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Maayan, A.

Publications and source records attributed to Maayan, A..

4 recordsLinked to original sources

Chemokine Signatures Of Pathogen-Specific T Cells I: Effector T Cells

The choreography of complex immune responses, including the priming, differentiation, and modulation of specific effector T cell populations generated in the immediate wake of an acute pathogen challenge, is in part controlled by chemokines, a large family of mostly secreted molecules involved in chemotaxis and other patho/physiological processes. T cells are both responsive to varied chemokine cues and a relevant source for certain chemokines themselves. Yet the actual range, regulation, and role of effector T cell-derived chemokines remains incompletely understood. Here, using different in vivo models of viral and bacterial infection as well as protective vaccination, we have defined the entire spectrum of chemokines produced by pathogen-specific CD8+ and CD4+T effector cells, and delineated several unique properties pertaining to the temporospatial organization of chemokine expression patterns, synthesis and secretion kinetics, and cooperative regulation. Collectively, our results position the "T cell chemokine response" as a notably prominent, largely invariant yet distinctive force at the forefront of pathogen-specific effector T cell activities, and establish novel practical and conceptual approaches that may serve as a foundation for future investigations into role of T cell-produced chemokines in infectious and other diseases.

immunology↗

Immune Profiling of Atherosclerotic Plaques Identifies Innate and Adaptive Dysregulations Associated with Ischemic Cerebrovascular Events

Atherosclerosis is driven by multifaceted contributions of the immune system within the circulation and at vascular focal sites. Yet the specific immune dysregulations within the atherosclerotic lesions that lead to clinical cerebro- and cardiovascular complications (i.e. ischemic stroke and myocardial infarction) are poorly understood. Here, using single-cell mass cytometry with Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) we found that atherosclerotic plaques were enriched in activated, differentiated, and exhausted subsets of T cells vs. blood. Next, using single-cell proteomic, transcriptomic, and cell-to-cell interaction analyses we found unique functional dysregulations of both T cells and macrophages in plaques of patients with clinically symptomatic (SYM; recent stroke of TIA) or asymptomatic (ASYM, no recent stroke) carotid artery disease. SYM plaques were enriched with a distinct CD4+ T cell subset, and T cells were activated, differentiated and presented subset specific exhaustion. SYM macrophages presented alternatively activated phenotypes including subsets associated with plaque vulnerability. In ASYM plaques, T cells and macrophages were activated and displayed a strong IL-1{beta} signaling across cell types, that was absent in SYM plaques. The identification of plaque-specific innate and adaptive immune dysregulations associated with cerebrovascular events provides the basis for the design of precisely tailored cardiovascular immunotherapies.

immunology↗

piNET: a versatile web platform for downstream analysis and visualization of proteomics data

Large proteomics data, including those generated by mass spectrometry, are being generated to characterize biological systems at the protein level. Computational methods and tools to identify and quantify peptides, proteins and post-translational modifications (PTMs) that are captured in modern mass spectrometers have matured over the years. On the other hand, tools for downstream analysis, interpretation and visualization of proteomics data sets, in particular those involving PTMs, require further improvement and integration to accelerate scientific discovery and maximize the impact of proteomics studies by connecting them better with biological knowledge across not only proteomics, but also other Omics domains. With the goal of addressing these challenges, the piNET server has been developed as a versatile web platform to facilitate mapping, annotation, analysis and visualization of peptide, PTM, and protein level quantitative data generated by either targeted, shotgun or other proteomics approaches. Building on our experience with large scale analysis of gene and protein expression profiles as part of the Library of Integrated Network Cellular Signatures (LINCS) project, piNET has been designed as a fast, versatile and easy to use web-based tool with three modules that provide mapping from peptides (with PTMs) to proteins, from PTM sites to modifying enzymes that target those sites, and finally from proteins (with PTMs) to pathways, and for further mechanistic insights to LINCS signatures of chemical and genetic perturbations. piNET is freely available at http://www.pinet-server.org.

bioinformatics↗

The Signaling Pathways Project: an integrated ‘omics knowledgebase for mammalian cellular signaling pathways

Integrated mining of public transcriptomic and ChIP-Seq datasets has the potential to illuminate facets of mammalian cellular signaling pathways not yet explored in the research literature. Here, we designed a web knowledgebase, the Signaling Pathways Project (SPP), which incorporates stable community classifications of the four major categories of signaling pathway node (receptors, enzymes, transcription factors and co-nodes) and their cognate bioactive small molecules (BSMs). We then mapped over 10,000 public transcriptomic or cistromic experiments to their relevant signaling pathway node, BSM or biosample of study. To provide for prediction of pathway node-target transcriptional regulatory relationships, we generated consensus omics signatures, or consensomes, based on measures of significant differential expression of genomic targets across all underlying transcriptomic experiments. To expose the SPP knowledgebase to researchers, a web browser interface accommodates a variety of routine data mining strategies. Consensomes were validated using alignment with literature-based knowledge, gene target-level integration of transcriptomic and ChIP-Seq data points, and in bench experiments that confirmed previously uncharacterized node-gene target regulatory relationships. SPP is freely accessible at https://beta.signalingpathways.org.

bioinformatics↗