Strain identifier
version 9.3 (current version)
General
@ref: 35874
BacDive-ID: 136454
keywords: genome sequence, Bacteria, mesophilic, Gram-negative
description: Escherichia coli CIP 54.52 is a mesophilic, Gram-negative bacterium of the family Enterobacteriaceae.
NCBI tax id
- NCBI tax id: 562
- Matching level: species
doi: 10.13145/bacdive136454.20250331.9.3
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: 35874
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
Culture and growth conditions
culture medium
- @ref: 35874
- name: MEDIUM 3 - Columbia agar
- growth: yes
- composition: Columbia agar (39.000 g);distilled water (1000.000 ml)
culture temp
- @ref: 35874
- growth: positive
- type: growth
- temperature: 30
Physiology and metabolism
oxygen tolerance
- @ref: 125439
- oxygen tolerance: obligate aerobe
- confidence: 92.1
Sequence information
Genome sequences
| @ref | description | accession | assembly level | database | NCBI tax ID |
|---|---|---|---|---|---|
| 66792 | Escherichia coli NCTC9002 | GCA_900450435 | contig | ncbi | 562 |
| 66792 | Escherichia coli strain NCTC9002 | 562.34338 | wgs | patric | 562 |
Genome-based predictions
predictions
| @ref | model | trait | description | prediction | confidence | training_data |
|---|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positive | Positive reaction to Gram-staining | no | 99.75 | no |
| 125438 | anaerobic | anaerobic | Ability to grow under anoxygenic conditions (including facultative anaerobes) | no | 95.756 | no |
| 125438 | spore-forming | spore-forming | Ability to form endo- or exospores | no | 87.698 | no |
| 125438 | aerobic | aerobic | Ability to grow under oxygenic conditions (including facultative aerobes) | no | 65.845 | no |
| 125438 | thermophile | thermophilic | Ability to grow at temperatures above or equal to 45°C | no | 98.5 | yes |
| 125438 | motile2+ | flagellated | Ability to perform flagellated movement | yes | 76.475 | no |
| 125439 | BacteriaNet | spore_formation | Ability to form endo- or exospores | no | 69 | |
| 125439 | BacteriaNet | motility | Ability to perform movement | yes | 66.3 | |
| 125439 | BacteriaNet | gram_stain | Reaction to gram-staining | variable | 65.9 | |
| 125439 | BacteriaNet | oxygen_tolerance | Oxygenic conditions needed for growth | obligate aerobe | 92.1 |
External links
@ref: 35874
culture collection no.: CIP 54.52, NCTC 9002, CCUG 25
straininfo link
- @ref: 93608
- straininfo: 53659
Reference
| @id | authors | title | doi/url | catalogue |
|---|---|---|---|---|
| 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 | |
| 35874 | Curators of the CIP | https://catalogue-crbip.pasteur.fr/fiche_catalogue.xhtml?crbip=CIP%2054.52 | Collection of Institut Pasteur (CIP 54.52) | |
| 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 | |
| 93608 | Reimer, 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 identifiers | 10.60712/SI-ID53659.1 | |
| 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 |