The structure of Rv3717 reveals a novel amidase from Mycobacterium tuberculosis

The article is OPEN ACCESS: 

http://journals.iucr.org/d/issues/2013/12/00/lv5048/index.html

The structure of Rv3717 reveals a novel amidase from Mycobacterium tuberculosis

A. Kumar, S. Kumar, D. Kumar, A. Mishra, R. P. Dewangan, P. Shrivastava, S. Ramachandran and B. Taneja

Abstract: Bacterial N-acetylmuramoyl-L-alanine amidases are cell-wall hydrolases that hydrolyze the bond between N-acetylmuramic acid and L-alanine in cell-wall glycopeptides. Rv3717 ofMycobacterium tuberculosis has been identified as a unique autolysin that lacks a cell-wall-binding domain (CBD) and its structure has been determined to 1.7 Å resolution by the Pt-­SAD phasing method. Rv3717 possesses an /-fold and is a zinc-dependent hydrolase. The structure reveals a short flexible hairpin turn that partially occludes the active site and may be involved in autoregulation. This type of autoregulation of activity of PG hydrolases has been observed in Bartonella henselae amidase (AmiB) and may be a general mechanism used by some of the redundant amidases to regulate cell-wall hydrolase activity in bacteria. Rv3717 utilizes its net positive charge for substrate binding and exhibits activity towards a broad spectrum of substrate cell walls. The enzymatic activity of Rv3717 was confirmed by isolation and identification of its enzymatic products by LC/MS. These studies indicate that Rv3717, an N-acetylmuramoyl-L-alanine amidase from M. tuberculosis, represents a new family of lytic amidases that do not have a separate CBD and are regulated conformationally.

PDB reference: 4lq6

The article is OPEN ACCESS

http://journals.iucr.org/d/issues/2013/12/00/lv5048/index.html

Integrated gene co-expression network analysis in the growth phase of Mycobacterium tuberculosis reveals new potential drug targets.

http://pubs.rsc.org/en/content/articlelanding/2013/mb/c3mb70278b#!divAbstract

We have carried out weighted gene co-expression network analysis of Mycobacterium tuberculosis to gain insights into gene expression architecture during log phase growth. The differentially expressed genes between at least one pair of 11 different M. tuberculosis strains as source of biological variability were used for co-expression network analysis. This data included genes with highest coefficient of variation in expression. Five distinct modules were identified using topological overlap based clustering. All the modules together showed significant enrichment in biological processes: fatty acid biosynthesis, cell membrane, intracellular membrane bound organelle, DNA replication, Quinone biosynthesis, cell shape and peptidoglycan biosynthesis, ribosome and structural constituents of ribosome and transposition. We then extracted the co-expressed connections which were supported either by transcriptional regulatory network or STRING database or high edge weight of topological overlap. The genes trpC, nadC, pitA, Rv3404c, atpA, pknA, Rv0996, purB, Rv2106 and Rv0796 emerged as top hub genes. After overlaying this network on the iNJ661 metabolic network, the reactions catalyzed by 15 highly connected metabolic genes were knocked down in silico and evaluated by Flux Balance Analysis. The results showed that in 12 out of 15 cases, in 11 more than 50% of reactions catalyzed by genes connected through co-expressed connections also had altered fluxes. The modules ‘Turquoise’, ‘Blue’ and ‘Red’ also showed enrichment in essential genes. We could map 152 of the previously known or proposed drug targets in these modules and identified 15 new potential drug targets based on their high degree of co-expressed connections and strong correlation with module eigengenes.

The Need of New Drugs for TB- It's Time for Action

Research resources for tuberculosis

Tuberculist: http://tuberculist.epfl.ch/ The TubercuList knowledge base integrates genome details, protein information, drug and transcriptome data, mutant and operon annotation, bibliography, structural views and comparative genomics, in a structured manner required for the rational development of new diagnostic, therapeutic and prophylactic measures against tuberculosis. With the means of expert curation and continuous updates, we deliver a broad view of the Mycobacterium tuberculosis genome.

TB Database: http://www.tbdb.org/ Tuberculosis (TB) is a public health challenge of paramount importance. Control of TB will require a multifaceted approach integrating efficient public health interventions with the discovery and use of new vaccines and drugs. TBDatabase (TBDB) makes available the tools and resources available at the Stanford Microarray Database and the Broad Institute. Anyone is welcome to access the published data available on the TBDB site without signing in. Some data in TBDB are unpublished and can therefore only be accessed by the authors and their collaborators after they sign in. The "Access Polices" page provides more information about TBDB accounts. A grant from the Bill & Melinda Gates Foundation has enabled us to create an integrated software platform for tuberculosis drug discovery and research. Learn more >

webTB.org:  http://www.webtb.org/ a resource for Mycobacterium tuberculosis researchers is brought to you by the TB Structural Genomics Consortium with lots of tools: Gene expression correlation display: This server presents the pair wise gene expression correlation for two or more genes. For a set of genes you can get all the pair wise correlations and express it as a matrix, graphically display it.Operon Search: Search for operons and directions in the TB genome. Known operons are listed by name. These data will be expanded as more sources are found. BLAST the TB genome: BLAST a sequence against the TB genome and other NCBI databases. Target Explorer: Target Explorer is intended to be an interactive web site that allows researchers in the Tuberculosis research community to experiment with different target selection criteria and explore alternative ways of prioritizing gene targets for experimentation (crystallization structure solution, high-throughput screening for inhibitor discovery, etc.) Mycobacterial Genome DataBase: The site is a database of genomes of mycobacterial strains sequenced in the lab of James C. Sacchettini at Texas A&M University. It provides access to sequence data (including coverage statistics) and comparison of polymorphisms among various strains of tuberculosis, with a focus on drug-resistance. The sequencing is done on an Illumina GenomeAnalyzer II (short reads). The data was analyzed using customized sequence-assembly methods written by Tom Ioerger and his group at Texas A&M. The Genome browser: Graphically scan the entire TB genome for information on each ORF with indications of any predicted operons and includes links back to the quick search page for more gene information ORF Progress search tool: Search the status and progress of MTb ORFs that are targeted and pursued by consortium members. Structure Gallery: See the protein structures determined by members of the consortium.Structure Summary pagesThis page is a front page portal to the structure information on known TB proteins. All other WebTB servers can be accessed from this page, including the Gallery and JMOL viewer. MTBreg Database: A database of proteins up- and down-regulated in Mycobacterium tuberculosis grown under conditions mimicking infection as well as information on proteins that are regulated by selected transcription factors or other regulatory proteins. TBDB Legacy Tools: Legacy tools from the former TBSGC site to search and browse the TB Genome

TBDreamDB : http://www.tbdreamdb.com/index.html Exciting news at TBDreamDB! The Database is currently undergoing complete redesign and data evaluation. The database will be converted to a fully searchable relational Database with a new look front end website as well. We hope to have the beta design up and running towards the end of 2011 early 2012. Any feedback would be great, simply contact us at the curator email below. Also please keep sending in any errors you find in the dataset. The data is being evaluated and corrected as it is being inserted into the new database format. -Your Emails are much appreciated!

Sanger Institute Welcome Trust: The Wellcome Trust and DEFRA has funded the Sanger Instiute to sequence reference genomes for Mycobacterium africanum http://www.sanger.ac.uk/resources/downloads/bacteria/mycobacterium.html Mycobacterium is a genus within the order Actinomycetales that comprises a large number of well characterised species, several of which are associated with human and animal disease such as tuberculosis and leprosy.

MGDD : http://mirna.jnu.ac.in/mgdd/index.html (Mycobacterial Genome Divergence Database) is a repository of genetic differences among different strains and species of organisms belonging to Mycobacterium tuberculosis complex. The differences are based on comparison of user chosen organisms. The query sequences are used to compare against subject sequences. The users can also choose the type of genetic divergence, that is, SNPs (Single Nucleotide Polymorphism), insertions, repeat expansion and divergent sequences that they are interested in. The results from a specific region (based on boundary defined by nucleotide sequence) or a specific gene can be displayed based on user's choice. Presently, the database has precomputed analysis from three different fully sequenced genomes of this complex. These are Mycobacterium tuberculosis H37Rv, Mycobacterium tuberculosis CDC1551 and Mycobacterium bovis AF2122/97. In future it will be updated with more strains species as fully sequenced genomes become available.

MTBreg: http://www.doe-mbi.ucla.edu/Services/MTBreg/ Proteins up- and down- regulated in Mycobacterium tuberculosis grown under conditions mimicking infection are included in this database. It also includes information on proteins that are regulated by selected transcription factors or other regulatory proteins. The literature data provided here is complimentary to the databases provided by Michael Strong that include recent TB computational functional linkages and the Prolinks Database by Peter Bowers.

MycoperonDB:  http://cdfd.org.in/mycoperondb/home.html is a database of computationaly predicted operons and transcriptional units of Mycobacteria. MycoperonDB is setup to provide operon and trancriptional unit information of different mycobacterial species at one place. At present, this database covers five species from mycobacteria and consist of an insilico model of operon organization of 18,053 genes . The operon information provides a basis and a refenece for a comprehensive understanding of how the transcriptional control are encoded in genome. The database has a user friendly web interface which takes simple sequence, gene name or ORF ID as an input and reports the transcription unit and operon associated with the input query.

GenoMycDB Browser: http://157.86.176.108/~catanho/genomycdb/ 

Several databases and computational tools have been created with the aim of organizing, integrating and analyzing the wealth of information generated by large-scale sequencing projects of mycobacterial genomes and those of other organisms. However, with very few exceptions, these databases and tools do not allow for massive and/or dynamic comparison of these data. GenoMycDB (http://www.dbbm.fiocruz.br/GenoMycDB) is a relational database built for large-scale comparative analyses of completely sequenced mycobacterial genomes, based on their predicted protein content. Its central structure is composed of the results obtained after pair-wise sequence alignments among all the predicted proteins coded by the genomes of six mycobacteria: Mycobacterium tuberculosis (strains H37Rv and CDC1551), M. bovis AF2122/97, M. avium subsp. paratuberculosis K10, M. leprae TN, and M. smegmatis MC2 155. The database stores the computed similarity parameters of every aligned pair, providing for each protein sequence the predicted subcellular localization, the assigned cluster of orthologous groups, the features of the corresponding gene, and links to several important databases. Tables containing pairs or groups of potential homologs between selected species/strains can be produced dynamically by user-defined criteria, based on one or multiple sequence similarity parameters. In addition, searches can be restricted according to the predicted subcellular localization of the protein, the DNA strand of the corresponding gene and/or the description of the protein. Massive data search and/or retrieval are available, and different ways of exporting the result are offered. GenoMycDB provides an on-line resource for the functional classification of mycobacterial proteins as well as for the analysis of genome structure, organization, and evolution.

TB Drug Target Database: http://www.bioinformatics.org/tbdtdb/ TB Drug Target Database contains information on the antituberculer drugs and the target proteins for the treatment of TB. Informations are avilable on the drugs and other possible inhibitors including their Structural details, also the analysis made to the target proteins are made available.

MIRU-VNTRplus web application: http://www.miru-vntrplus.org/MIRU/index.faces Molecular typing of bacteria from the Mycobacterium tuberculosis complex (MTBC) is essential for epidemiological purposes such as investigating the spreading of specific genotypes. Recently, mycobacterial interspersed repetitive units (MIRU) typing has become an important method, as it allows high-throughput, discriminatory and reproducible analysis of clinical isolates. MIRU is a MTBC specific name of a multiple locus VNTR [variable number of tandem repeats] analysis (MLVA) bacterial typing scheme. Because of its portable data format, MIRU typing has the potential to be a versatile tool for individual strain identification based on large reference databases. However, specialized bioinformatic web tools to analyze MIRU data and public reference databases are not available. To meet this need, a collection of 186 strains representing the major MTBC lineages was used for implementing a web server, MIRU-VNTRplus (http://www.miru-vntrplus.org/). For each strain species, lineage, and epidemiologic information was stored together with copy numbers of 24 MIRU loci, spoligotyping patterns, regions of difference (RD) profiles, single nucleotide polymorphisms (SNPs), susceptibility data, and IS6110 RFLP fingerprint images. Via the freely accessible MIRU-VNTRplus service users can compare their strain(s) with the reference strains for the assignment of MTBC species, lineages, and genotypes. For easier scientific communication a universal expanding nomenclature (MLVA MtbC15-9) to name different MIRU genotypes is maintained at the server. Comparisons can be based on MIRU-, spoligo-, RD-, SNP-, susceptibility-typing data, or by a combination of different data types. Several distance coefficients are available, including Jaccard's and categorical. Based upon the respective distance matrix, a dendrogram can be calculated using UPGMA or neighbor-joining clustering algorithms. The resulting trees may be exported in various data formats. MIRU-VNTRplus provides also functions for the user to analyze own strains without interrogating the reference database. Extensive documentation (manual and tutorials) of the service is available to make best use of all features.

Web resources for Mycobacterium tuberculosis

Mycobacterium tuberculosis the causative agent of tuberculosis (TB) still the major killer among human population, that has co-evolved with the human civilization so beautifully and so robustly, is really surprising. The war against tuberculosis is on and we are trying here to integrate major resources that are available for the disease and the organism all over the web to a single place. This is one of the open articles that would be upgraded time to time for acknowledging the recent development in the field, so that you as a used need not spend much time in data collection and integration. Hope this helps.   

General information about tuberculosis: 

Wiki page on tuberculosis on Wikipedia: http://en.wikipedia.org/wiki/Tuberculosis Tuberculosis, MTB, or TB (short for tubercle bacillus) is a common, and in many cases lethal, infectious disease caused by various strains of mycobacteria, usually Mycobacterium tuberculosis. Tuberculosis usually attacks the lungs but can also affect other parts of the body. It is spread through the air when people who have an active MTB infection cough, sneeze, or otherwise transmit their saliva through the air. Most infections in humans result in an asymptomatic, latent infection, and about one in ten latent infections eventually progress to active disease, which, if left untreated, kills more than 50% of those infected.

Wiki page on M. tuberculosis:   Mycobacterium tuberculosis (MTB) is a pathogenic bacterial species in the genus Mycobacterium and the causative agent of most cases of tuberculosis (TB). First discovered in 1882 by Robert Koch, M. tuberculosis has an unusual, waxy coating on its cell surface (primarily mycolic acid), which makes the cells impervious to Gram staining, so acid-fast detection techniques are used, instead. The physiology of M. tuberculosis is highly aerobic and requires high levels of oxygen. Primarily a pathogen of the mammalian respiratory system, MTB infects the lungs. The most frequently used diagnostic methods for TB are the tuberculin skin test, acid-fast stain, and chest radiographs. The M. tuberculosis genome was sequenced in 1998. 

Centers for Disease Control and Prevention (CDC) page on tuberculosis: Tuberculosis (TB) is a disease caused by a bacterium called Mycobacterium tuberculosis. The bacteria usually attack the lungs, but TB bacteria can attack any part of the body such as the kidney, spine, and brain. If not treated properly, TB disease can be fatal. TB disease was once the leading cause of death in the United States. Focusing on Data and Statistics, Diseases and Conditions, Emergencies and Disasters, Environmental Health, Healthy Living, Injury, Violence and Safety, Life Stages and Populations, Travelers' Health, Workplace Safety and Health,  Learn More »

Global TB database: http://www.who.int/tb/country/global_tb_database/en/index2.html Access the database to make data queries, interactive maps and country profiles. Country profiles: Country profiles provide key indicators, notification and treatment outcome data, and budget and financing graphs (for a subset of countries, including all high-burden countries). For high-burden countries, there is also a brief overview of TB control and epidemiology in the country, and a summary of achievements, challenges and planned activities related to implementing the first 5 components of the Stop TB Strategy.

U.S. National Library of Medicine Resource on tuberculosis:  Has a resourced on various fields of the disease, from the basics to the advanced including the disease data.

WHO page on tuberculosis: Too many people have undetected TB for too long; late detection of TB increases their risk of transmitting the disease to others, having poor health outcomes, or that they and their family will suffer distress and economic hardship. WHO has produced an overview of approaches, guidelines and tools to improve early detection of TB. It presents a framework to assess barriers for early detection and helps identify appropriate actions.

The Stop TB Partnership: The Stop TB Partnership is leading the way to a world without tuberculosis (TB), a disease that is curable but still kills three people every minute. Founded in 2001, the Partnership's mission is to serve every person who is vulnerable to TB and ensure that high-quality treatment is available to all who need it. Together our nearly 1000 partners are a collective force that is transforming the fight against TB in more than 100 countries. They include international and technical organizations, government programmes, research and funding agencies, foundations, NGOs, civil society and community groups and the private sector. We operate through a secretariat hosted by the World Health Organization (WHO) in Geneva, Switzerland and seven working groups whose role is to accelerate progress on access to TB diagnosis and treatment; research and development for new TB diagnostics, drugs and vaccines; and tackling drug resistant- and HIV-associated TB. The secretariat is governed by a coordinating board that sets strategic direction for the global fight against TB.