Bacillus licheniformis SHG10 is a bacterium that was isolated from soil.
genome sequence Bacteria| @ref 20215 |
|
|
| Domain Bacteria |
| Phylum Bacillota |
| Class Bacilli |
| Order Caryophanales |
| Family Bacillaceae |
| Genus Bacillus |
| Species Bacillus licheniformis |
| Full scientific name Bacillus licheniformis (Weigmann 1898) Chester 1901 (Approved Lists 1980) |
| Synonyms (1) |
| @ref | Name | Growth | Medium link | Composition | |
|---|---|---|---|---|---|
| 21492 | NUTRIENT AGAR (DSMZ Medium 1) | Medium recipe at MediaDive | Name: NUTRIENT AGAR (DSMZ Medium 1) Composition: Agar 15.0 g/l Peptone 5.0 g/l Meat extract 3.0 g/l Distilled water |
| @ref | Growth | Type | Temperature (°C) | |
|---|---|---|---|---|
| 21492 | positive | growth | 30 |
| @ref | Spore formation | Confidence | |
|---|---|---|---|
| 125438 | 95.341 |
| @ref | Sample type | Country | Country ISO 3 Code | Continent | |
|---|---|---|---|---|---|
| 21492 | soil | Egypt | EGY | Africa |
| @ref | Pathogenicity human | Biosafety level | Biosafety level comment | |
|---|---|---|---|---|
| 21492 | yes, in single cases | 1 | Risk group (German classification) |
| @ref | Description | Assembly level | INSDC accession | BV-BRC accession | NCBI tax ID | Score | |
|---|---|---|---|---|---|---|---|
| 66792 | ASM2953705v2 assembly for Bacillus subtilis DSM 28096 | complete | 1423 | 62.09 |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125439 | spore_formation | BacteriaNetⓘ | yes | 76.30 | no |
| 125439 | motility | BacteriaNetⓘ | yes | 73.10 | no |
| 125439 | gram_stain | BacteriaNetⓘ | variable | 81.10 | no |
| 125439 | oxygen_tolerance | BacteriaNetⓘ | obligate aerobe | 86.20 | no |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positiveⓘ | yes | 83.48 | no |
| 125438 | anaerobic | anaerobicⓘ | no | 86.95 | no |
| 125438 | aerobic | aerobicⓘ | yes | 72.53 | no |
| 125438 | spore-forming | spore-formingⓘ | yes | 95.34 | no |
| 125438 | thermophilic | thermophileⓘ | no | 95.17 | yes |
| 125438 | flagellated | motile2+ⓘ | yes | 87.78 | no |
| Topic | Title | Authors | Journal | DOI | Year | |
|---|---|---|---|---|---|---|
| Enzymology | SHG10 keratinolytic alkaline protease from Bacillus licheniformis SHG10 DSM 28096: Robust stability and unusual non-cumbersome purification. | Embaby AM, Saeed H, Hussein A | J Basic Microbiol | 10.1002/jobm.201600073 | 2016 | |
| Biotechnology | Raw agro-industrial orange peel waste as a low cost effective inducer for alkaline polygalacturonase production from Bacillus licheniformis SHG10. | Embaby AM, Masoud AA, Marey HS, Shaban NZ, Ghonaim TM | Springerplus | 10.1186/2193-1801-3-327 | 2014 |
| #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 ) |
| #21492 | Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 28096 |
| #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) . |
| #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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If you want to cite this particular strain cite the following doi:
https://doi.org/10.13145/bacdive130164.20251217.10
When using BacDive for research please cite the following paper
BacDive in 2025: the core database for prokaryotic strain data