The primary goal of my research program is to investigate the mechanisms of stem cell differentiation, especially in the context of the cardiovascular system. Driven by this goal, we also seek to generate new technologies that advance stem cell biology and promote translation of stem cell research into clinical practice. The primary strength of my program is the ability to span multiple subdisciplines within both basic science (e.g., stem cell biology, cell-cell fusion and extracellular matrices) and engineering (e.g., 3D bioprinting, cytometry instrumentation and microfabrication) fields. Our work has expanded fundamental models of stem cell differentiation and provided a path for improved clinical stem cell transplantation and cardiovascular tissue engineering. Recent pivotal works are shown below.
FIELD SUMMARY
Sci Transl Med. 2016 Jun 8;8(342):342ps13. doi: 10.1126/scitranslmed.aad2304.
Distilling complexity to advance cardiac tissue engineering.
I. Engineering Extracellular Matrices
The impact of cell-ECM interactions on cell fate processes has only recently been examined for stem cells, the preferred cell source for many tissue engineering applications. Critically lacking is a clear understanding of the impact of stem cell-ECM interactions on induction or repression of differentiation. We have shown that ECM interactions alone are capable of driving lineage-specific differentiation of stem cells and our group is particularly interested in the differentiation of cardiac lineages in this context. We are also interested in using ECM formulations best supportive of cardiac cell health and maturation to build engineered tissues.
Sci Rep. 2015 Dec 21;5:18705. doi: 10.1038/srep18705.
An integrated statistical model for enhanced murine cardiomyocyte differentiation via optimized engagement of 3D extracellular matrices.
Circ Res. 2017, 120:1318-1325 .
Myocardial tissue engineering with cells derived from human induced-pluipotent stem cells and a native-like, high-resolution, 3-dimensionally printed scaffold
Circ Res. 2020, 127:207-224.
In Situ Expansion, Differentiation, and Electromechanical Coupling of Human Cardiac Muscle in a 3D Bioprinted, Chambered Organoid
II. Stem Cell Fusion and Tissue Homeostasis
Many groups have now shown stem cells can spontaneously fuse with parenchymal cell types including cardiomyocytes. Our group is keen to understand how fusion products contribute to tissues, temporal changes in phenotype, and aberrant outcomes of fusion, including cancer metastasis.
Stem Cells Transl Med. 2015 Jun;4(6):685-94. doi: 10.5966/sctm.2014-0198. Epub 2015 Apr 6.
Tracking fusion of human mesenchymal stem cells after transplantation to the heart.
FASEB J. 2015 Sep;29(9):4036-45. doi: 10.1096/fj.15-271098. Epub 2015 Jun 17.
Apoptosis-induced cancer cell fusion: a mechanism of breast cancer metastasis.
Sci Rep. 2016 Mar 21;6:23270. doi: 10.1038/srep23270.
Single-cell RNA-seq reveals activation of unique gene groups as a consequence of stem cell-parenchymal cell fusion.
APL Bioeng. 2018, 2(3):031907.
Breast tumor cell hybrids form spontaneously in vivo and contribute to breast tumor metastases.
III. Technology Development to Improve Stem Cell Analyses and Transplantation
The future of stem cell transplantation depends on the identification of noninvasive biomarkers to characterize cells and cell aggregates prior to transplantation. Characterization is needed minimally to define cell state and ideally to predict those cells best poised to contribute to a specific tissue type. We hypothesize that intrinsic metabolic signatures detected with multiphoton microscopy provide a noninvasive means to assess stem cell state. We have therefore coupled multiphoton optics to a flow cytometry system to perform such analyses.
Integr Biol (Camb). 2013 Jul 24;5(7):993-1003. doi: 10.1039/c3ib20286k. Epub 2013 Jun 13.
Large particle multiphoton flow cytometry to purify intact embryoid bodies exhibiting enhanced potential for cardiomyocyte differentiation.
Cytometry A. 2014 Apr;85(4):353-8. doi: 10.1002/cyto.a.22436. Epub 2014 Jan 17.
Noninvasive sorting of stem cell aggregates based on intrinsic markers.