Zinc-binding to leukocyte cell derived chemotaxin 2 and implications for its associated

amyloidosis

By

Jethro Emmanuel Prinston

A thesis submitted in conformity with the requirements

for the degree of Master of Science

Graduate Department of Biochemistry

University of Toronto

©Copyright Jethro Emmanuel Prinston, 2020

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Zinc-binding to leukocyte cell derived chemotaxin 2 and implications for its associated

amyloidosis

Jethro Emmanuel Prinston Master of Science Graduate Department of Biochemistry University of Toronto 2020 Abstract

Deposition of leukocyte cell-derived chemotaxin 2 (LECT2) as amyloid (ALECT2) leads to ALECT2 amyloidosis, an amyloid disease with no known cure. Recent findings indicate that ALECT2 amyloidosis is severely underdiagnosed. All sequenced ALECT2 amyloidosis patients have a single nucleotide polymorphism that changes an isoleucine

(WT) to a valine (58V) at position 58. Currently, little is known of the mechanism by which the protein misfolds and aggregates. Herein, we demonstrate the first molecular characterization of the misfolding and aggregation of the mature LECT2 protein. Through various biophysical methods, we found that zinc-binding alters the secondary structure, increases the conformational stability, and reduces aggregation propensity of both WT and 58V-LECT2. No significant difference was found between the variants in their secondary structure, conformational stability, and zinc-binding affinity. However, zinc-free

58V-LECT2 was significantly more amyloidogenic than WT-LECT2. Therapies aimed at

ALECT2 amyloidosis should exploit putative conformational differences between zinc- bound and zinc-free LECT2.

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Acknowledgements

This study would not be made possible without the support of several individuals.

I thank current and previous members of the Chakrabartty Lab: Dr Natalie Galant,

Meghan Wing, Dr. Kevin Hadley, Dr. Yulong Sun, Joseph Marsilla, and Allison Medina-

Cruz for their support and the time spent together. Special thanks to Dr. Natalie Galant for being the life of the lab, for her willingness to help, and for being a role model scientist.

I thank Meghan Wing for being the Natalie to my Yulong. I thank Dr. Kevin Hadley for answering my impromptu questions in the lab and for his supportive nods during presentations. I thank Dr. Yulong Sun for his help with experimental design and for performing the site-directed mutagenesis and subsequent cloning for 58V-LECT2. I thank

Dr. Avijit Chakrabartty for his supervision and the opportunity to partake in this study. I thank Dr. Simon Sharpe and Dr. Walid Houry for their critical evaluation and insightful discussions.

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Table of Contents

Abstract ii

Acknowledgements iii

Table of Contents iv

List of Figures vii

List of Tables viii

List of Abbreviations ix

Chapter 1: Introduction 1

1.1 Background

1.1.1 Protein folding 1

1.1.2 Protein folding and the hydrophobic effect 2

1.1.3 Molecular chaperones in folding protein 4

1.1.4 Protein misfolding and pathology 5

1.2 ALECT2 Amyloidosis

1. 2.1 Pathophysiology of ALECT2 amyloidosis 7

1. 2.2 ALECT2 amyloidosis and its ethnic bias 9

1. 2.3 Diagnosis of ALECT2 amyloidosis 10

1. 2.4 Implications of the I58V change in ALECT2 amyloidosis 10

1. 2.5 Structure and reported physiological activities of LECT2 11

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1. 2.6 Potential pathogenesis of ALECT2 amyloidosis 14

1.3 Rationale and Present Study 15

Chapter 2: Materials and Methods

2.1 Protein Expression and Purification 19

2.2 Placement of Disulfide Bonds 20

2.3 Circular Dichroism Spectroscopy 20

2.4 Tryptophan Fluorescence Spectroscopy 21

2.5 Urea Denaturation 21

2.6 LECT2 Zinc Affinity 22

2.7 pH Dependence of Aggregation 23

2.8 Time Course of Aggregation 24

2.9 ThT Fluorescence Assay 24

Chapter 3: Results

3.1 LECT2 is recombinantly expressed with the correct disulfide bonds 26

3.2 Zinc binding alters conformation of LECT2 29

3.3 Zinc binding stabilizes LECT2 33

3.4 WT and 58V-LECT2 have no significant difference in affinity for zinc 37

3.5 Loss of zinc from LECT2 significantly raises its propensity for aggre- gation 39

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3.6 Zinc-free LECT2 might be the aggregation-prone intermediate that leads to amyloid 42 3.7 Zinc-free 58V-LECT2 forms amyloid, whereas zinc-free WT-LECT2 forms non-amyloid aggregates 44 Chapter 4: Discussion 47

Chapter 5: Future Directions 54

References 57

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List of Figures

Figures Page

1 Ribbon diagram of LECT2. 13

2 Proposed hypothesis of the formation of misfolded LECT2 and sub- 16

sequent amyloid fibrils.

3 SDS-PAGE gel showing different steps of the purification process for

recombinant LECT2. 27

4 Schematic representation of the amino acid sequence of the purified recombinant LECT2 protein. 28

5 Far-UV circular dichroism spectra of LECT2. 31

6 Tryptophan fluorescence spectra of LEC2. 32

7 Denaturation of LECT2 monitored by fluorescence. 34

8 Unfolding curves of LECT2 after baseline subtraction. 35

9 Zinc-binding to WT or 58V-LECT2 monitored by fluorescence. 38

10 pH-dependence of aggregation of zinc-bound and zinc-free LECT2. 41

11 Time-course of aggregation of zinc-bound and zinc-free LECT2. 43

12 ThT fluorescence of aggregated WT and 58V-LECT2. 46

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List of Tables

Table Page

1 Thermodynamic parameters governing the denaturation of zinc-bound and

zinc-free LECT2 at pH 7.4 36

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List of Abbreviations

A Adenine AD Alzheimer’s disease AL Amyloid light-chain ALECT2 Amyloid leukocyte cell derived chemotaxin 2 ALS Amyotrophic lateral sclerosis ATP Adenosine triphosphate Aβ Amyloid β ATTR Amyloid transthyretin BBB Blood-brain barrier BCA Bicinchoninic acid CD Circular dichroism CNS Central nervous system SOD1 Superoxide dismutase 1 EDTA Ethylenediaminetetraacetic acid ESRD End-stage renal disease G Guanine HD Huntington’s disease I58V Isoleucine to valine change at position 58 IAPP Islet amyloid polypeptide IHC Immunohistochemistry IPTG Isopropyl β-D-1-thiogalactopyranoside Kd Disassociation constant LB Lysogeny broth LCM Laser capture microdissection LECT2 Leukocyte cell-derived chemotaxin 2 MALDI Matrix-assisted laser desorption/ionization MF2 Mag-fura 2

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mRNA Messenger ribonucleic acid MS Mass spectrometry Ni-NTA Nickel-nitrilotriacetic acid PD Parkinson’s disease PDB Protein data bank RA Rheumatoid arthritis SDS-PAGE Sodium dodecyl sulfate polyacrylamide gel electrophoresis siRNA Small interfering ribonucleic acid SNP Single nucleotide polymorphism ThT Thioflavin T TTR Transthyretin UV Ultraviolet WT Wild type

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CHAPTER 1

INTRODUCTION

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CHAPTER 1

1. INTRODUCTION

1.1 Background

1.1.1 Protein folding

Proteins are macromolecules responsible for a multitude of biochemical functions and are central to biological processes in all living systems. A protein’s function is dictated by its three-dimensional structure which is – as postulated by Anfinsen – determined by the protein’s amino acid sequence (Anfinsen, 1973). For a newly synthesized polypeptide to correctly perform its function, it must first fold into its correct three-dimensional structure. This folding process begins as the unfolded polypeptide that is being synthesized by ribosomes forms local segments of secondary structure stabilized by intramolecular hydrogen bonds (Hardesty et al., 2014). Once formed, α-helices and β- sheets, which are often amphipathic, aid in the formation of tertiary structures with polar residues facing the solvent (usually water) and non-polar ones rearranging to form the hydrophobic core of the protein from which water molecules are excluded. Folding is a cooperative process and thus as regions of the protein fold and stabilize its conformation, the subsequent folding of other regions is accelerated. During folding, the polypeptide temporarily assumes various discrete, lower free energy states where it is partially folded and requires some activation energy to proceed to the next state until it reaches the energy levels of the native state. In proteins with multiple domains, folding seems to be hierarchical with smaller regions folding first and interacting to form large regions. The rate at which proteins fold varies greatly due to the large variability in their amino acid

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sequences and structure patterns. While small proteins can fold in microseconds, larger proteins may require hours to adopt the native state (Ivankov et al., 2009; Naganathan &

Muñ Oz, 2005).

1.1.2 Protein folding and the hydrophobic effect

Protein folding is a spontaneous process mainly driven by the hydrophobic effect which is the tendency for non-polar substances to associate in aqueous solvents (Southall et al., 2002). The hydrophobic effect facilitates folding by minimizing the number of non- polar residues exposed to water forcing them into the core of the protein (Pace et al.,

1996). The hydrophobic effect is to due to the formation of hydration shells comprised of ordered networks of hydrogen bonded water molecules surrounding nonpolar residues.

The order of these hydration shells reduces entropy in the system and is therefore thermodynamically unfavourable. During hydrophobic collapse, nonpolar residues fold inward exposing polar ones; this collapse leads to the formation of a molten globule with much of the secondary structure but little tertiary structure. Surrounding water molecules then form hydrogen bonds with the exposed polar residues which reduces both the number of water molecules restricted in the ordered hydration shells and the order in the system. The rise in entropy associated with the decrease of order is favourable and drives protein folding. Once folded, the hydrophobic core stabilizes the protein with the accumulation of abundant van de Waals forces (Voet et al., 2016).

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1.1.3 Molecular chaperones in protein folding

In vitro some proteins can fold quickly and spontaneously but in vivo, the environment is highly crowded, and many proteins require assistance to adopt their native and functional conformation in a biologically relevant timescale. This assistance is mediated by essential proteins known as molecular chaperones (Pelham, 1986).

Chaperones are found in all cellular compartments and may begin facilitating folding even as polypeptides are being synthesized by ribosomes (Hartl et al., 2011). To aid in folding, chaperones repeatedly bind and release unstable regions of partially folded or unfolded proteins to disrupt incorrect association of hydrophobic segments that would otherwise lead to non-native folding and/or aggregation (Voet et al., 2016). The cycle of binding and release is an ATP-dependent process that persists until the hydrophobic surface is no longer exposed which therefore generates a more efficient pathway for the correct folding of the protein. Chaperones play a key role in supressing protein aggregation by isolating individual proteins which in turn prevents protein-protein interaction that may interrupt correct folding. They also prevent aggregation by unfolding misfolded proteins which promotes their correct refolding (S. Lee & Tsai, 2005). Chaperones also aid in the refolding of proteins denatured by environmental factors including changing temperatures, mechanical forces, and extreme pH.

Chaperones along with components of the ubiquitin protease system (UPS) are part of a group of proteins known as the proteostasis network which is important for processes that maintain proteostasis or protein homeostasis including protein trafficking and degradation. For instance, chaperones work with E3 ubiquitin ligases to recognize and target misfolded proteins for proteasomal degradation (Kim et al., 2013). Although

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important for folding, chaperones are not folding catalysts which operate by accelerating rate limiting steps on the folding pathway. Folding catalysts include disulfide isomerase and peptide-prolyl isomerases which facilitate disulfide formation and interconversion between proline isomers respectively (Thomas et al., 1997).

1.1.4 Protein misfolding and pathology

During folding, polypeptide chains explore a funnel-shaped free energy landscape with multiple local minima. They sample various states at intermediate energy levels towards the lower energy level of native state. These partially folded intermediates may become trapped at non-native local minima and can undergo rapid hydrophobic collapse that may lead to disorganized globules or misfolded states stabilized by non-native interactions. In healthy cells, misfolded proteins are refolded by chaperones or degraded via the UPS. When misfolded proteins fail to undergo refolding or degradation, they tend to aggregate in a concentration-dependent manner due to exposed hydrophobic regions that promote intermolecular interactions (Labbadia & Morimoto, 2015; Lavatelli et al.,

2010). Most of these aggregates are amorphous but some will adopt a highly ordered fibrillar structure known as amyloid (Hartl, 2017). Amyloid fibrils, usually 7-13nm in diameter comprise protofilaments twisting around each other with a common core cross-

β structure in which β-strands are oriented perpendicularly to the fibril axis. This amyloid structure is vastly more stable than its precursor favoring its accumulation. The formation of amyloid and its deposition in various tissues lead to amyloidosis diseases which can be caused by more than 30 protein species. The pathological features of these conditions depend on the location of amyloid deposition and include neurodegeneration when

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localized within the central nervous system (CNS), but varied clinical presentations ranging from renal failure to cardiomyopathy outside of the CNS (Chiti & Dobson, 2017).

Amyloidosis diseases affecting the CNS including Alzheimer’s (AD), Parkinson’s

(PD), and Huntington’s (HD) are caused, at least in part by the misfolded protein species amyloid-β (Aβ), α-synuclein, and huntingtin respectively (Ghosh et al., 2014; Hoop et al.,

2016; Nilsberth et al., 2001). These conditions cause degeneration and death of neurons, impair cognitive and motor functions, and presently have no cure. In these CNS- associated amyloid diseases, toxicity is mainly mediated by pre-fibril oligomers rather than mature fibrils themselves (Benilova et al., 2012; Roberts & Brown, 2015). Amyloid depositions can be both extracellular (Aβ plaques deposition in AD) or intracellular (α- synuclein as Lewy bodies in PD) (Chiti & Dobson, 2017). CNS-associated amyloid diseases affect a significant proportion of the elderly, with AD affecting as much as 40% of individuals over 80 years of age. Although most cases of AD and PD are sporadic, there are familial forms of the conditions that lead to the development of early onset symptoms. The late onset of the sporadic forms of these conditions potentially signify a progressive accumulation of deposits over years. Currently, therapies targeting fibril formation and/or deposition in the CNS have been unsuccessful, one likely reason being the difficulty in transporting therapeutic molecules across the blood brain barrier (Lipsman et al., 2018; Pardridge, 2016).

Amyloidoses not affecting the CNS are caused by various protein species including immunoglobulin light chains, transthyretin (TTR), and islet amyloid polypeptide (IAPP).

Once considered rare diseases, these amyloidoses are now known to be underdiagnosed with some forms showing deposits in a quarter of the population over 80 (Galant et al.,

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2017; Tanskanen et al., 2008). Deposition can be systemic (affecting many organs) or localized (restricted to a single organ) and except for one form (Galectin-7), all non-CNS amyloid protein species deposit extracellularly. Due to the number of different organs affected, non-CNS amyloidoses present widely varied symptoms such as renal insufficiency when the primary deposition site is the kidney or arrhythmia when the heart is affected (Leung et al., 2005; Longhi et al., 2015; Nasr et al., 2015b). In non-CNS amyloidoses, toxicity arises from both the mature amyloid fibrils which physically hampers the function of the organ and oligomeric species that cause most of the cellular damage

(Kastritis & Dimopoulos, 2016). Specifically, while amyloid fibril deposition applies direct mechanical stress to the surrounding tissue, oligomeric species induce cytotoxicity by interacting directly with cellular receptors of the cell membrane (Gharibyan et al., 2007;

Lee et al., 2012). With the approval of three drugs targeting ATTR amyloidosis, therapies targeting non-CNS amyloidoses seem promising (Ihne et al., 2020).

1.2 ALECT2 Amyloidosis

1.2.1 Pathophysiology of ALECT2 amyloidosis

One of the more recent proteins found to form and deposit amyloid in human tissue is the leukocyte cell-derived chemotaxin 2 (LECT2) (Benson et al., 2008). LECT2 deposits as amyloid (ALECT2) in various organs causing ALECT2 amyloidosis. Deposition sites include the kidneys, liver, and spleen although only the kidneys appear to develop significant pathology (Sethi & Theis, 2018). In ALECT2 amyloidosis, amyloid deposition within the kidneys is restricted to the renal cortex and medullary involvement is not as

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common. Misfolded LECT2 largely accumulates in the renal cortical interstitium, comprising both the cells and extracellular matrix compartment surrounding the renal tubules (Sethi and Theis, 2018); deposition also occurs in the glomeruli and renal vessels.

This is unlike other forms of amyloidosis (e.g. light chain [AL] and serum amyloid A [AA] amyloidoses) in which amyloid preferably deposits in the glomeruli and blood vessels

(Said et al., 2013). ALECT2 deposits in the liver are seen mostly surrounding portal tracts with a distinctive globular appearance. Hepatic ALECT2 amyloidosis is mild with few if any symptoms and it is usually an incidental finding. No deposition has been identified in the cardiac myocardium or brain. While ALECT2-associated mortality is uncommon, renal

ALECT2 amyloidosis patients suffer from chronic renal insufficiency, and although only

10% have full nephrotic syndrome, more than 30% have proteinuria within nephrotic range (Said et al., 2014; Jiménez-Zepeda and Leung, 2014). With simple supportive care, two thirds of patients see a decline in kidney function with half of those cases progressing to end-stage renal disease (ESRD). The median survival rate from diagnosis is 62 months. Presently, no specific therapies exist for ALECT2 amyloidosis; kidney transplantation is an effective but high-risk intervention and recurrence of amyloid deposition in the transplanted kidney has been observed (Said et al., 2014; Jiménez-

Zepeda and Leung, 2014). Nonsurgical treatments of this condition are critically needed, and potential future therapies include reducing the supply of LECT2, inhibiting fibrillogenesis and enhancing clearance of amyloid by the immune system.

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1.2.2 ALECT2 amyloidosis and its ethnic bias

ALECT2 amyloidosis is unique since it has a strong ethnic bias affecting mostly people of Hispanic descent. The condition also disproportionately affects other ethnic groups including First Nations Peoples in Canada, Punjabis, Arabs, Egyptians, and Native

Americans (Hutton et al., 2014). In the US, the incidence of ALECT2 amyloidosis in

Caucasian and African Americans is low (Larsen et al., 2016a). While ALECT2 amyloidosis is the third most common form of renal amyloidosis in the general US population, it is the most common cause of renal amyloidosis in southwestern American states (New Mexico, Arizona, and Texas) where the concentration of Hispanic Americans is the highest. In these sates, ALECT2 accounts for 54% of all renal amyloidosis cases

(Dogan, 2017; Larsen et al., 2010). An autopsy study of 520 patients of Mexican descent in the US revealed that 3.1% had undiagnosed renal LECT2 amyloid deposits that were undetected prior to autopsy (Larsen et al., 2016a). ALECT2 deposits were also found in the liver, lungs, adrenals and spleen of most of these cases. Extrapolating this percentage to the US population indicates that 1,600,000 Hispanic Americans may develop ALECT2 amyloidosis in their lifetime. In Egypt, ALECT2 amyloidosis accounted for 31% of all renal amyloidosis cases making it the second most common cause of renal amyloidosis in

Egyptians (Larsen et al., 2016). These findings demonstrate that ALECT2 amyloidosis pathology is highly prevalent in several specific demographic groups and the disease is severely underdiagnosed.

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1.2.3 Diagnosis of ALECT2 amyloidosis

At present, ALECT2 amyloidosis can only be diagnosed by a biopsy followed by either immunohistochemical investigation or proteomics studies. For immunohisto- chemistry (IHC), a standard panel of antibodies targeting amyloidogenic proteins, including LECT2-specific antibodies are used. IHC is a sensitive method to detect amyloid deposits but can lack specificity. Since there are more than 30 proteins known to form amyloid in vivo, there is a possibility for false positive results and therefore misdiagnosis.

In fact, some ALECT2 amyloidosis patients received treatment for an erroneous diagnosis of AL amyloidosis (i.e. chemotherapy and stem cell transplant). The most reliable method for the diagnosis of ALECT2 amyloidosis is laser capture microdissection (LCM) followed by mass spectrometry (MS). LCM/MS provides a detailed proteomic analysis of the excised amyloid deposits with definitive results on the responsible protein (Paueksakon et al., 2014; Slowik & Apte, 2017). When IHC staining is weak and results are inconclusive, LCM/MS typing is mandatory to avoid misdiagnosis. Although LCM/MS is highly sensitive and specific, it requires special equipment and is therefore only available at few large medical centers.

1.2.4 Implications of the I58V change in ALECT2 amyloidosis

In all ALECT2 amyloidosis patients who have had their LECT2 genes sequenced, there is a single nucleotide polymorphism (SNP) in exon 3 of the LECT2 gene

(homozygous guanine, G, genotype instead of adenine, A [G172A], [SNP rs31517]). This

SNP results in the replacement of an isoleucine by a valine at position 58 (I58V) of the

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amino acid sequence of the LECT2 protein (Larsen et al., 2014; Yamagoe et al., 1998).

With an allele frequency ranging from 0.51 to 0.73 depending on the source, this SNP is common in people of Mexican descent (Larsen et al., 2014). It is also more prevalent in

Mexican Americans than some other groups (eg. Caucasians and African Americans).

The presence of this prevalent polymorphism in all ALECT2 amyloidosis patients who have had their LECT2 gene sequenced suggests that this SNP is necessary but not sufficient for disease development. It has been hypothesized that this SNP increases the amyloidogenic propensity of the protein. It is also possible that, in addition to the polymorphism, unknown environmental factors may be cooperating to lead to disease manifestation (Murphy et al., 2010; Paueksakon et al., 2014). For example, the I58V change may affect LECT2’s interaction with its various binding partners. This polymorphism is also involved in Japanese and German rheumatoid arthritis (RA) patients: those with the homozygous G genotype which codes for 58V-LECT2 have less severe symptoms (Kameoka et al., 2000; Kopprasch et al., 2005). This I58V change associated with ALECT2 amyloidosis seems to be protective for RA progression and severity.

1.2.5 Structure and reported physiological activities of LECT2

Full-length LECT2 is 151 amino acids long and has an N-terminal 18-residue signal peptide, which is cleaved in mature LECT2. Mass spectrometry analysis of recombinant human LECT2 expressed in mammalian cell culture indicates that the protein binds one zinc ion, has three intramolecular disulfide bonds (Okumura et al., 2009; Okumura,

Suzuki, et al., 2013). The zinc ion in LECT2 was shown to be coordinated by histidine

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residue at position 53 and 138 (His53 and His138), an aspartate at position 57 (Asp57) and a water molecule. LECT2 is mostly β-structured and has a distorted β-sandwich architecture (Figure 1). LECT2 is the sole mammalian protein structurally related to the

M23 family of zinc metalloendopeptidase, but it lacks a catalytic histidine residue and therefore has no intrinsic peptidase activity (Zheng et al., 2016).

While early studies demonstrated that LECT2 has chemotactic activity in vitro – it was shown to cause neutrophils to move directionally – its biological role is still not well understood (Yamagoe et al., 1996). In humans, LECT2 is expressed in various tissues but in far greater quantities by the liver which secretes it into the blood (Ovejero et al.,

2004; Yamagoe et al., 1997). Normal plasma LECT2 concentration was estimated to be

20ng/mL+/-3.4ng/mL (Ando et al., 2012). Its serum level increases in liver-related diseases: acute liver injury, hepatocellular carcinoma, fatty liver, obesity and insulin resistance which has prompted investigations of LECT2 as a potential biomarker (Lan et al., 2014; Okabe et al., 2014; Okumura, Unoki-Kubota, et al., 2013; Ong et al., 2011; Sato et al., 2004). LECT2 has been described as a hepatokine that links obesity to insulin resistance in skeletal muscle because LECT2-deficient mice showed improved skeletal muscle insulin sensitivity while treatment with the LECT2 protein impaired the insulin signalling pathway (Lan et al., 2014; Misu, 2018; Zhang et al., 2018). The increased serum levels of LECT2 observed in obesity is therefore expected to cause skeletal muscle insulin sensitivity. LECT2-deficient mice do not show overt phenotypes but exhibit fragmentation and shrinkage of microtubules compared to wild-type mice, suggesting a role in neurite extension for LECT2 (Koshimizu & Ohtomi, 2010). Another study showed

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Figure 1. Ribbon diagram of LECT2 (pdb code: 5B0H). The amino acid residues coordinating 53 57 138 the zinc ion (gray sphere), His , Asp , and His are shown in yellow, the valine residue at position 58 is in green and the three disulfide bonds are shown in magenta. LECT2 consists of mostly antiparallel β-strands connected by loops.

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that mice treated with recombinant LECT2 had significantly improved outcome in experimental sepsis compared to those treated with saline suggesting a role in immune response (Lu et al., 2013). LECT2 was also shown to antagonize MET receptor activation and suppress hepatocellular carcinoma vascular invasion (Chen et al., 2014).

Involvements in these different systems suggests LECT2 to be a multifactorial hepatokine with roles in glucose metabolism, cell growth, immunomodulation, and tumor suppression. While the biological function of LECT2 is still not well established, it is apparent that the pathophysiology of ALECT2 amyloidosis is not related to the protein’s known physiological roles.

1.2.6 Potential pathogenesis of ALECT2 amyloidosis

Currently, the pathobiology of ALECT2 amyloidosis is unknown; some researchers believe that due to its overrepresentation in patients, the valine in 58V-LECT2 might increase the propensity of the protein to aggregate. Others believe that damage to the liver could raise the concentration of secreted LECT2 and therefore increase the likelihood of aggregation. Circulating levels of LECT2 have indeed been found to increase in various conditions, and an increased local LECT2 concentration could promote aggregation in the organs affected by ALECT2 amyloidosis. However, the serum LECT2 concentration has not been shown to be abnormally higher in ALECT2 patients (Murphy et al., 2010). Some have suggested that interference in LECT2’s catabolic or transport pathway could also lead to elevated local concentration. Since the entire mature LECT2 protein (133-residue long) has been found in amyloid deposits, it is unlikely that the misfolded and aggregation-prone form of LECT2 is a result of proteolytic reactions.

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Therefore, the pathogenesis of ALECT2 has mostly remained unknown since its molecular underpinnings have not been investigated until now.

1.3 Experimental rationale of present study

When the present study was initiated, the molecular basis of ALECT2 amyloidosis had not been investigated. At the time, no single study had attempted to describe the mechanism of LECT2 aggregation and amyloid formation. Most of the available literature focused on clinical cases and patient samples to characterize ALECT2 amyloidosis. Even today, only one study has investigated the aggregation and amyloidogenicity of LECT2 itself: therein the authors utilized peptides with the sequence of different regions of LECT2 in vitro to identify the protein’s amyloidogenic core – sections of the protein with the highest propensity for amyloid formation (Tsiolaki et al., 2019). They found that it spans residues 56-76 and 91-101 which are, for the most part, either buried within LECT2 or comprise β-structured regions. In this present study, we sought to investigate the molecular basis for the aggregation of full-length mature LECT2. Here, we express the

LECT2 protein recombinantly and authenticated it by mass spectrometry. We used various biophysical techniques including circular dichroism, tryptophan and Thioflavin T

(ThT) fluorescence spectroscopy to assess the impact of zinc binding and the I58V change on the secondary structure, conformational stability, aggregation propensity and amyloidogenicity of LECT2.

The experimental rationale of our hypothesis is partially based on previous work from our laboratory that investigated the molecular mechanism of Cu/Zn superoxide dismutase (SOD1) aggregation. SOD1 aggregation in spinal motor neurons is a hallmark of amyotropic lateral sclerosis (ALS). The project assessed the effect of oxidation, metal-

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LECT2 Natively LECT2 misfolding Amyloid fibril folded LECT2 intermediate

Figure 2. Proposed hypothesis of the formation of misfolded LECT2 and subsequent amyloid fibrils. We suspect that natively folded LECT2 (square) misfolds into an aggregation-prone intermediate (circle) that associates with other misfolded LECT2 intermediates to form amyloid fibrils. The newly formed fibrils then deposit in various tissue including the cortical interstitium (shown).

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binding, and ALS-associated mutations on the propensity for SOD1 aggregation (Rakhit et al., 2002). The characterization of the misfolding and aggregation of SOD1 led to the discovery of a misfolding intermediate that is aggregation-prone. The effective investigation of SOD1 and the similarities between the two proteins – both small metal- binding aggregation-prone proteins – motivated LECT2’s own probing. We hypothesized that LECT2 forms a misfolding intermediate that is the precursor for amyloid formation

(Figure 2).

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CHAPTER 2

MATERIALS AND METHODS

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CHAPTER 2

MATERIALS AND METHODS

2.1 Protein Expression and Purification

The following describes the protocol for purification of recombinant mature LECT2 from inclusion bodies. The pE100/D-TOPO vector from GeneArt (Invitrogen) encoding the sequence of WT LECT2 (UniProt entry O14960, without the 18 amino acid long signal peptide) with a hexa-histidine tag was used for protein expression. Plasmids were transformed into BL21 competent cells (Invitrogen), plated onto LB-agar plates containing

100 µg/mL ampicillin (BioBasic), and incubated at 37 °C overnight. Colonies were inoculated in 50 mL of LB-medium with 100 µg/mL incubated at 37 °C overnight and diluted into 2 L of LB-medium. When the culture reached an absorbance of ~0.6 at 600 nm, it was induced with 1 mM IPTG. Cells were harvested the day after induction by centrifugation at 5000 rpm (Beckman Avanti JLA8.1 rotor) for 20 min a 4 °C. Cell pellets were stored at -80 °C. Frozen cell pellets were resuspended in 80mL of lysis buffer and the protein was purified from inclusion bodies by sonication and centrifugation as described previously (Palmer & Wingfield, 2012). The protein was refolded on nickel-NTA beads (Sigma) with equimolar reduced and oxidized glutathione (1 mM) at 4 °C for 72 hrs and the eluted protein was dialyzed and purified further on Superdex 75 10/300 GL size exclusion column. Mass spectrometry experiments performed at SPARC Biocentre found

100% coverage of the sequence of recombinant LECT2 authenticating the protein.

The following protocol describes the purification of LECT2 from the soluble fraction. The I58V mutant was generated using the Q5 site-directed mutagenesis kit (New

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England Biolabs). The glycerol stocks of SHuffle T7 cells with either WT or 58V-LECT2 sequence were used to inoculate a starter culture with 50 mL of LB-ampicillin (100 µg/mL) overnight at 37 °C. The starter culture was used to inoculate larger cultures (25 mL of starter culture for 1 L) in LB-ampicillin. When the absorbance of the culture reached ~0.6 at 600 nm, the temperature was lowered to 23 °C. At an absorbance of ~0.8, protein expression was induced with IPTG (0.5 mM) and ZnCl2 (0.05 mM) and the temperature was lowered to 16 °C. Cells were then harvested the next day by centrifugation and frozen at -80 °C before lysis. The frozen pellets were dissolved on ice in a lysis buffer consisting of 100 mM Tris-HCl at pH 7.4, 500 mM NaCl, 30 mM imidazole and a mixture of protease inhibitors (Roche) (one tablet per 40 mL).The lysate was sonicated for 5 mn (4 s on 4 s off) and centrifuged at 15000 g for 1 hr and the supernatant was collected and kept on ice. LECT2 was purified from the supernatant with Ni-NTA beads and the elution was dialyzed against 20 mM Tris-HCl at pH 7.4 and 100 mM NaCl at 4 °C.

2.2 Placement of Disulfide Bonds

Samples containing LECT2 with intact disulfide bonds were incubated with sequencing-grade trypsin (Promega) overnight at 37 °C. The generated tryptic peptides were analyzed by mass spectroscopy. Mass spectrometry experiments were performed at the AIMS mass spectrometry laboratory. Samples were ionized by ESI and masses recorded were used to confirm the presence of disulfide linked peptides with correct disulfide bonds.

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2.3 Circular Dichroism Spectroscopy

Purified WT and 58V-LECT2 samples (20-23 µM) were prepared with zinc (10 µM

ZnCl2) or without zinc (treated with 100 µM EDTA and dialyzed) in 20 mM Tris-HCl 100 mM NaCl. Far-UV CD spectra were recorded from 198 nm to 260 nm with an Aviv spectropolarimeter (model 62DS) at 25 °C (1 mm path length, 1 nm step sizes, 1 nm bandwidth and 10 s averaging time).

2.4 Tryptophan Fluorescence Spectroscopy

Purified WT and 58V-LECT2 (5.6 µM) samples were prepared in 10 mM Tris-HCl pH 7.4 and either ZnCl2 (10 µM) or EDTA (100 µM). Samples were incubated at room temperature overnight and the fluorescence emission of each sample was measured from

310 to 370 nm with excitation at 280 nm using a Photon Technology International QM-1 fluorescence spectrometer (1 cm path length, 1 nm step sizes, 1 s average time).

2.5 Urea Denaturation

0 and 10 M urea stock solutions in 10 mM Tris-HCl pH 7.4 were prepared as previously described (Grimsley et al., 2006b). Purified WT and 58V-LECT2 (5.6 µM) samples were prepared with urea (0-8.1 M) in 10mM Tris-HCl pH 7.4 and either ZnCl2

(10 µM) or EDTA (100 µM). Samples were incubated at room temperature overnight and the fluorescence intensity of each sample was measured from 310 to 370 nm by excitation at 280 nm. A 1 cm cuvette was used in a Photon Technology International QM-1

21

fluorescence spectrometer. Fluorescence intensities from 324 to 328 nm were averaged and plotted as a function of urea concentration. Equations fitting the observed upper and lower baselines were used to extrapolate fluorescence of the native and unfolded states linearly at all urea concentration. Fraction of native LECT2 (f) was calculated with observed, native and unfolded fluorescence [1].

(퐹표푏푠푒푟푣푒푑 + 퐹푢푛푓표푙푑푒푑) 푓 = (퐹푛푎푡푖푣푒 + 퐹푢푛푓표푙푑푒푑)

[1]

The result was then fit in Kaleidagraph to a two-state model of the linear extrapolation method (no baseline slopes) where fN and fU are fraction native for the native and unfolded states respectively, [D] is concentration of urea, ΔGN-U is the free energy change

(푓 + 푓 ) ∗ 푒−(훥퐺푁−푈/푅푇 + 푚퐺[퐷]/푅푇)) 푓 = 푁 푈 1 + 푒−(훥퐺푁−푈/푅푇 + 푚퐺[퐷]/푅푇)

[2]

of unfolding, mF and mU are sloping baselines for the native and unfolded protein res- pectively, and mG is the cooperativity of unfolding (Santoro & Bolen, 1988).

2.6 LECT2 Zinc Affinity

Zinc-free WT and 58V-LECT2 were prepared with 100 µM EDTA and dialysed in

20 mM Tris-HCl at pH 7.4 and 100 mM NaCl. Three solutions were prepared, mag-fura 2

(MF2) alone (Invitrogen), MF2 with zinc-free WT-LECT2 and MF2 with zinc-free 58V-

LECT2. Concentrations of LECT2 and MF2 were 5 µM and 1 µM respectively. 10X stock of increasing zinc concentrations were added to the master mixes and the mixture was

22

incubated at room temperature for 15 min. Aliquots of the three samples were added to a 384-well plate (PerkinElmer) in triplicates (10 µL each). The fluorescence of MF2 was measured for all samples at 510 nm by excitation at 323 nm and 390 nm using a

SpectraMax M5 plate reader. The ratios between the intensities when excited at 390 nm and 323 nm were used to calculate fraction of MF2 bound to zinc. Fraction saturation as a function of zinc concentration were analyzed with DYNAFIT (Kuzmič, 1996) using a custom program that describes the competition between LECT2 and MF2 for zinc to estimate the zinc Kd for WT-LECT2 and 58V-LECT2. The program is based on the

(i+1) (i) recursive equation [2] where F , F , F0, and Fs are fluorescence intensities of the (i+1)th and ith estimate, at zero zinc concentration and at complete saturation respectively. Kd1 describes the affinity of LECT2 (P) for zinc and Kd1 that of MF2 for zinc. Total concen-

[푍푛] 1 (푖+1) 0 퐹 = 퐹0 + (퐹푠 − 퐹0) 푖 + 푖 [푀]0 + 퐾푑1 퐹푠 − 퐹 퐹 − 퐹0 퐾푑2 [푍푛]0 + [푃]0 푖 + [ 퐹푠 − 퐹0 퐹푠 − 퐹 퐾푑1 ]

[3] tration of zinc, the protein (LECT2), and the fluorescent indicator (MF2) is indicated by

[Zn]0, [P]0, and [M]0 respectively.

2.7 pH Dependence of Aggregation

Solutions were prepared for each sample (5.6 µM WT or 58V-LECT2, 10 µM ZnCl2 or 100 µM EDTA) in 10 mM sodium acetate, 10 mM sodium borate, 10 mM Tris-HCl, 10 mM formate, and 0.04% sodium azide. The pH of the solutions was measured and adjusted with either HCl or NaOH. The samples were then placed in a shaking incubator at 37 °C and 990 rpm for 24 hrs. The samples were then centrifuged at 15000 rpm in a

23

table-top centrifuge for 10min and the concentration of soluble protein in the supernatant was measured via the BCA assay (Walker, 1994). The resulting data was fit to the

Henderson-Hasselbalch equation in Kaleidagraph where f is the fraction aggregated,

10푎(−2푝퐻) + 10푏(−푝퐻−푝퐾푎1) + 10푐(−푝퐾푎1−2푝퐾푎2) 푓 = 10(−푝퐾푎1−푝퐾푎2) + 10(−푝퐻−푝퐾푎1) + 10(−2푝퐻)

[4] a, b and c are baselines before pKa1, between pKa1 and pKa2 and after pKa2 respectively.

2.8 Time Course of Aggregation

Four 2.2 mL samples were prepared with either WT-LECT2 or 58V-LECT2 with added ZnCl2 (10 µM) or EDTA (100 µM) in 20 mM Tris-HCl and 0.02% sodium azide at pH 7.4. At time zero, right before starting incubation at 37 °C in the shaker at 990 rpm, an

30 µL aliquot of each sample was transferred into a new tube and centrifuged at 15000 rpm for 10 min at 25 °C. The supernatant was used to estimate concentration of soluble protein via the BCA assay. In the subsequent 24 hours more aliquots were taken from the incubating samples and their concentration of soluble protein was measured. The procedure was also repeated without shaking at room temperature.

2.9 ThT Fluorescence Assay

Samples containing LECT2 (WT or 58V) with either ZnCl2 (10 µM) or EDTA (100

µM) in 20mM Tris-HCl at pH 7.4 were agitated at 990 rpm for 24 hrs at room temperature.

Aggregated LECT2 were mixed with Thioflavin T (ThT) (Sigma) to final concentrations of

5.5 µM and 20 µM, respectively. After incubation at room temperature for 20 min,

24

fluorescence was measured using excitation at 420 nm and emission from 450 to 530 nm in a Photon Technology International QM-1 spectrometer (1 cm path length, 1 nm step sizes, 1 s average time).

25

CHAPTER 3

RESULTS

26

CHAPTER 3

3. RESULTS

3.1 LECT2 is recombinantly expressed with the correct disulfide bonds

To characterize WT and 58V-LECT2, we expressed the proteins recombinantly in

E. coli since this expression system had been used previously to produce LECT2 (Ito et al., 1997, 2003). LECT2 was purified from inclusion bodies under denaturing and reduced conditions. The protein was then refolded while bound to Ni-NTA beads in the presence of equimolar reduced and oxidized glutathione. Figure 3 shows different steps of the purification process with the last lane displaying a single band for the purified recombinant

LECT2. With six cysteines, formation of aberrant disulfide within LECT2 was possible. To confirm the formation of the correct disulfide bonds (Cys25-Cys60, Cys36-Cys41, Cys99-

Cys142) (Okumura et al., 2009), the purified and refolded LECT2 with the disulfide bonds intact (unreduced) was digested by trypsin. The resulting disulfide-bonded fragments were analyzed by mass spectrometry (Figure 4). The mass spectrometry results indicated the presence of disulfide linked peptides that are consistent with correct disulfide bond formation.

27

kDa 260

95

72

42

26 ~18.7kDa 17

Figure 3. SDS-PAGE gel showing different steps of the purification process for recombinant LECT2. The solubilized inclusion bodies were extracted from the lysate by centrifugation and LECT2 was purified by nickel-affinity and refolded on Ni-NTA beads with reduced and oxidized glutathione. The arrow points to the final purified sample used. SpectraBR was used as protein ladder.

28

Figure 4. Schematic representation of the amino acid sequence of the purified recombinant LECT2 protein. The protein with its disulfide-bonds intact was digested by trypsin and the mass of resulting fragments were measured by mass spectrometry confirming the formation of correct disulfide bonds. The residues highlighted in dark-blue are the disulfide-bonded fragments resulting from the trypsin digestion. Disulfide bonds are represented as solid, gray lines while the yellow dashed lines indicate relevant trypsin cleavage sites. The observed mass of the disulfide bonded fragment (underlined) matches its expected mass (in parenthesis).

29

3.2 Zinc binding alters structure of LECT2

To confirm correct folding and investigate possible differences in structure associated with the I58V change or zinc binding, we used circular dichroism spectroscopy. The crystal structure of LECT2 is that of a distorted β-sandwich (Figure 1)

(Zheng et al., 2016). Surprisingly, the CD spectrum for LECT2 did not contain the signature β-sheet CD band at 218nm, but possessed an atypical CD minimum at 205 nm, which matched previously published CD spectra (Figure 5) (Ito et al., 2003). The spectra of WT and 58V-LECT2 display the same minimum around 205 nm suggesting similar secondary structures. While the minimum remains near 205 nm, its intensity changes depending on the state of zinc-binding suggesting a small conformational change upon binding zinc.

We also investigated the effect of the I58V change and zinc binding on structure of LECT2 with tryptophan fluorescence spectroscopy. LECT2 has several fluorescent residues including six tyrosine residues and one tryptophan residue which permit the use of fluorescence spectroscopy in monitoring structural changes in their environment.

Fluorescence peaked near 330nm with an excitation wavelength of 280 nm suggesting tryptophan as the main source of fluorescence. Zinc binding was found to reduce fluorescence intensity (Figure 6) indicating a change in the local environment of the tryptophan and therefore a change in the conformation of LECT2 (Ghisaidoobe & Chung,

2014). The reduction in fluorescence intensity is accompanied by a blue shift in maximum wavelength (λmax, 329 to 327 nm for WT and 329 to 325 nm for 58V-LECT2) suggesting that the tryptophan’s fluorescence is likely being quenched by neighboring amino acid side chains rather than water. Quenching due to water is usually seen with a red shift in

30

λmax (Vivian & Callis, 2001). This quenching in fluorescence accompanied with a blue shift in λmax upon binding zinc suggests that the tryptophan becomes further buried within the core of LECT2 near a charged residue, possibly K101 or the N-terminus itself. This in turn suggests that zinc-binding tightens the overall conformation of LECT2. Contribution by tyrosine residues to the observed fluorescence is likely minimal because of their inherently lower quantum yield and additional quenching by the peptide chain.

31

1 1

A B )

) -1

0 -1 0

dmol

dmol

2 2

-1 -1

deg*cm

deg*cm

3 3 -2 -2

-3 -3

-4 -4 Mean Residue Ellipticity (10 Ellipticity Residue Mean -5 (10 Ellipticity Residue Mean -5 WT-LECT2 +Zn 58V-LECT2 +Zn WT-LECT2 -Zn 58V-LECT2 -Zn -6 -6 190 200 210 220 230 240 250 260 190 200 210 220 230 240 250 260 Wavelength (nm) Wavelength (nm)

Figure 5. Far-UV circular dichroism spectra of LECT2. (A) WT-LECT2 and (B) 58V-LECT2 with zinc (●) and without zinc (○) in 20 mM Tris-HCl (pH 7.4) and 100 mM NaCl. Circular dichroism was measured at 25°C (1 mm path length, 1 nm bandwidth, 1 nm step size and 10 s averaging time).

32

5 6 WT-LECT2 +Zn 58V-LECT2 +Zn A WT-LECT2 -Zn B 58V-LECT2 -Zn 4.5

5 4

3.5 4

3

3

2.5

Fluorescence Intensity (AU) Intensity Fluorescence Fluorescence Intensity (AU) Intensity Fluorescence 2 2

1.5

1 1 310 320 330 340 350 360 370 310 320 330 340 350 360 370 Wavelength (nm) Wavelength (nm)

Figure 6. Tryptophan fluorescence spectra of LEC2. (A) WT-LECT2 and (B) 58V-LEC2 with zinc (●) and without zinc (○) in 10 mM Tris-HCl pH7.4. Tryptophan fluorescence intensity of 5.6 µM samples was measured at room temperature by excitation at 280 nm and emission from 310 to 370 nm (1 cm path length, 1 nm step size and 1 s averaging time).

33

3.3 Zinc binding stabilizes LECT2

To further investigate the effects of zinc binding on LECT2 and the potential differences between the conformational stability of WT and 58V-LECT2, their denaturation – by urea

– was monitored by tryptophan fluorescence (Figure 7) (Grimsley et al., 2006a). Zinc- bound and zinc-free forms of WT and 58V-LECT2 were equilibrated at increasing concentrations of urea at room temperature overnight and fluorescence was measured from 310 nm to 370nm after exciting the samples at 280 nm. Fluorescence at specific wavelength was plotted at different urea concentration and no significant difference was observed between the results for WT and 58V-LECT2 suggesting little to no change between the stability of WT and 58V-LECT2. For all curves, the single transition displays cooperative unfolding between native and unfolded states with clear sloping baselines for both states. Attempts to apply the linear extrapolation model (Bolen & Santoro, 1988;

Santoro & Bolen, 1988) to calculate free energies of folding were confounded by the sloping baselines that interfered with curve fitting procedures. Consequently, the sloping baselines were subtracted and the fraction of native LECT2 was calculated using

Equation 1. The results were plotted in Figure 8 and fit to a two-state model (with no baselines) using Equation 2 which yielded ΔGN-U and -mG values. Zinc binding was shown to stabilize LECT2 raising ΔGN- from 5.48 ± 0.74 kcal/mol to 8.26 ± 0.96 kcal/mol for WT-LECT2 and 4.29 ± 0.36 kcal/mol to 6.41 ± 1.20 kcal/mol for 58V-LECT2. Zinc binding did not significantly affect the cooperativity of unfolding (mG). See Table 1 for summary. There seems to be a small reduction in stability associated with the I58V change but this difference is within error.

34

A B WT-LECT2 +Zn 58V-LECT2 +Zn WT-LECT2 -Zn 58V-LECT2 -Zn 1 1

0.8 0.8

0.6 0.6

Fluorescence (AU) Fluorescence

0.4 (AU) Fluorescence 0.4

0.2 0.2

0 0 0 1 2 3 4 5 6 7 8 0 1 2 3 4 5 6 7 8 [Urea] (M) [Urea] (M)

Figure 7. Denaturation of LECT2 monitored by fluorescence. WT-LECT2 (A) and 58V-LECT2 (B) with zinc (●) and without zinc (○) were denatured by urea. Samples with 5.6 µM LECT2 in different concentrations of urea (0 to 8.1 M in 10 mM Tris-HCl pH 7.4) were incubated overnight at room temperature and intrinsic tryptophan fluorescence intensity from 324 to 328nm was measured by excitation at 280 nm (1 cm path length, 1 nm step size and 1 s averaging time).

35

y = ((m1)+(m3)*exp(-1*(m5/59... Value Error m1 1.0184 0.012791 m3 0.0015105 0.016932 m5 8260.4 963.87 y = ((m1)+(m3)*exp(-1*(m5/59... m6 -2221.3 259 A WT-LECT2 +Zn B 58V-LECT2 +Zn Value Error 1 1 Chisq 0.020025 NA WT-LECT2 -Zn 58V-LECT2 -Zn m1 1.0148 0.023275 2 0.99464 NA R m3 0.0083268 0.030403 m5 6409.7 1202.1 0.8 0.8 m6 -1574.9 297.63 Chisq 0.073997 NA y = ((m1)+(m3)*exp(-1*(m5/59... R2 0.9817 NA Value Error 0.6 0.6 m1 1.0182 0.028028 m3 -0.0041081 0.01383 m5 5478.5 742.9 m6 -2120.3 278.86 0.4 0.4 Chisq 0.026605 NA

R2 0.99172 NA

Fraction of Fraction LECT2 native Fraction of native LECT2 native of Fraction y = ((m1)+(m3)*exp(-1*(m5/59... 0.2 0.2 Value Error m1 1.0156 0.015493 m3 0.003294 0.0099434 0 0 m5 4287.2 360.64 m6 -1772.7 145.69 Chisq 0.016599 NA

0 1 2 3 4 5 6 7 8 0 1 2 3 4 5 6 7 8 R2 0.99598 NA [Urea] (M) [Urea] (M) Figure 8. Unfolding curves of LECT2 after baseline subtraction. WT-LECT2 (A) and 58V-LECT2 (B) with zinc (●) and without zinc (○) were denatured by urea. Equations fitting the observed upper and lower baselines were used to extrapolate fluorescence of the native and unfolded states linearly at all urea concentration. Fraction of native LECT2 was calculated with equation 1 and fit (solid and dashed lines) to a two-state model of the linear extrapolation method (no baseline slopes).

36

Table 1. Thermodynamic paramaters governing the denaturation of zinc-bound and zinc-free LECT2 at pH 7.4. ΔGN-U and -mG values are extracted from the fit of the denaturation curve after subtraction of baselines.

ΔGN-U(kcal/mol) -mG(kcal/(mol•M))

WT-LECT2 +Zn 8.26 ± 0.96 2.22 ± 0.26

WT-LECT2 -Zn 5.48 ± 0.74 2.12 ± 0.28

58V-LECT2 +Zn 6.41 ± 1.20 1.57 ± 0.30

58V-LECT2 -Zn 4.29 ± 0.36 1.77 ± 0.146

37

3.4 WT and 58V-LECT2 have no significant difference in affinity for zinc

Here we investigate whether the I58V change significantly affects the affinity of

LECT2 for zinc. The binding affinity was measured via a competition assay with a fluorescent dye, mag fura 2 (MF2) (Sydor et al., 2013). Figure 9 shows MF2-zinc fraction saturation in the presence of either WT or 58V-LECT2 as a function of zinc concentration.

The curves superimposed, indicating little to no difference in zinc binding affinity. A custom script used in DYNAFIT to fit the result estimated the Kd values of WT and 58V-

LECT2 for zinc to be 6.9+/-2.5 nM and 3.5+/-1.9 nM respectively, exhibiting no significant differences since they overlap when the error values are added (Kuzmič, 1996). This similarity in zinc binding affinity was unexpected since the residue at position 58 is in proximity to the zinc binding site. This proximity could have affected the coordination of zinc and therefore the protein’s affinity for the metal.

38

1

0.8 WT K =6.9+/-2.5nM d 58V K =3.5+/-1.9nM d

0.6

0.4 Fraction Saturated Fraction

0.2

0 0.001 0.01 0.1 1 10 100 [Zn] (uM)

Figure 9. Zinc-binding to WT or 58V-LECT2 monitored by fluorescence. The fraction of MF2 saturated with zinc (shown as triplicates) is shown as a function of zinc concentration in the presence of either WT-LECT2 (○) or 58V-LECT2 (●). Fluorescence intensity was measured at 510nm by excitation at 323 and 390nm. DYNAFIT was used to fit fraction saturation data and produce zinc Kd values of 6.9±2.5 nM and 3.5±1.9 nM for WT-LECT2 and 58V-LECT2 respectively. The data are fit to a sigmoidal function as a guide for the eye.

39

3.5 Loss of zinc from LECT2 significantly raises its propensity for aggregation

We then compared the effect of zinc on the aggregation of WT and 58V-LECT2 at different pHs. Samples were agitated at 37 °C for 24 hrs at different pHs and the extent of aggregation was assessed via measurement of soluble protein concentration after centrifugation of the samples. Zinc-free LECT2 has a significantly higher propensity for aggregation and possesses an aggregation peak closer to physiological pH compared to the zinc bound forms (Figure 10). When zinc is bound, both WT and 58V-LECT2 display aggregation peaks around pH 9.5 and the fraction aggregated in those solutions only reach slightly over 50% aggregation. However, when LECT2 is zinc-free, the aggregation peak is shifted towards physiological pH and reached over 70% aggregation. Since the isoelectric point (pI) of recombinant LECT2 is estimated to be 9, the observed pH dependence of aggregation is likely partially due to isoelectric precipitation (Harikrishnan et al., 2012).

The resulting pH dependence of aggregation was fit to the Henderson Hasselbalch equation (Equation 4) which yielded pKas of 8.48±0.14 and 10.31±0.20 for zinc-bound

WT-LECT2, 7.88±0.18 and 9.69±0.25 for zinc-free WT-LECT2, 7.80±0.11 and 10.88±0.35 for zinc-bound 58V-LECT2 and 7.46±0.16 and 9.83±0.21 for zinc-free 58V-LECT2. The first pKa ranges from 7.46 to 8.48 and likely indicates the ionization of histidine residues.

The pKa of histidine residues is usually stated as 6.5 but has been found to vary depending on the degree of their burial within the protein (Edgcomb & Murphy, 2002;

Thurlkill et al., 2006). Recombinant LECT2 was expressed with a hexahistidine tag and has a total of eleven histidine residues, two of which help coordinate the zinc ion (His53 and His118) (Zheng et al., 2016). The pKas obtained from the fit of the data are slightly

40

lower for the histidine residues for 58V-LECT2. This is likely due to a small difference in fitting caused by a slightly stronger aggregation peak for zinc-bound WT-LECT2 (and not a real significant difference between the ionization of the two variants). Most of the data show significant overlap between the WT and 58-LECT2 which contradicts the different pKas estimated. The second set of pKas ranges from 9.69 to 10.88 which suggests the ionization of lysine residues, twelve of which exist within recombinant LECT2. The pKa values for WT and 58V-LECT2 are within error and suggest little difference in the ionization of lysine residues. The shift of the aggregation peak towards physiological pH associated with the loss of zinc is well illustrated in the decrease of the first set of pKas between zinc-bound and zinc-free LECT2.

41

1 1

A B 58V-LECT2 +Zn WT-LECT2 +Zn 58V-LECT2 -Zn WT-LECT2 -Zn 0.8 0.8

0.6 0.6

0.4 0.4

Fractionaggregated Fractionaggregated

0.2 0.2

0 0 4 5 6 7 8 9 10 11 12 4 5 6 7 8 9 10 11 12 pH pH

Figure 10. pH-dependence of aggregation of zinc-bound and zinc-free LECT2. The fraction of aggregated WT-LECT2 (A) and 58V-LECT2 (B) is shown as a function of pH with or without zinc. Following incubation of 5.6 µM LECT2 with either 10 µM ZnCl2 (●) or 100 µM EDTA (○) for 24hr

at 37 °C and 990 RPM, concentration of soluble protein was measured via BCA assay and fraction aggregated was calculated. The lines (solid and dashed) represent the fit of the data to the Henderson-Hasselbalch equation (Equation 4). The pKas yielded are 8.48±0.14 and 10.31±0.20 for zinc-bound WT-LECT2, 7.88±0.18 and 9.69±0.25 for zinc-free WT-LECT2, 7.80 ±0.11 and 10.88±0.35 for zinc-bound 58V-LECT2 and 7.46±0.16 and 9.83±0.21 for zinc-free 58V-LECT2.

42

3.6 Zinc-free LECT2 might be the aggregation-prone intermediate that leads to amyloid

To explore the rate of aggregation, incubation of zinc-bound and zinc-free WT and

58V-LECT2 was monitored for ~16 hrs. While zinc-bound LECT2 (WT and 58V) showed little to no aggregation (Figure 11A), the zinc-free LECT2 displayed clear aggregation over the same period. This suggests that the loss of zinc might be one of the first steps in the amyloid formation process; it also suggests that the zinc-free LECT2 might be an intermediate that leads to amyloid formation. Again, no significant difference was found between WT and 58V-LECT2. No aggregation was observed when LECT2 (zinc-bound or zinc-free) remained unagitated at room temperature (pH 7.4) (Figure 11B). This absence of aggregation confirms that in those conditions (unagitated at room temperature) zinc-free LECT2 does not aggregate during our spectroscopic experiments and the differences observed are due to changes in the protein’s conformation and stability.

Aggregation was incomplete (<100%) in both experiments (pH dependence and time-course of aggregation) (Figure 10 and 11). This incomplete aggregation may be due to the duration of the incubation (16hrs); a longer incubation period might be needed for complete aggregation. It could also be due to aggregates being too small to sediment by the centrifugal force applied since the fraction aggregated was measured by the concentration of soluble protein left in the supernatant after centrifugation.

43

1 1 WT-LECT2 -Zn WT-LECT2 +Zn A WT-LECT2 +Zn B WT-LECT2 -Zn 58V-LECT2 -Zn 58V-LECT2 +Zn 58V-LECT2 -Zn 0.8 58V-LECT2 +Zn 0.8

0.6 0.6

0.4 0.4 Fraction aggregated Fraction aggregated Fraction

0.2 0.2

0 0 0 2 4 6 8 10 12 14 16 0 2 4 6 8 10 12 14 16 Time (hr) Time (hr)

Figure 11. Time-course of aggregation of zinc-bound and zinc-free LECT2. (A) Samples are incubated at 37 °C and agitated at 990 RPM. The data for the zinc-bound and zinc-free samples are fit to linear and sigmoidal functions respectively as a guide for the eye. (B) Samples are incubated at 20 °C with no agitation. Fraction aggregated was calculated from measured soluble protein concentration during incubation of 5.6 µM LECT2 with either 10 µM ZnCl2 (WT▲, 58V △) or 100 µM EDTA (WT ●, 58V

○). Concentration of soluble protein was measured via BCA assay. The data are fit to linear function respectively as a guide for the eye.

44

3.7 Zinc-free 58V-LECT2 forms amyloid, whereas zinc-free WT-LECT2 forms non- amyloid aggregates

To assess amyloid formation more directly, we used ThT, an amyloid dye, to quantify amyloid formation. Aggregation of zinc-bound and zinc-free WT and 58V-LECT2 was induced by agitation at 37 °C for 24 hrs at pH 7.4. After aggregation, all four samples were incubated with ThT and fluorescence was measured (λEx: 420 nm and λEm: 450 to

530 nm) (Xue et al., 2017). Loss of zinc from the 58V-LECT2 seems to induce significant amyloid formation compared to zinc loss from WT-LECT2 as the ThT fluorescence intensity for zinc-free 58V-LECT2 was significantly greater than that of zinc-free WT-

LECT2 (Figure 12). The results display reduced fluorescence intensity and significant overlap of the spectra for both zinc-bound WT and 58V-LECT2, which suggests that zinc binding might prevent or markedly slow amyloid formation. In contrast, zinc-free WT-

LECT2 only produced moderate ThT fluorescence, indicating slightly more binding and amyloid formation than the zinc-bound LECT2 but less than zinc-free 58V-LECT2. Zinc- free 58V-LECT2 shows by far the strongest ThT fluorescence which suggests that zinc- free 58V-LECT2 is amyloidogenic and zinc-free WT-LECT2 is not. This experiment was repeated with triplicates and the result again suggest a higher propensity for amyloid formation for the 58V-LECT2 when zinc free (Figure 13).

From our previous experiments, we expected no difference in ThT fluorescence between variants WT and 58V-LECT2 but since zinc-free was shown to aggregate more, we expected a significantly higher fluorescence for the zinc-free forms. As expected, zinc- bound WT and 58V-LECT2 produced the same ThT fluorescence. However, zinc-free

58V-LECT2 showed significantly more fluorescence than zinc-free WT-LECT2. As the

45

strongest fluorescence was detected from zinc-free 58V-LECT2, this suggests that zinc- free 58V-LECT2 is significantly more amyloidogenic than WT-LECT2 which correspond to the overrepresentation of 58V-LECT2 in ALECT2 patients(Larsen et al., 2014).

46

20 20

WT-LECT2 +Zn 58V-LECT2 +Zn A WT-LECT2 -Zn B 58V-LECT2 -Zn

15 15

10 10

5 5

FluorescenceIntensity (AU) FluorescenceIntensity (AU)

0 0 450 460 470 480 490 500 510 520 530 450 460 470 480 490 500 510 520 530 Wavelength (nm) Wavelength (nm)

Figure 12. ThT fluorescence of aggregated WT and 58V-LECT2. Fluorescence of ThT with aggregated WT-LECT2 (A) and 58V-LECT2 (B) samples with zinc (●) and without zinc (○) is shown different emission wavelengths. LECT2 samples were agitated for 24 hr at 37 °C and 20 µM ThT was incubated with 5.6µM of WT or 58V- LECT2 for 20 mn at room temperature. ThT fluorescence intensity was measured by excitation at 420 nm and emission from 450 to 530 nm in a cuvette.

47

3.5 104

3 104

2.5 104

2 104

1.5 104 ThT fluorescence ThT

1 104

5000

0 WT-LECT2 +Zn WT-LECT2 -Zn 58V-LECT2 +Zn 58V-LECT2 -Zn Figure 13. ThT Fluorescence of different triplicate samples averaged from emission wavelength 475nm and 485nm. Samples were agitated at 990RPM for 24hrs at

37°C and kept unagitated at 25°C for 72hrs. Samples with 5.5uM protein and 20uM ThT were incubated at room temperature for 30mn before fluorescence measurement λex=420nm.

48

CHAPTER 4

DISCUSSION

49

CHAPTER 4

DISCUSSION

In summary, our analysis of trypsin digests of LECT2 shows that it was recombinantly expressed with the correct disulfide bonds in E. coli. The CD spectra of

WT and 58V-LECT2 display the same minimum at 205 nm and the intensity of the minimum changes depending on the state of zinc-binding. These results suggest that WT and 58V-LECT2 have similar secondary structures and that zinc binding causes a minor conformational change to the protein. Tryptophan fluorescence spectroscopy results also suggest no significant difference between the conformation of WT and 58V-LECT2, but they did suggest that zinc binding tightens the overall conformation of LECT2. Results of the urea denaturation experiments show that zinc binding stabilizes LECT2 and the I58V change causes a small reduction in stability that is within error however. Competition binding assays did not find a significant difference between the affinities of WT and 58V-

LECT2 for zinc. Aggregation assays show a significant increase in LECT2’s propensity for aggregation when zinc-free and a shift of the aggregation peak towards physiological pH. No significant difference was found in the pH dependence of aggregation of WT and

58V-LECT2. Our ThT assay with the aggregated samples shows no significant difference between the zinc-bound WT and 58V-LECT2. However, only zinc-free 58V-LECT2 was shown to form amyloid.

ALECT2 amyloidosis is a recently-identified, underdiagnosed, and incurable disease caused by deposition of the LECT2 protein as amyloid. The molecular basis for its pathogenesis has largely remained a matter of speculation. We present the first study of the impact of both the I58V change and the zinc binding on LECT2’s conformational

50

stability, aggregation propensity and amyloidogenicity. Our results strongly suggest that zinc-free LECT2 is a critical misfolding intermediate on the amyloidosis pathway. We also found that the two variants of LECT2 (WT and 58V) are remarkably similar except in their propensity for amyloid formation: zinc-free 58V-LECT2 forms amyloid while WT does not.

Our result showing that zinc-loss increases LECT2 aggregation propensity is consistent with a study that found that both mouse and human LECT2 oligomerizes when zinc-free (Okumura, Suzuki, et al., 2013). We demonstrate that zinc-loss does not only increase the aggregation propensity of LECT2, but also broadens the range of aggregation pH, shifting the peak closer to physiological pH (7.4). Metals play important roles in other protein misfolding diseases including amyotrophic lateral sclerosis (ALS) and AD which are associated with the Cu/Zn Superoxide Dismutase 1 (SOD1) and Aβ respectively. Similar to LECT2, demetallation of SOD1 was shown to promote aggregation due to partial unfolding (Banci et al., 2009; Sheng et al., 2013). In AD, however, Aβ peptides binding to metals (Cu, Zn and Fe) promotes aggregation (Boopathi

& Kolandaivel, 2016; Pithadia & Lim, 2012). Many proteins rely on metal cofactors for correct folding and LECT2, like SOD1, seems to partially unfold when demetallated, increasing its aggregation propensity.

Since we demonstrated that LECT2 tightly binds zinc, physiological demetallation of its native fold seems an unlikely occurrence. However, zinc-free LECT2 may still exist physiologically if nascent LECT2 polypeptides fail to bind zinc. If zinc-free LECT2 is indeed a critical physiologically relevant misfolding intermediate, then it – not native (zinc- bound) LECT2 – is the primary therapeutic target for ALECT2 amyloidosis. Such therapies would specifically target regions in LECT2 that may be unfolded or exposed in

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the zinc-free intermediate but hidden in the native conformation as to prevent oligomerization and fibril formation of misfolded LECT2 without affecting the normal physiological roles of natively folded LECT2 (Rakhit et al., 2007).

A recent study on LECT2 aggregation compared regions of the amyloidogenic core

– regions with high propensity for amyloid formation – of WT and 58V-LECT2 and found that although their resulting fibrils had the same overall morphology, a 58V peptide was slightly less amyloidogenic (Tsiolaki et al., 2019). We found no significant difference in structure and aggregation propensity between the two variants which is consistent with the similarities observed in the Tsiolaki study. We also observed no amyloid formation when LECT2 is zinc-bound. However, in contrast to the Tsiolaki study, our ThT binding experiments found the 58V-LECT2 to be significantly more amyloidogenic when zinc-free.

This discrepancy may be attributed to the use of peptide fragments rather than full-length

LECT2 in the Tsiolaki study where both WT and 58V-LECT2 peptides formed amyloid.

Isolated peptides and the full-length protein clearly have different aggregation properties.

Even peptide fragments representing sections of different length for either of the variants have different aggregation properties. The higher amyloidogenicity of 58V-LECT2 could explain its overrepresentation in ALECT2 patients and demonstrate that the high prevalence is not a mere consequence of the relatively high allele frequency. Since only

26 ALECT2 amyloidosis patients have had their LECT2 gene sequenced (Nasr et al.,

2015a), we cannot yet conclude that all patients express the I58V variant not that that it is necessary for ALECT2 amyloidosis. Tsiolaki et al did observe amyloid formation with peptides from both variant and our assays do suggest that both WT and 58V-LECT2 aggregate under similar conditions although only 58V-LECT2 forms amyloid.

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As lifespan lengthens, amyloid-related diseases are bound to become more prevalent increasing the need for effective therapies (Brookmeyer et al., 2018). To develop new therapies, three key strategies are being investigated: reduction of protein expression, sequestration of amyloid precursors, and clearance of existing amyloid fibrils

(Koike & Katsuno, 2019). The first two methods work by reducing or preventing oligomerization and therefore fibril formation while the third aims to reduce the load of existing amyloid deposition (Kristen et al., 2019). To reduce the expression of an amyloidogenic protein specifically, small interfering RNAs (siRNA) can target and hybridize with the protein’s mRNA leading to its degradation. Such methods would reduce the global expression of the target protein – including its native fold – which may have significant side effects depending on the protein’s role. Small molecules such as

Tafamidis, a pharmacological chaperone, can bind and stabilize proteins like homotetrameric TTR to inhibit its dissociation into monomers that may otherwise misfold and aggregate (Coelho et al., 2012). Peptides and antibodies that targets specific regions of pre-fibril intermediate states and the existing amyloid fibrils themselves can both stabilize amyloid precursors and bind existing amyloid to induce their clearance (Galant et al., 2016).

Zinc-free LECT2 appears to be an aggregation-prone misfolding intermediate and a tractable therapeutic target. The conformation–specific approach described above was used to develop antibodies targeting misfolded SOD1 and other potential therapies for

ATTR and AL amyloidosis (Galant et al., 2016; Rakhit et al., 2007). Galant and her colleagues developed antibodies that specifically target the misfolded monomeric form of

TTR which prevented fibrillogenesis with sub-stoichiometric concentrations (1:127,

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antibody to TTR) likely by binding amyloid nuclei to lengthen the lag phase and/or by capping ends of prefibrillar species (Galant et al., 2016). Sub-stoichiometric, in contrast to stoichiometric inhibition of aggregation reduces the minimum effective concentration of therapies and therefore the likelihood of adverse (off-target) effects. Meanwhile, all attempts at targeting amyloid formation in the CNS, including potential vaccines, small molecules, and monoclonal antibodies have failed (Habchi et al., 2017; Herline et al.,

2018). Vaccines for AD were initially promising; they were expected to work by inducing lasting antibody production against Aβ species to promote the clearance of these species from the CNS. However, when tested, they caused side effects that were sufficiently severe to halt clinical trials. Humanized monoclonal antibodies were expected to eliminate some of the drawbacks of vaccines while still inducing Aβ clearance, but they too are associated with side effects, although less serious (Herline et al., 2018).

Therapies targeting amyloid must have high affinity and specificity for misfolded monomers, oligomers and/or fibrils and promote clearance of the targeted toxic species.

In addition to these requirements, therapies targeting toxic species in the CNS must have good penetration through the blood-brain-barrier (BBB) further narrowing the pool of potential agents for CNS amyloid diseases (Lipsman et al., 2018; Mehta et al., 2017).

This partially explains the higher success rate of therapies intended for non-CNS amyloidoses where bypassing the blood-brain-barrier is not an issue. Thus, there is more hope for potential therapies that target zinc-free LECT2 to treat ALECT2 amyloidosis.

Therapeutic strategies such as siRNAs to reduce LECT2 expression or pharmaceutical chaperones to stabilize misfolded LECT2 are also theoretically viable. A reduction in

LECT2 expression (by siRNAs) would not only prevent LECT2 amyloid formation but

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likely act as a prophylactic treatment for other conditions associated with increased serum

LECT2 (Lan et al., 2014). If low serum LECT2 is of concern, pharmacological chaperones aiming to stabilize misfolded LECT2 would prevent amyloid formation without reducing its overall serum concentration (Convertino et al., 2016; Okumura et al., 2016).

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CHAPTER 5

FUTURE DIRECTIONS

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CHAPTER 5

FUTURE DIRECTIONS

Currently, we have found that 58V-LECT2 forms amyloid when zinc-free while WT-

LECT2 does not. This matches the prevalence of the 58V-LECT2 in the ALECT2 amyloidosis patients who have been sequenced. However, all results from our recent investigation suggest no significant difference in secondary structure, conformational stability, aggregation propensity, zinc-binding affinity and rate of aggregation. The similarity of these results leaves no explanation for the stark difference observed in amyloid formation when LECT2 is zinc-free. This may be due to the ThT assay being the only experiment thus far with the ability to detect significant differences between the variants. In this case, more sensitive methods are needed to unravel the source(s) of the observed difference. Such methods may include NMR to investigate the structural dynamics of WT and 58V-LECT2. Microscopy studies would also be useful. For example, transmission electron microscopy of LECT2 aggregates would be instrumental in defining the morphology of LECT2 aggregates, fibrils and pre-fibril species.

From the results of the ThT assay, we have concluded that only 58V-LECT2 forms amyloid when zinc-free, however similar results would be observed if WT-LECT2 formed amyloid at a slower rate. In this case, monitoring of both zinc-free WT and 58V-LECT2 on a longer timescale (maybe weeks) might determine whether WT-LECT2 is truly non- amyloidogenic (Eakin et al., 2004). The formation of WT-LECT2 amyloid at a slower rate than 58V-LECT2 would still correspond to the higher prevalence of 58V-LECT2 in

ALECT2 patients who have been sequenced.

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Zinc-free LECT2 is an aggregation-prone, misfolded intermediate that is the precursor to amyloid formation. Since targeting the misfolded intermediate has been a successful approach for inhibiting the formation of other amyloids, antibodies should be developed to target zinc-free LECT2. One of the steps in developing these conformation specific antibodies is the selection of cryptotopes which are regions exposed in the misfolded but buried in the native state of LECT2. These cryptotopes would then be synthesized as peptides and used as antigen for development of polyclonal antibodies specifically targeting misfolded LECT2.

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REFERENCES Ando, K., Kato, H., Kotani, T., Ozaki, M., Arimura, Y., & Yagi, J. (2012). Plasma leukocyte cell-derived chemotaxin 2 is associated with the severity of systemic inflammation in patients with sepsis. Microbiology and Immunology, 56(10), 708–718. https://doi.org/10.1111/j.1348-0421.2012.00488.x Anfinsen, C. B. (1973). Principles that govern the folding of protein chains. In Science (Vol. 181, Issue 4096, pp. 223–230). American Association for the Advancement of Science. https://doi.org/10.1126/science.181.4096.223 Banci, L., Bertini, I., Boca, M., Calderone, V., Cantini, F., Girotto, S., & Vieru, M. (2009). Structural and dynamic aspects related to oligomerization of apo SOD1 and its mutants. Proceedings of the National Academy of Sciences of the United States of America, 106(17), 6980–6985. https://doi.org/10.1073/pnas.0809845106 Benilova, I., Karran, E., & De Strooper, B. (2012). The toxic Aβ oligomer and Alzheimer’s disease: An emperor in need of clothes. In Nature Neuroscience (Vol. 15, Issue 3, pp. 349–357). Nature Publishing Group. https://doi.org/10.1038/nn.3028 Benson, M. D., James, S., Scott, K., Liepnieks, J. J., & Kluve-Beckerman, B. (2008). Leukocyte chemotactic factor 2: A novel renal amyloid protein. Kidney International, 74(2), 218–222. https://doi.org/10.1038/ki.2008.152 Bolen, D. W., & Santoro, M. M. (1988). Unfolding Free Energy Changes Determined By The Linear Extrapolation Method. 2. Incorporation of Ag°n_u Values In A Thermodynamic Cycle. Biochemistry, 27(21), 8069–8074. https://doi.org/10.1021/bi00421a015 Boopathi, S., & Kolandaivel, P. (2016). Fe2+ binding on amyloid β-peptide promotes aggregation. Proteins: Structure, Function and Bioinformatics, 84(9), 1257–1274. https://doi.org/10.1002/prot.25075 Brookmeyer, R., Abdalla, N., Kawas, C. H., & Corrada, M. M. (2018). Forecasting the prevalence of preclinical and clinical Alzheimer’s disease in the United States. Alzheimer’s and Dementia, 14(2), 121–129. https://doi.org/10.1016/j.jalz.2017.10.009 Chen, C. K., Yang, C. Y., Hua, K. T., Ho, M. C., Johansson, G., Jeng, Y. M., Chen, C. N., Chen, M. W., Lee, W. J., Su, J. L., Lai, T. C., Chou, C. C., Ho, B. C., Chang, C. F., Lee, P. H., Chang, K. J., Hsiao, M., Lin, M. T., & Kuo, M. L. (2014). Leukocyte cell- derived chemotaxin 2 antagonizes MET receptor activation to suppress hepatocellular carcinoma vascular invasion by protein tyrosine phosphatase 1B recruitment. Hepatology, 59(3), 974–985. https://doi.org/10.1002/hep.26738 Chiti, F., & Dobson, C. M. (2017). Protein Misfolding, Amyloid Formation, and Human Disease: A Summary of Progress Over the Last Decade. Annual Review of Biochemistry, 86(1), 27–68. https://doi.org/10.1146/annurev-biochem-061516- 045115 Coelho, T., Maia, L. F., Da Silva, A. M., Cruz, M. W., Planté-Bordeneuve, V., Lozeron, P.,

59

Suhr, O. B., Campistol, J. M., Conceição, I. M., Schmidt, H. H. J., Trigo, P., Kelly, J. W., Labaudinière, R., Chan, J., Packman, J., Wilson, A., & Grogan, D. R. (2012). Tafamidis for transthyretin familial amyloid polyneuropathy: A randomized, controlled trial. Neurology, 79(8), 785–792. https://doi.org/10.1212/WNL.0b013e3182661eb1 Convertino, M., Das, J., & Dokholyan, N. V. (2016). Pharmacological Chaperones: Design and Development of New Therapeutic Strategies for the Treatment of Conformational Diseases. https://doi.org/10.1021/acschembio.6b00195 Dogan, A. (2017). Amyloidosis: Insights from Proteomics. Annual Review of Pathology: Mechanisms of Disease, 12(1), 277–304. https://doi.org/10.1146/annurev-pathol- 052016-100200 Eakin, C. M., Attenello, F. J., Morgan, C. J., & Miranker, A. D. (2004). Oligomeric assembly of native-like precursors precedes amyloid formation by β-2 microglobulin. Biochemistry, 43(24), 7808–7815. https://doi.org/10.1021/bi049792q Edgcomb, S. P., & Murphy, K. P. (2002). Variability in the pKa of histidine side-chains correlates with burial within proteins. Proteins: Structure, Function and Genetics, 49(1), 1–6. https://doi.org/10.1002/prot.10177 Galant, N. J., Bugyei-Twum, A., Rakhit, R., Walsh, P., Sharpe, S., Arslan, P. E., Higaki, J. N., Torres, R., Tapia, J., & Chakrabartty, A. (2016). Substoichiometric inhibition of transthyretin misfolding by immune-targeting sparsely populated misfolding intermediates: a potential diagnostic and therapeutic for TTR amyloidoses OPEN. Nature Publishing Group. https://doi.org/10.1038/srep25080 Galant, N. J., Westermark, P., Higaki, J. N., & Chakrabartty, A. (2017). Transthyretin amyloidosis: An under-recognized neuropathy and cardiomyopathy. In Clinical Science (Vol. 131, Issue 5, pp. 395–409). Portland Press Ltd. https://doi.org/10.1042/CS20160413 Gharibyan, A. L., Zamotin, V., Yanamandra, K., Moskaleva, O. S., Margulis, B. A., Kostanyan, I. A., & Morozova-Roche, L. A. (2007). Lysozyme Amyloid Oligomers and Fibrils Induce Cellular Death via Different Apoptotic/Necrotic Pathways. Journal of Molecular Biology, 365(5), 1337–1349. https://doi.org/10.1016/j.jmb.2006.10.101 Ghisaidoobe, A. B. T., & Chung, S. J. (2014). Intrinsic tryptophan fluorescence in the detection and analysis of proteins: A focus on förster resonance energy transfer techniques. In International Journal of Molecular Sciences (Vol. 15, Issue 12, pp. 22518–22538). MDPI AG. https://doi.org/10.3390/ijms151222518 Ghosh, D., Sahay, S., Ranjan, P., Salot, S., Mohite, G. M., Singh, P. K., Dwivedi, S., Carvalho, E., Banerjee, R., Kumar, A., & Maji, S. K. (2014). The newly discovered Parkinsons disease associated finnish mutation (A53E) attenuates α-synuclein aggregation and membrane binding. Biochemistry, 53(41), 6419–6421. https://doi.org/10.1021/bi5010365 Grimsley, G. R., Huyghues-Despointes, B. M. P., Pace, C. N., & Scholtz, J. M. (2006a). Determining a Urea or Guanidinium Chloride Unfolding Curve. Cold Spring Harbor Protocols, 2006(1), pdb.prot4242. https://doi.org/10.1101/pdb.prot4242

60

Grimsley, G. R., Huyghues-Despointes, B. M. P., Pace, C. N., & Scholtz, J. M. (2006b). Preparation of Urea and Guanidinium Chloride Stock Solutions for Measuring Denaturant-Induced Unfolding Curves. Cold Spring Harbor Protocols, 2006(1), pdb.prot4241. https://doi.org/10.1101/pdb.prot4241 Habchi, J., Chia, S., Limbocker, R., Mannini, B., Ahn, M., Perni, M., Hansson, O., Arosio, P., Kumita, J. R., Challa, P. K., Cohen, S. I. A., Linse, S., Dobson, C. M., Knowles, T. P. J., & Vendruscolo, M. (2017). Systematic development of small molecules to inhibit specific microscopic steps of Aβ42 aggregation in Alzheimer’s disease. Proceedings of the National Academy of Sciences of the United States of America, 114(2), E200–E208. https://doi.org/10.1073/pnas.1615613114 Hardesty, B., Kramer, G., Tsalkova, T., Ramachandiran, V., McIntosh, B., & Brod, D. (2014). Folding of Nascent Peptides on Ribosomes. In The Ribosome (pp. 287–298). American Society of Microbiology. https://doi.org/10.1128/9781555818142.ch24 Harikrishnan, R., Kim, J. S., Kim, M. C., Balasundaram, C., & Heo, M. S. (2012). Expressed sequence tags (ESTs) based identification of genes and expression analysis of leukocyte cell-derived chemotaxin-2 (LECT2) from Epinephelus bruneus. Gene, 491(1), 88–101. https://doi.org/10.1016/j.gene.2011.08.029 Hartl, F. U. (2017). Protein Misfolding Diseases. https://doi.org/10.1146/annurev-biochem Hartl, F. U., Bracher, A., & Hayer-Hartl, M. (2011). Molecular chaperones in protein folding and proteostasis. In Nature (Vol. 475, Issue 7356, pp. 324–332). Nature Publishing Group. https://doi.org/10.1038/nature10317 Herline, K., Drummond, E., & Wisniewski, T. (2018). Recent advancements toward therapeutic vaccines against Alzheimer’s disease. Expert Review of Vaccines, 17(8), 707–721. https://doi.org/10.1080/14760584.2018.1500905 Hoop, C. L., Lin, H. K., Kar, K., Magyarfalvi, G., Lamley, J. M., Boatz, J. C., Mandal, A., Lewandowski, J. R., Wetzel, R., & Van Der Wel, P. C. A. (2016). Huntingtin exon 1 fibrils feature an interdigitated β-hairpin-based polyglutamine core. Proceedings of the National Academy of Sciences of the United States of America, 113(6), 1546– 1551. https://doi.org/10.1073/pnas.1521933113 Hutton, H. L., Demarco, M. L., Magil, A. B., & Taylor, P. (2014). Renal leukocyte chemotactic factor 2 (LECT2) amyloidosis in first nations people in northern british columbia, Canada: A report of 4 cases. American Journal of Kidney Diseases, 64(5), 790–792. https://doi.org/10.1053/j.ajkd.2014.06.017 Ihne, S., Morbach, C., Sommer, C., Geier, A., Knop, S., & Störk, S. (2020). Amyloidosis- the Diagnosis and Treatment of an Underdiagnosed Disease. Deutsches Arzteblatt International, 117(10), 159–166. https://doi.org/10.3238/arztebl.2020.0159 Ito, M., Nagata, K., Kato, Y., Oda, Y., Yamagoe, S., Suzuki, K., & Tanokura, M. (2003). Expression, oxidative refolding, and characterization of six-histidine-tagged recombinant human LECT2, a 16-kDa chemotactic protein with three disulfide bonds. Protein Expression and Purification, 27(2), 272–278. https://doi.org/10.1016/S1046- 5928(02)00634-4

61

Ito, M., Yamagoe, S., Tomizawa, K., Mizuno, S., Tanokura, M., & Suzuki, K. (1997). Preparation of recombinant six-histidine-tagged human LECT2, a chemotactic protein to neutrophils, in Escherichia coli. Cytotechnology, 25(1–3), 235–238. https://doi.org/10.1023/A:1007976103088 Ivankov, D. N., Bogatyreva, N. S., Lobanov, M. Y., & Galzitskaya, O. V. (2009). Coupling between Properties of the Protein Shape and the Rate of Protein Folding. https://doi.org/10.1371/journal.pone.0006476 Kameoka, Y., Yamagoe, S., Hatano, Y., Kasama, T., & Suzuki, K. (2000). Val58ILe polymorphism of the neutrophil chemoattractant LECT2 and rheumatoid arthritis in the Japanese population. Arthritis & Rheumatism, 43(6), 1419–1420. https://doi.org/10.1002/1529-0131(200006)43:6<1419::AID-ANR28>3.0.CO;2-I Kastritis, E., & Dimopoulos, M. A. (2016). Recent advances in the management of AL Amyloidosis. British Journal of Haematology, 172(2), 170–186. https://doi.org/10.1111/bjh.13805 Kim, Y. E., Hipp, M. S., Bracher, A., Hayer-Hartl, M., & Ulrich Hartl, F. (2013). Molecular Chaperone Functions in Protein Folding and Proteostasis. Annual Review of Biochemistry, 82(1), 323–355. https://doi.org/10.1146/annurev-biochem-060208- 092442 Koike, H., & Katsuno, M. (2019). Ultrastructure in transthyretin amyloidosis: From pathophysiology to therapeutic insights. In Biomedicines (Vol. 7, Issue 1). MDPI AG. https://doi.org/10.3390/biomedicines7010011 Kopprasch, S., Schroeder, H.-E., Graessler, J., Verlohren, M., Graessler, A., Zeissig, A., & Kuhlisch, E. (2005). Association of chondromodulin-II Val58Ile polymorphism with radiographic joint. In The Journal of Rheumatology Rheumatology The Journal of on June (Vol. 32, Issue 9). http://www.jrheum.org/content/32/9/1654http://www.jrheum.org/alerts1.SignupforTO Csandotheralertshttp://jrheum.com/faqwww.jrheum.orgwww.jrheum.orgDownloade dfrom Koshimizu, Y., & Ohtomi, M. (2010). Regulation of neurite extension by expression of LECT2 and neurotrophins based on findings in LECT2-knockout mice. Brain Research, 1311, 1–11. https://doi.org/10.1016/j.brainres.2009.11.010 Kristen, A. V, Ajroud-Driss, S., Conceição, I., Gorevic, P., Kyriakides, T., & Obici, L. (2019). Patisiran, an RNAi therapeutic for the treatment of hereditary transthyretin- mediated amyloidosis. Neurodegenerative Disease Management, 9(1), 5–23. https://doi.org/10.2217/nmt-2018-0033 Kuzmič, P. (1996). Program DYNAFIT for the analysis of enzyme kinetic data: Application to HIV proteinase. Analytical Biochemistry, 237(2), 260–273. https://doi.org/10.1006/abio.1996.0238 Labbadia, J., & Morimoto, R. I. (2015). The Biology of Proteostasis in Aging and Disease. https://doi.org/10.1146/annurev-biochem-060614-033955

62

Lan, F., Misu, H., Chikamoto, K., Takayama, H., Kikuchi, A., Mohri, K., Takata, N., Hayashi, H., Matsuzawa-Nagata, N., Takeshita, Y., Noda, H., Matsumoto, Y., Ota, T., Nagano, T., Nakagen, M., Miyamoto, K. I., Takatsuki, K., Seo, T., Iwayama, K., … Takamura, T. (2014). LECT2 functions as a hepatokine that links obesity to skeletal muscle insulin resistance. Diabetes, 63(5), 1649–1664. https://doi.org/10.2337/db13-0728 Larsen, C. P., Ismail, W., Kurtin, P. J., Vrana, J. A., Dasari, S., & Nasr, S. H. (2016). Leukocyte chemotactic factor 2 amyloidosis (ALECT2) is a common form of renal amyloidosis among Egyptians. Modern Pathology, 29(4), 416–420. https://doi.org/10.1038/modpathol.2016.29 Larsen, C. P., Kossmann, R. J., Beggs, M. L., Solomon, A., & Walker, P. D. (2014). Clinical, morphologic, and genetic features of renal leukocyte chemotactic factor 2 amyloidosis. Kidney International, 86(2), 378–382. https://doi.org/10.1038/ki.2014.11 Larsen, C. P., Walker, P. D., Weiss, D. T., & Solomon, A. (2010). Prevalence and morphology of leukocyte chemotactic factor 2-associated amyloid in renal biopsies. Kidney International, 77(9), 816–819. https://doi.org/10.1038/ki.2010.9 Lavatelli, F., Palladini, G., & Merlini, G. (2010). Pathogenesis of Systemic Amyloidoses. In Amyloidosis (pp. 49–64). Humana Press. https://doi.org/10.1007/978-1-60761- 631-3_4 Lee, C. C., Sun, Y., & Huang, H. W. (2012). How type II diabetes-related islet amyloid polypeptide damages lipid bilayers. Biophysical Journal, 102(5), 1059–1068. https://doi.org/10.1016/j.bpj.2012.01.039 Lee, S., & Tsai, F. T. F. (2005). Molecular Chaperones in Protein Quality Control. In Journal of Biochemistry and Molecular Biology (Vol. 38, Issue 3). Leung, N., Slezak, J. M., Bergstralh, E. J., Dispenzieri, A., Lacy, M. Q., Wolf, R. C., & Gertz, M. A. (2005). Acute renal insufficiency after high-dose melphalan in patients with primary systemic amyloidosis during stem cell transplantation. American Journal of Kidney Diseases. https://doi.org/10.1053/j.ajkd.2004.09.015 Lipsman, N., Meng, Y., Bethune, A. J., Huang, Y., Lam, B., Masellis, M., Herrmann, N., Heyn, C., Aubert, I., Boutet, A., Smith, G. S., Hynynen, K., & Black, S. E. (2018). Blood–brain barrier opening in Alzheimer’s disease using MR-guided focused ultrasound. Nature Communications, 9(1), 1–8. https://doi.org/10.1038/s41467-018- 04529-6 Longhi, S., Quarta, C. C., Milandri, A., Lorenzini, M., Gagliardi, C., Manuzzi, L., Bacchi- Reggiani, M. L., Leone, O., Ferlini, A., Russo, A., Gallelli, I., & Rapezzi, C. (2015). Atrial fibrillation in amyloidotic cardiomyopathy: prevalence, incidence, risk factors and prognostic role. Amyloid, 22(3), 147–155. https://doi.org/10.3109/13506129.2015.1028616 Lu, X. J., Chen, J., Yu, C. H., Shi, Y. H., He, Y. Q., Zhang, R. C., Huang, Z. A., Lv, J. N., Zhang, S., & Xu, L. (2013). LECT2 protects mice against bacterial sepsis by

63

activating macrophages via the CD209a receptor. Journal of Experimental Medicine, 210(1), 5–13. https://doi.org/10.1084/jem.20121466 Mehta, D., Jackson, R., Paul, G., Shi, J., & Sabbagh, M. (2017). Why do trials for Alzheimer’s disease drugs keep failing? A discontinued drug perspective for 2010- 2015. Expert Opinion on Investigational Drugs, 26(6), 735–739. https://doi.org/10.1080/13543784.2017.1323868 Misu, H. (2018). Pathophysiological significance of hepatokine overproduction in type 2 diabetes. In Diabetology International (Vol. 9, Issue 4, pp. 224–233). Springer Tokyo. https://doi.org/10.1007/s13340-018-0368-9 Murphy, C. L., Wang, S., Kestler, D., Larsen, C., Benson, D., Weiss, D. T., & Solomon, A. (2010). Leukocyte chemotactic factor 2 (LECT2)-associated renal amyloidosis: A case series. American Journal of Kidney Diseases, 56(6), 1100–1107. https://doi.org/10.1053/j.ajkd.2010.08.013 Naganathan, A. N., & Muñ Oz, V. (2005). Scaling of Folding Times with Protein Size. J. AM. CHEM. SOC, 127, 480–481. https://doi.org/10.1021/ja044449u Nasr, S. H., Dogan, A., & Larsen, C. P. (2015a). Leukocyte cell-derived chemotaxin 2- associated amyloidosis: A recently recognized disease with distinct clinicopathologic characteristics. Clinical Journal of the American Society of Nephrology, 10(11), 2084–2093. https://doi.org/10.2215/CJN.12551214 Nasr, S. H., Dogan, A., & Larsen, C. P. (2015b). Leukocyte cell-derived chemotaxin 2- associated amyloidosis: A recently recognized disease with distinct clinicopathologic characteristics. In Clinical Journal of the American Society of Nephrology (Vol. 10, Issue 11, pp. 2084–2093). American Society of Nephrology. https://doi.org/10.2215/CJN.12551214 Nilsberth, C., Westlind-Danielsson, A., Eckman, C. B., Condron, M. M., Axelman, K., Forsell, C., Stenh, C., Luthman, J., Teplow, D. B., Younkin, S. G., Näslund, J., & Lannfelt, L. (2001). The “Arctic” APP mutation (E693G) causes Alzheimer’s disease by enhanced Aβ protofibril formation. Nature Neuroscience, 4(9), 887–893. https://doi.org/10.1038/nn0901-887 Okabe, H., Delgado, E., Lee, J. M., Yang, J., Kinoshita, H., Hayashi, H., Tsung, A., Behari, J., Beppu, T., Baba, H., & Monga, S. P. (2014). Role of leukocyte cell-derived chemotaxin 2 as a biomarker in hepatocellular carcinoma. PLoS ONE, 9(6). https://doi.org/10.1371/journal.pone.0098817 Okumura, A., Suzuki, T., Dohmae, N., Okabe, T., Hashimoto, Y., Nakazato, K., Ohno, H., Miyazaki, Y., & Yamagoe, S. (2009). Identification and assignment of three disulfide bonds in mammalian leukocyte cell-derived chemotaxin 2 by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Bioscience Trends, 3(4), 139–143. http://www.ncbi.nlm.nih.gov/pubmed/20103838 Okumura, A., Suzuki, T., Miyatake, H., Okabe, T., Hashimoto, Y., Miyakawa, T., Zheng, H., Unoki-Kubota, H., Ohno, H., Dohmae, N., Kaburagi, Y., Miyazaki, Y., Tanokura, M., & Yamagoe, S. (2013). Leukocyte cell-derived chemotaxin 2 is a zinc-binding

64

protein. FEBS Letters, 587(5), 404–409. https://doi.org/10.1016/j.febslet.2013.01.025 Okumura, A., Unoki-Kubota, H., Matsushita, Y., Shiga, T., Moriyoshi, Y., Yamagoe, S., & Kaburagi, Y. (2013). Increased serum leukocyte cell-derived chemotaxin 2 (LECT2) levels in obesity and fatty liver. Bioscience Trends, 7(6), 276–283. http://www.ncbi.nlm.nih.gov/pubmed/24390366 Okumura, A., Unoki-Kubota, H., Yoshida-Hata, N., Yamamoto-Honda, R., Yamashita, S., Iwata, M., Tobe, K., Kajio, H., Noda, M., Katai, N., Yamagoe, S., & Kaburagi, Y. (2016). Reduced serum level of leukocyte cell-derived chemotaxin 2 is associated with the presence of diabetic retinopathy. Clinica Chimica Acta, 463, 145–149. https://doi.org/10.1016/j.cca.2016.10.031 Ong, H. T., Tan, P. K., Wang, S. M., Hian Low, D. T., Pj Ooi, L. L., & Hui, K. M. (2011). The tumor suppressor function of LECT2 in human hepatocellular carcinoma makes it a potential therapeutic target. Cancer Gene Therapy, 18(6), 399–406. https://doi.org/10.1038/cgt.2011.5 Ovejero, C., Cavard, C., Périanin, A., Hakvoort, T., Vermeulen, J., Godard, C., Fabre, M., Chafey, P., Suzuki, K., Romagnolo, B., Yamagoe, S., & Perret, C. (2004). Identification of the leukocyte cell-derived chemotaxin 2 as a direct target gene of β- catenin in the liver. Hepatology, 40(1), 167–176. https://doi.org/10.1002/hep.20286 Pace, C. N., Shirley, B. A., McNutt, M., & Gajiwala, K. (1996). Forces contributing to the conformational stability of proteins. The FASEB Journal, 10(1), 75–83. https://doi.org/10.1096/fasebj.10.1.8566551 Palmer, I., & Wingfield, P. T. (2012). Preparation and Extraction of Insoluble (Inclusion- Body) Curr Protoc Protein Sci Author Manuscript . Author manuscript; available in PMC 2012 December 10. . 2004 November ; CHAPTER: Unit–6.3. doi:10.1002/0471140864.ps0603s38. Proteins from Escherichia col. Bmj, 323(8 M), 1–25. https://doi.org/10.1002/0471140864.ps0603s38.Preparation Pardridge, W. M. (2016). CSF, blood-brain barrier, and brain drug delivery. Expert Opinion on Drug Delivery, 13(7), 963–975. https://doi.org/10.1517/17425247.2016.1171315 Paueksakon, P., Fogo, A. B., & Sethi, S. (2014). Leukocyte chemotactic factor 2 amyloidosis cannot be reliably diagnosed by immunohistochemical staining. Human Pathology, 45(7), 1445–1450. https://doi.org/10.1016/j.humpath.2014.02.020 Pelham, H. R. B. (1986). Speculations on the functions of the major heat shock and glucose-regulated proteins. In Cell (Vol. 46, Issue 7, pp. 959–961). Cell Press. https://doi.org/10.1016/0092-8674(86)90693-8 Pithadia, A. S., & Lim, M. H. (2012). Metal-associated amyloid-β species in Alzheimer’s disease. In Current Opinion in Chemical Biology (Vol. 16, Issues 1–2, pp. 67–73). Elsevier Current Trends. https://doi.org/10.1016/j.cbpa.2012.01.016 Rakhit, R., Cunningham, P., Furtos-Matei, A., Dahan, S., Qi, X.-F., Crow, J. P., Cashman,

65

N. R., Kondejewski, L. H., & Chakrabartty, A. (2002). Oxidation-induced Misfolding and Aggregation of Superoxide Dismutase and Its Implications for Amyotrophic Lateral Sclerosis*. https://doi.org/10.1074/jbc.M207356200 Rakhit, R., Robertson, J., Velde, C. Vande, Horne, P., Ruth, D. M., Griffin, J., Cleveland, D. W., Cashman, N. R., & Chakrabartty, A. (2007). An immunological epitope selective for pathological monomer-misfolded SOD1 in ALS. Nature Medicine, 13(6), 754–759. https://doi.org/10.1038/nm1559 Roberts, H. L., & Brown, D. R. (2015). Seeking a mechanism for the toxicity of oligomeric α-synuclein. In Biomolecules (Vol. 5, Issue 2, pp. 282–305). MDPI AG. https://doi.org/10.3390/biom5020282 Said, S. M., Sethi, S., Valeri, A. M., Leung, N., Cornell, L. D., Fidler, M. E., Herrera Hernandez, L., Vrana, J. A., Theis, J. D., Quint, P. S., Dogan, A., & Nasr, S. H. (2013). Article Renal Amyloidosis: Origin and Clinicopathologic Correlations of 474 Recent Cases. https://doi.org/10.2215/CJN.10491012 Santoro, M. M., & Bolen, D. W. (1988). Unfolding Free Energy Changes Determined by the Linear Extrapolation Method. 1. Unfolding of Phenylmethanesulfonyl a- Chymotrypsin Using Different Denaturants. Biochemistry, 27(21), 8063–8068. https://doi.org/10.1021/bi00421a014 Sato, Y., Watanabe, H., Kameyama, H., Kobayashi, T., Yamamoto, S., Takeishi, T., Hirano, K., Oya, H., Nakatsuka, H., Watanabe, T., Kokai, H., Yamagoe, S., Suzuki, K., Oya, K., Kojima, K., & Hatakeyama, K. (2004). Serum LECT2 level as a prognostic indicator in acute liver failure. Transplantation Proceedings, 36(8), 2359– 2361. https://doi.org/10.1016/j.transproceed.2004.07.007 Sethi, S., & Theis, J. D. (2018). Pathology and diagnosis of renal non-AL amyloidosis. In Journal of Nephrology (Vol. 31, Issue 3, pp. 343–350). Springer International Publishing. https://doi.org/10.1007/s40620-017-0426-6 Sheng, Y., Chattopadhyay, M., Whitelegge, J., & Selverstone Valentine, J. (2013). SOD1 Aggregation and ALS: Role of Metallation States and Disulfide Status. Current Topics in Medicinal Chemistry, 12(22), 2560–2572. https://doi.org/10.2174/1568026611212220010 Slowik, V., & Apte, U. (2017). Leukocyte Cell-Derived Chemotaxin-2: It’s Role in Pathophysiology and Future in Clinical Medicine. In Clinical and Translational Science (Vol. 10, Issue 4, pp. 249–259). Blackwell Publishing Ltd. https://doi.org/10.1111/cts.12469 Southall, N. T., Dill, K. A., & Haymet, A. D. J. (2002). A view of the hydrophobic effect. In Journal of Physical Chemistry B (Vol. 106, Issue 3, pp. 521–533). American Chemical Society . https://doi.org/10.1021/jp015514e Sydor, A. M., Lebrette, H., Ariyakumaran, R., Cavazza, C., & Zamble, D. B. (2013). Relationship between Ni(II) and Zn(II) Coordination and Nucleotide Binding by the Helicobacter pylori [NiFe]-Hydrogenase and Urease Maturation Factor HypB * □ S. https://doi.org/10.1074/jbc.M113.502781

66

Tanskanen, M., Peuralinna, T., Polvikoski, T., Notkola, I., Sulkava, R., Hardy, J., Singleton, A., Kiuru‐Enari, S., Paetau, A., Tienari, P. J., & Myllykangas, L. (2008). Senile systemic amyloidosis affects 25% of the very aged and associates with genetic variation in alpha2‐macroglobulin and tau : A population‐based autopsy study. Annals of Medicine, 40(3), 232–239. https://doi.org/10.1080/07853890701842988 Thomas, J. G., Ayling, A., & Baneyx, F. (1997). Molecular Chaperones, Folding Catalysts, and the Recovery of Active Recombinant Proteins from E. coli To Fold or to Refold Thomas, Ayling, and Baneyx (Vol. 66). Thurlkill, R. L., Grimsley, G. R., Scholtz, J. M., & Pace, C. N. (2006). pK values of the ionizable groups of proteins. Protein Science, 15(5), 1214–1218. https://doi.org/10.1110/ps.051840806 Tsiolaki, P. L., Nasi, G. I., Baltoumas, F. A., Fishman, S., Tu, H.-C., & Iconomidou, V. A. (2019). Delving into the amyloidogenic core of human leukocyte chemotactic factor 2. Journal of Structural Biology, 207(3), 260–269. https://doi.org/10.1016/j.jsb.2019.06.001 Vivian, J. T., & Callis, P. R. (2001). Mechanisms of tryptophan fluorescence shifts in proteins. Biophysical Journal, 80(5), 2093–2109. https://doi.org/10.1016/S0006- 3495(01)76183-8 Voet, D., Voet, J. G., & Pratt, C. W. (2016). Fundamentals of biochemistry : Life at the Molecular Level (5th ed.). Walker, J. M. (1994). The bicinchoninic acid (BCA) assay for protein quantitation. In Methods in molecular biology (Clifton, N.J.) (Vol. 32, pp. 5–8). https://doi.org/10.1385/1-59259-169-8:11 Xue, C., Lin, T. Y., Chang, D., & Guo, Z. (2017). Thioflavin T as an amyloid dye: Fibril quantification, optimal concentration and effect on aggregation. Royal Society Open Science, 4(1). https://doi.org/10.1098/rsos.160696 Yamagoe, S., Akasaka, T., Uchida, T., Hachiya, T., Okabe, T., Yamakawa, Y., Arai, T., Mizuno, S., & Suzuki, K. (1997). Expression of a neutrophil chemotactic protein LECT2 in human hepatocytes revealed by immunochemical studies using polyclonal and monoclonal antibodies to a recombinant LECT2. Biochemical and Biophysical Research Communications, 237(1), 116–120. https://doi.org/10.1006/bbrc.1997.7095 Yamagoe, S., Kameoka, Y., Hashimoto, K., Mizuno, S., & Suzuki, K. (1998). Molecular cloning, structural characterization, and chromosomal mapping of the human LECT2 gene. Genomics, 48(3), 324–329. https://doi.org/10.1006/geno.1997.5198 Yamagoe, S., Yamakawa, Y., Matsuo, Y., Minowada, J., Mizuno, S., & Suzuki, K. (1996). Purification and primary amino acid sequence of a novel neutrophil chemotactic factor LECT2. Immunology Letters, 52(1), 9–13. https://doi.org/10.1016/0165- 2478(96)02572-2

67

Zhang, Z., Zeng, H., Lin, J., Hu, Y., Yang, R., Sun, J., Chen, R., & Chen, H. (2018). Circulating LECT2 levels in newly diagnosed type 2 diabetes mellitus and their association with metabolic parameters. Medicine (United States), 97(15), e0354. https://doi.org/10.1097/MD.0000000000010354 Zheng, H., Miyakawa, T., Sawano, Y., Asano, A., Okumura, A., Yamagoe, S., & Tanokura, M. (2016). Crystal structure of human leukocyte cell-derived chemotaxin 2 (LECT2) reveals a mechanistic basis of functional evolution in a mammalian protein with an M23 metalloendopeptidase fold. Journal of Biological Chemistry, 291(33), 17133–17142. https://doi.org/10.1074/jbc.M116.720375

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