Exploring Immunome and Microbiome Interplay in Reproductive Health: Current Knowledge, Challenges, and Novel Diagnostic Tools

Abstract

The dynamic interplay between the immunome and microbiome in reproductive health is a complex and rapidly advancing research field, holding tremendously vast possibilities for the development of reproductive medicine. This immunome-microbiome relationship influences the innate and adaptive immune responses, thereby affecting the onset and progression of reproductive disorders. However, the mechanisms governing these interactions remain elusive and require innovative approaches to gather more understanding. This comprehensive review examines the current knowledge on reproductive microbiomes across various parts of female reproductive tract, with special consideration of bidirectional interactions between microbiomes and the immune system. Additionally, it explores innate and adaptive immunity, focusing on immunoglobulin (Ig) A and IgM antibodies, their regulation, self-antigen tolerance mechanisms, and their roles in immune homeostasis. This review also highlights ongoing technological innovations in microbiota research, emphasizing the need for standardized detection and analysis methods. For instance, we evaluate the clinical utility of innovative technologies such as Phage ImmunoPrecipitation Sequencing (PhIP-Seq) and Microbial Flow Cytometry coupled to Next-Generation Sequencing (mFLOW-Seq). Despite ongoing advancements, we emphasize the need for further exploration in this field, as a deeper understanding of immunome-microbiome interactions holds promise for innovative diagnostic and therapeutic strategies for reproductive health, like infertility treatment and management of pregnancy.

Fig. 1

Distribution of microbiota in the female reproductive tract (FRT). This figure illustrates the microbial composition in the FRT, which is divided into upper and lower reproductive tracts (URT and LRT). The LRT includes the vagina and ectocervix, both lined with a stratified squamous epithelium. This epithelium originates from the basement membrane and culminates in fully keratinized senescent cells. The URTs comprise the endocervix, uterus with endometrium, fallopian tubes, ovaries, peritoneal fluid, and placenta and features a monolayer columnar epithelium. In particular, the transition from stratified squamous epithelium to single columnar epithelium occurs in the “transformation zone” between the ectocervix and endocervix. Microbial abundance was generally higher in the LRT than in the URT, whereas microbial diversity increases from the outermost to the innermost regions. This figure has been adapted from BioRender.com (2023). Source: https://app.Biorender.com .

Fig. 2

Schematic representation of innate and adaptive immune systems. The immune system comprises two main components: innate and adaptive immunity. Innate immunity, depicted on the left, provides a rapid, nonspecific initial defense against various pathogens, and includes cell types like macrophages, dendritic cells, granulocytes, natural killer cells, and mast cells. The adaptive immune system, shown on the right, offers highly specific protection and involves T and B lymphocytes, with CD8+ T cells (cytotoxic T-lymphocytes) and CD4+ T cells (helper T cells) among its key components. In the middle, the activation of T and B cells is predominantly orchestrated through the stimulation of dendritic cells, macrophages, and natural killer T cells, underscoring the central role of innate immunity in modulating adaptive immune responses. Figure created using BioRender.com (2023). Source: https://app.Biorender.com .

Fig. 3

Interactions between microbiota in the reproductive and immune systems. The figure illustrates the mechanisms that govern the generation of IgA and IgM within the reproductive system and how these immunoglobulins, in turn, influence the microbiota. Microbiome-derived factors interact with pattern recognition receptors (PRR), including TLR, Dectin-1, and NOD ligands, while also affecting local and systemic immunity through metabolites. PRRs can directly bind to specific pathogen-associated molecular patterns (PAMPs) on the bacterial surface. Following this interaction, PRRs initiate intracellular signaling through macrophages and dendritic cells, inducing the production of cytokines and chemokines. These molecules, in turn, activate innate immunity through various innate immune cells, producing both pro- and anti-inflammatory responses for microbiota maintenance. The activation of CD4+ T cells by bacteria is crucial in initiating adaptive immune responses. This process involves the presentation of bacterial antigens to CD4+ T cells by antigen-presenting cells (APCs). CD4+ T cells, recognizing the antigens, are co-stimulated by cytokines produced by dendritic cells. Activated CD4 T cells differentiate into various effector cell types, such as regulatory T cells (Tregs), follicular helper T cells (Tfh), and T-helper 17 cells (Th17). Depending on the cytokine microenvironment, cytokines participate in antigen recognition and immune response regulation. These interactions facilitate B cell differentiation into plasma cells, which produce IgA and IgM, thereby contributing to the production of secretory IgA (sIgA) and secretory IgM (sIgM) via pIgR and FcμR receptors, consequently maintaining microbiota homeostasis. In addition, antimicrobial peptides (AMPs) and mucins play multifaceted roles in immunity, including direct antimicrobial defense, modulation of immune responses, influence on the generation of immunoglobulins (IgA and IgM), and contribution to the maintenance of immune tolerance and homeostasis. This figure was adapted from studies on immune interactions of the gut microbiota and was created using BioRender.com (2023). Source: https://app.Biorender.com .

Fig. 4.

Schematic of mFLOW-Seq for identifying microbiota targeted by host antibodies in biological samples. The process involves several key steps. Isolation of bacteria: bacteria are extracted from the biological samples. Incubation with antibodies: The isolated bacteria are then incubated with fluorescently labeled secondary antibodies, specifically anti-IgA, anti-IgM, and anti-IgG. FACS: employed to segregate the bacterial populations into two groups: IgA +/− , IgM +/− , and IgG +/− according to antibodies bound to bacteria. Microbiota analysis: the sorted bacterial populations are subjected to 16S rRNA gene/metagenomic sequencing. This sequencing helps identify which microbes are enriched in the Ig fraction, revealing microbiota and immunome interactions. This figure was created using BioRender.com (2023). Source: https://app.Biorender.com .

Fig. 5.

Overview of PhIP-Seq methodology. The PhIP-Seq methodology involves four key steps. (1) Phage library construction: Downloading or designing a protein database and utilizing bioinformatics tools to generate overlapping peptide sequences from microbiome database proteins. Synthesis of an oligonucleotide library encoding the peptide sequences. PCR-amplify the oligonucleotide library with adapters for cloning into the T7Select 10–3b mid-copy phage display system. (2) Propagation of phage library: The phage library amplified using Escherichia coli BLT 5403 to ensure library diversity and sufficient phage clones for subsequent experiments and sequencing. (3) Patient antibody–antigen interaction: Patient samples containing antibodies are incubated with the amplified phage library for specific interactions. (4) Phage immunoprecipitation and data analysis: Patient samples and their antigens are used in phage immunoprecipitation reactions to capture antibodies and their bound phages on beads coated with proteins A, M, and G. DNA recovered from the immunoprecipitated phage. IgA, IgM, and IgG contents in each sample quantified using ELISA for antibody input normalization. Amplify the library of peptide-encoding DNA sequences directly from the immunoprecipitate. PCR-amplified DNA, sample-specific barcodes, and sequencing adapters for NGS. Pool-barcoded amplicons for sequencing using NGS. (5) Data analysis and validation: Multiplexed data are aligned to reference sequences to create a count matrix. Statistical analysis identifies peptide enrichments, facilitating project-specific investigations, such as identifying common autoantigens, validating microbe-specific epitopes, and identifying potential biomarkers. This methodology provides a comprehensive approach for analyzing antibody epitopes and their association with microbiota. Figure adapted from BioRender.com (2023). Source: https://app.Biorender.com .