Dynamic Expression of Id3 Defines the Stepwise Differentiation of Tissue-Resident 2 Regulatory T Cells 3 Jenna M
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Single-Cell Rnaseq Reveals Seven Classes of Colonic Sensory Neuron
Gut Online First, published on February 26, 2018 as 10.1136/gutjnl-2017-315631 Neurogastroenterology ORIGINAL ARTICLE Gut: first published as 10.1136/gutjnl-2017-315631 on 26 February 2018. Downloaded from Single-cell RNAseq reveals seven classes of colonic sensory neuron James R F Hockley,1,2 Toni S Taylor,1 Gerard Callejo,1 Anna L Wilbrey,2 Alex Gutteridge,2 Karsten Bach,1 Wendy J Winchester,2 David C Bulmer,1 Gordon McMurray,2 Ewan St John Smith1 ► Additional material is ABSTRact pathways to the central nervous system (CNS).1 In published online only. To view Objective Integration of nutritional, microbial and the colorectum, sensory innervation is organised please visit the journal online (http:// dx. doi. org/ 10. 1136/ inflammatory events along the gut-brain axis can alter into two main pathways: thoracolumbar (TL) spinal gutjnl- 2017- 315631). bowel physiology and organism behaviour. Colonic afferents projecting via the lumbar splanchnic sensory neurons activate reflex pathways and give nerve (LSN) and lumbosacral (LS) spinal afferents 1Department of Pharmacology, University of Cambridge, rise to conscious sensation, but the diversity and projecting via the pelvic nerve (PN) that are respon- Cambridge, UK division of function within these neurons is poorly sible for transducing conscious sensations of full- 2Neuroscience and Pain understood. The identification of signalling pathways ness, discomfort, urgency and pain, in addition to Research Unit, Pfizer, contributing to visceral sensation is constrained by a reflex actions.2 Cambridge, UK paucity of molecular markers. Here we address this by Visceral sensory afferents act to maintain many comprehensive transcriptomic profiling and unsupervised aspects of GI physiology, such as continence and Correspondence to James R F Hockley, Department clustering of individual mouse colonic sensory neurons. -
F2RL2 Antibody Cat
F2RL2 Antibody Cat. No.: 56-323 F2RL2 Antibody F2RL2 Antibody immunohistochemistry analysis in formalin fixed and paraffin embedded human heart tissue followed by peroxidase conjugation of the secondary antibody and DAB staining. Specifications HOST SPECIES: Rabbit SPECIES REACTIVITY: Human This F2RL2 antibody is generated from rabbits immunized with a KLH conjugated IMMUNOGEN: synthetic peptide between 21-50 amino acids from the N-terminal region of human F2RL2. TESTED APPLICATIONS: IHC-P, WB For WB starting dilution is: 1:1000 APPLICATIONS: For IHC-P starting dilution is: 1:10~50 PREDICTED MOLECULAR 43 kDa WEIGHT: September 25, 2021 1 https://www.prosci-inc.com/f2rl2-antibody-56-323.html Properties This antibody is purified through a protein A column, followed by peptide affinity PURIFICATION: purification. CLONALITY: Polyclonal ISOTYPE: Rabbit Ig CONJUGATE: Unconjugated PHYSICAL STATE: Liquid BUFFER: Supplied in PBS with 0.09% (W/V) sodium azide. CONCENTRATION: batch dependent Store at 4˚C for three months and -20˚C, stable for up to one year. As with all antibodies STORAGE CONDITIONS: care should be taken to avoid repeated freeze thaw cycles. Antibodies should not be exposed to prolonged high temperatures. Additional Info OFFICIAL SYMBOL: F2RL2 Proteinase-activated receptor 3, PAR-3, Coagulation factor II receptor-like 2, Thrombin ALTERNATE NAMES: receptor-like 2, F2RL2, PAR3 ACCESSION NO.: O00254 GENE ID: 2151 USER NOTE: Optimal dilutions for each application to be determined by the researcher. Background and References Coagulation factor II (thrombin) receptor-like 2 (F2RL2) is a member of the large family of 7-transmembrane-region receptors that couple to guanosine-nucleotide-binding proteins. -
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
4-6 Weeks Old Female C57BL/6 Mice Obtained from Jackson Labs Were Used for Cell Isolation
Methods Mice: 4-6 weeks old female C57BL/6 mice obtained from Jackson labs were used for cell isolation. Female Foxp3-IRES-GFP reporter mice (1), backcrossed to B6/C57 background for 10 generations, were used for the isolation of naïve CD4 and naïve CD8 cells for the RNAseq experiments. The mice were housed in pathogen-free animal facility in the La Jolla Institute for Allergy and Immunology and were used according to protocols approved by the Institutional Animal Care and use Committee. Preparation of cells: Subsets of thymocytes were isolated by cell sorting as previously described (2), after cell surface staining using CD4 (GK1.5), CD8 (53-6.7), CD3ε (145- 2C11), CD24 (M1/69) (all from Biolegend). DP cells: CD4+CD8 int/hi; CD4 SP cells: CD4CD3 hi, CD24 int/lo; CD8 SP cells: CD8 int/hi CD4 CD3 hi, CD24 int/lo (Fig S2). Peripheral subsets were isolated after pooling spleen and lymph nodes. T cells were enriched by negative isolation using Dynabeads (Dynabeads untouched mouse T cells, 11413D, Invitrogen). After surface staining for CD4 (GK1.5), CD8 (53-6.7), CD62L (MEL-14), CD25 (PC61) and CD44 (IM7), naïve CD4+CD62L hiCD25-CD44lo and naïve CD8+CD62L hiCD25-CD44lo were obtained by sorting (BD FACS Aria). Additionally, for the RNAseq experiments, CD4 and CD8 naïve cells were isolated by sorting T cells from the Foxp3- IRES-GFP mice: CD4+CD62LhiCD25–CD44lo GFP(FOXP3)– and CD8+CD62LhiCD25– CD44lo GFP(FOXP3)– (antibodies were from Biolegend). In some cases, naïve CD4 cells were cultured in vitro under Th1 or Th2 polarizing conditions (3, 4). -
Monitoring Nociception by Analyzing Gene Expression Changes in the Central Nervous System of Mice
Zurich Open Repository and Archive University of Zurich Main Library Strickhofstrasse 39 CH-8057 Zurich www.zora.uzh.ch Year: 2010 Monitoring nociception by analyzing gene expression changes in the central nervous system of mice Asner, I N Posted at the Zurich Open Repository and Archive, University of Zurich ZORA URL: https://doi.org/10.5167/uzh-46678 Dissertation Originally published at: Asner, I N. Monitoring nociception by analyzing gene expression changes in the central nervous system of mice. 2010, University of Zurich, Vetsuisse Faculty. Monitoring Nociception by Analyzing Gene Expression Changes in the Central Nervous System of Mice Dissertation zur Erlangung der naturwissenschaftlichen Doktorwürde (Dr. sc. nat) vorgelegt der Mathematisch-naturwissenschaftlichen Fakultät der Universität Zürich von Igor Asner von St. Cergue VD Promotionskomitee Prof. Dr. Peter Sonderegger Prof. Dr. Kurt Bürki Prof. Dr. Hanns Ulrich Zeilhofer Dr. Paolo Cinelli (Leitung der Dissertation) Zürich, 2010 Table of contents Table of content Curriculum vitae 6 Publications 9 Summary 11 Zusammenfassung 14 1. Introduction 17 1.1. Pain and nociception 17 1.1.1 Nociceptive neurons and Mechanoceptors 18 1.1.2 Activation of the nociceptive neurons at the periphery 21 1.1.2.1 Response to noxious heat 22 1.1.2.2 Response to noxious cold 23 1.1.2.3 Response to mechanical stress 24 1.1.3 Nociceptive message processing in the Spinal Cord 25 1.1.3.1 The lamina I and the ascending pathways 25 1.1.3.2 The lamina II and the descending pathways 26 1.1.4 Pain processing and integration in the brain 27 1.1.4.1 The Pain Matrix 27 1.1.4.2 Activation of the descending pathways 29 1.1.5 Inflammatory Pain 31 1.2. -
Integrative Differential Expression and Gene Set Enrichment Analysis Using Summary Statistics for Scrna-Seq Studies
ARTICLE https://doi.org/10.1038/s41467-020-15298-6 OPEN Integrative differential expression and gene set enrichment analysis using summary statistics for scRNA-seq studies ✉ Ying Ma 1,7, Shiquan Sun 1,7, Xuequn Shang2, Evan T. Keller 3, Mengjie Chen 4,5 & Xiang Zhou 1,6 Differential expression (DE) analysis and gene set enrichment (GSE) analysis are commonly applied in single cell RNA sequencing (scRNA-seq) studies. Here, we develop an integrative 1234567890():,; and scalable computational method, iDEA, to perform joint DE and GSE analysis through a hierarchical Bayesian framework. By integrating DE and GSE analyses, iDEA can improve the power and consistency of DE analysis and the accuracy of GSE analysis. Importantly, iDEA uses only DE summary statistics as input, enabling effective data modeling through com- plementing and pairing with various existing DE methods. We illustrate the benefits of iDEA with extensive simulations. We also apply iDEA to analyze three scRNA-seq data sets, where iDEA achieves up to five-fold power gain over existing GSE methods and up to 64% power gain over existing DE methods. The power gain brought by iDEA allows us to identify many pathways that would not be identified by existing approaches in these data. 1 Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA. 2 School of Computer Science, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, P.R. China. 3 Department of Urology, University of Michigan, Ann Arbor, MI 48109, USA. 4 Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA. 5 Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL 60637, USA. -
5-Aza-29-Deoxycytidine Leads to Reduced Embryo Implantation and Reduced Expression of DNA Methyltransferases and Essential Endometrial Genes
5-Aza-29-deoxycytidine Leads to Reduced Embryo Implantation and Reduced Expression of DNA Methyltransferases and Essential Endometrial Genes Yu-Bin Ding, Chun-Lan Long, Xue-Qing Liu, Xue-Mei Chen, Liang-Rui Guo, Yin-Yin Xia, Jun-Lin He*, Ying- Xiong Wang* Department of Reproductive Biology, Chongqing Medical University, Chongqing, People’s Republic of China Abstract Background: The DNA demethylating agent 5-aza-29-deoxycytidine (5-aza-CdR) incorporates into DNA and decreases DNA methylation, sparking interest in its use as a potential therapeutic agent. We aimed to determine the effects of maternal 5- aza-CdR treatment on embryo implantation in the mouse and to evaluate whether these effects are associated with decreased levels of DNA methyltransferases (Dnmts) and three genes (estrogen receptor a [Esr1], progesterone receptor [Pgr], and homeobox A10 [Hoxa10]) that are vital for control of endometrial changes during implantation. Methods and Principal Findings: Mice treated with 5-aza-CdR had a dose-dependent decrease in number of implantation sites, with defected endometrial decidualization and stromal cell proliferation. Western blot analysis on pseudo-pregnant day 3 (PD3) showed that 0.1 mg/kg 5-aza-CdR significantly repressed Dnmt3a protein level, and 0.5 mg/kg 5-aza-CdR significantly repressed Dnmt1, Dnmt3a, and Dnmt3b protein levels in the endometrium. On PD5, mice showed significantly decreased Dnmt3a protein level with 0.1 mg/kg 5-aza-CdR, and significantly decreased Dnmt1 and Dnmt3a with 0.5 mg/kg 5-aza-CdR. Immunohistochemical staining showed that 5-aza-CdR repressed DNMT expression in a cell type–specific fashion within the uterus, including decreased expression of Dnmt1 in luminal and/or glandular epithelium and of Dnmt3a and Dnmt3b in stroma. -
A RUNX3 Enhancer Polymorphism Associated with Ankylosing
bioRxiv preprint doi: https://doi.org/10.1101/832840; this version posted November 6, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. A RUNX3 enhancer polymorphism associated with ankylosing spondylitis influences recruitment of Interferon Regulatory Factor 5 and factors of the Nucleosome Remodelling Deacetylase Complex in CD8+ T-cells Matteo Vecellio*1,2,3, Adrian Cortes4,5, Sarah Bonham6, Carlo Selmi7, Julian C Knight5, Roman Fischer6, Matthew A Brown8, B Paul Wordsworth1,2,3 $ and Carla J Cohen1,2,3 $. $ these authors contributed equally to this work Author affiliations 1Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK 2 National Institute for Health Research Oxford Musculoskeletal Biomedical Research Unit, Oxford, UK 3 National Institute for Health Research Oxford Comprehensive Biomedical Research Centre, Botnar Research Centre, Nuffield Orthopaedic Centre, Oxford, UK 4 Nuffield Department of Clinical Neurosciences, Division of Clinical Neurology, John Radcliffe Hospital, University of Oxford, Oxford, UK 5 Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK 6 Discovery Proteomics Facility, Target Discovery Institute, University of Oxford, Oxford, UK 7 Division of Rheumatology and Clinical Immunology, Humanitas Research Hospital, Rozzano, Milan, Italy 8 Guy’s, St Thomas’, King’s National Institute for Health Research Comprehensive Biomedical -
Tgfβ-Regulated Gene Expression by Smads and Sp1/KLF-Like Transcription Factors in Cancer VOLKER ELLENRIEDER
ANTICANCER RESEARCH 28 : 1531-1540 (2008) Review TGFβ-regulated Gene Expression by Smads and Sp1/KLF-like Transcription Factors in Cancer VOLKER ELLENRIEDER Signal Transduction Laboratory, Internal Medicine, Department of Gastroenterology and Endocrinology, University of Marburg, Marburg, Germany Abstract. Transforming growth factor beta (TGF β) controls complex induces the canonical Smad signaling molecules which vital cellular functions through its ability to regulate gene then translocate into the nucleus to regulate transcription (2). The expression. TGFβ binding to its transmembrane receptor cellular response to TGF β can be extremely variable depending kinases initiates distinct intracellular signalling cascades on the cell type and the activation status of a cell at a given time. including the Smad signalling and transcription factors and also For instance, TGF β induces growth arrest and apoptosis in Smad-independent pathways. In normal epithelial cells, TGF β healthy epithelial cells, whereas it can also promote tumor stimulation induces a cytostatic program which includes the progression through stimulation of cell proliferation and the transcriptional repression of the c-Myc oncogene and the later induction of an epithelial-to-mesenchymal transition of tumor induction of the cell cycle inhibitors p15 INK4b and p21 Cip1 . cells (1, 3). In the last decade it has become clear that both the During carcinogenesis, however, many tumor cells lose their tumor suppressing and the tumor promoting functions of TGF β ability to respond to TGF β with growth inhibition, and instead, are primarily regulated on the level of gene expression through activate genes involved in cell proliferation, invasion and Smad-dependent and -independent mechanisms (1, 2, 4). -
Immunogenic Dendritic Cell Generation from Pluripotent Stem Cells by Ectopic Expression of Runx3
Immunogenic Dendritic Cell Generation from Pluripotent Stem Cells by Ectopic Expression of Runx3 This information is current as Erika Takacs, Pal Boto, Emilia Simo, Tamas I. Csuth, of September 25, 2021. Bianka M. Toth, Hadas Raveh-Amit, Attila Pap, Elek G. Kovács, Julianna Kobolak, Szilvia Benkö, Andras Dinnyes and Istvan Szatmari J Immunol published online 16 November 2016 http://www.jimmunol.org/content/early/2016/11/15/jimmun Downloaded from ol.1600034 Supplementary http://www.jimmunol.org/content/suppl/2016/11/15/jimmunol.160003 Material 4.DCSupplemental http://www.jimmunol.org/ Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision • No Triage! Every submission reviewed by practicing scientists by guest on September 25, 2021 • Fast Publication! 4 weeks from acceptance to publication *average Subscription Information about subscribing to The Journal of Immunology is online at: http://jimmunol.org/subscription Permissions Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Email Alerts Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2016 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. Published November 16, 2016, doi:10.4049/jimmunol.1600034 The Journal of Immunology Immunogenic Dendritic Cell Generation from Pluripotent Stem Cells by Ectopic Expression of Runx3 Erika Takacs,*,1 Pal Boto,*,1 Emilia Simo,* Tamas I. Csuth,* Bianka M. -
G Protein-Coupled Receptors
S.P.H. Alexander et al. The Concise Guide to PHARMACOLOGY 2015/16: G protein-coupled receptors. British Journal of Pharmacology (2015) 172, 5744–5869 THE CONCISE GUIDE TO PHARMACOLOGY 2015/16: G protein-coupled receptors Stephen PH Alexander1, Anthony P Davenport2, Eamonn Kelly3, Neil Marrion3, John A Peters4, Helen E Benson5, Elena Faccenda5, Adam J Pawson5, Joanna L Sharman5, Christopher Southan5, Jamie A Davies5 and CGTP Collaborators 1School of Biomedical Sciences, University of Nottingham Medical School, Nottingham, NG7 2UH, UK, 2Clinical Pharmacology Unit, University of Cambridge, Cambridge, CB2 0QQ, UK, 3School of Physiology and Pharmacology, University of Bristol, Bristol, BS8 1TD, UK, 4Neuroscience Division, Medical Education Institute, Ninewells Hospital and Medical School, University of Dundee, Dundee, DD1 9SY, UK, 5Centre for Integrative Physiology, University of Edinburgh, Edinburgh, EH8 9XD, UK Abstract The Concise Guide to PHARMACOLOGY 2015/16 provides concise overviews of the key properties of over 1750 human drug targets with their pharmacology, plus links to an open access knowledgebase of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. The full contents can be found at http://onlinelibrary.wiley.com/doi/ 10.1111/bph.13348/full. G protein-coupled receptors are one of the eight major pharmacological targets into which the Guide is divided, with the others being: ligand-gated ion channels, voltage-gated ion channels, other ion channels, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. -
Multi-Functionality of Proteins Involved in GPCR and G Protein Signaling: Making Sense of Structure–Function Continuum with In
Cellular and Molecular Life Sciences (2019) 76:4461–4492 https://doi.org/10.1007/s00018-019-03276-1 Cellular andMolecular Life Sciences REVIEW Multi‑functionality of proteins involved in GPCR and G protein signaling: making sense of structure–function continuum with intrinsic disorder‑based proteoforms Alexander V. Fonin1 · April L. Darling2 · Irina M. Kuznetsova1 · Konstantin K. Turoverov1,3 · Vladimir N. Uversky2,4 Received: 5 August 2019 / Revised: 5 August 2019 / Accepted: 12 August 2019 / Published online: 19 August 2019 © Springer Nature Switzerland AG 2019 Abstract GPCR–G protein signaling system recognizes a multitude of extracellular ligands and triggers a variety of intracellular signal- ing cascades in response. In humans, this system includes more than 800 various GPCRs and a large set of heterotrimeric G proteins. Complexity of this system goes far beyond a multitude of pair-wise ligand–GPCR and GPCR–G protein interactions. In fact, one GPCR can recognize more than one extracellular signal and interact with more than one G protein. Furthermore, one ligand can activate more than one GPCR, and multiple GPCRs can couple to the same G protein. This defnes an intricate multifunctionality of this important signaling system. Here, we show that the multifunctionality of GPCR–G protein system represents an illustrative example of the protein structure–function continuum, where structures of the involved proteins represent a complex mosaic of diferently folded regions (foldons, non-foldons, unfoldons, semi-foldons, and inducible foldons). The functionality of resulting highly dynamic conformational ensembles is fne-tuned by various post-translational modifcations and alternative splicing, and such ensembles can undergo dramatic changes at interaction with their specifc partners.