Date of Degree


Document Type


Degree Name





Stephen Redenti

Subject Categories

Biochemistry | Bioinformatics


Microfluidic Devices; Photoreceptor Precursor Cells; Retinal Progenitor Cells; Stem-Cell Based Therapy; Systems Pharmacology; Transplantation


A common feature of several heterogeneous diseases that result in retinal degeneration (RD) is photoreceptor loss, leading to an irreversible decline in visual function [15-17]. There are no cell replacement treatments available for RD diseases such as age-related macular degeneration (AMD) and retinitis pigmentosa (RP). Although many RD cases are of a genetic origin, a promising strategy to treat diseased phenotypes is by replacing lost photoreceptor cells, for synaptic integration and restoration of visual function. To advance photoreceptor-replacement strategies as a practical therapy, in light of highly restricted integration rates reported across studies, this body of research focused on defining the molecular mechanisms facilitating migration of transplantable photoreceptor precursors in the retinal microenvironment. To accomplish this work we utilized bioinformatics, bioengineering and molecular biologic techniques for a systems level approach.

Guided by classic neuronal migration models, we hypothesized that transplanted photoreceptor precursors navigate to specific retinal lamina in part due to cell surface receptor expression and in response to spatially gradated directional ligand cues provided by the host retinal microenvironment. Given the neural origin of the mammalian retinal system, we also predicted that these chemotactic receptor-ligand pairs trigger intracellular signaling events in migrating photoreceptors analogous to canonical migration pathways exhibited by neuronal precursors. For a comprehensive account of these motility-deterministic biochemical interactions, we first performed in silico bioinformatics modeling of PPC transplantation into light-damaged retina by matching microarray datasets between PPC receptors and ligands in the light-damaged retinal microenvironment. We then refined the gene expression network data to focus on motility deterministic interactions at the interface of the PPC cell-surface receptors and extracellular ligands of the damaged retina. Our in silico network modeling generated a library of ligand-receptor pairs associated with cellular movement specific for this retinal transplantation paradigm and the intracellular signaling pathways induced by candidate chemotactic ligands.

Working from predicted interactions of in silico paired PPC receptors and retinal ligands, we then performed cell migration analysis to evaluate whether exposure to stromal derived factor-1α (SDF-1α) would guide the motility of PPCs and RPCs in vitro. We also assessed the chemotactic effects of epidermal growth factor (EGF) on RPCs. Cell surface expression of C-X-C chemokine receptor type 4 (CXCR4) receptors on PPCs and RPCs, and EGF receptor expression on RPCs were verified via immunocytochemical staining and validated by Western blot analysis. Boyden chamber analysis was used as an initial high-throughput screen to verify the motogenic effects of the ligands on PPCs and RPCs. We determined that RPC motility was optimally stimulated in these chambers by EGF concentrations in the range of 20-400ng/ml, with decreased stimulation at higher concentrations, suggesting concentration-dependence of EGF-induced motility. Both RPCs and PPCs also demonstrated a concentration-dependent chemotactic response to an optimal SDF-1α concentration of 100ng/ml.

Using bioinformatics downstream signaling pathway analysis of the EGF and SDF-1α ligands in a retina-specific gene network, we predicted a chemotactic function for EGF involving the MAPK and JAK-STAT intracellular signaling pathways. Based on targeted inhibition studies, we show that ligand binding, phosphorylation of EGFR and activation of the intracellular STAT3 and PI3Kinase signaling pathways are necessary to drive RPC motility. The JAK-STAT pathway was also implicated in transducing similar motogenic effects on PPCs with SDF-1α induction.

To test our hypothesis of the gradated nature of ECM ligand effects on both ontogenetic retinal cell types, we employed engineered microfluidic devices to generate quantifiable steady-state gradients of EGF and SDF-1α coupled with live-cell tracking, and analyzed the dynamics of individual RPC and PPC motility. Microfluidic analysis, including center of mass and maximum accumulated distance, revealed that EGF induced motility is chemokinetic in EGFR expressing RPCs with optimal activity observed in response to low concentration gradients. On the other hand, PPCs and RPCs exhibited significant chemotaxis towards the source of SDF-1α with longer accumulated Euclidean distances and Center of Mass (COM) compared to controls. We also ascertained that receptor mediated signaling was requisite for ligand-induced motility by using the CXCR4 inhibitor, AMD 3100, to antagonize the SDF-1α receptor. CXCR4 receptor inhibition resulted in decreases of PPC and RPC movement in uniform and steady state gradients for a number of migration indices measured.

To advance translational application of the characterized chemotactic signaling potential of transplantable photoreceptor precursors, we performed computational drug analysis of our newly identified motility-deterministic networks, to develop a library of FDA approved drugs and small molecules predicted to potentially influence the expression of target motility signaling mechanisms in photoreceptor progenitor cells. Using the Expression2Kinases software and LINCS drug computational algorithm, we were able to identify pharmacological drug targets that modulate the biochemical activity of transcriptional regulatory genes which govern the expression of candidate receptor protein targets, and provide preliminary results validating the up-regulatory effect of candidate drug aminophenazone on SDF-1α receptor CXCR4 expression. Results from this study demonstrate the applicability of our systems level in silico modeling of matched transplantable cell surface-receptors and transplantation site ligands to predict molecular signaling guiding migration. Verification of in silico predictions, using molecular and microfluidic analysis provide important data for defining cell response properties to specific ligands present during transplantation into the retinal microenvironment. The drug computational analysis provides a translational perspective to our in silico modeling paradigms extending its applicability.

Future studies will validate the functionality of resolved ligand-receptor pairs from our in silico library and characterize down-stream signaling guiding motility and homing. This systems level paradigm can effectively be applied to defining the molecular basis of transplantable cell migration in vivo toward improved efficiency for repair of retina and other neural tissue types.


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