Cervicovaginal microbiome, mucosal immunity, and pathogen factors that contribute to spontaneous clearance of Chlamydia trachomatis

Chlamydia trachomatis (CT) is the most commonly reported bacterial sexually transmitted infection in the U.S.
and untreated infections are a major cause of adverse sequelae, including pelvic inflammatory disease,
infertility, and ectopic pregnancy. Screening programs have failed to curb rising infection rates. As most
infections in women are asymptomatic and screening is only recommended annually, the incidence of CT is
likely higher than reported. While antibiotic therapy is curative, successful biomedical prevention strategies are
lacking. Most CT natural history studies evaluate CT in the short 1-2 week interval between screening and
follow-up for treatment. Few studies have had longer follow-up. Overall, these studies suggest spontaneous
clearance of CT (in the absence of antibiotic treatment) occurs in 11-44% of cases; however, the mechanisms
are poorly understood. The vaginal microbiome (VMB) is a major factor in preventing CT acquisition, and the
VMB may also aid in CT clearance by reducing CT proliferation and promoting effective immune responses.
Thus, identifying modifiable vaginal microenvironmental features that play a role in spontaneous clearance of
CT may lead to novel interventions. This proposal is submitted in response to PA-19-096 “Control of
Sexually Transmitted Infections (STIs) Through a Comprehensive Understanding of the Natural History
of Infection”. We propose to investigate the relations between spontaneous CT clearance and VMB
(structure, function, metabolome), mucosal immunity, and CT serovar-specific features. This proposal will
utilize archived cervicovaginal lavage samples collected from the Longitudinal Study of Vaginal Flora in which
3,620 cisgender women were followed quarterly for one year. Samples were retrospectively screened for CT
after the study concluded and detected CT spontaneous clearance (n=311) and persistence (n=321)
events. The specific aims utilize a repository with a long follow-up and will assess four domains that may drive
the natural history of CT: 1) demographic, clinical, and behavioral factors, 2) vaginal microbiome and
metabolome, 3) mucosal soluble markers of inflammation, 4) CT serovar composition. Our experienced, multi-
disciplinary team will adapt, refine, and apply modern methods in longitudinal epidemiology with machine-
learning and dimension-reduction techniques to assess high-dimensional, multi-omic data. We seek to identify
immunologic, metabolomic, and bacterial candidates that are associated with spontaneous CT clearance. This
epidemiologic study of over 600 archived samples presents the best available resource for identifying likely
natural clearance and persistence mechanisms. Findings from the analyses would provide the cost-benefit
justification for future confirmatory trials and experimental mechanistic studies. The results may lead to new CT
vaccine approaches by pinpointing correlates of protection against clinically-relevant serovars and informing
choice of adjuvants for optimal immune response. The data may also aid the design of antibiotic-sparing
approaches, such as live biotherapeutic formulations, which could enhance CT control programs.

Grant Number: 5R01AI167629-04
NIH Institute/Center: NIH
Principal Investigator: REBECCA BROTMAN