Borrelia miyamotoi HT31 is a bacterium of the family Borreliaceae.
genome sequence 16S sequence Bacteria| @ref 20215 |
|
|
| Domain Bacteria |
| Phylum Spirochaetota |
| Class Spirochaetia |
| Order Spirochaetales |
| Family Borreliaceae |
| Genus Borrelia |
| Species Borrelia miyamotoi |
| Full scientific name Borrelia miyamotoi Fukunaga et al. 1995 |
| @ref | Spore formation | Confidence | |
|---|---|---|---|
| 125438 | 94.372 |
Global distribution of 16S sequence D45192 (>99% sequence identity) for Borrelia miyamotoi subclade from Microbeatlas ![]()
| @ref | Biosafety level | Biosafety level comment | |
|---|---|---|---|
| 20215 | 2 | Risk group |
| @ref | Description | Assembly level | INSDC accession | BV-BRC accession | IMG accession | NCBI tax ID | Score | |
|---|---|---|---|---|---|---|---|---|
| 66792 | ASM1966850v1 assembly for Borrelia miyamotoi HT31 | complete | 47466 | 96.31 |
| @ref | Description | Accession | Length | Database | NCBI tax ID | |
|---|---|---|---|---|---|---|
| 20215 | Borrelia miyamotoi gene for 16S rRNA, partial sequence | D45192 | 1368 | 47466 |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positiveⓘ | no | 83.96 | no |
| 125438 | anaerobic | anaerobicⓘ | no | 78.39 | no |
| 125438 | aerobic | aerobicⓘ | no | 93.71 | no |
| 125438 | spore-forming | spore-formingⓘ | no | 94.37 | no |
| 125438 | thermophilic | thermophileⓘ | no | 91.15 | no |
| 125438 | flagellated | motile2+ⓘ | yes | 50.62 | no |
| #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) . |
| #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 ) |
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https://doi.org/10.13145/bacdive168084.20251217.10
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BacDive in 2025: the core database for prokaryotic strain data