Thermaerobacter composti (ATCC BAA-1731, JCM 15650)

Name: Thermaerobacter composti (ATCC BAA-1731, JCM 15650)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 161614

Type strain

Culture col. no. ATCC BAA-1731 JCM 15650

NCBI tax ID(s) 1294259 554949

Special Collections JCM

Links

Thermaerobacter composti JCM 15650 is a thermophilic prokaryote that was isolated from Food sludge compost.

thermophilic genome sequence 16S sequence

Name and taxonomic classification

SI-ID 28290

ATCC BAA-1731,JCM 15650

@ref 20215

Last LPSN update 2025-12-16 10:08:47

Domain Bacillati

Phylum Bacillota

Class Thermaerobacteria

Order Thermaerobacterales

Family Thermaerobacteraceae

Genus Thermaerobacter

Species Thermaerobacter composti

Full scientific name Thermaerobacter composti Yabe et al. 2010

Morphology

Culture and growth conditions

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
67770	positive	growth	70	thermophilic

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	obligate anaerobe	91.3

Spore formation

@ref	Spore formation	Confidence
125439		92.8

Isolation, sampling and environmental information

Isolation

@ref	Sample type	Country	Country ISO 3 Code	Continent
67770	Food sludge compost	Japan	JPN	Asia

Taxonmaps

69479

Global distribution of 16S sequence AB454087 (>99% sequence identity) for Thermaerobacter composti subclade from Microbeatlas

Aquatic Samples	84
Soil Samples	355
Animal Samples	128
Plant Samples	303
Total Samples	870

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID
67770	ASM131196v1 assembly for Thermaerobacter composti JCM 15650	contig	GCA_001311965	1294259.8	2728369702	1294259

Genome browser: GCA_001311965

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
67770	Thermaerobacter composti gene for 16S ribosomal RNA, partial sequence	AB454087	1566		1294259

GC content

@ref	GC-content (mol%)	Method
67770	72	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: Thermaerobacter composti JCM 15650
NCBI: GCA_001311965

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	obligate anaerobe	91.30	no
125439	gram_stain	BacteriaNetⓘ	negative	73.30	no
125439	motility	BacteriaNetⓘ	yes	50.80	no
125439	spore_formation	BacteriaNetⓘ	no	92.80	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Thermaerobacter composti JCM 15650
PATRIC: 1294259.8

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	54.97	no
125438	anaerobic	anaerobicⓘ	no	67.98	no
125438	spore-forming	spore-formingⓘ	no	76.68	no
125438	aerobic	aerobicⓘ	no	55.49	no
125438	thermophilic	thermophileⓘ	no	58.28	no
125438	flagellated	motile2+ⓘ	no	73.07	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Genetics	Complete genome sequence of Thermaerobacter composti strain Ins1, a spore-forming filamentous bacterium isolated from a deep geothermal reservoir.	Bregnard D, Gonzalez D, Di Francesco E, Mangia N, Regenspurg S, Junier P.	Microbiol Resour Announc	10.1128/mra.00058-24	2024
Phylogeny	Thermaerobacter composti sp. nov., a novel extremely thermophilic bacterium isolated from compost.	Yabe S, Kato A, Hazaka M, Yokota A	J Gen Appl Microbiol	10.2323/jgam.55.323	2009

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;
#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 .
#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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Thermaerobacter composti (ATCC BAA-1731, JCM 15650)

Name and taxonomic classification

Morphology

Culture and growth conditions

Culture temp

Physiology and metabolism

Oxygen tolerance

Spore formation

Isolation, sampling and environmental information

Isolation

Taxonmaps

Interaction and safety

Sequence information

Genome sequences

Genome browser: GCA_001311965

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

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