Blautia hydrogenotrophica (DSM 10507, S5a33, JCM 14656)

Name: Blautia hydrogenotrophica (DSM 10507, S5a33, JCM 14656)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 18073

Type strain

Strain Designation S5a33

Culture col. no. DSM 10507 S5a33 JCM 14656

NCBI tax ID(s) 476272 53443

Special Collections DSMZ JCM

History DSMZ <- A. Bernalier, S5a33 JCM <-- DSM 10507 <-- A. Bernalier S5a33.

Links

Blautia hydrogenotrophica S5a33 is an anaerobe bacterium that was isolated from human feces.

anaerobe genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 48838

DSM 10507,JCM 14656

@ref 20215

Last LPSN update 2026-05-29 08:29:10

Domain Bacteria

Phylum Bacillota

Class Clostridia

Order Eubacteriales

Family Lachnospiraceae

Genus Blautia

Species Blautia hydrogenotrophica

Full scientific name Blautia hydrogenotrophica (Bernalier et al. 1997) Liu et al. 2008

Synonyms (1)

Ruminococcus hydrogenotrophicus

BacDive ID	Other strains from **Blautia hydrogenotrophica** (2)	Type strain
157983	B. hydrogenotrophica H2_20, DSM 108220
163993	B. hydrogenotrophica JCM 31266

Morphology

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
3952	PYG MEDIUM (MODIFIED) (DSMZ Medium 104)		Medium recipe at MediaDive	Name: PYG MEDIUM (modified) (DSMZ Medium 104) Composition: Yeast extract 10.0 g/l Peptone 5.0 g/l Trypticase peptone 5.0 g/l Beef extract 5.0 g/l Glucose 5.0 g/l L-Cysteine HCl x H2O 0.5 g/l NaHCO3 0.4 g/l NaCl 0.08 g/l K2HPO4 0.04 g/l KH2PO4 0.04 g/l MgSO4 x 7 H2O 0.02 g/l CaCl2 x 2 H2O 0.01 g/l Hemin 0.005 g/l Ethanol 0.0038 g/l Resazurin 0.001 g/l Tween 80 Vitamin K1 NaOH Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)
3952	positive	growth	37
67770	positive	growth	37

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
3952	anaerobe
125438	anaerobe	90.562
125439	facultative anaerobe	99.567

Spore formation

@ref	Spore formation	Confidence
125439		93.333

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
68380	29016 ChEBI	arginine	-	hydrolysis	from API rID32A
68380	16024 ChEBI	D-mannose	-	fermentation	from API rID32A
68380	29985 ChEBI	L-glutamate	-	degradation	from API rID32A
68380	17632 ChEBI	nitrate	-	reduction	from API rID32A
68380	16634 ChEBI	raffinose	-	fermentation	from API rID32A
68380	27897 ChEBI	tryptophan	-	energy source	from API rID32A
68380	16199 ChEBI	urea	-	hydrolysis	from API rID32A

Metabolite production

@ref	Chebi-ID	Metabolite	Production
68380	35581 ChEBI	indole		from API rID32A

Metabolite tests

@ref	Chebi-ID	Metabolite	Indole test
68380	35581 ChEBI	indole	-	from API rID32A

Enzymes

@ref	Value	Activity	Ec
68380	alanine arylamidase	-	3.4.11.2	from API rID32A
68380	alkaline phosphatase	-	3.1.3.1	from API rID32A
68380	alpha-arabinosidase	-	3.2.1.55	from API rID32A
68380	alpha-fucosidase	-	3.2.1.51	from API rID32A
68380	alpha-galactosidase	-	3.2.1.22	from API rID32A
68380	alpha-glucosidase	+	3.2.1.20	from API rID32A
68380	arginine dihydrolase	-	3.5.3.6	from API rID32A
68380	beta-galactosidase	-	3.2.1.23	from API rID32A
68380	beta-Galactosidase 6-phosphate	-		from API rID32A
68380	beta-glucuronidase	-	3.2.1.31	from API rID32A
68380	glutamate decarboxylase	-	4.1.1.15	from API rID32A
68380	glutamyl-glutamate arylamidase	-		from API rID32A
68380	glycin arylamidase	-		from API rID32A
68380	histidine arylamidase	-		from API rID32A
68380	L-arginine arylamidase	-		from API rID32A
68380	leucine arylamidase	-	3.4.11.1	from API rID32A
68380	leucyl glycin arylamidase	-	3.4.11.1	from API rID32A
68380	N-acetyl-beta-glucosaminidase	-	3.2.1.52	from API rID32A
68380	phenylalanine arylamidase	-		from API rID32A
68380	proline-arylamidase	-	3.4.11.5	from API rID32A
68380	pyrrolidonyl arylamidase	-	3.4.19.3	from API rID32A
68380	serine arylamidase	-		from API rID32A
68380	tryptophan deaminase	-	4.1.99.1	from API rID32A
68380	tyrosine arylamidase	-		from API rID32A
68380	urease	-	3.5.1.5	from API rID32A

API rID32A

@ref	URE	ADH (Arg)	alpha GAL	beta GAL	beta-Galactosidase 6-phosphatebeta GP	alpha GLU	beta GLU	alpha ARA	beta GUR	beta-N-Acetyl-beta-glucosaminidasebeta NAG	MNE	RAF	GDC	alpha FUC	Reduction of nitrateNIT	IND	PAL	L-arginine arylamidaseArgA	ProA	LGA	Phenylalanine arylamidasePheA	Leucine arylamidaseLeuA	PyrA	Tyrosine arylamidaseTyrA	Alanine arylamidaseAlaA	Glycin arylamidaseGlyA	Histidine arylamidaseHisA	Glutamyl-glutamate arylamidaseGGA	Serine arylamidaseSerA
3952	-	-	-	-	-	+	+	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3952	-	-	-	-	-	+	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Host	#Human	-
#Host Body Product	#Gastrointestinal tract	#Feces (Stool)

Isolation

@ref	Sample type	Host species	Country	Country ISO 3 Code	Continent
3952	human feces	Homo sapiens	France	FRA	Europe
67770	Human feces	Homo sapiens

Taxonmaps

69479

Global distribution of 16S sequence X95624 (>99% sequence identity) for Blautia hydrogenotrophica subclade from Microbeatlas

Aquatic Samples	791
Soil Samples	83
Animal Samples	30351
Plant Samples	105
Total Samples	31330

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
3952	1	Risk group (German classification) According to TRBA 466

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
124043	ASM3435603v1 assembly for Blautia hydrogenotrophica DSM 10507	complete	GCA_034356035	476272.40		476272	99.32
67770	ASM15797v1 assembly for Blautia hydrogenotrophica DSM 10507	scaffold	GCA_000157975	476272.21	643886199	476272	30.29

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
3952	Blautia hydrogenotrophica 16S rRNA gene, strain S5a36	X95624	1458		53443
67770	Blautia hydrogenotrophica gene for 16S ribosomal RNA, partial sequence	AB910751	1495		53443

GC content

@ref	GC-content (mol%)	Method
3952	45	high performance liquid chromatography (HPLC)
67770	45.2	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: ASM3435603v1 assembly for Blautia hydrogenotrophica DSM 10507
NCBI: GCA_034356035

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	facultative anaerobe	99.57	no
125439	motility	BacteriaNetⓘ	yes	84.79	no
125439	gram_stain	BacteriaNetⓘ	positive	52.65	no
125439	spore_formation	BacteriaNetⓘ	yes	93.33	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Blautia hydrogenotrophica DSM 10507
PATRIC: 476272.21

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	69.88	no
125438	anaerobic	anaerobicⓘ	yes	90.56	no
125438	spore-forming	spore-formingⓘ	no	51.00	no
125438	aerobic	aerobicⓘ	no	95.67	no
125438	thermophilic	thermophileⓘ	no	94.27	no
125438	flagellated	motile2+ⓘ	no	84.84	no

Literature

Topic	Title	Authors	Journal	DOI	Year
	Complete genome sequences of Blautia hydrogenotrophica DSM 10507^T isolated from human feces and Blautia coccoides DSM 935^T isolated from mouse feces.	Boer T, Bengelsdorf FR, Daniel R, Poehlein A.	Microbiol Resour Announc	10.1128/mra.00016-24	2024
	Can our microbiome break our hearts? Collaborative production of p-cresol sulfate and indoxyl sulfate by commensal microbes increases susceptibility to thrombosis.	Machado Ribeiro TR, Brito CB, Byndloss MX.	mBio	10.1128/mbio.02692-23	2024
	Vitamin B12 analogues from gut microbes and diet differentially impact commensal propionate producers of the human gut.	Kundra P, Greppi A, Duppenthaler M, Pluss S, Pugin B, Lacroix C, Geirnaert A.	Front Nutr	10.3389/fnut.2024.1360199	2024
	MetaPep: A core peptide database for faster human gut metaproteomics database searches.	Sun Z, Ning Z, Cheng K, Duan H, Wu Q, Mayne J, Figeys D.	Comput Struct Biotechnol J	10.1016/j.csbj.2023.08.025	2023
	Technical versus biological variability in a synthetic human gut community.	van de Velde C, Joseph C, Simoens K, Raes J, Bernaerts K, Faust K.	Gut Microbes	10.1080/19490976.2022.2155019	2023
Pathogenicity	Microbe-derived uremic solutes enhance thrombosis potential in the host.	Nemet I, Funabashi M, Li XS, Dwidar M, Sangwan N, Skye SM, Romano KA, Cajka T, Needham BD, Mazmanian SK, Hajjar AM, Rey FE, Fiehn O, Tang WHW, Fischbach MA, Hazen SL.	mBio	10.1128/mbio.01331-23	2023
Pathogenicity	Quantifying the varying harvest of fermentation products from the human gut microbiota.	Arnoldini M, Sharma R, Moresi C, Chure G, Chabbey J, Slack E, Cremer J.	Cell	10.1016/j.cell.2025.07.005	2025
Metabolism	Formate cross-feeding and cooperative metabolic interactions revealed by transcriptomics in co-cultures of acetogenic and amylolytic human colonic bacteria.	Laverde Gomez JA, Mukhopadhya I, Duncan SH, Louis P, Shaw S, Collie-Duguid E, Crost E, Juge N, Flint HJ.	Environ Microbiol	10.1111/1462-2920.14454	2019
	Fast quantification of gut bacterial species in cocultures using flow cytometry and supervised classification.	van de Velde CC, Joseph C, Biclot A, Huys GRB, Pinheiro VB, Bernaerts K, Raes J, Faust K.	ISME Commun	10.1038/s43705-022-00123-6	2022
Metabolism	Microbiota metabolism of intestinal amino acids impacts host nutrient homeostasis and physiology.	Li TT, Chen X, Huo D, Arifuzzaman M, Qiao S, Jin WB, Shi H, Li XV, JRI Live Cell Bank Consortium, Iliev ID, Artis D, Guo CJ.	Cell Host Microbe	10.1016/j.chom.2024.04.004	2024
	Distinct in vitro utilization and degradation of porcine gastric mucin glycans by human intestinal bacteria.	de Ram C, Berkhout MD, O Pandeirada C, Vincken JP, Hooiveld GJEJ, Belzer C, Schols HA.	FEMS Microbiol Ecol	10.1093/femsec/fiaf066	2025
	Dynamic metabolic interactions and trophic roles of human gut microbes identified using a minimal microbiome exhibiting ecological properties.	Shetty SA, Kostopoulos I, Geerlings SY, Smidt H, de Vos WM, Belzer C.	ISME J	10.1038/s41396-022-01255-2	2022
	Methanogen Levels Are Significantly Associated with Fecal Microbiota Composition and Alpha Diversity in Healthy Adults and Irritable Bowel Syndrome Patients.	Wang T, van Dijk L, Rijnaarts I, Hermes GDA, de Roos NM, Witteman BJM, de Wit NJW, Govers C, Smidt H, Zoetendal EG.	Microbiol Spectr	10.1128/spectrum.01653-22	2022
Metabolism	Strain dropouts reveal interactions that govern the metabolic output of the gut microbiome.	Wang M, Osborn LJ, Jain S, Meng X, Weakley A, Yan J, Massey WJ, Varadharajan V, Horak A, Banerjee R, Allende DS, Chan ER, Hajjar AM, Wang Z, Dimas A, Zhao A, Nagashima K, Cheng AG, Higginbottom S, Hazen SL, Brown JM, Fischbach MA.	Cell	10.1016/j.cell.2023.05.037	2023
	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
Phylogeny	Blautia-a new functional genus with potential probiotic properties?	Liu X, Mao B, Gu J, Wu J, Cui S, Wang G, Zhao J, Zhang H, Chen W.	Gut Microbes	10.1080/19490976.2021.1875796	2021
	Carbohydrate complexity limits microbial growth and reduces the sensitivity of human gut communities to perturbations.	Ostrem Loss E, Thompson J, Cheung PLK, Qian Y, Venturelli OS.	Nat Ecol Evol	10.1038/s41559-022-01930-9	2023
	Design, construction, and in vivo augmentation of a complex gut microbiome.	Cheng AG, Ho PY, Aranda-Diaz A, Jain S, Yu FB, Meng X, Wang M, Iakiviak M, Nagashima K, Zhao A, Murugkar P, Patil A, Atabakhsh K, Weakley A, Yan J, Brumbaugh AR, Higginbottom S, Dimas A, Shiver AL, Deutschbauer A, Neff N, Sonnenburg JL, Huang KC, Fischbach MA.	Cell	10.1016/j.cell.2022.08.003	2022
	Berberine-microbiota interplay: orchestrating gut health through modulation of the gut microbiota and metabolic transformation into bioactive metabolites.	Dehau T, Cherlet M, Croubels S, Van De Vliet M, Goossens E, Van Immerseel F.	Front Pharmacol	10.3389/fphar.2023.1281090	2023
Genetics	High throughput genome scale modeling predicts microbial vitamin requirements contribute to gut microbiome community structure.	Molina Ortiz JP, Read MN, McClure DD, Holmes A, Dehghani F, Shanahan ER.	Gut Microbes	10.1080/19490976.2022.2118831	2022
Metabolism	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
Genetics	Insights on the Evolutionary Genomics of the Blautia Genus: Potential New Species and Genetic Content Among Lineages.	Maturana JL, Cardenas JP.	Front Microbiol	10.3389/fmicb.2021.660920	2021
Metabolism	Indoleacrylic Acid Produced by Commensal Peptostreptococcus Species Suppresses Inflammation.	Wlodarska M, Luo C, Kolde R, d'Hennezel E, Annand JW, Heim CE, Krastel P, Schmitt EK, Omar AS, Creasey EA, Garner AL, Mohammadi S, O'Connell DJ, Abubucker S, Arthur TD, Franzosa EA, Huttenhower C, Murphy LO, Haiser HJ, Vlamakis H, Porter JA, Xavier RJ.	Cell Host Microbe	10.1016/j.chom.2017.06.007	2017
	Deciphering microbial interactions in synthetic human gut microbiome communities.	Venturelli OS, Carr AC, Fisher G, Hsu RH, Lau R, Bowen BP, Hromada S, Northen T, Arkin AP.	Mol Syst Biol	10.15252/msb.20178157	2018
	Genetic Evidence Reveals the Indispensable Role of the rseC Gene for Autotrophy and the Importance of a Functional Electron Balance for Nitrate Reduction in Clostridium ljungdahlii.	Klask CM, Jager B, Casini I, Angenent LT, Molitor B.	Front Microbiol	10.3389/fmicb.2022.887578	2022
Genetics	Uneven distribution of cobamide biosynthesis and dependence in bacteria predicted by comparative genomics.	Shelton AN, Seth EC, Mok KC, Han AW, Jackson SN, Haft DR, Taga ME.	ISME J	10.1038/s41396-018-0304-9	2019
Metabolism	Functional assignment of multiple catabolic pathways for D-apiose.	Carter MS, Zhang X, Huang H, Bouvier JT, Francisco BS, Vetting MW, Al-Obaidi N, Bonanno JB, Ghosh A, Zallot RG, Andersen HM, Almo SC, Gerlt JA.	Nat Chem Biol	10.1038/s41589-018-0067-7	2018
Metabolism	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
Metabolism	Dissecting the in vivo metabolic potential of two human gut acetogens.	Rey FE, Faith JJ, Bain J, Muehlbauer MJ, Stevens RD, Newgard CB, Gordon JI.	J Biol Chem	10.1074/jbc.m110.117713	2010
Genetics	Comparative metagenomic analysis of plasmid encoded functions in the human gut microbiome.	Jones BV, Sun F, Marchesi JR.	BMC Genomics	10.1186/1471-2164-11-46	2010
Phylogeny	Functional gene analysis suggests different acetogen populations in the bovine rumen and tammar wallaby forestomach.	Gagen EJ, Denman SE, Padmanabha J, Zadbuke S, Al Jassim R, Morrison M, McSweeney CS.	Appl Environ Microbiol	10.1128/aem.01679-10	2010
Metabolism	Recurrent neural networks enable design of multifunctional synthetic human gut microbiome dynamics.	Baranwal M, Clark RL, Thompson J, Sun Z, Hero AO, Venturelli OS.	Elife	10.7554/elife.73870	2022
Genetics	Comparative analysis of two phenotypically-similar but genomically-distinct Burkholderia cenocepacia-specific bacteriophages.	Lynch KH, Stothard P, Dennis JJ, Dennis JJ.	BMC Genomics	10.1186/1471-2164-13-223	2012
Phylogeny	High-resolution microbial community reconstruction by integrating short reads from multiple 16S rRNA regions.	Amir A, Zeisel A, Zuk O, Elgart M, Stern S, Shamir O, Turnbaugh PJ, Soen Y, Shental N.	Nucleic Acids Res	10.1093/nar/gkt1070	2013
Metabolism	Gut microbial carbohydrate metabolism contributes to insulin resistance.	Takeuchi T, Kubota T, Nakanishi Y, Tsugawa H, Suda W, Kwon AT, Yazaki J, Ikeda K, Nemoto S, Mochizuki Y, Kitami T, Yugi K, Mizuno Y, Yamamichi N, Yamazaki T, Takamoto I, Kubota N, Kadowaki T, Arner E, Carninci P, Ohara O, Arita M, Hattori M, Koyasu S, Ohno H.	Nature	10.1038/s41586-023-06466-x	2023
Metabolism	Integrated culturing, modeling and transcriptomics uncovers complex interactions and emergent behavior in a three-species synthetic gut community.	D'hoe K, Vet S, Faust K, Moens F, Falony G, Gonze D, Llorens-Rico V, Gelens L, Danckaert J, De Vuyst L, Raes J	Elife	10.7554/eLife.37090	2018
	Fusimonas intestini gen. nov., sp. nov., a novel intestinal bacterium of the family Lachnospiraceae associated with diabetes in mice.	Kusada H, Kameyama K, Meng XY, Kamagata Y, Tamaki H.	Sci Rep	10.1038/s41598-017-18122-2	2017
Phylogeny	Blautia faecicola sp. nov., isolated from faeces from a healthy human.	Kim JS, Park JE, Lee KC, Choi SH, Oh BS, Yu SY, Eom MK, Kang SW, Han KI, Suh MK, Lee DH, Yoon H, Kim BY, Yang SJ, Lee JH, Lee JS, Park SH	Int J Syst Evol Microbiol	10.1099/ijsem.0.004015	2020
Phylogeny	Ruminococcus hydrogenotrophicus sp. nov., a new H2/CO2-utilizing acetogenic bacterium isolated from human feces.	Bernalier A, Willems A, Leclerc M, Rochet V, Collins MD	Arch Microbiol	10.1007/s002030050373	1996

References

#3952	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 10507
#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 )
#67770	Japan Collection of Microorganism (JCM) ; Curators of the JCM;
#68380	Automatically annotated from API rID32A .
#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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Blautia hydrogenotrophica (DSM 10507, S5a33, JCM 14656)

Name and taxonomic classification

Morphology

Culture and growth conditions

Culture medium

Culture temp

Physiology and metabolism

Oxygen tolerance

Spore formation

Metabolite utilization

Metabolite production

Metabolite tests

Enzymes

API rID32A

Isolation, sampling and environmental information

Isolation source categories

Isolation

Taxonmaps

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_034356035

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

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