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Evolutionary Genome Engineering to Model Microbial Evolution
Poster Title: Evolutionary Genome Engineering to Model Microbial Evolution
Submitted on 12 Sep 2016
Author(s): Petra Éva Szili, Ákos Nyerges, Bálint Csörgő, Bálint Kintses, Csaba Pál
Affiliations: Synthetic and Systems Biology Unit, BRC, HAS Szeged, Hungary
This poster was presented at Euroscion - Unlocking the potential of synthetic biology to enhance human health
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Poster Information
Abstract: Evolutional biology is on the verge of a big transition: the most recent advances in synthetic biology supply us with multiple tools for genome editing in a directed and combinatorial manner. This is important because in the case of complex or slowly evolving traits, natural diversity can be limited or biased, which will cause bias in the results too. In my project I use a genome engineering method called Multiplex Automated Genome Engineering (MAGE) to create highly diverse bacterial mutant libraries and to accelerate the investigation of evolutionary processes with their aid. The main focus of our lab is bacterial antimicrobial resistance, a relevant topic in modern healthcare.

The desired diversity is defined in the first step of the process. The engineering templates are 90-mer oligonucleotides. These oligonucleotides first designed in silico – to encode this desired diversity – and then the designed oligonucleotides are chemically synthetized. As a result, we have a diverse pool of oligonucleotides.
In the next step, using MAGE, I can incorporate these oligonucleotides into the bacterial genomes. In turn, the chemically encoded diversity in the oligonucleotide sequences will appear as genomically encoded mutations on the bacterial genomes. The result is a population with exceptionally high diversity of the target gene.

The recent breakthrough in our lab was the pORTMAGE system (you can see the outline of a pORTMAGE plasmid in the centre). This incorporates on only one plasmid everything that is necessary to integrate oligonucleotides to the genome. Plus its broad host range enables us high-throughput modification of genomes in a wide variety of enterobacteria, and minimizing the occurrence of off target mutations. These off-target mutations frequently interferes with evolutionary experiments.

So, if we have this diverse population, we can do several things with it. The first step is always the analysis of the created diversity. This happens with high-throughput methods both genotypically and phenotypically. We perform genotypic analysis with deep sequencing (I have used both Illumina and PacBio sequencing), and in parallel we can examine the phenotypic diversity with high-throughput, robotized screening. This way we can link the observed genotypes to their phenotypes.

In the future, I hope to use this method, with the repeating cycles of mutagenesis and selection, to model evolution of antibiotic resistance. I hope to get more detailed results than what has been achieved with traditional laboratory evolution, since with the enhanced diversity I have a chance to observe and analyze rarely occurring trajectories of antimicrobial resistance in evolution. With the wide host range of pORTMAGE I also wish to tackle the question of the conserved nature of evolution between species.
Summary: In my work I use a modified version of Multiplex Automated Genome engineering (MAGE) to enhance genetic diversity of bacterial populations and accelerate the modelling of evolutional processes.References: 1. Pál, Csaba, Balázs Papp, and György Pósfai. 2014. “The Dawn of Evolutionary Genome Engineering.” Nature Reviews Genetics advance online publication (May). doi:10.1038/nrg3746
2. Nyerges, Ákos, Bálint Csörgő, István Nagy, Balázs Bálint, Péter Bihari, Viktória Lázár, Gábor Apjok, et al. 2016. “A Highly Precise and Portable Genome Engineering Method Allows Comparison of Mutational Effects across Bacterial Species.” Proceedings of the National Academy of Sciences, February, 201520040. doi:10.1073/pnas.1520040113.
3. Ryan R Gallagher, Zhe Li, Aaron O Lewis & Farren J Isaacs - Rapid editing and evolution of bacterial genomes using libraries of synthetic DNA, Nature Protocols 9, 2301–2316 (2014) doi:10.1038/nprot.2014.082
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