Butyricicoccus faecihominis (DSM 100989, JCM 31056, YIT 12789)

Name: Butyricicoccus faecihominis (DSM 100989, JCM 31056, YIT 12789)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 132645

Type strain

Strain Designation KS-2

Culture col. no. DSM 100989 JCM 31056 YIT 12789 KS-2

NCBI tax ID(s) 1712515

Special Collections DSMZ JCM

Links

Butyricicoccus faecihominis KS-2 is a mesophilic prokaryote that was isolated from faeces from a healthy human adult.

mesophilic genome sequence 16S sequence

Name and taxonomic classification

SI-ID 398828

JCM 31056,DSM 100989

@ref 20215

Last LPSN update 2025-12-16 10:01:34

Domain Bacillati

Phylum Bacillota

Class Clostridia

Order Eubacteriales

Family Oscillospiraceae

Genus Butyricicoccus

Species Butyricicoccus faecihominis

Full scientific name Butyricicoccus faecihominis Takada et al. 2016

Morphology

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
24434	CMC MEDIUM (N2/CO2) (DSMZ Medium 110a)		Medium recipe at MediaDive	Name: CMC MEDIUM (N2/CO2) (DSMZ Medium 110a) Composition: Ground beef 500.0 g/l Casitone 30.0 g/l Yeast extract 5.0 g/l K2HPO4 5.0 g/l D-Glucose 4.0 g/l Na2CO3 1.5 g/l Cellobiose 1.0 g/l Maltose 1.0 g/l Starch 1.0 g/l L-Cysteine HCl x H2O 0.5 g/l Sodium resazurin 0.0005 g/l NaOH Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
24434	positive	growth	37	mesophilic
67770	positive	growth	37	mesophilic

Physiology and metabolism

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2
#Infection	#Patient
#Host	#Human
#Host Body Product	#Gastrointestinal tract

Isolation

@ref	Sample type	Country	Country ISO 3 Code	Continent
24434	faeces from a healthy human adult	Japan	JPN	Asia
67770	Human feces

Taxonmaps

69479

Global distribution of 16S sequence LC082228 (>99% sequence identity) for Eubacteriales from Microbeatlas

Aquatic Samples	757
Soil Samples	133
Animal Samples	56625
Plant Samples	65
Total Samples	57580

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
24434	1	Risk group (German classification)

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM1464801v1 assembly for Butyricicoccus faecihominis JCM 31056	scaffold	GCA_014648015	1712515.5	8066652108	1712515	63.66
66792	ASM1658637v1 assembly for Butyricicoccus faecihominis JCM 31056	contig	GCA_016586375	1712515.6	8113997141	1712515	46.55

Genome browser: GCA_014648015

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
24434	Butyricicoccus faecihominis gene for 16S ribosomal RNA, partial sequence	LC082228	1418		1712515

GC content

@ref	GC-content (mol%)	Method
24434	55.6	sequence analysis
67770	55.6	genome sequence analysis

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Butyricicoccus faecihominis JCM 31056
NCBI: GCA_014648015

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	67.80	no
125439	motility	BacteriaNetⓘ	yes	61.50	no
125439	gram_stain	BacteriaNetⓘ	variable	68.60	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate anaerobe	60.30	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Butyricicoccus faecihominis JCM 31056
NCBI: GCA_014648015.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	69.73	no
125438	anaerobic	anaerobicⓘ	yes	86.80	no
125438	aerobic	aerobicⓘ	no	96.49	no
125438	spore-forming	spore-formingⓘ	no	62.61	no
125438	thermophilic	thermophileⓘ	no	88.97	yes
125438	flagellated	motile2+ⓘ	no	82.63	no

Literature

Title	Authors	Journal	DOI	Year
Safety evaluation of Butyricicoccus faecihominis DSM 34943.	Pitt J, Bauter MR, Kumar R, Hasselwander O, Hibberd AA, Kane H, Wang Q, Auzanneau I, Bry S, David E, Seguinot P, Burns F, Smith AB, Carnovale M.	Toxicol Rep	10.1016/j.toxrep.2025.102145	2025
Characterization of fructooligosaccharide metabolism and fructooligosaccharide-degrading enzymes in human commensal butyrate producers.	Tanno H, Fujii T, Hirano K, Maeno S, Tonozuka T, Sakamoto M, Ohkuma M, Tochio T, Endo A.	Gut Microbes	10.1080/19490976.2020.1869503	2021
Oral administration of Blautia wexlerae ameliorates obesity and type 2 diabetes via metabolic remodeling of the gut microbiota.	Hosomi K, Saito M, Park J, Murakami H, Shibata N, Ando M, Nagatake T, Konishi K, Ohno H, Tanisawa K, Mohsen A, Chen YA, Kawashima H, Natsume-Kitatani Y, Oka Y, Shimizu H, Furuta M, Tojima Y, Sawane K, Saika A, Kondo S, Yonejima Y, Takeyama H, Matsutani A, Mizuguchi K, Miyachi M, Kunisawa J.	Nat Commun	10.1038/s41467-022-32015-7	2022
Association between gut microbiota composition and physical functioning in patients with knee osteoarthritis: a machine learning study.	de Sire A, Mancuso E, Marotta N, Massimino M, Zito R, Averta C, Bartalotta I, Palummo A, Cerantonio A, Citrigno L, Soverini M, Castagnetti A, Mannino GC, Ammendolia A, Andreozzi F.	Sci Rep	10.1038/s41598-025-24500-y	2025
Assessing the impact of broiler genotype on cecal and tracheal microbiome composition using full-length 16S rRNA sequencing.	Poudel S, Rahman FA, Granados EAF, Adhikari Y, Naeem M, Rochell SJ, Bourassa D.	Poult Sci	10.1016/j.psj.2025.106072	2025
Association of Mucin-Degrading Gut Microbiota and Dietary Patterns with Colonic Transit Time in Constipation: A Secondary Analysis of a Randomized Clinical Trial.	Wu X, Yang HJ, Ryu MS, Jung SJ, Ha K, Jeong DY, Park S.	Nutrients	10.3390/nu17010138	2024
Fecal microbiome analysis in patients with metabolic syndrome and type 2 diabetes.	Sinisterra Loaiza LI, Fernandez-Edreira D, Linares-Blanco J, Cepeda A, Cardelle-Cobas A, Fernandez-Lozano C.	PeerJ	10.7717/peerj.19108	2025
Fecal and Tissue Microbiota Are Associated with Tumor T-Cell Infiltration and Mesenteric Lymph Node Involvement in Colorectal Cancer.	Luu K, Ye JY, Lagishetty V, Liang F, Hauer M, Sedighian F, Kwaan MR, Kazanjian KK, Hecht JR, Lin AY, Jacobs JP.	Nutrients	10.3390/nu15020316	2023
Efficacy of a Multistrain Synbiotic Treatment in Acute and Post-Acute COVID-19 Patients: A Double-Blind, Placebo-Controlled Randomized Trial.	Giancola ML, Fontana A, Panebianco C, Mazzarelli A, Beccacece A, De Marco P, Cocomazzi G, De Giuli C, Grassi G, Fontana C, Baldini GM, Contu V, Copetti M, Perri F, Nicastri E, Pazienza V.	Microorganisms	10.3390/microorganisms12071443	2024
Personalized prediction of glycemic responses to food in women with diet-treated gestational diabetes: the role of the gut microbiota.	Popova PV, Isakov AO, Rusanova AN, Sitkin SI, Anopova AD, Vasukova EA, Tkachuk AS, Nemikina IS, Stepanova EA, Eriskovskaya AI, Stepanova EA, Pustozerov EA, Kokina MA, Vasilieva EY, Vasilyeva LB, Zgairy S, Rubin E, Even C, Turjeman S, Pervunina TM, Grineva EN, Koren O, Shlyakhto EV.	NPJ Biofilms Microbiomes	10.1038/s41522-025-00650-9	2025
Learning ecosystem-scale dynamics from microbiome data with MDSINE2.	Gibson TE, Kim Y, Acharya S, Kaplan DE, DiBenedetto N, Lavin R, Berger B, Allegretti JR, Bry L, Gerber GK.	Nat Microbiol	10.1038/s41564-025-02112-6	2025
Efficacy and Mechanism of the Action of Live and Heat-Killed Bacillus coagulans BC198 as Potential Probiotic in Ameliorating Dextran Sulfate Sodium-Induced Colitis in Mice.	Koh YC, Chang YC, Lin WS, Leung SY, Chen WJ, Wu SH, Wei YS, Gung CL, Chou YC, Pan MH.	ACS Omega	10.1021/acsomega.3c07529	2024
The adolescent and young adult microbiome and its association with substance use: a scoping review.	Browning BD, Kirkland AE, Green R, Engevik M, Alekseyenko AV, Leggio L, Tomko RL, Squeglia LM.	Alcohol Alcohol	10.1093/alcalc/agad055	2024
Modulation of the Gut Microbiota in Memory Impairment and Alzheimer's Disease via the Inhibition of the Parasympathetic Nervous System.	Park S, Wu X.	Int J Mol Sci	10.3390/ijms232113574	2022
Diagnostic and prognostic potential of the microbiome in ovarian cancer treatment response.	Asangba AE, Chen J, Goergen KM, Larson MC, Oberg AL, Casarin J, Multinu F, Kaufmann SH, Mariani A, Chia N, Walther-Antonio MRS.	Sci Rep	10.1038/s41598-023-27555-x	2023
Identification of microbial markers across populations in early detection of colorectal cancer.	Wu Y, Jiao N, Zhu R, Zhang Y, Wu D, Wang AJ, Fang S, Tao L, Li Y, Cheng S, He X, Lan P, Tian C, Liu NN, Zhu L.	Nat Commun	10.1038/s41467-021-23265-y	2021
ANCHOR: a 16S rRNA gene amplicon pipeline for microbial analysis of multiple environmental samples.	Gonzalez E, Pitre FE, Brereton NJB.	Environ Microbiol	10.1111/1462-2920.14632	2019
Reclassification of Eubacterium desmolans as Butyricicoccus desmolans comb. nov., and description of Butyricicoccus faecihominis sp. nov., a butyrate-producing bacterium from human faeces.	Takada T, Watanabe K, Makino H, Kushiro A	Int J Syst Evol Microbiol	10.1099/ijsem.0.001323	2016

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 )
#24434	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 100989
#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) .
#67770	Japan Collection of Microorganism (JCM) ; Curators of the JCM;
#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 )

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Butyricicoccus faecihominis (DSM 100989, JCM 31056, YIT 12789)

Name and taxonomic classification

Morphology

Culture and growth conditions

Culture medium

Culture temp

Physiology and metabolism

Isolation, sampling and environmental information

Isolation source categories

Isolation

Taxonmaps

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_014648015

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

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