Acetobacter sicerae (LMG 1531, NCIMB 8941, NCIB 8941)

Name: Acetobacter sicerae (LMG 1531, NCIMB 8941, NCIB 8941)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 167819

Type strain

Strain Designation NCIB 8941

Culture col. no. LMG 1531 NCIMB 8941 NCIB 8941

NCBI tax ID(s) 85325

Links

Acetobacter sicerae NCIB 8941 is a bacterium of the family Acetobacteraceae.

genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 14540

LMG 1531,ATCC 23748,NCIB 8941,NCIMB 8941,ICMP 8562

@ref 20215

Last LPSN update 2026-02-09 11:40:40

Domain Bacteria

Phylum Pseudomonadota

Class Alphaproteobacteria

Order Rhodospirillales

Family Acetobacteraceae

Genus Acetobacter

Species Acetobacter sicerae

Full scientific name Acetobacter sicerae Li et al. 2014

BacDive ID	Other strains from **Acetobacter sicerae** (1)	Type strain
163090	A. sicerae JCM 21163, ATCC 23747, IAM 14349, LMG 1530, ...

Morphology

Cell morphology

@ref	Gram stain	Confidence
125439	negative	98.9
125438	negative	97.5

Culture and growth conditions

Physiology and metabolism

Spore formation

@ref	Spore formation	Confidence
125438		93.314
125439		98.9

Isolation, sampling and environmental information

Taxonmaps

69479

Global distribution of 16S sequence AJ419840 (>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

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	ASM1151676v1 assembly for Acetobacter sicerae LMG 1531	contig	GCA_011516765	85325.3	2899125194	85325	59.35

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
20215	Acetobacter sicerae 16S rRNA gene, type strain LMG 1531T	AJ419840	1440		85325
124043	Acetobacter sicerae partial 16S rRNA gene, type strain LMG 1531T	AJ130729	323		85325

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Acetobacter sicerae LMG 1531
NCBI: GCA_011516765

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	98.90	no
125439	motility	BacteriaNetⓘ	yes	82.10	no
125439	gram_stain	BacteriaNetⓘ	negative	98.90	no
125439	oxygen_tolerance	BacteriaNetⓘ	aerobe	78.90	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Acetobacter sicerae strain LMG 1531
PATRIC: 85325.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	97.50	no
125438	anaerobic	anaerobicⓘ	no	93.30	no
125438	aerobic	aerobicⓘ	yes	81.58	no
125438	spore-forming	spore-formingⓘ	no	93.31	no
125438	thermophilic	thermophileⓘ	no	95.75	no
125438	flagellated	motile2+ⓘ	yes	70.07	no

Literature

Topic	Title	Authors	Journal	DOI	Year
	Phyto-synthesis, characterization of silver nanoparticles from mint leaf extract and its evaluation in antimicrobial and pharmacological applications.	Akhtar W, Hamza MI, Qayyum S, Khan MA, Mukhtar N, Kamal A, Sarwar R, Nazish M, Alrefae AF, Almutairi MH, Naseem MT.	BMC Plant Biol	10.1186/s12870-025-07043-2	2025
	Phyto-synthesis, characterization of silver nanoparticles from mint leaf extract and its evaluation in antimicrobial and pharmacological applications	Akhtar W, Hamza M, Qayyum S, Khan M, Mukhtar N, Kamal A, Sarwar R, Nazish M, Alrefae A, Almutairi M, Naseem M.	BMC Plant Biol		2025
	Commensal acidification of specific gut regions produces a protective priority effect against enteropathogenic bacterial infection.	Yang JL, Zhu H, Sadh P, Aumiller K, Guvener ZT, Ludington WB.	Appl Environ Microbiol	10.1128/aem.00707-25	2025
	Mifepristone Increases Life Span in Female Drosophila Without Detectable Antibacterial Activity.	Landis GN, Riggan L, Bell HS, Vu W, Wang T, Wang I, Tejawinata FI, Ko S, Tower J.	Front Aging	10.3389/fragi.2022.924957	2022
Genetics	Dual-omics strategy for selecting optimal fermentation strains in traditional koumiss production.	Wang X, Zhao Z, Zhao F, Li Y, Liang Y, Zhou R, Shen S, Yu J, Liu W, Menghe B.	Food Chem X	10.1016/j.fochx.2025.102407	2025
	Microbes associated with spontaneous cacao fermentations - A systematic review and meta-analysis.	Taylor AJ, Cardenas-Torres E, Miller MJ, Zhao SD, Engeseth NJ.	Curr Res Food Sci	10.1016/j.crfs.2022.08.008	2022
Genetics	Diverse Microbial Composition of Sourdoughs From Different Origins.	Comasio A, Verce M, Van Kerrebroeck S, De Vuyst L.	Front Microbiol	10.3389/fmicb.2020.01212	2020
Pathogenicity	Early-life exposure to low-dose oxidants can increase longevity via microbiome remodelling in Drosophila.	Obata F, Fons CO, Gould AP.	Nat Commun	10.1038/s41467-018-03070-w	2018
Genetics	Genomic exaptation enables Lasius niger adaptation to urban environments.	Konorov EA, Nikitin MA, Mikhailov KV, Lysenkov SN, Belenky M, Chang PL, Nuzhdin SV, Scobeyeva VA.	BMC Evol Biol	10.1186/s12862-016-0867-x	2017
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
	Acetobacter sacchari sp. nov., for a plant growth-promoting acetic acid bacterium isolated in Vietnam	Vu HTL, Yukphan P, Bui VTT, Charoenyingcharoen P, Malimas S, Nguyen LK, Muramatsu Y, Tanaka N, Tanasupawat S, Le BT, Nakagawa Y, Yamada Y.	Ann Microbiol		2019
Phylogeny	Acetobacter sicerae sp. nov., isolated from cider and kefir, and identification of species of the genus Acetobacter by dnaK, groEL and rpoB sequence analysis.	Li L, Wieme A, Spitaels F, Balzarini T, Nunes OC, Manaia CM, Van Landschoot A, De Vuyst L, Cleenwerck I, Vandamme P	Int J Syst Evol Microbiol	10.1099/ijs.0.058354-0	2014

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 .
#124043	Isabel Schober, Julia Koblitz: Data extracted from sequence databases, automatically matched based on designation and taxonomy .
#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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Acetobacter sicerae (LMG 1531, NCIMB 8941, NCIB 8941)

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

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_011516765

16S sequences

Genome-based predictions

Predictions

Literature

Literature

References

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