Reviewer #1 (Public Review): Endocannabinoids and their receptors modulate endometriosis pathogenesis and immune response

Endometriosis (EM), characterized by the presence of endometrial-like tissue outside the uterus, is the leading cause of chronic pelvic pain and infertility in females of reproductive age. Despite its high prevalence, the molecular mechanisms underlying EM pathogenesis remain poorly understood. The endocannabinoid system (ECS) is known to influence several cardinal features of this complex disease including pain, vascularization, and overall lesion survival, but the exact mechanisms are not known. Utilizing CNR1 knockout (k/o), CNR2 k/o and wild type (WT) mouse models of EM, we reveal contributions of ECS and these receptors in disease initiation, progression, and immune modulation. Particularly, we identified EM- specific T cell dysfunction in the CNR2 k/o mouse model of EM. We also demonstrate the impact of decidualization-induced changes on ECS components, and the unique disease- associated transcriptional landscape of ECS components in EM. Imaging Mass Cytometry (IMC) analysis revealed distinct features of the microenvironment between CNR1, CNR2, and WT genotypes in the presence or absence of decidualization. This study, for the first time provides an in-depth analysis of the involvement of the ECS in EM pathogenesis and lays the foundation for the development of novel therapeutic interventions to alleviate the burden of this debilitating condition. eLife assessment This study presents valuable findings on how the endocannabinoid system is involved in endometriosis progression using CNR1 and CNR2 knockout (KO) mouse models. The evidence supporting the authors' claims is incomplete; including bulk RNA-seq, flow cytometry, and imaging mass cytometry would have strengthened the study. This work might be of interest to medical scientists working on endometriosis. https://doi.org/10.7554/eLife.96523.2.sa3 Reviewed Preprint v2 • July 25, 2024 Revised by authors Reviewed Preprint v1 • April 19, 2024 Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 2 of 36

Endometriosis (EM) is a chronic gynecological disorder characterized by the presence and growth of endometrial like tissue outside the uterus, referred to as ectopic lesions. Despite its global impact on approximately 200 million individuals and the profound reduction in their quality of life, the exact origins of EM remain elusive1 . Accumulating evidence, including our previous studies, highlight that components of the endocannabinoid system (ECS) are dysregulated within EM lesion microenvironment as well as in the systemic circulation of EM patients2 –4 . The ECS is a complex signaling network comprised of canonical receptors (CNR1 and CNR2) and endocannabinoid (EC) ligands, along with non-canonical extended signaling network of ligands and enzymes (extensively reviewed elsewhere5 ). CNR1 and CNR2 are primarily expressed in nerve tissues, immune cells, and reproductive tissues, where they regulate various physiological processes, including pain perception, immune responses, and reproductive functions6 . Consequently, EM pathogenesis has been postulated as a consequence of EC deficiency7 ,8 . Even though the precise etiology of EM is not known, the widely accepted Sampson’s theory of retrograde menstruation suggests that EM lesions originate from refluxed, endometrial fragments deposited during menstruation9 . Both pregnancy and menstruation depend on spontaneous decidualization of endometrial stroma that is extensively remodelled under the influence of hormones, growth factors, and select cytokines that orchestrate immune cell recruitment and vascular adaptions10 . There is clear evidence that EM patients have defects in eutopic endometrium, including differential expression of key endometrial receptivity markers such as leukemia inhibitory factor (LIF), protein arginine methyltransferase 5 (PRMT5), and homeobox protein hox-A10 (HOXA10), that have been associated with EM and subsequent infertility11 –13 . Evidence also suggests that components of the ECS, including CNR1 and CNR2, are important in maintaining tissue integrity during decidualization and successful implantation of the embryo. Indeed, several reports indicate that mice lacking cannabinoid receptors, CNR1 and CNR2, displayed impaired implantation, increased pregnancy failure rates, heightened edema, and inadequate primary decidual zone formation, highlighting the crucial role of ECS signaling in successful decidualization, implantation, and pregnancy14 –16 . In EM, CNR1 and CNR2 activation aids in controlling lesion proliferation, pain, and vascularization17 ,18 . Keeping in view dysregulated ECS signalling and their central role in decidualization and fertility, we hypothesize that altered CNR1 and CNR2 expression will disrupt ECS signaling dynamics, leading to further lesion development. Furthermore, involvement of ECS in modulating immune response and homeostasis, may disrupt the immune dynamics and foster lesion establishment. We conducted a comprehensive investigation into the role of the dysregulated ECS in EM establishment and progression by utilizing CNR1 k/o and CNR2 k/o mouse models. To address the underlying causes of ECS dysfunction, we induced artificial decidualization in WT, CNR1 k/o, and CNR2 k/o mice and used the endometrial fragments from decidualized (DD) and undecidualized (UnD) uterine horns to induce EM in recipient mice of their respective genotypes. Furthermore, we explored the immunomodulatory potential of the ECS in EM, shedding light on how alterations in EC signaling may influence immune cell behavior within the localized peritoneal milieu in mice induced with EM. Our study contributes to the foundational knowledge around ECS dysregulation in EM and paves way for potential therapeutic strategies targeting ECS for disease management. Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 3 of 36

Animals Experiments described in this work were approved by the Queen’s University Institutional Animal Care Committee as per the guidelines provided by the Canadian Council of Animal Care. All animals were assigned randomly to the surgical procedures. All studies were performed using adult female mice at ages between 7 to 10 weeks. CNR1 k/o (B6.129P2(C)-Cnr1tm1.1Ltz/J) and CNR2 k/o (B6.129P2-Cnr2tm1Dgen/J) male and female breeder mice were obtained from Jackson Laboratory (Bar Harbor, USA) and were housed in the Queen’s University animal facility. CNR1 k/o and CNR2 k/o experimental female mice were obtained by trio breeding with their respective homozygous k/o male counterparts. C57BL/6j (WT) control female mice and vasectomized male mice at 7 to 10 weeks were obtained from Jackson Laboratory. All breeder mice were housed in standard breeding cages in a barrier facility and the experimental animals were housed in a conventional holding area. Animals were housed at constant temperature (22 ± 1 °C) and relative humidity (50%), with a 12:12 h light:dark cycle (light on 07.00–19.00 h). Food and water were available ad libitum. All experimental animals were acclimatized at the conventional housing facility for 1 week before starting the experiments. In vivo decidualization In this study, we have used a modified syngeneic mouse model of EM, where the donor fragments were obtained from artificially decidualized uterine horns. The method of artificial decidualization used in this study has been previously established and utilized by several research studies11 ,19 ,20 . To artificially induce decidualization, female mice were allowed to mate with vasectomized male mice to induce pseudopregnancy. After day 4 of pseudopregnancy, female mice were subjected to laparotomy to receive a 30μL. injection of sesame seed oil (S3547, Sigma, USA), intra-luminally into one uterine horn to induce DD. The contralateral, uninjected horn served as an UnD control. After sesame seed oil injection, animals were rested for 4 days, after which the DD was successfully induced in one uterine horn as shown in Figure 1A . These uterine horns were utilized as donor fragments to induce EM in recipient mice of their respective genotype. Figure 1B shows the representative images of EM lesions 7 days post-surgical induction. Mouse model of EM EM was surgically induced as described previously2 ,17 . Two independent groups (DD and UnD) per genotype were used in this study (n = 8–16). Briefly, the DD and UnD uterine horns from the donor mice were harvested, and uterine horns were longitudinally dissected to reveal the endometrium. Uterine fragments were obtained using a 3.0 mm epidermal biopsy punch (33–32, Integra™ Miltex®, USA). Recipient mice were anesthetized under 3.5% isoflurane vaporizer anesthesia to make a midline incision in the abdomen (n = 8–16) and two 3.0 mm DD or UnD uterine fragments were implanted on the right inner peritoneal wall using a veterinary grade tissue bonding glue (1469SB, 3M, USA). WT, CNR1 k/o, and CNR2 k/o control groups (n = 4) were sham operated with a midline incision in the abdomen without implantation of uterine fragments. Mice were sacrificed 7 days after EM induction surgery since the focus of the study was on the earlier time point of EM initiation after induction. Based on the previous studies, 7 days after EM induction appears to be the log phase of tissue repair and immune response21 . Blood was harvested through cardiac puncture to assess EC ligands. Peritoneal fluid (PF) was collected by injecting 3 ml of ice-cold phosphate buffered saline (PBS) into the peritoneal cavity. Spleens were collected in ice-cold RPMI media (11875093, ThermoFisher, Canada) before processing to obtain Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 4 of 36Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 4 of 36 Figure 1 Characterization of endocannabinoid ligands in a modified syngeneic mouse model of endometriosis A Overview of the modified syngeneic mouse model of EM where pseudo-pregnant WT, CNR1 k/o, and CNR2 k/o mice were induced with DD by injecting sesame oil into the lumen of one uterine horn and the contralateral horn served as UnD control. Two, 3mm UnD and DD harvested fragments were implanted into their respective recipient mouse strain to induce EM. B Representative images of the EM lesions from WT, CNR1 k/o, and CNR2 k/o mice retrieved from the peritoneal cavity at end point (7 days post EM induction surgery). C-J Bar plots (mean ± SD) showing the concentration of EC ligands 2AG, AEA, PEA, and OEA identified in the plasma and EM lesions from mice using targeted LC-MS approach. C-F 2AG, AEA, PEA, and OEA were detected in plasma samples without any significant differences between groups. G, J Significantly higher concentration of 2AG was observed between the DD lesions of CNR2 k/o and CNR1 k/o mice, and significantly higher levels of OEA in the DD lesions from CNR1 k/o mice compared to DD lesions from WT mice. H, I AEA and PEA levels in the tissue samples did not differ significantly between the comparison groups. n = 4–5 individual biological samples per genotype. Statistical analyses were performed using the ordinary one-way ANOVA with Holm-Sidak post hoc test. * p < 0.05 and ** p < 0.01. Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 5 of 36 single cell suspension. EM lesions were either snap frozen in liquid nitrogen and stored at -80°C or processed using 4% paraformaldehyde overnight (12–20 h), kept at 4°C in 70% ethanol, and then embedded in paraffin. Lipid extraction and targeted mass spectrometry Plasma was undiluted and ~ 10mg of tissue per sample were homogenized with RIPA buffer (89900, ThermoFisher, Canada) with 1:100 of protease inhibitor cocktail (535140-1ML, Sigma, Canada) to obtain tissue lysates. Both plasma and tissue lysates obtained were individually subjected to solid phase extraction (SPE). Internal standards, both deuterated and non-deuterated used in the study to assess the ECS ligands were purchased from Cayman Chemicals, USA (Supplementary Table 1 ). Aliquots of 100μL of plasma and tissue lysates were added to a protein precipitation plate (CE0-7565-R, Phenomenex, USA) along with 200μL of cold acetonitrile containing the deuterated internal standards. The filtrate was diluted with 500μL of water and submitted to SPE extraction on an Oasis HLB 96-Well Plate (WAT058951, Waters, Canada). Samples were washed with 60% methanol prior to elution with acetonitrile. The eluate was dried, reconstituted in 100μL of mobile phase A and analyzed by liquid chromatography-mass spectrometry (LC-MS as described in Supplementary Table 2 ). The endogenous concentration for the four compounds in human plasma were calculated by standard addition. Flow cytometry Single-cell suspensions were prepared from murine spleens by mechanical dissociation, RBC lysis, and centrifugation. Splenic cells and cells from PF were resuspended in staining buffer (PBS with 2% fetal bovine serum) at a concentration of 0.5 × 10^6 cells/mL. All antibodies used for flow cytometry analyses were purchased from BioLegend, USA, unless otherwise mentioned. The antibodies included CD45-FITC (103107), CD3-BV510 (100234), CD4-BV785 (100551), CD8-BV605 (100744), CD11b-AF700 (101222), F4/80-PE/Cy7 (123114), NK1.1-APC/Cy7 (108724), and CD19- PE/Dazzle 594 (115554). Staining was performed following the manufacturer’s recommendations. For each sample, 50μL of the antibody cocktail was added to 50μL of cell suspension in 96 well plates. The mixture was incubated at 4°C for 20 mins in the dark, along with anti-CD16/32 Fc block antibody (101319). After incubation, cells were washed twice with staining buffer and centrifuged before fixing the cells with fixation buffer (00-8222/49, ThermoFisher, Canada). Flow cytometry analysis was carried out using a Beckman Coulter CytoFlex S flow cytometer. Compensation controls were established using single antibody-stained cells. Isotype controls provided baseline levels of non-specific staining and cell populations were defined using fluorescence minus one (FMO) control. Data analysis employed FlowJo software (v 10.9; FlowJo, USA) as well as SPECTRE (v 1.0) computational toolkit in R (v 4.2.3) to obtain t-distributed stochastic neighbor embedding (t- SNE) plots based on the unsupervised flowSOM clusters generated by marker expression. In-vitro T-cell functional assay Total CD3+ T cells were isolated from splenocytes of naive WT and CNR2 k/o mice using a negative selection magnetic kit (19851A, StemCell, Canada) following the manufacturer’s instructions. All recombinant proteins and compounds were purchased from Biolegend, USA, unless otherwise mentioned. Subsequently, 250,000 T cells per well were seeded into a 96-well plate coated with anti-mouse CD3 [(2 μg/ml), (100340)]. RPMI-1640 media supplemented with rmIL-2 [(10 ng/ml), (575404)], anti-mouse CD28 [(5 μg/ml), (102116)], 10% fetal bovine serum, β-mercaptoethanol (50μM), and penicillin/streptomycin (100 U/ml) was used as the growth medium. T cells were then activated non-specifically with or without the cell activation cocktail consisting of Phorbol 12- myristate 13-acetate (PMA) and ionomycin [(50 ng/ml PMA and 1 μM ionomycin), (423301)] in the presence and absence of TNFα [(100 ng/ml), (410-MT-010/C, R&D Systems, USA)] to simulate a sterile inflammatory challenge. Following a 48-h incubation period, brefeldin A [(10 μg/ml), (11861, Cayman Chemicals, USA)] was introduced to the cells to measure intracellular interferon-gamma (IFNγ) levels at the 42-h time point. Flow cytometry analysis was conducted using a panel of Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 6 of 36 markers, purchased from Biolegend, USA unless otherwise mentioned, including CD3e-FITC (100306), CD4-AF700 (100430), CD8-PE/fire700 (100792), Ki67-PB (151223), FoxP3-PE (126404), IFNγ- BV605 (505840), and Live/dead-K0525 (L304966, ThermoFisher, Canada), to assess various T cell subsets and viability. Flow cytometry staining and acquisition was carried out as described above with the addition of permeabilization (00-8333-56, ThermoFisher, Canada) buffer to stain for intracellular markers (Ki-67 and IFNγ), according to the manufacturer’s instructions. Data analysis was performed using FlowJo software and visualized using GraphPad Prism (v 9.5.1). RNA isolation using RNeasy mini kit Snap frozen UnD and DD EM lesions from WT, CNR1 k/o, and CNR2 k/o were homogenized, and RNA was isolated using the RNeasy Mini Kit (74104, Qiagen, Canada), according to the manufacturer’s instructions. Briefly, ~20mg EM lesion tissues were placed individually in PowerBead Ceramic Tubes (13113-50, Qiagen, Canada) along with lysis buffer. Lesions were homogenized using a Bead Ruptor homogenizer (Omni International, USA) and lysates were extracted after centrifugation at 10,000 RCF. Lysate was mixed with 70% ethanol, added to the RNeasy spin column, and then centrifuged to bind the RNA to the column. Spin column was washed twice, and RNA was isolated using elution buffer. Total RNA quality was measured using the nanodrop spectrophotometer and stored at -80°C before shipping to BGI Global (Boston, USA) for bulk RNA analysis. RNA integrity was determined using the Agilent 4150 TapeStation System Agilent, USA) for sample quality control and only samples with RNA quality number ≥ 7 were considered for library preparation and further sequencing. RNA library preparation, sequencing, and analysis Library preparation began with mRNA enrichment using oligo dT beads, which selectively capture mRNA molecules. Next, the enriched mRNA was fragmented, and first-strand cDNA was synthesized using random N6 primers, followed by second-strand cDNA synthesis using deoxyuridine triphosphate (dUTP). After cDNA synthesis, end repair was performed to generate blunt ends, and 3′ adenylation was carried out to facilitate adaptor ligation. Adaptors were ligated to the 3′ adenylated cDNA fragments. To enrich the cDNA library for sequencing, PCR amplification was conducted. Prior to amplification, the dUTP-marked strand was specifically degraded by Uracil-DNA-Glycosylase (UDG). The remaining first-strand cDNA was then amplified using PCR primers. Following amplification, single-strand separation was achieved through denaturation by heat. The single-stranded DNA was cyclized using a splint oligo and DNA ligase. DNA nanoball synthesis was performed on the cyclized single-stranded DNA templates. This process facilitated the generation of clonal DNA clusters, providing the material necessary for subsequent sequencing. Sequencing was executed using the DNBSEQ Technology platform. The prepared DNA libraries were loaded onto the DNBSEQ sequencer and sequenced at an average depth of 30 million paired end reads (2 × 100) per library. The sequencing data was filtered with SOAPnuke by removing reads containing sequencing adapter; removing reads whose low-quality base ratio (base quality less than or equal to 15) is more than 20%, and removing reads whose unknown base (‘N’ base) ratio is more than 5%. Next, clean reads were obtained and stored in FASTQ format. Clean reads were mapped to the mouse reference genome (NCBI: GRCm38.p6) using HISAT2 (v2.0.4). The subsequent analysis and data mining were performed on Dr. Tom Multi-omics Data mining system (https://biosys.bgi.com ). Imaging Mass Cytometry: labeling A comprehensive panel of antibodies identifying innate and adaptive immune cell populations and cell types that are integral to EM lesion microenvironment (Supplementary Table 3 ) was designed and optimized as previously described22 ,23 . The formalin-fixed paraffin-embedded (FFPE) tissue sections (n = 2–3 per tissue type) underwent deparaffinization and heat-mediated antigen retrieval on the Ventana Discovery Ultra auto-stainer platform (Roche Diagnostics, Canada), following the below instructions. Initially, the slides were exposed to a temperature of 70 Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 7 of 36 °C in a pre-formulated EZ Prep solution (Roche Diagnostics, Canada), followed by a subsequent incubation at 95 °C in pre-formulated Cell Conditioning 1 solution (Roche Diagnostics, Canada). Following this, the slides were washed in 1 × PBS and then exposed to Dako Serum-free Protein Block solution (Agilent, USA) for 45 min at room temperature. An antibody cocktail, containing metal-conjugated antibodies, was prepared using Dako Antibody Diluent (Agilent, USA) at specified dilutions. The primary antibodies within this cocktail were applied to the slides and left to react overnight at 4 °C, after which the slides were washed with 0.2% Triton X-100 and 1 × PBS. For the subsequent step, a secondary antibody cocktail comprising metal-conjugated anti-biotin antibodies was created in Dako Antibody Diluent, at a predetermined dilution. The slides were treated with this anti-biotin cocktail for 1-h at room temperature and then washed with 0.2% Triton X-100 and 1 × PBS. For counterstaining, the slides were exposed to Cell-ID Intercalator-Ir (Fluidigm, Canada) diluted at a ratio of 1:400 in 1x PBS for 30 min at room temperature. After a 5- min rinse with distilled water, the slides were airdried in preparation for imaging mass cytometry (IMC) acquisition. The Hyperion Imaging System (Fluidigm, Canada) was employed for the IMC acquisition process. Imaging Mass Cytometry: Data analysis Lesions (n = 2–3 per tissue type) were grouped based on the origin of uterine fragments (i.e., UnD or DD) from three different genotypes (WT, CNR1 k/o, and CNR2 k/o). IMC data analysis methods employed in this study follow established procedures as outlined in Steinbock toolkit (Spatial Experiment v 1. 12. 0) for data preprocessing, image segmentation, and object quantification24 . Cell segmentation utilized a deep learning approach described by Greenwald et al25 . Briefly, dual-channel images were generated using nuclear and cytoplasmic markers, representing respective signals. The DeepCell tool with Mesmer, a pre-trained deep learning segmentation algorithm from TissueNet, was used to automate cell mask generation, requiring no additional user input. Given the IMC data was acquired in batches, we performed batch effect corrections using the harmony algorithm as described26 . This involved iterative clustering and correction of cell positions in the principal component analysis (PCA) space. Subsequently, unsupervised PhenoGraph clustering in R (v 4. 3. 2) was used to categorize cell types. For this, signals including αSMA, B220, CD19, β-catenin, CD3, CD4, CD8, CD11b, CD 11c, CD31, CD68, E-cadherin, MPO, pan- cytokeratin, and vimentin were utilized, employing a k-value of 60. To ascertain cell interactions, imcRtools (v 1. 8. 0) and cytomapper (v 1. 14. 0) in R were employed for visualization. A permutation test evaluated interactions with neighboring cells. Neighboring cells were defined as those within a 5-pixel radius (5 μm), and the buildSpatialGraph function established the number of one cluster neighbors interacting with another cluster. A default of 1000 permutations was set. Each iteration led to interaction score and p-value computation, and the significant outcomes (at alpha 1% risk) were depicted in heatmaps. To delineate spatial cellular neighborhoods, neighbor windows were computed, representing the N nearest cells to each cell. This process followed previous protocols. Employing imcRtools, cellular neighborhood grouping was conducted, leading to the identification of 8 cellular neighborhoods in the lesions. Statistics Statistical analyses performed to compare the concentration of EC ligands through targeted LC-MS and evaluation of immune cell population via flow cytometry were conducted using Prism GraphPad. A one-way analysis of variance (ANOVA) was performed with Holm-Sidak post-hoc test to determine the specific pairwise differences between the groups. For in-vitro T cell functional assay, two-way ANOVA was performed using Tukey’s post-hoc test to compare within and between the groups. The significance level was set at α = 0.05. Data are presented as mean ± standard deviation (SD) unless otherwise stated. Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 8 of 36

Ligands of the ECS are dysregulated in a mouse model of EM lacking CNR1 and CNR2 receptors Based on our previous work demonstrating dysregulated ligands of the ECS in both patients and our mouse model of EM2 , we first evaluated whether absence of CNR1 or CNR2 led to ECS ligand alterations. To do this, we performed targeted mass spectrometry on plasma and EM lesions obtained from CNR1 k/o, CNR2 k/o, and their WT controls. In these mice, EM was induced using UnD and DD tissues obtained from their respective strains into matched recipients (for example, UnD and DD from CNR1 k/o donor mice was implanted into CNR1 k/o recipient mice). We detected some of the major EC ligands such as, 2-Arachidonoylglycerol (2-AG), N-arachidonoylethanolamine (AEA), Palmitoylethanolamide (PEA) and Oleoylethanolamide (OEA) in plasma and EM lesions from all genotypes. All identified ECS ligands are predominantly anti-inflammatory and the range of 2-AG, AEA, PEA, and OEA in the plasma and lesions were comparable to our previous study2 . In the plasma, we found no significant differences in ECS ligands across all groups (Figure 1C- F ), which could be due to the rapid homeostasis achieved in circulation27 . However, in the lesion microenvironment, we captured higher levels of several EC ligands (Figure 1G-J ). In CNR1 k/o mice, significantly higher concentrations of OEA were observed in the DD compared to UnD lesions (Figure 1J ), and overall, was on average two-fold higher compared to both lesions from WT and CNR2 k/o mice. 2-AG, which selectively binds to the CNR2 receptor was significantly higher in both the UnD and DD EM lesions from CNR2 k/o mice (Figure 1G ) compared to the CNR1 k/o counterparts. This could indicate a compensatory response in the absence of CNR2. Together, these findings provide insights into potential dysregulation of ECS ligands in the absence of CNR1 and CNR2 and their involvement in DD vs UnD scenario during EM lesions establishment. Impact on gene expression and pathway alterations in EM lesions from mice in the absence of CNR1 and CNR2 Next, we investigated the effects of CNR1 and CNR2 absence on the transcriptomic profile of both UnD and DD EM lesions from their respective genotypes. Bulk RNA sequencing was performed on both UnD and DD lesions from WT, CNR1 k/o, and CNR2 k/o mice as detailed earlier to elucidate the molecular alterations associated with the disruption of these two-receptors signaling. Differential expression analysis revealed changes in gene expression profiles among the different genotypes and lesion types (Figure 2A ). A total of 1100 and 639 differentially expressed genes (DEGs) were found in both UnD and DD lesions of CNR1 k/o and CNR2 k/o mice, respectively, compared to WT controls (UnD data is provided in Supplementary Data 2 ). To gain insights into the biological implications of the observed gene expression changes, we conducted Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on the DEGs identified in UnD and DD lesions of CNR1 k/o and CNR2 k/o mice compared to WT mice. In the DD lesions from CNR1 k/o mice, KEGG pathway analysis revealed significant alterations in several pathways (Figure 2B ). Notably, the cell adhesion molecules pathway was prominently affected, indicating a potential role for CNR1 in mediating cell-cell interactions and tissue remodeling processes. Additionally, the cyclic adenosine monophosphate (cAMP) signaling emerged as another negatively impacted pathway, implicating CNR1 in modulating intracellular signaling cascades. In DD lesions from the CNR2 k/o mice, analysis highlighted distinct pathways affected in the context of inflammation and EM (Figure 2C ) including the cytokine receptor interactions pathway, pointing to the involvement of CNR2 in immune responses and inflammatory processes associated with EM. Furthermore, we captured alterations in the steroid hormone biosynthesis pathway suggesting a role for CNR2 in hormone- related mechanisms relevant to endometrial tissue development and homeostasis. Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 9 of 36Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 9 of 36 Figure 2 Transcriptomic profiling of endometriosis-like lesions from CNR1 and CNR2 knockout mice reveals extensive differential gene expression and altered pathways A Summary of the differentially expressed genes (DEGs) from bulk RNA sequencing analysis conducted on both UnD and DD lesions from WT, CNR1 k/o, and CNR2 k/o mice, revealing extensive changes in gene expression profiles among the different genotypes and lesion types. A total of 1100 and 639 DEGs were identified in both UnD and DD lesions of CNR1 k/o and CNR2 k/o mice, respectively, compared to WT controls. B KEGG pathway analysis revealed significantly altered cell adhesion molecules and cAMP signaling pathways in DD lesions of CNR1 k/o. C KEGG pathway analysis in DD lesions of CNR2 k/o mice showed changes associated with cytokine receptor interactions and steroid hormone biosynthesis pathways. D, E Venn diagrams showing the DEGs among the 59 genes directly associated with the ECS, where we found limited DEGs in DD lesions of CNR1 k/o (3) and CNR2 k/o mice (2), respectively. F A comprehensive gene ontology analysis highlighting the roles of 59 ECS genes across diverse biological processes (blue), cellular (orange), and molecular functions (light blue), accentuating their broader impact beyond canonical ECS functions. Gene Number indicates the number of DEGs enriched in pathway. Rich Ratio indicates the ratio of enriched DEGs to background genes and Q-value indicates significance, with a value closer to zero being more significant and is corrected by Benjamini-Hochberg method. Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 10 of 36 Next, we performed a subset analysis for genes directly involved in ECS signaling. A total of 59 key genes in ECS signaling were selected, as identified in a study by Tanaka et al28 . Surprisingly, despite the central role of CNR1 and CNR2 in ECS signaling, we found a limited number of DEGs related to this system. Out of 59 genes directly associated with ECS, only 3 (CNR1, PLCH1 and PLCH2) and 2 (CNR2 and PLAG2GE) DEGs were identified in the DD lesions of CNR1 k/o (Figure 2D ) and CNR2 k/o (Figure 2E ), respectively, compared to DD lesions from WT controls. This

suggests that CNR1 and CNR2 modulate the EM microenvironment through intricate interactions with other signaling pathways beyond the canonical ECS pathway. A comprehensive gene ontology (GO) classification analysis on the 59 identified ECS genes (Figure 2F ) unveiled their multifaceted roles in reproductive functions, immune system regulation, and cellular processes. The genes exhibited enrichment in molecular functions such as receptor activity and lipid binding. In terms of cellular components, these genes were associated with plasma membrane structures, and intracellular compartments, signifying their diverse subcellular localization and potential involvement in dynamic cellular processes. Furthermore, GO analysis highlighted their participation in biological processes such as immune response modulation, lipid metabolism, cell communication, and intracellular signaling pathways, indicating the broader impact of ECS beyond its canonical functions. The results of the UnD comparisons between the genotypes are provided in the supplementary files (Supplementary Figure 1 ). While the UnD lesions exhibited distinct gene expression patterns compared to DD lesions, common trends in the effects of CNR1 k/o and CNR2 k/o on gene expression were observed across both lesion types. Specifically, the cytokine receptor interaction, complement cascade, and inflammatory mediator pathways were significantly altered in the UnD lesions from CNR1 k/o and CNR2 k/o mice compared to UnD lesions from WT mice. Overall, our findings highlight the significant impact of CNR1 and CNR2 k/o on gene expression in EM lesions and the implications for EM pathogenesis. Disruption of genes related to adaptive immune response in EM lesions without CNR1 and CNR2 Building upon our previous investigation into the transcriptomic alterations, we conducted an indepth analysis of differentially expressed immune-related genes (as per InnateDB version 5.4) in both UnD and DD lesions across all genotypes. Here, our analysis is focused on the immune-related genes within DD lesions of CNR1 k/o and CNR2 k/o mice compared to WT controls. Comparison of the UnD lesions of CNR1 k/o and CNR2 k/o with WT EM mice are included in the supplementary files (Supplementary Figure 2 ) The differential expression bar plot (Figure 3A ) provides representation of the upregulated and downregulated genes in each comparison. The volcano plots for DD lesions from CNR1 k/o vs. WT (Figure 3B ) and CNR2 k/o vs. WT (Figure 3C ) illustrate the various DEGs. Notably, CNR1 k/o DD lesions exhibited 39 downregulated (eg., NLRP6 and IL1a, pivotal regulators of inflammatory response) and 14 upregulated genes (eg., CXCL9 and CXCL10, chemokines involved in immune cell recruitment), while CNR2 k/o DD lesions showed 40 downregulated (eg., SIGLECG and IL6, involved in immune regulation and pro- inflammatory response) and 25 upregulated genes (eg., C8a, C9, and MASP2, part of the complement system), highlighting substantial changes in gene expression associated with CNR1 and CNR2 disruption compared to the DD lesions from WT mice. Of particular interest, we observed significant downregulation of T cell-related genes (CD3e, CD3g, GATA3, and CTLA4) in the CNR2 k/o DD lesions (Supplementary Data 3 ), aligning with the CD3+ T cell dysfunction observed in the PF and spleen and further validations from in-vitro functional assay (mentioned below). However, we did not find the same differences (T cell-related genes) in the UnD lesions of CNR2 k/o mice. Moreover, UnD lesions of CNR2 k/o mice showed significantly low number of DEGs (11 compared to 65 in the DD lesions from CNR2 k/o mice) suggesting a decidualization dependent response (Supplementary Data 3 ). This observation clearly emphasises a potential link between CNR2 dysfunction with decidualization characterized by T cell signaling issues within the EM microenvironment. To understand functional implications of the DEGs, we conducted KEGG pathway analysis on specific differentially expressed immune genes in DD lesions from CNR1 k/o Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 11 of 36Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 11 of 36 Figure 3 Bulk RNA sequencing revealed alterations in immune-related gene expression and pathway in EM lesions from CNR1 k/o and CNR2 k/o mice A Bar plot overview of the differentially expressed (DE) immune-related genes among different genotypes and lesion types. B, C The volcano plots for DD lesions of CNR1 k/o vs. WT and CNR2 k/o vs. WT, respectively, revealed 39 downregulated and 14 upregulated genes in CNR1 k/o DD lesions, while CNR2 k/o DD lesions exhibited 40 downregulated and 25 upregulated genes. Log2 fold change as the x-axis and log10 Q-value (FDR adjusted) as the y-axis. Vertical dotted lines on the x-axis indicate ± 1-fold change and vertical dotted line on the y-axis indicate Q-value of 0.05. D, E KEGG pathway analysis of DEGs in CNR1 k/o DD lesions show significant alteration in the chemokine signaling pathway, cytokine-cytokine receptor interaction, and toll-like receptor signaling pathways, while in CNR2 k/o DD lesions, alterations were observed in pathways related to cytokine-cytokine receptor interaction, Th17, Th1 and Th2 cell differentiation. Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 12 of 36 and CNR2 k/o mice. Notably, in CNR1 k/o DD lesions compared to WT DD, the chemokine signaling pathway, cytokine-cytokine receptor interaction, and toll-like receptor (TLR) signaling pathways were negatively affected (Figure 3D ). These findings provide insights into the impact of CNR1 disruption on immune cell function within the DD environment. Conversely, CNR2 k/o DD lesions were associated with significant alterations in cytokine-cytokine receptor interaction, Th17, Th1, and Th2 cell differentiation pathways (Figure 3E ). These pathways are proven to be involved in T cell development, differentiation, and effector functions, aligning with our observed dysregulation of T cell-related genes. Together, these findings further elucidate the roles of CNR1 and CNR2 in modulating immune responses within the context of EM. Multispectral flow cytometry revealed altered immune cell profiles in a mouse model of EM lacking CNR1 and CNR2 Immune dysregulation is recognized as a crucial factor in the pathogenesis of EM29 . To elucidate the impact of CNR1 and CNR2 absence on immune cell populations, we performed multispectral immune profiling in splenocytes and cells from the PF from WT, CNR1 k/o, and CNR2 k/o mice harboring UnD and DD lesions. Representative gating panels of PF CD3 (y axis) vs CD11b (x axis) cells (Figure 4A-E ) illustrate distinct profiles among WT, CNR1 k/o, and CNR2 k/o mice with EM, as well as CNR2 k/o naïve, non-operated mice, and CNR2 k/o sham-operated controls. Strikingly, CD3+ T cell populations were nearly absent in the PF of CNR2 k/o mice with EM, regardless of lesion types (UnD and DD), when compared to other groups (Figure 4C and F ). This trend further extended to CD4+ helper T cells and CD8+ cytotoxic T cells (Figure 4G-H ). CNR1 k/o mice with DD lesions exhibited significantly reduced CD3+ (Figure 4F ), CD4+ (Figure 4G ), and CD8+ (Figure 4H ) T cell frequencies compared to their UnD counterparts, as well as lower CD19+ B cells and NK1.1+ NK cells (Figure 4K ) populations, compared to WT and CNR2 k/o mice. Concomitant with the reduction of T cell subsets, an increase in CD11b monocytes was observed in the PF of CNR2 k/o mice with UnD and DD lesions compared to WT and CNR1 k/o mice (Figure 4I ). Similarly, CNR1 k/o mice with DD lesions displayed higher monocyte/macrophage populations compared to their UnD counterparts (Figure 4I ). Furthermore, WT mice with DD lesions demonstrated significantly lower CD3+ T cell frequencies compared to their UnD counterparts (Figure 4F ), suggestive of a decidualization-associated effect. Splenocytes exhibited analogous trends (Figure 4L ), as depicted by tSNE plots (bar plots and contour gating plots in Supplementary Figure 3 and 4 ). These alterations in immune cell numbers reinforce the influence of CNR1 and CNR2 dysregulation and decidualization on immune cell populations, confirmed both locally in PF and systemically in the spleen. T cells from CNR2 k/o mice exhibit impaired viability upon TCR activation To validate the functional consequences of CNR2 deficiency on T cell behavior, we conducted a series of in-vitro assays using T cells isolated from splenocytes of naïve WT and CNR2 k/o mice. CD3+ T cells were activated non-specifically, with or without PMA/ionomycin cocktail, in the presence or absence of tumor necrosis factor alpha (TNFα) to create a sterile inflammatory challenge. We observed a significant reduction in the viability of total CD3+ T cells from CNR2 k/o mice upon activation with PMA/ionomycin (gating strategies in Supplementary Figure 5 ) compared to media controls (Figure 5A and B ). In contrast, WT CD3+ T cells activated with PMA/ionomycin, with or without TNFα, exhibited no significant difference in viability when compared to the media control (Figure 5A and B ). This observation aligns with our in-vivo findings, whereby CD3+ T cells from CNR2 k/o mice with EM exhibited a significant reduction in both the splenic and PF population, but not in the SHAM-operated mice, emphasizing the EM-specific nature of this effect. Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 13 of 36Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 13 of 36 Figure 4 Flow cytometry profiling of PF and splenic cells show altered immune cell phenotypes in CNR1 k/o and CNR2 k/o mice with EM A-E Gating panels of PF cells showing CD3 KO525-A on the y-axis vs CD11b APC-A700-A on the x-axis among WT, CNR1 k/o, and CNR2 k/o mice with DD EM lesions, as well as CNR2 k/o naive and CNR2 k/o sham-operated controls. F CD3+ total T cells in the PF of CNR2 k/o mice with EM lesions, regardless of lesion types, were significantly reduced compared to WT and CNR1 k/o mice with EM, as well as CNR2 k/o naïve and sham operated mice. G, H This extended to the subsets of CD3+ T cells, CD4+, and CD8+ T cells, respectively. CNR1 k/o mice with DD lesions also exhibited significantly decreased CD3+ total T cells, CD4+ helper T cells, and CD8+ cytotoxic T cell frequencies compared to their UnD counterparts. I CD11b+ monocyte/macrophage populations were increased in the PF of CNR2 k/o mice with UnD and DD lesions compared to WT and CNR1 k/o mice. CNR1 k/o mice with DD lesions displayed higher monocyte/macrophage populations compared to their UnD counterparts. K, J CNR1 k/o mice with DD lesions exhibited lower CD19+ B cells and NK1.1+ NK cell populations compared to WT and CNR2 k/o mice. L Immune cell populations in splenocytes were analogous to findings from PF cells, depicted by tSNE plots. n = 5–7 individual biological samples per genotype. Statistical analyses were performed using the ordinary one-way ANOVA with Holm-Sidak post hoc test. * p < 0.05, ** p < 0.01, *** p < 0.001 and **** p < 0.0001. Data presented as mean ± SD. Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 14 of 36 Additionally, the overall reduced viability of CD3+ T cells of CNR2 k/o mice upon PMA/ionomycin activation led to decrease in proliferation of CD4+ T cells (Figure 5C ) but not of CD8+ T cells (Figure 5D ). However, our results indicated that although CNR2-deficient T cells displayed reduced viability upon activation, they exhibited higher levels of IFNγ production compared to CD3+ T cells from WT mice, suggesting their functional competence (Supplementary Figure 5 ). These findings shed light on the intricate role of CNR2 in modulating T cell responses, with potential implications for immune dysregulation. Spatial cell analysis of EM lesions from WT, CNR1 k/o, and CNR2 k/o mice reveal altered immune cell populations To gain a comprehensive insight into the spatial distribution of immune cells and stromal cell types within EM lesion architecture of UnD and DD lesions of WT, CNR1 k/o, and CNR2 k/o mice, we employed IMC analysis. This approach aimed to elucidate the impact of CNR1 and CNR2 absence on the cellular composition and organization of EM lesions in mice. The schematic representation of the IMC procedure (Figure 6A ) outlines the steps involved in this analysis. Following the acquisition of two regions of interest (ROI) per section (based on the H&E stain), single-cell segmentation (Figure 6B ) and subsequent segmentation quality assessment (Figure 6C ) were performed. After batch effect correction of samples, non-linear dimensionality reduction of the sample type revealed a distinct expression pattern of immune cells and cell state markers between UnD and DD lesions, as well as differences between the genotypes (Figure 6D ). After unsupervised phenotyping and labeling of the different cell types, uniform manifold approximation and projection (UMAP) dimensionality reduction further highlighted the key differences in cell composition between UnD and DD lesions (Figure 6E ). Overall, combined expression of the cell types of DD lesions from all three genotypes exhibited increased stromal compartments, decreased epithelial cells, and heightened macrophage infiltration compared to the expression of cell types from UnD lesions. Representative images illustrate the distribution of different cell types based on unsupervised clustering and labeling (Figure 7A ). Further analysis of the cell type distribution (Figure 7B ) through bar plots unveiled several differences. Although not significant, due to relatively low number of biological replicates, T cell expression was increased (CD4+ helper T cells and CD8+ cytotoxic T cells) in both UnD and DD lesions of CNR1 k/o and CNR2 k/o mice compared to WT (Figure 7C ). This observation highlights that resident T cells are not impacted in the absence of CNR1 and CNR2 within the endometriotic milieu. Intriguingly, in EM lesions from CNR1 k/o and CNR2 k/o, we saw significantly elevated expression of monocytes/macrophages (Figure 7D ), stromal cells (Figure 7E ) and hallmarks of EM such as proliferation and vascularization (Figure 7F ) demonstrating an altered microenvironment in the absence of these receptors. To comprehend cell-cell interactions and their implications, we conducted cellular neighborhood (CN) analysis. This approach grouped cells based on information within their direct spatial vicinity and identified intricate spatial relationships among diverse cell types within the lesion microenvironment. This analysis revealed distinct clustering patterns across different cell types within the lesion architecture of the DD lesions from WT, CNR1 k/o, and CNR2 k/o mice (Supplementary Figure 6 ). Immune cells predominantly clustered together in CN 4, while other cell types (stroma, epithelial cells, and vasculature) exhibited distinct clustering patterns across CN 6, 3, and 8 in DD lesions (Figure 7G ). Although most of the immune cell types clustered together in the UnD lesions, cell types of the lesion architecture clustered distinctly compared to the DD lesions (Supplementary Figure 6 ). This clustering emphasizes the interplay between immune cells and the broader cellular components of the lesions. In summary, our comprehensive investigation has unveiled intricate spatial relationships among immune cells and diverse cell types within EM lesions in mice. The observed alterations in T cell expression, coupled with stromal dynamics, in CNR1 k/o and CNR2 k/o lesions underscore the pivotal roles of these receptors in shaping the endometriotic microenvironment. Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 15 of 36Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 15 of 36 Figure 5 In-vitro validation of CNR2 deficiency on CD3 T cell viability and functionality in conditions representative of EM lesion microenvironment A Representative gating of percentage live, CD3+ total T cells from WT and CNR2 k/o mice activated with or without PMA/Ionomycin cocktail in the presence or absence of TNFα and media control. Graph with live gating shows count on the y axis and live/dead-KO525 marker on the x axis. B Bar graphs of percentage live population of CD3+ total T cells from CNR2 k/o mice show a significant decrease in the viability of cells activated with PMA/ionomycin with or without TNFα. Whereas, no significant changes were observed in the CD3+ total T cells from WT mice as well as from CNR2 k/o mice in media. C Activation of CD3+ T cells of CNR2 k/o mice with PMA/ionomycin affected proliferation of CD4+ helper T cells specifically, with or without the presence of INFa when compared to both their media control and WT controls. D No significant changes were observed in the proliferative CD8+ cytotoxic T cells from CNR2 k/o mice compared to their WT controls across different activation and non-activation groups. Ordinary twoway ANOVA with Tukey’s post hoc test was performed to assess statistical significance. **p<0.05, **** p < 0.0001. Data presented as mean ± SD. Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 16 of 36Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 16 of 36 Figure 6 Imaging mass cytometry spatial profiling of immune cell distribution and cellular patterns in EM lesions in CNR1 k/o, CNR2 k/o, and WT mice A The IMC data collection and analysis workflow outlines the steps involved in gaining comprehensive insights into the spatial distribution of immune cells and relevant cell types within UnD and DD EM-like lesions of WT, CNR1 k/o, and CNR2 k/o mice. B, C Representative images showing the single-cell segmentation performed following the acquisition of 2 regions of interest (ROI) per section (3 biological samples per genotype) and segmentation quality of the data after segmentation analysis was conducted, respectively. D Non-linear dimensionality reduction after batch effect correction showed distinct expression patterns of immune cells and cell state markers between UnD and DD lesions. DD lesions from the CNR1 k/o and CNR2 k/o mice showed expression pattern that was significantly different from the DD lesions of WT mice, as well as compared to UnD lesions among different genotypes. E UMAP dimensionality reduction highlighted key cell types and differences in composition between UnD and DD lesions. DD lesions exhibited increased stroma and fibroblasts, decreased epithelial cells, and heightened macrophage infiltration compared to UnD lesions. Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 17 of 36Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 17 of 36 Figure 7 Imaging mass cytometry revealed altered cellular composition and neighborhoods in EM lesions from CNR1 k/o, CNR2 k/o, and WT mice A Representative image showing the distribution of different cell types within EM lesions (n = 2–3 per tissue type) based on unsupervised clustering and labeling. B Stacked bar plots reveal the distribution of various cell types within UnD and DD lesions of CNR1 k/o and CNR2 k/o mice compared to WT mice. C Increased CD3+ T cells and CD4+ helper T cells expression was found in the DD, EM lesions from CNR1 and CNR2 k/o mice compared to WT mice highlighting that T cells residing in the lesions were not affected. D CD11b+ monocyte and F4/80+ macrophage expression was significantly increased in the DD, EM lesions from mice lacking CNR1 and CNR2 compared to the WT controls. E Vimentin expressing stromal compartments that predominantly make up the EM lesions were also significantly increased in the DD lesions from CNR1 k/o and CNR2 k/o mice compared to WT mice. F Hallmark features of EM lesions, such as proliferation (Ki67+) and vascularization (CD31+) were significantly increased in the DD, EM lesions from mice lacking CNR1 and CNR2 compared to the WT controls. Combined, it highlights the effect on early lesion development and further progression through sustained proliferation due to dysregulated CNR1 and CNR2. G Heatmap representation of the CN analysis show distinct clustering patterns observed in the DD lesions among the different genotypes, where immune cells mainly clustered together in CN 4, while other cell types such as stroma, epithelial cells, and vasculature exhibited distinct clustering patterns across CN 6, 3, and 8, respectively. Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 18 of 36

Emerging evidence from our previously reported findings and others, implicated dysregulation of ECS, comprising CNR1 and CNR2 canonical receptors along with their EC ligands, in EM pathophysiology2 ,30 . The ECS is involved in several physiological processes including (but not limited to) pain perception, immune regulation, and reproductive functions31 ; CNR1 and CNR2 are expressed in immune cells, nerve tissues, and serve as critical regulators of reproductive processes including decidualization and embryo implantation32 ,33 . The etiology of EM has been speculated to be routed in defective decidualization and retrograde menstruation of the endometrial fragments combined with ECS dysregulation8 ,9 ,34 . While it is plausible that decreased ECS function influences EM lesion initiation, progression, and severe pain experience, it is not clear whether ECS dysfunction actively contributes to EM pathogenesis, or whether it represents a secondary consequence of alterations occurring within the refluxed endometrial tissue, leading to establishment of EM lesions. Keeping this central dogma in view and to provide insights into early events of EM pathogenesis, we induced EM in both CNR1 k/o and CNR2 k/o mice utilizing syngeneic, DD and UnD uterine endometrial fragments. Absence of CNR1 and CNR2 did not influence systemic levels of ECS ligands but the lesion microenvironment displayed significant changes in the levels of OEA and PEA, suggesting a tissue-specific response. One intriguing aspect of ECS involvement in EM is its role in decidualization, a process pivotal for uterine receptivity to embryo implantation and successful pregnancy, that may also contribute to EM establishment35 . Although both CNR1 and CNR2 are active in decidualization, CNR1 may have a more prominent role. Absence of CNR1 and CNR2 show compromised decidualization in mice in a CNR1-dependent manner validated through in-vitro studies36 . Similarly, in our study, EM lesions (both UnD and DD) from mice lacking CNR1 showed significantly more DEGs (2088), compared to CNR2 (287) and WT (2). Genes essential for decidualization such as IGFBP2, BMP3, PTGDR, WNT7a, and ESR1 were downregulated in the DD, EM lesions from CNR1 k/o mice compared to their UnD counterparts. This further reinforces the role of CNR1 in the uterine and EM lesion microenvironment, including their role in decidualization response. Moreover, the interplay between CNR1 and CNR2 are important since CNR2 contribute to immunomodulation, which is a key process during decidualization37 ,38 . Even though retrograde menstruation is considered the main mechanism by which endometrial fragments reach the peritoneal cavity and implant to form EM lesions, the retrograded menstrual debris itself does not undergo decidualization. However, some EM lesions in the peritoneal cavity, under the influence of estrogen and progesterone, can undergo decidualization as the lesions can exist in different evolutionary stages, from active red lesions to quiescent white lesions39 . Given the complexity of ECS signalling and compensatory mechanisms, we focused our investigation on the immune dysregulation aspect of EM pathophysiology. Our findings suggest that altered ECS dynamics during decidualization disrupt ECS signaling, leading to dysregulation of immune responses and aberrant cellular behavior. Indeed, immune dysfunction is a hallmark of EM29 ,40 , and ECS could play a crucial role in shaping immune responses particularly through its impact on T cell function yet there is no clear evidence. Alterations in T cell populations and functions have been associated with EM progression, suggesting their vital role in EM pathogenesis and maintenance41 ,42 . Our flow cytometry analysis revealed significant alterations in immune cell populations in mice bearing EM lesions, with a notable absence of CD3+ T cells, CD4+ helper T cells, and CD8+ cytotoxic T cells specifically in CNR2 k/o mice. Mechanistic in- vitro studies further confirmed an aberrant T cell response in CNR2 k/o mice, as with T cell receptor activation and stimulation there was decreased viability. Combined, our findings show that CNR2 is critical in T cell survival upon TCR activation with pathogen-associated molecular Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 19 of 36 patterns (PAMPs)/danger-associated molecular patterns (DAMPs) or antigen-mediated signals. These findings also shed light on a previously unrecognized role of CNR2 in EM-associated adaptive immune dysfunction given the critical role of T cells in immune surveillance and regulation. Furthermore, speculation of EM being a cause of ECS dysfunction could be of importance since CNR2 was found to be reduced in the lesions of EM patients, as shown by our previous study2 . In addition, the bulk RNA sequencing strengthens the finding of dysregulation of T cell-related genes in CNR2 k/o EM lesions. The observed downregulation of T cell-related genes such as CD3e, CD3g, GATA3, and CTLA4 is consistent with the diminished CD3+ T cell populations and highlights the relevance of CNR2 in T cell-mediated immune responses within the endometriotic microenvironment. KEGG pathway analysis of differentially expressed immune-related genes in CNR2 k/o DD lesions further revealed that Th1, Th2, and Th17 cell differentiation pathways were impacted, and the previous literature confirms dysregulation of these pathways in EM pathophysiology43 ,44 . Additionally, our in-vitro functional assay showing CD4+ helper T cells being affected (proliferation) more than the CD8+ cytotoxic T cell subset further adds to the subset specific behaviour of CNR2. Our results provide a missing link between the ECS and immune system functioning during EM. To gain insights into the early features of lesion initiation and establishment, we conducted IMC analysis of EM lesions across genotypes and different lesion types (DD and UnD). DD lesions from CNR1 and CNR2 k/o mice showed higher T cell residing in the lesions with increased stromal compartments and monocytes/macrophages population compared to WT lesions. Stromal cells contribute to the early development of EM lesions by promoting inflammation, angiogenesis, fibrosis, and immune modulation45 –47 . Additionally, the interaction between macrophages and stromal cells is important in EM, with the NLRP3 inflammasome playing a role in lesion development48 . Studies have implicated macrophages in EM lesion growth where they support angiogenesis (formation of blood vessels) by producing pro-angiogenic factors such as vascular endothelial growth factor (VEGF)49 –51 . Given the combined increase in proliferation, endothelial marker, and monocytes/macrophages in EM lesions from mice potentially indicates that they could modulate the early lesion microenvironment in the event of CNR1 and CNR2 dysregulation. Based on the proportion of these macrophages to certain phenotypes, such as M1 or M2, would dictate lesion development and subsequent progression. Further studies are required to tease out molecular interactions of CNR1 and CNR2 with specific immune cell subsets in a complex EM lesion microenvironment and determine how it contributes to establishment of blood supply and lesion survival. The dysregulation of the ECS, as evidenced by the altered expression of CNR1 and CNR2 in our mouse model of EM, appears to have far-reaching consequences on the cellular and molecular landscape of endometriotic lesions. Since CNR1 is widely expressed in the central nervous system where it regulates pain perception, mood, and other neurological processes, the dysregulation of CNR1 signaling may impact the sensory innervation and pain responses associated with the EM31 . Additionally, CNR1 has been shown to modulate immune cell function, including the production of pro-inflammatory cytokines52 . The loss of CNR1 signaling in immune cells infiltrating the endometriotic lesions likely contribute to the altered immune profiles observed in our study. In contrast, CNR2 is predominantly expressed in immune cells, such as macrophages, lymphocytes, and natural killer cells53 . This receptor plays a crucial role in the regulation of immune responses, including the modulation of cytokine production, cell migration, and proliferation. The significant reduction in CD3+ T cells in the peritoneal cavity and spleen of CNR2 knockout mice suggests that the loss of CNR2 may have a profound impact on T cell homeostasis and function in EM dependent manner, as this was not the case in sham operated mice. This impairment in T cell function has direct consequences on the adaptive immune response, as evidenced by the altered gene expression profiles and pathways related to immune function in Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 20 of 36 our transcriptomic analysis. But we haven’t conducted specific mechanistic experiments to tease out interplay between immune response and endometriosis lesion development in our model systems. Several limitations should be acknowledged in our study. Firstly, understanding the homeostatic aspects of ECS, both with and without the presence of CNR1 and CNR2, remains a complex challenge. While our global k/o mouse models provide valuable insights, further research utilizing targeted k/o specific to the uterus could offer a more precise understanding of their contributions to uterine physiology and further implications in EM establishment. The use of mouse models to study EM has inherent limitations due to species differences and the inability to fully recapitulate the human disease. The molecular and cellular complexities associated with DD and UnD endometrial tissues, as well as the timing of EM induction in these mice, may not perfectly mirror the human condition. No significant baseline alterations were observed in the immune profile between the CNR1 and CNR2 k/o and the WT mice without EM induction. However, the uterine environment has not been assessed to understand the baseline immune profile between the k/o and WT mice. These limitations emphasize the need for future investigations to enhance the translational relevance of our findings and further our understanding of the complex interplay between ECS, decidualization, and EM pathogenesis. In conclusion, our study offers evidence for the involvement of CNR1 and CNR2 dysregulation in EM pathogenesis. Through an integrative analysis of transcriptomic profiles, immune cell dynamics, and spatial relationships within EM lesions from mice, we unveil the intricate interactions between ECS, immune responses, and cellular changes in EM. By identifying potential mechanisms through which ECS disruption could impact EM, our research provides a foundation for the development of targeted therapies addressing the ECS’s influence on EM. These findings will advance our understanding of EM and lead to innovative therapeutic strategies to manage this complex disorder. Data availability Bulk mRNA sequencing data is provided in the supplementary files (Supplementary Data 4) and IMC data generated in this study has been deposited in Mendeley Data (https://data.mendeley.com /datasets/2ptns5yhzh/2 ). Code availability All the codes used in the current study are from previously published articles, as cited in the article. Authors do not report original code.

We thank Dr Alexandra Furtos and Karine Gilbert from the Regional Mass Spectrometry Centre at Université de Montréal for designing and performing mass-spectrometry evaluation; Dr Yuhong Wei and the Single Cell and Imaging Mass Cytometry Platform (SCIMAP) at McGill University Goodman Cancer Institute for processing, labeling, and acquiring samples for IMC imaging; Brittney Armitage-Brown from the Animal Care Services at Queen’s University for breeding mice utilized in this study. This work was supported by funding from the Canadian Institutes of Health Research (CIHR-394340) to C. T and M. K. Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 21 of 36 Author information Authors and Affiliations Contributions H. L., and C. T. designed and conceived experiments; H. L., K. Z., Y. W., P. Y., D. S., and A. M., conducted experiments. H. L., K. Z., and P. Y., analyzed results; H. L., and C. T., wrote the manuscript, generated the figures, and wrote the figure legend. C. T., and M. K., supervised the project and obtained research funding. All authors discussed the results and commented on the manuscript. Competing interests The authors declare no competing interests. Additional Declarations: The authors declare no competing interests. Funding: This research was supported with funds from Canadian Institutes of Health Research (CIHR) Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 22 of 36Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 22 of 36 Supplementary Figure 1 DEGs of bulk RNA sequencing between the UnD lesions from CNR1 k/o and CNR2 k/o compared to WT controls. A, B The volcano plots for DD lesions of CNR1 k/o and CNR2 k/o compared to WT, respectively. Log2 fold change is represented on the x-axis and log10 Q-value (FDR adjusted) as the y-axis. Vertical dotted lines on the x-axis indicate ± 1-fold change and vertical dotted line on the y-axis indicate Q-value of 0.05. C, D KEGG pathway analysis of DEGs of CNR1 k/o UnD lesions and CNR2 k/o UnD lesions compared to WT controls, respectively. Gene Number represents the number of DEGs enriched in the pathway. Rich Ratio shows the ratio of enriched DEGs to background genes and Q-value indicates significance, with a value closer to zero being more significant and is corrected by Benjamini-Hochberg method. Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 23 of 36Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 23 of 36 Supplementary Figure 2 KEGG pathway analysis of immune specific DEGs. A, B Immune specific genes that were differentially expressed were subjected to KEGG pathway analysis between CNR1 k/o UnD lesions and CNR2 k/o UnD lesions compared to WT UnD controls, respectively. Supplementary Figure 3 Gating panel representing T cells from splenocytes. A-G, Splenocytes stained for CD3 on the y-axis and CD11b on the x-axis among WT, CNR1 k/o, and CNR2 k/o mice with EM like condition, as well as CNR1 k/o and CNR2 k/o naive and sham-operated controls. Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 24 of 36Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 24 of 36 Supplementary Figure 4 Flow cytometry analysis of immune cell phenotypes in the splenocytes of WT, CNR1 k/o and CNR2 k/o mice with EMS. A-F Bar plot (mean ± SD) representation of splenocytes (SP) stained for CD3+ total T cells, CD4+ helper T cells, CD8+ cytotoxic T cells, CD19+ B cells, CD11b+ monocytes and F4/80 monocytes/macrophages of all the genotypes with EM lesions, respectively. n = 5-7 individual biological samples per genotype. Statistical analyses were performed using the ordinary one- way ANOVA with Holm-Sidak post hoc test. * p < 0.05, ** p < 0.01, *** p < 0.001 and **** p < 0.0001 Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 25 of 36Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 25 of 36 Supplementary Figure 5 In vitro functional assay and flow cytometry evaluation of activated CD3 T cells from naïve WT and CNR2 k/o mice. A, B Flow cytometry gating strategies for CD3+ T cells to identifiy the different phenotypes and functional state, respectively. C, Bar plots representing the percentage positive live cells that are double positive for proliferation (Ki67) and IFNγ markers. D, Bar plots showing the percentage positive live cells that are negative for Ki67 and positive for JFNy. Statistical analyses were performed using the ordinary one-way ANOVA with Holm-Sidak post hoc test. * p < 0.05, ** p < 0.01, *** p < 0.001 and **** p < 0.0001. Data presented as mean ± SD. Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 26 of 36Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 26 of 36 Supplementary Figure 6 IMC and cellular neighbourhoods (CN) in UnD, EMS lesions from CNR1 k/o, CNR2 k/o and WT mice. A, B Representative image of 8 distinct cell types from CN analysis of DD and UnD lesions from WT, CNR1 k/o, and CNR2 k/o mice, respectively. C Heatmap representation of CN analysis shows distinct clustering patterns observed in the UnD lesions among the different genotypes. The clustering reveals distinct spatial patterns of immune cell populations within the UnD lesions, which appear to differ from the observations in Figure 7G . This suggests potential spatial heterogeneity in the immune landscape of EM like lesions under conditions of decidualization. Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 27 of 36

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(1996) Vascular endothelial growth factor is produced by peritoneal fluid macrophages in endometriosis and is regulated by ovarian steroids Journal of Clinical Investigation 98 Klein T. W. (2005) Cannabinoid-based drugs as anti-inflammatory therapeutics Turcotte C., Blanchet M. R., Laviolette M, Flamand N. (2016) The CB2 receptor and its role as a regulator of inflammation Cellular and Molecular Life Sciences 73 Editors Reviewing Editor Sang Jun Han Baylor College of Medicine, Houston, United States of America Senior Editor Tadatsugu Taniguchi University of Tokyo, Tokyo, Japan Reviewer #1 (Public Review): Summary: The endocannabinoid system (ECS) components are dysregulated within the lesion microenvironment and systemic circulation of endometriosis patients. Using endometriosis mouse models and genetic loss of function approaches, Lingegowda et al. report that canonical ECS receptors, CNR1 and CNR2, are required for disease initiation, progression, and T-cell dysfunction. Strengths: The approach uses genetic approaches to establish in vivo causal relationships between dysregulated ECS and endometriosis pathogenesis. The experimental design incorporates both bulk and single-cell RNAseq approaches, as well as imaging mass spectrometry to characterize the mouse lesions. The identification of immune-related and T-cell-specific changes in the lesion microenvironment of CNR1 and CNR2 knockout (KO) mice represents a significant advance Weaknesses: Although the mouse phenotypic analyses involves a detailed molecular characterization of the lesion microenvironment using genomic approaches, detailed measurements of lesion size/burden and histopathology would provide a better understanding of how CNR1 or CNR2 loss contributes to endometriosis initiation and progression. The cell or tissue-specific effects of the CNR1 and CNR2 are not incorporated into the experimental design of the studies. Although this aspect of the approach is recognized as a major limitation, global CNR1 and CNR2 KO may affect normal female reproductive tract function, ovarian steroid hormone levels, decidualization response, or lead to preexisting alterations in host or donor tissues, which could affect lesion establishment and development in the surgically induced, syngeneic mouse model of endometriosis. https://doi.org/10.7554/eLife.96523.2.sa2 51. 52. 53. Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 31 of 36 Reviewer #2 (Public Review): Summary: The endocannabinoid system (ECS) regulates many critical functions, including reproductive function. Recent evidence indicates that dysregulated ECS contributes to endometriosis pathophysiology and microenvironment. Therefore, the authors further examined the dysregulated ECS and its mechanisms in endometriosis lesion establishment and progression using two different endometrial sources of mouse models of endometriosis with CNR1 and CNR2 knockout mice. The authors presented differential gene expressions and altered pathways, especially those related to the adaptive immune response in CNR1 and CNR2 ko lesions. Interstingly, the T-cell population was dramatically reduced in the peritoneal cavity lacking CNR2, and the loss of proliferative activity of CD4+ T helper cells. Imaging mass cytometry analysis provided spatial profiling of cell populations and potential relationships among immune cells and other cell types. This study provided fundamental knowledge of the endocannabinoid system in endometriosis pathophysiology. Strengths: Dysregulated ECS and its mechanisms in endometriosis pathogenesis were assessed using two different endometrial sources of mouse models of endometriosis with CNR1 and CNR2 knockout mice. Not only endometriotic lesions but also peritoneal exudate (and splenic) cells were analyzed to understand the specific local disease environment under the dysregulated ECS. Providing the results of transcriptional profiles and pathways, immune cell profiles, and spatial profiles of cell populations support altered immune cell population and their disrupted functions in endometriosis pathogenesis via dysregulation of ECS. L386: Role of CNR2 in T cells: Finding nearly absent CD3+ T cells in the peritoneal cavity of CNR2 ko mice is intriguing. Interpretation of the results is well-described in discussion. Weaknesses: The study was terminated and characterized 7 days after EM induction surgery without the details for selecting the time point to perform the experiments. The authors also mentioned that altered eutopic endometrium contributes to the establishment and progression of endometriosis. This reviewer agrees L324-325. If so, DEGs are likely identified between eutopic endometrium (with/without endometriosis lesion induction) and ectopic lesions. It would be nice to see the data (even though using publicly available data sets). Figure 7 CDEF. Please add the results of the statistical analyses and analyzed sample numbers. L444-450 cannot be reviewed without them. This reviewer agrees L498-500. In contrast, retrograded menstrual debris is not decidualized. The section could be modified to avoid misunderstanding. The authors addressed all my concerns. I do not have any comments. https://doi.org/10.7554/eLife.96523.2.sa1 Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 32 of 36 Author response: The following is the authors’ response to the original reviews. Public Reviews: Reviewer #1 (Public Review): Summary: The endocannabinoid system (ECS) components are dysregulated within the lesion microenvironment and systemic circulation of endometriosis patients. Using endometriosis mouse models and genetic loss of function approaches, Lingegowda et al. report that canonical ECS receptors, CNR1 and CNR2, are required for disease initiation, progression, and T-cell dysfunction. Strengths: The approach uses genetic approaches to establish in vivo causal relationships between dysregulated ECS and endometriosis pathogenesis. The experimental design incorporates both bulk and single-cell RNAseq approaches, as well as imaging mass spectrometry to characterize the mouse lesions. The identification of immune-related and T-cell-specific changes in the lesion microenvironment of CNR1 and CNR2 knockout (KO) mice represents a significant advance Weaknesses: Although the mouse phenotypic analyses involve a detailed molecular characterization of the lesion microenvironment using genomic approaches, detailed measurements of lesion size/burden and histopathology would provide a better understanding of how CNR1 or CNR2 loss contributes to endometriosis initiation and progression. The cell or tissue-specific effects of the CNR1 and CNR2 are not incorporated into the experimental design of the studies. Although this aspect of the approach is recognized as a major limitation, global CNR1 and CNR2 KO may affect normal female reproductive tract function, ovarian steroid hormone levels, decidualization response, or lead to preexisting alterations in host or donor tissues, which could affect lesion establishment and development in the surgically induced, syngeneic mouse model of endometriosis. We appreciate the reviewer's thoughtful and constructive feedback. We agree that the additional measurements of lesion size/burden and histopathology would provide valuable insights into the specific contributions of CNR1 and CNR2 to endometriosis progression. However, the focus of this study was on assessing the alterations in complex immune microenvironment due to the absence of CNR1 and CNR2, given their close relation in regulating immune cell populations. We will plan to incorporate these measurements in future studies to further strengthen the understanding of the disease pathogenesis. Regarding the potential effects of global knockout, the reviewer raises a valid concern. To address this, we will explore cell and/or tissue-specific knockout models in future experiments to better isolate the direct effects of CNR1 and CNR2 on the disease process, while minimizing potential confounding factors from systemic alterations. Reviewer #2 (Public Review): Summary: The endocannabinoid system (ECS) regulates many critical functions, including reproductive function. Recent evidence indicates that dysregulated ECS contributes to Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 33 of 36 endometriosis pathophysiology and the microenvironment. Therefore, the authors further examined the dysregulated ECS and its mechanisms in endometriosis lesion establishment and progression using two different endometrial sources of mouse models of endometriosis with CNR1 and CNR2 knockout mice. The authors presented differential gene expressions and altered pathways, especially those related to the adaptive immune response in CNR1 and CNR2 ko lesions. Interestingly, the T-cell population was dramatically reduced in the peritoneal cavity lacking CNR2, and the loss of proliferative activity of CD4+ T helper cells. Imaging mass cytometry analysis provided spatial profiling of cell populations and potential relationships among immune cells and other cell types. This study provided fundamental knowledge of the endocannabinoid system in endometriosis pathophysiology. Strengths: Dysregulated ECS and its mechanisms in endometriosis pathogenesis were assessed using two different endometrial sources of mouse models of endometriosis with CNR1 and CNR2 knockout mice. Not only endometriotic lesions, but also peritoneal exudate (and splenic) cells were analyzed to understand the specific local disease environment under the dysregulated ECS. Providing the results of transcriptional profiles and pathways, immune cell profiles, and spatial profiles of cell populations support altered immune cell population and their disrupted functions in endometriosis pathogenesis via dysregulation of ECS. In line 386: Role of CNR2 in T cells. The finding that nearly absent CD3+ T cells in the peritoneal cavity of CNR2 ko mice is intriguing. The interpretation of the results is well-described in the Discussion. Weaknesses: The study was terminated and characterized 7 days after EM induction surgery without the details for selecting the time point to perform the experiments. The authors also mentioned that altered eutopic endometrium contributes to the establishment and progression of endometriosis. This reviewer agrees with lines 324- 325. If so, DEGs are likely identified between eutopic endometrium (with/without endometriosis lesion induction) and ectopic lesions. It would be nice to see the data (even though using publicly available data sets). Figure 7 CDEF. The results of the statistical analyses and analyzed sample numbers should be added. Lines 444-450 cannot be reviewed without them. This reviewer agrees with lines 498-500. In contrast, retrograded menstrual debris is not decidualized. The section could be modified to avoid misunderstanding. We would like to thank the reviewer for insightful comments, suggestions and acknowledging the importance of the work presented in this manuscript. Regarding 7-day time point, we have provided rationale in lines 479-481, but agree that it isn’t sufficient and hence we have provided additional details on the selection of the 7-day time point for the experiments in methods section (Mouse model of EM). We have also noted the suggestion on providing comparison of differentially expressed genes in the eutopic endometrium vs ectopic lesions. Since there are publications comparing the eutopic vs ectopic gene expression patterns (PMIDs: 33868805 and 18818281), including a study exploring the ECS genes in the endometrium throughout different menstrual cycles (PMID: 35672435), we believe additional analysis using the same dataset may not yield new Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 34 of 36 information. However, we see the value in reviewer’s comment, and we will look at the gene expression patterns in the uterine vs endometriosis like lesions in our future studies with tissue or cell specific CNR1 and CNR2 knockout models to understand functional relevance of ECS in endometriosis initiation. Since the IMC study was exploratory for proof of concept, we did not have enough biological replicates for meaningful statistical validation (n = 2-3). We have clarified this information in the methods, results, and figure legends for appropriately representing the limitations of the current setup. Finally, we appreciate the feedback on the section discussing retrograded menstrual debris. Even though the menstrual debris may not be decidualized, some endometriotic lesions have the ability to decidualize based on their response to estrogen and progesterone in a cycling manner (PMID: 26450609), similar to the endometrium in the uterine cavity. We have clarified this in the revised MS. Recommendations for the Authors: Reviewer #1 (Recommendations For The Authors): The mechanism of how alterations in ECS contribute to the observed cellular and molecular changes is unclear. Connecting CNR1 or CNR2 function to a specific cell type or cellular process would provide a more detailed understanding of how dysregulated ECS contributes to endometriosis pathogenesis. We agree that integrating the functions of CNR1 or CNR2 to specific cell types or cellular processes would strengthen the mechanistic insights presented in our study. This would help elucidate specific pathways by which dysregulated ECS leads to the alterations in immune cell populations, gene expression profiles, and other key aspects of endometriosis development and progression. This is a rapidly evolving field and at this stage, we do not have published information to reflect on this aspect in the revised manuscript. (1) As mentioned in the text, the ECS components being studied are widely expressed and may affect multiple aspects of endometriosis pathogenesis and symptomatology. However, the cell or tissue-specific effects of the CNR1 and CNR2 are not incorporated into the experimental design of the studies. Although these limitations are mentioned in the discussion, it is important to know if global CNR1 and CNR2 KO affect normal female reproductive tract function, ovarian steroid hormone levels, decidualization response, or if preexisting alterations in host or donor tissues affect lesion development in the surgically induced, syngeneic mouse model of endometriosis. This would also be the case in studies on immune system dysfunction or lesion microenvironment, as it is possible preexisting immune system dysfunction following CNR1 or CNR2 loss could alter the disease trajectory and lead to a misinterpretation of the findings. Some of these potential confounders could be addressed using crossover approaches in Figure 1A experimental design, but the donor tissues are reported to be matched to the recipients based on genotype. The reviewer raised an excellent point that the widespread expression of the ECS components studied in our manuscript may affect multiple aspects of endometriosis pathogenesis and symptomatology. Indeed, the cell or tissue-specific effects of CNR1 and CNR2 knockout are not fully incorporated into our experimental design, which could lead to potential confounding factors that may affect the interpretation of some of our findings. However, as outlined in our previous comments, we will incorporate the tissue/cell specific knockout, as well the crossover approaches to elucidate if the loss of CNR1 and CNR2 function is lesion driven in future studies. We agree that it is important to understand the impact of Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 35 of 36 global CNR1 and CNR2 knockout on normal female reproductive tract function, ovarian steroid hormone levels, decidualization response, and other potential preexisting alterations in the host or donor tissues that could influence lesion development in the syngeneic mouse model of endometriosis. As outlined in the MS (lines 59-62), there are studies highlighting pregnancy specific impact including implantation and impaired primary decidual zone formation. We did not find any baseline alterations in the systemic immune profiles between the CNR1 and CNR2 knockout mice and the WT mice without EM induction. However, the uterine environment has not been assessed to understand the baseline immune profile between the knockout mice and WT mice. We agree with the reviewer that, the possibility of preexisting immune system dysfunction following CNR1 or CNR2 loss could alter the disease trajectory related to immune system dysfunction or lesion microenvironment. We have highlighted this in the limitations section. (2) The phenotypic characterization of the endometriosis mouse model with or without CNR1 or CNR2 KO is very limited. To better understand how the observed cellular and molecular alterations correlate with endometriosis pathogenesis and severity CNR1 and CNR2 K/O mice, a detailed characterization of lesion size differences and histopathology should be made. Importantly, the histopathological characterization of the lesions would complement the imaging mass spectrometry findings. We agree that more detailed characterization of the endometriosis lesions in our CNR1 and CNR2 knockout mouse models are required. As evident for our several previous publications, we have focused on detailed histopathological characterization of endometriotic lesions in our syngeneic mouse model of endometriosis including a multiple time course study (Symons et al, 2020, FASEB). In the present investigation, we focused on cataloging spatial and transcriptomic changes as we do not currently have any information on the global influence of CNR1 and CNR2 knockout on endometriosis lesion microenvironment, since we prioritized this aspect, we were not able to provide detailed histological assessment of lesions. However, the IMC analysis provides a detailed, spatially resolved profile of the cellular composition and interactions within the endometriotic lesions, which we believe offers valuable insights into the mechanisms by which the dysregulated ECS may contribute to endometriosis pathogenesis. This quantitative, high-dimensional approach complements the transcriptional profiling and other analyses we have performed. (3) Given the effect sizes and variance observed with the ECS ligand measurements, an N = 4-5 biological samples for mouse phenotypic studies seems too low. The reviewer raises a valid point about low sample size. As elaborated earlier, this was a proof of principle study to capture biologically significant alterations within lesion and surrounding peritoneal microenvironment in the absence of CNR1, CNR2 receptors. This information is crucial for establishing the potential mechanisms by which the dysregulated ECS may contribute to the pathogenesis of endometriosis. Now that we have established the framework and baseline understanding of immune-inflammatory alterations, we will refine our future experimental approaches and include more samples if becomes necessary. Reviewer #2 (Recommendations For The Authors): It is hard to read the labeling of figures. Please increase the font size of each figure. We have increased the font size of the labels where necessary to improve the readability. Supplementary Data 1, Table 1 seems like Supplementary Table 1. Please use the same labeling of the Supplementary tables and figures to avoid confusion. Harshavardhan Lingegowda et al., 2024 eLife. https://doi.org/10.7554/eLife.96523.2 36 of 36 We have updated the labeling accordingly and ensured that all supplementary tables and figures are consistently labeled. This reviewer suggests depositing RNA-seq and IMC data to NCBI etc. and listing the accession number in the MS. Thank you for your recommendation to deposit the RNA-seq and imaging mass cytometry (IMC) data from our study in public repositories such as NCBI. We appreciate your suggestion, as data sharing is an important aspect of scientific transparency and reproducibility. Bulk mRNA sequencing data has been attached as a supplementary file and IMC data has been deposited on Mendeley Data (DOI: 10.17632/2ptns5yhzh.1). Please clarify L363. We have clarified this in the revised MS. The revised text now reads: “However, we did not find the same differences (T cell-related genes) in the UnD lesions of CNR2 k/o mice. Moreover, UnD lesions of CNR2 k/o mice showed significantly low number of DEGs (11 compared to 65 in the DD lesions from CNR2 k/o mice) suggesting a decidualization dependent response (Supplementary Data 3).” Figure 7B: It is hard to see/understand the results in L438-440. It might be helpful if % is added to the figure. We have added more tick marks to the y-axis of Figure 7B to make it easier for the reader to interpret the percentages of the different cell types. Figure 7 legend: 2nd D should be G. We have revised the legend accordingly. Supplementary Figure 6: It seems immune cells are clustered in CN1, which is different from Figure 7. To easily understand Suppl Fig 6AB, please add some details in the legend. We have revised the legend as suggested. The revised legend now reads: “A, B Representative image of 8 distinct cell types from CN analysis of DD and UnD lesions from WT, CNR1 k/o, and CNR2 k/o mice, respectively. C Heatmap representation of CN analysis shows distinct clustering patterns observed in the UnD lesions among the different genotypes. The clustering reveals distinct spatial patterns of immune cell populations within the UnD lesions, which appear to differ from the observations in Figure 7G. This suggests potential spatial heterogeneity in the immune landscape of EM like lesions under conditions of decidualization.” https://doi.org/10.7554/eLife.96523.2.sa0