Name: Endobacterium cereale RZME27
Creator: BacDive
License: https://creativecommons.org/licenses/by/4.0/

Strain identifier

BacDive ID: 167105

Type strain:

Species: Endobacterium cereale

Strain Designation: RZME27

Culture col. no.: LMG 31256, CECT 9794

NCBI tax ID(s): 2663029 (species)

When using BacDive for research please cite our paper

Endobacterium cereale RZME27 is a bacterium of the family Rhizobiaceae.

Bacteria
genome sequence

Information on the name and the taxonomic classification. Name and taxonomic classification

	Last LPSN update	09-12-2024 (DD-MM-YYYY)
	Domain	*Bacteria*
	Phylum	*Pseudomonadota*
	Class	*Alphaproteobacteria*
	Order	*Hyphomicrobiales*
	Family	*Rhizobiaceae*
	Genus	*Endobacterium*
	Species	**Endobacterium cereale**
	Full Scientific Name (LPSN)	Endobacterium cereale corrig. Menéndez et al. 2021

Synonym

Endobacterium cerealis

Information on morphological and physiological properties Morphology

[Ref.: #125438]	Gram stain	negative Confidence in %97.833
[Ref.: #125439]	Gram stain	negative Confidence in %98.7

Information on physiology and metabolism Physiology and metabolism

[Ref.: #125439]

Oxygen tolerance

obligate aerobe Confidence in %98

[Ref.: #125439]

Ability of spore formation

no Confidence in %98

Information on genomic background e.g. entries in nucleic sequence databass Sequence information

Genome sequence information:

	Sequence accession description	Seq. accession number	Assembly level	Sequence database	Associated NCBI tax ID
[Ref.: #66792]	Endobacterium cereale RZME27	GCA_009617585	contig	GenBank ENA	2663029 tax ID	*

Data predicted using genome information as a basis Genome-based predictions

	Model	Trait	Prediction	Confidence in %	In training data
	Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Endobacterium cereale RZME27 NCBI: GCA_009617585.1
[Ref.: #125438]	gram-positive	gram-positiveⓘ	no	97.833	no
[Ref.: #125438]	anaerobic	anaerobicⓘ	no	95.596	no
[Ref.: #125438]	aerobic	aerobicⓘ	yes	75.894	no
[Ref.: #125438]	spore-forming	spore-formingⓘ	no	84.307	no
[Ref.: #125438]	thermophile	thermophilicⓘ	no	98.75	no
[Ref.: #125438]	motile2+	flagellatedⓘ	yes	69.756	no

	Model	Trait	Prediction	Confidence in %
	Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Endobacterium cereale RZME27 NCBI: GCA_009617585
[Ref.: #125439]	BacteriaNet	spore_formationⓘ	no	98
[Ref.: #125439]	BacteriaNet	motilityⓘ	yes	67.2
[Ref.: #125439]	BacteriaNet	gram_stainⓘ	negative	98.7
[Ref.: #125439]	BacteriaNet	oxygen_toleranceⓘ	obligate aerobe	98

Availability in culture collections External links

[Ref.: #20215]

Culture collection no.

LMG 31256, CECT 9794

Literature:

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Genome Analysis of Endobacterium cerealis, a Novel Genus and Species Isolated from Zea mays Roots in North Spain.	Menendez E, Flores-Felix JD, Ramirez-Bahena MH, Igual JM, Garcia-Fraile P, Peix A, Velazquez E	Microorganisms	10.3390/microorganisms8060939	2020	*

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) .

#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 .

* These data were automatically processed and therefore are not curated

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