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Front. Cell. Infect. Microbiol. | doi: 10.3389/fcimb.2019.00392

Early transcriptional landscapes of Chlamydia trachomatis-infected epithelial cells at single cell resolution

  • 1University of Technology Sydney, Australia
  • 2Max Planck Institute for Developmental Biology, Germany
  • 3Institute for Genome Sciences, University of Maryland School of Medicine, United States

Chlamydia are Gram-negative obligate intracellular bacterial pathogens responsible for a variety of diseases in humans and animals worldwide. C. trachomatis causes trachoma (infectious blindness) in disadvantaged populations, and is the most common bacterial sexually transmitted infection in humans, causing reproductive tract disease. Antibiotic therapy successfully treats diagnosed chlamydial infections, however asymptomatic infections are common. High- throughput transcriptomic approaches have explored chlamydial gene expression and infected host cell gene expression. However, these were performed on large cell populations, averaging gene expression profiles across all cells sampled and potentially obscuring biologically relevant subsets of cells. We generated a pilot dataset, applying single cell RNA-Seq (scRNA-Seq) to C. trachomatis infected and mock-infected epithelial cells to assess the utility of single cell approaches to identify early host cell biomarkers of chlamydial infection. 264 time-matched C. trachomatis-infected and mock-infected HEp-2 cells were collected and subjected to scRNA-Seq. After quality control, 200 cells were retained for analysis. Two distinct clusters distinguished 3-hour cells from 6- and 12-hours. Pseudotime analysis identified a possible infection-specific cellular trajectory for Chlamydia-infected cells, while differential expression analyses found temporal expression of metallothioneins and genes involved with cell cycle regulation, innate immune responses, cytoskeletal components, lipid biosynthesis and cellular stress. Changes to the host cell transcriptome at early times of C. trachomatis infection are readily discernible by scRNA-Seq, supporting the utility of single cell approaches to identify host cell biomarkers of chlamydial infection, and to further deconvolute the complex host response to infection.

Keywords: Chlamydia (Chlamydia trachomatis), Infection, single cell, Transcriptomics, bioinformatics

Received: 06 Aug 2019; Accepted: 01 Nov 2019.

Copyright: © 2019 Hayward, Marsh, Humphrys, Huston and Myers. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: PhD. Garry S. A. Myers, University of Technology Sydney, Ultimo, 2007, Australia,