Single-nucleus transcriptomic survey of cell diversity and functional maturation in postnatal mammalian hearts

Abstract

A fundamental challenge in understanding cardiac biology and disease is that the remarkable heterogeneity in cell type composition and functional states have not been well characterized at single-cell resolution in maturing and diseased mammalian hearts. Massively parallel single-nucleus RNA sequencing (snRNA-seq) has emerged as a powerful tool to address these questions by interrogating the transcriptome of tens of thousands of nuclei isolated from fresh or frozen tissues. snRNA-seq overcomes the technical challenge of isolating intact single cells from complex tissues, including the maturing mammalian hearts; reduces biased recovery of easily dissociated cell types; and minimizes aberrant gene expression during the whole-cell dissociation. Here we applied sNucDrop-seq, a droplet microfluidics-based massively parallel snRNA-seq method, to investigate the transcriptional landscape of postnatal maturing mouse hearts in both healthy and disease states. By profiling the transcriptome of nearly 20,000 nuclei, we identified major and rare cardiac cell types and revealed significant heterogeneity of cardiomyocytes, fibroblasts, and endothelial cells in postnatal developing hearts. When applied to a mouse model of pediatric mitochondrial cardiomyopathy, we uncovered profound cell type-specific modifications of the cardiac transcriptional landscape at single-nucleus resolution, including changes of subtype composition, maturation states, and functional remodeling of each cell type. Furthermore, we employed sNucDrop-seq to decipher the cardiac cell type-specific gene regulatory network (GRN) of GDF15, a heart-derived hormone and clinically important diagnostic biomarker of heart disease. Together, our results present a rich resource for studying cardiac biology and provide new insights into heart disease using an approach broadly applicable to many fields of biomedicine.

Single-Nucleus Sequencing of an Entire Mammalian Heart: Cell Type Composition and Velocity

“…This disparity might be due to different isolation protocols, on the one hand, and the fact that we used whole hearts instead of isolated ventricles, on the other hand. However, more recent findings, also based on single-nucleus sequencing [5], are in accordance with our data, so that we further assume that this kind of holistic approach may yield more robust results than approaches relying on single-marker genes. Moreover, we not only observed various immune cells but also identified cells of neuronal origin (7.4%) and cardiac glial cells (0.2%) representing the innervated system of the heart and confirming the comprehensiveness of our data.…”

“…Whereas research efforts aim to avoid these issues by relying on embryonic and neonatal murine hearts or focusing on non-myocyte populations in adult mouse hearts, we desisted from single-cell Ribonucleic acid sequencing (RNA-seq) and instead conducted single-nucleus RNA-seq (snRNA-seq), which has been shown to present similar transcriptomic results [3]. Currently, existing studies on adult mammalian hearts concentrate only on selected substructures such as the ventricle [4] or the conduction system [5]. To our knowledge, we present the first snRNA-seq analysis of an entire adult mammalian heart.…”

Dissecting Fibroblast Heterogeneity in Health and Fibrotic Disease

“…A single-cell RNA-seq analysis identified two major fibroblast populations in adult mouse ventricles; however, the distribution of expression of an epicardium marker amongst the cells indicated that these clusters do not reflect the two developmental origins [67•]. Similarly, a single-nucleus transcriptomic approach of early postnatal heart tissue identified two fibroblast populations that were actually only subtly different and both expressed high levels of specific ECM genes (periostin, fibrillin 1 and collagen 5a1) [68]. Further exploration into the overlap, sub-clustering and differing functions of these populations is warranted.…”

Large particle fluorescence-activated cell sorting enables high quality single cell RNA-sequencing and functional analysis of adult cardiomyocytes

“…However, this approach is technically challenging, low throughput, and time intensive, which may in turn lead to significant transcriptomic changes during isolation. In lieu of whole cell scRNA-seq, others have utilized single nuclear RNA-seq (snRNA-seq), which overcomes the challenges of isolating large CMs [14][15][16] . While this approach can broadly capture cellular heterogeneity, snRNA-seq inherently detects fewer molecules and may skew gene expression towards transcripts predominantly localized in the nucleus (e.g.…”