Ornithinimicrobium cavernae DSM 105806 is an aerobe bacterium that was isolated from sediment of cave.
aerobe genome sequence 16S sequence Bacteria| @ref 20215 |
|
|
| Domain Bacteria |
| Phylum Actinomycetota |
| Class Actinomycetes |
| Order Micrococcales |
| Family Ornithinimicrobiaceae |
| Genus Ornithinimicrobium |
| Species Ornithinimicrobium cavernae |
| Full scientific name Ornithinimicrobium cavernae Zhang et al. 2019 |
| @ref | Name | Growth | Medium link | Composition | |
|---|---|---|---|---|---|
| 66534 | R2A MEDIUM (DSMZ Medium 830) | Medium recipe at MediaDive | Name: R2A MEDIUM (DSMZ Medium 830) Composition: Agar 15.0 g/l Casamino acids 0.5 g/l Starch 0.5 g/l Glucose 0.5 g/l Proteose peptone 0.5 g/l Yeast extract 0.5 g/l K2HPO4 0.3 g/l Na-pyruvate 0.3 g/l MgSO4 x 7 H2O 0.05 g/l Distilled water |
| @ref | Description | Assembly level | INSDC accession | BV-BRC accession | IMG accession | NCBI tax ID | Score | |
|---|---|---|---|---|---|---|---|---|
| 66792 | ASM312162v1 assembly for Ornithinimicrobium cavernae KCTC 49018 | contig | 2666047 | 65.42 |
| @ref | Description | Accession | Length | Database | NCBI tax ID | |
|---|---|---|---|---|---|---|
| 66534 | Ornithinimicrobium cavernae 16S ribosomal RNA gene, partial sequence | MH177974 | 1498 | 2666047 |
| @ref | GC-content (mol%) | Method | |
|---|---|---|---|
| 66534 | 70.9 | sequence analysis |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125439 | oxygen_tolerance | BacteriaNetⓘ | obligate aerobe | 96.65 | no |
| 125439 | gram_stain | BacteriaNetⓘ | positive | 98.29 | no |
| 125439 | motility | BacteriaNetⓘ | no | 89.10 | no |
| 125439 | spore_formation | BacteriaNetⓘ | yes | 45.59 | no |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positiveⓘ | yes | 90.02 | no |
| 125438 | anaerobic | anaerobicⓘ | no | 95.94 | no |
| 125438 | spore-forming | spore-formingⓘ | no | 67.38 | no |
| 125438 | aerobic | aerobicⓘ | yes | 87.95 | yes |
| 125438 | thermophilic | thermophileⓘ | no | 93.21 | yes |
| 125438 | flagellated | motile2+ⓘ | no | 91.00 | no |
| Topic | Title | Authors | Journal | DOI | Year | |
|---|---|---|---|---|---|---|
| Description of Ornithinimicrobium cryptoxanthini sp. nov., a Novel Actinomycete Producing beta-cryptoxanthin Isolated from the Tongtian River Sediments. | Huang Y, Jiao Y, Zhang S, Tao Y, Zhang S, Jin D, Pu J, Liu L, Yang J, Lu S. | J Microbiol | 10.1007/s12275-023-00029-5 | 2023 | ||
| Phylogeny | Ornithinimicrobium sediminis sp. nov., a novel actinobacterium isolated from a saline lake sediment. | Gao L, Fang BZ, Liu YH, Huang Y, Jiao JY, Li L, Antunes A, Li WJ | Arch Microbiol | 10.1007/s00203-022-02898-7 | 2022 | |
| Phylogeny | Ornithinimicrobium cavernae sp. nov., an actinobacterium isolated from a karst cave. | Zhang LY, Ming H, Meng XL, Fang BZ, Jiao JY, Salam N, Zhang XT, Li WJ, Nie GX | Antonie Van Leeuwenhoek | 10.1007/s10482-018-1141-6 | 2018 | |
| Phylogeny | Description of Ornithinimicrobium ciconiae sp. nov., and Ornithinimicrobium avium sp. nov., isolated from the faeces of the endangered and near-threatened birds. | Lee SY, Sung H, Kim PS, Kim HS, Lee JY, Lee JY, Jeong YS, Tak EJ, Han JE, Hyun DW, Bae JW | J Microbiol | 10.1007/s12275-021-1323-1 | 2021 |
| #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 ) |
| #66534 | Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 105806 |
| #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) . |
| #67771 | Korean Collection for Type Cultures (KCTC) ; Curators of the KCTC; |
| #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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