1. health and fitness
2. disease

Bacteria-based methods for engineering and
characterization of proteases and affinity
proteins
LISA SANDERSJÖÖ
Royal Institute of Technology
School of Biotechnology
Stockholm 2015
© Lisa Sandersjöö
Stockholm 2015
KTH Royal Institute of Technology
School of Biotechnology
AlbaNova University Center
SE-106 91 Stockholm
Printed by Universitetsservice US-AB
Drottning Kristinas väg 53B
SE-100 44 Stockholm
Sweden
TRITA-BIO Report 2015:10
ISSN 1654-2312
ISBN 978-91-7595-525-4
Abstract
This thesis is focused on the development of methods for characterization and engineering of both
proteases and affinity proteins. In addition, a prodrug concept for small affinity proteins is developed.
Two of the developed methods are for engineering and/or characterization of proteases. First, a method
for substrate profiling and engineering of proteases was investigated (paper I). In this method, a
protease and a reporter are co-expressed in E. coli. The reporter is comprised of an enzyme, which
confers resistance to an antibiotic, fused to a substrate, and a degradation tag. In absence of sitespecific proteolysis within the reporter, the degradation tag renders the entire reporter a substrate for
the intracellular degradation machinery. Thus, by applying competitive growth in presence of the
antibiotic, a substrate that is preferred by a model protease could be enriched relative to less efficiently
hydrolyzed substrates. Then, an alternative method for substrate profiling was developed (paper III).
Here, the substrate is instead displayed on the surface of bacteria, and located between two antiidiotypic domains, where one blocks the other from interacting with a reporter. Site-specific proteolysis
releases the blocking domain and is therefore reflected in reporter binding. After incubation with
fluorescently labeled reporter, the proteolysis can be analyzed by flow cytometry. When large libraries
of potential substrates for matrix metalloprotease 1 (MMP-1) were screened, a panel of substrates with
the previously reported motif PXXXHy was enriched, thereby demonstrating the potential of the
method. This method offers the possibility for high-throughput substrate profiling of proteases as well
as engineering of substrates for use in for example protease-activated prodrugs.
In another study, a new prodrug concept for small affinity proteins was developed to improve the tissue
selectivity in future in vivo studies (paper II). This concept takes advantage of the local upregulation of
proteases in the diseased tissue in various disorders. By fusing a targeting domain to an anti-idiotypic
binding partner via a protease-sensitive linker, the targeting domain is masked from interacting with its
target until activation by site-specific proteolysis within the linker. The concept was demonstrated for a
small affinity protein (Affibody molecule). Bacterial display was employed to engineer the so-called
pro-Affibody. When displayed on the bacterial surface, the pro-Affibody showed over 1.000-fold
increase in apparent binding affinity upon activation by a disease-associated protease. Additionally, the
activated pro-Affibody could bind to its target expressed on cancer cells, as opposed to the nonactivated pro-Affibody. This concept is likely to be extendable to other small affinity proteins and opens
up for the possibility to develop new such prodrugs to previously non-druggable targets.
In the last study, a screening method for protein-based aggregation inhibitors was developed (paper
IV). In this method, a reporter and an inhibitor are co-expressed in E. coli. The reporter is comprised of
green fluorescent protein (GFP) fused to an aggregation prone peptide. Upon aggregation, the
fluorescence is decreased, but it is then restored when the reporter is co-expressed with an inhibitor. In
a model screening experiment, an Affibody molecule that targets the A! peptide (involved in
Alzheimer’s disease) could be enriched from a background of non-inhibiting Affibody molecules. Also
this method is likely to be extendable to other types of affinity proteins, and also to different
aggregation prone peptides/proteins involved in other diseases.
In conclusion, the methods and concepts presented in this thesis could in the future yield new means
for the engineering and characterization of proteins with desired properties to be used in both
biotechnological and medical applications.
Sammanfattning
Den här avhandlingen fokuserar på utveckling av olika metoder och koncept för engineering av både
proteaser och affinitetsproteiner.
Två av metoderna är till för engineering och karaktärisering av proteaser. Den första metoden är för
substratprofiliering och engineering av proteaser (paper I). I den här metoden så uttrycks ett proteas
och ett reporterprotein tillsammans i E. coli. Reporterproteinet består av ett enzym, vilket ger upphov
till antibiotikaresistens, som är fuserat till en substratpeptid och en degraderingssekvens. Om inte
substratet i reporterproteinet hydrolyseras av proteaset så gör degraderingssekvensen så att hela
reportern blir ett substrat för cellens intracellulära degraderingsmaskineri. I ett selektionsexperiment
där celler fick växa i medium med tillsatt antibiotika så anrikades ett substrat som kan hydrolyseras
effektivt jämfört med andra substrat som hydrolyseras mindre effektivt av proteaset. Den andra
metoden är till för substratprofilering (paper III). I den här metoden så uttrycks substratet på ytan av
bakterier istället. Substratet är placerat i en linker mellan två anti-idiotypa proteindomäner, där den
ena hindrar den andra från att binda till ett reporterprotein. Hydrolys av substratet gör att den
blockerande domänen klyvs bort och kan därmed påvisas genom reporterbinding. Efter inmärkning
med en fluorescent reporter så kan hydrolysen analyseras med flödescytometri. När stora
substratbibliotek för matrix metalloproteas-1 (MMP-1) analyserades och sorterades så anrikades flera
substrat med en sekvens (PXXXHy) som tidigare har visats vara effektiv för hydrolys av MMP-1, vilket
demonstrerar potentialen för metoden. Den här metoden kan användas för effektiv substratprofilering
av proteaser och engineering av substrat som kan användas i t.ex. ”prodrugs” som aktiveras av proteas.
I en annan studie så utvecklades ett nytt prodrug-koncept för små affinitetsproteiner för att öka
selektiviteten för sjuk vävnad i framtida in vivo studier (paper II). Det här konceptet utnyttjar att
proteaser är lokalt överuttryckta i den sjuka vävnaden i flertalet sjukdomar. En målsökande domän
fuserades till en anti-idiotypisk bindningspartner för att blockera den målsökande domänen från att
binda till sitt målprotein. Genom att länka ihop domänerna via ett substrat för ett proteas så kan den
målsökande domänen aktiveras genom hydrolys av linkern. Konceptet visades för ett litet
affinitetsprotein (Affibodymolekyl). Bakteriell display användes för att utveckla den så kallade proAffibodyn och när den uttrycktes på bakteriens yta så var det 1,000 gångers skillnad i affinitet före och
efter aktivering av ett proteas. Den aktiverade pro-Affibodyn kunde även binda till sitt målprotein
uttryckt på cancerceller till skillnad från den icke-aktiverade pro-Affibodyn. Det här konceptet kan
troligtvis expanderas till andra små affinitetsproteiner och öppnar upp för utvecklingen av prodrugs
mot målproteiner som tidigare varit svåra att rikta terapi mot eftersom de även finns i frisk vävnad.
I den sista studien så utvecklades en metod för engineering av aggregerings-inhibitorer. Ett
reporterprotein och en inhibitor uttrycks här tillsammans i E. coli. Reporterproteinet består av green
fluorescent protein (GFP) fuserat till en aggregerande peptid. Vid aggregering minskar fluorescensen,
men när även en inhibitor uttrycks så ökar den igen. En Affibodymolekyl som binder till A!-peptiden
(involverad i Alzheimer’s) kunde här anrikas från en bakgrund av icke-inhiberande Affibodymolekyler.
Även den här metoden kan troligtvis expanderas till att omfatta även andra små affinitetsproteiner och
andra peptider/proteiner som aggregerar, vilka är involverade i andra sjukdomar.
Sammanfattningsvis så kan metoderna och koncepten som presenteras i den här avhandlingen i
framtiden bidra till nya möjligheter för engineering och karaktärisering av proteiner med önskade
egenskaper för användning i både biotekniska och medicinska tillämpningar.
List of appended papers
This thesis is based on the following articles and manuscripts, referred to in the text by their
Roman numerals (I-IV). The papers can be found in the appendix.
Paper I
Sandersjöö L*, Kostallas G*, Löfblom J, Samuelson P. (2014) A protease
substrate profiling method that links site-specific proteolysis with antibiotic
resistance. Biotechnology Journal 9:155-62
Paper II
Sandersjöö L, Jonsson A, Löfblom J. (2015) A new prodrug form of Affibody
molecules (pro-Affibody) is selectively activated by cancer-associated
proteases. Cell Mol Life Sci 72:1405–1415
Paper III
Sandersjöö L, Jonsson A, Löfblom, J. Bacterial display of self-blocking
affinity proteins for efficient protease substrate profiling. Manuscript
Paper IV
Lindberg H, Sandersjöö L, Ståhl S, Löfblom J. Development of a
fluorescence-based high-throughput intracellular method for function-based
isolation of protein-based aggregation inhibitors. Manuscript
* These authors contributed equally to this work.
The papers are reproduced with permission from the copyright holders.
Contributions to the included papers
Paper I
Performed all the experimental planning and work together with coauthor. Wrote the manuscript
together with coauthors.
Paper II
Main responsible for experimental planning and performance, and manuscript writing.
Paper I
Main responsible for experimental planning and performance, and manuscript writing.
Paper I
Performed experimental planning and work together with coauthor. Minor contribution to
manuscript writing.
Contents
INTRODUCTION ..................................................................................................... 1
Proteins................................................................................................................ 1
Proteins as drug targets and therapeutics ................................................................................. 2
Protein engineering..............................................................................................3
Protein engineering by rational design ..................................................................................... 3
Protein engineering by directed evolution ................................................................................ 5
Proteases.............................................................................................................. 7
Protease substrate profiling....................................................................................................... 8
Engineering of proteases ..........................................................................................................14
Affinity proteins ................................................................................................ 20
Alternative scaffold proteins.................................................................................................... 20
Affibody molecules................................................................................................................... 22
PRESENT INVESTIGATION ..................................................................................23
Aims of the thesis......................................................................................................................... 25
A protease substrate profiling method that links site-specific proteolysis with antibiotic
resistance (paper I)...................................................................................................................... 26
A new prodrug form of Affibody molecules (pro-Affibody) is selectively activated by cancerassociated proteases (paper II) ...................................................................................................31
Bacterial display of self-blocking affinity proteins for efficient protease substrate profiling
(paper III) .....................................................................................................................................37
A new bacterial intracellular screening assay for discovery of protein-based aggregation
inhibitors (paper IV).................................................................................................................... 42
Concluding remarks and future perspectives ............................................................................. 46
Populärvetenskaplig sammanfattning .................................................................. 48
Acknowledgements ...............................................................................................50
References ............................................................................................................52
INTRODUCTION
Lisa Sandersjöö
Proteins
Proteins are essential for virtually every process in a living organism as they catalyze biochemical
reactions, form receptors and channels in membranes, carry out cell signaling and transportation
of molecules, and provide structural support among various other things. Given the variety of the
functions that they can perform, it might seem astonishing that naturally occurring proteins are
comprised of only 20 different building blocks, the amino acids, but they can be combined into
an extreme variability. The different side chains of the amino acids give the protein its chemical
and physical properties. The distinctive functionalities of the proteins are given by the order of
which the amino acids are incorporated into the growing peptide chain, which then folds into
complex three-dimensional structures (fig. 1). This order is predefined by the DNA sequences in
our genes, but the relationship between the primary amino acid sequence and the structure of a
protein is extremely complex and consequently it is usually not possible to predict the structure
from the sequence.
b
a
S
I
S
E
H
T
S
A
L
c
S
I
d
Figure 1: The structure of proteins. The sequence of amino acids in a polypeptide chain of a protein is
termed the primary sequence (a), which then forms local regular secondary structures, such as !-helices or
"-strands (b), which are further packed into one or several compact globular units giving the protein its
tertiary structure (c). If the protein contains several polypeptide chains, these are arranged in the
quaternary structure (d). Shown in c and d are the structures for green fluorescent protein (PDB ID: 1KYS),
and hemoglobin (PDB ID: 2M6Z) generated with the UCSF Chimera package.
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Bacteria-based methods for engineering and characterization of proteases and affinity proteins
Proteins as drug targets and therapeutics
Since proteins act in so many fundamental processes, it is not surprising that protein
malfunction such as mutations, misregulation, and misfolding are associated with several
diseases. Besides being the cause of the disease, proteins can also be used to detect or treat
diseases. Numerous drug targets have been identified as a result of the enhanced insight in
human diseases following the advances in genomic and proteomic research [1], and most modern
drug targets are proteins due to the increased knowledge of proteins as key players in our bodies
[2]. Advancements in molecular biology, such as development of recombinant DNA techniques
[3], and various production systems for recombinant proteins, have extended the possibility to
use proteins also as therapeutics [4]. Protein therapeutics can act in different ways, e.g. through
replacement of the defect or lacking protein as for insulin, which was the first recombinant
protein therapeutic approved for clinical use in 1982 [4, 5], or by interacting with other proteins
in the body. Compared to small chemical compounds, protein therapeutics have the ability to
perform more complex functions. Proteins also often demonstrate a higher selectivity for their
molecular targets than small molecules, and therefore have less potential for off-target adverse
effects caused by interference with normal biological functions [4]. Although the majority of the
drugs on the market are small molecules [6], the estimated success rate for clinical approval is
today higher for protein therapeutics than for small molecules [7].
Challenges for protein therapeutics include protein solubility, route of administration,
distribution, immunogenicity, and stability [4, 8]. Additionally, even though protein therapeutics
are more selective for their targets than small molecules, the target proteins are rarely expressed
solely in diseased tissue [9]. Thus, on-target related side effects could result in toxicities or even
making the target non-druggable. However, many of these issues can be addressed in protein
engineering efforts with the aim to change or improve the properties of the protein therapeutics
[10].
In this thesis, different methods and concepts for protein engineering are developed. In paper I
and paper III, two different methods for engineering and/or characterization of proteases are
developed. In paper II, a prodrug concept, for the potential reduction of on-target related side
effects of affinity proteins, is developed. In paper IV, a method for engineering of aggregation
inhibitors is developed.
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Lisa Sandersjöö
Protein engineering
Protein engineering describes the process of altering proteins to change their properties. This
enables the analysis of the relationship between structure and function, which could increase the
understanding of how certain proteins function and have evolved. Protein engineering also
enables the generation of novel proteins with modified or entirely new properties. This has for
example revolutionized protein therapeutics due to the ability to tailor the proteins for specific
clinical applications. Protein engineering has also enabled the use of enzymes as catalyst in
industrial processes under conditions where natural enzymes have no activity.
Protein engineering involves three distinct steps: i) deciding on the protein changes, ii) making
those changes (mutagenesis) and iii) evaluating the resulting protein variants for improved
properties (screening or selection) [11]. Two main approaches to protein engineering can be
taken; rational design or directed evolution (fig. 2). In rational design, positions in the protein
sequence are chosen carefully for mutation based on detailed knowledge of the protein structure
and function, and often with the help of computational modeling. As opposed to rational design,
directed evolution can be applied to proteins without using structural data or computational
resources. However, it is also here beneficial to know which positions to target for mutagenesis.
Additionally, there is the option to create novel proteins by de novo computational protein
design, which has been successful in several cases including protein-protein interaction
complexes and enzymes [12-15], but still remains challenging.
Protein engineering by rational design
Rational approaches involve amino acid replacements, deletions or insertions at predefined sites
within the protein. The positions and the new amino acids are selected based on a combination of
knowledge about the structure and the mechanism of the protein [16]. Computational methods
or alanine scanning mutagenesis [17] could assist when deciding on which residues to mutate.
The changes are then introduced by a limited number of site-directed mutations, followed by the
production and analysis of the protein variants (fig. 2a). The use of site-directed mutagenesis has
provided fundamental insights into allostery, stability, folding, and specificity, as it was used to
study these phenomena [18-20]. Another rational engineering approach is to assemble structural
elements from different proteins into a new hybrid [21]. Regardless of how the variants are
generated, rational design approaches tend to be laborious and hence, the number of alterations
that can be explored is fairly limited [22]. Despite the successful outcome in many cases, the
major challenges when using rational design are the general lack of understanding of how
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Bacteria-based methods for engineering and characterization of proteases and affinity proteins
protein structure relates to function, and the difficulty to predict what effect an amino acid
substitution will have on the function of the protein [23].
a
Purify and analyze
each variant
Make rational
mutations
Starting protein
Specifically designed
protein variants
Protein variant with
desired function
b
Screen/select for
desired properties
Generate diversity
Starting protein
Large library of protein variants
Variants with desired
function (for further
characterization)
Figure 2: Schematic summary of rational design and directed evolution approaches for
protein engineering. a) In rational design, a few carefully chosen mutations are introduced followed by
purification and analysis of each protein variant separately. b) In directed evolution, large libraries of
protein variants are generated followed by screening or selection for the desired properties. This is typically
an iterative process, which in the end generates candidates with the desired properties that can be further
characterized.
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Lisa Sandersjöö
Protein engineering by directed evolution
Directed evolution, also known as combinatorial protein engineering, is a powerful tool in which
populations of protein variants can be screened (or selected) in the search for the desired
function. Directed evolution includes two separate steps that are typically performed in an
iterative fashion; first molecular diversity is generated and then the protein variants that have
the desired function are identified either by screening or selection (fig. 2b).
Generation of diversity
Two of the most common methods for constructing libraries of protein variants are random
mutagenesis and site-directed randomization. A common methodology in the random
mutagenesis approach is the error-prone polymerase chain reaction (ePCR) [24, 25]. Here, the
gene for the protein of interest is PCR amplified under conditions that cause the polymerase to
introduce errors along the length of the amplified sequence. This method requires no prior
information on the protein structure since the mutations are randomly incorporated throughout
the sequence. This could help to identify “hot spots” where mutations strongly affect the function
of the protein [26]. However, there are some limitations regarding the genetic diversity that can
be generated. Usually only one nucleotide per mutated codon is changed, giving an average of
around six possible substitution on the amino acids level for the commonly used ePCR methods
[27]. It is also affected by the codon degeneracy in the genetic code, creating an amino acid bias
as some amino acids are encoded by several codons, whereas others only by one [28]. Other
methods, such as DNA shuffling [29, 30] and ITCHY/SCRATCHY [31, 32] or related strategies,
can be engaged for the recombination of different gene pools.
Perhaps even more powerful than directed evolution in a completely random manner, is the
combination of directed evolution with knowledge-based protein engineering. Semi-rational
approaches use knowledge about the structure and/or function of the protein to identify
positions to target for site-directed randomization [33]. The chosen positions can be randomized
using oligonucleotides that contain degenerate codons. There are some different approaches to
create degenerate codons, either they can be fully randomized (NNN) or more carefully
diversified (e.g. NNK). The latter strategy allows for fewer types of nucleotides in one position,
but still includes all the amino acids. This creates less redundancy and fewer stop codons [11, 34].
To even further reduce the redundancy, different approaches to generate trinucleotide synthons,
where each amino acid is represented by only one codon, have been developed [35]. Besides
reducing the library size on the genetic level, this also offers the possibility to introduce higher
relative amounts of certain amino acids at desired positions. Saturation mutagenesis of already a
few of the amino acids within a protein will create a larger protein sequence space than what can
be analyzed with available methods. Therefore, more constrained diversification can be made
using fewer amino acids instead of fully randomizing the residues [36-39]. However, since
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Bacteria-based methods for engineering and characterization of proteases and affinity proteins
beneficial mutations are rare and coupled mutations could have synergistic effects [40-42], large
libraries are often needed to be able to explore a large protein sequence space and identify the
rare variants.
Identification of variants with the desired function
Given all the different approaches to generate diversity, the limit in directed evolution is rarely
the generation of the repertoire, but instead the following identification of the few interesting
variants within that repertoire. It does not matter how large or cleverly designed the starting
library is if there is no possibility to isolate the useful clones within it. Isolation of useful clones is
highly dependent on an effective screening or selection strategy, which preferable should be
high-throughput to increase the likelihood to find clones with the desired properties. Other
desired properties of the screening/selection methods are: sufficient sensitivity (high signal to
noise) to be able to isolate lower activity clones early in the evolution; sufficient reproducibility to
be able to find small improvements; robustness; and most importantly, sensitivity to the desired
function of the protein [43].
Common to the high-throughput methods is the genotypic-phenotypic link, which is the physical
connection between the gene and the protein. This link enables analysis of all variants in a single
batch experiment instead of analyzing them individually and can be established using various
microorganisms or cell-free systems [44, 45]. Depending on the type of protein (e.g. enzyme,
affinity protein), different methods that report on different traits (e.g. enzymatic activity, binding
to a target protein) exist. Some of the existing methods will be described in the next chapters. It
is extremely important to design the methods so that they focus on the correct properties of
interest since in the end you will get what you select/screen for [46]. In this thesis, two methods
that report on site-specific proteolysis (paper I and III) and one that report on aggregation
inhibitory capacity (paper IV) are developed.
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Lisa Sandersjöö
Proteases
Proteases are the largest family of enzymes, encoded by more than 2% of the genes of the human
genome. These enzymes catalyze the cleavage of proteins by hydrolysis of peptide bonds and
were initially thought to be merely responsible for non-specific protein degradation in food
digestion and protein turnover. However, this concept has been widely revised and now it is well
established that proteases are crucial in the control of biological processes in all living organisms.
Proteases can be divided into 6 different classes (aspartic, glutamic, metallo, cysteine, serine and
threonine), depending on the mechanism by which they hydrolyze peptide bonds. In the first
three classes, an activated water molecule acts as the nucleophile that attacks the peptide bond,
which is hydrolyzed. The remaining classes instead utilize an amino acid residue (Cys, Ser or Thr
respectively), located in the active site as the nucleophile [47]. Among human proteases, the most
abundant are metallo, serine, and cysteine proteases, represented by 192, 184, and 164 genes,
respectively [48]. In addition to the differences in catalytic mechanisms, proteases also vary in
their size and shape, from a single catalytic unit of 15 kDa [49] to large complexes like the
proteasome and meprin metalloproteinases with molecular weights of up to 6 MDa [50].
Additionally, the substrate specificity of proteases is also highly variable, ranging from limited
proteolysis of a subset of proteins to very promiscuous degradation.
By their ability to catalyze highly specific proteolytic reactions, proteases play important roles in
the regulation of cellular functions such as DNA replication, cell cycle regulation, cell
proliferation, differentiation and migration, wound healing, immunity, angiogenesis and
apoptosis. Additionally, many viruses, infectious organisms and parasites use proteases as
virulence factors [47, 51-53]. Given the biological relevance of proteases, it is easy to understand
that alterations in proteolytic systems contribute to several disease conditions such as cancer,
neurodegenerative disorders as well as cardiovascular and inflammatory diseases [47]. In the
Mammalian Degradome Database, more than 100 diseases are listed that are caused by
mutations in protease encoding genes, resulting in loss or gain of protease function [48].
Additionally, upregulation of proteolysis is associated with different types of cancer as well as
inflammation, and a common approach is to target the proteases for inhibition [54]. However,
clinical trials with matrix metalloprotease (MMP) inhibitors for cancer treatment failed due to
severe side effects. The inhibitors were broad and targeted several MMPs and following studies
revealed that the biological activities of MMPs range from stimulation of proliferation to
induction of apoptosis [55]. A different approach is to take advantage of the upregulation of
proteases in the tumor microenvironment for the activation of prodrugs, which are inactive until
they undergo site-specific proteolysis by a disease-associated protease [56]. This approach is
explored in paper II in this thesis. Here, an affinity protein is blocked from interacting with its
target until it is activated by a disease-associated protease.
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Bacteria-based methods for engineering and characterization of proteases and affinity proteins
Besides their role in nature, proteases are also important tools in industrial applications and
biomedical research, for example in mass spectral analysis of protein mixtures, where protease
digestion is a routine step for sample preparation.
Protease substrate profiling
A very important mechanism of proteases is their ability to discriminate among potential
substrates, which is termed the substrate specificity of the protease. According to the Schechter
and Berger nomenclature, residues C-terminal to the scissile bond in the substrate are referred to
as the prime-side (P’) and N-terminal residues are referred to as the nonprime-side (P). The
corresponding substrate binding pockets on the enzyme are referred to as S’ and S (fig. 3a) [57].
The substrate specificity is a crucial feature in maintaining the fidelity of the biological processes
in which a protease participates. Therefore, characterization of the substrate repertoire of
proteases could provide information to better understand these biological processes. Moreover, it
could help in the development of inhibitors as they are typically based on the structure of known
substrates. In principle, a substrate could be changed into an efficient inhibitor by replacing the
part of the substrate that reacts with the active site of the protease with a functional group that
covalently binds to amino acid residues of the enzyme and thereby inhibits the catalytic
mechanism [54]. Besides this, information about substrate preferences could be used in the
development of protease-activated prodrugs or probes for measuring protease activity in vivo.
Several different techniques, which utilize chemically or biologically generated libraries of
substrates, have been developed for substrate profiling of proteases and some of them will be
described below.
Methods based on chemical peptide libraries
A convenient way to study the substrate preference of proteases is to attach a fluorogenic leaving
group to the substrate peptide. Usually, a fluorogenic leaving group is attached directly to the
scissile bond and replaces C-terminal residues (fig. 3b, upper part). Therefore, this technique
gives no information about preferences C-terminal to the scissile bond. To study preferences of
both nonprime and prime residues, quenched substrate libraries are needed (fig. 3b, lower part).
In positional scanning synthetic combinatorial libraries (PS-SCL), several sublibraries of
fluorogenic peptides are synthesized. In each library, one residue within the substrate is fixed,
while all other positions contain equimolar amounts of all naturally occurring amino acids, but
typically excluding cysteine (fig. 3c). After protease treatment, the fluorescence intensity from
each sublibrary reflects the importance of the fixed amino acid in that position without the
influence of neighboring amino acids. To overcome the limitation that only prime residues can be
Page |8
Lisa Sandersjöö
determined, a variation of PS-SCL that allows sequential determination of nonprime and prime
subsite preferences, by the use of donor and quencher peptides, has also been developed [58-60].
The use of mixture-based oriented peptide libraries offers determination of both the nonprime
and prime sides in a two-step process without the need of fluorogenic reporters. First, the primeside motif is determined by partial digestion of a random mixture of N-terminally capped
peptides followed by Edman sequencing. The relative abundance of the amino acids found in
each sequencing cycle indicates which amino acids that are preferred at each position
downstream of the cleavage site. This is then used to design a secondary library, to determine
motifs on the nonprime side. In this secondary library, the prime-side motif serves as an anchor
to direct the cleavage to the defined scissile bond, the N-terminal is unblocked, and a biotin is
attached to the C terminus. After proteolysis, the undigested peptides and C-terminal fragments
are removed with immobilized avidin, so that the N-terminal fragments can be sequenced with
Edman degradation (fig. 3d) [61].
When pools of mixed substrates are used as in the methods described above, no information is
obtained about how the cooperativity between the different residues in the substrate influences
substrate recognition. To this end, the proteolytic processing of single substrates must be
determined. As opposed to PS-SCL and mixture-based oriented peptide libraries, which only
provides information on average preferences, microarrays allow for individual analysis of
different sequences. Each spot on the array represents an individual fluorogenic substrate, which
can be chemically attached to a glass slide (fig. 3e) or deposited on to the surface as nanoliter
droplets (fig. 3f). Following incubation with protease, the fluorescence intensity of each spot
reveals the hydrolysis of the particular substrate sequence, which is located in that spot [62, 63].
Alternatively, if each library member is fused to a unique peptide nucleic acid (PNA) sequence,
the proteolysis can be carried out in solution, followed by capture to predefined locations on
oligonucleotide microarrays (fig. 3g) [64-66].
Page | 9
Bacteria-based methods for engineering and characterization of proteases and affinity proteins
a
N-terminus
C-terminus
Nonprime side
Prime side
P4
P3
P2
P1
P1’
P2’
P3’
P4’
S4
S3
S2
S1
S1’
S2’
S3’
S4’
Protease
b
P3
P2
P1
F
P2
P1
P1’
P2’
PX
F
PX
c
X4
X2
X3
X4
X3
20x
20x
X4
20x
X2
+
F
Q
P2
P1
+ P1’
Ac-XXXXXXXXXXXX
X1
F
P2’
PX
X1
Second generation library
NH2-XXXXXXP1’P2’P3’P4’P5’P6’-biotin
Proteolysis
P3
Ac
F
P3
P1
Degenerate peptide library
F
P2
Ac
Q
PX’
P2
d
P1
Ac
P3
PX
Proteolysis
Ac-XXXXXX + NH2-XXXXXX
F
N-terminal sequencing
NH2-XXXXXX
P1’P2’P3’P4’P5’P6’-biotin
P4
Ac
Xn
20x
20x
X3
X2
X1
Immobilized avidin
Motif for P’ positions
F
NH2-XXXXXX
N-terminal sequencing
Equimolar mixture of amino acids
Motif for P positions
Individual amino acid kept
constant in each sublibrary
e
F
F
F
F
Proteolysis
Protease added in aerosol
f
F
F
F
F
Proteolysis
g
F
F
+
F
Capture
on slide
Figure 3: Overview of methods using chemically synthesized peptides for substrate profiling
of proteases. a) Residues N-terminally and C-terminally to the scissile bond are termed nonprime and
prime residues, respectively. b) A fluorogenic leaving group can be used to determine prime residues,
whereas FRET peptides are needed to determine both the prime and nonprime residues. c) In positional
scanning, 20 sublibraries with one constant amino acid are constructed for each position. Analysis of the
fluorescence upon proteolysis gives the average importance of each amino acid in a certain position. d) In
mixture-based oriented peptide libraries, N-capped peptide libraries are synthesized and after proteolysis,
N-terminal sequencing reveals the relative preference of the amino acids in each position. A second library
based on the outcome from the first is then synthesized, and N-terminal sequencing after proteolysis reveals
the preference of the prime site. e,f,g) Arrays with substrates provide information about cooperativity
between residues due to analysis of individual substrates. The substrate peptides can be chemically attached
to the surface (e), or deposited in droplets (f). Alternatively, already digested substrates can be captured on
the slide through PNA-DNA interactions (g).
Page |10
Lisa Sandersjöö
Methods based on biological substrate libraries
The synthesis of peptide substrates could be costly, especially if they contain chemical
modifications. Additionally, although most proteases recognize their substrates in an extended
(beta-strand-like) conformation [67], the specificity of proteases on small synthetic substrates
and substrates located in a structural context are often different [68]. Therefore, in addition to
chemical peptide libraries, alternative methods based on biologically generated peptide
substrates have been developed. In these methods, the substrate sequence is typically located
between different protein domains.
The most popular approach has been substrate phage display, which has been used to determine
the substrate specificity of several proteases including subtilisin, factor Xa, furin, HIV-1 protease,
caspases, plasmin and MMPs [69-75]. In substrate phage display, the substrate sequence is
displayed on the surface of phage particles between an affinity tag and the display scaffold
protein, typically the pIII protein. The affinity tag enables immobilization of the substrate phage
to a solid support. After incubation with the protease of interest, the phage particles containing
cleavable substrate sequences are released, whereas phage particles with non-cleavable
sequences remain immobilized (fig. 4a).
Other methods instead rely on bacterial expression of the substrates in combination with
fluorescence-activated cell sorting (FACS). In FACS, the cells are screened at high speed and
sorted based on their fluorescence and light scattering properties. Excitation by a laser, followed
by detection of scattered light and fluorescence, is performed for each cell. Droplets containing
single cells are then generated. An electrostatic charge is applied to individual droplets that
contain cells that meet the desired criteria. When the droplets pass through an electric field, the
charged ones are deflected into a collection tube.
One bacteria-based method uses genetically encoded and short-lived fluorescent reporters,
which are expressed in the cytoplasm of E. coli [76]. The reporter is comprised of green
fluorescent protein (GFP) fused to a C-terminal degradation tag (ssrA), which targets the
reporter for destruction by the cell’s intracellular degradation machinery, such as ClpXP. By
introducing a substrate peptide between GFP and the degradation tag along with co-expression
of a protease, the reporter will escape degradation in the event of site-specific proteolysis. Thus,
cells containing a functional combination of protease and substrate will exhibit increased
fluorescence and can be sorted by FACS (fig. 4b). This method has been used to determine the
substrate repertoire of the tobacco etch virus protease (TEVp) [77].
Another bacteria-based method is CLiPS (cellular libraries of peptide substrates) [78], in which
substrate libraries are displayed on the surface of E. coli. In addition to determining substrate
specificity, this method has also been used to provide cleavage kinetics of different substrates
[78, 79], and to identify peptides that interact with exosites and thereby accelerate cleavage of
the active site sequence [80]. The substrates are displayed on the bacterial surface using
Page | 11
Bacteria-based methods for engineering and characterization of proteases and affinity proteins
circularly permuted outer membrane protein X (CPX). The substrate is located between the Nterminal of CPX and a peptide ligand for a red fluorescent probe. In addition, a green fluorescent
probe ligand is fused to the C-terminus of CPX to avoid collecting false positives, which do not
display the substrate. In absence of proteolysis, the cells will exhibit high red and green
fluorescence. In the event of proteolysis, the peptide ligand responsible for binding to the red
probe will be cleaved off, and the cells will therefore exhibit a reduced red fluorescent signal (fig.
4c). When including exosites, these are located between the C-terminus of CPX and the green
fluorescent probe ligand. This method has been used to identify cleavage sequence motifs of
caspase-3, enteropeptidase, and TEVp as well as exosites for thrombin and caspase-7 [78-80].
a
Substrate Affinity tag
Phage particle
Release of variants with
functional substrates by
site-specific proteolysis
ClpX
Site-specific
proteolysis
Count
b
ClpP
Protease
GFP
Fluorescence intensity
No site-specific
proteolysis
ClpX
Count
ssrA
ClpP
Fluorescence intensity
c
Tag 1
Intact substrate:
high green / high
red fluorescence
Tag 2
Substrate
CPX
E. coli
+ protease &
fluorescent probes
Cleaved substrate:
high green / reduced
red fluorescence
Figure 4: Overview of methods using biological substrate libraries for substrate profiling of
proteases. a) In substrate phage display, the substrate is displayed on the phage surface between the
display scaffold and an affinity tag. After immobilization to a solid support, the phage particles displaying
functional substrates are released by site-specific proteolysis. b) Cytoplasmic expression of a protease and a
short-lived reporter, comprised of GFP fused to the substrate and degradation tag, targets the entire reporter
for destruction in absence of proteolysis, whereas site-specific proteolysis will rescue GFP, thus rendering the
cell fluorescent. c) In CLiPS, the substrate is displayed on the E. coli surface between CPX and a ligand to a
fluorescent probe, which is released by site-specific proteolysis, thereby reducing the fluorescence.
Page |12
Lisa Sandersjöö
Proteomics-based identification of protease substrates
Testing the substrate sequence when it is part of a folded fusion protein, as in the methods
described above, could overcome some limitations compared to short peptides. However, it is not
always that the substrate sequence is presented the same way as in its native protein. Therefore,
it is useful to also study proteases on a proteomic scale. For this purpose, several approaches
including gel-based and MS-based methods have been developed.
Two-dimensional gel electrophoresis (2D-PAGE) separates complex mixtures into resolvable
spots by their isoelectric point and molecular weight. Protein spots of interest are then excised
and identified by mass spectrometry (MS). By pre-staining proteolyzed and non-proteolyzed
samples with different fluorophores, they can be run in the same gel and compared. Substrate
candidates are identified by a reduction in intensity for the spot corresponding to the intact
substrate, and the appearance of spots corresponding to cleavage fragments. Alternatively,
protease targets can be identified by an intermediate in-gel protease treatment. The proteins that
migrate off the diagonal in the post-proteolysis electrophoresis are likely to be substrates for the
digesting protease. Gel-based proteomics has some limitations such as throughput, the bias for
high-abundance proteins, and missed detection of small cleavage fragments and proteins with
very basic or acidic isoelectric points [81, 82].
MS-based methods take advantage of the new N- and C-terminals, termed neo-terminis,
generated upon proteolysis. Cell lysates can be used as large substrate libraries for exogenously
applied proteases. By labeling of the primary amines in the proteolyzed sample before
trypsination, the fragments containing neo-terminis can be enriched for, either by negative or
positive selections, which greatly reduce the sample complexity before LC-MS/MS analysis.
Alternatively, the proteome sample could be digested into peptides first, followed by subsequent
blocking of the N-termini, thus generating a peptide library. This library is then treated with the
protease followed by peptide enrichment and MS analysis [82-85].
Need for new methods for substrate profiling of proteases
As discussed above, several chemical and biological approaches have been developed to
investigate the substrate specificity of proteases. Although most of them have contributed
significantly to the field of protease research, all of them suffer more or less from limitations with
sensitivity, labor intensity, throughput, lack of information of the cooperativity between
positions, or that they only reveal subsite preference of the substrate. Thus, novel highthroughput and quantitative methods are welcomed. Therefore, in this thesis we aimed to
develop two new bacteria-based methods for this purpose (paper I and III).
Page | 13
Bacteria-based methods for engineering and characterization of proteases and affinity proteins
Engineering of proteases
Proteases are inexpensive choices for catalyzing the hydrolysis of peptide bonds in industrial
processes and have been used in the detergent, leather, and food industries for a long time. Many
industrial processes require the proteases to be active under non-physiological conditions, such
as high temperatures, various pH, and in presence of nonaqueous solvents. Thus, protein
engineering has been applied to adapt them to these conditions. The bacterial protease subtilisin
BNP’ was early on a model system in many engineering efforts to improve the activity in organic
solvents [86], enhance the stability at higher temperatures [87], and under alkaline conditions
[88], as well as the resistance to chemical oxidation [89], or various combinations thereof [90],
mostly carried out by rational approaches.
Protease therapeutics could potentially allow for smaller dosages and higher efficacy due to the
catalytic activities of proteases, i.e. one protease molecule can inactivate numerous target
proteins. Several natural proteases have been approved for treatments of hemophilia, stroke,
acute myocardial infarction, traumatic bleeding, sepsis, muscle spasms, and digestive disorders
[91]. Of these, some have been engineered for improved properties such as increased serum halflife, and reduced inactivation by inhibitors [91].
The engineering of proteases for enhanced and/or altered specificity though, has been somewhat
limited. The earliest approaches were based on rational design, and there are several examples
where structure-guided mutagenesis of only a few amino acids within the substrate-binding
pocket has been successful in altering the substrate specificity, usually by transplanting the
specificity between homologous proteases [92-94]. However, despite extensive structural
knowledge and substantial efforts, it has not always been possible to swap specificities between
related enzymes only by mutations in the substrate-binding pocket. The conversion of trypsin
into a chymotrypsin-like protease required replacement of two surface loops with analogous
loops from chymotrypsin, in conjunction with site-directed mutagenesis at multiple sites, thus
illustrating that substrate specificity determinants do not always contact the substrate [95, 96].
Although many of these efforts have pioneered the field of protease engineering, it has been
difficult to generate proteases with dramatically different properties, especially when structural
data is missing. On the other hand, the use of directed evolution approaches where target genes
are partially or completely mutated, opens up new possibilities. This is exemplified by the highly
successful reprogramming of the substrate specificity of the E. coli outer membrane protein T
(OmpT). This has generated a series of protease variants capable of hydrolyzing a variety of
substrate sequences with high selectivity and catalytic efficiency [97-100].
As efficient methods for generation of genetic diversity have been implemented, the rate-limiting
step in directed evolution of proteases is the availability of different high-throughput methods.
Screening and selection methods for enzymes are typically more challenging to develop than
those for binding molecules, which mostly rely on prolonged capture of the ligand. For enzymes
Page |14
Lisa Sandersjöö
on the other hand, the substrate turnover should be proportional to the output signal to be able
to select for appropriate catalytic properties. Some novel approaches have been developed for the
engineering of proteases, where the most efficient ones so far have been fluorescence-based
screening methods coupled with isolation of cells with desired properties by FACS. In principle,
even larger libraries could be sampled with selection methods, but this still remains to be proven.
In paper I in this thesis, a selection approach, in which proteolytic processing is coupled to
growth in presence of an antibiotic compound, is explored.
Fluorescence-based methods for directed evolution of proteases
The most successful method for isolation of proteases with novel substrate specificities from
large libraries has been a bacteria-based method, in which the protease is displayed on the
surface of E. coli. This approach exploits the electrostatic interaction between the negatively
charged bacterial surface and positively charged and fluorescent substrates, thus being captured
on the surface. To be able to fully reprogram the protease, a counterselection substrate, which
should not be cleaved by the protease, is used in addition to the selection substrate. The selection
substrate is a positively charged FRET peptide, which contains a green fluorophore and a
quencher. Upon proteolysis the quencher is released, while the fluorescent product is retained on
the cell surface. The counterselection substrate is a zwitterionic compound, containing a single
red fluorophore, with positive and negative charge placed on the two respective sides of the
scissile bond. The intact substrate has no net charge, but proteolytic processing generates a
positively charged and fluorescent product, which can be captured on the cell surface. FACS is
then used to isolate variants with high green fluorescence and low red fluorescence (fig. 5a). As
mentioned above, this method has been used to generate OmpT variants with novel substrate
specificities [97-101]. To address the problem that the substrate specificity of proteases for
sequences presented as peptides or within folded proteins could differ, this method has also been
extended to substrate sequences that are presented within a structural context. The protein
MDM2, a p53 antagonist, is fused to a C-terminal poly-Arg tail for surface capture and an Nterminal extension with the putative substrate sequence connected to the p53-TAD sequence,
hence resulting in blocking of the binding surface of MDM2. Proteolysis results in release of the
p53-TAD sequence, thus allowing MDM2 to bind to a fluorescent reporter, which allows for
isolation by FACS [102].
For proteases that cannot be displayed on the bacterial surface, other methods where the
protease is expressed intracellularly have been developed. The method with short-lived
fluorescent reporters that escape degradation after site-specific proteolysis (fig. 4b), previously
used for substrate profiling [77], could potentially be used also for protease engineering. Instead
of inserting substrate libraries within the reporter, libraries of proteases could be used to screen
for variants with altered specificity against a desired sequence. This has not yet been
demonstrated, but a soluble variant of tobacco etch virus protease (TEVp) was enriched from a
Page | 15
Bacteria-based methods for engineering and characterization of proteases and affinity proteins
large background of less soluble variants [76]. In addition, this method offers the combination of
libraries for both substrates and proteases.
Another interesting approach is the Yeast ER screening (YESS), which utilizes a multifunctional
substrate sequence that contains a selection substrate and one or more counterselection
substrates. All substrates are flanked by different epitope tags to allow for labeling with
fluorescent antibodies once the constructs are displayed on the cell surface due to the N-terminal
fusion to Aga2. Cells that exhibit the desired fluorescence profile can then be isolated by FACS
(fig. 5b). A key feature of this system is that ER retention sequences are attached to both the
substrate sequence and the protease to increase their resident time in the ER, in which the
proteolysis takes place. This allows for modulation of the sensitivity and dynamic range. The
retention signals can be added to allow for longer interaction of the protease and substrate
sequence, and then removed to allow for isolation of enzymes that process the substrate with
higher efficiency in later rounds of directed evolution. This method has been used to engineer
different variants of TEVp with either altered selectivity or increased catalytic efficiency [103].
This method could in principle also be used for substrate profiling.
In addition, other fluorescence-based methods have been used to isolate variants with different
properties. A subtilisin variant with improved resistance to a particular inhibitor was isolated by
encapsulation of protease-secreting bacterial cells, a fluorogenic substrate, and the inhibitor in
droplets followed by flow cytometric sorting [104]. The use of GFP to report for the solubility of
an N-terminally attached passenger protein has been demonstrated for several proteins [105,
106], and was used to isolate a TEVp variant with improved solubility [107]. In paper IV in this
thesis, we also used this approach, but instead in an effort to develop an assay for screening of
affinity proteins with aggregation inhibitory propensities.
Page |16
Lisa Sandersjöö
a
Q
hv
F
OmpT
OmpT
E. coli
Enzyme variant specific for new substrate
Library of different enzyme variants
hv
hv
FACS sorting
Q
F
F
OmpT
F
F
Q
Non-specific enzyme variant
Undesired wild-type
substrate
Desired new substrate
hv
F
OmpT
Enzyme variant with wild-type specificity
b
te
tra
tag
2
Aga2
Aga2
Aga1
Aga1
Aga1
ERS
tag1
bs
c.
Aga2
te
stra
sub
u
s. s
b
c. su
b
c. su
tag1
u
s. s
ate
bstr
ER
tag1
u
s. s
ERS
te
tra
bs
te
stra
b
c. su
tag
2
Aga2
Figure 5: Fluorescence-based methods for directed evolution of proteases. a) The protease OmpT
is displayed on the surface of E. coli cells, which are incubated with a positively charged FRET peptide
containing a selection substrate and, a zwitterionic and fluorescent counterselection substrate. Proteolysis
renders the substrates fluorescent and positive, respectively. Positively charged peptides are captured on the
negatively charged cell surface, thus giving different fluorescence profiles depending on the cleaved
substrates. b) In YESS, the proteolysis takes place in the ER of yeast cells and the resulting construct is
displayed on the cell surface. By introducing both a selection and a counterselection substrate, which are
flanked by different epitope tags, the cells get different fluorescence profiles depending on the cleaved
substrates upon incubation with labeled antibodies. ERS, ER retention signal; c substrate, counter-selection
substrate; s substrate, selection substrate.
Page | 17
Bacteria-based methods for engineering and characterization of proteases and affinity proteins
Plate-based methods for directed evolution of proteases
An alternative to flow cytometry is to use plate-based screening. One such method is based on
previous findings that a recognition sequence for human immunodeficiency virus type I protease
(HIV PR) could be inserted in a surface loop of E. coli !-galactosidase (!-gal), so that !-gal
activity was retained in absence of the protease, but diminished by proteolytic processing of the
substrate [108]. By introducing a desired substrate sequence in the loop, HIV PR variants with
altered specificity could be identified by a decrease in !-gal activity, which was reflected in loss of
blue color when grown at X-gal containing plates (fig. 6a). Since wild type HIV PR catalyzes the
cleavage of essential E. coli proteins, and therefore is cytotoxic, variants with broad specificity
can be eliminated simply by growth [109].
A common approach in the regulation of reporter genes is to localize a transcription factor at a
site, which is physically separated from the nucleus. One such approach for screening of
proteases with altered substrate specificity is the yeast-based GASP (genetic assay for sitespecific proteolysis). Here, a transcription factor is anchored to the plasma membrane via a
cleavable linker, and a transmembrane domain. If the linker is cleaved by a co-expressed
protease, the transcription factor is released and diffuses to the nucleus where it activates the
expression of one or more reporter genes (fig. 6b). The GASP system has been used to change the
specificity of Hepatitis A virus 3C protease by activation of the reporter genes conferring growth
on plates with selective media as well as !-gal activity [110]. Another similar method, however
bacteria-based, instead utilizes a transcription repressor made up by two DNA-binding domains
with the substrate inserted in between them. If the substrate is cleaved, the repressor is rendered
non-functional and the reporter genes that confer growth in selective media as well as !-gal
activity are transcribed. A TEVp mutant with altered specificity towards the substrate peptide
ENLYFQD instead of ENLYFQG was engineered by this method [111].
Need for new high-throughput methods for engineering of proteases
As described above, several interesting methods have been developed for protease engineering
and some of them have been successfully used to alter substrate specificity. However, all of them
are screening methods, thus suffering from a limited throughput due to either the throughput
rate of a flow cytometer or what can be screened manually on plates. We therefore sought to
explore the concept of a complementary selection method that is based on survival instead
(paper I). This would allow only the desired clones to appear, thus limiting the labor intensity
and increasing the throughput.
Page |18
Lisa Sandersjöö
a
Site-specific proteolysis
β-gal
Blue color
Loss of color
X-gal
P1
b
’
P2
’
’
PX
PX
P2
P1
P1’
P2’
PX’
TF
Site-specific
proteolysis
Cytoplasm
TF
Transmembrane
domain
Reporter gene expression
Nucleus
Figure 6: Plate-based methods for directed evolution of proteases. a) When a substrate within a
surface-exposed loop of !-gal is cleaved, the enzyme is rendered inactive, which results in loss of blue color
when the cells are grown on X-gal containing plates. b) In GASP, a transcription factor is anchored to the
plasma membrane through a substrate peptide and a transmembrane domain. If the substrate is cleaved, the
transcription factor can diffuse to the nucleus and activate reporter genes. TF; transcription factor.
Page | 19
Bacteria-based methods for engineering and characterization of proteases and affinity proteins
Affinity proteins
Affinity is the extent to which two molecules interact with each other and as the name implies,
affinity proteins have affinity for their targets. The targets are typically biomolecules such as
other proteins. Affinity proteins are essential in many areas of life science such as for separation,
detection and diagnostics. Additionally, a large fraction of the proteins used as therapeutics are
affinity proteins [8]. The most widely used affinity reagents are antibodies, which were early
discovered as naturally evolved affinity proteins. Antibodies can be generated by immunization
or by recombinant means [112]. The advances in protein engineering techniques have led to that
also other affinity reagents than full-length antibodies have emerged. These proteins are derived
from both antibodies and non-immunoglobulin proteins from human or other origin. The nonimmunoglobulin derived affinity proteins are often referred to as alternative scaffolds, which will
be described below.
In general, affinity proteins can be engineered to have high affinity and selectivity for their
targets and therefore potentially reduce the off-target effects, compared to small molecular
compounds. However, the target proteins are rarely expressed only in the diseased tissue [9],
which could result in on-target related side effects. The use of pro-drugs, which are activated in
the diseased tissue, offers possibilities to increase the tissue selectivity of protein therapeutics,
such as affinity proteins. As mentioned previously, proteases are upregulated in a range of
diseases and could therefore be used to activate prodrugs [56, 113]. This has been demonstrated
for prodrug forms of antibodies [114, 115], cytokines [116, 117], and now also for an alternative
scaffold protein (paper II).
Alternative scaffold proteins
Alternative scaffold proteins are commonly based on a relatively small single peptide chain,
which folds into a rigid framework that can withstand diversification at multiple sites. Apart
from a small size and the stable core, additional attractive features are high solubility and
thermal stability and a cost-efficient production in bacteria or by chemical peptide synthesis
[118-121]. Several of the alternative scaffolds are devoid of cysteines, which enables site-specific
modifications simply by introducing a single cysteine followed by thiol-directed chemistry [118,
122]. Additionally, the generally high thermal and chemical stability of these proteins offers the
possibility for other labeling methods or modifications that require harsh conditions [120].
The small size of the scaffold proteins might be beneficial for tissue penetration [123], and in
vivo imaging applications where the fast clearance results in a high image contrast [124]. In
Page |20
Lisa Sandersjöö
other applications where a fast clearance is not desired, the scaffold proteins can be fused to
other domains or PEGylated to prolong the circulation time [125]. The small size and the stability
of the scaffold proteins facilitates the generation of multi-domain constructs, which could be
used to target two antigens [126, 127], increase the apparent affinity due to avidity effects [128]
or target two epitopes on the same antigen [129]. Another approach, which is explored in paper
II and III in this thesis, is to fuse two domains that interact with each other, in order to create a
self-blocking affinity protein, which is inactive until it undergoes site-specific proteolysis within
the linker region. This can either be used as a prodrug with the aim to reduce on-target related
side effects (paper II), or as a tool for substrate profiling of proteases (paper III).
A large number of proteins have been investigated as potential scaffolds for new affinity proteins
and some examples are Adnectins (based on a fibronectin domain) [130, 131], Affibody molecules
(derived from staphylococcal protein A) [132, 133], Anticalins (derived from lipocalins) [134, 135]
and DARPins (based on ankyrin-repeat proteins) [136, 137] among many others [138]. Affibody
molecules have been used in this thesis and will therefore be described in more detail below.
The engineering of alternative scaffold proteins is commonly carried out by directed evolution
approaches. Often, fixed positions within the scaffold protein are targeted for randomization,
followed by isolation of interesting candidates by different selection or screening methods. One
of the most well-established selection methods for engineering of affinity proteins is phage
display [139, 140]. Here, the proteins are displayed on the surface of phage particles. The phage
particles that display library members with affinity for the target protein are captured to a solid
support. Another selection method is ribosome display [141, 142], where the proteins are
physically linked to their corresponding mRNAs. Also here, the variants with affinity for the
target are captured to a solid support. Since this method does not require insertion of the
recombinant DNA into a host organism, it can theoretically allow for very large libraries. Many of
the screening methods instead rely on expression of the proteins on the surface of cells, such as
yeast [143], bacterial [144], and mammalian [145] display. The large particle size and multivalent
display enables the use of FACS, thus allowing for additional control and monitoring of the
enrichment. In addition to the display systems, intracellular methods, such as protein
complementation assays (PCA), have also been developed [146, 147]. However, all the methods
mentioned above rely on prolonged capture of a ligand. Therefore, they primarily select/screen
for target binding and not any final mechanism of action of the affinity proteins, which could be
desirable in some applications. In an attempt to take the engineering of affinity proteins one step
further, we investigated another approach, which aims to screen directly for function instead of
binding (paper IV).
Page | 21
Bacteria-based methods for engineering and characterization of proteases and affinity proteins
Affibody molecules
Affibody molecules are derived from the B-domain of staphylococcal protein A [148] that was
engineered for improved chemical stability. This resulted in the Z-domain [149], which is a small
(6.5 kDa) and cysteine-free three-helix bundle made up by a single polypeptide of 58 amino
acids. Libraries of Affibody molecules are typically generated by randomizing 13 surface-located
positions in helix one and two (fig. 7) [133, 150]. Affibody molecules generally possess high
stability, solubility, and ease of production in prokaryotic hosts and by chemical synthesis [132,
151]. Affibody molecules have been extensively investigated as candidates for in vivo molecular
imaging [124] and to a less extent also for therapy, e.g. targeted payload delivery [152, 153].
Additionally, other applications such as affinity chromatography [154, 155], protein microarrays
[156], biosensors [157], and different fluorescence-based assays [158, 159] among various others
[132, 151] have also been investigated.
Several selection and screening methods such as phage display [133], staphylococcal display
[160], microbead display [161], ribosome display [162], and a protein complementation assay
(PCA) [147] have been employed for the generation of Affibody molecules with affinities to a
range of targets including, but not limited to, EGFR, HER2, TNF-", and the amyloid-! peptide
[132, 147, 160, 163-165].
Helix 1
Helix 2
Helix 3
Figure 7: The structure of an Affibody molecule. Highlighted in gold are the 13 positions in helix 1 and
2 that are typically targeted for randomization. The figure is generated from a structure of the Z domain
(PDB ID 2SPZ) with the UCSF Chimera package.
Page |22
PRESENT INVESTIGATION
Lisa Sandersjöö
Aims of the thesis
The general aim of this thesis was to develop new methods and concepts for protein engineering
and characterization.
Paper I
The aim of this study was to develop a new selection method for characterization and engineering
of proteases. The method is based on cytoplasmic expression of a protease and a reporter in E.
coli.
Paper II
The aim of this study was to develop a prodrug concept for Affibody molecules to potentially
reduce on-target related side effects in future in vivo studies. The concept is based on intramolecular masking of a target-binding domain until activation by site-specific proteolysis.
Paper III
The aim of this study was to develop a method for substrate profiling of proteases. The method is
based on display of substrates on the surface of S. carnosus.
Paper IV
The aim of this study was to develop a screening method for protein-based aggregation
inhibitors. The method is based on cytoplasmic expression of an aggregation prone peptide and
potential inhibitors in E. coli.
Page | 25
Bacteria-based methods for engineering and characterization of proteases and affinity proteins
A protease substrate profiling method that links site-specific
proteolysis with antibiotic resistance (paper I)
There are two commonly used approaches to isolate interesting variants from large libraries. The
libraries can either be sampled by examining each member individually (screening) or by
applying conditions, which simultaneously test all members and only allow for the clones with
desirable properties to appear (selection). The choice of method typically depends on how
frequent the useful variants are in the libraries, and on the availability of suitable methods.
Although the high-throughout screening methods (typically flow cytometry-based) have been
very successful in both protease engineering [103, 166] and protease substrate profiling [77],
selection based on growth advantage in bacteria could, at least in theory, handle larger numbers
of mutants since it is only limited by the transformation frequency and not the throughput rate of
a flow cytometer. Additionally, survival systems also offer the advantage of coupling of the
selection and amplification steps.
We therefore sought to evolve a successful screening method (fig. 4b) [76] into a selection
method, which is based on survival instead of fluorescence, with the aim to develop a convenient
and high-throughput platform for characterization and engineering of proteases. The two
methods are compatible with shared restriction sites flanking the region where the library is
inserted. This would then allow us to do pre-enrichments from large libraries with the selection
method and then easily transfer the resulting pool to the screening method, in which the sorting
parameters can be more fine-tuned.
In this novel selection method, we used genetically encoded short-lived reporter proteins that
confer resistance to an antibiotic upon site-specific proteolysis, but are rapidly degraded in
absence of site-specific proteolysis. The key feature of this method is its use of the inbuilt
degradation machinery within E. coli cells. A degradation tag, the ssrA tag, is added to proteins
that should be targeted for degradation by intracellular proteases such as Clp(X/A)P [167]. We
used an extended ssrA tag, which contains two extra amino acids (AANDENYNYALAA) and has
been shown to give a more efficient degradation of the tagged proteins [168]. Chloramphenicol
acetyltransferase (CAT), an enzyme that confers resistance to chloramphenicol (Cml), is used as
the reporter for proteolysis. CAT is fused to a substrate peptide and the ssrA tag at the C-terminal
end, thereby rendering the entire reporter a substrate for ClpXP. The reporter and the protease
are co-expressed in E. coli, and if site-specific proteolysis occurs, CAT is released from the
degradation tag and thus escapes degradation. Consequently, the bacteria will gain resistance to
Cml and exhibit growth advantage in media supplemented with Cml, as opposed to those cells in
which there is no site-specific proteolysis of the substrate (fig. 8).
Page |26
Lisa Sandersjöö
ClpX
Site-specific
proteolysis
ClpP
Protease
CAT
ssrA
No site-specific
proteolysis
ClpX
ClpP
Figure 8: Schematic overview of the antibiotic resistance-based proteolysis assay. A protease
and a reporter, which contains a substrate peptide, are co-expressed in E. coli cells. The reporter contains the
enzyme CAT, which confers resistance to Cml, fused to the substrate peptide and the ssrA degradation tag at
the C-terminal, thus rendering the entire reporter a substrate for intracellular proteases, such as ClpXP.
Cells, in which site-specific proteolysis occurs within the reporter, will be able to grow in presence of Cml
since CAT escapes degradation when the ssrA tag is cleaved off (upper part). The cells, in which no sitespecific proteolysis occurs, will not grow in presence of Cml since the entire reporter, including CAT, is
degraded (lower part).
When developing the assay, we used the tobacco etch virus protease (TEVp), which is often used
in biotechnology research, in particular for removal of affinity tags, due to its stringent substrate
specificity and activity under a wide range of conditions [169, 170]. TEVp recognizes the
substrate sequence ENLYFQ"G/S [171] and cleaves the bond indicated with an arrow. The
substrate peptides ENLYFQV and ENLYFQP are processed with intermediate and poor
efficiency, respectively [172].
Page | 27
Bacteria-based methods for engineering and characterization of proteases and affinity proteins
Using this approach, we could demonstrate that cells co-expressing TEVp and reporters with a
cleavable substrate peptide could grow on agar plates (fig. 9a) and in liquid media (fig. 9b)
supplemented with Cml, as opposed to cells co-expressing TEVp and a reporter without a
substrate peptide. Additionally, when different substrate peptides were introduced in the
reporter, the growth rate of the bacteria correlated with the processing efficiency of the different
substrate peptides by TEVp (fig. 9c). Moreover, co-expression of an inactive variant of TEVp and
a reporter with a cleavable substrate peptide did not support cell growth (fig. 9c).
a
CAT-ssrA (neg ctrl)
CAT-subG-ssrA
CAT-subG (pos ctrl)
!
b
c
&
OD 600
OD 600
CAT-subG-ssrA
CAT-ssrA (neg ctrl)
CAT-subG (pos ctrl)
CAT-subG-ssrA
CAT-subP-ssrA
CAT-subV-ssrA
CAT-ssrA (neg ctrl)
CAT-subG (pos ctrl)
CAT-subG-ssrA TEVp-D81N
"
%
!
Time (h)
!
"
#
$
Time (h)
Figure 9: Substrate peptide cleavage supports cell growth in selective media. a) and b) Bacteria
co-expressing TEVp and either of CAT-subG-ssrA (blue), the negative control CAT-ssrA, which lacks a
substrate peptide (red), or the positive control CAT-subG, which lacks the degradation tag (green) were
spread on agar plates (a) or inoculated in LB media (b) supplemented with Cml. c) Cells co-expressing TEVp
and either a reporter containing the substrate peptides subG (blue), subV (purple), subP (cyan), or the
positive control (green), or the negative control (red) were grown in Cml-containing LB media. Cells coexpressing an inactive TEVp variant and the reporter CAT-subG-ssrA (black) were also included. Growth
was followed over time by OD600 measurements. SubX represents the substrate peptide ENLYFQX.
Page |28
Lisa Sandersjöö
In a model selection experiment, we could demonstrate that by applying competitive growth in
selective media, the bacteria that expressed the preferred substrate peptide were enriched from a
background of cells expressing substrates that are less efficiently hydrolyzed (fig. 10).
a
&!!
!"#$"%&'(")*+,
%!
$!
-2345678455#2
"!
-234567!455#2
#!
!
-23455#2
!
'
(
%
)*+,-./0
b
-.%&#./0)%.)-1/
&!!
!"#$"%&'(")*+,
%!
$!
-2345678455#2
"!
-234567!455#2
#!
!
-23455#2
!
'
(
%
)*+,-./0
Figure 10: Enrichment of cells expressing an efficiently processed substrate from a
background of cells expressing substrates that are less efficiently hydrolyzed. Cells coexpressing TEVp and either CAT-subG-ssrA (blue), CAT-subP-ssrA (orange), or CAT-ssrA (red) were mixed
at an approximate ratio of 1:2:2 before being inoculated into media with (a) or without (b) Cml. Shown are
the clonal distribution of the cultures at different time points during selection as determined by DNA
sequencing. SubX represents the substrate peptide ENLYFQX.
Page | 29
Bacteria-based methods for engineering and characterization of proteases and affinity proteins
In this project, we sought to develop a convenient high-throughput method for characterization
and engineering of proteases. In theory, the method offers (i) substrate profiling of proteases by
insertion of different substrate peptides between CAT and the ssrA tag or (ii) engineering of
proteases by introduction of protease libraries along with a constant substrate peptide or (iii) a
combination thereof. However, simple in theory, the method proved to be more challenging in
practice. Even though there was a clear difference in the growth rates for the different variants
when grown as individual cultures and we could perform a model selection experiment, it proved
difficult to select for cells expressing a functional protease and substrate combination from a
large background of cells expressing suboptimal combinations due to the growth of false
positives.
Reasons for the growth of false positives could possibly be due to unfavorable events that slow
down or block the degradation of ssrA-tagged proteins, thus enabling ssrA-tagged CAT to
accumulate in the cell and confer resistance to Cml. Since the number of ClpXP proteases is
limited in a cell (ca 100 copies, [173]), these proteases might be saturated in presence of high
levels of ssrA tagged proteins. Genomic mutations in either clpX or clpP, encoding for ClpXP, or
sspB that encodes for the protein sspB, which assists in the delivery of ssrA-tagged substrates to
ClpX [174], could potentially also slow down degradation of CAT. Some of these issues could
perhaps be addressed by adjusting the expression levels of TEVp, the reporter, and ClpXP to find
a suitable balance between substrate cleavage by TEVp and degradation by ClpXP. This could be
done by overexpression of ClpXP and by altering induction conditions, promoter strengths, and
plasmid copy numbers, but would require extensive optimizations.
Another potential problem when inserting libraries of substrate peptides is the risk for
premature stop codons or frameshifts between CAT and the ssrA tag, which would lead to false
positives due to lack of the ssrA tag. One way to circumvent this is to use an N-terminal
degradation tag instead. Such tags are available, for example the RepA tag, which directs proteins
to ClpAP, but tend to be less efficient than the ssrA tag [175]. Additionally, the recent
advancements in the synthesis of oligonucleotides have resulted in a higher quality of the
libraries, thereby reducing the risk for premature stop codons.
In summary, we have demonstrated the concept for a selection method based on competitive
growth in selective media. A short-lived reporter with a protease-sensitive peptide is coexpressed with the protease of interest in the cytoplasm of E. coli. Clones, in which site-specific
proteolysis occurs acquire resistance to Cml, thus enabling straightforward identification of
proteolysis simply by growth in presence of Cml. Selection based on survival is attractive due to
its high throughput and that it is less labor-intense compared to screening methods. However, a
selection pressure based on survival is also complicated due to the higher tendency to generate
false positives. Nevertheless, our results show that the concept works in principle and with more
investigations focusing on modifications and optimizations, it could potentially be further
developed into a functional selection method.
Page |30
Lisa Sandersjöö
A new prodrug form of Affibody molecules (pro-Affibody) is
selectively activated by cancer-associated proteases (paper II)
The upregulation of proteases in several disease conditions make them suitable candidates for
the activation of prodrugs. In this study, we aimed to develop a prodrug strategy for improving
the tissue selectivity of Affibody molecules for future in vivo studies. Tissue selectivity is
important when the target protein is expressed in both tumor and healthy tissue. Binding of a
drug to the target in healthy tissue might result in undesired toxicity.
To investigate the potential of creating a ‘‘prodrug-like’’ Affibody molecule (pro-Affibody), we
fused a “targeting” Affibody molecule to a “blocking” Affibody molecule. A linker containing a
protease substrate connects the two Affibody molecules. We used a high-affinity HER2-targeting
Affibody molecule (ZHER2) and its anti-idiotypic partner (anti-ZHER2). The new pro-Affibody is
thus composed of: (1) a targeting domain (ZHER2), (2) a blocking domain (anti-ZHER2), and (3) a
protease-cleavable linker (fig. 11). We decided to use matrix metalloprotease 1 (MMP-1) as the
protease for activation due to its recurrent upregulation in breast cancer [176] and that the
upregulation is associated with high HER2 expression in breast cancer cells [177].
An important aspect to consider is the affinity between the targeting domain and the target
(ZHER2 and HER2) relative to the affinity between the targeting domain and the blocking domain
(ZHER2 and anti-ZHER2). The covalent linkage drives the equilibrium towards the blocked state due
to the high local concentration. Therefore, the blocking domain can have a much weaker affinity
than that between the target and the targeting domain. The blocking domain should have a fast
off-rate to enable rapid dissociation upon proteolysis (fig. 11). In this pro-Affibody, we used a
high affinity (22 pM) HER2-targeting Affibody molecule, and a blocking domain with relatively
fast off-rate (0.058 s-1).
Page | 31
Bacteria-based methods for engineering and characterization of proteases and affinity proteins
a
Without protease
Target binding
Affibody molecule
Target protein
Blocking
Affibody molecule
With protease
Linker with
protease site
Protease
b
Proteolysis of linker
c
/%".&01'&+**2%'%()#%**+,$'&"#$%&3'
42&',5&')#5&%"*%
!"#$%&'%()#%**+,$'
,5#:".'-%..'
6+*%"*%7'&+**2%'8%9$9'&2:5#;
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)*+,&"#$%&#'(
!"#$%&#'(
!"#$%&'%()#%**+,$'
-",-%#'-%..'
Figure 11: Schematic illustration of the pro-Affibody concept. a) The pro-Affibody is composed of a
target binding Affibody molecule (green) and an anti-idiotypic Affibody molecule (purple) fused via a
protease-cleavable linker. The masking domain (purple) is intended to block the antigen-binding surface of
the target binding Affibody molecule from interacting with its target and thus prevent target binding until
selective proteolysis releases the masking domain and restores the binding capacity of the Affibody molecule.
b) Fusion of the masking domain to the target-binding domain increases the local concentration, thus
shifting the equilibrium towards the bound (blocked) state. After hydrolysis of the linker, the blocking
domain is free to diffuse upon dissociation, thus shifting the equilibrium towards the free (active) state. c)
The target-binding domain of the pro-Affibody will only be able to bind to its target upon activation of the
pro-Affibody by proteases, which are upregulated in diseased tissue, thereby potentially reducing side effects
caused by on-target, but off-tissue binding.
Page |32
Lisa Sandersjöö
To engineer the pro-Affibody, we used a bacterial display technology in combination with flow
cytometry [178] since it omits the purification step of recombinant proteins before analysis, thus
increasing the throughput of the assay. In this technology, the pro-Affibody is displayed on the
surface of the Gram-positive bacteria Staphylococcus carnosus (S. carnosus) in fusion to a
reporter tag for simultaneous monitoring of the surface expression. By treating the bacterial cells
with protease (MMP-1) before incubation with labeled HER2, the proteolytic cleavage can be
analyzed by flow cytometry (fig. 12a).
1. No activation
2. Activation by proteolysis
Hypothetic dot plot from
flow cytometric analysis
Target binding
a
Target
Z2
Target
Z1
Z2
Z1
2
1
HSA ABP
HSA ABP
Surface expression level
(HSA binding)
S. carnosus
S. carnosus
b
2
HER2 binding
HER2 binding
c
10
1
10
10
0
10
0
10
1
10
2
10
1
10
10
0
2
10
0
10
1
10
1234(5,.6,.7
d
3
10
2
8&9,0%9'6(5:(;;<=
2
10
10
1
0
0
10
0
10
1
10
2
!"#$%&'(')*#'++,-.(/'0'/
10
1234(5,.6,.7
% of maximum binding
10
Surface expression level
Surface expression level
3
10
3
8-9(%&9,0%9'6
2
10
10
1
0
0
10
10
0
10
1
10
2
!"#$%&'(')*#'++,-.(/'0'/
10
3
HER2 (nM)
Figure 12: Staphylococcal surface display for characterization of the pro-Affibody. a)
Schematic illustration of the staphylococcal surface display technology when displaying a pro-Affibody and
a hypothetic dot plot from flow cytometry. Bacteria are incubated with target and HSA, labeled with two
different fluorophores, for simultaneous analysis of target binding and surface expression by flow cytometry.
Bacteria displaying the non-activated pro-Affibody exhibit the signal for surface expression only (1), while
bacteria displaying the pro-Affibody, which has been activated by recombinant protease exhibit signals for
both surface expression and target binding (2). b) Representative density plot of bacteria displaying the nonactivated pro-Affibody analyzed by flow cytometry. c) Representative density plot of bacteria displaying the
pro-Affibody, which has been activated by MMP-1, analyzed by flow cytometry d) Binding to HER2 of
activated (green) or non-activated pro-Affibody (red). The concentration of HER2 was titrated from 0.1 to
1000 nM. Data was fitted by non-linear regression to a 1:1 binding model.
Page | 33
Bacteria-based methods for engineering and characterization of proteases and affinity proteins
We began by determining if the anti-idiotypic Affibody (anti-ZHER2) could block the interaction
between ZHER2 and the HER2 receptor. Bacteria displaying the pro-Affibody were therefore
incubated with labeled HER2 and analyzed with flow cytometry. For comparison, another
sample, in which the bacteria were treated with MMP-1 prior to incubation with labeled HER2,
was also analyzed. The results demonstrated that the blocking domain indeed inhibited binding
of ZHER2 to HER2 (fig. 12b) whereas the MMP-1 treated pro-Affibody was activated and regained
its binding activity towards HER2 (fig. 12c). The pro-Affibody was engineered to find a suitable
linker and substrate peptide and the best-performing variant demonstrated over 1,000-fold
difference in apparent affinity between non-activated and activated pro-Affibody, when displayed
on the bacterial surface (fig. 12d). In summary, these experiments demonstrated that the nonactivated pro-Affibody was efficiently masked from binding to HER2, and that proteolysis by
MMP-1 activated the targeting domain.
To verify the results obtained with the surface-displayed pro-Affibody, we expressed and purified
the pro-Affibody and analyzed it as a soluble protein. After treatment with MMP-1, SDS-PAGE
analysis showed two bands of expected sizes, indicating site-specific hydrolysis of the substrate
peptide within the linker (fig 13a).
The soluble pro-Affibody was further characterized with Surface Plasmon Resonance (SPR)based biosensor technology, to investigate the masking and activation of the pro-Affibody in
more detail. Protease-activated and non-activated pro-Affibody molecules were injected over a
sensor chip with HER2 immobilized on the surface. For comparison, the original monomeric
ZHER2 was also included in the experiment. The activated pro-Affibody demonstrated a high
response followed by a slow dissociation, while the non-activated pro-Affibody yielded a very low
signal, despite the relatively high concentration (100 nM) that was injected (fig. 13b). The
sensorgrams of the activated pro-Affibody and the original HER2 binder (ZHER2) were nearly
identical with a somewhat decreased apparent on-rate for the activated pro-Affibody (fig. 13b).
We reasoned that this might be due to the presence of the blocking domain in the solution, which
could slightly reduce the active concentration of ZHER2. We therefore injected an equimolar mix of
the two monomeric domains (ZHER2 and anti-ZHER2), which resulted in an essentially identical
sensorgram as for the activated pro-Affibody, thus confirming the hypothesis (fig. 13b). To be
able to study any potential weak interaction between the non-activated pro-Affibody and HER2,
the concentration of both the activated and the non-activated pro-Affibody was increased up to
900 nM. The activated pro-Affibody was saturated already at 100 nM and generated similar
responses for 300 and 900 nM. The non-activated pro-Affibody demonstrated weak binding at
the higher concentrations, although much weaker than the activated variant (fig. 13c).
Importantly, these results confirmed that masking of the pro-Affibody primarily affected the
association rate, which was considerably reduced, while the dissociation was basically unaffected,
as expected (fig. 13c).
Page |34
Lisa Sandersjöö
b
c
20.1
14.4
M
1
2
a
Figure 13: Characterization of soluble non-activated and protease-activated pro-Affibody. a)
SDS-PAGE of non-activated (1) and activated pro-Affibody (2). M represents molecular weight marker with
indicated sizes in kDa. b) Sensorgram from SPR experiments with HER2 immobilized on the chip surface.
Shown is the response from 100 nM of the activated (green) and non-activated pro-Affibody (red), the HER2binding Affibody molecule (ZHER2) (blue) and the two non-fused monomeric domains of the pro-Affibody
mixed in an equimolar ratio (black). c) Sensorgram from SPR experiments with HER2 immobilized on the
chip surface. The response from 100, 300 and 900 nM of the activated (green) and non-activated proAffibody (red) is shown.
For future tumor-targeting studies in vivo, we also wanted to verify binding to native HER2 on
cancer cells. The ability of activated and non-activated pro-Affibody to bind to HER2overexpressing SKOV3 cells was therefore analyzed by flow cytometry (fig. 14a). The proAffibody was treated with MMP-1 (activated) or buffer (non-activated) before being incubated
with the cells, which were then analyzed by flow cytometry. The cells that had been incubated
with the activated pro-Affibody showed a large increase in fluorescence intensity compared to
those incubated with the non-activated pro-Affibody, thus confirming that the masking and the
activation worked as intended and that the activated pro-Affibody was able to target native HER2
on cancer cells (fig. 14b).
a
./012'34523(6
7'34523(6
b
2(3#'
150
*+,-
*+,-
100
50
0
!"#$%&'())
!"#$%&'())
10
1
10
2
10
3
!"#$"#%&'(&)*+,-&./001
Figure 14: Flow cytometric analysis of binding to cancer cells of the pro-Affibody. a) The proAffibody was treated with MMP-1 (activated) or buffer (non-activated) before HER2-overexpressing SKOV3
cells were labeled with the non-activated or the activated pro-Affibody followed by a fluorescently labeled
anti-Affibody antibody. b) Representative histograms from flow-cytometric analysis of binding to SKOV3
cells of activated (green) and non-activated (red) pro-Affibody.
Page | 35
Bacteria-based methods for engineering and characterization of proteases and affinity proteins
In summary, we have developed a new prodrug strategy for Affibody molecules (pro-Affibody), in
which the targeting domain is blocked from interacting with its target until the pro-Affibody is
activated by site-specific proteolysis. After successfully demonstrating the concept for a HER2targeting pro-Affibody, we believe that the concept can be easily extended to other Affibody
molecules, given the straightforward generation of anti-idiotypes. We reasoned that using a small
protein-domain, which has a stable three-dimensional structure, as blocker rather than a linear
peptide could possibly minimize potential unspecific proteolysis in serum. Additionally, the small
size and stability of Affibody molecules facilitates the construction of multi-domain constructs.
This prodrug approach, in which anti-idiotypic blocking domains are used, is probably not only
efficient for Affibody molecules; it could also be applicable to other small affinity proteins (e.g.
Adnectins, Anticalins, Darpins, etc.) as long as there is a straightforward way to generate the
anti-idiotypes.
This prodrug concept is highly relevant for affinity proteins targeting receptors such as HER3
and EGFR where the difference in expression levels of diseased tissue and healthy tissue are
smaller than for HER2. The EGFR-targeting antibody cetuximab for example causes dose
limiting skin toxicity due to the widespread expression of EGFR in the skin [179, 180]. A prodrug
variant of cetuximab that is masked by a protease-sensitive peptide has been investigated in
preclinical studies. It demonstrated similar efficacy as cetuximab and reduced toxicity [114]. A
prodrug approach with activation in diseased tissue only could be especially important for
targeted delivery of payloads where even a low dose may cause toxicity to normal cells. For
instance, an antibody drug conjugate (ADC) targeting CD44v6, which is also expressed in healthy
skin, caused such severe skin toxicity in early clinical trials that the study had to be terminated
[181].
In this proof-of-concept study we used MMP-1 for activation since its upregulation is associated
with high HER2 expression in cancer cells. However, the optimal protease and substrate peptide
for each disease, as well as the stability towards endogenous proteases has to be extensively
investigated to get selective activation in diseased tissue. Nonetheless, the fact that the
upregulation of a wide range of proteases is associated with various disease conditions and
therefore could be used for the activation of prodrugs is likely to increase the applicability of the
strategy.
Page |36
Lisa Sandersjöö
Bacterial display of self-blocking affinity proteins for efficient
protease substrate profiling (paper III)
Based on the results from paper I, where intracellular expression of both protease and substrate
proved challenging, potentially due to lack of control of reaction conditions, and the results in
paper II, where proteolytic processing of a substrate peptide within a surface-displayed proAffibody increased the cell’s fluorescence upon labeling with a fluorescent target, we sought to
develop another bacteria-based method for substrate profiling of proteases.
In this approach, the substrate is located in a linker that connects two domains. One of the
domains masks the other from binding to the reporter HER2 as long as the linker is intact. Upon
site-specific proteolysis of the substrate within the linker, the masking domain will diffuse away.
Thereby, the remaining domain can bind to a reporter. The fusion protein is displayed on the
surface of the Gram-positive bacteria S. carnosus in fusion to an albumin binding protein, ABP,
used as a spacer and for monitoring of the surface expression level. By addition of fluorescently
labeled reporter, the proteolysis can be analyzed by flow cytometry (fig. 15). Compared to
another similar method (CLiPS, which was described in the introduction), here the proteolysis
results in an increase instead of loss of the fluorescence, which could potentially reduce the risk
AntiZHER2
HER2
ZHER2
substrate library
HSA
AntiZHER2 ZHER2
ABP
Reporter (HER2) binding
of enriching for false positives.
Cleavable substrate
Surface expression level
(HSA binding)
S. carnosus
HER2
Non-cleavable
substrate
AntiZHER2 Z
HER2
HSA
ABP
Reporter (HER2) binding
ABP
Surface expression level
(HSA binding)
Figure 15: Schematic overview of the assay for substrate profiling of proteases. Substrate
peptides are displayed on the surface of S. carnosus within a linker that connects two domains, where one
(ZHER2) has affinity to the reporter HER2, whereas the other (anti-ZHER2) has affinity to ZHER2, thus blocking
its interaction with the reporter. If the substrate within the linker is processed by the protease, the blocking
domain will diffuse away and enable reporter binding (upper part). If the substrate is not cleaved, reporter
binding will remain blocked (lower part). Therefore, proteolysis is reflected in reporter binding, which can be
analyzed by flow cytometry after incubation with fluorescent reporter.
Page | 37
Bacteria-based methods for engineering and characterization of proteases and affinity proteins
We again used TEVp as a model protease when testing the concept. We introduced the same
three substrate peptides as in paper I, ENLYFQG, ENLYFQV and ENLYFQP, and analyzed the
protease-treated cells by flow cytometry. As anticipated, the efficiency by which TEVp processes
the substrate peptides was reflected in reporter binding (fig. 16a). Additionally, simply by
adjusting the concentration of TEVp, we could increase the difference between the optimal
substrate ENLYFQG and the moderate substrate ENLYFQV (fig. 16b), which was not that
straightforward in paper I.
10
2
10
1
10
0
ENLYFQG
10
0
10
1
10
2
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10
3
10
2
10
1
10
0
3
10
Surface expression level
10
3
10
2
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1
10
0
ENLYFQG
10
0
10
1
10
2
10
Surface expression level
0
10
1
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10
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Surface expression level
ENLYFQV
10
ENLYFQP
10
Surface expression level
Reporter binding
Reporter binding
b
ENLYFQV
Reporter binding
3
Reporter binding
10
Reporter binding
Reporter binding
a
3
Surface expression level
10
3
10
2
10
1
10
0
ENLYFQP
10
0
10
1
10
2
10
3
Surface expression level
Figure 16: Proteolytic processing is reflected in reporter binding. a) Density plots after proteolytic
processing of three different substrate peptides by TEVp. Reporter (HER2) binding is shown on the y-axis
and surface expression (HSA binding) is shown on the x-axis. b) Same as in a, but with lower concentration
of TEVp and shorter time of proteolysis.
Encouraged by these results and a model screening experiment, in which we could enrich for
cells displaying the preferred substrate (ENLYFQG) from a large background of cells expressing a
less efficiently hydrolyzed substrate (ENLYFQP), we decided to construct a library of various
TEVp substrate peptides. Three positions were randomized (P6, P3, P1 that are considered to be
important specificity determinants within the substrate) (fig. 17a) to see if we could enrich for the
preferred substrate in a library setting. After two rounds of sorting (fig. 17b), the majority of the
clones contained the preferred substrate ENLYFQG. Additionally, one other substrate was
present, but this was shown to be as inefficiently hydrolyzed as the substrates ENLYFQV and
ENLYFQP when the clones were analyzed separately (fig. 17c).
Page |38
Lisa Sandersjöö
a
N
L
Y
F
Q
G/S
P5
P4
P3
P2
P1
P1’
X
N
L
X
F
X
G
10
2
10
1
Reporter binding
3
10
1
10
2
10
3
10
4
10
10
4
10
3
10
2
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1
5
Sorting round 2
10
1
10
2
10
3
10
4
10
5
Surface expression level
1.0
Without TEVp
With TEVp
0.5
G
FQ
LD
FN
G
LN
EN
LY
sc
trl
0.0
Po
c
Reporter binding / surface expression
Surface expression level
5
P
10
10
Library design
FQ
4
V
10
Sorting round 1
TEV substrate
EN
LY
5
FQ
10
EN
LY
Reporter binding
b
E
P6
Figure 17: Enrichment of an efficiently hydrolyzed TEVp substrate. a) Schematic illustration of the
library design. Positions P6, P3 and P1 in the TEVp substrate (upper part) were targeted for randomization
to generate the library (lower part). b) Density plots from flow cytometric sorting of the TEVp substrate
library. The signal for proteolysis (HER2 binding) is shown on the y-axis and surface expression (HSA
binding) is shown on the x-axis. c) Flow cytometric analysis of different TEVp substrates as indicated in the
figure. Monomeric ZHER2 is used as positive control. The columns show values of reporter binding normalized
against surface expression level.
We then used this approach in an effort to investigate the substrate preference of MMP-1, which
was used for activation of the pro-Affibody in paper II. Based on the cleavage site sequence logo
for MMP-1 in the Merops database [182], where there is a slight preference for proline in the P3
position and leucine in the P1’ position, we decided to construct two libraries in which one of
these positions was held constant in each library (fig. 18a).
Page | 39
Bacteria-based methods for engineering and characterization of proteases and affinity proteins
After five rounds of sorting with increased stringency (lower protease concentration or shorter
time) in later rounds (fig. 18b), we identified several clones with substrate peptides that were
more efficiently processed than the substrate we used within the pro-Affibody in paper II. Most
of the clones contained the motif PXXXHy, where XHy is a hydrophobic amino acid. This motif has
previously been shown to be hydrolyzed by MMPs [70], thus further demonstrating the ability of
the method to isolate clones displaying efficiently processed substrates. After an initial analysis
of all the individual clones, we picked a few interesting candidates to be analyzed in more detail.
By following the reaction over time for different protease concentrations, we could determine the
apparent kcat/KM for the different substrates. All the tested substrates had values 6-8 fold higher
than the substrate that was used in the pro-Affibody. The substrate used in the pro-Affibody had
an apparent kcat/KM value of 0,5 #M-1 h-1 when displayed on the cell surface. This is in the same
range as a previously reported value for that peptide sequence (1,40 #M-1 h-1) [183].
a
P
X
X
X
X
X
A
P3
P2
P1
P1’
P2’
P3’
P4’
G
X
X
X
L
X
X
A
P4
P3
P2
P1
P1’
P2’
P3’
P4’
Sorting round 2
Sorting round 3
1
0
10
-1
10
-1
10
0
10
1
10
2
10
Surface expression level
3
10
Sorting round 4
10
2
102
102
10
1
10
0
10
-1
10
-1
10
0
10
1
10
2
10
Surface expression level
3
10
10
1
10
0
10-1
10
-1
10
0
10
1
10
2
Surface expression level
10
3
Sorting round 5
3
103
Reporter binding
Reporter binding
Reporter binding
2
10
MMP library 2
3
10
10
MMP library 1
10
1
10
0
10
-1
Reporter binding
Sorting round 1
3
10
Reporter binding
b
G
P4
10-1
100
101
102
Surface expression level
103
10
3
10
2
10
1
10
0
10
-1
-1
10
10
0
10
1
2
10
Surface expression level
3
10
Figure 18: Flow cytometric screening of substrate libraries processed by MMP-1. a) Schematic
illustration of the library design. Positions P3 or P1’ were held constant in one library each. b) Density plots
from flow cytometric sorting of library 1 (the track in which the concentration was decreased in round 3 and
4). The signal for proteolysis (HER2 binding) is shown on the y-axis and surface expression (HSA binding) is
shown on the x-axis.
Page |40
Lisa Sandersjöö
In summary, we have developed a new method for substrate profiling of proteases, in which the
substrate is displayed on the surface of bacteria and located in between two protein domains. As
long as the substrate is intact, one domain will mask the other from binding to a fluorescent
reporter. Proteolysis will enable reporter binding, thus resulting in increased fluorescence of the
bacterial cell. Compared to the method presented in paper I, this one offers enhanced control
over the reaction conditions since the protease is added exogenously and the surface expression
level can be monitored. Like other high-throughput methods, this one gives no information on
where the scissile bond is located, but to obtain this information the part that is cleaved off from
the surface could be analyzed by MS.
We believe that this assay could be used for substrate profiling of proteases in general, and also
in the search for substrates for future pro-Affibodies in particular. However, one important factor
that has to be considered and further investigated is how selective a substrate is for the protease
of interest. When using the substrate for activation of prodrugs, it should “only” be cleaved by the
protease of interest and not by other endogenous proteases. One approach to achieve this is to
alter between positive screenings using the intended protease and negative screenings using nonpreferred proteases. Another approach is to screen the outcome against different proteases and
then move on only with the variants that are selectively hydrolyzed by the protease of interest. To
be able to screen against multiple proteases simultaneously, cell lysates with an inhibitor for the
protease of interest added, could be used.
Page | 41
Bacteria-based methods for engineering and characterization of proteases and affinity proteins
A new bacterial intracellular screening assay for discovery of
protein-based aggregation inhibitors (paper IV)
Most affinity proteins used as pharmaceuticals are selected mainly based on their affinity without
taking into account the final and desired mechanism of action. This could for example be the
capacity to inhibit the aggregation of peptides/proteins that are involved in disorders like
Alzheimer’s and Parkinson’s disease. In this study, we sought to develop a method that is based
on direct functional screening for aggregation-inhibition capacity with focus on aggregation
inhibitors of the amyloid beta (A!) peptide, which is involved in Alzheimer’s disease. To achieve
this, the aggregation behavior of the A! peptide must be coupled to a readily measurable
property.
It has previously been demonstrated that when proteins are N-terminally fused to green
fluorescent protein (GFP) and expressed in E. coli, the fluorescence intensity of the cells
correlates with the solubility of the N-terminal passenger protein [106]. Additionally, when the
A! peptide was fused to GFP and expressed in E. coli, the cells exhibited decreased fluorescence
as compared to when more soluble mutants of the A! peptide were fused to GFP [184]. This
feature was later used to screen libraries of small molecular compound in micro-well plates for
identification of aggregation inhibitors [185].
To allow for identification of protein-based inhibitors and to achieve a higher throughput, we
decided to develop a method where the target protein and the aggregation inhibitor are coexpressed in bacteria in combination with isolation of variants with desired traits using FACS.
The concept of the method is based on that the aggregation-prone peptide (AP) is fused to the Nterminal of enhanced GFP (EGFP) and expressed in E. coli cells, thus resulting in aggregation
and consequently decreased fluorescence of the cells. By co-expression of a protein-based
aggregation inhibitor (AI), the AP-GFP fusion will be prevented from aggregation and thereby
the fluorescence is restored (fig. 19). To avoid biases from cell-to-cell variations in expression
levels among variants in future libraries, the inhibitor is fused to another fluorescent protein,
mCherry, thus allowing for normalization of expression levels. Two-color FACS can then be used
to sort out bacterial cells containing inhibitors with a high potency with reduced risk of sorting
for high expression.
Page |42
Lisa Sandersjöö
AP
Genetic constructs:
GFP
Non-aggregated GFP
AP
GFP
Aggregated AP-GFP fusion
Inhibition of AP-GFP aggregation
Expression in E. coli:
AP
AP-GFP
GFP
Fluorescence intensity
AI
GFP
Fluorescence intensity
Restored GFP fluorescence
Counts
Low GFP fluorescence
Counts
High GFP fluorescence
Counts
Flow-cytometric
analysis:
GFP
AI
Fluorescence intensity
Figure 19: Schematic overview of the concept of using GFP as an aggregation reporter in E.
coli. N-terminal fusion of an aggregation-prone peptide (AP) to GFP will result in aggregation and hence
reduced fluorescence. Co-expression of an aggregation inhibitor (AI) will decrease the aggregation, thus
resulting in restored GFP fluorescence.
When developing the method, we used the Alzheimer’s related A!1-42 peptide as the aggregation
prone peptide (AP) together with the dimeric ZA!3 Affibody molecule, which binds to and
prevents aggregation of the A! peptide [164, 186, 187], as the aggregation inhibitor (AI).
When the A!1-42 peptide was fused to GFP and co-expressed with a negative control Affibody
molecule (ZHER2) in the cytoplasm of E. coli, the fluorescence was decreased compared to cells
expressing GFP without an N-terminal fusion (fig. 20). Fusion of a more soluble variant of the A!
peptide (A!1-42F19S/L34P) to GFP did not reduce the fluorescence as dramatically, indicating
that the aggregation properties of the peptide indeed correlate with the intensity of the GFP
fluorescence (fig. 20). When the A!-targeting Affibody molecule instead was co-expressed, there
was a shift in fluorescence as compared to a negative control Affibody molecule (fig. 20).
Page | 43
Bacteria-based methods for engineering and characterization of proteases and affinity proteins
EGFP + ZHER2 !
A1-42F19S/L34P-EGFP + ZHER2
A1-42-EGFP + (ZA3)2
A1-42-EGFP + ZHER2
1000
500
0
100
101
102
103
Figure 20: Aggregation propensity is reflected in GFP fluorescence. Comparison of the
fluorescence intensity of E. coli cells co-expressing a negative control Affibody molecule, ZHER2, and enhanced
GFP (EGFP) without an N-terminal fusion (green), or EGFP fused to the A! peptide (blue), or EGFP fused to
a soluble mutant of the A! peptide (black), or cells expressing the A!-targeting dimeric Affibody molecule
(ZA!3)2 together with EGFP fused to the A! peptide (red).
Different cultivation conditions (including temperature, time and concentrations for induction)
were investigated to find conditions where the difference in fluorescence signal between the
inhibiting and non-inhibiting Affibody molecules were as large as possible. These conditions
were then applied in a model screening experiment, in which cells co-expressing A!-GFP and the
A!-targeting Affibody molecule successfully could be enriched from a large excess of cells coexpressing A!-GFP and the non-inhibitory Affibody molecule (fig. 21).
Figure 21: Enrichment of cells expressing an aggregation inhibitor from a background of cells
expressing a non-inhibitor. Cells co-expressing A!-GFP and either the A!-targeting Affibody molecule or
a non-inhibitory Affibody molecule were mixed at a ratio of 1:10.000 before flow cytometric sorting. Shown
are dotplots before (left) and after (right) one round of sorting.
Page |44
Lisa Sandersjöö
In summary, we have developed a screening method that is intended to allow for the discovery of
protein-based aggregation inhibitors. By expressing both the aggregation prone peptide and the
potential inhibitor intracellularly, the method becomes label-free and precludes the need for
target production, purification and labeling. To allow for more control of the reaction conditions
and be able to fine-tune the expression level of AP-GFP, different promoters could be
investigated, something which is on going.
In this study, the Alzheimer’s related A! peptide and an Affibody molecule, which is known to
inhibit aggregation of A! peptides, were used. It should be possible to also expand the method
into a general technology for discovery of different classes of protein-based inhibitors for
different aggregation-prone targets involved in various diseases.
Page | 45
Bacteria-based methods for engineering and characterization of proteases and affinity proteins
Concluding remarks and future perspectives
The overall focus of this thesis has been development of different methods and concepts for
protein engineering. In paper I and III, the focus for the methods was on substrate profiling and
engineering of proteases. The intracellular expression of protease and substrate in paper I offers
both substrate profiling and engineering in principle, but it proved challenging with a selection
method based on survival due to the growth of false positives. However, this could potentially be
solved by further optimizations of the balance between proteolysis of the substrate and the
degradation machinery that was utilized. In paper III, we decided to display the substrate on the
surface of bacteria instead. This offered better control of the reaction conditions since the
protease was added separately. We could successfully enrich for substrates that were efficiently
processed by two different proteases, but we lost the possibility to use the same method also for
protease engineering. The multivalent expression of the substrate in bacteria makes both the
methods quantitative and we could thus use them for ranking of different substrates. One
limitation is that none of the methods tell us where the scissile bond is located within the
substrate. However, for the method in paper III, the part of the substrate that is cleaved off from
the surface could be analyzed by MS to obtain that information. In general, the engineering of
proteases offers the possibility to use them as catalysts in industrial processes and it has for a
long time been a goal to also use them as therapeutics due to their potential to inactivate several
target molecules, thus potentially offering lower and less frequent dosing. Substrate profiling of
proteases could provide insights into the biology of proteases and help in the design of inhibitors
as well as probes for measuring protease activity that could be used as diagnostics. The method
in paper III could be a valuable tool for the engineering of substrates, which are selectively
hydrolyzed by certain proteases for use in protease-activated prodrugs.
In paper II, the aim was to develop a general prodrug concept for Affibody molecules, in which a
targeting domain is activated upon site-specific proteolysis. This was demonstrated for a HER2
targeting pro-Affibody, which is activated by MMP-1. Based on the results in paper III, the
activation could probably be improved by changing the substrate within the pro-Affibody, but the
stability of the substrate towards other proteases has to be thoroughly investigated before taking
the pro-Affibody any further. This concept should be possible to extend to other alternative
scaffold proteins as long as there is a convenient way to generate the blocking domains. This
opens up for the possibility to target proteins that are over-expressed in diseased tissue, but also
expressed in normal tissue where a conventional affinity protein probably would cause on-target
related side effects. If both the target and the protease need to be expressed to get activation of
the drug, the therapeutic window can be increased. Since proteases have been shown to be locally
upregulated
in
different
diseases
such
as
cancer,
cardiovascular,
autoimmune
and
neurodegenerative disorders, there is a great potential to use them for tissue-selective activation
Page |46
Lisa Sandersjöö
of prodrugs. In the emerging field of antibody drug conjugates (ADC), prodrug approaches have
a great potential since even very small doses may cause toxicity to normal cells.
In paper IV, the aim was to develop a screening method for aggregation inhibitors that is based
on function rather than affinity. Here, intracellular bacterial co-expression was used again, with
GFP as the reporter for the aggregation behavior. This method could potentially also be evolved
into a selection method where the aggregation prone peptide is fused to for example CAT, the
enzyme that confers resistance to Cml that we used in paper I. CAT has previously been used as a
solubility reporter [188]. By fusing proteins to the N-terminal of CAT and express the proteins in
E. coli, the solubility of the passenger protein could be reported simply by growth of the bacteria
in presence of Cml. Even though a selection method based on Cml resistance proved challenging
in paper I, here we do not depend on the degradation machinery, which was used and probably
saturated in the method in paper I. E. coli has several attractive features such as high
transformation frequency, rapid growth rate and that it is a well studied host organism for
recombinant proteins. The concept is likely to be extendable to other host organisms, such as
yeast, to allow for other types of proteins that are not easily expressed in E. coli. In general, the
discovery of agents that can prevent disease-related protein aggregation could lead to new
efficient therapies for treatment of protein-aggregation related disorders, such as Alzheimer’s
and Parkinson’s disease. Hopefully, this method could be a relevant tool for the discovery of such
new candidate therapeutics in the future.
In summary, the work of this thesis has been focused on development of methods and concepts
for engineering and characterization of proteins. Further development of these methods and
concepts has the potential to yield efficient new means for the engineering of proteins with
desired properties to be used in both biotechnological and medical applications.
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Bacteria-based methods for engineering and characterization of proteases and affinity proteins
Populärvetenskaplig sammanfattning
Här kommer en sammanfattning på svenska för er som tappert har försökt förstå vad min
avhandling handlar om, men kanske inte känner er så hemma i protein engineering-världen.
Proteiner är inte bara något man äter för att bygga muskler utan de är väldigt viktiga byggstenar i
våra kroppar där de tar hand om en massa vitala processer. Protein engineering innebär att göra
om proteiner så att de får andra egenskaper än de hade från början. Ett exempel på varför man
skulle vilja göra det är för enzymer (en typ av proteiner) som används i tvättmedel. Från början
så var de enzymerna inte aktiva vid de höga temperaturer som man använder när man tvättar.
Genom protein engineering så har man lyckats ta fram nya enzymvarianter som är mer
värmestabila. Ett annat exempel är insulin som ges till diabetiker. Från början använde man
insulin som isolerades från grisars bukspottskörtlar. Genom protein engineering har man lyckats
ta fram olika varianter som antingen är mer snabbverkande eller där effekten håller i längre för
att det ska bli smidigare för patienterna. Dessutom kan man nu producera insulin i bakterier
genom att stoppa in DNAt som kodar för det mänskliga insulinet i bakterier, så nu behöver man
inte rena fram det från grisar längre.
Protein engineering kan göras på olika sätt. Antingen så kan man studera proteinets struktur
(om den finns tillgänglig) och funktion (om man känner till den) och göra kvalificerade
gissningar för hur man ska ändra proteinet. Det är ganska svårt att göra de gissningarna så ofta
får man prova sig fram, vilket gör att det blir väldigt arbetsintensivt och tidskrävande. Ett annat
tillvägagångssätt är istället att introducera en massa mutationer på en gång, antingen helt
slumpartat över hela proteinet eller inriktat på ett fåtal positioner inom proteinet. Man får då en
samling av proteinvarianter. De här samlingarna är ofta väldigt stora (en miljon till en miljard
varianter är inte ovanligt). Sedan vill man titta på varje variant i samlingen för att se om det är
någon som har de egenskaper som man är ute efter. Det här går oftast inte att göra genom att
manuellt titta på en i taget för det skulle ta alldeles för lång tid. Ett alternativ är istället metoder
som kan fiska ut de varianter som har de egenskaper som man är ute efter. De egenskaperna kan
t.ex. vara ökad värmestabilitet som i fallet med enzymerna i tvättmedel, bättre på att specifikt
klippa i andra proteiner, eller att kunna binda till något som t.ex. finns på en cancercell, men inte
en frisk cell för att specifikt kunna leverera läkemedel dit.
Fokus för en stor del av den här avhandlingen har varit utveckling av metoder för att fiska ut de
intressanta varianterna ur samlingarna av proteinvarianter. Här gäller det att koppla ihop den
egenskap man är ute efter med en egenskap som man kan "se" för att kunna plocka ut de
varianter som man är intresserad av. Som avhandlingens titeln säger så använder vi oss av
bakterier som får producera proteinerna. I ett projekt kopplades specifik klyvning av ett protein
(egenskapen vi var intresserade av) ihop med bakteriell tillväxt i antibiotika (den synbara
Page |48
Lisa Sandersjöö
egenskapen). De bakterier som innehåller varianter med den önskade egenskapen kan då växa
till sig, medan övriga dör. I andra projekt kopplades den önskade egenskapen istället ihop med
något som kallas fluorescens. Det innebär att de bakterier som innehåller proteinvarianter med
den önskade egenskapen blir "självlysande". De kan sedan automatiskt sorteras ut med hjälp av
en maskin som kan analysera och sortera ca 10,000 bakterier i sekunden till olika rör. När man
har fiskat ut bakterierna som innehåller intressanta proteiner så kan man sedan enkelt plocka ut
proteinerna från bakterierna.
I ett annat projekt så utvecklades istället ett koncept för att minska biverkningar för framtida
cancerläkemedel. Genom att ta fram proteiner som kan binda till målproteiner som finns på ytan
av cancerceller så kan man skapa målsökande läkemedel. Tyvärr är det inte alltid så svart eller
vitt så att målproteinet antingen finns eller inte finns på ytan av sjuka/friska celler utan det är
oftast snarare olika nivåer på de olika cellerna. Det här gör att det målsökande läkemedlet även
kan ”råka” ge sig på friska celler som har lite av målproteinet på ytan. Det här kan ge upphov till
svåra biverkningar. För att minska det här problemet så har vi utvecklat ett koncept där det
målsökande läkemedlet är inaktivt tills det når den sjuka vävnaden, t.ex. tumör, där det aktiveras
av en typ av enzymer som finns i större mängder i den sjuka vävnaden än i frisk vävnad i många
sjukdomar. Det här tillför en extra kontrollmekanism för att läkemedlet ska få en effekt och
skulle därför kunna minska biverkningar för framtida läkemedel.
Page | 49
Bacteria-based methods for engineering and characterization of proteases and affinity proteins
Acknowledgements
Tack till KTH Center for Applied Proteomics, funded by the Erling-Persson Family
Foundation, för finansiering av projekt.
Tack till KTHs allmänna resestipendier, Gålöstiftelsen, Sixten Gemzéus fond, KVA,
Knut och Alice Wallenbergs stiftelse och Svenska Kemistsamfundet för resestipendier
som möjliggjort deltagande i konferenser.
Tack alla ni som på ett eller annat sätt har hjälpt mig med den här avhandlingen och på vägen
dit. Jag vill speciellt tacka:
John, du har gått från att vara min tredje handledare, till andra och numera huvudhandledare.
Jag är väldigt tacksam över att jag fick bli en del av din och Stefans grupp och för att du alltid tar
dig tid att svara på frågor, dela med dig av din kunskap och styra mig åt rätt håll när jag inte vet
vad jag ska fokusera på. Du har en otrolig förmåga att alltid lyckas vända allt till något positivt
och intressant.
Stefan, min otroligt positiva, numera, bihandledare. Tack för att jag fick komma till din och
Johns fantastiska grupp och för att du alltid är så entusiastisk och peppar och coachar. Tack
också för din positiva inställning till konferenser och kurser utomlands.
Patrik, för att du med din kurs väckte mitt intresse för molekylär bioteknik och sen gav mig
möjlighet att exjobba hos dig och även påbörja doktorandstudierna.
Alla PIs på avdelningen för att ni har skapat den fantastiska stämningen vi har. Speciellt tack till
Per-Åke för att du engagerar dig i de flesta doktoranders projekt, tar en extra funderare och
alltid delar med dig av din kunskap.
My, för att du granskade och kom med många bra synpunkter på hur jag kunde förbättra och
förtydliga avhandlingen.
EP, för att du läste avhandlingen och kom med tänkvärda kommentarer. Jag kanske inte riktigt
visade min fulla uppskattning för det där och då, men i slutändan var jag väldigt tacksam över
det.
Page |50
Lisa Sandersjöö
Andreas, för all vägledning i labbet, vilket till slut resulterade i två projekt ihop. Tack för att du
alltid tar dig tid att svara på frågor, diskutera och komma med input och för att du poängterar
vikten av att fundera på vad man egentligen vill visa med sina experiment.
Hanna, min andra samarbetspartner, för att du så snyggt fick ihop manuskriptet och lyckades
leta fram bra data från alla hundratals FACS-filerna. Tack också för att du alltid tar dig tid att
hjälpa till med allt från cellodling, FACSen, staffar och massa annat trots att du egentligen har
mycket viktigare saker att göra.
Jojje, min exjobbshandledare, för att du introducerade mig till bakterier, proteaser,
degraderingssystem och livet på labbet.
Per-Olof, för att du tog dig tid att diskutera enzymkinetik och upplägg av experiment med en
något desperat doktorand i jakten på sista manuset.
Emma och Lan Lan, för att ni håller koll på alla beställningar, även de gånger jag själv inte har
en aning om vad jag har beställt.
Bahram, Jenny, Lili, Malin, Marica och Mehri för alla hundratals plattor som ni har
sekvensat åt mig och för alla de gånger jag har fått låna era PCR-maskiner. Tack också till
Roxana för att du gör ett helt fantastiskt jobb i diskrummet och på många sätt underlättar för
oss alla i labbet.
Världens bästa staff-grupp: Stefan, John, Nina, Helena, Magdalena, Filippa, Hanna,
Tarek, Ronny, Andreas, Ken, Jonas och Sebastian och alla tidigare och nuvarande
exjobbare. Det spelar ingen roll om vi bowlar, curlar, dansar på en stängd uteservering i
Frankrike eller seglar i ösregn, det är alltid lika roligt att ha gruppaktiviteter med er.
Alla gamla och nya rumskamrater, Hanna, Magnus, Francis, Sarah, EriC, Rezan, Josef,
Nima, Jonas och Fredrik med flera, för alla rums-middagar, bubbel-luncher, stretchningar,
Rikard-pyntning/plundring, fantastiska citat, Porsche-spaningar och annat roligt som livade upp
dagarna innan vi gjorde om rummet till ett bibliotek.
Tack alla ni som har varit resesällskap på alla konferenser genom åren.
Tack alla fantastiska Plan3-tjejer för middagar, stickjuntor, tantklubbar, julpyssel och annat som
vi har hittat på under de här åren.
Sist, men inte minst, vill jag tacka min familj och mina vänner utanför KTH för att ni alltid
stöttat mig i mina lite annorlunda intressen och påmint om att det finns en värld där utanför
också (där proteiner mest är något man äter och enzymer funkar som klister).
Page | 51
Bacteria-based methods for engineering and characterization of proteases and affinity proteins
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