Database Commons
Database Commons

a catalog of worldwide biological databases

Database Profile

MiST

General information

URL: https://mistdb.com
Full name: microbial signal transduction database
Description: MiST is a comprehensive library of the signal transduction proteins from completely sequenced bacterial and archaeal genomes.
Year founded: 2007
Last update: 2019
Version: v3
Accessibility:
Accessible
Country/Region: United States

Classification & Tag

Data type:
DNA
Data object:
Database category:
Major species:
NA
Keywords:

Contact information

University/Institution: University of Tennessee
Address:
City:
Province/State:
Country/Region: United States
Contact name (PI/Team): Ulrich LE
Contact email (PI/Helpdesk): ulrichle@ornl.gov

Publications

19900966
The MiST2 database: a comprehensive genomics resource on microbial signal transduction. [PMID: 19900966]
Ulrich LE, Zhulin IB.

The MiST2 database (http://mistdb.com) identifies and catalogs the repertoire of signal transduction proteins in microbial genomes. Signal transduction systems regulate the majority of cellular activities including the metabolism, development, host-recognition, biofilm production, virulence, and antibiotic resistance of human pathogens. Thus, knowledge of the proteins and interactions that comprise these communication networks is an essential component to furthering biomedical discovery. These are identified by searching protein sequences for specific domain profiles that implicate a protein in signal transduction. Compared to the previous version of the database, MiST2 contains a host of new features and improvements including the following: draft genomes; extracytoplasmic function (ECF) sigma factor protein identification; enhanced classification of signaling proteins; novel, high-quality domain models for identifying histidine kinases and response regulators; neighboring two-component genes; gene cart; better search capabilities; enhanced taxonomy browser; advanced genome browser; and a modern, biologist-friendly web interface. MiST2 currently contains 966 complete and 157 draft bacterial and archaeal genomes, which collectively contain more than 245 000 signal transduction proteins. The majority (66%) of these are one-component systems, followed by two-component proteins (26%), chemotaxis (6%), and finally ECF factors (2%).

Nucleic Acids Res. 2010:38(Database issue) | 207 Citations (from Europe PMC, 2025-12-20)
17135192
MiST: a microbial signal transduction database. [PMID: 17135192]
Ulrich LE, Zhulin IB.

Signal transduction pathways control most cellular activities in living cells ranging from regulation of gene expression to fine-tuning enzymatic activity and controlling motile behavior in response to extracellular and intracellular signals. Because of their extreme sequence variability and extensive domain shuffling, signal transduction proteins are difficult to identify, and their current annotation in most leading databases is often incomplete or erroneous. To overcome this problem, we have developed the microbial signal transduction (MiST) database (http://genomics.ornl.gov/mist), a comprehensive library of the signal transduction proteins from completely sequenced bacterial and archaeal genomes. By searching for domain profiles that implicate a particular protein as participating in signal transduction, we have systematically identified 69 270 two- and one-component proteins in 365 bacterial and archaeal genomes. We have designed a user-friendly website to access and browse the predicted signal transduction proteins within various organisms. Further capabilities include gene/protein sequence retrieval, visualized domain architectures, interactive chromosomal views for exploring gene neighborhood, advanced querying options and cross-species comparison. Newly available, complete genomes are loaded into the database each month. MiST is the only comprehensive and up-to-date electronic catalog of the signaling machinery in microbial genomes.

Nucleic Acids Res. 2007:35(Database issue) | 87 Citations (from Europe PMC, 2025-12-20)

Ranking

All databases:
924/6895 (86.613%)
Pathway:
58/451 (87.361%)
924
Total Rank
289
Citations
16.056
z-index

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Record metadata

Created on: 2018-01-27
Curated by:
Lina Ma [2022-04-26]
Fatima Batool [2018-12-27]
Tongkun Guo [2018-02-25]