Person: Kuznetsov, Gleb
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Kuznetsov
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Gleb
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Kuznetsov, Gleb
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Publication Optimizing complex phenotypes through model-guided multiplex genome engineering(BioMed Central, 2017) Kuznetsov, Gleb; Goodman, Daniel B.; Filsinger, Gabriel; Landon, Matthieu; Rohland, Nadin; Aach, John; Lajoie, Marc J.; Church, GeorgeWe present a method for identifying genomic modifications that optimize a complex phenotype through multiplex genome engineering and predictive modeling. We apply our method to identify six single nucleotide mutations that recover 59% of the fitness defect exhibited by the 63-codon E. coli strain C321.∆A. By introducing targeted combinations of changes in multiplex we generate rich genotypic and phenotypic diversity and characterize clones using whole-genome sequencing and doubling time measurements. Regularized multivariate linear regression accurately quantifies individual allelic effects and overcomes bias from hitchhiking mutations and context-dependence of genome editing efficiency that would confound other strategies. Electronic supplementary material The online version of this article (doi:10.1186/s13059-017-1217-z) contains supplementary material, which is available to authorized users.Publication Millstone: software for multiplex microbial genome analysis and engineering(BioMed Central, 2017) Goodman, Daniel B.; Kuznetsov, Gleb; Lajoie, Marc J.; Ahern, Brian W.; Napolitano, Michael G.; Chen, Kevin Y.; Chen, Changping; Church, GeorgeInexpensive DNA sequencing and advances in genome editing have made computational analysis a major rate-limiting step in adaptive laboratory evolution and microbial genome engineering. We describe Millstone, a web-based platform that automates genotype comparison and visualization for projects with up to hundreds of genomic samples. To enable iterative genome engineering, Millstone allows users to design oligonucleotide libraries and create successive versions of reference genomes. Millstone is open source and easily deployable to a cloud platform, local cluster, or desktop, making it a scalable solution for any lab. Electronic supplementary material The online version of this article (doi:10.1186/s13059-017-1223-1) contains supplementary material, which is available to authorized users.Publication Biocontainment of Genetically Modified Organisms by Synthetic Protein Design(Nature Research, 2015-02-05) Mandell, Daniel; Lajoie, Marc J.; Mee, Michael T.; Takeuchi, Ryo; Kuznetsov, Gleb; Norville, Julie; Gregg, Christopher J.; Stoddard, Barry L.; Church, GeorgeGenetically modified organisms (GMOs) are increasingly deployed at large scales and in open environments. Genetic biocontainment strategies are needed to prevent unintended proliferation of GMOs in natural ecosystems. Existing biocontainment methods are insufficient either because they impose evolutionary pressure on the organism to eject the safeguard, because they can be circumvented by environmentally available compounds, or because they can be overcome by horizontal gene transfer (HGT). Here we computationally redesign essential enzymes in the first organism possessing an altered genetic code to confer metabolic dependence on nonstandard amino acids for survival. The resulting GMOs cannot metabolically circumvent their biocontainment mechanisms using environmentally available compounds, and they exhibit unprecedented resistance to evolutionary escape via mutagenesis and HGT. This work provides a foundation for safer GMOs that are isolated from natural ecosystems by reliance on synthetic metabolites.Publication Emergent Rules for Codon Choice Elucidated by Editing Rare Arginine Codons in Escherichia coli(National Academy of Sciences, 2016-09-20) Napolitano, Michael G.; Landon, Matthieu; Gregg, Christopher J.; Lajoie, Marc J.; Govindarajan, Lakshmi; Mosberg, Joshua A.; Kuznetsov, Gleb; Goodman, Daniel B.; Vargas-Rodriguez, Oscar; Isaacs, Farren J.; Söll, Dieter; Church, GeorgeThe degeneracy of the genetic code allows nucleic acids to encode amino acid identity as well as noncoding information for gene regulation and genome maintenance. The rare arginine codons AGA and AGG (AGR) present a case study in codon choice, with AGRs encoding important transcriptional and translational properties distinct from the other synonymous alternatives (CGN). We created a strain of Escherichia coli with all 123 instances of AGR codons removed from all essential genes. We readily replaced 110 AGR codons with the synonymous CGU codons, but the remaining 13 “recalcitrant” AGRs required diversification to identify viable alternatives. Successful replacement codons tended to conserve local ribosomal binding site-like motifs and local mRNA secondary structure, sometimes at the expense of amino acid identity. Based on these observations, we empirically defined metrics for a multidimensional “safe replacement zone” (SRZ) within which alternative codons are more likely to be viable. To evaluate synonymous and nonsynonymous alternatives to essential AGRs further, we implemented a CRISPR/Cas9-based method to deplete a diversified population of a wild-type allele, allowing us to evaluate exhaustively the fitness impact of all 64 codon alternatives. Using this method, we confirmed the relevance of the SRZ by tracking codon fitness over time in 14 different genes, finding that codons that fall outside the SRZ are rapidly depleted from a growing population. Our unbiased and systematic strategy for identifying unpredicted design flaws in synthetic genomes and for elucidating rules governing codon choice will be crucial for designing genomes exhibiting radically altered genetic codes.