Genetic architecture of microbial behaviors, adaptation, and evolution

Complex bacterial behaviors

Bacteria thrive in a seemingly limitless range of extreme environments, accompanied by exotic metabolisms and rather sophisticated behaviors. However, our modern molecular understanding of bacteria comes from studies of a limited range of phenotypes in a handful of model organisms. There is now an urgent need for methods that rapidly and comprehensively reveal the genetic basis of phenotypes across the microbial biosphere. We have developed a powerful computational framework for revealing the genetic basis of bacterial traits by correlating the inheritance patterns of genes and phenotypes across all the sequenced bacterial genomes (Jim et al. Genome Research 2004 14:109; Slonim et al. Mol. Syst. Biol. 2006, 2:2006.0005). From an experimental perspective, we have developed a whole-genome fitness profiling method using microarray-based genetic footprinting (Girgis et al. PLoS Genetics 2007, 3(9): e154), and are applying it to a wide array of complex bacterial behaviors (Amini et al. PLoS Pathogens 2009 5(5):e1000432; Goodarzi et al. Molecular Syst. Biol. 2010 6:378; Goodarzi et al. Nature Methods 2009, 6(8):581). Application of these technologies to E. coli chemotaxis reveals essentially all the previously known components of flagellar-mediated chemotaxis on the time-scale of weeks. Remarkably, we also identify three dozen additional novel loci that operate through diverse mechanisms to affect a behavior that was assumed to be ‘completely characterized’. Furthermore, we have developed a genome-wide epistasis analysis framework that efficiently reveals the organization of these genes within signaling and regulatory networks such as the Rcs phosphorelay pathway and the cyclic-di-GMP second-messenger system.

Antibiotic susceptibility and evolution of resistance

Antibiotic susceptibility is one of the most important yet poorly characterized bacterial phenotypes. The severity of the antibiotic-resistance crisis demands extreme urgency for developing novel antibiotics. Such drugs could target entirely novel pathways or modulate intrinsic resistance programs that increase the efficacy of antibiotics in current use. Such a rational target discovery program requires a deep basic understanding of antibiotic resistance, well beyond that which currently exists. We need a comprehensive understanding of how all cellular processes influence and intersect with antibiotic sensitivity. To do this, we have developed an experimental system that quantifies the degree to which every genetic locus contributes to antibiotic sensitivity. This provides a knowledge scaffold for identifying central pathways whose genetic or chemical targeting may potentiate drug sensitivity. By applying this framework to mild resistance, we have identified a large number of loci whose genetic perturbations significantly affect antibiotic sensitivity. Strikingly, we find dozens of loci in which null mutations dramatically increase resistance (Girgis et al. PLoS One 2009, 4(5):e5629).

Related publications

Regulatory and metabolic rewiring during laboratory evolution of ethanol tolerance in E. coli
Mol Syst Biol. 2010 Jun 8; 6:378. PDF
Goodarzi H, Bennett BD, Amini S, Reaves ML, Hottes AK, Rabinowitz JD, Tavazoie S

Global protein occupancy landscape of a bacterial genome
Molecular Cell. 2009 Jul 31;35(2):247-53 PDF
Vora T, Hottes AK, Tavazoie S

Global discovery of adaptive mutations
Nature Methods. 2009 Aug; 6(8):581-3 PDF
Goodarzi H, Hottes AK, Tavazoie S

Genetic architecture of intrinsic antibiotic susceptibility.
PLoS ONE. 2009 May 20;4(5):e5629. PDF
Girgis HS, Hottes AK, Tavazoie S

Genetic dissection of an exogenously induced biofilm in laboratory and clinical isolates of E. coli.
PLoS Pathog. 2009 May;5(5):e1000432. Epub 2009 May 15. PDF
Amini S, Goodarzi H, Tavazoie S

Predictive behavior within microbial genetic networks
Science (2008) 320:1313-1317, Epub 2008 May 8 PDF
Tagkopoulos I, Liu Y, Tavazoie S

A comprehensive genetic characterization of bacterial motility
PLoS Genetics (2007) 3 (9): e154 PDF
Girgis H, Liu Y, Ryu W, Tavazoie S

Ab initio genotype-phenotype association reveals the intrinsic modularity of genetic networks.
Molecular Systems Biology 2006; 2:2006.0005. Epub 2006 Jan 31. PDF
(Slonim N, Elemento O, equal contribution) and Tavazoie S

A cross-genomic approach for systematic mapping of phenotypic traits to genes.
Genome Research 2004 Jan; 14(1):109-15. PDF
Jim K, Parmar K, Singh M, Tavazoie S

Selection analyses of insertional mutants using subgenic-resolution arrays.
Nature Biotechnology 2001 19: 1060-1065. PDF
Badarinarayana V, Estep PW 3rd, Shendure J, Edwards J, Tavazoie S, Lam F, Church GM