Systems Biology-based tissue engineering

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BACKGROUND: Cell fate decisions are controlled by the integration of extrinsic signals and intrinsic effectors into gene regulatory networks (GRNs). Thus, by understanding the topology of GRNs, it is possible to predict and manipulate cell fate from a given input signal. Human pluripotent stem cells (hPSCs) represent the only non-transformed human cell lines. Thus, in combination with CRISPR-based genome engineering, hPSCs are also a powerful tool for fundamental and applied science and an ideal model in which to apply systems approaches and develop synthetic biology platforms. RECENT PROGRESS: During our current NSERC Discovery funding cycle, we drafted GRNs of human mesendoderm specification, which we used to optimize human skeletal muscle, cartilage, and vascular tissue engineering. Moreover, to develop more precise GRNs, we developed a novel algorithm and R-language based application, ExCluster, to identify and quantify differentially spliced transcripts from RNA-seq data. GOAL: The neural crest is an evolutionarily conserved transient population of migratory multipotent progenitor cells. The neural crest has been studied using lower vertebrate model organisms for over 150 years. Our goal is to delineate human neural crest GRNs and use them to drive directed differentiation and reprogramming to neural crest derivatives. OVERARCHING HYPOTHESES: 1) The high degree of evolutionary conservation in neural crest development will allow us to deduce high-resolution GRNs from which to engineer human neural crest derivatives. 2) Integration of transcriptional and post-transcriptional networks will generate high-resolution predictive GRNs of human neural crest specification and differentiation. EXPERIMENTAL DESIGN: Aim 1: We will integrate publicly available chick, frog, zebrafish, and mouse embryonic omics datasets which will be used to draft a reference neural crest GRN. Aim 2: We will use single cell omics profiling of hPSC neural crest differentiation to independently draft transcriptional networks. Aim 3: We will build post-transcriptional GRNs of NCC lineages. Aim 4: Tissue engineer neural crest lineages using directed differentiation and CRISPR-activated genetic reprogramming. TRAINING: The proposed research program will provide an excellent platform for interdisciplinary training of at least 3 PhD students, including two currently in my lab. IMPACT: For 15 years, our NSERC Discovery research program has driven technology development, tissue engineering and GRN modelling approaches, which we and others have then applied to translational research. Beyond the impact on tissue engineering, the tools and approaches that we develop as part of this program should impact additional fields such as synthetic biology and life and evolutionary sciences.