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

Dissecting the Ca2+ dependence of DesA1 function in Mycobacterium tuberculosis

Mycobacterium tuberculosis (M. tb) has a complex cell wall, composed largely of mycolic acids, that are crucial to its structural maintenance. The M. tb desaturase A1 (DesA1) is an essential Ca2+-binding protein that catalyses a key step in mycolic acid biosynthesis. To investigate the structural and functional significance of Ca2+ binding, we introduced mutations at key residues in its Ca2+-binding βγ-crystallin motif to generate DesA1F303A, E304Q, and F303A-E304Q. Complementation of a conditional ΔdesA1 strain of Mycobacterium smegmatis, with the Ca2+ non-binders F303A or F303A-E304Q, failed to rescue its growth phenotype; these complements also exhibited enhanced cell wall permeability. Our findings highlight the criticality of Ca2+ in DesA1 function, and its implicit role in the maintenance of mycobacterial cellular integrity.

3D Hydrogel Culture System Recapitulates Key Tuberculosis Phenotypes and Demonstrates Pyrazinamide Efficacy

The mortality caused by tuberculosis (TB) infections is a global concern, and there is a need to improve understanding of the disease. Current in vitro infection models to study the disease have limitations such as short investigation durations and divergent transcriptional signatures. This study aims to overcome these limitations by developing a 3D collagen culture system that mimics the biomechanical and extracellular matrix (ECM) of lung microenvironment (collagen fibers, stiffness comparable to in vivo conditions) as the infection primarily manifests in the lungs. The system incorporates Mycobacterium tuberculosis (Mtb) infected human THP-1 or primary monocytes/macrophages. Dual RNA sequencing reveals higher mammalian gene expression similarity with patient samples than 2D macrophage infections. Similarly, bacterial gene expression more accurately recapitulates in vivo gene expression patterns compared to bacteria in 2D infection models. Key phenotypes observed in humans, such as foamy macrophages and mycobacterial cords, are reproduced in the model. This biomaterial system overcomes challenges associated with traditional platforms by modulating immune cells and closely mimicking in vivo infection conditions, including showing efficacy with clinically relevant concentrations of anti-TB drug pyrazinamide, not seen in any other in vitro infection model, making it reliable and readily adoptable for tuberculosis studies and drug screening.

Transcriptome analysis of Edwardsiella piscicida during intracellular infection reveals excludons are involved with the activation of a mitochondrion-like energy generation program

Phylogenetic evidence suggests a shared ancestry between mitochondria and modern Proteobacteria, a phylum including several genera of intracellular pathogens. Studying these diverse pathogens, particularly during intracellular infection of their hosts, can reveal characteristics potentially representative of the mitochondrial-Proteobacterial ancestor by identifying traits shared with mitochondria. While transcriptomic approaches can provide global insights into intracellular acclimatization by pathogens, they are often limited by excess host RNAs in extracts. Here, we developed a method employing magnetic nanoparticles to enrich RNA from an intracellular Gammaproteobacterium, Edwardsiella piscicida, within zebrafish, Danio rerio, fin fibroblasts, enabling comprehensive exploration of the bacterial transcriptome. Our findings revealed that the intracellular E. piscicida transcriptome reflects a mitochondrion-like energy generation program characterized by the suppression of glycolysis and sugar transport, coupled with upregulation of the tricarboxylic acid (TCA) cycle and alternative import of simple organic acids that directly flux into TCA cycle intermediates or electron transport chain donors. Additionally, genes predicted to be members of excludons, loci of gene pairs antagonistically co-regulated by overlapping antisense transcription, are significantly enriched in the set of all genes with perturbed sense and antisense transcription, suggesting a general but important involvement of excludons with intracellular acclimatization. Notably, genes involved with the activation of the mitochondrion-like energy generation program, specifically with metabolite import and glycolysis, are also members of predicted excludons. Other intracellular Proteobacterial pathogens appear to employ a similar mitochondrion-like energy generation program, suggesting a potentially conserved mechanism for optimized energy acquisition from hosts centered around the TCA cycle.IMPORTANCEPhylogenetic evidence suggests that mitochondria and Proteobacteria, a phylum encompassing various intracellular pathogens, share a common ancestral lineage. In this study, we developed a novel method employing magnetic nanoparticles to explore the transcriptome of an aquatic Gammaproteobacterium, Edwardsiella piscicida, during intracellular infection of host cells. We show that the strategy E. piscicida uses to generate energy strikingly mirrors the function of mitochondria-energy generators devoid of glycolytic processes. Notably, several implicated genes are members of excludons-gene pairs antagonistically co-regulated by overlapping antisense transcription. Other intracellular Proteobacterial pathogens appear to adopt a similar mitochondrion-like energy generation program, indicating a possibly conserved strategy for optimized energy acquisition from hosts centered around the tricarboxylic acid cycle.

Mycobacterium tuberculosis-THP-1 like macrophages protein-protein interaction map revealed through dual RNA-seq analysis and a computational approach

Introduction. Infection caused by Mycobacterium tuberculosis (M. tb) is still a leading cause of mortality worldwide with estimated 1.4 million deaths annually.Hypothesis/Gap statement. Despite macrophages' ability to kill bacterium, M. tb can grow inside these innate immune cells and the exploration of the infection has traditionally been characterized by a one-sided relationship, concentrating solely on the host or examining the pathogen in isolation.Aim. Because of only a handful of M. tb-host interactions have been experimentally characterized, our main goal is to predict protein-protein interactions during the early phases of the infection.Methodology. In this work, we performed an integrative computational approach that exploits differentially expressed genes obtained from Dual RNA-seq analysis combined with known domain-domain interactions.Results. A total of 2381 and 7214 genes were identified as differentially expressed in M. tb and in THP-1-like macrophages, respectively, revealing different transcriptional profiles in response to infection. Over 48 h of infection, the host-pathogen network revealed 25 016 PPIs. Analysis of the resulting predicted network based on cellular localization information of M. tb proteins, indicated the implication of interacting nodes including the bacterial PE/PPE/PE_PGRS family. In addition, M. tb proteins interacted with host proteins involved in NF-kB signalling pathway as well as interfering with the host apoptosis ability via the potential interaction of M. tb TB16.3 with human TAB1 and M. tb GroEL2 with host protein kinase C delta, respectively.Conclusion. The prediction of the full range of interactions between M. tb and host will contribute to better understanding of the pathogenesis of this bacterium and may provide advanced approaches to explore new therapeutic targets against tuberculosis.

Pathogenicity and virulence of Mycobacterium tuberculosis

Mycobacterium tuberculosis (Mtb) is the causative agent of tuberculosis, an infectious disease with one of the highest morbidity and mortality rates worldwide. Leveraging its highly evolved repertoire of non-protein and protein virulence factors, Mtb invades through the airway, subverts host immunity, establishes its survival niche, and ultimately escapes in the setting of active disease to initiate another round of infection in a naive host. In this review, we will provide a concise synopsis of the infectious life cycle of Mtb and its clinical and epidemiologic significance. We will also take stock of its virulence factors and pathogenic mechanisms that modulate host immunity and facilitate its spread. Developing a greater understanding of the interface between Mtb virulence factors and host defences will enable progress toward improved vaccines and therapeutics to prevent and treat tuberculosis.

Mechanopathology of biofilm-like Mycobacterium tuberculosis cords

Mycobacterium tuberculosis (Mtb) cultured axenically without detergent forms biofilm-like cords, a clinical identifier of virulence. In lung-on-chip (LoC) and mouse models, cords in alveolar cells contribute to suppression of innate immune signaling via nuclear compression. Thereafter, extracellular cords cause contact-dependent phagocyte death but grow intercellularly between epithelial cells. The absence of these mechanopathological mechanisms explains the greater proportion of alveolar lesions with increased immune infiltration and dissemination defects in cording-deficient Mtb infections. Compression of Mtb lipid monolayers induces a phase transition that enables mechanical energy storage. Agent-based simulations demonstrate that the increased energy storage capacity is sufficient for the formation of cords that maintain structural integrity despite mechanical perturbation. Bacteria in cords remain translationally active despite antibiotic exposure and regrow rapidly upon cessation of treatment. This study provides a conceptual framework for the biophysics and function in tuberculosis infection and therapy of cord architectures independent of mechanisms ascribed to single bacteria.

Transcription factor mce3R modulates antibiotics and disease persistence in Mycobacteriumtuberculosis

Transcription factors (TFs) of Mycobacterium tuberculosis (Mtb), an etiological agent of tuberculosis, regulate a network of pathways that help prolong the survival of Mtb inside the host. In this study, we have characterized a transcription repressor gene (mce3R) from the TetR family, that encodes for Mce3R protein in Mtb. We demonstrated that the mce3R gene is dispensable for the growth of Mtb on cholesterol. Gene expression analysis suggests that the transcription of genes belonging to the mce3R regulon is independent of the carbon source. We found that, in comparison to the wild type, the mce3R deleted strain (Δmce3R) generated more intracellular ROS and demonstrated reduced susceptibility to oxidative stress. Total lipid analysis suggests that mce3R regulon encoded proteins modulate the biosynthesis of cell wall lipids in Mtb. Interestingly, the absence of Mce3R increased the frequency of generation of antibiotic persisters in Mtb and imparted in-vivo growth advantage phenotype in guinea pigs. In conclusion, genes belonging to the mce3R regulon modulate the frequency of generation of persisters in Mtb. Hence, targeting mce3R regulon encoded proteins could potentiate the current regimen by eliminating persisters during Mtb infection.

Biosensor-integrated transposon mutagenesis reveals rv0158 as a coordinator of redox homeostasis in Mycobacterium tuberculosis

Mycobacterium tuberculosis (Mtb) is evolutionarily equipped to resist exogenous reactive oxygen species (ROS) but shows vulnerability to an increase in endogenous ROS (eROS). Since eROS is an unavoidable consequence of aerobic metabolism, understanding how Mtb manages eROS levels is essential yet needs to be characterized. By combining the Mrx1-roGFP2 redox biosensor with transposon mutagenesis, we identified 368 genes (redoxosome) responsible for maintaining homeostatic levels of eROS in Mtb. Integrating redoxosome with a global network of transcriptional regulators revealed a hypothetical protein (Rv0158) as a critical node managing eROS in Mtb. Disruption of rv0158 (rv0158 KO) impaired growth, redox balance, respiration, and metabolism of Mtb on glucose but not on fatty acids. Importantly, rv0158 KO exhibited enhanced growth on propionate, and the Rv0158 protein directly binds to methylmalonyl-CoA, a key intermediate in propionate catabolism. Metabolite profiling, ChIP-Seq, and gene-expression analyses indicate that Rv0158 manages metabolic neutralization of propionate toxicity by regulating the methylcitrate cycle. Disruption of rv0158 enhanced the sensitivity of Mtb to oxidative stress, nitric oxide, and anti-TB drugs. Lastly, rv0158 KO showed poor survival in macrophages and persistence defect in mice. Our results suggest that Rv0158 is a metabolic integrator for carbon metabolism and redox balance in Mtb.

Genetic epidemiology of resistance to M. tuberculosis Infection: importance of study design and recent findings

Resistance to M. tuberculosis, often referred to as "RSTR" in the literature, is being increasingly studied because of its potential relevance as a clinical outcome in vaccine studies. This review starts by addressing the importance of epidemiological characterization of this phenotype, and ongoing challenges in that characterization. Then, this review summarizes the extant genetic and genomic studies of this phenotype, including heritability studies, candidate gene studies, and genome-wide association studies, as well as whole transcriptome studies. Findings from recent studies that used longitudinal characterization of the RSTR phenotype are compared to those using a cross-sectional definition, and the challenges of using tuberculin skin test and interferon-gamma release assay are discussed. Finally, future directions are proposed. Since this is a rapidly evolving area of public health significance, this review will help frame future research questions and study designs.

Disrupting the ArcA Regulatory Network Amplifies the Fitness Cost of Tetracycline Resistance in Escherichia coli

There is an urgent need for strategies to discover secondary drugs to prevent or disrupt antimicrobial resistance (AMR), which is causing >700,000 deaths annually. Here, we demonstrate that tetracycline-resistant (Tet^R) Escherichia coli undergoes global transcriptional and metabolic remodeling, including downregulation of tricarboxylic acid cycle and disruption of redox homeostasis, to support consumption of the proton motive force for tetracycline efflux. Using a pooled genome-wide library of single-gene deletion strains, at least 308 genes, including four transcriptional regulators identified by our network analysis, were confirmed as essential for restoring the fitness of Tet^R E. coli during treatment with tetracycline. Targeted knockout of ArcA, identified by network analysis as a master regulator of this new compensatory physiological state, significantly compromised fitness of Tet^R E. coli during tetracycline treatment. A drug, sertraline, which generated a similar metabolome profile as the arcA knockout strain, also resensitized Tet^R E. coli to tetracycline. We discovered that the potentiating effect of sertraline was eliminated upon knocking out arcA, demonstrating that the mechanism of potential synergy was through action of sertraline on the tetracycline-induced ArcA network in the Tet^R strain. Our findings demonstrate that therapies that target mechanistic drivers of compensatory physiological states could resensitize AMR pathogens to lost antibiotics. IMPORTANCE Antimicrobial resistance (AMR) is projected to be the cause of >10 million deaths annually by 2050. While efforts to find new potent antibiotics are effective, they are expensive and outpaced by the rate at which new resistant strains emerge. There is desperate need for a rational approach to accelerate the discovery of drugs and drug combinations that effectively clear AMR pathogens and even prevent the emergence of new resistant strains. Using tetracycline-resistant (Tet^R) Escherichia coli, we demonstrate that gaining resistance is accompanied by loss of fitness, which is restored by compensatory physiological changes. We demonstrate that transcriptional regulators of the compensatory physiologic state are promising drug targets because their disruption increases the susceptibility of Tet^R E. coli to tetracycline. Thus, we describe a generalizable systems biology approach to identify new vulnerabilities within AMR strains to rationally accelerate the discovery of therapeutics that extend the life span of existing antibiotics.

MicroRNA-20b carried by mesenchymal stem cell-derived extracellular vesicles protects alveolar epithelial type II cells from Mycobacterium tuberculosis infection in vitro

Mesenchymal stem cells (MSCs) have been largely used for their immunomodulatory and regenerative properties in the treatment of immune-based disorders and bacterial infections. This study explores the function of MSC-derived extracellular vesicles (MSC-EVs) in alveolar epithelial type II cells (AECII) against Mycobacterium tuberculosis (MTB) infection. EVs were extracted from the acquired MSCs. AECII-like MLE-15 and A549 cells were treated with MSC-EVs and then subjected to MTB infection. MSC-EVs treatment significantly prevented the increase in bacterial load, and it prevented the production of proinflammatory cytokines in cells induced by MTB infection. MicroRNA-20b (miR-20b) was upregulated in cells after MSC-EVs treatment. Artificial inhibition of miR-20b blocked the protective effects of MSC-EVs against MTB infection. A Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis was performed to analyze the key molecules involved in the immune regulation in cells mediated by miR-20b. miR-20b directly targeted nuclear factor of activated T cells 5 (NFAT5) and inactivated the Toll-Like Receptor (TLR) signaling pathway by reducing the formation of TLR2-TLR4 dimer after MTB infection. In conclusion, this study suggests that MSC-EVs carry miR-20b to inhibit NFAT5 and inactivate the TLR signaling pathway, thus mediating innate immune response and preventing AECII from MTB infection-induced damage.

The mycobacterial desaturase DesA2 is associated with mycolic acid biosynthesis

Mycolic acids are critical for the survival and virulence of Mycobacterium tuberculosis, the causative agent of tuberculosis. Double bond formation in the merochain of mycolic acids remains poorly understood, though we have previously shown desA1, encoding an aerobic desaturase, is involved in mycolic acid desaturation. Here we show that a second desaturase encoded by desA2 is also involved in mycolate biosynthesis. DesA2 is essential for growth of the fast-growing Mycobacterium smegmatis in laboratory media. Conditional depletion of DesA2 led to a decrease in mycolic acid biosynthesis and loss of mycobacterial viability. Additionally, DesA2-depleted cells also accumulated fatty acids of chain lengths C19-C24. The complete loss of mycolate biosynthesis following DesA2 depletion, and the absence of any monoenoic derivatives (found to accumulate on depletion of DesA1) suggests an early role for DesA2 in the mycolic acid biosynthesis machinery, highlighting its potential as a drug target.

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.

Chemical-genetic interaction mapping links carbon metabolism and cell wall structure to tuberculosis drug efficacy

Efforts to improve tuberculosis therapy include optimizing multidrug regimens to take advantage of drug–drug synergies. However, the complex host environment has a profound effect on bacterial metabolic state and drug activity, making predictions of optimal drug combinations difficult. In this study, we leverage a newly developed library of conditional knockdown Mycobacterium tuberculosis mutants in which genetic depletion of essential genes mimics the effect of drug therapy. This tractable system allowed us to assess the effect of growth condition on predicted drug–drug interactions. We found that these interactions can be differentially sensitive to the metabolic state, and select in vitro–defined interactions can be leveraged to accelerate bacterial killing during infection. These findings suggest strategies for optimizing tuberculosis therapy.

Current chemotherapy against Mycobacterium tuberculosis (Mtb), an important human pathogen, requires a multidrug regimen lasting several months. While efforts have been made to optimize therapy by exploiting drug–drug synergies, testing new drug combinations in relevant host environments remains arduous. In particular, host environments profoundly affect the bacterial metabolic state and drug efficacy, limiting the accuracy of predictions based on in vitro assays alone. In this study, we utilized conditional Mtb knockdown mutants of essential genes as an experimentally tractable surrogate for drug treatment and probe the relationship between Mtb carbon metabolism and chemical–genetic interactions (CGIs). We examined the antitubercular drugs isoniazid, rifampicin, and moxifloxacin and found that CGIs are differentially responsive to the metabolic state, defining both environment-independent and -dependent interactions. Specifically, growth on the in vivo–relevant carbon source, cholesterol, reduced rifampicin efficacy by altering mycobacterial cell surface lipid composition. We report that a variety of perturbations in cell wall synthesis pathways restore rifampicin efficacy during growth on cholesterol, and that both environment-independent and cholesterol-dependent in vitro CGIs could be leveraged to enhance bacterial clearance in the mouse infection model. Our findings present an atlas of chemical–genetic–environmental interactions that can be used to optimize drug–drug interactions, as well as provide a framework for understanding in vitro correlates of in vivo efficacy.

Machine Learning of All Mycobacterium tuberculosis H37Rv RNA-seq Data Reveals a Structured Interplay between Metabolism, Stress Response, and Infection

Mycobacterium tuberculosis is one of the most consequential human bacterial pathogens, posing a serious challenge to 21st century medicine. A key feature of its pathogenicity is its ability to adapt its transcriptional response to environmental stresses through its transcriptional regulatory network (TRN). While many studies have sought to characterize specific portions of the M. tuberculosis TRN, and some studies have performed system-level analysis, few have been able to provide a network-based model of the TRN that also provides the relative shifts in transcriptional regulator activity triggered by changing environments. Here, we compiled a compendium of nearly 650 publicly available, high quality M. tuberculosis RNA-sequencing data sets and applied an unsupervised machine learning method to obtain a quantitative, top-down TRN. It consists of 80 independently modulated gene sets known as “iModulons,” 41 of which correspond to known regulons. These iModulons explain 61% of the variance in the organism’s transcriptional response. We show that iModulons (i) reveal the function of poorly characterized regulons, (ii) describe the transcriptional shifts that occur during environmental changes such as shifting carbon sources, oxidative stress, and infection events, and (iii) identify intrinsic clusters of regulons that link several important metabolic systems, including lipid, cholesterol, and sulfur metabolism. This transcriptome-wide analysis of the M. tuberculosis TRN informs future research on effective ways to study and manipulate its transcriptional regulation and presents a knowledge-enhanced database of all published high-quality RNA-seq data for this organism to date.

IMPORTANCEMycobacterium tuberculosis H37Rv is one of the world's most impactful pathogens, and a large part of the success of the organism relies on the differential expression of its genes to adapt to its environment. The expression of the organism's genes is driven primarily by its transcriptional regulatory network, and most research on the TRN focuses on identifying and quantifying clusters of coregulated genes known as regulons. While previous studies have relied on molecular measurements, in the manuscript we utilized an alternative technique that performs machine learning to a large data set of transcriptomic data. This approach is less reliant on hypotheses about the role of specific regulatory systems and allows for the discovery of new biological findings for already collected data. A better understanding of the structure of the M. tuberculosis TRN will have important implications in the design of improved therapeutic approaches.

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

Our studies show that the mycolic acid desaturase regulator (MadR) acts as a molecular switch, controlling the desaturation and biosynthesis of mycolic acids, key lipids of the cell envelopes of mycobacteria. MadR works by a distinct mechanism wherein it binds various acyl-coenzyme As (aceyl-CoAs), but only saturated acyl-CoAs relieve DNA binding and repression. This suggests a unique mechanism that involves sensing of acyl-CoA pools as a checkpoint for coordinating mycolic acid remodeling and biosynthesis in response to cell surface perturbation. Our findings further our understanding of how mycobacteria control cell wall composition in response to stress across various environments ranging from soil to an intracellular niche in infected macrophages, with implications for understanding strategies for pathogenesis in the tubercle bacillus.

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 β-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.

Mycobacterial Membranes as Actionable Targets for Lipid-Centric Therapy in Tuberculosis

Infectious diseases remain significant health concerns worldwide, and resistance is particularly common in patients with tuberculosis caused by Mycobacterium tuberculosis. The development of anti-infectives with novel modes of action may help overcome resistance. In this regard, membrane-active agents, which modulate membrane components essential for the survival of pathogens, present attractive antimicrobial agents. Key advantages of membrane-active compounds include their ability to target slow-growing or dormant bacteria and their favorable pharmacokinetics. Here, we comprehensively review recent advances in the development of membrane-active chemotypes that target mycobacterial membranes and discuss clinically relevant membrane-active antibacterial agents that have shown promise in counteracting bacterial infections. We discuss the relationship between the membrane properties and the synthetic requirements within the chemical scaffold, as well as the limitations of current membrane-active chemotypes. This review will lay the chemical groundwork for the development of membrane-active antituberculosis agents and will foster the discovery of more effective antitubercular agents.

Dual RNA sequencing reveals dendritic cell reprogramming in response to typhoidal Salmonella invasion

Salmonella enterica represent a major disease burden worldwide. S. enterica serovar Typhi (S. Typhi) is responsible for potentially life-threatening Typhoid fever affecting 10.9 million people annually. While non-typhoidal Salmonella (NTS) serovars usually trigger self-limiting diarrhoea, invasive NTS bacteraemia is a growing public health challenge. Dendritic cells (DCs) are key professional antigen presenting cells of the human immune system. The ability of pathogenic bacteria to subvert DC functions and prevent T cell recognition contributes to their survival and dissemination within the host. Here, we adapted dual RNA-sequencing to define how different Salmonella pathovariants remodel their gene expression in tandem with that of infected DCs. We find DCs harness iron handling pathways to defend against invading Salmonellas, which S. Typhi is able to circumvent by mounting a robust response to nitrosative stress. In parallel, we uncover the alternative strategies invasive NTS employ to impair DC functions.

Aulicino, Antanaviciute et al investigate the transcriptional response to invasive Salmonella strains in dendritic cells (DCs). They show that S. Typhi mount a response against nitrosative stress pathways and propose a role of iron uptake and transport in preventing infection, which the pathogen can bypass. In parallel, they find that invasive Salmonella employs several mechanisms targeting more classic aspects of immunity to impair DC function.

Dissecting the Mycobacterium bovis BCG Response to Macrophage Infection to Help Prioritize Targets for Anti-Tuberculosis Drug and Vaccine Discovery

New strategies are required to reduce the worldwide burden of tuberculosis. Intracellular survival and replication of Mycobacterium tuberculosis after macrophage phagocytosis is a fundamental step in the complex host–pathogen interactions that lead to granuloma formation and disease. Greater understanding of how the bacterium survives and thrives in these environments will inform novel drug and vaccine discovery programs. Here, we use in-depth RNA sequencing of Mycobacterium bovis BCG from human THP-1 macrophages to describe the mycobacterial adaptations to the intracellular environment. We identify 329 significantly differentially regulated genes, highlighting cholesterol catabolism, the methylcitrate cycle and iron homeostasis as important for mycobacteria inside macrophages. Examination of multi-functional gene families revealed that 35 PE/PPE genes and five cytochrome P450 genes were upregulated 24 h after infection, highlighting pathways of potential significance. Comparison of the intracellular transcriptome to gene essentiality and immunogenicity studies identified 15 potential targets that are both required for intracellular survival and induced on infection, and eight upregulated genes that have been demonstrated to be immunogenic in TB patients. Further insight into these new and established targets will support drug and vaccine development efforts.

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.

Biosynthesis of the redox cofactor mycofactocin is controlled by the transcriptional regulator MftR and induced by long-chain acyl-CoA species

Mycofactocin (MFT) is a ribosomally synthesized and post-translationally-modified redox cofactor found in pathogenic mycobacteria. While MFT biosynthetic proteins have been extensively characterized, the physiological conditions under which MFT biosynthesis is required are not well understood. To gain insights into the mechanisms of regulation of MFT expression in Mycobacterium smegmatis mc²155, we investigated the DNA-binding and ligand-binding activities of the putative TetR-like transcription regulator, MftR. In this study, we demonstrated that MftR binds to the mft promoter region. We used DNase I footprinting to identify the 27 bp palindromic operator located 5′ to mftA and found it to be highly conserved in Mycobacterium tuberculosis, Mycobacterium bovis, Mycobacterium ulcerans, and Mycobacterium marinum. To determine under which conditions the mft biosynthetic gene cluster (BGC) is induced, we screened for effectors of MftR. As a result, we found that MftR binds to long-chain acyl-CoAs with low micromolar affinities. To demonstrate that oleoyl-CoA induces the mft BGC in vivo, we re-engineered a fluorescent protein reporter system to express an MftA–mCherry fusion protein. Using this mCherry fluorescent readout, we show that the mft BGC is upregulated in M. smegmatis mc²155 when oleic acid is supplemented to the media. These results suggest that MftR controls expression of the mft BGC and that MFT production is induced by long-chain acyl-CoAs. Since MFT-dependent dehydrogenases are known to colocalize with acyl carrier protein/CoA-modifying enzymes, these results suggest that MFT might be critical for fatty acid metabolism or cell wall reorganization.

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.

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.

Mycobacterium tuberculosis (MTB) persists within the host by counteracting disparate stressors including hypoxia. Peterson et al. report a transcriptional program that coordinates sequential state transitions to drive MTB in and out of hypoxia-induced dormancy. Among varied properties, this program encodes advanced preparedness to infect the host in favorable conditions.

Best practices on the differential expression analysis of multi-species RNA-seq

Advances in transcriptome sequencing allow for simultaneous interrogation of differentially expressed genes from multiple species originating from a single RNA sample, termed dual or multi-species transcriptomics. Compared to single-species differential expression analysis, the design of multi-species differential expression experiments must account for the relative abundances of each organism of interest within the sample, often requiring enrichment methods and yielding differences in total read counts across samples. The analysis of multi-species transcriptomics datasets requires modifications to the alignment, quantification, and downstream analysis steps compared to the single-species analysis pipelines. We describe best practices for multi-species transcriptomics and differential gene expression.

Single START-domain protein Mtsp17 is involved in transcriptional regulation in Mycobacterium smegmatis

Tuberculosis caused by the pathogen Mycobacterium tuberculosis (MTB), remains a significant threat to global health. Elucidating the mechanisms of essential MTB genes provides an important theoretical basis for drug exploitation. Gene mtsp17 is essential and is conserved in the Mycobacterium genus. Although Mtsp17 has a structure closely resembling typical steroidogenic acute regulatory protein-related lipid transfer (START) family proteins, its biological function is different. This study characterizes the transcriptomes of Mycobacterium smegmatis to explore the consequences of mtsp17 downregulation on gene expression. Suppression of the mtsp17 gene resulted in significant down-regulation of 3% and upregulation of 1% of all protein-coding genes. Expression of desA1, an essential gene involved in mycolic acid synthesis, and the anti-SigF antagonist MSMEG_0586 were down-regulated in the conditional Mtsp17 knockout mutant and up-regulated in the Mtsp17 over-expression strain. Trends in the changes of 70 of the 79 differentially expressed genes (Log2 fold change > 1.5) in the conditional Mtsp17 knockout strain were the same as in the SigF knockout strain. Our data suggest that Mtsp17 is likely an activator of desA1 and Mtsp17 regulates the SigF regulon by SigF regulatory pathways through the anti-SigF antagonist MSMEG_0586. Our findings indicate the role of Mtsp17 may be in transcriptional regulation, provide new insights into the molecular mechanisms of START family proteins, and uncover a new node in the regulatory network of mycobacteria.

History and Future Perspectives on the Discipline of Quantitative Systems Pharmacology Modeling and Its Applications

Mathematical biology and pharmacology models have a long and rich history in the fields of medicine and physiology, impacting our understanding of disease mechanisms and the development of novel therapeutics. With an increased focus on the pharmacology application of system models and the advances in data science spanning mechanistic and empirical approaches, there is a significant opportunity and promise to leverage these advancements to enhance the development and application of the systems pharmacology field. In this paper, we will review milestones in the evolution of mathematical biology and pharmacology models, highlight some of the gaps and challenges in developing and applying systems pharmacology models, and provide a vision for an integrated strategy that leverages advances in adjacent fields to overcome these challenges.

Dual RNA-Seq of Mtb-Infected Macrophages In Vivo Reveals Ontologically Distinct Host-Pathogen Interactions

Dissecting the in vivo host-pathogen interplay is crucial to understanding the molecular mechanisms governing control or progression of intracellular infections. In this work, we explore the in vivo molecular dynamics of Mtb infection by performing dual RNA-seq on Mycobacterium tuberculosis-infected, ontogenetically distinct macrophage lineages isolated directly from murine lungs. We first define an in vivo signature of 180 genes specifically upregulated by Mtb in mouse lung macrophages, then we uncover a divergent transcriptional response of the bacteria between alveolar macrophages that appear to sustain Mtb growth through increased access to iron and fatty acids and interstitial macrophages that restrict Mtb growth through iron sequestration and higher levels of nitric oxide. We use an enrichment protocol for bacterial transcripts, which enables us to probe Mtb physiology at the host cell level in an in vivo environment, with broader application in understanding the infection dynamics of intracellular pathogens in general.

In this study Pisu et al. performed dual RNA-seq on Mycobacterium tuberculosis-infected, ontogenetically distinct macrophage lineages isolated directly from infected murine lungs. The transcriptional response of host and bacteria diverged between alveolar macrophages that sustain Mtb growth and interstitial macrophages that restrict Mtb growth.

Evolution of Drug-Resistant Mycobacterium tuberculosis Strains and Their Adaptation to the Human Lung Environment

In the last two decades, multi (MDR), extensively (XDR), extremely (XXDR) and total (TDR) drug-resistant Mycobacterium tuberculosis (M.tb) strains have emerged as a threat to public health worldwide, stressing the need to develop new tuberculosis (TB) prevention and treatment strategies. It is estimated that in the next 35 years, drug-resistant TB will kill around 75 million people and cost the global economy $16.7 trillion. Indeed, the COVID-19 pandemic alone may contribute with the development of 6.3 million new TB cases due to lack of resources and enforced confinement in TB endemic areas. Evolution of drug-resistant M.tb depends on numerous factors, such as bacterial fitness, strain's genetic background and its capacity to adapt to the surrounding environment, as well as host-specific and environmental factors. Whole-genome transcriptomics and genome-wide association studies in recent years have shed some insights into the complexity of M.tb drug resistance and have provided a better understanding of its underlying molecular mechanisms. In this review, we will discuss M.tb phenotypic and genotypic changes driving resistance, including changes in cell envelope components, as well as recently described intrinsic and extrinsic factors promoting resistance emergence and transmission. We will further explore how drug-resistant M.tb adapts differently than drug-susceptible strains to the lung environment at the cellular level, modulating M.tb-host interactions and disease outcome, and novel next generation sequencing (NGS) strategies to study drug-resistant TB.

Metabolic Versatility of Mycobacterium tuberculosis during Infection and Dormancy

Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB), is a highly successful intracellular pathogen with the ability to withstand harsh conditions and reside long-term within its host. In the dormant and persistent states, the bacterium tunes its metabolism and is able to resist the actions of antibiotics. One of the main strategies Mtb adopts is through its metabolic versatility-it is able to cometabolize a variety of essential nutrients and direct these nutrients simultaneously to multiple metabolic pathways to facilitate the infection of the host. Mtb further undergo extensive remodeling of its metabolic pathways in response to stress and dormancy. In recent years, advancement in systems biology and its applications have contributed substantially to a more coherent view on the intricate metabolic networks of Mtb. With a more refined appreciation of the roles of metabolism in mycobacterial infection and drug resistance, and the success of drugs targeting metabolism, there is growing interest in further development of anti-TB therapies that target metabolism, including lipid metabolism and oxidative phosphorylation. Here, we will review current knowledge revolving around the versatility of Mtb in remodeling its metabolism during infection and dormancy, with a focus on central carbon metabolism and lipid metabolism.

Targeted RNA sequencing enhances gene expression profiling of ultra-low input samples

RNA-seq is the standard method for profiling gene expression in many biological systems. Due to the wide dynamic range and complex nature of the transcriptome, RNA-seq provides an incomplete characterization, especially of lowly expressed genes and transcripts. Targeted RNA sequencing (RNA CaptureSeq) focuses sequencing on genes of interest, providing exquisite sensitivity for transcript detection and quantification. However, uses of CaptureSeq have focused on bulk samples and its performance on very small populations of cells is unknown. Here we show CaptureSeq greatly enhances transcriptomic profiling of target genes in ultra-low-input samples and provides equivalent performance to that on bulk samples. We validate the performance of CaptureSeq using multiple probe sets on samples of iPSC-derived cortical neurons. We demonstrate up to 275-fold enrichment for target genes, the detection of 10% additional genes and a greater than 5-fold increase in identified gene isoforms. Analysis of spike-in controls demonstrated CaptureSeq improved both detection sensitivity and expression quantification. Comparison to the CORTECON database of cerebral cortex development revealed CaptureSeq enhanced the identification of sample differentiation stage. CaptureSeq provides sensitive, reliable and quantitative expression measurements on hundreds-to-thousands of target genes from ultra-low-input samples and has the potential to greatly enhance transcriptomic profiling when samples are limiting.

PerSort Facilitates Characterization and Elimination of Persister Subpopulation in Mycobacteria

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.

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.

IMPORTANCEMycobacterium 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.

Alveolar macrophages generate a noncanonical NRF2-driven transcriptional response to Mycobacterium tuberculosis in vivo

Alveolar macrophages (AMs) are the first cells to be infected during Mycobacterium tuberculosis (M.tb.) infection. Thus, the AM response to infection is the first of many steps leading to initiation of the adaptive immune response required for efficient control of infection. A hallmark of M.tb. infection is the slow initiation of the adaptive response, yet the mechanisms responsible for this are largely unknown. To study the initial AM response to infection, we developed a system to identify, sort, and analyze M.tb.-infected AMs from the lung within the first 10 days of infection. In contrast to what has been previously described using in vitro systems, M.tb.-infected AMs up-regulate a cell-protective antioxidant transcriptional signature that is dependent on the lung environment but not bacterial virulence. Computational approaches including pathway analysis and transcription factor motif enrichment analysis identify NRF2 as a master regulator of the response. Using knockout mouse models, we demonstrate that NRF2 drives expression of the cell-protective signature in AMs and impairs the control of early bacterial growth. AMs up-regulate a substantial pro-inflammatory response to M.tb. infection only 10 days after infection, yet comparisons with bystander AMs from the same infected animals demonstrate that M.tb.-infected AMs generate a less robust inflammatory response than the uninfected cells around them. Our findings demonstrate that the initial macrophage response to M.tb. in the lung is far less inflammatory than has previously been described by in vitro systems and may impede the overall host response to infection.

The sensor kinase MtrB of Mycobacterium tuberculosis regulates hypoxic survival and establishment of infection

Paired two-component systems (TCSs), having a sensor kinase (SK) and a cognate response regulator (RR), enable the human pathogen Mycobacterium tuberculosis to respond to the external environment and to persist within its host. Here, we inactivated the SK gene of the TCS MtrAB, mtrB, generating the strain ΔmtrB We show that mtrB loss reduces the bacterium's ability to survive in macrophages and increases its association with autophagosomes and autolysosomes. Notably, the ΔmtrB strain was markedly defective in establishing lung infection in mice, with no detectable lung pathology following aerosol challenge. ΔmtrB was less able to withstand hypoxic and acid stresses and to form biofilms and had decreased viability under hypoxia. Transcriptional profiling of ΔmtrB by gene microarray analysis, validated by quantitative RT-PCR, indicated down-regulation of the hypoxia-associated dosR regulon, as well as genes associated with other pathways linked to adaptation of M. tuberculosis to the host environment. Using in vitro biochemical assays, we demonstrate that MtrB interacts with DosR (a noncognate RR) in a phosphorylation-independent manner. Electrophoretic mobility shift assays revealed that MtrB enhances the binding of DosR to the hspX promoter, suggesting an unexpected role of MtrB in DosR-regulated gene expression in M. tuberculosis Taken together, these findings indicate that MtrB functions as a regulator of DosR-dependent gene expression and in the adaptation of M. tuberculosis to hypoxia and the host environment. We propose that MtrB may be exploited as a chemotherapeutic target against tuberculosis.

Underestimated Manipulative Roles of Mycobacterium tuberculosis Cell Envelope Glycolipids During Infection

The Mycobacterium tuberculosis cell envelope has been evolving over time to make the bacterium transmissible and adaptable to the human host. In this context, the M. tuberculosis cell envelope contains a peripheral barrier full of lipids, some of them unique, which confer M. tuberculosis with a unique shield against the different host environments that the bacterium will encounter at the different stages of infection. This lipid barrier is mainly composed of glycolipids that can be characterized by three different subsets: trehalose-containing, mannose-containing, and 6-deoxy-pyranose-containing glycolipids. In this review, we explore the roles of these cell envelope glycolipids in M. tuberculosis virulence and pathogenesis, drug resistance, and further, how these glycolipids may dictate the M. tuberculosis cell envelope evolution from ancient to modern strains. Finally, we address how these M. tuberculosis cell envelope glycolipids are impacted by the host lung alveolar environment, their role in vaccination and masking host immunity, and subsequently the impact of these glycolipids in shaping how M. tuberculosis interacts with host cells, manipulating their immune response to favor the establishment of an infection.

Hybridization-based capture of pathogen mRNA enables paired host-pathogen transcriptional analysis

Dual transcriptional profiling of host and bacteria during infection is challenging due to the low abundance of bacterial mRNA. We report Pathogen Hybrid Capture (PatH-Cap), a method to enrich for bacterial mRNA and deplete bacterial rRNA simultaneously from dual RNA-seq libraries using transcriptome-specific probes. By addressing both the differential RNA content of the host relative to the infecting bacterium and the overwhelming abundance of uninformative structural RNAs (rRNA, tRNA) of both species in a single step, this approach enables analysis of very low-input RNA samples. By sequencing libraries before (pre-PatH-Cap) and after (post-PatH-Cap) enrichment, we achieve dual transcriptional profiling of host and bacteria, respectively, from the same sample. Importantly, enrichment preserves relative transcript abundance and increases the number of unique bacterial transcripts per gene in post-PatH-Cap libraries compared to pre-PatH-Cap libraries at the same sequencing depth, thereby decreasing the sequencing depth required to fully capture the transcriptional profile of the infecting bacteria. We demonstrate that PatH-Cap enables the study of low-input samples including single eukaryotic cells infected by 1-3 Pseudomonas aeruginosa bacteria and paired host-pathogen temporal gene expression analysis of Mycobacterium tuberculosis infecting macrophages. PatH-Cap can be applied to the study of a range of pathogens and microbial species, and more generally, to lowly-abundant species in mixed populations.

The mycobacterial cell envelope - a moving target

Mycobacterium tuberculosis, the leading cause of death due to infection, has a dynamic and immunomodulatory cell envelope. The cell envelope structurally and functionally varies across the length of the cell and during the infection process. This variability allows the bacterium to manipulate the human immune system, tolerate antibiotic treatment and adapt to the variable host environment. Much of what we know about the mycobacterial cell envelope has been gleaned from model actinobacterial species, or model conditions such as growth in vitro, in macrophages and in the mouse. In this Review, we combine data from different experimental systems to build a model of the dynamics of the mycobacterial cell envelope across space and time. We describe the regulatory pathways that control metabolism of the cell wall and surface lipids in M. tuberculosis during growth and stasis, and speculate about how this regulation might affect antibiotic susceptibility and interactions with the immune system.

Mycobacterium tuberculosis Metabolism

Mycobacterium tuberculosis is the cause of tuberculosis (TB), a disease which continues to overwhelm health systems in endemic regions despite the existence of effective combination chemotherapy and the widespread use of a neonatal anti-TB vaccine. For a professional pathogen, M. tuberculosis retains a surprisingly large proportion of the metabolic repertoire found in nonpathogenic mycobacteria with very different lifestyles. Moreover, evidence that additional functions were acquired during the early evolution of the M. tuberculosis complex suggests the organism has adapted (and augmented) the metabolic pathways of its environmental ancestor to persistence and propagation within its obligate human host. A better understanding of M. tuberculosis pathogenicity, however, requires the elucidation of metabolic functions under disease-relevant conditions, a challenge complicated by limited knowledge of the microenvironments occupied and nutrients accessed by bacilli during host infection, as well as the reliance in experimental mycobacteriology on a restricted number of experimental models with variable relevance to clinical disease. Here, we consider M. tuberculosis metabolism within the framework of an intimate host-pathogen coevolution. Focusing on recent advances in our understanding of mycobacterial metabolic function, we highlight unusual adaptations or departures from the better-characterized model intracellular pathogens. We also discuss the impact of these mycobacterial "innovations" on the susceptibility of M. tuberculosis to existing and experimental anti-TB drugs, as well as strategies for targeting metabolic pathways. Finally, we offer some perspectives on the key gaps in the current knowledge of fundamental mycobacterial metabolism and the lessons which might be learned from other systems.

Linking aberrant chromatin features in chronic lymphocytic leukemia to transcription factor networks

In chronic lymphocytic leukemia (CLL), a diverse set of genetic mutations is embedded in a deregulated epigenetic landscape that drives cancerogenesis. To elucidate the role of aberrant chromatin features, we mapped DNA methylation, seven histone modifications, nucleosome positions, chromatin accessibility, binding of EBF1 and CTCF, as well as the transcriptome of B cells from CLL patients and healthy donors. A globally increased histone deacetylase activity was detected and half of the genome comprised transcriptionally downregulated partially DNA methylated domains demarcated by CTCF. CLL samples displayed a H3K4me3 redistribution and nucleosome gain at promoters as well as changes of enhancer activity and enhancer linkage to target genes. A DNA binding motif analysis identified transcription factors that gained or lost binding in CLL at sites with aberrant chromatin features. These findings were integrated into a gene regulatory enhancer containing network enriched for B‐cell receptor signaling pathway components. Our study predicts novel molecular links to targets of CLL therapies and provides a valuable resource for further studies on the epigenetic contribution to the disease.

Antibody Fab-Fc properties outperform titer in predictive models of SIV vaccine-induced protection

Characterizing the antigen-binding and innate immune-recruiting properties of the humoral response offers the chance to obtain deeper insights into mechanisms of protection than revealed by measuring only overall antibody titer. Here, a high-throughput, multiplexed Fab-Fc Array was employed to profile rhesus macaques vaccinated with a gp120-CD4 fusion protein in combination with different genetically encoded adjuvants, and subsequently subjected to multiple heterologous simian immunodeficiency virus (SIV) challenges. Systems analyses modeling protection and adjuvant differences using Fab-Fc Array measurements revealed a set of correlates yielding strong and robust predictive performance, while models based on measurements of response magnitude alone exhibited significantly inferior performance. At the same time, rendering Fab-Fc measurements mathematically independent of titer had relatively little impact on predictive performance. Similar analyses for a distinct SIV vaccine study also showed that Fab-Fc measurements performed significantly better than titer. These results suggest that predictive modeling with measurements of antibody properties can provide detailed correlates with robust predictive power, suggest directions for vaccine improvement, and potentially enable discovery of mechanistic associations.

INKA, an integrative data analysis pipeline for phosphoproteomic inference of active kinases

Identifying hyperactive kinases in cancer is crucial for individualized treatment with specific inhibitors. Kinase activity can be discerned from global protein phosphorylation profiles obtained with mass spectrometry‐based phosphoproteomics. A major challenge is to relate such profiles to specific hyperactive kinases fueling growth/progression of individual tumors. Hitherto, the focus has been on phosphorylation of either kinases or their substrates. Here, we combined label‐free kinase‐centric and substrate‐centric information in an Integrative Inferred Kinase Activity (INKA) analysis. This multipronged, stringent analysis enables ranking of kinase activity and visualization of kinase–substrate networks in a single biological sample. To demonstrate utility, we analyzed (i) cancer cell lines with known oncogenes, (ii) cell lines in a differential setting (wild‐type versus mutant, +/− drug), (iii) pre‐ and on‐treatment tumor needle biopsies, (iv) cancer cell panel with available drug sensitivity data, and (v) patient‐derived tumor xenografts with INKA‐guided drug selection and testing. These analyses show superior performance of INKA over its components and substrate‐based single‐sample tool KARP, and underscore target potential of high‐ranking kinases, encouraging further exploration of INKA's functional and clinical value.

Tree-ensemble analysis assesses presence of multifurcations in single cell data

We introduce TreeTop, an algorithm for single cell data analysis to identify and assign a branching score to branch points in biological processes which may have multi‐level branching hierarchies. We demonstrate branch point identification for processes with varying topologies, including T‐cell maturation, B‐cell differentiation and hematopoiesis. Our analyses are consistent with recent experimental studies suggesting a shallower hierarchy of differentiation events in hematopoiesis, rather than the classical multi‐level hierarchy.