Strain identifier

BacDive ID: 148942

Type strain: No

Species: Streptococcus pneumoniae

NCBI tax ID(s): 1313 (species)

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

@ref: 53274

BacDive-ID: 148942

keywords: genome sequence, Bacteria, Gram-positive

description: Streptococcus pneumoniae CCUG 36618 is a Gram-positive bacterium that was isolated from Human blood.

NCBI tax id

  • NCBI tax id: 1313
  • Matching level: species

doi: 10.13145/bacdive148942.20250331.9.3

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 pneumoniae
  • full scientific name: Streptococcus pneumoniae (Klein 1884) Chester 1901 (Approved Lists 1980)
  • synonyms

    @refsynonym
    20215Micrococcus pneumoniae
    20215Staphylococcus pneumoniae

@ref: 53274

domain: Bacteria

phylum: Firmicutes

class: Bacilli

order: Lactobacillales

family: Streptococcaceae

genus: Streptococcus

species: Streptococcus pneumoniae

type strain: no

Morphology

cell morphology

@refmotilityconfidencegram stain
125438no91
12543890.244positive

Physiology and metabolism

oxygen tolerance

  • @ref: 125439
  • oxygen tolerance: microaerophile
  • confidence: 96.2

Isolation, sampling and environmental information

isolation

  • @ref: 53274
  • sample type: Human blood
  • sampling date: 1996-07-29
  • geographic location: Göteborg
  • country: Sweden
  • origin.country: SWE
  • continent: Europe

isolation source categories

Cat1Cat2Cat3
#Host#Human
#Host Body Product#Fluids#Blood

Sequence information

Genome sequences

@refdescriptionaccessionassembly leveldatabaseNCBI tax ID
66792Streptococcus pneumoniae CCUG 36618GCA_001856065scaffoldncbi1313
66792Streptococcus pneumoniae strain CCUG 366181313.13769wgspatric1313

Genome-based predictions

predictions

@refmodeltraitdescriptionpredictionconfidencetraining_data
125438gram-positivegram-positivePositive reaction to Gram-stainingyes90.244no
125438anaerobicanaerobicAbility to grow under anoxygenic conditions (including facultative anaerobes)no90.187no
125438aerobicaerobicAbility to grow under oxygenic conditions (including facultative aerobes)no97.505no
125438spore-formingspore-formingAbility to form endo- or exosporesno83.371no
125438thermophilethermophilicAbility to grow at temperatures above or equal to 45°Cno95no
125438motile2+flagellatedAbility to perform flagellated movementno91no
125439BacteriaNetspore_formationAbility to form endo- or exosporesno86.2
125439BacteriaNetmotilityAbility to perform movementno73.8
125439BacteriaNetgram_stainReaction to gram-stainingpositive79.4
125439BacteriaNetoxygen_toleranceOxygenic conditions needed for growthmicroaerophile96.2

External links

@ref: 53274

culture collection no.: CCUG 36618

straininfo link

  • @ref: 103423
  • straininfo: 57939

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
53274Curators of the CCUGhttps://www.ccug.se/strain?id=36618Culture Collection University of Gothenburg (CCUG) (CCUG 36618)
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
103423Reimer, 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-ID57939.1
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