Peptacetobacter hiranonis (DSM 13275, JCM 10541, KCTC 15199)

Name: Peptacetobacter hiranonis (DSM 13275, JCM 10541, KCTC 15199)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 2798

Type strain

Strain Designation TO-931

Culture col. no. DSM 13275 JCM 10541 KCTC 15199 TO-931

NCBI tax ID(s) 500633 89152

Special Collections DSMZ JCM KCTC

History DSMZ <- Y. Benno, JCM; JCM 10541 <- F. Takamine, University of the Ryukyus, Okinawa, Japan; TO-931 JCM <-- F. Takamine TO-931.

Links

Peptacetobacter hiranonis TO-931 is an anaerobe bacterium that was isolated from human faeces.

anaerobe genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 49451

KCTC 15199,DSM 13275,JCM 10541,KCTC 13902

@ref 20215

Last LPSN update 2026-05-29 08:25:33

Domain Bacteria

Phylum Bacillota

Class Clostridia

Order Peptostreptococcales

Family Peptostreptococcaceae

Genus Peptacetobacter

Species Peptacetobacter hiranonis

Full scientific name Peptacetobacter hiranonis (Kitahara et al. 2001) Chen et al. 2020

Synonyms (1)

Clostridium hiranonis

BacDive ID	Other strains from **Peptacetobacter hiranonis** (1)	Type strain
160991	P. hiranonis JCM 10542

Morphology

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
4987	PY + X MEDIUM (N2/CO2) (DSMZ Medium 104c)		Medium recipe at MediaDive	Name: PY + X MEDIUM (N2/CO2) (DSMZ Medium 104c) Composition: Yeast extract 10.0 g/l D-Glucose 5.0 g/l Trypticase peptone 5.0 g/l Meat peptone 5.0 g/l Na2CO3 1.0 g/l L-Cysteine HCl x H2O 0.5 g/l NaHCO3 0.4 g/l NaCl 0.08 g/l KH2PO4 0.04 g/l K2HPO4 0.04 g/l MgSO4 x 7 H2O 0.02 g/l CaCl2 x 2 H2O 0.01 g/l Sodium resazurin 0.0005 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)
4987	positive	growth	37
67770	positive	growth	37

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
4987	anaerobe
125438	anaerobe	93.775
125439	obligate anaerobe	99.139

Pathway annotation

Computationally determined by

@ref	pathway	enzyme coverage	annotated reactions
66794	L-lactaldehyde degradation	100	3 of 3
66794	aminopropanol phosphate biosynthesis	100	2 of 2
66794	cis-vaccenate biosynthesis	100	2 of 2
66794	coenzyme A metabolism	100	4 of 4
66794	ppGpp biosynthesis	100	4 of 4
66794	CDP-diacylglycerol biosynthesis	100	2 of 2
66794	UDP-GlcNAc biosynthesis	100	3 of 3
66794	folate polyglutamylation	100	1 of 1
66794	anapleurotic synthesis of oxalacetate	100	1 of 1
66794	phenylmercury acetate degradation	100	2 of 2
66794	6-hydroxymethyl-dihydropterin diphosphate biosynthesis	100	8 of 8
66794	vitamin B1 metabolism	92.31	12 of 13
66794	palmitate biosynthesis	90.91	20 of 22
66794	chorismate metabolism	88.89	8 of 9
66794	degradation of sugar alcohols	87.5	14 of 16
66794	reductive acetyl coenzyme A pathway	85.71	6 of 7
66794	phenylalanine metabolism	84.62	11 of 13
66794	flavin biosynthesis	80	12 of 15
66794	peptidoglycan biosynthesis	80	12 of 15
66794	photosynthesis	78.57	11 of 14
66794	valine metabolism	77.78	7 of 9
66794	aspartate and asparagine metabolism	77.78	7 of 9
66794	acetate fermentation	75	3 of 4
66794	sulfopterin metabolism	75	3 of 4
66794	vitamin B12 metabolism	73.53	25 of 34
66794	NAD metabolism	72.22	13 of 18
66794	cardiolipin biosynthesis	71.43	5 of 7
66794	purine metabolism	70.21	66 of 94
66794	threonine metabolism	70	7 of 10
66794	selenocysteine biosynthesis	66.67	4 of 6
66794	acetoin degradation	66.67	2 of 3
66794	octane oxidation	66.67	2 of 3
66794	formaldehyde oxidation	66.67	2 of 3
66794	pyrimidine metabolism	66.67	30 of 45
66794	ketogluconate metabolism	62.5	5 of 8
66794	C4 and CAM-carbon fixation	62.5	5 of 8
66794	methionine metabolism	61.54	16 of 26
66794	hydrogen production	60	3 of 5
66794	factor 420 biosynthesis	60	3 of 5
66794	metabolism of amino sugars and derivatives	60	3 of 5
66794	glycine betaine biosynthesis	60	3 of 5
66794	glycolysis	58.82	10 of 17
66794	propanol degradation	57.14	4 of 7
66794	tetrahydrofolate metabolism	57.14	8 of 14
66794	glutamate and glutamine metabolism	57.14	16 of 28
66794	heme metabolism	57.14	8 of 14
66794	serine metabolism	55.56	5 of 9
66794	cysteine metabolism	55.56	10 of 18
66794	d-mannose degradation	55.56	5 of 9
66794	lysine metabolism	52.38	22 of 42
66794	glycolate and glyoxylate degradation	50	3 of 6
66794	adipate degradation	50	1 of 2
66794	glycogen biosynthesis	50	2 of 4
66794	CMP-KDO biosynthesis	50	2 of 4
66794	isoleucine metabolism	50	4 of 8
66794	ethanol fermentation	50	1 of 2
66794	Entner Doudoroff pathway	50	5 of 10
66794	gluconeogenesis	50	4 of 8
66794	citric acid cycle	50	7 of 14
66794	butanoate fermentation	50	2 of 4
66794	biotin biosynthesis	50	2 of 4
66794	alanine metabolism	48.28	14 of 29
66794	isoprenoid biosynthesis	46.15	12 of 26
66794	proline metabolism	45.45	5 of 11
66794	metabolism of disaccharids	45.45	5 of 11
66794	histidine metabolism	44.83	13 of 29
66794	CO2 fixation in Crenarchaeota	44.44	4 of 9
66794	oxidative phosphorylation	42.86	39 of 91
66794	tryptophan metabolism	42.11	16 of 38
66794	non-pathway related	42.11	16 of 38
66794	glycogen metabolism	40	2 of 5
66794	arachidonate biosynthesis	40	2 of 5
66794	propionate fermentation	40	4 of 10
66794	lipoate biosynthesis	40	2 of 5
66794	3-chlorocatechol degradation	40	2 of 5
66794	methylglyoxal degradation	40	2 of 5
66794	polyamine pathway	39.13	9 of 23
66794	sulfate reduction	38.46	5 of 13
66794	leucine metabolism	38.46	5 of 13
66794	urea cycle	38.46	5 of 13
66794	arginine metabolism	37.5	9 of 24
66794	carnitine metabolism	37.5	3 of 8
66794	vitamin B6 metabolism	36.36	4 of 11
66794	d-xylose degradation	36.36	4 of 11
66794	pentose phosphate pathway	36.36	4 of 11
66794	glutathione metabolism	35.71	5 of 14
66794	degradation of pentoses	35.71	10 of 28
66794	tyrosine metabolism	35.71	5 of 14
66794	lipid metabolism	35.48	11 of 31
66794	sphingosine metabolism	33.33	2 of 6
66794	methane metabolism	33.33	1 of 3
66794	cyanate degradation	33.33	1 of 3
66794	IAA biosynthesis	33.33	1 of 3
66794	degradation of hexoses	33.33	6 of 18
66794	pantothenate biosynthesis	33.33	2 of 6
66794	lipid A biosynthesis	33.33	3 of 9
66794	molybdenum cofactor biosynthesis	33.33	3 of 9
66794	phenylpropanoid biosynthesis	30.77	4 of 13
66794	ascorbate metabolism	27.27	6 of 22
66794	degradation of aromatic, nitrogen containing compounds	25	3 of 12
66794	lactate fermentation	25	1 of 4
66794	cyclohexanol degradation	25	1 of 4
66794	toluene degradation	25	1 of 4
66794	dTDPLrhamnose biosynthesis	25	2 of 8
66794	4-hydroxymandelate degradation	22.22	2 of 9
66794	nitrate assimilation	22.22	2 of 9

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	Geographic location	Country	Country ISO 3 Code	Continent
4987	human faeces	Homo sapiens	Okinawa	Japan	JPN	Asia
67770	Human feces	Homo sapiens

Taxonmaps

69479

Global distribution of 16S sequence AB971817 (>99% sequence identity) for Peptacetobacter hiranonis subclade from Microbeatlas

Aquatic Samples	98
Soil Samples	27
Animal Samples	7429
Plant Samples	36
Total Samples	7590

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
4987	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
66792	ASM815178v1 assembly for Peptacetobacter hiranonis DSM 13275	complete	GCA_008151785	89152.14	8062836459	89152	92.92
67770	ASM15605v1 assembly for Peptacetobacter hiranonis DSM 13275	scaffold	GCA_000156055	500633.7	642979371	500633	55.11

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
4987	Clostridium hiranonis gene for 16S rRNA, partial sequence, strain:TO-931	AB023970	1393		500633
67770	[Clostridium] hiranonis gene for 16S ribosomal RNA, partial sequence, strain: JCM 10541	AB971817	1410		89152

GC content

@ref	GC-content (mol%)	Method
4987	31.1	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: ASM815178v1 assembly for Peptacetobacter hiranonis DSM 13275
BV-BRC: 89152.14

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	obligate anaerobe	99.14	no
125439	gram_stain	BacteriaNetⓘ	positive	59.02	no
125439	motility	BacteriaNetⓘ	yes	53.63	no
125439	spore_formation	BacteriaNetⓘ	yes	42.70	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Peptacetobacter hiranonis DSM 13275
NCBI: GCA_008151785.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	81.69	no
125438	anaerobic	anaerobicⓘ	yes	93.78	no
125438	aerobic	aerobicⓘ	no	98.12	yes
125438	spore-forming	spore-formingⓘ	no	54.91	no
125438	thermophilic	thermophileⓘ	no	87.76	no
125438	flagellated	motile2+ⓘ	no	80.70	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Genetics	Genomic insights into tigecycline non-susceptibility in Clostridioides difficile: the role of the Tet P determinant and efflux mechanisms.	Dang Z, Xia P, Huang J, Yang B, Liao J, Han Q, Xia Y.	BMC Microbiol	10.1186/s12866-025-04143-9	2025
	Comparative Genomic and Physiological Analysis against Clostridium scindens Reveals Eubacterium sp. c-25 as an Atypical Deoxycholic Acid Producer of the Human Gut Microbiota.	Song I, Gotoh Y, Ogura Y, Hayashi T, Fukiya S, Yokota A.	Microorganisms	10.3390/microorganisms9112254	2021
	Identification and Characterization of Major Bile Acid 7alpha-Dehydroxylating Bacteria in the Human Gut.	Kim KH, Park D, Jia B, Baek JH, Hahn Y, Jeon CO.	mSystems	10.1128/msystems.00455-22	2022
Genetics	A computational screen for alternative genetic codes in over 250,000 genomes.	Shulgina Y, Eddy SR.	Elife	10.7554/elife.71402	2021
	BaiCD gene cluster abundance is negatively correlated with Clostridium difficile infection.	Solbach P, Chhatwal P, Woltemate S, Tacconelli E, Buhl M, Gerhard M, Thoeringer CK, Vehreschild MJGT, Jazmati N, Rupp J, Manns MP, Bachmann O, Suerbaum S.	PLoS One	10.1371/journal.pone.0196977	2018
Phylogeny	Berberine alters gut microbial function through modulation of bile acids.	Wolf PG, Devendran S, Doden HL, Ly LK, Moore T, Takei H, Nittono H, Murai T, Kurosawa T, Chlipala GE, Green SJ, Kakiyama G, Kashyap P, McCracken VJ, Gaskins HR, Gillevet PM, Ridlon JM.	BMC Microbiol	10.1186/s12866-020-02020-1	2021
Metabolism	Systematic assessment of secondary bile acid metabolism in gut microbes reveals distinct metabolic capabilities in inflammatory bowel disease.	Heinken A, Ravcheev DA, Baldini F, Heirendt L, Fleming RMT, Thiele I.	Microbiome	10.1186/s40168-019-0689-3	2019
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
	Evolutionary dynamics of Clostridium difficile over short and long time scales.	He M, Sebaihia M, Lawley TD, Stabler RA, Dawson LF, Martin MJ, Holt KE, Seth-Smith HM, Quail MA, Rance R, Brooks K, Churcher C, Harris D, Bentley SD, Burrows C, Clark L, Corton C, Murray V, Rose G, Thurston S, van Tonder A, Walker D, Wren BW, Dougan G, Parkhill J.	Proc Natl Acad Sci U S A	10.1073/pnas.0914322107	2010
Enzymology	Structural and functional characterization of BaiA, an enzyme involved in secondary bile acid synthesis in human gut microbe.	Bhowmik S, Jones DH, Chiu HP, Park IH, Chiu HJ, Axelrod HL, Farr CL, Tien HJ, Agarwalla S, Lesley SA.	Proteins	10.1002/prot.24353	2014
Metabolism	Clostridium scindens: a human gut microbe with a high potential to convert glucocorticoids into androgens.	Ridlon JM, Ikegawa S, Alves JM, Zhou B, Kobayashi A, Iida T, Mitamura K, Tanabe G, Serrano M, De Guzman A, Cooper P, Buck GA, Hylemon PB.	J Lipid Res	10.1194/jlr.m038869	2013
Metabolism	Isolation and characterization of a bile acid inducible 7alpha-dehydroxylating operon in Clostridium hylemonae TN271.	Ridlon JM, Kang DJ, Hylemon PB.	Anaerobe	10.1016/j.anaerobe.2009.05.004	2010
Metabolism	The 'in vivo lifestyle' of bile acid 7alpha-dehydroxylating bacteria: comparative genomics, metatranscriptomic, and bile acid metabolomics analysis of a defined microbial community in gnotobiotic mice.	Ridlon JM, Devendran S, Alves JM, Doden H, Wolf PG, Pereira GV, Ly L, Volland A, Takei H, Nittono H, Murai T, Kurosawa T, Chlipala GE, Green SJ, Hernandez AG, Fields CJ, Wright CL, Kakiyama G, Cann I, Kashyap P, McCracken V, Gaskins HR	Gut Microbes	10.1080/19490976.2019.1618173	2019
Phylogeny	Characterization of Peptacetobacter hominis gen. nov., sp. nov., isolated from human faeces, and proposal for the reclassification of Clostridium hiranonis within the genus Peptacetobacter.	Chen XJ, Wang ZQ, Zhou ZY, Zeng NY, Huang QF, Wang ZW, Tang WL, Zhou HW	Int J Syst Evol Microbiol	10.1099/ijsem.0.003925	2020
Phylogeny	Clostridium hiranonis sp. nov., a human intestinal bacterium with bile acid 7alpha-dehydroxylating activity.	Kitahara M, Takamine F, Imamura T, Benno Y	Int J Syst Evol Microbiol	10.1099/00207713-51-1-39	2001

References

#4987	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 13275
#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) .
#66794	Antje Chang, Lisa Jeske, Sandra Ulbrich, Julia Hofmann, Julia Koblitz, Ida Schomburg, Meina Neumann-Schaal, Dieter Jahn, Dietmar Schomburg: BRENDA, the ELIXIR core data resource in 2021: new developments and updates. Nucleic Acids Res. 49: D498 - D508 2020 ( DOI 10.1093/nar/gkaa1025 , PubMed 33211880 )
#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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Peptacetobacter hiranonis (DSM 13275, JCM 10541, KCTC 15199)

Name and taxonomic classification

Morphology

Culture and growth conditions

Culture medium

Culture temp

Physiology and metabolism

Oxygen tolerance

Pathway annotation

Isolation, sampling and environmental information

Isolation source categories

Isolation

Taxonmaps

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_008151785

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

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