Shinella daejeonensis JCM 16236 is a bacterium that was isolated from Sludge of a leachate treatment plant.
genome sequence 16S sequence Bacteria| @ref 20215 |
|
|
| Domain Bacteria |
| Phylum Pseudomonadota |
| Class Alphaproteobacteria |
| Order Hyphomicrobiales |
| Family Rhizobiaceae |
| Genus Shinella |
| Species Shinella daejeonensis |
| Full scientific name Shinella daejeonensis Lee et al. 2011 |
| @ref | Growth | Type | Temperature (°C) | |
|---|---|---|---|---|
| 67770 | positive | growth | 30 |
| @ref | Sample type | Geographic location | Country | Country ISO 3 Code | Continent | |
|---|---|---|---|---|---|---|
| 67770 | Sludge of a leachate treatment plant | Daejeon | Republic of Korea | KOR | Asia |
| @ref | Description | Assembly level | INSDC accession | BV-BRC accession | IMG accession | NCBI tax ID | Score | |
|---|---|---|---|---|---|---|---|---|
| 66792 | ASM2428123v1 assembly for Shinella daejeonensis JCM 16236 | contig | 659017 | 66.69 |
| @ref | Description | Accession | Length | Database | NCBI tax ID | |
|---|---|---|---|---|---|---|
| 67770 | Shinella daejeonensis strain MJ02 16S ribosomal RNA gene, partial sequence | GQ241319 | 1400 | 659017 |
| @ref | GC-content (mol%) | Method | |
|---|---|---|---|
| 67770 | 64.3 | high performance liquid chromatography (HPLC) |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125439 | spore_formation | BacteriaNetⓘ | no | 98.90 | no |
| 125439 | motility | BacteriaNetⓘ | yes | 62.10 | no |
| 125439 | gram_stain | BacteriaNetⓘ | negative | 99.30 | no |
| 125439 | oxygen_tolerance | BacteriaNetⓘ | obligate aerobe | 94.90 | no |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positiveⓘ | no | 98.33 | no |
| 125438 | anaerobic | anaerobicⓘ | no | 96.73 | no |
| 125438 | aerobic | aerobicⓘ | yes | 81.39 | no |
| 125438 | spore-forming | spore-formingⓘ | no | 91.09 | no |
| 125438 | thermophilic | thermophileⓘ | no | 98.88 | no |
| 125438 | flagellated | motile2+ⓘ | yes | 64.44 | no |
| Topic | Title | Authors | Journal | DOI | Year | |
|---|---|---|---|---|---|---|
| Phylogeny | Shinella daejeonensis sp. nov., a nitrate-reducing bacterium isolated from sludge of a leachate treatment plant. | Lee M, Woo SG, Ten LN | Int J Syst Evol Microbiol | 10.1099/ijs.0.026435-0 | 2010 |
| #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 ) |
| #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) . |
| #67770 | Japan Collection of Microorganism (JCM) ; Curators of the JCM; |
| #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/bacdive161742.20251217.10
When using BacDive for research please cite the following paper
BacDive in 2025: the core database for prokaryotic strain data