Strain identifier

BacDive ID: 23102

Type strain: No

Species: Microbacterium lacus

Strain Designation: SDZ, SDZm4

Strain history: <- W. Tappe, Forschungszentrum Jülich (IGB), Germany; SDZm4 <- W. Tappe and S. Kummer

NCBI tax ID(s): 415217 (species)

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

@ref: 19076

BacDive-ID: 23102

DSM-Number: 26765

keywords: genome sequence, Bacteria, mesophilic

description: Microbacterium lacus SDZ is a mesophilic bacterium that was isolated from typic Hapludalf soil.

NCBI tax id

  • NCBI tax id: 415217
  • Matching level: species

strain history

  • @ref: 19076
  • history: <- W. Tappe, Forschungszentrum Jülich (IGB), Germany; SDZm4 <- W. Tappe and S. Kummer

doi: 10.13145/bacdive23102.20250331.9.3

Name and taxonomic classification

LPSN

  • @ref: 20215
  • description: domain/bacteria
  • keyword: phylum/actinomycetota
  • domain: Bacteria
  • phylum: Actinomycetota
  • class: Actinomycetes
  • order: Micrococcales
  • family: Microbacteriaceae
  • genus: Microbacterium
  • species: Microbacterium lacus
  • full scientific name: Microbacterium lacus Kageyama et al. 2008

@ref: 19076

domain: Bacteria

phylum: Actinobacteria

class: Actinobacteria

order: Actinomycetales

family: Microbacteriaceae

genus: Microbacterium

species: Microbacterium lacus

full scientific name: Microbacterium lacus Kageyama et al. 2008

strain designation: SDZ, SDZm4

type strain: no

Morphology

cell morphology

@refmotilityconfidencegram stain
125438no92.875
12543890.45positive
12543995.1positive

Culture and growth conditions

culture medium

  • @ref: 19076
  • name: TRYPTICASE SOY YEAST EXTRACT MEDIUM (DSMZ Medium 92)
  • growth: yes
  • link: https://mediadive.dsmz.de/medium/92
  • composition: Name: TRYPTICASE SOY YEAST EXTRACT MEDIUM (DSMZ Medium 92) Composition: Trypticase soy broth 30.0 g/l Agar 15.0 g/l Yeast extract 3.0 g/l Distilled water

culture temp

  • @ref: 19076
  • growth: positive
  • type: growth
  • temperature: 28

Physiology and metabolism

oxygen tolerance

  • @ref: 125439
  • oxygen tolerance: obligate aerobe
  • confidence: 97.7

Isolation, sampling and environmental information

isolation

  • @ref: 19076
  • sample type: typic Hapludalf soil
  • country: Germany
  • origin.country: DEU
  • continent: Europe

isolation source categories

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

Safety information

risk assessment

  • @ref: 19076
  • biosafety level: 1
  • biosafety level comment: Risk group (German classification)

Sequence information

Genome sequences

@refdescriptionaccessionassembly leveldatabaseNCBI tax ID
66792Microbacterium lacus SDZm4GCA_002812805contigncbi415217
66792Microbacterium lacus strain SDZm4415217.3wgspatric415217

Genome-based predictions

predictions

@refmodeltraitdescriptionpredictionconfidencetraining_data
125438gram-positivegram-positivePositive reaction to Gram-stainingyes90.45no
125438anaerobicanaerobicAbility to grow under anoxygenic conditions (including facultative anaerobes)no97.916no
125438spore-formingspore-formingAbility to form endo- or exosporesno74.695no
125438aerobicaerobicAbility to grow under oxygenic conditions (including facultative aerobes)yes85.146no
125438thermophilethermophilicAbility to grow at temperatures above or equal to 45°Cno96.429yes
125438motile2+flagellatedAbility to perform flagellated movementno92.875no
125439BacteriaNetspore_formationAbility to form endo- or exosporesno74.9
125439BacteriaNetmotilityAbility to perform movementno75.7
125439BacteriaNetgram_stainReaction to gram-stainingpositive95.1
125439BacteriaNetoxygen_toleranceOxygenic conditions needed for growthobligate aerobe97.7

External links

@ref: 19076

culture collection no.: DSM 26765

straininfo link

  • @ref: 87339
  • straininfo: 397793

literature

topicPubmed-IDtitleauthorsjournalDOIyearmeshtopic2
Metabolism23396336Degradation of sulfadiazine by Microbacterium lacus strain SDZm4, isolated from lysimeters previously manured with slurry from sulfadiazine-medicated pigs.Tappe W, Herbst M, Hofmann D, Koeppchen S, Kummer S, Thiele B, Groeneweg JAppl Environ Microbiol10.1128/AEM.03636-122013Animals, Bacterial Typing Techniques, Carbon Radioisotopes, Manure/microbiology, Molecular Sequence Data, Mycobacterium/genetics/isolation & purification/*metabolism, Pyrimidines, Soil Microbiology, Sulfadiazine/chemistry/*metabolism/therapeutic use, SwineGenetics
Metabolism25715827A novel isolated Terrabacter-like bacterium can mineralize 2-aminopyrimidine, the principal metabolite of microbial sulfadiazine degradation.Tappe W, Hofmann D, Disko U, Koeppchen S, Kummer S, Vereecken HBiodegradation10.1007/s10532-015-9722-92015Biodegradation, Environmental, Carbon Dioxide/metabolism, Carbon Radioisotopes, Gas Chromatography-Mass Spectrometry, *Genes, Bacterial, Humans, Micrococcaceae/*metabolism, Phylogeny, Pyrimidines/*metabolism, RNA, Ribosomal, 16S/*genetics, Soil Pollutants/*metabolism, Sulfadiazine/*metabolismPhylogeny

Reference

@idauthorscataloguedoi/urltitle
19076Curators of the DSMZLeibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH (DSM 26765)https://www.dsmz.de/collection/catalogue/details/culture/DSM-26765
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
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)
87339Reimer, L.C., Lissin, A.,Schober, I., Witte,J.F., Podstawka, A., Lüken, H., Bunk, B.,Overmann, J.10.60712/SI-ID397793.1StrainInfo: 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