Limosilactobacillus reuteri subsp. murium (DSM 110570, LMG 31634, lpuph1)

Name: Limosilactobacillus reuteri subsp. murium (DSM 110570, LMG 31634, lpuph1)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 160080

Type strain

Strain Designation lpuph1

Culture col. no. DSM 110570 LMG 31634 lpuph1

NCBI tax ID(s) 863368

Special Collections DSMZ

Links

Limosilactobacillus reuteri subsp. murium lpuph1 is a mesophilic prokaryote that was isolated from mouse gastrointestinal tract.

mesophilic genome sequence

Name and taxonomic classification

SI-ID 400698

LMG 31634,DSM 110570

@ref 20215

Last LPSN update 2025-12-16 10:08:24

Domain Bacillati

Phylum Bacillota

Class Bacilli

Order Lactobacillales

Family Lactobacillaceae

Genus Limosilactobacillus

Species Limosilactobacillus reuteri subsp. murium

Full scientific name Limosilactobacillus reuteri subsp. murium Li et al. 2021

Morphology

Cell morphology

@ref	Gram stain	Confidence
125439	positive	90.1
125438		90
125438	positive	93.649

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
66984	MRS MEDIUM (DSMZ Medium 11)		Medium recipe at MediaDive	Name: MRS MEDIUM (DSMZ Medium 11) Composition: Glucose 20.0 g/l Casein peptone 10.0 g/l Meat extract 10.0 g/l Na-acetate 5.0 g/l Yeast extract 5.0 g/l (NH4)3 citrate 2.0 g/l K2HPO4 2.0 g/l Tween 80 1.0 g/l MgSO4 x 7 H2O 0.2 g/l MnSO4 x H2O 0.05 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
66984	positive	growth	37	mesophilic

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	microaerophile	93.4

Spore formation

@ref	Spore formation	Confidence
125439		94

Isolation, sampling and environmental information

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
66984	mouse gastrointestinal tract	Lincoln, Nebraska	USA	USA	North America

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM17945v1 assembly for Limosilactobacillus reuteri subsp. murium lpuph1	contig	GCA_000179455	863368.3	2506381017	863368	52.92

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Limosilactobacillus reuteri subsp. murium lpuph1
NCBI: GCA_000179455

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	94.00	no
125439	motility	BacteriaNetⓘ	no	85.30	no
125439	gram_stain	BacteriaNetⓘ	positive	90.10	no
125439	oxygen_tolerance	BacteriaNetⓘ	microaerophile	93.40	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Limosilactobacillus reuteri subsp. murium lpuph1
NCBI: GCA_000179455.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	93.65	no
125438	anaerobic	anaerobicⓘ	no	81.56	no
125438	aerobic	aerobicⓘ	no	94.75	no
125438	spore-forming	spore-formingⓘ	no	89.08	no
125438	thermophilic	thermophileⓘ	no	97.84	no
125438	flagellated	motile2+ⓘ	no	90.00	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Limosilactobacillus balticus sp. nov., Limosilactobacillus agrestis sp. nov., Limosilactobacillus albertensis sp. nov., Limosilactobacillus rudii sp. nov. and Limosilactobacillus fastidiosus sp. nov., five novel Limosilactobacillus species isolated from the vertebrate gastrointestinal tract, and proposal of six subspecies of Limosilactobacillus reuteri adapted to the gastrointestinal tract of specific vertebrate hosts.	Li F, Cheng CC, Zheng J, Liu J, Quevedo RM, Li J, Roos S, Ganzle MG, Walter J.	Int J Syst Evol Microbiol	10.1099/ijsem.0.004644	2021

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) .
#66984	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 110570
#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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Limosilactobacillus reuteri subsp. murium (DSM 110570, LMG 31634, lpuph1)

Name and taxonomic classification

Morphology

Cell morphology

Culture and growth conditions

Culture medium

Culture temp

Physiology and metabolism

Oxygen tolerance

Spore formation

Isolation, sampling and environmental information

Isolation

Interaction and safety

Sequence information

Genome sequences

Genome browser: GCA_000179455

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

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