Comparison of cardiogenic potential of induced Pluripotent Stem Cells (iPSCs) generated from murine various tissues: the role of epigenetic memory in reprogramming
Bibliographic record
Abstract
Introduction Coronary artery disease (CAD), i.e. myocardial infarction and ischemic cardiomyopathy, is the global leading cause of death. Ischemia leads to loss of functional cardiomyocytes, which contributes to a variety of types of heart failure. Although conventional treatments including pharmacological therapy and coronary revascularization procedures exist, novel therapeutic approaches are still needed. The prospect of stem‐cell‐based therapies might have considerable therapeutic potential. Induced pluripotent stem cells (iPSCs) can be generated from a variety of somatic cells as a potential resource of replacement cells, making them ideal cellular models to provide a renewable source of cardiomyocytes for cell‐based therapy. However, an ideal cell type with superior cardiomyocyte (CM) potential has yet to be identified. Masseter muscle cells (MMC) characterized as Isl‐1 + cells, a genetic marker associated with stem and progenitor states, also contribute to various cardiovascular lineages and have similar embryological origins. We postulate the regenerative potential of masseter muscle cell lineages may yield valuable developmental and clinical insights in the identification of a cell source capable of enhanced cardiomyocyte differentiation and may be used in cell‐based therapy. This study aims to study the role of epigenetic memory in the cardiogenic potential of different lineages of iPSC. Methods A variety of cell sources including masseter muscle cells (MMC), dermal fibroblasts (Fib), bone marrow mesenchymal cells (BMC), and Trunk skeletal muscle cells (TMC) from mouse were isolated. These cell sources were then transfected with Yamanaka's factors (Oct4, Sox2, c‐Myc, and Klf‐4) to generate four lineages of iPSCs. These four iPSC cell lineages were differentiated into iPSC‐CMs via 3‐D culture protocols and analyzed for differences in their differentiation potential as well as the efficiency of differentiation. Cardiomyocytes differentiation was analyzed by spontaneous contractions, immunostaining, flow cytometry test, and patch clamp. The epigenetic signatures of somatic cells, iPSCs, and derived Cardiomyocytes were analyzed by Real‐time PCR. Methylation study was used to evaluate epigenetic memory of four lineages of iPSCs. Results Spontaneous beating was observed in 80% colonies of MMC‐derived iPSC‐cardiomyocytes (MMC‐CM), which was significantly higher than other groups. Cardiac genes Isl‐1, Nkx2.5, and GATA4 were also significantly upregulated in MMC‐CM. MMC‐CM exerted robust cardiac functional phenotype, indicated by enhanced contractility and electrophysiological properties. Low methylation levels of the cardiac mesodermal gene (Isl‐1) in MMC and M‐iPSC were similar to neonatal cardiomyocytes and were maintained in MMC‐CM. Cardiac genes were epigenetically silenced in other somatic cells. Conclusion iPSCs derived from masseter muscle cell sources have better cardiogenic differentiation capabilities than other somatic cell sources. Epigenetic memory significantly contributes to the prominent cardiogenic potential of masseter‐derived iPSCs. Support or Funding Information National Institutes of Health grants (HL110740)
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".