High content analysis identifies unique morphological features of reprogrammed cardiomyocytes

Abstract

Direct reprogramming of fibroblasts into cardiomyocytes is a promising approach for cardiac regeneration but still faces challenges in efficiently generating mature cardiomyocytes. Systematic optimization of reprogramming protocols requires scalable, objective methods to assess cellular phenotype beyond what is captured by transcriptional signatures alone. To address this question, we automatically segmented reprogrammed cardiomyocytes from immunofluorescence images and analyzed cell morphology. We also introduce a method to quantify sarcomere structure using Haralick texture features, called SarcOmere Texture Analysis (SOTA). We show that induced cardiac-like myocytes (iCLMs) are highly variable in expression of cardiomyocyte markers, producing subtypes that are not typically seen in vivo. Compared to neonatal mouse cardiomyocytes, iCLMs have more variable cell size and shape, have less organized sarcomere structure, and demonstrate reduced sarcomere length. Taken together, these results indicate that traditional methods of assessing cardiomyocyte reprogramming by quantifying induction of cardiomyocyte marker proteins may not be sufficient to predict functionality. The automated image analysis methods described in this study may enable more systematic approaches for improving reprogramming techniques above and beyond existing algorithms that rely heavily on transcriptome profiling.

Striated myocyte structural integrity: Automated analysis of sarcomeric z-discs

“…In the absence of the actin co-stain, α-actinin pixels can no longer be classified as z-lines or off-target staining, and ZlineDetection can no longer decouple these two metrics and instead reports the simple α-actinin OOP that has been used previously [5,18,30,32]. Existing algorithms that quantify sarcomere architecture from only a z-line stain, isolate z-lines from off-target staining by using signal processing to identify double wavelets in an image [72], quantify local, micron-scale organization [73], or manually remove off-target staining [5,18,30,32]. These previous works have used a range of metrics to then classify tissue or cell architecture, many of which describe similar properties to those provided by ZlineDetection.…”

“…These previous works have used a range of metrics to then classify tissue or cell architecture, many of which describe similar properties to those provided by ZlineDetection. For example, the local sarcomere organization algorithm developed by Sutcliffe et al [73] scored isolated cells without actin co-staining (Figs 4 and 6d in Sutcliffe et al [73]) with a sarcomere organization index, which ranges from 0-2. The sarcomere organization index [73] was~0.1 for a primary cell they qualitatively classified as "disorganized", but~0.4 for both a "well-organized" primary cell and a reprogrammed cardiomyocyte, even though the latter had disorganized myofibrils and some α-actinin punctate patterns indicative of premyofibrils.…”

“…By contrast, the α-actinin OOP, which measures organization globally, was 0.2, 0.52, 0.17 for the three cell types, respectively. As such, the cell-tissue scale OOP and the sarcomere scale organization index [73] provide qualitatively different measurements, but the key difference is in the scale at which the measurement is happening. Because tissue level organization influences the strength of tissue contraction [19], we believe a global metric is essential.…”

Cell states beyond transcriptomics: integrating structural organization and gene expression in hiPSC-derived cardiomyocytes

“…As a second step, we implemented a previously described global alignment measurement (Sutcliffe et al, 2018) that captured the large-scale alignment of myofibrils, an important attribute of overall structural organization of cardiomyocytes that is not captured by the local structural metric. The three global order parameters comprising this measurement describe the regularity, alignment, and spacing of the myofibrils within each individual cell independently of the total number or density of myofibrils (Supplemental Figure 3J-K).…”

Direct cell-fate conversion of somatic cells: Toward regenerative medicine and industries

“…148),165), 177) The analysis of miRNAs in other direct reprogramming methods may result in their improvement. Other molecular and cellular analyses, such as signal transduction, 174),183),197) metabolic remodeling, 198) time-lapse imaging, 170) and cell morphological studies, 168) have been performed. Recently, single-cell analyses, such as single-cell RNA sequencing (scRNA-seq), have been performed in many direct reprogramming studies.…”