Nascent polypeptide-Associated Complex and Signal Recognition Particle have cardiac-specific roles in heart development and remodeling.

Establishing a catalog of Congenital Heart Disease (CHD) genes and identifying functional networks would improve our understanding of its oligogenic underpinnings. Our studies identified protein biogenesis cofactors Nascent polypeptide-Associated Complex (NAC) and Signal-Recognition-Particle (SRP) as disease candidates and novel regulators of cardiac differentiation and morphogenesis. Knockdown (KD) of the alpha- (Nacα) or beta-subunit (bicaudal, bic) of NAC in the developing Drosophila heart disrupted cardiac developmental remodeling resulting in a fly with no heart. Heart loss was rescued by combined KD of Nacα with the posterior patterning Hox gene Abd-B. Consistent with a central role for this interaction in cardiogenesis, KD of Nacα in cardiac progenitors derived from human iPSCs impaired cardiac differentiation while co-KD with human HOXC12 and HOXD12 rescued this phenotype. Our data suggest that Nacα KD preprograms cardioblasts in the embryo for abortive remodeling later during metamorphosis, as Nacα KD during translation-intensive larval growth or pupal remodeling only causes moderate heart defects. KD of SRP subunits in the developing fly heart produced phenotypes that targeted specific segments and cell types, again suggesting cardiac-specific and spatially regulated activities. Together, we demonstrated directed function for NAC and SRP in heart development, and that regulation of NAC function depends on Hox genes.

Trajectory reconstruction identifies dysregulation of perinatal maturation programs in pluripotent stem cell-derived cardiomyocytes.

A limitation in the application of pluripotent stem cell-derived cardiomyocytes (PSC-CMs) is the failure of these cells to achieve full functional maturity. The mechanisms by which directed differentiation differs from endogenous development, leading to consequent PSC-CM maturation arrest, remain unclear. Here, we generate a single-cell RNA sequencing (scRNA-seq) reference of mouse in vivo CM maturation with extensive sampling of previously difficult-to-isolate perinatal time periods. We subsequently generate isogenic embryonic stem cells to create an in vitro scRNA-seq reference of PSC-CM-directed differentiation. Through trajectory reconstruction, we identify an endogenous perinatal maturation program that is poorly recapitulated in vitro. By comparison with published human datasets, we identify a network of nine transcription factors (TFs) whose targets are consistently dysregulated in PSC-CMs across species. Notably, these TFs are only partially activated in common ex vivo approaches to engineer PSC-CM maturation. Our study can be leveraged toward improving the clinical viability of PSC-CMs.

Conserved transcription factors promote cell fate stability and restrict reprogramming potential in differentiated cells.

Defining the mechanisms safeguarding cell fate identity in differentiated cells is crucial to improve 1) - our understanding of how differentiation is maintained in healthy tissues or altered in a disease state, and 2) - our ability to use cell fate reprogramming for regenerative purposes. Here, using a genome-wide transcription factor screen followed by validation steps in a variety of reprogramming assays (cardiac, neural and iPSC in fibroblasts and endothelial cells), we identified a set of four transcription factors (ATF7IP, JUNB, SP7, and ZNF207 [AJSZ]) that robustly opposes cell fate reprogramming in both lineage and cell type independent manners. Mechanistically, our integrated multi-omics approach (ChIP, ATAC and RNA-seq) revealed that AJSZ oppose cell fate reprogramming by 1) - maintaining chromatin enriched for reprogramming TF motifs in a closed state and 2) - downregulating genes required for reprogramming. Finally, KD of AJSZ in combination with MGT overexpression, significantly reduced scar size and improved heart function by 50%, as compared to MGT alone post-myocardial infarction. Collectively, our study suggests that inhibition of barrier to reprogramming mechanisms represents a promising therapeutic avenue to improve adult organ function post-injury.

Genetic architecture of natural variation of cardiac performance from flies to humans.

Deciphering the genetic architecture of human cardiac disorders is of fundamental importance but their underlying complexity is a major hurdle. We investigated the natural variation of cardiac performance in the sequenced inbred lines of the Drosophila Genetic Reference Panel (DGRP). Genome-wide associations studies (GWAS) identified genetic networks associated with natural variation of cardiac traits which were used to gain insights as to the molecular and cellular processes affected. Non-coding variants that we identified were used to map potential regulatory non-coding regions, which in turn were employed to predict transcription factors (TFs) binding sites. Cognate TFs, many of which themselves bear polymorphisms associated with variations of cardiac performance, were also validated by heart-specific knockdown. Additionally, we showed that the natural variations associated with variability in cardiac performance affect a set of genes overlapping those associated with average traits but through different variants in the same genes. Furthermore, we showed that phenotypic variability was also associated with natural variation of gene regulatory networks. More importantly, we documented correlations between genes associated with cardiac phenotypes in both flies and humans, which supports a conserved genetic architecture regulating adult cardiac function from arthropods to mammals. Specifically, roles for PAX9 and EGR2 in the regulation of the cardiac rhythm were established in both models, illustrating that the characteristics of natural variations in cardiac function identified in Drosophila can accelerate discovery in humans.

Essential metabolism for a minimal cell.

JCVI-syn3A, a robust minimal cell with a 543 kbp genome and 493 genes, provides a versatile platform to study the basics of life. Using the vast amount of experimental information available on its precursor, Mycoplasma mycoides capri, we assembled a near-complete metabolic network with 98% of enzymatic reactions supported by annotation or experiment. The model agrees well with genome-scale in vivo transposon mutagenesis experiments, showing a Matthews correlation coefficient of 0.59. The genes in the reconstruction have a high in vivo essentiality or quasi-essentiality of 92% (68% essential), compared to 79% in silico essentiality. This coherent model of the minimal metabolism in JCVI-syn3A at the same time also points toward specific open questions regarding the minimal genome of JCVI-syn3A, which still contains many genes of generic or completely unclear function. In particular, the model, its comparison to in vivo essentiality and proteomics data yield specific hypotheses on gene functions and metabolic capabilities; and provide suggestions for several further gene removals. In this way, the model and its accompanying data guide future investigations of the minimal cell. Finally, the identification of 30 essential genes with unclear function will motivate the search for new biological mechanisms beyond metabolism.

One way that researchers can test whether they understand a biological system is to see if they can accurately recreate it as a computer model. The more they learn about living things, the more the researchers can improve their models and the closer the models become to simulating the original. In this approach, it is best to start by trying to model a simple system. Biologists have previously succeeded in creating 'minimal bacterial cells'. These synthetic cells contain fewer genes than almost all other living things and they are believed to be among the simplest possible forms of life that can grow on their own. The minimal cells can produce all the chemicals that they need to survive ­ in other words, they have a metabolism. Accurately recreating one of these cells in a computer is a key first step towards simulating a complete living system. Breuer et al. have developed a computer model to simulate the network of the biochemical reactions going on inside a minimal cell with just 493 genes. By altering the parameters of their model and comparing the results to experimental data, Breuer et al. explored the accuracy of their model. Overall, the model reproduces experimental results, but it is not yet perfect. The differences between the model and the experiments suggest new questions and tests that could advance our understanding of biology. In particular, Breuer et al. identified 30 genes that are essential for life in these cells but that currently have no known purpose. Continuing to develop and expand models like these to reproduce more complex living systems provides a tool to test current knowledge of biology. These models may become so advanced that they could predict how living things will respond to changing situations. This would allow scientists to test ideas sooner and make much faster progress in understanding life on Earth. Ultimately, these models could one day help to accelerate medical and industrial processes to save lives and enhance productivity.