Acidithiobacillus thiooxidans CLST is a mesophilic prokaryote that was isolated from salt flat brine.
mesophilic genome sequence 16S sequence| @ref 20215 |
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| Domain Pseudomonadati |
| Phylum Pseudomonadota |
| Class Acidithiobacillia |
| Order Acidithiobacillales |
| Family Acidithiobacillaceae |
| Genus Acidithiobacillus |
| Species Acidithiobacillus thiooxidans |
| Full scientific name Acidithiobacillus thiooxidans (Waksman and Joffe 1922) Kelly and Wood 2000 |
| Synonyms (3) |
| @ref | Name | Growth | Medium link | Composition | |
|---|---|---|---|---|---|
| 24475 | ACIDITHIOBACILLUS THIOOXIDANS MEDIUM (DSMZ Medium 71) | Medium recipe at MediaDive | Name: ACIDITHIOBACILLUS THIOOXIDANS MEDIUM (DSMZ Medium 71; with strain-specific modifications) Composition: Elemental sulfur 10.0 g/l (NH4)2SO4 3.0 g/l KH2PO4 3.0 g/l MgSO4 x 7 H2O 0.5 g/l CaCl2 x 2 H2O 0.25 g/l Distilled water |
| @ref | Growth | Type | Temperature (°C) | Range | |
|---|---|---|---|---|---|
| 24475 | positive | growth | 30 | mesophilic |
| @ref | Sample type | Geographic location | Country | Country ISO 3 Code | Continent | Latitude | Longitude | |
|---|---|---|---|---|---|---|---|---|
| 24475 | salt flat brine | Antofagasta region, Gorbea salt flat | Chile | CHL | Middle and South America | -25.4367 | -68.6981 -25.4367/-68.6981 |
Global distribution of 16S sequence KX100033 (>99% sequence identity) for Acidithiobacillus from Microbeatlas ![]()
| @ref | Biosafety level | Biosafety level comment | |
|---|---|---|---|
| 24475 | 1 | Risk group (German classification) |
| @ref | Description | Assembly level | INSDC accession | BV-BRC accession | IMG accession | NCBI tax ID | |
|---|---|---|---|---|---|---|---|
| 66792 | ASM207986v1 assembly for Acidithiobacillus thiooxidans CLST | scaffold | 930 |
| @ref | Description | Accession | Length | Database | NCBI tax ID | |
|---|---|---|---|---|---|---|
| 24475 | Acidithiobacillus thiooxidans strain CL 16S ribosomal RNA gene, partial sequence | KX100033 | 1536 | 930 |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125439 | spore_formation | BacteriaNetⓘ | no | 98.60 | no |
| 125439 | motility | BacteriaNetⓘ | yes | 60.30 | no |
| 125439 | gram_stain | BacteriaNetⓘ | negative | 97.90 | no |
| 125439 | oxygen_tolerance | BacteriaNetⓘ | facultative anaerobe | 84.00 | no |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positiveⓘ | no | 96.49 | no |
| 125438 | anaerobic | anaerobicⓘ | no | 83.07 | no |
| 125438 | aerobic | aerobicⓘ | yes | 58.38 | no |
| 125438 | spore-forming | spore-formingⓘ | no | 91.64 | no |
| 125438 | thermophilic | thermophileⓘ | no | 93.24 | yes |
| 125438 | flagellated | motile2+ⓘ | yes | 67.28 | no |
| Title | Authors | Journal | DOI | Year | |
|---|---|---|---|---|---|
| Bioleaching of Transition Metals From Limonitic Laterite Deposits and Reassessment of the Multiple Roles of Sulfur-Oxidizing Acidophiles in the Process. | Johnson DB, Smith SL, Santos AL. | Front Microbiol | 10.3389/fmicb.2021.703177 | 2021 |
| #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 ) |
| #24475 | Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 103717 |
| #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) . |
| #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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https://doi.org/10.13145/bacdive132685.20251217.10
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BacDive in 2025: the core database for prokaryotic strain data