The transcriptome of Mycobacterium tuberculosis

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/.

Computational insights into promoter architecture of toxin-antitoxin systems of Mycobacterium tuberculosis

Toxin-antitoxin (TA) systems are two component genetic modules widespread in many bacterial genomes, including Mycobacterium tuberculosis (Mtb). The TA systems play a significant role in biofilm formation, antibiotic tolerance and persistence of pathogen inside the host cells. Deciphering regulatory motifs of Mtb TA systems is the first essential step to understand their transcriptional regulation. In this study, in silico approaches, that is, the knowledge based motif discovery and de novo motif discovery were used to identify the regulatory motifs of 79 Mtb TA systems. The knowledge based motif discovery approach was used to design a Perl based bio-tool Mtb-sig-miner available at (https://github.com/zoozeal/Mtb-sig-miner), which could successfully detect sigma (σ) factor specific regulatory motifs in the promoter region of Mtb TA modules. The manual curation of Mtb-sig-miner output hits revealed that the majority of them possessed σ^B regulatory motif in their promoter region. On the other hand, de novo approach resulted in the identification of a novel conserved motif [(T/A)(G/T)NTA(G/C)(C/A)AT(C/A)] within the promoter region of 14 Mtb TA systems. The identified conserved motif was also validated for its activity as conserved core region of operator sequence of corresponding TA system by molecular docking studies. The strong binding of respective antitoxin/toxin with the identified novel conserved motif reflected the validation of identified motif as the core region of operator sequence of respective TA systems. These findings provide computational insight to understand the transcriptional regulation of Mtb TA systems.

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

A map of the transcriptional organization of genes of an organism is a basic tool that is necessary to understand and facilitate a more accurate genetic manipulation of the organism. Operon maps are largely generated by computational prediction programs that rely on gene conservation and genome architecture and may not be physiologically relevant. With the widespread use of RNA sequencing (RNAseq), the prediction of operons based on actual transcriptome sequencing rather than computational genomics alone is much needed. Here, we report a validated operon map of Mycobacterium tuberculosis, developed using RNAseq data from both the exponential and stationary phases of growth. At least 58.4% of M. tuberculosis genes are organized into 749 operons. Our prediction algorithm, REMap (RNA Expression Mapping of operons), considers the many cases of transcription coverage of intergenic regions, and avoids dependencies on functional annotation and arbitrary assumptions about gene structure. As a result, we demonstrate that REMap is able to more accurately predict operons, especially those that contain long intergenic regions or functionally unrelated genes, than previous operon prediction programs. The REMap algorithm is publicly available as a user-friendly tool that can be readily modified to predict operons in other bacteria.

Comparative analyses of transport proteins encoded within the genomes of Mycobacterium tuberculosis and Mycobacterium leprae

The co-emergence of multidrug resistant pathogenic bacterial strains and the Human Immunodeficiency Virus pandemic has made tuberculosis a leading public health threat. The causative agent is Mycobacterium tuberculosis (Mtu), a facultative intracellular parasite. Mycobacterium leprae (Mle), a related organism that causes leprosy, is an obligate intracellular parasite. Given that different transporters are required for bacterial growth and persistence under a variety of growth conditions, we conducted comparative analyses of transport proteins encoded within the genomes of these two organisms. A minimal set of genes required for intracellular and extracellular life was identified. Drug efflux systems utilizing primary active transport mechanisms have been preferentially retained in Mle and still others preferentially lost. Transporters associated with environmental adaptation found in Mtu were mostly lost in Mle. These findings provide starting points for experimental studies that may elucidate the dependencies of pathogenesis on transport for these two pathogenic mycobacteria. They also lead to suggestions regarding transporters that function in intra- versus extra-cellular growth.

The impact of transcriptomics on the fight against tuberculosis: focus on biomarkers, BCG vaccination, and immunotherapy

In 1882 Robert Koch identified Mycobacterium tuberculosis as the causative agent of tuberculosis (TB), a disease as ancient as humanity. Although there has been more than 125 years of scientific effort aimed at understanding the disease, serious problems in TB persist that contribute to the estimated 1/3 of the world population infected with this pathogen. Nonetheless, during the first decade of the 21st century, there were new advances in the fight against TB. The development of high-throughput technologies is one of the major contributors to this advance, because it allows for a global vision of the biological phenomenon. This paper analyzes how transcriptomics are supporting the translation of basic research into therapies by resolving three key issues in the fight against TB: (a) the discovery of biomarkers, (b) the explanation of the variability of protection conferred by BCG vaccination, and (c) the development of new immunotherapeutic strategies to treat TB.

Transcriptional profiling of mycobacterium tuberculosis during infection: lessons learned

Infection with Mycobacterium tuberculosis, the causative agent of tuberculosis, is considered one of the biggest infectious disease killers worldwide. A significant amount of attention has been directed toward revealing genes involved in the virulence and pathogenesis of this air-born pathogen. With the advances in technologies for transcriptional profiling, several groups, including ours, took advantage of DNA microarrays to identify transcriptional units differentially regulated by M. tuberculosis within a host. The main idea behind this approach is that pathogens tend to regulate their gene expression levels depending on the host microenvironment, and preferentially express those needed for survival. Identifying this class of genes will improve our understanding of pathogenesis. In our case, we identified an in vivo expressed genomic island that was preferentially active in murine lungs during early infection, as well as groups of genes active during chronic tuberculosis. Other studies have identified additional gene groups that are active during macrophage infection and even in human lungs. Despite all of these findings, one of the lingering questions remaining was whether in vivo expressed transcripts are relevant to the virulence, pathogenesis, and persistence of the organism. The work of our group and others addressed this question by examining the contribution of in vivo expressed genes using a strategy based on gene deletions followed by animal infections. Overall, the analysis of most of the in vivo expressed genes supported a role of these genes in M. tuberculosis pathogenesis. Further, these data suggest that in vivo transcriptional profiling is a valid approach to identify genes required for bacterial pathogenesis.