Acetobacterium tundrae DSM 917 is a bacterium that was isolated from soil.
Bacteria| @ref 20215 |
|
|
| Domain Bacteria |
| Phylum Bacillota |
| Class Clostridia |
| Order Eubacteriales |
| Family Eubacteriaceae |
| Genus Acetobacterium |
| Species Acetobacterium tundrae |
| Full scientific name Acetobacterium tundrae Simankova et al. 2001 |
| BacDive ID | Other strains from Acetobacterium tundrae (1) | Type strain |
|---|---|---|
| 5411 | A. tundrae Z-4493, DSM 9173 (type strain) |
| @ref | Name | Growth | Medium link | Composition | |
|---|---|---|---|---|---|
| 394 | TRYPTICASE SOY YEAST EXTRACT MEDIUM (DSMZ Medium 92) | Medium recipe at MediaDive | Name: TRYPTICASE SOY YEAST EXTRACT MEDIUM (DSMZ Medium 92) Composition: Trypticase soy broth 30.0 g/l Agar 15.0 g/l Yeast extract 3.0 g/l Distilled water |
| @ref | Growth | Type | Temperature (°C) | |
|---|---|---|---|---|
| 394 | positive | growth | 30 |
| 394 | Sample typesoil |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positiveⓘ | yes | 62.26 | no |
| 125438 | anaerobic | anaerobicⓘ | yes | 88.78 | no |
| 125438 | spore-forming | spore-formingⓘ | no | 51.83 | no |
| 125438 | aerobic | aerobicⓘ | no | 92.48 | no |
| 125438 | thermophilic | thermophileⓘ | no | 87.64 | yes |
| 125438 | flagellated | motile2+ⓘ | yes | 65.58 | no |
| Topic | Title | Authors | Journal | DOI | Year | |
|---|---|---|---|---|---|---|
| Genetics | Insights into the genome structure of four acetogenic bacteria with specific reference to the Wood-Ljungdahl pathway. | Esposito A, Tamburini S, Triboli L, Ambrosino L, Chiusano ML, Jousson O | Microbiologyopen | 10.1002/mbo3.938 | 2019 |
| #394 | Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 917 |
| #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 ) |
| #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 ) |
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If you want to cite this particular strain cite the following doi:
https://doi.org/10.13145/bacdive7537.20260601.11
When using BacDive for research please cite the following paper
BacDive in 2025: the core database for prokaryotic strain data