Acetobacter conturbans (LMG 1627, NCIMB 8945)

Name: Acetobacter conturbans (LMG 1627, NCIMB 8945)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 167133

Type strain

Culture col. no. LMG 1627 NCIMB 8945

NCBI tax ID(s) 1737472

Links

Acetobacter conturbans LMG 1627 is a bacterium of the family Acetobacteraceae.

genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 14593

LMG 1627,NCIB 8945,NCIMB 8945

@ref 20215

Last LPSN update 2026-05-29 08:46:04

Domain Bacteria

Phylum Pseudomonadota

Class Alphaproteobacteria

Order Rhodospirillales

Family Acetobacteraceae

Genus Acetobacter

Species Acetobacter conturbans

Full scientific name Acetobacter conturbans Sombolestani et al. 2020

Morphology

Cell morphology

@ref	Gram stain	Confidence
125439	negative	93.057
125438	negative	96.833

Culture and growth conditions

Physiology and metabolism

Spore formation

@ref	Spore formation	Confidence
125438		91.711
125439		99.163

Isolation, sampling and environmental information

Taxonmaps

69479

Global distribution of 16S sequence MN744433 (>99% sequence identity) for Acetobacter from Microbeatlas

Aquatic Samples	132
Soil Samples	133
Animal Samples	499
Plant Samples	124
Total Samples	888

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM1151675v1 assembly for Acetobacter conturbans LMG 1627	contig	GCA_011516755	1737472.3	2905236147	1737472	59.81

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
20215	Acetobacter conturbans strain LMG 1627 16S ribosomal RNA gene, partial sequence	MN744433	1476		1737472

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: ASM1151675v1 assembly for Acetobacter conturbans LMG 1627
BV-BRC: 1737472.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	motility	BacteriaNetⓘ	yes	66.93	no
125439	gram_stain	BacteriaNetⓘ	negative	93.06	no
125439	oxygen_tolerance	BacteriaNetⓘ	aerobe	78.03	no
125439	spore_formation	BacteriaNetⓘ	no	99.16	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Acetobacter sp. LMG 1627
PATRIC: 1737472.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	96.83	no
125438	anaerobic	anaerobicⓘ	no	94.09	no
125438	spore-forming	spore-formingⓘ	no	91.71	no
125438	aerobic	aerobicⓘ	yes	82.05	no
125438	thermophilic	thermophileⓘ	no	96.85	no
125438	flagellated	motile2+ⓘ	yes	51.12	no

Literature

Topic	Title	Authors	Journal	DOI	Year
	Comprehensive deciphering prophages in genus Acetobacter on the ecology, genomic features, toxin-antitoxin system, and linkage with CRISPR-Cas system.	Qian C, Ma J, Liang J, Zhang L, Liang X.	Front Microbiol	10.3389/fmicb.2022.951030	2022
Phylogeny	Novel acetic acid bacteria from cider fermentations: Acetobacter conturbans sp. nov. and Acetobacter fallax sp. nov.	Sombolestani AS, Cleenwerck I, Cnockaert M, Borremans W, Wieme AD, De Vuyst L, Vandamme P	Int J Syst Evol Microbiol	10.1099/ijsem.0.004511	2020

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 )

Content

About us

Acetobacter conturbans (LMG 1627, NCIMB 8945)

Name and taxonomic classification

Morphology

Cell morphology

Culture and growth conditions

Physiology and metabolism

Spore formation

Isolation, sampling and environmental information

Taxonmaps

Interaction and safety

Sequence information

Genome sequences

Genome browser: GCA_011516755

16S sequences

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

Help

Social Media