Peptoniphilus indolicus (DSM 20464, ATCC 29427, CCM 5987)

Name: Peptoniphilus indolicus (DSM 20464, ATCC 29427, CCM 5987)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 17997

Type strain

Strain Designation R13

Culture col. no. DSM 20464 ATCC 29427 CCM 5987 R13

NCBI tax ID(s) 997350 33030

Special Collections DSMZ

History DSMZ <- ATCC <- G.H. Sorensen, R13

Links

Peptoniphilus indolicus R13 is an anaerobe animal pathogen that was isolated from summer mastitis secretion of heifer.

anaerobe animal pathogen genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 45858

KCTC 15023,ATCC 29427,CCM 5987,DSM 20464,CCUG 17639,NCIMB 702666,NCDO2666,NCTC11088,CCUG 46591

@ref 20215

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

Domain Bacteria

Phylum Bacillota

Class Clostridia

Order Tissierellales

Family Peptoniphilaceae

Genus Peptoniphilus

Species Peptoniphilus indolicus

Full scientific name Peptoniphilus indolicus (Christiansen 1934) Ezaki et al. 2001

Synonyms (4)

Peptostreptococcus indolicus
Peptococcus indolicus
"Micrococcus indolicus"
"Schleiferella indolica"

Morphology

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
8835	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)
8835	positive	growth	37

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
8835	anaerobe
125438	anaerobe	96.36
125439	anaerobe	99.398

Murein

@ref	Murein short key	Type
8835	A21.05	A4ß L-Orn-D-Glu

Pathway annotation

Computationally determined by

@ref	pathway	enzyme coverage	annotated reactions
66794	palmitate biosynthesis	100	22 of 22
66794	methylglyoxal degradation	100	5 of 5
66794	cis-vaccenate biosynthesis	100	2 of 2
66794	adipate degradation	100	2 of 2
66794	butanoate fermentation	100	4 of 4
66794	coenzyme A metabolism	100	4 of 4
66794	CDP-diacylglycerol biosynthesis	100	2 of 2
66794	folate polyglutamylation	100	1 of 1
66794	UDP-GlcNAc biosynthesis	100	3 of 3
66794	biotin biosynthesis	100	4 of 4
66794	L-lactaldehyde degradation	100	3 of 3
66794	anapleurotic synthesis of oxalacetate	100	1 of 1
66794	suberin monomers biosynthesis	100	2 of 2
66794	threonine metabolism	90	9 of 10
66794	CO2 fixation in Crenarchaeota	88.89	8 of 9
66794	chorismate metabolism	88.89	8 of 9
66794	serine metabolism	88.89	8 of 9
66794	isoleucine metabolism	87.5	7 of 8
66794	propanol degradation	85.71	6 of 7
66794	vitamin B1 metabolism	84.62	11 of 13
66794	cellulose degradation	80	4 of 5
66794	pyrimidine metabolism	80	36 of 45
66794	peptidoglycan biosynthesis	80	12 of 15
66794	alanine metabolism	79.31	23 of 29
66794	aspartate and asparagine metabolism	77.78	7 of 9
66794	valine metabolism	77.78	7 of 9
66794	purine metabolism	76.6	72 of 94
66794	glutamate and glutamine metabolism	75	21 of 28
66794	ppGpp biosynthesis	75	3 of 4
66794	acetate fermentation	75	3 of 4
66794	vitamin B6 metabolism	72.73	8 of 11
66794	NAD metabolism	72.22	13 of 18
66794	cardiolipin biosynthesis	71.43	5 of 7
66794	reductive acetyl coenzyme A pathway	71.43	5 of 7
66794	photosynthesis	71.43	10 of 14
66794	tetrahydrofolate metabolism	71.43	10 of 14
66794	phenylalanine metabolism	69.23	9 of 13
66794	degradation of sugar alcohols	68.75	11 of 16
66794	formaldehyde oxidation	66.67	2 of 3
66794	flavin biosynthesis	66.67	10 of 15
66794	molybdenum cofactor biosynthesis	66.67	6 of 9
66794	acetoin degradation	66.67	2 of 3
66794	glycolysis	64.71	11 of 17
66794	glutathione metabolism	64.29	9 of 14
66794	6-hydroxymethyl-dihydropterin diphosphate biosynthesis	62.5	5 of 8
66794	phenylacetate degradation (aerobic)	60	3 of 5
66794	hydrogen production	60	3 of 5
66794	Entner Doudoroff pathway	60	6 of 10
66794	degradation of aromatic, nitrogen containing compounds	58.33	7 of 12
66794	methionine metabolism	57.69	15 of 26
66794	cysteine metabolism	55.56	10 of 18
66794	oxidative phosphorylation	54.95	50 of 91
66794	proline metabolism	54.55	6 of 11
66794	urea cycle	53.85	7 of 13
66794	non-pathway related	52.63	20 of 38
66794	histidine metabolism	51.72	15 of 29
66794	aminopropanol phosphate biosynthesis	50	1 of 2
66794	selenocysteine biosynthesis	50	3 of 6
66794	ketogluconate metabolism	50	4 of 8
66794	tryptophan metabolism	50	19 of 38
66794	sulfopterin metabolism	50	2 of 4
66794	ethanol fermentation	50	1 of 2
66794	toluene degradation	50	2 of 4
66794	glycogen biosynthesis	50	2 of 4
66794	arginine metabolism	50	12 of 24
66794	tyrosine metabolism	50	7 of 14
66794	phenylmercury acetate degradation	50	1 of 2
66794	lipid metabolism	48.39	15 of 31
66794	lysine metabolism	47.62	20 of 42
66794	leucine metabolism	46.15	6 of 13
66794	citric acid cycle	42.86	6 of 14
66794	ubiquinone biosynthesis	42.86	3 of 7
66794	starch degradation	40	4 of 10
66794	arachidonate biosynthesis	40	2 of 5
66794	propionate fermentation	40	4 of 10
66794	glycine metabolism	40	4 of 10
66794	ethylmalonyl-CoA pathway	40	2 of 5
66794	4-hydroxyphenylacetate degradation	40	4 of 10
66794	phenylpropanoid biosynthesis	38.46	5 of 13
66794	isoprenoid biosynthesis	38.46	10 of 26
66794	C4 and CAM-carbon fixation	37.5	3 of 8
66794	gluconeogenesis	37.5	3 of 8
66794	pentose phosphate pathway	36.36	4 of 11
66794	heme metabolism	35.71	5 of 14
66794	glycolate and glyoxylate degradation	33.33	2 of 6
66794	IAA biosynthesis	33.33	1 of 3
66794	nitrate assimilation	33.33	3 of 9
66794	acetyl CoA biosynthesis	33.33	1 of 3
66794	d-mannose degradation	33.33	3 of 9
66794	enterobactin biosynthesis	33.33	1 of 3
66794	octane oxidation	33.33	1 of 3
66794	degradation of hexoses	33.33	6 of 18
66794	pantothenate biosynthesis	33.33	2 of 6
66794	degradation of pentoses	32.14	9 of 28
66794	degradation of sugar acids	32	8 of 25
66794	coenzyme M biosynthesis	30	3 of 10
66794	phenol degradation	30	6 of 20
66794	benzoyl-CoA degradation	28.57	2 of 7
66794	polyamine pathway	26.09	6 of 23
66794	cyclohexanol degradation	25	1 of 4
66794	lactate fermentation	25	1 of 4
66794	CMP-KDO biosynthesis	25	1 of 4
66794	sulfate reduction	23.08	3 of 13
66794	ascorbate metabolism	22.73	5 of 22
66794	lipid A biosynthesis	22.22	2 of 9
66794	allantoin degradation	22.22	2 of 9
66794	4-hydroxymandelate degradation	22.22	2 of 9

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Infection	#Disease	-
#Host	#Mammals	#Bovinae (Cow, Cattle)
#Host Body Product	#Fluids	-

Isolation

8835

Sample typesummer mastitis secretion of heifer

Taxonmaps

69479

Global distribution of 16S sequence GU993268 (>99% sequence identity) for Peptoniphilus indolicus from Microbeatlas

Aquatic Samples	94
Soil Samples	203
Animal Samples	1754
Plant Samples	32
Total Samples	2083

Interaction and safety

Risk assessment

@ref	Pathogenicity animal	Biosafety level	Biosafety level comment
8835		2	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	ASM22731v1 assembly for Peptoniphilus indolicus ATCC 29427	scaffold	GCA_000227315	997350.3	2513237301	997350	12.82

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
20218	Peptoniphilus indolicus strain ATCC 29427 16S ribosomal RNA gene, partial sequence	GU993268	1287		997350
8835	Peptoniphilus indolicus gene for 16S ribosomal RNA, partial sequence	D14147	1372		997350

GC content

8835

GC-content (mol%)34.0

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: ASM22731v1 assembly for Peptoniphilus indolicus ATCC 29427
BV-BRC: 997350.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	anaerobe	99.40	no
125439	gram_stain	BacteriaNetⓘ	variable	56.09	no
125439	spore_formation	BacteriaNetⓘ	yes	36.44	no
125439	motility	BacteriaNetⓘ	yes	50.01	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Peptoniphilus indolicus ATCC 29427 ATCC 29427
NCBI: GCA_000227315.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	85.35	no
125438	anaerobic	anaerobicⓘ	yes	96.36	yes
125438	aerobic	aerobicⓘ	no	95.29	no
125438	spore-forming	spore-formingⓘ	no	70.89	no
125438	thermophilic	thermophileⓘ	no	93.34	no
125438	flagellated	motile2+ⓘ	no	82.18	no

Literature

Topic	Title	Authors	Journal	DOI	Year
	Community metabolic modeling of host-microbiota interactions through multi-objective optimization.	Lambert A, Budinich M, Mahe M, Chaffron S, Eveillard D.	iScience	10.1016/j.isci.2024.110092	2024
Genetics	Emerging Aeromonas spp. infections in Europe: characterization of human clinical isolates from German patients.	Schwartz K, Borowiak M, Strauch E, Deneke C, Richter MH, German Aeromonas Study Group.	Front Microbiol	10.3389/fmicb.2024.1498180	2024
Metabolism	Structure of the glycerol phosphate-containing O-polysaccharides and serological studies of the lipopolysaccharides of Proteus mirabilis CCUG 10704 (OE) and Proteus vulgaris TG 103 classified into a new Proteus serogroup, O54.	Kolodziejska K, Perepelov AV, Zablotni A, Drzewiecka D, Senchenkova SN, Zych K, Shashkov AS, Knirel YA, Sidorczyk Z.	FEMS Immunol Med Microbiol	10.1111/j.1574-695x.2006.00084.x	2006
	Development and Validation of a Loop-Mediated Isothermal Amplification (LAMP) Assay for Rapid Detection of Glaesserella (Haemophilus) parasuis.	Pilchova V, Seinige D, Hennig-Pauka I, Buttner K, Abdulmawjood A, Kehrenberg C.	Microorganisms	10.3390/microorganisms9010041	2020
	Insight into bio-metal interface formation in vacuo: interplay of S-layer protein with copper and iron.	Makarova AA, Grachova EV, Neudachina VS, Yashina LV, Bluher A, Molodtsov SL, Mertig M, Ehrlich H, Ehrlich H, Adamchuk VK, Laubschat C, Vyalikh DV.	Sci Rep	10.1038/srep08710	2015
Metabolism	Preservation of Archaeal Surface Layer Structure During Mineralization.	Kish A, Miot J, Lombard C, Guigner JM, Bernard S, Zirah S, Guyot F.	Sci Rep	10.1038/srep26152	2016
Enzymology	Abilities of the mCP Agar method and CRENAME alpha toxin-specific real-time PCR assay to detect Clostridium perfringens spores in drinking water.	Maheux AF, Berube E, Boudreau DK, Villeger R, Cantin P, Boissinot M, Bissonnette L, Bergeron MG.	Appl Environ Microbiol	10.1128/aem.02791-13	2013
	Robust Demarcation of the Family Caryophanaceae (Planococcaceae) and Its Different Genera Including Three Novel Genera Based on Phylogenomics and Highly Specific Molecular Signatures.	Gupta RS, Patel S.	Front Microbiol	10.3389/fmicb.2019.02821	2019
Phylogeny	The completely annotated genome and comparative genomics of the Peptoniphilaceae bacterium str. ING2-D1G, a novel acidogenic bacterium isolated from a mesophilic biogas reactor.	Tomazetto G, Hahnke S, Langer T, Wibberg D, Blom J, Maus I, Puhler A, Klocke M, Schluter A	J Biotechnol	10.1016/j.jbiotec.2017.05.027	2017
	Aeromonas caviae subsp. aquatica subsp. nov., a New Multidrug-Resistant Subspecies Isolated from a Drinking Water Storage Tank.	Moreira VH, Berbert LC, Adesoji AT, Bianco K, Cavalcante JJV, Pellegrino FLPC, Albano RM, Clementino MM, Cardoso AM.	Microorganisms	10.3390/microorganisms13040897	2025
Phylogeny	Characterization of a novel Gram-stain-positive anaerobic coccus isolated from the female genital tract: Genome sequence and description of Murdochiella vaginalis sp. nov.	Diop K, Diop A, Khelaifia S, Robert C, Pinto FD, Delerce J, Raoult D, Fournier PE, Bretelle F, Fenollar F.	Microbiologyopen	10.1002/mbo3.570	2018
Genetics	Non-contiguous finished genome sequence and description of Kallipyga massiliensis gen. nov., sp. nov., a new member of the family Clostridiales Incertae Sedis XI.	Hugon P, Ramasamy D, Robert C, Couderc C, Raoult D, Fournier PE.	Stand Genomic Sci	10.4056/sigs.4047997	2013
Phylogeny	Description of three new Peptoniphilus species cultured in the vaginal fluid of a woman diagnosed with bacterial vaginosis: Peptoniphilus pacaensis sp. nov., Peptoniphilus raoultii sp. nov., and Peptoniphilus vaginalis sp. nov.	Diop K, Diop A, Michelle C, Richez M, Rathored J, Bretelle F, Fournier PE, Fenollar F.	Microbiologyopen	10.1002/mbo3.661	2019
Phylogeny	Anaerosphaera aminiphila gen. nov., sp. nov., a glutamate-degrading, Gram-positive anaerobic coccus isolated from a methanogenic reactor treating cattle waste.	Ueki A, Abe K, Suzuki D, Kaku N, Watanabe K, Ueki K	Int J Syst Evol Microbiol	10.1099/ijs.0.011858-0	2009

References

#8835	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 20464
#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 )
#20218	Verslyppe, B., De Smet, W., De Baets, B., De Vos, P., Dawyndt P.: StrainInfo introduces electronic passports for microorganisms.. Syst Appl Microbiol. 37: 42 - 50 2014 ( DOI 10.1016/j.syapm.2013.11.002 , PubMed 24321274 )
#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 )
#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 )

Rate our new design

Content

About us

Peptoniphilus indolicus (DSM 20464, ATCC 29427, CCM 5987)

Name and taxonomic classification

Morphology

Culture and growth conditions

Culture medium

Culture temp

Physiology and metabolism

Oxygen tolerance

Murein

Pathway annotation

Isolation, sampling and environmental information

Isolation source categories

Isolation

Taxonmaps

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_000227315

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

Help

Social Media