4D-Healing Data-Driven Drug Discovery in Wound Healing

The healing of wounds is a complex, multifactorial process that remains incompletely understood. Europe faces an increasing number of costly chronic wounds profoundly affecting patients` quality of life. The wound healing process is highly dynamic and heterogeneous and its understanding could provide insights into regenerative medicine. Contribution of the different cell lineages cannot be assessed by bulk transcriptomics analysis. Additionally, a static snapshot by single cell analyses may be uninformative. 4D-HEALING will map the four spatiotemporal dimensions of human wound healing in an unprecedented way: the transcriptome of thousands of cells from an in vivo monitored human wound will be analysed by RNAseq at the single cell level. We will model the transcriptional dynamics of cell lineages involved in all phases of healing, from injury to resolution. To gather positional information we propose a novel computational tool to predict "cell docking", based on the probability of cell-to- cell interactions and producing a neighbouring map that will be validated by annotating situ positional information of cells (multiplexed hybridization approach). The emerged knowledge will provide a 4D map of the cell types involved in human wound healing that will allow us to create a dynamic mathematical model of the process, to disentangle the crosstalk among cell signalling and interactions, transitional states and position during healing. These models integrated together with FDA-approved drug databases will permit informed choices on molecular candidates that can be pharmacologically modulated. Candidate compounds will be tested in ex vivo human skin organ cultures mimicking acute and chronic wound environments. The resulting leads will undergo standard drug development programs. The project will deliver data-driven, comprehensive understanding of the human wound healing process and in vitro proof of concept of a novel topical therapy to enhance chronic wound healing.

Wound healing is a highly dynamic and heterogeneous process, which makes the dissection of the contribution of the different cell lineages by bulk transcriptomics analysis challenging. Thus, a static snapshot by single-cell analyses might be uninformative. In 4D-HEALING we are mapping the four spatiotemporal dimensions of human wound healing in an unprecedented way: the transcriptome of thousands of cells from an in vivo monitored human wound by RNA-Seq at the single-cell level. We collected 3 mm scalp skin punches from two donors on 5 different days in three sets: one for dermis cell disaggregation, the second for dermis and epidermis cell disaggregation, and the third for histology and spatial RNA analysis. We performed single-cell RNA-Seq on the dermis and dermis-epidermis datasets and with the results we are modelling the transcriptional dynamics of cell lineages involved in all phases of healing, from injury to resolution. To gather positional information, we are developing novel computational tools to predict "cell docking" and produce a neighbouring map that will be validated by annotating the positional information of cells. The emerging knowledge is providing a 4D map of the cell types involved in human wound healing allowing us to create a dynamic mathematical model, to disentangle the crosstalk among cell signalling and interactions, transitional states and position during the healing process. These models integrated together with FDA-approved drug databases are permitting informed choices on molecular candidates that can be pharmacologically modulated. Our single-cell RNA-Seq data analysis revealed that in fibroblasts MMP-2 and cathepsin K are upregulated at Day 0 and then slowly regressing during Days 2 and 3, both well known to be involved in the extracellular matrix remodelling during wound healing and present in fresh scars, but are also highly up-regulated in diabetic chronic wounds. MMP-2 can be targeted by using Angiotensin- Converting Enzyme inhibitors like Captopril and Lisinopril. We plan to try this discovery out on 2D and 3D for Epidermolysis Bullosa (EB), but as the nature of EB chronic wounds is different from the ones in diabetes, we will do it in combination with some other drugs. We will test the effect of candidate drugs on 2D and 3D- preparations based on iPSC lines we already made, both for WT and EB. The resulting leads will undergo standard drug development programs. Thus, the project is delivering a data-driven, comprehensive understanding of the human wound healing process and in vitro proof of concept of a novel topical therapy to enhance chronic wound healing. Understanding wound healing will shed light on regenerative medicine.