Komagataeibacter saccharivorans (CIP 109786, LMG 1582, JCM 25121)

Name: Komagataeibacter saccharivorans (CIP 109786, LMG 1582, JCM 25121)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 134628

Type strain

Culture col. no. CIP 109786 LMG 1582 JCM 25121 BCC 36444 NRIC 0614 2 more

NCBI tax ID(s) 1307941 265959

Special Collections JCM CIP

History CIP <- 2008, T. Uchimura, Tokyo Univ., Tokyo, Japan: strain NRIC 0614 JCM <-- NRIC 0614 <-- LMG 1582 <-- LMD 29.3 ("Acetobacter mesoxydans subsp. saccharovorans") <-- J. Frateur 1 ("Acetobacter mesoxydans var. sucrasiferum") <-- Inst. für die Essigindustrie Berlin ("Bacterium dihydroxyacetonicum") CIP <- 2008, T. Uchimura, Tokyo Univ., Tokyo, Japan: strain NRIC 0614

Links

Komagataeibacter saccharivorans CIP 109786 is an obligate aerobe, Gram-negative, rod-shaped bacterium of the family Acetobacteraceae.

Gram-negative rod-shaped obligate aerobe genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 14560

LMG 1582,LMD 29.3,NCCB 29003,CIP 109786,BCC 36444,CECT 7869,JCM 25121,TBRC 4566

@ref 20215

Last LPSN update 2026-05-29 08:38:22

Domain Bacteria

Phylum Pseudomonadota

Class Alphaproteobacteria

Order Rhodospirillales

Family Acetobacteraceae

Genus Komagataeibacter

Species Komagataeibacter saccharivorans

Full scientific name Komagataeibacter saccharivorans (Lisdiyanti et al. 2006) Yamada et al. 2013

Synonyms (2)

"Komagatabacter saccharivorans"
Gluconacetobacter saccharivorans

BacDive ID	Other strains from **Komagataeibacter saccharivorans** (1)	Type strain
163327	K. saccharivorans JCM 25122, LMG 1584

Morphology

Cell morphology

@ref	Gram stain	Cell shape	Confidence
33079	negative	rod-shaped
125439	negative		97.289
125438	negative		97.333

Culture and growth conditions

Culture medium

@ref	Name	Growth	Composition	Medium link
33079	MEDIUM 1 - for Acetobacter, Azotobacter, Gluconobacter, Gluconacetobacter, Mesorhizodium ciceri and Pseudomonas doudoroffii		Distilled water make up to (1000.000 ml);Agar (15.000 g);Yeast extract (5.000 g);Peptone (3.000 g);Mannitol (25.000 g)
33079	CIP Medium 1			Medium recipe at CIP

Culture temp

@ref	Growth	Type	Temperature (°C)
33079	positive	growth	30
67770	positive	growth	30

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
33079	obligate aerobe
125439	obligate aerobe	94.252

Spore formation

@ref	Spore formation	Confidence
125439		99.593
125438		92.327

Observation

67770

Observationquinones: Q-10

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
33079	17632 ChEBI	nitrate	-	reduction
33079	16301 ChEBI	nitrite	-	reduction

Metabolite production

@ref	Chebi-ID	Metabolite	Production
33079	35581 ChEBI	indole

Enzymes

@ref	Value	Activity	Ec
68382	acid phosphatase	+	3.1.3.2	from API zym
68382	alkaline phosphatase	-	3.1.3.1	from API zym
68382	alpha-chymotrypsin	-	3.4.21.1	from API zym
68382	alpha-fucosidase	-	3.2.1.51	from API zym
68382	alpha-galactosidase	-	3.2.1.22	from API zym
68382	alpha-glucosidase	-	3.2.1.20	from API zym
68382	alpha-mannosidase	-	3.2.1.24	from API zym
68382	beta-galactosidase	-	3.2.1.23	from API zym
68382	beta-glucosidase	-	3.2.1.21	from API zym
68382	beta-glucuronidase	-	3.2.1.31	from API zym
33079	catalase	+	1.11.1.6
68382	cystine arylamidase	-	3.4.11.3	from API zym
68382	esterase (C 4)	+		from API zym
68382	esterase lipase (C 8)	-		from API zym
68382	leucine arylamidase	+	3.4.11.1	from API zym
68382	lipase (C 14)	-		from API zym
68382	N-acetyl-beta-glucosaminidase	-	3.2.1.52	from API zym
68382	naphthol-AS-BI-phosphohydrolase	+		from API zym
33079	oxidase	-
68382	trypsin	+	3.4.21.4	from API zym
33079	urease	-	3.5.1.5
68382	valine arylamidase	+		from API zym

API zym

@ref	Control	Alkaline phosphatase	Esterase (C 4)	2-naphtyl caprylateEsterase Lipase (C 8)	Lipase (C 14)	L-leucyl-2-naphthylamideLeucine arylamidase	L-valyl-2-naphthylamideValine arylamidase	L-cystyl-2-naphthylamideCystine arylamidase	Trypsin	alpha- Chymotrypsin	Acid phosphatase	Naphthol-AS-BI-phosphateNaphthol-AS-BI-phosphohydrolase	alpha- Galactosidase	beta- Galactosidase	beta- Glucuronidase	alpha- Glucosidase	beta- Glucosidase	N-acetyl-beta- glucosaminidase	alpha- Mannosidase	alpha- Fucosidase
33079	-	-	+	-	-	+	+	-	+	-	+	+	-	-	-	-	-	-	-	-

Isolation, sampling and environmental information

Isolation

@ref	Sample type	Country	Country ISO 3 Code	Continent	Isolation date
33079		Germany	DEU	Europe
67770	Beet juice	Germany	DEU	Europe
33079	Beet juice	Germany	DEU	Europe	1927

Taxonmaps

69479

Global distribution of 16S sequence AB166740 (>99% sequence identity) for Komagataeibacter from Microbeatlas

Aquatic Samples	42
Soil Samples	74
Animal Samples	149
Plant Samples	78
Total Samples	343

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
33079	1	Risk group (French classification)

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
67770	ASM320782v1 assembly for Komagataeibacter saccharivorans LMG 1582	contig	GCA_003207825	265959.6	2837595999	265959	58.4
124043	ASM2599455v1 assembly for Komagataeibacter saccharivorans NRIC 0614	contig	GCA_025994555	1307941.3		1307941	33.1

16S sequences

@ref	Description	Accession	Length	NCBI tax ID
67770	Gluconacetobacter saccharivorans gene for 16S rRNA, partial sequence, strain: LMG 1582	AB166740	1386	265959
67770	Gluconacetobacter saccharivorans gene for 16S rRNA, partial sequence, strain: JCM 25121	AB645734	1411	265959
124043	Gluconacetobacter saccharivorans 16S rRNA gene, type strain LMG 1582T	AJ012466	1481	265959
124043	Gluconacetobacter saccharivorans strain LMG 1582 16S ribosomal RNA gene, partial sequence.	JF794010	1354	265959

GC content

@ref	GC-content (mol%)	Method
67770	61	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: ASM320782v1 assembly for Komagataeibacter saccharivorans LMG 1582
BV-BRC: 265959.6

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	94.25	no
125439	gram_stain	BacteriaNetⓘ	negative	97.29	no
125439	motility	BacteriaNetⓘ	yes	76.74	no
125439	spore_formation	BacteriaNetⓘ	no	99.59	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Komagataeibacter saccharivorans strain LMG 1582
PATRIC: 265959.6

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	97.33	no
125438	anaerobic	anaerobicⓘ	no	90.36	yes
125438	spore-forming	spore-formingⓘ	no	92.33	no
125438	aerobic	aerobicⓘ	yes	77.98	yes
125438	thermophilic	thermophileⓘ	no	96.25	yes
125438	flagellated	motile2+ⓘ	no	60.17	no

Literature

Topic	Title	Authors	Journal	DOI	Year
	Genome Sequence of Komagataeibacter saccharivorans Strain JH1, Isolated from Fruit Flies.	Hollensteiner J, Poehlein A, Kloskowski P, Ali TT, Daniel R.	Microbiol Resour Announc	10.1128/mra.00098-20	2020
Metabolism	Bacterial nanocellulose from agro-industrial wastes: low-cost and enhanced production by Komagataeibacter saccharivorans MD1.	Abol-Fotouh D, Hassan MA, Shokry H, Roig A, Azab MS, Kashyout AEB.	Sci Rep	10.1038/s41598-020-60315-9	2020
	Dynamic changes in physicochemical, bacterial, and volatile profiles during kombucha fermentation of mulberry fruits and leaves.	Xu C, Yu Z, Zhou S, Feng H, Du Q, Yuan X, Fan R, Jiang H, Yang Y, Han R, Wang X.	Food Res Int	10.1016/j.foodres.2025.116813	2025
	Dynamic changes in physicochemical, bacterial, and volatile profiles during kombucha fermentation of mulberry fruits and leaves	Xu C, Yu Z, Zhou S, Feng H, Du Q, Yuan X, Fan R, Jiang H, Yang Y, Han R, Wang X.	Food Research International.		2025
	Dynamic changes in microbial communities and volatile compounds in kombucha fermentation using Flos sophorae and Elm fruits, compared to black and green tea	Xu C, Zhou S, Zhang J, Bu D, Zang C, Fan R, Wang J, Guo T, Han R, Yang Y.	Food Research International.		2024
	Dynamic changes in microbial communities and volatile compounds in kombucha fermentation using Flos sophorae and Elm fruits, compared to black and green tea.	Xu C, Zhou S, Zhang J, Bu D, Zang C, Fan R, Wang J, Guo T, Han R, Yang Y.	Food Res Int	10.1016/j.foodres.2024.115233	2024
	Efficiency of freeze- and spray-dried microbial preparation as active dried starter culture in kombucha fermentation.	Phan Van T, Nguyen QD, Nguyen NN, Do AD.	J Sci Food Agric	10.1002/jsfa.13697	2024
	Bacterial valorization of agricultural-waste into a nano-sized cellulosic matrix for mitigating emerging pharmaceutical pollutants: An eco-benign approach.	Walling B, Bharali P, Ramachandran D, Kanagasabai V, Dutta N, Hazarika S, Maadurshni GB, Manivannan J, Kumari S, Acharjee SA, Gogoi B, Alemtoshi, Sorhie V, Vishwakarma V.	Int J Biol Macromol	10.1016/j.ijbiomac.2024.133684	2024
	Revealing the influence of microbiota on the flavor of kombucha during natural fermentation process by metagenomic and GC-MS analysis	Yao L, Zhang J, Lu J, Chen D, Song S, Wang H, Sun M, Feng T.	Food Res Int		2023
	In-situ biofabrication of bacterial nanocellulose (BNC)/graphene oxide (GO) nano-biocomposite and study of its cationic dyes adsorption properties.	Walling B, Bharali P, Ramachandran D, Viswanathan K, Hazarika S, Dutta N, Mudoi P, Manivannan J, Manjunath Kamath S, Kumari S, Vishwakarma V, Sorhie V, Gogoi B, Acharjee SA, Alemtoshi.	Int J Biol Macromol	10.1016/j.ijbiomac.2023.126309	2023
	Revealing the influence of microbiota on the flavor of kombucha during natural fermentation process by metagenomic and GC-MS analysis.	Yao L, Zhang J, Lu J, Chen D, Song S, Wang H, Sun M, Feng T.	Food Res Int	10.1016/j.foodres.2023.112909	2023
Genetics	Exploring microbial players for metagenomic profiling of carbon cycling bacteria in sundarban mangrove soils.	Das BK, Gadnayak A, Chakraborty HJ, Pradhan SP, Raut SS, Das SK.	Sci Rep	10.1038/s41598-025-89418-x	2025
	Evaluation of microbiota-induced changes in biochemical, sensory properties and volatile profile of kombucha produced by reformed microbial community.	Kilmanoglu H, Yigit Cinar A, Durak MZ.	Food Chem X	10.1016/j.fochx.2024.101469	2024
	Storage time and temperature affect microbial dynamics of yeasts and acetic acid bacteria in a kombucha beverage.	Grassi A, Cristani C, Palla M, Di Giorgi R, Giovannetti M, Agnolucci M.	Int J Food Microbiol	10.1016/j.ijfoodmicro.2022.109934	2022
Genetics	Customized 16S-23S rDNA ITS Amplicon Metagenomics for Acetic Acid Bacteria Species Identification in Vinegars and Kombuchas.	Ribic A, Trcek J.	Microorganisms	10.3390/microorganisms12051023	2024
Phenotype	Population mixing mediates the intestinal flora composition and facilitates invasiveness in a globally invasive fruit fly.	Wang Y, Li Z, Zhao Z.	Microbiome	10.1186/s40168-023-01664-1	2023
	Bacterial Cellulose production by K. saccharivorans BC1 strain using crude distillery effluent as cheap and cost effective nutrient medium.	Gayathri G, Srinikethan G.	Int J Biol Macromol	10.1016/j.ijbiomac.2019.07.159	2019
	Nature of back slopping kombucha fermentation process: insights from the microbial succession, metabolites composition changes and their correlations.	Liao T, Li XR, Fan L, Zhang B, Zheng WM, Hua JJ, Li L, Mahror N, Cheng LH.	Front Microbiol	10.3389/fmicb.2024.1433127	2024
Genetics	Hidden Markov Model-Based Prokaryotic Genome Space Mining Reveals the Widespread Pervasiveness of Complex I and Its Potential Evolutionary Scheme.	Shirsath A, Khairnar SV, Anand A, Prabhakaran DM, Anand A.	Genome Biol Evol	10.1093/gbe/evaf154	2025
Phylogeny	Longitudinal dynamics of intestinal bacteria in the life cycle and their effects on growth and development of potato tuber moth.	Fu Q, Wang W, Chen B, Hu Y, Ma R, Zhu E, Jin S, Cai H, Xiao G, Du G.	Front Microbiol	10.3389/fmicb.2025.1542589	2025
	Isolation and Characterization of Cellulose Nanocrystals from Bacterial Cellulose Synthesized via Ancylobacter sp. STN1A Using Residual Glycerol.	Pena-Ortiz M, Garcia A, Martirani-Von Abercron SM, Marin P, Marques S, Khiari R, Dufresne A, Serrano L.	Polymers (Basel)	10.3390/polym17091240	2025
	A Review on the Interaction of Acetic Acid Bacteria and Microbes in Food Fermentation: A Microbial Ecology Perspective.	Han D, Yang Y, Guo Z, Dai S, Jiang M, Zhu Y, Wang Y, Yu Z, Wang K, Rong C, Yu Y.	Foods	10.3390/foods13162534	2024
	Shedding Light on the Formation and Structure of Kombucha Biofilm Using Two-Photon Fluorescence Microscopy.	Tran T, Grandvalet C, Winckler P, Verdier F, Martin A, Alexandre H, Tourdot-Marechal R.	Front Microbiol	10.3389/fmicb.2021.725379	2021
Enzymology	Metagenome-Assembled Genomes Contribute to Unraveling of the Microbiome of Cocoa Fermentation.	Almeida OGG, De Martinis ECP.	Appl Environ Microbiol	10.1128/aem.00584-21	2021
	Utilizing kombucha culture for coffee fermentation and biochemical characteristic analysis.	Kim H, Jeon J, Lee J, Song C, Gu B, Kim NM, Yang TH, Oh S, Park S, Pal K, Kim GJ, Kim D.	Curr Res Food Sci	10.1016/j.crfs.2025.100996	2025
Genetics	Time and temperature influence on physicochemical, microbiological, and sensory profiles of yerba mate kombucha.	Treviso RL, Sant'Anna V, Fabricio MF, Ayub MAZ, Brandelli A, Hickert LR.	J Food Sci Technol	10.1007/s13197-024-05951-z	2024
	Microbial Dynamics between Yeasts and Acetic Acid Bacteria in Kombucha: Impacts on the Chemical Composition of the Beverage.	Tran T, Grandvalet C, Verdier F, Martin A, Alexandre H, Tourdot-Marechal R.	Foods	10.3390/foods9070963	2020
	Selection of Acetic Acid Bacterial Strains and Vinegar Production From Local Maltese Food Sources.	Mizzi J, Gaggia F, Bozzi Cionci N, Di Gioia D, Attard E.	Front Microbiol	10.3389/fmicb.2022.897825	2022
Phylogeny	Culture-Dependent and Metabarcoding Characterization of the Sugar Beet (Beta vulgaris L.) Microbiome for High-Yield Isolation of Bacteria with Plant Growth-Promoting Traits.	Krstic Tomic T, Atanaskovic I, Nikolic I, Jokovic N, Stevic T, Stankovic S, Beric T, Lozo J.	Microorganisms	10.3390/microorganisms11061538	2023
	From a Basic Microalga and an Acetic Acid Bacterium Cellulose Producer to a Living Symbiotic Biofilm.	Nobrega V, Faria M, Quintana A, Kaufmann M, Ferreira A, Cordeiro N.	Materials (Basel)	10.3390/ma12142275	2019
Genetics	Microbiological, Functional, and Chemico-Physical Characterization of Artisanal Kombucha: An Interesting Reservoir of Microbial Diversity	Njieukam J, Ciccone M, Gottardi D, Ricci A, Parpinello G, Siroli L, Lanciotti R, Patrignani F.	Foods		2024
	The Effect of Dekkera bruxellensis Concentration and Inoculation Time on Biochemical Changes and Cellulose Biosynthesis by Komagataeibacter intermedius.	Devanthi PVP, Pratama F, Kho K, Taherzadeh MJ, Aslanzadeh S.	J Fungi (Basel)	10.3390/jof8111206	2022
	Comparison of Cultivable Acetic Acid Bacterial Microbiota in Organic and Conventional Apple Cider Vinegar.	Stornik A, Skok B, Trcek J.	Food Technol Biotechnol	10.17113/ftb.54.01.16.4082	2016
	Microbial Composition of SCOBY Starter Cultures Used by Commercial Kombucha Brewers in North America.	Harrison K, Curtin C.	Microorganisms	10.3390/microorganisms9051060	2021
	Multi-omics characterization of the microbial populations and chemical space composition of a water kefir fermentation.	Arrieta-Echeverri MC, Fernandez GJ, Duarte-Riveros A, Correa-Alvarez J, Bardales JA, Villanueva-Mejia DF, Sierra-Zapata L.	Front Mol Biosci	10.3389/fmolb.2023.1223863	2023
	Innovative Analogs of Unpasteurized Kombucha Beverages: Comparative Analysis of Mint/Nettle Kombuchas, Considering Their Health-Promoting Effect, Polyphenolic Compounds and Chemical Composition.	Pawlus P, Kolniak-Ostek J.	Int J Mol Sci	10.3390/ijms25147572	2024
	Microbial Interactions in Kombucha through the Lens of Metabolomics.	Tran T, Roullier-Gall C, Verdier F, Martin A, Schmitt-Kopplin P, Alexandre H, Grandvalet C, Tourdot-Marechal R.	Metabolites	10.3390/metabo12030235	2022
	Sisymbrium Officinale (the Singers' Plant) as an Ingredient: Analysis of Somatosensory Active Volatile Isothiocyanates in Model Food and Drinks.	De Nisi P, Borgonovo G, Tramontana S, Grassi S, Picozzi C, Scaglioni L, Mazzini S, Mangieri N, Bassoli A.	Foods	10.3390/foods10020308	2021
	Kombucha: a novel model system for cooperation and conflict in a complex multi-species microbial ecosystem.	May A, Narayanan S, Alcock J, Varsani A, Maley C, Aktipis A.	PeerJ	10.7717/peerj.7565	2019
	Effect of Fermentation Time on Antioxidant and Anti-Ageing Properties of Green Coffee Kombucha Ferments.	Zofia NL, Aleksandra Z, Tomasz B, Martyna ZD, Magdalena Z, Zofia HB, Tomasz W.	Molecules	10.3390/molecules25225394	2020
	Kombucha Beverage from Green, Black and Rooibos Teas: A Comparative Study Looking at Microbiology, Chemistry and Antioxidant Activity.	Gaggia F, Baffoni L, Galiano M, Nielsen DS, Jakobsen RR, Castro-Mejia JL, Bosi S, Truzzi F, Musumeci F, Dinelli G, Di Gioia D.	Nutrients	10.3390/nu11010001	2018
Genetics	A Combined Metagenomics and Metatranscriptomics Approach to Unravel Costa Rican Cocoa Box Fermentation Processes Reveals Yet Unreported Microbial Species and Functionalities.	Verce M, Schoonejans J, Hernandez Aguirre C, Molina-Bravo R, De Vuyst L, Weckx S.	Front Microbiol	10.3389/fmicb.2021.641185	2021
	Description of Komagataeibacter melaceti sp. nov. and Komagataeibacter melomenusus sp. nov. Isolated from Apple Cider Vinegar.	Maric L, Cleenwerck I, Accetto T, Vandamme P, Trcek J.	Microorganisms	10.3390/microorganisms8081178	2020
Phylogeny	Reclassification of Gluconacetobacter hansenii strains and proposals of Gluconacetobacter saccharivorans sp. nov. and Gluconacetobacter nataicola sp. nov.	Lisdiyanti P, Navarro RR, Uchimura T, Komagata K	Int J Syst Evol Microbiol	10.1099/ijs.0.63252-0	2006

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 )
#33079	Collection of Institut Pasteur ; Curators of the CIP; CIP 109786
#67770	Japan Collection of Microorganism (JCM) ; Curators of the JCM;
#68382	Automatically annotated from API zym .
#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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Komagataeibacter saccharivorans (CIP 109786, LMG 1582, JCM 25121)

Name and taxonomic classification

Morphology

Cell morphology

Culture and growth conditions

Culture medium

Culture temp

Physiology and metabolism

Oxygen tolerance

Spore formation

Observation

Metabolite utilization

Metabolite production

Enzymes

API zym

Isolation, sampling and environmental information

Isolation

Taxonmaps

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_003207825

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

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