Evidence map›Paper›PMID 22157236›Full record

ArticleGut microbes

Bacterial adaptation to the gut environment favors successful colonization: microbial and metabonomic characterization of a simplified microbiota mouse model.

Enea Rezzonico, Renaud Mestdagh, Michèle Delley, Séverine Combremont, Marc-Emmanuel Dumas, Elaine Holmes, Jeremy Nicholson, Rodrigo Bibiloni

Abstract read
In one paragraph

Article in Gut microbes. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Enea RezzonicoNestlé Research Centre, Bioanalytical Science Department, Lausanne, Switzerland.
Renaud Mestdagh
Michèle Delley
Séverine Combremont
Marc-Emmanuel Dumas
Elaine Holmes
Jeremy Nicholson
Rodrigo Bibiloni

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rodent models harboring a simple yet functional human intestinal microbiota provide a valuable tool to study the relationships between mammals and their bacterial inhabitants. In this study, we aimed to develop a simplified gnotobiotic mouse model containing 10 easy-to-grow bacteria, readily available from culture repositories, and of known genome sequence, that overall reflect the dominant commensal bacterial makeup found in adult human feces. We observed that merely inoculating a mix of fresh bacterial cultures into ex-germ free mice did not guarantee a successful intestinal colonization of the entire bacterial set, as mice inoculated simultaneously with all strains only harbored 3 after 21 d. Therefore, several inoculation procedures were tested and levels of individual strains were quantified using molecular tools. Best results were obtained by inoculating single bacterial strains into individual animals followed by an interval of two weeks before allowing the animals to socialize to exchange their commensal microbes. Through this procedure, animals were colonized with almost the complete bacterial set (9/10). Differences in the intestinal composition were also reflected in the urine and plasma metabolic profiles, where changes in lipids, SCFA, and amino acids were observed. We conclude that adaptation of bacterial strains to the host's gut environment (mono-colonization) may predict a successful establishment of a more complex microbiota in rodents.

Indexed as

Adaptation, PhysiologicalAnimalsBacteriaFecesFemaleGastrointestinal TractMaleMetabolomeMetabolomicsMiceMicrobial ViabilityModels, AnimalPlasmaSex FactorsSpecific Pathogen-Free OrganismsSymbiosis

Identifiers

PMID22157236
PMCPMC3337120

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.