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− | <p>To acquire comprehensive knowledge on the AMP’s behavior in a fusion, we obtained the bacterial self-targeting efficiency of a randomly synthesized library of 0.3 million peptides. Then, we built a custom-made machine learning guided AMP optimization software, AMP Designer (see details in our webpage <a href="https://2018.igem.org/Team:Paris_Bettencourt/Software ">Paris_Bettencourt/Software </a>). Using this software, we found a specific engineering method that changes the charge distribution around | + | <p>To acquire comprehensive knowledge on the AMP’s behavior in a fusion, we obtained in the literature the bacterial self-targeting efficiency of a randomly synthesized library of 0.3 million peptides. Then, we built a custom-made machine learning guided AMP optimization software, AMP Designer (see details in our webpage <a href="https://2018.igem.org/Team:Paris_Bettencourt/Software ">Paris_Bettencourt/Software </a>). Using this software, we found a specific engineering method that changes the charge distribution around positive clusters on the AMP sequence. Based on this semi-rational approach, we designed ~ 12,000 variant library that we attached to mCherry through a linker in order to optimize the already characterized effectiveness of core-AMPs. The common pattern discovered in our top-efficient AMP fusions was the presence of charge-reduced peptide along with charge-increased peptide, indicating the important trade-off between AMP’s efficiency alone, and the AMP’s impact on protein expression, folding and assembly.</p> |
</div> | </div> | ||
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− | <p>We chose to fuse the natural AMPs that we tested in StarCore designs to the fluorescent protein mCherry. This allowed us to | + | <p>We chose to fuse the natural AMPs that we tested in StarCore designs to the fluorescent protein mCherry. This allowed us to estimate the protein expressing-folding level. It also served as a “simulated core” that allowed us to test AMP activity in the context of a fusion protein. As we learned in the production section, protein expression and folding are critical to obtaining an effective StarCore. |
</p> | </p> | ||
</div> | </div> | ||
<div class='textbody'> | <div class='textbody'> | ||
− | <p>We chose to focus library diversity on positively charged residues. Charge density is known to critically affect both protein folding and AMP function. Thus we simulated a few ideas on charge modification, in the environment of AMP Designer. One interesting principle we found using AMP Designer, is positive-cluster modification method, which is significantly better than random mutagenesis, in both the diversity of outcomes and the final efficiency (~ 3-fold higher). To elaborate, it is a systematic way to generate mutations, to move, concentrate and amplify positive charges, around the existing positive charged clusters on the AMP. These mutations are described in Figure 1.</p> | + | <p>We chose to focus library diversity on positively charged residues. Charge density is known to critically affect both protein folding and AMP function. Thus we simulated a few ideas on charge modification, in the environment of AMP Designer. One interesting principle we found using AMP Designer, is positive-cluster modification method, which is significantly better than random mutagenesis, in both the diversity of outcomes and the final efficiency (~ 3-fold higher). To elaborate, it is a systematic way to generate mutations, to move, concentrate and amplify positive charges, around the existing positive charged clusters on the AMP sequence. These mutations are described in Figure 1.</p> |
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− | <p>We cloned the DNA sequence library into a T7-based expression vector and transformed it into easy-to-lyse | + | <p>We cloned the DNA sequence library into a T7-based expression vector and transformed it into an easy-to-lyse E. coli strain (XJ Autolysis strain). Cells were grown in a slightly modified recipe of auto-induction media that triggers the StarCore expression by IPTG, and λ endolysin by arabinose, in early log phase. Peptide expression was measured by lysate’s mCherry fluorescence. After a freeze-thaw cycle to fully lyse the cell (no alive individuals left, tested by growth recovery), the lysates were added to fresh cultures of E. coli. Effects on growth were quantified by OD600 measurements. Of 12 000 total clones screened, we selected the 200 most effective for Sanger sequencing and further analysis.<p> |
</div> | </div> | ||
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− | <p>Greatest surprise was the decrease in charge found | + | <p>Greatest surprise was the decrease in charge found among the most effective mutants of the library. The difficulty of protein folding (in this case mCherry) in presence of concentrated charge is well known to professional companies that offer protein synthesis. As folding is an issue in any AMP related construct, charge distribution has a different effect on efficiency compared pure AMPs that only have a secondary structure. The necessity of a unique library for fusion-AMPs is vindicated. |
As a future direction of this project, we would aim to define a biologically relevant and high throughput assay for screening AMPs. With our method, we can not assess the mode of action of AMPs or its target. We would also like to test the cytotoxicity of the constructs against different cell lines. Developing the use of compartmentalized self-replication through the droplet microfluidics can be a possible way.<p> | As a future direction of this project, we would aim to define a biologically relevant and high throughput assay for screening AMPs. With our method, we can not assess the mode of action of AMPs or its target. We would also like to test the cytotoxicity of the constructs against different cell lines. Developing the use of compartmentalized self-replication through the droplet microfluidics can be a possible way.<p> | ||
</div> | </div> |
Revision as of 14:10, 6 December 2018
Optimization
Based on the results of the Testing and Modeling groups, we arrived at the following simple model for how StarCores function.
1: Why are StarCore Proteins Difficult to Express? |
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We were expecting that free AMPs behaved differently when they are fused to a protein scaffold. The previously available literature that describes free AMPs did not seem to apply for our constructs. With these considerations in mind, we set out to improve on the basic StarCore designs developed in the Design Section. Our method of choice was a combination of synthetic random library, rational mutagenesis and machine learning aided design.
To acquire comprehensive knowledge on the AMP’s behavior in a fusion, we obtained in the literature the bacterial self-targeting efficiency of a randomly synthesized library of 0.3 million peptides. Then, we built a custom-made machine learning guided AMP optimization software, AMP Designer (see details in our webpage Paris_Bettencourt/Software ). Using this software, we found a specific engineering method that changes the charge distribution around positive clusters on the AMP sequence. Based on this semi-rational approach, we designed ~ 12,000 variant library that we attached to mCherry through a linker in order to optimize the already characterized effectiveness of core-AMPs. The common pattern discovered in our top-efficient AMP fusions was the presence of charge-reduced peptide along with charge-increased peptide, indicating the important trade-off between AMP’s efficiency alone, and the AMP’s impact on protein expression, folding and assembly.
Design and Results
1. Design of the AMP Twist Library: Positive-cluster modification principle
We chose to fuse the natural AMPs that we tested in StarCore designs to the fluorescent protein mCherry. This allowed us to estimate the protein expressing-folding level. It also served as a “simulated core” that allowed us to test AMP activity in the context of a fusion protein. As we learned in the production section, protein expression and folding are critical to obtaining an effective StarCore.
We chose to focus library diversity on positively charged residues. Charge density is known to critically affect both protein folding and AMP function. Thus we simulated a few ideas on charge modification, in the environment of AMP Designer. One interesting principle we found using AMP Designer, is positive-cluster modification method, which is significantly better than random mutagenesis, in both the diversity of outcomes and the final efficiency (~ 3-fold higher). To elaborate, it is a systematic way to generate mutations, to move, concentrate and amplify positive charges, around the existing positive charged clusters on the AMP sequence. These mutations are described in Figure 1.
2. Screening 12 000 AMP variants for activity
We cloned the DNA sequence library into a T7-based expression vector and transformed it into an easy-to-lyse E. coli strain (XJ Autolysis strain). Cells were grown in a slightly modified recipe of auto-induction media that triggers the StarCore expression by IPTG, and λ endolysin by arabinose, in early log phase. Peptide expression was measured by lysate’s mCherry fluorescence. After a freeze-thaw cycle to fully lyse the cell (no alive individuals left, tested by growth recovery), the lysates were added to fresh cultures of E. coli. Effects on growth were quantified by OD600 measurements. Of 12 000 total clones screened, we selected the 200 most effective for Sanger sequencing and further analysis.
In the figure below, the most effective mutants of 4 parent antimicrobial peptides: Ovispirin, Bactofencin, Arenicin, V6_peptide are sequenced. Interestingly, we observe that the efficient peptides fall into two groups of mutants; where they either mutate to negatively charged amino-acids to decrease the net positive charge, which might lead to an increased protein folding efficiency; or else they mutate to positively charged amino-acids increasing the net positive charge which might improve the bactericidal efficiency. Further testing is required to fully understand the effect of charge distribution on the expression efficiency and its simultaneous effect on the bactericidal efficacy.
Methods
1. Library design
Due to their short length, AMPs were expressed as a fusion protein to prevent post-transcriptional degradation. The fluorescent reporter mCherry was chosen for this purpose. A long flexible linker was chosen to give the AMPs freedom to interact with the membrane.
Box 1: Library Design |
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Roughly 12 000 variants were designed using 5 templates from naturally occurring peptides. 3 types of variation rules were applied: |
2. Twist Library Cloning
We first used cold fusion assembly to construct a low-copy expression vector containing mCherry. Into this vector, the Twist DNA library was cloned using Golden Gate assembly.
Once our pDuet-mCherry vector obtained, we pursue the cloning procedure by performing Golden Gate assembly of the all the library. This method enabled us to join the 12k variants in a one-pot reaction. For this, 60 cycles of digestion/ligation were realized to minimize the level of empty vector. High-efficiency electrocompetent cells were used to recover the all library size. After plasmid purification, the plasmids containing the library were transformed once more into expression cells.
3. AMP-mCherry expression
To express our constructs, we chose to use XJ BL21(De3) autolysis strain. These cells are suitable for T7 regulated protein expression. The production of the lambda lysozyme is inducible by addition of arabinose. Subsequently, the cells can be efficiently lysed by one freeze/thaw cycle as the bacterial membrane is fragilized by the endotoxin. After transformation, we manually picked around 5k single colonies and grown them overnight. Auto-induction media was preferred to other complete media to decrease the pipetting steps.
4. AMP activity assay
We obtained a cell lysate by freeze-thawing our XJ bacterial strains, that are specifically engineering to lyse reliably. It is this lysate that contains our AMPs and is used in lieu of antibiotics for the killing assay. The lysate was diluted 1:4, and added to 96 well plates containing LB. Once made, the wells were inoculated with E.coli (ask which strain), that was pre-incubated for 2h at 37 C. The OD600 and mcherry fluorescence of the original lysate plates was measured and the OD600 was measured for the killing plates after 8h to determine the killing effect. Blanks including only LB-lysate were used as a negative control. AMP containing-lysate was used, as opposed to only internal expression because many AMPs that are effective when produced in vivo, often display different properties once isolated, probably due to poor stability, half-life, or inability to penetrate lipid membranes to reach their targets.
Conclusion
Greatest surprise was the decrease in charge found among the most effective mutants of the library. The difficulty of protein folding (in this case mCherry) in presence of concentrated charge is well known to professional companies that offer protein synthesis. As folding is an issue in any AMP related construct, charge distribution has a different effect on efficiency compared pure AMPs that only have a secondary structure. The necessity of a unique library for fusion-AMPs is vindicated. As a future direction of this project, we would aim to define a biologically relevant and high throughput assay for screening AMPs. With our method, we can not assess the mode of action of AMPs or its target. We would also like to test the cytotoxicity of the constructs against different cell lines. Developing the use of compartmentalized self-replication through the droplet microfluidics can be a possible way.
References
1.Bechinger, B., and S-U. Gorr. Antimicrobial peptides mechanisms of action and resistance. Journal of dental research 96.3 (2017) 254-260.
2.Tucker et al., Discovery of Next-Generation Antimicrobials through Bacterial Self-Screening of Surface-Displayed Peptide Libraries, Cell (2018)-doi.org/10.1016/j.cell.2017.12.009.