Ex uno, plures-From One Tissue to Many Cells: A Review of Single-Cell Transcriptomics in Cardiovascular Biology.

Recent technological advances have revolutionized the study of tissue biology and garnered a greater appreciation for tissue complexity. In order to understand cardiac development, heart tissue homeostasis, and the effects of stress and injury on the cardiovascular system, it is essential to characterize the heart at high cellular resolution. Single-cell profiling provides a more precise definition of tissue composition, cell differentiation trajectories, and intercellular communication, compared to classical bulk approaches. Here, we aim to review how recent single-cell multi-omic studies have changed our understanding of cell dynamics during cardiac development, and in the healthy and diseased adult myocardium

Bayesian model selection reveals biological origins of zero inflation in single-cell transcriptomics.

BACKGROUND: Single-cell RNA sequencing is a powerful tool for characterizing cellular heterogeneity in gene expression. However, high variability and a large number of zero counts present challenges for analysis and interpretation. There is substantial controversy over the origins and proper treatment of zeros and no consensus on whether zero-inflated count distributions are necessary or even useful. While some studies assume the existence of zero inflation due to technical artifacts and attempt to impute the missing information, other recent studies argue that there is no zero inflation in scRNA-seq data. RESULTS: We apply a Bayesian model selection approach to unambiguously demonstrate zero inflation in multiple biologically realistic scRNA-seq datasets. We show that the primary causes of zero inflation are not technical but rather biological in nature. We also demonstrate that parameter estimates from the zero-inflated negative binomial distribution are an unreliable indicator of zero inflation. CONCLUSIONS: Despite the existence of zero inflation in scRNA-seq counts, we recommend the generalized linear model with negative binomial count distribution, not zero-inflated, as a suitable reference model for scRNA-seq analysis

Natural genetic variation determines microglia heterogeneity in wild-derived mouse models of Alzheimer\u27s disease.

Genetic and genome-wide association studies suggest a central role for microglia in Alzheimer\u27s disease (AD). However, single-cell RNA sequencing (scRNA-seq) of microglia in mice, a key preclinical model, has shown mixed results regarding translatability to human studies. To address this, scRNA-seq of microglia from C57BL/6J (B6) and wild-derived strains (WSB/EiJ, CAST/EiJ, and PWK/PhJ) with and without APP/PS1 demonstrates that genetic diversity significantly alters features and dynamics of microglia in baseline neuroimmune functions and in response to amyloidosis. Results show significant variation in the abundance of microglial subtypes or states, including numbers of previously identified disease-associated and interferon-responding microglia, across the strains. For each subtype, significant differences in the expression of many genes are observed in wild-derived strains relative to B6, including 19 genes previously associated with human AD including Apoe, Trem2, and Sorl1. This resource is critical in the development of appropriately targeted therapeutics for AD and other neurological diseases

Proteomic and transcriptomic profiling reveal different aspects of aging in the kidney.

Little is known about the molecular changes that take place in the kidney during the aging process. In order to better understand these changes, we measured mRNA and protein levels in genetically diverse mice at different ages. We observed distinctive change in mRNA and protein levels as a function of age. Changes in both mRNA and protein are associated with increased immune infiltration and decreases in mitochondrial function. Proteins show a greater extent of change and reveal changes in a wide array of biological processes including unique, organ-specific features of aging in kidney. Most importantly, we observed functionally important age-related changes in protein that occur in the absence of corresponding changes in mRNA. Our findings suggest that mRNA profiling alone provides an incomplete picture of molecular aging in the kidney and that examination of changes in proteins is essential to understand aging processes that are not transcriptionally regulated

Dynamic Interstitial Cell Response during Myocardial Infarction Predicts Resilience to Rupture in Genetically Diverse Mice.

Cardiac ischemia leads to the loss of myocardial tissue and the activation of a repair process that culminates in the formation of a scar whose structural characteristics dictate propensity to favorable healing or detrimental cardiac wall rupture. To elucidate the cellular processes underlying scar formation, here we perform unbiased single-cell mRNA sequencing of interstitial cells isolated from infarcted mouse hearts carrying a genetic tracer that labels epicardial-derived cells. Sixteen interstitial cell clusters are revealed, five of which were of epicardial origin. Focusing on stromal cells, we define 11 sub-clusters, including diverse cell states of epicardial- and endocardial-derived fibroblasts. Comparing transcript profiles from post-infarction hearts in C57BL/6J and 129S1/SvImJ inbred mice, which displays a marked divergence in the frequency of cardiac rupture, uncovers an early increase in activated myofibroblasts, enhanced collagen deposition, and persistent acute phase response in 129S1/SvImJ mouse hearts, defining a crucial time window of pathological remodeling that predicts disease outcome

Association of RGS2 and RGS5 variants with schizophrenia symptom severity

Several lines of evidence indicate that Regulator of G Protein Signaling 4 (RGS4) contributes to schizophrenia vulnerability. RGS4 is one of a family of molecules that modulate signaling via G-protein coupled receptors. Five genes encoding members of this family (RGS2, RGS4, RGS5, RGS8 and RGS16) map to chromosome 1q23.3-1q31. Due to overlapping cellular functions and chromosomal proximity, we hypothesized that multiple RGS genes may contribute to schizophrenia severity and treatment responsiveness

Mouse Phenome Database: an integrative database and analysis suite for curated empirical phenotype data from laboratory mice.

The Mouse Phenome Database (MPD; https://phenome.jax.org) is a widely used resource that provides access to primary experimental trait data, genotypic variation, protocols and analysis tools for mouse genetic studies. Data are contributed by investigators worldwide and represent a broad scope of phenotyping endpoints and disease-related traits in naïve mice and those exposed to drugs, environmental agents or other treatments. MPD houses individual animal data with detailed, searchable protocols, and makes these data available to other resources via API. MPD provides rigorous curation of experimental data and supporting documentation using relevant ontologies and controlled vocabularies. Most data in MPD are from inbreds and other reproducible strains such that the data are cumulative over time and across laboratories. The resource has been expanded to include the QTL Archive and other primary phenotype data from mapping crosses as well as advanced high-diversity mouse populations including the Collaborative Cross and Diversity Outbred mice. Furthermore, MPD provides a means of assessing replicability and reproducibility across experimental conditions and protocols, benchmarking assays in users\u27 own laboratories, identifying sensitized backgrounds for making new mouse models with genome editing technologies, analyzing trait co-inheritance, finding the common genetic basis for multiple traits and assessing sex differences and sex-by-genotype interactions. Nucleic Acids Res 2018 Jan 4; 46(D1):D843-D850

Genetic dissection of the pluripotent proteome through multi-omics data integration.

Genetic background drives phenotypic variability in pluripotent stem cells (PSCs). Most studies to date have used transcript abundance as the primary molecular readout of cell state in PSCs. We performed a comprehensive proteogenomics analysis of 190 genetically diverse mouse embryonic stem cell (mESC) lines. The quantitative proteome is highly variable across lines, and we identified pluripotency-associated pathways that were differentially activated in the proteomics data that were not evident in transcriptome data from the same lines. Integration of protein abundance to transcript levels and chromatin accessibility revealed broad co-variation across molecular layers as well as shared and unique drivers of quantitative variation in pluripotency-associated pathways. Quantitative trait locus (QTL) mapping localized the drivers of these multi-omic signatures to genomic hotspots. This study reveals post-transcriptional mechanisms and genetic interactions that underlie quantitative variability in the pluripotent proteome and provides a regulatory map for mESCs that can provide a basis for future mechanistic studies

Efficacious, effective, and embedded interventions: Implementation research in infectious disease control

Background: Research in infectious disease control is heavily skewed towards high end technology; development of new drugs, vaccines and clinical interventions. Oft ignored, is the evidence to inform the best strategies that ensure the embedding of interventions into health systems and amongst populations. In this paper we undertake an analysis of the challenge in the development of research for the sustainable implementation of disease control interventions. Results: We highlight the fundamental differences between the research paradigms associated with the development of technologies and interventions for disease control on the one hand and the research paradigms required for enhancing the sustainable uptake of those very same interventions within the communities on the other. We provide a definition for implementation research in an attempt to underscore its critical role and explore the multidisciplinary science needed to address the challenges in disease control. Conclusion: The greatest value for money in health research lies in the sustainable and effective implementation of already proven, efficacious solutions. The development of implementation research that can help provide some solutions on how this can be achieved is sorely needed

Cross-Priming Dendritic Cells Exacerbate Immunopathology After Ischemic Tissue Damage in the Heart.

BACKGROUND: Ischemic heart disease is a leading cause of heart failure and despite advanced therapeutic options, morbidity and mortality rates remain high. Although acute inflammation in response to myocardial cell death has been extensively studied, subsequent adaptive immune activity and anti-heart autoimmunity may also contribute to the development of heart failure. After ischemic injury to the myocardium, dendritic cells (DC) respond to cardiomyocyte necrosis, present cardiac antigen to T cells, and potentially initiate a persistent autoimmune response against the heart. Cross-priming DC have the ability to activate both CD4 METHODS: We induced type 2 myocardial infarction-like ischemic injury in the heart by treatment with a single high dose of the β-adrenergic agonist isoproterenol. We characterized the DC population in the heart and mediastinal lymph nodes and analyzed long-term cardiac immunopathology and functional decline in wild type and RESULTS: A diverse DC population, including cross-priming DC, is present in the heart and activated after ischemic injury. CONCLUSION: Activation of cytotoxic CD