Fibrobacter succinogenes (ATCC 19169, S85)

Name: Fibrobacter succinogenes (ATCC 19169, S85)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 140659

Type strain

Strain Designation S85

Culture col. no. ATCC 19169 S85

NCBI tax ID(s) 833 834

Special Collections Literature strains

Links

Fibrobacter succinogenes S85 is a bacterium of the family Fibrobacteraceae.

genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 36881

ATCC 19169,CCUG 27826

@ref 20215

Last LPSN update 2026-05-29 08:39:46

Domain Bacteria

Phylum Fibrobacterota

Class Fibrobacteria

Order Fibrobacterales

Family Fibrobacteraceae

Genus Fibrobacter

Species Fibrobacter succinogenes

Full scientific name Fibrobacter succinogenes (Hungate 1950) Montgomery et al. 1988

Synonyms (2)

"Ruminobacter succinogenes"
Bacteroides succinogenes

Morphology

Cell morphology

@ref	Gram stain	Confidence
125438	negative	96.714
125439	negative	98.036

Culture and growth conditions

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	facultative anaerobe	90.128

Spore formation

@ref	Spore formation	Confidence
125439		99.891

Observation

43382

ObservationCellulase activity under high tannin concentration

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
43382	62968 ChEBI	cellulose	+	fermentation
43382	62968 ChEBI	cellulose	+	hydrolysis

Enzymes

@ref	Value	Activity	Ec
43382	cellulase	+	3.2.1.4

Isolation, sampling and environmental information

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM2466v1 assembly for Fibrobacter succinogenes subsp. succinogenes S85	complete	GCA_000024665	59374.5	646311927	59374	98.27
66792	ASM14650v1 assembly for Fibrobacter succinogenes subsp. succinogenes S85	complete	GCA_000146505	59374.8	650377942	59374	96.9

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
124043	Fibrobacter succinogenes partial S85 16S rRNA gene, strain ATCC 19169	AJ496032	1410		59374
124043	Fibrobacter succinogenes subsp. succinogenes S85 16S ribosomal RNA, partial sequence.	M62696	1443		59374

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: ASM2466v1 assembly for Fibrobacter succinogenes subsp. succinogenes S85
BV-BRC: 59374.5

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	gram_stain	BacteriaNetⓘ	negative	98.04	no
125439	oxygen_tolerance	BacteriaNetⓘ	facultative anaerobe	90.13	no
125439	motility	BacteriaNetⓘ	yes	51.26	no
125439	spore_formation	BacteriaNetⓘ	no	99.89	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Fibrobacter succinogenes subsp. succinogenes S85 S85
NCBI: GCA_000146505.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	96.71	no
125438	anaerobic	anaerobicⓘ	yes	75.22	no
125438	aerobic	aerobicⓘ	no	81.41	no
125438	spore-forming	spore-formingⓘ	no	83.55	no
125438	thermophilic	thermophileⓘ	no	90.59	no
125438	flagellated	motile2+ⓘ	no	77.06	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Transcriptome	Transcriptomic analysis of the interactions between Fibrobacter succinogenes S85, Selenomonas ruminantium PC18 and a live yeast strain used as a ruminant feed additive.	Desvignes P, Ruiz P, Guillot L, Danon J, Durand A, Beaumont M, Chaucheyras-Durand F, Forano E.	BMC Genomics	10.1186/s12864-025-11894-2	2025
Genetics	*Dynamic genome-based metabolic modeling of the predominant cellulolytic rumen bacterium Fibrobacter succinogenes* S85**.	Fakih I, Got J, Robles-Rodriguez CE, Siegel A, Forano E, Munoz-Tamayo R.	mSystems	10.1128/msystems.01027-22	2023
Genetics	In Vivo Competitions between Fibrobacter succinogenes, Ruminococcus flavefaciens, and Ruminoccus albus in a Gnotobiotic Sheep Model Revealed by Multi-Omic Analyses.	Yeoman CJ, Fields CJ, Lepercq P, Ruiz P, Forano E, White BA, Mosoni P.	mBio	10.1128/mbio.03533-20	2021
Phylogeny	Cellulolytic bacteria in the large intestine of mammals.	Froidurot A, Julliand V.	Gut Microbes	10.1080/19490976.2022.2031694	2022
Metabolism	Evaluating Models of Cellulose Degradation by Fibrobacter succinogenes S85.	Burnet MC, Dohnalkova AC, Neumann AP, Lipton MS, Smith RD, Suen G, Callister SJ.	PLoS One	10.1371/journal.pone.0143809	2015
Metabolism	Characterization of variations within the rumen metaproteome of Holstein dairy cattle relative to morning feed offering.	Honan MC, Greenwood SL.	Sci Rep	10.1038/s41598-020-59974-5	2020
Metabolism	Deciphering the unique cellulose degradation mechanism of the ruminal bacterium Fibrobacter succinogenes S85.	Raut MP, Couto N, Karunakaran E, Biggs CA, Wright PC.	Sci Rep	10.1038/s41598-019-52675-8	2019
	A global analysis of gene expression in Fibrobacter succinogenes S85 grown on cellulose and soluble sugars at different growth rates.	Neumann AP, Weimer PJ, Suen G.	Biotechnol Biofuels	10.1186/s13068-018-1290-x	2018
	FibroChip, a Functional DNA Microarray to Monitor Cellulolytic and Hemicellulolytic Activities of Rumen Microbiota.	Comtet-Marre S, Chaucheyras-Durand F, Bouzid O, Mosoni P, Bayat AR, Peyret P, Forano E.	Front Microbiol	10.3389/fmicb.2018.00215	2018
	Influence of dietary carbohydrate profile on the dairy cow rumen meta-proteome.	Mulakala BK, Smith KM, Snider MA, Ayers A, Honan MC, Greenwood SL.	J Dairy Sci	10.3168/jds.2022-21812	2022
Metabolism	Localization of ruminal cellulolytic bacteria on plant fibrous materials as determined by fluorescence in situ hybridization and real-time PCR.	Shinkai T, Kobayashi Y.	Appl Environ Microbiol	10.1128/aem.01896-06	2007
Metabolism	Influence of the composition of the cellulolytic flora on the development of hydrogenotrophic microorganisms, hydrogen utilization, and methane production in the rumens of gnotobiotically reared lambs.	Chaucheyras-Durand F, Masseglia S, Fonty G, Forano E.	Appl Environ Microbiol	10.1128/aem.01784-10	2010
Metabolism	Characterization and synergistic interactions of Fibrobacter succinogenes glycoside hydrolases.	Qi M, Jun HS, Forsberg CW.	Appl Environ Microbiol	10.1128/aem.01037-07	2007
	Genomic differences between Fibrobacter succinogenes S85 and Fibrobacter intestinalis DR7, identified by suppression subtractive hybridization.	Qi M, Nelson KE, Daugherty SC, Nelson WC, Hance IR, Morrison M, Forsberg CW.	Appl Environ Microbiol	10.1128/aem.02514-07	2008
Metabolism	In vivo 23Na nuclear magnetic resonance study of maintenance of a sodium gradient in the ruminal bacterium Fibrobacter succinogenes S85.	Schwaab V, Matheron C, Delort AM, Gaudet G, Forano E.	Appl Environ Microbiol	10.1128/aem.67.9.4390-4392.2001	2001
Metabolism	Diet-induced alterations in total and metabolically active microbes within the rumen of dairy cows.	Lettat A, Benchaar C.	PLoS One	10.1371/journal.pone.0060978	2013
Metabolism	Degradation of wheat straw by Fibrobacter succinogenes S85: a liquid- and solid-state nuclear magnetic resonance study.	Matulova M, Nouaille R, Capek P, Pean M, Forano E, Delort AM.	Appl Environ Microbiol	10.1128/aem.71.3.1247-1253.2005	2005
Metabolism	BcsZ inhibits biofilm phenotypes and promotes virulence by blocking cellulose production in Salmonella enterica serovar Typhimurium.	Ahmad I, Rouf SF, Sun L, Cimdins A, Shafeeq S, Le Guyon S, Schottkowski M, Rhen M, Romling U, Romling U.	Microb Cell Fact	10.1186/s12934-016-0576-6	2016
	Designing novel cellulase systems through agent-based modeling and global sensitivity analysis.	Apte AA, Senger RS, Fong SS.	Bioengineered	10.4161/bioe.29160	2014
Metabolism	Fiber-degrading systems of different strains of the genus Fibrobacter.	Bera-Maillet C, Ribot Y, Forano E.	Appl Environ Microbiol	10.1128/aem.70.4.2172-2179.2004	2004
Phylogeny	Novel molecular features of the fibrolytic intestinal bacterium Fibrobacter intestinalis not shared with Fibrobacter succinogenes as determined by suppressive subtractive hybridization.	Qi M, Nelson KE, Daugherty SC, Nelson WC, Hance IR, Morrison M, Forsberg CW.	J Bacteriol	10.1128/jb.187.11.3739-3751.2005	2005
	Effects of Condensed Tannins on Endoglucanase Activity and Filter Paper Digestion by Fibrobacter succinogenes S85.	Bae HD, McAllister TA, Yanke J, Cheng KJ, Muir AD.	Appl Environ Microbiol	10.1128/aem.59.7.2132-2138.1993	1993
Metabolism	Interactions between carbon and nitrogen metabolism in Fibrobacter succinogenes S85: a 1H and 13C nuclear magnetic resonance and enzymatic study.	Matheron C, Delort AM, Gaudet G, Liptaj T, Forano E.	Appl Environ Microbiol	10.1128/aem.65.5.1941-1948.1999	1999
Enzymology	Antigenic nature of the chloride-stimulated cellobiosidase and other cellulases of Fibrobacter succinogenes subsp. succinogenes S85 and related fresh isolates.	Huang L, McGavin M, Forsberg CW, Lam JS, Cheng KJ.	Appl Environ Microbiol	10.1128/aem.56.5.1229-1234.1990	1990
Metabolism	Factors affecting adhesion of Fibrobacter succinogenes subsp. succinogenes S85 and adherence-defective mutants to cellulose.	Gong J, Forsberg CW.	Appl Environ Microbiol	10.1128/aem.55.12.3039-3044.1989	1989
	Effects of Physicochemical Factors on the Adhesion to Cellulose Avicel of the Ruminal Bacteria Ruminococcus flavefaciens and Fibrobacter succinogenes subsp. succinogenes.	Roger V, Fonty G, Komisarczuk-Bony S, Gouet P.	Appl Environ Microbiol	10.1128/aem.56.10.3081-3087.1990	1990
Enzymology	Separation of outer and cytoplasmic membranes of Fibrobacter succinogenes and membrane and glycogen granule locations of glycanases and cellobiase.	Gong J, Forsberg CW.	J Bacteriol	10.1128/jb.175.21.6810-6821.1993	1993
Metabolism	13C and 1H nuclear magnetic resonance study of glycogen futile cycling in strains of the genus Fibrobacter.	Matheron C, Delort AM, Gaudet G, Forano E, Liptaj T.	Appl Environ Microbiol	10.1128/aem.64.1.74-81.1998	1998
Enzymology	Purification, characterization, and mode of action of endoxylanases 1 and 2 from Fibrobacter succinogenes S85.	Matte A, Forsberg CW.	Appl Environ Microbiol	10.1128/aem.58.1.157-168.1992	1992
	Rumen microbial and fermentation characteristics are affected differently by bacterial probiotic supplementation during induced lactic and subacute acidosis in sheep.	Lettat A, Noziere P, Silberberg M, Morgavi DP, Berger C, Martin C.	BMC Microbiol	10.1186/1471-2180-12-142	2012
	The sequence of the single 16S rRNA gene of the thermophilic eubacterium Rhodothermus marinus reveals a distant relationship to the group containing Flexibacter, Bacteroides, and Cytophaga species.	Andresson OS, Fridjonsson OH.	J Bacteriol	10.1128/jb.176.20.6165-6169.1994	1994
Metabolism	Phylogeny of dissimilatory sulfite reductases supports an early origin of sulfate respiration.	Wagner M, Roger AJ, Flax JL, Brusseau GA, Stahl DA.	J Bacteriol	10.1128/jb.180.11.2975-2982.1998	1998
Metabolism	An rRNA approach for assessing the role of obligate amino acid-fermenting bacteria in ruminal amino acid deamination.	Krause DO, Russell JB.	Appl Environ Microbiol	10.1128/aem.62.3.815-821.1996	1996
	Structure of the cel-3 gene from Fibrobacter succinogenes S85 and characteristics of the encoded gene product, endoglucanase 3.	McGavin MJ, Forsberg CW, Crosby B, Bell AW, Dignard D, Thomas DY.	J Bacteriol	10.1128/jb.171.10.5587-5595.1989	1989
Enzymology	Development and validation of a real-time PCR method to quantify rumen protozoa and examination of variability between entodinium populations in sheep offered a hay-based diet.	Skillman LC, Toovey AF, Williams AJ, Wright AD.	Appl Environ Microbiol	10.1128/aem.72.1.200-206.2006	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 )
#43382	Hee Dong Bae, Tim A. MacAllister, Jay Yanke, K-J. Cheng and A. D. Muir: Effects of Condensed Tannins on Endoglucanase Activity and Filter Paper Digestion by Fibrobacter succinogenes S85. 59(7): 2132 - 2138 1993 ( DOI 10.1128/aem.59.7.2132-2138.1993 , PubMed 16348990 )
#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) .
#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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Fibrobacter succinogenes (ATCC 19169, S85)

Name and taxonomic classification

Morphology

Cell morphology

Culture and growth conditions

Physiology and metabolism

Oxygen tolerance

Spore formation

Observation

Metabolite utilization

Enzymes

Isolation, sampling and environmental information

Interaction and safety

Sequence information

Genome sequences

Genome browser: GCA_000024665

16S sequences

Genome-based predictions

Predictions

Literature

Literature

References

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