Chlamydia trachomatis Whole-Proteome Microarray Analysis of The Netherlands Chlamydia Cohort Study

Trends in Chlamydia trachomatis IgG seroprevalence in the general population of the Netherlands over 20 years

OBJECTIVES

To report sex and age-specific Chlamydia trachomatis (Ct) seroprevalence estimates in the general population of the Netherlands between 1996 and 2017 and identify risk factors associated with Ct seropositivity.

METHODS

Participants (n=5158, aged 15-59 years) were included from three independent nationwide population-based serosurveillance studies in 1996, 2007 and 2017. Participants completed a questionnaire on demographics and sexual behaviour. Serum antibodies were analysed using Medac Ct IgG ELISA test. Census weights were assigned to achieve seroprevalence estimates representative of the general Dutch population. Weighted seroprevalence estimates were stratified by gender, age and birth cohort. Trends and risk factors in men and women were identified using multivariable logistic regression.

RESULTS

Weighted overall Ct seroprevalence was 10.5% (95% CI: 9.2% to 12.0%) in women and 5.8% (95% CI: 4.7% to 7.0%) in men. Among women <25 years, there was a non-significant increase in seroprevalence from 5.9% (95% CI 3.7% to 9.2%) in 1996, to 7.6% (95% CI 5.1% to 11.1%) in 2007 and 8.8% (95% CI 5.5% to 13.9%) in 2017. Among women ≥25 years, the seroprevalence significantly decreased from 15.6% (95% CI: 12.2% to 19.7%) in 1996 to 9.5% (95% CI: 7.2% to 12.4%) in 2007 but did not further drop (11.2% (95% CI 8.1% to 15.3%) in 2017). In men, we did not observe trends between study rounds. In both men and women, having a non-Western migration background was a risk factor for seropositivity. In women, having had a prior sexually transmitted infection and ≥2 recent sex partners were risk factors for seropositivity as well.

CONCLUSIONS

We have not found evidence for a decrease in population seroprevalence in those under 25 years old despite decades of intensified testing-and-treatment efforts in the Netherlands. This suggests further monitoring of Ct burden in the general population is needed. If serum banks are used for this, specifically individuals <25 years old and with diverse migration backgrounds should be included.

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.

López Font F, A. Zayas Rodríguez F. Persistence in Chlamydia

Chlamydia spp. are important causes of acute and persistent/chronic infections. All Chlamydia spp. display a unique biphasic developmental cycle alternating between an infectious elementary body (EB) and a replicative form, the reticulate body (RB), followed by the multiplication of RBs by binary fission and progressive differentiation back into EBs. During its intracellular life, Chlamydia employs multiple mechanisms to ensure its persistence inside the host. These include evasion of diverse innate immune responses, modulation of host cell structure and endocytosis, inhibition of apoptosis, activation of pro-signaling pathways, and conversion to enlarged, non-replicative but viable “aberrant bodies” (ABs). Early research described several systems for Chlamydial persistence with a significant number of variables that make a direct comparison of results difficult. Now, emerging tools for genetic manipulations in Chlamydia and advances in global microarray, transcriptomics, and proteomics have opened new and exciting opportunities to understand the persistent state of Chlamydia and link the immune and molecular events of persistence with the pathogenesis of recurrent and chronic Chlamydial infections. This chapter reviews our current understanding and advances in the molecular biology of Chlamydia persistence.

Proteomics approaches: A review regarding an importance of proteome analyses in understanding the pathogens and diseases

Proteomics is playing an increasingly important role in identifying pathogens, emerging and re-emerging infectious agents, understanding pathogenesis, and diagnosis of diseases. Recently, more advanced and sophisticated proteomics technologies have transformed disease diagnostics and vaccines development. The detection of pathogens is made possible by more accurate and time-constrained technologies, resulting in an early diagnosis. More detailed and comprehensive information regarding the proteome of any noxious agent is made possible by combining mass spectrometry with various gel-based or short-gun proteomics approaches recently. MALDI-ToF has been proved quite useful in identifying and distinguishing bacterial pathogens. Other quantitative approaches are doing their best to investigate bacterial virulent factors, diagnostic markers and vaccine candidates. Proteomics is also helping in the identification of secreted proteins and their virulence-related functions. This review aims to highlight the role of cutting-edge proteomics approaches in better understanding the functional genomics of pathogens. This also underlines the limitations of proteomics in bacterial secretome research.

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

BACKGROUND

Previous research revealed antibodies targeting Chlamydia trachomatis (CT) elementary bodies was not associated with reduced endometrial or incident infection in CT-exposed women. However, data on the role of CT protein-specific antibodies in protection are limited.

METHODS

A whole-proteome CT array screening serum pools from CT-exposed women identified 121 immunoprevalent proteins. Individual sera were probed using a focused array. IgG antibody frequencies and endometrial or incident infection relationships were examined using Wilcoxon Rank sum test. The impact of breadth and magnitude of protein-specific IgGs on ascension and incident infection were examined using multivariable stepwise logistic regression. Complementary RNA-sequencing quantified CT gene transcripts in cervical swabs from infected women.

RESULTS

IgG to Pgp3 and CT005 were associated with reduced endometrial infection; anti-CT443, -CT486 and -CT123 were associated with increased incident infection. Increased breadth of protein recognition did not however predict protection from endometrial or incident infection. mRNAs for immunoprevalent CT proteins were highly abundant in the cervix.

CONCLUSIONS

Protein-specific CT antibodies are not sufficient to protect against ascending or incident infection but broad recognition of CT proteins by IgG correlates with cervical CT gene transcript abundance, suggesting CT protein abundance correlates with immunogenicity and signifies their potential as vaccine candidates.

What Can Serology Tell Us About the Burden of Infertility in Women Caused by Chlamydia?

Chlamydia trachomatis (CT) causes pelvic inflammatory disease, which may result in tubal factor infertility (TFI) in women. Serologic assays may be used to determine the proportion of women with and without TFI who have had previous CT infection and to generate estimates of infertility attributable to chlamydia. Unfortunately, most existing CT serologic assays are challenged by low sensitivity and, sometimes, specificity for prior CT infection; however, they are currently the only available tests available to detect prior CT infection. Modeling methods such as finite mixture modeling may be a useful adjunct to quantitative serologic data to obtain better estimates of CT-related infertility. In this article, we review CT serological assays, including the use of antigens preferentially expressed during upper genital tract infection, and suggest future research directions. These methodologic improvements, coupled with creation of new biomarkers for previous CT infection, should improve our understanding of chlamydia's contribution to female infertility.

Development of Helicobacter pylori Whole-Proteome Arrays and Identification of Serologic Biomarkers for Noncardia Gastric Cancer in the MCC-Spain Study

BACKGROUND

Helicobacter pylori (H. pylori) is a bacterial carcinogen and the leading risk factor for noncardia gastric cancer (NCGC). Detecting antibodies against specific H. pylori proteins in peripheral blood can be applied to characterize infection and determine disease associations. Most studies analyzing the association between H. pylori infection and gastric cancer have focused on previously identified antigens, predominantly the virulence factor cytotoxin-associated gene A (CagA). Selecting antigens in an unbiased approach may, however, allow the identification of novel biomarkers.

METHODS

Using a combination of multiple spotting technique and cell-free, on-chip protein expression, we displayed the H. pylori genome (strain 26695) on high-density microarrays. Immunogenic proteins were identified by serum pool incubations and henceforth analyzed in individual samples. To test its applicability, we used sera from a multicase-control (MCC)-Spain study. Serologic responses between NCGC cases and controls were assessed by conditional logistic regression estimating ORs and 95% confidence intervals.

RESULTS

We successfully expressed 93% of the 1,440 H. pylori open reading frames in situ. Of these, 231 (17%) were found to be immunogenic. By comparing 58 NCGC cases with 58 matched controls, we confirmed a higher seroprevalence of CagA among cases (66%) than controls (31%). We further identified a potential novel marker, the Helicobacter outer membrane protein A (HopA).

CONCLUSIONS

In this study, we provide evidence that our H. pylori whole-proteome microarray offers a platform for unbiased de novo identification of serologic biomarkers.

IMPACT

Given its versatile workflow, antibody responses against other H. pylori strains and possible associations with diverse H. pylori-related outcomes can be systematically analyzed.