ИСТИНА

Background/Objectives: Previously published data and the results of our own research suggest the significant role of T-cadherin in endothelial function under normal conditions and in pathology (https://doi.org/10.1016/j.ejcb.2021.151183). Our preliminary findings, investigating the mechanisms of endothelial dysfunction using an in vivo model of angiotensin 2-induced endothelial dysfunction in wild-type C57/Bl and T-cadherin knockout CDH13-/- mice, highlight the crucial role of T-cadherin. To further investigate the involvement of T-cadherin in the development of pulmonary pathologies, we conducted the transcriptome analysis of individual human lung cells (scRNAseq), constructed protein interaction maps using STRING analysis, and confirmed the bioinformatic data by RT-PCR analysis. Methods: We first utilized the GSE164829 series, comprising two datasets – WholeLungeDissociates and PrimaryPulmonaryEndothelialCells (DOI: 10.1161/CIRCULATIONAHA.120.052318) for bioinformatic analysis. Subsequently, we focused solely on the PrimaryPulmonaryEndothelialCells dataset (GSM5020383 - primary pulmonary arterial cells (HPAEC0), GSM5020384 - primary pulmonary venous cells (HPMEC0), GSM5020385 - primary pulmonary microvascular cells (HPVEC0)). Data analysis was conducted using the R package Seurat (v. 4.1.0). The first 30 components were applied, employing the FindClusters function with a resolution parameter set to 0.1. Cell type annotation was performed using the automatic cell type identification tool - R-package SingleR. To identify cellular targets and signaling partners of T-cadherin cascades, we utilized Protein-Protein Interaction Networks Functional Enrichment Analysis STRING: functional protein association networks (string-db.org). We examined the obtained clusters of endothelial cells with different levels of T-cadherin expression. Protein interaction maps were constructed for each cluster. Total RNA was reverse-transcribed to generate cDNA, followed by real-time polymerase chain reaction (PCR). Primer design was carried out using NCBI Primer-BLAST. Results: Bioinformatic analysis yielded 5 cell clusters expressing CDH13 (T-cadherin), with automatic typing as follows: 0 - arterial (EFNB2, SOX17, BMX, SEMA3G, HEY1, LTBP4, FBLN5, GJA5, GJA4); capillary (CA4, PRX, RGCC, SPARC, SGK1); 1 – venous (NR2F2, VCAM1, ACKR1, SELP); 2 – aerocytes (EDNRB, TBX2, FOXP2, CLEC4E, SPON2, PRKG, CHRM2, S100A4, EDA); 3 - microvascular cells (GPIHBP1, CD36, FCN3, BTNL9, BTNL8, CD14, IL7R, IL18R1); 4 – lymphatic (PROX1, LYVE1, FLT4, PDPN), 5 (blood cells). Co-expression of CDH13, CDH5 (VE-cadherin), and CTNNB1 (β-catenin) genes was detected in all clusters. Construction of protein-protein interaction maps using the STRING.ORG web platform revealed potential protein partners of T-cadherin, including CTNNB1, CDH5, CDH2, CAV1, BRCA1, DNMT1, SRFP1, and ADIPOR1. The bioinformatic findings were further validated through RT-PCR analysis. Total RNA was extracted from the human endothelial cell line Eahy926 (cells overexpressing T-cadherin or transfected with a control plasmid). RT-PCR confirmed the expression of target genes identified by bioinformatics. Endothelial cells overexpressing T-cadherin exhibited reduced mRNA levels of β-catenin, VE-cadherin, CDH2 (N-cadherin), CAV1 (caveolin 1), BRCA1, SRFP1, and AdipoR2. Conclusion: T-cadherin exhibits ubiquitous expression in both in endothelial cells in the lungs and endothelial cell line Eahy926 in vitro. Our bioinformatic analysis identified 5 distinct cell clusters expressing CDH13, which co-expressed CDH5 (VE-cadherin) and CTNNB1 (β-catenin) genes. Subsequently, RT-PCR analysis not only confirmed the expression of these target genes but also revealed that T-cadherin overexpression led to a reduction in the mRNA levels of β-catenin, VE-cadherin, CDH2 (N-cadherin), CAV1 (caveolin 1), BRCA1, SRFP1, and AdipoR2. These findings strongly suggest that T-cadherin plays a pivotal role in regulating the physiology of pulmonary endothelial cells. Grant References: The study was supported by the Russian Science Foundation, grant No. 19-75-30007, https://rscf.ru/project/19-75-30007/. This research was performed under the State Assignment # 03р-23/110-03 of Lomonosov Moscow State University.