Marinomonas rhizomae (CECT 7377, NCIMB 14431, IVIA-Po-145)

Name: Marinomonas rhizomae (CECT 7377, NCIMB 14431, IVIA-Po-145)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 168741

Type strain

Strain Designation IVIA-Po-145

Culture col. no. CECT 7377 NCIMB 14431 IVIA-Po-145

NCBI tax ID(s) 491948

Links

Marinomonas rhizomae IVIA-Po-145 is a prokaryote of the family Oceanospirillaceae.

genome sequence 16S sequence

Name and taxonomic classification

SI-ID 376931

CECT 7377,NCIMB 14431

@ref 20215

Last LPSN update 2025-12-16 10:10:25

Domain Pseudomonadati

Phylum Pseudomonadota

Class Gammaproteobacteria

Order Oceanospirillales

Family Oceanospirillaceae

Genus Marinomonas

Species Marinomonas rhizomae

Full scientific name Marinomonas rhizomae Lucas-Elío et al. 2011

Morphology

Cell morphology

@ref	Gram stain	Confidence
125438	negative	98.9
125439	negative	99.6

Culture and growth conditions

Physiology and metabolism

Spore formation

@ref	Spore formation	Confidence
125439		99.9
125438		91.683

Isolation, sampling and environmental information

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
20215	1	Risk group

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM331548v1 assembly for Marinomonas rhizomae CECT 7377	scaffold	GCA_003315485	491948.3	2770939446	491948	70.23
66792	ASM372127v1 assembly for Marinomonas rhizomae IVIA-Po-145	contig	GCA_003721275	491948.4	2837149368	491948	66.79

Genome browser: GCA_003315485

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
20215	Marinomonas rhizomae strain IVIA-Po-145 16S ribosomal RNA gene, partial sequence	EU188443	1426		491948

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Marinomonas rhizomae CECT 7377
NCBI: GCA_003315485

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	99.90	no
125439	motility	BacteriaNetⓘ	yes	70.30	no
125439	gram_stain	BacteriaNetⓘ	negative	99.60	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	86.10	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Marinomonas rhizomae CECT 7377
NCBI: GCA_003315485.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	98.90	no
125438	anaerobic	anaerobicⓘ	no	96.45	no
125438	aerobic	aerobicⓘ	yes	76.27	no
125438	spore-forming	spore-formingⓘ	no	91.68	no
125438	thermophilic	thermophileⓘ	no	96.36	no
125438	flagellated	motile2+ⓘ	yes	82.69	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Marinomonas lutimaris sp. nov., isolated from a tidal flat sediment of the East China Sea.	Gao Y, Wei Y, Wang P	Int J Syst Evol Microbiol	10.1099/ijsem.0.005368	2022
Phylogeny	Marinomonas mangrovi sp. nov., isolated from mangrove sediment.	Zhang DC, Margesin R	Int J Syst Evol Microbiol	10.1099/ijs.0.000136	2015
Phylogeny	Marinomonas alcarazii sp. nov., M. rhizomae sp. nov., M. foliarum sp. nov., M. posidonica sp. nov. and M. aquiplantarum sp. nov., isolated from the microbiota of the seagrass Posidonia oceanica.	Lucas-Elio P, Marco-Noales E, Espinosa E, Ordax M, Lopez MM, Garcias-Bonet N, Marba N, Duarte CM, Sanchez-Amat A	Int J Syst Evol Microbiol	10.1099/ijs.0.027227-0	2010

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 .
#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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Marinomonas rhizomae (CECT 7377, NCIMB 14431, IVIA-Po-145)

Name and taxonomic classification

Morphology

Cell morphology

Culture and growth conditions

Physiology and metabolism

Spore formation

Isolation, sampling and environmental information

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_003315485

16S sequences

Genome-based predictions

Predictions

Literature

Literature

References

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