Clostridium beijerinckii JCM 8025 is a mesophilic prokaryote of the family Clostridiaceae.
mesophilic genome sequence 16S sequence| @ref 20215 |
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| Domain Bacillati |
| Phylum Bacillota |
| Class Clostridia |
| Order Eubacteriales |
| Family Clostridiaceae |
| Genus Clostridium |
| Species Clostridium beijerinckii |
| Full scientific name Clostridium beijerinckii Donker 1926 (Approved Lists 1980) |
| Synonyms (1) |
| @ref | Growth | Type | Temperature (°C) | Range | |
|---|---|---|---|---|---|
| 67770 | positive | growth | 37 | mesophilic |
Global distribution of 16S sequence AB647332 (>99% sequence identity) for Clostridium from Microbeatlas ![]()
| @ref | Description | Assembly level | INSDC accession | NCBI tax ID | Score | |
|---|---|---|---|---|---|---|
| 67770 | ASM200629v1 assembly for Clostridium beijerinckii NRRL B-591 | contig | 1520 | 2.63 |
| @ref | Description | Accession | Length | Database | NCBI tax ID | |
|---|---|---|---|---|---|---|
| 67770 | Clostridium beijerinckii gene for 16S ribosomal RNA, partial sequence, strain: JCM 8025 | AB647332 | 1473 | 1520 |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125439 | spore_formation | BacteriaNetⓘ | yes | 79.60 | no |
| 125439 | motility | BacteriaNetⓘ | yes | 79.00 | no |
| 125439 | gram_stain | BacteriaNetⓘ | positive | 73.70 | no |
| 125439 | oxygen_tolerance | BacteriaNetⓘ | anaerobe | 96.20 | no |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positiveⓘ | yes | 50.40 | no |
| 125438 | anaerobic | anaerobicⓘ | yes | 83.86 | no |
| 125438 | aerobic | aerobicⓘ | no | 92.43 | no |
| 125438 | spore-forming | spore-formingⓘ | yes | 78.21 | no |
| 125438 | thermophilic | thermophileⓘ | no | 93.41 | yes |
| 125438 | flagellated | motile2+ⓘ | yes | 75.74 | 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 | |
| Genetics | Towards continuous industrial bioprocessing with solventogenic and acetogenic clostridia: challenges, progress and perspectives. | Vees CA, Neuendorf CS, Pflugl S. | J Ind Microbiol Biotechnol | 10.1007/s10295-020-02296-2 | 2020 | |
| Biobutanol production from coffee silverskin. | Hijosa-Valsero M, Garita-Cambronero J, Paniagua-Garcia AI, Diez-Antolinez R. | Microb Cell Fact | 10.1186/s12934-018-1002-z | 2018 | ||
| Valorization of agricultural wastes for biofuel applications. | Awogbemi O, Kallon DVV. | Heliyon | 10.1016/j.heliyon.2022.e11117 | 2022 |
| #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 ) |
| #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 ) |
| #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/bacdive165723.20251217.10
When using BacDive for research please cite the following paper
BacDive in 2025: the core database for prokaryotic strain data