Carol Gross's laboratory studies regulatory networks in E. coli, an organism that is amenable to genetic and biochemical methods. Current lab projects focus on three related areas:
Molecular basis for control of transcription in E. coli

Prokaryotes dynamically alter their gene expression programs to suit their environmental circumstance. The σ subunits of RNA polymerase are central to this adaptation: σs instigate gene expression by recognizing and melting promoter DNA elements, and each σ represents a specific set of promoters. We study the molecular basis for promoter melting, and the basis for the promoters specificity of σs. We have established specific interactions between residues in alternative σs and nucleotides in promoters that enable transcription initiation and determine promoter specificity.

We integrate this knowledge with screens of promoter libraries to model promoter strength and function based on promoter sequence. Sequenced bacterial genomes cannot be translated into transcriptional regulatory circuit maps largely because accurate prediction of promoters from sequence information is difficult. We perform in vivo and in vitro activity assays on libraries of natural and mutated forms of E. coli σE promoters. We then apply position weight matrix-based models to identify active promoters and predict promoter strength based on promoter sequence.

Representative publications:
Rhodius VA, Mutalik VK. 2010. Predicting strength and function for promoters of the Escherichia coli alternative sigma factor, sigmaE. Proceedings of the National Academy of Sciences, 107(7):2854-9
Koo BM, Rhodius VA, Nonaka G, deHaseth PL, Gross CA. 2009. Reduced capacity of alternative sigmas to melt promoters ensures stringent promoter recognition. Genes & Development, 23: 2426:2436.
Young BA, Gruber TM, Gross CA. 2004. Minimal machinery of RNA polymerase holoenzyme sufficient for promoter melting. Science, 03(5662):1382-4.
E. coli stress response circuit architecture

E. coli employs intricate control circuitry to monitor and respond to stresses presented by its environment. We are defining the molecular mechanisms responsible for activating and modulating the activity of stress responses. We also define the genome-wide outputs of stress response circuits, allowing us to place the circuits in a global context of gene expression.

The cytoplasmic heat stress response is mediated by σ32. The σ32 mRNA directly senses changes in temperature and unleashes a chaperone response that sequesters and re-folds heat-denatured proteins. Our lab has revealed that the σ32 response is dynamically controlled by multiple feedback loops that integrate information from cytoplasmic folding conditions to regulate σ32 activity.

The periplasmic response, mediated by σE, responds to unfolded proteins in the periplasm. Our lab has established circuitry integrating chaperones, proteases, and sRNAs to activate and regulation of the response. We are currently studying additional inputs and outputs to the reponse, as well as modelling the roles of different parts of this control circuit.

Genomic technology allows us to determine the global outputs of stress responses. Using transcriptional arrays, we have shown both the σ32 and σE-mediated response to have a highly targeted response regulon. We are currently applying high-throughput sequencing tools to determine the molecular mechanisms through which E. coli 's tranlational capacity is altered in response to temperature stress.

Representative Publications:
Chaba R, Grigorova IL, Flynn JM, Baker TA, Gross CA. 2007. Design principles of the proteolytic cascade governing the sigmaE-mediated envelope stress response in Escherichia coli: keys to graded, buffered, and rapid signal transduction. Genes & Development, 21(1):124-36.
Rhodius VA, Suh WC, Nonaka G, West J, Gross CA. 2006. Conserved and variable functions of the sigmaE stress response in related genomes. PLoS Biology (1):e2.
High-throughput, quantitative analyses of genetic interactions in E. coli

High-throughput genetic interaction studies are a powerful tool for identifying gene function and mapping pathway organization in different genetically tractable organisms. Recent advances in the ability to generate double mutants en masse in S. cerevisiae and S. pombe have dramatically accelerated the acquisition of genetic interaction information to guide further characterization of these model organisms.

We have recently developed a method, based on F factor driven conjugation, which allows for high-throughput generation of double mutants in E. coli. This method, termed genetic interaction analysis technology for E. coli (GIANT-coli), permits us to systematically generate double-mutant cells on solid media in high-density arrays and assess their fitness. Using GIANT-coli , systematic genetic interaction data can be rapidly accumulated and combined with information from small-scale studies as well as with other large datasets (eg protein-protein interaction datasets, gene-expression data) to provide novel insights on bacterial physiology.

We anticipate adapting this methodology to give additional phenotypic readouts such as promoter activity (gfp or lacZ fusions), biofilm formation (Congo-red or calcofluor plates, crystal violet absorption), siderophore production (chrome azurol S plates), and growth inhibition (halo assays). Moreover, our goal is to extend GIANT-coli to other gram-negative and gram-positive bacteria. Together, these methodologies should lead to rapid progress in discovery of gene function and network architecture in bacteria.

Representative publications:
Typas A, Nichols RJ, Siegele DA, Shales M, Collins SR, Lim B, Braberg H, Yamamoto N, Takeuchi R, Wanner BL, Mori H, Weissman JS, Krogan NJ, Gross CA. 2008. High-throughput, quantitative analyses of genetic interactions in E. coli. Nature Methods, 5(9):781-7.