TB database 2010: overview and update

Regulatory role of Mycobacterium tuberculosis MtrA on dormancy/resuscitation revealed by a novel target gene-mining strategy

Introduction

The unique dormancy of Mycobacterium tuberculosis plays a significant role in the major clinical treatment challenge of tuberculosis, such as its long treatment cycle, antibiotic resistance, immune escape, and high latent infection rate.

Methods

To determine the function of MtrA, the only essential response regulator, one strategy was developed to establish its regulatory network according to high-quality genome-wide binding sites.

Results and discussion

The complex modulation mechanisms were implied by the strong bias distribution of MtrA binding sites in the noncoding regions, and 32.7% of the binding sites were located inside the target genes. The functions of 288 potential MtrA target genes predicted according to 294 confirmed binding sites were highly diverse, and DNA replication and damage repair, lipid metabolism, cell wall component biosynthesis, cell wall assembly, and cell division were the predominant pathways. Among the 53 pathways shared between dormancy/resuscitation and persistence, which accounted for 81.5% and 93.0% of the total number of pathways, respectively, MtrA regulatory genes were identified not only in 73.6% of their mutual pathways, but also in 75.4% of the pathways related to dormancy/resuscitation and persistence respectively. These results suggested the pivotal roles of MtrA in regulating dormancy/resuscitation and the apparent relationship between dormancy/resuscitation and persistence. Furthermore, the finding that 32.6% of the MtrA regulons were essential in vivo and/or in vitro for M. tuberculosis provided new insight into its indispensability. The findings mentioned above indicated that MtrA is a novel promising therapeutic target for tuberculosis treatment since the crucial function of MtrA may be a point of weakness for M. tuberculosis.

In silico drug design strategies for discovering novel tuberculosis therapeutics

INTRODUCTION

Tuberculosis remains a significant concern in global public health due to its intricate biology and propensity for developing antibiotic resistance. Discovering new drugs is a protracted and expensive endeavor, often spanning over a decade and incurring costs in the billions. However, computer-aided drug design (CADD) has surfaced as a nimbler and more cost-effective alternative. CADD tools enable us to decipher the interactions between therapeutic targets and novel drugs, making them invaluable in the quest for new tuberculosis treatments.

AREAS COVERED

In this review, the authors explore recent advancements in tuberculosis drug discovery enabled by in silico tools. The main objectives of this review article are to highlight emerging drug candidates identified through in silico methods and to provide an update on the therapeutic targets associated with Mycobacterium tuberculosis.

EXPERT OPINION

These in silico methods have not only streamlined the drug discovery process but also opened up new horizons for finding novel drug candidates and repositioning existing ones. The continued advancements in these fields hold great promise for more efficient, ethical, and successful drug development in the future.

M. tuberculosis AlkX Encoded by rv3249c Regulates a Conserved Alkane Hydroxylase System That Is Important for Replication in Macrophages and Biofilm Formation

Mycobacterium tuberculosis is a highly specialized human pathogen. The success of M. tuberculosis is due to its ability to replicate within host macrophages, resist host immune responses, and ultimately enter a persistent state during a latent tuberculosis infection. Understanding how M. tuberculosis adapts to and replicates in the intracellular environment of the host is crucial for the development of novel, targeted therapeutics. We report the characterization of an M. tuberculosis mutant lacking Rv3249c, a TetR transcriptional regulator. We show that Rv3249c directly represses the adjacent alkB-rubA-rubB operon encoding an alkane hydroxylase/rubredoxin system. For consistency with related systems, we have named the rv3249c gene alkX. The alkX mutant survived better than wild-type M. tuberculosis inside macrophages. This could be phenocopied by overexpression of the alkB-rubA-rubB locus. We hypothesized that the improved intracellular survival phenotype is a result of increased fitness of the mutant; however, we found that the alkX mutant had a defect when grown on some host-associated carbon sources in vitro. We also found that the alkX mutant had a defect in biofilm formation, also linked to the overexpression of the alkB-rubAB genes. Combined, these results define the primary role of AlkX as a transcriptional repressor of the alkB-rubAB operon and suggest the operon contributes to intracellular survival of the pathogen. IMPORTANCE Mycobacterium tuberculosis, the causative agent of tuberculosis (TB), is the leading cause of death worldwide due to a single infectious agent. It is important to understand how M. tuberculosis adapts to and replicates in the intracellular environment of the host. In this study, we characterized the TetR transcriptional regulator Rv3249c and show that it regulates a highly conserved alkane hydroxylase/rubredoxin system. Our data demonstrate that the AlkBRubAB system contributes to the success of the bacterium in host macrophages.

In silico Methods for Identification of Potential Therapeutic Targets

At the initial stage of drug discovery, identifying novel targets with maximal efficacy and minimal side effects can improve the success rate and portfolio value of drug discovery projects while simultaneously reducing cycle time and cost. However, harnessing the full potential of big data to narrow the range of plausible targets through existing computational methods remains a key issue in this field. This paper reviews two categories of in silico methods—comparative genomics and network-based methods—for finding potential therapeutic targets among cellular functions based on understanding their related biological processes. In addition to describing the principles, databases, software, and applications, we discuss some recent studies and prospects of the methods. While comparative genomics is mostly applied to infectious diseases, network-based methods can be applied to infectious and non-infectious diseases. Nonetheless, the methods often complement each other in their advantages and disadvantages. The information reported here guides toward improving the application of big data-driven computational methods for therapeutic target discovery.

Graphical abstract

In Silico Drug Discovery Strategies Identified ADMET Properties of Decoquinate RMB041 and Its Potential Drug Targets against Mycobacterium tuberculosis

The highly adaptive cellular response of Mycobacterium tuberculosis to various antibiotics and the high costs for clinical trials, hampers the development of novel antimicrobial agents with improved efficacy and safety. Subsequently, in silico drug screening methods are more commonly being used for the discovery and development of drugs, and have been proven useful for predicting the pharmacokinetics, toxicities, and targets, of prospective new antimicrobial agents. In this investigation we used a reversed target fishing approach to determine potential hit targets and their possible interactions between M. tuberculosis and decoquinate RMB041, a propitious new antituberculosis compound. Two of the 13 identified targets, Cyp130 and BlaI, were strongly proposed as optimal drug-targets for dormant M. tuberculosis, of which the first showed the highest comparative binding affinity to decoquinate RMB041. The metabolic pathways associated with the selected target proteins were compared to previously published molecular mechanisms of decoquinate RMB041 against M. tuberculosis, whereby we confirmed disrupted metabolism of proteins, cell wall components, and DNA. We also described the steps within these pathways that are inhibited and elaborated on decoquinate RMB041’s activity against dormant M. tuberculosis. This compound has previously showed promising in vitro safety and good oral bioavailability, which were both supported by this in silico study. The pharmacokinetic properties and toxicity of this compound were predicted and investigated using the online tools pkCSM and SwissADME, and Discovery Studio software, which furthermore supports previous safety and bioavailability characteristics of decoquinate RMB041 for use as an antimycobacterial medication.

IMPORTANCE This article elaborates on the mechanism of action of a novel antibiotic compound against both, active and dormant Mycobacterium tuberculosis and describes its pharmacokinetics (including oral bioavailability and toxicity). Information provided in this article serves useful during the search for drugs that shorten the treatment regimen for Tuberculosis and cause minimal adverse effects.

Multiple genetic paths including massive gene amplification allow Mycobacterium tuberculosis to overcome loss of ESX-3 secretion system substrates

The Mycobacterium tuberculosis (Mtb) ESX-3 type VII secretion system plays a critical role in iron acquisition. Infection of mice with highly attenuated Mtb deletion mutants lacking esxG or esxH, genes encoding key ESX-3 substrates, unexpectedly yielded suppressor mutants with restored capacity to grow in vivo and in vitro in the absence of iron supplementation. Whole-genome sequencing identified two mechanisms of suppression, the disruption of a transcriptional repressor that regulates expression of an ESX-3 paralogous region encoding EsxR and EsxS, and a massive 38- to 60-fold gene amplification of this same region. These data are significant because they reveal a previously unrecognized iron acquisition regulon and inform mechanisms of Mtb chromosome evolution.

Mycobacterium tuberculosis (Mtb) possesses five type VII secretion systems (T7SS), virulence determinants that include the secretion apparatus and associated secretion substrates. Mtb strains deleted for the genes encoding substrates of the ESX-3 T7SS, esxG or esxH, require iron supplementation for in vitro growth and are highly attenuated in vivo. In a subset of infected mice, suppressor mutants of esxG or esxH deletions were isolated, which enabled growth to high titers or restored virulence. Suppression was conferred by mechanisms that cause overexpression of an ESX-3 paralogous region that lacks genes for the secretion apparatus but encodes EsxR and EsxS, apparent ESX-3 orphan substrates that functionally compensate for the lack of EsxG or EsxH. The mechanisms include the disruption of a transcriptional repressor and a massive 38- to 60-fold gene amplification. These data identify an iron acquisition regulon, provide insight into T7SS, and reveal a mechanism of Mtb chromosome evolution involving “accordion-type” amplification.

Drug Discovery for Mycobacterium tuberculosis Using Structure-Based Computer-Aided Drug Design Approach

Developing new, more effective antibiotics against resistant Mycobacterium tuberculosis that inhibit its essential proteins is an appealing strategy for combating the global tuberculosis (TB) epidemic. Finding a compound that can target a particular cavity in a protein and interrupt its enzymatic activity is the crucial objective of drug design and discovery. Such a compound is then subjected to different tests, including clinical trials, to study its effectiveness against the pathogen in the host. In recent times, new techniques, which involve computational and analytical methods, enhanced the chances of drug development, as opposed to traditional drug design methods, which are laborious and time-consuming. The computational techniques in drug design have been improved with a new generation of software used to develop and optimize active compounds that can be used in future chemotherapeutic development to combat global tuberculosis resistance. This review provides an overview of the evolution of tuberculosis resistance, existing drug management, and the design of new anti-tuberculosis drugs developed based on the contributions of computational techniques. Also, we show an appraisal of available software and databases on computational drug design with an insight into the application of this software and databases in the development of anti-tubercular drugs. The review features a perspective involving machine learning, artificial intelligence, quantum computing, and CRISPR combination with available computational techniques as a prospective pathway to design new anti-tubercular drugs to combat resistant tuberculosis.

CoryneRegNet 7, the reference database and analysis platform for corynebacterial gene regulatory networks

We present the newest version of CoryneRegNet, the reference database for corynebacterial regulatory interactions, available at www.exbio.wzw.tum.de/coryneregnet/. The exponential growth of next-generation sequencing data in recent years has allowed a better understanding of bacterial molecular mechanisms. Transcriptional regulation is one of the most important mechanisms for bacterial adaptation and survival. These mechanisms may be understood via an organism's network of regulatory interactions. Although the Corynebacterium genus is important in medical, veterinary and biotechnological research, little is known concerning the transcriptional regulation of these bacteria. Here, we unravel transcriptional regulatory networks (TRNs) for 224 corynebacterial strains by utilizing genome-scale transfer of TRNs from four model organisms and assigning statistical significance values to all predicted regulations. As a result, the number of corynebacterial strains with TRNs increased twenty times and the back-end and front-end were reimplemented to support new features as well as future database growth. CoryneRegNet 7 is the largest TRN database for the Corynebacterium genus and aids in elucidating transcriptional mechanisms enabling adaptation, survival and infection.

Revisiting the expression signature of pks15/1 unveils regulatory patterns controlling phenolphtiocerol and phenolglycolipid production in pathogenic mycobacteria

One of the most important and exclusive characteristics of mycobacteria is their cell wall. Amongst its constituent components are two related families of glycosylated lipids, diphthioceranates and phthiocerol dimycocerosate (PDIM) and its variant phenolic glycolipids (PGL). PGL have been associated with cell wall impermeability, phagocytosis, defence against nitrosative and oxidative stress and, intriguingly, biofilm formation. In bacteria from the Mycobacterium tuberculosis complex (MTBC), the biosynthetic pathway of the phenolphthiocerol moiety of PGL depends upon the expression of several genes encoding type I polyketide synthases (PKS), namely ppsA-E and pks15/1 which constitute the PDIM + PGL locus, and that are highly conserved in PDIM/PGL-producing strains. Consensus has not been achieved regarding the genetic organization of pks15/1 locus and knowledge is lacking on its transcriptional signature. Here we explore publicly available datasets of transcriptome data (RNA-seq) from more than 100 MTBC experiments in 40 growth conditions to outline the transcriptional structure and signature of pks15/1, using a differential expression approach to infer the regulatory patterns involving these and related genes. We show that pks1 expression is highly correlated with fadD22, Rv2949c, lppX, fadD29 and, also, pks6 and pks12, with the first three putatively integrating into a polycistronic structure. We evidence dynamic transcriptional heterogeneity within the genes involved in phenolphtiocerol and phenolic glycolipid production, most exhibiting up-regulation upon acidic pH and antibiotic exposure and down-regulation under hypoxia, dormancy, and low/high iron concentration. We finally propose a model based on transcriptome data in which σD positively regulates pks1, pks15 and fadD22, while σB and σE factors exert negative regulation at an upper level.

In Silico Strategies in Tuberculosis Drug Discovery

Tuberculosis (TB) remains a serious threat to global public health, responsible for an estimated 1.5 million mortalities in 2018. While there are available therapeutics for this infection, slow-acting drugs, poor patient compliance, drug toxicity, and drug resistance require the discovery of novel TB drugs. Discovering new and more potent antibiotics that target novel TB protein targets is an attractive strategy towards controlling the global TB epidemic. In silico strategies can be applied at multiple stages of the drug discovery paradigm to expedite the identification of novel anti-TB therapeutics. In this paper, we discuss the current TB treatment, emergence of drug resistance, and the effective application of computational tools to the different stages of TB drug discovery when combined with traditional biochemical methods. We will also highlight the strengths and points of improvement in in silico TB drug discovery research, as well as possible future perspectives in this field.

High-Throughput Screen for Cell Wall Synthesis Network Module in Mycobacterium tuberculosis Based on Integrated Bioinformatics Strategy

BACKGROUND

Mycobacterium tuberculosis is one of the deadliest pathogens in humans. Co-infection of M. tuberculosis with HIV and the emergence of multi-drug-resistant tuberculosis (TB) constitute a serious global threat. However, no effective anti-TB drugs are available, with the exception of first-line drugs such as isoniazid. The cell wall of M. tuberculosis, which is primarily responsible for the lack of effective anti-TB drugs and the escape of the bacteria from host immunity, is an important drug target. The core components of the cell wall of M. tuberculosis are peptidoglycan, arabinogalactan, and mycotic acid. However, the functional genome and metabolic regulation pathways for the M. tuberculosis cell wall are still unknown. In this study, we used the biclustering algorithm integrated into cMonkey, sequence alignment, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and other bioinformatics methods to scan the whole genome of M. tuberculosis as well as to identify and statistically analyze the genes related to the synthesis of the M. tuberculosis cell wall.

METHOD

We performed high-throughput genome-wide screening for M. tuberculosis using Biocarta, KEGG, National Cancer Institute Pathway Interaction Database (NCI-PID), HumanCyc, and Reactome. We then used the Database of Origin and Registration (DOOR) established in our laboratory to classify the collection of operons for M. tuberculosis cell wall synthetic genes. We used the cMonkey double clustering algorithm to perform clustering analysis on the gene expression profile of M. tuberculosis for cell wall synthesis. Finally, we visualized the results using Cytoscape.

RESULT AND CONCLUSION

Through bioinformatics and statistical analyses, we identified 893 M. tuberculosis H37Rv cell wall synthesis genes, distributed in 20 pathways, involved in 46 different functions related to cell wall synthesis, and clustered in 386 modules. We identified important pivotal genes and proteins in the cell wall synthesis pathway such as murA, a class of operons containing genes involved in cell wall synthesis such as ID6951, and a class of operons indispensable for the survival of the bacteria. In addition, we found 41 co-regulatory modules for cell wall synthesis and five co-expression networks of molecular complexes involved in peptidoglycan biosynthesis, membrane transporter synthesis, and other cell wall processes.

The conserved actinobacterial transcriptional regulator FtsR controls expression of ftsZ and further target genes and influences growth and cell division in Corynebacterium glutamicum

Background

Key mechanisms of cell division and its regulation are well understood in model bacteria such as Escherichia coli and Bacillus subtilis. In contrast, current knowledge on the regulation of cell division in Actinobacteria is rather limited. FtsZ is one of the key players in this process, but nothing is known about its transcriptional regulation in Corynebacterium glutamicum, a model organism of the Corynebacteriales.

Results

In this study, we used DNA affinity chromatography to search for transcriptional regulators of ftsZ in C. glutamicum and identified the Cg1631 protein as candidate, which was named FtsR. Both deletion and overexpression of ftsR caused growth defects and an altered cell morphology. Plasmid-based expression of native ftsR or of homologs of the pathogenic relatives Corynebacterium diphtheriae and Mycobacterium tuberculosis in the ΔftsR mutant could at least partially reverse the mutant phenotype. Absence of ftsR caused decreased expression of ftsZ, in line with an activator function of FtsR. In vivo crosslinking followed by affinity purification of FtsR and next generation sequencing of the enriched DNA fragments confirmed the ftsZ promoter as in vivo binding site of FtsR and revealed additional potential target genes and a DNA-binding motif. Analysis of strains expressing ftsZ under control of the gluconate-inducible gntK promoter revealed that the phenotype of the ΔftsR mutant is not solely caused by reduced ftsZ expression, but involves further targets.

Conclusions

In this study, we identified and characterized FtsR as the first transcriptional regulator of FtsZ described for C. glutamicum. Both the absence and the overproduction of FtsR had severe effects on growth and cell morphology, underlining the importance of this regulatory protein. FtsR and its DNA-binding site in the promoter region of ftsZ are highly conserved in Actinobacteria, which suggests that this regulatory mechanism is also relevant for the control of cell division in related Actinobacteria.

Electronic supplementary material

The online version of this article (10.1186/s12866-019-1553-0) contains supplementary material, which is available to authorized users.

Mycobacterial phosphatase PstP regulates global serine threonine phosphorylation and cell division

Protein phosphatase PstP is conserved throughout the Actinobacteria in a genetic locus related to cell wall synthesis and cell division. In many Actinobacteria it is the sole annotated serine threonine protein phosphatase to counter the activity of multiple serine threonine protein kinases. We used transcriptional knockdown, electron microscopy and comparative phosphoproteomics to investigate the putative dual functions of PstP as a specific regulator of cell division and as a global regulator of protein phosphorylation. Comparative phosphoproteomics in the early stages of PstP depletion showed hyperphosphorylation of protein kinases and their substrates, confirming PstP as a negative regulator of kinase activity and global serine and threonine phosphorylation. Analysis of the 838 phosphorylation sites that changed significantly, suggested that PstP may regulate diverse phosphoproteins, preferentially at phosphothreonine near acidic residues, near the protein termini, and within membrane associated proteins. Increased phosphorylation of the activation loop of protein kinase B (PknB) and of the essential PknB substrate CwlM offer possible explanations for the requirement for pstP for growth and for cell wall defects when PstP was depleted.

An Aspartate-Specific Solute-Binding Protein Regulates Protein Kinase G Activity To Control Glutamate Metabolism in Mycobacteria

Signaling by serine/threonine phosphorylation controls diverse processes in bacteria, and identification of the stimuli that activate protein kinases is an outstanding question in the field. Recently, we showed that nutrients stimulate phosphorylation of the protein kinase G substrate GarA in Mycobacterium smegmatis and Mycobacterium tuberculosis and that the action of GarA in regulating central metabolism depends upon whether it is phosphorylated. Here we present an investigation into the mechanism by which nutrients activate PknG. Two unknown genes were identified as co-conserved and co-expressed with PknG: their products were a putative lipoprotein, GlnH, and putative transmembrane protein, GlnX. Using a genetic approach, we showed that the membrane protein GlnX is functionally linked to PknG. Furthermore, we determined that the ligand specificity of GlnH matches the amino acids that stimulate GarA phosphorylation. We determined the structure of GlnH in complex with different amino acid ligands (aspartate, glutamate, and asparagine), revealing the structural basis of ligand specificity. We propose that the amino acid concentration in the periplasm is sensed by GlnH and that protein-protein interaction allows transmission of this information across the membrane via GlnX to activate PknG. This sensory system would allow regulation of nutrient utilization in response to changes in nutrient availability. The sensor, signaling, and effector proteins are conserved throughout the Actinobacteria, including the important human pathogen Mycobacterium tuberculosis, industrial amino acid producer Corynebacterium glutamicum, and antibiotic-producing Streptomyces species.IMPORTANCE Tuberculosis (TB) kills 5,000 people every day, and the prevalence of multidrug-resistant TB is increasing in every country. The processes by which the pathogen Mycobacterium tuberculosis senses and responds to changes in its environment are attractive targets for drug development. Bacterial metabolism differs dramatically between growing and dormant cells, and these changes are known to be important in pathogenesis of TB. Here, we used genetic and biochemical approaches to identify proteins that allow M. tuberculosis to detect amino acids in its surroundings so that it can regulate its metabolism. We have also shown how individual amino acids are recognized. The findings have broader significance for other actinobacterial pathogens, such as nontuberculous mycobacteria, as well as Actinobacteria used to produce billions of dollars of amino acids and antibiotics every year.

TIBLE: a web-based, freely accessible resource for small-molecule binding data for mycobacterial species

Database URL

http://www-cryst.bioc.cam.ac.uk/tible/.

PdtaS Deficiency Affects Resistance of Mycobacteria to Ribosome Targeting Antibiotics

Two-component regulatory systems (TCSSs) are key regulatory elements responsible for the adaptation of bacteria to environmental stresses. A classical TCSS is typically comprised of a sensory histidine kinase and a corresponding response regulator. Here, we used homologous recombination to construct a Mycobacterium smegmatis mutant defective in the synthesis of cytosolic histidine kinase PdtaS (Msmeg_1918). The resulting ΔpdtaS mutant strain was tested in the Phenotype Microarray screening system, which allowed us to identify aminoglycoside antibiotic sensitivity, tetracyclines antibiotic resistance as well as membrane transport and respiration, as the main processes affected by removal of pdtaS. The antibiotic sensitivity profiles were confirmed by survival assessment and complementation studies. To gain insight into the molecular mechanisms responsible for the observed phenotype, we compared ribosomal RNA and protein profiles of the mutant and wild-type strains. We carried out Northern blotting and qRT-PCR to compare rRNA levels and analyzed ribosome sedimentation patterns of the wild-type and mutant strains on sucrose gradients. Isolated ribosomes were further used to estimate relative abundance of individual proteins in the ribosomal subunits using label free mass spectrometry analysis. Additionally, the ΔpdtaS mutant revealed lower activity of the respiratory chain as measured by the rate of TTC (triphenyltetrazolium chloride) reduction, while at the same time showing only insignificant changes in the uptake of aminoglycosides. We postulate that deficiency of PdtaS affects the oxidative respiration rates and ribosomal composition causing relevant changes to intrinsic resistance or susceptibility to antibiotics targeting ribosomes, which are commonly used to treat mycobacterial infections.

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.

A genome-wide structure-based survey of nucleotide binding proteins in M. tuberculosis

Nucleoside tri-phosphates (NTP) form an important class of small molecule ligands that participate in, and are essential to a large number of biological processes. Here, we seek to identify the NTP binding proteome (NTPome) in M. tuberculosis (M.tb), a deadly pathogen. Identifying the NTPome is useful not only for gaining functional insights of the individual proteins but also for identifying useful drug targets. From an earlier study, we had structural models of M.tb at a proteome scale from which a set of 13,858 small molecule binding pockets were identified. We use a set of NTP binding sub-structural motifs derived from a previous study and scan the M.tb pocketome, and find that 1,768 proteins or 43% of the proteome can theoretically bind NTP ligands. Using an experimental proteomics approach involving dye-ligand affinity chromatography, we confirm NTP binding to 47 different proteins, of which 4 are hypothetical proteins. Our analysis also provides the precise list of binding site residues in each case, and the probable ligand binding pose. As the list includes a number of known and potential drug targets, the identification of NTP binding can directly facilitate structure-based drug design of these targets.

Decoding the similarities and differences among mycobacterial species

Mycobacteriaceae comprises pathogenic species such as Mycobacterium tuberculosis, M. leprae and M. abscessus, as well as non-pathogenic species, for example, M. smegmatis and M. thermoresistibile. Genome comparison and annotation studies provide insights into genome evolutionary relatedness, identify unique and pathogenicity-related genes in each species, and explore new targets that could be used for developing new diagnostics and therapeutics. Here, we present a comparative analysis of ten-mycobacterial genomes with the objective of identifying similarities and differences between pathogenic and non-pathogenic species. We identified 1080 core orthologous clusters that were enriched in proteins involved in amino acid and purine/pyrimidine biosynthetic pathways, DNA-related processes (replication, transcription, recombination and repair), RNA-methylation and modification, and cell-wall polysaccharide biosynthetic pathways. For their pathogenicity and survival in the host cell, pathogenic species have gained specific sets of genes involved in repair and protection of their genomic DNA. M. leprae is of special interest owing to its smallest genome (1600 genes and ~1300 psuedogenes), yet poor genome annotation. More than 75% of the pseudogenes were found to have a functional ortholog in the other mycobacterial genomes and belong to protein families such as transferases, oxidoreductases and hydrolases.

Members of the Mycobacteriaceae family, which are known to adapt to different environmental niches, comprise bacterial species with varied genome sizes. They are unique in their cell-wall composition, which is remarkably thick and lipid-rich as compared to other bacteria. We performed a comparative analysis at the proteome level for ten mycobacterial species that differ in their pathogenicity, genome size and environmental niches. A total of 1080 orthologous clusters with representation from all ten species were obtained, and these were further examined for their domain annotations, domain architecture similarities and enriched GO terms. These core orthologous clusters are enriched in various biosynthetic pathways. The proteins that are specific to each of the ten species were also investigated for their GO functions. The M. leprae genome has a large number of pseudogenes and we searched for their functional orthologs in other mycobacterial species in order to understand the functions that are lost from the M. leprae genome. The proteins present exclusively in M. leprae genome were studied in more detail, in order to predict putative drug targets and diagnostic markers. These findings, which have implications in understanding evolution of mycobacterial genomes, identify species-specific proteins that have potential for use in developing new diagnostic tools and therapeutics.

Integration of Metabolomics and Transcriptomics Reveals a Complex Diet of Mycobacterium tuberculosis during Early Macrophage Infection

The nutrients consumed by intracellular pathogens are mostly unknown. This is mainly due to the challenge of disentangling host and pathogen metabolism sharing the majority of metabolic pathways and hence metabolites. Here, we investigated the metabolic changes of Mycobacterium tuberculosis, the causative agent of tuberculosis, and its human host cell during early infection. To this aim, we combined gene expression data of both organisms and metabolite changes during the course of infection through integration into a genome-wide metabolic network. This led to the identification of infection-specific metabolic alterations, which we further exploited to model host-pathogen interactions quantitatively by flux balance analysis. These in silico data suggested that tubercle bacilli consume up to 33 different nutrients during early macrophage infection, which the bacteria utilize to generate energy and biomass to establish intracellular growth. Such multisubstrate fueling strategy renders the pathogen’s metabolism robust toward perturbations, such as innate immune responses or antibiotic treatments.

Nutrient acquisition from the host environment is crucial for the survival of intracellular pathogens, but conceptual and technical challenges limit our knowledge of pathogen diets. To overcome some of these technical roadblocks, we exploited an experimentally accessible model for early infection of human macrophages by Mycobacterium tuberculosis, the etiological agent of tuberculosis, to study host-pathogen interactions with a multi-omics approach. We collected metabolomics and complete transcriptome RNA sequencing (dual RNA-seq) data of the infected macrophages, integrated them in a genome-wide reaction pair network, and identified metabolic subnetworks in host cells and M. tuberculosis that are modularly regulated during infection. Up- and downregulation of these metabolic subnetworks suggested that the pathogen utilizes a wide range of host-derived compounds, concomitant with the measured metabolic and transcriptional changes in both bacteria and host. To quantify metabolic interactions between the host and intracellular pathogen, we used a combined genome-scale model of macrophage and M. tuberculosis metabolism constrained by the dual RNA-seq data. Metabolic flux balance analysis predicted coutilization of a total of 33 different carbon sources and enabled us to distinguish between the pathogen’s substrates directly used as biomass precursors and the ones further metabolized to gain energy or to synthesize building blocks. This multiple-substrate fueling confers high robustness to interventions with the pathogen’s metabolism. The presented approach combining multi-omics data as a starting point to simulate system-wide host-pathogen metabolic interactions is a useful tool to better understand the intracellular lifestyle of pathogens and their metabolic robustness and resistance to metabolic interventions.

IMPORTANCE The nutrients consumed by intracellular pathogens are mostly unknown. This is mainly due to the challenge of disentangling host and pathogen metabolism sharing the majority of metabolic pathways and hence metabolites. Here, we investigated the metabolic changes of Mycobacterium tuberculosis, the causative agent of tuberculosis, and its human host cell during early infection. To this aim, we combined gene expression data of both organisms and metabolite changes during the course of infection through integration into a genome-wide metabolic network. This led to the identification of infection-specific metabolic alterations, which we further exploited to model host-pathogen interactions quantitatively by flux balance analysis. These in silico data suggested that tubercle bacilli consume up to 33 different nutrients during early macrophage infection, which the bacteria utilize to generate energy and biomass to establish intracellular growth. Such multisubstrate fueling strategy renders the pathogen’s metabolism robust toward perturbations, such as innate immune responses or antibiotic treatments.

A tuberculosis biomarker database: the key to novel TB diagnostics

New diagnostic innovations for tuberculosis (TB), including point-of-care solutions, are critical to reach the goals of the End TB Strategy. However, despite decades of research, numerous reports on new biomarker candidates, and significant investment, no well-performing, simple and rapid TB diagnostic test is yet available on the market, and the search for accurate, non-DNA biomarkers remains a priority. To help overcome this 'biomarker pipeline problem', FIND and partners are working on the development of a well-curated and user-friendly TB biomarker database. The web-based database will enable the dynamic tracking of evidence surrounding biomarker candidates in relation to target product profiles (TPPs) for needed TB diagnostics. It will be able to accommodate raw datasets and facilitate the verification of promising biomarker candidates and the identification of novel biomarker combinations. As such, the database will simplify data and knowledge sharing, empower collaboration, help in the coordination of efforts and allocation of resources, streamline the verification and validation of biomarker candidates, and ultimately lead to an accelerated translation into clinically useful tools.

Mycobacterium tuberculosis Rv1474c is a TetR-like transcriptional repressor that regulates aconitase, an essential enzyme and RNA-binding protein, in an iron-responsive manner

Mycobacterium tuberculosis (M.tb), tuberculosis (TB) causing bacteria, employs several mechanisms to maintain iron homeostasis which is critical for its survival and pathogenesis. M.tb aconitase (Acn), a [4Fe-4S] cluster-containing essential protein, apart from participating in energy cycle, also binds to predicted iron-responsive RNA elements. In this study, we identified Rv1474c as a regulator of its operonic partner acn and carried out its biochemical and functional characterization. The binding motif for Rv1474c in the upstream region of acn (Rv1475c)-Rv1474c operon was verified by gel-shift assays. Reporter assays in E. coli followed by over-expression studies in mycobacteria, using both wild type and a DNA-binding defective mutant, demonstrated Rv1474c as a Tet-R like repressor of acn. Rv1474c, besides binding tetracycline, could also bind iron which negatively influenced its DNA binding activity. Further, a consistent decrease in the relative transcript levels of acn when M.tb was grown in iron-deficient conditions as compared to either normal or other stress conditions, indicated regulation of acn by Rv1474c in an iron-responsive manner in vivo. The absence of homologs in the human host and its association with indispensable iron homeostasis makes Rv1474c an attractive target for designing novel anti-mycobacterials.

A Comparison of the Sensititre MycoTB Plate, the Bactec MGIT 960, and a Microarray-Based Molecular Assay for the Detection of Drug Resistance in Clinical Mycobacterium tuberculosis Isolates in Moscow, Russia

Background

The goal of this study was to compare the consistency of three assays for the determination of the drug resistance of Mycobacterium tuberculosis (MTB) strains with various resistance profiles isolated from the Moscow region.

Methods

A total of 144 MTB clinical isolates with a strong bias toward drug resistance were examined using Bactec MGIT 960, Sensititre MycoTB, and a microarray-based molecular assay TB-TEST to detect substitutions in the rpoB, katG, inhA, ahpC, gyrA, gyrB, rrs, eis, and embB genes that are associated with resistance to rifampin, isoniazid, fluoroquinolones, second-line injectable drugs and ethambutol.

Results

The average correlation for the identification of resistant and susceptible isolates using the three methods was approximately 94%. An association of mutations detected with variable resistance levels was shown. We propose a change in the breakpoint minimal inhibitory concentration for kanamycin to less than 5 μg/ml in the Sensititre MycoTB system. A pairwise comparison of the minimal inhibitory concentrations (MICs) of two different drugs revealed an increased correlation in the first-line drug group and a partial correlation in the second-line drug group, reflecting the history of the preferential simultaneous use of drugs from these groups. An increased correlation with the MICs was also observed for drugs sharing common resistance mechanisms.

Conclusions

The quantitative measures of phenotypic drug resistance produced by the Sensititre MycoTB and the timely detection of mutations using the TB-TEST assay provide guidance for clinicians for the choice of the appropriate drug regimen.

Bioinformatics tools and databases for whole genome sequence analysis of Mycobacterium tuberculosis

Tuberculosis (TB) is an infectious disease of global public health importance caused by Mycobacterium tuberculosis complex (MTC) in which M. tuberculosis (Mtb) is the major causative agent. Recent advancements in genomic technologies such as next generation sequencing have enabled high throughput cost-effective generation of whole genome sequence information from Mtb clinical isolates, providing new insights into the evolution, genomic diversity and transmission of the Mtb bacteria, including molecular mechanisms of antibiotic resistance. The large volume of sequencing data generated however necessitated effective and efficient management, storage, analysis and visualization of the data and results through development of novel and customized bioinformatics software tools and databases. In this review, we aim to provide a comprehensive survey of the current freely available bioinformatics software tools and publicly accessible databases for genomic analysis of Mtb for identifying disease transmission in molecular epidemiology and in rapid determination of the antibiotic profiles of clinical isolates for prompt and optimal patient treatment.

Comparative Proteomic Analyses of Avirulent, Virulent, and Clinical Strains of Mycobacterium tuberculosis Identify Strain-specific Patterns

Mycobacterium tuberculosis is an adaptable intracellular pathogen, existing in both dormant as well as active disease-causing states. Here, we report systematic proteomic analyses of four strains, H37Ra, H37Rv, and clinical isolates BND and JAL, to determine the differences in protein expression patterns that contribute to their virulence and drug resistance. Resolution of lysates of the four strains by liquid chromatography, coupled to mass spectrometry analysis, identified a total of 2161 protein groups covering ∼54% of the predicted M. tuberculosis proteome. Label-free quantification analysis of the data revealed 257 differentially expressed protein groups. The differentially expressed protein groups could be classified into seven K-means cluster bins, which broadly delineated strain-specific variations. Analysis of the data for possible mechanisms responsible for drug resistance phenotype of JAL suggested that it could be due to a combination of overexpression of proteins implicated in drug resistance and the other factors. Expression pattern analyses of transcription factors and their downstream targets demonstrated substantial differential modulation in JAL, suggesting a complex regulatory mechanism. Results showed distinct variations in the protein expression patterns of Esx and mce1 operon proteins in JAL and BND strains, respectively. Abrogating higher levels of ESAT6, an important Esx protein known to be critical for virulence, in the JAL strain diminished its virulence, although it had marginal impact on the other strains. Taken together, this study reveals that strain-specific variations in protein expression patterns have a meaningful impact on the biology of the pathogen.

Host Immune Responses Differ between M. africanum- and M. tuberculosis-Infected Patients following Standard Anti-tuberculosis Treatment

Epidemiological differences exist between Mycobacterium africanum (Maf)- and Mycobacterium tuberculosis (Mtb)-infected patients, but to date, contributing host factors have not been characterised. We analysed clinical outcomes, as well as soluble markers and gene expression profiles in unstimulated, and ESAT6/CFP-10-, whole-Maf- and Mtb-stimulated blood samples of 26 Maf- and 49 Mtb-HIV-negative tuberculosis patients before, and after 2 and 6 months of anti-tuberculosis therapy. Before treatment, both groups had similar clinical parameters, but differed in few cytokines concentration and gene expression profiles. Following treatment the body mass index, skinfold thickness and chest X-ray scores showed greater improvement in the Mtb- compared to Maf-infected patients, after adjusting for age, sex and ethnicity (p = 0.02; 0.04 and 0.007, respectively). In addition, in unstimulated blood, IL-12p70, IL12A and TLR9 were significantly higher in Maf-infected patients, while IL-15, IL-8 and MIP-1α were higher in Mtb-infected patients. Overnight stimulation with ESAT-6/CFP-10 induced significantly higher levels of IFN-γ and TNF-α production, as well as gene expression of CCL4, IL1B and TLR4 in Mtb- compared to Maf-infected patients. Our study confirms differences in clinical features and immune genes expression and concentration of proteins associated with inflammatory processes between Mtb- and Maf-infected patients following anti-tuberculosis treatment These findings have public health implications for treatment regimens, and biomarkers for tuberculosis diagnosis and susceptibility.

Longitudinal whole genome analysis of pre and post drug treatment Mycobacterium tuberculosis isolates reveals progressive steps to drug resistance

Tuberculosis (TB) is one of the leading causes of death due to an infectious disease in the world. Understanding the mechanisms of drug resistance has become pivotal in the detection and treatment of newly emerging resistant TB cases. We have analyzed three pairs of Mycobacterium tuberculosis strains pre- and post-drug treatment to identify mutations involved in the progression of resistance to the drugs rifampicin and isoniazid. In the rifampicin resistant strain, we confirmed a mutation in rpoB (S450L) that is known to confer resistance to rifampicin. We discovered a novel L101R mutation in the katG gene of an isoniazid resistant strain, which may directly contribute to isoniazid resistance due to the proximity of the mutation to the katG isoniazid-activating site. Another isoniazid resistant strain had a rare mutation in the start codon of katG. We also identified a number of mutations in each longitudinal pair, such as toxin-antitoxin mutations that may influence the progression towards resistance or may play a role in compensatory fitness. These findings improve our knowledge of drug resistance progression during therapy and provide a methodology to monitor longitudinal strains using whole genome sequencing, polymorphism comparison, and functional annotation.

Transcription Factor Binding Site Mapping Using ChIP-Seq

Transcription factors (TFs) play a central role in regulating gene expression in all bacteria. Yet until recently, studies of TF binding were limited to a small number of factors at a few genomic locations. Chromatin immunoprecipitation followed by sequencing (ChIP-Seq) provides the ability to map binding sites globally for TFs, and the scalability of the technology enables the ability to map binding sites for every DNA binding protein in a prokaryotic organism. We have developed a protocol for ChIP-Seq tailored for use with mycobacteria and an analysis pipeline for processing the resulting data. The protocol and pipeline have been used to map over 100 TFs from Mycobacterium tuberculosis, as well as numerous TFs from related mycobacteria and other bacteria. The resulting data provide evidence that the long-accepted spatial relationship between TF binding site, promoter motif, and the corresponding regulated gene may be too simple a paradigm, failing to adequately capture the variety of TF binding sites found in prokaryotes. In this article we describe the protocol and analysis pipeline, the validation of these methods, and the results of applying these methods to M. tuberculosis.

MycoBASE: expanding the functional annotation coverage of mycobacterial genomes

Background

Central to most omic scale experiments is the interpretation and examination of resulting gene lists corresponding to differentially expressed, regulated, or observed gene or protein sets. Complicating interpretation is a lack of functional annotation assigned to a large percentage of many microbial genomes. This is particularly noticeable in mycobacterial genomes, which are significantly divergent from many of the microbial model species used for gene and protein functional characterization, but which are extremely important clinically. Mycobacterial species, ranging from M. tuberculosis to M. abscessus, are responsible for deadly infectious diseases that kill over 1.5 million people each year across the world. A better understanding of the coding capacity of mycobacterial genomes is therefore necessary to shed increasing light on putative mechanisms of virulence, pathogenesis, and functional adaptations.

Description

Here we describe the improved functional annotation coverage of 11 important mycobacterial genomes, many involved in human diseases including tuberculosis, leprosy, and nontuberculous mycobacterial (NTM) infections. Of the 11 mycobacterial genomes, we provide 9899 new functional annotations, compared to NCBI and TBDB annotations, for genes previously characterized as genes of unknown function, hypothetical, and hypothetical conserved proteins. Functional annotations are available at our newly developed web resource MycoBASE (Mycobacterial Annotation Server) at strong.ucdenver.edu/mycobase.

Conclusion

Improved annotations allow for better understanding and interpretation of genomic and transcriptomic experiments, including analyzing the functional implications of insertions, deletions, and mutations, inferring the function of understudied genes, and determining functional changes resulting from differential expression studies. MycoBASE provides a valuable resource for mycobacterial researchers, through improved and searchable functional annotations and functional enrichment strategies. MycoBASE will be continually supported and updated to include new genomes, enabling a powerful resource to aid the quest to better understand these important pathogenic and environmental species.

Towards understanding the biological function of the unusual chaperonin Cpn60.1 (GroEL1) of Mycobacterium tuberculosis

The 60 kDa heat shock proteins, also known as Cpn60s (GroELs) are components of the essential protein folding machinery of the cell, but are also dominant antigens in many infectious diseases. Although generally essential for cellular survival, in some organisms such as Mycobacterium tuberculosis, one or more paralogous Cpn60s are known to be dispensable. In M. tuberculosis, Cpn60.2 (GroEL2) is essential for cell survival, but the biological role of the non-essential Cpn60.1 (GroEL1) is still elusive. To understand the relevance of Cpn60.1 (GroEL1) in M. tuberculosis physiology, detailed transcriptomic analyses for the wild type H37Rv and cpn60.1 knockout (groEL1-KO) were performed under in vitro stress conditions: stationary phase, cold shock, low aeration, mild cold shock and low pH. Additionally, the survival of the groEL1-KO was assessed in macrophages at multiplicity of infection (MOI) of 1:1 and 1:5. We observed that survival under low aeration was significantly compromised in the groEL1-KO. Further, the gene expression analyses under low aeration showed change in expression of several key virulence factors like two component system PhoP/R and MprA/B, sigma factors SigM and C and adversely affected known hypoxia response regulators Rv0081, Rv0023 and DosR. Our work is therefore suggestive of an important role of Cpn60.1 (GroEL1) for survival under low aeration by affecting the expression of genes known for hypoxia response.

Integrated Modeling of Gene Regulatory and Metabolic Networks in Mycobacterium tuberculosis

Mycobacterium tuberculosis (MTB) is the causative bacterium of tuberculosis, a disease responsible for over a million deaths worldwide annually with a growing number of strains resistant to antibiotics. The development of better therapeutics would greatly benefit from improved understanding of the mechanisms associated with MTB responses to different genetic and environmental perturbations. Therefore, we expanded a genome-scale regulatory-metabolic model for MTB using the Probabilistic Regulation of Metabolism (PROM) framework. Our model, MTBPROM2.0, represents a substantial knowledge base update and extension of simulation capability. We incorporated a recent ChIP-seq based binding network of 2555 interactions linking to 104 transcription factors (TFs) (representing a 3.5-fold expansion of TF coverage). We integrated this expanded regulatory network with a refined genome-scale metabolic model that can correctly predict growth viability over 69 source metabolite conditions and predict metabolic gene essentiality more accurately than the original model. We used MTBPROM2.0 to simulate the metabolic consequences of knocking out and overexpressing each of the 104 TFs in the model. MTBPROM2.0 improves performance of knockout growth defect predictions compared to the original PROM MTB model, and it can successfully predict growth defects associated with TF overexpression. Moreover, condition-specific models of MTBPROM2.0 successfully predicted synergistic growth consequences of overexpressing the TF whiB4 in the presence of two standard anti-TB drugs. MTBPROM2.0 can screen in silico condition-specific transcription factor perturbations to generate putative targets of interest that can help prioritize future experiments for therapeutic development efforts.

Comparative Genome and Network Centrality Analysis to Identify Drug Targets of Mycobacterium tuberculosis H37Rv

Potential drug targets of Mycobacterium tuberculosis H37Rv were identified through systematically integrated comparative genome and network centrality analysis. The comparative analysis of the complete genome of Mycobacterium tuberculosis H37Rv against Database of Essential Genes (DEG) yields a list of proteins which are essential for the growth and survival of the pathogen. Those proteins which are nonhomologous with human were selected. The resulting proteins were then prioritized by using the four network centrality measures: degree, closeness, betweenness, and eigenvector. Proteins whose centrality value is close to the centre of gravity of the interactome network were proposed as a final list of potential drug targets for the pathogen. The use of an integrated approach is believed to increase the success of the drug target identification process. For the purpose of validation, selective comparisons have been made among the proposed targets and previously identified drug targets by various other methods. About half of these proteins have been already reported as potential drug targets. We believe that the identified proteins will be an important input to experimental study which in the way could save considerable amount of time and cost of drug target discovery.

RegulonDB version 9.0: high-level integration of gene regulation, coexpression, motif clustering and beyond

RegulonDB (http://regulondb.ccg.unam.mx) is one of the most useful and important resources on bacterial gene regulation,as it integrates the scattered scientific knowledge of the best-characterized organism, Escherichia coli K-12, in a database that organizes large amounts of data. Its electronic format enables researchers to compare their results with the legacy of previous knowledge and supports bioinformatics tools and model building. Here, we summarize our progress with RegulonDB since our last Nucleic Acids Research publication describing RegulonDB, in 2013. In addition to maintaining curation up-to-date, we report a collection of 232 interactions with small RNAs affecting 192 genes, and the complete repertoire of 189 Elementary Genetic Sensory-Response units (GENSOR units), integrating the signal, regulatory interactions, and metabolic pathways they govern. These additions represent major progress to a higher level of understanding of regulated processes. We have updated the computationally predicted transcription factors, which total 304 (184 with experimental evidence and 120 from computational predictions); we updated our position-weight matrices and have included tools for clustering them in evolutionary families. We describe our semiautomatic strategy to accelerate curation, including datasets from high-throughput experiments, a novel coexpression distance to search for ‘neighborhood’ genes to known operons and regulons, and computational developments.

Combining Metabolite-Based Pharmacophores with Bayesian Machine Learning Models for Mycobacterium tuberculosis Drug Discovery

Integrated computational approaches for Mycobacterium tuberculosis (Mtb) are useful to identify new molecules that could lead to future tuberculosis (TB) drugs. Our approach uses information derived from the TBCyc pathway and genome database, the Collaborative Drug Discovery TB database combined with 3D pharmacophores and dual event Bayesian models of whole-cell activity and lack of cytotoxicity. We have prioritized a large number of molecules that may act as mimics of substrates and metabolites in the TB metabolome. We computationally searched over 200,000 commercial molecules using 66 pharmacophores based on substrates and metabolites from Mtb and further filtering with Bayesian models. We ultimately tested 110 compounds in vitro that resulted in two compounds of interest, BAS 04912643 and BAS 00623753 (MIC of 2.5 and 5 μg/mL, respectively). These molecules were used as a starting point for hit-to-lead optimization. The most promising class proved to be the quinoxaline di-N-oxides, evidenced by transcriptional profiling to induce mRNA level perturbations most closely resembling known protonophores. One of these, SRI58 exhibited an MIC = 1.25 μg/mL versus Mtb and a CC₅₀ in Vero cells of >40 μg/mL, while featuring fair Caco-2 A-B permeability (2.3 x 10⁻⁶ cm/s), kinetic solubility (125 μM at pH 7.4 in PBS) and mouse metabolic stability (63.6% remaining after 1 h incubation with mouse liver microsomes). Despite demonstration of how a combined bioinformatics/cheminformatics approach afforded a small molecule with promising in vitro profiles, we found that SRI58 did not exhibit quantifiable blood levels in mice.

Structure of Ribosomal Silencing Factor Bound to Mycobacterium tuberculosis Ribosome

The ribosomal silencing factor RsfS slows cell growth by inhibiting protein synthesis during periods of diminished nutrient availability. The crystal structure of Mycobacterium tuberculosis (Mtb) RsfS, together with the cryo-electron microscopy (EM) structure of the large subunit 50S of Mtb ribosome, reveals how inhibition of protein synthesis by RsfS occurs. RsfS binds to the 50S at L14, which, when occupied, blocks the association of the small subunit 30S. Although Mtb RsfS is a dimer in solution, only a single subunit binds to 50S. The overlap between the dimer interface and the L14 binding interface confirms that the RsfS dimer must first dissociate to a monomer in order to bind to L14. RsfS interacts primarily through electrostatic and hydrogen bonding to L14. The EM structure shows extended rRNA density that it is not found in the Escherichia coli ribosome, the most striking of these being the extended RNA helix of H54a.

Sequence-Structure-Function Classification of a Catalytically Diverse Oxidoreductase Superfamily in Mycobacteria

The deazaflavin cofactor F420 enhances the persistence of mycobacteria during hypoxia, oxidative stress, and antibiotic treatment. However, the identities and functions of the mycobacterial enzymes that utilize F420 under these conditions have yet to be resolved. In this work, we used sequence similarity networks to analyze the distribution of the largest F420-dependent protein family in mycobacteria. We show that these enzymes are part of a larger split β-barrel enzyme superfamily (flavin/deazaflavin oxidoreductases, FDORs) that include previously characterized pyridoxamine/pyridoxine-5'-phosphate oxidases and heme oxygenases. We show that these proteins variously utilize F420, flavin mononucleotide, flavin adenine dinucleotide, and heme cofactors. Functional annotation using phylogenetic, structural, and spectroscopic methods revealed their involvement in heme degradation, biliverdin reduction, fatty acid modification, and quinone reduction. Four novel crystal structures show that plasticity in substrate binding pockets and modifications to cofactor binding motifs enabled FDORs to carry out a variety of functions. This systematic classification and analysis provides a framework for further functional analysis of the roles of FDORs in mycobacterial pathogenesis and persistence.

Crystal structure of the Mycobacterium tuberculosis transcriptional regulator Rv0302

Mycobacterium tuberculosis is a pathogenic bacterial species, which is neither Gram positive nor Gram negative. It has a unique cell wall, making it difficult to kill and conferring resistance to antibiotics that disrupt cell wall biosynthesis. Thus, the mycobacterial cell wall is critical to the virulence of these pathogens. Recent work shows that the mycobacterial membrane protein large (MmpL) family of transporters contributes to cell wall biosynthesis by exporting fatty acids and lipidic elements of the cell wall. The expression of the Mycobacterium tuberculosis MmpL proteins is controlled by a complicated regulatory network system. Here we report crystallographic structures of two forms of the TetR-family transcriptional regulator Rv0302, which participates in regulating the expression of MmpL proteins. The structures reveal a dimeric, two-domain molecule with architecture consistent with the TetR family of regulators. Comparison of the two Rv0302 crystal structures suggests that the conformational changes leading to derepression may be due to a rigid body rotational motion within the dimer interface of the regulator. Using fluorescence polarization and electrophoretic mobility shift assays, we demonstrate the recognition of promoter and intragenic regions of multiple mmpL genes by this protein. In addition, our isothermal titration calorimetry and electrophoretic mobility shift experiments indicate that fatty acids may be the natural ligand of this regulator. Taken together, these experiments provide new perspectives on the regulation of the MmpL family of transporters.

Structural Basis for the Regulation of the MmpL Transporters of Mycobacterium tuberculosis

The mycobacterial cell wall is critical to the virulence of these pathogens. Recent work shows that the MmpL (mycobacterial membrane protein large) family of transporters contributes to cell wall biosynthesis by exporting fatty acids and lipidic elements of the cell wall. The expression of the Mycobacterium tuberculosis MmpL proteins is controlled by a complex regulatory network, including the TetR family transcriptional regulators Rv3249c and Rv1816. Here we report the crystal structures of these two regulators, revealing dimeric, two-domain molecules with architecture consistent with the TetR family of regulators. Buried extensively within the C-terminal regulatory domains of Rv3249c and Rv1816, we found fortuitous bound ligands, which were identified as palmitic acid (a fatty acid) and isopropyl laurate (a fatty acid ester), respectively. Our results suggest that fatty acids may be the natural ligands of these regulatory proteins. Using fluorescence polarization and electrophoretic mobility shift assays, we demonstrate the recognition of promoter and intragenic regions of multiple mmpL genes by these proteins. Binding of palmitic acid renders these regulators incapable of interacting with their respective operator DNAs, which will result in derepression of the corresponding mmpL genes. Taken together, these experiments provide new perspectives on the regulation of the MmpL family of transporters.

InbR, a TetR family regulator, binds with isoniazid and influences multidrug resistance in Mycobacterium bovis BCG

Isoniazid (INH), an anti-tuberculosis (TB) drug, has been widely used for nearly 60 years. However, the pathway through which Mycobacterium tuberculosis responds INH remain largely unclear. In this study, we characterized a novel transcriptional factor, InbR, which is encoded by Rv0275c and belongs to the TetR family, that is directly responsive to INH. Disrupting inbR made mycobacteria more sensitive to INH, whereas overexpressing inbR decreased bacterial susceptibility to the drug. InbR could bind specifically to the upstream region of its own operon at two inverted repeats and act as an auto-repressor. Furthermore, InbR directly bind with INH, and the binding reduced InbR’s DNA-binding ability. Interestingly, susceptibilities were also changed by InbR for other anti-TB drugs, such as rifampin, implying that InbR may play a role in multi-drug resistance. Additionally, microarray analyses revealed a portion genes of the inbR regulon have similar expression patterns in inbR-overexpressing strain and INH-treated wild type strain, suggesting that these genes, for example iniBAC, may be responsible to the drug resistance of inbR-overexpressing strain. The regulation of these genes by InbR were further assessed by ChIP-seq assay. InbR may regulate multiple drug resistance of mycobacteria through the regulation of these genes.

The Eukaryotic Pathogen Databases: a functional genomic resource integrating data from human and veterinary parasites

Over the past 20 years, advances in high-throughput biological techniques and the availability of computational resources including fast Internet access have resulted in an explosion of large genome-scale data sets "big data." While such data are readily available for download and personal use and analysis from a variety of repositories, often such analysis requires access to seldom-available computational skills. As a result a number of databases have emerged to provide scientists with online tools enabling the interrogation of data without the need for sophisticated computational skills beyond basic knowledge of Internet browser utility. This chapter focuses on the Eukaryotic Pathogen Databases (EuPathDB: http://eupathdb.org) Bioinformatic Resource Center (BRC) and illustrates some of the available tools and methods.

Surface hydrolysis of sphingomyelin by the outer membrane protein Rv0888 supports replication of Mycobacterium tuberculosis in macrophages

Sphingomyelinases secreted by pathogenic bacteria play important roles in host-pathogen interactions ranging from interfering with phagocytosis and oxidative burst to iron acquisition. This study shows that the Mtb protein Rv0888 possesses potent sphingomyelinase activity cleaving sphingomyelin, a major lipid in eukaryotic cells, into ceramide and phosphocholine, which are then utilized by Mtb as carbon, nitrogen and phosphorus sources, respectively. An Mtb rv0888 deletion mutant did not grow on sphingomyelin as a sole carbon source anymore and replicated poorly in macrophages indicating that Mtb utilizes sphingomyelin during infection. Rv0888 is an unusual membrane protein with a surface-exposed C-terminal sphingomyelinase domain and a putative N-terminal channel domain that mediated glucose and phosphocholine uptake across the outer membrane in an M. smegmatis porin mutant. Hence, we propose to name Rv0888 as SpmT (sphingomyelinase of Mycobacterium tuberculosis). Erythrocyte membranes contain up to 27% sphingomyelin. The finding that Rv0888 accounts for half of Mtb's hemolytic activity is consistent with its sphingomyelinase activity and the observation that Rv0888 levels are increased in the presence of erythrocytes and sphingomyelin by 5- and 100-fold, respectively. Thus, Rv0888 is a novel outer membrane protein that enables Mtb to utilize sphingomyelin as a source of several essential nutrients during intracellular growth.

SInCRe-structural interactome computational resource for Mycobacterium tuberculosis

We have developed an integrated database for Mycobacterium tuberculosis H37Rv (Mtb) that collates information on protein sequences, domain assignments, functional annotation and 3D structural information along with protein–protein and protein–small molecule interactions. SInCRe (Structural Interactome Computational Resource) is developed out of CamBan (Cambridge and Bangalore) collaboration. The motivation for development of this database is to provide an integrated platform to allow easily access and interpretation of data and results obtained by all the groups in CamBan in the field of Mtb informatics. In-house algorithms and databases developed independently by various academic groups in CamBan are used to generate Mtb-specific datasets and are integrated in this database to provide a structural dimension to studies on tuberculosis. The SInCRe database readily provides information on identification of functional domains, genome-scale modelling of structures of Mtb proteins and characterization of the small-molecule binding sites within Mtb. The resource also provides structure-based function annotation, information on small-molecule binders including FDA (Food and Drug Administration)-approved drugs, protein–protein interactions (PPIs) and natural compounds that bind to pathogen proteins potentially and result in weakening or elimination of host–pathogen protein–protein interactions. Together they provide prerequisites for identification of off-target binding.

Database URL:http://proline.biochem.iisc.ernet.in/sincre

Global analyses of TetR family transcriptional regulators in mycobacteria indicates conservation across species and diversity in regulated functions

BACKGROUND

Mycobacteria inhabit diverse niches and display high metabolic versatility. They can colonise both humans and animals and are also able to survive in the environment. In order to succeed, response to environmental cues via transcriptional regulation is required. In this study we focused on the TetR family of transcriptional regulators (TFTRs) in mycobacteria.

RESULTS

We used InterPro to classify the entire complement of transcriptional regulators in 10 mycobacterial species and these analyses showed that TFTRs are the most abundant family of regulators in all species. We identified those TFTRs that are conserved across all species analysed and those that are unique to the pathogens included in the analysis. We examined genomic contexts of 663 of the conserved TFTRs and observed that the majority of TFTRs are separated by 200 bp or less from divergently oriented genes. Analyses of divergent genes indicated that the TFTRs control diverse biochemical functions not limited to efflux pumps. TFTRs typically bind to palindromic motifs and we identified 11 highly significant novel motifs in the upstream regions of divergently oriented TFTRs. The C-terminal ligand binding domain from the TFTR complement in M. tuberculosis showed great diversity in amino acid sequence but with an overall architecture common to other TFTRs.

CONCLUSION

This study suggests that mycobacteria depend on TFTRs for the transcriptional control of a number of metabolic functions yet the physiological role of the majority of these regulators remain unknown.

CMRegNet-An interspecies reference database for corynebacterial and mycobacterial regulatory networks

Background

Organisms utilize a multitude of mechanisms for responding to changing environmental conditions, maintaining their functional homeostasis and to overcome stress situations. One of the most important mechanisms is transcriptional gene regulation. In-depth study of the transcriptional gene regulatory network can lead to various practical applications, creating a greater understanding of how organisms control their cellular behavior.

Description

In this work, we present a new database, CMRegNet for the gene regulatory networks of Corynebacterium glutamicum ATCC 13032 and Mycobacterium tuberculosis H37Rv. We furthermore transferred the known networks of these model organisms to 18 other non-model but phylogenetically close species (target organisms) of the CMNR group. In comparison to other network transfers, for the first time we utilized two model organisms resulting into a more diverse and complete network of the target organisms.

Conclusion

CMRegNet provides easy access to a total of 3,103 known regulations in C. glutamicum ATCC 13032 and M. tuberculosis H37Rv and to 38,940 evolutionary conserved interactions for 18 non-model species of the CMNR group. This makes CMRegNet to date the most comprehensive database of regulatory interactions of CMNR bacteria. The content of CMRegNet is publicly available online via a web interface found at http://lgcm.icb.ufmg.br/cmregnet.

Maximum flow approach to prioritize potential drug targets of Mycobacterium tuberculosis H37Rv from protein-protein interaction network

Background

In spite of the implementations of several strategies, tuberculosis (TB) is overwhelmingly a serious global public health problem causing millions of infections and deaths every year. This is mainly due to the emergence of drug-resistance varieties of TB. The current treatment strategies for the drug-resistance TB are of longer duration, more expensive and have side effects. This highlights the importance of identification and prioritization of targets for new drugs. This study has been carried out to prioritize potential drug targets of Mycobacteriumtuberculosis H37Rv based on their flow to resistance genes.

Methods

The weighted proteome interaction network of the pathogen was constructed using a dataset from STRING database. Only a subset of the dataset with interactions that have a combined score value ≥770 was considered. Maximum flow approach has been used to prioritize potential drug targets. The potential drug targets were obtained through comparative genome and network centrality analysis. The curated set of resistance genes was retrieved from literatures. Detail literature review and additional assessment of the method were also carried out for validation.

Results

A list of 537 proteins which are essential to the pathogen and non-homologous with human was obtained from the comparative genome analysis. Through network centrality measures, 131 of them were found within the close neighborhood of the centre of gravity of the proteome network. These proteins were further prioritized based on their maximum flow value to resistance genes and they are proposed as reliable drug targets of the pathogen. Proteins which interact with the host were also identified in order to understand the infection mechanism.

Conclusion

Potential drug targets of Mycobacteriumtuberculosis H37Rv were successfully prioritized based on their flow to resistance genes of existing drugs which is believed to increase the druggability of the targets since inhibition of a protein that has a maximum flow to resistance genes is more likely to disrupt the communication to these genes. Purposely selected literature review of the top 14 proteins showed that many of them in this list were proposed as drug targets of the pathogen.

Electronic supplementary material

The online version of this article (doi:10.1186/s40169-015-0061-6) contains supplementary material, which is available to authorized users.

Differential expression of two members of Rv1922-LipD operon in Mycobacterium tuberculosis: Does rv1923 qualify for membership?

rv1922 and rv1923 (lipD) are members of Rv1922-LipD operon in the genome of Mycobacterium tuberculosis. rv1922 was expressed under aerobic and stress conditions, whereas rv1923 was not expressed in aerobically grown bacteria but expressed moderately under oxidative stress conditions. Different expression of both the operonic genes under normal and stress conditions posed apprehensions for the inclusion of rv1922 and rv1923 in the same operon. The results from this study indicated that although the genes were expressed in an operonic manner, there existed the possibility of differential regulation for rv1923 which has been supported by in silico analysis for the presence of putative internal regulatory sites in the operon.