Poster #47 - Katherine Beigel

Evaluation of potential ligand-receptor interactions between mechanically stressed human visceral smooth muscle cells and other cell types in the human bowel

Sharon M. Wolfson (MD)1,2, Katherine Beigel (MS)3, Sierra E. Anderson (MS)1, Brooke Deal (PhD)1, Molly Weiner1,4, Se-Hwan Lee (PhD)6, Deanne Taylor (PhD)1,2,3, Su Chin Heo (PhD)4,5,6,7,8, Robert O. Heuckeroth (MD, PhD)1,2**, Sohaib K. Hashmi (MD, PhD)1,4,5,9** ** SKH and ROH contributed equally to this work Affiliations 1The Children's Hospital of Philadelphia Research Institute and the Abramson Research Center, 3615 Civic Center Blvd, Philadelphia, PA 19104, USA 2Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA 3The Department of Biomedical and Health Informatics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA 4Perelman School of Medicine at the University of Pennsylvania, 3400 Civic Center Blvd, Philadelphia, PA 19104, USA 5Department of Bioengineering, The University of Pennsylvania School of Engineering and Applied Science, 220 S 33rd St, Philadelphia, PA 19104, USA 6McKay Orthopaedic Research Laboratory, Department of Orthopaedic Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. 7Center for Engineering Mechanobiology, University of Pennsylvania, Philadelphia, PA, USA. 8Translational Musculoskeletal Research Center, Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA. 9Department of Internal Medicine, Division of Gastroenterology and Hepatology, Hospital of the University of Pennsylvania, 3400 Civic Center Blvd, Philadelphia, PA 19104, USA

Intercellular communication can be inferred from gene expression data by examining the likelihood of ligand-receptor interaction. This study demonstrates the use of the published R package NicheNet with bulk RNA-sequencing (RNA-seq) and single nuclei RNA-sequencing (snRNA-seq) data for prediction of ligand-receptor interactions, using a modified version of NicheNet's workflow and prior model. This method was used to predict how ligands expressed by stressed human intestinal smooth muscle cells (HISMCs) may affect other cells in the bowel wall. Bowel smooth muscle experiences mechanical stress constantly during normal function, and unusual mechanical stressors in various disease states. Here, we test the hypothesis that pathologic mechanical stress could alter transcription to induce smooth muscle phenotypic class switching. Primary HISMCs, seeded on scaffolds, were subjected to pathologic, high frequency (1 Hz) uniaxial 3% cyclic stretch (loaded) or left unstretched (unloaded) in culture for 6 hours. Total RNA-seq was used to define loading-induced changes in gene expression. Loaded HISMCs had a less contractile phenotype, with increased expression of synthetic SMC genes, proinflammatory cytokines, and altered expression of axon guidance molecules, growth factors and morphogens. Many of the differentially expressed genes encode secreted ligands that could influence smooth muscle cells, but also on other cells present in the bowel wall. To explore cell types that may be affected by ligands that are differentially expressed between the loaded and unloaded conditions, we utilized a published snRNA-seq atlas of human large intestine and our modified NicheNet workflow and prior model to infer potential ligand-receptor interactions and potential downstream effects of ligand-receptor signaling. While more research is needed to validate predicted ligand-receptor interactions, the results of this analysis suggest that altered mechanical stress induces broad changes in HISMC gene expression that may have the potential to influence function of other cell types in the bowel wall.