Methylocucumis oryzae (MCC 3492, KCTC 15683, JCM 32869)

Name: Methylocucumis oryzae (MCC 3492, KCTC 15683, JCM 32869)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 164401

Type strain

Culture col. no. MCC 3492 KCTC 15683 JCM 32869

NCBI tax ID(s) 1632867

Special Collections JCM KCTC

History M. C. Rahalkar; Agharkar Res. Inst., India; Sn10-6.

Links

Methylocucumis oryzae JCM 32869 is a bacterium that was isolated from Flooded rice field rhizosphere in Junnar.

genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 24595

KCTC:15683,JCM:32869

@ref 20215

Last LPSN update 2026-02-09 11:39:50

Domain Bacteria

Phylum Pseudomonadota

Class Gammaproteobacteria

Order Methylococcales

Family Methylococcaceae

Genus Methylocucumis

Species Methylocucumis oryzae

Full scientific name Methylocucumis oryzae Pandit and Rahalkar 2019

Synonyms (1)

"Candidatus Methylocucumis oryzae"

Morphology

Cell morphology

@ref	Gram stain	Confidence
125439	negative	95.8
125438	negative	98

Culture and growth conditions

Culture temp

@ref	Growth	Type	Temperature (°C)
67770	positive	growth	25

Physiology and metabolism

Spore formation

@ref	Spore formation	Confidence
125439		99.3

Isolation, sampling and environmental information

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
67770	Flooded rice field rhizosphere in Junnar	Maharashtra State	India	IND	Asia

Taxonmaps

69479

Global distribution of 16S sequence KP793700 (>99% sequence identity) for Methylocucumis oryzae subclade from Microbeatlas

Aquatic Samples	1117
Soil Samples	141
Animal Samples	54
Plant Samples	152
Total Samples	1464

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID
67770	Methcu1.0 assembly for Methylocucumis oryzae Sn10-6	contig	GCA_000963695	1632867.4	2648501810	1632867

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
67770	Methylocucumis oryzae strain Sn10-6 16S ribosomal RNA gene, partial sequence	KP793700	1522		1632867

GC content

@ref	GC-content (mol%)	Method
67770	43.9	genome sequence analysis

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Methylocucumis oryzae Sn10-6
NCBI: GCA_000963695

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	99.30	no
125439	motility	BacteriaNetⓘ	no	61.90	no
125439	gram_stain	BacteriaNetⓘ	negative	95.80	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	74.60	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Methylocucumis oryzae Sn10-6
NCBI: GCA_000963695.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	98.00	no
125438	anaerobic	anaerobicⓘ	no	82.30	no
125438	aerobic	aerobicⓘ	yes	73.40	no
125438	spore-forming	spore-formingⓘ	no	88.06	no
125438	thermophilic	thermophileⓘ	no	94.46	no
125438	flagellated	motile2+ⓘ	yes	60.70	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Description of 'Candidatus Methylocucumis oryzae', a novel Type I methanotroph with large cells and pale pink colour, isolated from an Indian rice field.	Pandit PS, Hoppert M, Rahalkar MC	Antonie Van Leeuwenhoek	10.1007/s10482-018-1136-3	2018
Phylogeny	Renaming of 'Candidatus Methylocucumis oryzae' as Methylocucumis oryzae gen. nov., sp. nov., a novel Type I methanotroph isolated from India.	Pandit PS, Rahalkar MC	Antonie Van Leeuwenhoek	10.1007/s10482-018-01218-8	2018

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 )
#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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Methylocucumis oryzae (MCC 3492, KCTC 15683, JCM 32869)

Name and taxonomic classification

Morphology

Cell morphology

Culture and growth conditions

Culture temp

Physiology and metabolism

Spore formation

Isolation, sampling and environmental information

Isolation

Taxonmaps

Interaction and safety

Sequence information

Genome sequences

Genome browser: GCA_000963695

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

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