Methanococcus voltae DSM 7078 is an anaerobe archaeon that was isolated from sea sediment.
anaerobe genome sequence Archaea| @ref 20215 |
|
|
| Domain Archaea |
| Phylum Methanobacteriota |
| Class Methanococci |
| Order Methanococcales |
| Family Methanococcaceae |
| Genus Methanococcus |
| Species Methanococcus voltae |
| Full scientific name Methanococcus voltae Balch and Wolfe 1981 |
| BacDive ID | Other strains from Methanococcus voltae (6) | Type strain |
|---|---|---|
| 6994 | M. voltae PS, DSM 1537, ATCC 33273, OCM 70 (type strain) | |
| 6995 | M. voltae PS-3, DSM 4254 | |
| 6996 | M. voltae PS-6, DSM 4310 | |
| 6997 | M. voltae PS-7, DSM 4311 | |
| 6999 | M. voltae P2F9701a, DSM 14649, OCM 745 | |
| 161888 | M. voltae JCM 16865, OCM 197 |
| @ref | Gram stain | Confidence | |
|---|---|---|---|
| 125439 | negative | 99.439 |
| @ref | Name | Growth | Medium link | Composition | |
|---|---|---|---|---|---|
| 2976 | METHANOGENIUM MEDIUM (H2/CO2) (DSMZ Medium 141) | Medium recipe at MediaDive | Name: METHANOGENIUM MEDIUM (H2/CO2) (DSMZ Medium 141) Composition: NaHCO3 4.89237 g/l MgCl2 x 6 H2O 3.91389 g/l Yeast extract 1.95695 g/l Trypticase peptone 1.95695 g/l Na-acetate 0.978474 g/l Na2S x 9 H2O 0.489237 g/l L-Cysteine HCl x H2O 0.489237 g/l KCl 0.332681 g/l NH4Cl 0.244618 g/l K2HPO4 0.136986 g/l MgSO4 x 7 H2O 0.0293542 g/l Nitrilotriacetic acid 0.0146771 g/l NaCl 0.00978474 g/l MnSO4 x H2O 0.00489237 g/l Fe(NH4)2(SO4)2 x 6 H2O 0.00195695 g/l CoSO4 x 7 H2O 0.00176125 g/l ZnSO4 x 7 H2O 0.00176125 g/l FeSO4 x 7 H2O 0.000978474 g/l CaCl2 x 2 H2O 0.000978474 g/l Sodium resazurin 0.000489237 g/l NiCl2 x 6 H2O 0.000293542 g/l AlK(SO4)2 x 12 H2O 0.000195695 g/l CuSO4 x 5 H2O 9.78474e-05 g/l Pyridoxine hydrochloride 9.78474e-05 g/l Na2MoO4 x 2 H2O 9.78474e-05 g/l H3BO3 9.78474e-05 g/l Nicotinic acid 4.89237e-05 g/l Riboflavin 4.89237e-05 g/l (DL)-alpha-Lipoic acid 4.89237e-05 g/l Thiamine HCl 4.89237e-05 g/l Calcium D-(+)-pantothenate 4.89237e-05 g/l p-Aminobenzoic acid 4.89237e-05 g/l Folic acid 1.95695e-05 g/l Biotin 1.95695e-05 g/l Na2WO4 x 2 H2O 3.91389e-06 g/l Na2SeO3 x 5 H2O 2.93542e-06 g/l Vitamin B12 9.78474e-07 g/l Distilled water |
| @ref | Growth | Type | Temperature (°C) | |
|---|---|---|---|---|
| 2976 | positive | growth | 35 |
| @ref | Sample type | Geographic location | Country | Country ISO 3 Code | Continent | |
|---|---|---|---|---|---|---|
| 2976 | sea sediment | Maharashtra, Arabian Sea | India | IND | Asia |
| @ref | Description | Assembly level | INSDC accession | BV-BRC accession | IMG accession | NCBI tax ID | Score | |
|---|---|---|---|---|---|---|---|---|
| 66792 | ASM1420329v1 assembly for Methanococcus maripaludis DSM 7078 | scaffold | 39152 | 75.39 |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125439 | oxygen_tolerance | BacteriaNetⓘ | facultative anaerobe | 93.00 | no |
| 125439 | gram_stain | BacteriaNetⓘ | negative | 99.44 | no |
| 125439 | motility | BacteriaNetⓘ | no | 84.01 | no |
| 125439 | spore_formation | BacteriaNetⓘ | no | 99.35 | no |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positiveⓘ | no | 62.39 | no |
| 125438 | anaerobic | anaerobicⓘ | yes | 88.85 | yes |
| 125438 | aerobic | aerobicⓘ | no | 87.68 | yes |
| 125438 | spore-forming | spore-formingⓘ | no | 89.57 | no |
| 125438 | thermophilic | thermophileⓘ | no | 69.93 | yes |
| 125438 | flagellated | motile2+ⓘ | no | 82.38 | no |
| #2976 | Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 7078 |
| #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 ) |
You found an error in BacDive? Please tell us about it!
Note that changes will be reviewed and judged. If your changes are legitimate, changes will occur within the next BacDive update. Only proposed changes supported by the according reference will be reviewed. The BacDive team reserves the right to reject proposed changes.
Successfully sent
If you want to cite this particular strain cite the following doi:
https://doi.org/10.13145/bacdive6998.20260601.11
When using BacDive for research please cite the following paper
BacDive in 2025: the core database for prokaryotic strain data