Knoellia locipacati (KACC 15114, JCM 17313, DMZ1)

Name: Knoellia locipacati (KACC 15114, JCM 17313, DMZ1)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 133714

Type strain

Strain Designation DMZ1

Culture col. no. KACC 15114 JCM 17313 DMZ1 NBRC 109775

NCBI tax ID(s) 882824

Special Collections JCM Literature strains

History JCM <-- J.-W. Bae; Dept. of Biol., Kyung Hee Univ., South Korea; DMZ1.

Links

Knoellia locipacati DMZ1 is an aerobe, Gram-positive, rod-shaped bacterium that was isolated from soil.

Gram-positive rod-shaped aerobe genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 390856

JCM 17313,NBRC 109775

@ref 20215

Last LPSN update 2026-05-29 08:38:09

Domain Bacteria

Phylum Actinomycetota

Class Actinomycetes

Order Micrococcales

Family Intrasporangiaceae

Genus Knoellia

Species Knoellia locipacati

Full scientific name Knoellia locipacati Shin et al. 2012

Morphology

Cell morphology

@ref	Gram stain	Cell shape	Confidence
30256	positive	rod-shaped
125438			91
125438	positive		91.886
125439	positive		92.386

Pigmentation

30256

Productionyes

Culture and growth conditions

Culture temp

@ref	Growth	Type	Temperature (°C)
30256	positive	growth	10-37
30256	positive	optimum	30
67770	positive	growth	28

Culture pH

@ref	Ability	Type	PH	PH range
30256	positive	optimum	7.0-8.0
30256	positive	growth	6.0-9.0	alkaliphile

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
30256	aerobe
125439	facultative anaerobe	90.687

Spore formation

@ref	Spore formation	Confidence
125439		95.798

Halophily

@ref	Salt	Growth	Tested relation	Concentration
30256	NaCl	positive	growth	0-5 %
30256	NaCl	positive	optimum	1 %

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
30256	22599 ChEBI	arabinose	+	carbon source
30256	17057 ChEBI	cellobiose	+	carbon source
30256	28757 ChEBI	fructose	+	carbon source
30256	28260 ChEBI	galactose	+	carbon source
30256	18403 ChEBI	L-arabitol	+	carbon source
30256	17716 ChEBI	lactose	+	carbon source
30256	17306 ChEBI	maltose	+	carbon source
30256	29864 ChEBI	mannitol	+	carbon source
30256	37684 ChEBI	mannose	+	carbon source
30256	17814 ChEBI	salicin	+	carbon source
30256	30911 ChEBI	sorbitol	+	carbon source
30256	17992 ChEBI	sucrose	+	carbon source
30256	27082 ChEBI	trehalose	+	carbon source
30256	17151 ChEBI	xylitol	+	carbon source
30256	18222 ChEBI	xylose	+	carbon source

Enzymes

@ref	Value	Activity	Ec
30256	acid phosphatase	+	3.1.3.2
30256	alkaline phosphatase	+	3.1.3.1
30256	catalase	+	1.11.1.6

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Environmental	#Terrestrial	#Soil

Isolation

@ref	Sample type	Country	Country ISO 3 Code	Continent
30256	soil
67770	soil of the Demilitarized Zone	Republic of Korea	KOR	Asia

Taxonmaps

69479

Global distribution of 16S sequence HQ171909 (>99% sequence identity) for Knoellia locipacati from Microbeatlas

Aquatic Samples	682
Soil Samples	727
Animal Samples	2228
Plant Samples	124
Total Samples	3761

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
124043	ASM3953964v1 assembly for Knoellia locipacati JCM 17313	scaffold	GCA_039539645			882824	75.49
66792	ASM799283v1 assembly for Knoellia locipacati NBRC 109775	contig	GCA_007992835	882824.3	3001391077	882824	75.03

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
30256	Knoellia locipacati strain DMZ1 16S ribosomal RNA gene, partial sequence	HQ171909	1448		882824

GC content

@ref	GC-content (mol%)	Method
30256	72.6
67770	72.6	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: ASM3953964v1 assembly for Knoellia locipacati JCM 17313
NCBI: GCA_039539645

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	facultative anaerobe	90.69	no
125439	gram_stain	BacteriaNetⓘ	positive	92.39	no
125439	motility	BacteriaNetⓘ	no	63.81	no
125439	spore_formation	BacteriaNetⓘ	no	95.80	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Knoellia locipacati strain NBRC 109775
PATRIC: 882824.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	91.89	yes
125438	anaerobic	anaerobicⓘ	no	96.72	yes
125438	aerobic	aerobicⓘ	yes	88.03	no
125438	spore-forming	spore-formingⓘ	no	74.82	no
125438	thermophilic	thermophileⓘ	no	96.50	yes
125438	flagellated	motile2+ⓘ	no	91.00	yes

Literature

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Knoellia locipacati sp. nov., from soil of the Demilitarized Zone in South Korea.	Shin NR, Roh SW, Kim MS, Jung MJ, Whon TW, Bae JW	Int J Syst Evol Microbiol	10.1099/ijs.0.031880-0	2011

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 )
#26598	IJSEM 342 2012 ( DOI 10.1099/ijs.0.031880-0 , PubMed 21421930 )
#30256	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 #26598
#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 .
#124043	Isabel Schober, Julia Koblitz: Data extracted from sequence databases, automatically matched based on designation and taxonomy .
#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

Knoellia locipacati (KACC 15114, JCM 17313, DMZ1)

Name and taxonomic classification

Morphology

Cell morphology

Pigmentation

Culture and growth conditions

Culture temp

Culture pH

Physiology and metabolism

Oxygen tolerance

Spore formation

Halophily

Metabolite utilization

Enzymes

Isolation, sampling and environmental information

Isolation source categories

Isolation

Taxonmaps

Interaction and safety

Sequence information

Genome sequences

Genome browser: GCA_039539645

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

Help

Social Media