Nanoluciferase Reporter Mycobacteriophage for Sensitive and Rapid Detection of Mycobacterium tuberculosis Drug Susceptibility.

Phenotypic testing for drug susceptibility of Mycobacterium tuberculosis is critical to basic research and managing the evolving problem of antimicrobial resistance in tuberculosis management, but it remains a specialized technique to which access is severely limited. Here, we report on the development and validation of an improved phage-mediated detection system for M. tuberculosis We incorporated a nanoluciferase (Nluc) reporter gene cassette into the TM4 mycobacteriophage genome to create phage TM4-nluc. We assessed the performance of this reporter phage in the context of cellular limit of detection and drug susceptibility testing using multiple biosafety level 2 drug-sensitive and -resistant auxotrophs as well as virulent M. tuberculosis strains. For both limit of detection and drug susceptibility testing, we developed a standardized method consisting of a 96-hour cell preculture followed by a 72-hour experimental window for M. tuberculosis detection with or without antibiotic exposure. The cellular limit of detection of M. tuberculosis in a 96-well plate batch culture was ≤102 CFU. Consistent with other phenotypic methods for drug susceptibility testing, we found TM4-nluc to be compatible with antibiotics representing multiple classes and mechanisms of action, including inhibition of core central dogma functions, cell wall homeostasis, metabolic inhibitors, compounds currently in clinical trials (SQ109 and Q203), and susceptibility testing for bedaquiline, pretomanid, and linezolid (components of the BPaL regimen for the treatment of multi- and extensively drug-resistant tuberculosis). Using the same method, we accurately identified rifampin-resistant and multidrug-resistant M. tuberculosis strains.IMPORTANCEMycobacterium tuberculosis, the causative agent of tuberculosis disease, remains a public health crisis on a global scale, and development of new interventions and identification of drug resistance are pillars in the World Health Organization End TB Strategy. Leveraging the tractability of the TM4 mycobacteriophage and the sensitivity of the nanoluciferase reporter enzyme, the present work describes an evolution of phage-mediated detection and drug susceptibility testing of M. tuberculosis, adding a valuable tool in drug discovery and basic biology research. With additional validation, this system may play a role as a quantitative phenotypic reference method and complement to genotypic methods for diagnosis and antibiotic susceptibility testing.

The Mycobacterium tuberculosis regulatory network and hypoxia.

We have taken the first steps towards a complete reconstruction of the Mycobacterium tuberculosis regulatory network based on ChIP-Seq and combined this reconstruction with system-wide profiling of messenger RNAs, proteins, metabolites and lipids during hypoxia and re-aeration. Adaptations to hypoxia are thought to have a prominent role in M. tuberculosis pathogenesis. Using ChIP-Seq combined with expression data from the induction of the same factors, we have reconstructed a draft regulatory network based on 50 transcription factors. This network model revealed a direct interconnection between the hypoxic response, lipid catabolism, lipid anabolism and the production of cell wall lipids. As a validation of this model, in response to oxygen availability we observe substantial alterations in lipid content and changes in gene expression and metabolites in corresponding metabolic pathways. The regulatory network reveals transcription factors underlying these changes, allows us to computationally predict expression changes, and indicates that Rv0081 is a regulatory hub.

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.

A high-resolution network model for global gene regulation in Mycobacterium tuberculosis.

The resilience of Mycobacterium tuberculosis (MTB) is largely due to its ability to effectively counteract and even take advantage of the hostile environments of a host. In order to accelerate the discovery and characterization of these adaptive mechanisms, we have mined a compendium of 2325 publicly available transcriptome profiles of MTB to decipher a predictive, systems-scale gene regulatory network model. The resulting modular organization of 98% of all MTB genes within this regulatory network was rigorously tested using two independently generated datasets: a genome-wide map of 7248 DNA-binding locations for 143 transcription factors (TFs) and global transcriptional consequences of overexpressing 206 TFs. This analysis has discovered specific TFs that mediate conditional co-regulation of genes within 240 modules across 14 distinct environmental contexts. In addition to recapitulating previously characterized regulons, we discovered 454 novel mechanisms for gene regulation during stress, cholesterol utilization and dormancy. Significantly, 183 of these mechanisms act uniquely under conditions experienced during the infection cycle to regulate diverse functions including 23 genes that are essential to host-pathogen interactions. These and other insights underscore the power of a rational, model-driven approach to unearth novel MTB biology that operates under some but not all phases of infection.

Global analysis of mRNA stability in Mycobacterium tuberculosis.

Mycobacterium tuberculosis (MTB) is a highly successful pathogen that infects over a billion people. As with most organisms, MTB adapts to stress by modifying its transcriptional profile. Remodeling of the transcriptome requires both altering the transcription rate and clearing away the existing mRNA through degradation, a process that can be directly regulated in response to stress. To understand better how MTB adapts to the harsh environs of the human host, we performed a global survey of the decay rates of MTB mRNA transcripts. Decay rates were measured for 2139 of the ~4000 MTB genes, which displayed an average half-life of 9.5 min. This is nearly twice the average mRNA half-life of other prokaryotic organisms where these measurements have been made. The transcriptome was further stabilized in response to lowered temperature and hypoxic stress. The generally stable transcriptome described here, and the additional stabilization in response to physiologically relevant stresses, has far-ranging implications for how this pathogen is able to adapt in its human host.

Characterization of oral swab samples for diagnosis of pulmonary tuberculosis.

Oral swab analysis (OSA) has been shown to detect Mycobacterium tuberculosis (MTB) DNA in patients with pulmonary tuberculosis (TB). In previous analyses, qPCR testing of swab samples collected from tongue dorsa was up to 93% sensitive relative to sputum GeneXpert, when 2 swabs per patient were tested. The present study modified sample collection methods to increase sample biomass and characterized the viability of bacilli present in tongue swabs. A qPCR targeting conserved bacterial ribosomal rRNA gene (rDNA) sequences was used to quantify bacterial biomass in samples. There was no detectable reduction in total bacterial rDNA signal over the course of 10 rapidly repeated tongue samplings, indicating that swabs collect only a small portion of the biomass available for testing. Copan FLOQSwabs collected ~2-fold more biomass than Puritan PurFlock swabs, the best brand used previously (p = 0.006). FLOQSwabs were therefore evaluated in patients with possible TB in Uganda. A FLOQSwab was collected from each patient upon enrollment (Day 1) and, in a subset of sputum GeneXpert Ultra-positive patients, a second swab was collected on the following day (Day 2). Swabs were tested for MTB DNA by manual IS6110-targeted qPCR. Relative to sputum GeneXpert Ultra, single-swab sensitivity was 88% (44/50) on Day 1 and 94.4% (17/18) on Day 2. Specificity was 79.2% (42/53). Among an expanded sample of Ugandan patients, 62% (87/141) had colony-forming bacilli in their tongue dorsum swab samples. These findings will help guide further development of this promising TB screening method.

Hypoxia: a window into Mycobacterium tuberculosis latency.

Tuberculosis is a massive public health problem on a global scale and the success of Mycobacterium tuberculosis is linked to its ability to persist within humans for long periods without causing any overt disease symptoms. Hypoxia is predicted to be a key host-induced stress limiting growth of the pathogen in vivo. However, multiple studies in vitro and in vivo indicate that M. tuberculosis adapts to oxygen limitation by entering into a metabolically altered state, while awaiting the opportunity to reactivate. Molecular signatures of bacteria adapted to hypoxia in vitro are accumulating, although correlations to human disease are only now being established. Similarly, defining the mechanisms that control this adaptation is an active area of research. In this review we discuss the historical precedents linking hypoxia and latency, and the gathering knowledge of M. tuberculosis hypoxic responses. We also examine the role of these responses in tuberculosis latency, and identify promising avenues for future studies.

Ultrasensitive detection of lipoarabinomannan with plasmonic grating biosensors in clinical samples of HIV negative patients with tuberculosis.

BACKGROUND: Timely diagnosis of tuberculosis disease is critical for positive patient outcomes, yet potentially millions go undiagnosed or unreported each year. Sputum is widely used as the testing input, but limited by its complexity, heterogeneity, and sourcing problems. Finding methods to interrogate noninvasive, non-sputum clinical specimens is indispensable to improving access to tuberculosis diagnosis and care. In this work, economical plasmonic gratings were used to analyze tuberculosis biomarker lipoarabinomannan (LAM) from clinical urine samples by single molecule fluorescence assay (FLISA) and compared with gold standard sputum GeneXpert MTB/ RIF, culture, and reference ELISA testing results. METHODS AND FINDINGS: In this study, twenty sputum and urine sample sets were selected retrospectively from a repository of HIV-negative patient samples collected before initiation of anti-tuberculosis therapy. GeneXpert MTB/RIF and culture testing of patient sputum confirmed the presence or absence of pulmonary tuberculosis while all patient urines were reference ELISA LAM-negative. Plasmonic gratings produced by low-cost soft lithography were bound with anti-LAM capture antibody, incubated with patient urine samples, and biotinylated detection antibody. Fluorescently labeled streptavidin revealed single molecule emission by epifluorescence microscope. Using a 1 fg/mL baseline for limit of detection, single molecule FLISA demonstrated good qualitative agreement with gold standard tests on 19 of 20 patients, including accurately predicting the gold-standard-negative patients, while one gold-standard-positive patient produced no observable LAM in urine. CONCLUSIONS: Single molecule FLISA by plasmonic grating demonstrated the ability to quantify tuberculosis LAM from complex urine samples of patients from a high endemic setting with negligible interference from the complex media itself. Moreover, agreement with patient diagnoses by gold standard testing suggests that single molecule FLISA could be used as a highly sensitive test to diagnose tuberculosis noninvasively.

A comprehensive map of genome-wide gene regulation in Mycobacterium tuberculosis.

Mycobacterium tuberculosis (MTB) is a pathogenic bacterium responsible for 12 million active cases of tuberculosis (TB) worldwide. The complexity and critical regulatory components of MTB pathogenicity are still poorly understood despite extensive research efforts. In this study, we constructed the first systems-scale map of transcription factor (TF) binding sites and their regulatory target proteins in MTB. We constructed FLAG-tagged overexpression constructs for 206 TFs in MTB, used ChIP-seq to identify genome-wide binding events and surveyed global transcriptomic changes for each overexpressed TF. Here we present data for the most comprehensive map of MTB gene regulation to date. We also define elaborate quality control measures, extensive filtering steps, and the gene-level overlap between ChIP-seq and microarray datasets. Further, we describe the use of TF overexpression datasets to validate a global gene regulatory network model of MTB and describe an online source to explore the datasets.

The DNA-binding network of Mycobacterium tuberculosis.

Mycobacterium tuberculosis (MTB) infects 30% of all humans and kills someone every 20-30 s. Here we report genome-wide binding for ~80% of all predicted MTB transcription factors (TFs), and assayed global expression following induction of each TF. The MTB DNA-binding network consists of ~16,000 binding events from 154 TFs. We identify >50 TF-DNA consensus motifs and >1,150 promoter-binding events directly associated with proximal gene regulation. An additional ~4,200 binding events are in promoter windows and represent strong candidates for direct transcriptional regulation under appropriate environmental conditions. However, we also identify >10,000 'dormant' DNA-binding events that cannot be linked directly with proximal transcriptional control, suggesting that widespread DNA binding may be a common feature that should be considered when developing global models of coordinated gene expression.

Mapping and manipulating the Mycobacterium tuberculosis transcriptome using a transcription factor overexpression-derived regulatory network.

BACKGROUND: Mycobacterium tuberculosis senses and responds to the shifting and hostile landscape of the host. To characterize the underlying intertwined gene regulatory network governed by approximately 200 transcription factors of M. tuberculosis, we have assayed the global transcriptional consequences of overexpressing each transcription factor from an inducible promoter. RESULTS: We cloned and overexpressed 206 transcription factors in M. tuberculosis to identify the regulatory signature of each. We identified 9,335 regulatory consequences of overexpressing each of 183 transcription factors, providing evidence of regulation for 70% of the M. tuberculosis genome. These transcriptional signatures agree well with previously described M. tuberculosis regulons. The number of genes differentially regulated by transcription factor overexpression varied from hundreds of genes to none, with the majority of expression changes repressing basal transcription. Exploring the global transcriptional maps of transcription factor overexpressing (TFOE) strains, we predicted and validated the phenotype of a regulator that reduces susceptibility to a first line anti-tubercular drug, isoniazid. We also combined the TFOE data with an existing model of M. tuberculosis metabolism to predict the growth rates of individual TFOE strains with high fidelity. CONCLUSION: This work has led to a systems-level framework describing the transcriptome of a devastating bacterial pathogen, characterized the transcriptional influence of nearly all individual transcription factors in M. tuberculosis, and demonstrated the utility of this resource. These results will stimulate additional systems-level and hypothesis-driven efforts to understand M. tuberculosis adaptations that promote disease.

Mycobacterium tuberculosis growth following aerobic expression of the DosR regulon.

The Mycobacterium tuberculosis regulator DosR is induced by multiple stimuli including hypoxia, nitric oxide and redox stress. Overlap of these stimuli with conditions thought to promote latency in infected patients fuels a model in which DosR regulon expression is correlated with bacteriostasis in vitro and a proxy for latency in vivo. Here, we find that inducing the DosR regulon to wildtype levels in aerobic, replicating M. tuberculosis does not alter bacterial growth kinetics. We conclude that DosR regulon expression alone is insufficient for bacterial latency, but rather is expressed during a range of growth states in a dynamic environment.

The Helicobacter pylori urease B subunit binds to CD74 on gastric epithelial cells and induces NF-kappaB activation and interleukin-8 production.

The pathogenesis associated with Helicobacter pylori infection is the result of both bacterial factors and the host response. We have previously shown that H. pylori binds to CD74 on gastric epithelial cells. In this study, we sought to identify the bacterial protein responsible for this interaction. H. pylori urease from a pool of bacterial surface proteins was found to coprecipitate with CD74. To determine how urease binds to CD74, we used recombinant urease A and B subunits. Recombinant urease B was found to bind directly to CD74 in immunoprecipitation and flow cytometry studies. By utilizing both recombinant urease subunits and urease B knockout bacteria, the urease B-CD74 interaction was shown to induce NF-kappaB activation and interleukin-8 (IL-8) production. This response was decreased by blocking CD74 with monoclonal antibodies. Further confirmation of the interaction of urease B with CD74 was obtained using a fibroblast cell line transfected with CD74 that also responded with NF-kappaB activation and IL-8 production. The binding of the H. pylori urease B subunit to CD74 expressed on gastric epithelial cells presents a novel insight into a previously unrecognized H. pylori interaction that may contribute to the proinflammatory immune response seen during infection.