Paired single-cell imaging of calcium and expres-sion to map niches of identity and function
Clark, A. P.; Gergen, P.; Saucerman, J. J.
Show abstract
Cellular identity is often inferred from molecular markers, while function is measured independently, obscuring how these dimensions align at single-cell resolution. In cardiomyocytes, this disconnect is especially limiting, as calcium dynamics and subtype markers are typically assessed in bulk or separate cells then averaged across populations. In human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs), this gap has limited our ability to determine whether heterogeneity in electrophysiology and calcium handling reflects noise, maturation, or structured biological states. This lack of clarity is due in part to the lack of methods that directly link live functional measurements with molecular identity at single-cell resolution. Here, we introduce CARBONITE (Calcium Recordings Before Identification by Expression), a scalable single-cell imaging framework that pairs live calcium dynamics with protein expression and spatial phenotyping. Using high-content imaging in 96-well plates, CARBONITE integrates per-cell calcium transient features with immunofluorescent identification applied to cardiomyocyte subtype markers, enabling quantitative functional-molecular mapping within the same cells. Applying CARBONITE to mixed human induced pluripotent stem cell derived cardiomyocyte (iPSC-CM) populations reveals heterogeneity in calcium transient dynamics and marker expression within individual wells. Canonical atrial and ventricular markers capture only a subset of functional variability. Notably, calcium transient shape segregates cells into two discrete functional states that exhibit perinuclear ANP (atrial marker) enrichment and nucleation state (i.e., mono- vs. binucleation). Notably, these groups show know relationship to MYL2 (ventricular marker) expression. Binucleated cells are more likely to exhibit a spike-like calcium transient, identifying nucleation as a dominant and previously underappreciated axis of cardiomyocyte identity influencing calcium function. Together, these results establish CARBONITE as a functional multimodal single-cell platform that reveals organizational principles of cell identity, providing a foundation for dissecting functional niches in development and disease.
Matching journals
The top 8 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Prolonged β-Adrenergic Stimulation Disperses Ryanodine Receptor Clusters in Cardiomyocytes: Implications for Heart Failure 93%
- 3D-Cardiomics: A spatial transcriptional atlas of the mammalian heart 93%
- Standardised method for cardiomyocyte isolation and purification from individual murine neonatal, infant, and adult hearts 92%
Similar papers in this journal
- An Integrated Optogenetic and Bioelectronic Platform for Regulating Cardiomyocyte Function 92%
- Matrix architecture and mechanics regulate myofibril organization, costamere assembly, and contractility of engineered myocardial microtissues 91%
- 3D Bioprinted Fat-Myocardium Model Unravels the Role of Adipocyte Hypertrophy in Atrial Dysfunction 90%
Similar papers in this journal
Similar papers in this journal
- Creating cell-specific computational models of stem cell-derived cardiomyocytes using optical experiments 92%
- Transcriptomic entropy benchmarks stem cell-derived cardiomyocyte maturation against endogenous tissue at single cell level 91%
- cytoNet: Spatiotemporal Network Analysis of Cell Communities 91%
Similar papers in this journal
- Spatiotemporal single-cell RNA sequencing of developing hearts reveals interplay between cellular differentiation and morphogenesis 94%
- Modeling cardiac fibroblast heterogeneity from human pluripotent stem cell-derived epicardial cells 94%
- Single-cell transcriptome analysis reveals CD34 as a novel marker of human sinoatrial node pacemaker cardiomyocytes 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.