Strain identifier

BacDive ID: 142300

Type strain: No

Species: Escherichia coli

NCBI tax ID(s): 562 (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: 45565

BacDive-ID: 142300

keywords: genome sequence, Bacteria, Gram-negative

description: Escherichia coli CCUG 11447 is a Gram-negative bacterium that was isolated from Pig enteritis.

NCBI tax id

  • NCBI tax id: 562
  • Matching level: species

doi: 10.13145/bacdive142300.20250331.9.3

Name and taxonomic classification

LPSN

  • @ref: 20215
  • description: domain/bacteria
  • keyword: phylum/pseudomonadota
  • domain: Bacteria
  • phylum: Pseudomonadota
  • class: Gammaproteobacteria
  • order: Enterobacterales
  • family: Enterobacteriaceae
  • genus: Escherichia
  • species: Escherichia coli
  • full scientific name: Escherichia coli (Migula 1895) Castellani and Chalmers 1919 (Approved Lists 1980)
  • synonyms

    • @ref: 20215
    • synonym: Bacillus coli

@ref: 45565

domain: Bacteria

phylum: Proteobacteria

class: Gammaproteobacteria

order: Enterobacterales

family: Enterobacteriaceae

genus: Escherichia

species: Escherichia coli

type strain: no

Morphology

cell morphology

  • @ref: 125438
  • gram stain: negative
  • confidence: 99.75

Isolation, sampling and environmental information

isolation

  • @ref: 45565
  • sample type: Pig enteritis
  • country: United Kingdom
  • origin.country: GBR
  • continent: Europe

isolation source categories

Cat1Cat2Cat3
#Host#Mammals#Suidae (Pig,Swine)
#Host Body-Site#Gastrointestinal tract
#Infection#Disease

Sequence information

Genome sequences

@refdescriptionaccessionassembly leveldatabaseNCBI tax ID
66792Escherichia coli NCTC10758GCA_900448605contigncbi562
66792Escherichia coli strain NCTC10758562.34180wgspatric562

Genome-based predictions

predictions

@refmodeltraitdescriptionpredictionconfidencetraining_data
125438gram-positivegram-positivePositive reaction to Gram-stainingno99.75no
125438anaerobicanaerobicAbility to grow under anoxygenic conditions (including facultative anaerobes)no95.787no
125438spore-formingspore-formingAbility to form endo- or exosporesno86.948no
125438aerobicaerobicAbility to grow under oxygenic conditions (including facultative aerobes)no59.788no
125438thermophilethermophilicAbility to grow at temperatures above or equal to 45°Cno98no
125438motile2+flagellatedAbility to perform flagellated movementyes73.356no
125439BacteriaNetspore_formationAbility to form endo- or exosporesno86.8
125439BacteriaNetmotilityAbility to perform movementyes61.7
125439BacteriaNetgram_stainReaction to gram-stainingnegative83.8
125439BacteriaNetoxygen_toleranceOxygenic conditions needed for growthaerobe86.4

External links

@ref: 45565

culture collection no.: CCUG 11447, NCTC 10758

straininfo link

  • @ref: 97843
  • straininfo: 53713

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
45565Curators of the CCUGhttps://www.ccug.se/strain?id=11447Culture Collection University of Gothenburg (CCUG) (CCUG 11447)
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
97843Reimer, 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-ID53713.1
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