enabled a detailed structure to be constructed by

comparing calculated and observed diffraction patterns. �-� intersheet and interstrand

interactions stabilised this structure, which supported the theory of an important role

of aromatic residues in amyloid formation and stability. The theory was derived from

the importance of benzene rings in other areas of macromolecular assembly (Gazit

2002b) and studies of amyloidogenic fragments. Studies, involving both the IAPP and

A� peptides, determining which fragments formed amyloid and which residues were

critical to amyloid formation, found phenylalanine residues to be critical to

amyloidogenesis. Other amyloid forming fragments also appeared to have a high


156

concentration of aromatic residues. Our studies showed cross-� structures similar to

those postulated for other amyloid. The results were commensurate with and add to

those of the other studies referenced herein.

Bibliography

157

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