Defining Trained Immunity and Its Role in Health and Disease
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2016: Immunometabolism
Immunometabolism & 9, 2016 Paris, September 8 33è Journée Institut Cochin-JC Dreyfus & 7è Institut Cochin symposium, Paris (France) hursday, September 8, 2016 Metabolism and Immune cell Role of Immune cells in Diabetes and TFunction in Physiology and Cancer Atherosclerosis 09:00 Arginine and tryptophan metabolisms as team 14:30 players in immune regulation. Philippe Lesnik, Institute of Cardiometabolism and Ursula Grohmann, University of Perugia, Italy Nutrition (ICAN), Paris, France 09:30 Metabolism and survival of inflammatory cells. 15:00 Epigenomic control of macrophage activation in obesity Véronique Witko-Sarsat, Institut Cochin, Paris, and type 2 diabetes France Nicolas Venteclef, Centre de recherche des Cordeliers, Paris, France 10:00 T cell metabolism: it’s not all about glucose. Russell Jones, McGill University, Montreal, Canada 15:30 Coffee Break 10:30 Coffee Break 16:00 MAIT cells at the crossroad of microbiota, inflammation and diabetes. 11:00 Agnes Lehuen, Institut Cochin, Paris, France Olivier Hermine, Institut Imagine, Paris, France 16:30 Immunoregulation of liver fibrosis: novel targets. 11:30 The role of the hypoxic microenvironment in priming Sophie Lotersztajn, Centre de recherche sur immune response. l’inflammation CRI, Paris, France Randall Johnson, University of Cambridge, UK 17:00 Immune mechanisms of atherosclerosis. 12:00 Metabolism and T cell responses. Ziad Mallat, HEGP, Paris, France; King’s college, Christoph Hess, University Hospital Basel, Cambridge, UK Switzerland 17:30 Physiology of pro-inflammatory cytokines in metabolism: Therapeutic consequences. 12:30 Lunch Marc Donath, University Hospital Basel , Switzerland riday, September 9, 2016 Impact of Nutriments on Immune FCells at Steady state and Infection Keynote 09:00 Metabolic conditioning of hematopoietic stem 11:30 The birth of Immunometabolism and Implications for cell lineage specification: The Yins and Yangs of Metabolic Diseases. -
Figure S1. Representative Report Generated by the Ion Torrent System Server for Each of the KCC71 Panel Analysis and Pcafusion Analysis
Figure S1. Representative report generated by the Ion Torrent system server for each of the KCC71 panel analysis and PCaFusion analysis. (A) Details of the run summary report followed by the alignment summary report for the KCC71 panel analysis sequencing. (B) Details of the run summary report for the PCaFusion panel analysis. A Figure S1. Continued. Representative report generated by the Ion Torrent system server for each of the KCC71 panel analysis and PCaFusion analysis. (A) Details of the run summary report followed by the alignment summary report for the KCC71 panel analysis sequencing. (B) Details of the run summary report for the PCaFusion panel analysis. B Figure S2. Comparative analysis of the variant frequency found by the KCC71 panel and calculated from publicly available cBioPortal datasets. For each of the 71 genes in the KCC71 panel, the frequency of variants was calculated as the variant number found in the examined cases. Datasets marked with different colors and sample numbers of prostate cancer are presented in the upper right. *Significantly high in the present study. Figure S3. Seven subnetworks extracted from each of seven public prostate cancer gene networks in TCNG (Table SVI). Blue dots represent genes that include initial seed genes (parent nodes), and parent‑child and child‑grandchild genes in the network. Graphical representation of node‑to‑node associations and subnetwork structures that differed among and were unique to each of the seven subnetworks. TCNG, The Cancer Network Galaxy. Figure S4. REVIGO tree map showing the predicted biological processes of prostate cancer in the Japanese. Each rectangle represents a biological function in terms of a Gene Ontology (GO) term, with the size adjusted to represent the P‑value of the GO term in the underlying GO term database. -
A Flexible Microfluidic System for Single-Cell Transcriptome Profiling
www.nature.com/scientificreports OPEN A fexible microfuidic system for single‑cell transcriptome profling elucidates phased transcriptional regulators of cell cycle Karen Davey1,7, Daniel Wong2,7, Filip Konopacki2, Eugene Kwa1, Tony Ly3, Heike Fiegler2 & Christopher R. Sibley 1,4,5,6* Single cell transcriptome profling has emerged as a breakthrough technology for the high‑resolution understanding of complex cellular systems. Here we report a fexible, cost‑efective and user‑ friendly droplet‑based microfuidics system, called the Nadia Instrument, that can allow 3′ mRNA capture of ~ 50,000 single cells or individual nuclei in a single run. The precise pressure‑based system demonstrates highly reproducible droplet size, low doublet rates and high mRNA capture efciencies that compare favorably in the feld. Moreover, when combined with the Nadia Innovate, the system can be transformed into an adaptable setup that enables use of diferent bufers and barcoded bead confgurations to facilitate diverse applications. Finally, by 3′ mRNA profling asynchronous human and mouse cells at diferent phases of the cell cycle, we demonstrate the system’s ability to readily distinguish distinct cell populations and infer underlying transcriptional regulatory networks. Notably this provided supportive evidence for multiple transcription factors that had little or no known link to the cell cycle (e.g. DRAP1, ZKSCAN1 and CEBPZ). In summary, the Nadia platform represents a promising and fexible technology for future transcriptomic studies, and other related applications, at cell resolution. Single cell transcriptome profling has recently emerged as a breakthrough technology for understanding how cellular heterogeneity contributes to complex biological systems. Indeed, cultured cells, microorganisms, biopsies, blood and other tissues can be rapidly profled for quantifcation of gene expression at cell resolution. -
Old Vaccines for New Infections: Exploiting Innate Immunity to Control COVID-19 and Prevent Future Pandemics Downloaded by Guest on October 2, 2021 Table 1
PERSPECTIVE Old vaccines for new infections: Exploiting innate immunity to control COVID-19 and prevent PERSPECTIVE future pandemics Konstantin Chumakova, Michael S. Avidanb, Christine S. Bennc,d, Stefano M. Bertozzie,f,g, Lawrence Blatth, Angela Y. Changd, Dean T. Jamisoni, Shabaana A. Khaderj, Shyam Kottililk, Mihai G. Neteal,m, Annie Sparrown, and Robert C. Gallok,1 Edited by Peter Palese, Icahn School of Medicine at Mount Sinai, New York, NY, and approved March 17, 2021 (received for review January 29, 2021) The COVID-19 pandemic triggered an unparalleled pursuit of vaccines to induce specific adaptive immu- nity, based on virus-neutralizing antibodies and T cell responses. Although several vaccines have been developed just a year after SARS-CoV-2 emerged in late 2019, global deployment will take months or even years. Meanwhile, the virus continues to take a severe toll on human life and exact substantial economic costs. Innate immunity is fundamental to mammalian host defense capacity to combat infections. Innate immune responses, triggered by a family of pattern recognition receptors, induce interferons and other cytokines and activate both myeloid and lymphoid immune cells to provide protection against a wide range of pathogens. Epidemiological and biological evidence suggests that the live-attenuated vaccines (LAV) targeting tuberculosis, measles, and polio induce protective innate immunity by a newly described form of immunological memory termed “trained immunity.” An LAV designed to induce adaptive immunity targeting a particular pathogen may also induce innate immunity that mitigates other infectious diseases, including COVID-19, as well as future pandemic threats. Deployment of existing LAVs early in pandemics could complement the development of specific vaccines, bridging the protection gap until specific vac- cines arrive. -
Chronic Tissue Inflammation and Metabolic Disease
Downloaded from genesdev.cshlp.org on September 27, 2021 - Published by Cold Spring Harbor Laboratory Press REVIEW Chronic tissue inflammation and metabolic disease Yun Sok Lee and Jerrold Olefsky Department of Medicine, Division of Endocrinology and Metabolism, University of California at San Diego, La Jolla, California 92093, USA Obesity is the most common cause of insulin resistance, Although there are a number of potential, and some- and the current obesity epidemic is driving a parallel times overlapping, mechanisms that can contribute to in- rise in the incidence of T2DM. It is now widely recognized sulin resistance and β-cell dysfunction, in this current that chronic, subacute tissue inflammation is a major eti- review we focus on the role of chronic tissue inflamma- ologic component of the pathogenesis of insulin resis- tion in these metabolic defects. The reader is referred to tance and metabolic dysfunction in obesity. Here, we other excellent reviews on possible causes of insulin resis- summarize recent advances in our understanding of tance and β-cell dysfunction, independent of chronic tis- immunometabolism. We discuss the characteristics of sue inflammation (Halban et al. 2014; DeFronzo et al. chronic inflammation in the major metabolic tissues 2015; Czech 2017; Newgard 2017; Guilherme et al. and how obesity triggers these events, including a focus 2019; Kahn et al. 2019; Roden and Shulman 2019; Scherer on the role of adipose tissue hypoxia and macrophage-de- 2019; Alonge et al. 2021; Sangwung et al. 2020). rived exosomes. Last, we also review current and potential The interconnections between inflammation and meta- new therapeutic strategies based on immunomodulation. -
What Your Genome Doesn't Tell
UC San Diego UC San Diego Electronic Theses and Dissertations Title Multi-layered epigenetic control of T cell fate decisions Permalink https://escholarship.org/uc/item/8rs7c7b3 Author Yu, Bingfei Publication Date 2018 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California UNIVERSITY OF CALIFORNIA SAN DIEGO Multi-layered epigenetic control of T cell fate decisions A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Biology by Bingfei Yu Committee in charge: Professor Ananda Goldrath, Chair Professor John Chang Professor Stephen Hedrick Professor Cornelis Murre Professor Wei Wang 2018 Copyright Bingfei Yu, 2018 All rights reserved. The dissertation of Bingfei Yu is approved, and it is ac- ceptable in quality and form for publication on microfilm and electronically: Chair University of California San Diego 2018 iii DEDICATION To my parents who have been giving me countless love, trust and support to make me who I am. iv EPIGRAPH Stay hungary. Stay foolish. | Steve Jobs quoted from the back cover of the 1974 edition of the Whole Earth Catalog v TABLE OF CONTENTS Signature Page.................................. iii Dedication..................................... iv Epigraph.....................................v Table of Contents................................. vi List of Figures.................................. ix Acknowledgements................................x Vita........................................ xii Abstract of -
Infectious Agents As Stimuli of Trained Innate Immunity
International Journal of Molecular Sciences Review Infectious Agents as Stimuli of Trained Innate Immunity Paulina Rusek 1, Mateusz Wala 2 ID , Magdalena Druszczy ´nska 1 and Marek Fol 1,* 1 Department of Immunology and Infectious Biology, Faculty of Biology and Environmental Protection, University of Lodz, Banacha St. 12/16, 90-237 Lodz, Poland; [email protected] (P.R.); [email protected] (M.D.) 2 Department of Plant Physiology and Biochemistry, Faculty of Biology and Environmental Protection, University of Lodz, Banacha St. 12/16, 90-237 Lodz, Poland; [email protected] * Correspondence: [email protected]; Tel.: +48-42-635-44-72 Received: 22 December 2017; Accepted: 2 February 2018; Published: 3 February 2018 Abstract: The discoveries made over the past few years have modified the current immunological paradigm. It turns out that innate immunity cells can mount some kind of immunological memory, similar to that observed in the acquired immunity and corresponding to the defense mechanisms of lower organisms, which increases their resistance to reinfection. This phenomenon is termed trained innate immunity. It is based on epigenetic changes in innate immune cells (monocytes/macrophages, NK cells) after their stimulation with various infectious or non-infectious agents. Many infectious stimuli, including bacterial or fungal cells and their components (LPS, β-glucan, chitin) as well as viruses or even parasites are considered potent inducers of innate immune memory. Epigenetic cell reprogramming occurring at the heart of the phenomenon may provide a useful basis for designing novel prophylactic and therapeutic strategies to prevent and protect against multiple diseases. In this article, we present the current state of art on trained innate immunity occurring as a result of infectious agent induction. -
Application of Microrna Database Mining in Biomarker Discovery and Identification of Therapeutic Targets for Complex Disease
Article Application of microRNA Database Mining in Biomarker Discovery and Identification of Therapeutic Targets for Complex Disease Jennifer L. Major, Rushita A. Bagchi * and Julie Pires da Silva * Department of Medicine, Division of Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; [email protected] * Correspondence: [email protected] (R.A.B.); [email protected] (J.P.d.S.) Supplementary Tables Methods Protoc. 2021, 4, 5. https://doi.org/10.3390/mps4010005 www.mdpi.com/journal/mps Methods Protoc. 2021, 4, 5. https://doi.org/10.3390/mps4010005 2 of 25 Table 1. List of all hsa-miRs identified by Human microRNA Disease Database (HMDD; v3.2) analysis. hsa-miRs were identified using the term “genetics” and “circulating” as input in HMDD. Targets CAD hsa-miR-1 Targets IR injury hsa-miR-423 Targets Obesity hsa-miR-499 hsa-miR-146a Circulating Obesity Genetics CAD hsa-miR-423 hsa-miR-146a Circulating CAD hsa-miR-149 hsa-miR-499 Circulating IR Injury hsa-miR-146a Circulating Obesity hsa-miR-122 Genetics Stroke Circulating CAD hsa-miR-122 Circulating Stroke hsa-miR-122 Genetics Obesity Circulating Stroke hsa-miR-26b hsa-miR-17 hsa-miR-223 Targets CAD hsa-miR-340 hsa-miR-34a hsa-miR-92a hsa-miR-126 Circulating Obesity Targets IR injury hsa-miR-21 hsa-miR-423 hsa-miR-126 hsa-miR-143 Targets Obesity hsa-miR-21 hsa-miR-223 hsa-miR-34a hsa-miR-17 Targets CAD hsa-miR-223 hsa-miR-92a hsa-miR-126 Targets IR injury hsa-miR-155 hsa-miR-21 Circulating CAD hsa-miR-126 hsa-miR-145 hsa-miR-21 Targets Obesity hsa-mir-223 hsa-mir-499 hsa-mir-574 Targets IR injury hsa-mir-21 Circulating IR injury Targets Obesity hsa-mir-21 Targets CAD hsa-mir-22 hsa-mir-133a Targets IR injury hsa-mir-155 hsa-mir-21 Circulating Stroke hsa-mir-145 hsa-mir-146b Targets Obesity hsa-mir-21 hsa-mir-29b Methods Protoc. -
Immunometabolism Research Focus: Cell Metabolism & NAD+ Metabolism
www.adipogen.com Immunometabolism Research Focus: Cell Metabolism & NAD+ Metabolism Immunometabolism is a research field that provides new insights into the dynamic cross-talk between the immune system (immunity) and metabolic processes of an organism (metabolism). Immunometabolism tries to understand how metabolism controls the function of immune cells. It can be studied at a macroscopic level (e.g. in adipose tissues (see Figure 1) or in a tumor microenvironment) and at a microscopic level, the cellular bioenergetics of immune cells (see Figure 2). The activation, growth and proliferation, function and homeostasis of immune cells are intimately linked to dynamic changes in cellular metabolism configurations. The utilization of particular metabolic pathways is controlled by growth factors and nutrient availability (dictated by competition between other interacting cells) and by the balance of internal metabolites, reactive oxygen species (ROS) and reducing/oxidizing substrates. Major metabolic pathways (see Figure 2) that shape the immune cell response include glycolysis, the tricarboxylic acid (TCA) cycle, the pentose phosphate pathway (PPP), fatty acid oxidation (FAO), fatty acid synthesis (FAS) and amino acid (AA) metabolism (e.g. Glutamine, Arginine, Tryptophan). The various immune cell subsets use distinct metabolic pathways to promote cell survival, lineage generation and function. For example, inflammatory M1 macrophages or rapidly proliferating effector T cells, including T helper 1 (TH1), TH17 and cytotoxic CD8+ T cells, use metabolic pathways that support cell proliferation and the production of cytokines, such as glycolysis or fatty acid synthesis. M2 macrophages or immunosuppressive regulatory T (Treg) cells use metabolic pathways which inhibit inflammatory signals and are associated with suppressive functions, such as TCA cycle and fatty acid oxidation. -
Vaccine Immunology Claire-Anne Siegrist
2 Vaccine Immunology Claire-Anne Siegrist To generate vaccine-mediated protection is a complex chal- non–antigen-specifc responses possibly leading to allergy, lenge. Currently available vaccines have largely been devel- autoimmunity, or even premature death—are being raised. oped empirically, with little or no understanding of how they Certain “off-targets effects” of vaccines have also been recog- activate the immune system. Their early protective effcacy is nized and call for studies to quantify their impact and identify primarily conferred by the induction of antigen-specifc anti- the mechanisms at play. The objective of this chapter is to bodies (Box 2.1). However, there is more to antibody- extract from the complex and rapidly evolving feld of immu- mediated protection than the peak of vaccine-induced nology the main concepts that are useful to better address antibody titers. The quality of such antibodies (e.g., their these important questions. avidity, specifcity, or neutralizing capacity) has been identi- fed as a determining factor in effcacy. Long-term protection HOW DO VACCINES MEDIATE PROTECTION? requires the persistence of vaccine antibodies above protective thresholds and/or the maintenance of immune memory cells Vaccines protect by inducing effector mechanisms (cells or capable of rapid and effective reactivation with subsequent molecules) capable of rapidly controlling replicating patho- microbial exposure. The determinants of immune memory gens or inactivating their toxic components. Vaccine-induced induction, as well as the relative contribution of persisting immune effectors (Table 2.1) are essentially antibodies— antibodies and of immune memory to protection against spe- produced by B lymphocytes—capable of binding specifcally cifc diseases, are essential parameters of long-term vaccine to a toxin or a pathogen.2 Other potential effectors are cyto- effcacy. -
Single Cell Derived Clonal Analysis of Human Glioblastoma Links
SUPPLEMENTARY INFORMATION: Single cell derived clonal analysis of human glioblastoma links functional and genomic heterogeneity ! Mona Meyer*, Jüri Reimand*, Xiaoyang Lan, Renee Head, Xueming Zhu, Michelle Kushida, Jane Bayani, Jessica C. Pressey, Anath Lionel, Ian D. Clarke, Michael Cusimano, Jeremy Squire, Stephen Scherer, Mark Bernstein, Melanie A. Woodin, Gary D. Bader**, and Peter B. Dirks**! ! * These authors contributed equally to this work.! ** Correspondence: [email protected] or [email protected]! ! Supplementary information - Meyer, Reimand et al. Supplementary methods" 4" Patient samples and fluorescence activated cell sorting (FACS)! 4! Differentiation! 4! Immunocytochemistry and EdU Imaging! 4! Proliferation! 5! Western blotting ! 5! Temozolomide treatment! 5! NCI drug library screen! 6! Orthotopic injections! 6! Immunohistochemistry on tumor sections! 6! Promoter methylation of MGMT! 6! Fluorescence in situ Hybridization (FISH)! 7! SNP6 microarray analysis and genome segmentation! 7! Calling copy number alterations! 8! Mapping altered genome segments to genes! 8! Recurrently altered genes with clonal variability! 9! Global analyses of copy number alterations! 9! Phylogenetic analysis of copy number alterations! 10! Microarray analysis! 10! Gene expression differences of TMZ resistant and sensitive clones of GBM-482! 10! Reverse transcription-PCR analyses! 11! Tumor subtype analysis of TMZ-sensitive and resistant clones! 11! Pathway analysis of gene expression in the TMZ-sensitive clone of GBM-482! 11! Supplementary figures and tables" 13" "2 Supplementary information - Meyer, Reimand et al. Table S1: Individual clones from all patient tumors are tumorigenic. ! 14! Fig. S1: clonal tumorigenicity.! 15! Fig. S2: clonal heterogeneity of EGFR and PTEN expression.! 20! Fig. S3: clonal heterogeneity of proliferation.! 21! Fig. -
Innate Immune Responses to Mycobacterium Tuberculosis Infection
Linköping University Medical Dissertation No. 1761 Clara Braian Braian Clara FACULTY OF MEDICINE AND HEALTH SCIENCES Linköping University Medical Dissertation No. 1761, 2020 Department of Biomedical and Clinical Sciences Linköping University SE-581 83 Linköping, Sweden Innate immune responses Innate to Innate immune responses to www.liu.se Mycobacterium tuberculosis infection How extracellular traps and trained immunity can restrict bacterial growth Mycobacterium tuberculosis Mycobacterium Clara Braian infection 2020 Linkoping University Medical Dissertation No. 1761 Innate immune responses to Mycobacterium tuberculosis infection How extracellular traps and trained immunity can restrict bacterial grow th Clara Braian D e p a r t m e n t f i o m e d i c a l a n d l i n i c a l c i e n c e s D i v i s i o n o f n f l a m m a t i o n n d n f e c t i o n F a c u l t y o f M e d i c i n e n d e a l t h c i e n c e s L i n k ö p i n g s n i v e r s i t e t , E - 5 8 1 3 L i n k ö p i n g , w e d e n L i n k ö p i n g 2 0 2 0 © Clara Braian, 2020 All rights reserved. Paper I, II and III are reprinted with permission from the respective publishers.