This page is still under construction. Below is a list of active and past projects in the lab.
Coordinate regulation of virulence in Salmonella typhimurium
Salmonella is the causative agent for a wide range of diseases in humans, including gastroenteritis and enteric fever. Worldwide, Salmonella is estimated to cause over sixteen million cases of typhoid fever, resulting in approximately six hundred thousand deaths, and over one billion cases of acute gastroenteritis, resulting in approximately three million deaths, each year. Over five hundred genes in Salmonella are directly involved in pathogenesis. Yet, only a subset of these is expressed at a given time. Currently, an integrated model for differential gene expression is lacking. To address this problem, our lab in collaboration with Jim Slauch investigating how Salmonella dynamically regulates gene expression during the different phases of the infection cycle. By characterizing how these genes are coordinately expressed and regulated, we aim to understand the infection process and, more importantly, discover novel targets for antibiotics.
Role of cross talk in regulating the dynamic expression of the flagellar Salmonella pathogenicity island 1 and type 1 fimbrial genes
Journal of Bacteriology, 192(21):5767-77, 2010
Saini S, Slauch JM, Aldridge PD, Rao CV
The role of coupled positive feedback in the expression of the SPI1 type three secretion system in Salmonella
PLoS Pathogens, 6(7):e1001025, 2010
Saini S, Ellermeier JR, Slauch JM, Rao CV
SprB is the molecular link between Salmonella pathogenicity island 1 (SPI1) and SPI4
Journal of Bacteriology, 192(9):2459-62, 2010
Saini S, Rao CV
Role of FimW, FimY, and FimZ in regulating the expression of type i fimbriae in Salmonella enterica serovar Typhimurium
Journal of Bacteriology, 191(9):3003-10, 2009
Saini S, Pearl JA, Rao CV
The Salmonella SPI1 type three secretion system responds to periplasmic disulfide bond status via the flagellar apparatus and the RcsCDB system
Journal of Bacteriology, 190(1):87-97, 2008
Lin D, Rao CV, Slauch JM
Regulation of arabinose and xylose metabolism in Escherichia coli
Glucose, xylose, and arabinose are the three most abundant sugars found in plant biomass. A key step in producing various chemical and biofuels from plant biomass will involve engineering strains capable of efficiently fermenting these three sugars. The challenge is that bacteria such as Escherichia coli will often consume one sugar at a time when fed multiple sugars in a process known as carbon catabolite repression. The classic example involves glucose and lactose, where E. coli will first consume glucose, and only when it has consumed all of the glucose will it begin to consume lactose. In addition to lactose, glucose also represses the consumption of many other sugars including arabinose and xylose.
Our lab characterized a second hierarchy in E. coli sugar utilization that exists between arabinose and xylose. We demonstrated that, when grown in a mixture of these two sugars, E. coli will consume arabinose before it consumes xylose. Consistent with a mechanism involving catabolite repression, the expression of the xylose metabolic genes is repressed in the presence of arabinose. We found that this repression is AraC dependent and involves a mechanism in which arabinose-bound AraC binds to the xylose promoters and represses gene expression. These results provide the first mechanistic characterization of catabolite repression in bacteria involving a sugar other than glucose. Moreover, by identifying the molecular mechanisms preventing E. coli from simultaneously fermenting these three sugars, we have laid the foundation for future engineering work.
Regulation of arabinose and xylose metabolism in Escherichia coli
Applied and Environmental Microbiology, 76(5):1524-32, 2010
Desai TD, Rao CV
Designing orthogonal factors for regulating transcription and translation
The goal of synthetic biology is to engineer and reprogram cellular processes for producing novel compounds and also improving health and the environment through the rational implementation of well-characterized genetic components. Introducing novel functionality into cells, however, requires components that do not interfere with native cellular processes. As we consider more complex synthetic biology applications, greater premium will be placed on expanding our genetic toolbox. Towards this goal, our lab has developed a set of computational algorithms for reprogramming the specificity of transcriptional factors and ribosomes in bacteria. In both cases, we were able to experimentally validate these algorithms.
A central theme in both applications is the engineering of orthogonal pairs of regulatory factors, orthogonal in the sense that the engineered factor binds a sequence not recognized by the native factor but does not bind the sequences that are recognized by the native factor.
Engineering transcription factors with novel DNA-binding specificity using comparative genomics
Nucleic Acids Research, 37(8):2493-503, 2009
Desai TA, Rodionov DA, Gelfand MS, Alm EJ, Rao CV
Computational design of orthogonal ribosomes
Nucleic Acids Research, 36(12):4038-46, 2008
Chubiz LM, Rao CV
Bacillus subtilis Chemotaxis
Our lab in collaboration with George Ordal is investigating chemotaxis in the model Gram-positive bacterium Bacillus subtilis. While Escherichia coli has long been the paradigm for bacterial chemotaxis, the pathway architecture is not conserved in other species of bacteria. Interestingly, B. subtilis behaves in an identical manner to E. coli with regards to chemotaxis. The pathways in the two bacteria also have homologous proteins. Yet, how these proteins are “wired” to one another in the two pathways is entirely different. We seek to understand why these two pathways are “wired” differently and the extent of degeneracy in the basic design.
Attractant binding induces distinct structural changes to the polar and lateral signaling clusters in Bacillus subtilis chemotaxis.
Journal of Biological Chemistry, November 2010,
Wu K, Walukiewicz HE, Glekas GD, Ordal GW, Rao CV
Site-specific methylation in Bacillus subtilis chemotaxis: The effect of covalent modifications to the chemotaxis receptor McpB.
Microbiology, September 2010,
Glekas GD, Cates JR, Cohen TM, Rao CV, Ordal GW
A PAS domain binds asparagine in the chemotaxis receptor McpB in Bacillus subtilis
Journal of Biological Chemistry, 285(3):1870-8, 2010
Glekas GD, Foster RM, Cates JR, Estrella JA, Wawrzyniak MJ, Rao CV, Ordal GW
The molecular basis of excitation and adaptation during chemotactic sensory transduction in bacteria
Contributions to Microbiology, 16:33-64, 2009
Rao CV, Ordal GW
The three adaptation systems of Bacillus subtilis chemotaxis
Trends in Microbiology, 16(10):480-7, 2008
Rao CV, Glekas GD, Ordal GW
Phosphatase localization in bacterial chemotaxis: divergent mechanisms, convergent principles
Physical Biology, 14;2(3):148-58, 2005
Rao CV, Kirby JR, Arkin AP
Design and diversity in bacterial chemotaxis: a comparative study in Escherichia coli and Bacillus subtilis
PLoS Biology, 2(2):E49, 2004
Rao CV, Kirby JR, Arkin AP
Assembly of the bacterial flagellum
The flagellum is a rotary motor that enables bacteria to swim in liquids and swarm on surfaces. Over 50 genes
divided among at least 17 operons are involved in assembling flagella. Assembly proceeds in a sequential manner beginning
at the base along the inner plasma membrane and concluding at the distal tip of the filament. These genes are expressed in a temporal hierarchy that is coupled to the assembly process itself.
Our lab are investigating how Salmonella controls the number of flagella that it builds as a model for organelle development. In collaboration with Phil Aldridge, we have found that Salmonella uses protein secretion as a proxy signal for flagellar abundance. In other words, we discovered how Salmonella is able to count flagella. We are currently uncovering the regulatory network that controls flagellar abundance in response to protein secretion.
Continuous control of flagellar gene expression by the σ28–FlgM regulatory circuit in Salmonella enterica
Molecular Microbiology, November, 2010,
Saini S, Floess E, Aldridge C, Brown J, Aldridge PD, Rao CV
The interaction dynamics of a negative feedback loop regulates flagellar number in Salmonella enterica serovar Typhimurium
Molecular Microbiology, 78(6):1416–1430, 2010,
Aldridge C, Poonchareon K, Saini S, Soloyva A, Rao CV, Imada K, Minamino T, Aldridge PD
FliZ Induces a Kinetic Switch in Flagellar Gene Expression
Journal of Bacteriology, 192(24):6477-81, 2010
Saini S, Koirala S, Floess E, Mears PJ, Chemla YR, Golding I, Aldridge C,
Aldridge PD, Rao CV
High-resolution, long-term characterization of bacterial motility using optical tweezers
Nature Methods, 6(11):831-5, 2009
Min TL, Mears PJ, Chubiz LM, Rao CV, Golding I, Chemla YR
The rate of protein secretion dictates the temporal dynamics of flagellar gene expression
Molecular Microbiology, 70(4):924-37, 2008
Brown JD, Saini S, Aldridge C, Herbert J, Rao CV, Aldridge PD
FliZ Is a posttranslational activator of FlhD4C2-dependent flagellar gene expression
Journal of Bacteriology, 190(14):4979-88, 2008
Saini S, Brown JD, Aldridge PD, Rao CV
Physical structure of transcriptional regulation
We are investigating how transcriptional regulation is genetically encoded. In particular, we are interested in understanding how the behavior of a gene circuit is determined by its physical encoding within the genome. By physical encoding, we mean the orientation and relative proximity of a transcription factor to its target structural genes. We have shown that, in addition to the specific regulatory mechanism employed, the behavior of a gene circuit may also be determined by how it is physically encoded within the genome. In particular, we found that the sensitivity and metabolic cost associated with an inducible gene circuit can be altered by different genetic encodings. These results are significant because they are among the first to demonstrate how different encodings of otherwise equivalent gene circuits can affect their behavior.
The role of configuration and coupling in autoregulatory gene circuits.
Molecular Microbiology, 75(2):513-27, 2010
Wu K, Rao CV