Mycobacterium marinum Lausanne 1848 is a bacterium of the family Mycobacteriaceae.
genome sequence Bacteria| @ref 20215 |
|
|
| Domain Bacteria |
| Phylum Actinomycetota |
| Class Actinomycetes |
| Order Mycobacteriales |
| Family Mycobacteriaceae |
| Genus Mycobacterium |
| Species Mycobacterium marinum |
| Full scientific name Mycobacterium marinum Aronson 1926 (Approved Lists 1980) |
| @ref | Name | Growth | Medium link | Composition | |
|---|---|---|---|---|---|
| 11107 | LÖWENSTEIN-JENSEN MEDIUM (DSMZ Medium 354) | Medium recipe at MediaDive | Name: LÖWENSTEIN-JENSEN MEDIUM (DSMZ Medium 354) Composition: Potato flour 18.6104 g/l L-Asparagin 2.23325 g/l KH2PO4 1.55087 g/l Mg-citrate 0.372208 g/l Malachite green 0.248139 g/l MgSO4 0.148883 g/l Glycerol Fresh egg mixture Distilled water | ||
| 11107 | MIDDLEBROOK MEDIUM (DSMZ Medium 645) | Medium recipe at MediaDive | Name: MIDDLEBROOK MEDIUM (DSMZ Medium 645) Composition: Bacto Middlebrook 7H10 agar 20.9945 g/l Glycerol Distilled water | ||
| 11107 | PEPTONE - MEAT EXTRACT - SOIL EXTRACT AGAR (PFE) (DSMZ Medium 251) | Medium recipe at MediaDive | Name: PEPTONE - MEAT EXTRACT - SOIL EXTRACT AGAR (PFE) (DSMZ Medium 251) Composition: Glycerol 20.0 g/l Agar 20.0 g/l Proteose peptone no. 3 5.0 g/l Meat extract 3.0 g/l Soil extract Distilled water |
| @ref | Growth | Type | Temperature (°C) | |
|---|---|---|---|---|
| 11107 | positive | growth | 22-28 |
| @ref | Description | Assembly level | INSDC accession | BV-BRC accession | IMG accession | NCBI tax ID | Score | |
|---|---|---|---|---|---|---|---|---|
| 66792 | ASM343160v1 assembly for Mycobacterium marinum DSM 43519 | scaffold | 1781 | 35.35 |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125439 | spore_formation | BacteriaNetⓘ | yes | 75.00 | no |
| 125439 | motility | BacteriaNetⓘ | no | 96.30 | no |
| 125439 | gram_stain | BacteriaNetⓘ | positive | 96.80 | no |
| 125439 | oxygen_tolerance | BacteriaNetⓘ | microaerophile | 88.50 | no |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positiveⓘ | yes | 87.46 | no |
| 125438 | anaerobic | anaerobicⓘ | no | 98.16 | no |
| 125438 | aerobic | aerobicⓘ | yes | 80.26 | no |
| 125438 | spore-forming | spore-formingⓘ | no | 63.80 | no |
| 125438 | thermophilic | thermophileⓘ | no | 95.00 | no |
| 125438 | flagellated | motile2+ⓘ | no | 92.50 | no |
| #11107 | Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 43519 |
| #20215 | Parte, A.C., Sardà Carbasse, J., Meier-Kolthoff, J.P., Reimer, L.C. and Göker, M.: List of Prokaryotic names with Standing in Nomenclature (LPSN) moves to the DSMZ. IJSEM ( DOI 10.1099/ijsem.0.004332 ) |
| #66792 | Julia Koblitz, Joaquim Sardà, Lorenz Christian Reimer, Boyke Bunk, Jörg Overmann: Automatically annotated for the DiASPora project (Digital Approaches for the Synthesis of Poorly Accessible Biodiversity Information) . |
| #125438 | Julia Koblitz, Lorenz Christian Reimer, Rüdiger Pukall, Jörg Overmann: Predicting bacterial phenotypic traits through improved machine learning using high-quality, curated datasets. 2024 ( DOI 10.1101/2024.08.12.607695 ) |
| #125439 | Philipp Münch, René Mreches, Martin Binder, Hüseyin Anil Gündüz, Xiao-Yin To, Alice McHardy: deepG: Deep Learning for Genome Sequence Data. R package version 0.3.1 . |
| #126262 | A. Lissin, I. Schober, J. F. Witte, H. Lüken, A. Podstawka, J. Koblitz, B. Bunk, P. Dawyndt, P. Vandamme, P. de Vos, J. Overmann, L. C. Reimer: StrainInfo—the central database for linked microbial strain identifiers. ( DOI 10.1093/database/baaf059 ) |
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If you want to cite this particular strain cite the following doi:
https://doi.org/10.13145/bacdive8271.20251217.10
When using BacDive for research please cite the following paper
BacDive in 2025: the core database for prokaryotic strain data