Identification and integration of systems level microbial synthetic lethality interactions to enhance genome design

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Synthetic biology is an emerging discipline that has the potential to revolutionize many areas from the chemical industry to medicine. The goal is to redesign biological organisms such as the yeast Saccharomyces cerevisiae or the gut microbe Escherichia coli to produce chemicals of interest. The range of molecules that can be produced by these biological organisms is virtually any biological molecules (from biofuels, to aromas, to antibodies for cancer treatment), with a more biosustainable production. The recent advances of in vitro DNA synthesis and assembly methods support the idea that synthetic biology is on the verge of blooming, allowing the materialization of new genome designs. However, these technical abilities now pose the deciphering of biological complexity as the next grand challenge for rational genome designs. The long-term goal of this research program is thus to enhance genome design by increasing our current knowledge of molecular interactions and constraints allowing organisms to thrive. Deleting a gene is a classical way of deciphering gene functions by studying the cellular processes in which the target gene is involved. In the bacterial model organism E. coli, a useful resource named the Keio collection is available where each of the ~3800 non-essential genes were individually deleted. While single-gene deletion provides information on the function of the gene itself, about a third of E. coli genes are still lacking experimental evidence of function. Considering that genes are working in complex networks, studying double-gene deletions on a genome-wide scale has the potential to establish new functional relationships between genes and increase our understanding of such networks. The number of combinations for double deletions is nevertheless daunting (> 9 million in E. coli) and probing it requires a high-throughput method. Random transposon mutagenesis is such method where a DNA element called transposon can integrate itself at virtually any location in the genome and be identified using high-throughput sequencing. The absence of insertions in a gene is used to infer essentiality, based on killing that depletes from the population the cells having an insertion in an important gene. In the current research program, we propose to apply a transposon mutagenesis method that we recently optimized, to the complete Keio collection single-gene mutant strains, hereby identifying all viable and non-viable double-gene deletions possible in E. coli. To further our understanding of these interactions, we will integrate the data we generated with computational models and generate several hypotheses of novel gene functions. The current limitation on genome design being the lack of complete knowledge of gene functions, our research program will provide a key resource for the community and improve genome reduction design, importantly contributing to the development of synthetic biology.