Affibody molecules for proteomic and therapeutic applications › smash › get › diva2:13368 › FULLTEXT01.pdf · gave enhanced identification of proteins in a shotgun proteomics

Affibody molecules for proteomic and therapeutic applications

CAROLINE GRÖNWALL

Royal Institute of Technology School of Biotechnology

Stockholm 2008

© Caroline Grönwall Stockholm 2008 Royal Institute of Technology School of Biotechnology AlbaNova University Center SE-106 91 Stockholm Sweden Printed by Universitetsservice US-AB Drottning Kristinas väg 53B SE-100 44 Stockholm Sweden ISBN 978-91-7178-901-3 TRITA BIO-Report 2008:3 ISSN 1654-2312

Cover illustration: hydrophobic core of the ZAβ3:Aβ complex, reproduced with permission from Hoyer et al., 2008.

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Caroline Grönwall (2008): Affibody molecules for proteomic and therapeutic

applications. School of Biotechnology, Royal Institute of Technology (KTH), Stockholm, Sweden.

Abstract This thesis describes generation and characterization of Affibody molecules with future applications in proteomics research, protein structure determinations, therapeutic treatment of disease and medical imaging for in vivo diagnostics. Affibody molecules are engineered affinity proteins developed by combinatorial protein engineering from the 58-residue protein A-derived Z domain scaffold. Novel Affibody molecules targeting human proteins were selected from a combinatorial library using phage display technology.

In the first two investigations, an Affibody molecule specifically targeting the high abundant human serum protein transferrin was generated. The intended future use of this Affibody ligand would be as capture ligand for depletion of transferrin from human samples in proteomics analysis. Strong and highly specific transferrin binding of the selected Affibody molecule was demonstrated by biosensor technology, dot blot analysis and affinity chromatography. Efficient Affibody-mediated depletion of transferrin in human plasma and cerebrospinal fluid (CSF) was demonstrated in combination with IgG and HSA removal. Furthermore, depletion of five high abundant proteins including transferrin from human CSF gave enhanced identification of proteins in a shotgun proteomics analysis.

Two studies involved the selection and characterization of Affibody molecules recognizing Alzheimer’s amyloid beta (Aβ) peptides. Future prospect for the affinity ligands would primarily be for therapeutic applications in treatment of Alzheimer’s disease. The developed Aβ-binding Affibody molecules were found to specifically bind to non-aggregated forms of Aβ and to be capable of efficiently and selectively capture Aβ peptides from spiked human serum. Interestingly, the Aβ-binding Affibody ligands were found to bind much better to Aβ as dimeric constructs, and with impressive affinity as cysteine-bridged dimers (KD ≈ 17 nM). NMR spectroscopy studies revealed that the original helix one, of the two Affibody molecules moieties of the cysteine-bridged dimers, was unfolded upon binding, forming intermolecular β-sheets that stabilized the Aβ peptide, enabling a high resolution structure of the peptide. Furthermore, the Aβ-binding Affibody molecules were found to inhibit Aβ fibrillation in vitro.

In the last study, Affibody molecules directed to the interleukin 2 (IL-2) receptor alpha (CD25) were generated. CD25-binding Affibody molecules could potentially have a future use in medical imaging of inflammation, and possibly in therapeutic treatment of disease conditions with CD25 overexpression. The selected Affibody molecules were demonstrated to bind specifically to human CD25 with an apparent affinity of 130-240 nM. Moreover, the CD25-targeting Affibody molecules were found to have overlapping binding sites with the natural ligand IL-2 and an IL-2 blocking monoclonal antibody. Furthermore, the Affibody molecules demonstrated selective binding to CD25 expressing cells.

Keywords: Affibody, protein engineering, phage display, amyloid beta peptide, transferrin, CD25, IL-2 receptor, proteomics

© Caroline Grönwall 2008

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List of publications

This thesis is based upon the following five papers, which are referred to in the text by their Roman numerals (I-V). The five papers are found in the appendix.

I Grönwall, C., Sjöberg, A., Ramström, M., Höidén-Guthenberg, I., Hober, S., Jonasson, P., and Ståhl, S. (2007). Affibody-mediated transferrin depletion for proteomics applications. Biotechnology Journal 2: 1389-1398

II Ramström, M., Zuberovic, A., Grönwall, C., Hanrieder, J., Bergquist, J., and Hober,

S. (2008). Development of affinity columns for the removal of high-abundant proteins in cerebrospinal fluid. Manuscript.

III Grönwall*, C., Jonsson*, A., Lindström, S., Ståhl, S., and Herne, N. (2007). Selection

and characterization of Affibody ligands binding to Alzheimer amyloid ß peptides. Journal of Biotechnology 128: 162-183

IV Hoyer, W., Grönwall, C., Jonsson, A., Ståhl, S., and Härd, T. (2008). Stabilization of

a β-hairpin structure in monomeric Alzheimer’s amyloid β-peptide inhibits amyloid formation. Proc. Natl. Acad. Sci. USA. In Press.

V Grönwall, C., Snelders, E., Jarelöv-Palm, A., Eriksson, F., Herne, N., and Ståhl, S.

(2008). Generation of Affibody ligands binding the IL-2 receptor alpha. Biotechnol. Appl. Biochem. In Press.

*These authors contributed equally to this work. All papers are reproduced with permission from the copyright holders.

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Contents

INTRODUCTION .................................................................................................................. 1 1. Proteins............................................................................................................................... 1

1.1 Protein engineering...............................................................................................................3 2. Affinity proteins ................................................................................................................ 4

2.1 Antibodies..............................................................................................................................5 2.2 Antibody fragments..............................................................................................................7 2.3 Alternative protein scaffolds ...............................................................................................8 2.4 Affibody molecules.............................................................................................................12

3. Protein selection systems............................................................................................... 15 3.1 Different selection systems................................................................................................15 3.2 Phage display technology...................................................................................................17

4. Proteins in biotherapeutic applications ....................................................................... 22 5. Proteomics ....................................................................................................................... 25 PRESENT INVESTIGATION........................................................................................... 29 6. Affibody mediated depletion for proteomics research ............................................. 30

6.1 Selection of an Affibody ligand binding to human transferrin (I) ...............................30 6.2 Characterization of the transferrin-binding Affibody molecule (I)..............................32 6.3 Affibody-mediated depletion of HSA, IgG and transferrin from plasma (I) .............33 6.4 Depletion of high abundant proteins from CSF for proteomics analysis (I, II) ........35 6.5 Future aspects......................................................................................................................36

7. Affibody molecules binding amyloid beta peptides (III, IV)................................... 37 7.1 Phage display selection of Affibody molecules binding Aβ (III) .................................39 7.2 Biosensor analysis of selected binders (III).....................................................................40 7.3 Construction of head-to-tail dimeric and cysteine to serine mutated Affibody ligands (III) ...............................................................................................................................................41 7.4 Affibody-mediated capture of Aβ from spiked serum or plasma (III)........................41 7.5 Dimeric Affibody molecules bind to non-aggregated Aβ (III) ....................................42 7.6 The Affibody molecules bind to an Aβ-epitope that enables inhibition of aggregation (III, IV) .........................................................................................................................45 7.7 In solution NMR structure of Aβ in complex with an Affibody molecule (IV)........46 7.8 Ongoing studies ..................................................................................................................47

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8. Generation of Affibody molecules targeting the IL-2 receptor alpha (V)............. 48 8.1 Selection of Affibody molecules binding the IL-2 receptor alpha (V) ........................50 8.2 Biosensor characterization of selected binders (V) ........................................................53 8.3 Competition of Affibody molecules with antibodies and IL-2 (V)..............................54 8.4 Affibody molecules bind to native CD25 on cells (V)...................................................55 8.5 Future aspects (V)...............................................................................................................57

9. Concluding remarks........................................................................................................ 58

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Abbreviations

ABD Albumin-binding domain Aβ Amyloid beta CDR Complementarity determining region CH Constant domain of the antibody heavy chain CL Constant domain of the antibody light chain CSF Cerebrospinal fluid DNA Deoxyribonucleic acid ELISA Enzyme-linked immunosorbent assay Fab Fragment, antigen binding (Antibody) Fc Fragment, crystallizable (Antibody) FDA Food and drug administration FcRn Neonatal Fc receptor HER2 Epidermal growth factor receptor-2 (HER2/neu, ErbB-2) HRP Horseradish peroxidase HSA Human serum albumin IgG Immunoglobulin G IMAC Immobilized metal ion affinity chromatography KA Association equilibrium constant KD Dissociation equilibrium constant kDa Kilodalton mAb Monoclonal antibody MALDI-TOF Matrix assisted laser desorption/ionization - time-of-flight mRNA Messenger ribonucleic acid MS Mass spectrometry NMR Nuclear magnetic resonance PCA Protein complementation assay PCR Polymerase chain reaction PBMC Peripheral blood mononuclear cell scFv Single chain variable fragment (Antibody) SPA Staphylococcal protein A SDS-PAGE Sodium dodecyl sulfate polyacrylamide gel electrophoresis VH Variable domain of the antibody heavy chain VL Variable domain of the antibody light chain

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CAROLINE GRÖNWALL 1

INTRODUCTION

1. Proteins

Proteins constitute a big part of our lives. They are involved in nearly all processes of life, e.g. building up the cells and organs in our bodies, regulating biochemical reactions, digesting our food, mediating signaling between cells, protecting us from infections and transporting molecules within cells or to other parts of the body. Differences in our proteins are what makes us who we are and essentially decide everything from eye color to intelligence and prevalence for many diseases. Despite the enormous variation in function, in principal all proteins are built up by combinations of only 20 amino acids. Each amino acid has unique chemical characteristics and when they are joined together covalently with peptide bonds they form a linear polymer, the polypeptide chain, with varying length and composition. The chain of amino acids is then more or less spontaneously forming a three dimensional structure that gives the protein its functionality. All information required for protein production is stored in our genetic code, carried in the deoxyribonucleic acid, DNA. The fundamental process of information flow from DNA to protein is often referred to as the central dogma, a concept first introduced after the double helix structure of DNA was suggested by Watson and Crick in 1953 [Watson and Crick, 1953] . The genetic code is composed of four different nucleotides, adenine (A), guanine (G), cytosine (C) and thymine (T), building up a specific DNA sequence that is organized into genes. The genes are converted into proteins by transcription of a messenger molecule, mRNA, which is a complementary copy of DNA. The mRNA molecules are thereafter used as template for translation of the corresponding protein. A three-letter code is utilized for converting the DNA sequence into a protein sequence. Thus, a set of three

2 AFFIBODY MOLECULES FOR PROTEOMIC AND THERAPEUTIC APPLICATIONS

nucleotides makes up a so called codon, coding for a single amino acid residue. The primary amino acid sequence of the polypeptide folds into secondary structure elements with helical (α-helix) or more planar (β-sheets) structures that are connected by loops or turns. These secondary structures folds into a three dimension structure, termed the protein’s tertiary structure. Some proteins will in addition be composed of several polypeptide chains, interacting with each other to form the protein’s quaternary structure.

Fig. 1.1. The central dogma. A simplified overview of the information flow from DNA to protein. The number of protein coding genes in the human genome is currently estimated to be

around 23 000 [www.ensembl.org]. However, the actual number of functionally different proteins will be higher due to processing and modification of the proteins after transcription and translation. Even though the sequence of the human genome and hundreds of genomes from other organisms now are known [www.genomesonline.org], we do not understand the function of all proteins and a significant fraction of the encoded human proteins still remains uncharacterized. Increasing our knowledge about proteins will not only give us more insight in the molecular complexity of life but could also help in designing new medical treatments for common diseases. This can be illustrated by the fact that the vast majority of all pharmaceutical drugs on the market today acts through proteins in the body [Drews, 2000].

The biological function of proteins is often dependent on interactions with other biomolecules and based on molecular recognition. All processes in life progress through complex networks of interactions mediated by proteins. The proteins ability to selectively recognize other molecules has been intensively explored through applications in biotechnology and medicine, and can for example be used as tools in research, in industrial processes or for therapeutic treatment of diseases. A widely used class of proteins for different applications is the so called affinity proteins (e.g. antibodies) that can be generated to specifically and with high affinity bind to other molecules.


1.1 Protein engineering For some applications it can be desired to modify the structure or function of a protein. This process is usually referred to as protein engineering. Recombinant DNA technology has given scientists the tools to alter specific DNA positions to change the encoded polypeptide and design new proteins. It has also made it possible to introduce genes or gene fragments in a host organism and to produce proteins in large amounts recombinantly. Proteins can be engineered for a number of different reasons, e.g. to increase stability and solubility, to enhance activities or to change the molecular recognition. The field of protein engineering can be divided into rational and combinatorial methods. In a rational approach, collected data and knowledge about the proteins structure and function gives a prediction about the result of a given alteration of the amino acid sequence. Gene fusion strategies [Ståhl, 1997] and site-directed mutagenesis [Smith, 1985b] are common strategies to achieve rational protein engineering. However, proteins are complex macromolecules and rational design of proteins is often very complicated, e.g. in terms of creating a modified protein with desired activity or binding specificity. In combinatorial methods, a number of mutations are combined to create pools of different protein variants (so called combinatorial libraries) from which proteins with desired functions can be isolated using methods mimicking the natural process of evolution [Brannigan and Wilkinson, 2002].

This thesis discusses the development of affinity proteins with novel binding properties generated by combinatorial protein engineering.


2. Affinity proteins

Proteins are naturally involved in interactions with other biomolecules and most proteins have capability of molecular recognition, as described in chapter 1. Affinity proteins is a term typically used for engineered proteins that have the ability of molecular recognition by specific binding to other biomolecules. These proteins have become an invaluable tool in molecular biology research and biotechnology. Binding proteins can be used as reagents in a wide range of applications, e.g. for bioseparations, detection, and proteomics analysis. Furthermore, proteins binding highly specifically to defined targets in the body can be used as therapeutic drugs or for diagnostics, and the use of such proteins in medical applications is rapidly growing.

Antibodies, described in section 2.1, are naturally evolved affinity proteins, designed by nature to specifically bind to other molecules. They are the most extensively used affinity proteins and there are today approximately 10,000 antibodies commercially available, employed in research and diagnostics [Borrebaeck, 2000; Michaud et al., 2003]. Furthermore, more that 20 antibody-based products have been approved as biopharmaceuticals and at least 150 antibody drug candidates are today in clinical development [Carter, 2006]. However, molecular recognition and specific binding in nature are not at all unique for antibodies and there exist many other naturally designed binding proteins that can be used as starting point for developing of new affinity ligands. Cyclic and linear peptides were among the first alternative affinity molecules to be investigated [Cwirla et al., 1990; Devlin et al., 1990; Scott and Smith, 1990] and peptides have demonstrated to be useful in a number of applications [Scott and Smith, 1990; Wrighton et al., 1996; Arap et al., 2002]. Limitations with peptides are their susceptibility to degradation and that the unfolded state typically results in lower affinities [Nilsson and Tolmachev, 2007]. In recent years, however, efforts in protein engineering have lead to the development of a number of alternative affinity proteins, based on so called scaffold proteins [Binz et al., 2005] described in section 2.3 and 2.4. These new affinity ligands have demonstrated great potential as affinity reagents in various applications and recently also for therapeutic approaches. This thesis describes studies of the type of affinity proteins that are called Affibody molecules, derived from protein A, presented in section 2.5.


2.1 Antibodies Antibodies, or immunoglobulins (Ig), are key proteins of the specific immune system of humans and other higher vertebrates. They are designed to recognize pathogenic and foreign substances and thus involved in the protection against invading pathogens, such as bacteria and virus. Antibodies bind specifically to their target molecule, referred to as their antigen, and through the evolution, the immune system has developed the capability of producing antibodies specific for almost any molecule. Because of their exceptional properties of natural molecular recognition, antibodies has been intensely studied and used in many areas of biological research, biotechnology and for medical diagnostics and therapy. Furthermore, combinatorial protein engineering and selection systems for generation of new affinity proteins, here described in chapter 3, can be viewed as biotechnological ways to mimic the natural diversity and selection of antibodies in the immune system.

Immunoglobulins in humans can be divided into five different subclasses (IgG, IgM, IgA, IgE, and IgD) based on the structure of their constant regions. The IgG subclass is the most abundant in the circulation, constituting 80% of the total serum immunoglobulins. The IgG molecule is a 150 kDa protein composed of four polypeptide chains, two identical larger heavy chains and two identical shorter light chains. Each light chain is coupled to a heavy chain via a disulfide bound and the two heavy-light dimers are correspondingly disulfide bridged, forming the typical Y-shaped antibody structure (Fig. 2.1) [Goldsby et al., 2003]. Furthermore, in early experimental observations antibodies were digested with papain protease, generating two identical antigen binding fragments (Fab, fragment antigen binding) and one without antigen binding activity (Fc, fragment crystallizable) and these terms are still used for describing the antibody structure [Holliger and Hudson, 2005]. The antigen-recognizing activity is localized in the N-terminal part of the heavy and light chain, called the variable regions (VH, VL). Specificity for an antigen is created by variations in the complementary determining regions (CDRs) within the variable regions. The great diversification creating the large repertoire of antibodies recognizing different antigens is possible by combining a limited set of antibody genes followed by somatic hypermutations [Goldsby et al., 2003]. By contrast, the constant parts of the antibody are relatively conserved and contain binding sites for receptors and other proteins, mediating effector functions important for the antibody function in the immune response [Ward and Ghetie, 1995]. The bivalent structure of the antibody will give avidity effects and contribute to a high functional binding affinity.


Fig. 2.1. A schematic representation of an IgG antibody molecule and a scFv antibody fragment. The IgG molecule consists of two identical heavy chains (H) and two identical light chains (L), forming a typical Y-shape, stabilized by several disulfide bonds. The heavy chain consists of three constant domains (CH1-3) and one variable domain (VH), while the light chain includes one constant domain (CL) and one variable domain (VL). The variable domains are responsible for the antigen-binding mediated by three hypervariable loops, denoted complementary determining regions (CDRs).

Antibodies can be produced by immunizing animals with an antigen. The animal will

then generate a pool of antibodies towards different epitopes of the antigen. These antibodies produced from an immunization are referred to as polyclonal antibodies and they will have different amino acid sequences recognizing different epitopes on the same antigen. Although polyclonal antibodies have many useful applications, therapeutic use would in most cases require a more defined reagent, binding to only one epitope. Monoclonal antibodies, i.e. antibodies directed to a single epitope, were first introduced by Köhler and Milstein 1975 through their hybridoma technology [Kohler and Milstein, 1975]. This technology also earned Köhler and Milstein the Nobel Prize in 1984. In hybridoma technology an antibody-producing B-cell is fused with a myeloma cancer cell. The generated hybrid cell will have inherited the ability of antibody production from the B-cell and immortal growth from the tumor cell, providing the possibility of indefinite production of a specific antibody. However, although the technology is still broadly used for generation of specific antibodies, the method is relatively laborious and has several other limitations. The produced antibodies are of rodent origin (most commonly mouse), which would elicit an immune response potentially leading to side effects if it was to be used for medical application, e.g. in repeated therapeutic treatment. This problem can however be minimized by humanization of the therapeutic monoclonal antibody, in which


the antigen binding CDRs from the mouse antibody can be grafted into a human antibody framework [Jones et al., 1986]. There exist today also approaches using transgenic mice to produce almost fully human antibodies [Fishwild et al., 1996]. Furthermore, since the antigen has to be recognized as foreign by the immunized mouse, in order to give a good immune response and antibody producing cells, it can be difficult to generate antibodies to highly conserved proteins. Today, new antibodies can in addition be generated using in vitro selection methods such as phage display technology (described in chapter 3) providing new opportunities for antibody production without the problems associated with hybridoma method

e development of new engineered antibody formats and antibody fragments, presented in 2.2.

2.2 Antibody fragments

e creatio

ology and poor immunogenicity [Wark and Hudson, 2006]. Monoclonal antibodies are excellent affinity proteins but the intact antibody format

suffers from some disadvantages for certain applications. Antibodies are relatively large glycosylated proteins with a complex architecture and several polypeptide chains, which complicates recombinant production and manufacturing [Gill and Damle, 2006]. Furthermore, the Fc-part of the antibody is responsible for recruitment of cytotoxic effector functions through complement and interactions with receptors (γFc). The Fc domain is also providing the long serum half-life of antibodies by interactions with the neonatal Fc receptor (FcRn). These functions are often demanded in therapeutic applications but they can in some cases not be required and even undesired. In addition, in medical applications the large size of antibodies could lead to decrease in tissue penetration efficiency and the long serum half life are disadvantageous for medical imaging resulting in poor contrast [Holliger and Hudson, 2005]. This has lead to th

The constantly increasing knowledge about antibodies and the advances in protein engineering have paved the way for the development of a large number of different engineered recombinant antibody fragments. The modular structure of antibodies makes it possible to remove constant domains in order to reduce size and still retain antigen binding specificity. The smaller antibody fragments lack many of the limitations of complete antibodies described above. They can be produced more economically and are more suitable for a range of diagnostic and therapeutic applications. Furthermore, since full size antibodies are not suitable for in vitro selection, the introduction of engineered antibody fragments has enabled th

n of so called antibody libraries and contributed to the advances in antibody research. The antibody Fab fragment was one of the first antibody derivatives, with a size of

around 55 kDa. Among the most popular antibody formats is the 28 kDa single-chain antibody (scFv) in which the variable domains of heavy (VH) and light chain (VL) are combined


with a flexible polypeptide linker (Fig. 2.1) [Bird et al., 1988; Huston et al., 1988]. The scFv antibodies were invented nearly 20 years ago and were early used in phage display selections of antibodies [McCafferty et al., 1990], and are now an established antibody format for many different applications. The scFv and Fab fragments are monovalent binders but they can be engineered into multivalent binders to gain avidity effects if desired [Holliger and Hudson, 2005]. One way to create dimeric scFv is to reduce the linker which results in self-assembly into dimers, so called diabodies [Holliger et al., 1993]. In scFv and Fab antibodies, the natural combining of the variable region from the heavy chain and the light chain are preserved. Single domain antibodies have been constructed, consisting of only VH or VL, although the first attempts gave poor results due to problems with solubility and aggregation [Holliger and Hudson, 2005]. Thereafter, human single domain antibody scaffolds have been engineered to improve solubility and stability and specific binders have been selected [Holt et al., 2003; Colby et al., 2004; Jespers et al., 2004]. In nature, single domain antibodies (dAbs) have been discovered in two completely separate types of organisms, camelids and cartilaginous fish, e.g sharks. These naturally evolved single V-like domains have successfully been engineered and used as scaffolds for selection of affinity proteins [Holliger and Hudson, 2005; Streltsov et al., 2005; Harmsen and De Haard, 2007].

2.3 Alternative protein scaffolds The success of antibody engineering and the increasing experience in the field of combinatorial libraries and protein engineering have inspired researchers to develop new non-immunoglobulin affinity protein without the limitations of antibodies. Consequently, today antibodies are facing increasing competition from a large number so called engineered protein scaffolds [Hosse et al., 2006]. The term “scaffold” reflects the use of a protein framework that can carry altered amino acids or insertions giving protein variants with entirely novel functions, typically new binding specificity. Most of the proteins used as scaffolds are naturally involved in protein binding although they show a large diversity in structure and function. The choice of scaffold protein is mostly dependent on the intended use of the generated affinity ligands. However, some generally important features can be presented: the scaffold should preferably be relatively small, i.e. being composed of a single polypeptide chain, and having a highly stable architecture [Nygren and Skerra, 2004]. High stability independent of disulfide bonds is a clear advantage, facilitating high yields in bacterial expression and enabling intracellular applications. Moreover, the absence of intramolecular cysteines gives the possibility to introduce a unique cysteine for labeling or other chemical modifications. The protein should further be stable enough to be highly tolerant to randomization in order to create a library with functional members. Usually, a library of a chosen protein scaffold is created by selective random


mutagenesis of an appropriate number of surface exposed residues. Considerations should also be made about the origin of the protein used as a scaffold. If the affinity proteins are intended for therapeutic use, the problem of potential immunogenicity may be an issue to consider. If the protein is of foreign origin it will be likely to cause some immune response if no precaution is taken, but also scaffolds based on human proteins would have the potential of becoming immunogenic by the introduced amino acids and altered binding sites. In addition, when using human protein scaffolds, the risk of causing autoimmunity reaction would, at least in theory, need to

Here only a selection is presented, focusing on the Affibo

ave been selecte

be considered. There are now approximately 50 suggested protein scaffolds reported and they have

been intensely reviewed over the last years [Nygren and Skerra, 2004; Binz et al., 2005; Hey et al., 2005; Hosse et al., 2006; Skerra, 2007].

dy scaffold described in section 2.4. The different scaffolds are most commonly classified based on their structure and the

utilized binding-site engineering strategies. Protein scaffolds with an immunoglobulin-like structure with randomized loops can be compared to scaffolds with a compact structure with flat surface randomization or scaffolds with cavity randomization. One example of an immunoglobulin-like scaffold is the 10th fibronectin type III domain (10Fn3, the scaffold is also referred to as monobody or adnectin). 10Fn3 is a small, 10 kDa, β-sheet domain, that resembles the VH domain of an antibody with CDR-like loops, but lack disulfide bonds. Fibronectin is naturally a mediator of protein-protein interactions in humans. Randomization was first made in two surface loops and binders selected with phage display [Koide et al., 1998]. More recently, three loops have been randomized and binders have successfully been selected using mRNA display [Xu et al., 2002; Karatan et al., 2004]. Another scaffold with β-sheet framework with slightly different properties is the lipocalin (anticalin), characterized by a rigid β-barrel structure and four flexible loops. The variable loop structures form an entry to a ligand-binding cavity. The binding site can adapt to extremely different shapes and in nature the members of the lipocalin family demonstrate a large variety of functions. However, the ability to specifically bind low molecular weight molecules is well characterized for many lipocalins [Schlehuber and Skerra, 2005]. Beste and colleagues have demonstrated that the bilin-binding protein (BBP), a lipocalin from Pieris brassicae, can be used as a scaffold for selection of new affinity proteins by randomization of the ligand binding site and selection of fluorescein-specific binders [Beste et al., 1999]. Thereafter, several anticalin affinity ligands h

d targeting both small molecules and proteins [Schlehuber and Skerra, 2005]. Various modified protease inhibitor have been reported used as scaffold proteins,

usually generated for targeting proteases of pharmaceutical importance. Protease inhibitors are suitable as scaffolds, being small, stable and demonstrating their binding activity in an exposed peptide loop that can be targeted for randomization in creation of a combinatorial library


[Nygren and Skerra, 2004]. The Kunitz domain is an example of a natural serine protease inhibitor that successfully have been utilized as a scaffold for library construction and selection of protease inhibitors of potentially therapeutic interest [Dennis and Lazarus, 1994; Williams and Baird, 2003]. Another specialized scaffold is the PDZ domains (PSD-95/Discs-large/ZO-1-domains) that mediate specific protein-peptide interactions. Libraries with variants of the engineered PDZ can be used for selection of binders that target proteins with a free C-terminus peptide [Schneider et al., 1999; Ferrer et al., 2005]. An example of a scaffold that is used for display of a single loop peptide is the thioredoxin (TrxA). The TrxA is a robust enzyme with a short active site loop that permits insertions of diverse and quite long peptides. Affinity binders, so-called peptide aptamers, have been selected from random loop libraries displayed on TrXA [Borghouts et al., 2005]. There also exist scaffolds with a more oligomeric structure, such as the avimers. Avimers are designed multidomain proteins derived from the human A-domains that occur in the low-density lipoprotein receptor (LDLR) and the conformation of each 39 amino acid domain is determined by three cysteine bridges. Selections have generated binders with high affinity to clinically relevant targets [Silverman et al., 200

s have been generated using primarily ribosomal display [Binz e

ith similar roperties, having a surface randomization directly on secondary structure elements.

5]. A new class of affinity proteins is the so-called repeat motif proteins that contain

consecutive copies of a small structural unit that assembles to form contiguous domains. Repeat proteins occur in nature as mediators for protein-protein interactions and the modular structure can make them adaptable to the size of a target protein. The ankyrin repeat (AR) protein is such a protein, composed of 33 residue repeat domains consisting of a β-turn followed by two α-helices giving a stable structure. The ankyrin repeats form a basis for the darpin (designed ankyrin repeat protein) which is a scaffold comprised of usually three repeats of an artificial consensus ankyrin repeat domain. Randomization to create combinatorial libraries is to a large extent performed on secondary structure elements giving a rather flat binding surface. High affinity binder

t al., 2003; Binz et al., 2004]. Affibody molecules presented in detail in section 2.4 are based on a scaffold w

p


Table 2.1. Examples of non-immunoglobulin scaffolds for generation of new affinity ligands. Name Scaffold Residues

/S-S bonds Secondary structure

Randomization Selection method

Reference/ Company

Adnectin Fibronectin 94/- β-sandwich 2-3 loops phage display mRNA display yeast-two-hybrid

Koide et al., 1998 Xu et al., 2002 Compound Therapeutics

Affibody Protein A 58/- α3 13 aa on 2 α-

helices phage display Nord et al., 1997

Affibody AB Anticalin Lipocalin

(BBP) 160-180/ 2 S-S

β-barrel 4 loops (16 aa) phage display Beste et al., 1999 Pieris Proteolab

Aptamer TrxA 108/1 S-S α /β 20 aa loop insert phage display

yeast-two-hybrid

Borghouts et al., 2005 Aptanomics

Avimer LDLR-A

domain n× ~40/ 3 S-S +Ca2+

oligomeric, ~4-loops

21 aa in each domain

phage display Silverman et al., 2005 Amgen

Darpin Ankyrin

repeat 67 + n×33/-

α2 /β2 7 aa on β-turn and 1 α-helix (of every repeat)

ribosome display

Binz et al., 2004 Molecular Partners

Kunitz domain

APPI 58/3 S-S α /β 1-2 loops phage display Dennis et al., 1994 Williams and Baird, 2003 Dyax

PDZ-domain

Ras-binding AF-6

~100/- α3 /β5 entire domain by PCR mutagenesis

phage display Schneider et al., 1999 Ferrer et al., 2003 BioTech Studio LLC


2.4 Affibody molecules Affibody molecules are based on a 58 amino acid protein domain, derived from staphylococcal protein A (SPA). SPA consists of five homologous Ig-binding domains (E, D, A, B, and C), all capable of binding the Fc part of antibodies from different species and subclasses [Moks et al., 1986]. They have all five in addition been demonstrated to interact with the Fab part of antibodies belonging to the human VH3 subclass [Jansson et al., 1998]. The domain B was in 1987 engineered by mutagenesis of two amino acids in order to primarily increase chemical stability. The asparagine-glycine sequence in residue 28-29 (Asn28-Gly29) was replaced with asparagine-alanine (Asn28-Ala29) to ensure resistance to hydroxylamine cleavage and the first alanine residue (Ala1) was changed to valine (Val1) for subcloning purposes [Nilsson et al., 1987]. The new protein domain was denoted Z and was first used as an Ig-binding affinity tag for recovery of fusion proteins. The Z domain demonstrated retained Fc interaction, binding with an affinity in the range of 10-60 nM to the Fc portion of human IgG1 [Jendeberg et al., 1995]. Significant lower affinity was shown to the VH3 Fab region than for the original B domain [Jansson et al., 1998].

Fig. 2.2. A schematic picture of the Affibody scaffold derived from the engineered 58 amino acid α-helical protein A domain Z. Combinatorial protein libraries have been created by mutagenesis of 13 surface-located amino acid residues in helices 1 and 2.


The Z domain is highly stable, consisting of three α-helices forming a bundle structure. The small size (6.5 kDa), absence of internal cysteines and high solubility allows inexpensive production in a prokaryotic host. Furthermore, the relatively small size and rapid folding kinetics enable the Z domain to be efficiently produced by solid-phase peptide synthesis, providing possibilities for introduction of non-biological groups [Engfeldt et al., 2005].

The Z domain has been used for protein engineering as a scaffold for selection of novel affinity ligands. To create a combinatorial library, thirteen surface exposed residues in helix one and two, of which a majority were involved in the native interaction with Fc [Deisenhofer, 1981], were subjected to randomization (Fig. 2.2) [Nord et al., 1995]. Hence, the original IgG binding capability was lost. The members of the Z library were denoted Affibody molecules and it could in a pioneering paper 1997 be demonstrated that specific novel affinity proteins could be isolated from the library by phage display selection technology [Nord et al., 1997]. Since then a large number of Affibody molecules have been selected, targeting a variety of different proteins representing different origin and molecular sizes. Selection from the current Affibody library, with 3×109 members [Grönwall et al., 2007a] have generally yielded binders in the low to mid nanomolar range. In addition, to generate higher affinity binders straight-forward affinity maturation strategies have been applied using second generation libraries and selection [Gunneriusson et al., 1999; Nord et al., 2001; Orlova et al., 2006; Friedman et al., 2008]. In this approach, affinities down to 20 pM have been reported [Orlova et al., 2006]. In table 2.2, a selection of Affibody molecules with publically available information is presented.

Initially, Affibody molecules were investigated for a range of biotechnological applications, but different therapeutic and molecular imaging approaches have recently come into focus. Affibody ligands have shown potential in applications such as for bioseparations [Nord et al., 2000; Nord et al., 2001; Gräslund et al., 2002], as detection reagents [Karlström and Nygren, 2001; Rönnmark et al., 2002b; Andersson et al., 2003; Renberg et al., 2005], in inhibition of receptor interactions [Sandström et al., 2003], for depletion in proteomics research [Grönwall et al., 2007b], and for tumor targeting applications [Wikman et al., 2004; Steffen et al., 2005; Friedman et al., 2007].

The most thoroughly investigated Affibody molecule is the high affinity binder targeting the in breast cancer important cell surface receptor HER2. The Affibody molecule have exhibited very promising result as an imaging agent for tumor visualization [Nilsson and Tolmachev, 2007; Tolmachev et al., 2007a] in preclinical and pilot clinical applications [Baum et al., 2006; Orlova et al., 2007]. The small size and high specificity of the Affibody molecules results in a good tissue penetration and rapid blood clearance, which enables low background in medical imaging and makes them very suitable as imaging agents. Future therapeutic applications for the HER2 Affibody molecule can also be envisioned since tumor growth


inhibition was recently achieved in a mice model [Tolmachev et al., 2007b]. In biotherapeutic applications, a short half-life is likely to be disadvantageous and the unmodified Affibody molecules are therefore not suitable. However, it has recently been demonstrated that the pharmacokinetics of the Affibody molecules can easily be modulated by fusion to an albumin binding domain, giving an interaction with serum albumin, resulting in prolonged half-life [Tolmachev et al., 2007b].

Table 2.2. Published or publically available Affibody molecules selected by phage display. Protein Size

(kDa) Origin Affinity Library Reference*

Aβ peptides 4.5 human disulfide linked dimer 320 nM (biosensor analysis) 17 nM (isothermal titration calorimetry)

3×109 [Grönwall et al., 2007a] [IV: Hoyer et al., 2008]

Apolipoprotein A1 ~28 human 1 μM 4×107 [Nord et al., 1997] CD25 55 human 130 nM 3×109 [V: Grönwall et al.,

2008] CD28 90 human 8 μM 4×107 [Sandström et al., 2003] c-Jun 70 (dimer) human 5 μM 3×109 [Lundberg et al., 2008] EGFR 100 (ECD) human 130 nM 1st generation

5 nM 2nd generation 3×109

affinity mat. [Friedman et al., 2007] [Friedman et al., 2008]

Factor VIII 90 human 100 nM 1st generation 5 nM 2nd generation

4×107

affinity mat. [Nord et al., 2001]

Fibrinogen** 340 human N.D 3×109 www.affibody.se Gp120 120 HIV virus 100 nM 3×109 [Wikman et al., 2006] HER2 100 (ECD) human 50 nM 1st generation

22 pM 2nd generation 3×109

affinity mat. [Wikman et al., 2004] [Orlova et al., 2006]

IgA 150 human 500 nM/ N.D

4×107/ 3×109

[Rönnmark et al., 2002a] www.affibody.se

IgE 190 human N.D 3×109 www.affibody.se IgM 900 human N.D 3×109 www.affibody.se IL-8 ~8 human N.D 3×109 www.affibody.se Insulin 6 human 30 μM/

N.D 4×107/ 3×109

[Nord et al., 1997] www.affibody.se

RSV G protein 11 RSV virus 10 μM 4×107 [Hansson et al., 1999] Taq polymerase ~90 bacteria 2 μM 1st generation

30 nM 2nd generation 4×107

affinity mat. [Nord et al., 1997] [Gunneriusson et al., 1999]

TNF-α*** ~18 (monomer)

human 95 pM 3×109 [Kronqvist et al., 2008]

Transferrin 80 human 400 nM 3×109 [Grönwall et al., 2007b] Transthyretin 54 human N.D 3×109 www.affibody.se

* All presented unpublished Affibody molecules as well as some of the published molecules are commercially available (Feb 2008) from Affibody AB (Bromma, Sweden) or Abcam (Cambridge, UK). ** An Affibody molecule targeting fibrinogen is in addition part or the Multiple Affinity Human-7 Removal System manufactured by Agilent Technologies (Santa Clara, CA, USA). *** Selected using Staphylococcal display.


3. Protein selection systems

In nature, evolution has generated the great diversity of proteins with all different features required for the processes of life primarily by using the 20 amino acids. Despite all our efforts to fully understand the nature of proteins, we are still far from being able to create new proteins with desired structure and function merely by rational design. By utilizing DNA technology it is possible to make changes in already existing proteins in order to generate new variants with possibly new features. However, it is a challenge to predict what combination of changes in the different amino acid residues that is needed to design a protein with novel functionality. One way of solving this problem is to use combinatorial strategies to generate diversity and create a pool of different protein variants, a so called library, and use the concept of in vitro evolution to find the protein with the best properties. The desired function could for example be improved stability or solubility, or modified substrate specificity or improved properties of an enzyme. This thesis will hereinafter focus on the generation of proteins with novel binding specificity. When developing affinity proteins with new binding specificities, proteins can be selected for the capability to bind to a target molecule. There are a variety of different strategies, commonly termed protein selection systems, for isolating proteins with new affinity specificity from a combinatorial protein library.

This chapter will present different selection systems, focusing on the phage display selection technology that has been utilized in the articles presented in this thesis.

3.1 Different selection systems Since sequencing of proteins is difficult, all successful affinity protein selection systems are based on linkage between the genotype and phenotype of the affinity protein. This enables easy identification and amplifications of the selected polypeptides via the nucleic acids, DNA or RNA. The selection procedure can be summarized in the steps: diversification, selection and amplification. It includes construction of a protein or peptide library, screening for binding to a defined target molecule, amplification of selected molecules and identification of binding clones. The selection is typically repeated a number of times to enrich molecules with desired binding properties. After selection and identification, the selected novel protein can be recombinantly produced and characterized in more detail. The success of a selection strategy depends to high extent on the diversity and quality of the constructed library. However, methods for construction of affinity protein libraries will not be discussed in detail in this thesis.


The different selection systems can be divided into three different groups: cell-dependent display systems, cell-free display systems and non-display systems. In the cell-dependent display systems, the affinity proteins are displayed on the surface of phage particles or cells, or expressed in a cellular compartment. The most utilized system in this group is phage display [Barbas III, 2001] described in more detail in section 3.2. A large number of strategies for expressing affinity proteins from libraries on the surface of different cell types have been investigated. Two examples of bacterial display are display on the gram negative bacterium E. coli [Francisco et al., 1993; Daugherty et al., 1998] and display on the gram positive bacterium Staphylococcus carnosus [Löfblom et al., 2005; Kronqvist et al., 2008]. Yeast surface display on Saccharomyces cerevisiae was one of the first developed alternatives to phage display, described more than ten years ago [Boder and Wittrup, 1997; Gai and Wittrup, 2007]. The major advantage with cell surface display systems is the possibility of using fluorescence labeling and flow cytometry sorting for the screening, enabling affinity discrimination in the selection. However, there are some limitations using cell-dependent systems, foremost associated with the fact that the possible library size depends on the transformation efficiency of DNA. This has led to the exploration of different cell-free systems with the main common feature that they use in vitro transcription and translation for construction of protein libraries. This enables the creation of libraries with up to 1013 members and allows the possibility to introduce in vitro mutagenesis during the amplification which can give a directed evolution in every selection round [Roberts, 1999]. Cell-free systems include ribosomal display, first described by Mattheakis et al. [Mattheakis et al., 1994] and subsequently explored for selection by Hanes and Plückthun [Hanes and Plückthun, 1997]. In ribosomal display, DNA sequences encoding the protein library and a ribosome-binding site but not containing a stop codon after the gene encoding the protein of interest, is transcribed and translated in vitro. This results in a stalling of the ribosome and a coupling of the coding mRNA to the translated protein. The mRNA-ribosome-protein complex can then be subjected to a target molecule. Another example of cell-free display is the mRNA display system, where the mRNA is covalently linked to the polypeptide through the antibiotic puromycin [Nemoto et al., 1997; Roberts and Szostak, 1997]. Several different microbead display approaches have also been proposed for cell-free protein selections, utilizing in vitro transcription and translation of DNA immobilized to beads [Sepp et al., 2002; Nord et al., 2003]. The main advantage of using beads as carriers is that it enables flow cytometry sorting for the isolation of binders.

There are in addition selection systems that are not based on display of libraries and selection by incubation with a target molecule and isolation of binders. In these non-display systems, the target protein is co-expressed with the individual library members in vivo. Two examples are the protein complementary assay (PCA) [Koch et al., 2006] and yeast-two-hybrid


systems [Parrish et al., 2006]. However, these systems have so far mostly been explored for discovering of new protein-protein interaction and not for selections of affinity ligands.

It is not evident that one selection system is clearly advantageous over the others, since they all have their pros and cons. It is likely that the different systems will be further developed in the coming years and they might all possibly find their special applications. Still phage display technology has hitherto been the “work-horse” in combinatorial protein engineering. Moreover, protein selection systems can besides being used for selection for binding specificity be used for isolation of protein with other desired functions such as enzymatic activity. They are also powerful tools in proteomics research and for epitope mapping applications [Chao et al., 2004; Sidhu and Koide, 2007].

Table 3.1. Examples of different selection systems employed in combinatorial protein engineering. Selection System Illustrative References Cell-dependent systems Phage display Barbas et al., 2001 Bacterial display Löfblom et al., 2005

Daugherty et al., 1998 Yeast display Border and Wittrup, 1997 Cell-free systems Ribosomal display Hanes and Plückthun, 1997 mRNA display Nemoto et al., 1997

Roberts and Szostak, 1997 Non-display systems Yeast-two-hybrid Parrish et al., 2006 PCA Koch et al., 2006

3.2 Phage display technology In phage display, peptides or proteins are displayed on the surface of filamentous bacterophage particles which contain the encoding DNA, thus giving a physical link between the phenotype of the displayed polypeptide and the corresponding genotype. The method for displaying polypeptides on phage particles was first described by George Smith in 1985 [Smith, 1985a]. Since then phage display technology has proved to be a powerful tool for screening libraries of proteins and peptides for selection of molecules with desired properties and it is still the dominating method for construction of protein libraries and selection of affinity proteins. Phage display was first developed for the M13 filamentous phage and even though several alternative phage systems have been explored, such as bacteriophage T4, T7, and lambda [Mikawa et al., 1996; Ren and Black, 1998; Santini et al., 1998; Houshmand et al., 1999], M13 still remains the most extensively studied and most commonly used phage. The M13 phage specifically infects E. coli cells expressing F-pilus on its surface and replicates and assembles


without killing the host in contrast to lytic bacteriophage species (e.g. T4, T7, lambda). The filamentous phage consists of a single-stranded circular DNA molecule enclosed by a protein capsid tube, forming a 1 μm × 5 nm long rod-like virus particle. Filamentous phage is considered good subcloning vectors because of the high tolerance for insertion of large foreign genes since the phage can simply respond to the larger genome by assembly of a larger phage particle. The phage genome encodes in total eleven proteins, six non-structural proteins involved in DNA replication and virus assembly (pI, pII, pIV, pV, pX, and pXI), and five capsid proteins (pIII, pVI, pVII, pVIII, and pIX). For display of foreign proteins on the surface, the gene encoding the protein of interest is fused to the phage gene encoding one of the coat proteins. In the virus assembly process, the produced fusion proteins are transported into the bacterial periplasm or the cytoplasmic membrane and incorporated into the phage particle [Webster, 2001]. Although display systems have been described for all five coat proteins [Jespers et al., 1995; Gao et al., 1999], the most commonly used coat proteins for displaying affinity proteins are the major coat protein, pVIII, produced in 2700 copies covering the whole phage particle, or coat protein pIII, displayed in only 5 copies localized at the tip of the phage and important for infection of E. coli by attaching to the F-pilus [Hoess, 2001; Webster, 2001]. Display in fusion to pVIII will give a more multivalent display and generally only short peptide are tolerated by the phage [Kretzschmar and Geiser, 1995]. The far most frequently used fusion partner in combinatorial protein engineering for library members (e. g. antibodies) is the 42 kDa coat protein III [Bradbury and Marks, 2004]. For both pIII and pVIII display, different vector systems can be applied for the expression of the fusion proteins depending the preferred expression level and selection strategy. For pIII display, the earliest developed phage display vectors involve whole phage DNA in which the gene of interest is fused to the wt gene for pIII (“type 3” system). In this system every copy of coat protein III will be expressed in fusion to the foreign protein. Since this gives several copies of the affinity protein on the phage it will lead to avidity effects which could influence the selection procedure and complicate affinity discrimination. However, for selection of lower affinity binders or binders towards “difficult” targets this could potentially be desired. Furthermore, the incorporation of larger polypeptides in fusion to pIII will compromise the infection capability of the phage since protein III is essential in the infection process. To circumvent these problems, the 33 system and the 3+3 phage display system were developed. In the 33 system, an extra gene encoding protein III can be incorporated in the phage genome, giving expression of a mix of wt pIII and pIII fused to the foreign protein [Smith and Petrenko, 1997]. The 3+3 system uses a phagemid vector [Bass et al., 1990] for expression of the protein III fusion protein. In addition to the protein III gene, the phagemid contains the origin of replication for both M13 and E. coli and the M13 phage packaging signal, but lacks all other phage genes encoding proteins required to produce functional phage particles. The phagemid


can be delivered to E. coli cells by standard transformation and grown as a plasmid. Furthermore, the phagemid can be packed into a recombinant M13 phage particle by the aid of infectious helper phage. The helper phage contains all necessary proteins for phage replication and assembly including the wt protein III but has a slightly deficient origin of replication giving a preferential packaging of phagemid. Phagemid in combination with helper phage will thus optimally result in phage particles monovalenty expressing the pIII fusion protein on their surface and containing the phagemid vector. Typically, to give display of in average one fusion protein per phage, the majority of produced phages will only express the wt protein. For display on the phage coat protein VIII, equivalent systems have been developed i.e. 88 and 8+8 [Smith and Petrenko, 1997].

Fig. 3.1. Schematic illustration of a phage used in the 3+3 phage display system. The foreign protein of interest is displayed in fusion to the phage coat protein III (pIII). In the 3+3 system, the foreign gene is fused to the pIII encoding gene in a phagemid vector. The phagemid contains the phage ori of replication and packaging signal but lacks genes encoding other phage proteins. Superinfection with helper phage provides all phage proteins and allows for generation of infectious phage particles displaying a mixture of wt pIII and pIII fused to the protein of interest.

In general, a typical selection procedure using the phage display technology, often

referred to as panning, is performed as follows (Fig. 3.2). E. coli cells containing the transformed plasmid library are infected by helper phage to produce phage particles displaying different protein variants on their surface. The phage is then incubated with the target protein, either immobilized on a solid phase, such as paramagnetic beads or microtiter plates, or free in solution. For selection in solution, phage in complex with target protein can be captured on a solid phase after the selection. A common strategy is to utilize biotinylated target protein and a streptavidin surface. After the selection, unbound phage is washed away and phage specifically binding the target protein is eluted. Subsequently, the eluted phage is used to infect new E. coli cells to amplify selected clones and phage particles are rescued by superinfection of helper phage to create a new phage library that can be used in a new round of selection. Typically, three to five rounds of panning is required to enrich the clones that express variants capable of binding the target protein with high affinity. To improve the discrimination between binders and non-binders and generate binders with higher affinity, the stringency normally is increased by each round of selection by increasing the number of washes and/or decreasing the


concentration of target protein. The most commonly used method for elution of bound phage from the solid phase is by a short incubation with low pH buffer, but a number other elution methods such as alkaline buffers, competitive elution, and proteolytic cleavage, can be used. After the last round of selection, proteins expressed on the phage can be identified by DNA sequencing of individual clones. Furthermore, individually selected clones can be further screened for their binding capability to the target protein, typically by ELISA. Screening can be conduced on intact phage or alternatively with soluble protein that in most cases can be expressed directly from the phagemid vector. A large number of alternative phage display selection strategies for affinity proteins has been described and reviewed extensively elsewhere [Hoogenboom and Chames, 2000; Sidhu, 2000; Hoess, 2001; Bradbury and Marks, 2004; Paschke, 2006; Sergeeva et al., 2006; Sidhu and Koide, 2007].

Phage display technology has been used for display of a variety of different affinity proteins. The technology was originally invented for cDNA fragments [Smith, 1985a; Parmley and Smith, 1988] and peptides [Cwirla et al., 1990; Devlin et al., 1990; Scott and Smith, 1990]. However, new techniques for amplifying and subcloning antibody genes in the early nineties made it possible to express different antibody fragment on the surface of phage [McCafferty et al., 1990; Barbas et al., 1991; Kang et al., 1991] and antibody phage libraries could be developed, which still is the most widely used and maybe the most successful application of phage display. Phage display of naïve, immunized, or synthetic antibody libraries have been created [Rader and Barbas, 1997; Bradbury and Marks, 2004] as well as libraries of alternative non-immunoglobulin protein scaffolds [Nygren and Skerra, 2004; Binz et al., 2005]. In this thesis, phage display selections of novel Affibody molecules binding three different targets, will be presented (I, III, V).


Fig. 3.2. Schematic overview of the phage display selection procedure. Libraries of proteins are displayed on phage particles as fusions to phage coat proteins. The phage library is exposed to a target molecule and bound phage-target complexes are captured on a solid phase, followed by washing for removal of unbound or weakly bound phage and subsequent elution of bound phage. The retained phage can be amplified by re-infecting a bacterial host and phage particles can be rescued by superinfection of helper phage, creating a new phage pool. The amplified pool is typically cycled through 3-5 selection rounds to enrich for target-binding clones. Individual clones can be subjected to screening for binding to the target molecule for ranking of binding. The amino acid sequences of the encoded proteins are identified by DNA sequencing.


4. Proteins in biotherapeutic applications

The dominating class of prescribed drugs of today is based on small organic molecules. Engineered proteins for therapeutics represent a rather new generation of pharmaceuticals that has increased dramatically under the last years and is now starting to show potential for competition with small-molecule drugs [Walsh, 2005].

Protein-based drugs can be classified in four different groups depending on their function and therapeutic application, in accordance with a recent report by Leader and colleagues. The first group constitutes proteins with an enzymatic and regulatory activity e.g. hormone. They can either replace a deficient protein, enhance a normal protein activity, or provide novel functions. Another group of therapeutic proteins acts as vaccines. These proteins have the potential to be used for activation of the immune system to give protection against foreign agents or for possible treatment of cancer or autoimmune disease. The third group of therapeutic proteins includes proteins with targeting activity. This group of proteins functions by specifically recognizing and binding to target biomolecules. By binding, they can interfere or block functions, target molecules or organisms for destruction, or stimulate a signaling pathway. They can also be used for delivery of other proteins or compounds to a specific site. Consequently, they can be used in therapy either with a direct function or as carrier of a molecule with effector function. The last class of proteins for therapeutic applications consists of proteins used for diagnostics. These proteins can be used for in vivo diagnostics, for example in medical imaging [Leader et al., 2008].

Isolation of proteins from their native source is associated with many limitations and the first breakthrough for protein-based drugs came with the development of recombinant DNA technology. The first recombinant protein that was approved for therapeutic use 25 years ago was E. coli produced insulin for treatment of diabetes. Today, recombinant proteins can be produced in bacteria, yeast, insect cells, mammalian cells, and transgenic animals and plants. The choice of system used for production can depend on the proteins properties, demands for cost of production and required modifications of the protein for biological activity. For examples will production in bacteria not give glycosylation of the produced protein and no glycosylation or change in the glycosylation pattern can have a dramatic effect on activity, pharmacokinetics, and immunogenicity of the therapeutic protein. There are now more that 130 proteins or peptides approved by the US Food and Drug Administration (FDA), and globally several hundreds are currently undergoing clinical trials [Walsh, 2005;


Leader et al., 2008]. Proteins therapeutics have several advantageous compared to small chemical molecules, e.g. being highly specific, well tolerated by the body, and having specific and complex functions that are difficult to mimic [Leader et al., 2008].

This thesis will mainly focus on affinity proteins with potential for therapeutic use and for in vivo diagnostics. Today, most affinity proteins used or investigated in medical application are antibody based. Since monoclonal antibodies (see chapter 2.1) first were developed they have been explored as therapeutic agents. New technical achievements have made it possible to develop antibodies to a wide range of target molecules and with modern engineering tools the novel antibodies can be designed to ensure high specificity and functionality [Brekke and Sandlie, 2003; Carter, 2006]. The exquisite specific binding properties and the possibility of induction of effector functions make antibodies well suited as therapeutic agents. Antibodies can function therapeutically by a variety of different mechanisms. One way is by blocking the activity of a specific molecule, for example a growth factor or a cytokine, either by binding to the factor itself or by binding to the corresponding receptor. Antibodies can also be used for targeting and to eliminate a defined cell population. Either the antibody binding can induce a signaling pathway leading to cell death or the natural effector function of antibodies can induce antibody-dependent cellular cytotoxity (ADCC) or complement-mediated cytotoxicity. Moreover, to further enhance the cytotoxicity, the antibodies can be coupled to various cytotoxic substances, including radioisotopes, toxins or small chemotherapeutic drugs [Stockwin and Holmes, 2003]. There are currently approximately 200 antibodies in clinical trials and more than 20 therapeutic antibody-based drugs have been approved for treatment of cancer, transplant rejections, rheumatoid arthritis and Cohn’s disease, and for antiviral prophylaxis [Brekke and Sandlie, 2003; Leader et al., 2008]. Consequently, antibodies now represent around 20 % of all biopharmaceuticals in clinical trials and they are the second largest biopharmaceutical product category after the vaccines [Leader et al., 2008]. In addition to full size antibodies, antibody fragments such as Fab and scFv (see chapter 2.2) have been evaluated as targeting therapeutic agents. The smaller size will give shorter half-lives and improved tissue penetration that can be advantageous for certain applications. The small size makes them also easier to produce recombinantly and to humanize for prevention of immune responses. However, antibody fragment will not have the natural ability to induce effector functions [Holliger and Hudson, 2005]. More recently, alternative affinity proteins have been developed based on non-immunoglobulin scaffolds (see chapter 2.3 and 2.4). These new affinity ligands have demonstrated promising results for targeting therapeutically interesting molecules and could potentially represent a new generation of targeting therapeutic proteins with great potential [Hey et al., 2005].

Affinity proteins can, as mentioned previously, be used for in vivo diagnostics as imaging agents to identify or localize a pathological condition. Protein-based imaging agents


are currently used for detection of cancer, image myocardial injury or identification of sites of infection [Leader et al., 2008]. Medical imaging can provide important prognostic information and be invaluable for decision between different treatments. Important features for a targeting imaging agent are high affinity for the target molecule and high specificity, avoiding unspecific binding to healthy tissue. Furthermore, the agent should quickly localize the target and unbound agent should be cleared from the body, facilitating high imaging contrast and reducing the time required before examination in the clinic. Monoclonal antibodies are thus not the preferred format for imaging agents due to their large size and long half-lives [Nilsson and Tolmachev, 2007].

Another interesting field of applications for affinity proteins in the context of therapeutics is for extracorporeal depletion. In apheresis, harmful cells or proteins can be removed from the circulation extracorporeally. This can be accomplished by leading the blood or plasma through a device and capture the harmful component with an affinity reagent, thus specifically removing the disease-causing agent outside the body. Apheresis has for example been utilized for treatment of leukemia, sepsis and autoimmune disease [Bosch, 2003; Borberg, 2006]. With high specificity in the protein-protein interaction, one might envision future therapies based on extracorporeal removal of harmful agents employing new affinity proteins as capturing agents.

Although proteins are considered to have great potential in future therapeutic strategies, there are still some challenges that have to be faced in the development of new protein-based drugs. Proteins are large complicated macromolecules and many factors can affect the therapeutic effect, e g. stability, route of administration, immunogenicity, and pharmacokinetics. The solutions for the challenges can be manipulations of primary structure, incorporation of chemical and post-translational modifications and utilization of fusion partners [Marshall et al., 2003]. Moreover, the cost for developing and producing new protein drugs is in many cases very high, leading to expensive treatment of patients. Despite this, proteins as pharmaceuticals have so far been a great success and protein-based drugs are foreseen to have an expanding role in medicine in the future.


5. Proteomics

Proteomics is a large-scale approach to investigate proteins and their function. The word is an analogue to the term genomics and reflects the study of an organisms proteome, that is all protein encoded by the organisms genome. After the completion of the human genome sequence [Lander et al., 2001; Venter et al., 2001; Consortium, 2004] it became clear that we cannot yet easily determine or predict the functions of all encoded gene products. In fact, a significant number of genes in the annotated genomes today codes for proteins that remain to be characterized [Saghatelian and Cravatt, 2005]. To explore the function and interactions of all proteins provide a great challenge and to investigate individual proteins “one at a time” is incredibly time consuming. However, precise knowledge of protein function is not always required to initially shed light on important events in an organism’s life. One approach for exploring human proteins is the Human Protein Atlas (HPA) effort (www.proteinatlas.org) with the main goal to determine the detailed localization of proteins, and compare the abundance of a given protein in healthy and various cancer tissues [Uhlén et al., 2005]. While the genome is considered mostly static the proteome is highly dynamic and the protein profile of expressed proteins changes over time depending on internal and external stimuli. Consequently, recognition of differently expressed proteins, so called biomarkers, is highly interesting and can provide information about the state of an organism and increase knowledge about the processes of life.

In proteomics research, a major effort is made to discover new biomarkers for common diseases. Identification of biomarkers can lead to new information about the disease and development of new platforms for diagnostics and novel therapeutic approaches. The primary clinical aims of today are to allow early detection and individualized treatment of disease, and furthermore the invention of therapies with improved clinical outcome [Muller et al., 2007]. In the clinic, body fluids are the most attractive samples, with low degree of invasiveness, minimal cost and easy sample collection and preparation [Hu et al., 2006]. Proteins in body fluids serve several important functions including transport, catalytic activation, humoral immunity, protease inhibition, maintenance of oncotic pressure and buffering. In healthy individuals, the amounts of most of these proteins are kept in balance. Any deviation from the norm may indicate disease, or a healing process, or may be an effect of medical treatment. Hence, body fluids provide rich sources of potential biomarkers and analysis of the body fluid proteome has become a very promising approach for discovering new biomarkers for disease [Hu et al., 2006]. Human serum and plasma are potentially the most valuable samples and are attracting an increasing interest in proteomics research [Issaq et


al., 2007]. Plasma perfuses all organs in the body and the plasma proteome has been proposed to contain basically all human proteins, although some at very low concentrations [Anderson et al., 2004]. Another especially interesting body fluid is cerebrospinal fluid (CSF). This body fluid surrounds the brain and is therefore frequently explored for biomarkers of conditions related to the central nervous system [Rohlff, 2000]. Since plasma has limited or no contact with the ventricular space, analysis of CSF can provide complementary information about the central nervous system that not can be acquired from analysis of plasma samples.

The proteomics field is highly diverse with a large variety of different approaches and techniques for requiring information about proteome, including expression analysis, studies of protein localization, protein interactions and quantification of biomarkers [Falk et al., 2007]. In this thesis the main focus will be on mass spectrometry techniques for analysis of the body fluids proteome.

Mass spectrometry (MS) has today become one of the most important tools in proteomics research [Tyers and Mann, 2003]. The inventions of electrospray ionization (ESI) [Yamashita and Fenn, 1984] and matrix assisted laser desorption/ionization (MALDI) [Karas and Hillenkamp, 1988] in the eighties first made it possible to analyze macromolecules and lead to the development of new instruments with more improved mass determinations utilizing for example time-of-flight (TOF) analyzers. MS makes in possible to identify proteins and peptides in a sample. Masses can be obtained with high accuracy and compared to a protein database. Historically, the gold standard for separation of proteins in complex mixture has been two-dimensional polyacrylamide gel electrophoreses (2D-PAGE) and the technique is still a workhorse for proteomics analysis. In 2D-PAGE, proteins are separated according to isoelectric point (pI) and size, and visualized on the gel with different staining methods. Studies have shown the ability to differentiate between up to 3000 proteins [Gorg et al., 2004]. 2D gel electrophoreses can be combined with MALDI-TOF MS for identification of the separated proteins and this is today the most common method in expression proteomics. Prior to MS-analysis, the obtained proteins in a selected 2D gel spot are digested in the gel and the resulting peptides are extracted. The peptide masses can be determined with MS, giving a “peptide mass fingerprint”, and matched to theoretical masses utilizing bioinformatics tools e.g. the publically available mascot (www.matrixscience.com) or ProFound (https://prowl.rockefeller.edu/prowl-cgi/profound.exe). However, 2D gel electrophoresis is relatively labor intensive and time consuming [Falk et al., 2007]. An alternative approach is so called shotgun proteomics [MacCoss et al., 2002], where all proteins are simultaneously digested in an investigated sample. The peptides are then separated by liquid-based separation and subsequently detected by tandem mass spectrometry MS/MS. It has been demonstrated that the shotgun proteomics approach can be used for exploration of human body fluids [Ramström et al., 2003; Nilsson et al., 2004; Ramström et al., 2005].

http://www.matrixscience/


One of the major challenges when analyzing the body fluids proteome is the high level of complexity of the samples. One of the first choices of preferred sample for analysis is as mentioned above, human plasma. However, human plasma has an immense dynamic range of the concentrations of the proteins present in the sample, varying at least from pg/ml to mg/ml. The most interesting biomarkers might unfortunately be present at very low concentration. Analysis is further complicated by the high total protein content, plasma being extremely protein-rich and containing over 60 mg proteins per milliliter [Anderson and Anderson, 2002]. Other body fluids have lower protein content, for example is the total protein content in CSF around 0.35 mg/ml, which is approximately 200 times lower than in plasma [Reiber, 2001]. A variety of different methods have been applied for fractionation and separation of the proteins prior to the analysis, in order to achieve higher sensitivity. Examples of separation strategies are methods based on differences in hydrophobicity, isoelectric point and size [Falk et al., 2007]. One of the largest problems is the predominance of several high abundant proteins. In plasma, the most abundant protein, serum albumin (HSA), constitutes 55% of the total protein content in plasma [Anderson and Anderson, 2002] and the 22 most abundant proteins constitutes more that 99% of the total protein [Tirumalai et al., 2003]. Selective removal of these high abundant components is often a good alternative to more general fractionation methods. Different strategies for depletion of high abundant proteins can be considered including dye-based methods and affinity columns [Zolotarjova et al., 2005]. For example, the most well-known strategies for HSA-depletion are based on Cibracron-Blue Sepharose media or antibodies. Today, there are several commercially availed methods enabling removal of several high abundant plasma proteins simultaneously [Gorg et al., 2004; Björhall et al., 2005]. Depletion of HSA in combination with one or several other abundant proteins in plasma has proved to considerably enhance the resolution for proteomics analysis using both electrophoresis and LC-MS-based techniques [Björhall et al., 2005; Cho et al., 2005; Echan et al., 2005; Ramström et al., 2005; Gong et al., 2006]. Some of the desirable features of affinity-based methods are the high specificity, to minimize removal of non-targeted proteins, and the high stability to enable re-use and reproducibility. Antibodies are the most commonly used affinity ligands for creation of capture media for depletion purposes. However, antibodies have several disadvantages e.g. stability problems and high manufacturing costs. The studies presented in this thesis, instead utilizes the affinity ligands Affibody molecules as capture ligands for depletion of human samples for applications in proteomics research.



PRESENT INVESTIGATION

In this section of the thesis, three main projects will be presented, based on five original articles. A summary of the results will be given, and envisioned future developments and applications are discussed. All three projects aim to develop new affinity proteins targeting human proteins. However, the future applications for the new affinity ligands range from being tools in proteomics research and protein structure determinations, to being potential future therapeutic agents for treatment of disease or imaging agents for in vivo diagnostics. The protein A-derived Affibody scaffold has been employed for developing new affinity proteins and phage display technology has been used for selecting Affibody molecules from a combinatorial protein library.

Objectives:

• To develop an Affibody molecule binding to human transferrin that can be used for depletion of the high abundant protein from human samples for proteomics research.

• To select and characterize Affibody ligands targeting the Alzheimer’s amyloid beta

peptides. Future prospect for the affinity ligands is for therapeutic applications in treatment of Alzheimer’s disease and for structural studies of the amyloid beta peptides.

• To generate Affibody molecules binding the human IL-2 receptor alpha (CD25),

primarily for medical imaging of inflammation but also for possible therapeutic treatment of disease conditions with CD25 overexpression.


6. Affibody mediated depletion for proteomics research

In proteomic research, one of the major efforts is identification of new biomarkers in body fluids, such as plasma and cerebrospinal fluid. However, as described in chapter 5, analysis of body fluids is complicated by the presence of a rather small number of high abundant proteins, constituting the major fraction of the total protein content. Removal of the most highly abundant proteins would significantly increase the sensitivity in the identification of low abundant proteins that are present in far lower concentrations. One of the most abundant proteins in plasma and CSF is transferrin. Serum transferrin is a member of the ironbinding metalloprotein group and the 80 kDa glycoprotein consists of two homologous loops with the capacity of binding one Fe3+ ion each. Furthermore, since transferrin is responsible for iron transportation in the circulation, it is consequently present in high concentrations. Removal of transferrin from human samples could thus potentially facilitate proteomics analysis.

In this thesis a novel Affibody molecule was selected targeting human transferrin (I). Furthermore, the isolated novel Affibody molecule was employed together with other affinity ligands for depletion of plasma and CSF samples for proteomics analysis (I, II).

6.1 Selection of an Affibody ligand binding to human transferrin (I)

Affibody molecules binding to human transferrin were selected by phage display technology. Biotinylated human iron-saturated transferrin (holotransferrin) was used as target in the selection and bound phage was captured by streptavidin-coated paramagnetic beads. The stringency in the selection was increased for each round of selection by increasing the number of washes and by increasing the amount of detergent in the washing buffer. The selection conditions are summarized in table 6.1. Individual clones were screened using an ABD-based Affibody screening ELISA (ABAS-ELISA) for their transferrin binding activity after the third and fourth selection round (Fig. 6.1). In the ABAS-ELISA, Affibody proteins were expressed directly from the phagemid vector as fusion proteins to a streptococcal protein G-derived albumin binding domain (ABD), captured in HSA-coated microtiter wells and analyzed for binding to biotinylated transferrin. The screening revealed that 46% of the 93 analyzed clones from selection round 4 and 8% of the 279 analyzed clones from round 3 were positive for


binding to transferrin. DNA sequencing of 60 positive clones gave eleven new unique phagemid insert with one molecule being dominant and occurring 50 times while the other ten occurred once each. Moreover, all transferrin-binding clones from the fourth round turned out to be the dominating Affibody molecule Ztranf:917.

Table 6.1: Summary of phage display selection of Affibody molecules binding transferrin.

PHAGE DISPLAY SELECTION TRANSFERRIN

Target protein: Holotransferrin-biotin

Solid phase: Streptavidin paramagnetic beads

Buffer conditions:

Selection 3% TPBSB (0.1% Tween 20)*

Block 5% TPBSB (0.1% Tween 20)

Wash 3% TPBSB

Cycle Target concentration (nM) Number of washes / % Tween 20

1 100 2 / 0.1%

2 100 5 / 0.2%

3 100 7 / 0.3%

4 100 10 / 0.4% * PBS containing 3% bovine serum albumin (BSA) and 0.1 % Tween 20

Five of the isolated Affibody molecules from the transferrin selection were chosen for

further characterization, subcloned as monomeric His6 fusion proteins and expressed in E. coli. The IMAC-purified Affibody proteins were analyzed for binding to transferrin with biosensor technology in a Biacore instrument. The Biacore analysis revealed that only the dominating Affibody molecule, Ztranf:917, demonstrated significant binding to transferrin, while the other Affibody ligands showed considerably weaker binding. Hence, the transferrin-binding Affibody molecule Ztranf:917 was chosen for future studies and the other molecules were not investigated further.


Fig. 6.1. ELISA screening for binding to transferrin after four rounds of phage display selection.

6.2 Characterization of the transferrin-binding Affibody molecule (I)

The binding properties and specificity of the selected transferrin-binding Affibody molecule Ztranf:917 were initially analyzed with biosensor technology. The monomeric Affibody molecule was subjected to kinetic analysis by injecting different concentration over a transferrin-immobilized biosensor surface (Fig. 6.2A). The affinity of the Affibody molecule could be estimated to 400 nM by steady-state determination assuming one-to-one binding. Furthermore, the Affibody molecule was subcloned, expressed and purified as a head-to-tail dimer with a C-terminal cysteine ((Ztranf:917)2-cys). The introduced cysteine could be used for single-point immobilization of the Affibody molecule to a Biacore biosensor surface. The specificity of the anti-transferrin Affibody ligand was investigated by separate injections of nine high abundant human serum proteins over the Affibody surface. The transferrin-binding Affibody molecule showed a strikingly high specificity for transferrin and only low background binding to the control proteins could be observed (Fig. 6.2B).

Furthermore, the specificity was more extensively studied by dot blot analysis. In this assay, sixteen serum proteins including transferrin were applied to a nitrocellulose membrane and stained with the anti-transferrin Affibody molecule (Ztranf:917)2-cys. The Affibody ligand demonstrated very high specificity to transferrin and in principle no unspecific binding could be detected. Some low background staining was observed for IgM but it was also present on a control membrane incubated without Affibody ligand and therefore most probably caused by crossreactivity of the secondary antibodies.

The selectivity of the transferrin-binding Affibody molecule was further demonstrated by affinity chromatography. The dimeric anti-transferrin Affibody molecule (Ztranf:917)2-cys was


coupled to an affinity resin by single-point immobilization via the C-terminal cysteine. The affinity resin was packed in gravity flow columns and used for capturing transferrin from human plasma. SDS-PAGE analysis with silver straining of the eluted protein fraction revealed one single band of protein captured from the plasma and the protein was confirmed to be transferrin with Western blot analysis. Hence, the transferrin-binding Affibody molecule demonstrated very high level of selectivity and could therefore presumably be suitable for depletion of biological samples.

Fig. 6.2. Biacore binding studies. A. Kinetic analysis of the monomeric transferrin-binding Affibody molecule Ztranf:917. The Affibody molecule was injected at concentrations ranging from 12.5 nM to 800 nM over a biosensor surface with immobilized transferrin. B. Biacore specificity analysis. Human serum proteins were separately injected over a biosensor surface with transferrin-binding Affibody molecule immobilized through directed thiol-coupling. Sensorgrams are shown for the following proteins: transferrin (squares), α-2-macroglobulin, HSA, transthyretin, complement C4, IgA, IgG, hemopexin and IgM.

6.3 Affibody-mediated depletion of HSA, IgG and transferrin from plasma (I)

The use of the anti-transferrin Affibody molecule for depletion of human samples was first evaluated by depletion of transferrin in combination with Affibody-mediated depletion of HSA and IgG in human plasma. The depletion was performed in three steps, first incubating the plasma sample twice repeatedly with the anti-transferrin Affibody resin, followed by incubation of the transferrin depleted sample once with a combined anti-HSA and anti-IgG affinity resin. The anti-IgG/HSA resin was constructed by single-point immobilization via the C-terminal cysteines of dimeric Z ((Zwt)2-cys) and the protein G derived albumin binding protein (ABP-cys) to the affinity matrix. The transferrin concentration before and after depletion was determined using a commercially available transferrin quantification ELISA. It was demonstrated that 85% of the total transferrin content in the plasma sample was depleted after only two cycles of transferrin removal. The degree of depletion after one round of transferrin removal could be determined to 65% which would give an expected depletion after two rounds of 88% which was consistent with the observed value. The plasma samples were


further analyzed using SDS-PAGE to visualize the depletion efficiency of the three proteins (Fig. 6.3). The observed protein bands before and after depletion were excised and analyzed using in-gel tryptic digestion and MALDI-TOF mass spectrometry to determine their identity. The depletion of HSA and IgG was proven to be very efficient and these proteins could not be detected in the depleted sample. In the transferrin depleted sample the vast majority of transferrin was removed and consequently only a very faint band corresponding to transferrin could be detected. In conclusion, the transferrin-binding Affibody molecule clearly showed potential as a depletion reagent for human samples.

Fig. 6.3. SDS-PAGE analysis after Affibody-mediated depletion of HSA, IgG, and transferrin from human samples using affinity resins with thiol-coupled with anti-HSA Affibody molecule (ABP-cys), anti-IgG Affibody molecule ((Zwt)2-cys), and anti-transferrin Affibody molecule ((Ztranf:917)2-cys). The identities of high abundant protein bands were determined by in gel digestion and MALDI-TOF mass spectrometry. Arrowheads indicate transferrin. A. Depletion of human plasma. Lane 1, undepleted plasma. Lane 2, HSA and IgG depleted plasma. Lane 3, HSA, IgG, and transferrin depleted plasma. Protein band were identified as: I. α-2-macroglobulin; II. transferrin; III. HSA; IV. IgG; V. haptoglobulin; VI. IgG; VII. complement C3; VIII. α-1-antitrypsin; IX. fibrinogen; X. apolipoprotein A1. B. Depletion of human CSF. Lane 1, undepleted CSF. Lane 2, HSA depleted CSF. Lane 3, HSA, IgG and transferrin depleted CSF. Protein band were identified as: I. transferrin; II. HSA; III. IgG; IV. IgG V. transthyretin; VI. cystatin C; VII. β-2-microglobulin; VIII. prostaglandin-H2 D-isomerase; IX. apolipoprotein A1.


6.4 Depletion of high abundant proteins from CSF for proteomics analysis (I, II)

A series of CSF depletion experiments were performed to further evaluate the transferrin-binding Affibody molecule for depletion of human samples. In an initial depletion experiment, transferrin was depleted together with HSA and IgG. In this experiment, HSA was first depleted from the CSF sample and subsequently transferrin and IgG were captured using a combined affinity resin. The depleted samples were analyzed using SDS-PAGE and the transferrin concentration before and after depletion was determined using the previously mentioned quantification ELISA (Fig 6.3). High transferrin depletion efficiency was achieved and up to 78% of the total amount of transferrin was found to be removed with only one round of depletion.

Encouraged by these experiments, the depletion strategy was enlarged to comprise in total five high abundant CSF proteins: HSA, IgG, transferrin, cystatin C and transthyretin. For the removal of transferrin, IgG, and HSA, affinity resins coupled with (Ztranf:917)2-cys, for (Zwt)2-cys and APB-cys were utilized as described before. Capture of transthyretin was achieved using a phage display selected dimeric Affibody molecule with a C-terminal cysteine available from Affibody AB. It was a single-point-immobilized to a resin via the C-terminal cysteine. Unfortunately, no Affibody molecule was available for cystatin C. Instead, polyclonal antibodies were used to create an anti-cystatin C affinity resin. Three different depletion columns were developed for the CSF depletion, giving a three step depletion procedure. First the CSF samples were applied to an anti-HSA column, thereafter to a column for combined depletion of HSA, IgG, transferrin and transthyretin, and in the third and last step cystatin C was removed using the antibody column. The depletion efficiencies were assessed with SDS-PAGE analysis and by commercially available ELISA quantification kits. The deviations between three consecutively depleted samples were minor for the Affibody mediated depletions, indicating highly reproducible performance. However, the antibody column for cystatin C depletion showed somewhat decreased capacity between two following samples, probably caused by the influence of regeneration of the column. The proportions of depleted proteins were estimated to be 99%, 95%, 74%, 92% and 83% for HSA, IgG, transferrin, transthyretin and cystatin C, respectively. Furthermore, shotgun proteomics based on off-line LC-MALDI MS/MS was used for protein identification in native as well as depleted CSF and the achieved data was compared. Enhanced identification of lower abundant components was observed in the depleted fraction, in terms of more detected peptides per proteins. Hence, these results indicate that the designed affinity columns should have potential for depletion of


samples for proteomics analysis aiming to find and characterize new biomarkers in cerebrospinal fluid.

6.5 Future aspects The first results using Affibody molecules for depletion of human samples clearly suggests a potential for the development of Affibody-based resins for the removal of high abundant proteins for proteomics analysis. It would be interesting to further evaluate the designed affinity columns used in the experiments presented in this thesis using different proteomics analysis approaches. Furthermore, the efficiency of the developed affinity resins could most probably be further improved by optimizing depletion conditions. It could also be considered to develop additional Affibody molecules targeting several other known high abundant proteins in plasma and CSF and create combined affinity resins for removal of a larger number of proteins to further improve the sensitivity of analysis.


7. Affibody molecules binding amyloid beta peptides (III, IV)

Amyloid beta (Aβ) peptides are suggested to be the causative agents in Alzheimer’s disease and their potency to oligomerize and form amyloid fibrils in the brain is one of the key events of the disease (see box 7.1). Affibody molecules targeting Aβ could potentially be used in different therapeutic approaches for treatment of Alzheimer’s disease, as well as for gaining increased knowledge about Aβ and the oligomerizaton process. One of the potential therapeutic uses of the Affibody molecules is for depletion of non-aggregated amyloid beta from the circulation. It has been demonstrated that elimination of soluble Aβ from the circulation could alter the equilibrium between free Aβ in the circulation and oligomerized toxic Aβ forms in the central nervous system, leading to reduced Aβ burden in the brain. According to the so called peripheral sink theory, this could possibly be accomplished by peripheral administration of an affinity protein that by targeting free Aβ changes the transportation and dynamic equilibrium of Aβ over the blood brain barrier [DeMattos et al., 2001]. Another way for depletion of Aβ from the circulation could be by extracorporeal removal of soluble non-aggregated Aβ. This would obviously require an apheresis device with an affinity medium specifically capturing free Aβ peptides. A different therapeutic approach for Alzheimer’s disease could be to inhibit aggregation of Aβ in the brain by targeting soluble forms and eliminating toxic oligomers by blocking oligomerization. The common denominator for the therapeutic approaches suggested here is that the therapeutic agent should target soluble forms of Aβ. Consequently, our main aim when developing Affibody ligands binding Aβ was to isolate binders that would target monomeric or oligomeric Aβ rather that aggregated fibrillar Aβ.

The work in this thesis involves selection and characterization of new Affibody molecules binding to Aβ (III) as well as the use of these molecules in NMR structure determinations of monomeric Aβ in solution (IV).


Box 7.1 | AMYLOID BETA AND ALZHEIMER’S DISEASE Alzheimer’s disease (AD) is the most common cause of dementia among elderly. It is a chronic and fatal neurodegenerative disorder with devastating impact on the health of the patients, typically involving loss of memory and other cognitive functions [Cummings, 2004]. The neuropathological hallmarks of AD are the presence of extracellular deposition of the small peptide amyloid beta (Aβ) in senile plaques and intracellular aggregation of the protein tau causing neurofibrillary tangles. The disease will eventually lead to neuron degeneration and loss of synaptic function. The Aβ-protein is suggested to play a central role in AD and the proposed key event is the oligomerization of Aβ peptides and formation of long insoluble amyloid fibrils that builds up plaques in the brain. Aβ derives from the amyloid precursor protein (APP) and is cleaved of from the transmembrane bound protein in a natural process involving two proteases referred to as β- and γ-secretases. Depending on the exact cleavage by the γ-secretase, three different forms of Aβ peptide are produced with 38, 40 or 42 residues, respectively [Selkoe, 2001; Goedert and Spillantini, 2006]. The Aβ42 is the most pathogenic variant, far more prone to oligomerize and form fibrils than the more abundantly produced shorter peptide Aβ40. The known genetic mutations, giving prevalence for familiar AD with early onset, dominantly result in increased production of Aβ42, evidently supporting the hypothesis of amyloid beta peptides as the major causative agent in AD [Selkoe, 2004; Findeis, 2007]. Furthermore, today, accumulating data suggests that it is small soluble oligomers of amyloid beta rather than fibrils that are toxic to neurons and cause synaptic dysfunction [Haass and Selkoe, 2007; Walsh and Selkoe, 2007]. A large effort is currently made for understanding the structural mechanisms for oligomerization of Aβ and formation of amyloid fibrils with the hope that it will increase our understanding of AD.

Simplified schematic overview of the generation of Aβ peptides from APP.

Alzheimer’s disease has been known for over 100 years and every year 5 million new patients gets affected world wide, but the available treatments still have very modest results [Roberson and Mucke, 2006]. Today, new promising therapies are being developed focusing on reducing the Aβ production or eliminating the harmful peptides. Strategies for reducing production of Aβ42 involve targeting the γ-secretase. However, γ-secretase normally cleaves other substrates critical for the nervous system and inhibition of the secretase must be selective for APP in order to have real potential as a drug. Recently, immunotherapy against Aβ has demonstrated very promising results. Active immunization with Aβ peptides appeared to reduce amyloid deposits in patients and improve cognitive function. However, clinical trials were halted because of a significant side effect of meningoencephalitis in a subset of the patients. Another approach is using passive immunization by administration of a therapeutic antibody [Roberson and Mucke, 2006; Findeis, 2007]. Peripheral administration of anti-Aβ antibodies have shown very positive results in a transgenic mouse model [DeMattos et al., 2001] and there is now ongoing clinical trials in phase II with so far no reports of side effects [Roberson and Mucke, 2006].


7.1 Phage display selection of Affibody molecules binding Aβ (III)

Aβ-specific Affibody molecules were selected by phage display technology using biotinylated Aβ40 peptide as target protein and streptavidin-coated paramagnetic beads for in-solution capture of phage-target complexes. Since the Aβ40 variant of amyloid beta has a considerably slower aggregation rate than the 42 residue peptide, the use of Aβ40 as target protein should favor selection of binders toward soluble Aβ. Furthermore, the peptide used in this selection contained one biotin molecule per Aβ peptide, covalently coupled to the N-terminal, giving a uniform target protein. To increase the stringency of the selection, the target concentration was decreased and the number of washes increased for each round of selection. The selection conditions are summarized in table 7.1. Individual clones were screened for Aβ-binding capability after four rounds of selection using a phage ELISA setup. The screening revealed that approximately 90% of the 384 randomly picked clones seemed to bind Aβ40. DNA sequencing of 192 positive clones showed that 44 new Affibody molecules had been isolated, occurring between 1 to 38 times. Sixteen of the Affibody clones were chosen for further characterization based on their degree of occurrence and sequence similarities (Fig. 7.1).

Table 7.1: Summary of phage display conditions in selection of Affibody molecules binding Aβ.

PHAGE DISPLAY SELECTION Aβ

Target protein: Aβ40-biotin

Solid phase: Streptavidin paramagnetic beads

Buffer conditions:



Wash 3% TPBSB (0.05% Tween 20)

Cycle Target concentration (nM) Number of washes

1 50 2

2 10 4

3 2 8

4 0.4 11 * PBS containing 3% bovine serum albumin (BSA) and 0.05 % Tween 20


Fig. 7.1. Amino acid sequence corresponding to wild-type Z aligned to amino acid sequences of 16 different Affibody variants selected against the Aβ peptide. The 13 randomized amino acids positions are presented and horizontal bars indicate amino acid identities. The three α-helices in the Z scaffold are boxed. The figures on the right represent the number of times for each variant occurred upon sequencing of 192 clones.

7.2 Biosensor analysis of selected binders (III)

The isolated sixteen Affibody molecules from the Aβ selection were initially expressed directly from the phagemid vector as fusion protein to an albumin binding domain (ABD) and purified using HSA-mediated affinity chromatography. Binding to amyloid beta was investigated by biosensor analysis using a Biacore 2000 instrument. The purified Affibody proteins were separately injected over biosensor surfaces with immobilized Aβ40 and Aβ42. All sixteen Affibody molecules demonstrated binding to both Aβ peptides. Furthermore, the Affibody molecules showed no binding to control proteins. The two most promising Affibody molecules as suggested by binding properties and solubility observations, ZAβ1 and ZAβ3, were subjected to further Biacore analysis. The Affibody proteins were subcloned and expressed as monomers with a hexahistidine tag. Different concentrations of purified Affibody protein were injected over a Aβ40 surface, created by immobilization of biotinylated Aβ40 on a streptavidin chip. Taking advantage of the biotin-streptavidin interaction would give a directed coupling of the Aβ peptide. In this experimental setup the apparent affinities of the Aβ-binding Affibody ligands, ZAβ1 and ZAβ3, could be estimated to 260 nM and 320 nM, respectively. However, the two Affibody molecules both contained an internal cysteine and in addition it could be possible that the small Aβ peptides might not behave in the same way immobilized as in solution and that several different oligomeric species of Aβ could be present on the chip.


Hence, biosensor analysis might not be the best choice of method of choice for an exact determination of the kinetic constants of this particular interaction.

7.3 Construction of head-to-tail dimeric and cysteine to serine mutated Affibody ligands (III)

All the selected Affibody molecules had a conserved internal cysteine at residue 28. If the Affibody molecules were going to be used in an affinity resin this could possible lead to suboptimal capture of the target molecule due to ligand multimerization. Therefore, new Affibody ligands were constructed by substituting the cysteine with a serine in ZAβ1 and ZAβ3, giving the Affibody molecules ZAβ1S and ZAβ3S. Both monomeric and head-to-tail dimeric constructs were created with an N-terminal His6-tag. Furthermore, dimeric molecules were constructed with an introduced C-terminal cysteine for directed labeling. The proteins were intracellularly expressed in E. coli and purified using IMAC.

7.4 Affibody-mediated capture of Aβ from spiked serum or plasma (III)

To investigate the selectivity of the Aβ-binding Affibody molecules, their capability to capture amyloid beta peptides from spiked E. coli lysate and human serum and plasma was investigated. Head-to-tail dimers of the two best Affibody molecules, both the original variants ((ZAβ1)2 and (ZAβ3)2) and the new cysteine to serine mutated molecules ((ZAβ1S)2 and (ZAβ3S)2), were coupled to affinity resins. Aβ-peptides were captured from 1 ml E. coli lysate, human plasma or human serum, spiked with 100 μg/ml Aβ42. The eluted fractions were analyzed with SDS-PAGE demonstrating that the Affibody ligands were able to efficiently and selectively capture Aβ from the complex samples (Fig. 7.2). A column with no coupled Affibody molecule or an irrelevant Affibody molecule showed no binding to Aβ. No band in the same molecular range as Aβ was seen in capture experiments using unspiked samples. Some higher molecular size bands were observed in all eluted fractions from plasma and serum samples, also when using an empty affinity column, suggesting that they represent high abundant proteins unspecifically interacting with the affinity resin. As expected, no unspecific bands were observed when analyzing capture from spiked E. coli lysate.

Both the original Affibody ligands and the cysteine mutated variants performed equally well in the capture experiments. Somewhat harsher elution conditions were necessary to use for the original molecules, indicating higher affinity binding. Thus, the mutated Affibody


molecules might be considered better suited as capture agents on affinity resins, giving a more convenient regeneration of the resin. Furthermore, the Cys-to-Ser mutated variants would allow directed coupling through the introduced C-terminal cysteine to the affinity resin. The main purpose with this experiment was to demonstrate the selectivity of the affinity ligands and explore the thought of using the Affibody molecules in an affinity resin for depletion of harmful Aβ-peptides from the circulation in an apheresis therapeutic approach for Alzheimer’s disease. However, in a real apheresis situation the Aβ concentrations would naturally be considerably lower and a validated medical device with optimally immobilized affinity proteins would be necessary.

Fig. 7.2. SDS-PAGE analysis of protein fractions resulting from the capture of Aβ peptides from human serum spiked with 100 μg/ml Aβ42 using an affinity chromatography column coupled with the Aβ binding Affibody molecule His6-(ZAβ3S)2. Arrow indicates the molecular size of monomeric Aβ (4.5 kDa).

7.5 Dimeric Affibody molecules bind to non-aggregated Aβ (III)

The aim of the phage display selection was to isolate Affibody ligands that would recognize monomeric and low molecular weight oligomeric Aβ. In order to study how aggregation of Aβ would affect the binding of the Affibody molecules, a series of aggregation studies were performed. Aβ42 peptide was treated with solvents, according to a previously described protocol [Stine et al., 2003] in order to make it “as monomeric as possible” and thereafter allowed to oligomerize at 4°C. Samples were collected at different timepoints and analyzed using size exclusion chromatography, Western blot and dot blot assays (Fig 7.3).


Fig. 7.3. Analysis of aggregated Aβ42 using Western blot, dot blot and size exclusion chromatography (SEC). Aβ42 was treated with HFIP (1,1,1,3,3,3-hexa-fluoro-2-propanol) and lyophilized in order to make the peptide as monomeric as possible. After dissolving, the peptide was allowed to aggregate at 4°C and samples were collected at different time points. Western blot analysis (A) of unheated samples with the mAb 6E10, binding equally to all forms of Aβ, was used for visualizing the aggregation. Dot blot analysis (B) of aggregated Aβ42 was applied for comparing the Aβ-binding Affibody molecule His6-(ZAβ3S)2-cys with the mAb 6E10. SEC was used for analysis of Aβ42 aggregated 6 h 4°C with a Superdex 75 column (C) and a Superdex peptide column (D) and the result was compared to a protein standard (top panels). The two Aβ peaks from the Superdex peptide column were collected and applied to a nitrocellulose membrane and analyzed with the Affibody molecule His6-(ZAβ3S)2-cys and the mAb 6E10 (E).

When analyzing the capability of the Affibody molecules to bind the aggregated

peptides in a dot blot, the Affibody molecules seemed not to bind after a certain time of aggregation, suggesting that the Affibody ligand were not able to recognize more aggregated Aβ species. A clear shift towards larger insoluble forms of amyloid beta could be observed in Western blotting by detection with a monoclonal antibody after 24 of incubation compared to


4 h or at the start of the incubation. However, Western blotting will not give a true picture of the oligomeric composition of the samples due to that the SDS-PAGE separation only reveal SDS-stable forms of Aβ. To give more accurate information about oligomeric forms present, the aggregated samples were further analyzed using size exclusion chromatography (SEC). Two different columns designed for different size ranges were applied and the results from both columns showed that after 6 h of aggregation the samples contains one fraction of very large aggregated Aβ and one fraction of soluble non-aggregated Aβ, presumably Aβ monomers or dimers. These two fractions were collected and immediately applied to a nitrocellulose membrane and binding of the Affibody molecules was studied. The analysis revealed that the Affibody molecules recognized Aβ in the fraction of non-aggregated peptide while none or very low binding could be observed for the fraction of larger aggregated Aβ species. For comparison, two different monoclonal antibodies known to recognize all forms of amyloid beta, bound without problem to both Aβ fractions. Hence, the Aβ-binding Affibody molecules were demonstrated to preferentially recognize non-aggregated Aβ.

In the phage display selection of Affibody molecules targeting Aβ it seems to be favorable for the selected molecules to have an internal cysteine in residue 28, proposed by the fact that this position was conserved in all selected molecules. However, as described in chapter 7.3, the cysteine was substituted by a serine in the two best binders in order to create ligands more suitable for affinity chromatography. When analyzing the new mutated versions, ZAβ1S and ZAβ3S, for their binding to Aβ in biosensor analysis it was found that the binding of the Cys-to-Ser mutants to Aβ was considerably weaker than for the original ligands, ZAβ1 and ZAβ3. Interestingly, the overall binding strength seemed to be inpart restored when creating head-to-tail dimers of the mutated molecules ((ZAβ1S)2 and (ZAβ3S)2) (Fig. 7.4). The significant difference between monomers and dimers of ZAβS could not only be explained by avidity effects. Rather, this suggested that disulfide-linked Affibody dimers were indeed selected in the phage display procedure and that two Affibody molecules in this way contribute to the high affinity binding to the Aβ-peptide. Furthermore, it is interesting to notice that the cysteine are positioned in residue 28, in the flexible loop between helix one and two, giving a good possibility for both Affibody molecules to target the peptide simultaneously.

In conclusion, these two separate experiments together suggested that the Affibody molecules bound as dimers, either formed by a cysteine bridge or through head-to-tail constructs, to non-aggregated Aβ-peptide. However, at this point it was not clear how this interaction could appear, since that would imply that the recruited binding surface of this Affibody molecule should generated two separate interactions with the small Aβ-peptide.


Fig. 7.4. Biacore binding studies of the second generation cysteine to serine mutated Aβ-binder, ZAβS, as monomer and dimer compared to the original monomeric binder, ZAβ. The sensorgrams were obtained after injection of 5 μM His6-ZAβ3 , His6-ZAβ3S, and His6-(ZAβ3S)2 over a biotin- Aβ40 coupled streptavidin biosensor surface.

7.6 The Affibody molecules bind to an Aβ-epitope that enables inhibition of aggregation (III, IV)

The initial studies of the Affibody molecule’s binding site were performed on membrane-immobilized 10-mer peptides covering the residues 14-42 of the Aβ-peptide, each peptide with nine amino acids overlap to the next peptide. It was found that the Affibody molecules predominantly bound to peptides representing amino acid residues 31-34 in the Aβ-peptide. A significantly weaker interaction, easily confused with unspecific binding, was also noticed with the peptides with the common amino acids 19-24. Interestingly, the C-terminal of the Aβ-peptide has been suggested to be important for the dimerisation and oligomerization of Aβ. It could therefore be speculated that the Affibody molecules binding to aa 31-34 might to some extent have the capacity to influence the aggregation of the peptide.

Hence, studies were performed using thioflavin T fluorescence that visualizes amyloid fibrils for monitoring Aβ40 fibrillation with and without the presence of Affibody molecules. Interestingly, it was found that the Affibody molecules were indeed able to inhibit aggregation of the Aβ-peptide. The inhibition was stoichiometric in the sense that two times higher concentration of Affibody molecules compared to Aβ concentration was required for complete inhibition, supporting previous results which suggested that dimers of the Affibody molecules bind to monomers of Aβ. Furthermore, isothermal titration calorimetry (ITC) determination revealed that the disulfide-bridge dimer ZAβ3 bound to monomeric Aβ40 with an affinity of 17 nM. This affinity is significantly higher that what could be estimated for the


head-to-tail dimers (III), and obviously the interaction with the Aβ-peptides were much favored for the phage selected disulfide-bridge dimers.

7.7 In solution NMR structure of Aβ in complex with an Affibody molecule (IV) Nuclear magnetic resonance (NMR) spectroscopy was used for determination of the

structure of the complex between Aβ40 and the disulfide-linked dimer of ZAβ3. The analysis of 15N HSQC demonstrated that two Affibody molecules bind to two distinct sites on one Aβ40 peptide. Moreover, the binding is coupled to folding of both the Aβ40 and the Affibody molecule, as indicated by the greatly improved resonance dispersion in HSQC spectra upon complex formation. The high-resolution structure of the complex reveals that it consists of four-stranded anti-parallel β-sheet and four α-helices (Fig. 7.5). The conformation of Aβ40 is a β-hairpin in which Aβ residues 17-23 and 30-36 build up the central strands of the β-sheet. Both faces of the Aβ-hairpin are buried within a large hydrophobic tunnel-like cavity formed by the ZAβ3 dimer. In the two ZAβ3 molecules, residues 15-18, part of helix 1 in the originating Z domain, forms β-strands interacting with the Aβ40 molecule’s residues 20-23 and 33-36. The unfolding of the original helix 1 opens up a hydrophobic cleft exposing the core of the ZAβ3 dimer. The results provide the first high-resolution structure of Aβ in β conformation and the position of the secondary structure elements resemble structures observed in fibrillar Aβ. The Affibody molecule stabilizes the formed β-sheet by extending it intermolecularly and thus seems to capture Aβ in an amyloid-like but monomeric conformation. Consequently, the Affibody molecules might in this way inhibit Aβ fibrillation. It can be speculated that the observed β-hairpin conformation of Aβ is an important intermediate in oligomerization and fibrillation.

Furthermore, this is the first interaction demonstrated for an Affibody molecule when it is not retaining its typical triple-helical bundle structure. Still, the interaction seems to be highly specific (III) and could thus just indicate a further degree of flexibility of the Affibody scaffold as such, in this particular case by unfolding part of helix 1 in order to generate the dimeric variant with ability for high-affinity binding to Aβ-peptides.


Fig. 7.5. High resolution NMR structure of the ZAβ3:Aβ40 complex. Ribbon drawings illustrating topologies of the original Z domain scaffold (A) and the ZAβ3:Aβ40 complex (B). C. Polar contacts in the ZAβ3:Aβ40 complex. Experimentally validated hydrogen bonds (green), hydrogen bonds observed in >50% of the stimulated annealing structures (yellow), and salt bridges (red) are displayed. Residues of the two ZAβ3 subunits are labeled Z and Z´, respectively. D. The hydrophobic core of the complex. Nonpolar sidechains with water exposure <33% are displayed as orange sticks (for Aβ40) or white sticks and spheres (for ZAβ3). Disulfide bond is shown in yellow. (Reproduced with permission from Hoyer et al., 2008.)

7.8 Ongoing studies The positive results from the Affibody-mediated inhibition of Aβ aggregation, together with the increased knowledge of the quite remarkable binding properties of the dimeric Aβ-binding Affibody molecules have lead to continued studies. The Affibody molecules are currently investigated for their capability to inhibit Aβ fibrillation in vivo in a Drosophila study. It would be of interest to find out the Affibody molecules potential as therapeutic agents in treatment of Alzheimer’s disease and this might be the first step in that direction. Moreover, co-expression of the Affibody molecule ZAβ3 and amyloid beta peptides in E. coli is under investigation and could prove to be a very useful tool for production of amyloid beta peptides with high yields.


8. Generation of Affibody molecules targeting the IL-2 receptor alpha (V)

The interleukin 2 (IL-2) receptor alpha, also denoted CD25, has an important role in the regulation of cellular immunity and is normally almost exclusively expressed on activated T-cells, as described in box 8.1. The very low expression of the receptor on resting immune cells makes it an interesting target for targeted diagnosis and therapy. CD25 has been found to be overexpressed on T-cells involved in autoimmune disorders, abnormal T-cells in leukemia and T-cells participating in allograft rejections. An Affibody molecule targeting CD25 could possibly be used as a therapeutic agent for these conditions. The Affibody molecule could either work directly by blocking the interaction of IL-2 to its receptor or be used for delivering effector groups such as toxins or radionuclides. The Affibody molecules could also possibly be used in diagnostics applications to detect soluble CD25 in the circulation for exploring the potential for correlating serum levels of CD25 with disease activity in autoimmune conditions. Furthermore, Affibody molecules have recently demonstrated to be suitable as agents for in vivo imaging. Hence, the primary aim of the project was to develop an Affibody molecule that could be utilized in medical imaging of CD25 positive cells. Targeting CD25 in medical imaging could presumably be used for visualizing inflammation or infiltration of active immune cells in solid tumors. It is known that active CD25-expressing T-cells are of importance for the way the body recognize and battle abnormal tumor cells. Imaging of active immune cells in tumors could be used for better understanding the impact of T-cells in cancer and for clinical diagnosis, possibly giving important information about progression and therapy responses.

In this thesis, selection and initial characterization of novel Affibody molecules targeting human CD25 on active T-cells are presented (V).


Box 8.1 | IL-2 RECEPTOR ALPHA

Schematic picture of the IL-2 receptor complex.

Interleukin 2 (IL-2) is an immunoregulatory cytokine that play a major role in T-cell activation and the cellular immune response. When a T-cells gets activated after interaction with an antigen presenting cell it immediately starts to express IL-2 and its corresponding alpha receptor. The following autocrine interaction of IL-2 with its receptor complex results in the proliferation and differentiation of T-cells, B-cells and natural killer (NK) cells [Gaffen, 2001]. The IL-2 receptor complex is a heterotrimer composed of the alpha subunit (IL-2Rα), beta subunit (IL-2Rβ), and the common cytokine gamma subunit (γc) [Wang et al., 2005]. The 55 kDa α-chain, also referred to as CD25 or the Tac antigen, is specific for IL-2 [Rickert et al., 2005]. Binding of IL-2 to CD25 leads to the subsequent recruitment of the alpha and gamma chain, initiating a complex cascade of signaling events. Resting T-cells do not express CD25 and less that 5% of normal peripheral blood cells express the receptor [Morris and Waldmann, 2000]. Thus, CD25 is an interesting marker for studying activated immune cells. CD25 can in addition be used for defining the regulatory T-cells population (CD4+ CD25+ FOXP+ cells), suggested to contribute in suppressing autoimmune responses and maintaining a balance in the immune system [Frey and Brauer, 2006]. A TARGET FOR THERAPEUTICS AND IMAGING The IL-2 receptor alpha (CD25) has been found to be significantly overexpressed on cells involved in a number of inflammatory autoimmune diseases, organ transplant rejections and in different T-cell malignancies [Morris and Waldmann, 2000; Waldmann, 2007b]. These findings, together with the fact that CD25 is to a very low extent expressed on resting normal cells makes CD25 an exceptionally good target for immunotherapy. There are today two monoclonal antibodies targeting CD25 for therapeutic purposes on the market, the first generation chimeric antibody, basiliximab, and the second generation humanized version, daclizumab. They function by identifying CD25 and blocking the interaction with the ligand IL-2. Daclizumab was approved by the FDA in 1997, as the third monoclonal antibody and the first humanized antibody. It is approved for therapeutic treatment to prevent organ rejection in kidney transplantations but has recently demonstrated promising results in treatment of T-cell leukemia and several autoimmune diseases such as T-cell mediated uveitis and multiple sclerosis [Brekke and Sandlie, 2003; Waldmann, 2007a]. Apart from being a promising therapeutic target, CD25 could also be considered in the field of medical imaging. In vivo targeting of CD25 could potentially be used for visualization of inflammation and for exploring infiltration of active immune cells in tumors.


8.1 Selection of Affibody molecules binding the IL-2 receptor alpha (V)

Affibody molecules recognizing the human IL-2 receptor alpha (CD25) were selected by phage display selection technology using the target protein fused to the Fc part of human IgG1 (CD25-Fc). Streptavidin coated paramagnetic beads with captured biotinylated (Zwt)2 were used as solid support to capture phage bound to the target protein. The applied (Zwt)2 molecule is a head-to-tail dimer of the engineered IgG-binding protein A domain Z, site-specifically biotinylated via an introduced C-terminal cysteine. By taking advantage of the interaction between Z and Fc, biotinylation of the target protein could be avoided, thus keeping the protein as native as possible without risking altering of important sites by unspecific biotinylation. The stringency of the selection was increased for each round by decreasing the amount of target protein, increasing the number of washes and the detergent concentration in the washing buffer. Furthermore, before every round of selection a negative selection towards human Fc was performed to eliminate binding to the Fc part of the target fusion protein. The selection conditions are summarized in table 8.1. Monitoring the phage titers during the selection procedure demonstrated that the percentage eluted phage compared to phage put into the selection increased as expected for each round of selection, indication an amplification of phage binding to the target protein.

Table 8.1: Summary of phage display conditions in selection of Affibody molecules binding CD25.

PHAGE DISPLAY SELECTION CD25

Target protein: CD25-Fc

Solid phase: (Zwt)2-biotin coated streptavidin paramagnetic beads

Buffer conditions:



Wash 3% TPBSB

Cycle Target concentration (nM) Number of washes / % Tween 20

1 100 3 / 0.1%

2 50 5 / 0.5%

3 20 7 / 0.5%

4 10 7 / 0.5% * PBS containing 3% bovine serum albumin (BSA) and 0.1 % Tween 20


Affibody proteins from individual clones were expressed and screened in an ELISA for their CD25-binding activity after the fourth round of selection (Fig. 8.1). The ELISA screening showed that approximately 40% of the clones seemed to bind CD25. Furthermore, no clones demonstrated any binding to human Fc, proving a successful negative selection strategy. Interestingly, selection using protein A beads as for capture of phage-target complex gave only 8% ELISA positive clones and a solid phase selection strategy using CD25-Fc coated ELISA wells resulted in no positive binders towards CD25 and gave only unwanted Fc-binding despite negative selection efforts.

Fig. 8.1. ELISA screening for CD25-binding activity (black bars) of Affibody clones after four rounds of phage display selection. A control screening for background binding to Fc was performed in parallel (grey bars).

Upon sequencing 101 ELISA-positive clones, 16 new unique Affibody molecules were

found occurring 1 to 56 times (Fig. 8.2). Sequence cluster analysis of the amino acid sequences of the Affibody molecules revealed both some sequence similarities and differences between the molecules and two main clusters of sequences could be observed, one group containing the most dominating clone ZCD25:2015 (occurring 56 times) and the other group containing among others the sequence ZCD25:2020 (occurring 4 times). From these two groups of molecules, five different Affibody variants were selected for further characterization (ZCD25:2015, ZCD25:2018,

ZCD25:2020, ZCD25:2021, ZCD25:2022). The Affibody molecules were subcloned and expressed as monomers with an N-terminal hexahistidine tag. An initial biosensor analysis screening of the IMAC-purified proteins revealed that four out of five analyzed Affibody molecules (ZCD25:2015, ZCD25:2018, ZCD25:2020, ZCD25:2022) demonstrated significant binding to CD25, while the fifth molecule (ZCD25:2021) showed considerably weaker binding. The two most promising CD25-binding Affibody molecules, ZCD25:2015 and ZCD25:2020, were chosen for further binding analysis.


Fig. 8.2. Affibody molecules isolated in the phage display selection against CD25. A. Amino acid sequence corresponding to wild-type Z aligned to amino acid sequences of different Affibody molecules selected against human CD25. The 13 randomized amino acid residuals are presented for the Affibody molecules and horizontal bars indicate amino acid identities. The three α-helices in the Z scaffold are boxed. The figures on the right represent the number of times each variant occurred upon DNA sequencing of 101 clones. B. Sequence clustering. The Affibody molecules were clustered using an average-link hierarchical clustering method, and the result is illustrated in a dendrogram.


8.2 Biosensor characterization of selected binders (V)

The two best CD25-binding Affibody molecules, ZCD25:2015 and ZCD25:2020, were subjected to further biosensor analysis. Firstly, the monomeric Affibody proteins were injected at different concentrations over a Biacore biosensor surface with immobilized CD25 and the resulting sensorgrams were analyzed to determine kinetic properties assuming one-to-one binding. The dissociation equilibrium constants (KD) were estimated to be 240 nM for ZCD25:2015 and 130 nM for ZCD25:2020 by steady-state determinations. Furthermore, no difference could be observed between binding to CD25 with or without the fusion-partner Fc. In order to gain avidity effect, head-to-tail dimers of the two CD25-binding Affibody molecules were constructed, expressed as His6-tagged proteins and purified with IMAC purification. The difference in apparent affinity could clearly be visualized in biosensor analysis and the binding of the dimeric Affibody molecule seemed to be comparable to the binding of the natural ligand IL-2 to the immobilized CD25 (Fig. 8.3A).

Furthermore, dimeric Affibody molecules with an introduced C-terminal cysteine enabling site-directed coupling were constructed. The two purified Affibody proteins were site-specifically separately immobilized to biosensor surfaces via the C-terminal cysteines. This experimental setup was then utilized for studying the specificity of the Affibody ligands. Seven high abundant serum proteins and CD25, polyclonal human Fc and streptavidin were separately injected over the Affibody surfaces. Both CD25-binding Affibody molecules demonstrated very high specificity and only very low background binding could be observed for the control proteins (Fig. 8.3B). Moreover, the Affibody molecules showed high specificity towards the human variant of CD25 compared to murin CD25. The mouse variant gave approximately a 100 fold lower response in the biosensor analysis.


Fig. 8.3. Biacore binding studies of CD25-binding Affibody molecules. A. Comparison of the CD25-binding Affibody molecules ZCD25:2015 and ZCD25:2020, as monomeric and dimeric proteins, to the natural ligand IL-2. The proteins His6- ZCD25:2015, His6- ZCD25:2020, His6-(ZCD25:2015)2, His6-(ZCD25:2020)2, and IL-2 were separately injected over an amine-coupled CD25 surface at a concentration of 50 nM. B. Biacore specificity analysis. Control proteins were separately injected over a thiol-coupled anti-CD25 Affibody His6-(ZCD25:2020)2-cys surface at a concentration of 3 µg/ml. Sensorgrams are shown for the following proteins: CD25-Fc (filled squares), HSA, IgG, Fc, hemopexin, fibrinogen, IgA, complement C4 and streptavidin.

8.3 Competition of Affibody molecules with antibodies and IL-2 (V)

Biosensor analysis of competitive binding was used as a tool for epitope mapping of the two candidate binders ZCD25:2015 and ZCD25:2020 (Fig. 8.4). Firstly, competition with monoclonal antibodies was investigated by subsequently injecting CD25 and different mAbs over an Affibody surface, using a coinjection protocol that gives two subsequent injections with a short interval. If the mAb binding site was available after binding of CD25 to the Affibody surface, the mAb would be able to bind when injected in the second injection. The Affibody molecules demonstrated strong competition with the IL-2 blocking mAb 2A3 but no competition with the mAbs ON94 and M-A251, with no IL-2 blocking capacity. Secondly, competition with IL-2 was investigated by mixing equal amount of CD25 with different concentrations of IL-2 and injecting over the Affibody surface. This experiment clearly showed that the binding of CD25 to the Affibody surface was efficiently blocked by IL-2. Consequently, the Affibody molecules were found to compete with IL-2 in a dose dependent manner. The binding of IL-2 to CD25 is well characterized and of clinical importance. The Affibody molecules´ ability to block binding of IL-2 to the receptor is interesting in the context of using the Affibody molecules as therapeutic agents. The competition studies imply that the Affibody molecule should interact with a site that is overlapping with the binding sites of the therapeutic monoclonal antibodies Basiliximab and Daclizumab.


Interestingly, the two CD25-binding Affibody molecules ZCD25:2015 and ZCD25:2020 were found to compete for the same binding site despite considerable differences in amino acid sequences.

Fig. 8.4. Biacore competition studies. A. Competition between the CD25-binding Affibody molecule ZCD25:2020 and the natural ligand IL-2. Equal amount of CD25-Fc, 50 nM, was mixed with 0 nM (filled squares), 5 nM (open triangles), 50 nM (filled circles) or 500 nM (open squares) IL-2 and separately injected over a thiol-coupled anti-CD25 Affibody His6-(ZCD25:2020)2-cys surface. B. Competition between the CD25-binding Affibody molecule ZCD25:2020 and monoclonal antibodies. CD25-Fc was injected over a thiol-coupled anti-CD25 Affibody His6-(ZCD25:2020)2-cys surface, directly followed by an injection of the monoclonal antibody using the Biacore command coinject. Three monoclonal antibodies were studied: ON94 (filled circles) and MA-251 (open diamonds) with no IL-2 blocking capacity and 2A3 (open circles) binding to the Tac-epitope blocking IL-2 binding. HBS buffer (filled squares) was injected as negative control and IL-2 (open triangles) as positive control.

8.4 Affibody molecules bind to native CD25 on cells (V)

The Affibody molecules ability to recognize native CD25 expressed on the surface of human cells was investigated by fluorescence microscopy and flow cytometry. The Affibody head-to-tail dimer His6-(ZCD25:2020)2-cys was site-specifically labeled with Oregon Green® 488 via the C-terminal cysteine. The Affibody ligand was confirmed to bind to both the CD25 expressing IL-2 dependent cell line NK92 and CD25 positive primary peripheral blood mononuclear cells (CD4+, CD25+, PBMCs) isolated from healthy blood donors. Clear staining of the cells with the Oregon Green labeled dimer was demonstrated in both fluorescence microscopy and flow cytometry analysis (Fig. 8.5A). No binding to CD25 negative cells was observed. Furthermore, a clear binding of the monomeric CD25-binding Affibody molecule ZCD25:2020 was observed in flow cytometry analysis of phytohaemagglutinin (PHA) activated PMBC using detection with goat anti-Affibody antibodies and Alexa 647® conjugated anti-goat-antibodies (Fig. 8.5B). CD25 expression on the different cell types was confirmed with CD25 specific antibodies,


showing expected CD25 expression levels. An irrelevant negative control Affibody molecule showed no binding to the CD25 positive cells.

Fig. 8.5. Fluorescence microscopy and flow cytometry analysis of the CD25-binding Affibody molecules binding to native CD25 on cells. A. The human IL-2 dependent cell line NK92 and primary CD25 positive PBMC isolated from healthy blood donors were stained with dimeric Affibody molecule ((His6-ZCD25:2020)2) directly conjugated with Oregon Green 488®. CD25 negative PBMC was used as negative control. B. Flow cytometry analysis of the monomeric CD25-binding Affibody molecule His6-ZCD25:2020 binding to phytohaemagglutinin (PHA) activated PMBC using detection with goat anti-Affibody antibodies and Alexa 647® conjugated anti-goat-antibodies.


8.5 Future aspects (V) The selected Affibody molecules targeting CD25 (IL-2 receptor alpha) demonstrated significant binding to both recombinant CD25 and native CD25 expressed on cells. The Affibody molecules were found to have overlapping binding sites with the natural ligand IL-2 which would possibly enable future therapeutic applications by blocking the IL-2 interaction. Thus, it would be interesting to further evaluate the Affibody molecules potential as prospective therapeutic and medical imaging agents. A first step could be to study the functional effect of Affibody mediated IL-2 blocking in cell assays. The potential use of the Affibody ligands for medical imaging of inflammation could be investigated in vivo using a mouse model. However, an affinity maturation effort should perhaps be considered in order to gain a high affinity binder more suitable for therapeutic and medical imaging applications.


9. Concluding remarks

The studies presented in this thesis all aim to develop new Affibody molecules and explore different applications for the generated affinity proteins. In the first studies, an Affibody molecule specifically recognizing high abundant human protein transferrin was isolated using phage display technology. Depletion of high abundant protein from human body fluid samples have proved to be a valuable strategy for enhancing the sensitivity in proteomics analysis. The isolated transferrin-binding Affibody molecule was demonstrated to be highly specific with the capacity to efficiently remove transferrin from human plasma and CSF when coupled to an affinity resin. In the initial studies, the transferrin-capturing Affibody resin, in combination with resins capturing IgG and HSA gave very promising results in depletion of plasma and CSF. Furthermore, in a more extensive study, depletion of five high abundant proteins including transferrin from human CSF samples gave enhanced identification of proteins in shotgun proteomics analysis. These results clearly suggest a potential for Affibody-based resins for depletion of high abundant proteins for proteomics analyses when searching for new biomarkers.

In the second group of studies, Affibody molecules were developed with the future aim to be used for therapeutic depletion of harmful Aβ peptides involved in Alzheimer’s disease. The Aβ peptides are known to aggregate and form neural plaques in the brain of Alzheimer’s patients and lower molecular weight oligomers are found to be highly toxic to neurons. Affibody molecules binding to Aβ peptides were isolated by phage display technology and the selected affinity ligands were found to specifically bind to non-aggregated forms of Aβ. Furthermore, the Aβ-binding Affibody molecules were demonstrated to efficiently capture Aβ from spiked plasma when coupled to an affinity resin, thus showing potential for future therapeutic apheresis applications. Interestingly, the selected Affibody ligands, as cysteine-bridged dimers, were found to interact with a single Aβ. NMR spectroscopy studies revealed that the original helices one in the two Affibody molecules were unfolded upon binding, forming intermolecular β-sheets that stabilized the Aβ peptide by burying the peptide in a tunnel-like cavity and enabled a high resolution structure determination of Aβ in solution. The revealed conformation of Aβ could give suggestions for a structural mechanism for amyloid formation that possibly could shed a light on the Aβ oligomerization which is a critical step in Alzheimer’s pathology. Furthermore, the Aβ-binding Affibody molecules were found to efficiently act as stoichiometric inhibitors of Aβ fibrillation in vitro. This could possibly be employed in future therapeutic applications of the Affibody molecules for inhibiting Aβ


aggregation by blocking or eliminating soluble monomeric Aβ. However, Affibody-mediated inhibition Aβ fibrillation needs to be further investigated in an in vivo model.

The last study included in this thesis aimed to generate an Affibody molecule with an intended use for molecular imaging and therapeutic targeting of activated immune cells. The IL-2 receptor alpha (CD25) is exclusively expressed on active T-cells and has been found to be overexpressed in allograft rejections, several autoimmune diseases and T-cell malignancies. Affibody molecules targeting human CD25 were isolated by phage display using Fc-fused target protein and the selected CD25-targeting Affibody molecules were found to selectively recognize human CD25. This selection strategy avoids biotinylation of the target protein. Moreover, the Affibody ligands were found to compete for the same binding site as the natural ligand IL-2 and an IL-2 blocking monoclonal antibody. This implies that the Affibody molecules should bind to the same binding site as the monoclonal antibodies daclizumab and basiliximab, approved for therapeutic use. The generated Affibody molecules were further demonstrated to recognize native CD25 expressed on the surface of human cells. CD25-targeting Affibody molecules could thus possibly be used in future therapeutic applications by blocking the IL-2 interaction with the receptor or by delivering an effector molecule to harmful CD25 overexpressing cells. Furthermore, an Affibody molecule binding to CD25 might be used as labeling reagent for molecular imaging for visualization of infiltration of active immune cells in tumors or for monitoring of inflammatory responses. The first generation binders selected in the presented study show potential as CD25-targeting agents. Nonetheless, an affinity maturation strategy should be considered for generation of second generation high affinity binders, more suitable for therapeutic and imaging applications in order to further investigate the binders in in vivo experiments.

The different studies presented in this thesis together demonstrate a variety of applications for affinity proteins such as Affibody molecules. Moreover, the difference in binding properties and high target specificity of the isolated Affibody molecules illustrate the power of combinatorial protein engineering and selection strategies in generation of proteins with novel functions.


Acknowledgements

Tänk att det redan har gått fem år och att jag är skriver den här sidan måste betyda att jag har överlevt

och snart är färdig. Hade nästan gett upp hoppet när jag nära på injicerade mig själv med ormgift av

misstag under mina första månader eller när jag stod i kyl-labbet med mössa och vantar och renade

protein för miljonte gången för några år sen. Trots en del proteiner som vägrat samarbeta och fager som

inte vill binda, så har ändå tiden här med er alla varit fantastisk och en del ögonblick när affibaffisarna

(ursäkta, Affibody® molekylerna menar jag så klart) plötsligt binder och allt fungerar har varit näst intill

magiska.

Det finns många som har hjälpt mig på vägen och gjort den här avhandlingen möjlig som jag vill tacka:

Först, tack till Affibody AB för finansiellt stöd och för att jag har fått möjligheten att tillbringa stor del av

min doktorandtid på företaget.

Sen kanske jag borde tacka MAAP-gruppen på KI för att ni lyckades få mig att vilja forska och på något

sätt lyckades lura Stefan till att låta mig doktorera på kth. Bra jobbat!

Stefan, för att du är världens och förmodligen universums bästa handledare. Du är så otroligt positiv och

entusiastisk att du gör det helt omöjligt att inte tycka det är roligt med forskning. Även om jag ibland har

blivit lite matt när du ritat upp alla pekfigurer innan jag börjat labba, har det alltid efter ett möte med dig

känts som att jag kan klara vad som helst. Tack för att du har hjälpt till och lyckats hitta en bra balans

mellan akademi och industri i samarbetet med affi. Hoppas du har lila kalsonger på mitt försvar!

Mathias, för att du är en inspirationskälla för alla, din entusiasm och drivkraft skapar en positiv atmosfär

där allt är möjligt.

Per-Åke, för att du är Mr Affibody som har koll på allt värt och veta om Z och det mesta om alla andra

proteiner. Alltid roligt att bli stoppad av dig vid skrivaren när du har kommit på någon ny idé. Tack för all

hjälp och alla bra diskussioner!

Sophia, för all din kunskap om proteiner och ditt stöd som bihandledare. Tack också för allt jobb med

CSF depletion peket.

Tack även till alla andra PI:s i DNA-corner, ni bidrar alla till en rolig och spännande arbetsplats.


Mikaela, min ständiga partner i team affybabes. Utan dig hade den här doktorandtiden varit väldigt

mycket tråkigare och otroligt mycket svårare. Tack för tusentals affibody diskussioner och miljoner frågor

om allt. Hur ska jag klara mig ute i den riktiga världen utan dig?? Tack också för sällskap på alla kurser,

konferenser och fantastiska resor..du är den perfekta reskamraten, alltid redo med nöd-mat! Skönt också

att ha någon att dela avhandlings-stressen med..vet att du kommer göra ett superbra jobb på ditt försvar!

Stefans grupp, alla nuvarande, gamla, wannabes and hang-arounds, Stefan, Mikaela, John, Nina, Andreas,

Maria, Henrik, Johan, Basha, Julia, Sverker, Denise, Sara, Alex, Josefine. Tack för allt roligt, alla middagar,

och helger på Gotland och i Skärgården, alla galna spel och lekar..visst måste vi vara den absolut bästa

gruppen!

Exjobbarna. Sara, Josefine och Sverker, tack för att ni alla har gjort ett fantastiskt jobb trots att ni har fått

riktigt svåra projekt och en handledare som spenderar stor del av tiden på bussen mellan KTH och Affi.

Margareta, tack för alla depletion försök, pekskrivande och för din ms-expertis.

Skrivrummet på KTH, alla gamla och nya, Mikaela, Hanna, Nina, Johanna, Henrik, Cilla, Maggan

mfl..ledsen att jag ockuperat fönsterplatsen fast jag varit borta så mycket men tycker ändå att känns som

hemma i rummet! Kul att vi till slut fick in en y-kromosom också.

Tove, för allt roligt vi har gjort tillsammans! För att vi överlevde fagdisplay kursen och jag överlevde

galen shopping i NY med dig. Alla fester, skidresor, tennisspelande, och sköna semestrar med kite-surf

lektioner och kräksjuka. Säker på att det kommer bli många glas vin och snack om livet även i framtiden.

Vet att du gillar att följa dokusåpan C&C.

KTH-tjejerna, Mikaela, Tove, Emma, Cilla, Emilie, Torun, My, Esther, Malin, Sara, mfl. Tack för alla

härliga middagar, förfester, limekolor, och teatrar! Ni är alla fantastiska vänner!

I also want to thank my collaborators:

Eveline and Fredrik, thanks for all work with the CD25 Affibody. Special thanks to Eveline for your

patients with “cells that should look like dead and then hopefully start living again”.

Wolfgang and Torleif, for all the Abeta work. You have really done a great job, never thought the Abeta-

binder would turn out to be this cool.


Jag har haft turen att jobba på två arbetsplatser. När jag först började labba på Affibody tror jag att

planen var att jag skulle vara där några månader men sen blev jag visst fast i flera år och i slutändan har

jag förmodligen varit mer tid på Affibody än på KTH. Stort tack till alla på Affibody som har gjort så att

jag har känt mig som en del av företaget! Lite extra tack till:

Lars A, för du har gett mig möjligheten att jobba på Affibody gett mig erfarenhet av den riktiga världen

ute i industrin. Tack för alla roliga projekt du har hittat åt mig och för att du alltid har haft det

akademiska tänket så att samarbetet har blivit så bra som möjligt.

AMG-gruppen, Elin, Tove, Malin, Andreas, Olof, Anna, Anders, Susanne, Sverker, Mikaela och ex-

jobbare. Tack för massa bra selektionskunskap, trevliga grupp-aktiviteter och för att ni har gjort så att jag

har känt mig som en självklar del av gruppen.

Andreas. För alla samarbeten, fag och biacore hjälp! Vi kommer förmodligen att få Alzheimers

tillsammans efter alla Abeta labbar. Tack för att du har hållit mig alert på labbet med vassa kommentarer

och sett till att jag inte tror att kvinnor på något sätt är lika smarta som män. Tack också för dina

fantastiska quickstep lektioner och så klart för bra bilkörning och en galet rolig vecka i CA! Vet att du

kommer att hitta ett ”life of luxury” i Carmel en dag.

Nina, för utmärkt projektledning i alla mina projekt. Hoppas det inte har varit alltför jobbigt att bli

inslängd i alla konstiga mer eller mindre akademiska projekt.

Leena, den kanske viktigaste personen på Affibody. Tack för alla buffertar, plattor och beställningar. Du

har gjort det otroligt lyxigt att labba på Affibody.

Anna S, för bra samarbete med transferrin-depletion projektet och all hjälp på labbet!

Rummet på Affi, Malin, Sara, Olof. Tack för trevligt sällskap, bra hjälp, och massa roligt-inte-så-mkt-

jobb-snackande. Speciellt tack Malin för alla selektions och biacore diskussioner, jag har lärt mig massor

och det har varit skönt att alltid ha en bundsförvant i biacore och affinitets frågor.

Olof W, för alla gånger du ympat odlingar åt mig och för att du är min vän trots att jag är lite galen.

Tack också till alla andra Affibodianer för hjälp på labbet, sköna kaffepauser och micro-luncher, kul

teaterbesök, roliga pubar och galna fester!

Tennis-tjejerna på affi & kth. Vi är väl inte direkt några proffs än...men tack för alla sköna tennismornar!


När vi ändå pratar träning. Yoga-sushi gruppen. För att ni ser till att jag går på yoga och minskar min

stress..och äter god mat en gång i veckan!

Anna, för att du alltid är en supervän och för att du och Hans (och Nils och Märta så klart) är min

extrafamilj. Tack för att jag alltid har kunnat fly till stränkan när jag tyckt doktorerande och stockholmsliv

blivit lite jobbigt. Hur galen jag än blivit och hur uppochner vänt mitt liv än blivit så har du alltid sett till

att jag har fått massor med te, god mat, och perfekt distraktion av söta bebisar.

Perstorpsgänget: Patrik, Jonas, Charlotte, Linda, Niklas. För att när vi ses har tiden stått stilla och ni

kommer alltid att vara mina vänner. Ni får mig att komma ihåg att egentligen så är doktorerande inte så

viktigt. Det finns massor med andra saker i livet och den bästa stunden kan ändå vara att äta makaroner

på en fjälltopp.

Alla andra vänner, tack för ert stöd! Nu går jag ut ur avhandlingdimman och kommer att ha mer tid och

umgås igen!

Tack också till min fantastiska familj som alltid finns där för mig och ser till att jag inte tappar förmågan

till att argumentera i en riktigt hetsig diskussion. Jag älskar våra middagar som alltid avbryts med att

någon måste söka på internet. Ni har lärt mig att alltid ta ställning till saker och aldrig någonsin ge upp.

Min brorsa Thomas och familj (Stina, Arvid). För att du höll lite koll på mig i Linköping när vi bodde i

samma stad och för att du står för det logiska och naturveteskapliga som kan förklaras med ettor och

nollor. Fortfarande lite arg för den gången du sa att du inte trodde på DNA..men kanske kan förlåta dig.

Min brorsa Anders och familj (Karin, Agnes, Hilda, Engla och Love). Du kan vara skyldig till mitt första

naturvetenskapliga intresse genom att tvinga mig att lära mig alla fågelarter utantill, men sen dess har du

ju också försökt lärt mig mer nyttiga saker som t ex hur jag PR-mässigt bäst presenterar min forskning.

Tack för att du och hela härliga familjen alltid finns inom räckhåll i Knivsta!

Mamma Lilian och pappa Bengt. För att ni alltid är ett fantastiskt stöd och tror på mig. Ni är bäst! Trots

att jag ibland har haft lite svårt att förklara vad det egentligen är jag gör har ni alltid varit intresserade.

Tack för att ni har lärt mig att jag kan klara vad som helst bara jag försöker!

C, for messing up my life and kidnapping me to thailand. Let’s stay crazy together and make life more

interesting!


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