Escherichia coli CCUG 11303 is a prokaryote of the family Enterobacteriaceae.
genome sequence| @ref 20215 |
|
|
| 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 (1) |
| @ref | Gram stain | Confidence | |
|---|---|---|---|
| 125438 | negative | 99.75 |
| @ref | Oxygen tolerance | Confidence | |
|---|---|---|---|
| 125439 | aerobe | 90.1 |
| @ref | Description | Assembly level | INSDC accession | BV-BRC accession | NCBI tax ID | Score | |
|---|---|---|---|---|---|---|---|
| 66792 | 38891_B02 assembly for Escherichia coli NCTC9003 | contig | 562 | 78.36 |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125439 | spore_formation | BacteriaNetⓘ | no | 80.20 | no |
| 125439 | motility | BacteriaNetⓘ | yes | 68.10 | no |
| 125439 | gram_stain | BacteriaNetⓘ | negative | 82.40 | no |
| 125439 | oxygen_tolerance | BacteriaNetⓘ | aerobe | 90.10 | no |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positiveⓘ | no | 99.75 | no |
| 125438 | anaerobic | anaerobicⓘ | no | 96.40 | no |
| 125438 | spore-forming | spore-formingⓘ | no | 87.45 | no |
| 125438 | thermophilic | thermophileⓘ | no | 98.50 | no |
| 125438 | aerobic | aerobicⓘ | no | 61.09 | no |
| 125438 | flagellated | motile2+ⓘ | yes | 76.74 | no |
| Topic | Title | Authors | Journal | DOI | Year | |
|---|---|---|---|---|---|---|
| Critical analysis of methods to determine growth, control and analysis of biofilms for potential non-submerged antibiofilm surfaces and coatings. | Redfern J, Cunliffe AJ, Goeres DM, Azevedo NF, Verran J. | Biofilm | 10.1016/j.bioflm.2024.100187 | 2024 | ||
| Evaluation of the Vibrant DNA microarray for the high-throughput multiplex detection of enteric pathogens in clinical samples. | Yang Y, Rajendran V, Jayaraman V, Wang T, Bei K, Krishna K, Rajasekaran K, Rajasekaran JJ, Krishnamurthy H. | Gut Pathog | 10.1186/s13099-019-0329-2 | 2019 | ||
| Well-Dispersed Silver Nanoparticles on Cellulose Filter Paper for Bacterial Removal. | Chien HW, Tsai MY, Kuo CJ, Lin CL. | Nanomaterials (Basel) | 10.3390/nano11030595 | 2021 | ||
| Studies of PET nonwovens modified by novel antimicrobials configured with both N-halamine and dual quaternary ammonium with different alkyl chain length. | Chien HW, Chen YY, Chen YL, Cheng CH, Lin JC. | RSC Adv | 10.1039/c9ra00094a | 2019 | ||
| Pathogenicity | Direct antimicrobial susceptibility testing of gram-negative bacilli in blood cultures by an electrochemical method. | Huang AH, Wu JJ, Weng YM, Ding HC, Chang TC. | J Clin Microbiol | 10.1128/jcm.36.10.2882-2886.1998 | 1998 |
| #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. IJSEM ( DOI 10.1099/ijsem.0.004332 ) |
| #45423 | Culture Collection University of Gothenburg (CCUG) ; Curators of the CCUG; CCUG 11303 |
| #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) . |
| #125438 | Julia Koblitz, Lorenz Christian Reimer, Rüdiger Pukall, Jörg Overmann: Predicting bacterial phenotypic traits through improved machine learning using high-quality, curated datasets. 2024 ( DOI 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 . |
| #126262 | A. Lissin, I. Schober, J. F. Witte, H. Lüken, A. Podstawka, J. Koblitz, B. Bunk, P. Dawyndt, P. Vandamme, P. de Vos, J. Overmann, L. C. Reimer: StrainInfo—the central database for linked microbial strain identifiers. ( DOI 10.1093/database/baaf059 ) |
You found an error in BacDive? Please tell us about it!
Note that changes will be reviewed and judged. If your changes are legitimate, changes will occur within the next BacDive update. Only proposed changes supported by the according reference will be reviewed. The BacDive team reserves the right to reject proposed changes.
Successfully sent
If you want to cite this particular strain cite the following doi:
https://doi.org/10.13145/bacdive142166.20251217.10
When using BacDive for research please cite the following paper
BacDive in 2025: the core database for prokaryotic strain data