Objectives: In the recent years, single cell (SC) and single nuclei (SN) RNA sequencing (SC-RNAseq, SN-RNAseq) became state-of-the art to analyze the complexity of tissue transcriptomes. We sought to uncover the cellular composition in different localizations of the adult human heart and to compare the cellular and nuclear transcription profiles by SC-RNAseq and SN-RNAseq, respectively.
Methods: We chose five cardiac tissue samples for each technique (all samples: n = 10). Samples from right and left atrium (RA, LA), and left ventricle (LV) from six individuals (male and female) with diagnoses such as aortic stenosis (AS) or mitral valve insufficiency (MVI) were analyzed. In three cases, we analyzed RA and LV from the same individual to compare different locations of the heart. Living SCs (non-myocyte cells, NMCs) were isolated from fresh cardiac biopsies by enzymatic digestion, followed by filtration steps and a MACS-based dead cell removal step. SNs (all cardiac cell types) were isolated by homogenization of frozen cardiac tissue and sucrose density gradient centrifugation followed by flow cytometry based sorting. Samples were then processed by a droplet-based microfluidic sequencing technology and sequences were aligned to the human genome generating RNA expression profiles on SC or SN resolution. Bioinformatic analysis was performed onto SC/SN transcriptomes and population clusters were identified via principal component analysis and unsupervised clustering. Clusters were then assigned to a specific cell type by canonical marker and ontology analyses.
Result: All together more than 30.000 SC and SN were analyzed. We identified 1800 genes per cell/nucleus (median). We could identify the four major subtypes of resident NMCs: cardiac fibroblasts (CFs), smooth muscle cells (SMCs)/pericytes (PCs), endothelial cells (ECs), and macrophages. CFs and SMCs/PCs were detected to a similar amount in SC and SN samples. However, we found less ECs in SC samples compared with SN samples indicating a probable selective cell death of ECs by enzymatic digestion steps in the SC preparation protocol. Cardiomyocyte analysis proved to be only possible in SN-RNAseq samples. We found distinct nuclear and cellular gene expression profiles, especially for CFs and SMCs/PCs, further elucidating the complex transcriptional processes.
Conclusion: SC-RNAseq and SN-RNAseq offer complemental ways to analyze the distribution of main cardiac cell types and transcriptomes in the adult human heart.
