Strain identifier

BacDive ID: 153314

Type strain: No

Species: Streptococcus agalactiae

NCBI tax ID(s): 1105270 (strain), 1311 (species)

For citation purpose refer to the digital object identifier (doi) of the current version.
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General

@ref: 58464

BacDive-ID: 153314

keywords: genome sequence, Bacteria, microaerophile, mesophilic

description: Streptococcus agalactiae CCUG 49086 is a microaerophile, mesophilic bacterium that was isolated from Human blood,newborn female.

NCBI tax id

NCBI tax idMatching level
1105270strain
1311species

doi: 10.13145/bacdive153314.20250331.9.3

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: 58464

domain: Bacteria

phylum: Firmicutes

class: Bacilli

order: Lactobacillales

family: Streptococcaceae

genus: Streptococcus

species: Streptococcus agalactiae

type strain: no

Culture and growth conditions

culture temp

  • @ref: 58464
  • growth: positive
  • type: growth
  • temperature: 37

Physiology and metabolism

oxygen tolerance

@refoxygen toleranceconfidence
58464microaerophile
125439microaerophile95.9

spore formation

  • @ref: 125439
  • spore formation: no
  • confidence: 97.5

Isolation, sampling and environmental information

isolation

  • @ref: 58464
  • sample type: Human blood,newborn female
  • sampling date: 1998-07-18
  • geographic location: Näl
  • country: Sweden
  • origin.country: SWE
  • continent: Europe

isolation source categories

Cat1Cat2Cat3
#Host#Human#Female
#Host Body Product#Fluids#Blood
#Infection#Patient
#Host#Human#Child

Sequence information

Genome sequences

@refdescriptionaccessionassembly leveldatabaseNCBI tax ID
66792Streptococcus agalactiae CCUG 49086GCA_000311645contigncbi1105270
66792Streptococcus agalactiae CCUG 490861105270.3wgspatric1105270
66792Streptococcus agalactiae CCUG 490862698536685draftimg1105270

Genome-based predictions

predictions

@refmodeltraitdescriptionpredictionconfidencetraining_data
125439BacteriaNetoxygen_toleranceOxygenic conditions needed for growthmicroaerophile95.9
125439BacteriaNetgram_stainReaction to gram-stainingpositive81
125439BacteriaNetmotilityAbility to perform movementno81.3
125439BacteriaNetspore_formationAbility to form endo- or exosporesno97.5
125438gram-positivegram-positivePositive reaction to Gram-stainingyes86.251no
125438anaerobicanaerobicAbility to grow under anoxygenic conditions (including facultative anaerobes)no90.582yes
125438spore-formingspore-formingAbility to form endo- or exosporesno85.51no
125438aerobicaerobicAbility to grow under oxygenic conditions (including facultative aerobes)no96.119yes
125438thermophilethermophilicAbility to grow at temperatures above or equal to 45°Cno95.913yes
125438motile2+flagellatedAbility to perform flagellated movementno88.5no

External links

@ref: 58464

culture collection no.: CCUG 49086

straininfo link

  • @ref: 107137
  • straininfo: 215251

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
58464Curators of the CCUGhttps://www.ccug.se/strain?id=49086Culture Collection University of Gothenburg (CCUG) (CCUG 49086)
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
107137Reimer, 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-ID215251.1
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