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. 2018 Jun 11;8:8893. doi: 10.1038/s41598-018-27253-z

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© The Author(s) 2018

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Microbiological factors that influence Chlamydia disease modelling. (A) C. pecorum detection via qPCR, at either 3 levels of detection for the urogenital site (not detectable, detectable not quantifiable (<100 copies/µl sample) and detectable and quantifiable (>100 copies/µl sample) or 2 levels of detection for the ocular site (not detectable and detectable). (B) Non-zero copy number of C. pecorum 16 S rRNA genes detected in urogenital and ocular samples via qPCR by clinical disease states. Median values are indicated by the red dashed line. (C) Microbiome compositions at the phylum level of urogenital and ocular sites by clinical disease state. Significances are indicated by *(p < 0.05), **(p < 0.01) or not significantly different (ns).