Strain identifier
BacDive ID: 170243
Type strain: ![]()
Species: Haladaptatus salinisoli
Strain Designation: PSR8
NCBI tax ID(s): 2884876 (species)
version 9.3 (current version)
General
@ref: 20215
BacDive-ID: 170243
keywords: genome sequence, 16S sequence, Archaea
description: Haladaptatus salinisoli PSR8 is an archaeon of the family Halobacteriaceae.
NCBI tax id
- NCBI tax id: 2884876
- Matching level: species
doi: 10.13145/bacdive170243.20250331.9.3
Name and taxonomic classification
LPSN
- @ref: 20215
- description: domain/archaea
- keyword: phylum/methanobacteriota
- domain: Archaea
- phylum: Methanobacteriota
- class: Halobacteria
- order: Halobacteriales
- family: Halobacteriaceae
- genus: Haladaptatus
- species: Haladaptatus salinisoli
- full scientific name: Haladaptatus salinisoli Xin et al. 2022
@ref: 20215
domain: Archaea
phylum: Euryarchaeota
class: Halobacteria
order: Halobacteriales
family: Halobacteriaceae
genus: Haladaptatus
species: Haladaptatus salinisoli
full scientific name: Haladaptatus salinisoli Xin et al. 2022
strain designation: PSR8
type strain: yes
Physiology and metabolism
spore formation
- @ref: 125439
- spore formation: no
- confidence: 91.8
Sequence information
16S sequences
- @ref: 20215
- description: Haladaptatus salinisoli strain PSR8 16S ribosomal RNA gene, partial sequence
- accession: MK680098
- length: 1472
- database: nuccore
- NCBI tax ID: 2884876
Genome sequences
- @ref: 66792
- description: Haladaptatus salinisoli PSR8
- accession: GCA_020614375
- assembly level: complete
- database: ncbi
- NCBI tax ID: 2884876
Genome-based predictions
predictions
| @ref | model | trait | description | prediction | confidence | training_data |
|---|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positive | Positive reaction to Gram-staining | no | 74.301 | no |
| 125438 | anaerobic | anaerobic | Ability to grow under anoxygenic conditions (including facultative anaerobes) | no | 83.407 | no |
| 125438 | aerobic | aerobic | Ability to grow under oxygenic conditions (including facultative aerobes) | yes | 83.315 | no |
| 125438 | spore-forming | spore-forming | Ability to form endo- or exospores | no | 80.481 | no |
| 125438 | thermophile | thermophilic | Ability to grow at temperatures above or equal to 45°C | no | 72.65 | no |
| 125438 | motile2+ | flagellated | Ability to perform flagellated movement | no | 86 | no |
| 125439 | BacteriaNet | spore_formation | Ability to form endo- or exospores | no | 91.8 | |
| 125439 | BacteriaNet | motility | Ability to perform movement | no | 56.5 | |
| 125439 | BacteriaNet | gram_stain | Reaction to gram-staining | negative | 89.2 | |
| 125439 | BacteriaNet | oxygen_tolerance | Oxygenic conditions needed for growth | aerobe | 79.3 |
External links
@ref: 20215
culture collection no.: CGMCC 1.17025, JCM 34142
literature
- topic: Phylogeny
- Pubmed-ID: 36256551
- title: Haladaptatus halobius sp. nov. and Haladaptatus salinisoli sp. nov., two extremely halophilic archaea isolated from Gobi saline soil.
- authors: Xin YJ, Bao CX, Tan S, Hou J, Cui HL
- journal: Int J Syst Evol Microbiol
- DOI: 10.1099/ijsem.0.005543
- year: 2022
- mesh: RNA, Ribosomal, 16S/genetics, Phylogeny, *Soil, DNA, Archaeal/genetics, Base Composition, Sequence Analysis, DNA, Fatty Acids/chemistry, DNA, Bacterial/genetics, Bacterial Typing Techniques, *Halobacteriaceae, Glycolipids/chemistry, Sulfates, Phosphatidylglycerols/analysis, Nucleotides, Amino Acids, Phosphatidic Acids/analysis, Esters
- topic2: Transcriptome
Reference
| @id | authors | title | doi/url |
|---|---|---|---|
| 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 | 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) | https://diaspora-project.de/progress.html#genomes |
| 125438 | Julia Koblitz, Lorenz Christian Reimer, Rüdiger Pukall, Jörg Overmann | Predicting bacterial phenotypic traits through improved machine learning using high-quality, curated datasets | 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 | https://github.com/GenomeNet/deepG |