Epigenetic alterations pose one major hallmark of organismal aging. Here, we provide an overview on recent findings describing the epigenetic changes that arise during aging and in related maladies such as neurodegeneration and cancer. Specifically, we focus on alterations of histone modifications and DNA methylation and illustrate the link with metabolic pathways. Age-related epigenetic, transcriptional and metabolic deregulations are highly interconnected, which renders dissociating cause and effect complicated. However, growing amounts of evidence support the notion that aging is not only accompanied by epigenetic alterations, but also at least in part induced by those. DNA methylation clocks emerged as a tool to objectively determine biological aging and turned out as a valuable source in search of factors positively and negatively impacting human life span. Moreover, specific epigenetic signatures can be used as biomarkers for age-associated disorders or even as targets for therapeutic approaches, as will be covered in this review. Finally, we summarize recent potential intervention strategies that target epigenetic mechanisms to extend healthy life span and provide an outlook on future developments in the field of longevity research.

Analyses on the cellular level are indispensable to expand our understanding of complex tissues like the mammalian heart. Single-nucleus sequencing (snRNA-seq) allows for the exploration of cellular composition and cell features without major hurdles of single-cell sequencing. We used snRNA-seq to investigate for the first time an entire adult mammalian heart. Single-nucleus quantification and clustering led to an accurate representation of cell types, revealing 24 distinct clusters with endothelial cells (28.8%), fibroblasts (25.3%), and cardiomyocytes (22.8%) constituting the major cell populations. An additional RNA velocity analysis allowed us to study transcription kinetics and was utilized to visualize the transitions between mature and nascent cellular states of the cell types. We identified subgroups of cardiomyocytes with distinct marker profiles. For example, the expression of Hand2os1 distinguished immature cardiomyocytes from differentiated cardiomyocyte populations. Moreover, we found a cell population that comprises endothelial markers as well as markers clearly related to cardiomyocyte function. Our velocity data support the idea that this population is in a trans-differentiation process from an endothelial cell-like phenotype towards a cardiomyocyte-like phenotype. In summary, we present the first report of sequencing an entire adult mammalian heart, providing realistic cell-type distributions combined with RNA velocity kinetics hinting at interrelations.

Single-cell RNA-sequencing (scRNA-seq) provides high-resolution insights into complex tissues. Cardiac tissue, however, poses a major challenge due to the delicate isolation process and the large size of mature cardiomyocytes. Regardless of the experimental technique, captured cells are often impaired and some capture sites may contain multiple or no cells at all. All this refers to “low quality” potentially leading to data misinterpretation. Common standard quality control parameters involve the number of detected genes, transcripts per cell, and the fraction of transcripts from mitochondrial genes. While cutoffs for transcripts and genes per cell are usually user-defined for each experiment or individually calculated, a fixed threshold of 5% mitochondrial transcripts is standard and often set as default in scRNA-seq software. However, this parameter is highly dependent on the tissue type. In the heart, mitochondrial transcripts comprise almost 30% of total mRNA due to high energy demands. Here, we demonstrate that a 5%-threshold not only causes an unacceptable exclusion of cardiomyocytes but also introduces a bias that particularly discriminates pacemaker cells. This effect is apparent for our in vitro generated induced-sinoatrial-bodies (iSABs; highly enriched physiologically functional pacemaker cells), and also evident in a public data set of cells isolated from embryonal murine sinoatrial node tissue (Goodyer William et al. in Circ Res 125:379–397, 2019). Taken together, we recommend omitting this filtering parameter for scRNA-seq in cardiovascular applications whenever possible.

The recent development and broad application of sequencing techniques at the single-cell level is generating an unprecedented amount of data. The different techniques have their individual limits, but the datasets also offer unexpected possibilities when utilized collectively. Here, we applied snRNA-seq in whole adult murine hearts from an inbred (C57BL/6NRj) and an outbred (Fzt:DU) mouse strain to directly compare the data with the publicly available scRNA-seq data of the tabula muris project. Explicitly choosing a single-nucleus approach allowed us to pin down the typical heart tissue-specific technical bias, coming up with novel insights on the mammalian heart cell composition. For our integrated dataset, cardiomyocytes, fibroblasts, and endothelial cells constituted the three main cell populations accounting for about 75% of all cells. However, their numbers severely differed between the individual datasets, with cardiomyocyte proportions ranging from about 9% in the tabula muris data to around 23% for our BL6 data, representing the prime example for cell capture technique related bias when using a conventional single-cell approach for these large cells. Most strikingly in our comparison was the discovery of a minor population of cardiomyocytes characterized by proliferation markers that could not be identified by analyzing the datasets individually. It is now widely accepted that the heart has an, albeit very restricted, regenerative potential. However there is still an ongoing debate where new cardiomyocytes arise from. Our findings support the idea that the renewal of the cardiomyocyte pool is driven by cytokinesis of resident cardiomyocytes rather than differentiation of progenitor cells. We thus provide data that can contribute to an understanding of heart cell regeneration, which is a prerequisite for future applications to enhance the process of heart repair.

Background: The immune response is a crucial factor for mediating the benefit of cardiac cell therapies. Our previous research showed that cardiomyocyte transplantation alters the cardiac immune response and, when combined with short-term pharmacological CCR2 inhibition, resulted in diminished functional benefit. However, the specific role of innate immune cells, especially CCR2 macrophages on the outcome of cardiomyocyte transplantation, is unclear. Methods: We compared the cellular, molecular, and functional outcome following cardiomyocyte transplantation in wildtype and T cell- and B cell-deficient Rag2^del mice. The cardiac inflammatory response was assessed using flow cytometry. Gene expression profile was assessed using single-cell and bulk RNA sequencing. Cardiac function and morphology were determined using magnetic resonance tomography and immunohistochemistry respectively. Results: Compared to wildtype mice, Rag2^del mice show an increased innate immune response at steady state and disparate macrophage response after MI. Subsequent single-cell analyses after MI showed differences in macrophage development and a lower prevalence of CCR2 expressing macrophages. Cardiomyocyte transplantation increased NK cells and monocytes, while reducing CCR2⁻MHC-II^lo macrophages. Consequently, it led to increased mRNA levels of genes involved in extracellular remodelling, poor graft survival, and no functional improvement. Using machine learning-based feature selection, Mfge8 and Ccl7 were identified as the primary targets underlying these effects in the heart. Conclusions: Our results demonstrate that the improved functional outcome following cardiomyocyte transplantation is dependent on a specific CCR2 macrophage response. This work highlights the need to study the role of the immune response for cardiomyocyte cell therapy for successful clinical translation.

Markus Wolfien, Anne-Marie Galow, Paula Müller, Madeleine Bartsch, Ronald M Brunner, Tom Goldammer, Olaf Wolkenhauer, Andreas Hoeflich, Robert David; Single Nu