bioRxivCell BiologyPreprint
Transcriptomic profiling of normal and glaucomatous trabecular meshwork cells in a tissue-like soft ECM environment
Rajanya GhoshiD, Rachel HadvinaiD, Ana Nicolle StratiD, Preethi S. GanapathyiD, William Daniel StameriD, Kate E. KelleriD, Yutao LiuiD, Samuel HerbergiD
Abstract
Purpose. Trabecular meshwork (TM) dysfunction contributes to the elevated intraocular pressure in primary open-angle glaucoma. To better understand the molecular signature distinguishing glaucomatous from normal TM cells, we interrogated their genome-wide transcriptomic differences in a tissue-like soft extracellular matrix (ECM) microenvironment. Methods. Primary human glaucomatous and normal TM cell strains (N = 5 each) from three independent laboratories were plated on bioengineered collagen type I/hyaluronic acid/elastin-like polypeptide ECM hydrogels in 10% FBS media for 4-5 days, then serum-free media for 2 days. Cell-laden hydrogels were homogenized in TRIzol for RNA isolation, quality assessment, and library preparation, followed by paired-end 100-bp Illumina sequencing. Differential expression was assessed using DESeq2, including glaucoma status, originating laboratory, and donor age/sex in the model. Differentially expressed genes (DEGs) were defined as p < 0.05 and |fold change| [≥] 2, followed by Gene Ontology (GO) enrichment and QIAGEN Ingenuity Pathway Analysis (IPA). Results. In total, 588 DEGs distinguished the glaucomatous from the normal TM transcriptome (393 up-regulated in glaucomatous TM; 195 up-regulated in normal TM, i.e., down-regulated in glaucomatous TM). GO and IPA causal analyses revealed three coordinated disease programs: (i) TGF-{beta}/Wnt-driven ECM remodeling and fibrosis, (ii) NF-{kappa}B-associated inflammation, and (iii) a hypoxia/metabolic-stress program linked to p300/CREBBP chromatin co-activation. Conclusions. These data define a transcriptomic signature of glaucomatous TM cells when cultured in a soft physiologic ECM microenvironment, independent of the originating laboratory, with three mechanistic axes (ECM/fibrosis, inflammation, hypoxia/metabolism), and nominate p300 (encoded by EP300) as a candidate upstream node integrating these programs.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- Citations
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