Slackia piriformis (DSM 22477, JCM 16070, YIT 12062)

Name: Slackia piriformis (DSM 22477, JCM 16070, YIT 12062)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 3068

Type strain

Culture col. no. DSM 22477 JCM 16070 YIT 12062 KCTC 15189

NCBI tax ID(s) 742818 626934

Special Collections DSMZ JCM KCTC Literature strains

History <- Y. Watanabe, Yakult Central Inst. Microbiol. Res., Tokyo, Japan <- F. Nagai and M. Morotomi Y. Watanabe A15 (=YIT 12062).

Links

Slackia piriformis DSM 22477 is an obligate anaerobe, mesophilic, Gram-positive prokaryote that was isolated from human faeces .

Gram-positive rod-shaped obligate anaerobe mesophilic genome sequence 16S sequence

Name and taxonomic classification

SI-ID 401197

JCM 16070,DSM 22477

@ref 20215

Last LPSN update 2026-02-09 11:18:25

Domain Bacteria

Phylum Actinomycetota

Class Coriobacteriia

Order Eggerthellales

Family Eggerthellaceae

Genus Slackia

Species Slackia piriformis

Full scientific name Slackia piriformis Nagai et al. 2010

Morphology

Cell morphology

@ref	Gram stain	Cell length	Cell width	Cell shape	Confidence
29633	positive	0.9-2.6 µm	0.4-1.1 µm	rod-shaped
125438					90.5
125439	negative				98.1

Pigmentation

29633

Productionyes

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
16259	COLUMBIA BLOOD MEDIUM (DSMZ Medium 693)		Medium recipe at MediaDive	Name: COLUMBIA BLOOD MEDIUM (DSMZ Medium 693) Composition: Defibrinated sheep blood 50.0 g/l Columbia agar base
16259	PYG MEDIUM (MODIFIED) (DSMZ Medium 104)		Medium recipe at MediaDive	Name: PYG MEDIUM (modified) (DSMZ Medium 104; with strain-specific modifications) 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 Arginine 3.0 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 Vitamin K1 NaOH Tween 80 Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
16259	positive	growth	37	mesophilic
29633	positive	growth	37	mesophilic
29633	positive	optimum	37	mesophilic
67770	positive	growth	37	mesophilic

Culture pH

@ref	Ability	Type	PH
29633	positive	optimum	7
29633	positive	growth	7

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
16259	obligate anaerobe
29633	anaerobe
125439	facultative anaerobe	98.9

Spore formation

@ref	Spore formation	Confidence
29633
125439		99.8

Observation

29633

Observationaggregates in chains

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
29633	acid phosphatase	+	3.1.3.2
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-glucosidase	-	3.2.1.21	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
16259	-	+	-	-	-	-	-	-	-	-	-	-	+	-	-	-	-	-	+	-	+	+	-	+	+	+	+	-	+

Isolation, sampling and environmental information

Isolation source categories

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

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
16259	human faeces (healthy Japanese adult)	Tokyo	Japan	JPN	Asia
67770	Human feces

Taxonmaps

69479

Global distribution of 16S sequence AB601000 (>99% sequence identity) for Slackia piriformis subclade from Microbeatlas

Aquatic Samples	888
Soil Samples	204
Animal Samples	19381
Plant Samples	65
Total Samples	20538

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
16259	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
67770	Slac_piri_YIT_12062_V1 assembly for Slackia piriformis YIT 12062	scaffold	GCA_000296445	742818.3	2529292933	742818	76.98

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
20218	Slackia piriformis gene for 16S ribosomal RNA, partial sequence	AB601000	1472		742818
16259	Slackia piriformis gene for 16S rRNA, partial sequence, strain: YIT 12062	AB490806	1463		742818

GC content

@ref	GC-content (mol%)	Method
16259	58.3
67770	58.3	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: Slackia piriformis YIT 12062
NCBI: GCA_000296445

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	99.80	no
125439	motility	BacteriaNetⓘ	yes	70.00	no
125439	gram_stain	BacteriaNetⓘ	negative	98.10	no
125439	oxygen_tolerance	BacteriaNetⓘ	facultative anaerobe	98.90	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Slackia piriformis YIT 12062
PATRIC: 742818.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	82.56	yes
125438	anaerobic	anaerobicⓘ	yes	87.41	yes
125438	spore-forming	spore-formingⓘ	no	80.38	no
125438	aerobic	aerobicⓘ	no	94.76	yes
125438	thermophilic	thermophileⓘ	no	88.26	yes
125438	flagellated	motile2+ⓘ	no	90.50	yes

Literature

Topic	Title	Authors	Journal	DOI	Year
Genetics	A Genomic Toolkit for the Mechanistic Dissection of Intractable Human Gut Bacteria.	Bisanz JE, Soto-Perez P, Noecker C, Aksenov AA, Lam KN, Kenney GE, Bess EN, Haiser HJ, Kyaw TS, Yu FB, Rekdal VM, Ha CWY, Devkota S, Balskus EP, Dorrestein PC, Allen-Vercoe E, Turnbaugh PJ.	Cell Host Microbe	10.1016/j.chom.2020.04.006	2020
	Effects of meglumine antimoniate and allopurinol treatment on the fecal microbiome profile in dogs with leishmaniosis.	Marti-Carreras J, Carrasco M, Noguera-Julian M, Francino O, Leal RO, Ferrer L, Oliva G, Molina J, Roura X.	Anim Microbiome	10.1186/s42523-025-00447-3	2025
Phylogeny	Gestational diabetes mellitus and gut microbiota: microbial signatures across different fetal birth weight outcomes and their impact on maternal and neonatal health.	Xia D, Wang H, Wang W.	BMC Pregnancy Childbirth	10.1186/s12884-025-08324-2	2025
	Machine Learning Based Metagenomic Prediction of Inflammatory Bowel Disease.	Mihajlovic A, Mladenovic K, Loncar-Turukalo T, Brdar S.	Stud Health Technol Inform	10.3233/shti210591	2021
	The increased tendency for anemia in traditional Chinese medicine deficient body constitution is associated with the gut microbiome.	Liang Y, Chen Y, Lin Y, Huang W, Qiu Q, Sun C, Yuan J, Xu N, Chen X, Xu F, Shang X, Deng Y, Liu Y, Tan F, He C, Li J, Deng Q, Zhang X, Guan H, Liang Y, Fang X, Jiang X, Han L, Huang L, Yang Z.	Front Nutr	10.3389/fnut.2024.1359644	2024
	Microbial community of civet excreta fed by robusta cherry coffee in Indonesian civet coffee production.	Winarsih S, Hasanah U, Nuraida L, Andarwulan N, Kusuma WA.	J Adv Vet Anim Res	10.5455/javar.2025.l921	2025
	Long-term alterations in gut microbiota following mild COVID-19 recovery: bacterial and fungal community shifts.	Li D, Zhang DY, Chen SJ, Lv YT, Huang SM, Chen C, Zeng F, Chen RX, Zhang XD, Xiong JX, Chen FD, Jiang YH, Chen Z, Mo CY, Chen JJ, Zhu XL, Zhang LJ, Bai FH.	Front Cell Infect Microbiol	10.3389/fcimb.2025.1565887	2025
	Metagenomic Sequencing Analysis Identifies Cross-Cohort Gut Microbial Signatures Associated With Age-Related Macular Degeneration.	Xue W, Peng P, Wen X, Meng H, Qin Y, Deng T, Guo S, Chen T, Li X, Liang J, Zhang F, Xie Z, Jin M, Liang Q, Wei L.	Invest Ophthalmol Vis Sci	10.1167/iovs.64.5.11	2023
	Could Infectious Agents Play a Role in the Onset of Age-related Macular Degeneration? A Scoping Review.	Larsen PP, Dinet V, Delcourt C, Helmer C, Linard M.	Ophthalmol Sci	10.1016/j.xops.2024.100668	2025
Metabolism	Metabolism of Daidzein and Genistein by Gut Bacteria of the Class Coriobacteriia.	Soukup ST, Stoll DA, Danylec N, Schoepf A, Kulling SE, Huch M.	Foods	10.3390/foods10112741	2021
	Disentangling the Progression of Non-alcoholic Fatty Liver Disease in the Human Gut Microbiota.	Wang T, Guo XK, Xu H.	Front Microbiol	10.3389/fmicb.2021.728823	2021
Genetics	A metagenome-wide association study of gut microbiome and visceral fat accumulation.	Nie X, Chen J, Ma X, Ni Y, Shen Y, Yu H, Panagiotou G, Bao Y.	Comput Struct Biotechnol J	10.1016/j.csbj.2020.09.026	2020
	Quantification of Slackia and Eggerthella spp. in Human Feces and Adhesion of Representatives Strains to Caco-2 Cells.	Cho GS, Ritzmann F, Eckstein M, Huch M, Briviba K, Behsnilian D, Neve H, Franz CM.	Front Microbiol	10.3389/fmicb.2016.00658	2016
Genetics	Microbiome Analysis for Wastewater Surveillance during COVID-19.	Brumfield KD, Leddy M, Usmani M, Cotruvo JA, Tien CT, Dorsey S, Graubics K, Fanelli B, Zhou I, Registe N, Dadlani M, Wimalarante M, Jinasena D, Abayagunawardena R, Withanachchi C, Huq A, Jutla A, Colwell RR.	mBio	10.1128/mbio.00591-22	2022
Phylogeny	Hugonella massiliensis gen. nov., sp. nov., genome sequence, and description of a new strictly anaerobic bacterium isolated from the human gut.	Elsawi Z, Togo AH, Beye M, Dubourg G, Andrieu C, Armsrtong N, Richez M, di Pinto F, Bittar F, Labas N, Fournier PE, Raoult D, Khelaifia S.	Microbiologyopen	10.1002/mbo3.458	2017
Phylogeny	Slackia piriformis sp. nov. and Collinsella tanakaei sp. nov., new members of the family Coriobacteriaceae, isolated from human faeces.	Nagai F, Watanabe Y, Morotomi M	Int J Syst Evol Microbiol	10.1099/ijs.0.017533-0	2009

References

#16259	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 22477
#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 )
#26023	IJSEM 2639 2010 ( DOI 10.1099/ijs.0.017533-0 , PubMed 20023061 )
#29633	Barberan A, Caceres Velazquez H, Jones S, Fierer N.: Hiding in Plain Sight: Mining Bacterial Species Records for Phenotypic Trait Information. mSphere 2: 2017 ( DOI 10.1128/mSphere.00237-17 , PubMed 28776041 ) - originally annotated from #26023
#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 .
#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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Slackia piriformis (DSM 22477, JCM 16070, YIT 12062)

Name and taxonomic classification

Morphology

Cell morphology

Pigmentation

Culture and growth conditions

Culture medium

Culture temp

Culture pH

Physiology and metabolism

Oxygen tolerance

Spore formation

Observation

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_000296445

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

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