Cite this strain

Achromobacter sp. (JCM 18799)

Name: Achromobacter sp. (JCM 18799)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 162299

Type strain

Culture col. no. JCM 18799

NCBI tax ID(s) 1295134

Special Collections JCM

History N. Takizawa <-- H. Kiyohara AFK2.

Links

JCM 18799 is a mesophilic prokaryote that was isolated from Soil.

mesophilic genome sequence

Name and taxonomic classification

SI-ID 131709

JCM 18799

@ref 20215

Last LPSN update 2025-12-16 10:08:57

Domain Pseudomonadati

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	94.331

Culture and growth conditions

Culture temp

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

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	aerobe	90.5

Isolation, sampling and environmental information

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
67770	Soil	Okayama	Japan	JPN	Asia

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID
66792	ASM131220v1 assembly for Achromobacter sp. JCM 18799	contig	GCA_001312205	1295134.5	2728369714	1295134

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Achromobacter sp. JCM 18799
NCBI: GCA_001312205

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	84.50	no
125439	motility	BacteriaNetⓘ	yes	51.10	no
125439	gram_stain	BacteriaNetⓘ	negative	75.60	no
125439	oxygen_tolerance	BacteriaNetⓘ	aerobe	90.50	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Achromobacter sp. JCM 18799
PATRIC: 1295134.5

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	94.33	no
125438	anaerobic	anaerobicⓘ	no	96.39	no
125438	spore-forming	spore-formingⓘ	no	85.18	no
125438	aerobic	aerobicⓘ	yes	84.39	no
125438	thermophilic	thermophileⓘ	no	97.93	yes
125438	flagellated	motile2+ⓘ	yes	74.78	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 )
#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;
#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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