Aminobacter niigataensis (DSM 7050, ATCC 49932, JCM 7853)

Name: Aminobacter niigataensis (DSM 7050, ATCC 49932, JCM 7853)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 11860

Type strain

Strain Designation DM-81

Culture col. no. DSM 7050 ATCC 49932 JCM 7853 CCUG 48820 DM-81 2 more

NCBI tax ID(s) 83265

Special Collections DSMZ CCUG JCM

History <- JCM <- T. Urakami, DM-81 T. Urakami DM-81.

Links

Aminobacter niigataensis DM-81 is an aerobe, mesophilic prokaryote that was isolated from soil.

aerobe mesophilic genome sequence 16S sequence

Name and taxonomic classification

SI-ID 42762

ATCC 49932,JCM 7853,DSM 7050,CCM 4330,CCUG 48820,KACC 10905,KACC 11260,IAM 15265

@ref 20215

Last LPSN update 2026-02-09 11:20:41

Domain Bacteria

Phylum Pseudomonadota

Class Alphaproteobacteria

Order Hyphomicrobiales

Family Phyllobacteriaceae

Genus Aminobacter

Species Aminobacter niigataensis

Full scientific name Aminobacter niigataensis Urakami et al. 1992

Morphology

Cell morphology

@ref	Gram stain	Confidence
125438	negative	98.833
125439	negative	97.4

Colony morphology

58342

Incubation period2 days

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
2960	NUTRIENT AGAR (DSMZ Medium 1)		Medium recipe at MediaDive	Name: NUTRIENT AGAR (DSMZ Medium 1) Composition: Agar 15.0 g/l Peptone 5.0 g/l Meat extract 3.0 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
2960	positive	growth	30	mesophilic
58342	positive	growth	30	mesophilic
67770	positive	growth	30	mesophilic

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
58342	aerobe
125439	obligate aerobe	96.2

Spore formation

@ref	Spore formation	Confidence
125439		97.2

Observation

67770

Observationquinones: Q-10

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Environmental	#Terrestrial	#Soil

Isolation

@ref	Sample type
2960	soil
58342	Soil
67770	Soil

Taxonmaps

69479

Global distribution of 16S sequence AJ011761 (>99% sequence identity) for Mesorhizobium from Microbeatlas

Aquatic Samples	308
Soil Samples	780
Animal Samples	145
Plant Samples	31
Total Samples	1264

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
2960	1	Risk group (German classification) According to TRBA 466

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM1420001v1 assembly for Aminobacter niigataensis DSM 7050	contig	GCA_014200015	83265.3	2829772224	83265	74.5
124043	ASM3953481v1 assembly for Aminobacter niigataensis JCM 7853	scaffold	GCA_039534815			83265	65.46

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
20218	Aminobacter niigataensis strain DSM7050T, 16S rRNA gene, partial	AJ011761	1466		83265

GC content

@ref	GC-content (mol%)	Method
67770	63.2	high performance liquid chromatography (HPLC)

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Aminobacter niigataensis DSM 7050
NCBI: GCA_014200015

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	97.20	no
125439	motility	BacteriaNetⓘ	yes	69.40	no
125439	gram_stain	BacteriaNetⓘ	negative	97.40	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	96.20	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Aminobacter niigataensis strain DSM 7050
PATRIC: 83265.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	98.83	no
125438	anaerobic	anaerobicⓘ	no	94.62	yes
125438	aerobic	aerobicⓘ	yes	83.66	yes
125438	spore-forming	spore-formingⓘ	no	85.91	no
125438	thermophilic	thermophileⓘ	no	99.49	yes
125438	flagellated	motile2+ⓘ	yes	54.48	no

Literature

Topic	Title	Authors	Journal	DOI	Year
	Metformin hydrolase is a recently evolved nickel-dependent heteromeric ureohydrolase.	Sinn M, Riede L, Fleming JR, Funck D, Lutz H, Bachmann A, Mayans O, Hartig JS.	Nat Commun	10.1038/s41467-024-51752-5	2024
Metabolism	The complete genome of 2,6-dichlorobenzamide (BAM) degrader Aminobacter sp. MSH1 suggests a polyploid chromosome, phylogenetic reassignment, and functions of plasmids.	Nielsen TK, Horemans B, Lood C, T'Syen J, van Noort V, Lavigne R, Ellegaard-Jensen L, Hylling O, Aamand J, Springael D, Hansen LH.	Sci Rep	10.1038/s41598-021-98184-5	2021
Genetics	Phylogenomic Reconstruction and Metabolic Potential of the Genus Aminobacter.	Artuso I, Turrini P, Pirolo M, Lugli GA, Ventura M, Visca P.	Microorganisms	10.3390/microorganisms9061332	2021
	Pathogenic shifts in endogenous microbiota impede tissue regeneration via distinct activation of TAK1/MKK/p38.	Arnold CP, Merryman MS, Harris-Arnold A, McKinney SA, Seidel CW, Loethen S, Proctor KN, Guo L, Sanchez Alvarado A.	Elife	10.7554/elife.16793	2016

References

#2960	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 7050
#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 )
#20218	Verslyppe, B., De Smet, W., De Baets, B., De Vos, P., Dawyndt P.: StrainInfo introduces electronic passports for microorganisms.. Syst Appl Microbiol. 37: 42 - 50 2014 ( DOI 10.1016/j.syapm.2013.11.002 , PubMed 24321274 )
#58342	Culture Collection University of Gothenburg (CCUG) ; Curators of the CCUG; CCUG 48820
#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) .
#67770	Japan Collection of Microorganism (JCM) ; Curators of the JCM;
#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 .
#124043	Isabel Schober, Julia Koblitz: Data extracted from sequence databases, automatically matched based on designation and taxonomy .
#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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Aminobacter niigataensis (DSM 7050, ATCC 49932, JCM 7853)

Name and taxonomic classification

Morphology

Cell morphology

Colony morphology

Culture and growth conditions

Culture medium

Culture temp

Physiology and metabolism

Oxygen tolerance

Spore formation

Observation

Isolation, sampling and environmental information

Isolation source categories

Isolation

Taxonmaps

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_014200015

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

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