Apelin Enhances Directed Cardiac Differentiation of Mouse and Human Embryonic Stem Cells

Apelin is a peptide ligand for an orphan G-protein coupled receptor (APJ receptor) and serves as a critical gradient for migration of mesodermal cells fated to contribute to the myocardial lineage. The present study was designed to establish a robust cardiac differentiation protocol, specifically, to evaluate the effect of apelin on directed differentiation of mouse and human embryonic stem cells (mESCs and hESCs) into cardiac lineage. Different concentrations of apelin (50, 100, 500 nM) were evaluated to determine its differentiation potential. The optimized dose of apelin was then combined with mesodermal differentiation factors, including BMP-4, activin-A, and bFGF, in a developmentally specific temporal sequence to examine the synergistic effects on cardiac differentiation. Cellular, molecular, and physiologic characteristics of the apelin-induced contractile embryoid bodies (EBs) were analyzed. It was found that 100 nM apelin resulted in highest percentage of contractile EB for mESCs while 500 nM had the highest effects on hESCs. Functionally, the contractile frequency of mESCs-derived EBs (mEBs) responded appropriately to increasing concentration of isoprenaline and diltiazem. Positive phenotype of cardiac specific markers was confirmed in the apelin-treated groups. The protocol, consisting of apelin and mesodermal differentiation factors, induced contractility in significantly higher percentage of hESC-derived EBs (hEBs), up-regulated cardiac-specific genes and cell surface markers, and increased the contractile force. In conclusion, we have demonstrated that the treatment of apelin enhanced cardiac differentiation of mouse and human ESCs and exhibited synergistic effects with mesodermal differentiation factors

Fetal Myocardium in the Kidney Capsule: An In Vivo Model of Repopulation of Myocytes by Bone Marrow Cells

Debate surrounds the question of whether the heart is a post-mitotic organ in part due to the lack of an in vivo model in which myocytes are able to actively regenerate. The current study describes the first such mouse model — a fetal myocardial environment grafted into the adult kidney capsule. Here it is used to test whether cells descended from bone marrow can regenerate cardiac myocytes. One week after receiving the fetal heart grafts, recipients were lethally irradiated and transplanted with marrow from green fluorescent protein (GFP)-expressing C57Bl/6J (B6) donors using normal B6 recipients and fetal donors. Levels of myocyte regeneration from GFP marrow within both fetal myocardium and adult hearts of recipients were evaluated histologically. Fetal myocardium transplants had rich neovascularization and beat regularly after 2 weeks, continuing at checkpoints of 1, 2, 4, 6, 8 and12 months after transplantation. At each time point, GFP-expressing rod-shaped myocytes were found in the fetal myocardium, but only a few were found in the adult hearts. The average count of repopulated myocardium with green rod-shaped myocytes was 996.8 cells per gram of fetal myocardial tissue, and 28.7 cells per adult heart tissue, representing a thirty-five fold increase in fetal myocardium compared to the adult heart at 12 months (when numbers of green rod-shaped myocytes were normalized to per gram of myocardial tissue). Thus, bone marrow cells can differentiate to myocytes in the fetal myocardial environment. The novel in vivo model of fetal myocardium in the kidney capsule appears to be valuable for testing repopulating abilities of potential cardiac progenitors

Cardiogenic Induction of Pluripotent Stem Cells Streamlined Through a Conserved SDF-1/VEGF/BMP2 Integrated Network

BACKGROUND: Pluripotent stem cells produce tissue-specific lineages through programmed acquisition of sequential gene expression patterns that function as a blueprint for organ formation. As embryonic stem cells respond concomitantly to diverse signaling pathways during differentiation, extraction of a pro-cardiogenic network would offer a roadmap to streamline cardiac progenitor output. METHODS AND RESULTS: To resolve gene ontology priorities within precursor transcriptomes, cardiogenic subpopulations were here generated according to either growth factor guidance or stage-specific biomarker sorting. Innate expression profiles were independently delineated through unbiased systems biology mapping, and cross-referenced to filter transcriptional noise unmasking a conserved progenitor motif (55 up- and 233 down-regulated genes). The streamlined pool of 288 genes organized into a core biological network that prioritized the "Cardiovascular Development" function. Recursive in silico deconvolution of the cardiogenic neighborhood and associated canonical signaling pathways identified a combination of integrated axes, CXCR4/SDF-1, Flk-1/VEGF and BMP2r/BMP2, predicted to synchronize cardiac specification. In vitro targeting of the resolved triad in embryoid bodies accelerated expression of Nkx2.5, Mef2C and cardiac-MHC, enhanced beating activity, and augmented cardiogenic yield. CONCLUSIONS: Transcriptome-wide dissection of a conserved progenitor profile thus revealed functional highways that coordinate cardiogenic maturation from a pluripotent ground state. Validating the bioinformatics algorithm established a strategy to rationally modulate cell fate, and optimize stem cell-derived cardiogenesis

Harnessing learning biases is essential for applying social learning in conservation

Social learning can influence how animals respond to anthropogenic changes in the environment, determining whether animals survive novel threats and exploit novel resources or produce maladaptive behaviour and contribute to human-wildlife conflict. Predicting where social learning will occur and manipulating its use are, therefore, important in conservation, but doing so is not straightforward. Learning is an inherently biased process that has been shaped by natural selection to prioritize important information and facilitate its efficient uptake. In this regard, social learning is no different from other learning processes because it too is shaped by perceptual filters, attentional biases and learning constraints that can differ between habitats, species, individuals and contexts. The biases that constrain social learning are not understood well enough to accurately predict whether or not social learning will occur in many situations, which limits the effective use of social learning in conservation practice. Nevertheless, we argue that by tapping into the biases that guide the social transmission of information, the conservation applications of social learning could be improved. We explore the conservation areas where social learning is highly relevant and link them to biases in the cues and contexts that shape social information use. The resulting synthesis highlights many promising areas for collaboration between the fields and stresses the importance of systematic reviews of the evidence surrounding social learning practices.BBSRC David Phillips Fellowship (BB/H021817/1