Acetoanaerobium noterae (NOT-3, ATCC 35199)

Name: Acetoanaerobium noterae (NOT-3, ATCC 35199)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 168331

Type strain

Strain Designation NOT-3

Culture col. no. NOT-3 ATCC 35199

NCBI tax ID(s) 745369

Links

Acetoanaerobium noterae NOT-3 is a prokaryote of the family Peptostreptococcaceae.

genome sequence 16S sequence

Name and taxonomic classification

SI-ID 40917

ATCC 35199

@ref 20215

Last LPSN update 2025-12-16 10:10:19

Domain Bacillati

Phylum Bacillota

Class Clostridia

Order Peptostreptococcales

Family Peptostreptococcaceae

Genus Acetoanaerobium

Species Acetoanaerobium noterae

Full scientific name Acetoanaerobium noterae Sleat et al. 1985

Morphology

Culture and growth conditions

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	anaerobe	95.7

Isolation, sampling and environmental information

Taxonmaps

69479

Global distribution of 16S sequence GU562448 (>99% sequence identity) for Acetoanaerobium sticklandii from Microbeatlas

Aquatic Samples	13161
Soil Samples	1323
Animal Samples	6000
Plant Samples	370
Total Samples	20854

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
20215	1	Risk group

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	IMG-taxon 2588253727 annotated assembly for Acetoanaerobium noterae ATCC 35199	scaffold	GCA_900168025	745369.3	2588253727	745369	70.71

Genome browser: GCA_900168025

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
20215	Acetoanaerobium noterae strain ATCC 35199 16S ribosomal RNA gene, partial sequence	GU562448	1415		745369

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Acetoanaerobium noterae ATCC 35199
NCBI: GCA_900168025

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	55.80	no
125439	motility	BacteriaNetⓘ	yes	64.60	no
125439	gram_stain	BacteriaNetⓘ	variable	78.70	no
125439	oxygen_tolerance	BacteriaNetⓘ	anaerobe	95.70	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Acetoanaerobium noterae ATCC 35199
NCBI: GCA_900168025.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	69.33	no
125438	anaerobic	anaerobicⓘ	yes	85.65	no
125438	aerobic	aerobicⓘ	no	92.82	no
125438	spore-forming	spore-formingⓘ	yes	58.60	no
125438	thermophilic	thermophileⓘ	no	87.66	no
125438	flagellated	motile2+ⓘ	yes	78.95	no

Literature

Title	Authors	Journal	DOI	Year
Energy conservation under extreme energy limitation: the role of cytochromes and quinones in acetogenic bacteria.	Rosenbaum FP, Muller V.	Extremophiles	10.1007/s00792-021-01241-0	2021
The Sporomusa type Nfn is a novel type of electron-bifurcating transhydrogenase that links the redox pools in acetogenic bacteria.	Kremp F, Roth J, Muller V.	Sci Rep	10.1038/s41598-020-71038-2	2020
Using gas mixtures of CO, CO₂ and H₂ as microbial substrates: the do's and don'ts of successful technology transfer from laboratory to production scale.	Takors R, Kopf M, Mampel J, Bluemke W, Blombach B, Eikmanns B, Bengelsdorf FR, Weuster-Botz D, Durre P.	Microb Biotechnol	10.1111/1751-7915.13270	2018
Acetoanaerobium pronyense sp. nov., an anaerobic alkaliphilic bacterium isolated from a carbonate chimney of the Prony Hydrothermal Field (New Caledonia).	Bes M, Merrouch M, Joseph M, Quemeneur M, Payri C, Pelletier B, Ollivier B, Fardeau ML, Erauso G, Postec A	Int J Syst Evol Microbiol	10.1099/ijs.0.000307	2015

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) .
#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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Acetoanaerobium noterae (NOT-3, ATCC 35199)

Name and taxonomic classification

Morphology

Culture and growth conditions

Physiology and metabolism

Oxygen tolerance

Isolation, sampling and environmental information

Taxonmaps

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_900168025

16S sequences

Genome-based predictions

Predictions

Literature

Literature

References

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