REMap: Operon map of M. tuberculosis based on RNA sequence data

Exopolysaccharide Biosynthesis in Rhizobium leguminosarum bv. trifolii Requires a Complementary Function of Two Homologous Glycosyltransferases PssG and PssI

The Pss-I region of Rhizobium leguminosarum bv. trifolii TA1 comprises more than 20 genes coding for glycosyltransferases, modifying enzymes, and polymerization/export proteins, altogether determining the biosynthesis of symbiotically relevant exopolysaccharides. In this study, the role of homologous PssG and PssI glycosyltransferases in exopolysaccharide subunit synthesis were analyzed. It was shown that the glycosyltransferase-encoding genes of the Pss-I region were part of a single large transcriptional unit with potential downstream promoters activated in specific conditions. The ΔpssG and ΔpssI mutants produced significantly lower amounts of the exopolysaccharide, while the double deletion mutant ΔpssIΔpssG produced no exopolysaccharide. Complementation of double mutation with individual genes restored exopolysaccharide synthesis, but only to the level similar to that observed for the single ΔpssI or ΔpssG mutants, indicating that PssG and PssI serve complementary functions in the process. PssG and PssI interacted with each other in vivo and in vitro. Moreover, PssI displayed an expanded in vivo interaction network comprising other GTs involved in subunit assembly and polymerization/export proteins. PssG and PssI proteins were shown to interact with the inner membrane through amphipathic helices at their C-termini, and PssG also required other proteins involved in exopolysaccharide synthesis to localize in the membrane protein fraction.

A d-Phenylalanine-Benzoxazole Derivative Reveals the Role of the Essential Enzyme Rv3603c in the Pantothenate Biosynthetic Pathway of Mycobacterium tuberculosis

New drugs and new targets are urgently needed to treat tuberculosis. We discovered that d-phenylalanine-benzoxazole Q112 displays potent antibacterial activity against Mycobacterium tuberculosis (Mtb) in multiple media and in macrophage infections. A metabolomic profiling indicates that Q112 has a unique mechanism of action. Q112 perturbs the essential pantothenate/coenzyme A biosynthetic pathway, depleting pantoate while increasing ketopantoate, as would be expected if ketopantoate reductase (KPR) were inhibited. We searched for alternative KPRs, since the enzyme annotated as PanE KPR is not essential in Mtb. The ketol-acid reductoisomerase IlvC catalyzes the KPR reaction in the close Mtb relative Corynebacterium glutamicum, but Mtb IlvC does not display KPR activity. We identified the essential protein Rv3603c as an orthologue of PanG KPR and demonstrated that a purified recombinant Rv3603c has KPR activity. Q112 inhibits Rv3603c, explaining the metabolomic changes. Surprisingly, pantothenate does not rescue Q112-treated bacteria, indicating that Q112 has an additional target(s). Q112-resistant strains contain loss-of-function mutations in the twin arginine translocase TatABC, further underscoring Q112's unique mechanism of action. Loss of TatABC causes a severe fitness deficit attributed to changes in nutrient uptake, suggesting that Q112 resistance may derive from a decrease in uptake.

Multiple transcription factors co-regulate the Mycobacterium tuberculosis adaptation response to vitamin C

Background

Latent tuberculosis infection is attributed in part to the existence of Mycobacterium tuberculosis in a persistent non-replicating dormant state that is associated with tolerance to host defence mechanisms and antibiotics. We have recently reported that vitamin C treatment of M. tuberculosis triggers the rapid development of bacterial dormancy. Temporal genome-wide transcriptome analysis has revealed that vitamin C-induced dormancy is associated with a large-scale modulation of gene expression in M. tuberculosis.

Results

An updated transcriptional regulatory network of M.tuberculosis (Mtb-TRN) consisting of 178 regulators and 3432 target genes was constructed. The temporal transcriptome data generated in response to vitamin C was overlaid on the Mtb-TRN (vitamin C Mtb-TRN) to derive insights into the transcriptional regulatory features in vitamin C-adapted bacteria. Statistical analysis using Fisher’s exact test predicted that 56 regulators play a central role in modulating genes which are involved in growth, respiration, metabolism and repair functions. Rv0348, DevR, MprA and RegX3 participate in a core temporal regulatory response during 0.25 h to 8 h of vitamin C treatment. Temporal network analysis further revealed Rv0348 to be the most prominent hub regulator with maximum interactions in the vitamin C Mtb-TRN. Experimental analysis revealed that Rv0348 and DevR proteins interact with each other, and this interaction results in an enhanced binding of DevR to its target promoter. These findings, together with the enhanced expression of devR and Rv0348 transcriptional regulators, indicate a second-level regulation of target genes through transcription factor- transcription factor interactions.

Conclusions

Temporal regulatory analysis of the vitamin C Mtb-TRN revealed that there is involvement of multiple regulators during bacterial adaptation to dormancy. Our findings suggest that Rv0348 is a prominent hub regulator in the vitamin C model and large-scale modulation of gene expression is achieved through interactions of Rv0348 with other transcriptional regulators.

A computational system for identifying operons based on RNA-seq data

An operon is a set of neighboring genes in a genome that is transcribed as a single polycistronic message. Genes that are part of the same operon often have related functional roles or participate in the same metabolic pathways. The majority of all bacterial genes are co-transcribed with one or more other genes as part of a multi-gene operon. Thus, accurate identification of operons is important in understanding co-regulation of genes and their functional relationships. Here, we present a computational system that uses RNA-seq data to determine operons throughout a genome. The system takes the name of a genome and one or more files of RNA-seq data as input. Our method combines primary genomic sequence information with expression data from the RNA-seq files in a unified probabilistic model in order to identify operons. We assess our method's ability to accurately identify operons in a range of species through comparison to external databases of operons, both experimentally confirmed and computationally predicted, and through focused experiments that confirm new operons identified by our method. Our system is freely available at https://cs.wellesley.edu/~btjaden/Rockhopper/.

Validation of Novel Mycobacterium tuberculosis Isoniazid Resistance Mutations Not Detectable by Common Molecular Tests

Resistance to the first-line antituberculosis (TB) drug isoniazid (INH) is widespread, and the mechanism of resistance is unknown in approximately 15% of INH-resistant (INH-R) strains. To improve molecular detection of INH-R TB, we used whole-genome sequencing (WGS) to analyze 52 phenotypically INH-R Mycobacterium tuberculosis complex (MTBC) clinical isolates that lacked the common katG S315T or inhA promoter mutations. Approximately 94% (49/52) of strains had mutations at known INH-associated loci that were likely to confer INH resistance. All such mutations would be detectable by sequencing more DNA adjacent to existing target regions. Use of WGS minimized the chances of missing infrequent INH resistance mutations outside commonly targeted hotspots. We used recombineering to generate 12 observed clinical katG mutations in the pansusceptible H37Rv reference strain and determined their impact on INH resistance. Our functional genetic experiments have confirmed the role of seven suspected INH resistance mutations and discovered five novel INH resistance mutations. All recombineered katG mutations conferred resistance to INH at a MIC of ≥0.25 μg/ml and should be added to the list of INH resistance determinants targeted by molecular diagnostic assays. We conclude that WGS is a useful tool for detecting uncommon INH resistance mutations that would otherwise be missed by current targeted molecular testing methods and suggest that its use (or use of expanded conventional or next-generation-based targeted sequencing) may provide earlier diagnosis of INH-R TB.