Cite this strain

"Rubeoparvulum massiliense" (DSM 100479, Mt6)

BacDive ID 160310

Type strain

Strain Designation Mt6

Culture col. no. DSM 100479 Mt6

NCBI tax ID(s) 1631346

Special Collections DSMZ Cadoret human gut

Links

"Rubeoparvulum massiliense" Mt6 is a mesophilic prokaryote that was isolated from stool sample.

mesophilic genome sequence 16S sequence

Name and taxonomic classification

SI-ID 400403

DSM 100479

@ref 20215

Last LPSN update 2025-12-16 10:08:27

Domain Bacillati

Phylum Bacillota

Class Bacilli

Order Caryophanales

Family Bacillaceae

Genus "Rubeoparvulum"

Species "Rubeoparvulum massiliense"

Full scientific name Rubeoparvulum massiliense Tidjani Alou et al. 2017

Morphology

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
67213	COLUMBIA BLOOD MEDIUM (DSMZ Medium 693)		Medium recipe at MediaDive	Name: COLUMBIA BLOOD MEDIUM (DSMZ Medium 693) Composition: Defibrinated sheep blood 50.0 g/l Columbia agar base

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
67213	positive	growth	37	mesophilic

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	anaerobe	91.2

Isolation, sampling and environmental information

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
67213	stool sample	Marseille	France	FRA	Europe

Taxonmaps

69479

Global distribution of 16S sequence LN828926 (>99% sequence identity) for Rubeoparvulum massiliense subclade from Microbeatlas

Aquatic Samples	314
Soil Samples	869
Animal Samples	188
Plant Samples	131
Total Samples	1502

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	Rubeoparvulum massiliensis assembly for Rubeoparvulum massiliense mt6	contig	GCA_001049895	1631346.7	2690315779	1631346	71.24

Genome browser: GCA_001049895

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
67213	Bacillaceae bacterium mt6 partial 16S rRNA gene, strain mt6	LN828926	1538		1631346

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Rubeoparvulum massiliense mt6
NCBI: GCA_001049895

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	yes	66.90	no
125439	motility	BacteriaNetⓘ	no	57.80	no
125439	gram_stain	BacteriaNetⓘ	positive	73.60	no
125439	oxygen_tolerance	BacteriaNetⓘ	anaerobe	91.20	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Rubeoparvulum massiliense mt6
NCBI: GCA_001049895.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	68.03	no
125438	anaerobic	anaerobicⓘ	no	66.58	no
125438	aerobic	aerobicⓘ	no	55.56	no
125438	spore-forming	spore-formingⓘ	yes	79.10	no
125438	thermophilic	thermophileⓘ	no	76.44	yes
125438	flagellated	motile2+ⓘ	yes	71.67	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Genetics	Gut Bacteria Missing in Severe Acute Malnutrition, Can We Identify Potential Probiotics by Culturomics?	Tidjani Alou M, Million M, Traore SI, Mouelhi D, Khelaifia S, Bachar D, Caputo A, Delerce J, Brah S, Alhousseini D, Sokhna C, Robert C, Diallo BA, Diallo A, Parola P, Golden M, Lagier JC, Raoult D.	Front Microbiol	10.3389/fmicb.2017.00899	2017
Genetics	Rubeoparvulum massiliense gen. nov., sp. nov., a new bacterial genus isolated from the human gut of a Senegalese infant with severe acute malnutrition.	Tidjani Alou M, Rathored J, Lagier JC, Khelaifia S, Michelle C, Sokhna C, Diallo A, Diallo AB, Fournier PE, Raoult D, Edouard S.	New Microbes New Infect	10.1016/j.nmni.2016.11.003	2017

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) .
#67213	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 100479
#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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"Rubeoparvulum massiliense" (DSM 100479, Mt6)

Name and taxonomic classification

Morphology

Culture and growth conditions

Culture medium

Culture temp

Physiology and metabolism

Oxygen tolerance

Isolation, sampling and environmental information

Isolation

Taxonmaps

Interaction and safety

Sequence information

Genome sequences

Genome browser: GCA_001049895

16S sequences

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

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