Phantasus, a web application for visual and interactive gene expression analysis.

Transcriptomic profiling became a standard approach to quantify a cell state, which led to the accumulation of huge amount of public gene expression datasets. However, both reuse of these datasets or analysis of newly generated ones requires significant technical expertise. Here, we present Phantasus: a user-friendly web application for interactive gene expression analysis which provides a streamlined access to more than 96,000 public gene expression datasets, as well as allows analysis of user-uploaded datasets. Phantasus integrates an intuitive and highly interactive JavaScript-based heatmap interface with an ability to run sophisticated R-based analysis methods. Overall Phantasus allows users to go all the way from loading, normalizing, and filtering data to doing differential gene expression and downstream analysis. Phantasus can be accessed online at https://alserglab.wustl.edu/phantasus or can be installed locally from Bioconductor (https://bioconductor.org/packages/phantasus). Phantasus source code is available at https://github.com/ctlab/phantasus under an MIT license.

Integrated multi-omics analysis of adverse cardiac remodeling and metabolic inflexibility upon ErbB2 and ERRα deficiency.

Functional oncogenic links between ErbB2 and ERRα in HER2+ breast cancer patients support a therapeutic benefit of co-targeted therapies. However, ErbB2 and ERRα also play key roles in heart physiology, and this approach could pose a potential liability to cardiovascular health. Herein, using integrated phosphoproteomic, transcriptomic and metabolic profiling, we uncovered molecular mechanisms associated with the adverse remodeling of cardiac functions in mice with combined attenuation of ErbB2 and ERRα activity. Genetic disruption of both effectors results in profound effects on cardiomyocyte architecture, inflammatory response and metabolism, the latter leading to a decrease in fatty acyl-carnitine species further increasing the reliance on glucose as a metabolic fuel, a hallmark of failing hearts. Furthermore, integrated omics signatures of ERRα loss-of-function and doxorubicin treatment exhibit common features of chemotherapeutic cardiotoxicity. These findings thus reveal potential cardiovascular risks in discrete combination therapies in the treatment of breast and other cancers.

Loss of Mir146b with aging contributes to inflammation and mitochondrial dysfunction in thioglycollate-elicited peritoneal macrophages.

Macrophages undergo programmatic changes with age, leading to altered cytokine polarization and immune dysfunction, shifting these critical immune cells from protective sentinels to disease promoters. The molecular mechanisms underlying macrophage inflammaging are poorly understood. Using an unbiased RNA sequencing (RNA-seq) approach, we identified Mir146b as a microRNA whose expression progressively and unidirectionally declined with age in thioglycollate-elicited murine macrophages. Mir146b deficiency led to altered macrophage cytokine expression and reduced mitochondrial metabolic activity, two hallmarks of cellular aging. Single-cell RNA-seq identified patterns of altered inflammation and interferon gamma signaling in Mir146b-deficient macrophages. Identification of Mir146b as a potential regulator of macrophage aging provides novel insights into immune dysfunction associated with aging.

Transcriptomic profiling of experimental arterial injury reveals new mechanisms and temporal dynamics in vascular healing response.

OBJECTIVE: Endovascular interventions cause arterial injury and induce a healing response to restore vessel wall homeostasis. Complications of defective or excessive healing are common and result in increased morbidity and repeated interventions. Experimental models of intimal hyperplasia are vital for understanding the vascular healing mechanisms and resolving the clinical problems of restenosis, vein graft stenosis, and dialysis access failure. Our aim was to systematically investigate the transcriptional, histologic, and systemic reaction to vascular injury during a prolonged time. METHODS: Balloon injury of the left common carotid artery was performed in male rats. Animals (n = 69) were euthanized before or after injury, either directly or after 2 hours, 20 hours, 2 days, 5 days, 2 weeks, 6 weeks, and 12 weeks. Both injured and contralateral arteries were subjected to microarray profiling, followed by bioinformatic exploration, histologic characterization of the biopsy specimens, and plasma lipid analyses. RESULTS: Immune activation and coagulation were key mechanisms in the early response, followed by cytokine release, tissue remodeling, and smooth muscle cell modulation several days after injury, with reacquisition of contractile features in later phases. Novel pathways related to clonal expansion, inflammatory transformation, and chondro-osteogenic differentiation were identified and immunolocalized to neointimal smooth muscle cells. Analysis of uninjured arteries revealed a systemic component of the reaction after local injury, underlined by altered endothelial signaling, changes in overall tissue bioenergy metabolism, and plasma high-density lipoprotein levels. CONCLUSIONS: We demonstrate that vascular injury induces dynamic transcriptional landscape and metabolic changes identifiable as early, intermediate, and late response phases, reaching homeostasis after several weeks. This study provides a temporal "roadmap" of vascular healing as a publicly available resource for the research community.

GAM: a web-service for integrated transcriptional and metabolic network analysis.

Novel techniques for high-throughput steady-state metabolomic profiling yield information about changes of nearly thousands of metabolites. Such metabolomic profiles, when analyzed together with transcriptional profiles, can reveal novel insights about underlying biological processes. While a number of conceptual approaches have been developed for data integration, easily accessible tools for integrated analysis of mammalian steady-state metabolomic and transcriptional data are lacking. Here we present GAM ('genes and metabolites'): a web-service for integrated network analysis of transcriptional and steady-state metabolomic data focused on identification of the most changing metabolic subnetworks between two conditions of interest. In the web-service, we have pre-assembled metabolic networks for humans, mice, Arabidopsis and yeast and adapted exact solvers for an optimal subgraph search to work in the context of these metabolic networks. The output is the most regulated metabolic subnetwork of size controlled by false discovery rate parameters. The subnetworks are then visualized online and also can be downloaded in Cytoscape format for subsequent processing. The web-service is available at: https://artyomovlab.wustl.edu/shiny/gam/.

Targeted next-generation sequencing (NGS) of nine candidate genes with custom AmpliSeq in patients and a cardiomyopathy risk group.

BACKGROUND: Hypertrophic cardiomyopathy is a common genetic cardiac disease. Prevention and early diagnosis of this disease are very important. Because of the large number of causative genes and the high rate of mutations involved in the pathogenesis of this disease, traditional methods of early diagnosis are ineffective. METHODS: We developed a custom AmpliSeq panel for NGS sequencing of the coding sequences of ACTC1, MYBPC3, MYH7, MYL2, MYL3, TNNI3, TNNT2, TPM1, and CASQ2. A genetic analysis of student cohorts (with and without cardiomyopathy risk in their medical histories) and patients with cardiomyopathies was performed. For the statistical and bioinformatics analysis, Polyphen2, SIFT, SnpSift and PLINK software were used. To select genetic markers in the patients with cardiomyopathy and in the students of the high risk group, four additive models were applied. RESULTS: Our AmpliSeq custom panel allowed us to efficiently explore targeted sequences. Based on the score analysis, we detected three substitutions in the MYBPC3 and CASQ2 genes and six combinations between loci in the MYBPC3, MYH7 and CASQ2 genes that were responsible for cardiomyopathy risk in our cohorts. We also detected substitutions in the TNNT2 gene that can be considered as protective against cardiomyopathy. CONCLUSION: We used NGS with AmpliSeq libraries and Ion PGM sequencing to develop improved predictive information for patients at risk of cardiomyopathy.