Bacteroides cellulolyticus (DSM 102145, Sanger 22, Sanger_22)

Name: Bacteroides cellulolyticus (DSM 102145, Sanger 22, Sanger_22)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 131625

Type strain

Strain Designation Sanger 22, Sanger_22

Culture col. no. DSM 102145 Sanger 22 Sanger_22 JCM 35042

NCBI tax ID(s) 2981780

Special Collections DSMZ JCM

History DSMZ <- H. Browne, Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, United Kingdom; Sanger_22

Links

Bacteroides cellulolyticus Sanger 22 is a bacterium that was isolated from faeces from healthy human.

genome sequence Bacteria

Name and taxonomic classification

SI-ID 405161

JCM 35042,DSM 102145

@ref 20215

Last LPSN update 2026-05-29 08:37:39

Domain Bacteria

Phylum Bacteroidota

Class Bacteroidia

Order Bacteroidales

Family Bacteroidaceae

Genus Bacteroides

Species Bacteroides cellulolyticus

Full scientific name Bacteroides cellulolyticus Hitch et al. 2022

Morphology

Cell morphology

@ref	Gram stain	Confidence
125439	negative	96.517
125438	negative	94.492

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
23421	CHOPPED MEAT MEDIUM (DSMZ Medium 78)		Medium recipe at MediaDive	Name: CHOPPED MEAT MEDIUM (DSMZ Medium 78) Composition: Ground beef 500.0 g/l Casitone 30.0 g/l Agar 15.0 g/l Ethanol 9.5 g/l (optional) K2HPO4 5.0 g/l Yeast extract 5.0 g/l L-Cysteine HCl 0.5 g/l Haemin 0.005 g/l (optional) Resazurin 0.001 g/l Vitamin K3 0.0005 g/l (optional) Vitamin K1 (optional) NaOH (optional) Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)
23421	positive	growth	37

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125438	anaerobe	91.74
125439	obligate anaerobe	96.781

Spore formation

@ref	Spore formation	Confidence
125439		99.839

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Host	#Human	-
#Host Body Product	#Gastrointestinal tract	#Feces (Stool)

Isolation

@ref	Sample type	Host species	Geographic location	Country	Country ISO 3 Code	Continent
23421	faeces from healthy human	Homo sapiens	Cambridgeshire	United Kingdom	GBR	Europe

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM2556713v1 assembly for Bacteroides cellulolyticus Sanger_22	scaffold	GCA_025567135	2981780.4	8055109053	2981780	68.18

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: ASM2556713v1 assembly for Bacteroides cellulolyticus Sanger_22
NCBI: GCA_025567135

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	gram_stain	BacteriaNetⓘ	negative	96.52	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate anaerobe	96.78	no
125439	motility	BacteriaNetⓘ	no	78.85	no
125439	spore_formation	BacteriaNetⓘ	no	99.84	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Bacteroides cellulolyticus Sanger_22
NCBI: GCA_025567135.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	94.49	no
125438	anaerobic	anaerobicⓘ	yes	91.74	no
125438	aerobic	aerobicⓘ	no	93.73	no
125438	spore-forming	spore-formingⓘ	no	89.17	no
125438	thermophilic	thermophileⓘ	no	93.58	yes
125438	flagellated	motile2+ⓘ	no	89.00	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 )
#23421	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 102145
#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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