Modulation of the cervix by steroid hormones and commensal microbiome play a central role in the health of the female reproductive tract. Here we describe organ-on-a-chip (Organ Chip) models that recreate the human cervical epithelial-stromal interface with a functional epithelial barrier and production of mucus with biochemical and hormone-responsive properties similar to living cervix. When Cervix Chips are populated with optimal healthy versus dysbiotic microbial communities (dominated by Lactobacillus crispatus and Gardnerella vaginalis, respectively), significant differences in tissue innate immune responses, barrier function, cell viability, proteome, and mucus composition are observed that are similar to those seen in vivo. Thus, human Cervix Organ Chips represent physiologically relevant in vitro models to study cervix physiology and host-microbiome interactions, and hence may be used as a preclinical testbed for development of therapeutic interventions to enhance women’s health.

Glycans modify protein, lipid, and even RNA molecules to form the regulatory outer coat on cells called the glycocalyx. The changes in glycosylation have been linked to the initiation and progression of many diseases. Herein, we report a DIA-based glycomic workflow, termed GlycanDIA, to identify and quantify glycans with high sensitivity and precision. The GlycanDIA workflow combines higher energy collisional dissociation (HCD)-MS/MS and staggered windows for glycomic analysis, which facilitates the sensitivity in identification and precision in quantification compared to conventional glycomic methods. To facilitate its use, we also develop a generic search engine, GlycanDIA Finder, incorporating an iterative decoy searching for confident glycan identification from DIA data. Our results demonstrate that GlycanDIA can distinguish glycan composition and isomers from N-glycans, O-glycans, and human milk oligosaccharides (HMOs), while it also reveals information on low-abundant modified glycans. With the improved sensitivity and precision, we perform experiments to profile N-glycans from RNA samples, which have been underrepresented due to their low abundance. Using this integrative workflow to unravel the N-glycan profile in cellular and tissue glycoRNA samples, we find that RNA-glycans have different abundant forms as compared to protein-glycans and there are also tissue-specific differences, suggesting their distinct functions in biological processes.

Protein-protein interactions in the cell membrane are typically mediated by glycans, with terminal sialic acid often involved in these interactions. To probe the nature of the interactions, we developed quantitative cross-linking methods involving the glycans of the glycoproteins and the polypeptide moieties of proteins. We designed and synthesized biotinylated enrichable cross-linkers that were click-tagged to metabolically incorporate azido-sialic acid on cell surface glycans to allow cross-linking of the azido-glycans with lysine residues on proximal polypeptides. The glycopeptide-peptide cross-links (GPx) were enriched using biotin groups through affinity purification with streptavidin resin beads. Workflows using two linkers, one photocleavable and the other disulfide, were developed and applied to reveal the sialic acid-mediated cell-surface protein networks of PNT2 (prostate) cells. Glycopeptide-peptide pairs were identified, with 12000 GPx linked by sialylated glycoforms revealing interactions between source glycoproteins and nearly 700 target proteins. Protein-protein interactions were characterized by as many as 40 peptide pairs, and the extent of the interactions between proteins was prioritized by the number of GPx. Quantitation was performed by counting the number of GPx that identify the protein pairs. Abundant membrane proteins such as ITGB1 yielded an interactome consisting of around 400 other proteins, which were ranked from the most extensive interaction, having the largest number of GPx, to at least one. The interactome was further confirmed separately by published databases. This tool will enhance our understanding of glycosylation on protein-protein interactions and provide new potential targets for therapeutics.

Glycans modify protein, lipid, and even RNA molecules to form the regulatory outer coat on cells called the glycocalyx. The changes in glycosylation have been linked to the initiation and progression of many diseases. Thus, while the significance of glycosylation is well established, a lack of accessible methods to characterize glycans has hindered the ability to understand their biological functions. Mass spectrometry (MS)-based methods have generally been at the core of most glycan profiling efforts; however, modern data-independent acquisition (DIA), which could increase sensitivity and simplify workflows, has not been benchmarked for analyzing glycans. Herein, we developed a DIA-based glycomic workflow, termed GlycanDIA, to identify and quantify glycans with high sensitivity and accuracy. The GlycanDIA workflow combined higher energy collisional dissociation (HCD)-MS/MS and staggered windows for glycomic analysis, which facilitates the sensitivity in identification and the accuracy in quantification compared to conventional data-dependent acquisition (DDA)-based glycomics. To facilitate its use, we also developed a generic search engine, GlycanDIA Finder, incorporating an iterative decoy searching for confident glycan identification and quantification from DIA data. The results showed that GlycanDIA can distinguish glycan composition and isomers from N -glycans, O -glycans, and human milk oligosaccharides (HMOs), while it also reveals information on low-abundant modified glycans. With the improved sensitivity, we performed experiments to profile N -glycans from RNA samples, which have been underrepresented due to their low abundance. Using this integrative workflow to unravel the N -glycan profile in cellular and tissue glycoRNA samples, we found that RNA-glycans have specific forms as compared to protein-glycans and are also tissue-specific differences, suggesting distinct functions in biological processes. Overall, GlycanDIA can provide comprehensive information for glycan identification and quantification, enabling researchers to obtain in-depth and refined details on the biological roles of glycosylation. Graphical

Cell membrane glycoproteins are generally highly fucosylated and sialylated, and post-translational modifications play important roles in the proteins' functions of signaling, binding and cellular processing. For these reasons, methods for measuring sialic acid-mediated protein–protein interactions have been developed. However, determining the role of fucose in these interactions has been limited by technological barriers that have thus far hindered the ability to characterize and observe fucose-mediated protein–protein interactions. Herein, we describe a method to metabolically label mammalian cells with modified fucose, which incorporates a bioorthogonal group into cell membrane glycoproteins thereby enabling the characterization of cell-surface fucose interactome. Copper-catalyzed click chemistry was used to conjugate a proximity labeling probe, azido-FeBABE. Following the addition of hydrogen peroxide (H₂O₂), the fucose-azido-FeBABE catalyzed the formation of hydroxyl radicals, which in turn oxidized the amino acids in the proximity of the labeled fucose residue. The oxidized peptides were identified using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Variations in degree of protein oxidation were obtained with different H₂O₂ reaction times yielding the acquisition of spatial information of the fucose-interacting proteins. In addition, specific glycoprotein–protein interactions were constructed for Galectin-3 (LEG3) and Galectin-3-binding protein (LG3BP) illustrating the further utility of the method. This method identifies new fucose binding partners thereby enhancing our understanding of the cell glycocalyx.