Strain identifier
BacDive ID: 162473
Type strain: 
Species: Jejuia pallidilutea
Strain history: M. Hosokawa A1R.
NCBI tax ID(s): 504487 (species)
version 9.3 (current version)
General
@ref: 67770
BacDive-ID: 162473
keywords: genome sequence, Bacteria, mesophilic, Gram-negative
description: Jejuia pallidilutea JCM 19302 is a mesophilic, Gram-negative bacterium of the family Flavobacteriaceae.
NCBI tax id
- NCBI tax id: 504487
- Matching level: species
strain history
- @ref: 67770
- history: M. Hosokawa A1R.
doi: 10.13145/bacdive162473.20250331.9.3
Name and taxonomic classification
LPSN
- @ref: 20215
- description: domain/bacteria
- keyword: phylum/bacteroidota
- domain: Bacteria
- phylum: Bacteroidota
- class: Flavobacteriia
- order: Flavobacteriales
- family: Flavobacteriaceae
- genus: Jejuia
- species: Jejuia pallidilutea
- full scientific name: Jejuia pallidilutea Lee et al. 2009
synonyms
- @ref: 20215
- synonym: Hyunsoonleella pallidilutea
@ref: 67770
domain: Bacteria
phylum: Bacteroidetes
class: Flavobacteriia
order: Flavobacteriales
family: Flavobacteriaceae
genus: Jejuia
species: Jejuia pallidilutea
full scientific name: Jejuia pallidilutea Lee et al. 2009
type strain: no
Morphology
cell morphology
| @ref | motility | confidence | gram stain |
|---|---|---|---|
| 125438 | no | 94 | |
| 125438 | 96.981 | negative | |
| 125439 | 99.8 | negative |
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: 96.9
spore formation
| @ref | spore formation | confidence |
|---|---|---|
| 125438 | no | 92.482 |
| 125439 | no | 98.5 |
Sequence information
Genome sequences
| @ref | description | accession | assembly level | database | NCBI tax ID |
|---|---|---|---|---|---|
| 66792 | Jejuia pallidilutea JCM 19302 | 504487.4 | wgs | patric | 504487 |
| 66792 | Jejuia pallidilutea JCM19302 | 2609460213 | draft | img | 504487 |
| 67770 | Jejuia pallidilutea JCM 19302 | GCA_000764795 | contig | ncbi | 504487 |
GC content
- @ref: 67770
- GC-content: 33.8
- 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 | no | 96.981 | no |
| 125438 | anaerobic | anaerobic | Ability to grow under anoxygenic conditions (including facultative anaerobes) | no | 94.866 | no |
| 125438 | spore-forming | spore-forming | Ability to form endo- or exospores | no | 92.482 | no |
| 125438 | aerobic | aerobic | Ability to grow under oxygenic conditions (including facultative aerobes) | yes | 81.278 | no |
| 125438 | thermophile | thermophilic | Ability to grow at temperatures above or equal to 45°C | no | 95.934 | yes |
| 125438 | motile2+ | flagellated | Ability to perform flagellated movement | no | 94 | no |
| 125439 | BacteriaNet | spore_formation | Ability to form endo- or exospores | no | 98.5 | |
| 125439 | BacteriaNet | motility | Ability to perform movement | no | 70.3 | |
| 125439 | BacteriaNet | gram_stain | Reaction to gram-staining | negative | 99.8 | |
| 125439 | BacteriaNet | oxygen_tolerance | Oxygenic conditions needed for growth | obligate aerobe | 96.9 |
External links
@ref: 67770
culture collection no.: JCM 19302
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 |