bioRxivMicrobiologyPreprint
Genital tract microbiome dynamics are associated with time of Chlamydia infection
L. Zhao, S. R. Lundy, F. O. Eko, J. U. Igietseme, Y. O. Omosun
Abstract
BackgroundWe have previously shown that the time of Chlamydia infection was crucial in determining the chlamydial infectivity and pathogenesis. This study aims to determine whether the time of Chlamydia infection affects the genital tract microbiome. This study analyzed mice vaginal, uterine, and ovary/oviduct microbiome with and without Chlamydia infection. The mice were infected with Chlamydia at either 10:00 am (ZT3) or 10:00 pm (ZT15). ResultsThe results showed that mice infected at ZT3 had higher Chlamydia infectivity than those infected at ZT15. There was more variation in the compositional complexity of the vaginal microbiome (alpha diversity) of mice infected at ZT3 than those mice infected at ZT15 throughout the infection within each treatment group, with both Shannon and Simpson diversity index values decreased over time. The analysis of samples collected four weeks post-infection showed that there were significant taxonomical differences (beta diversity) between different parts of the genital tract--vagina, uterus, and ovary/oviduct--and this difference was associated with the time of infection. Firmicutes and Proteobacteria were the most abundant phyla within the microbiome in all three genital tract regions for all the samples collected during this experiment. Additionally, Firmicutes was the dominant phylum in the uterine microbiome of ZT3 Chlamydia infected mice. ConclusionThe results show that the time of infection is associated with the microbial dynamics in the genital tract. And this association is more robust in the upper genital tract than in the vagina. This result implies that more emphasis should be placed on understanding the changes in the microbial dynamics of the upper genital tract over the course of infection.
- organism: mouse
- assay: metagenomics
- research focus: clustering
- research focus: differential expression
- approach: statistical model
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