Dethiosulfovibrio marinus WS 100 is an anaerobe bacterium that was isolated from Thiodendron bacterial sulfur mat.
anaerobe genome sequence 16S sequence Bacteria| @ref 20215 |
|
|
| Domain Bacteria |
| Phylum Synergistota |
| Class Synergistia |
| Order Synergistales |
| Family Dethiosulfovibrionaceae |
| Genus Dethiosulfovibrio |
| Species Dethiosulfovibrio marinus |
| Full scientific name Dethiosulfovibrio marinus Surkov et al. 2001 |
| @ref | Name | Growth | Medium link | Composition | |
|---|---|---|---|---|---|
| 4758 | DETHIOSULFOVIBRIO MEDIUM (DSMZ Medium 906) | Medium recipe at MediaDive | Name: DETHIOSULFOVIBRIO MEDIUM (DSMZ Medium 906) Composition: NaCl 19.98 g/l Yeast extract 4.99501 g/l MgCl2 x 6 H2O 2.997 g/l Na3-citrate x 5 H2O 2.997 g/l Na2S2O3 x 5 H2O 2.4975 g/l Peptone 1.998 g/l KH2PO4 0.999001 g/l Na2S x 9 H2O 0.499501 g/l CaCl2 x 2 H2O 0.1998 g/l HCl 0.0024975 g/l FeCl2 x 4 H2O 0.0014985 g/l Sodium resazurin 0.0004995 g/l CoCl2 x 6 H2O 0.00018981 g/l MnCl2 x 4 H2O 9.99001e-05 g/l ZnCl2 6.99301e-05 g/l Na2MoO4 x 2 H2O 3.5964e-05 g/l NiCl2 x 6 H2O 2.3976e-05 g/l H3BO3 5.99401e-06 g/l CuCl2 x 2 H2O 1.998e-06 g/l Distilled water |
| Cat1 | Cat2 | Cat3 | |
|---|---|---|---|
| #Environmental | #Microbial community | #Microbial mat | |
| #Host | #Microbial | #Bacteria | |
| #Condition | #Sulfuric | - |
Global distribution of 16S sequence AF234544 (>99% sequence identity) for Dethiosulfovibrio from Microbeatlas ![]()
| @ref | Description | Assembly level | INSDC accession | BV-BRC accession | IMG accession | NCBI tax ID | Score | |
|---|---|---|---|---|---|---|---|---|
| 66792 | ASM2156887v1 assembly for Dethiosulfovibrio marinus DSM 12537 | scaffold | 133532 | 67.18 |
| @ref | Description | Accession | Length | Database | NCBI tax ID | |
|---|---|---|---|---|---|---|
| 4758 | Dethiosulfovibrio marinus strain WS 100 16S ribosomal RNA gene, partial sequence | AF234544 | 1393 | 133532 |
| @ref | GC-content (mol%) | Method | |
|---|---|---|---|
| 4758 | 51.8 | thermal denaturation, midpoint method (Tm) |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positiveⓘ | no | 81.49 | no |
| 125438 | anaerobic | anaerobicⓘ | yes | 96.27 | yes |
| 125438 | aerobic | aerobicⓘ | no | 95.18 | yes |
| 125438 | spore-forming | spore-formingⓘ | no | 72.92 | no |
| 125438 | thermophilic | thermophileⓘ | no | 83.25 | yes |
| 125438 | flagellated | motile2+ⓘ | yes | 65.32 | no |
| Topic | Title | Authors | Journal | DOI | Year | |
|---|---|---|---|---|---|---|
| Metabolism | Sulphur isotope fractionation during the reduction of elemental sulphur and thiosulphate by Dethiosulfovibrio spp. | Surkov AV, Bottcher ME, Kuever J | Isotopes Environ Health Stud | 10.1080/10256016.2011.626525 | 2012 | |
| Phylogeny | Dethiosulfovibrio russensis sp. nov., Dethosulfovibrio marinus sp. nov. and Dethosulfovibrio acidaminovorans sp. nov., novel anaerobic, thiosulfate- and sulfur-reducing bacteria isolated from 'Thiodendron' sulfur mats in different saline environments. | Surkov AV, Dubinina GA, Lysenko AM, Glockner FO, Kuever J | Int J Syst Evol Microbiol | 10.1099/00207713-51-2-327 | 2001 |
| #4758 | Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 12537 |
| #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) . |
| #67770 | Japan Collection of Microorganism (JCM) ; Curators of the JCM; |
| #69479 | João F Matias Rodrigues, Janko Tackmann,Gregor Rot, Thomas SB Schmidt, Lukas Malfertheiner, Mihai Danaila,Marija Dmitrijeva, Daniela Gaio, Nicolas Näpflin and Christian von Mering. University of Zurich.: MicrobeAtlas 1.0 beta . |
| #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 ) |
| #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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