Cite this strain

"Bittarella massiliensis" (DSM 101081, GD6)

BacDive ID 169699

Type strain

Strain Designation GD6

Culture col. no. DSM 101081 GD6

Special Collections Cadoret human gut DSMZ

"Bittarella massiliensis" GD6 is a mesophilic prokaryote that was isolated from human stool specimen.

mesophilic genome sequence

Name and taxonomic classification

Culture Collection Numbers

DSM 101081 GD6

@ref 20215

Last LPSN update 2025-12-16 10:10:38

Domain Bacillati

Phylum Bacillota

Class Clostridia

Order Eubacteriales

Family Oscillospiraceae

Genus "Bittarella"

Species "Bittarella massiliensis"

Full scientific name Bittarella massiliensis Durand et al. 2017

BacDive ID	Other strains from "Bittarella massiliensis" (1)	Type strain
2675	". massiliensis" DSM 4029, ATCC 29733, VPI C48-50

Morphology

Cell morphology

@ref	Gram stain	Confidence
125439	negative	92.3

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
69085	FASTIDIOUS ANAEROBE BROTH (DSMZ Medium 1203a)		Medium recipe at MediaDive	Name: FASTIDIOUS ANAEROBE BROTH (DSMZ Medium 1203a) Composition: Fastidious Anaerobe Basal Broth 35.4 g/l Deionized water

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
69085	positive	growth	37	mesophilic

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125438	anaerobe	92.562
125439	anaerobe	99.9

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
68380	29016 ChEBI	arginine	-	hydrolysis	from API rID32A
68380	16024 ChEBI	D-mannose	-	fermentation	from API rID32A
68380	29985 ChEBI	L-glutamate	-	degradation	from API rID32A
68380	17632 ChEBI	nitrate	-	reduction	from API rID32A
68380	16634 ChEBI	raffinose	-	fermentation	from API rID32A
68380	27897 ChEBI	tryptophan	-	energy source	from API rID32A
68380	16199 ChEBI	urea	-	hydrolysis	from API rID32A

Metabolite production

@ref	Chebi-ID	Metabolite	Production
68380	35581 ChEBI	indole		from API rID32A

Metabolite tests

@ref	Chebi-ID	Metabolite	Indole test
68380	35581 ChEBI	indole	-	from API rID32A

Enzymes

@ref	Value	Activity	Ec
68380	alanine arylamidase	-	3.4.11.2	from API rID32A
68380	alkaline phosphatase	+	3.1.3.1	from API rID32A
68380	alpha-arabinosidase	-	3.2.1.55	from API rID32A
68380	alpha-fucosidase	-	3.2.1.51	from API rID32A
68380	alpha-galactosidase	-	3.2.1.22	from API rID32A
68380	alpha-glucosidase	+	3.2.1.20	from API rID32A
68380	arginine dihydrolase	-	3.5.3.6	from API rID32A
68380	beta-galactosidase	-	3.2.1.23	from API rID32A
68380	beta-Galactosidase 6-phosphate	-		from API rID32A
68380	beta-glucosidase	-	3.2.1.21	from API rID32A
68380	beta-glucuronidase	-	3.2.1.31	from API rID32A
68380	glutamate decarboxylase	-	4.1.1.15	from API rID32A
68380	glutamyl-glutamate arylamidase	-		from API rID32A
68380	glycin arylamidase	-		from API rID32A
68380	histidine arylamidase	-		from API rID32A
68380	L-arginine arylamidase	-		from API rID32A
68380	leucine arylamidase	-	3.4.11.1	from API rID32A
68380	leucyl glycin arylamidase	-	3.4.11.1	from API rID32A
68380	N-acetyl-beta-glucosaminidase	-	3.2.1.52	from API rID32A
68380	phenylalanine arylamidase	-		from API rID32A
68380	proline-arylamidase	-	3.4.11.5	from API rID32A
68380	pyrrolidonyl arylamidase	-	3.4.19.3	from API rID32A
68380	serine arylamidase	-		from API rID32A
68380	tryptophan deaminase	-	4.1.99.1	from API rID32A
68380	tyrosine arylamidase	-		from API rID32A
68380	urease	-	3.5.1.5	from API rID32A

API rID32A

@ref	URE	ADH (Arg)	alpha GAL	beta GAL	beta-Galactosidase 6-phosphatebeta GP	alpha GLU	beta GLU	alpha ARA	beta GUR	beta-N-Acetyl-beta-glucosaminidasebeta NAG	MNE	RAF	GDC	alpha FUC	Reduction of nitrateNIT	IND	PAL	L-arginine arylamidaseArgA	ProA	LGA	Phenylalanine arylamidasePheA	Leucine arylamidaseLeuA	PyrA	Tyrosine arylamidaseTyrA	Alanine arylamidaseAlaA	Glycin arylamidaseGlyA	Histidine arylamidaseHisA	Glutamyl-glutamate arylamidaseGGA	Serine arylamidaseSerA
69085	-	-	-	-	-	+	-	-	-	-	-	-	-	-	-	-	+	-	-	-	-	-	-	-	-	-	-	-	-

Isolation, sampling and environmental information

Isolation

@ref	Sample type	Country	Country ISO 3 Code	Continent
69085	human stool specimen	France	FRA	Europe

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	Bittarella massiliensis assembly for Bittarella massiliensis (ex Durand et al. 2017) GD6	scaffold	GCA_001486165	1720313.6	2775506834	1720313	72.02

Genome browser: GCA_001486165

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Bittarella massiliensis GD6
NCBI: GCA_001486165

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	70.40	no
125439	motility	BacteriaNetⓘ	yes	53.80	no
125439	gram_stain	BacteriaNetⓘ	negative	92.30	no
125439	oxygen_tolerance	BacteriaNetⓘ	anaerobe	99.90	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Bittarella massiliensis GD6
NCBI: GCA_001486165.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	73.57	no
125438	anaerobic	anaerobicⓘ	yes	92.56	no
125438	aerobic	aerobicⓘ	no	97.68	no
125438	spore-forming	spore-formingⓘ	no	57.33	no
125438	thermophilic	thermophileⓘ	no	93.80	yes
125438	flagellated	motile2+ⓘ	no	84.70	no

Literature

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) .
#68380	Automatically annotated from API rID32A .
#69085	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 101081
#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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