Vallitalea pronyensis (DSM 25904, JCM 18391, FatNI3)

Name: Vallitalea pronyensis (DSM 25904, JCM 18391, FatNI3)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 24771

Type strain

Strain Designation FatNI3

Culture col. no. DSM 25904 JCM 18391 FatNI3

NCBI tax ID(s) 1348613

Special Collections DSMZ JCM

History <- M.-L. Fardeau, Lab. Microbiol. de l'IRD/ESIL, Univ. de Provence et de la Méditerranée, Marseille, France; FatNI3 <- F. Ben Aissa and M.-L. Fardeau {2011} M.-L. Fardeau FatNI3.

Links

Vallitalea pronyensis FatNI3 is an anaerobe bacterium that was isolated from active chimney in a shallow submarine hydrothermal field.

anaerobe genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 396958

JCM 18391,DSM 25904

@ref 20215

Last LPSN update 2026-02-09 11:24:04

Domain Bacteria

Phylum Bacillota

Class Clostridia

Order Eubacteriales

Family Vallitaleaceae

Genus Vallitalea

Species Vallitalea pronyensis

Full scientific name Vallitalea pronyensis Ben Aissa et al. 2014

Morphology

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
21266	SPOROMUSA MEDIUM (MARINE) (DSMZ Medium 311b)		Medium recipe at MediaDive	Name: SPOROMUSA MEDIUM (MARINE) (DSMZ Medium 311b) Composition: NaCl 24.8756 g/l Betaine x H2O 6.66667 g/l Yeast extract 1.99005 g/l Casitone 1.99005 g/l Na2CO3 1.49254 g/l MgSO4 x 7 H2O 0.497512 g/l NH4Cl 0.497512 g/l K2HPO4 0.348259 g/l Na2S x 9 H2O 0.298507 g/l L-Cysteine HCl x H2O 0.298507 g/l CaCl2 x 2 H2O 0.248756 g/l KH2PO4 0.228856 g/l HCl 0.00248756 g/l FeSO4 x 7 H2O 0.00199005 g/l FeCl2 x 4 H2O 0.00149254 g/l NaOH 0.000497512 g/l Sodium resazurin 0.000497512 g/l CoCl2 x 6 H2O 0.000189055 g/l Pyridoxine hydrochloride 9.95025e-05 g/l MnCl2 x 4 H2O 9.95025e-05 g/l ZnCl2 6.96517e-05 g/l p-Aminobenzoic acid 4.97512e-05 g/l Calcium D-(+)-pantothenate 4.97512e-05 g/l Nicotinic acid 4.97512e-05 g/l Riboflavin 4.97512e-05 g/l Thiamine HCl 4.97512e-05 g/l (DL)-alpha-Lipoic acid 4.97512e-05 g/l Na2MoO4 x 2 H2O 3.58209e-05 g/l NiCl2 x 6 H2O 2.38806e-05 g/l Biotin 1.99005e-05 g/l Folic acid 1.99005e-05 g/l H3BO3 5.97015e-06 g/l Na2WO4 x 2 H2O 3.9801e-06 g/l Na2SeO3 x 5 H2O 2.98507e-06 g/l CuCl2 x 2 H2O 1.99005e-06 g/l Vitamin B12 9.95025e-07 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)
21266	positive	growth	30
67770	positive	growth	37

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
21266	anaerobe
125439	facultative anaerobe	93.7

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Environmental	#Aquatic	#Hydrothermal vent
#Environmental	#Aquatic	#Thermal spring
#Condition	#Thermophilic (>45°C)	-

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
21266	active chimney in a shallow submarine hydrothermal field	New Caledonia, Noumea, Prony Bay	France	FRA	Europe
67770	Hydrothermal chimney in Prony Bay	New Caledonia	French Overseas	FRA

Taxonmaps

69479

Global distribution of 16S sequence KC876639 (>99% sequence identity) for Vallitalea pronyensis subclade from Microbeatlas

Aquatic Samples	67
Soil Samples
Animal Samples	8
Plant Samples
Total Samples	75

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
21266	1	Risk group (German classification)

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM1814144v1 assembly for Vallitalea pronyensis FatNI3	complete	GCA_018141445	1348613.3	2994834431	1348613	94.15

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
21266	Vallitalea sp. Ni3 16S ribosomal RNA gene, partial sequence	KC876639	1480		1348613

GC content

@ref	GC-content (mol%)	Method
21266	36.6	high performance liquid chromatography (HPLC)

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Vallitalea pronyensis FatNI3
NCBI: GCA_018141445

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	yes	84.50	no
125439	motility	BacteriaNetⓘ	yes	69.30	no
125439	gram_stain	BacteriaNetⓘ	positive	85.90	no
125439	oxygen_tolerance	BacteriaNetⓘ	facultative anaerobe	93.70	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Vallitalea pronyensis FatNI3
NCBI: GCA_018141445.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	65.60	no
125438	anaerobic	anaerobicⓘ	yes	83.50	yes
125438	aerobic	aerobicⓘ	no	87.50	yes
125438	spore-forming	spore-formingⓘ	yes	65.66	no
125438	thermophilic	thermophileⓘ	no	89.34	yes
125438	flagellated	motile2+ⓘ	yes	82.81	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Vallitalea okinawensis sp. nov., isolated from Okinawa Trough sediment and emended description of the genus Vallitalea.	Sun YT, Zhou N, Wang BJ, Liu XD, Jiang CY, Ge X, Liu SJ	Int J Syst Evol Microbiol	10.1099/ijsem.0.003158	2018
Phylogeny	Vallitalea pronyensis sp. nov., isolated from a marine alkaline hydrothermal chimney.	Ben Aissa F, Postec A, Erauso G, Payri C, Pelletier B, Hamdi M, Ollivier B, Fardeau ML	Int J Syst Evol Microbiol	10.1099/ijs.0.055756-0	2014

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 )
#21266	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 25904
#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) .
#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 .
#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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Vallitalea pronyensis (DSM 25904, JCM 18391, FatNI3)

Name and taxonomic classification

Morphology

Culture and growth conditions

Culture medium

Culture temp

Physiology and metabolism

Oxygen tolerance

Isolation, sampling and environmental information

Isolation source categories

Isolation

Taxonmaps

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_018141445

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

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