Transcriptome transfer provides a model for understanding the phenotype of cardiomyocytes

Abstract

We show that the transfer of the adult ventricular myocyte (AVM) transcriptome into either a fibroblast or an astrocyte converts the host cell into a cardiomyocyte. Transcriptome-effected cardiomyocytes (tCardiomyocytes) display morphologies, immunocytochemical properties, and expression profiles of postnatal cardiomyocytes. Cell morphology analysis shows that tCardiomyoctes are elongated and have a similar length-to-width ratio as AVMs. These global phenotypic changes occur in a time-dependent manner and confer electroexcitability to the tCardiomyocytes. tCardiomyocyte generation does not require continuous overexpression of specific transcription factors; for example, the expression level of transcription factor Mef2c is higher in tCardiomyocytes than in fibroblasts, but similar in tCardiomyocytes and AVMs. These data highlight the dominant role of the gene expression profile in developing and maintaining cellular phenotype. The transcriptomeinduced phenotype remodeling-generated tCardiomyocyte has significant implications for understanding and modulating cardiac disease development.C ardiomyocytes are among the most sought-after cells in regenerative medicine because they may help to repair an injured heart by replacing lost tissue (1, 2). Functional cardiomyocyte-like cells have been induced from embryonic stem cells (ESCs), induced from pluripotent stem cells (iPSCs), and generated from direct conversion of fibroblasts using defined transcription factor transduction (3-7). ESC-derived and iPSCderived cardiomyocytes exhibit many characteristics of cardiomyocytes, including electric activity, contractile movement, and up-regulation of cardiac genes; however, both stem cellderived cardiomyocytes are mixed populations of atrial, ventricular, and other cells, limiting their use in research and clinical application. In addition to heterogeneity of the cells, stem cellderived cardiomyocytes remain embryonic cardiomyocytes even after 2 mo under standard 2D culture conditions (5, 6). Transcription factor-induced cardiomyocytes also have many characteristics of neonatal cardiomyocytes (4). Furthermore, carcinogenesis and early senescence often develop in transcription factor-mediated induction of such phenotypic changes (8, 9).We have previously shown that the transfer of transcriptome (TIPeR) from a rat astrocyte into a rat neuron converts the electrically active neuron into an electrically quiescent tAstrocyte cell (10). We asked whether the change in expression profile (i.e., modulation of relative abundance of gene products) could transdifferentiate electrically quiescent cells into electrically excitable cells. Here we demonstrate the conversion of an electrically quiescent fibroblast directly into an electrically excitable tCardiomyocyte in a mouse system. We also show that another electrically quiescent cell, the astrocyte, can be converted into a tCardiomyocyte. This conversion was confirmed by a diverse set of single-cell phenotyping procedures. Results Generation of tCardiomyocytes from Fibroblasts by Trans...

Inputs drive cell phenotype variability

“…As cutting edge discovery of plasticity and diversity within and across neuron types continues, the causes of these phenomena remain unclear (De la Rossa et al 2013;Dulcis et al 2013). We suspect that adaptive responses to inputs of this kind may cause the variability that is observed in high-throughput studies of phenotypically similar cells (Eberwine and Bartfai 2011;Kim et al 2011). In other words, a cell type that might have been expected to be homogenous, sharing a common end fate, might rather be heterogeneous due to each cell within the cell type adapting to a distinct input history.…”

Identifying functional gene regulatory network phenotypes underlying single cell transcriptional variability

“…In these instances, distinct network inputs appear to drive the differing regulatory networks towards a similar transcriptional state (Figure 6). Thus, our fuzzy-logic network modeling predicts that the pervasive transcriptional variability observed in vivo is likely a product of distinct regulatory network interactions as well as response to distinct network stimuli (Raj & van Oudenaarden 2008; Eberwine & Bartfai 2011; Kim et al 2011; Bendall et al 2012; Pe’er & Hacohen 2011; Amir et al 2013; Buganim et al 2012b). …”

Perspectives on cell reprogramming with RNA

“…The host cell then undergoes a phenotypic conversion and stably expresses the donor cell phenotype [15]. This method has been used to convert post-mitotic neurons have been converted to tAstrocytes while fibroblasts as well as astrocytes have been converted into tCardiomyocytes [16]. …”