Name: Microbacterium nanhaiense OAcT-400
Creator: BacDive
License: https://creativecommons.org/licenses/by/4.0/

Strain identifier

BacDive ID: 131477

Type strain:

Species: Microbacterium nanhaiense

Strain Designation: OAcT-400

Culture col. no.: DSM 26811, CGMCC 4.7181, KCTC 29185

Strain history: <- Jing Li

NCBI tax ID(s): 1301026 (species)

SI-ID 407069

DSM 26811

Special Collections

DSMZ
KCTC

Section

When using BacDive for research please cite our paper

Microbacterium nanhaiense OAcT-400 is an aerobe, mesophilic bacterium that was isolated from sea sediment.

aerobe
mesophilic
16S sequence
Bacteria
genome sequence

Information on the name and the taxonomic classification. Name and taxonomic classification

	Last LPSN update	09-12-2024 (DD-MM-YYYY)
	Domain	*Bacteria*
	Phylum	*Actinomycetota*
	Class	*Actinomycetes*
	Order	*Micrococcales*
	Family	*Microbacteriaceae*
	Genus	*Microbacterium*
	Species	**Microbacterium nanhaiense**
	Full Scientific Name (LPSN)	Microbacterium nanhaiense Yan et al. 2015

Information on morphological and physiological properties Morphology

[Ref.: #125439]	Gram stain	positive Confidence in %97.5

[Ref.: #125438]	Motility	no Confidence in %90

Information on culture and growth conditions Culture and growth conditions

[Ref.: #22704]

Culture medium

R2A MEDIUM (DSMZ Medium 830)

[Ref.: #22704]

Culture medium growth

[Ref.: #22704]

Culture medium link

Medium recipe at MediaDive

[Ref.: #22704]

Culture medium composition

expand / minimize

[Ref.: #22704]

Culture medium

OXOID NUTRIENT BROTH (DSMZ Medium 948)

[Ref.: #22704]

Culture medium growth

[Ref.: #22704]

Culture medium link

Medium recipe at MediaDive

[Ref.: #22704]

Culture medium composition

expand / minimize

	Temperatures	Kind of temperature		Temperature
[Ref.: #22704]			growth	28 °C
[Ref.: #67771]			growth	28 °C

Information on physiology and metabolism Physiology and metabolism

[Ref.: #67771]	Oxygen tolerance	aerobe
[Ref.: #125439]	Oxygen tolerance	aerobe Confidence in %91.7

Information on isolation source, the sampling and environmental conditions Isolation, sampling and environmental information

[Ref.: #22704]	Sample type/isolated from	sea sediment
[Ref.: #22704]	Geographic location (country and/or sea, region)	South China Sea, site N42-5 at a depth of 2093 m
[Ref.: #22704]	Country	China
[Ref.: #22704]	Country ISO 3 Code	CHN
[Ref.: #22704]	Continent	Asia

[Ref.: #67771]	Sample type/isolated from	From sediment in South China sea(depth 2093m)
[Ref.: #67771]	Country	China
[Ref.: #67771]	Country ISO 3 Code	CHN
[Ref.: #67771]	Continent	Asia
* marker position based on {}

Isolation sources categories

#Environmental	#Aquatic	#Marine
#Environmental	#Aquatic	#Sediment

What are isolation sources categories?

[Ref.: #69479]

Global distribution of 16S sequence KC505174 (>99% sequence identity) for Microbacterium from Microbeatlas

Aquatic Samples	62
Soil Samples	83
Animal Samples	474
Plant Samples	36
Total Samples	655

Information on possible application of the strain and its possible interaction with e.g. potential hosts Safety information

[Ref.: #22704]

Biosafety level

Risk group (German classification)
According to TRBA 466

Information on genomic background e.g. entries in nucleic sequence databass Sequence information

16S Sequence information:

	Sequence accession description	Seq. accession number	Sequence length (bp)	Sequence database	Associated NCBI tax ID
[Ref.: #22704]	Microbacterium nanhaiense strain OAct400 16S ribosomal RNA gene, partial sequence	KC505174	1446	GenBank ENA	1301026 tax ID

Genome sequence information:

	Sequence accession description	Seq. accession number	Assembly level	Sequence database	Associated NCBI tax ID
[Ref.: #66792]	Microbacterium nanhaiense CGMCC 4.7181	GCA_014646015	contig	GenBank ENA	1301026 tax ID	*
[Ref.: #66792]	Microbacterium nanhaiense strain CGMCC 4.7181	1301026.3	wgs	PATRIC	1301026 tax ID	*

[Ref.: #22704]

GC-content

73.8 mol%

thermal denaturation, midpoint method (Tm)

Data predicted using genome information as a basis Genome-based predictions

	Model	Trait	Prediction	Confidence in %	In training data
	Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Microbacterium nanhaiense strain CGMCC 4.7181 PATRIC: 1301026.3
[Ref.: #125438]	gram-positive	gram-positiveⓘ	yes	88.368	no
[Ref.: #125438]	anaerobic	anaerobicⓘ	no	96.957	no
[Ref.: #125438]	spore-forming	spore-formingⓘ	no	74.812	no
[Ref.: #125438]	aerobic	aerobicⓘ	yes	81.492	yes
[Ref.: #125438]	thermophile	thermophilicⓘ	no	93.967	yes
[Ref.: #125438]	motile2+	flagellatedⓘ	no	90	no

	Model	Trait	Prediction	Confidence in %
	Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Microbacterium nanhaiense CGMCC 4.7181 NCBI: GCA_014646015
[Ref.: #125439]	BacteriaNet	spore_formationⓘ	no	63.4
[Ref.: #125439]	BacteriaNet	motilityⓘ	no	67.3
[Ref.: #125439]	BacteriaNet	gram_stainⓘ	positive	97.5
[Ref.: #125439]	BacteriaNet	oxygen_toleranceⓘ	aerobe	91.7

Availability in culture collections External links

[Ref.: #22704]

Culture collection no.

DSM 26811, CGMCC 4.7181, KCTC 29185

[Ref.: #89894]

SI-ID 407069

Literature:

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Microbacterium nanhaiense sp. nov., an actinobacterium isolated from sea sediment.	Yan L, Wang J, Chen Z, Guan Y, Li J	Int J Syst Evol Microbiol	10.1099/ijsem.0.000480	2015	*

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 )

#22704

Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 26811

#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) .

#67771 Korean Collection for Type Cultures (KCTC) ; Curators of the KCTC;

#69479

João F Matias Rodrigues, Janko Tackmann,Gregor Rot, Thomas SB Schmidt, Lukas Malfertheiner, Mihai Danaila,Marija Dmitrijeva, Daniela Gaio, Nicolas Näpflin and Christian von Mering. University of Zurich.: MicrobeAtlas 1.0 beta .

#89894

Reimer, 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 identifiers . ( DOI 10.60712/SI-ID407069.1 )

#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 .

* These data were automatically processed and therefore are not curated

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Microbacterium nanhaiense strain CGMCC 4.7181

Microbacterium nanhaiense CGMCC 4.7181

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