Strain identifier
BacDive ID: 161180
Type strain:
Species: Bifidobacterium longum subsp. infantis
Strain history: AS 1.3006.
NCBI tax ID(s): 1682 (subspecies)
General
@ref: 67770
BacDive-ID: 161180
keywords: genome sequence, Bacteria, mesophilic
description: Bifidobacterium longum subsp. infantis JCM 11660 is a mesophilic bacterium of the family Bifidobacteriaceae.
NCBI tax id
- NCBI tax id: 1682
- Matching level: subspecies
strain history
- @ref: 67770
- history: AS 1.3006.
doi: 10.13145/bacdive161180.20250331.9.3
Name and taxonomic classification
LPSN
- @ref: 20215
- description: domain/bacteria
- keyword: phylum/actinomycetota
- domain: Bacteria
- phylum: Actinomycetota
- class: Actinomycetes
- order: Bifidobacteriales
- family: Bifidobacteriaceae
- genus: Bifidobacterium
- species: Bifidobacterium longum subsp. infantis
- full scientific name: Bifidobacterium longum subsp. infantis (Reuter 1963) Mattarelli et al. 2008
synonyms
- @ref: 20215
- synonym: Bifidobacterium infantis
@ref: 67770
domain: Bacteria
phylum: Actinobacteria
class: Actinobacteria
order: Bifidobacteriales
family: Bifidobacteriaceae
genus: Bifidobacterium
species: Bifidobacterium longum subsp. infantis
full scientific name: Bifidobacterium longum subsp. infantis (Reuter 1963) Mattarelli et al. 2008
type strain: no
Morphology
cell morphology
@ref | motility | confidence | gram stain |
---|---|---|---|
125438 | no | 93 | |
125439 | 94 | negative |
Culture and growth conditions
culture temp
- @ref: 67770
- growth: positive
- type: growth
- temperature: 37
Physiology and metabolism
spore formation
@ref | spore formation | confidence |
---|---|---|
125438 | no | 90.266 |
125439 | no | 97.2 |
Sequence information
Genome sequences
@ref | description | accession | assembly level | database | NCBI tax ID |
---|---|---|---|---|---|
66792 | Bifidobacterium longum subsp. infantis JCM 11660 | GCA_015102035 | complete | ncbi | 1682 |
66792 | Bifidobacterium longum subsp. infantis strain JCM 11660 | 1682.161 | complete | patric | 1682 |
Genome-based predictions
predictions
@ref | model | trait | description | prediction | confidence | training_data |
---|---|---|---|---|---|---|
125438 | gram-positive | gram-positive | Positive reaction to Gram-staining | yes | 87.277 | no |
125438 | anaerobic | anaerobic | Ability to grow under anoxygenic conditions (including facultative anaerobes) | yes | 81.309 | no |
125438 | aerobic | aerobic | Ability to grow under oxygenic conditions (including facultative aerobes) | no | 91.516 | no |
125438 | spore-forming | spore-forming | Ability to form endo- or exospores | no | 90.266 | no |
125438 | thermophile | thermophilic | Ability to grow at temperatures above or equal to 45°C | no | 92.967 | no |
125438 | motile2+ | flagellated | Ability to perform flagellated movement | no | 93 | no |
125439 | BacteriaNet | spore_formation | Ability to form endo- or exospores | no | 97.2 | |
125439 | BacteriaNet | motility | Ability to perform movement | yes | 81.2 | |
125439 | BacteriaNet | gram_stain | Reaction to gram-staining | negative | 94 | |
125439 | BacteriaNet | oxygen_tolerance | Oxygenic conditions needed for growth | obligate aerobe | 61.8 |
External links
@ref: 67770
culture collection no.: JCM 11660, CGMCC 1.3006
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 |