Achromobacter sp. (MTCC 12117, MCC 2980, JCM 31426)

Name: Achromobacter sp. (MTCC 12117, MCC 2980, JCM 31426)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 164058

Type strain

Culture col. no. MTCC 12117 MCC 2980 JCM 31426

NCBI tax ID(s) 134375

Special Collections JCM

History P. Sar; Dept. of Biotechnol., Indian Inst. of Technol. Kharagpur, India; KAs 3-5.

Links

JCM 31426 is a bacterium of the family Alcaligenaceae.

genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 131727

JCM 31426,MTCC 12117

@ref 20215

Last LPSN update 2026-02-09 11:39:45

Domain Bacteria

Phylum Pseudomonadota

Class Betaproteobacteria

Order Burkholderiales

Family Alcaligenaceae

Genus Achromobacter

Full scientific name Achromobacter Yabuuchi and Yano 1981

Morphology

Cell morphology

@ref	Gram stain	Confidence
125438	negative	95.918

Culture and growth conditions

Culture temp

@ref	Growth	Type	Temperature (°C)
67770	positive	growth	30

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125438	aerobe	90.012
125439	obligate aerobe	95.8

Isolation, sampling and environmental information

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID
67770	ASM197548v2 assembly for Achromobacter sp. KAs 3-5	scaffold	GCA_001975485	1915388.3	2987446798	1915388

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
67770	Achromobacter sp. KAs3-5 16S ribosomal RNA gene, partial sequence	JX173986	1389		1915388

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Achromobacter sp. KAs 3-5
NCBI: GCA_001975485

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	88.50	no
125439	motility	BacteriaNetⓘ	yes	61.10	no
125439	gram_stain	BacteriaNetⓘ	negative	74.30	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	95.80	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Achromobacter sp. KAs 3-5 KAs 3-5
NCBI: GCA_001975485.2

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	95.92	no
125438	anaerobic	anaerobicⓘ	no	97.79	no
125438	aerobic	aerobicⓘ	yes	90.01	no
125438	spore-forming	spore-formingⓘ	no	88.79	no
125438	thermophilic	thermophileⓘ	no	99.43	yes
125438	flagellated	motile2+ⓘ	yes	83.28	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 )
#67770	Japan Collection of Microorganism (JCM) ; Curators of the JCM;
#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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