Ferroacidibacillus organovorans (JCM 31945)

Name: Ferroacidibacillus organovorans (JCM 31945)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 164161

Type strain

Culture col. no. JCM 31945

NCBI tax ID(s) 1765683

Special Collections JCM

History JCM <-- D. B. Johnson; Bangor Univ., UK; SLC66.

Ferroacidibacillus organovorans JCM 31945 is a bacterium of the family Alicyclobacillaceae.

genome sequence 16S sequence Bacteria

Name and taxonomic classification

Culture Collection Numbers

JCM 31945

@ref 20215

Last LPSN update 2026-05-29 08:45:20

Domain Bacteria

Phylum Bacillota

Class Bacilli

Order Caryophanales

Family Alicyclobacillaceae

Genus Ferroacidibacillus

Species Ferroacidibacillus organovorans

Full scientific name Ferroacidibacillus organovorans Johnson et al. 2023

Morphology

Culture and growth conditions

Culture temp

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

Physiology and metabolism

Isolation, sampling and environmental information

Taxonmaps

69479

Global distribution of 16S sequence AY040739 (>99% sequence identity) for Acidibacillus ferrooxidans subclade from Microbeatlas

Aquatic Samples	33
Soil Samples	2
Animal Samples	22
Plant Samples	1
Total Samples	58

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
67770	ASM164272v1 assembly for Ferroacidibacillus organovorans SLC66	contig	GCA_001642725	1765683.12	2786546842	1765683	53.5
67770	ASM160248v1 assembly for Ferroacidibacillus organovorans SLC66	contig	GCA_001602485	1765683.11	2786546841	1765683	40.75

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
67770	Ferroacidibacillus organovorans strain SLC66 16S ribosomal RNA gene, partial sequence	AY040739	1467		1765683

GC content

@ref	GC-content (mol%)	Method
67770	52	genome sequence analysis

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: ASM164272v1 assembly for Ferroacidibacillus organovorans SLC66
NCBI: GCA_001642725

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	gram_stain	BacteriaNetⓘ	negative	66.82	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	72.55	no
125439	motility	BacteriaNetⓘ	yes	46.58	no
125439	spore_formation	BacteriaNetⓘ	no	89.65	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Acidibacillus ferrooxidans SLC66
NCBI: GCA_001642725.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	66.72	no
125438	anaerobic	anaerobicⓘ	no	88.21	no
125438	aerobic	aerobicⓘ	yes	75.37	no
125438	spore-forming	spore-formingⓘ	yes	78.38	no
125438	thermophilic	thermophileⓘ	no	56.70	yes
125438	flagellated	motile2+ⓘ	yes	69.14	no

Literature

Title	Authors	Journal	DOI	Year
Sulfoacidibacillus ferrooxidans, gen. nov., sp. nov., Sulfoacidibacillus thermotolerans, gen. nov., sp. nov., and Ferroacidibacillus organovorans, gen. nov., sp. nov.: Extremely acidophilic chemolitho-heterotrophic Firmicutes.	Johnson DB, Holmes DS, Vergara E, Holanda R, Pakostova E.	Res Microbiol	10.1016/j.resmic.2022.104008	2023

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 .

Content

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Ferroacidibacillus organovorans (JCM 31945)

Name and taxonomic classification

Culture Collection Numbers

Morphology

Culture and growth conditions

Culture temp

Physiology and metabolism

Isolation, sampling and environmental information

Taxonmaps

Interaction and safety

Sequence information

Genome sequences

Genome browser: GCA_001642725

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

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