Strain identifier

BacDive ID: 13163

Type strain: Yes

Species: Pseudomonas duriflava

Strain Designation: HR2

Strain history: <- H. Liu, Nanjing Agricultural University

NCBI tax ID(s): 459528 (species)

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

@ref: 15695

BacDive-ID: 13163

DSM-Number: 21419

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

description: Pseudomonas duriflava HR2 is an aerobe, mesophilic, Gram-negative bacterium that was isolated from desert soil.

NCBI tax id

  • NCBI tax id: 459528
  • Matching level: species

strain history

  • @ref: 15695
  • history: <- H. Liu, Nanjing Agricultural University

doi: 10.13145/bacdive13163.20250331.9.3

Name and taxonomic classification

LPSN

  • @ref: 20215
  • description: domain/bacteria
  • keyword: phylum/pseudomonadota
  • domain: Bacteria
  • phylum: Pseudomonadota
  • class: Gammaproteobacteria
  • order: Pseudomonadales
  • family: Pseudomonadaceae
  • genus: Pseudomonas
  • species: Pseudomonas duriflava
  • full scientific name: Pseudomonas duriflava Liu et al. 2008
  • synonyms

    • @ref: 20215
    • synonym: Chryseomonas duriflava

@ref: 15695

domain: Bacteria

phylum: Proteobacteria

class: Gammaproteobacteria

order: Pseudomonadales

family: Pseudomonadaceae

genus: Pseudomonas

species: Pseudomonas duriflava

full scientific name: Pseudomonas duriflava Liu et al. 2008

strain designation: HR2

type strain: yes

Morphology

cell morphology

@refgram staincell lengthcell widthcell shapemotilityconfidence
32574negative0.9 µm0.7 µmrod-shapedno
125438negative98.75
125439negative99.5

pigmentation

  • @ref: 32574
  • production: no

Culture and growth conditions

culture medium

  • @ref: 15695
  • name: TRYPTICASE SOY BROTH AGAR (DSMZ Medium 535)
  • growth: yes
  • link: https://mediadive.dsmz.de/medium/535
  • composition: Name: TRYPTICASE SOY BROTH AGAR (DSMZ Medium 535) Composition: Trypticase soy broth 30.0 g/l Agar 15.0 g/l Distilled water

culture temp

@refgrowthtypetemperature
15695positivegrowth28
32574positivegrowth05-42
32574positiveoptimum33.5

culture pH

@refabilitytypepHPH range
32574positivegrowth05-09alkaliphile
32574positiveoptimum7.5

Physiology and metabolism

oxygen tolerance

@refoxygen toleranceconfidence
32574aerobe
125438aerobe91.184

spore formation

@refspore formationconfidence
32574no
125439no99.6

halophily

@refsaltgrowthtested relationconcentration
32574NaClpositivegrowth0-2 %
32574NaClpositiveoptimum0.5 %

metabolite utilization

@refChebi-IDmetaboliteutilization activitykind of utilization tested
3257422599arabinose+carbon source
3257417057cellobiose+carbon source
3257428260galactose+carbon source
3257428053melibiose+carbon source
3257433942ribose+carbon source
325744853esculin+hydrolysis

enzymes

  • @ref: 32574
  • value: catalase
  • activity: +
  • ec: 1.11.1.6

Isolation, sampling and environmental information

isolation

  • @ref: 15695
  • sample type: desert soil
  • geographic location: Xinjiang Province
  • country: China
  • origin.country: CHN
  • continent: Asia

isolation source categories

Cat1Cat2Cat3
#Environmental#Terrestrial#Desert
#Environmental#Terrestrial#Soil
#Condition#Xerophilic

Safety information

risk assessment

  • @ref: 15695
  • biosafety level: 1
  • biosafety level comment: Risk group (German classification)

Sequence information

16S sequences

  • @ref: 15695
  • description: Pseudomonas duriflava strain HR2 16S ribosomal RNA gene, partial sequence
  • accession: EU046271
  • length: 1404
  • database: nuccore
  • NCBI tax ID: 459528

Genome sequences

@refdescriptionaccessionassembly leveldatabaseNCBI tax ID
66792Pseudomonas duriflava CGMCC 1.6858GCA_007830155contigncbi459528
66792Pseudomonas duriflava strain CGMCC 1.6858459528.3wgspatric459528
66792Pseudomonas duriflava CGMCC 1.68582596583584draftimg459528

GC content

  • @ref: 32574
  • GC-content: 55.2

Genome-based predictions

predictions

@refmodeltraitdescriptionpredictionconfidencetraining_data
125438gram-positivegram-positivePositive reaction to Gram-stainingno98.75yes
125438anaerobicanaerobicAbility to grow under anoxygenic conditions (including facultative anaerobes)no97.59yes
125438spore-formingspore-formingAbility to form endo- or exosporesno83.889no
125438aerobicaerobicAbility to grow under oxygenic conditions (including facultative aerobes)yes91.184no
125438thermophilethermophilicAbility to grow at temperatures above or equal to 45°Cno98.497yes
125438motile2+flagellatedAbility to perform flagellated movementyes85.916no
125439BacteriaNetspore_formationAbility to form endo- or exosporesno99.6
125439BacteriaNetmotilityAbility to perform movementyes88.7
125439BacteriaNetgram_stainReaction to gram-stainingnegative99.5
125439BacteriaNetoxygen_toleranceOxygenic conditions needed for growthobligate aerobe86.8

External links

@ref: 15695

culture collection no.: DSM 21419, CGMCC 1.6858, KCTC 22129

straininfo link

  • @ref: 82371
  • straininfo: 408087

Reference

@idauthorscataloguedoi/urltitleID_cross_referencepubmed
15695Curators of the DSMZLeibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH (DSM 21419)https://www.dsmz.de/collection/catalogue/details/culture/DSM-21419
20215Parte, A.C., Sardà Carbasse, J., Meier-Kolthoff, J.P., Reimer, L.C. and Göker, M.10.1099/ijsem.0.004332List of Prokaryotic names with Standing in Nomenclature (LPSN) moves to the DSMZ
32574Barberan A, Caceres Velazquez H, Jones S, Fierer N.10.1128/mSphere.00237-17Hiding in Plain Sight: Mining Bacterial Species Records for Phenotypic Trait Information2878928776041
66792Julia Koblitz, Joaquim Sardà, Lorenz Christian Reimer, Boyke Bunk, Jörg Overmannhttps://diaspora-project.de/progress.html#genomesAutomatically annotated for the DiASPora project (Digital Approaches for the Synthesis of Poorly Accessible Biodiversity Information)
82371Reimer, L.C., Lissin, A.,Schober, I., Witte,J.F., Podstawka, A., Lüken, H., Bunk, B.,Overmann, J.10.60712/SI-ID408087.1StrainInfo: A central database for resolving microbial strain identifiers
125438Julia Koblitz, Lorenz Christian Reimer, Rüdiger Pukall, Jörg Overmann10.1101/2024.08.12.607695Predicting bacterial phenotypic traits through improved machine learning using high-quality, curated datasets
125439Philipp Münch, René Mreches, Martin Binder, Hüseyin Anil Gündüz, Xiao-Yin To, Alice McHardyhttps://github.com/GenomeNet/deepGdeepG: Deep Learning for Genome Sequence Data. R package version 0.3.1