We believe that the production of homogeneous and functional

We believe that the production of homogeneous and functional PSC-derived ventricular CMs using a non-transgenic approach will open new avenues for basic research and clinical applications. First, a pure population of ventricular CMs generated by the MB-based method offers a safer and more effective option for cell therapy and tissue engineering compared to the use of mixed populations of PSC-derived CMs, which are more likely to cause abnormal electrical activity (Liao et al., 2010) or less efficient contractile function (van Laake et al., 2008). From a research perspective, the MB-purified ventricular CMs represent a powerful in vitro tool for disease investigation and drug discovery. They can be used as better-defined in vitro model systems for genetic or idiopathic cardiac diseases such as long QT syndrome (Itzhaki et al., 2011; Moretti et al., 2010). They can also serve as an in vitro model to test chamber-specific effects of candidate cardiac drugs (Liang et al., 2013). These purified CMs will yield more accurate genetic and epigenetic information through high-throughput sequencing techniques. We anticipate that this MB-based cell-sorting method can be adopted for isolating other cardiac cells, such as nodal am630 and atrial CMs, and has the potential to be used in isolating other cell types from differentiating PSCs, such as neuronal cells and pancreatic β cells.
Experimental Procedures
Author Contributions
Acknowledgments
Introduction Pluripotent stem cells are particularly promising cell types, possessing the ability to self-replicate and differentiate into all cell types in the body, including hepatocytes (Sun et al., 2013). This promises in theory an “off-the-shelf” alternative to donated tissue. Differentiation procedures have advanced over the last decade, and efficient protocols to generate stem cell-derived hepatocyte-like cells (HLCs) from either human embryonic stem cells (hESCs) or induced pluripotent stem cells (iPSCs) now exist (Lavon et al., 2004; Hay et al., 2007, 2008, 2011; Cai et al., 2007; Duan et al., 2007; Basma et al., 2009; Sullivan et al., 2010; Touboul et al., 2010; Si-Tayeb et al., 2010; Rashid et al., 2010; Payne et al., 2011; Zhou et al., 2012, 2014; Medine et al., 2013; Takayama et al., 2013a; Szkolnicka et al., 2014a). These procedures utilize growth factors, mimicking each stages of embryonic development, and can deliver homogenous populations of HLCs. Although these prototype systems have provided confidence in pluripotent stem cell technologies, their amenability to defined scale-up with clinical-grade hESC lines has not been achieved. HLCs derived from pluripotent stem cells have shown significant promise in vitro, accurately modeling human drug exposure (Medine et al., 2013; Szkolnicka et al., 2014b; Holmgren et al., 2014; Ware et al., 2015). HLCs have also been employed to study the hepatitis C virus life cycle (Wu et al., 2012; Roelandt et al., 2012; Zhou et al., 2014, Carpentier et al., 2014) and, more recently, the malaria parasite (Ng et al., 2015). HLCs have also been derived from patients with monogenic metabolic liver diseases and have been shown to recapitulate features of α1-antitrypsin deficiency, familial hypercholesterolemia, and glycogen storage disease (Rashid et al., 2010). The ability to generate population-specific HLCs that accurately represent adult liver tissue has significant implications in the drug development process and in stratifying patient healthcare. Despite these advances, HLCs derived from pluripotent stem cells still display an immature phenotype (Godoy et al., 2015; Forbes et al., 2015). This phenotypic immaturity has contributed to the limited the use of stem cell-derived hepatocytes for clinical application (Schwartz et al., 2014). Efforts to address this have utilized natural and synthetic culture substrates to improve mature hepatocyte function and enhance stability (Takayama et al., 2013b; Jitraruch et al., 2014; Villarin et al., 2015). Other studies have used small molecules to replace growth factors to drive down the cost of the method (Hay et al., 2007, 2008; Siller et al., 2015); however, those published methods both still rely upon the use of undefined components, highlighting the need to develop defined systems.