Strain identifier

BacDive ID: 7975

Type strain: No

Species: Micromonospora purpureochromogenes

Strain history: VKM Ac-1326 <-- INA 166.

NCBI tax ID(s): 47872 (species)

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General

@ref: 11287

BacDive-ID: 7975

DSM-Number: 43814

keywords: genome sequence, 16S sequence, Bacteria, spore-forming, mesophilic

description: Micromonospora purpureochromogenes DSM 43814 is a spore-forming, mesophilic bacterium that was isolated from soil.

NCBI tax id

  • NCBI tax id: 47872
  • Matching level: species

strain history

@refhistory
11287<- NRRL <- ATCC <- G.F. Gauze, INA
67770KCC A-0233 <-- BKM A-614 <-- LIA 0744 <-- INA 472.
67770VKM Ac-1326 <-- INA 166.

doi: 10.13145/bacdive7975.20250331.9.3

Name and taxonomic classification

LPSN

  • @ref: 20215
  • description: domain/bacteria
  • keyword: phylum/actinomycetota
  • domain: Bacteria
  • phylum: Actinomycetota
  • class: Actinomycetes
  • order: Micromonosporales
  • family: Micromonosporaceae
  • genus: Micromonospora
  • species: Micromonospora purpureochromogenes
  • full scientific name: Micromonospora purpureochromogenes corrig. (Waksman and Curtis 1916) Luedemann 1971 (Approved Lists 1980)
  • synonyms

    @refsynonym
    20215Actinomyces purpeochromogenus
    20215Micromonospora brunnea

@ref: 11287

domain: Bacteria

phylum: Actinobacteria

class: Actinobacteria

order: Actinomycetales

family: Micromonosporaceae

genus: Micromonospora

species: Micromonospora purpureochromogenes

full scientific name: Micromonospora purpureochromogenes (Waksman and Curtis 1916) Luedemann 1971 emend. Carro et al. 2018

type strain: no

Morphology

cell morphology

@refgram stainconfidencemotility
125439positive99.2
12543890.5no

multimedia

  • @ref: 11287
  • multimedia content: https://www.dsmz.de/microorganisms/photos/DSM_43814.jpg
  • caption: Medium 554 28°C
  • intellectual property rights: © Leibniz-Institut DSMZ

Culture and growth conditions

culture medium

@refnamegrowthlinkcomposition
11287N-Z-AMINE-MEDIUM (DSMZ Medium 554)yeshttps://mediadive.dsmz.de/medium/554Name: N-Z-AMINE-MEDIUM (DSMZ Medium 554) Composition: Starch 20.0 g/l Agar 20.0 g/l Glucose 10.0 g/l N-Z amine 5.0 g/l Yeast extract 5.0 g/l CaCO3 1.0 g/l Distilled water
11287GYM STREPTOMYCES MEDIUM (DSMZ Medium 65)yeshttps://mediadive.dsmz.de/medium/65Name: GYM STREPTOMYCES MEDIUM (DSMZ Medium 65) Composition: Agar 18.0 g/l Malt extract 10.0 g/l Yeast extract 4.0 g/l Glucose 4.0 g/l CaCO3 2.0 g/l Distilled water

culture temp

@refgrowthtypetemperature
11287positivegrowth28
67770positivegrowth28

Physiology and metabolism

oxygen tolerance

  • @ref: 125439
  • oxygen tolerance: obligate aerobe
  • confidence: 99.7

spore formation

  • @ref: 125438
  • spore formation: yes
  • confidence: 92.322

Isolation, sampling and environmental information

isolation

@refsample type
11287soil
67770Soil

isolation source categories

  • Cat1: #Environmental
  • Cat2: #Terrestrial
  • Cat3: #Soil

Safety information

risk assessment

  • @ref: 11287
  • biosafety level: 1
  • biosafety level comment: Risk group (German classification)

Sequence information

16S sequences

@refdescriptionaccessionlengthdatabaseNCBI tax ID
20218Micromonospora purpureochromogenes ATCC 27334 16S-23S ribosomal RNA intergenic spacerAY371891355nuccore47872
11287M.brunnea 16S rRNA geneX926051475nuccore47872

Genome sequences

@refdescriptionaccessionassembly leveldatabaseNCBI tax ID
66792Micromonospora purpureochromogenes strain DSM 4381447872.6wgspatric47872
66792Micromonospora brunnea DSM 438142857413125draftimg47872
67770Micromonospora purpureochromogenes DSM 43814GCA_013410185contigncbi47872

Genome-based predictions

predictions

@refmodeltraitdescriptionpredictionconfidencetraining_data
125438gram-positivegram-positivePositive reaction to Gram-stainingyes89.192no
125438anaerobicanaerobicAbility to grow under anoxygenic conditions (including facultative anaerobes)no94.874no
125438spore-formingspore-formingAbility to form endo- or exosporesyes92.322no
125438aerobicaerobicAbility to grow under oxygenic conditions (including facultative aerobes)yes85.98no
125438thermophilethermophilicAbility to grow at temperatures above or equal to 45°Cno94.5yes
125438motile2+flagellatedAbility to perform flagellated movementno90.5no
125439BacteriaNetspore_formationAbility to form endo- or exosporesyes54.8
125439BacteriaNetmotilityAbility to perform movementno78.6
125439BacteriaNetgram_stainReaction to gram-stainingpositive99.2
125439BacteriaNetoxygen_toleranceOxygenic conditions needed for growthobligate aerobe99.7

External links

@ref: 11287

culture collection no.: DSM 43814, ATCC 27334, CBS 130.76, IFO 14069, IMET 8304, INA 166, JCM 3233, NBRC 14069, NRRL B-16079, VKM Ac-614, JCM 10141, CECT 3290, NCIMB 12732, VKM Ac-1326, BCRC 12627, IMSNU 20080, INA 472

straininfo link

  • @ref: 77409
  • straininfo: 38749

Reference

@idauthorscataloguedoi/urltitlejournalpubmed
11287Curators of the DSMZLeibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH (DSM 43814)https://www.dsmz.de/collection/catalogue/details/culture/DSM-43814
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
20218Verslyppe, B., De Smet, W., De Baets, B., De Vos, P., Dawyndt P.10.1016/j.syapm.2013.11.002StrainInfo introduces electronic passports for microorganisms.Syst Appl Microbiol. 37: 42-50 201424321274
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)
67770Curators of the JCMhttps://jcm.brc.riken.jp/en/
77409Reimer, L.C., Lissin, A.,Schober, I., Witte,J.F., Podstawka, A., Lüken, H., Bunk, B.,Overmann, J.10.60712/SI-ID38749.1StrainInfo: 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