1
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Krueger A, Łyszkiewicz M, Heissmeyer V. Post-transcriptional control of T-cell development in the thymus. Immunol Lett 2022; 247:1-12. [DOI: 10.1016/j.imlet.2022.04.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 03/18/2022] [Accepted: 04/26/2022] [Indexed: 11/05/2022]
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2
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Svoronos AA, Campbell SG, Engelman DM. MicroRNA function can be reversed by altering target gene expression levels. iScience 2021; 24:103208. [PMID: 34755085 PMCID: PMC8560630 DOI: 10.1016/j.isci.2021.103208] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Revised: 07/14/2021] [Accepted: 09/29/2021] [Indexed: 11/17/2022] Open
Abstract
Paradoxically, many microRNAs appear to exhibit entirely opposite functions when placed in different contexts. For example, miR-125b has been shown to be pro-apoptotic in some studies, but anti-apoptotic in others. To investigate this phenomenon, we combine computational modeling with experimental approaches to examine how the function of miR-125b in apoptosis varies with respect to the expression levels of its pro-apoptotic and anti-apoptotic targets. In doing so, we elucidate a general trend that miR-125b is more pro-apoptotic when its anti-apoptotic targets are overexpressed, whereas it is more anti-apoptotic when its pro-apoptotic targets are overexpressed. We show that it is possible to completely reverse miR-125b′s function in apoptosis by modifying the expression levels of its target genes. Furthermore, miR-125b′s function may also be altered by the presence of anticancer drugs. These results suggest that the function of a microRNA can vary substantially and is dependent on its target gene expression levels. Many miRNAs exhibit entirely opposite functions when placed in different contexts miR-125b can be pro- or anti-apoptotic depending on target gene expression levels The function of a miRNA can be reversed by altering target gene expression levels The presence of anticancer drugs can also alter a miRNA's function
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Affiliation(s)
- Alexander A Svoronos
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA.,Department of Molecular Biophysics and Biochemistry, Yale University, 266 Whitney Av., P.O. Box 208114, New Haven, CT 06520, USA
| | - Stuart G Campbell
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA
| | - Donald M Engelman
- Department of Molecular Biophysics and Biochemistry, Yale University, 266 Whitney Av., P.O. Box 208114, New Haven, CT 06520, USA
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3
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Mendenhall AR, Martin GM, Kaeberlein M, Anderson RM. Cell-to-cell variation in gene expression and the aging process. GeroScience 2021; 43:181-196. [PMID: 33595768 PMCID: PMC8050212 DOI: 10.1007/s11357-021-00339-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Accepted: 02/04/2021] [Indexed: 12/11/2022] Open
Abstract
There is tremendous variation in biological traits, and much of it is not accounted for by variation in DNA sequence, including human diseases and lifespan. Emerging evidence points to differences in the execution of the genetic program as a key source of variation, be it stochastic variation or programmed variation. Here we discuss variation in gene expression as an intrinsic property and how it could contribute to variation in traits, including the rate of aging. The review is divided into sections describing the historical context and evidence to date for nongenetic variation, the different approaches that may be used to detect nongenetic variation, and recent findings showing that the amount of variation in gene expression can be both genetically programmed and epigenetically controlled. Finally, we present evidence that changes in cell-to-cell variation in gene expression emerge as part of the aging process and may be linked to disease vulnerability as a function of age. These emerging concepts are likely to be important across the spectrum of biomedical research and may well underpin what we understand as biological aging.
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Affiliation(s)
- Alexander R Mendenhall
- Department of Laboratory Medicine and Pathology, School of Medicine, University of Washington, Seattle, WA, USA.
- Nathan Shock Center for Excellence in the Basic Biology of Aging, School of Medicine, University of Washington, Seattle, WA, USA.
| | - George M Martin
- Department of Laboratory Medicine and Pathology, School of Medicine, University of Washington, Seattle, WA, USA
- Nathan Shock Center for Excellence in the Basic Biology of Aging, School of Medicine, University of Washington, Seattle, WA, USA
| | - Matt Kaeberlein
- Department of Laboratory Medicine and Pathology, School of Medicine, University of Washington, Seattle, WA, USA
- Nathan Shock Center for Excellence in the Basic Biology of Aging, School of Medicine, University of Washington, Seattle, WA, USA
| | - Rozalyn M Anderson
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin and Geriatric Research Education and Clinical Center, William S Middleton Memorial Veterans Hospital, Madison, WI, USA.
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4
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Sartorius K, Swadling L, An P, Makarova J, Winkler C, Chuturgoon A, Kramvis A. The Multiple Roles of Hepatitis B Virus X Protein (HBx) Dysregulated MicroRNA in Hepatitis B Virus-Associated Hepatocellular Carcinoma (HBV-HCC) and Immune Pathways. Viruses 2020; 12:v12070746. [PMID: 32664401 PMCID: PMC7412373 DOI: 10.3390/v12070746] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 07/08/2020] [Accepted: 07/09/2020] [Indexed: 12/11/2022] Open
Abstract
Currently, the treatment of hepatitis B virus (HBV)-associated hepatocellular carcinoma (HCC) [HBV-HCC] relies on blunt tools that are unable to offer effective therapy for later stage pathogenesis. The potential of miRNA to treat HBV-HCC offer a more targeted approach to managing this lethal carcinoma; however, the complexity of miRNA as an ancillary regulator of the immune system remains poorly understood. This review examines the overlapping roles of HBx-dysregulated miRNA in HBV-HCC and immune pathways and seeks to demonstrate that specific miRNA response in immune cells is not independent of their expression in hepatocytes. This interplay between the two pathways may provide us with the possibility of using candidate miRNA to manipulate this interaction as a potential therapeutic option.
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Affiliation(s)
- Kurt Sartorius
- Faculty of Commerce, Law and Management, University of the Witwatersrand, Johannesburg 2050, South Africa
- Department of Public Health Medicine, School of Nursing and Public Health, University of KwaZulu-Natal, Durban 4041, South Africa;
- UKZN Gastrointestinal Cancer Research Centre, Durban 4041, South Africa
- Correspondence:
| | - Leo Swadling
- Division of Infection and Immunity, University College London, London WC1E6BT, UK;
| | - Ping An
- Basic Research Laboratory, Centre for Cancer Research, National Cancer Institute, Leidos Biomedical Research, Inc. Frederick Nat. Lab. for Cancer Research, Frederick, MD 20878, USA; (P.A.); (C.W.)
| | - Julia Makarova
- National Research University Higher School of Economics, Faculty of Biology and Biotechnology, 10100 Moscow, Russia;
| | - Cheryl Winkler
- Basic Research Laboratory, Centre for Cancer Research, National Cancer Institute, Leidos Biomedical Research, Inc. Frederick Nat. Lab. for Cancer Research, Frederick, MD 20878, USA; (P.A.); (C.W.)
| | - Anil Chuturgoon
- Department of Public Health Medicine, School of Nursing and Public Health, University of KwaZulu-Natal, Durban 4041, South Africa;
| | - Anna Kramvis
- Hepatitis Virus Diversity Research Unit, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg 2050, South Africa;
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5
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Early microRNA indicators of PPARα pathway activation in the liver. Toxicol Rep 2020; 7:805-815. [PMID: 32642447 PMCID: PMC7334544 DOI: 10.1016/j.toxrep.2020.06.006] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Revised: 06/01/2020] [Accepted: 06/19/2020] [Indexed: 12/29/2022] Open
Abstract
MicroRNAs (miRNAs) are short non-coding RNA species that play key roles in post-transcriptional regulation of gene expression. MiRNAs also serve as a promising source of early biomarkers for different environmental exposures and health effects, although there is limited information linking miRNA changes to specific target pathways. In this study, we measured liver miRNAs in male B6C3F1 mice exposed to a known chemical activator of the peroxisome proliferator-activated receptor alpha (PPARα) pathway, di(2-ethylhexyl) phthalate (DEHP), for 7 and 28 days at concentrations of 0, 750, 1500, 3000, or 6000 ppm in feed. At the highest dose tested, DEHP altered 61 miRNAs after 7 days and 171 miRNAs after 28 days of exposure, with 48 overlapping miRNAs between timepoints. Analysis of these 48 common miRNAs indicated enrichment in PPARα–related targets and other pathways related to liver injury and cancer. Four of the 10 miRNAs exhibiting a clear dose trend were linked to the PPARα pathway: mmu-miRs-125a-5p, -182−5p, -20a−5p, and -378a−3p. mmu-miRs-182−5p and -378a−3p were subsequently measured using digital drop PCR across a dose range for DEHP and two related phthalates with weaker PPARα activity, di-n-octyl phthalate and n-butyl benzyl phthalate, following 7-day exposures. Analysis of mmu-miRs-182−5p and -378a−3p by transcriptional benchmark dose analysis correctly identified DEHP as having the greatest potency. However, benchmark dose estimates for DEHP based on these miRNAs (average 163; range 126−202 mg/kg-day) were higher on average than values for PPARα target genes (average 74; range 29−183 mg/kg-day). These findings identify putative miRNA biomarkers of PPARα pathway activity and suggest that early miRNA changes may be used to stratify chemical potency.
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Key Words
- AIC, Akaike Information Criterion
- ALT, alanine aminotransferase
- AOP, adverse outcome pathway
- AST, aspartate aminotransferase
- Acox1, acyl-Coenzyme A oxidase 1
- Adverse outcome pathway (AOP)
- AhR, aryl hydrocarbon receptor
- BBP, n-butyl benzyl phthalate
- BMD, benchmark dose
- BMDA, apical-based benchmark dose
- BMDL, BMD lower confidence interval
- BMDT, transcriptional-based benchmark dose
- BMR, benchmark response
- BROD, benzyloxyresorufin O-debenzylation
- Benchmark dose (BMD)
- Biomarkers
- CAR, constitutive androstane receptor
- DEGs, differentially expressed genes
- DEHP, di (2-thylhexyl) phthalate
- DEmiRs, differentially expressed miRNAs
- DNOP, di-n-octyl phthalate
- EPA, U.S. Environmental Protection Agency
- EROD, ethoxyresorufin O-dealkylation
- GEO, Gene Expression Omnibus
- HCA, hepatocellular adenoma
- HCC, hepatocellular carcinoma
- Hepatocellular carcinoma
- IPA, Ingenuity Pathway Analysis
- Liver toxicity
- MOA, mode of action
- MicroRNAs
- Mode of action (MOA)
- Nrf2, nuclear receptor erythroid 2-like 2
- POD, point-of-departure
- PPARα, peroxisome proliferator-activated receptor alpha
- PROD, pentoxyresorufin O-depentylation
- PXR, pregnane X receptor
- Peroxisome proliferator-activated receptor alpha (PPARα)
- Phthalate
- SDH, sorbitol dehydrogenase
- TMM, trimmed mean of M-values
- ddPCR, droplet digital polymerase chain reaction
- mRNA, messenger RNA
- miRNAs, microRNAs
- mtDNA, mitochondrial
- rRNA, ribosomal RNA
- smallRNA-seq, small RNA sequencing
- tRNA, transfer RNA
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Baskara-Yhuellou I, Tost J. The impact of microRNAs on alterations of gene regulatory networks in allergic diseases. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2020; 120:237-312. [PMID: 32085883 DOI: 10.1016/bs.apcsb.2019.11.006] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Allergic diseases including asthma are worldwide on the rise and contribute significantly to health expenditures. Allergic diseases are prototypic diseases with a strong gene by environment interaction component and epigenetic mechanisms might mediate the effects of the environment on the disease phenotype. MicroRNAs, small non-coding RNAs (miRNAs), regulate gene expression post-transcriptionally. Functional single-stranded miRNAs are generated in multiple steps of enzymatic processing from their precursors and mature miRNAs are included into the RNA-induced silencing complex (RISC). They imperfectly base-pair with the 3'UTR region of targeted genes leading to translational repression or mRNA decay. The cellular context and microenvironment as well the isoform of the mRNA control the dynamics and complexity of the regulatory circuits induced by miRNAs that regulate cell fate decisions and function. MiR-21, miR-146a/b and miR-155 are among the best understood miRNAs of the immune system and implicated in different diseases including allergic diseases. MiRNAs are implicated in the induction of the allergy reinforcing the Th2 phenotype (miR-19a, miR-24, miR-27), while other miRNAs promote regulatory T cells associated with allergen tolerance or unresponsiveness. In the current chapter we describe in detail the biogenesis and regulatory function of miRNAs and summarize current knowledge on miRNAs in allergic diseases and allergy relevant cell fate decisions focusing mainly on immune cells. Furthermore, we evoke the principles of regulatory loops and feedback mechanisms involving miRNAs on examples with relevance for allergic diseases. Finally, we show the potential of miRNAs and exosomes containing miRNAs present in several biological fluids that can be exploited with non-invasive procedures for diagnostic and potentially therapeutic purposes.
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Affiliation(s)
- Indoumady Baskara-Yhuellou
- Laboratory for Epigenetics & Environment, Centre National de Recherche en Génomique Humaine, CEA-Institut de Biologie François Jacob, Evry, France
| | - Jörg Tost
- Laboratory for Epigenetics & Environment, Centre National de Recherche en Génomique Humaine, CEA-Institut de Biologie François Jacob, Evry, France
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7
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Chen Y, Shen Y, Lin P, Tong D, Zhao Y, Allesina S, Shen X, Wu CI. Gene regulatory network stabilized by pervasive weak repressions: microRNA functions revealed by the May-Wigner theory. Natl Sci Rev 2019; 6:1176-1188. [PMID: 34691996 PMCID: PMC8291590 DOI: 10.1093/nsr/nwz076] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2019] [Revised: 06/07/2019] [Accepted: 06/10/2019] [Indexed: 01/01/2023] Open
Abstract
Food web and gene regulatory networks (GRNs) are large biological networks, both of which can be analyzed using the May-Wigner theory. According to the theory, networks as large as mammalian GRNs would require dedicated gene products for stabilization. We propose that microRNAs (miRNAs) are those products. More than 30% of genes are repressed by miRNAs, but most repressions are too weak to have a phenotypic consequence. The theory shows that (i) weak repressions cumulatively enhance the stability of GRNs, and (ii) broad and weak repressions confer greater stability than a few strong ones. Hence, the diffuse actions of miRNAs in mammalian cells appear to function mainly in stabilizing GRNs. The postulated link between mRNA repression and GRN stability can be seen in a different light in yeast, which do not have miRNAs. Yeast cells rely on non-specific RNA nucleases to strongly degrade mRNAs for GRN stability. The strategy is suited to GRNs of small and rapidly dividing yeast cells, but not the larger mammalian cells. In conclusion, the May-Wigner theory, supplanting the analysis of small motifs, provides a mathematical solution to GRN stability, thus linking miRNAs explicitly to 'developmental canalization'.
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Affiliation(s)
- Yuxin Chen
- School of Life Science, Sun Yat-Sen University, Guangzhou 510275, China
| | - Yang Shen
- School of Life Science, Sun Yat-Sen University, Guangzhou 510275, China
- Target Discovery Research, Boehringer Ingelheim Pharma GmbH & Co KG, 88397 Biberach an der Riß, Germany
| | - Pei Lin
- School of Life Science, Sun Yat-Sen University, Guangzhou 510275, China
| | - Ding Tong
- School of Life Science, Sun Yat-Sen University, Guangzhou 510275, China
- Department of Biostatistics, School of Public Health, Yale University, New Haven, CT 06520, UK
| | - Yixin Zhao
- School of Life Science, Sun Yat-Sen University, Guangzhou 510275, China
| | - Stefano Allesina
- Department of Ecology and Evolution, University of Chicago, Chicago, IL 60637, UK
| | - Xu Shen
- School of Life Science, Sun Yat-Sen University, Guangzhou 510275, China
| | - Chung-I Wu
- School of Life Science, Sun Yat-Sen University, Guangzhou 510275, China
- Department of Ecology and Evolution, University of Chicago, Chicago, IL 60637, UK
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8
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Rzepiela AJ, Ghosh S, Breda J, Vina-Vilaseca A, Syed AP, Gruber AJ, Eschbach K, Beisel C, van Nimwegen E, Zavolan M. Single-cell mRNA profiling reveals the hierarchical response of miRNA targets to miRNA induction. Mol Syst Biol 2018; 14:e8266. [PMID: 30150282 PMCID: PMC6110312 DOI: 10.15252/msb.20188266] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2018] [Revised: 07/31/2018] [Accepted: 08/03/2018] [Indexed: 12/14/2022] Open
Abstract
miRNAs are small RNAs that regulate gene expression post-transcriptionally. By repressing the translation and promoting the degradation of target mRNAs, miRNAs may reduce the cell-to-cell variability in protein expression, induce correlations between target expression levels, and provide a layer through which targets can influence each other's expression as "competing RNAs" (ceRNAs). However, experimental evidence for these behaviors is limited. Combining mathematical modeling with RNA sequencing of individual human embryonic kidney cells in which the expression of two distinct miRNAs was induced over a wide range, we have inferred parameters describing the response of hundreds of miRNA targets to miRNA induction. Individual targets have widely different response dynamics, and only a small proportion of predicted targets exhibit high sensitivity to miRNA induction. Our data reveal for the first time the response parameters of the entire network of endogenous miRNA targets to miRNA induction, demonstrating that miRNAs correlate target expression and at the same time increase the variability in expression of individual targets across cells. The approach is generalizable to other miRNAs and post-transcriptional regulators to improve the understanding of gene expression dynamics in individual cell types.
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Affiliation(s)
- Andrzej J Rzepiela
- Biozentrum, University of Basel and Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Souvik Ghosh
- Biozentrum, University of Basel and Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Jeremie Breda
- Biozentrum, University of Basel and Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Arnau Vina-Vilaseca
- Biozentrum, University of Basel and Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Afzal P Syed
- Biozentrum, University of Basel and Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Andreas J Gruber
- Biozentrum, University of Basel and Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Katja Eschbach
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
| | - Christian Beisel
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
| | - Erik van Nimwegen
- Biozentrum, University of Basel and Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Mihaela Zavolan
- Biozentrum, University of Basel and Swiss Institute of Bioinformatics, Basel, Switzerland
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9
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Hope JL, Stairiker CJ, Spantidea PI, Gracias DT, Carey AJ, Fike AJ, van Meurs M, Brouwers-Haspels I, Rijsbergen LC, Fraietta JA, Mueller YM, Klop RC, Stelekati E, Wherry EJ, Erkeland SJ, Katsikis PD. The Transcription Factor T-Bet Is Regulated by MicroRNA-155 in Murine Anti-Viral CD8 + T Cells via SHIP-1. Front Immunol 2017; 8:1696. [PMID: 29358931 PMCID: PMC5765282 DOI: 10.3389/fimmu.2017.01696] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2017] [Accepted: 11/16/2017] [Indexed: 12/21/2022] Open
Abstract
We report here that the expression of the transcription factor T-bet, which is known to be required for effector cytotoxic CD8+ T lymphocytes (CTL) generation and effector memory cell formation, is regulated in CTL by microRNA-155 (miR-155). Importantly, we show that the proliferative effect of miR-155 on CD8+ T cells is mediated by T-bet. T-bet levels in CTL were controlled in vivo by miR-155 via SH2 (Src homology 2)-containing inositol phosphatase-1 (SHIP-1), a known direct target of miR-155, and SHIP-1 directly downregulated T-bet. Our studies reveal an important and unexpected signaling axis between miR-155, T-bet, and SHIP-1 in in vivo CTL responses and suggest an important signaling module that regulates effector CTL immunity.
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Affiliation(s)
- Jennifer L Hope
- Department of Immunology, Erasmus MC University Medical Center, Rotterdam, Netherlands.,Department of Microbiology and Immunology, Drexel University College of Medicine, Philadelphia, PA, United States
| | - Christopher J Stairiker
- Department of Immunology, Erasmus MC University Medical Center, Rotterdam, Netherlands.,Department of Microbiology and Immunology, Drexel University College of Medicine, Philadelphia, PA, United States
| | - Panagiota I Spantidea
- Department of Immunology, Erasmus MC University Medical Center, Rotterdam, Netherlands
| | - Donald T Gracias
- Department of Microbiology and Immunology, Drexel University College of Medicine, Philadelphia, PA, United States
| | - Alison J Carey
- Department of Microbiology and Immunology, Drexel University College of Medicine, Philadelphia, PA, United States.,Department of Pediatrics, Drexel University College of Medicine, Philadelphia, PA, United States
| | - Adam J Fike
- Department of Microbiology and Immunology, Drexel University College of Medicine, Philadelphia, PA, United States
| | - Marjan van Meurs
- Department of Immunology, Erasmus MC University Medical Center, Rotterdam, Netherlands
| | - Inge Brouwers-Haspels
- Department of Immunology, Erasmus MC University Medical Center, Rotterdam, Netherlands
| | - Laurine C Rijsbergen
- Department of Immunology, Erasmus MC University Medical Center, Rotterdam, Netherlands
| | - Joseph A Fraietta
- Center for Cellular Immunotherapies and Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, United States
| | - Yvonne M Mueller
- Department of Immunology, Erasmus MC University Medical Center, Rotterdam, Netherlands
| | - Rosemarieke C Klop
- Department of Immunology, Erasmus MC University Medical Center, Rotterdam, Netherlands
| | - Erietta Stelekati
- Institute for Immunology, University of Pennsylvania, Philadelphia, PA, United States
| | - E John Wherry
- Institute for Immunology, University of Pennsylvania, Philadelphia, PA, United States
| | - Stefan J Erkeland
- Department of Immunology, Erasmus MC University Medical Center, Rotterdam, Netherlands
| | - Peter D Katsikis
- Department of Immunology, Erasmus MC University Medical Center, Rotterdam, Netherlands
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10
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Gao PF, Guo XH, Du M, Cao GQ, Yang QC, Pu ZD, Wang ZY, Zhang Q, Li M, Jin YS, Wang XJ, Liu H, Li BG. LncRNA profiling of skeletal muscles in Large White pigs and Mashen pigs during development1,2. J Anim Sci 2017; 95:4239-4250. [DOI: 10.2527/jas2016.1297] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Affiliation(s)
- P. F. Gao
- Department of Animal Science and Veterinary Medicine, Shanxi Agricultural University, Taigu, 030801, P.R. China
| | - X. H. Guo
- Department of Animal Science and Veterinary Medicine, Shanxi Agricultural University, Taigu, 030801, P.R. China
| | - M. Du
- Department of Animal Science, Washington State University, Pullman 99164
| | - G. Q. Cao
- Department of Animal Science and Veterinary Medicine, Shanxi Agricultural University, Taigu, 030801, P.R. China
| | - Q. C. Yang
- Department of Animal Science and Veterinary Medicine, Shanxi Agricultural University, Taigu, 030801, P.R. China
| | - Z. D. Pu
- Department of Animal Science and Veterinary Medicine, Shanxi Agricultural University, Taigu, 030801, P.R. China
| | - Z. Y. Wang
- Department of Animal Science and Veterinary Medicine, Shanxi Agricultural University, Taigu, 030801, P.R. China
| | - Q. Zhang
- Department of Animal Science and Veterinary Medicine, Shanxi Agricultural University, Taigu, 030801, P.R. China
| | - M. Li
- Department of Animal Science and Veterinary Medicine, Shanxi Agricultural University, Taigu, 030801, P.R. China
| | - Y. S. Jin
- Department of Animal Science and Veterinary Medicine, Shanxi Agricultural University, Taigu, 030801, P.R. China
| | - X. J. Wang
- Shanxi Livestock and Poultry Breeding Station, Taiyuan 030000, P.R. China
| | - H. Liu
- Datong Pig Breeding Farm, Datong 037000, P.R. China
| | - B. G. Li
- Department of Animal Science and Veterinary Medicine, Shanxi Agricultural University, Taigu, 030801, P.R. China
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11
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Kasper DM, Moro A, Ristori E, Narayanan A, Hill-Teran G, Fleming E, Moreno-Mateos M, Vejnar CE, Zhang J, Lee D, Gu M, Gerstein M, Giraldez A, Nicoli S. MicroRNAs Establish Uniform Traits during the Architecture of Vertebrate Embryos. Dev Cell 2017; 40:552-565.e5. [PMID: 28350988 DOI: 10.1016/j.devcel.2017.02.021] [Citation(s) in RCA: 50] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2016] [Revised: 01/10/2017] [Accepted: 02/24/2017] [Indexed: 12/28/2022]
Abstract
Proper functioning of an organism requires cells and tissues to behave in uniform, well-organized ways. How this optimum of phenotypes is achieved during the development of vertebrates is unclear. Here, we carried out a multi-faceted and single-cell resolution screen of zebrafish embryonic blood vessels upon mutagenesis of single and multi-gene microRNA (miRNA) families. We found that embryos lacking particular miRNA-dependent signaling pathways develop a vascular trait similar to wild-type, but with a profound increase in phenotypic heterogeneity. Aberrant trait variance in miRNA mutant embryos uniquely sensitizes their vascular system to environmental perturbations. We discovered a previously unrecognized role for specific vertebrate miRNAs to protect tissue development against phenotypic variability. This discovery marks an important advance in our comprehension of how miRNAs function in the development of higher organisms.
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Affiliation(s)
- Dionna M Kasper
- Section of Cardiology, Department of Internal Medicine, Yale Cardiovascular Research Center, Yale University School of Medicine, New Haven, CT 06511, USA
| | - Albertomaria Moro
- Section of Cardiology, Department of Internal Medicine, Yale Cardiovascular Research Center, Yale University School of Medicine, New Haven, CT 06511, USA
| | - Emma Ristori
- Section of Cardiology, Department of Internal Medicine, Yale Cardiovascular Research Center, Yale University School of Medicine, New Haven, CT 06511, USA
| | - Anand Narayanan
- Section of Cardiology, Department of Internal Medicine, Yale Cardiovascular Research Center, Yale University School of Medicine, New Haven, CT 06511, USA
| | - Guillermina Hill-Teran
- Section of Cardiology, Department of Internal Medicine, Yale Cardiovascular Research Center, Yale University School of Medicine, New Haven, CT 06511, USA
| | - Elizabeth Fleming
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Miguel Moreno-Mateos
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Charles E Vejnar
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Jing Zhang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Donghoon Lee
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Mengting Gu
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Mark Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA; Department of Computer Science, Yale University, New Haven, CT 06520, USA
| | - Antonio Giraldez
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06510, USA; Yale Stem Cell Center, Yale University School of Medicine, New Haven, CT 06510, USA; Yale Cancer Center, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Stefania Nicoli
- Section of Cardiology, Department of Internal Medicine, Yale Cardiovascular Research Center, Yale University School of Medicine, New Haven, CT 06511, USA; Department of Pharmacology, Yale University School of Medicine, New Haven, CT 06510, USA.
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Abstract
MicroRNAs (miRNAs) are crucial post-transcriptional regulators of haematopoietic cell fate decisions. They act by negatively regulating the expression of key immune development genes, thus contributing important logic elements to the regulatory circuitry. Deletion studies have made it increasingly apparent that they confer robustness to immune cell development, especially under conditions of environmental stress such as infectious challenge and ageing. Aberrant expression of certain miRNAs can lead to pathological consequences, such as autoimmunity and haematological cancers. In this Review, we discuss the mechanisms by which several miRNAs influence immune development and buffer normal haematopoietic output, first at the level of haematopoietic stem cells, then in innate and adaptive immune cells. We then discuss the pathological consequences of dysregulation of these miRNAs.
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Wallaert A, Durinck K, Taghon T, Van Vlierberghe P, Speleman F. T-ALL and thymocytes: a message of noncoding RNAs. J Hematol Oncol 2017; 10:66. [PMID: 28270163 PMCID: PMC5341419 DOI: 10.1186/s13045-017-0432-0] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2017] [Accepted: 02/24/2017] [Indexed: 02/06/2023] Open
Abstract
In the last decade, the role for noncoding RNAs in disease was clearly established, starting with microRNAs and later expanded towards long noncoding RNAs. This was also the case for T cell acute lymphoblastic leukemia, which is a malignant blood disorder arising from oncogenic events during normal T cell development in the thymus. By studying the transcriptomic profile of protein-coding genes, several oncogenic events leading to T cell acute lymphoblastic leukemia (T-ALL) could be identified. In recent years, it became apparent that several of these oncogenes function via microRNAs and long noncoding RNAs. In this review, we give a detailed overview of the studies that describe the noncoding RNAome in T-ALL oncogenesis and normal T cell development.
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Affiliation(s)
- Annelynn Wallaert
- Center for Medical Genetics, Ghent University, Ghent, Belgium. .,Cancer Research Institute Ghent, Ghent, Belgium.
| | - Kaat Durinck
- Center for Medical Genetics, Ghent University, Ghent, Belgium.,Cancer Research Institute Ghent, Ghent, Belgium
| | - Tom Taghon
- Cancer Research Institute Ghent, Ghent, Belgium.,Department of Clinical Chemistry, Microbiology and Immunology, Ghent University, Ghent, Belgium
| | - Pieter Van Vlierberghe
- Center for Medical Genetics, Ghent University, Ghent, Belgium.,Cancer Research Institute Ghent, Ghent, Belgium
| | - Frank Speleman
- Center for Medical Genetics, Ghent University, Ghent, Belgium.,Cancer Research Institute Ghent, Ghent, Belgium
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14
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Jin HY, Oda H, Chen P, Yang C, Zhou X, Kang SG, Valentine E, Kefauver JM, Liao L, Zhang Y, Gonzalez-Martin A, Shepherd J, Morgan GJ, Mondala TS, Head SR, Kim PH, Xiao N, Fu G, Liu WH, Han J, Williamson JR, Xiao C. Differential Sensitivity of Target Genes to Translational Repression by miR-17~92. PLoS Genet 2017; 13:e1006623. [PMID: 28241004 PMCID: PMC5348049 DOI: 10.1371/journal.pgen.1006623] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2016] [Revised: 03/13/2017] [Accepted: 02/08/2017] [Indexed: 12/19/2022] Open
Abstract
MicroRNAs (miRNAs) are thought to exert their functions by modulating the expression of hundreds of target genes and each to a small degree, but it remains unclear how small changes in hundreds of target genes are translated into the specific function of a miRNA. Here, we conducted an integrated analysis of transcriptome and translatome of primary B cells from mutant mice expressing miR-17~92 at three different levels to address this issue. We found that target genes exhibit differential sensitivity to miRNA suppression and that only a small fraction of target genes are actually suppressed by a given concentration of miRNA under physiological conditions. Transgenic expression and deletion of the same miRNA gene regulate largely distinct sets of target genes. miR-17~92 controls target gene expression mainly through translational repression and 5’UTR plays an important role in regulating target gene sensitivity to miRNA suppression. These findings provide molecular insights into a model in which miRNAs exert their specific functions through a small number of key target genes. MicroRNAs (miRNAs) are small RNAs encoded by our genome. Each miRNA binds hundreds of target mRNAs and performs specific functions. It is thought that miRNAs exert their function by reducing the expression of all these target genes and each to a small degree. However, these target genes often have very diverse functions. It has been unclear how small changes in hundreds of target genes with diverse functions are translated into the specific function of a miRNA. Here we take advantage of recent technical advances to globally examine the mRNA and protein levels of 868 target genes regulated by miR-17~92, the first oncogenic miRNA, in mutant mice with transgenic overexpression or deletion of this miRNA gene. We show that miR-17~92 regulates target gene expression mainly at the protein level, with little effect on mRNA. Surprisingly, only a small fraction of target genes respond to miR-17~92 expression changes. Further studies show that the sensitivity of target genes to miR-17~92 is determined by a non-coding region of target mRNA. Our findings demonstrate that not every target gene is equal, and suggest that the function of a miRNA is mediated by a small number of key target genes.
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Affiliation(s)
- Hyun Yong Jin
- Department of Immunology and Microbial Science, The Scripps Research Institute, La Jolla, California, United States of America
- Kellogg School of Science and Technology, The Scripps Research Institute, La Jolla, California, United States of America
| | - Hiroyo Oda
- Department of Immunology and Microbial Science, The Scripps Research Institute, La Jolla, California, United States of America
| | - Pengda Chen
- State Key Laboratory of Cellular Stress Biology, Innovation Center for Cell Signaling Network, School of Life Sciences, Xiamen University, Xiamen, Fujian, China
| | - Chao Yang
- State Key Laboratory of Cellular Stress Biology, Innovation Center for Cell Signaling Network, School of Life Sciences, Xiamen University, Xiamen, Fujian, China
| | - Xiaojuan Zhou
- State Key Laboratory of Cellular Stress Biology, Innovation Center for Cell Signaling Network, School of Life Sciences, Xiamen University, Xiamen, Fujian, China
| | - Seung Goo Kang
- Division of Biomedical Convergence/Institute of Bioscience & Biotechnology, College of Biomedical Science, Kangwon National University, Chuncheon, Republic of Korea
| | - Elizabeth Valentine
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, California, United States of America
| | - Jennifer M. Kefauver
- Department of Immunology and Microbial Science, The Scripps Research Institute, La Jolla, California, United States of America
- Kellogg School of Science and Technology, The Scripps Research Institute, La Jolla, California, United States of America
| | - Lujian Liao
- Shanghai Key Laboratory of Regulatory Biology, Shanghai Key Laboratory of Brain Functional Genomics (Ministry of Education), School of Life Sciences, East China Normal University, Shanghai, China
| | - Yaoyang Zhang
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, China
| | - Alicia Gonzalez-Martin
- Department of Immunology and Microbial Science, The Scripps Research Institute, La Jolla, California, United States of America
| | - Jovan Shepherd
- Department of Immunology and Microbial Science, The Scripps Research Institute, La Jolla, California, United States of America
| | - Gareth J. Morgan
- Department of Molecular and Experimental Medicine, The Scripps Research Institute, La Jolla, California, United States of America
| | - Tony S. Mondala
- Next Generation Sequencing Core, The Scripps Research Institute, La Jolla, California, United States of America
| | - Steven R. Head
- Next Generation Sequencing Core, The Scripps Research Institute, La Jolla, California, United States of America
| | - Pyeung-Hyeun Kim
- Department of Molecular Bioscience/Institute of Bioscience & Biotechnology, College of Biomedical Science, Kangwon National University, Chuncheon, Republic of Korea
| | - Nengming Xiao
- State Key Laboratory of Cellular Stress Biology, Innovation Center for Cell Signaling Network, School of Life Sciences, Xiamen University, Xiamen, Fujian, China
| | - Guo Fu
- State Key Laboratory of Cellular Stress Biology, Innovation Center for Cell Signaling Network, School of Life Sciences, Xiamen University, Xiamen, Fujian, China
| | - Wen-Hsien Liu
- State Key Laboratory of Cellular Stress Biology, Innovation Center for Cell Signaling Network, School of Life Sciences, Xiamen University, Xiamen, Fujian, China
| | - Jiahuai Han
- State Key Laboratory of Cellular Stress Biology, Innovation Center for Cell Signaling Network, School of Life Sciences, Xiamen University, Xiamen, Fujian, China
| | - James R. Williamson
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, California, United States of America
| | - Changchun Xiao
- Department of Immunology and Microbial Science, The Scripps Research Institute, La Jolla, California, United States of America
- State Key Laboratory of Cellular Stress Biology, Innovation Center for Cell Signaling Network, School of Life Sciences, Xiamen University, Xiamen, Fujian, China
- * E-mail:
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16
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Chiang K, Shu J, Zempleni J, Cui J. Dietary MicroRNA Database (DMD): An Archive Database and Analytic Tool for Food-Borne microRNAs. PLoS One 2015; 10:e0128089. [PMID: 26030752 PMCID: PMC4451068 DOI: 10.1371/journal.pone.0128089] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2015] [Accepted: 04/23/2015] [Indexed: 11/21/2022] Open
Abstract
With the advent of high throughput technology, a huge amount of microRNA information has been added to the growing body of knowledge for non-coding RNAs. Here we present the Dietary MicroRNA Databases (DMD), the first repository for archiving and analyzing the published and novel microRNAs discovered in dietary resources. Currently there are fifteen types of dietary species, such as apple, grape, cow milk, and cow fat, included in the database originating from 9 plant and 5 animal species. Annotation for each entry, a mature microRNA indexed as DM0000*, covers information of the mature sequences, genome locations, hairpin structures of parental pre-microRNAs, cross-species sequence comparison, disease relevance, and the experimentally validated gene targets. Furthermore, a few functional analyses including target prediction, pathway enrichment and gene network construction have been integrated into the system, which enable users to generate functional insights through viewing the functional pathways and building protein-protein interaction networks associated with each microRNA. Another unique feature of DMD is that it provides a feature generator where a total of 411 descriptive attributes can be calculated for any given microRNAs based on their sequences and structures. DMD would be particularly useful for research groups studying microRNA regulation from a nutrition point of view. The database can be accessed at http://sbbi.unl.edu/dmd/.
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Affiliation(s)
- Kevin Chiang
- Department of Computer Science and Engineering, University of Nebraska-Lincoln, Lincoln, NE, United States of America
| | - Jiang Shu
- Department of Computer Science and Engineering, University of Nebraska-Lincoln, Lincoln, NE, United States of America
| | - Janos Zempleni
- Department of Nutrition and Health Sciences, University of Nebraska-Lincoln, Lincoln, NE, United States of America
| | - Juan Cui
- Department of Computer Science and Engineering, University of Nebraska-Lincoln, Lincoln, NE, United States of America
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