Sphingopyxis panaciterrulae DSM 27163 is a bacterium that was isolated from soil of ginseng field.
genome sequence Bacteria| @ref 20215 |
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| Domain Bacteria |
| Phylum Pseudomonadota |
| Class Alphaproteobacteria |
| Order Sphingomonadales |
| Family Sphingomonadaceae |
| Genus Sphingopyxis |
| Species Sphingopyxis panaciterrulae |
| Full scientific name Sphingopyxis panaciterrulae Srinivasan et al. 2010 |
| BacDive ID | Other strains from Sphingopyxis panaciterrulae (1) | Type strain |
|---|---|---|
| 14286 | S. panaciterrulae DSM 25122, JCM 14844, KCTC 22112, DCY 34 (type strain) |
| Cat1 | Cat2 | Cat3 | |
|---|---|---|---|
| #Engineered | #Agriculture | #Field | |
| #Environmental | #Terrestrial | #Soil | |
| #Host | #Plants | #Herbaceous plants (Grass,Crops) |
| @ref | Sample type | Geographic location | Country | Country ISO 3 Code | Continent | |
|---|---|---|---|---|---|---|
| 19106 | soil of ginseng field | Daejeon | Republic of Korea | KOR | Asia |
| @ref | Description | Assembly level | INSDC accession | BV-BRC accession | IMG accession | NCBI tax ID | Score | |
|---|---|---|---|---|---|---|---|---|
| 66792 | ASM1419929v1 assembly for Sphingopyxis panaciterrulae DSM 27163 | contig | 462372 | 66.07 |
| @ref | GC-content (mol%) | Method | |
|---|---|---|---|
| 19106 | 62.3 | high performance liquid chromatography (HPLC) |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125439 | spore_formation | BacteriaNetⓘ | no | 97.20 | no |
| 125439 | motility | BacteriaNetⓘ | yes | 75.80 | no |
| 125439 | gram_stain | BacteriaNetⓘ | negative | 98.70 | no |
| 125439 | oxygen_tolerance | BacteriaNetⓘ | obligate aerobe | 97.50 | no |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positiveⓘ | no | 93.95 | no |
| 125438 | anaerobic | anaerobicⓘ | no | 94.10 | no |
| 125438 | spore-forming | spore-formingⓘ | no | 90.33 | no |
| 125438 | aerobic | aerobicⓘ | yes | 89.36 | no |
| 125438 | thermophilic | thermophileⓘ | no | 97.41 | no |
| 125438 | flagellated | motile2+ⓘ | yes | 64.40 | no |
| Topic | Title | Authors | Journal | DOI | Year | |
|---|---|---|---|---|---|---|
| Phylogeny | Sphingopyxis indica sp. nov., isolated from a high dose point hexachlorocyclohexane (HCH)-contaminated dumpsite. | Jindal S, Dua A, Lal R | Int J Syst Evol Microbiol | 10.1099/ijs.0.040840-0 | 2012 | |
| Phylogeny | Sphingopyxis panaciterrulae sp. nov., isolated from soil of a ginseng field. | Srinivasan S, Kim MK, Sathiyaraj G, Veena V, Mahalakshmi M, Kalaiselvi S, Kim YJ, Yang DC | Int J Syst Evol Microbiol | 10.1099/ijs.0.019414-0 | 2009 |
| #19106 | Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 27163 |
| #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) . |
| #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 . |
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If you want to cite this particular strain cite the following doi:
https://doi.org/10.13145/bacdive23282.20251217.10
When using BacDive for research please cite the following paper
BacDive in 2025: the core database for prokaryotic strain data