Neisseria sp. (KCTC 22739, JCM 16337)

Name: Neisseria sp. (KCTC 22739, JCM 16337)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 161762

Type strain

Culture col. no. KCTC 22739 JCM 16337

NCBI tax ID(s) 192066

Special Collections JCM KCTC

Links

JCM 16337 is a mesophilic prokaryote that was isolated from Human dental caries.

mesophilic genome sequence 16S sequence

Name and taxonomic classification

SI-ID 393270

JCM 16337

@ref 20215

Last LPSN update 2025-12-16 10:08:49

Domain Pseudomonadati

Phylum Pseudomonadota

Class Betaproteobacteria

Order Neisseriales

Family Neisseriaceae

Genus Neisseria

Full scientific name Neisseria Trevisan 1885 (Approved Lists 1980)

Morphology

Cell morphology

@ref	Gram stain	Confidence
125438	negative	98.448
125439	positive	98.5
125439		96.6

Culture and growth conditions

Culture temp

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

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	obligate aerobe	90.8

Spore formation

@ref	Spore formation	Confidence
125438		91.923

Isolation, sampling and environmental information

Isolation

67770

Sample typeHuman dental caries

Taxonmaps

69479

Global distribution of 16S sequence GQ203291 (>99% sequence identity) for Kingella from Microbeatlas

Aquatic Samples	403
Soil Samples	61
Animal Samples	4090
Plant Samples	17
Total Samples	4571

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
67770	ASM223744v1 assembly for Neisseria sp. KEM232	complete	GCA_002237445	655307.3	2765235961	655307	96.89
66792	Neisseria sp. KEM232	complete		655307.4		655307	94.5

Genome browser: GCA_002237445

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
67770	Neisseria sp. KEM232 16S ribosomal RNA gene, partial sequence	GQ203291	1423		655307

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Neisseria sp. KEM232
PATRIC: 655307.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	80.90	no
125439	motility	BacteriaNetⓘ	no	96.60	no
125439	gram_stain	BacteriaNetⓘ	positive	98.50	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	90.80	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Neisseria sp. KEM232
PATRIC: 655307.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	98.45	no
125438	anaerobic	anaerobicⓘ	no	93.26	no
125438	spore-forming	spore-formingⓘ	no	91.92	no
125438	aerobic	aerobicⓘ	yes	51.74	no
125438	thermophilic	thermophileⓘ	no	97.93	yes
125438	flagellated	motile2+ⓘ	no	87.04	no

Literature

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 )
#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 .
#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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