Strain identifier

BacDive ID: 142362

Type strain: No

Species: Streptococcus agalactiae

NCBI tax ID(s): 1311 (species)

For citation purpose refer to the digital object identifier (doi) of the current version.
Archive
version 9.3 (current version):
version 9.1:
version 9:
version 8.1:
version 8:
version 7.1:
version 7:
version 6:
version 5:
version 4.1:
version 4:
version 9.3 (current version)

General

@ref: 45639

BacDive-ID: 142362

keywords: genome sequence, Bacteria

description: Streptococcus agalactiae CCUG 12039 is a bacterium of the family Streptococcaceae.

NCBI tax id

  • NCBI tax id: 1311
  • Matching level: species

doi: 10.13145/bacdive142362.20250331.9.3

Name and taxonomic classification

LPSN

  • @ref: 20215
  • description: domain/bacteria
  • keyword: phylum/bacillota
  • domain: Bacteria
  • phylum: Bacillota
  • class: Bacilli
  • order: Lactobacillales
  • family: Streptococcaceae
  • genus: Streptococcus
  • species: Streptococcus agalactiae
  • full scientific name: Streptococcus agalactiae Lehmann and Neumann 1896 (Approved Lists 1980)
  • synonyms

    @refsynonym
    20215Streptococcus difficile
    20215Streptococcus difficilis

@ref: 45639

domain: Bacteria

phylum: Firmicutes

class: Bacilli

order: Lactobacillales

family: Streptococcaceae

genus: Streptococcus

species: Streptococcus agalactiae

type strain: no

Morphology

cell morphology

  • @ref: 125439
  • gram stain: positive
  • confidence: 90.3

Physiology and metabolism

oxygen tolerance

  • @ref: 125439
  • oxygen tolerance: microaerophile
  • confidence: 96.4

spore formation

  • @ref: 125439
  • spore formation: no
  • confidence: 92.5

Sequence information

Genome sequences

@refdescriptionaccessionassembly leveldatabaseNCBI tax ID
66792Streptococcus agalactiae NCTC8187GCA_900475355completencbi1311
66792Streptococcus agalactiae strain NCTC81871311.1679completepatric1311
66792Streptococcus agalactiae NCTC 81872875613586completeimg1311

Genome-based predictions

predictions

@refmodeltraitdescriptionpredictionconfidencetraining_data
125438gram-positivegram-positivePositive reaction to Gram-stainingyes85.613no
125438anaerobicanaerobicAbility to grow under anoxygenic conditions (including facultative anaerobes)no89.439no
125438aerobicaerobicAbility to grow under oxygenic conditions (including facultative aerobes)no96.011no
125438spore-formingspore-formingAbility to form endo- or exosporesno86.01no
125438thermophilethermophilicAbility to grow at temperatures above or equal to 45°Cno95.942no
125438motile2+flagellatedAbility to perform flagellated movementno88.5no
125439BacteriaNetspore_formationAbility to form endo- or exosporesno92.5
125439BacteriaNetmotilityAbility to perform movementno78.7
125439BacteriaNetgram_stainReaction to gram-stainingpositive90.3
125439BacteriaNetoxygen_toleranceOxygenic conditions needed for growthmicroaerophile96.4

External links

@ref: 45639

culture collection no.: CCUG 12039, NCTC 8187

straininfo link

  • @ref: 97897
  • straininfo: 57437

Reference

@idauthorstitledoi/urlcatalogue
20215Parte, 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 DSMZ10.1099/ijsem.0.004332
45639Curators of the CCUGhttps://www.ccug.se/strain?id=12039Culture Collection University of Gothenburg (CCUG) (CCUG 12039)
66792Julia Koblitz, Joaquim Sardà, Lorenz Christian Reimer, Boyke Bunk, Jörg OvermannAutomatically annotated for the DiASPora project (Digital Approaches for the Synthesis of Poorly Accessible Biodiversity Information)https://diaspora-project.de/progress.html#genomes
97897Reimer, L.C., Lissin, A.,Schober, I., Witte,J.F., Podstawka, A., Lüken, H., Bunk, B.,Overmann, J.StrainInfo: A central database for resolving microbial strain identifiers10.60712/SI-ID57437.1
125438Julia Koblitz, Lorenz Christian Reimer, Rüdiger Pukall, Jörg OvermannPredicting bacterial phenotypic traits through improved machine learning using high-quality, curated datasets10.1101/2024.08.12.607695
125439Philipp Münch, René Mreches, Martin Binder, Hüseyin Anil Gündüz, Xiao-Yin To, Alice McHardydeepG: Deep Learning for Genome Sequence Data. R package version 0.3.1https://github.com/GenomeNet/deepG