RNA-Seq Analysis of Lgr6+ Stem Cells and Identification of an Lgr6 Isoform
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Applying Screening Techniques to Two Orphan Gpcrs
Universidade de Lisboa Faculdade de Farmácia Deorphanization of receptors: Applying screening techniques to two orphan GPCRs Ana Catarina Rufas da Silva Santos Mestrado Integrado em Ciências Farmacêuticas 2019 Universidade de Lisboa Faculdade de Farmácia Deorphanization of receptors: Applying screening techniques to two orphan GPCRs Ana Catarina Rufas da Silva Santos Monografia de Mestrado Integrado em Ciências Farmacêuticas apresentada à Universidade de Lisboa através da Faculdade de Farmácia Orientadora: Ghazl Al Hamwi, PhD Student Co-Orientadora: Professora Doutora Elsa Maria Ribeiro dos Santos Anes, Professora Associada com Agregação em Microbiologia 2019 Abstract G-Protein Coupled Receptors represent one of the largest families of cellular receptors discovered and one of the main sources of attractive drug targets. In contrast, it also has a large number of understudied or orphan receptors. Pharmacological assays such as β-Arrestin recruitment assays, are one of the possible approaches for deorphanization of receptors. In this work, I applied the assay system previously mentioned to screen compounds in two orphan receptors, GRP37 and MRGPRX3. GPR37 has been primarily associated with a form of early onset Parkinsonism due to its’ expression patterns, and physiological role as substrate to ubiquitin E3, parkin. Although extensive literature regarding this receptor is available, the identification of a universally recognized ligand has not yet been possible. Two compounds were proposed as ligands, but both were met with controversy. These receptor association with Autosomal Recessive Juvenile Parkinson positions it as a very attractive drug target, and as such its’ deorphanization is a prime objective for investigators in this area. Regarding MRGPRX3 information is much scarcer. -
Mechanical Forces Induce an Asthma Gene Signature in Healthy Airway Epithelial Cells Ayşe Kılıç1,10, Asher Ameli1,2,10, Jin-Ah Park3,10, Alvin T
www.nature.com/scientificreports OPEN Mechanical forces induce an asthma gene signature in healthy airway epithelial cells Ayşe Kılıç1,10, Asher Ameli1,2,10, Jin-Ah Park3,10, Alvin T. Kho4, Kelan Tantisira1, Marc Santolini 1,5, Feixiong Cheng6,7,8, Jennifer A. Mitchel3, Maureen McGill3, Michael J. O’Sullivan3, Margherita De Marzio1,3, Amitabh Sharma1, Scott H. Randell9, Jefrey M. Drazen3, Jefrey J. Fredberg3 & Scott T. Weiss1,3* Bronchospasm compresses the bronchial epithelium, and this compressive stress has been implicated in asthma pathogenesis. However, the molecular mechanisms by which this compressive stress alters pathways relevant to disease are not well understood. Using air-liquid interface cultures of primary human bronchial epithelial cells derived from non-asthmatic donors and asthmatic donors, we applied a compressive stress and then used a network approach to map resulting changes in the molecular interactome. In cells from non-asthmatic donors, compression by itself was sufcient to induce infammatory, late repair, and fbrotic pathways. Remarkably, this molecular profle of non-asthmatic cells after compression recapitulated the profle of asthmatic cells before compression. Together, these results show that even in the absence of any infammatory stimulus, mechanical compression alone is sufcient to induce an asthma-like molecular signature. Bronchial epithelial cells (BECs) form a physical barrier that protects pulmonary airways from inhaled irritants and invading pathogens1,2. Moreover, environmental stimuli such as allergens, pollutants and viruses can induce constriction of the airways3 and thereby expose the bronchial epithelium to compressive mechanical stress. In BECs, this compressive stress induces structural, biophysical, as well as molecular changes4,5, that interact with nearby mesenchyme6 to cause epithelial layer unjamming1, shedding of soluble factors, production of matrix proteins, and activation matrix modifying enzymes, which then act to coordinate infammatory and remodeling processes4,7–10. -
Functional and Molecular Heterogeneity Of
ARTICLE https://doi.org/10.1038/s41467-020-15716-9 OPEN Functional and molecular heterogeneity of D2R neurons along dorsal ventral axis in the striatum ✉ Emma Puighermanal1,2 , Laia Castell1, Anna Esteve-Codina 3, Su Melser4,5, Konstantin Kaganovsky 6, Charleine Zussy1, Jihane Boubaker-Vitre1, Marta Gut3,7, Stephanie Rialle1, Christoph Kellendonk8,9, Elisenda Sanz2, Albert Quintana 2, Giovanni Marsicano4,5, Miquel Martin1, Marcelo Rubinstein10,11,12, ✉ Jean-Antoine Girault 13,14,15, Jun B. Ding6 & Emmanuel Valjent 1 1234567890():,; Action control is a key brain function determining the survival of animals in their environ- ment. In mammals, neurons expressing dopamine D2 receptors (D2R) in the dorsal striatum (DS) and the nucleus accumbens (Acb) jointly but differentially contribute to the fine reg- ulation of movement. However, their region-specific molecular features are presently unknown. By combining RNAseq of striatal D2R neurons and histological analyses, we identified hundreds of novel region-specific molecular markers, which may serve as tools to target selective subpopulations. As a proof of concept, we characterized the molecular identity of a subcircuit defined by WFS1 neurons and evaluated multiple behavioral tasks after its temporally-controlled deletion of D2R. Consequently, conditional D2R knockout mice displayed a significant reduction in digging behavior and an exacerbated hyperlocomotor response to amphetamine. Thus, targeted molecular analyses reveal an unforeseen hetero- geneity in D2R-expressing striatal neuronal populations, underlying specific D2R’s functional features in the control of specific motor behaviors. 1 IGF, CNRS, INSERM, Université Montpellier, Montpellier, France. 2 Neuroscience Institute, Department of Cell Biology, Physiology and Immunology, Autonomous University of Barcelona, Bellaterra, Spain. -
CD157 and CD200 at the Crossroads of Endothelial Remodeling and Immune Regulation
Editorial Commentary Page 1 of 7 CD157 and CD200 at the crossroads of endothelial remodeling and immune regulation Masuko Katoh1, Masaru Katoh2 1M & M PrecMed, Tokyo, Japan; 2Department of Omics Network, National Cancer Center, Tokyo, Japan Correspondence to: Masaru Katoh. Department of Omics Network, National Cancer Center, 5-1-1 Tsukiji, Chuo-ward, Tokyo 104-0045, Japan. Email: [email protected]. Comment on: Wakabayashi T, Naito H, Suehiro JI, et al. CD157 Marks Tissue-Resident Endothelial Stem Cells with Homeostatic and Regenerative Properties. Cell Stem Cell 2018;22:384-97.e6. Received: 11 March 2019; Accepted: 08 April 2019; Published: 19 April 2019. doi: 10.21037/sci.2019.04.01 View this article at: http://dx.doi.org/10.21037/sci.2019.04.01 The endothelial cells that coat the inner wall of blood cells formed more CD31 (PECAM1)-positive colonies than vessels are essential for the maintenance of the vascular CD200 single-positive or CD157/CD200 double-negative network, metabolic homeostasis and stem cell populations liver endothelial cells in vitro. The expression levels of Atf3, in tissue or tumor microenvironments (1-3). Angiogenesis Fosl2, Myc and Sox7 were significantly upregulated in the is defined as neovascular formation through the sprouting CD157/CD200 double-positive cells compared with the and proliferation of endothelial cells from preexisting CD200 single-positive or CD157/CD200 double-negative blood vessels. VEGF (VEGFA) and FGFs that transduce cells; however, the functions of these transcription factors signals through VEGFR2 and FGFRs, respectively, are in CD157/CD200 double-positive endothelial cells remain representative proangiogenic factors (4,5). -
Genome-Wide Prediction of Small Molecule Binding to Remote
bioRxiv preprint doi: https://doi.org/10.1101/2020.08.04.236729; this version posted August 5, 2020. 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. 1 Genome-wide Prediction of Small Molecule Binding 2 to Remote Orphan Proteins Using Distilled Sequence 3 Alignment Embedding 1 2 3 4 4 Tian Cai , Hansaim Lim , Kyra Alyssa Abbu , Yue Qiu , 5,6 1,2,3,4,7,* 5 Ruth Nussinov , and Lei Xie 1 6 Ph.D. Program in Computer Science, The Graduate Center, The City University of New York, New York, 10016, USA 2 7 Ph.D. Program in Biochemistry, The Graduate Center, The City University of New York, New York, 10016, USA 3 8 Department of Computer Science, Hunter College, The City University of New York, New York, 10065, USA 4 9 Ph.D. Program in Biology, The Graduate Center, The City University of New York, New York, 10016, USA 5 10 Computational Structural Biology Section, Basic Science Program, Frederick National Laboratory for Cancer Research, 11 Frederick, MD 21702, USA 6 12 Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel 13 Aviv, Israel 7 14 Helen and Robert Appel Alzheimer’s Disease Research Institute, Feil Family Brain & Mind Research Institute, Weill 15 Cornell Medicine, Cornell University, New York, 10021, USA * 16 [email protected] 17 July 27, 2020 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.08.04.236729; this version posted August 5, 2020. -
Edinburgh Research Explorer
Edinburgh Research Explorer International Union of Basic and Clinical Pharmacology. LXXXVIII. G protein-coupled receptor list Citation for published version: Davenport, AP, Alexander, SPH, Sharman, JL, Pawson, AJ, Benson, HE, Monaghan, AE, Liew, WC, Mpamhanga, CP, Bonner, TI, Neubig, RR, Pin, JP, Spedding, M & Harmar, AJ 2013, 'International Union of Basic and Clinical Pharmacology. LXXXVIII. G protein-coupled receptor list: recommendations for new pairings with cognate ligands', Pharmacological reviews, vol. 65, no. 3, pp. 967-86. https://doi.org/10.1124/pr.112.007179 Digital Object Identifier (DOI): 10.1124/pr.112.007179 Link: Link to publication record in Edinburgh Research Explorer Document Version: Publisher's PDF, also known as Version of record Published In: Pharmacological reviews Publisher Rights Statement: U.S. Government work not protected by U.S. copyright General rights Copyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s) and / or other copyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated with these rights. Take down policy The University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorer content complies with UK legislation. If you believe that the public display of this file breaches copyright please contact [email protected] providing details, and we will remove access to the work immediately and investigate your claim. Download date: 02. Oct. 2021 1521-0081/65/3/967–986$25.00 http://dx.doi.org/10.1124/pr.112.007179 PHARMACOLOGICAL REVIEWS Pharmacol Rev 65:967–986, July 2013 U.S. -
Lgr5 Homologues Associate with Wnt Receptors and Mediate R-Spondin Signalling
ARTICLE doi:10.1038/nature10337 Lgr5 homologues associate with Wnt receptors and mediate R-spondin signalling Wim de Lau1*, Nick Barker1{*, Teck Y. Low2, Bon-Kyoung Koo1, Vivian S. W. Li1, Hans Teunissen1, Pekka Kujala3, Andrea Haegebarth1{, Peter J. Peters3, Marc van de Wetering1, Daniel E. Stange1, Johan E. van Es1, Daniele Guardavaccaro1, Richard B. M. Schasfoort4, Yasuaki Mohri5, Katsuhiko Nishimori5, Shabaz Mohammed2, Albert J. R. Heck2 & Hans Clevers1 The adult stem cell marker Lgr5 and its relative Lgr4 are often co-expressed in Wnt-driven proliferative compartments. We find that conditional deletion of both genes in the mouse gut impairs Wnt target gene expression and results in the rapid demise of intestinal crypts, thus phenocopying Wnt pathway inhibition. Mass spectrometry demonstrates that Lgr4 and Lgr5 associate with the Frizzled/Lrp Wnt receptor complex. Each of the four R-spondins, secreted Wnt pathway agonists, can bind to Lgr4, -5 and -6. In HEK293 cells, RSPO1 enhances canonical WNT signals initiated by WNT3A. Removal of LGR4 does not affect WNT3A signalling, but abrogates the RSPO1-mediated signal enhancement, a phenomenon rescued by re-expression of LGR4, -5 or -6. Genetic deletion of Lgr4/5 in mouse intestinal crypt cultures phenocopies withdrawal of Rspo1 and can be rescued by Wnt pathway activation. Lgr5 homologues are facultative Wnt receptor components that mediate Wnt signal enhancement by soluble R-spondin proteins. These results will guide future studies towards the application of R-spondins for regenerative purposes of tissues expressing Lgr5 homologues. The genes Lgr4, Lgr5 and Lgr6 encode orphan 7-transmembrane 4–5 post-induction onwards. -
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. -
Investigation of Candidate Genes and Mechanisms Underlying Obesity
Prashanth et al. BMC Endocrine Disorders (2021) 21:80 https://doi.org/10.1186/s12902-021-00718-5 RESEARCH ARTICLE Open Access Investigation of candidate genes and mechanisms underlying obesity associated type 2 diabetes mellitus using bioinformatics analysis and screening of small drug molecules G. Prashanth1 , Basavaraj Vastrad2 , Anandkumar Tengli3 , Chanabasayya Vastrad4* and Iranna Kotturshetti5 Abstract Background: Obesity associated type 2 diabetes mellitus is a metabolic disorder ; however, the etiology of obesity associated type 2 diabetes mellitus remains largely unknown. There is an urgent need to further broaden the understanding of the molecular mechanism associated in obesity associated type 2 diabetes mellitus. Methods: To screen the differentially expressed genes (DEGs) that might play essential roles in obesity associated type 2 diabetes mellitus, the publicly available expression profiling by high throughput sequencing data (GSE143319) was downloaded and screened for DEGs. Then, Gene Ontology (GO) and REACTOME pathway enrichment analysis were performed. The protein - protein interaction network, miRNA - target genes regulatory network and TF-target gene regulatory network were constructed and analyzed for identification of hub and target genes. The hub genes were validated by receiver operating characteristic (ROC) curve analysis and RT- PCR analysis. Finally, a molecular docking study was performed on over expressed proteins to predict the target small drug molecules. Results: A total of 820 DEGs were identified between -
See Also Figure 1
Figure S1. Box-and-whisker plots depicting the range of expression values per developmental stage, with DESeq normalization (A) or quantile normalization (B). See also Figure 1. Figure S2. Lv-Setmar expression has low variation over developmental time. A. A plot of Lv-setmar versus Lv-ubiquitin expression over time demonstrates that Lv-setmar exhibits less temporal variation than Lv-ubiquitin. B. A representative gel showing Lv-setmar qPCR products amplified from cDNAs representing each sequenced stage in this study, demonstrating comparable product levels and an absence of spurious amplification products. See also Figure 1E. Figure S3. LvEDGE database. Screen shots showing the home page (A), the search window (B), an example search with a temporal expression plot (C), and the numerical data reflected in the plot (D) for the LvEDGE public database, which hosts the data described herein. stage 1 2 3 4 5 6 7 8 9 10 11 Category Subcategory 2-cell 60-cell EB HB TVP MB EG MG LG EP LP meiotic Cell Division Cytokinesis Mitosis checkpoint cell division recombination cell cycle stem cell left-right cell left-right Development maintenance asymmetry morphogenesis asymmetry regulation of multicellular organismal process cell soma cell soma Gene Expression chromatin SWI/SNF Control Chromatin modification chromatin binding complex methylated histone Binding negative sequence- sequence- sequence- regulation of sequence- specific DNA specific DNA specific DNA transcription specific DNA sequence-specific DNA binding binding binding binding factor activity -
Supplementary Table S5. Differentially Expressed Gene Lists of PD-1High CD39+ CD8 Tils According to 4-1BB Expression Compared to PD-1+ CD39- CD8 Tils
BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) J Immunother Cancer Supplementary Table S5. Differentially expressed gene lists of PD-1high CD39+ CD8 TILs according to 4-1BB expression compared to PD-1+ CD39- CD8 TILs Up- or down- regulated genes in Up- or down- regulated genes Up- or down- regulated genes only PD-1high CD39+ CD8 TILs only in 4-1BBneg PD-1high CD39+ in 4-1BBpos PD-1high CD39+ CD8 compared to PD-1+ CD39- CD8 CD8 TILs compared to PD-1+ TILs compared to PD-1+ CD39- TILs CD39- CD8 TILs CD8 TILs IL7R KLRG1 TNFSF4 ENTPD1 DHRS3 LEF1 ITGA5 MKI67 PZP KLF3 RYR2 SIK1B ANK3 LYST PPP1R3B ETV1 ADAM28 H2AC13 CCR7 GFOD1 RASGRP2 ITGAX MAST4 RAD51AP1 MYO1E CLCF1 NEBL S1PR5 VCL MPP7 MS4A6A PHLDB1 GFPT2 TNF RPL3 SPRY4 VCAM1 B4GALT5 TIPARP TNS3 PDCD1 POLQ AKAP5 IL6ST LY9 PLXND1 PLEKHA1 NEU1 DGKH SPRY2 PLEKHG3 IKZF4 MTX3 PARK7 ATP8B4 SYT11 PTGER4 SORL1 RAB11FIP5 BRCA1 MAP4K3 NCR1 CCR4 S1PR1 PDE8A IFIT2 EPHA4 ARHGEF12 PAICS PELI2 LAT2 GPRASP1 TTN RPLP0 IL4I1 AUTS2 RPS3 CDCA3 NHS LONRF2 CDC42EP3 SLCO3A1 RRM2 ADAMTSL4 INPP5F ARHGAP31 ESCO2 ADRB2 CSF1 WDHD1 GOLIM4 CDK5RAP1 CD69 GLUL HJURP SHC4 GNLY TTC9 HELLS DPP4 IL23A PITPNC1 TOX ARHGEF9 EXO1 SLC4A4 CKAP4 CARMIL3 NHSL2 DZIP3 GINS1 FUT8 UBASH3B CDCA5 PDE7B SOGA1 CDC45 NR3C2 TRIB1 KIF14 TRAF5 LIMS1 PPP1R2C TNFRSF9 KLRC2 POLA1 CD80 ATP10D CDCA8 SETD7 IER2 PATL2 CCDC141 CD84 HSPA6 CYB561 MPHOSPH9 CLSPN KLRC1 PTMS SCML4 ZBTB10 CCL3 CA5B PIP5K1B WNT9A CCNH GEM IL18RAP GGH SARDH B3GNT7 C13orf46 SBF2 IKZF3 ZMAT1 TCF7 NECTIN1 H3C7 FOS PAG1 HECA SLC4A10 SLC35G2 PER1 P2RY1 NFKBIA WDR76 PLAUR KDM1A H1-5 TSHZ2 FAM102B HMMR GPR132 CCRL2 PARP8 A2M ST8SIA1 NUF2 IL5RA RBPMS UBE2T USP53 EEF1A1 PLAC8 LGR6 TMEM123 NEK2 SNAP47 PTGIS SH2B3 P2RY8 S100PBP PLEKHA7 CLNK CRIM1 MGAT5 YBX3 TP53INP1 DTL CFH FEZ1 MYB FRMD4B TSPAN5 STIL ITGA2 GOLGA6L10 MYBL2 AHI1 CAND2 GZMB RBPJ PELI1 HSPA1B KCNK5 GOLGA6L9 TICRR TPRG1 UBE2C AURKA Leem G, et al. -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase