Garicola koreensis SJ5-4 is a bacterium that was isolated from saeu-jeot .
genome sequence 16S sequence Bacteria| @ref 20215 |
|
|
| Domain Bacteria |
| Phylum Actinomycetota |
| Class Actinomycetes |
| Order Micrococcales |
| Family Micrococcaceae |
| Genus Garicola |
| Species Garicola koreensis |
| Full scientific name Garicola koreensis Lo et al. 2015 |
| @ref | Name | Growth | Medium link | Composition | |
|---|---|---|---|---|---|
| 22146 | BACTO MARINE BROTH (DIFCO 2216) (DSMZ Medium 514) | Medium recipe at MediaDive | Name: BACTO MARINE BROTH (DIFCO 2216) (DSMZ Medium 514) Composition: NaCl 19.45 g/l MgCl2 5.9 g/l Bacto peptone 5.0 g/l Na2SO4 3.24 g/l CaCl2 1.8 g/l Yeast extract 1.0 g/l KCl 0.55 g/l NaHCO3 0.16 g/l Fe(III) citrate 0.1 g/l KBr 0.08 g/l SrCl2 0.034 g/l H3BO3 0.022 g/l Na2HPO4 0.008 g/l Na-silicate 0.004 g/l NaF 0.0024 g/l (NH4)NO3 0.0016 g/l Distilled water |
| Cat1 | Cat2 | Cat3 | |
|---|---|---|---|
| #Engineered | #Food production | #Vegetable (incl. Grains) | |
| #Engineered | #Food production | #Fermented |
Global distribution of 16S sequence JX152781 (>99% sequence identity) for Garicola koreensis subclade from Microbeatlas ![]()
| @ref | Biosafety level | Biosafety level comment | |
|---|---|---|---|
| 22146 | 1 | Risk group (German classification) |
| @ref | Description | Assembly level | INSDC accession | BV-BRC accession | IMG accession | NCBI tax ID | Score | |
|---|---|---|---|---|---|---|---|---|
| 124043 | ASM3954392v1 assembly for Garicola koreensis JCM 18572 | scaffold | 1262554 | 73.94 | ||||
| 66792 | ASM1419544v1 assembly for Garicola koreensis DSM 28238 | contig | 1262554 | 55.64 |
| @ref | Description | Accession | Length | Database | NCBI tax ID | |
|---|---|---|---|---|---|---|
| 22146 | Garicola koreensis strain SJ5-4 16S ribosomal RNA gene, partial sequence | JX152781 | 1459 | 1262554 |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125439 | spore_formation | BacteriaNetⓘ | no | 92.20 | no |
| 125439 | motility | BacteriaNetⓘ | no | 52.80 | no |
| 125439 | gram_stain | BacteriaNetⓘ | positive | 69.80 | no |
| 125439 | oxygen_tolerance | BacteriaNetⓘ | obligate aerobe | 90.50 | no |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positiveⓘ | yes | 85.69 | no |
| 125438 | anaerobic | anaerobicⓘ | no | 92.32 | no |
| 125438 | spore-forming | spore-formingⓘ | no | 79.78 | no |
| 125438 | aerobic | aerobicⓘ | yes | 76.95 | no |
| 125438 | thermophilic | thermophileⓘ | no | 86.82 | yes |
| 125438 | flagellated | motile2+ⓘ | no | 89.50 | no |
| Topic | Title | Authors | Journal | DOI | Year | |
|---|---|---|---|---|---|---|
| Phylogeny | Garicola koreensis gen. nov., sp. nov., isolated from saeu-jeot, traditional Korean fermented shrimp. | Lo N, Lee SH, Jin HM, Jung JY, Schumann P, Jeon CO | Int J Syst Evol Microbiol | 10.1099/ijs.0.000056 | 2015 |
| #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 ) |
| #22146 | Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 28238 |
| #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; |
| #69479 | João F Matias Rodrigues, Janko Tackmann,Gregor Rot, Thomas SB Schmidt, Lukas Malfertheiner, Mihai Danaila,Marija Dmitrijeva, Daniela Gaio, Nicolas Näpflin and Christian von Mering. University of Zurich.: MicrobeAtlas 1.0 beta . |
| #124043 | Isabel Schober, Julia Koblitz: Data extracted from sequence databases, automatically matched based on designation and taxonomy . |
| #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 ) |
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If you want to cite this particular strain cite the following doi:
https://doi.org/10.13145/bacdive130439.20251217.10
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BacDive in 2025: the core database for prokaryotic strain data