Mycobacterium tuberculosis is one of the most successful pathogens in the world, still responsible for millions of deaths each year. Nearly half of its protein coding genes have functions that are unknown. This website aggregates information and data our group and others on the functions and updated annotations of genes in the M. tuberculosis H37Rv genome.

Functional classes of Mtb genes	Latest News
	6-16-2024: Added annotations from TBCAP and links to BioCyc on each gene page 1-9-2024: Posted RNAseq and TnSeq datasets on Datasets.html page 2-24-2023: Added gene modules based on analysis of transcriptomic datasets 8-25-2022: Added links to genes with correlated TnSeq profiles (TnSeqCorr) 7-26-2022: Added updated annotations based on recent publications 10-13-2021: Updated top 10 homologs in PDB for each gene; add links to PATRIC 10-01-2021: Added links to Vulnerability Index and AlphaFold model for each gene; Improved Search (so keywords work, not just ORF ids and gene names) 04-28-2021: Added Gene Expression data on transcriptional responses to drug treatments (Boshoff et al, 2004) 03-14-2018: Updated GO terms from Uniprot 03-14-2018: Added enzyme reactions from iSM810 metabolic model Several targets have had spot titer images uploaded to the website under the 'links to additional information' section: /U19/genes/detail/Rv1475c/ Click on 'Photo of spot titer' to pen the PDF file with the images: /media/RawData/Misc/Rv1475c/Rv1475c_spot.pdf 09-19-2017: New TnSeq data added for PPE68, EccD1, PE35 and EspI [expand] TnSeq data has been added for PPE68, EccD1, PE35 and EspI knockouts. Data can be found in their respective gene pages: /U19/genes/detail/Rv3877/ ABMP data has been added for Rv0480c, Rv1059, Rv2971, and Rv3368c knockouts. Data can be found in their respective gene pages: /U19/genes/detail/Rv1059/ ORF pages now have new operon images that include ncRNAs, tRNAs, sRNAs, rRNAs, and transcriptional start sites. You can click on any ORF arrow (blue) or name in the image to go directly to that ORF's page. Take a look: /U19/genes/detail/Rv2869c/ We have added more ABMP data using a new analysis method. Check out an example: /U19/genes/detail/Rv3285/ For an explanation of the analysis, see this document: /media//ABMP_score.pdf http://orca1.tamu.edu/essentiality/transit/ /U19/genes/go/list/ The following genes have new metabolomic data added to their gene pages: Orf Name Description Type Rv1016c lpqT Probable conserved lipoprotein LpqT Conditional Rv1130 prpD Possible methylcitrate dehydratase PrpD Conditional Rv1713 engA Probable GTP-binding protein EngA Essential Rv3244c lpqB Probable conserved lipoprotein LpqB Essential Rv3280 accD5 Probable propionyl-CoA carboxylase beta chain 5 AccD5 (pccase) (propanoyl-CoA:carbon dioxide ligase) Essential Rv3311 - hypothetical protein Conditional Rv3722c - hypothetical protein Essential Rv3801c fadD32 Fatty-acid-AMP ligase FadD32 (fatty-acid-AMP synthetase) (fatty-acid-AMP synthase) Also shown to have acyl-ACP ligase activity Essential RNA-Seq data for H37Rv grown on various conditions is now available. Raw data can be obtained at GEO through this private link : http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?token=otwhmwyerjsrhsd&acc=GSE67035 The data can also be visualized by using the following tool: http://orca1.tamu.edu/U19_Expr/conditions.html Disruption of M. tuberculosis membrane protein PerM (Rv0955) resulted in an IFN-γ-dependent persistence defect in chronic mouse infection. See publication: Goodsmith N, Guo XV, Vandal OH1, Vaubourgeix J, Wang R, Botella H, Song S, Bhatt K, Liba A, Salgame P, Schnappinger D, Ehrt S. Disruption of an M. tuberculosis membrane protein causes a magnesium-dependent cell division defect and failure to persist in mice. PLoS Pathog. 2015 Feb 6;11(2):e1004645. doi: 10.1371/journal.ppat.1004645. eCollection 2015. http://www.ncbi.nlm.nih.gov/pubmed/25658098 Ganapathy et. al. Publication to be disclosed. GO-Terms Assigned: GO:1902693 and GO:0045454. Publication to be disclosed. GO-Term(s) Assigned: GO:0047547 Publication to be disclosed. Individual gene pages now include a section with clustering of the Boshoff Transcriptional Response Data, showing which other genes are significantly up- or down- regulated and in which conditions. Example: /U19/genes/detail/Rv0127/ We have added a shopping-like functionality to facilitate printing labels for samples. 1. Go to the sample list. 2. Click on the "shopping cart" icon to add samples you wish to print. 3. Go to the sample "shopping cart". 4. Add texts you wish to appear on the labels. 5. Click the "Print Labels" button to generate a PDF that can be printed on label paper. Click "Post a comment" at the bottom of a gene page to add a message or click reply to respond to other messages. Created a sequence design tool: FLUTE Sequence Builder The ability to analyze and visualize expression data is slowly being added to the website. This is a work in progress, and will be continually improved. You can see an example in the RNA-Seq Data section of Rv3263. Scrolling down to the "RNA-Seq Data section" and clicking [+] to expand the list of available data will provide options to download or analyze the data. This is a test of the notification system. Line Break.

Vast quantities of new genome sequence are added to public databases on a daily basis. But, while we are constantly deluged with new gene sequences we still have a limited ability to define their functions. Almost all functions are defined by comparison with genes from other strains in which experimental data are available. But these experimental data have not kept pace with the availability of new sequence. In fact, for most bacterial species, many genes have no known function and even those that are annotated have only limited information. This is particularly striking for Mycobacterium tuberculosis (Mtb), where only 52% of protein-coding genes have a putative function.

We plan to discover the roles of genes from Mtb, an important and widespread human pathogen, with previously unknown functions. Critically, we will target genes that fulfill vital roles in bacterial growth and survival, genes we have previously identified in genome-wide screens. This offers three major advantages. First, we will concentrate on only the most important unannotated genes. Second, phenotypes allow us to use the power of synthetic lethality to identify interactions. And third, phenotypes provide us with a context in which we can understand the outcome of biochemical and genetic assays. In addition to defining the roles for Mtb genes we aim to establish an efficient pathway for identifying gene function that can serve as a paradigm for other bacterial species. To accomplish this we will undertake an ambitious program to construct large numbers of Mtb mutants. This will be possible as we will take advantage of substantial mycobacterial genetic expertise among the participants. Moreover, we will use a number of analytic modalities brought in through a set of highly interconnected projects and cores.

This project was originally funded by the NIH as part of the NIAID Functional Genomics Program, under grant U19 AI107774 (2013-2018). The NIAID Functional Genomics Program for understanding the functions of uncharacterized genes in infectious disease pathogens will generate experimental data to determine the biochemical function(s) of hypothetical genes, unknown open reading frames, and noncoding RNAs. The program will apply state-of-the-art technologies to determine the biochemical and physiological roles of these gene components. Obtaining a more comprehensive understanding of uncharacterized genes in infectious disease pathogens will lead to improved genomic annotation and allow for the development of potential new targets for medical diagnostics, therapeutics and vaccines. The program will distribute data, software, and reagents generated from the research projects to the broader scientific community.

The successor of the original project has been funded by NIH as P01 AI143575 (Pathway Analysis in Tuberculosis; program director: S. Ehrt; 2020-2025).