Genomics and transcriptomics of the Mycobacterium tuberculosis complex

The goal of eliminating tuberculosis (TB) by 2050 depends on the development of improved TB diagnostics, drugs and vaccines. Advances in these areas require a deep understanding of the disease and its causative agent, Mycobacterium tuberculosis (M. tb). Mycobacterial species that cause TB in humans and other mammalian hosts are grouped within the M. tb complex. Development of powerful technologies such as next-generation sequencing and microarrays opened up new avenues for comparative and functional genomics of the M. tb complex. Due to the large and increasingly complex datasets generated from these technologies, the bottleneck in biological investigation has shifted from data generation to analysis. The objectives of this thesis were to establish and employ strategies for the analysis, integration, and interpretation of high-throughput sequencing and microarray datasets using a range of bioinformatics and statistical tools. In the area of comparative genomics, we assessed the genetic diversity in the M. tb complex using various methods, such as SNP (single nucleotide polymorphism) genotyping, automated Sanger sequencing and next-generation sequencing. In a study comparing the genomes of the virulent M. bovis and M. bovis BCG vaccine strains, we identified a set of SNPs that were common to all BCG strains, and could provide novel insights on the molecular basis of BCG attenuation. In another study, we surveyed the genetic variation in the highly immunodominant esx gene family among clinical isolates of M. tb and identified sequence polymorphisms in known T- cell epitopes on Esx proteins that could affect their immunogenicity. We exploited the power of next-generation sequencing to detect sequence variation among M. tb strains that could result in phenotypic differences. By comparing the genomes of drug-resistant mutants with the sensitive wild-type strain we were able to identify the target of the anti-TB drug, pyridomycin. Using a similar approach we identified a mutation that makes M. tb strains incapable of producing PDIMs (phthiocerol dimycocerosates), which are cell wall associated lipids involved in M. tb virulence. In the area of functional genomics, we mapped genome-wide binding sites for transcription factors using chromatin immunoprecipitation followed by hybridization to microarrays (ChIP-on-chip) or sequencing (ChIP-seq), and performed transcription profiling by means of high-throughput cDNA sequencing (RNA-seq). We carried out a comprehensive study to characterize the whole transcriptome of M. tb in exponential and stationary phases of growth, and understand the genome-wide dynamics of two key components of the transcription machinery, namely, RNA polymerase and NusA. By systematic integration of the ChIP-seq and RNA-seq data, we identified a set of transcription units (TU) in the M. tb genome, and mapped their putative promoters. Analysis of RNAP and NusA binding across the promoter and body of TUs and their correlation with transcription uncovered new functional aspects of the transcriptional complex in M. tb. We also exploited the ChIP-on-chip and ChIP-seq technologies to define the regulon of the M. tb sigma factor F, and gain a better understanding of the regulatory role of the nucleoid associated protein, EspR. Altogether, this thesis has improved our knowledge of the evolution, physiology and virulence of the M. tb complex. In addition, we have established next generation sequencing as a powerful tool for comparative and functional studies, with potential applications in the clinical setting

High-resolution transcriptome and genome-wide dynamics of RNA polymerase and NusA in Mycobacterium tuberculosis

To construct a regulatory map of the genome of the human pathogen, Mycobacterium tuberculosis, we applied two complementary high-resolution approaches: strand-specific RNA-seq, to survey the global transcriptome, and ChIP-seq, to monitor the genome-wide dynamics of RNA polymerase (RNAP) and the anti-terminator NusA. Although NusA does not bind directly to DNA, but rather to RNAP and/or to the nascent transcript, we demonstrate that NusA interacts with RNAP ubiquitously throughout the chromosome, and that its profile mirrors RNAP distribution in both the exponential and stationary phases of growth. Generally, promoter-proximal peaks for RNAP and NusA were observed, followed by a decrease in signal strength reflecting transcriptional polarity. Differential binding of RNAP and NusA in the two growth conditions correlated with transcriptional activity as reflected by RNA abundance. Indeed, a significant association between expression levels and the presence of NusA throughout the gene body was detected, confirming the peculiar transcription-promoting role of NusA. Integration of the data sets pinpointed transcriptional units, mapped promoters and uncovered new anti-sense and non-coding transcripts. Highly expressed transcriptional units were situated mainly on the leading strand, despite the relatively unbiased distribution of genes throughout the genome, thus helping the replicative and transcriptional complexes to alig

Ten simple rules for the sharing of bacterial genotype—Phenotype data on antimicrobial resistance

The increasing availability of high-throughput sequencing (frequently termed next-generation sequencing (NGS)) data has created opportunities to gain deeper insights into the mechanisms of a number of diseases and is already impacting many areas of medicine and public health. The area of infectious diseases stands somewhat apart from other human diseases insofar as the relevant genomic data comes from the microbes rather than their human hosts. A particular concern about the threat of antimicrobial resistance (AMR) has driven the collection and reporting of large-scale datasets containing information from microbial genomes together with antimicrobial susceptibility test (AST) results. Unfortunately, the lack of clear standards or guiding principles for the reporting of such data is hampering the field's advancement. We therefore present our recommendations for the publication and sharing of genotype and phenotype data on AMR, in the form of 10 simple rules. The adoption of these recommendations will enhance AMR data interoperability and help enable its large-scale analyses using computational biology tools, including mathematical modelling and machine learning. We hope that these rules can shed light on often overlooked but nonetheless very necessary aspects of AMR data sharing and enhance the field's ability to address the problems of understanding AMR mechanisms, tracking their emergence and spread in populations, and predicting microbial susceptibility to antimicrobials for diagnostic purposes

In silico evaluation of WHO-endorsed molecular methods to detect drug resistant tuberculosis

Universal drug susceptibility testing (DST) for tuberculosis is a major goal of the END TB strategy. PCR-based molecular diagnostic tests have been instrumental in increasing DST globally and several assays have now been endorsed by the World Health Organization (WHO) for use in the diagnosis of drug resistance. These endorsed assays, however, each interrogate a limited number of mutations associated with resistance, potentially limiting their sensitivity compared to sequencing-based methods. We applied an in silico method to compare the sensitivity and specificity of WHO-endorsed molecular based diagnostics to the mutation set identified by the WHO mutations catalogue using phenotypic DST as the reference. We found that, in silico, the mutation sets used by probe-based molecular diagnostic tests to identify rifampicin, isoniazid, pyrazinamide, levofloxacin, moxifloxacin, amikacin, capreomycin and kanamycin resistance produced similar sensitivities and specificities to the WHO mutation catalogue. PCR-based diagnostic tests were most sensitive for drugs where mechanisms of resistance are well established and localised to small genetic regions or a few prevalent mutations. Approaches using sequencing technologies can provide advantages for drugs where our knowledge of resistance is limited, or where complex resistance signatures exist

A Method for Amplicon Deep Sequencing of Drug Resistance Genes in Plasmodium falciparum Clinical Isolates from India.

A major challenge to global malaria control and elimination is early detection and containment of emerging drug resistance. Next-generation sequencing (NGS) methods provide the resolution, scalability, and sensitivity required for high-throughput surveillance of molecular markers of drug resistance. We have developed an amplicon sequencing method on the Ion Torrent PGM platform for targeted resequencing of a panel of six Plasmodium falciparum genes implicated in resistance to first-line antimalarial therapy, including artemisinin combination therapy, chloroquine, and sulfadoxine-pyrimethamine. The protocol was optimized using 12 geographically diverse P. falciparum reference strains and successfully applied to multiplexed sequencing of 16 clinical isolates from India. The sequencing results from the reference strains showed 100% concordance with previously reported drug resistance-associated mutations. Single-nucleotide polymorphisms (SNPs) in clinical isolates revealed a number of known resistance-associated mutations and other nonsynonymous mutations that have not been implicated in drug resistance. SNP positions containing multiple allelic variants were used to identify three clinical samples containing mixed genotypes indicative of multiclonal infections. The amplicon sequencing protocol has been designed for the benchtop Ion Torrent PGM platform and can be operated with minimal bioinformatics infrastructure, making it ideal for use in countries that are endemic for the disease to facilitate routine large-scale surveillance of the emergence of drug resistance and to ensure continued success of the malaria treatment policy

Population Genetics, Evolutionary Genomics, and Genome-Wide Studies of Malaria: A View Across the International Centers of Excellence for Malaria Research.

The study of the three protagonists in malaria-the Plasmodium parasite, the Anopheles mosquito, and the human host-is key to developing methods to control and eventually eliminate the disease. Genomic technologies, including the recent development of next-generation sequencing, enable interrogation of this triangle to an unprecedented level of scrutiny, and promise exciting progress toward real-time epidemiology studies and the study of evolutionary adaptation. We discuss the use of genomics by the International Centers of Excellence for Malaria Research, a network of field sites and laboratories in malaria-endemic countries that undertake cutting-edge research, training, and technology transfer in malarious countries of the world

Towards a new tuberculosis drug: pyridomycin - nature's isoniazid

Tuberculosis, a global threat to public health, is becoming untreatable due to widespread drug resistance to frontline drugs such as the InhA-inhibitor isoniazid. Historically, by inhibiting highly vulnerable targets, natural products have been an important source of antibiotics including potent anti-tuberculosis agents. Here, we describe pyridomycin, a compound produced by Dactylosporangium fulvum with specific cidal activity against mycobacteria. By selecting pyridomycin-resistant mutants of Mycobacterium tuberculosis, whole-genome sequencing and genetic validation, we identified the NADH-dependent enoyl(Acyl-Carrier-Protein) reductase InhA as the principal target and demonstrate that pyridomycin inhibits mycolic acid synthesis in M. tuberculosis. Furthermore, biochemical and structural studies show that pyridomycin inhibits InhA directly as a competitive inhibitor of the NADH-binding site, thereby identifying a new, druggable pocket in InhA. Importantly, the most frequently encountered isoniazid-resistant clinical isolates remain fully susceptible to pyridomycin, thus opening new avenues for drug development

Catalogue of mutations in Mycobacterium tuberculosis complex and their association with drug resistance

96 páginas, figuras y tablasThis work was funded by grants provided by Unitaid and the United States Agency for International DevelopmentPeer reviewe

Virulence Regulator EspR of Mycobacterium tuberculosis Is a Nucleoid-Associated Protein

The principal virulence determinant of Mycobacterium tuberculosis (Mtb), the ESX-1 protein secretion system, is positively controlled at the transcriptional level by EspR. Depletion of EspR reportedly affects a small number of genes, both positively or negatively, including a key ESX-1 component, the espACD operon. EspR is also thought to be an ESX-1 substrate. Using EspR-specific antibodies in ChIP-Seq experiments (chromatin immunoprecipitation followed by ultra-high throughput DNA sequencing) we show that EspR binds to at least 165 loci on the Mtb genome. Included in the EspR regulon are genes encoding not only EspA, but also EspR itself, the ESX-2 and ESX-5 systems, a host of diverse cell wall functions, such as production of the complex lipid PDIM (phenolthiocerol dimycocerosate) and the PE/PPE cell-surface proteins. EspR binding sites are not restricted to promoter regions and can be clustered. This suggests that rather than functioning as a classical regulatory protein EspR acts globally as a nucleoid-associated protein capable of long-range interactions consistent with a recently established structural model. EspR expression was shown to be growth phase-dependent, peaking in the stationary phase. Overexpression in Mtb strain H37Rv revealed that EspR influences target gene expression both positively or negatively leading to growth arrest. At no stage was EspR secreted into the culture filtrate. Thus, rather than serving as a specific activator of a virulence locus, EspR is a novel nucleoid-associated protein, with both architectural and regulatory roles, that impacts cell wall functions and pathogenesis through multiple genes