Evidence map›Paper›PMID 35583200›Full record

ArticleCPT: pharmacometrics & systems pharmacology2022

Modeling the bacterial dynamics in the gut microbiota following an antibiotic-induced perturbation.

Jinju Guk, Antoine Bridier-Nahmias, Mélanie Magnan, Nathalie Grall, Xavier Duval, Olivier Clermont, Etienne Ruppé, Camille d'Humières, Olivier Tenaillon, Erick Denamur and 4 more

Open access · goldAbstract read
In one paragraph

Article in CPT: pharmacometrics & systems pharmacology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.7field-weighted citation impact, top 34% of its field
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

4 citing papers in PubMed, 8 citations in OpenAlex.

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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

14 authors at 1 institution in 1 country.

Jinju GukUniversité de Paris, IAME, INSERM, Paris, France.
Antoine Bridier-NahmiasUniversité de Paris, IAME, INSERM, Paris, France.
Mélanie MagnanUniversité de Paris, IAME, INSERM, Paris, France.
Nathalie GrallUniversité de Paris, IAME, INSERM, Paris, France.
Xavier DuvalUniversité de Paris, IAME, INSERM, Paris, France.
Olivier ClermontUniversité de Paris, IAME, INSERM, Paris, France.
Etienne RuppéUniversité de Paris, IAME, INSERM, Paris, France.
Camille d'HumièresUniversité de Paris, IAME, INSERM, Paris, France.
Olivier TenaillonUniversité de Paris, IAME, INSERM, Paris, France.
Erick DenamurUniversité de Paris, IAME, INSERM, Paris, France.
France MentréUniversité de Paris, IAME, INSERM, Paris, France.ORCID 0000-0002-7045-1275
Jérémie GuedjUniversité de Paris, IAME, INSERM, Paris, France.ORCID 0000-0002-5534-5482
Charles BurdetUniversité de Paris, IAME, INSERM, Paris, France.ORCID 0000-0003-4138-0794
CEREMI study group
Inserm · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent studies have highlighted the importance of ecological interactions in dysbiosis of gut microbiota, but few focused on their role in antibiotic-induced perturbations. We used the data from the CEREMI trial in which 22 healthy volunteers received a 3-day course of ceftriaxone or cefotaxime antibiotics. Fecal samples were analyzed by 16S rRNA gene profiling, and the total bacterial counts were determined in each sample by flux cytometry. As the gut exposure to antibiotics could not be experimentally measured despite a marked impact on the gut microbiota, it was reconstructed using the counts of susceptible Escherichia coli. The dynamics of absolute counts of bacterial families were analyzed using a generalized Lotka-Volterra equations and nonlinear mixed effect modeling. Bacterial interactions were studied using a stepwise approach. Two negative and three positive interactions were identified. Introducing bacterial interactions in the modeling approach better fitted the data, and provided different estimates of antibiotic effects on each bacterial family than a simple model without interaction. The time to return to 95% of the baseline counts was significantly longer in ceftriaxone-treated individuals than in cefotaxime-treated subjects for two bacterial families: Akkermansiaceae (median [range]: 11.3 days [0; 180.0] vs. 4.2 days [0; 25.6], p = 0.027) and Tannerellaceae (13.7 days [6.1; 180.0] vs. 6.2 days [5.4; 17.3], p = 0.003). Taking bacterial interaction as well as individual antibiotic exposure profile into account improves the analysis of antibiotic-induced dysbiosis.

Indexed as

Gastrointestinal MicrobiomeAnti-Bacterial AgentsBacteriaCefotaximeCeftriaxoneDysbiosisHumansRNA, Ribosomal, 16SAnti-Bacterial AgentsCefotaximeCeftriaxoneRNA, Ribosomal, 16S

Identifiers

PMID35583200
PMCPMC9286716
OpenAlexW4280498117

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.