Strain identifier
BacDive ID: 158083
Type strain: ![]()
Species: Methylosinus sp.
Strain Designation: PW1
Strain history: <- A. Vorobev, Univ. of Washington, Seattle, USA; PW1 <- M. G. Kalyuzhnaya <- A. J. Auman
NCBI tax ID(s): 427 (species)
General
@ref: 64657
BacDive-ID: 158083
DSM-Number: 24492
keywords: genome sequence, 16S sequence, Bacteria, mesophilic, Gram-negative
description: Methylosinus sp. PW1 is a mesophilic, Gram-negative bacterium that was isolated from sediment.
NCBI tax id
- NCBI tax id: 427
- Matching level: species
strain history
- @ref: 64657
- history: <- A. Vorobev, Univ. of Washington, Seattle, USA; PW1 <- M. G. Kalyuzhnaya <- A. J. Auman
doi: 10.13145/bacdive158083.20250331.9.3
Name and taxonomic classification
LPSN
- @ref: 20215
- description: domain/bacteria
- keyword: phylum/pseudomonadota
- domain: Bacteria
- phylum: Pseudomonadota
- class: Alphaproteobacteria
- order: Hyphomicrobiales
- family: Methylocystaceae
- genus: Methylosinus
- species: Methylosinus sp.
- full scientific name: Methylosinus (ex Whittenbury et al. 1970) Bowman et al. 1993
@ref: 64657
domain: Bacteria
phylum: Proteobacteria
class: Alphaproteobacteria
order: Rhizobiales
family: Methylocystaceae
genus: Methylosinus
species: Methylosinus sp.
full scientific name: Methylosinus sp.
strain designation: PW1
type strain: no
Morphology
cell morphology
| @ref | gram stain | confidence |
|---|---|---|
| 125438 | negative | 97 |
| 125439 | negative | 97.3 |
Culture and growth conditions
culture medium
- @ref: 64657
- name: MINERAL MEDIUM (DSMZ Medium 1007)
- growth: yes
- link: https://mediadive.dsmz.de/medium/1007
- composition: Name: MINERAL MEDIUM (DSMZ Medium 1007) Composition: KNO3 0.25 g/l KH2PO4 0.1 g/l MgSO4 x 7 H2O 0.05 g/l CaCl2 x 2 H2O 0.01 g/l EDTA 0.005 g/l FeSO4 x 7 H2O 0.002 g/l CoCl2 x 6 H2O 0.0002 g/l CuCl2 x 5 H2O 0.0001 g/l ZnSO4 x 7 H2O 0.0001 g/l Na2MoO4 3e-05 g/l MnCl2 x 4 H2O 3e-05 g/l NiCl2 x 6 H2O 2e-05 g/l Distilled water
culture temp
- @ref: 64657
- growth: positive
- type: growth
- temperature: 25
Physiology and metabolism
oxygen tolerance
- @ref: 125439
- oxygen tolerance: aerobe
- confidence: 93.2
spore formation
- @ref: 125439
- spore formation: no
- confidence: 95.6
Isolation, sampling and environmental information
isolation
- @ref: 64657
- sample type: sediment
- geographic location: LakeWashington
- country: USA
- origin.country: USA
- continent: North America
isolation source categories
| Cat1 | Cat2 | Cat3 |
|---|---|---|
| #Environmental | #Aquatic | #Sediment |
| #Environmental | #Terrestrial | #Sediment |
taxonmaps
- @ref: 69479
- File name: preview.99_1539.png
- url: https://microbeatlas.org/index.html?action=taxon&taxon_id=90_86;96_208;97_227;98_1215;99_1539&stattab=map
- Last taxonomy: Methylosinus
- 16S sequence: AF150802
- Sequence Identity:
- Total samples: 5561
- soil counts: 930
- aquatic counts: 3886
- animal counts: 346
- plant counts: 399
Sequence information
16S sequences
- @ref: 64657
- description: Methylosinus sp. PW1 16S ribosomal RNA gene, partial sequence
- accession: AF150802
- length: 1452
- database: nuccore
- NCBI tax ID: 107636
Genome sequences
| @ref | description | accession | assembly level | database | NCBI tax ID |
|---|---|---|---|---|---|
| 66792 | Methylosinus sp. PW1 | GCA_000745215 | contig | ncbi | 107636 |
| 66792 | Methylosinus sp. PW1 | 107636.3 | wgs | patric | 107636 |
| 66792 | Methylosinus sp. PW1 | 2582581241 | draft | img | 107636 |
Genome-based predictions
predictions
| @ref | model | trait | description | prediction | confidence | training_data |
|---|---|---|---|---|---|---|
| 125439 | BacteriaNet | oxygen_tolerance | Oxygenic conditions needed for growth | aerobe | 93.2 | |
| 125439 | BacteriaNet | gram_stain | Reaction to gram-staining | negative | 97.3 | |
| 125439 | BacteriaNet | motility | Ability to perform movement | yes | 55.1 | |
| 125439 | BacteriaNet | spore_formation | Ability to form endo- or exospores | no | 95.6 | |
| 125438 | gram-positive | gram-positive | Positive reaction to Gram-staining | no | 97 | no |
| 125438 | anaerobic | anaerobic | Ability to grow under anoxygenic conditions (including facultative anaerobes) | no | 85.811 | no |
| 125438 | spore-forming | spore-forming | Ability to form endo- or exospores | no | 86.899 | no |
| 125438 | aerobic | aerobic | Ability to grow under oxygenic conditions (including facultative aerobes) | yes | 74.19 | no |
| 125438 | thermophile | thermophilic | Ability to grow at temperatures above or equal to 45°C | no | 95.124 | no |
| 125438 | motile2+ | flagellated | Ability to perform flagellated movement | yes | 67.743 | no |
External links
@ref: 64657
culture collection no.: DSM 24492
straininfo link
- @ref: 110926
- straininfo: 408043
Reference
| @id | authors | title | doi/url | catalogue |
|---|---|---|---|---|
| 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 | |
| 64657 | Curators of the DSMZ | https://www.dsmz.de/collection/catalogue/details/culture/DSM-24492 | Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH (DSM 24492) | |
| 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 | |
| 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 | https://microbeatlas.org/ | |
| 110926 | Reimer, L.C., Lissin, A.,Schober, I., Witte,J.F., Podstawka, A., Lüken, H., Bunk, B.,Overmann, J. | StrainInfo: A central database for resolving microbial strain identifiers | 10.60712/SI-ID408043.1 | |
| 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 |