Cite this strain

"Methylobacterium indicum" (MTCC 12298, JCM 30761)

BacDive ID 163873

Type strain

Culture col. no. MTCC 12298 JCM 30761

NCBI tax ID(s) 1775910

Special Collections JCM

Links

Name and taxonomic classification

"Methylobacterium indicum" JCM 30761 is a mesophilic, Gram-negative bacterium that was isolated from Surface sterilized rice seeds.

Gram-negative mesophilic genome sequence 16S sequence Bacteria

Culture Collection Numbers

MTCC 12298 JCM 30761

Last LPSN update 2024-12-09 10:52:42

Domain Bacteria

Phylum Pseudomonadota

Class Alphaproteobacteria

Order Hyphomicrobiales

Family Methylobacteriaceae

Genus Methylobacterium

Species "Methylobacterium indicum"

Full scientific name Methylobacterium indicum Chaudhry et al. 2016

BacDive ID	Other strains from "Methylobacterium indicum" (1)	Type strain
163874	". indicum" JCM 30762, MTCC 12299

Morphology

Cell morphology

@ref	Gram stain	Confidence
125439	negative	92.2
125438	negative	98.302

Culture and growth conditions

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
67770	positive	growth	30	mesophilic

Physiology and metabolism

Spore formation

@ref	Spore formation	Confidence
125439		96.6

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	aerobe	92.2

Isolation, sampling and environmental information

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
67770	Surface sterilized rice seeds	Fazilka, Punjab	India	IND	Asia

Taxonmaps

69479

Global distribution of 16S sequence KP272100 (>99% sequence identity) for Methylobacterium from Microbeatlas

Aquatic Samples	1956
Soil Samples	1060
Animal Samples	4713
Plant Samples	1630
Total Samples	9359

Safety information

Sequence information

GC content

@ref	GC-content (mol%)	Method
67770	69.9	genome sequence analysis

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
67770	Methylobacterium indicum strain SE2.11 16S ribosomal RNA gene, partial sequence	KP272100	1450		1775910

Genome sequences

@ref	Description	Accession	Assembly level	Database	NCBI tax ID
67770	Methylobacterium indicum SE2.11	GCA_001043895	contig		1775910

Genome-based predictions

Predictions

Predictions from Diaspora project based on:
Methylobacterium indicum SE2.11
NCBI: GCA_001043895

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	96.60	no
125439	motility	BacteriaNetⓘ	yes	58.10	no
125439	gram_stain	BacteriaNetⓘ	negative	92.20	no
125439	oxygen_tolerance	BacteriaNetⓘ	aerobe	92.20	no

Predictions from Diaspora project based on:
Methylobacterium indicum SE2.11
NCBI: GCA_001043895.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	98.30	no
125438	anaerobic	anaerobicⓘ	no	95.72	no
125438	aerobic	aerobicⓘ	yes	86.53	no
125438	spore-forming	spore-formingⓘ	no	86.62	no
125438	thermophilic	thermophileⓘ	no	97.50	yes
125438	flagellated	motile2+ⓘ	yes	75.83	no

External links

Literature

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Methylobacterium indicum sp. nov., a facultative methylotrophic bacterium isolated from rice seed.	Chaudhry V, Baindara P, Pal VK, Chawla N, Patil PB, Korpole S	Syst Appl Microbiol	10.1016/j.syapm.2015.12.006	2015

Culture collection no.

Culture collection no.
MTCC 12298
JCM 30761

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 .

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