Strain identifier
BacDive ID: 167685
Type strain: 
Species: Geomonas edaphica
Strain Designation: Red53
NCBI tax ID(s): 2570226 (species)
version 9.3 (current version)
General
@ref: 20215
BacDive-ID: 167685
keywords: genome sequence, 16S sequence, Bacteria, Gram-negative
description: Geomonas edaphica Red53 is a Gram-negative bacterium of the family Geobacteraceae.
NCBI tax id
- NCBI tax id: 2570226
- Matching level: species
doi: 10.13145/bacdive167685.20250331.9.3
Name and taxonomic classification
LPSN
- @ref: 20215
- description: domain/bacteria
- keyword: phylum/pseudomonadota
- domain: Bacteria
- phylum: Pseudomonadota
- class: Deltaproteobacteria
- order: Desulfuromonadales
- family: Geobacteraceae
- genus: Geomonas
- species: Geomonas edaphica
- full scientific name: Geomonas edaphica Xu et al. 2020
@ref: 20215
domain: Bacteria
phylum: Pseudomonadota
class: Deltaproteobacteria
order: Desulfuromonadales
family: Geobacteraceae
genus: Geomonas
species: Geomonas edaphica
full scientific name: Geomonas edaphica Xu et al. 2020
strain designation: Red53
type strain: yes
Morphology
cell morphology
| @ref | gram stain | confidence |
|---|---|---|
| 125438 | negative | 96.394 |
| 125439 | negative | 92.6 |
Physiology and metabolism
oxygen tolerance
- @ref: 125439
- oxygen tolerance: anaerobe
- confidence: 97.6
spore formation
- @ref: 125439
- spore formation: no
- confidence: 98.3
Sequence information
16S sequences
- @ref: 20215
- description: Geomonas edaphica strain Red53 16S ribosomal RNA gene, partial sequence
- accession: MH915554
- length: 1424
- database: nuccore
- NCBI tax ID: 2570226
Genome sequences
- @ref: 66792
- description: Geomonas edaphica Red53
- accession: GCA_004917075
- assembly level: contig
- database: ncbi
- NCBI tax ID: 2570226
Genome-based predictions
predictions
| @ref | model | trait | description | prediction | confidence | training_data |
|---|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positive | Positive reaction to Gram-staining | no | 96.394 | no |
| 125438 | anaerobic | anaerobic | Ability to grow under anoxygenic conditions (including facultative anaerobes) | yes | 68.836 | no |
| 125438 | aerobic | aerobic | Ability to grow under oxygenic conditions (including facultative aerobes) | no | 76.022 | no |
| 125438 | spore-forming | spore-forming | Ability to form endo- or exospores | no | 79.663 | no |
| 125438 | thermophile | thermophilic | Ability to grow at temperatures above or equal to 45°C | no | 92.181 | no |
| 125438 | motile2+ | flagellated | Ability to perform flagellated movement | yes | 71.724 | no |
| 125439 | BacteriaNet | spore_formation | Ability to form endo- or exospores | no | 98.3 | |
| 125439 | BacteriaNet | motility | Ability to perform movement | yes | 60.6 | |
| 125439 | BacteriaNet | gram_stain | Reaction to gram-staining | negative | 92.6 | |
| 125439 | BacteriaNet | oxygen_tolerance | Oxygenic conditions needed for growth | anaerobe | 97.6 |
External links
@ref: 20215
culture collection no.: NBRC 114064, MCCC 1K04027
literature
- topic: Phylogeny
- Pubmed-ID: 31608033
- title: Geomonas oryzae gen. nov., sp. nov., Geomonas edaphica sp. nov., Geomonas ferrireducens sp. nov., Geomonas terrae sp. nov., Four Ferric-Reducing Bacteria Isolated From Paddy Soil, and Reclassification of Three Species of the Genus Geobacter as Members of the Genus Geomonas gen. nov.
- authors: Xu Z, Masuda Y, Itoh H, Ushijima N, Shiratori Y, Senoo K
- journal: Front Microbiol
- DOI: 10.3389/fmicb.2019.02201
- year: 2019
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 |