Tissue-engineered cardiac patch for advanced functional maturation of human ESC-derived cardiomyocytes.

Human embryonic stem cell-derived cardiomyocytes (hESC-CMs) provide a promising source for cell therapy and drug screening. Several high-yield protocols exist for hESC-CM production; however, methods to significantly advance hESC-CM maturation are still lacking. Building on our previous experience with mouse ESC-CMs, we investigated the effects of 3-dimensional (3D) tissue-engineered culture environment and cardiomyocyte purity on structural and functional maturation of hESC-CMs. 2D monolayer and 3D fibrin-based cardiac patch cultures were generated using dissociated cells from differentiated Hes2 embryoid bodies containing varying percentage (48-90%) of CD172a (SIRPA)-positive cardiomyocytes. hESC-CMs within the patch were aligned uniformly by locally controlling the direction of passive tension. Compared to hESC-CMs in age (2 weeks) and purity (48-65%) matched 2D monolayers, hESC-CMs in 3D patches exhibited significantly higher conduction velocities (CVs), longer sarcomeres (2.09 ± 0.02 vs. 1.77 ± 0.01 μm), and enhanced expression of genes involved in cardiac contractile function, including cTnT, αMHC, CASQ2 and SERCA2. The CVs in cardiac patches increased with cardiomyocyte purity, reaching 25.1 cm/s in patches constructed with 90% hESC-CMs. Maximum contractile force amplitudes and active stresses of cardiac patches averaged to 3.0 ± 1.1 mN and 11.8 ± 4.5 mN/mm(2), respectively. Moreover, contractile force per input cardiomyocyte averaged to 5.7 ± 1.1 nN/cell and showed a negative correlation with hESC-CM purity. Finally, patches exhibited significant positive inotropy with isoproterenol administration (1.7 ± 0.3-fold force increase, EC50 = 95.1 nm). These results demonstrate highly advanced levels of hESC-CM maturation after 2 weeks of 3D cardiac patch culture and carry important implications for future drug development and cell therapy studies.

Cross-hemispheric collaboration and segregation associated with task difficulty as revealed by structural and functional connectivity.

Although it is known that brain regions in one hemisphere may interact very closely with their corresponding contralateral regions (collaboration) or operate relatively independent of them (segregation), the specific brain regions (where) and conditions (how) associated with collaboration or segregation are largely unknown. We investigated these issues using a split field-matching task in which participants matched the meaning of words or the visual features of faces presented to the same (unilateral) or to different (bilateral) visual fields. Matching difficulty was manipulated by varying the semantic similarity of words or the visual similarity of faces. We assessed the white matter using the fractional anisotropy (FA) measure provided by diffusion tensor imaging (DTI) and cross-hemispheric communication in terms of fMRI-based connectivity between homotopic pairs of cortical regions. For both perceptual and semantic matching, bilateral trials became faster than unilateral trials as difficulty increased (bilateral processing advantage, BPA). The study yielded three novel findings. First, whereas FA in anterior corpus callosum (genu) correlated with word-matching BPA, FA in posterior corpus callosum (splenium-occipital) correlated with face-matching BPA. Second, as matching difficulty intensified, cross-hemispheric functional connectivity (CFC) increased in domain-general frontopolar cortex (for both word and face matching) but decreased in domain-specific ventral temporal lobe regions (temporal pole for word matching and fusiform gyrus for face matching). Last, a mediation analysis linking DTI and fMRI data showed that CFC mediated the effect of callosal FA on BPA. These findings clarify the mechanisms by which the hemispheres interact to perform complex cognitive tasks.

Dissecting the Functional Impacts of Non-Coding Genetic Variation

A large proportion of the variation in traits between individuals can be attributed to variation in the nucleotide sequence of the genome. The most commonly studied traits in human genetics are related to disease and disease susceptibility. Although scientists have identified genetic causes for over 4,000 monogenic diseases, the underlying mechanisms of many highly prevalent multifactorial inheritance disorders such as diabetes, obesity, and cardiovascular disease remain largely unknown. Identifying genetic mechanisms for complex traits has been challenging because most of the variants are located outside of protein-coding regions, and determining the effects of such non-coding variants remains difficult. In this dissertation, I evaluate the hypothesis that such non-coding variants contribute to human traits and diseases by altering the regulation of genes rather than the sequence of those genes. I will specifically focus on studies to determine the functional impacts of genetic variation associated with two related complex traits: gestational hyperglycemia and fetal adiposity. At the genomic locus associated with maternal hyperglycemia, we found that genetic variation in regulatory elements altered the expression of the HKDC1 gene. Furthermore, we demonstrated that HKDC1 phosphorylates glucose in vitro and in vivo, thus demonstrating that HKDC1 is a fifth human hexokinase gene. At the fetal-adiposity associated locus, we identified variants that likely alter VEPH1 expression in preadipocytes during differentiation. To make such studies of regulatory variation high-throughput and routine, we developed POP-STARR, a novel high throughput reporter assay that can empirically measure the effects of regulatory variants directly from patient DNA. By combining targeted genome capture technologies with STARR-seq, we assayed thousands of haplotypes from 760 individuals in a single experiment. We subsequently used POP-STARR to identify three key features of regulatory variants: that regulatory variants typically have weak effects on gene expression; that the effects of regulatory variants are often coordinated with respect to disease-risk, suggesting a general mechanism by which the weak effects can together have phenotypic impact; and that nucleotide transversions have larger impacts on enhancer activity than transitions. Together, the findings presented here demonstrate successful strategies for determining the regulatory mechanisms underlying genetic associations with human traits and diseases, and value of doing so for driving novel biological discovery.