Comparison of the transcriptome, lipidome, and c-di-GMP production between BCGΔBCG1419c and BCG, with Mincle- and Myd88-dependent induction of proinflammatory cytokines in murine macrophages.

We have previously reported the transcriptomic and lipidomic profile of the first-generation, hygromycin-resistant (HygR) version of the BCGΔBCG1419c vaccine candidate, under biofilm conditions. We recently constructed and characterized the efficacy, safety, whole genome sequence, and proteomic profile of a second-generation version of BCGΔBCG1419c, a strain lacking the BCG1419c gene and devoid of antibiotic markers. Here, we compared the antibiotic-less BCGΔBCG1419c with BCG. We assessed their colonial and ultrastructural morphology, biofilm, c-di-GMP production in vitro, as well as their transcriptomic and lipidomic profiles, including their capacity to activate macrophages via Mincle and Myd88. Our results show that BCGΔBCG1419c colonial and ultrastructural morphology, c-di-GMP, and biofilm production differed from parental BCG, whereas we found no significant changes in its lipidomic profile either in biofilm or planktonic growth conditions. Transcriptomic profiling suggests changes in BCGΔBCG1419c cell wall and showed reduced transcription of some members of the DosR, MtrA, and ArgR regulons. Finally, induction of TNF-α, IL-6 or G-CSF by bone-marrow derived macrophages infected with either BCGΔBCG1419c or BCG required Mincle and Myd88. Our results confirm that some differences already found to occur in HygR BCGΔBCG1419c compared with BCG are maintained in the antibiotic-less version of this vaccine candidate except changes in production of PDIM. Comparison with previous characterizations conducted by OMICs show that some differences observed in BCGΔBCG1419c compared with BCG are maintained whereas others are dependent on the growth condition employed to culture them.

MtrA modulates Mycobacterium tuberculosis cell division in host microenvironments to mediate intrinsic resistance and drug tolerance.

The success of Mycobacterium tuberculosis (Mtb) is largely attributed to its ability to physiologically adapt and withstand diverse localized stresses within host microenvironments. Here, we present a data-driven model (EGRIN 2.0) that captures the dynamic interplay of environmental cues and genome-encoded regulatory programs in Mtb. Analysis of EGRIN 2.0 shows how modulation of the MtrAB two-component signaling system tunes Mtb growth in response to related host microenvironmental cues. Disruption of MtrAB by tunable CRISPR interference confirms that the signaling system regulates multiple peptidoglycan hydrolases, among other targets, that are important for cell division. Further, MtrA decreases the effectiveness of antibiotics by mechanisms of both intrinsic resistance and drug tolerance. Together, the model-enabled dissection of complex MtrA regulation highlights its importance as a drug target and illustrates how EGRIN 2.0 facilitates discovery and mechanistic characterization of Mtb adaptation to specific host microenvironments within the host.

Mathematical models to study the biology of pathogens and the infectious diseases they cause.

Mathematical models have many applications in infectious diseases: epidemiologists use them to forecast outbreaks and design containment strategies; systems biologists use them to study complex processes sustaining pathogens, from the metabolic networks empowering microbial cells to ecological networks in the microbiome that protects its host. Here, we (1) review important models relevant to infectious diseases, (2) draw parallels among models ranging widely in scale. We end by discussing a minimal set of information for a model to promote its use by others and to enable predictions that help us better fight pathogens and the diseases they cause.

MadR mediates acyl CoA-dependent regulation of mycolic acid desaturation in mycobacteria.

Mycobacterium tuberculosis has a lipid-rich cell envelope that is remodeled throughout infection to enable adaptation within the host. Few transcriptional regulators have been characterized that coordinate synthesis of mycolic acids, the major cell wall lipids of mycobacteria. Here, we show that the mycolic acid desaturase regulator (MadR), a transcriptional repressor of the mycolate desaturase genes desA1 and desA2, controls mycolic acid desaturation and biosynthesis in response to cell envelope stress. A madR-null mutant of M. smegmatis exhibited traits of an impaired cell wall with an altered outer mycomembrane, accumulation of a desaturated α-mycolate, susceptibility to antimycobacterials, and cell surface disruption. Transcriptomic profiling showed that enriched lipid metabolism genes that were significantly down-regulated upon madR deletion included acyl-coenzyme A (aceyl-CoA) dehydrogenases, implicating it in the indirect control of ß-oxidation pathways. Electromobility shift assays and binding affinities suggest a unique acyl-CoA pool-sensing mechanism, whereby MadR is able to bind a range of acyl-CoAs, including those with unsaturated as well as saturated acyl chains. MadR repression of desA1/desA2 is relieved upon binding of saturated acyl-CoAs of chain length C16 to C24, while no impact is observed upon binding of shorter chain and unsaturated acyl-CoAs. We propose this mechanism of regulation as distinct to other mycolic acid and fatty acid synthesis regulators and place MadR as the key regulatory checkpoint that coordinates mycolic acid remodeling during infection in response to host-derived cell surface perturbation.

Quantitative prediction of conditional vulnerabilities in regulatory and metabolic networks using PRIME.

The ability of Mycobacterium tuberculosis (Mtb) to adopt heterogeneous physiological states underlies its success in evading the immune system and tolerating antibiotic killing. Drug tolerant phenotypes are a major reason why the tuberculosis (TB) mortality rate is so high, with over 1.8 million deaths annually. To develop new TB therapeutics that better treat the infection (faster and more completely), a systems-level approach is needed to reveal the complexity of network-based adaptations of Mtb. Here, we report a new predictive model called PRIME (Phenotype of Regulatory influences Integrated with Metabolism and Environment) to uncover environment-specific vulnerabilities within the regulatory and metabolic networks of Mtb. Through extensive performance evaluations using genome-wide fitness screens, we demonstrate that PRIME makes mechanistically accurate predictions of context-specific vulnerabilities within the integrated regulatory and metabolic networks of Mtb, accurately rank-ordering targets for potentiating treatment with frontline drugs.

Mycobacterium abscessus biofilms produce an extracellular matrix and have a distinct mycolic acid profile.

A non-tuberculous mycobacterium, Mycobacterium abscessus is an emerging opportunistic pathogen associated with difficult to treat pulmonary infections, particularly in patients suffering from cystic fibrosis. It is capable of forming biofilms in vitro that result in an increase of already high levels of antibiotic resistance in this bacterium. Evidence that M. abscessus forms biofilm-like microcolonies in patient lungs and on medical devices further implicated the need to investigate this biofilm in detail. Therefore, in this study we characterized the M. abscessus pellicular biofilm, formed on a liquid-air interface, by studying its molecular composition, and its transcriptional profile in comparison to planktonic cells. Using scanning electron micrographs and fluorescence microscopy, we showed that M. abscessus biofilms produce an extracellular matrix composed of lipids, proteins, carbohydrates and extracellular DNA. Transcriptomic analysis of biofilms revealed an upregulation of pathways involved in the glyoxylate shunt, redox metabolism and mycolic acid biosynthesis. Genes involved in elongation and desaturation of mycolic acids were highly upregulated in biofilms and, mirroring those findings, biochemical analysis of mycolates revealed molecular changes and an increase in mycolic acid chain length. Together these results give us an insight into the complex structure of M. abscessus biofilms, the understanding of which may be adapted for clinical use in treatment of biofilm infections, including strategies for dispersing the extracellular matrix, allowing antibiotics to gain access to bacteria within the biofilm.

A systems-level gene regulatory network model for Plasmodium falciparum.

Many of the gene regulatory processes of Plasmodium falciparum, the deadliest malaria parasite, remain poorly understood. To develop a comprehensive guide for exploring this organism's gene regulatory network, we generated a systems-level model of P. falciparum gene regulation using a well-validated, machine-learning approach for predicting interactions between transcription regulators and their targets. The resulting network accurately predicts expression levels of transcriptionally coherent gene regulatory programs in independent transcriptomic data sets from parasites collected by different research groups in diverse laboratory and field settings. Thus, our results indicate that our gene regulatory model has predictive power and utility as a hypothesis-generating tool for illuminating clinically relevant gene regulatory mechanisms within P. falciparum. Using the set of regulatory programs we identified, we also investigated correlates of artemisinin resistance based on gene expression coherence. We report that resistance is associated with incoherent expression across many regulatory programs, including those controlling genes associated with erythrocyte-host engagement. These results suggest that parasite populations with reduced artemisinin sensitivity are more transcriptionally heterogenous. This pattern is consistent with a model where the parasite utilizes bet-hedging strategies to diversify the population, rendering a subpopulation more able to navigate drug treatment.

Transcriptome signature of cell viability predicts drug response and drug interaction in Mycobacterium tuberculosis.

There is an urgent need for new drug regimens to rapidly cure tuberculosis. Here, we report the development of drug response assayer (DRonA) and "MLSynergy," algorithms to perform rapid drug response assays and predict response of Mycobacterium tuberculosis (Mtb) to drug combinations. Using a transcriptome signature for cell viability, DRonA detects Mtb killing by diverse mechanisms in broth culture, macrophage infection, and patient sputum, providing an efficient and more sensitive alternative to time- and resource-intensive bacteriologic assays. Further, MLSynergy builds on DRonA to predict synergistic and antagonistic multidrug combinations using transcriptomes of Mtb treated with single drugs. Together, DRonA and MLSynergy represent a generalizable framework for rapid monitoring of drug effects in host-relevant contexts and accelerate the discovery of efficacious high-order drug combinations.

PerSort Facilitates Characterization and Elimination of Persister Subpopulation in Mycobacteria.

Mycobacterium tuberculosis (MTB) generates phenotypic diversity to persist and survive the harsh conditions encountered during infection. MTB avoids immune effectors and antibacterial killing by entering into distinct physiological states. The surviving cells, persisters, are a major barrier to the timely and relapse-free treatment of tuberculosis (TB). We present for the first time, PerSort, a method to isolate and characterize persisters in the absence of antibiotic or other pressure. We demonstrate the value of PerSort to isolate translationally dormant cells that preexisted in small numbers within Mycobacterium species cultures growing under optimal conditions but that dramatically increased in proportion under stress conditions. The translationally dormant subpopulation exhibited multidrug tolerance and regrowth properties consistent with those of persister cells. Furthermore, PerSort enabled single-cell transcriptional profiling that provided evidence that the translationally dormant persisters were generated through a variety of mechanisms, including vapC30, mazF, and relA/spoT overexpression. Finally, we demonstrate that notwithstanding the varied mechanisms by which the persister cells were generated, they converge on a similar low-oxygen metabolic state that was reversed through activation of respiration to rapidly eliminate persisters fostered under host-relevant stress conditions. We conclude that PerSort provides a new tool to study MTB persisters, enabling targeted strategies to improve and shorten the treatment of TB.IMPORTANCE Mycobacterium tuberculosis (MTB) persists and survives antibiotic treatments by generating phenotypically heterogeneous drug-tolerant subpopulations. The surviving cells, persisters, are a major barrier to the relapse-free treatment of tuberculosis (TB), which is already killing >1.8 million people every year and becoming deadlier with the emergence of multidrug-resistant strains. This study describes PerSort, a cell sorting method to isolate and characterize, without antibiotic treatment, translationally dormant persisters that preexist in small numbers within Mycobacterium cultures. Characterization of this subpopulation has discovered multiple mechanisms by which mycobacterial persisters emerge and unveiled the physiological basis for their dormant and multidrug-tolerant physiological state. This analysis has discovered that activating oxygen respiratory physiology using l-cysteine eliminates preexisting persister subpopulations, potentiating rapid antibiotic killing of mycobacteria under host-relevant stress. PerSort serves as a new tool to study MTB persisters for enabling targeted strategies to improve and shorten the treatment of TB.

Biofilms of the non-tuberculous Mycobacterium chelonae form an extracellular matrix and display distinct expression patterns.

Mycobacterium chelonae is an environmental, non-tuberculous mycobacterial species, capable of causing infections in humans. Biofilm formation is a key strategy used by M. chelonae in colonising niches in the environment and in the host. We studied a water-air interface (pellicle) biofilm of M. chelonae using a wide array of approaches to outline the molecular structure and composition of the biofilm. Scanning electron micrographs showed that M. chelonae biofilms produced an extracellular matrix. Using a combination of biochemical analysis, Raman spectroscopy, and fluorescence microscopy, we showed the matrix to consist of proteins, carbohydrates, lipids and eDNA. Glucose was the predominant sugar present in the biofilm matrix, and its relative abundance decreased in late (established) biofilms. RNA-seq analysis of the biofilms showed upregulation of genes involved in redox metabolism. Additionally, genes involved in mycolic acid, other lipid and glyoxylate metabolism were also upregulated in the early biofilms.

Transcriptional portrait of M. bovis BCG during biofilm production shows genes differentially expressed during intercellular aggregation and substrate attachment.

Mycobacterium tuberculosis and M. smegmatis form drug-tolerant biofilms through dedicated genetic programs. In support of a stepwise process regulating biofilm production in mycobacteria, it was shown elsewhere that lsr2 participates in intercellular aggregation, while groEL1 was required for biofilm maturation in M. smegmatis. Here, by means of RNA-Seq, we monitored the early steps of biofilm production in M. bovis BCG, to distinguish intercellular aggregation from attachment to a surface. Genes encoding for the transcriptional regulators dosR and BCG0114 (Rv0081) were significantly regulated and responded differently to intercellular aggregation and surface attachment. Moreover, a M. tuberculosis H37Rv deletion mutant in the Rv3134c-dosS-dosR regulon, formed less biofilm than wild type M. tuberculosis, a phenotype reverted upon reintroduction of this operon into the mutant. Combining RT-qPCR with microbiological assays (colony and surface pellicle morphologies, biofilm quantification, Ziehl-Neelsen staining, growth curve and replication of planktonic cells), we found that BCG0642c affected biofilm production and replication of planktonic BCG, whereas ethR affected only phenotypes linked to planktonic cells despite its downregulation at the intercellular aggregation step. Our results provide evidence for a stage-dependent expression of genes that contribute to biofilm production in slow-growing mycobacteria.

Intricate Genetic Programs Controlling Dormancy in Mycobacterium tuberculosis.

Mycobacterium tuberculosis (MTB) displays the remarkable ability to transition in and out of dormancy, a hallmark of the pathogen's capacity to evade the immune system and exploit susceptible individuals. Uncovering the gene regulatory programs that underlie the phenotypic shifts in MTB during disease latency and reactivation has posed a challenge. We develop an experimental system to precisely control dissolved oxygen levels in MTB cultures in order to capture the transcriptional events that unfold as MTB transitions into and out of hypoxia-induced dormancy. Using a comprehensive genome-wide transcription factor binding map and insights from network topology analysis, we identify regulatory circuits that deterministically drive sequential transitions across six transcriptionally and functionally distinct states encompassing more than three-fifths of the MTB genome. The architecture of the genetic programs explains the transcriptional dynamics underlying synchronous entry of cells into a dormant state that is primed to infect the host upon encountering favorable conditions.

Path-seq identifies an essential mycolate remodeling program for mycobacterial host adaptation.

The success of Mycobacterium tuberculosis (MTB) stems from its ability to remain hidden from the immune system within macrophages. Here, we report a new technology (Path-seq) to sequence miniscule amounts of MTB transcripts within up to million-fold excess host RNA Using Path-seq and regulatory network analyses, we have discovered a novel transcriptional program for in vivo mycobacterial cell wall remodeling when the pathogen infects alveolar macrophages in mice. We have discovered that MadR transcriptionally modulates two mycolic acid desaturases desA1/desA2 to initially promote cell wall remodeling upon in vitro macrophage infection and, subsequently, reduces mycolate biosynthesis upon entering dormancy. We demonstrate that disrupting MadR program is lethal to diverse mycobacteria making this evolutionarily conserved regulator a prime antitubercular target for both early and late stages of infection.

The BCGΔBCG1419c Vaccine Candidate Reduces Lung Pathology, IL-6, TNF-α, and IL-10 During Chronic TB Infection.

Mycobacterium tuberculosis (M. tuberculosis), the causative agent of human tuberculosis (TB), is estimated to be harbored by up to 2 billion people in a latent TB infection (LTBI) state. The only TB vaccine approved for use in humans, BCG, does not confer protection against establishment of or reactivation from LTBI, so new vaccine candidates are needed to specifically address this need. Following the hypothesis that mycobacterial biofilms resemble aspects of LTBI, we modified BCG by deleting the BCG1419c gene to create the BCGΔBCG1419c vaccine strain. In this study, we compared cytokine profiles, bacterial burden, and lung lesions after immunization with BCG or BCGΔBCG1419c before and after 6 months of aerosol infection with M. tuberculosis H37Rv in the resistant C57BL/6 mouse model. Our results show that in infected mice, BCGΔBCG1419c significantly reduced lung lesions and IL-6 in comparison to the unmodified BCG strain, and was the only vaccine that decreased production of TNF-α and IL-10 compared to non-vaccinated mice, while vaccination with BCG or BCGΔBCG1419c significantly reduced IFN-γ production. Moreover, transcriptome profiling of BCGΔBCG1419c suggests that compared to BCG, it has decreased expression of genes involved in mycolic acids (MAs) metabolism, and antigenic chaperones, which might be involved in reduced pathology compared to BCG-vaccinated mice.

Network analysis identifies Rv0324 and Rv0880 as regulators of bedaquiline tolerance in Mycobacterium tuberculosis.

The resilience of Mycobacterium tuberculosis (MTB) emerges from its ability to effectively counteract immunological, environmental and antitubercular challenges. Here, we demonstrate that MTB can tolerate drug treatment by adopting a tolerant state that can be deciphered through systems analysis of its transcriptional responses. Specifically, we demonstrate how treatment with the antitubercular drug bedaquiline activates a regulatory network that coordinates multiple resistance mechanisms to push MTB into a tolerant state. Disruption of this network, by knocking out its predicted transcription factors, Rv0324 and Rv0880, significantly increased bedaquiline killing and enabled the discovery of a second drug, pretomanid, that potentiated killing by bedaquiline. We demonstrate that the synergistic effect of this combination emerges, in part, through disruption of the tolerance network. We discuss how this network strategy also predicts drug combinations with antagonistic interactions, potentially accelerating the discovery of new effective combination drug regimens for tuberculosis.

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.

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.

Inhibitors of Streptococcus pneumoniae surface endonuclease EndA discovered by high-throughput screening using a PicoGreen fluorescence assay.

The human commensal pathogen Streptococcus pneumoniae expresses a number of virulence factors that promote serious pneumococcal diseases, resulting in significant morbidity and mortality worldwide. These virulence factors may give S. pneumoniae the capacity to escape immune defenses, resist antimicrobial agents, or a combination of both. Virulence factors also present possible points of therapeutic intervention. The activities of the surface endonuclease, EndA, allow S. pneumoniae to establish invasive pneumococcal infection. EndA's role in DNA uptake during transformation contributes to gene transfer and genetic diversification. Moreover, EndA's nuclease activity degrades the DNA backbone of neutrophil extracellular traps (NETs), allowing pneumococcus to escape host immune responses. Given its potential impact on pneumococcal pathogenicity, EndA is an attractive target for novel antimicrobial therapy. Herein, we describe the development of a high-throughput screening assay for the discovery of nuclease inhibitors. Nuclease-mediated digestion of double-stranded DNA was assessed using fluorescence changes of the DNA dye ligand, PicoGreen. Under optimized conditions, the assay provided robust and reproducible activity data (Z'= 0.87) and was used to screen 4727 small molecules against an imidazole-rescued variant of EndA. In total, six small molecules were confirmed as novel EndA inhibitors, some of which may have utility as research tools for understanding pneumococcal pathogenesis and for drug discovery.