Sphingorhabdus rigui 01SU5-P is a mesophilic prokaryote that was isolated from surface freshwater of wetland.
mesophilic genome sequence 16S sequence| @ref 20215 |
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| Domain Pseudomonadati |
| Phylum Pseudomonadota |
| Class Alphaproteobacteria |
| Order Sphingomonadales |
| Family Sphingomonadaceae |
| Genus Sphingorhabdus |
| Species Sphingorhabdus rigui |
| Full scientific name Sphingorhabdus rigui (Baik et al. 2013) Park et al. 2014 |
| Synonyms (1) |
| @ref | Name | Growth | Medium link | Composition | |
|---|---|---|---|---|---|
| 20822 | R2A MEDIUM (DSMZ Medium 830) | Medium recipe at MediaDive | Name: R2A MEDIUM (DSMZ Medium 830) Composition: Agar 15.0 g/l Casamino acids 0.5 g/l Starch 0.5 g/l Glucose 0.5 g/l Proteose peptone 0.5 g/l Yeast extract 0.5 g/l K2HPO4 0.3 g/l Na-pyruvate 0.3 g/l MgSO4 x 7 H2O 0.05 g/l Distilled water |
| @ref | Oxygen tolerance | Confidence | |
|---|---|---|---|
| 125439 | aerobe | 99.4 |
| 67770 | Observationquinones: Q-10 |
| @ref | Chebi-ID | Metabolite | Utilization activity | Kind of utilization tested | |
|---|---|---|---|---|---|
| 68369 | 17128 ChEBI | adipate | + | assimilation | from API 20NE |
| 68369 | 29016 ChEBI | arginine | - | hydrolysis | from API 20NE |
| 68369 | 17634 ChEBI | D-glucose | + | assimilation | from API 20NE |
| 68369 | 17634 ChEBI | D-glucose | - | fermentation | from API 20NE |
| 68369 | 16899 ChEBI | D-mannitol | - | assimilation | from API 20NE |
| 68369 | 16024 ChEBI | D-mannose | + | assimilation | from API 20NE |
| 68369 | 27689 ChEBI | decanoate | - | assimilation | from API 20NE |
| 68369 | 4853 ChEBI | esculin | + | hydrolysis | from API 20NE |
| 68369 | 5291 ChEBI | gelatin | - | hydrolysis | from API 20NE |
| 68369 | 24265 ChEBI | gluconate | - | assimilation | from API 20NE |
| 68369 | 30849 ChEBI | L-arabinose | - | assimilation | from API 20NE |
| 68369 | 25115 ChEBI | malate | + | assimilation | from API 20NE |
| 68369 | 17306 ChEBI | maltose | - | assimilation | from API 20NE |
| 68369 | 59640 ChEBI | N-acetylglucosamine | - | assimilation | from API 20NE |
| 68369 | 17632 ChEBI | nitrate | - | reduction | from API 20NE |
| 68369 | 27897 ChEBI | tryptophan | - | energy source | from API 20NE |
| 68369 | 16199 ChEBI | urea | - | hydrolysis | from API 20NE |
| Cat1 | Cat2 | Cat3 | |
|---|---|---|---|
| #Environmental | #Aquatic | #Freshwater | |
| #Environmental | #Aquatic | #Surface water | |
| #Environmental | #Terrestrial | #Wetland (Swamp) |
| @ref | Sample type | Geographic location | Country | Country ISO 3 Code | Continent | Latitude | Longitude | |
|---|---|---|---|---|---|---|---|---|
| 20822 | surface freshwater of wetland | Woopo Wetland | Republic of Korea | KOR | Asia | 35.55 | 128.417 35.55/128.417 | |
| 67770 | Freshwater of Woopo wetland (35° 33' N 128° 25' E) in Gyeongnam Province | Republic of Korea | KOR | Asia | 35.55 | 128.417 35.55/128.417 |
Global distribution of 16S sequence HQ436492 (>99% sequence identity) for Sphingorhabdus from Microbeatlas ![]()
| @ref | Biosafety level | Biosafety level comment | |
|---|---|---|---|
| 20822 | 1 | Risk group (German classification) |
| @ref | Description | Assembly level | INSDC accession | BV-BRC accession | IMG accession | NCBI tax ID | Score | |
|---|---|---|---|---|---|---|---|---|
| 66792 | ASM1419659v1 assembly for Sphingorhabdus rigui DSM 29050 | scaffold | 1282858 | 75.84 | ||||
| 124043 | ASM3953783v1 assembly for Sphingorhabdus rigui JCM 17509 | contig | 1282858 | 73.13 |
| @ref | Description | Accession | Length | Database | NCBI tax ID | |
|---|---|---|---|---|---|---|
| 20822 | Sphingopyxis rigui strain 01SU5-P 16S ribosomal RNA gene, partial sequence | HQ436492 | 1435 | 1282858 |
| @ref | GC-content (mol%) | Method | |
|---|---|---|---|
| 67770 | 57.3 | high performance liquid chromatography (HPLC) |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125439 | spore_formation | BacteriaNetⓘ | no | 98.80 | no |
| 125439 | motility | BacteriaNetⓘ | yes | 72.10 | no |
| 125439 | gram_stain | BacteriaNetⓘ | negative | 99.70 | no |
| 125439 | oxygen_tolerance | BacteriaNetⓘ | aerobe | 99.40 | no |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positiveⓘ | no | 97.97 | no |
| 125438 | anaerobic | anaerobicⓘ | no | 96.44 | no |
| 125438 | aerobic | aerobicⓘ | yes | 86.74 | no |
| 125438 | spore-forming | spore-formingⓘ | no | 92.57 | no |
| 125438 | thermophilic | thermophileⓘ | no | 94.03 | no |
| 125438 | flagellated | motile2+ⓘ | no | 68.73 | no |
| Topic | Title | Authors | Journal | DOI | Year | |
|---|---|---|---|---|---|---|
| Phylogeny | Sphingopyxis rigui sp. nov. and Sphingopyxis wooponensis sp. nov., isolated from wetland freshwater, and emended description of the genus Sphingopyxis. | Baik KS, Choe HN, Park SC, Hwang YM, Kim EM, Park C, Seong CN | Int J Syst Evol Microbiol | 10.1099/ijs.0.044057-0 | 2012 | |
| Phylogeny | Sphingorhabdus pulchriflava sp. nov., isolated from a river. | Jung GY, Nam IH, Han YS, Ahn JS, Rhee SK, Kim SJ | Int J Syst Evol Microbiol | 10.1099/ijsem.0.003503 | 2019 |
| #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 ) |
| #20822 | Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 29050 |
| #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; |
| #68369 | Automatically annotated from API 20NE . |
| #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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