Sutcliffiella horikoshii PN 122 is a bacterium of the family Bacillaceae.
Bacteria| @ref 20215 |
|
|
| Domain Bacteria |
| Phylum Bacillota |
| Class Bacilli |
| Order Caryophanales |
| Family Bacillaceae |
| Genus Sutcliffiella |
| Species Sutcliffiella horikoshii |
| Full scientific name Sutcliffiella horikoshii (Nielsen et al. 1995) Gupta et al. 2020 |
| Synonyms (1) |
| BacDive ID | Other strains from Sutcliffiella horikoshii (3) | Type strain |
|---|---|---|
| 1142 | S. horikoshii PN 121, JP 277, DSM 8719, ATCC 700161, CIP ... (type strain) | |
| 1141 | S. horikoshii PB 19, DSM 6951 | |
| 1143 | S. horikoshii PN 119, 874 X, DSM 9711 |
| @ref | Gram stain | Confidence | |
|---|---|---|---|
| 125438 | negative | 99.75 |
| @ref | Name | Growth | Medium link | Composition | |
|---|---|---|---|---|---|
| 3699 | ALKALINE NUTRIENT AGAR (DSMZ Medium 31) | Medium recipe at MediaDive | Name: ALKALINE NUTRIENT AGAR (DSMZ Medium 31; with strain-specific modifications) Composition: Agar 15.0 g/l Na2CO3 anhydrous 5.3 g/l Peptone 5.0 g/l NaCl 5.0 g/l NaHCO3 4.2 g/l Meat extract 3.0 g/l Distilled water |
| @ref | Growth | Type | Temperature (°C) | |
|---|---|---|---|---|
| 3699 | positive | growth | 30 |
| 3699 | GC-content (mol%)41.1 |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positiveⓘ | no | 99.75 | no |
| 125438 | anaerobic | anaerobicⓘ | no | 95.97 | no |
| 125438 | spore-forming | spore-formingⓘ | no | 87.00 | no |
| 125438 | aerobic | aerobicⓘ | no | 67.07 | no |
| 125438 | thermophilic | thermophileⓘ | no | 98.50 | yes |
| 125438 | flagellated | motile2+ⓘ | yes | 76.80 | no |
| #3699 | Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 9712 |
| #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 ) |
| #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 ) |
| #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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If you want to cite this particular strain cite the following doi:
https://doi.org/10.13145/bacdive1144.20260601.11
When using BacDive for research please cite the following paper
BacDive in 2025: the core database for prokaryotic strain data