Evidence map›Paper›PMID 27199748›Full record

ArticleFrontiers in pharmacology2016

Metagenomic Analysis of Antibiotic-Induced Changes in Gut Microbiota in a Pregnant Rat Model.

Imran Khan, Esam I Azhar, Aymn T Abbas, Taha Kumosani, Elie K Barbour, Didier Raoult, Muhammad Yasir

Abstract read
In one paragraph

Article in Frontiers in pharmacology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing 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

34 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Dynamic Changes in the Gut Microbiota During Peripartum in Jennies.Animals : an open access journal from MDPI · 2025
    Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. An altered gut microbiome in pre-eclampsia: cause or consequence.Frontiers in cellular and infection microbiology · 2024
    Review
  10. Article
  11. Article
  12. Review
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Variation of Gut Microbiome in Free-Ranging Female Tibetan Macaques (Animals : an open access journal from MDPI · 2020
    Article
  19. Review
  20. Observational
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

7 authors.

Imran KhanBiochemistry Department, Faculty of Science, King Abdulaziz UniversityJeddah, Saudi Arabia; Special Infectious Agents Unit, King Fahd Medical Research Center, King Abdulaziz UniversityJeddah, Saudi Arabia.
Esam I AzharSpecial Infectious Agents Unit, King Fahd Medical Research Center, King Abdulaziz UniversityJeddah, Saudi Arabia; Medical Laboratory Technology Department, Faculty of Applied Medical Sciences, King Abdulaziz UniversityJeddah, Saudi Arabia.
Aymn T AbbasSpecial Infectious Agents Unit, King Fahd Medical Research Center, King Abdulaziz UniversityJeddah, Saudi Arabia; Biotechnology Research Laboratories, Gastroenterology Surgery Center, Mansoura UniversityMansoura, Egypt.
Taha KumosaniBiochemistry Department, Faculty of Science, King Abdulaziz UniversityJeddah, Saudi Arabia; Biochemistry Department, Faculty of Science - Production of Bioproducts for Industrial Applications Research Group - Experimental Biochemistry Unit, King Fahd Medical Research Center King Abdulaziz UniversityJeddah, Saudi Arabia.
Elie K BarbourFaculty of Agricultural and Food Sciences, American University of BeirutBeirut, Lebanon; Adjunct to Biochemistry Department, Faculty of Science - Production of Bioproducts for Industrial Applications Research Group, King Abdulaziz UniversityJeddah, Saudi Arabia.
Didier RaoultSpecial Infectious Agents Unit, King Fahd Medical Research Center, King Abdulaziz UniversityJeddah, Saudi Arabia; URMITE CNRS-IRD 198 UMR 6236, Faculté de Médecine et de Pharmacie, Université de la MéditerranéeMarseille, France.
Muhammad YasirSpecial Infectious Agents Unit, King Fahd Medical Research Center, King Abdulaziz University Jeddah, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Food and Drug Administration (FDA, USA)-approved category B antibiotics are commonly prescribed to treat infections during pregnancy. The aim of this study was to investigate antibiotic-induced changes in gut microbiota (GM) that occur during pregnancy. The 16S rRNA amplicon deep-sequencing method was used to analyze the effect of category B antibiotics (azithromycin, amoxicillin and cefaclor) on GM during pregnancy using a rat model. The GM composition was substantially modulated by pregnancy and antibiotics administration. Firmicutes, Bacteroidetes, Proteobacteria, Chlamydiae, Actinobacteria, and Cyanobacteria were the dominant phyla. Antibiotic treatment during pregnancy increased the relative abundance of Proteobacteria and reduced Firmicutes. The genera Shigella, Streptococcus, Candidatus Arthromitus, and Helicobacter were significantly (p < 0.05) more abundant during pregnancy. Antibiotics significantly (p < 0.05) reduced the relative abundance of Lactobacillus but increased that of Enterobacter. There was a significant (p < 0.05) decrease in Lactobacillus sp., Lactobacillus gallinarum and Lactobacillus crispatus during pregnancy. Antibiotic treatment reduced bacterial diversity; the lowest number of operational taxonomic units (OTUs) were detected in the cefaclor-treated groups. Antibiotics significantly (p < 0.05) promoted weight gain during pregnancy, and increased relative abundance of Shigella sonnei, Enterococcus hormaechei, and Acinetobacter sp. GM perturbations were accompanied by increases in Proteobacteria abundance and weight gain in pregnancy following antibiotic treatment.

Indexed as

16S rRNA geneamoxicillinazithromycincefaclorgut microbiotapregnancyrats

Identifiers

PMID27199748
PMCPMC4849429

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.