Strain identifier
BacDive ID: 166078
Type strain: ![]()
Species: Cellulomonas sp.
Strain history: T. Kudo HA101.
NCBI tax ID(s): 1298613 (species)
version 9.3 (current version)
General
@ref: 67770
BacDive-ID: 166078
keywords: genome sequence, Bacteria, mesophilic
description: Cellulomonas sp. JCM 9808 is a mesophilic bacterium that was isolated from Soil from Kushiro Marsh.
NCBI tax id
- NCBI tax id: 1298613
- Matching level: species
strain history
- @ref: 67770
- history: T. Kudo HA101.
doi: 10.13145/bacdive166078.20250331.9.3
Name and taxonomic classification
LPSN
- @ref: 20215
- description: domain/bacteria
- keyword: phylum/actinomycetota
- domain: Bacteria
- phylum: Actinomycetota
- class: Actinomycetes
- order: Micrococcales
- family: Cellulomonadaceae
- genus: Cellulomonas
- species: Cellulomonas sp.
- full scientific name: Cellulomonas Bergey et al. 1923 (Approved Lists 1980)
@ref: 67770
domain: Bacteria
phylum: Actinobacteria
class: Actinobacteria
order: Micrococcales
family: Cellulomonadaceae
genus: Cellulomonas
species: Cellulomonas sp.
full scientific name: Cellulomonas sp.
type strain: no
Morphology
cell morphology
- @ref: 125439
- gram stain: positive
- confidence: 99.9
Culture and growth conditions
culture temp
- @ref: 67770
- growth: positive
- type: growth
- temperature: 30
Physiology and metabolism
oxygen tolerance
- @ref: 125439
- oxygen tolerance: obligate aerobe
- confidence: 99.2
Isolation, sampling and environmental information
isolation
- @ref: 67770
- sample type: Soil from Kushiro Marsh
- geographic location: Hokkaido
- country: Japan
- origin.country: JPN
- continent: Asia
Sequence information
Genome sequences
| @ref | description | accession | assembly level | database | NCBI tax ID |
|---|---|---|---|---|---|
| 66792 | Cellulomonas sp. JCM 9808 | 1298613.3 | wgs | patric | 1298613 |
| 66792 | Cellulomonas sp. JCM 9808 | 2734481912 | draft | img | 1298613 |
| 67770 | Cellulomonas sp. JCM 9808 | GCA_001312685 | contig | ncbi | 1298613 |
Genome-based predictions
predictions
| @ref | model | trait | description | prediction | confidence | training_data |
|---|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positive | Positive reaction to Gram-staining | yes | 80.196 | no |
| 125438 | anaerobic | anaerobic | Ability to grow under anoxygenic conditions (including facultative anaerobes) | no | 83.683 | no |
| 125438 | spore-forming | spore-forming | Ability to form endo- or exospores | no | 86.213 | no |
| 125438 | aerobic | aerobic | Ability to grow under oxygenic conditions (including facultative aerobes) | no | 53.098 | no |
| 125438 | thermophile | thermophilic | Ability to grow at temperatures above or equal to 45°C | no | 92.565 | yes |
| 125438 | motile2+ | flagellated | Ability to perform flagellated movement | no | 74 | no |
| 125439 | BacteriaNet | spore_formation | Ability to form endo- or exospores | yes | 56.8 | |
| 125439 | BacteriaNet | motility | Ability to perform movement | no | 82.8 | |
| 125439 | BacteriaNet | gram_stain | Reaction to gram-staining | positive | 99.9 | |
| 125439 | BacteriaNet | oxygen_tolerance | Oxygenic conditions needed for growth | obligate aerobe | 99.2 |
External links
@ref: 67770
culture collection no.: JCM 9808
Reference
| @id | authors | title | doi/url |
|---|---|---|---|
| 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 | 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) | https://diaspora-project.de/progress.html#genomes |
| 67770 | Curators of the JCM | https://jcm.brc.riken.jp/en/ | |
| 125438 | Julia Koblitz, Lorenz Christian Reimer, Rüdiger Pukall, Jörg Overmann | Predicting bacterial phenotypic traits through improved machine learning using high-quality, curated datasets | 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 | https://github.com/GenomeNet/deepG |