Keratinibaculum paraultunense (DSM 26752, JCM 18769, KD-1)

Name: Keratinibaculum paraultunense (DSM 26752, JCM 18769, KD-1)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 22970

Type strain

Strain Designation KD-1

Culture col. no. DSM 26752 JCM 18769 KD-1

NCBI tax ID(s) 1278232

Special Collections DSMZ JCM

History <- Y. Huang, Biogas Inst. of Ministry of Agriculture, Chengdu, P.R. China <- Y. Huang and Y. Sun Y. Huang KD-1.

Links

Keratinibaculum paraultunense KD-1 is an anaerobe bacterium that was isolated from soil from grassy marshland.

anaerobe genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 397748

JCM 18769,DSM 26752

@ref 20215

Last LPSN update 2026-02-09 11:23:38

Domain Bacteria

Phylum Bacillota

Class Clostridia

Order Tissierellales

Family Tissierellaceae

Genus Keratinibaculum

Species Keratinibaculum paraultunense

Full scientific name Keratinibaculum paraultunense Huang et al. 2015

Morphology

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
19350	PY + X MEDIUM (DSMZ Medium 104b)		Medium recipe at MediaDive	Name: PY + X MEDIUM (DSMZ Medium 104b) 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 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)
19350	positive	growth	55
67770	positive	growth	55

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
19350	anaerobe
125438	anaerobe	93.351
125439	anaerobe	99.8

Pathway annotation

Computationally determined by

@ref	pathway	enzyme coverage	annotated reactions
66794	coenzyme A metabolism	100	4 of 4
66794	adipate degradation	100	2 of 2
66794	formaldehyde oxidation	100	3 of 3
66794	sulfopterin metabolism	100	4 of 4
66794	folate polyglutamylation	100	1 of 1
66794	CDP-diacylglycerol biosynthesis	100	2 of 2
66794	lipoate biosynthesis	100	5 of 5
66794	anapleurotic synthesis of oxalacetate	100	1 of 1
66794	palmitate biosynthesis	95.45	21 of 22
66794	vitamin B1 metabolism	92.31	12 of 13
66794	chorismate metabolism	88.89	8 of 9
66794	vitamin B12 metabolism	88.24	30 of 34
66794	cellulose degradation	80	4 of 5
66794	aspartate and asparagine metabolism	77.78	7 of 9
66794	serine metabolism	77.78	7 of 9
66794	acetate fermentation	75	3 of 4
66794	biotin biosynthesis	75	3 of 4
66794	ppGpp biosynthesis	75	3 of 4
66794	glycogen biosynthesis	75	3 of 4
66794	peptidoglycan biosynthesis	73.33	11 of 15
66794	NAD metabolism	72.22	13 of 18
66794	photosynthesis	71.43	10 of 14
66794	cardiolipin biosynthesis	71.43	5 of 7
66794	reductive acetyl coenzyme A pathway	71.43	5 of 7
66794	histidine metabolism	68.97	20 of 29
66794	octane oxidation	66.67	2 of 3
66794	d-mannose degradation	66.67	6 of 9
66794	flavin biosynthesis	66.67	10 of 15
66794	CO2 fixation in Crenarchaeota	66.67	6 of 9
66794	UDP-GlcNAc biosynthesis	66.67	2 of 3
66794	acetoin degradation	66.67	2 of 3
66794	selenocysteine biosynthesis	66.67	4 of 6
66794	L-lactaldehyde degradation	66.67	2 of 3
66794	purine metabolism	64.89	61 of 94
66794	glycolysis	64.71	11 of 17
66794	pyrimidine metabolism	64.44	29 of 45
66794	heme metabolism	64.29	9 of 14
66794	tetrahydrofolate metabolism	64.29	9 of 14
66794	degradation of sugar alcohols	62.5	10 of 16
66794	6-hydroxymethyl-dihydropterin diphosphate biosynthesis	62.5	5 of 8
66794	methylglyoxal degradation	60	3 of 5
66794	threonine metabolism	60	6 of 10
66794	metabolism of amino sugars and derivatives	60	3 of 5
66794	hydrogen production	60	3 of 5
66794	factor 420 biosynthesis	60	3 of 5
66794	methionine metabolism	57.69	15 of 26
66794	propanol degradation	57.14	4 of 7
66794	cysteine metabolism	55.56	10 of 18
66794	alanine metabolism	55.17	16 of 29
66794	phenylalanine metabolism	53.85	7 of 13
66794	glutamate and glutamine metabolism	53.57	15 of 28
66794	tryptophan metabolism	52.63	20 of 38
66794	oxidative phosphorylation	50.55	46 of 91
66794	ethanol fermentation	50	1 of 2
66794	CMP-KDO biosynthesis	50	2 of 4
66794	cis-vaccenate biosynthesis	50	1 of 2
66794	pantothenate biosynthesis	50	3 of 6
66794	suberin monomers biosynthesis	50	1 of 2
66794	butanoate fermentation	50	2 of 4
66794	glycine metabolism	50	5 of 10
66794	phenylmercury acetate degradation	50	1 of 2
66794	aminopropanol phosphate biosynthesis	50	1 of 2
66794	ketogluconate metabolism	50	4 of 8
66794	glutathione metabolism	50	7 of 14
66794	urea cycle	46.15	6 of 13
66794	lysine metabolism	45.24	19 of 42
66794	non-pathway related	44.74	17 of 38
66794	molybdenum cofactor biosynthesis	44.44	4 of 9
66794	ubiquinone biosynthesis	42.86	3 of 7
66794	degradation of aromatic, nitrogen containing compounds	41.67	5 of 12
66794	arginine metabolism	41.67	10 of 24
66794	propionate fermentation	40	4 of 10
66794	starch degradation	40	4 of 10
66794	glycogen metabolism	40	2 of 5
66794	degradation of hexoses	38.89	7 of 18
66794	lipid metabolism	38.71	12 of 31
66794	leucine metabolism	38.46	5 of 13
66794	sulfate reduction	38.46	5 of 13
66794	isoprenoid biosynthesis	38.46	10 of 26
66794	isoleucine metabolism	37.5	3 of 8
66794	carnitine metabolism	37.5	3 of 8
66794	pentose phosphate pathway	36.36	4 of 11
66794	polyamine pathway	34.78	8 of 23
66794	acetyl CoA biosynthesis	33.33	1 of 3
66794	IAA biosynthesis	33.33	1 of 3
66794	sulfoquinovose degradation	33.33	1 of 3
66794	valine metabolism	33.33	3 of 9
66794	sphingosine metabolism	33.33	2 of 6
66794	ascorbate metabolism	31.82	7 of 22
66794	phenylpropanoid biosynthesis	30.77	4 of 13
66794	myo-inositol biosynthesis	30	3 of 10
66794	benzoyl-CoA degradation	28.57	2 of 7
66794	degradation of pentoses	28.57	8 of 28
66794	tyrosine metabolism	28.57	4 of 14
66794	arachidonic acid metabolism	27.78	5 of 18
66794	vitamin B6 metabolism	27.27	3 of 11
66794	proline metabolism	27.27	3 of 11
66794	metabolism of disaccharids	27.27	3 of 11
66794	gluconeogenesis	25	2 of 8
66794	toluene degradation	25	1 of 4
66794	cyclohexanol degradation	25	1 of 4
66794	C4 and CAM-carbon fixation	25	2 of 8
66794	nitrate assimilation	22.22	2 of 9
66794	lipid A biosynthesis	22.22	2 of 9

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Environmental	#Terrestrial	#Grassland
#Environmental	#Terrestrial	#Soil

Isolation

@ref	Sample type	Country	Country ISO 3 Code	Continent
19350	soil from grassy marshland	Finland	FIN	Europe
67770	Grassy marshland

Taxonmaps

69479

Global distribution of 16S sequence KC188660 (>99% sequence identity) for Keratinibaculum paraultunense subclade from Microbeatlas

Aquatic Samples	96
Soil Samples	13
Animal Samples	64
Plant Samples	6
Total Samples	179

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
19350	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	ASM1676717v1 assembly for Keratinibaculum paraultunense KD-1	complete	GCA_016767175	1278232.5	8062362333	1278232	97.58
67770	ASM434335v1 assembly for Keratinibaculum paraultunense DSM 26752	scaffold	GCA_004343355	1278232.3	2784746792	1278232	70.83

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
19350	Keratinibaculum paraultunense strain KD-1 16S ribosomal RNA gene, partial sequence	KC188660	1491		1278232

GC content

@ref	GC-content (mol%)	Method
19350	28	thermal denaturation, midpoint method (Tm)

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Keratinibaculum paraultunense DSM 26752
NCBI: GCA_004343355

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	anaerobe	99.80	no
125439	gram_stain	BacteriaNetⓘ	positive	74.80	no
125439	motility	BacteriaNetⓘ	yes	72.00	no
125439	spore_formation	BacteriaNetⓘ	yes	71.80	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Keratinibaculum paraultunense KD-1
NCBI: GCA_016767175.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	63.03	no
125438	anaerobic	anaerobicⓘ	yes	93.35	no
125438	aerobic	aerobicⓘ	no	96.21	no
125438	spore-forming	spore-formingⓘ	yes	57.69	no
125438	thermophilic	thermophileⓘ	yes	57.38	yes
125438	flagellated	motile2+ⓘ	yes	69.40	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Metabolism	Genome-wide analysis of Keratinibaculum paraultunense strain KD-1( T) and its key genes and metabolic pathways involved in the anaerobic degradation of feather keratin.	Wu W, Ma S, Chen R, Huang Y, Deng Y	Arch Microbiol	10.1007/s00203-022-03226-9	2022
Phylogeny	Isolation and characterization of Keratinibaculum paraultunense gen. nov., sp. nov., a novel thermophilic, anaerobic bacterium with keratinolytic activity.	Huang Y, Sun Y, Ma S, Chen L, Zhang H, Deng Y	FEMS Microbiol Lett	10.1111/1574-6968.12184	2013

References

#19350	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 26752
#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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Keratinibaculum paraultunense (DSM 26752, JCM 18769, KD-1)

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_016767175

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

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