Clostridium felsineum Wis 42-A is an anaerobe bacterium of the family Clostridiaceae.
anaerobe genome sequence 16S sequence Bacteria| @ref 20215 |
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| Domain Bacteria |
| Phylum Bacillota |
| Class Clostridia |
| Order Eubacteriales |
| Family Clostridiaceae |
| Genus Clostridium |
| Species Clostridium felsineum |
| Full scientific name Clostridium felsineum (Carbone and Tombolato 1917) Bergey et al. 1939 (Approved Lists 1980) |
| Synonyms (3) |
| BacDive ID | Other strains from Clostridium felsineum (3) | Type strain |
|---|---|---|
| 2586 | C. felsineum 541, DSM 794, ATCC 17788, NCIMB 10690, JCM ... (type strain) | |
| 2543 | C. felsineum 2038, 10022, DSM 793, ATCC 17777, NCIMB 10659, ... | |
| 2656 | C. felsineum 653, DSM 7320, ATCC 17797 |
| @ref | Name | Growth | Medium link | Composition | |
|---|---|---|---|---|---|
| 2662 | CLOSTRIDIUM ACETOBUTYLICUM MEDIUM (DSMZ Medium 411) | Medium recipe at MediaDive | Name: CLOSTRIDIUM ACETOBUTYLICUM MEDIUM (DSMZ Medium 411) Composition: Potato 200.0 g/l D-Glucose 6.0 g/l CaCO3 2.0 g/l L-Cysteine HCl x H2O 0.5 g/l Sodium resazurin 0.0005 g/l Distilled water |
| @ref | Growth | Type | Temperature (°C) | |
|---|---|---|---|---|
| 2662 | positive | growth | 35 |
Global distribution of 16S sequence Y18172 (>99% sequence identity) for Clostridium from Microbeatlas ![]()
| @ref | Description | Assembly level | INSDC accession | BV-BRC accession | NCBI tax ID | Score | IMG accession | |
|---|---|---|---|---|---|---|---|---|
| 66792 | ASM200617v2 assembly for Clostridium felsineum DSM 6424 | complete | 36839 | 98.59 | ||||
| 66792 | Clostridium roseum Wis 42-A | complete | 84029 | 43.78 |
| @ref | Description | Accession | Length | Database | NCBI tax ID | |
|---|---|---|---|---|---|---|
| 20218 | Clostridium roseum 16S rRNA gene, partial, strain DSM 6424 | Y18172 | 1460 | 84029 |
| @ref | GC-content (mol%) | Method | |
|---|---|---|---|
| 2662 | 29.8 | sequence analysis |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125439 | spore_formation | BacteriaNetⓘ | yes | 92.00 | no |
| 125439 | motility | BacteriaNetⓘ | yes | 86.30 | no |
| 125439 | gram_stain | BacteriaNetⓘ | positive | 79.60 | no |
| 125439 | oxygen_tolerance | BacteriaNetⓘ | facultative anaerobe | 99.30 | no |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positiveⓘ | yes | 64.70 | no |
| 125438 | anaerobic | anaerobicⓘ | yes | 87.80 | yes |
| 125438 | aerobic | aerobicⓘ | no | 94.55 | no |
| 125438 | spore-forming | spore-formingⓘ | yes | 79.32 | no |
| 125438 | thermophilic | thermophileⓘ | no | 91.38 | yes |
| 125438 | flagellated | motile2+ⓘ | yes | 78.74 | no |
| Topic | Title | Authors | Journal | DOI | Year | |
|---|---|---|---|---|---|---|
| Phylogeny | Microbial solvent formation revisited by comparative genome analysis. | Poehlein A, Solano JDM, Flitsch SK, Krabben P, Winzer K, Reid SJ, Jones DT, Green E, Minton NP, Daniel R, Durre P. | Biotechnol Biofuels | 10.1186/s13068-017-0742-z | 2017 |
| #2662 | Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 6424 |
| #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 ) |
| #20218 | Verslyppe, B., De Smet, W., De Baets, B., De Vos, P., Dawyndt P.: StrainInfo introduces electronic passports for microorganisms.. Syst Appl Microbiol. 37: 42 - 50 2014 ( DOI 10.1016/j.syapm.2013.11.002 , PubMed 24321274 ) |
| #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) . |
| #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 ) |
| #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/bacdive2655.20251217.10
When using BacDive for research please cite the following paper
BacDive in 2025: the core database for prokaryotic strain data