Strain identifier
BacDive ID: 163973
Type strain: 
Species: Arthrobacter sp.
Strain history: W. Iwasaki; Dept. of Biol. Sci., Grad. Sch. of Sci., Univ. of Tokyo, Japan; Hiyo6.
NCBI tax ID(s): 1667 (species)
version 9.3 (current version)
General
@ref: 67770
BacDive-ID: 163973
keywords: genome sequence, Bacteria, mesophilic
description: Arthrobacter sp. JCM 31234 is a mesophilic bacterium that was isolated from Soil at Hiyoriyama, affected by the 2011 Great East Japan Earthquake tsunami.
NCBI tax id
- NCBI tax id: 1667
- Matching level: species
strain history
- @ref: 67770
- history: W. Iwasaki; Dept. of Biol. Sci., Grad. Sch. of Sci., Univ. of Tokyo, Japan; Hiyo6.
doi: 10.13145/bacdive163973.20250331.9.3
Name and taxonomic classification
LPSN
- @ref: 20215
- description: domain/bacteria
- keyword: phylum/actinomycetota
- domain: Bacteria
- phylum: Actinomycetota
- class: Actinomycetes
- order: Micrococcales
- family: Micrococcaceae
- genus: Arthrobacter
- species: Arthrobacter sp.
- full scientific name: Arthrobacter Conn and Dimmick 1947 (Approved Lists 1980)
@ref: 67770
domain: Bacteria
phylum: Actinobacteria
class: Actinobacteria
order: Micrococcales
family: Micrococcaceae
genus: Arthrobacter
species: Arthrobacter sp.
full scientific name: Arthrobacter sp.
type strain: no
Morphology
cell morphology
- @ref: 125438
- motility: no
- confidence: 91.5
Culture and growth conditions
culture temp
- @ref: 67770
- growth: positive
- type: growth
- temperature: 28
Physiology and metabolism
oxygen tolerance
- @ref: 125439
- oxygen tolerance: obligate aerobe
- confidence: 93.9
Isolation, sampling and environmental information
isolation
- @ref: 67770
- sample type: Soil at Hiyoriyama, affected by the 2011 Great East Japan Earthquake tsunami
- geographic location: Sendai, Miyagi Pref.
- country: Japan
- origin.country: JPN
- continent: Asia
Sequence information
Genome sequences
- @ref: 67770
- description: Arthrobacter sp. Hiyo6
- accession: GCA_001263635
- assembly level: contig
- database: ncbi
- NCBI tax ID: 1588022
GC content
- @ref: 67770
- GC-content: 63.3
- method: genome sequence analysis
Genome-based predictions
predictions
| @ref | model | trait | description | prediction | confidence | training_data |
|---|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positive | Positive reaction to Gram-staining | yes | 84.034 | no |
| 125438 | anaerobic | anaerobic | Ability to grow under anoxygenic conditions (including facultative anaerobes) | no | 86.523 | no |
| 125438 | aerobic | aerobic | Ability to grow under oxygenic conditions (including facultative aerobes) | yes | 72.341 | no |
| 125438 | spore-forming | spore-forming | Ability to form endo- or exospores | no | 81.456 | no |
| 125438 | thermophile | thermophilic | Ability to grow at temperatures above or equal to 45°C | no | 88.5 | no |
| 125438 | motile2+ | flagellated | Ability to perform flagellated movement | no | 91.5 | no |
| 125439 | BacteriaNet | spore_formation | Ability to form endo- or exospores | no | 73.7 | |
| 125439 | BacteriaNet | motility | Ability to perform movement | no | 84.4 | |
| 125439 | BacteriaNet | gram_stain | Reaction to gram-staining | positive | 89.5 | |
| 125439 | BacteriaNet | oxygen_tolerance | Oxygenic conditions needed for growth | obligate aerobe | 93.9 |
External links
@ref: 67770
culture collection no.: JCM 31234
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 |
| 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 |