Multiomics analysis reveals the mechanical stress-dependent changes in trabecular meshwork cytoskeletal-extracellular matrix interactions

Abstract

Trabecular meshwork (TM) tissue is subjected to constant mechanical stress due to the ocular pulse created by the cardiac cycle. This brings about alterations in the membrane lipids and associated cell–cell adhesion and cell–extracellular matrix (ECM) interactions, triggering intracellular signaling responses to counter mechanical insults. A loss of such response can lead to elevated intraocular pressure (IOP), a major risk factor for primary open-angle glaucoma. This study is aimed to understand the changes in signaling responses by TM subjected to mechanical stretch. We utilized multiomics to perform an unbiased mRNA sequencing to identify changes in transcripts, mass spectrometry- (MS-) based quantitative proteomics for protein changes, and multiple reaction monitoring (MRM) profiling-based MS and high-performance liquid chromatography (HPLC-) based MS to characterize the lipid changes. We performed pathway analysis to obtain an integrated map of TM response to mechanical stretch. The human TM cells subjected to mechanical stretch demonstrated an upregulation of protein quality control, oxidative damage response, pro-autophagic signal, induction of anti-apoptotic, and survival signaling. We propose that mechanical stretch-induced lipid signaling via increased ceramide and sphingomyelin potentially contributes to increased TM stiffness through actin-cytoskeleton reorganization and profibrotic response. Interestingly, increased phospholipids and diacylglycerol due to mechanical stretch potentially enable cell membrane remodeling and changes in signaling pathways to alter cellular contractility. Overall, we propose the mechanistic interplay of macromolecules to bring about a concerted cellular response in TM cells to achieve mechanotransduction and IOP regulation when TM cells undergo mechanical stretch.

Identification of the novel role of sterol regulatory element binding proteins (SREBPs) in mechanotransduction and intraocular pressure regulation

“…In our recent work (38) on HTM cells subjected to mechanical stress, we showed a significant increase in the N-SREBP2 that is involved in cholesterol biogenesis. To better understand the mechanosensing functionality of SREBPs, here we provide empirical evidence by utilizing multiple systems to qualitatively and quantitatively assess the potential changes in SREBPs localization under mechanical stress.…”

“…On the other hand, in vivo studies in SCAP f/f mice injected with AdCre confirmed that the molecular inactivation of SREBPs by knocking down SCAP significantly lowered IOP by 10 days post-injection. In our recent study, we observed that TM cells under mechanical stress showed increased SREBP2 protein levels (38). The SREBP2 is primarily known to contribute to cholesterol production.…”

“…HTM cells were subjected to cyclic mechanical stretch as published earlier (38). 2 h post stretch, cells were fixed and processed for IF analysis.…”

“…After determining the protein concentration and the immunoblotting process was performed as published earlier (38, 54). Blots were stripped using mild stripping buffer if required to reprobe for the loading control and multiple proteins within the same molecular weight range.…”

Reverse translation of artificial intelligence in glaucoma: Connecting basic science with clinical applications

“…For instance, genome-wide association studies (GWAS) have revealed hundreds of POAG-related genetic loci with consistent effects across ancestries ( 23 , 110 , 111 ); and whole-genome-based polygenic risk score enables the prediction of future glaucoma risks ( 112 ). Furthermore, multi-omics investigations can help identify the molecular signature for glaucoma predisposition ( 113 ), patient-specific tear composition ( 114 ), mechanical stress-derived trabecular meshwork cytoskeletal changes ( 115 ), and risk factors for IOP elevation ( 116 ). Integrating image data with multi-omics data (e.g., genomics, transcriptomics, proteomics, and metabolomics) using approaches such as spatial transcriptomics ( 117 ) may reveal novel genotype-phenotype associations and causal inferences, allowing the understanding of glaucoma-related disease etiology in a highly localized manner as well as the identification of more biologically-related glaucoma phenotypes.…”