PROJECT SUMMARY/ABSTRACT
Human induced pluripotent stem cells (hiPSCs) have emerged as useful tools in research due to their capacity
to differentiate into any adult somatic cell type, including cardiomyocytes (CMs). These hiPSC-CMs have
potential use for developing preclinical models of both normal, disease-state, and even patient-specific heart
function. However, hiPSC-CM are currently limited in their clinical translatability. One of the primary challenges
in deriving cardiac tissue models from hiPSCs is heterogeneity of cardiac differentiation outcomes. Heterogeneity
in hiPSC cardiac differentiation results in low, inconsistent CM yield as well as limited control over CM subtype.
Overcoming differentiation heterogeneity will improve scalability and lower the cost of utilizing hiPSC-CM based
tissue models, as current differentiation methods achieve increased homogeneity by discarding cells that fail to
differentiate into CMs or specific CM subtypes, which is inefficient. This proposal hypothesizes that heterogeneity
in terminally differentiated hiPSCs arises from heterogeneity between hiPSC clonal lineages that leads to
variable response to differentiation cues. Accordingly, accounting for these variable responses should improve
homogeneity and consistency of hiPSC cardiac differentiation. To test this theory, a cell barcoding platform,
ClonMapper, will be used to address heterogeneity of hiPSC-CM differentiation. ClonMapper uses unique,
heritable single-guide RNA (sgRNA) barcode sequences to label cells and track clonal lineage dynamics in
response to experimental conditions, such as differentiation cues. This can be used to resolve the transcriptomic
heterogeneity of clonal lineages in hiPSCs and connect it to the transcriptomic heterogeneity of those same
lineages at different timepoints in cardiac differentiation. Aim 1 of this proposal will verify if ClonMapper is
compatible with hiPSC cardiac differentiation by labelling hiPSC populations with sgRNA barcodes and
characterizing their pluripotency. Aim 2 will connect transcriptomic heterogeneity of hiPSC lineages to
heterogeneity at different timepoints. This will allow identification of which lineages diverge from an hiPSC-V-CM
fate and when, characterization of lineages as having high (HDE) or no/low differentiation efficiency (n/LDE),
and creation of gene expression signatures associated with HDE or n/LDE lineages. The gene expression
signatures of HDE and n/LDE lineages will be used in Aim 3 to identify gene modulators that can be used as
added differentiation stimuli to shift n/LDE lineage gene expression to mimicking HDE lineage gene expression,
i.e., shift towards an hiPSC-V-CM state. The results from these studies will identify a potential source of
heterogeneity in hiPSC cardiac differentiation outcomes, elucidate the underlying mechanisms that cause this,
and establish methods for reducing heterogeneity to improve quantity and consistency of specific hiPSC-CM
subtype yield (in this case hiPSC-V-CM), advancing the clinical relevance of hiPSC-CMs.
