Genetic mutations to the Lamin A/C gene (LMNA) can cause heart disease, but the mechanisms making cardiac tissues uniquely vulnerable to the mutations remain largely unknown. Further, patients with LMNA mutations have highly variable presentation of heart disease progression and type. In vitro patient-specific experiments could provide a powerful platform for studying this phenomenon, but the use of induced pluripotent stem cell-derived cardiomyocytes (iPSC-CM) introduces heterogeneity in maturity and function thus complicating the interpretation of the results of any single experiment. We hypothesized that integrating single cell RNA sequencing (scRNA-seq) with analysis of the tissue architecture and contractile function would elucidate some of the probable mechanisms. To test this, we investigated five iPSC-CM lines, three controls and two patients with a (c.357-2A>G) mutation. The patient iPSC-CM tissues had significantly weaker stress generation potential than control iPSC-CM tissues demonstrating the viability of our in vitro approach. Through scRNA-seq, differentially expressed genes between control and patient lines were identified. Some of these genes, linked to quantitative structural and functional changes, were cardiac specific, explaining the targeted nature of the disease progression seen in patients. The results of this work demonstrate the utility of combining in vitro tools in exploring heart disease mechanics.

As sarcomeres produce the force necessary for contraction, assessment of sarcomere order is paramount in evaluation of cardiac and skeletal myocytes. The uniaxial force produced by sarcomeres is ideally perpendicular to their z-lines, which couple parallel myofibrils and give cardiac and skeletal myocytes their distinct striated appearance. Accordingly, sarcomere structure is often evaluated by staining for z-line proteins such as alpha-actinin. However, due to limitations of current analysis methods, which require manual or semi-manual handling of images, the mechanism by which sarcomere and by extension z-line architecture can impact contraction and which characteristics of z-line architecture should be used to assess striated myocytes has not been fully explored. Challenges such as isolating z-lines from regions of off-target staining that occur along immature stress fibers and cell boundaries and choosing metrics to summarize overall z-line architecture have gone largely unaddressed in previous work. While an expert can qualitatively appraise tissues, these challenges leave researchers without robust, repeatable tools to assess z-line architecture across different labs and experiments. Additionally, the criteria used by experts to evaluate sarcomeric architecture have not been well-defined. We address these challenges by providing metrics that summarize different aspects of z-line architecture that correspond to expert tissue quality assessment and demonstrate their efficacy through an examination of engineered tissues and single cells. In doing so, we have elucidated a mechanism by which highly elongated cardiomyocytes become inefficient at producing force. Unlike previous manual or semi-manual methods, characterization of z-line architecture using the metrics discussed and implemented in this work can quantitatively evaluate engineered tissues and contribute to a robust understanding of the development and mechanics of striated muscles.

Nuclear shape defects are a distinguishing characteristic in laminopathies, cancers, and other pathologies. Correlating these defects to the symptoms, mechanisms, and progression of disease requires unbiased, quantitative, and high-throughput means of quantifying nuclear morphology. To accomplish this, we developed a method of automatically segmenting fluorescently stained nuclei in 2D microscopy images and then classifying them as normal or dysmorphic based on three geometric features of the nucleus using a package of Matlab codes. As a test case, cultured skin-fibroblast nuclei of individuals possessing LMNA splice-site mutation (c.357-2A>G), LMNA nonsense mutation (c.736 C>T, pQ246X) in exon 4, LMNA missense mutation (c.1003C>T, pR335W) in exon 6, Hutchinson-Gilford Progeria Syndrome, and no LMNA mutations were analyzed. For each cell type, the percentage of dysmorphic nuclei, and other morphological features such as average nuclear area and average eccentricity were obtained. Compared to blind observers, our procedure implemented in Matlab codes possessed similar accuracy to manual counting of dysmorphic nuclei while being significantly more consistent. The automatic quantification of nuclear defects revealed a correlation between in vitro results and age of patients for initial symptom onset. Our results demonstrate the method's utility in experimental studies of diseases affecting nuclear shape through automated, unbiased, and accurate identification of dysmorphic nuclei.