Caniella muris (DSM 105314, H1, WCA-FA-Sto1-30.01)

Name: Caniella muris (DSM 105314, H1, WCA-FA-Sto1-30.01)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 169745

Type strain

Strain Designation H1, WCA-FA-Sto1-30.01

Culture col. no. DSM 105314 H1 WCA-FA-Sto1-30.01

NCBI tax ID(s) 2941502

Special Collections Mouse-Microbiome 2 DSMZ DZIF

Links

Caniella muris H1 is a mesophilic prokaryote that was isolated from stomach content; 8-week-old wild mouse.

mesophilic genome sequence

Name and taxonomic classification

SI-ID 406246

DSM 105314

@ref 20215

Last LPSN update 2025-12-16 10:10:39

Domain Bacillati

Phylum Actinomycetota

Class Coriobacteriia

Order Coriobacteriales

Family Atopobiaceae

Genus Caniella

Species Caniella muris

Full scientific name Caniella muris Afrizal et al. 2023

BacDive ID	Other strains from **Caniella muris** (2)	Type strain
169746	C. muris CLA-SR-94, DSM 110323 (type strain)
169747	C. muris CLA-SR-156, DSM 110983

Morphology

Cell morphology

@ref	Motility	Confidence
125438		92.5

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
69164	PYG MEDIUM (MODIFIED) (DSMZ Medium 104)		Medium recipe at MediaDive	Name: PYG MEDIUM (MODIFIED) (DSMZ Medium 104) Composition: Yeast extract 10.0 g/l Peptone 5.0 g/l Trypticase peptone 5.0 g/l Beef extract 5.0 g/l Glucose 5.0 g/l L-Cysteine HCl x H2O 0.5 g/l NaHCO3 0.4 g/l NaCl 0.08 g/l K2HPO4 0.04 g/l KH2PO4 0.04 g/l MgSO4 x 7 H2O 0.02 g/l CaCl2 x 2 H2O 0.01 g/l Hemin 0.005 g/l Ethanol 0.0038 g/l Resazurin 0.001 g/l Tween 80 Vitamin K1 NaOH Distilled water
69164	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
69164	positive	growth	37	mesophilic

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	anaerobe	91.5

Spore formation

@ref	Spore formation	Confidence
125439		95

Isolation, sampling and environmental information

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent	Latitude	Longitude
69164	stomach content; 8-week-old wild mouse	Freising	Germany	DEU	Europe	48.6618	12.267 48.6618/12.267

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	NCBI tax ID	Score
66792	Atopobiaceae_gen_nov2_DSM105314 assembly for Caniella muris DSM 105314	contig	GCA_943192985	2941501.3	2941502	51.2

Genome browser: GCA_943192985

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Caniella muris DSM 105314
NCBI: GCA_943192985

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	95.00	no
125439	motility	BacteriaNetⓘ	yes	61.40	no
125439	gram_stain	BacteriaNetⓘ	positive	74.70	no
125439	oxygen_tolerance	BacteriaNetⓘ	anaerobe	91.50	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Caniella sp. DSM 105314 Atopobiaceae_gen_nov2_DSM105314
NCBI: GCA_943192985.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	aerobic	aerobicⓘ	no	96.89	no
125438	gram-positive	gram-positiveⓘ	yes	87.11	no
125438	anaerobic	anaerobicⓘ	yes	88.38	no
125438	spore-forming	spore-formingⓘ	no	83.91	no
125438	thermophilic	thermophileⓘ	no	92.35	yes
125438	flagellated	motile2+ⓘ	no	92.50	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) .
#69164	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 105314
#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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