Reduced Endometrial Ascension and Enhanced Reinfection Associated with IgG Antibodies to Specific Chlamydia trachomatis Proteins in Women at Risk for Chlamydia

Contributions of diverse models of the female reproductive tract to the study of Chlamydia trachomatis-host interactions

Chlamydia trachomatis is a common cause of sexually transmitted infections in humans with devastating sequelae. Understanding of disease on all scales, from molecular details to the immunology underlying pathology, is essential for identifying new ways of preventing and treating chlamydia. Infection models of various complexity are essential to understand all aspects of chlamydia pathogenesis. Cell culture systems allow for research into molecular details of infection, including characterization of the unique biphasic Chlamydia developmental cycle and the role of type-III-secreted effectors in modifying the host environment to allow for infection. Multicell type and organoid culture provide means to investigate how cells other than the infected cells contribute to the control of infection. Emerging comprehensive three-dimensional biomimetic systems may fill an important gap in current models to provide information on complex phenotypes that cannot be modeled in simpler in vitro models.

A Machine Learning-Based Analytic Pipeline Applied to Clinical and Serum IgG Immunoproteome Data To Predict Chlamydia trachomatis Genital Tract Ascension and Incident Infection in Women

We developed a reusable and open-source machine learning (ML) pipeline that can provide an analytical framework for rigorous biomarker discovery. We implemented the ML pipeline to determine the predictive potential of clinical and immunoproteome antibody data for outcomes associated with Chlamydia trachomatis (Ct) infection collected from 222 cis-gender females with high Ct exposure. We compared the predictive performance of 4 ML algorithms (naive Bayes, random forest, extreme gradient boosting with linear booster [xgbLinear], and k-nearest neighbors [KNN]), screened from 215 ML methods, in combination with two different feature selection strategies, Boruta and recursive feature elimination. Recursive feature elimination performed better than Boruta in this study. In prediction of Ct ascending infection, naive Bayes yielded a slightly higher median value of are under the receiver operating characteristic curve (AUROC) 0.57 (95% confidence interval [CI], 0.54 to 0.59) than other methods and provided biological interpretability. For prediction of incident infection among women uninfected at enrollment, KNN performed slightly better than other algorithms, with a median AUROC of 0.61 (95% CI, 0.49 to 0.70). In contrast, xgbLinear and random forest had higher predictive performances, with median AUROC of 0.63 (95% CI, 0.58 to 0.67) and 0.62 (95% CI, 0.58 to 0.64), respectively, for women infected at enrollment. Our findings suggest that clinical factors and serum anti-Ct protein IgGs are inadequate biomarkers for ascension or incident Ct infection. Nevertheless, our analysis highlights the utility of a pipeline that searches for biomarkers and evaluates prediction performance and interpretability. IMPORTANCE Biomarker discovery to aid early diagnosis and treatment using machine learning (ML) approaches is a rapidly developing area in host-microbe studies. However, lack of reproducibility and interpretability of ML-driven biomarker analysis hinders selection of robust biomarkers that can be applied in clinical practice. We thus developed a rigorous ML analytical framework and provide recommendations for enhancing reproducibility of biomarkers. We emphasize the importance of robustness in selection of ML methods, evaluation of performance, and interpretability of biomarkers. Our ML pipeline is reusable and open-source and can be used not only to identify host-pathogen interaction biomarkers but also in microbiome studies and ecological and environmental microbiology research.

Unique T cell signatures are associated with reduced Chlamydia trachomatis reinfection in a highly exposed cohort

Chlamydia trachomatis (CT) is the most common bacterial sexually transmitted infection (STI) in the United States, despite effective antibiotics. Information regarding natural immunity to CT will inform vaccine design. The objectives of this study were to determine immune cell populations and functional features associated with reduced risk of CT reinfection or endometrial CT infection. PBMCs were collected from a cohort of CT-exposed women who were tested for CT and other STIs at the cervix and endometrium (to determine ascension) and were repeatedly tested over the course of a year (to determine reinfection). Mass cytometry identified major immune populations and T cell subsets. Women with CT had increased CD4+ effector memory T cells (TEM) compared to uninfected women. Specifically, Th2, Th17, and Th17 DN CD4+ TEM were increased. Th17 and Th17 DN CD4+ central memory T cells (TCM) were increased in women who did not experience follow-up CT infection, suggesting that these cells may be important for protection. These data indicate that peripheral T cells display distinct features that correlate with natural immunity to CT and suggest that the highly plastic Th17 lineage plays a role in protection against reinfection.

Genetic susceptibility loci for Chlamydia trachomatis endometrial infection influence expression of genes involved in T cell function, tryptophan metabolism and epithelial integrity

Objectives

Identify genetic loci of enhanced susceptibility to Chlamydial trachomatis (Ct) upper genital tract infection in women.

Methods

We performed an integrated analysis of DNA genotypes and blood-derived mRNA profiles from 200 Ct-exposed women to identify expression quantitative trait loci (eQTL) and determine their association with endometrial chlamydial infection using a mediation test. We further evaluated the effect of a lead eQTL on the expression of CD151 by immune cells from women with genotypes associated with low and high whole blood expression of CD151, respectively.

Results

We identified cis-eQTLs modulating mRNA expression of 81 genes (eGenes) associated with altered risk of ascending infection. In women with endometrial infection, eGenes involved in proinflammatory signaling were upregulated. Downregulated eGenes included genes involved in T cell functions pivotal for chlamydial control. eGenes encoding molecules linked to metabolism of tryptophan, an essential chlamydial nutrient, and formation of epithelial tight junctions were also downregulated in women with endometrial infection. A lead eSNP rs10902226 was identified regulating CD151, a tetrospanin molecule important for immune cell adhesion and migration and T cell proliferation. Further in vitro experiments showed that women with a CC genotype at rs10902226 had reduced rates of endometrial infection with increased CD151 expression in whole blood and T cells when compared to women with a GG genotype.

Conclusions

We discovered genetic variants associated with altered risk for Ct ascension. A lead eSNP for CD151 is a candidate genetic marker for enhanced CD4 T cell function and reduced susceptibility.