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Background Tuberculosis (Tb) is a disease with worldwide presence and a major cause of death in several developing countries. Current diagnostic methodologies often lack specificity and sensitivity, whereas a long time is needed to obtain a conclusive result. Material and methods In an effort to develop better diagnostic methods, this study aimed at the discovery of a biomarker signature for Tb diagnosis using a Nuclear Magnetic Resonance based metabolomics approach. In this study, we acquired 1H NMR spectra of blood serum samples of groups of healthy subjects, individuals with latent Tb and of patients with pulmonary and extra-pulmonary Tb. The resulting data were treated with uni- and multivariate statistical analysis. Results/Conclusion Six metabolites (inosine, hypoxanthine, mannose, asparagine, aspartate and glutamate) were validated by an independent cohort, all of them related with metabolic processes described as associated with TB infection. The findings of the study are according with the WHO Target Product Profile recommendations for a triage test to rule-out active TB.

Elucidation of signaling events in a pathogen is potentially important to tackle the infection caused by it. Such events mediated by protein phosphorylation play important roles in infection, and therefore, to predict the phosphosites and substrates of the serine/threonine protein kinases, we have developed a Machine learning-based approach for Mycobacterium tuberculosis serine/threonine protein kinases using kinase-peptide structure-sequence data. This approach utilizes features derived from kinase three-dimensional-structure environment and known phosphosite sequences to generate support vector machine (SVM)-based kinase-specific predictions of phosphosites of serine/threonine protein kinases (STPKs) with no or scarce data of their substrates. SVM outperformed the four machine learning algorithms we tried (random forest, logistic regression, SVM, and k-nearest neighbors) with an area under the curve receiver-operating characteristic value of 0.88 on the independent testing dataset and a 10-fold cross-validation accuracy of ~81.6% for the final model. Our predicted phosphosites of M. tuberculosis STPKs form a useful resource for experimental biologists enabling elucidation of STPK mediated posttranslational regulation of important cellular processes.

Mycobacterium tuberculosisencounters diverse microenvironments as it attempts to establish itself within its human host. The bacterium survives oxidative assault (ROS and RNS) when it is inside the host macrophages. Redox sensory and regulation processes therefore assume significant importance, as these are essential processes forM. tuberculosisto survive under these hostile conditions. The thioredoxin system that maintains balance between the thiol/dithiol couple plays a key role in maintaining redox homeostasis inM. tuberculosis. The most explored function of the thioredoxin system is elimination of toxic molecules such as free radicals, while very little is known about its role in other metabolic processes. In the present study, we aimed to reduce the knowledge gap about the thioredoxin system inM. tuberculosis. We attempted to capture targets of all the thioredoxins (viz., TrxB and TrxC) and a thioredoxin-like protein, NrdH inM. tuberculosisunder aerobic and hypoxic conditions by performing thioredoxin trapping chromatography followed by mass spectrometry. Targets were classified using the PANTHER classification system and most enriched processes were figured out using Gene Ontology analysis. We found that TrxC captured the maximum number of targets in both the physiological conditions. Also, we suggest that the thioredoxin system might play an important role in hypoxic conditions by targeting proteins responsible to sense and maintain hypoxic conditions. Furthermore, our studies establish a link between TrxB and iron-sulfur cluster biogenesis inM. tuberculosis. Ultimately, these findings open a novel avenue to target the thioredoxin system for screening new anti-mycobacterial drug targets.ImportanceTuberculosis (TB), an infectious disease caused by bacteriaM. tuberculosis, is the leading cause of death in the list of infectious diseases. Worldwide 1.7 billion people are estimated to be infected with TB, containing active and latent cases. An alarming situation is thatM. tuberculosishas developed resistance against one or many of the first line drugs leading to emergence of drug resistant or multidrug resistant TB. Novel drugs targeting the drug resistant bacteria is an urgent need to cure the disease. Our study provides the framework to identify new drug targets. The significance of our study is to understand the thioredoxin system in more details by identifying their target proteins, which might facilitate development of new anti-tubercular drugs.

Although skin is the primary affected organ in Leprosy, the role of the skin microbiome in its pathogenesis is not well understood. Recent reports have shown that skin of leprosy patients (LP) harbours perturbed microbiota which grants inflammation and disease progression. Herein, we present the results of nested Polymerase Chain Reaction-Denaturing Gradient Gel Electrophoresis (PCR-DGGE) which was initially performed for investigating the diversity of bacterial communities from lesional skin (LS) and non-lesional skin (NLS) sites of LP (n = 11). Further, we performed comprehensive analysis of 16S rRNA profiles corresponding to skin samples from participants (n = 90) located in two geographical locations i.e. Hyderabad and Miraj in India. The genus Staphylococcus was observed to be one of the representative bacteria characterizing healthy controls (HC; n = 30), which in contrast was underrepresented in skin microbiota of LP. Taxa affiliated to phyla Firmicutes and Proteobacteria were found to be signatures of HC and LS, respectively. Observed diversity level changes, shifts in core microbiota, and community network structure support the evident dysbiosis in normal skin microbiota due to leprosy. Insights obtained indicate the need for exploring skin microbiota modulation as a potential therapeutic option for leprosy.

The rapidly advancing SARS-CoV-2 pandemic of epic proportions has put science and technology organisations and the scientific community under the spotlight as never before placing a great responsib...

Nucleocytoplasmic shuttling of viral elements, supported by several host factors, is essential for the replication of the human immunodeficiency virus (HIV). HIV-1 uses a nuclear RNA export pathway mediated by viral protein Rev to transport its Rev response element (RRE)-containing partially spliced and unspliced transcripts aided by the host nuclear RNA export protein CRM1. The factor(s) interacting with the CRM1-Rev complex are potential antiretroviral target(s) and could serve as a retroviral model system to study nuclear export machinery adapted by these viruses. We earlier reported that cellular Staufen-2 interacts with Rev, facilitating viral-RNA export. Here, we identified the formation of a complex between Staufen-2, CRM1 and Rev. Molecular docking and simulations mapped the interacting residues in the RNA-binding Domain 4 of Staufen-2 as R336 and R337, which were experimentally verified to be critical for interactions among Staufen-2, CRM1 and Rev by mutational analysis. Staufen-2 mutants defective in interaction with CRM1 or Rev failed to supplement the Rev-RNA export activity and viral production, demonstrating the importance of these interactions. Rev-dependent reporter assays and proviral DNA-construct transfection-based studies in Staufen-2 knockout cells in the presence of leptomycin-B (LMB) revealed a significant reduction in CRM1-mediated Rev-dependent RNA export with decreased virus production as compared to Staufen-2 knockout background or LMB treatment alone, suggesting the relevance of these interactions in augmenting RNA export activity of Rev. Our observations provide further insights into the mechanistic intricacies of unspliced viral-RNA export to the cytoplasm and support the notion that abrogating such interactions can reduce HIV-1 proliferation.

Regulation of complement activation in the host cells is mediated primarily by the regulators of complement activation (RCA) family proteins that are formed by tandemly repeating complement control protein (CCP) domains. Functional annotation of these proteins, however, is challenging as contiguous CCP domains are found in proteins with varied functions. Here, by employing an in silico approach, we identify five motifs which are conserved spatially in a specific order in the regulatory CCP domains of known RCA proteins. We report that the presence of these motifs in a specific pattern is sufficient to annotate regulatory domains in RCA proteins. We show that incorporation of the lost motif in the fourth long-homologous repeat (LHR-D) in complement receptor 1 regains its regulatory activity. Additionally, the motif pattern also helped annotate human polydom as a complement regulator. Thus, we propose that the motifs identified here are the determinants of functionality in RCA proteins., Hina Ojha et al. show that the presence of five motifs in a specific pattern in CCP (complement control protein) domains is indicative of functional RCA (regulators of complement activation) proteins. This study suggests that an in silico regulatory RCA prediction tool CoReDo can be used to identify putative regulatory RCA proteins.

The transcription factor Rv0081 of Mycobacterium tuberculosis controls hypoxic gene expression and acts as a regulatory hub in the latent phase of tuberculosis (TB) infection. We report here the crystal structure of Rv0081 at 2.9 Å resolution revealing that it belongs to the well-known ArsR/SmtB family proteins. However, unlike other members in this family, Rv0081 has neither a metal-binding domain nor does it possess Cys residues, suggesting an alternate mechanism of gene regulation. Our structural and biochemical analyses suggest the molecular basis for the recognition of self-regulatory DNA sequences and a plausible mechanism of regulation of Rv0081 in the latent phase of TB infection. DATABASE: Structural data are available in the Protein Data Bank under the accession number - 6JMI.

The ability of chaperonins to buffer mutations that affect protein folding pathways suggests that their abundance should be evolutionarily advantageous. Here, we investigate the effect of chaperonin overproduction on cellular fitness in Escherichia coli. We demonstrate that chaperonin abundance confers 1) an ability to tolerate higher temperatures, 2) improved cellular fitness, and 3) enhanced folding of metabolic enzymes, which is expected to lead to enhanced energy harvesting potential.

Volume 191, no. 21, p. 6525–6538, 2009, [https://doi.org/10.1128/JB.00652-09][1]. Page 6528, Fig. 1C: There has been an erroneous and unintentional (potential) duplication related to the two top rows of the left and middle panels. Given the age of the article and that the SCM lab has since closed

In the first six months of its deadly spread across the world, the Covid-19 incidence has exhibited interesting dichotomy between the rich and the poor countries. Surprisingly, the incidence and the Case Fatality Rate has been much higher in the richer countries compared with the poorer countries. However, the reasons behind this dichotomy have not been explained based on data or evidence, although some of the factors for the susceptibility of populations to SARS-CoV-2 infections have been proposed. We have taken into consideration all publicly available data and mined for the possible explanations in order to understand the reasons for this phenomenon. The data included many parameters including demography of nations, prevalence of communicable and non-communicable diseases, sanitation parameters etc. Results of our analyses suggest that demography, improved sanitation and hygiene, and higher incidence of autoimmune disorders as the most plausible factors to explain higher death rates in the richer countries Thus, the much debated “hygiene hypothesis” appears to lend credence to the Case Fatality Rate dichotomy between the rich and the poor countries.SignificanceThe current COVID-19 epidemic has emerged as one of the deadliest of all infectious diseases in recent times and has affected all nations, especially the developed ones. In such times it is imperative to understand the most significant factor contributing towards higher mortality. Our analysis shows a higher association of demography, sanitation & autoimmunity to COVID-19 mortality as compared to the developmental parameters such as the GDP and the HDI globally. The dependence of sanitation parameters as well as autoimmunity upon the mortality gives direct evidences in support of the lower deaths in nations whose population do not confer to higher standards of hygiene practices and have lower prevalence of autoimmune diseases. This study calls attention to immune training and strengthening through various therapeutic interventions across populations.

Among the two GroEL paralogs in Mycobacterium tuberculosis, GroEL1 and GroEL2, GroEL1 has a characteristic histidine-rich C terminus. Since histidine richness is likely to be involved in metal binding, we attempted to decipher the role of GroEL1 in chelating metals and the consequence on M. tuberculosis physiology. Isothermal titration calorimetry showed that GroEL1 binds copper and other metals. Mycobacterial viability assay, redox balance, and DNA protection assay concluded that GroEL1 protects from copper stress in vitro. Solution X-ray scattering and constrained modeling of GroEL1 -/+ copper ions showed reorientation of the apical domain as seen in functional assembly. We conclude that the duplication of chaperonin genes in M. tuberculosis might have led to their evolutionary divergence and consequent functional divergence of chaperonins.

Although 23% of world population is infected with Mycobacterium tuberculosis ( M. tb ), only 5-10% manifest the disease. Individuals surely exposed to M. tb that remain asymptomatic are considered potential latent TB (LTB) cases. Such asymptomatic M. tb .-exposed individuals represent a reservoir for active TB cases. Although accurate discrimination and early treatment of patients with active TB and asymptomatic M. tb .-exposed individuals are necessary to control TB, identifying those individuals at risk of developing active TB still remains a tremendous clinical challenge. This study aimed to characterize the differences in the serum metabolic profile specifically associated to active TB infected individuals or to asymptomatic M. tb .-exposed population. Interestingly, significant changes in a specific set of metabolites were shared when comparing either asymptomatic house-hold contacts of active TB patients (HHC-TB) or active TB patients (A-TB) to clinically healthy controls (HC). Furthermore, this analysis revealed statistically significant lower serum levels of aminoacids such as alanine, lysine, glutamate and glutamine, and citrate and choline in patients with A-TB, when compared to HHC-TB. The predictive ability of these metabolic changes was also evaluated. Although further validation in independent cohorts and comparison with other pulmonary infectious diseases will be necessary to assess the clinical potential, this analysis enabled the discrimination between HHC-TB and A-TB patients with an AUC value of 0.904 (confidence interval 0.81-1.00, p -value < 0.0001). Overall, the strategy described in this work could provide a sensitive, specific, and minimally invasive method that could eventually be translated into a clinical tool for TB control.

Decrypting the interface residues of the protein complexes provides insight into the functions of the proteins and, hence, the overall cellular machinery. Computational methods have been devised in the past to predict the interface residues using amino acid sequence information, but all these methods have been majorly applied to predict for prokaryotic protein complexes. Since the composition and rate of evolution of the primary sequence is different between prokaryotes and eukaryotes, it is important to develop a method specifically for eukaryotic complexes. Here, we report a new hybrid pipeline for predicting the protein-protein interaction interfaces in a pairwise manner from the amino acid sequence information of the interacting proteins. It is based on the framework of Co-evolution, machine learning (Random Forest), and Network Analysis named CoRNeA trained specifically on eukaryotic protein complexes. We use Co-evolution, physicochemical properties, and contact potential as major group of features to train the Random Forest classifier. We also incorporate the intra-contact information of the individual proteins to eliminate false positives from the predictions keeping in mind that the amino acid sequence of a protein also holds information for its own folding and not only the interface propensities. Our prediction on example datasets shows that CoRNeA not only enhances the prediction of true interface residues but also reduces false positive rates significantly.

The Nobel Prize in Physiology or Medicine 2016 was awarded to Yoshinori Ohsumi of the Tokyo Institute of Technology, Japan, for his discoveries of mechanisms for autophagy [1].

Background A comprehensive map of the human-M. tuberculosis (MTB) protein interactome would help fill the gaps in our understanding of the disease, and computational prediction can aid and complement experimental studies towards this end. Several sequence-based in silico approaches tap the existing data on experimentally validated protein-protein interactions (PPIs); these PPIs serve as templates from which novel interactions between pathogen and host are inferred. Such comparative approaches typically make use of local sequence alignment, which, in the absence of structural details about the interfaces mediating the template interactions, could lead to incorrect inferences, particularly when multi-domain proteins are involved. Results We propose leveraging the domain-domain interaction (DDI) information in PDB complexes to score and prioritize candidate PPIs between host and pathogen proteomes based on targeted sequence-level comparisons. Our method picks out a small set of human-MTB protein pairs as candidates for physical interactions, and the use of functional meta-data suggests that some of them could contribute to the in vivo molecular cross-talk between pathogen and host that regulates the course of the infection. Further, we present numerical data for Pfam domain families that highlights interaction specificity on the domain level. Not every instance of a pair of domains, for which interaction evidence has been found in a few instances (i.e. structures), is likely to functionally interact. Our sorting approach scores candidates according to how “distant” they are in sequence space from known examples of DDIs (templates). Thus, it provides a natural way to deal with the heterogeneity in domain-level interactions. Conclusions Our method represents a more informed application of local alignment to the sequence-based search for potential human-microbial interactions that uses available PPI data as a prior. Our approach is somewhat limited in its sensitivity by the restricted size and diversity of the template dataset, but, given the rapid accumulation of solved protein complex structures, its scope and utility are expected to keep steadily improving. Electronic supplementary material The online version of this article (doi:10.1186/s12859-017-1550-y) contains supplementary material, which is available to authorized users.

The ability of chaperonins to buffer mutations that affect protein folding pathways suggests that their abundance should be evolutionarily advantageous. Here, we investigate the effect of chaperonin overproduction on cellular fitness inEscherichia coli. We demonstrate that chaperonin abundance confers (a) an ability to tolerate higher temperatures, (b) improved cellular fitness and (c) enhanced folding of metabolic enzymes, which is expected to lead to enhanced energy harvesting potential.

Background Latent tuberculosis infection is attributed in part to the existence of Mycobacterium tuberculosis in a persistent non-replicating dormant state that is associated with tolerance to host defence mechanisms and antibiotics. We have recently reported that vitamin C treatment of M. tuberculosis triggers the rapid development of bacterial dormancy. Temporal genome-wide transcriptome analysis has revealed that vitamin C-induced dormancy is associated with a large-scale modulation of gene expression in M. tuberculosis. Results An updated transcriptional regulatory network of M.tuberculosis (Mtb-TRN) consisting of 178 regulators and 3432 target genes was constructed. The temporal transcriptome data generated in response to vitamin C was overlaid on the Mtb-TRN (vitamin C Mtb-TRN) to derive insights into the transcriptional regulatory features in vitamin C-adapted bacteria. Statistical analysis using Fisher’s exact test predicted that 56 regulators play a central role in modulating genes which are involved in growth, respiration, metabolism and repair functions. Rv0348, DevR, MprA and RegX3 participate in a core temporal regulatory response during 0.25 h to 8 h of vitamin C treatment. Temporal network analysis further revealed Rv0348 to be the most prominent hub regulator with maximum interactions in the vitamin C Mtb-TRN. Experimental analysis revealed that Rv0348 and DevR proteins interact with each other, and this interaction results in an enhanced binding of DevR to its target promoter. These findings, together with the enhanced expression of devR and Rv0348 transcriptional regulators, indicate a second-level regulation of target genes through transcription factor- transcription factor interactions. Conclusions Temporal regulatory analysis of the vitamin C Mtb-TRN revealed that there is involvement of multiple regulators during bacterial adaptation to dormancy. Our findings suggest that Rv0348 is a prominent hub regulator in the vitamin C model and large-scale modulation of gene expression is achieved through interactions of Rv0348 with other transcriptional regulators.

Leprosy is an infectious disease that has predilection in skin and peripheral nerves. Skin has its own microbiome, however it is not extensively studied in Indian leprosy patients. Here, by using next-generation 16S rDNA sequencing, we have attempted to assess the skin associated microbial diversity pertaining to affected and unaffected skin of Indian leprosy patients. A total of 90 skin swab samples were collected from 60 individuals (30 healthy controls, 30 patients) residing in Hyderabad and Miraj, two distinct geographical locations in India to assess the homo/heterogeneity of skin microbial signatures. While a large increase in genus Methylobacterium and Pseudomonas was seen in patients from Miraj and Hyderabad respectively, a considerable decrease in genus Staphylococcus in the leprosy patients (as compared to controls) from both geographical locations was also observed. We expect that, these datasets can not-only provide further interesting insights, but will also help to observe dynamics of microbiome in the diseased state and generate hypotheses to test for skin microbiome transplantation studies in leprosy., Measurement(s)DNATechnology Type(s)DNA sequencingFactor Type(s)experimental conditionSample Characteristic - OrganismHomo sapiensSample Characteristic - Environmentmicrobial communitySample Characteristic - LocationIndia Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.9897089

Metabolic adaptation of Mycobacterium tuberculosis (M. tuberculosis) to microbicidal intracellular environment of host macrophages is fundamental to its pathogenicity. However, an in-depth understanding of metabolic adjustments through key reaction pathways and networks is limited. To understand how such changes occur, we measured the cellular metabolome of M. tuberculosis subjected to four microbicidal stresses using liquid chromatography-mass spectrometric multiple reactions monitoring (LC-MRM/MS). Overall, 87 metabolites were identified. The metabolites best describing the separation between stresses were identified through multivariate analysis. The coupling of the metabolite measurements with existing genome-scale metabolic model, and using constraint-based simulation led to several new concepts and unreported observations in M. tuberculosis; such as (i) the high levels of released ammonia as an adaptive response to acidic stress was due to increased flux through L-asparaginase rather than urease activity; (ii) nutrient starvation-induced anaplerotic pathway for generation of TCA intermediates from phosphoenolpyruvate using phosphoenolpyruvate kinase; (iii) quenching of protons through GABA shunt pathway or sugar alcohols as possible mechanisms of early adaptation to acidic and oxidative stresses; and (iv) usage of alternate cofactors by the same enzyme as a possible mechanism of rewiring metabolic pathways to overcome stresses. Besides providing new leads and important nodes that can be used for designing intervention strategies, the study advocates the strength of applying flux balance analyses coupled with metabolomics to get a global picture of complex metabolic adjustments.

MotivationDecrypting the interface residues of the protein complexes provide insight into the functions of the proteins and hence the overall cellular machinery. Computational methods have been devised in the past to predict the interface residues using amino acid sequence information but all these methods have been majorly applied to predict for prokaryotic protein complexes. Since the composition and rate of evolution of the primary sequence is different between prokaryotes and eukaryotes, it is important to develop a method specifically for eukaryotic complexes.nnResultsHere we report a new hybrid pipeline for the prediction of protein-protein interaction interfaces from the amino acid sequence information which is based on the framework of co-evolution, machine learning (random forest) and network analysis named CoRNeA trained specifically on eukaryotic protein complexes. We use conservation, structural and contact potential as major group of features to train the random forest classifier. We also incorporate the intra contact information of the individual proteins to eliminate false positives from the predictions keeping in mind that the amino acid sequence also holds information for its own folding and not only the interface propensities. Our prediction on example datasets shows that CoRNeA not only enhances the prediction of true interface residues but also reduces false positive rates significantly.

Mycobacterium smegmatis, the saprophytic soil mycobacterium, is routinely used as a surrogate system to study the human pathogen Mycobacterium tuberculosis. It has also been reported as an opportunistic pathogen in immunocompromised hosts. In addition, it can exist in several ecological setups, thereby suggesting its capacity to adapt to a variety of environmental cues. In this study, we employed untargeted proton nuclear magnetic resonance (1H-NMR)-based metabolomics to identify metabolites and metabolic pathways critical for early adaptive responses to acidic stress, oxidative stress, and nutrient starvation in Mycobacterium smegmatis. We identified 31, 20, and 46 metabolites that showed significant changes in levels in response to acidic, oxidative, and nutrient starvation stresses, respectively. Pathway analyses showed significant perturbations in purine-pyrimidine, amino-acid, nicotinate-nicotinamide, and energy metabolism pathways. Besides these, differential levels of intermediary metabolites involved in α-glucan biosynthesis pathway were observed. We also detected high levels of organic osmolytes, methylamine, and betaine during nutrient starvation and oxidative stress. Further, tracing the differential levels of these osmolytes through computational search tools, gene expression studies (using reverse transcription-PCR [RT-PCR]), and enzyme assays, we detected the presence of a putative pathway of biosynthesis of betaine, methylamine, and dimethylamine previously unreported in Mycobacterium smegmatis. IMPORTANCE Alterations in metabolite levels provide fast and direct means to regulate enzymatic reactions and, therefore, metabolic pathways. This study documents, for the first time, the metabolic changes that occur in Mycobacterium smegmatis as a response to three stresses, namely, acidic stress, oxidative stress, and nutrient starvation. These stresses are also faced by intracellular mycobacteria during infection and therefore may be extended to frame therapeutic interventions for pathogenic mycobacteria. In addition to the purine-pyrimidine, amino acid, nicotinate-nicotinamide, and energy metabolism pathways that were found to be affected in response to different stresses, a novel putative methylamine biosynthesis pathway was identified to be present in Mycobacterium smegmatis.

Background A previous laboratory study involving wild type, mutant and devR/dosR complemented strains of Mycobacterium tuberculosis reported the attenuation phenotype of complemented strain, Comp1. This phenotype was intriguing since the parental strain H37Rv, devR mutant (Mut1) and additional complemented strains, Comp9 and Comp11, were virulent in the guinea pig model. Results Towards deciphering the mechanism underlying the attenuation of Comp1, a whole genome sequencing approach was undertaken. Eight Single Nucleotide Polymorphisms (SNPs) unique to the Comp1 strain were identified. Of these, 5 SNPs were non-synonymous and included a G➞A mutation resulting in a W1591Stop mutation in ppsD gene of the phthiocerol dimycocerosate (PDIM) biosynthetic cluster. Targeted sequence analysis confirmed this mutation in only Comp1 strain and not in wild type (H37Rv), devR knockout (Mut1) or other complemented (Comp9 and Comp11) bacteria. Differential expression of the PDIM locus in Comp1 bacteria was observed which was associated with a partial deficiency of PDIM, an increased sensitivity to detergent and a compromised ability to infect human THP-1 cells. Conclusions It is proposed that a spontaneous mutation in the ppsD gene of Comp1 underlies down-modulation of the PDIM locus which is associated with defects in permeability and infectivity as well as virulence attenuation in guinea pigs. Our study demonstrates the value of whole genome sequencing for resolving unexplainable bacterial phenotypes and recommends the assessment of PDIM status while assessing virulence properties of laboratory-manipulated strains of M. tuberculosis. Electronic supplementary material The online version of this article (10.1186/s12864-019-5482-y) contains supplementary material, which is available to authorized users.

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

The transcription factor Rv0081 ofM. tuberculosiscontrols the hypoxic gene expression and acts as a regulatory hub in the latent phase of tuberculosis infection. We report here the crystal structure of Rv0081 at 3.3 Å resolution revealing that it belongs to the well-known ArsR/SmtB family proteins. ArsR/SmtB family transcriptional repressors exert gene regulation by reversible metal binding. Hypoxia in general is sensed by bacterial transcriptional regulators via metals or Cys-mediated thiol switches. Oxygen sensing typically leads to transcriptional repressor changing its conformational state with altered DNA-binding property under different oxygen levels. Surprisingly Rv0081 neither has a metal binding domain nor does it possess Cys residues suggesting an alternate mechanism of gene regulation. Our structural analysis identified Ser 48, Ser 49, Ser 52 and Gln 53 as potential residues of Rv0081 involved in DNA binding. We probed DNA-binding of Rv0081 with electrophoretic mobility shift assay (EMSA) as well as surface plasmon resonance (SPR), where the Alanine mutants of these residues showed diminished DNA binding. Similarly, Aspartate mutants of these Ser residues was shown to fail to bind to DNA. Since, phosphorylation of various regulatory proteins is one of the important controlling mechanisms, we expected the role of Ser-phosphorylation of Rv0081 in hypoxic condition. Probing Rv0081 with anti-phosphoserine antibodies inM. tuberculosiscell lysate showed marked enhancement in the phosphorylation of Rv0081 protein under hypoxia. Overall, our structural and biochemical analysis provides the molecular basis for the regulation of Rv0081 in the latent phase of tuberculosis infection.IMPORTANCETuberculosis is one of the deadliest infectious diseases caused by the bacteriumMycobacterium tuberculosis. In about 90% of the infected people,M. tuberculosisexists in a dormant or a latent stage which can be reactivated in favorable conditions. Hypoxia (low oxygen pressure) is one of causes of dormancy. Understanding hypoxic gene regulation inM. tuberculosisis therefore an important step to understand latency. Rv0081 is a transcriptional regulator of genes expressed during hypoxia. In order to understand the mechanism by which Rv00081 regulates gene expression during hypoxia, we have solved the crystal structure of Rv0081 and identified amino acid residues which are critical in its transcriptional regulator activity. The crystal structure is suggestive of mechanism of gene regulation under hypoxia.

Chaperonins are a class of molecular chaperones that assemble into a large double ring architecture with each ring constituting seven to nine subunits and enclosing a cavity for substrate encapsulation. The well-studied Escherichia coli chaperonin GroEL binds non-native substrates and encapsulates them in the cavity thereby sequestering the substrates from unfavorable conditions and allowing the substrates to fold. Using this mechanism, GroEL assists folding of about 10–15 % of cellular proteins. Surprisingly, about 30 % of the bacteria express multiple chaperonin genes. The presence of multiple chaperonins raises questions on whether they increase general chaperoning ability in the cell or have developed specific novel cellular roles. Although the latter view is widely supported, evidence for the former is beginning to appear. Some of these chaperonins can functionally replace GroEL in E. coli and are generally indispensable, while others are ineffective and likewise are dispensable. Additionally, moonlighting functions for several chaperonins have been demonstrated, indicating a functional diversity among the chaperonins. Furthermore, proteomic studies have identified diverse substrate pools for multiple chaperonins. We review the current perception on multiple chaperonins and their physiological and functional specificities.

It has been more than 100 years since the discovery of X-ray diffraction by crystals. The evolution of this technique has transformed our understanding of Nature very profoundly. In India, the early proponents of this area of research were Kedareshwar Banerjee, A R Verma, S Ramaseshan and G N Ramachandran, etc. In this article, contributions of some of them are highlighted.

Members of the NrdH family of redox proteins, which consists of small glutaredoxin-like proteins with thioredoxin-like activity, serve as the reducing partners of class Ib ribonucleotide reductases. Here, we report the crystal structure of NrdH from Mycobacterium tuberculosis, refined to a crystallographic R factor of 14.02% (Rfree = 15.53%) at 0.87 Å resolution. The tertiary structure of M. tuberculosis NrdH has a typical thioredoxin fold as expected. The extremely high resolution of the structure allows us to dissect the functionality of the protein in great depth. Structural superimposition of M. tuberculosis NrdH and thioredoxin reductase over the Escherichia coli thioredoxin reductase-thioredoxin complex suggests the ability of NrdH to accept electrons from M. tuberculosis thioredoxin reductase. This raises the important question of why glutaredoxins are unable to accept electrons from thioredoxin reductases and why thioredoxins are unable to reduce ribonucleotide reductases. Furthermore, forms of NrdH from other organisms have been shown to be a specific reductant of class Ib ribonucleotide reductases. We attempt to explain this substrate specificity by modeling the C-terminal peptide of a ribunucleotide subunit, NrdE, in the active site of NrdH using the already available Grx-NrdA-Cter-peptide structure. Statistical coupling analysis of NrdH, glutaredoxins, and thioredoxins reveals different sets of co-evolving contiguous clusters of amino acid residues, which might explain the differences in the biochemical properties of these structurally similar yet functionally distinct subclasses of proteins.

Chaperonins are a class of molecular chaperones that form cylindrical assemblies and for sequestering the non-native protein and thereby assisting their folding. Genomic annotation studies have identified multiple copies of chaperonin genes in about 30% of the bacteria. Mycobacterium tuberculosis was the first organism where two copies were observed, and similarly other mycobacteria bear two and rarely three copies. Owing to the pathogenic lifestyle, the chaperonins of mycobacteria have been demonstrated to be secretory and possess antigenic properties. Furthermore, biochemical and structural studies have demonstrated that these chaperonins are unusual. One of the chaperonins that exists in operonic arrangement with the co-chaperonin gene has been shown to be required in several pathogenic stages of the bacteria. The other copy that exists independently is essential and thus might be functioning as a general chaperone. Several groups have worked to unravel the functional diversity of these mysterious molecules employing structural, immunochemical, cell-biological, computational and genetic tools. We review the current understanding on the mycobacterial chaperonins and the new paradigms that have arisen.

Identification of bacterial modulons from series of gene expression measurements on microarrays is a principal problem, especially relevant for inadequately studied but practically important species. Usage of a priori information on regulatory interactions helps to evaluate parameters for regulatory subnetwork inference. We suggest a procedure for modulon construction where a seed regulon is iteratively updated with genes having expression patterns similar to those for regulon member genes. A set of genes essential for a regulon is used to control modulon updating. Essential genes for a regulon were selected as a subset of regulon genes highly related by different measures to each other. Using Escherichia coli as a model, we studied how modulon identification depends on the data, including the microarray experiments set, the adopted relevance measure and the regulon itself. We have found that results of modulon identification are highly dependent on all parameters studied and thus the resulting modulon varies substantially depending on the identification procedure. Yet, modulons that were identified correctly displayed higher stability during iterations, which allows developing a procedure for reliable modulon identification in the case of less studied species where the known regulatory interactions are sparse.

Cyclic AMP (cAMP) receptor protein, which acts as the sensor of cAMP levels in cells, is a well-studied transcription factor that is best known for allosteric changes effected by the binding of cAMP. Although genetic and biochemical data on the protein are available from several sources, structural information about the cAMP-free protein has been lacking. Therefore, the precise atomic events that take place upon binding of cAMP, leading to conformational changes in the protein and its activation to bind DNA, have been elusive. In this work we solved the cAMP-free crystal structure of the Mycobacterium tuberculosis homolog of cAMP receptor protein at 2.9 Å resolution, and carried out normal-mode analysis to map conformational transitions among its various conformational states. In our structure, the cAMP-binding domain holds onto the DNA-binding domain via strong hydrophobic interactions, thereby freezing the latter in a conformation that is not competent to bind DNA. The two domains release each other in the presence of cAMP, making the DNA-binding domain more flexible and allowing it to bind its cognate DNA via an induced-fit mechanism. The structure of the cAMP-free protein and results of the normal-mode analysis therefore highlight an elegant mechanism of the allosteric changes effected by the binding of cAMP.

The Mycobacterium tuberculosis genome sequence reveals remarkable absence of many nucleoid-associated proteins (NAPs), such as HNS, Hfq or DPS. In order to characterize the nucleoids of M. tuberculosis, we have attempted to identify NAPs, and report an interesting finding that a chaperonin-homolog, GroEL1, is nucleoid associated. We report that M. tuberculosis GroEL1 binds DNA with low specificity but high affinity, suggesting that it might have naturally evolved to bind DNA. We are able to demonstrate that GroEL1 can effectively function as a DNA-protecting agent against DNase I or hydroxyl-radicals. Moreover, Atomic Force Microscopic studies reveal that GroEL1 can condense a large DNA into a compact structure. We also provide in vivo evidences that include presence of GroEL1 in purified nucleoids, in vivo crosslinking followed by Southern hybridizations and immunofluorescence imaging in M. tuberculosis confirming that GroEL1: DNA interactions occur in natural biological settings. These findings therefore reveal that M. tuberculosis GroEL1 has evolved to be associated with nucleoids.

High throughput structural genomics efforts have been making the structures of proteins available even before their function has been fully characterized. Therefore, methods that exploit the structural knowledge to provide evidence about the functions of proteins would be useful. Such methods would beneeded to complement the sequence-based function annotation approaches. The current study describes generation of 3D-structural motifs for metal-binding sites from the known metalloproteins. It then scans all the available protein structures in the PDB database for putative metal-binding sites. Our analysis predicted more than 1000 novel metal-binding sites in proteins using three-residue templates, and more than 150 novel metal-binding sites using four-residue templates. Prediction of metal-binding site in a yeast protein YDR533c led to the hypothesis that it might function as metal-dependent amidopeptidase. The structural motifs identified by our method present novel metal-binding sites that reveal newer mechanisms for a few well-known proteins. Proteins 2008. © 2007 Wiley-Liss, Inc.

Cellular functions are determined by interactions among proteins in the cells. Recognition of these interactions forms an important step in understanding biology at the systems level. Here, we report an interaction network of Escherichia coli, obtained by training a Support Vector Machine on the high quality of interactions in the EcoCyc database, and with the assumption that the periplasmic and cytoplasmic proteins may not interact with each other. The data features included correlation coefficient between bit score phylogenetic profiles, frequency of their co-occurrence in predicted operons, and a new measure—the distance between translational start sites of the genes. The combined genome context methods show a high accuracy of prediction on the test data and predict a total of 78,122 binary interactions. The majority of the interactions identified by high-throughput experimental methods correspond to indirect interaction (interactions through neighbors) in the predicted network. Correlation of the predicted network with the gene essentiality data shows that the essential genes in E. coli exhibit a high linking number, whereas the nonessential genes exhibit a low linking number. Furthermore, our predicted protein–protein interaction network shows that the proteins involved in replication, DNA repair, transcription, translation, and cell wall synthesis are highly connected. We therefore believe that our predicted network will serve as a useful resource in understanding prokaryotic biology.