Schleiferia thermophila TU-20 is a bacterium that was isolated from water from a hot spring.
genome sequence 16S sequence Bacteria| @ref 20215 |
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| Domain Bacteria |
| Phylum Bacteroidota |
| Class Flavobacteriia |
| Order Flavobacteriales |
| Family Schleiferiaceae |
| Genus Schleiferia |
| Species Schleiferia thermophila |
| Full scientific name Schleiferia thermophila Albuquerque et al. 2011 |
| @ref | Name | Growth | Medium link | Composition | |
|---|---|---|---|---|---|
| 15689 | MODIFIED THERMUS 162 MEDIUM (DSMZ Medium 630) | Medium recipe at MediaDive | Name: MODIFIED THERMUS 162 MEDIUM (DSMZ Medium 630) Composition: Agar 28.0 g/l Na2HPO4 x 12 H2O 4.3 g/l Yeast extract 2.5 g/l Tryptone 2.5 g/l KH2PO4 0.544 g/l MgCl2 x 6 H2O 0.2 g/l CaSO4 x 2 H2O 0.04 g/l Nitrilotriacetic acid 0.0064 g/l Fe(III) citrate 0.00122472 g/l FeCl2 x 4 H2O 0.0005 g/l MnCl2 x 4 H2O 0.00025 g/l CoCl2 x 4 H2O 0.00015 g/l CuCl2 x 2 H2O 2.5e-05 g/l Na2MoO4 x 2 H2O 2.5e-05 g/l H3BO3 1e-05 g/l NiCl2 x 6 H2O 1e-05 g/l Distilled water |
| Cat1 | Cat2 | Cat3 | |
|---|---|---|---|
| #Environmental | #Aquatic | #Thermal spring | |
| #Condition | #Thermophilic (>45°C) | - |
Global distribution of 16S sequence HQ172900 (>99% sequence identity) for Schleiferia thermophila subclade from Microbeatlas ![]()
| @ref | Description | Assembly level | INSDC accession | BV-BRC accession | IMG accession | NCBI tax ID | Score | |
|---|---|---|---|---|---|---|---|---|
| 67770 | ASM386517v1 assembly for Schleiferia thermophila JCM 30197 | contig | 884107 | 73.26 | ||||
| 67770 | ASM333743v1 assembly for Schleiferia thermophila DSM 21410 | scaffold | 884107 | 73.23 |
| @ref | Description | Accession | Length | Database | NCBI tax ID | |
|---|---|---|---|---|---|---|
| 15689 | Schleiferia thermophila strain TU-20 16S ribosomal RNA gene, partial sequence | HQ172900 | 1499 | 884107 |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125439 | oxygen_tolerance | BacteriaNetⓘ | obligate aerobe | 80.22 | no |
| 125439 | gram_stain | BacteriaNetⓘ | negative | 74.90 | no |
| 125439 | spore_formation | BacteriaNetⓘ | no | 99.46 | no |
| 125439 | motility | BacteriaNetⓘ | no | 92.12 | no |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positiveⓘ | no | 98.50 | no |
| 125438 | anaerobic | anaerobicⓘ | no | 93.76 | no |
| 125438 | aerobic | aerobicⓘ | yes | 81.99 | no |
| 125438 | spore-forming | spore-formingⓘ | no | 93.38 | no |
| 125438 | thermophilic | thermophileⓘ | no | 88.58 | no |
| 125438 | flagellated | motile2+ⓘ | no | 86.91 | no |
| Topic | Title | Authors | Journal | DOI | Year | |
|---|---|---|---|---|---|---|
| Phylogeny | Thermaurantimonas aggregans gen. nov., sp. nov., a moderately thermophilic heterotrophic aggregating bacterium isolated from microbial mats at a terrestrial hot spring. | Iino T, Kawai S, Yuki M, Dekio I, Ohkuma M, Haruta S | Int J Syst Evol Microbiol | 10.1099/ijsem.0.003888 | 2020 | |
| Phylogeny | Schleiferia thermophila gen. nov., sp. nov., a slightly thermophilic bacterium of the phylum 'Bacteroidetes' and the proposal of Schleiferiaceae fam. nov. | Albuquerque L, Rainey FA, Nobre MF, da Costa MS | Int J Syst Evol Microbiol | 10.1099/ijs.0.028852-0 | 2010 |
| #15689 | Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 21410 |
| #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 ) |
| #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 . |
| #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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