Priestia taiwanensis FJAT-14571 is a bacterium that was isolated from soil.
genome sequence 16S sequence Bacteria| @ref 20215 |
|
|
| Domain Bacteria |
| Phylum Bacillota |
| Class Bacilli |
| Order Caryophanales |
| Family Bacillaceae |
| Genus Priestia |
| Species Priestia taiwanensis |
| Full scientific name Priestia taiwanensis (Liu et al. 2015) Gupta et al. 2020 |
| Synonyms (1) |
| @ref | Name | Growth | Medium link | Composition | |
|---|---|---|---|---|---|
| 22584 | 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) | |
|---|---|---|---|---|
| 22584 | positive | growth | 30 |
| @ref | Sample type | Geographic location | Country | Country ISO 3 Code | Continent | Latitude | Longitude | |
|---|---|---|---|---|---|---|---|---|
| 22584 | soil | Xinbei City, Yeh-Liu geological site (121.701567° E 25.210779° N) | Taiwan, Province of China | TWN | Asia | 25.2108 | 121.702 25.2108/121.702 |
Global distribution of 16S sequence KF040588 (>99% sequence identity) for Priestia taiwanensis subclade from Microbeatlas ![]()
| @ref | Biosafety level | Biosafety level comment | |
|---|---|---|---|
| 22584 | 1 | Risk group (German classification) |
| @ref | Description | Assembly level | INSDC accession | BV-BRC accession | IMG accession | NCBI tax ID | Score | |
|---|---|---|---|---|---|---|---|---|
| 66792 | ASM1690875v1 assembly for Priestia taiwanensis DSM 27845 | contig | 1347902 | 72.83 | ||||
| 66792 | ASM1463835v1 assembly for Priestia taiwanensis CGMCC 1.12698 | scaffold | 1347902 | 72.62 |
| @ref | GC-content (mol%) | Method | |
|---|---|---|---|
| 22584 | 40.8 | thermal denaturation, midpoint method (Tm) |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125439 | spore_formation | BacteriaNetⓘ | yes | 91.70 | no |
| 125439 | motility | BacteriaNetⓘ | yes | 88.20 | no |
| 125439 | gram_stain | BacteriaNetⓘ | positive | 75.90 | no |
| 125439 | oxygen_tolerance | BacteriaNetⓘ | facultative anaerobe | 94.60 | no |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positiveⓘ | yes | 70.04 | no |
| 125438 | anaerobic | anaerobicⓘ | no | 92.75 | no |
| 125438 | aerobic | aerobicⓘ | yes | 64.42 | no |
| 125438 | spore-forming | spore-formingⓘ | yes | 85.64 | no |
| 125438 | thermophilic | thermophileⓘ | no | 89.66 | yes |
| 125438 | flagellated | motile2+ⓘ | yes | 86.39 | no |
| Topic | Title | Authors | Journal | DOI | Year | |
|---|---|---|---|---|---|---|
| Enzymology | Unveiling novel features and phylogenomic assessment of indigenous Priestia megaterium AB-S79 using comparative genomics. | Adeniji AA, Chukwuneme CF, Conceicao EC, Ayangbenro AS, Wilkinson E, Maasdorp E, de Oliveira T, Babalola OO. | Microbiol Spectr | 10.1128/spectrum.01466-24 | 2025 | |
| Phylogeny | Bacillus taiwanensis sp. nov., isolated from a soil sample from Taiwan. | Liu B, Liu GH, Sengonca C, Schumann P, Wang MK, Xiao RF, Zheng XF, Chen Z | Int J Syst Evol Microbiol | 10.1099/ijs.0.000222 | 2015 |
| #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 ) |
| #22584 | Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 27845 |
| #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 . |
| #124043 | Isabel Schober, Julia Koblitz: Data extracted from sequence databases, automatically matched based on designation and taxonomy . |
| #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/bacdive131357.20251217.10
When using BacDive for research please cite the following paper
BacDive in 2025: the core database for prokaryotic strain data