Welcome to the Mycoplasma genitalium database!
M. genitalium is a gram-positive bacterium and human pathogen. Among all freely-culturable organism, M. genitalium has the smallest genome, containing slightly more than 580 kb. Primarily due to its reduced genome size, M. genitalium has been the subject of intense research over the past thirty years. M. genitalium was the second organism to be completely sequenced, and the first organism to have its genome completely synthesized de novo and to be comprehensively modeled. M. genitalium's close relatives have also been the first to have their genome be transplated into a recipient cell. This PGDB provides a comprehensive description of M. genitalium molecular biology.
Cross references
Taxonomy: 243273, ATCC: 33530, BioProject: 97, CMR: gmg, GenBank: L43967, RefSeq: NC_000908
Genetic code
Mold, protozoa, coelenterate mitochondria, mycoplasma, and spiroplasma (4)
Content
| Content | Value | Units | Content | Value | Units | Content | Value | Units | |||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Compartments | 6 | Proteins | 683 | Transcriptional regulation | |||||||
| Chromosomes | 1 | Monomers | 482 | Interactions | 30 | ||||||
| Length | 580076 | nt | DNA-binding | 17 | Transcriptional regulators | 5 | |||||
| GC-content | 31.7 | % | Integral membrane | 85 | Regulated promoters | 26 | |||||
| Transcription units | 335 | Lipoprotein | 14 | Pathways | 17 | ||||||
| Monocistrons | 231 | Secreted | 20 | Stimuli | 10 | ||||||
| Polycistrons | 104 | Terminal organelle | 8 | Quantitative parameters | 1836 | ||||||
| Genes | 525 | Complexes | 201 | Cell composition | 73 | ||||||
| mRNA | 482 | DNA-binding | 39 | Media composition | 83 | ||||||
| rRNA | 3 | Reactions | 1857 | Reaction Keq | 225 | ||||||
| sRNA | 4 | DNA damage | 137 | Reaction Km | 483 | ||||||
| tRNA | 36 | DNA repair | 32 | Reaction Vmax | 434 | ||||||
| Chromosome features | 2305 | Metabolic | 645 | RNA expression | 525 | ||||||
| DnaA boxes | 2283 | Protein decay | 40 | RNA half-lives | 525 | ||||||
| Short tandem repeats | 19 | Protein modification | 63 | Stimulus values | 10 | ||||||
| Other | 3 | Replication Initiation | 15 | Transcr. reg. activity | 2 | ||||||
| Metabolites | 722 | RNA decay | 25 | Transcr. reg. affinity | 30 | ||||||
| Amino acids | 29 | RNA modification | 91 | Other | 154 | ||||||
| Antibiotic | 32 | RNA processing | 20 | Processes | 28 | ||||||
| Gases | 4 | Transcription | 4 | States | 16 | ||||||
| Ions | 19 | Translation | 20 | ||||||||
| Lipids | 82 | tRNA aminoacylation | 39 | ||||||||
| Vitamins | 27 | Other | 726 |
Data sources
About WholeCellKB
WholeCellKB is a collection of free, open-source model organism databases designed specifically to enable comprehensive, dynamic simulations of entire cells and organisms. WholeCellKB provides comprehensive, quantitative descriptions of individual species including:
- Cellular chemical composition,
- Growth medium composition,
- Gene locations, lengths, and directions,
- Transcription unit organization and transcriptional regulation,
- Macromolecule composition,
- Reaction stoichiometry, kinetics, and catalysis, and
- Extensive links and cross-links to all references used to construct each database.
WholeCellKB currently contains a single database of Mycoplasma genitalium, an extremely small gram-positive bacterium and common human pathogen. This database is the most comprehensive description of any single organism to date, and was used to develop the first whole-cell computational model. The M. genitalium database was curated from over 900 primary research articles, reviews, books, and databases over four years by a team of three researchers at Stanford University.
Getting started
The best ways to get started are to browse or search this database using the menu or the search box at the top of this page. See the tutorial for additional help getting started.
More information
Please see the following for more information or to cite WholeCellKB:
Karr JR, Sanghvi JC, Macklin DN, Arora A, Covert MW. WholeCellKB: Model Organism Databases for Comprehensive Whole-Cell Models. Nucleic Acids Research 41, D787-D792 (2013). Nucleic Acids Research | PubMed
Karr JR, Sanghvi JC, Macklin DN, Gutschow MV, Jacobs JM, Bolival B, Assad-Garcia N, Glass JI, Covert MW. A Whole-Cell Computational Model Predicts Phenotype from Genotype. Cell 150, 389-401 (2012). Cell | PubMed
Need help?
Please view the tutorial, about page, or contact us at wholecell@lists.stanford.edu.
