Evidence map›Paper›PMID 25761873›Full record

ArticlePathogens and disease2015

Chlamydia caviae infection alters abundance but not composition of the guinea pig vaginal microbiota.

Elizabeth Neuendorf, Pawel Gajer, Anne K Bowlin, Patricia X Marques, Bing Ma, Hongqiu Yang, Li Fu, Michael S Humphrys, Larry J Forney, Garry S A Myers and 3 more

Abstract read
In one paragraph

Article in Pathogens and disease, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Biology · 2026
    Article
  2. Study Models forMicroorganisms · 2025
    Review
  3. Article
  4. Article
  5. Article
  6. Article
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  8. Article
  9. Review
  10. Article
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  17. Review
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

13 authors.

Elizabeth NeuendorfInstitute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA.
Pawel GajerInstitute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, USA.
Anne K BowlinArkansas Children's Hospital Research Institute, Little Rock, AR 72202, USA.
Patricia X MarquesDepartment of Microbial Pathogenesis, University of Maryland School of Dentistry, Baltimore, MD 21201, USA.
Bing MaInstitute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, USA.
Hongqiu YangInstitute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA.
Li FuInstitute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA.
Michael S HumphrysInstitute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA.
Larry J ForneyDepartment of Biological Sciences, Institute for Bioinformatics and Evolutionary Studies (IBEST), University of Idaho, Moscow, ID 83843, USA.
Garry S A MyersInstitute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, USA.
Patrik M BavoilDepartment of Biological Sciences, Institute for Bioinformatics and Evolutionary Studies (IBEST), University of Idaho, Moscow, ID 83843, USA.
Roger G RankArkansas Children's Hospital Research Institute, Little Rock, AR 72202, USA.
Jacques RavelInstitute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, USA jravel@som.umaryland.edu.

Funding

Serologic Biomarkers of Human Sexually Transmitted Infection and DiseaseU19AI084044 · NIAID · UNIVERSITY OF MARYLAND BALTIMORE · PI BAVOIL, PATRIK M · 2009 to 2018
$22.8M
Genomics Resources Core (GRC)P30GM103324 · NIGMS · UNIVERSITY OF IDAHO · PI FORNEY, LARRY J · 2013 to 2017
$5.0M
NIAID NIH HHS U19 AI084044NIAID NIH HHS U19AI084044NIGMS NIH HHS P30 GM103324
6 · The paper itself

Abstract

In humans, the vaginal microbiota is thought to be the first line of defense again pathogens including Chlamydia trachomatis. The guinea pig has been extensively used as a model to study chlamydial infection because it shares anatomical and physiological similarities with humans, such as a squamous vaginal epithelium as well as some of the long-term outcomes caused by chlamydial infection. In this study, we aimed to evaluate the guinea pig-C. caviae model of genital infection as a surrogate for studying the role of the vaginal microbiota in the early steps of C. trachomatis infection in humans. We used culture-independent molecular methods to characterize the relative and absolute abundance of bacterial phylotypes in the guinea pig vaginal microbiota in animals non-infected, mock-infected or infected by C. caviae. We showed that the guinea pig and human vaginal microbiotas are of different bacterial composition and abundance. Chlamydia caviae infection had a profound effect on the absolute abundance of bacterial phylotypes but not on the composition of the guinea pig vaginal microbiota. Our findings compromise the validity of the guinea pig-C. caviae model to study the role of the vaginal microbiota during the early steps of sexually transmitted infection.

Indexed as

Disease Models, AnimalMicrobiotaAnimalsChlamydia InfectionsFemaleGuinea PigsReproductive Tract InfectionsVaginaChlamydia trachomatisLactobacillusmicrobiomemodel organismvagina

Identifiers

PMID25761873
PMCPMC4445005

What OpenQuestion holds

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LicenceCC BY-NC
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.