Reconstruction and topological characterization of the sigma factor regulatory network of Mycobacterium tuberculosis

Gene Regulatory Mechanism of Mycobacterium Tuberculosis during Dormancy

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb) complex, is a zoonotic disease that remains one of the leading causes of death worldwide. Latent tuberculosis infection reactivation is a challenging obstacle to eradicating TB globally. Understanding the gene regulatory network of Mtb during dormancy is important. This review discusses up-to-date information about TB gene regulatory networks during dormancy, focusing on the regulation of lipid and energy metabolism, dormancy survival regulator (DosR), White B-like (Wbl) family, Toxin-Antitoxin (TA) systems, sigma factors, and MprAB. We outline the progress in vaccine and drug development associated with Mtb dormancy.

Design of a tunable bacterial gene expression system using engineered σ factors

Extracytoplasmic function (ECF) σ factors selectively upregulate expression of specific genes in bacteria. These σ factors, belonging to the σ70 family, are much smaller than the primary, housekeeping σ factor with two helical domains that interact with the Pribnow box and the -35 element of the promoter DNA. Structural studies reveal that promoter specificity in a σ factor is determined by the interactions between a loop (L3) and the Pribnow box element. Similarly, the efficiency of transcription initiation is governed by the polypeptide linker between the two promoter-binding domains. Both these polypeptide segments are dynamic and poorly conserved among ECF σ factor homologs. This feature hitherto limited insights from protein-DNA interactions to be correlated with transcription initiation efficiency. Here, we describe an approach to characterize these features that govern the dynamic range of gene expression using chimeric Escherichia coli σE. The L3 loop and linker polypeptides in these σE chimeras were replaced by the corresponding segments from 10 annotated and functional Mycobacterium tuberculosis ECF σ's. In vitro and in vivo measurements to determine the effect of these polypeptide replacements provided an experimentally validated σE chimera- gene expression level data set. We illustrate the utility of this chimeric σE library in improving the efficiency of a biosynthetic pathway in E. coli. In a two-enzyme step, unaffected by feedback inhibition and substrate concentration, we show an increase in desired product levels by altering the relative intracellular levels of the target enzymes using this library of σ factors. The chimeric σE library thus demonstrates the feasibility of engineering σ factors to achieve bespoke expression levels of target genes for diverse applications in synthetic microbiology.

IMPORTANCE

The synthesis of organic compounds involves the action of multiple enzymes in a biosynthetic pathway. Incorporating such biosynthetic pathways into microbes often leads to substantial cellular and metabolic stress resulting in low titers of the target compound. This limitation can be offset, in part, by optimizing enzyme efficiency and cellular enzyme concentration. The former involves significant efforts to achieve improvements in catalytic efficiency with the caveat that the metabolic load on a microbial cell imposed by the overexpression of the exogenous enzyme could result in reduced cell fitness. Here, we demonstrate the feasibility of engineered σ factors to modulate gene expression levels without significant genetic engineering. We note that changing the sequence of two flexible polypeptide loops without any changes to the structural scaffold of the transcription initiation factor σE could modulate the expression levels of the target genes. This ability provides a route to improve the efficiency of a biosynthetic pathway without altering the overall genomic makeup. The σE chimera library thus provides an avenue for pre-determined conditional gene expression of specific genes in Escherichia coli.

Adaptation of the Mycobacterium tuberculosis transcriptome to biofilm growth

Mycobacterium tuberculosis (M. tb), the causative agent of tuberculosis (TB), is a leading global cause of death from infectious disease. Biofilms are increasingly recognized as a relevant growth form during M. tb infection and may impede treatment by enabling bacterial drug and immune tolerance. M. tb has a complicated regulatory network that has been well-characterized for many relevant disease states, including dormancy and hypoxia. However, despite its importance, our knowledge of the genes and pathways involved in biofilm formation is limited. Here we characterize the biofilm transcriptomes of fully virulent clinical isolates and find that the regulatory systems underlying biofilm growth vary widely between strains and are also distinct from regulatory programs associated with other environmental cues. We used experimental evolution to investigate changes to the transcriptome during adaptation to biofilm growth and found that the application of a uniform selection pressure resulted in loss of strain-to-strain variation in gene expression, resulting in a more uniform biofilm transcriptome. The adaptive trajectories of transcriptomes were shaped by the genetic background of the M. tb population leading to convergence on a sub-lineage specific transcriptome. We identified widespread upregulation of non-coding RNA (ncRNA) as a common feature of the biofilm transcriptome and hypothesize that ncRNA function in genome-wide modulation of gene expression, thereby facilitating rapid regulatory responses to new environments. These results reveal a new facet of the M. tb regulatory system and provide valuable insight into how M. tb adapts to new environments.

Molecular insight into thymoquinone mechanism of action against Mycobacterium tuberculosis

Natural products are promising antimicrobials, usually having multiple and different cellular targets than synthetic antibiotics. Their influence on bacteria at various metabolic and functional levels contributes to higher efficacy even against drug-resistant strains. One such compound is a naturally occurring p-benzoquinone - thymoquinone. It is effective against different bacteria, including multidrug-resistant and extremely drug-resistant Mycobacterium tuberculosis. Its antibacterial mechanism of action was studied in several bacterial species except mycobacteria. To get an insight into the antimycobacterial activity of thymoquinone at the molecular level, we performed metabolomic and transcriptomic analyzes of bacteria exposed to this compound. The expression of genes coding stress-responsive sigma factors revealed that thymoquinone rapidly induces the production of sigE transcripts. At the same time, prolonged influence results in the overexpression of all sigma factor genes and significantly upregulates sigF. The metabolomic analysis confirmed that the antimycobacterial activity of thymoquinone was related to the depletion of NAD and ATP pools and the downregulation of plasma membrane lipids. This state was observed after 24 h and was persistent the next day, suggesting that bacteria could not activate catabolic mechanisms and produce energy. Additionally, the presence of a thymoquinone nitrogen derivative in the bacterial broth and the culture was reported.

Sulphides from garlic essential oil dose-dependently change the distribution of glycerophospholipids and induce N6-tuberculosinyladenosine formation in mycobacterial cells

The antimicrobial properties of garlic are widely known, and numerous studies confirmed its ability to inhibit the growth of Mycobacterium tuberculosis. In this work, we explored the molecular mechanism of action of sulphides present in garlic essential oil against mycobacteria. The targeted transcriptomics and untargeted LC-MS metabolomics were applied to study dose- and time-dependent metabolic changes in bacterial cells under the influence of stressing agent. Expression profiles of genes coding stress-responsive sigma factors regulatory network and metabolic observations proved that sulphides from garlic essential oil are an efficient and specific agent affecting glycerophospholipids levels and their distribution within the cell envelope. Additionally, sulphides induced the Dimroth rearrangement of 1-Tuberculosinyladenosine to N6-tuberculosinyladenosine in mycobacterial cells as a possible neutralization mechanism protecting the cell from a basic nucleophilic environment. Sulphides affected cell envelope lipids and formation of N6-tuberculosinyladenosine in M. tuberculosis.

The Pre-Adaptation of a Stroke-Specific Self-Management Program Among Older Adults

Objectives: Managing multimorbidity as aging stroke patients is complex; standard self-management programs necessitate adaptations. We used visual analytics to examine complex relationships among aging stroke survivors' comorbidities. These findings informed pre-adaptation of a component of the Chronic Disease Self-Management Program. Methods: Secondary analysis of 2013-2014 Medicare claims with stroke as an index condition, hospital readmission within 90 days (n = 42,938), and 72 comorbidities. Visual analytics identified patient subgroups and co-occurring comorbidities. Guided by the framework for reporting adaptations and modifications to evidence-based interventions, an interdisciplinary team developed vignettes that highlighted multimorbidity to customize the self-management program. Results: There were five significant subgroups (z = 6.19, p < .001) of comorbidities such as obesity and cancer. We constructed 6 vignettes based on the 5 subgroups. Discussion: Aging stroke patients often face substantial disease-management hurdles. We used visual analytics to inform pre-adaptation of a self-management program to fit the needs of older adult stroke survivors.

Exposure of Mycobacterium tuberculosis to human alveolar lining fluid shows temporal and strain-specific adaptation to the lung environment

Upon infection, Mycobacterium tuberculosis ( M.tb ) reaches the alveolar space and comes in close contact with human alveolar lining fluid (ALF) for an uncertain period of time prior to its encounter with alveolar cells. We showed that homeostatic ALF hydrolytic enzymes modify the M.tb cell envelope, driving M.tb -host cell interactions. Still, the contribution of ALF during M.tb infection is poorly understood. Here, we exposed 4 M.tb strains with different levels of virulence, transmissibility, and drug resistance (DR) to physiological concentrations of human ALF for 15-min and 12-h, and performed RNA sequencing. Gene expression analysis showed a temporal and strain-specific adaptation to human ALF. Differential expression (DE) of ALF-exposed vs. unexposed M.tb revealed a total of 397 DE genes associated with lipid metabolism, cell envelope and processes, intermediary metabolism and respiration, and regulatory proteins, among others. Most DE genes were detected at 12-h post-ALF exposure, with DR- M.tb strain W-7642 having the highest number of DE genes. Interestingly, genes from the KstR2 regulon, which controls the degradation of cholesterol C and D rings, were significantly upregulated in all strains post-ALF exposure. These results indicate that M.tb -ALF contact drives initial metabolic and physiologic changes in M.tb , with potential implications in infection outcome.

IMPORTANCE

Tuberculosis, caused by airborne pathogen Mycobacterium tuberculosis ( M.tb ), is one of the leading causes of mortality worldwide. Upon infection, M.tb reaches the alveoli and gets in contact with human alveolar lining fluid (ALF), where ALF hydrolases modify the M.tb cell envelope driving subsequent M.tb -host cell interactions. Still, the contributions of ALF during infection are poorly understood. We exposed 4 M.tb strains to ALF for 15-min and 12-h and performed RNA sequencing, demonstrating a temporal and strain-specific adaptation of M.tb to ALF. Interestingly, genes associated with cholesterol degradation were highly upregulated in all strains. This study shows for the first time that ALF drives global metabolic changes in M.tb during the initial stages of the infection, with potential implications in disease outcome. Biologically relevant networks and common and strain-specific bacterial determinants derived from this study could be further investigated as potential therapeutic candidates.

The Rip1 intramembrane protease contributes to iron and zinc homeostasis in Mycobacterium tuberculosis

Mycobacterium tuberculosis is exposed to a variety of stresses during a chronic infection, as the immune system simultaneously produces bactericidal compounds and starves the pathogen of essential nutrients. The intramembrane protease, Rip1, plays an important role in the adaptation to these stresses, at least partially by the cleavage of membrane-bound transcriptional regulators. Although Rip1 is known to be critical for surviving copper intoxication and nitric oxide exposure, these stresses do not fully account for the regulatory protein's essentiality during infection. In this work, we demonstrate that Rip1 is also necessary for growth in low-iron and low-zinc conditions, similar to those imposed by the immune system. Using a newly generated library of sigma factor mutants, we show that the known regulatory target of Rip1, SigL, shares this defect. Transcriptional profiling under iron-limiting conditions supported the coordinated activity of Rip1 and SigL and demonstrated that the loss of these proteins produces an exaggerated iron starvation response. These observations demonstrate that Rip1 coordinates several aspects of metal homeostasis and suggest that a Rip1- and SigL-dependent pathway is necessary to thrive in the iron-deficient environments encountered during infection. IMPORTANCE Metal homeostasis represents a critical point of interaction between the mammalian immune system and potential pathogens. While the host attempts to intoxicate microbes with high concentrations of copper or starve the invader of iron and zinc, successful pathogens have acquired mechanisms to overcome these defenses. Our work identifies a regulatory pathway consisting of the Rip1 intramembrane protease and the sigma factor, SigL, that is essential for the important human pathogen, Mycobacterium tuberculosis, to grow in low-iron or low-zinc conditions such as those encountered during infection. In conjunction with Rip1's known role in resisting copper toxicity, our work implicates this protein as a critical integration point that coordinates the multiple metal homeostatic systems required for this pathogen to survive in host tissue.

Adaptation of the Mycobacterium tuberculosis transcriptome to biofilm growth

Mycobacterium tuberculosis ( M. tb ), the causative agent of tuberculosis (TB), is a leading global cause of death from infectious disease. Biofilms are increasingly recognized as a relevant growth form during M. tb infection and may impede treatment by enabling bacterial drug and immune tolerance. M. tb has a complicated regulatory network that has been well-characterized for many relevant disease states, including dormancy and hypoxia. However, despite its importance, our knowledge of the genes and pathways involved in biofilm formation is limited. Here we characterize the biofilm transcriptomes of fully virulent clinical isolates and find that the regulatory systems underlying biofilm growth vary widely between strains and are also distinct from regulatory programs associated with other environmental cues. We used experimental evolution to investigate changes to the transcriptome during adaptation to biofilm growth and found that the application of a uniform selection pressure resulted in loss of strain-to-strain variation in gene expression, resulting in a more uniform biofilm transcriptome. The adaptive trajectories of transcriptomes were shaped by the genetic background of the M. tb population leading to convergence on a sub-lineage specific transcriptome. We identified widespread upregulation of non-coding RNA (ncRNA) as a common feature of the biofilm transcriptome and hypothesize that ncRNA function in genome-wide modulation of gene expression, thereby facilitating rapid regulatory responses to new environments. These results reveal a new facet of the M. tb regulatory system and provide valuable insight into how M. tb adapts to new environments.

Importance

Understanding mechanisms of resistance and tolerance in Mycobacterium tuberculosis ( M. tb ) can help us develop new treatments that capitalize on M. tb 's vulnerabilities. Here we used transcriptomics to study both the regulation of biofilm formation in clinical isolates as well as how those regulatory systems adapt to new environments. We find that closely related clinical populations have diverse strategies for growth under biofilm conditions, and that genetic background plays a large role in determining the trajectory of evolution. These results have implications for future treatment strategies that may be informed by our knowledge of the evolutionary constraints on strain(s) from an individual infection. This work provides new information about the mechanisms of biofilm formation in M. tb and outlines a framework for population level approaches for studying bacterial adaptation.

Subtyping Social Determinants of Health in All of Us: Network Analysis and Visualization Approach

Background

Social determinants of health (SDoH), such as financial resources and housing stability, account for between 30-55% of people's health outcomes. While many studies have identified strong associations among specific SDoH and health outcomes, most people experience multiple SDoH that impact their daily lives. Analysis of this complexity requires the integration of personal, clinical, social, and environmental information from a large cohort of individuals that have been traditionally underrepresented in research, which is only recently being made available through the All of Us research program. However, little is known about the range and response of SDoH in All of Us, and how they co-occur to form subtypes, which are critical for designing targeted interventions.

Objective

To address two research questions: (1) What is the range and response to survey questions related to SDoH in the All of Us dataset? (2) How do SDoH co-occur to form subtypes, and what are their risk for adverse health outcomes?

Methods

For Question-1, an expert panel analyzed the range of SDoH questions across the surveys with respect to the 5 domains in Healthy People 2030 (HP-30), and analyzed their responses across the full All of Us data (n=372,397, V6). For Question-2, we used the following steps: (1) due to the missingness across the surveys, selected all participants with valid and complete SDoH data, and used inverse probability weighting to adjust their imbalance in demographics compared to the full data; (2) an expert panel grouped the SDoH questions into SDoH factors for enabling a more consistent granularity; (3) used bipartite modularity maximization to identify SDoH biclusters, their significance, and their replicability; (4) measured the association of each bicluster to three outcomes (depression, delayed medical care, emergency room visits in the last year) using multiple data types (surveys, electronic health records, and zip codes mapped to Medicaid expansion states); and (5) the expert panel inferred the subtype labels, potential mechanisms that precipitate adverse health outcomes, and interventions to prevent them.

Results

For Question-1, we identified 110 SDoH questions across 4 surveys, which covered all 5 domains in HP-30. However, the results also revealed a large degree of missingness in survey responses (1.76%-84.56%), with later surveys having significantly fewer responses compared to earlier ones, and significant differences in race, ethnicity, and age of participants of those that completed the surveys with SDoH questions, compared to those in the full All of Us dataset. Furthermore, as the SDoH questions varied in granularity, they were categorized by an expert panel into 18 SDoH factors. For Question-2, the subtype analysis (n=12,913, d=18) identified 4 biclusters with significant biclusteredness (Q=0.13, random-Q=0.11, z=7.5, P<0.001), and significant replication (Real-RI=0.88, Random-RI=0.62, P<.001). Furthermore, there were statistically significant associations between specific subtypes and the outcomes, and with Medicaid expansion, each with meaningful interpretations and potential targeted interventions. For example, the subtype Socioeconomic Barriers included the SDoH factors not employed, food insecurity, housing insecurity, low income, low literacy, and low educational attainment, and had a significantly higher odds ratio (OR=4.2, CI=3.5-5.1, P-corr<.001) for depression, when compared to the subtype Sociocultural Barriers. Individuals that match this subtype profile could be screened early for depression and referred to social services for addressing combinations of SDoH such as housing insecurity and low income. Finally, the identified subtypes spanned one or more HP-30 domains revealing the difference between the current knowledge-based SDoH domains, and the data-driven subtypes.

Conclusions

The results revealed that the SDoH subtypes not only had statistically significant clustering and replicability, but also had significant associations with critical adverse health outcomes, which had translational implications for designing targeted SDoH interventions, decision-support systems to alert clinicians of potential risks, and for public policies. Furthermore, these SDoH subtypes spanned multiple SDoH domains defined by HP-30 revealing the complexity of SDoH in the real-world, and aligning with influential SDoH conceptual models such as by Dahlgren-Whitehead. However, the high-degree of missingness warrants repeating the analysis as the data becomes more complete. Consequently we designed our machine learning code to be generalizable and scalable, and made it available on the All of Us workbench, which can be used to periodically rerun the analysis as the dataset grows for analyzing subtypes related to SDoH, and beyond.

Mycobacterial Regulatory Systems Involved in the Regulation of Gene Expression Under Respiration-Inhibitory Conditions

Mycobacterium tuberculosis is the causative agent of tuberculosis. M. tuberculosis can survive in a dormant state within the granuloma, avoiding the host-mounting immune attack. M. tuberculosis bacilli in this state show increased tolerance to antibiotics and stress conditions, and thus the transition of M. tuberculosis to the nonreplicating dormant state acts as an obstacle to tuberculosis treatment. M. tuberculosis in the granuloma encounters hostile environments such as hypoxia, nitric oxide, reactive oxygen species, low pH, and nutrient deprivation, etc., which are expected to inhibit respiration of M. tuberculosis. To adapt to and survive in respiration-inhibitory conditions, it is required for M. tuberculosis to reprogram its metabolism and physiology. In order to get clues to the mechanism underlying the entry of M. tuberculosis to the dormant state, it is important to understand the mycobacterial regulatory systems that are involved in the regulation of gene expression in response to respiration inhibition. In this review, we briefly summarize the information regarding the regulatory systems implicated in upregulation of gene expression in mycobacteria exposed to respiration-inhibitory conditions. The regulatory systems covered in this review encompass the DosSR (DevSR) two-component system, SigF partner switching system, MprBA-SigE-SigB signaling pathway, cAMP receptor protein, and stringent response.

SigE: A master regulator of Mycobacterium tuberculosis

The Extracellular function (ECF) sigma factor SigE is one of the best characterized out of the 13 sigma factors encoded in the Mycobacterium tuberculosis chromosome. SigE is required for blocking phagosome maturation and full virulence in both mice and guinea pigs. Moreover, it is involved in the response to several environmental stresses as surface stress, oxidative stress, acidic pH, and phosphate starvation. Underscoring its importance in M. tuberculosis physiology, SigE is subjected to a very complex regulatory system: depending on the environmental conditions, its expression is regulated by three different sigma factors (SigA, SigE, and SigH) and a two-component system (MprAB). SigE is also regulated at the post-translational level by an anti-sigma factor (RseA) which is regulated by the intracellular redox potential and by proteolysis following phosphorylation from PknB upon surface stress. The set of genes under its direct control includes other regulators, as SigB, ClgR, and MprAB, and genes involved in surface remodeling and stabilization. Recently SigE has been shown to interact with PhoP to activate a subset of genes in conditions of acidic pH. The complex structure of its regulatory network has been suggested to result in a bistable switch leading to the development of heterogeneous bacterial populations. This hypothesis has been recently reinforced by the finding of its involvement in the development of persister cells able to survive to the killing activity of several drugs.

A Framework for Modeling and Interpreting Patient Subgroups Applied to Hospital Readmission: Visual Analytical Approach

BACKGROUND

A primary goal of precision medicine is to identify patient subgroups and infer their underlying disease processes with the aim of designing targeted interventions. Although several studies have identified patient subgroups, there is a considerable gap between the identification of patient subgroups and their modeling and interpretation for clinical applications.

OBJECTIVE

This study aimed to develop and evaluate a novel analytical framework for modeling and interpreting patient subgroups (MIPS) using a 3-step modeling approach: visual analytical modeling to automatically identify patient subgroups and their co-occurring comorbidities and determine their statistical significance and clinical interpretability; classification modeling to classify patients into subgroups and measure its accuracy; and prediction modeling to predict a patient's risk of an adverse outcome and compare its accuracy with and without patient subgroup information.

METHODS

The MIPS framework was developed using bipartite networks to identify patient subgroups based on frequently co-occurring high-risk comorbidities, multinomial logistic regression to classify patients into subgroups, and hierarchical logistic regression to predict the risk of an adverse outcome using subgroup membership compared with standard logistic regression without subgroup membership. The MIPS framework was evaluated for 3 hospital readmission conditions: chronic obstructive pulmonary disease (COPD), congestive heart failure (CHF), and total hip arthroplasty/total knee arthroplasty (THA/TKA) (COPD: n=29,016; CHF: n=51,550; THA/TKA: n=16,498). For each condition, we extracted cases defined as patients readmitted within 30 days of hospital discharge. Controls were defined as patients not readmitted within 90 days of discharge, matched by age, sex, race, and Medicaid eligibility.

RESULTS

In each condition, the visual analytical model identified patient subgroups that were statistically significant (Q=0.17, 0.17, 0.31; P<.001, <.001, <.05), significantly replicated (Rand Index=0.92, 0.94, 0.89; P<.001, <.001, <.01), and clinically meaningful to clinicians. In each condition, the classification model had high accuracy in classifying patients into subgroups (mean accuracy=99.6%, 99.34%, 99.86%). In 2 conditions (COPD and THA/TKA), the hierarchical prediction model had a small but statistically significant improvement in discriminating between readmitted and not readmitted patients as measured by net reclassification improvement (0.059, 0.11) but not as measured by the C-statistic or integrated discrimination improvement.

CONCLUSIONS

Although the visual analytical models identified statistically and clinically significant patient subgroups, the results pinpoint the need to analyze subgroups at different levels of granularity for improving the interpretability of intra- and intercluster associations. The high accuracy of the classification models reflects the strong separation of patient subgroups, despite the size and density of the data sets. Finally, the small improvement in predictive accuracy suggests that comorbidities alone were not strong predictors of hospital readmission, and the need for more sophisticated subgroup modeling methods. Such advances could improve the interpretability and predictive accuracy of patient subgroup models for reducing the risk of hospital readmission, and beyond.

M. tuberculosis Transcription Machinery: A Review on the Mycobacterial RNA Polymerase and Drug Discovery Efforts

Mycobacterium tuberculosis (MTB) is the main source of tuberculosis (TB), one of the oldest known diseases in the human population. Despite the drug discovery efforts of past decades, TB is still one of the leading causes of mortality and claimed more than 1.5 million lives worldwide in 2020. Due to the emergence of drug-resistant strains and patient non-compliance during treatments, there is a pressing need to find alternative therapeutic agents for TB. One of the important areas for developing new treatments is in the inhibition of the transcription step of gene expression; it is the first step to synthesize a copy of the genetic material in the form of mRNA. This further translates to functional protein synthesis, which is crucial for the bacteria living processes. MTB contains a bacterial DNA-dependent RNA polymerase (RNAP), which is the key enzyme for the transcription process. MTB RNAP has been targeted for designing and developing antitubercular agents because gene transcription is essential for the mycobacteria survival. Initiation, elongation, and termination are the three important sequential steps in the transcription process. Each step is complex and highly regulated, involving multiple transcription factors. This review is focused on the MTB transcription machinery, especially in the nature of MTB RNAP as the main enzyme that is regulated by transcription factors. The mechanism and conformational dynamics that occur during transcription are discussed and summarized. Finally, the current progress on MTB transcription inhibition and possible drug target in mycobacterial RNAP are also described to provide insight for future antitubercular drug design and development.

Pyridine-N-Oxide Alkaloids from Allium stipitatum and Their Synthetic Disulfide Analogs as Potential Drug Candidates against Mycobacterium tuberculosis: A Molecular Docking, QSBAR, and ADMET Prediction Approach

In this study, we consider pyridine-N-oxide alkaloids from Allium stipitatum and their synthetic disulfide analogs (PDAs) as candidates for next-generational antimycobacterial agents, in light of growing resistance to existing conventional therapies. In silico studies involving molecular docking simulations of 12 PDAs were carried out against 7 Mycobacterium tuberculosis target proteins (MTs) to determine their theoretical binding affinities. Compounds A3, A6, and B9 demonstrated stronger binding affinities on similar MTs. Molecular descriptors (MDs) describing structural and physicochemical properties of the compounds were also calculated using ChemDes, explored using Pearson's correlation analysis, and principal component analysis (PCA) in comparison with MDs from conventional antitubercular medicines. The PDAs possessed similar scores as isoniazid and pyrazinamide. The MDs were also used to conduct a quantitative structure-binding affinity relationship (QSBAR) study by building good fit and significant models through principal component regression (PCR) and partial least squares regression (PLSR). Leave-one-out cross-validation was adopted in the PLSR, resulting in good predictive models on all MTs (range of R² = 0.7541‐0.8992; range of Q² = 0.6183‐0.8162). Both PCR and PLSR models predicted the significant effects of ndonr, Hy, Mol wt, nhev, nring, ndb, Log P, W, Pol, ISIZ, TIAC, Getov, and UI on the binding of ligands to the MTs. In silico prediction of PDAs' ADMET profiles was conducted with QikProp utility. The ADMET profiles of the compounds were favorable. The outcome of the current study strengthens the significance of these compounds as promising lead candidates for the treatment of multidrug-resistant tuberculosis.

Exposure to Nepalese Propolis Alters the Metabolic State of Mycobacterium tuberculosis

Propolis is a natural product proved to be efficient against Mycobacterium tuberculosis. Although it is produced by bees, its active alcoholic-aqueous fraction contains plant-derived molecules. To gain some insight into its mechanism of antimycobacterial activity, we studied the metabolic changes in bacterial cells treated with extract of Trigona sp. propolis from Nepal. The detailed metabolomic and transcriptomic analysis performed in this study indicated target points in bacterial cells under propolis extract influence. The profile of lipids forming the outer and middle layer of the mycobacterial cell envelope was not changed by propolis treatment, however, fluctuations in the profiles of amphipathic glycerophospholipids were observed. The enrichment analysis revealed bacterial metabolic pathways affected by Trigona sp. propolis treatment. The early metabolic response involved much more pathways than observed after 48 h of incubation, however, the highest enrichment ratio was observed after 48 h, indicating the long-lasting influence of propolis. The early bacterial response was related to the increased demand for energy and upregulation of molecules involved in the formation of the cell membrane. The transcriptomic analysis confirmed that bacteria also suffered from oxidative stress, which was more pronounced on the second day of exposure. This was the first attempt to explain the action of Nepalese propolis extract against mycobacteria.

Rapid adaptation of a complex trait during experimental evolution of Mycobacterium tuberculosis

Tuberculosis (TB), caused by Mycobacterium tuberculosis (M. tb), is a leading cause of death due to infectious disease. TB is not traditionally associated with biofilms, but M. tb biofilms are linked with drug and immune tolerance and there is increasing recognition of their contribution to the recalcitrance of TB infections. Here, we used M. tb experimental evolution to investigate this complex phenotype and identify candidate loci controlling biofilm formation. We identified novel candidate loci, adding to our understanding of the genetic architecture underlying M. tb biofilm development. Under selective pressure to grow as a biofilm, regulatory mutations rapidly swept to fixation and were associated with changes in multiple traits, including extracellular matrix production, cell size, and growth rate. Genetic and phenotypic paths to enhanced biofilm growth varied according to the genetic background of the parent strain, suggesting that epistatic interactions are important in M. tb adaptation to changing environments.

Expression, Purification, and In Silico Characterization of Mycobacterium smegmatis Alternative Sigma Factor SigB

Sigma factor B (SigB), an alternative sigma factor (ASF), is very similar to primary sigma factor SigA (σ ⁷⁰) but dispensable for growth in both Mycobacterium smegmatis (Msmeg) and Mycobacterium tuberculosis (Mtb). It is involved in general stress responses including heat, oxidative, surface, starvation stress, and macrophage infections. Despite having an extremely short half-life, SigB tends to operate downstream of at least three stress-responsive extra cytoplasmic function (ECF) sigma factors (SigH, SigE, SigL) and SigF involved in multiple signaling pathways. There is very little information available regarding the regulation of SigB sigma factor and its interacting protein partners. Hence, we cloned the SigB gene into pET28a vector and optimized its expression in three different strains of E. coli, viz., (BL21 (DE3), C41 (DE3), and CodonPlus (DE3)). We also optimized several other parameters for the expression of recombinant SigB including IPTG concentration, temperature, and time duration. We achieved the maximum expression of SigB at 25°C in the soluble fraction of the cell which was purified by affinity chromatography using Ni-NTA and further confirmed by Western blotting. Further, structural characterization demonstrates the instability of SigB in comparison to SigA that is carried out using homology modeling and structure function relationship. We have done protein-protein docking of RNA polymerase (RNAP) of Msmeg and SigB. This effort provides a platform for pulldown assay, structural, and other studies with the recombinant protein to deduce the SigB interacting proteins, which might pave the way to study its signaling networks along with its regulation.

System-Level Analysis of Transcriptional and Translational Regulatory Elements in Streptomyces griseus

Bacteria belonging to Streptomyces have the ability to produce a wide range of secondary metabolites through a shift from primary to secondary metabolism regulated by complex networks activated after vegetative growth terminates. Despite considerable effort to understand the regulatory elements governing gene expression related to primary and secondary metabolism in Streptomyces, system-level information remains limited. In this study, we integrated four multi-omics datasets from Streptomyces griseus NBRC 13350: RNA-seq, ribosome profiling, dRNA-seq, and Term-Seq, to analyze the regulatory elements of transcription and translation of differentially expressed genes during cell growth. With the functional enrichment of gene expression in different growth phases, one sigma factor regulon and four transcription factor regulons governing differential gene transcription patterns were found. In addition, the regulatory elements of transcription termination and post-transcriptional processing at transcript 3′-end positions were elucidated, including their conserved motifs, stem-loop RNA structures, and non-terminal locations within the polycistronic operons, and the potential regulatory elements of translation initiation and elongation such as 5′-UTR length, RNA structures at ribosome-bound sites, and codon usage were investigated. This comprehensive genetic information provides a foundational genetic resource for strain engineering to enhance secondary metabolite production in Streptomyces.

Streptomyces clavuligerus: The Omics Era

The Streptomyces clavuligerus genome consists in a linear chromosome of about 6.7 Mb and four plasmids (pSCL1 to pSCL4), the latter one of 1.8 Mb. Deletion of pSCL4, results in viable mutants with high instability in the chromosome arms, which may lead to chromosome circularisation. Transcriptomic and proteomic studies comparing different mutants with the wild-type strain improved our knowledge on the biosynthesis and regulation of clavulanic acid, cephamycin C and holomycin. Additional knowledge has been obtained on the SARP-type CcaR activator and the network of connections with other regulators (Brp, AreB, AdpA, BldG, RelA) controlling ccaR expression. The transcriptional pattern of the cephamycin and clavulanic acid clusters is supported by the binding of CcaR to different promoters and confirmed that ClaR is a CcaR-dependent activator that controls the late steps of clavulanic biosynthesis. Metabolomic studies allowed the detection of new metabolites produced by S. clavuligerus such as naringenin, desferroxamines, several N-acyl tunicamycins, the terpenes carveol and cuminyl alcohol or bafilomycin J. Heterologous expression of S. clavuligerus terpene synthases resulted in the formation of no less than 15 different terpenes, although none of them was detected in S. clavuligerus culture broth. In summary, application of the Omic tools results in a better understanding of the molecular biology of S. clavuligerus, that allows the use of this strain as an industrial actinobacterial platform and helps to improve CA production.

Proline-Glutamate/Proline-Proline-Glutamate (PE/PPE) proteins of Mycobacterium tuberculosis: The multifaceted immune-modulators

The PE/PPE proteins encoded by seven percent (7%) of Mycobacterium tuberculosis (Mtb) genome are the chief constituents to pathogen's virulence reservoir. The fact that these genes have evolved along ESX secretory system in pathogenic Mtb strains make their investigation very intriguing. There is lot of speculation about the prominent role of these proteins at host pathogen interface and in disease pathogenesis. Nevertheless, the exact function of PE/PPE proteins still remains a mystery which calls for further research targeting these proteins. This article is an effort to document all the facts known so far with regard to these unique proteins which involves their origin, evolution, transcriptional control, and most important their role as host immune-modulators. Our understanding strongly points towards the versatile nature of these PE/PPE proteins as Mtb's host immune sensors and as decisive factors in shaping the outcome of infection. Further investigation on these proteins will surely pave way for newer and effective vaccines and therapeutics to control Tuberculosis (TB).

Tanshinones from Salvia miltiorrhiza inhibit Mycobacterium tuberculosis via disruption of the cell envelope surface and oxidative stress

The unique structure of Mycobacterium tuberculosis cell envelope provides impermeable barrier against environmental stimuli. In the situation that this barrier is disturbed Mycobacteria react at the transcriptional and translational level to redirect metabolic processes and to maintain integrity of the cell. In this work we aimed to explore the early metabolic response of M. tuberculosis to tanshinones, which are active antimycobacterial compounds of Salvia miltiorrhiza Bunge root. The investigation of the expression of sigma factors revealed the significant shifts in the general bacterial regulatory network, whereas LC-MS metabolomics evidenced the changes in the composition of bacterial cell envelope and indicated altered metabolic pathways. Tanshinones acted via the disruption of the cell envelope surface and generation of reactive oxygen species. Bacteria responded with overproduction of inner region of outer membrane, fluctuations in the production of glycerophosphoinositolglycans, as well as changes in the levels of mycobactins, accompanied by enrichment of metabolic pathways related to redox balance and repair of damages caused by tanshinones.

Usnic Acid Treatment Changes the Composition of Mycobacterium tuberculosis Cell Envelope and Alters Bacterial Redox Status

Mycobacterium tuberculosis developed efficient adaptation mechanisms in response to different environmental conditions. This resulted in the ability to survive in human macrophages and in resistance to numerous antibiotics. To get insight into bacterial responses to potent antimycobacterial natural compounds, we tested how usnic acid, a lichen-derived secondary metabolite, would influence mycobacteria at transcriptomic and metabolomic levels. The analysis of expression of sigma factors revealed a profound impact of usnic acid on one of the primary genetic regulatory systems of M. tuberculosis Combined liquid chromatography-mass spectrometry and nuclear magnetic resonance analyses allowed us to observe the perturbations in metabolic pathways, as well as in lipid composition, which took place within 24 h of exposure. Early bacterial response was related to redox homeostasis, lipid synthesis, and nucleic acid repair. Usnic acid treatment provoked disturbances of redox state in mycobacterial cells and increased production of structural elements of the cell wall and cell membrane. In addition, to increase the number of molecules related to restoration of redox balance, the rearrangements of the cell envelope were the first defense mechanisms observed under usnic acid treatment.IMPORTANCE The evaluation of mechanisms of mycobacterial response to natural products has been barely studied. However, it might be helpful to reveal bacterial adaptation strategies, which are eventually crucial for the discovery of new drug targets and, hence, understanding the resistance mechanisms. This study showed that the first-line mycobacterial defense against usnic acid, a potent antimicrobial agent, is the remodeling of the cell envelope and restoring redox homeostasis. Transcriptomic data correlated with metabolomics analysis. The observed metabolic changes appeared similar to those exerted by antibiotics.

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.

Kinetic Modeling and Meta-Analysis of the Bacillus subtilis SigB Regulon during Spore Germination and Outgrowth

The exponential increase in the number of conducted studies combined with the development of sequencing methods have led to an enormous accumulation of partially processed experimental data in the past two decades. Here, we present an approach using literature-mined data complemented with gene expression kinetic modeling and promoter sequence analysis. This approach allowed us to identify the regulon of Bacillus subtilis sigma factor SigB of RNA polymerase (RNAP) specifically expressed during germination and outgrowth. SigB is critical for the cell's response to general stress but is also expressed during spore germination and outgrowth, and this specific regulon is not known. This approach allowed us to (i) define a subset of the known SigB regulon controlled by SigB specifically during spore germination and outgrowth, (ii) identify the influence of the promoter sequence binding motif organization on the expression of the SigB-regulated genes, and (iii) suggest additional sigma factors co-controlling other SigB-dependent genes. Experiments then validated promoter sequence characteristics necessary for direct RNAP-SigB binding. In summary, this work documents the potential of computational approaches to unravel new information even for a well-studied system; moreover, the study specifically identifies the subset of the SigB regulon, which is activated during germination and outgrowth.

Systems and synthetic biology to elucidate secondary metabolite biosynthetic gene clusters encoded in Streptomyces genomes

Covering: 2010 to 2020 Over the last few decades, Streptomyces have been extensively investigated for their ability to produce diverse bioactive secondary metabolites. Recent advances in Streptomyces research have been largely supported by improvements in high-throughput technology 'omics'. From genomics, numerous secondary metabolite biosynthetic gene clusters were predicted, increasing their genomic potential for novel bioactive compound discovery. Additional omics, including transcriptomics, translatomics, interactomics, proteomics and metabolomics, have been applied to obtain a system-level understanding spanning entire bioprocesses of Streptomyces, revealing highly interconnected and multi-layered regulatory networks for secondary metabolism. The comprehensive understanding derived from this systematic information accelerates the rational engineering of Streptomyces to enhance secondary metabolite production, integrated with the exploitation of the highly efficient 'Design-Build-Test-Learn' cycle in synthetic biology. In this review, we describe the current status of omics applications in Streptomyces research to better understand the organism and exploit its genetic potential for higher production of valuable secondary metabolites and novel secondary metabolite discovery.

Drivers and sites of diversity in the DNA adenine methylomes of 93 Mycobacterium tuberculosis complex clinical isolates

This study assembles DNA adenine methylomes for 93 Mycobacterium tuberculosis complex (MTBC) isolates from seven lineages paired with fully-annotated, finished, de novo assembled genomes. Integrative analysis yielded four key results. First, methyltransferase allele-methylome mapping corrected methyltransferase variant effects previously obscured by reference-based variant calling. Second, heterogeneity analysis of partially active methyltransferase alleles revealed that intracellular stochastic methylation generates a mosaic of methylomes within isogenic cultures, which we formalize as ‘intercellular mosaic methylation’ (IMM). Mutation-driven IMM was nearly ubiquitous in the globally prominent Beijing sublineage. Third, promoter methylation is widespread and associated with differential expression in the ΔhsdM transcriptome, suggesting promoter HsdM-methylation directly influences transcription. Finally, comparative and functional analyses identified 351 sites hypervariable across isolates and numerous putative regulatory interactions. This multi-omic integration revealed features of methylomic variability in clinical isolates and provides a rational basis for hypothesizing the functions of DNA adenine methylation in MTBC physiology and adaptive evolution.

How High-Risk Comorbidities Co-Occur in Readmitted Patients With Hip Fracture: Big Data Visual Analytical Approach

BACKGROUND

When older adult patients with hip fracture (HFx) have unplanned hospital readmissions within 30 days of discharge, it doubles their 1-year mortality, resulting in substantial personal and financial burdens. Although such unplanned readmissions are predominantly caused by reasons not related to HFx surgery, few studies have focused on how pre-existing high-risk comorbidities co-occur within and across subgroups of patients with HFx.

OBJECTIVE

This study aims to use a combination of supervised and unsupervised visual analytical methods to (1) obtain an integrated understanding of comorbidity risk, comorbidity co-occurrence, and patient subgroups, and (2) enable a team of clinical and methodological stakeholders to infer the processes that precipitate unplanned hospital readmission, with the goal of designing targeted interventions.

METHODS

We extracted a training data set consisting of 16,886 patients (8443 readmitted patients with HFx and 8443 matched controls) and a replication data set consisting of 16,222 patients (8111 readmitted patients with HFx and 8111 matched controls) from the 2010 and 2009 Medicare database, respectively. The analyses consisted of a supervised combinatorial analysis to identify and replicate combinations of comorbidities that conferred significant risk for readmission, an unsupervised bipartite network analysis to identify and replicate how high-risk comorbidity combinations co-occur across readmitted patients with HFx, and an integrated visualization and analysis of comorbidity risk, comorbidity co-occurrence, and patient subgroups to enable clinician stakeholders to infer the processes that precipitate readmission in patient subgroups and to propose targeted interventions.

RESULTS

The analyses helped to identify (1) 11 comorbidity combinations that conferred significantly higher risk (ranging from P<.001 to P=.01) for a 30-day readmission, (2) 7 biclusters of patients and comorbidities with a significant bicluster modularity (P<.001; Medicare=0.440; random mean 0.383 [0.002]), indicating strong heterogeneity in the comorbidity profiles of readmitted patients, and (3) inter- and intracluster risk associations, which enabled clinician stakeholders to infer the processes involved in the exacerbation of specific combinations of comorbidities leading to readmission in patient subgroups.

CONCLUSIONS

The integrated analysis of risk, co-occurrence, and patient subgroups enabled the inference of processes that precipitate readmission, leading to a comorbidity exacerbation risk model for readmission after HFx. These results have direct implications for (1) the management of comorbidities targeted at high-risk subgroups of patients with the goal of pre-emptively reducing their risk of readmission and (2) the development of more accurate risk prediction models that incorporate information about patient subgroups.

Abasy Atlas v2.2: The most comprehensive and up-to-date inventory of meta-curated, historical, bacterial regulatory networks, their completeness and system-level characterization

Some organism-specific databases about regulation in bacteria have become larger, accelerated by high-throughput methodologies, while others are no longer updated or accessible. Each database homogenize its datasets, giving rise to heterogeneity across databases. Such heterogeneity mainly encompasses different names for a gene and different network representations, generating duplicated interactions that could bias network analyses. Abasy (Across-bacteria systems) Atlas consolidates information from different sources into meta-curated regulatory networks in bacteria. The high-quality networks in Abasy Atlas enable cross-organisms analyses, such as benchmarking studies where gold standards are required. Nevertheless, network incompleteness still casts doubts on the conclusions of network analyses, and available sampling methods cannot reflect the curation process. To tackle this problem, the updated version of Abasy Atlas presented in this work provides historical snapshots of regulatory networks. Thus, network analyses can be performed at different completeness levels, making possible to identify potential bias and to predict future results. We leverage the recently found constraint in the complexity of regulatory networks to develop a novel model to quantify the total number of regulatory interactions as a function of the genome size. This completeness estimation is a valuable insight that may aid in the daunting task of network curation, prediction, and validation. The new version of Abasy Atlas provides 76 networks (204,282 regulatory interactions) covering 42 bacteria (64% Gram-positive and 36% Gram-negative) distributed in 9 species (Mycobacterium tuberculosis, Bacillus subtilis, Escherichia coli, Corynebacterium glutamicum, Staphylococcus aureus, Pseudomonas aeruginosa, Streptococcus pyogenes, Streptococcus pneumoniae, and Streptomyces coelicolor), containing 8459 regulons and 4335 modules.

Database URL: https://abasy.ccg.unam.mx/.

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

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

Efficient identification of multiple pathways: RNA-Seq analysis of livers from 56Fe ion irradiated mice

Background

mRNA interaction with other mRNAs and other signaling molecules determine different biological pathways and functions. Gene co-expression network analysis methods have been widely used to identify correlation patterns between genes in various biological contexts (e.g., cancer, mouse genetics, yeast genetics). A challenge remains to identify an optimal partition of the networks where the individual modules (clusters) are neither too small to make any general inferences, nor too large to be biologically interpretable. Clustering thresholds for identification of modules are not systematically determined and depend on user-settable parameters requiring optimization. The absence of systematic threshold determination may result in suboptimal module identification and a large number of unassigned features.

Results

In this study, we propose a new pipeline to perform gene co-expression network analysis. The proposed pipeline employs WGCNA, a software widely used to perform different aspects of gene co-expression network analysis, and Modularity Maximization algorithm, to analyze novel RNA-Seq data to understand the effects of low-dose ⁵⁶Fe ion irradiation on the formation of hepatocellular carcinoma in mice. The network results, along with experimental validation, show that using WGCNA combined with Modularity Maximization, provides a more biologically interpretable network in our dataset, than that obtainable using WGCNA alone. The proposed pipeline showed better performance than the existing clustering algorithm in WGCNA, and identified a module that was biologically validated by a mitochondrial complex I assay.

Conclusions

We present a pipeline that can reduce the problem of parameter selection that occurs with the existing algorithm in WGCNA, for applicable RNA-Seq datasets. This may assist in the future discovery of novel mRNA interactions, and elucidation of their potential downstream molecular effects.

Primary transcriptome and translatome analysis determines transcriptional and translational regulatory elements encoded in the Streptomyces clavuligerus genome

Determining transcriptional and translational regulatory elements in GC-rich Streptomyces genomes is essential to elucidating the complex regulatory networks that govern secondary metabolite biosynthetic gene cluster (BGC) expression. However, information about such regulatory elements has been limited for Streptomyces genomes. To address this limitation, a high-quality genome sequence of β-lactam antibiotic-producing Streptomyces clavuligerus ATCC 27 064 is completed, which contains 7163 newly annotated genes. This provides a fundamental reference genome sequence to integrate multiple genome-scale data types, including dRNA-Seq, RNA-Seq and ribosome profiling. Data integration results in the precise determination of 2659 transcription start sites which reveal transcriptional and translational regulatory elements, including −10 and −35 promoter components specific to sigma (σ) factors, and 5′-untranslated region as a determinant for translation efficiency regulation. Particularly, sequence analysis of a wide diversity of the −35 components enables us to predict potential σ-factor regulons, along with various spacer lengths between the −10 and −35 elements. At last, the primary transcriptome landscape of the β-lactam biosynthetic pathway is analyzed, suggesting temporal changes in metabolism for the synthesis of secondary metabolites driven by transcriptional regulation. This comprehensive genetic information provides a versatile genetic resource for rational engineering of secondary metabolite BGCs in Streptomyces.

The Effect of 2-Thiocyanatopyridine Derivative 11026103 on Burkholderia Cenocepacia: Resistance Mechanisms and Systemic Impact

Bacteria of the Burkholderia cepacia complex (Bcc) are associated with significant decline of lung functions in cystic fibrosis patients. Bcc infections are virtually impossible to eradicate due to their irresponsiveness to antibiotics. The 2-thiocyanatopyridine derivative 11026103 is a novel, synthetic compound active against Burkholderia cenocepacia. To characterize mechanisms of resistance to 11026103, B. cenocepacia was subjected to chemical mutagenesis, followed by whole genome sequencing. Parallel mutations in resistant isolates were localized in a regulatory protein of the efflux system Resistance-Nodulation-Division (RND)-9 (BCAM1948), RNA polymerase sigma factor (BCAL2462) and its cognate putative anti-sigma factor (BCAL2461). Transcriptomic analysis identified positive regulation of a major facilitator superfamily (MFS) efflux system BCAL1510-1512 by BCAL2462. Artificial overexpression of both efflux systems increased resistance to the compound. The effect of 11026103 on B. cenocepacia was analyzed by RNA-Seq and a competitive fitness assay utilizing an essential gene knockdown mutant library. 11026103 exerted a pleiotropic effect on transcription including profound downregulation of cluster of orthologous groups (COG) category “Translation, ribosomal structure, and biogenesis”. The competitive fitness assay identified many genes which modulated susceptibility to 11026103. In summary, 11026103 exerts a pleiotropic cellular response in B. cenocepacia which can be prevented by efflux system-mediated export.

Genome-wide mutational biases fuel transcriptional diversity in the Mycobacterium tuberculosis complex

The Mycobacterium tuberculosis complex (MTBC) members display different host-specificities and virulence phenotypes. Here, we have performed a comprehensive RNAseq and methylome analysis of the main clades of the MTBC and discovered unique transcriptional profiles. The majority of genes differentially expressed between the clades encode proteins involved in host interaction and metabolic functions. A significant fraction of changes in gene expression can be explained by positive selection on single mutations that either create or disrupt transcriptional start sites (TSS). Furthermore, we show that clinical strains have different methyltransferases inactivated and thus different methylation patterns. Under the tested conditions, differential methylation has a minor direct role on transcriptomic differences between strains. However, disruption of a methyltransferase in one clinical strain revealed important expression differences suggesting indirect mechanisms of expression regulation. Our study demonstrates that variation in transcriptional profiles are mainly due to TSS mutations and have likely evolved due to differences in host characteristics.

Modulation of extracytoplasmic function (ECF) sigma factor promoter selectivity by spacer region sequence

The ability of bacteria to adapt to stress depends on the conditional expression of specific sets of genes. Bacillus subtilis encodes seven extracytoplasmic function (ECF) sigma (σ) factors that regulate functions important for survival under conditions eliciting cell envelope stress. Of these, four have been studied in detail: σ^M, σ^W, σ^X and σ^V. These four σ factors recognize overlapping sets of promoters, although the sequences that determine this overlapping recognition are incompletely understood. A major role in promoter selectivity has been ascribed to the core −10 and −35 promoter elements. Here, we demonstrate that a homopolymeric T-tract motif, proximal to the −35 element, functions in combination with the core promoter sequences to determine selectivity for ECF sigma factors. This motif is most critical for promoter activation by σ^V, and contributes variably to activation by σ^M, σ^X and σ^W. We propose that this motif, which is a feature of the deduced promoter consensus for a subset of ECF σ factors from many species, imparts intrinsic DNA curvature to influence promoter activity. The differential effect of this region among ECF σ factors thereby provides a mechanism to modulate the nature and extent of regulon overlap.

Mycobacterial SigA and SigB Cotranscribe Essential Housekeeping Genes during Exponential Growth

Mycobacterial σ^B belongs to the group II family of sigma factors, which are widely considered to transcribe genes required for stationary-phase survival and the response to stress. Here we explored the mechanism underlying the observed hypersensitivity of ΔsigB deletion mutants of Mycobacterium smegmatis, M. abscessus, and M. tuberculosis to rifampin (RIF) and uncovered an additional constitutive role of σ^B during exponential growth of mycobacteria that complements the function of the primary sigma factor, σ^A Using chromatin immunoprecipitation sequencing (ChIP-Seq), we show that during exponential phase, σ^B binds to over 200 promoter regions, including those driving expression of essential housekeeping genes, like the rRNA gene. ChIP-Seq of ectopically expressed σ^A-FLAG demonstrated that at least 61 promoter sites are recognized by both σ^A and σ^B These results together suggest that RNA polymerase holoenzymes containing either σ^A or σ^B transcribe housekeeping genes in exponentially growing mycobacteria. The RIF sensitivity of the ΔsigB mutant possibly reflects a decrease in the effective housekeeping holoenzyme pool, which results in susceptibility of the mutant to lower doses of RIF. Consistent with this model, overexpression of σ^A restores the RIF tolerance of the ΔsigB mutant to that of the wild type, concomitantly ruling out a specialized role of σ^B in RIF tolerance. Although the properties of mycobacterial σ^B parallel those of Escherichia coli σ³⁸ in its ability to transcribe a subset of housekeeping genes, σ^B presents a clear departure from the E. coli paradigm, wherein the cellular levels of σ³⁸ are tightly controlled during exponential growth, such that the transcription of housekeeping genes is initiated exclusively by a holoenzyme containing σ⁷⁰ (E.σ⁷⁰).IMPORTANCE All mycobacteria encode a group II sigma factor, σ^B, closely related to the group I principal housekeeping sigma factor, σ^A Group II sigma factors are widely believed to play specialized roles in the general stress response and stationary-phase transition in the bacteria that encode them. Contrary to this widely accepted view, we show an additional housekeeping function of σ^B that complements the function of σ^A in logarithmically growing cells. These findings implicate a novel and dynamic partnership between σ^A and σ^B in maintaining the expression of housekeeping genes in mycobacteria and can perhaps be extended to other bacterial species that possess multiple group II sigma factors.

An integrated whole genome analysis of Mycobacterium tuberculosis reveals insights into relationship between its genome, transcriptome and methylome

Human tuberculosis disease (TB), caused by Mycobacterium tuberculosis (Mtb), is a complex disease, with a spectrum of outcomes. Genomic, transcriptomic and methylation studies have revealed differences between Mtb lineages, likely to impact on transmission, virulence and drug resistance. However, so far no studies have integrated sequence-based genomic, transcriptomic and methylation characterisation across a common set of samples, which is critical to understand how DNA sequence and methylation affect RNA expression and, ultimately, Mtb pathogenesis. Here we perform such an integrated analysis across 22 M. tuberculosis clinical isolates, representing ancient (lineage 1) and modern (lineages 2 and 4) strains. The results confirm the presence of lineage-specific differential gene expression, linked to specific SNP-based expression quantitative trait loci: with 10 eQTLs involving SNPs in promoter regions or transcriptional start sites; and 12 involving potential functional impairment of transcriptional regulators. Methylation status was also found to have a role in transcription, with evidence of differential expression in 50 genes across lineage 4 samples. Lack of methylation was associated with three novel variants in mamA, likely to cause loss of function of this enzyme. Overall, our work shows the relationship of DNA sequence and methylation to RNA expression, and differences between ancient and modern lineages. Further studies are needed to verify the functional consequences of the identified mechanisms of gene expression regulation.

Selectivity among Anti-σ Factors by Mycobacterium tuberculosis ClpX Influences Intracellular Levels of Extracytoplasmic Function σ Factors

Extracytoplasmic function σ factors that are stress inducible are often sequestered in an inactive complex with a membrane-associated anti-σ factor. Mycobacterium tuberculosis membrane-associated anti-σ factors have a small, stable RNA gene A (ssrA)-like degron for targeted proteolysis. Interaction between the unfoldase, ClpX, and a substrate with an accessible degron initiates energy-dependent proteolysis. Four anti-σ factors with a mutation in the degron provided a set of natural substrates to evaluate the influence of the degron on degradation strength in ClpX-substrate processivity. We note that a point mutation in the degron (X-Ala-Ala) leads to an order-of-magnitude difference in the dwell time of the substrate on ClpX. Differences in ClpX/anti-σ interactions were correlated with changes in unfoldase activities. Green fluorescent protein (GFP) chimeras or polypeptides with a length identical to that of the anti-σ factor degron also demonstrate degron-dependent variation in ClpX activities. We show that degron-dependent ClpX activity leads to differences in anti-σ degradation, thereby regulating the release of free σ from the σ/anti-σ complex. M. tuberculosis ClpX activity thus influences changes in gene expression by modulating the cellular abundance of ECF σ factors.IMPORTANCE The ability of Mycobacterium tuberculosis to quickly adapt to changing environmental stimuli occurs by maintaining protein homeostasis. Extracytoplasmic function (ECF) σ factors play a significant role in coordinating the transcription profile to changes in environmental conditions. Release of the σ factor from the anti-σ is governed by the ClpXP2P1 assembly. M. tuberculosis ECF anti-σ factors have an ssrA-like degron for targeted degradation. A point mutation in the degron leads to differences in ClpX-mediated proteolysis and affects the cellular abundance of ECF σ factors. ClpX activity thus synchronizes changes in gene expression with environmental stimuli affecting M. tuberculosis physiology.

Incipient and Subclinical Tuberculosis: a Clinical Review of Early Stages and Progression of Infection

Tuberculosis (TB) is the leading infectious cause of mortality worldwide, due in part to a limited understanding of its clinical pathogenic spectrum of infection and disease. Historically, scientific research, diagnostic testing, and drug treatment have focused on addressing one of two disease states: latent TB infection or active TB disease. Recent research has clearly demonstrated that human TB infection, from latent infection to active disease, exists within a continuous spectrum of metabolic bacterial activity and antagonistic immunological responses. This revised understanding leads us to propose two additional clinical states: incipient and subclinical TB. The recognition of incipient and subclinical TB, which helps divide latent and active TB along the clinical disease spectrum, provides opportunities for the development of diagnostic and therapeutic interventions to prevent progression to active TB disease and transmission of TB bacilli. In this report, we review the current understanding of the pathogenesis, immunology, clinical epidemiology, diagnosis, treatment, and prevention of both incipient and subclinical TB, two emerging clinical states of an ancient bacterium.

Multisystem Analysis of Mycobacterium tuberculosis Reveals Kinase-Dependent Remodeling of the Pathogen-Environment Interface

Tuberculosis is the leading killer among infectious diseases worldwide. Increasing multidrug resistance has prompted new approaches for tuberculosis drug development, including targeted inhibition of virulence determinants and of signaling cascades that control many downstream pathways. We used a multisystem approach to determine the effects of a potent small-molecule inhibitor of the essential Mycobacterium tuberculosis Ser/Thr protein kinases PknA and PknB. We observed differential levels of phosphorylation of many proteins and extensive changes in levels of gene expression, protein abundance, cell wall lipids, and intracellular metabolites. The patterns of these changes indicate regulation by PknA and PknB of several pathways required for cell growth, including ATP synthesis, DNA synthesis, and translation. These data also highlight effects on pathways for remodeling of the mycobacterial cell envelope via control of peptidoglycan turnover, lipid content, a SigE-mediated envelope stress response, transmembrane transport systems, and protein secretion systems. Integrated analysis of phosphoproteins, transcripts, proteins, and lipids identified an unexpected pathway whereby threonine phosphorylation of the essential response regulator MtrA decreases its DNA binding activity. Inhibition of this phosphorylation is linked to decreased expression of genes for peptidoglycan turnover, and of genes for mycolyl transferases, with concomitant changes in mycolates and glycolipids in the cell envelope. These findings reveal novel roles for PknA and PknB in regulating multiple essential cell functions and confirm that these kinases are potentially valuable targets for new antituberculosis drugs. In addition, the data from these linked multisystems provide a valuable resource for future targeted investigations into the pathways regulated by these kinases in the M. tuberculosis cell.

Tuberculosis is the leading killer among infectious diseases worldwide. Increasing drug resistance threatens efforts to control this epidemic; thus, new antitubercular drugs are urgently needed. We performed an integrated, multisystem analysis of Mycobacterium tuberculosis responses to inhibition of its two essential serine/threonine protein kinases. These kinases allow the bacterium to adapt to its environment by phosphorylating cellular proteins in response to extracellular signals. We identified differentially phosphorylated proteins, downstream changes in levels of specific mRNA and protein abundance, and alterations in the metabolite and lipid content of the cell. These results include changes previously linked to growth arrest and also reveal new roles for these kinases in regulating essential processes, including growth, stress responses, transport of proteins and other molecules, and the structure of the mycobacterial cell envelope. Our multisystem data identify PknA and PknB as promising targets for drug development and provide a valuable resource for future investigation of their functions.

Sigma factors mediated signaling in Mycobacterium tuberculosis

Activation of signaling cascades is critical for Mycobacterium tuberculosis (Mtb) to adapt the macrophage lifestyle. Parallel to several signal systems, sigma factor systems, especially the extra-cytoplasmic function sigma factors, are crucial for Mtb signaling. Most sigma factors lack a signal sensory domain and often are activated by various proteins that perceive the environmental cues and relay the signals through variegated post-translational modifications via the activity of antisigma factor, protein kinase and related transcriptional regulators. Antisigma factors are further controlled by multiple mechanisms. SigK senses the environmental redox state directly. Phosphorylation and lysine acetylation added another dimension to the regulatory hierarchy. This review will provide insights into Mtb pathogenesis, and lay the foundation for the discovery of novel approaches for therapeutic interventions.

Raising orphans from a metadata morass: A researcher's guide to re-use of public 'omics data

More than 15 petabases of raw RNAseq data is now accessible through public repositories. Acquisition of other 'omics data types is expanding, though most lack a centralized archival repository. Data-reuse provides tremendous opportunity to extract new knowledge from existing experiments, and offers a unique opportunity for robust, multi-'omics analyses by merging metadata (information about experimental design, biological samples, protocols) and data from multiple experiments. We illustrate how predictive research can be accelerated by meta-analysis with a study of orphan (species-specific) genes. Computational predictions are critical to infer orphan function because their coding sequences provide very few clues. The metadata in public databases is often confusing; a test case with Zea mays mRNA seq data reveals a high proportion of missing, misleading or incomplete metadata. This metadata morass significantly diminishes the insight that can be extracted from these data. We provide tips for data submitters and users, including specific recommendations to improve metadata quality by more use of controlled vocabulary and by metadata reviews. Finally, we advocate for a unified, straightforward metadata submission and retrieval system.

JAK2V617F influences epigenomic changes in myeloproliferative neoplasms

Negative valine (V) to phenylalanine (F) switch at the Janus kinase (JAK2) 617 codon (V617F) is the dominant driver mutation in patients with myeloproliferative neoplasms (MPNs). JAK2V617F was proved to be sufficient for cell transformation; however, independent mutations might influence the following epigenomic modifications. To assess the JAK2V617F-induced downstream epigenomic changes without interferences, we profiled the epigenomic changes in ectopically expressed JAK2V617F in Ba/F3 cells. Antibodies against phosphorylated signal transducer and activator of transcription 3 (pSTAT3) and enhancer of zeste homolog 2 (EZH2) were used for chromatin-immunoprecipitation sequencing (ChIP-seq) to detect the downstream epigenomic targets in the JAK2-STAT3 signaling pathway. To confirm the JAK2V617F-induced epigenetic changes in vivo, DNA methylation changes in the target loci in patients with MPNs were detected through methylation-specific polymerase chain reaction and were clustered against the changes within controls. We found that ectopically expressed JAK2V617F in Ba/F3 cells reduced the binding specificity; it was associated with cis-regulatory elements and recognized DNA motifs in both pSTAT3-downstream and EZH2-associated targets. Overlapping target loci between the control and JAK2V617F were <3% and 0.4%, respectively, as identified through pSTAT3 and EZH2 ChIP-seq. Furthermore, the methylation changes in the direct target loci (FOXH1, HOXC9, and SRF) were clustered independently from the control locus (L1TD1) and other mutation genes (HMGA2 and Lin28A) in the analyzed MPN samples. Therefore, JAK2V617F influences target binding in both pSTAT3 and EZH2. Without mutations in epigenetic regulators, JAK2V617F can induce downstream epigenomic modifications. Thus, epigenetic changes in JAK2 downstream targets might be trackable in vivo.

The fused SnoaL_2 domain in the Mycobacterium tuberculosis sigma factor σJ modulates promoter recognition

Extra-cytoplasmic function (ECF) σ-factors are widespread in bacteria, linking environmental stimuli with changes in gene expression. These transcription factors span several phylogenetically distinct groups and are remarkably diverse in their activation and regulatory mechanisms. Here, we describe the structural and biochemical features of a Mycobacterium tuberculosis ECF factor σJ that suggests that the SnoaL_2 domain at the C-terminus can modulate the activity of this initiation factor in the absence of a cognate regulatory anti-σ factor. M. tuberculosis σJ can bind promoter DNA in vitro; this interaction is substantially impaired by the removal of the SnoaL_2 domain. This finding is consistent with assays to evaluate σJ-mediated gene expression. Structural similarity of the SnoaL_2 domain with epoxide hydrolases also suggests a novel functional role for this domain. The conserved sequence features between M. tuberculosis σJ and other members of the ECF41 family of σ-factors suggest that the regulatory mechanism involving the C-terminal SnoaL_2 domain is likely to be retained in this family of proteins. These studies suggest that the ECF41 family of σ-factors incorporate features of both-the σ70 family and bacterial one-component systems thereby providing a direct mechanism to implement environment-mediated transcription changes.

Mycobacterium tuberculosis hypoxic response protein 1 (Hrp1) augments the pro-inflammatory response and enhances the survival of Mycobacterium smegmatis in murine macrophages

PURPOSE

The DosR/DosS two-component regulatory system of Mycobacterium tuberculosis regulates the expression of numerous genes under stress conditions and is important for the long-term survival of M. tuberculosis in the host. The rv2626c gene of M. tuberculosis is one of the most strongly induced transcripts of the dormancy regulon. This study focused on the immunological effects and possible function of Rv2626c in maintaining mycobacterial survival under various stress conditions.

METHODOLOGY

We heterologously expressed the Rv2626c protein in Mycobacterium smegmatis by constructing a recombinant strain Ms_rv2626c. The viability of Ms_rv2626c was evaluated both in vivo and ex vivo. Different stress conditions, including acidified sodium nitrite, malachite green, low pH, SDS and lysozyme, were used to evaluate the effect of Rv2626c on bacterial resistance. An in vitro assay using a macrophage infection model was utilized to investigate the potential effect of Rv2626c to alter the immune response of host cell and its associated pathways. The effect of Rv2626c on cell necrosis was also explored.

RESULTS

The expression of Rv2626c-enhanced M. smegmatis survival under hypoxia and nitric oxide stress in vitro, and this enhancement was maintained within macrophages and in mouse tissues. In addition, macrophages infected with M. smegmatis expressing Rv2626c showed significantly higher interleukin-1β (IL-1β), IL-6, tumour necrosis factor-α (TNF-α) and inducible nitric oxide synthase (iNOS) expression, as well as a higher level of cell necrosis, compared with the control.

CONCLUSION

M. tuberculosis protein Rv2626c plays a significant role in stimulating macrophages to provoke a pro-inflammatory response and in mycobacterial survival during infection.

B. Enabling Comprehension of Patient Subgroups and Characteristics in Large Bipartite Networks: Implications for Precision Medicine

A primary goal of precision medicine is to identify patient subgroups based on their characteristics (e.g., comorbidities or genes) with the goal of designing more targeted interventions. While network visualization methods such as Fruchterman-Reingold have been used to successfully identify such patient subgroups in small to medium sized data sets, they often fail to reveal comprehensible visual patterns in large and dense networks despite having significant clustering. We therefore developed an algorithm called ExplodeLayout, which exploits the existence of significant clusters in bipartite networks to automatically "explode" a traditional network layout with the goal of separating overlapping clusters, while at the same time preserving key network topological properties that are critical for the comprehension of patient subgroups. We demonstrate the utility of ExplodeLayout by visualizing a large dataset extracted from Medicare consisting of readmitted hip-fracture patients and their comorbidities, demonstrate its statistically significant improvement over a traditional layout algorithm, and discuss how the resulting network visualization enabled clinicians to infer mechanisms precipitating hospital readmission in specific patient subgroups.