Moving beyond DNA: towards functional analysis of the vaginal microbiome by non-sequencing-based methods

Meta-analysis reveals the vaginal microbiome is a better predictor of earlier than later preterm birth

BACKGROUND

High-throughput sequencing measurements of the vaginal microbiome have yielded intriguing potential relationships between the vaginal microbiome and preterm birth (PTB; live birth prior to 37 weeks of gestation). However, results across studies have been inconsistent.

RESULTS

Here, we perform an integrated analysis of previously published datasets from 12 cohorts of pregnant women whose vaginal microbiomes were measured by 16S rRNA gene sequencing. Of 2039 women included in our analysis, 586 went on to deliver prematurely. Substantial variation between these datasets existed in their definition of preterm birth, characteristics of the study populations, and sequencing methodology. Nevertheless, a small group of taxa comprised a vast majority of the measured microbiome in all cohorts. We trained machine learning (ML) models to predict PTB from the composition of the vaginal microbiome, finding low to modest predictive accuracy (0.28-0.79). Predictive accuracy was typically lower when ML models trained in one dataset predicted PTB in another dataset. Earlier preterm birth (< 32 weeks, < 34 weeks) was more predictable from the vaginal microbiome than late preterm birth (34-37 weeks), both within and across datasets. Integrated differential abundance analysis revealed a highly significant negative association between L. crispatus and PTB that was consistent across almost all studies. The presence of the majority (18 out of 25) of genera was associated with a higher risk of PTB, with L. iners, Prevotella, and Gardnerella showing particularly consistent and significant associations. Some example discrepancies between studies could be attributed to specific methodological differences but not most study-to-study variations in the relationship between the vaginal microbiome and preterm birth.

CONCLUSIONS

We believe future studies of the vaginal microbiome and PTB will benefit from a focus on earlier preterm births and improved reporting of specific patient metadata shown to influence the vaginal microbiome and/or birth outcomes.

Exploring the Microbiome in Human Reproductive Tract: High-Throughput Methods for the Taxonomic Characterization of Microorganisms

Microorganisms are important due to their widespread presence and multifaceted roles across various domains of life, ecology, and industries. In humans, they underlie the proper functioning of multiple systems crucial to well-being, including immunological and metabolic functions. Emerging research addressing the presence and roles of microorganisms within human reproduction is increasingly relevant. Studies implementing new methodologies (e.g., to investigate vaginal, uterine, and semen microenvironments) can now provide relevant insights into fertility, reproductive health, or pregnancy outcomes. In that sense, cutting-edge sequencing techniques, as well as others such as meta-metabolomics, culturomics, and meta-proteomics, are becoming more popular and accessible worldwide, allowing the characterization of microbiomes at unprecedented resolution. However, they frequently involve rather complex laboratory protocols and bioinformatics analyses, for which researchers may lack the required expertise. A suitable pipeline would successfully enable both taxonomic classification and functional profiling of the microbiome, providing easy-to-understand biological interpretations. However, the selection of an appropriate methodology would be crucial, as it directly impacts the reproducibility, accuracy, and quality of the results and observations. This review focuses on the different current microbiome-related techniques in the context of human reproduction, encompassing niches like vagina, endometrium, and seminal fluid. The most standard and reliable methods are 16S rRNA gene sequencing, metagenomics, and meta-transcriptomics, together with complementary approaches including meta-proteomics, meta-metabolomics, and culturomics. Finally, we also offer case examples and general recommendations about the most appropriate methods and workflows and discuss strengths and shortcomings for each technique.

Advances in mass spectrometry technologies to characterize cervicovaginal microbiome functions that impact spontaneous preterm birth

Preterm birth (PTB) is a leading cause of morbidity and mortality in young children. Infection is a major cause of this adverse outcome, particularly in PTBs characterised by spontaneous rupture of membranes, referred to as spontaneous (s)PTB. However, the aetiology of sPTB is not well defined and specific bacteria associated with sPTB differ between studies and at the individual level. This may be due to many factors including a lack of understanding of strain-level differences in bacteria that influence how they function and interact with each other and the host. Metaproteomics and metabolomics are mass spectrometry-based methods that enable the collection of detailed microbial and host functional information. Technological advances in this field have dramatically increased the resolution of these approaches, enabling the simultaneous detection of thousands of proteins or metabolites. These data can be used for taxonomic analysis of vaginal bacteria and other microbes, to understand microbiome-host interactions, and identify diagnostic biomarkers or therapeutic targets. Although these methods have been used to assess host proteins and metabolites, few have characterized the microbial compartment in the context of pregnancy. The utilisation of metaproteomic and metabolomic-based approaches has the potential to vastly improve our understanding of the mechanisms leading to sPTB.