Strain identifier

BacDive ID: 163051

Type strain: No

Species: Agrobacterium sp.

Strain history: IAM 13943 <-- LMG 27 <-- A. C. Hayward 0363 <-- A. Kerr E27/2.

NCBI tax ID(s): 361 (species)

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

@ref: 67770

BacDive-ID: 163051

keywords: genome sequence, Bacteria, mesophilic, Gram-negative

description: Agrobacterium sp. JCM 20994 is a mesophilic, Gram-negative bacterium that was isolated from Soil.

NCBI tax id

  • NCBI tax id: 361
  • Matching level: species

strain history

  • @ref: 67770
  • history: IAM 13943 <-- LMG 27 <-- A. C. Hayward 0363 <-- A. Kerr E27/2.

doi: 10.13145/bacdive163051.20250331.9.3

Name and taxonomic classification

LPSN

  • @ref: 20215
  • description: domain/bacteria
  • keyword: phylum/pseudomonadota
  • domain: Bacteria
  • phylum: Pseudomonadota
  • class: Alphaproteobacteria
  • order: Hyphomicrobiales
  • family: Rhizobiaceae
  • genus: Agrobacterium
  • species: Agrobacterium sp.
  • full scientific name: Agrobacterium Conn 1942 (Approved Lists 1980)

@ref: 67770

domain: Bacteria

phylum: Proteobacteria

class: Alphaproteobacteria

order: Hyphomicrobiales

family: Rhizobiaceae

genus: Agrobacterium

species: Agrobacterium sp.

full scientific name: Agrobacterium sp.

type strain: no

Morphology

cell morphology

@refgram stainconfidence
125438negative98.5
125439negative99.6

Culture and growth conditions

culture temp

  • @ref: 67770
  • growth: positive
  • type: growth
  • temperature: 25

Physiology and metabolism

oxygen tolerance

  • @ref: 125439
  • oxygen tolerance: obligate aerobe
  • confidence: 97.8

spore formation

@refspore formationconfidence
125439no99.1
125438no95.432

Isolation, sampling and environmental information

isolation

  • @ref: 67770
  • sample type: Soil
  • geographic location: South Australia
  • country: Australia
  • origin.country: AUS
  • continent: Australia and Oceania

Sequence information

Genome sequences

@refdescriptionaccessionassembly leveldatabaseNCBI tax ID
66792Agrobacterium tumefaciens CFBP5506GCA_005144495completencbi358
66792Agrobacterium tumefaciens strain CFBP5506358.246wgspatric358

GC content

  • @ref: 67770
  • GC-content: 60.3
  • method: thermal denaturation, midpoint method (Tm)

Genome-based predictions

predictions

@refmodeltraitdescriptionpredictionconfidencetraining_data
125438gram-positivegram-positivePositive reaction to Gram-stainingno98.5no
125438anaerobicanaerobicAbility to grow under anoxygenic conditions (including facultative anaerobes)no96.209no
125438spore-formingspore-formingAbility to form endo- or exosporesno95.432no
125438aerobicaerobicAbility to grow under oxygenic conditions (including facultative aerobes)yes86.685no
125438thermophilethermophilicAbility to grow at temperatures above or equal to 45°Cno100yes
125438motile2+flagellatedAbility to perform flagellated movementyes69.853no
125439BacteriaNetspore_formationAbility to form endo- or exosporesno99.1
125439BacteriaNetmotilityAbility to perform movementyes69.5
125439BacteriaNetgram_stainReaction to gram-stainingnegative99.6
125439BacteriaNetoxygen_toleranceOxygenic conditions needed for growthobligate aerobe97.8

External links

@ref: 67770

culture collection no.: JCM 20994, CFBP 5506, IAM 13943, LMG 27

straininfo link

  • @ref: 113819
  • straininfo: 460

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
67770Curators of the JCMhttps://jcm.brc.riken.jp/en/
113819Reimer, 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 identifiers10.60712/SI-ID460.1
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