172 resultados para Latent tuberculosis


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Because of its essential nature, each step of transcription, viz., initiation, elongation, and termination, is subjected to elaborate regulation. A number of transcription factors modulate the rates of transcription at these different steps, and several inhibitors shut down the process. Many modulators, including small molecules and proteinaceous inhibitors, bind the RNA polymerase (RNAP) secondary channel to control transcription. We describe here the first small protein inhibitor of transcription in Mycobacterium tuberculosis. Rv3788 is a homolog of the Gre factors that binds near the secondary channel of RNAP to inhibit transcription. The factor also affected the action of guanosine pentaphosphate (pppGpp) on transcription and abrogated Gre action, indicating its function in the modulation of the catalytic center of RNAP. Although it has a Gre factor-like domain organization with the conserved acidic residues in the N terminus and retains interaction with RNAP, the factor did not show any transcript cleavage stimulatory activity. Unlike Rv3788, another Gre homolog from Mycobacterium smegmatis, MSMEG_6292 did not exhibit transcription-inhibitory activities, hinting at the importance of the former in influencing the lifestyle of M. tuberculosis.

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Background: Tuberculosis (TB) is an enduring health problem worldwide and the emerging threat of multidrug resistant (MDR) TB and extensively drug resistant (XDR) TB is of particular concern. A better understanding of biomarkers associated with TB will aid to guide the development of better targets for TB diagnosis and for the development of improved TB vaccines. Methods: Recombinant proteins (n = 7) and peptide pools (n = 14) from M. tuberculosis (M.tb) antigens associated with M.tb pathogenicity, modification of cell lipids or cellular metabolism, were used to compare T cell immune responses defined by IFN-gamma production using a whole blood assay (WBA) from i) patients with TB, ii) individuals recovered from TB and iii) individuals exposed to TB without evidence of clinical TB infection from Minsk, Belarus. Results: We identified differences in M.tb target peptide recognition between the test groups, i.e. a frequent recognition of antigens associated with lipid metabolism, e.g. cyclopropane fatty acyl phospholipid synthase. The pattern of peptide recognition was broader in blood from healthy individuals and those recovered from TB as compared to individuals suffering from pulmonary TB. Detection of biologically relevant M.tb targets was confirmed by staining for intracellular cytokines (IL-2, TNF-alpha and IFN-gamma) in T cells from non-human primates (NHPs) after BCG vaccination. Conclusions: PBMCs from healthy individuals and those recovered from TB recognized a broader spectrum of M.tb antigens as compared to patients with TB. The nature of the pattern recognition of a broad panel of M.tb antigens will devise better strategies to identify improved diagnostics gauging previous exposure to M.tb; it may also guide the development of improved TB-vaccines.

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A decade since the availability of Mycobacterium tuberculosis (Mtb) genome sequence, no promising drug has seen the light of the day. This not only indicates the challenges in discovering new drugs but also suggests a gap in our current understanding of Mtb biology. We attempt to bridge this gap by carrying out extensive re-annotation and constructing a systems level protein interaction map of Mtb with an objective of finding novel drug target candidates. Towards this, we synergized crowd sourcing and social networking methods through an initiative `Connect to Decode' (C2D) to generate the first and largest manually curated interactome of Mtb termed `3interactome pathway' (IPW), encompassing a total of 1434 proteins connected through 2575 functional relationships. Interactions leading to gene regulation, signal transduction, metabolism, structural complex formation have been catalogued. In the process, we have functionally annotated 87% of the Mtb genome in context of gene products. We further combine IPW with STRING based network to report central proteins, which may be assessed as potential drug targets for development of drugs with least possible side effects. The fact that five of the 17 predicted drug targets are already experimentally validated either genetically or biochemically lends credence to our unique approach.

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Although sequencing of Mycobacterium tuberculosis genome lead to better understanding of transcription units and gene functions, interactions occurring during transcription initiation between RNA polymerase and promoters is yet to be elucidated. Different stages of transcription initiation include promoter specific binding of RNAP, isomerization, abortive initiation and promoter clearance. We have now analyzed these events with four promoters of M. tuberculosis viz. P-gyrB1, P-gyrR, P-rrnPCL1 and P-metU. The promoters differed from each other in their rates of open complex formation, decay, promoter clearance and abortive transcription. The equilibrium binding and kinetic studies of various steps revealed distinct rate limiting events for each of the promoter, which also differed markedly in their characteristics from the respective promoters of Mycobacterium smegmatis. Surprisingly, the transcription at gyr promoter was enhanced in the presence of initiating nucleotides and decreased in the presence of alarmone, pppGpp, a pattern typically seen with rRNA promoters studied so far. The gyr promoter of M. smegmatis, on the other hand, was not subjected to pppGpp mediated regulation. The marked differences in the transcription initiation pathway seen with rrn and gyr promoters of M. smegmatis and M. tuberculosis suggest that such species specific differences in the regulation of expression of the crucial housekeeping genes could be one of the key determinants contributing to the differences in growth rate and lifestyle of the two organisms. Moreover, the distinct rate limiting steps during transcription initiation of each one of the promoters studied point at variations in their intracellular regulation.

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The role of FIC (Filamentation induced by cAMP)(2) domain containing proteins in the regulation of many vital pathways, mostly through the transfer of NMPs from NTPs to specific target proteins (NMPylation), in microorganisms, higher eukaryotes, and plants is emerging. The identity and function of FIC domain containing protein of the human pathogen, Mycobacterium tuberculosis, remains unknown. In this regard, M. tuberculosis fic gene (Mtfic) was cloned, overexpressed, and purified to homogeneity for its biochemical characterisation. It has the characteristic FIC motif, HPFREGNGRSTR (HPFxxGNGRxxR), spanning 144th to 155th residue. Neither the His-tagged nor the GST-tagged MtFic protein, overexpressed in Escherichia coil, nor expression of Mtfic in Mycobacterium smegmatis, yielded the protein in the soluble fraction. However, the maltose binding protein (MBP) tagged MtFic (MBP-MtFic) could be obtained partly in the soluble fraction. The cloned, overexpressed, and purified recombinant MBP-MtFic showed conversion of ATP, GTP, CTP, and UTP into AMP. GMP, CMP, and UMP, respectively. Sequence alignment with several FIC motif containing proteins, complemented with homology modeling on the FIC motif containing protein, VbhT of Bartonella schoenbuchensis as the template, showed conservation and interaction of residues constituting the FIC domain. Site-specific mutagenesis of the His144, or Glu148, or Asn150 of the FIC motif, or of Arg87 residue that constitutes the FIC domain, or complete deletion of the FIC motif, abolished the NTP to NMP conversion activity. The design of NMP formation assay using the recombinant, soluble MtFic would enable identification of its target substrate for NMPylation. (C) 2012 Elsevier Inc. All rights reserved.

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Type I DNA topoisomerases from bacteria catalyse relaxation of negatively supercoiled DNA in a Mg2+ dependent manner. Although topoisomerases of distinct classes have been subjected for anti-cancer and anti-infective drug development, bacterial type I enzymes are way behind in this regard. Our studies with Mycobacterium smegmatis topoisomerase I (MstopoI) revealed several of its distinct properties compared to the well studied Escherichia coli topoisomerase I (EctopoI) suggesting the possibility of targeting the mycobacterial enzyme for inhibitor development. Here, we describe Mycobacterium tuberculosis topoisomerase I (MttopoI) and compare its properties with MstopoI and EctopoI. The enzyme cleaves DNA at preferred sites in a pattern similar to its ortholog from M. smegmatis. Oligonucleotides containing the specific recognition sequence inhibited the activity of the enzyme in a manner similar to that of MstopoI. Substitution of the acidic residues, D111 and E115 which are involved in Mg2+ co-ordination, to alanines affected the DNA relaxation activity. Unlike the wild type enzyme, D111A was dependent on Mg2+ for DNA cleavage and both the mutants were compromised in religation. The monoclonal antibody (mAb), 2F3G4, developed against MstopoI inhibited the relaxation activity of MttopoI. These studies affirm the characteristics of MttopoI to be similar to MstopoI and set a stage to target it for the development of specific small molecule inhibitors. (C) 2012 Elsevier Inc. All rights reserved.

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Song-selection and mood are interdependent. If we capture a song’s sentiment, we can determine the mood of the listener, which can serve as a basis for recommendation systems. Songs are generally classified according to genres, which don’t entirely reflect sentiments. Thus, we require an unsupervised scheme to mine them. Sentiments are classified into either two (positive/negative) or multiple (happy/angry/sad/...) classes, depending on the application. We are interested in analyzing the feelings invoked by a song, involving multi-class sentiments. To mine the hidden sentimental structure behind a song, in terms of “topics”, we consider its lyrics and use Latent Dirichlet Allocation (LDA). Each song is a mixture of moods. Topics mined by LDA can represent moods. Thus we get a scheme of collecting similar-mood songs. For validation, we use a dataset of songs containing 6 moods annotated by users of a particular website.

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Facet-based sentiment analysis involves discovering the latent facets, sentiments and their associations. Traditional facet-based sentiment analysis algorithms typically perform the various tasks in sequence, and fail to take advantage of the mutual reinforcement of the tasks. Additionally,inferring sentiment levels typically requires domain knowledge or human intervention. In this paper, we propose aseries of probabilistic models that jointly discover latent facets and sentiment topics, and also order the sentiment topics with respect to a multi-point scale, in a language and domain independent manner. This is achieved by simultaneously capturing both short-range syntactic structure and long range semantic dependencies between the sentiment and facet words. The models further incorporate coherence in reviews, where reviewers dwell on one facet or sentiment level before moving on, for more accurate facet and sentiment discovery. For reviews which are supplemented with ratings, our models automatically order the latent sentiment topics, without requiring seed-words or domain-knowledge. To the best of our knowledge, our work is the first attempt to combine the notions of syntactic and semantic dependencies in the domain of review mining. Further, the concept of facet and sentiment coherence has not been explored earlier either. Extensive experimental results on real world review data show that the proposed models outperform various state of the art baselines for facet-based sentiment analysis.

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Background: A better understanding of the quality of cellular immune responses directed against molecularly defined targets will guide the development of TB diagnostics and identification of molecularly defined, clinically relevant M.tb vaccine candidates. Methods: Recombinant proteins (n = 8) and peptide pools (n = 14) from M. tuberculosis (M.tb) targets were used to compare cellular immune responses defined by IFN-gamma and IL-17 production using a Whole Blood Assay (WBA) in a cohort of 148 individuals, i.e. patients with TB + (n = 38), TB- individuals with other pulmonary diseases (n = 81) and individuals exposed to TB without evidence of clinical TB (health care workers, n = 29). Results: M.tb antigens Rv2958c (glycosyltransferase), Rv2962c (mycolyltransferase), Rv1886c (Ag85B), Rv3804c (Ag85A), and the PPE family member Rv3347c were frequently recognized, defined by IFN-gamma production, in blood from healthy individuals exposed to M.tb (health care workers). A different recognition pattern was found for IL-17 production in blood from M.tb exposed individuals responding to TB10.4 (Rv0288), Ag85B (Rv1886c) and the PPE family members Rv0978c and Rv1917c. Conclusions: The pattern of immune target recognition is different in regard to IFN-gamma and IL-17 production to defined molecular M.tb targets in PBMCs from individuals frequently exposed to M.tb. The data represent the first mapping of cellular immune responses against M.tb targets in TB patients from Honduras.

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Mycobacterium tuberculosis, the causative agent of tuberculosis, is at increased risk of accumulating damaged guanine nucleotides such as 8-oxo-dGTP and 8-oxo-GTP because of its residency in the oxidative environment of the host macrophages. By hydrolyzing the oxidized guanine nucleotides before their incorporation into nucleic acids, MutT proteins play a critical role in allowing organisms to avoid their deleterious effects. Mycobacteria possess several MutT proteins. Here, we purified recombinant M. tuberculosis MutT2 (MtuMutT2) and M. smegmatis MutT2 (MsmMutT2) proteins from M. tuberculosis (a slow grower) and M. smegmatis (fast growing model mycobacteria), respectively, for their biochemical characterization. Distinct from the Escherichia coli MutT, which hydrolyzes 8-oxo-dGTP and 8-oxo-GTP, the mycobacterial proteins hydrolyze not only 8-oxo-dGTP and 8-oxo-GTP but also dCTP and 5-methyl-dCTP. Determination of kinetic parameters (K-m and V-max) revealed that while MtuMutT2 hydrolyzes dCTP nearly four times better than it does 8-oxo-dGTP, MsmMutT2 hydrolyzes them nearly equally. Also, MsmMutT2 is about 14 times more efficient than MtuMutT2 in its catalytic activity of hydrolyzing 8-oxo-dGTP. Consistent with these observations, MsmMutT2 but not MtuMutT2 rescues E. coli for MutT deficiency by decreasing both the mutation frequency and A-to-C mutations (a hallmark of MutT deficiency). We discuss these findings in the context of the physiological significance of MutT proteins.

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Bacteria use a number of small basic proteins for organization and compaction of their genomes. By their interaction with DNA, these nucleoid-associated proteins (NAPs) also influence gene expression. Rv3852, a NAP of Mycobacterium tuberculosis, is conserved among the pathogenic and slow-growing species of mycobacteria. Here, we show that the protein predominantly localizes in the cell membrane and that the carboxy-terminal region with the propensity to form a transmembrane helix is necessary for its membrane localization. The protein is involved in genome organization, and its ectopic expression in Mycobacterium smegmatis resulted in altered nucleoid morphology, defects in biofilm formation, sliding motility, and change in apolar lipid profile. We demonstrate its crucial role in regulating the expression of KasA, KasB, and GroEL1 proteins, which are in turn involved in controlling the surface phenotypes in mycobacteria.

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In this paper, we present a novel approach that makes use of topic models based on Latent Dirichlet allocation(LDA) for generating single document summaries. Our approach is distinguished from other LDA based approaches in that we identify the summary topics which best describe a given document and only extract sentences from those paragraphs within the document which are highly correlated given the summary topics. This ensures that our summaries always highlight the crux of the document without paying any attention to the grammar and the structure of the documents. Finally, we evaluate our summaries on the DUC 2002 Single document summarization data corpus using ROUGE measures. Our summaries had higher ROUGE values and better semantic similarity with the documents than the DUC summaries.

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Approximately one third of the world population is infected with Mycobacterium tuberculosis, the causative agent of tuberculosis. A better understanding of the pathogen biology is crucial to develop new tools/strategies to tackle its spread and treatment. In the host macrophages, the pathogen is exposed to reactive oxygen species, known to damage dGTP and GTP to 8-oxo-dGTP and 8-oxo-GTP, respectively. Incorporation of the damaged nucleotides in nucleic acids is detrimental to organisms. MutT proteins, belonging to a class of Nudix hydrolases, hydrolyze 8-oxo-G nucleoside triphosphates/diphosphates to the corresponding nucleoside monophosphates and sanitize the nucleotide pool. Mycobacteria possess several MutT proteins. However, a functional homolog of Escherichia coli MutT has not been identified. Here, we characterized MtuMutT1 and Rv1700 proteins of M. tuberculosis. Unlike other MutT proteins, MtuMutT1 converts 8-oxo-dGTP to 8-oxo-dGDP, and 8-oxo-GTP to 8-oxo-GDP. Rv1700 then converts them to the corresponding nucleoside monophosphates. This observation suggests the presence of a two-stage mechanism of 8-oxo-dGTP/8-oxo-GTP detoxification in mycobacteria. MtuMutT1 converts 8-oxo-dGTP to 8-oxo-dGDP with a K-m of similar to 50 mu M and V-max of similar to 0.9 pmol/min per ng of protein, and Rv1700 converts 8-oxo-dGDP to 8-oxo-dGMP with a K-m of similar to 9.5 mu M and V-max of similar to 0.04 pmol/min per ng of protein. Together, MtuMutT1 and Rv1700 offer maximal rescue to E. coli for its MutT deficiency by decreasing A to C mutations (a hallmark of MutT deficiency). We suggest that the concerted action of MtuMutT1 and Rv1700 plays a crucial role in survival of bacteria against oxidative stress.

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The relative levels of different sigma factors dictate the expression profile of a bacterium. Extracytoplasmic function sigma factors synchronize the transcriptional profile with environmental conditions. The cellular concentration of free extracytoplasmic function sigma factors is regulated by the localization of this protein in a sigma/anti-sigma complex. Anti-sigma factors are multi-domain proteins with a receptor to sense environmental stimuli and a conserved anti-sigma domain (ASD) that binds a sigma factor. Here we describe the structure of Mycobacterium tuberculosis anti-sigma(D) (RsdA) in complex with the -35 promoter binding domain of sigma(D) (sigma(D)(4)). We note distinct conformational features that enable the release of sigma(D) by the selective proteolysis of the ASD in RsdA. The structural and biochemical features of the sigma(D)/RsdA complex provide a basis to reconcile diverse regulatory mechanisms that govern sigma/anti-sigma interactions despite high overall structural similarity. Multiple regulatory mechanisms embedded in an ASD scaffold thus provide an elegant route to rapidly re-engineer the expression profile of a bacterium in response to an environmental stimulus.

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Latent variable methods, such as PLCA (Probabilistic Latent Component Analysis) have been successfully used for analysis of non-negative signal representations. In this paper, we formulate PLCS (Probabilistic Latent Component Segmentation), which models each time frame of a spectrogram as a spectral distribution. Given the signal spectrogram, the segmentation boundaries are estimated using a maximum-likelihood approach. For an efficient solution, the algorithm imposes a hard constraint that each segment is modelled by a single latent component. The hard constraint facilitates the solution of ML boundary estimation using dynamic programming. The PLCS framework does not impose a parametric assumption unlike earlier ML segmentation techniques. PLCS can be naturally extended to model coarticulation between successive phones. Experiments on the TIMIT corpus show that the proposed technique is promising compared to most state of the art speech segmentation algorithms.