Project description
Fast evolving pathogens as global health threat
coming soon...
Generation of binding proteins by directed evolution
This year the iGEM Team Bielefeld-CeBiTec aims to create a method for generating synthetic binding proteins,
our so-called Evobodies. This works by creating a library of binding proteins and increasing their affinity
towards a target by directed evolution (Fig. 1). As a starting point, we randomise the binding regions of
synthetic antibody-like proteins (Fig. 1a). Following we screen this library for affinity towards a target by
using a bacterial two-hybrid system (Fig. 1b). To further increase the Evobodies affinity, we combine the selection
via the two-hybrid system with an in vivo mutagenesis system (Fig. 1c). Doing this we hope to generate strong
and specific binding proteins by combining the powerful genetics of E. coli with the biological idea of
antibody generation and maturation in vertebrates.
We designed our Evobody approach as an alternative to conventional methods for the generation of binding proteins. In our vision it should be possible to clone each protein encoding sequence into one of our plasmids, let our system do the work and get a high affinity binding protein, which can be either used for medical, diagnostic or scientific applications.
Figure 1: Overview
We designed our Evobody approach as an alternative to conventional methods for the generation of binding proteins. In our vision it should be possible to clone each protein encoding sequence into one of our plasmids, let our system do the work and get a high affinity binding protein, which can be either used for medical, diagnostic or scientific applications.
The starting point - synthetic binding protein library
As starting point, we want to create a library of many binding proteins with a high chance to contain a protein
with the potential to bind our target protein. In doing so we choose the core region of the antibody-mimetic mono-
and nanobodies. In the coding region of those proteins, we randomized the loop regions, which are known to bind
other proteins to obtain our library.
The randomization strategy as well as the choice of the protein scaffold is a key part of library generation. We identified amino acids, which are present in most protein-protein interaction areas and created a randomization scheme so that only these amino acids are encoded in the antibody-mimetics binding region. Read more about our library design here.
The randomization strategy as well as the choice of the protein scaffold is a key part of library generation. We identified amino acids, which are present in most protein-protein interaction areas and created a randomization scheme so that only these amino acids are encoded in the antibody-mimetics binding region. Read more about our library design here.
Figure 2: Library
Survival of the fittest - bacterial two-hybrid
In the next step, the binding protein library should be screened for proteins with an innate affinity for our target.
We want to realize this by using a bacterial two-hybrid system. Therefore, our target protein (1) is fused to a DNA
binding domain (2), which localises upstream of a reporter cassette (3). The binding protein (4) is fused to a RNA polymerase
subunit (5). Interaction between the binding and the target protein leads to recruitment of the RNA polymerase to the promoter
region of the reporter cassette and activates the reporter gene expression. By using an antibiotic resistance as a reporter
gene the output of the bacterial two hybrid system should lead to the survival E. coli cells carrying a good binding
protein and the death of all cells with a bad binding protein.
![](https://static.igem.org/mediawiki/2016/9/9e/Bielefeld_CeBiTec_2016_10_14_project_description_selection.png)
From the two-hybrid system we expect foremost a selection of the binding protein library. Furthermore, we expect a correlation between binding - target protein affinity and the activated gene expression strength of the reporter. By using an antibiotic resistance protein as a reporter we predict increased levels of the resistance protein inside a cell with a high affinity binding protein. The outcome of this should be an increase of individual fitness for bacteria with good binding proteins, which should lead to a higher growth rate under strong selective pressure. The complete two-hybrid system should cumulate in a correlation between binding protein affinity and bacterial growth rate, which should lead to selection of a few bacteria with strong binding proteins. Find out more on our selection page.
![](https://static.igem.org/mediawiki/2016/9/9e/Bielefeld_CeBiTec_2016_10_14_project_description_selection.png)
Figure 3: Bacterial-two hybrid system. Interaction between the binding protein (4) and the target protein (1)
lead to recruitment of RNA polymerase (5) to the promoter upstream of the reporter cassette (3) and subsequent
expression of the reporter gene. In this case the reporter is beta-lactamase, which expression leads to degradation
of ampicillin (blue squares) and survival of the bacteria.
From the two-hybrid system we expect foremost a selection of the binding protein library. Furthermore, we expect a correlation between binding - target protein affinity and the activated gene expression strength of the reporter. By using an antibiotic resistance protein as a reporter we predict increased levels of the resistance protein inside a cell with a high affinity binding protein. The outcome of this should be an increase of individual fitness for bacteria with good binding proteins, which should lead to a higher growth rate under strong selective pressure. The complete two-hybrid system should cumulate in a correlation between binding protein affinity and bacterial growth rate, which should lead to selection of a few bacteria with strong binding proteins. Find out more on our selection page.
Accessing the sequence space - in vivo mutagenesis
After selection of the bulk of our library we will increase the affinity of our Evobodies in a process similar to the affinity
maturation of antibodies(Teng und Papavasiliou 2007). As
addressed above we will select our Evobodies by increasing the selection pressure. At the same time, we will use an in vivo
mutagenesis system. Thereby ,we can increase the sequence diversity beyond the limits of our library. Slightly modifications of
binding proteins identified during the initial selection will are the basis for the directed evolution.
![](https://static.igem.org/mediawiki/2016/d/d4/Bielefeld_CeBiTec_2016_10_14_project_description_mutation.png)
In detail, we will compare two different possibilities to diversify our binding proteins. The first approach is the use of an error-prone polymerase I in an otherwise Pol I temperature-sensitive E. coli strain. (Camps et al. 2003) Growth at a non-permissive temperature should result in accumulation of mutations in the part of the genom maintained by DNA polymerase I. The interesting idea behind this approach is the fact that large parts of plasmids carrying an origin of replication from the ColE1-familiy are replicated by the polymerase I. (Camps et al. 2003; Camps 2010) Because of this, the usage of the error-prone polymerase I should mutant mainly our Evobody sequence on a plasmid. Thereby off-target mutations, which are a major obstacle of in vivo mutagenesis, should be minimized. (Camps et al. 2003)
Our other approach is based on creating a plasmid borne hypermutator system by modulating the E. coli DNA fidelity systems. (Badran und Liu 2015) We will express known mutator genes under tight regulation from a plasmid. By using a plasmid borne mutator system, in contrast to the more classical approaches of incorporating the mutator genes directly inside the genom. (Agilent Technologies; Greener et al. 1997) Thereby we want to circumvent the known problems with globally increased mutation rate, which are genetic instability or general unviability.
Over the course of our project we want to find out which mutagenesis system is most suitable to our directed evolution approach. Therefore we will compare both possibilities in terms of mutagenesis rate, -spectrum, -controllability and -specifity. How will we do this? Find out on our mutation page.
![](https://static.igem.org/mediawiki/2016/d/d4/Bielefeld_CeBiTec_2016_10_14_project_description_mutation.png)
Figure 4: In vivo mutagenesis. By using an in vivo mutagenesis system a single Evobody coding
sequence can be evolved to various different variants, each with a unique binding site. The single starting sequence is
replicated during growth and thereby mutations are incorporated either through error-prone polymerase I or a combination
of global mutator genes. The process results in the creating of the library of binding proteins with different binding properties.
In detail, we will compare two different possibilities to diversify our binding proteins. The first approach is the use of an error-prone polymerase I in an otherwise Pol I temperature-sensitive E. coli strain. (Camps et al. 2003) Growth at a non-permissive temperature should result in accumulation of mutations in the part of the genom maintained by DNA polymerase I. The interesting idea behind this approach is the fact that large parts of plasmids carrying an origin of replication from the ColE1-familiy are replicated by the polymerase I. (Camps et al. 2003; Camps 2010) Because of this, the usage of the error-prone polymerase I should mutant mainly our Evobody sequence on a plasmid. Thereby off-target mutations, which are a major obstacle of in vivo mutagenesis, should be minimized. (Camps et al. 2003)
Our other approach is based on creating a plasmid borne hypermutator system by modulating the E. coli DNA fidelity systems. (Badran und Liu 2015) We will express known mutator genes under tight regulation from a plasmid. By using a plasmid borne mutator system, in contrast to the more classical approaches of incorporating the mutator genes directly inside the genom. (Agilent Technologies; Greener et al. 1997) Thereby we want to circumvent the known problems with globally increased mutation rate, which are genetic instability or general unviability.
Over the course of our project we want to find out which mutagenesis system is most suitable to our directed evolution approach. Therefore we will compare both possibilities in terms of mutagenesis rate, -spectrum, -controllability and -specifity. How will we do this? Find out on our mutation page.
Improve a part
Mutator gene dnaQ926 - BBa_K1333108
Introduction
DnaQ is part of the DNA polymerase III and is responsible for the proofreading activity of this complex. The dnaQ926 variant
loses this activity through mutation of two function essential amino acids inside the active site. The complete loss of proofreading
as well as the resulting saturation of mismatch-repair makes dnaQ926 the single strongest mutator gene known. (Fijalkowska und Schaaper 1996)
Literature
- Agilent Technologies: XL1-Red Competent Cells. Instruction Manual 2015.
- Badran, Ahmed H.; Liu, David R. (2015): Development of potent in vivo mutagenesis plasmids with broad mutational spectra. In: Nature communications 6, S. 8425. DOI: 10.1038/ncomms9425.
- Camps, Manel (2010): Modulation of ColE1-like plasmid replication for recombinant gene expression. In: Recent patents on DNA & gene sequences 4 (1), S. 58–73.
- Camps, Manel; Naukkarinen, Jussi; Johnson, Ben P.; Loeb, Lawrence A. (2003): Targeted gene evolution in Escherichia coli using a highly error-prone DNA polymerase I. In: Proceedings of the National Academy of Sciences of the United States of America 100 (17), S. 9727–9732. DOI: 10.1073/pnas.1333928100.
- Fijalkowska, I. J.; Schaaper, R. M. (1996): Mutants in the Exo I motif of Escherichia coli dnaQ: defective proofreading and inviability due to error catastrophe. In: Proceedings of the National Academy of Sciences of the United States of America 93 (7), S. 2856–2861.
- Greener, A.; Callahan, M.; Jerpseth, B. (1997): An efficient random mutagenesis technique using an E. coli mutator strain. In: Molecular biotechnology 7 (2), S. 189–195. DOI: 10.1007/BF02761755.
- Teng, Grace; Papavasiliou, F. Nina (2007): Immunoglobulin somatic hypermutation. In: Annual review of genetics 41, S. 107–120. DOI: 10.1146/annurev.genet.41.110306.130340.