Genome-scale gene/reaction essentiality and synthetic lethality analysis

Synthetic lethals are to pairs of non-essential genes whose simultaneous deletion prohibits growth. One can extend the concept of synthetic lethality by considering gene groups of increasing size where only the simultaneous elimination of all genes is lethal, whereas individual gene deletions are not. We developed optimization-based procedures for the exhaustive and targeted enumeration of multi-gene (and by extension multi-reaction) lethals for genome-scale metabolic models. Specifically, these approaches are applied to iAF1260, the latest model of Escherichia coli, leading to the complete identification of all double and triple gene and reaction synthetic lethals as well as the targeted identification of quadruples and some higher-order ones. Graph representations of these synthetic lethals reveal a variety of motifs ranging from hub-like to highly connected subgraphs providing a birds-eye view of the avenues available for redirecting metabolism and uncovering complex patterns of gene utilization and interdependence. The procedure also enables the use of falsely predicted synthetic lethals for metabolic model curation. By analyzing the functional classifications of the genes involved in synthetic lethals, we reveal surprising connections within and across clusters of orthologous group functional classifications

Metabolic Adaptation of Ralstonia solanacearum during Plant Infection: A Methionine Biosynthesis Case Study

MetE and MetH are two distinct enzymes that catalyze a similar biochemical reaction during the last step of methionine biosynthesis, MetH being a cobalamin-dependent enzyme whereas MetE activity is cobalamin-independent. In this work, we show that the last step of methionine synthesis in the plant pathogen Ralstonia solanacearum is under the transcriptional control of the master pathogenicity regulator HrpG. This control is exerted essentially on metE expression through the intermediate regulator MetR. Expression of metE is strongly and specifically induced in the presence of plant cells in a hrpG- and metR-dependent manner. metE and metR mutants are not auxotrophic for methionine and not affected for growth inside the plant but produce significantly reduced disease symptoms on tomato whereas disruption of metH has no impact on pathogenicity. The finding that the pathogen preferentially induces metE expression rather than metH in the presence of plant cells is indicative of a probable metabolic adaptation to physiological host conditions since this induction of metE occurs in an environment in which cobalamin, the required co-factor for MetH, is absent. It also shows that MetE and MetH are not functionally redundant and are deployed during specific stages of the bacteria lifecycle, the expression of metE and metH being controlled by multiple and distinct signals

Query Large Scale Microarray Compendium Datasets Using a Model-Based Bayesian Approach with Variable Selection

In microarray gene expression data analysis, it is often of interest to identify genes that share similar expression profiles with a particular gene such as a key regulatory protein. Multiple studies have been conducted using various correlation measures to identify co-expressed genes. While working well for small datasets, the heterogeneity introduced from increased sample size inevitably reduces the sensitivity and specificity of these approaches. This is because most co-expression relationships do not extend to all experimental conditions. With the rapid increase in the size of microarray datasets, identifying functionally related genes from large and diverse microarray gene expression datasets is a key challenge. We develop a model-based gene expression query algorithm built under the Bayesian model selection framework. It is capable of detecting co-expression profiles under a subset of samples/experimental conditions. In addition, it allows linearly transformed expression patterns to be recognized and is robust against sporadic outliers in the data. Both features are critically important for increasing the power of identifying co-expressed genes in large scale gene expression datasets. Our simulation studies suggest that this method outperforms existing correlation coefficients or mutual information-based query tools. When we apply this new method to the Escherichia coli microarray compendium data, it identifies a majority of known regulons as well as novel potential target genes of numerous key transcription factors

Modulation of Bacterial Type III Secretion System by a Spermidine Transporter Dependent Signaling Pathway

10.1371/journal.pone.0001291PLoS ONE212

The Type III Secreted Protein BspR Regulates the Virulence Genes in Bordetella bronchiseptica

Bordetella bronchiseptica is closely related with B. pertussis and B. parapertussis, the causative agents of whooping cough. These pathogenic species share a number of virulence genes, including the gene locus for the type III secretion system (T3SS) that delivers effector proteins. To identify unknown type III effectors in Bordetella, secreted proteins in the bacterial culture supernatants of wild-type B. bronchiseptica and an isogenic T3SS-deficient mutant were compared with iTRAQ-based, quantitative proteomic analysis method. BB1639, annotated as a hypothetical protein, was identified as a novel type III secreted protein and was designated BspR (Bordetella secreted protein regulator). The virulence of a BspR mutant (ΔbspR) in B. bronchiseptica was significantly attenuated in a mouse infection model. BspR was also highly conserved in B. pertussis and B. parapertussis, suggesting that BspR is an essential virulence factor in these three Bordetella species. Interestingly, the BspR-deficient strain showed hyper-secretion of T3SS-related proteins. Furthermore, T3SS-dependent host cell cytotoxicity and hemolytic activity were also enhanced in the absence of BspR. By contrast, the expression of filamentous hemagglutinin, pertactin, and adenylate cyclase toxin was completely abolished in the BspR-deficient strain. Finally, we demonstrated that BspR is involved in the iron-responsive regulation of T3SS. Thus, Bordetella virulence factors are coordinately but inversely controlled by BspR, which functions as a regulator in response to iron starvation

Genomic mining of prokaryotic repressors for orthogonal logic gates

Genetic circuits perform computational operations based on interactions between freely diffusing molecules within a cell. When transcription factors are combined to build a circuit, unintended interactions can disrupt its function. Here, we apply 'part mining' to build a library of 73 TetR-family repressors gleaned from prokaryotic genomes. The operators of a subset were determined using an in vitro method, and this information was used to build synthetic promoters. The promoters and repressors were screened for cross-reactions. Of these, 16 were identified that both strongly repress their cognate promoter (5- to 207-fold) and exhibit minimal interactions with other promoters. Each repressor-promoter pair was converted to a NOT gate and characterized. Used as a set of 16 NOT/NOR gates, there are >10[superscript 54] circuits that could be built by changing the pattern of input and output promoters. This represents a large set of compatible gates that can be used to construct user-defined circuits.United States. Air Force Office of Scientific Research (Award FA9550-11-C-0028)American Society for Engineering Education. National Defense Science and Engineering Graduate Fellowship (32 CFR 168a)United States. Defense Advanced Research Projects Agency. Chronical of Lineage Indicative of Origins (N66001-12-C-4016)United States. Office of Naval Research (N00014-13-1-0074)National Institutes of Health (U.S.) (GM095765)National Science Foundation (U.S.). Synthetic Biology Engineering Research Center (SA5284-11210

Prediction by Promoter Logic in Bacterial Quorum Sensing

Quorum-sensing systems mediate chemical communication between bacterial cells, coordinating cell-density-dependent processes like biofilm formation and virulence-factor expression. In the proteobacterial LuxI/LuxR quorum sensing paradigm, a signaling molecule generated by an enzyme (LuxI) diffuses between cells and allosterically stimulates a transcriptional regulator (LuxR) to activate its cognate promoter (pR). By expressing either LuxI or LuxR in positive feedback from pR, these versatile systems can generate smooth (monostable) or abrupt (bistable) density-dependent responses to suit the ecological context. Here we combine theory and experiment to demonstrate that the promoter logic of pR – its measured activity as a function of LuxI and LuxR levels – contains all the biochemical information required to quantitatively predict the responses of such feedback loops. The interplay of promoter logic with feedback topology underlies the versatility of the LuxI/LuxR paradigm: LuxR and LuxI positive-feedback systems show dramatically different responses, while a dual positive/negative-feedback system displays synchronized oscillations. These results highlight the dual utility of promoter logic: to probe microscopic parameters and predict macroscopic phenotype