Pelotalea chapellei (DSM 13688, 172, ATCC 51744)

Name: Pelotalea chapellei (DSM 13688, 172, ATCC 51744)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 5797

Type strain

Strain Designation 172

Culture col. no. DSM 13688 172 ATCC 51744

NCBI tax ID(s) 44671

Special Collections DSMZ

History <- J. D. Coates, Southern Illinois University Carbondale, USA; 172 <- J. D. Coates; {1994}

Links

Pelotalea chapellei 172 is an anaerobe bacterium that was isolated from deep aquifer sediments.

anaerobe genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 49509

DSM 13688,ATCC 51744

@ref 20215

Last LPSN update 2026-02-09 11:19:03

Domain Bacteria

Phylum Thermodesulfobacteriota

Class Desulfuromonadia

Order Geobacterales

Family Geobacteraceae

Genus Pelotalea

Species Pelotalea chapellei

Full scientific name Pelotalea chapellei (Coates et al. 2001) Xu et al. 2022

Synonyms (2)

"Pseudopelobacter chapellei"
Geobacter chapellei

Morphology

Cell morphology

@ref	Gram stain	Confidence
125438	negative	95.294
125439	negative	99.1

Colony morphology

4953

Incubation period3-7 days

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
4953	GEOBACTER SULFURREDUCENS MEDIUM (DSMZ Medium 826)		Medium recipe at MediaDive	Name: GEOBACTER SULFURREDUCENS MEDIUM (DSMZ Medium 826) Composition: Na2-fumarate 7.91296 g/l NaHCO3 2.4728 g/l NH4Cl 1.48368 g/l Na-acetate 0.811078 g/l Na2HPO4 0.593472 g/l KCl 0.098912 g/l MgSO4 x 7 H2O 0.0296736 g/l Nitrilotriacetic acid 0.0148368 g/l NaCl 0.0098912 g/l MnSO4 x H2O 0.0049456 g/l ZnSO4 x 7 H2O 0.00178042 g/l CoSO4 x 7 H2O 0.00178042 g/l CaCl2 x 2 H2O 0.00098912 g/l FeSO4 x 7 H2O 0.00098912 g/l NiCl2 x 6 H2O 0.000296736 g/l AlK(SO4)2 x 12 H2O 0.000197824 g/l CuSO4 x 5 H2O 9.8912e-05 g/l H3BO3 9.8912e-05 g/l Na2MoO4 x 2 H2O 9.8912e-05 g/l Pyridoxine hydrochloride 9.8912e-05 g/l p-Aminobenzoic acid 4.9456e-05 g/l Calcium D-(+)-pantothenate 4.9456e-05 g/l Nicotinic acid 4.9456e-05 g/l Riboflavin 4.9456e-05 g/l Thiamine HCl 4.9456e-05 g/l (DL)-alpha-Lipoic acid 4.9456e-05 g/l Folic acid 1.97824e-05 g/l Biotin 1.97824e-05 g/l Na2WO4 x 2 H2O 3.95648e-06 g/l Na2SeO3 x 5 H2O 2.96736e-06 g/l Vitamin B12 9.8912e-07 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)
4953	positive	growth	25

Physiology and metabolism

Oxygen tolerance

4953

Oxygen toleranceanaerobe

Spore formation

@ref	Spore formation	Confidence
125439		99.1

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Environmental	#Aquatic	#Groundwater
#Environmental	#Aquatic	#Sediment

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
4953	deep aquifer sediments	Atlantic Coastal Plain, South Carolina	USA	USA	North America

Taxonmaps

69479

Global distribution of 16S sequence U41561 (>99% sequence identity) for Geobacter chapellei subclade from Microbeatlas

Aquatic Samples	1
Soil Samples	7
Animal Samples
Plant Samples
Total Samples	8

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
4953	1	Risk group (German classification) According to TRBA 466

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM1853119v1 assembly for Pelotalea chapellei DSM 13688	contig	GCA_018531195	44671.3	3001932971	44671	66.76

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
4953	Geobacter chapellei strain 172 16S ribosomal RNA gene, partial sequence	U41561	1472		44671

GC content

@ref	GC-content (mol%)	Method
4953	50.2	high performance liquid chromatography (HPLC)
4953	51.1	sequence analysis

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Pelotalea chapellei DSM 13688
NCBI: GCA_018531195

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	99.10	no
125439	motility	BacteriaNetⓘ	yes	55.90	no
125439	gram_stain	BacteriaNetⓘ	negative	99.10	no
125439	oxygen_tolerance	BacteriaNetⓘ	facultative aerobe	67.40	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Geobacter chapellei strain DSM 13688
PATRIC: 44671.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	95.29	no
125438	anaerobic	anaerobicⓘ	yes	71.19	yes
125438	spore-forming	spore-formingⓘ	no	78.06	no
125438	aerobic	aerobicⓘ	no	80.01	yes
125438	thermophilic	thermophileⓘ	no	93.32	yes
125438	flagellated	motile2+ⓘ	yes	68.25	no

Literature

References

#4953	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 13688
#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) .
#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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