Strain identifier

BacDive ID: 163286

Type strain: No

Species: Hafnia alvei

Strain history: R. Sakazaki 287 <-- ATCC 9760 <-- Parke, Davis & Co.; 04414 <-- NCTC 6578 <-- E. F. Gale strain Cadaveris.

NCBI tax ID(s): 569 (species)

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

@ref: 67770

BacDive-ID: 163286

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

description: Hafnia alvei JCM 24184 is a mesophilic, Gram-negative bacterium of the family Hafniaceae.

NCBI tax id

  • NCBI tax id: 569
  • Matching level: species

strain history

  • @ref: 67770
  • history: R. Sakazaki 287 <-- ATCC 9760 <-- Parke, Davis & Co.; 04414 <-- NCTC 6578 <-- E. F. Gale strain Cadaveris.

doi: 10.13145/bacdive163286.20250331.9.3

Name and taxonomic classification

LPSN

  • @ref: 20215
  • description: domain/bacteria
  • keyword: phylum/pseudomonadota
  • domain: Bacteria
  • phylum: Pseudomonadota
  • class: Gammaproteobacteria
  • order: Enterobacterales
  • family: Hafniaceae
  • genus: Hafnia
  • species: Hafnia alvei
  • full scientific name: Hafnia alvei Møller 1954 (Approved Lists 1980)

@ref: 67770

domain: Bacteria

phylum: Proteobacteria

class: Gammaproteobacteria

order: Enterobacterales

family: Hafniaceae

genus: Hafnia

species: Hafnia alvei

full scientific name: Hafnia alvei M›ller 1954

type strain: no

Morphology

cell morphology

  • @ref: 125438
  • gram stain: negative
  • confidence: 99.985

Culture and growth conditions

culture temp

  • @ref: 67770
  • growth: positive
  • type: growth
  • temperature: 37

Physiology and metabolism

spore formation

@refspore formationconfidence
125439no97
125438no90.135

enzymes

  • @ref: 67770
  • value: lysine decarboxylase
  • ec: 4.1.1.18

Sequence information

16S sequences

  • @ref: 67770
  • description: Hafnia alvei gene for 16S rRNA, partial sequence, strain: JCM 24184
  • accession: AB435601
  • length: 512
  • database: nuccore
  • NCBI tax ID: 569

Genome sequences

@refdescriptionaccessionassembly leveldatabaseNCBI tax ID
66792Hafnia alvei strain NCTC6578569.80wgspatric569
66792Hafnia alvei NCTC 65782835273707draftimg569
67770Hafnia alvei NCTC6578GCA_900451125contigncbi569

Genome-based predictions

predictions

@refmodeltraitdescriptionpredictionconfidencetraining_data
125438gram-positivegram-positivePositive reaction to Gram-stainingno99.985no
125438anaerobicanaerobicAbility to grow under anoxygenic conditions (including facultative anaerobes)no95.874no
125438spore-formingspore-formingAbility to form endo- or exosporesno90.135no
125438aerobicaerobicAbility to grow under oxygenic conditions (including facultative aerobes)no61.765no
125438thermophilethermophilicAbility to grow at temperatures above or equal to 45°Cno99.5no
125438motile2+flagellatedAbility to perform flagellated movementyes74.429no
125439BacteriaNetspore_formationAbility to form endo- or exosporesno97
125439BacteriaNetmotilityAbility to perform movementyes69.7
125439BacteriaNetgram_stainReaction to gram-stainingnegative86.5
125439BacteriaNetoxygen_toleranceOxygenic conditions needed for growthobligate aerobe87.2

External links

@ref: 67770

culture collection no.: JCM 24184, ATCC 9760, NCTC 6578

straininfo link

  • @ref: 114004
  • straininfo: 35124

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/
114004Reimer, 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-ID35124.1
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