Microbacterium sp. (DSM 103506, H83)

Name: Microbacterium sp. (DSM 103506, H83)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 157951

Type strain

Strain Designation H83

Culture col. no. DSM 103506 H83

NCBI tax ID(s) 51671

Special Collections DSMZ

History DSMZ <- D. Lymperopoulou, University of California, Berkeley, USA; H83

Links

H83 is a bacterium that was isolated from Indoor air, residential bathroom.

genome sequence Bacteria

Name and taxonomic classification

SI-ID 402041

DSM 103506

@ref 20215

Last LPSN update 2026-05-29 08:43:51

Domain Bacteria

Phylum Actinomycetota

Class Actinomycetes

Order Micrococcales

Family Microbacteriaceae

Genus Microbacterium

Full scientific name Microbacterium Orla-Jensen 1919 (Approved Lists 1980)

Synonyms (2)

Aureobacterium
Paramicrobacterium

Morphology

Cell morphology

@ref	Gram stain	Confidence
125439	positive	97.417

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
64523	TRYPTICASE SOY YEAST EXTRACT MEDIUM (DSMZ Medium 92)		Medium recipe at MediaDive	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	Growth	Type	Temperature (°C)
64523	positive	growth	28

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	obligate aerobe	96.882

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Engineered	#Built environment	#House
#Engineered	#Built environment	#Indoor
#Environmental	#Air	#Indoor Air

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
64523	Indoor air, residential bathroom	CA, Piedmont	USA	USA	North America

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM165040v1 assembly for Microbacterium sp. H83	contig	GCA_001650405	1827324.3	2675903239	1827324	66.22

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: ASM165040v1 assembly for Microbacterium sp. H83
BV-BRC: 1827324.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	96.88	no
125439	motility	BacteriaNetⓘ	no	83.88	no
125439	gram_stain	BacteriaNetⓘ	positive	97.42	no
125439	spore_formation	BacteriaNetⓘ	no	77.32	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Microbacterium sp. H83
PATRIC: 1827324.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	89.03	no
125438	anaerobic	anaerobicⓘ	no	96.15	no
125438	spore-forming	spore-formingⓘ	no	77.51	no
125438	aerobic	aerobicⓘ	yes	84.88	no
125438	thermophilic	thermophileⓘ	no	94.90	no
125438	flagellated	motile2+ⓘ	no	74.50	no

Literature

References

#20215	Parte, 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 DSMZ. IJSEM ( DOI 10.1099/ijsem.0.004332 )
#64523	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 103506
#66792	Julia Koblitz, Joaquim Sardà, Lorenz Christian Reimer, Boyke Bunk, Jörg Overmann: Automatically annotated for the DiASPora project (Digital Approaches for the Synthesis of Poorly Accessible Biodiversity Information) .
#125438	Julia Koblitz, Lorenz Christian Reimer, Rüdiger Pukall, Jörg Overmann: Predicting bacterial phenotypic traits through improved machine learning using high-quality, curated datasets. 2024 ( DOI 10.1101/2024.08.12.607695 )
#125439	Philipp Münch, René Mreches, Martin Binder, Hüseyin Anil Gündüz, Xiao-Yin To, Alice McHardy: deepG: Deep Learning for Genome Sequence Data. R package version 0.3.1 .
#126262	A. Lissin, I. Schober, J. F. Witte, H. Lüken, A. Podstawka, J. Koblitz, B. Bunk, P. Dawyndt, P. Vandamme, P. de Vos, J. Overmann, L. C. Reimer: StrainInfo—the central database for linked microbial strain identifiers. ( DOI 10.1093/database/baaf059 )

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