Strain identifier

BacDive ID: 167684

Type strain: Yes

Species: Geomonas terrae

Strain Designation: Red111

NCBI tax ID(s): 2562681 (species)

For citation purpose refer to the digital object identifier (doi) of the current version.
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General

@ref: 20215

BacDive-ID: 167684

keywords: genome sequence, 16S sequence, Bacteria, Gram-negative

description: Geomonas terrae Red111 is a Gram-negative bacterium of the family Geobacteraceae.

NCBI tax id

  • NCBI tax id: 2562681
  • Matching level: species

doi: 10.13145/bacdive167684.20250331.9.3

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 terrae
  • full scientific name: Geomonas terrae Xu et al. 2020

@ref: 20215

domain: Bacteria

phylum: Pseudomonadota

class: Deltaproteobacteria

order: Desulfuromonadales

family: Geobacteraceae

genus: Geomonas

species: Geomonas terrae

full scientific name: Geomonas terrae Xu et al. 2020

strain designation: Red111

type strain: yes

Morphology

cell morphology

@refgram stainconfidence
125438negative96.327
125439negative98.5

Physiology and metabolism

oxygen tolerance

  • @ref: 125439
  • oxygen tolerance: anaerobe
  • confidence: 98.7

spore formation

  • @ref: 125439
  • spore formation: no
  • confidence: 98.7

Sequence information

16S sequences

  • @ref: 20215
  • description: Geomonas terrae strain Red111 16S ribosomal RNA gene, partial sequence
  • accession: MH915556
  • length: 1426
  • database: nuccore
  • NCBI tax ID: 2562681

Genome sequences

  • @ref: 66792
  • description: Geomonas terrae Red111
  • accession: GCA_004791675
  • assembly level: scaffold
  • database: ncbi
  • NCBI tax ID: 2562681

Genome-based predictions

predictions

@refmodeltraitdescriptionpredictionconfidencetraining_data
125438gram-positivegram-positivePositive reaction to Gram-stainingno96.327no
125438anaerobicanaerobicAbility to grow under anoxygenic conditions (including facultative anaerobes)yes70.089no
125438aerobicaerobicAbility to grow under oxygenic conditions (including facultative aerobes)no76.495no
125438spore-formingspore-formingAbility to form endo- or exosporesno79.363no
125438thermophilethermophilicAbility to grow at temperatures above or equal to 45°Cno91.695no
125438motile2+flagellatedAbility to perform flagellated movementyes70.635no
125439BacteriaNetspore_formationAbility to form endo- or exosporesno98.7
125439BacteriaNetmotilityAbility to perform movementyes56.1
125439BacteriaNetgram_stainReaction to gram-stainingnegative98.5
125439BacteriaNetoxygen_toleranceOxygenic conditions needed for growthanaerobe98.7

External links

@ref: 20215

culture collection no.: NBRC 114026, MCCC 1K04029

literature

topicPubmed-IDtitleauthorsjournalDOIyear
Phylogeny31608033Geomonas 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.Xu Z, Masuda Y, Itoh H, Ushijima N, Shiratori Y, Senoo KFront Microbiol10.3389/fmicb.2019.022012019
Phylogeny35197944Genome Analysis and Description of Three Novel Diazotrophs Geomonas Species Isolated From Paddy Soils.Liu GH, Yang S, Tang R, Xie CJ, Zhou SGFront Microbiol10.3389/fmicb.2021.8014622022

Reference

@idauthorstitledoi/url
20215Parte, 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 DSMZ10.1099/ijsem.0.004332
66792Julia Koblitz, Joaquim Sardà, Lorenz Christian Reimer, Boyke Bunk, Jörg OvermannAutomatically annotated for the DiASPora project (Digital Approaches for the Synthesis of Poorly Accessible Biodiversity Information)https://diaspora-project.de/progress.html#genomes
125438Julia Koblitz, Lorenz Christian Reimer, Rüdiger Pukall, Jörg OvermannPredicting bacterial phenotypic traits through improved machine learning using high-quality, curated datasets10.1101/2024.08.12.607695
125439Philipp Münch, René Mreches, Martin Binder, Hüseyin Anil Gündüz, Xiao-Yin To, Alice McHardydeepG: Deep Learning for Genome Sequence Data. R package version 0.3.1https://github.com/GenomeNet/deepG