Integrating endometrial proteomic and single cell transcriptomic pipelines reveals distinct menstrual cycle and endometriosis-associated molecular profiles

Abstract

Endometriosis is a debilitating gynecological disorder affecting approximately 10% of the female population. Despite its prevalence, robust methods to classify and treat endometriosis remain elusive. Changes throughout the menstrual cycle in tissue size, architecture, cellular composition, and individual cell phenotypes make it extraordinarily challenging to identify markers or cell types associated with uterine pathologies since disease-state alterations in gene and protein expression are convoluted with cycle phase variations. Here, we developed an integrated workflow to generate both proteomic and single–cell RNA–sequencing (scRNA–seq) data sets using tissues and cells isolated from the uteri of control and endometriotic donors. Using a linear mixed effect model (LMM), we identified proteins associated with cycle stage and disease, revealing a set of genes that drive separation across these two biological variables. Further, we analyzed our scRNA–seq data to identify cell types expressing cycle and disease–associated genes identified in our proteomic data. A module scoring approach was used to identify cell types driving the enrichment of certain biological pathways, revealing several pathways of interest across different cell subpopulations. Finally, we identified ligand–receptor pairs including Axl/Tyro3 – Gas6, that may modulate interactions between endometrial macrophages and/or endometrial stromal/epithelial cells. Analysis of these signaling pathways in an independent cohort of endometrial biopsies revealed a significant decrease in Tyro3 expression in patients with endometriosis compared to controls, both transcriptionally and through histological staining. This measured decrease in Tryo3 in patients with disease could serve as a novel diagnostic biomarker or treatment avenue for patients with endometriosis. Taken together, this integrated approach provides a framework for integrating LMMs, proteomic and RNA–seq data to deconvolve the complexities of complex uterine diseases and identify novel genes and pathways underlying endometriosis.

An integrated single-cell reference atlas of the human endometrium

“…We identified two subtypes of decidualised stromal cells and macrophages as endometriosis-relevant. The observed dysregulation of stromal-immune cell homeostasis is in line with previous reports 16,20,28,29,78 , but overall, findings have been inconsistent. For example, some studies reported an increase in stromal cells in endometriosis cases, while others reported no changes.…”

“…the eutopic endometrium) differs between those with and without endometriosis 26,27 . Recently, single-cell studies analysing small sample sizes, reported dysregulation of the stromal and immune compartments in the endometrium of women with endometriosis to various degrees 16,18,20,28,29 . Larger sample sets are now needed if we are to unpick whether and how the endometrium differs in those with and without the condition.…”

Organoid co-culture model of the cycling human endometrium in a fully-defined synthetic extracellular matrix reveals epithelial-stromal crosstalk

“…Our initial studies demonstrating the establishment of endometrial organoids in a synthetic ECM 26 were guided in part by published histologic analysis of endometrial integrin expression patterns from a subset of the 24 known integrins. 37, 56–62 We sought additional insights into cell population-specific integrin expression by probing a single cell RNA-sequencing dataset 43 (scRNAseq, N=6; Fig 1C; Fig S1) to profile the integrin expression across the endometrial proliferative or secretory phase epithelia and stroma in addition to the immune and vascular cellular compartments. Across all cells in the data set, transcripts for all eighteen α chains and all eight β chains, except integrin β3, were detected (data not shown).…”

“…scRNAseq data collection, processing and analysis as described elsewhere (in preparation) 43 . Data was downloaded and Seurat (V3) was used to create dot plots and violin plots of specific genes of interest on scaled data.…”

“…Endometrial ECM processing for proteomics, proteomics data collection, processing and analysis is described elsewhere. 43 Briefly, fresh endometrial biopsies were collected and processed using 50 µl of RapiGest (Waters Corporation) reconstituted in 50 mM NH4HCO3 at a concentration of 2mg/ml to digest the endometrial biopsy sample for 24 hours at 37˚C. Next, urea (ThermoFisher) and dithiothreitol (ThermoFisher) were added to the sample to bring the mixture of a final concentration of 4 mM and 5 mM, respectively.…”