Original Article Identification of Key Genes in Preeclampsia-Associated Trophoblast Cells Using Bioinformatics Analysis
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Datasheet PDF (RUO)
BioVendor - Laboratorní medicína a.s. Karásek 1767/1 621 00 Brno-Řečkovice a Mokrá Hora Date of issue: 05.01.2021 PRODUCT DATASHEET Stanniocalcin 2 Human HEK293 Cat. No.: RD172096100 Type: Recombinant protein Size: 0.1 mg Source: HEK293 Species: Human Description Total 289 AA. Mw: 31.9 kDa (calculated). C-Terminal Flag-tag, 12AA (highlighted). The AA sequence is identical to Swiss-Prot- O76061 (STC2, aa 25–302). Other names Stanniocalcin-related protein, STC-related protein, STCRP, STC2 Introduction to the molecule Stanniocalcin 2 (STC2) is a secreted, homodimeric glycoprotein that is expressed in a wide variety of tissues including muscle, heart, pancreas, kidney, spleen, prostate, small intestine, colon and peripheral blood leukocytes. The encoded protein has 10 of its 15 cysteine residues conserved among stanniocalcin family members and is phosphorylated by casein kinase 2 exclusively on its serine residues. Its C-terminus contains a cluster of histidine residues which may interact with metal ions. STC2 may have autocrine or paracrine functions. The protein may play a role in the regulation of renal and intestinal calcium and phosphate transport, cell metabolism, or cellular calcium/phosphate homeostasis. Constitutive overexpression of human stanniocalcin 2 in mice resulted in pre- and postnatal growth restriction, reduced bone and skeletal muscle growth, and organomegaly. STC2 is also known to be involved in the regulation of unfolded protein response in the endoplasmic reticulum (ER), as well as in the regulation of cell proliferation under hypoxic conditions. In addition, a series of recent studies have shown that STC2 is also associated with cancer development. The expression of STC2 is up-regulated in several cancer types, including gastric cancer, neuroblastoma, colon cancer, prostate cancer and breast cancer. -
Investigating Cone Photoreceptor Development Using Patient-Derived NRL Null Retinal Organoids
ARTICLE https://doi.org/10.1038/s42003-020-0808-5 OPEN Investigating cone photoreceptor development using patient-derived NRL null retinal organoids Alyssa Kallman1,11, Elizabeth E. Capowski 2,11, Jie Wang 3, Aniruddha M. Kaushik4, Alex D. Jansen2, Kimberly L. Edwards2, Liben Chen4, Cynthia A. Berlinicke3, M. Joseph Phillips2,5, Eric A. Pierce6, Jiang Qian3, ✉ ✉ Tza-Huei Wang4,7, David M. Gamm2,5,8 & Donald J. Zack 1,3,9,10 1234567890():,; Photoreceptor loss is a leading cause of blindness, but mechanisms underlying photoreceptor degeneration are not well understood. Treatment strategies would benefit from improved understanding of gene-expression patterns directing photoreceptor development, as many genes are implicated in both development and degeneration. Neural retina leucine zipper (NRL) is critical for rod photoreceptor genesis and degeneration, with NRL mutations known to cause enhanced S-cone syndrome and retinitis pigmentosa. While murine Nrl loss has been characterized, studies of human NRL can identify important insights for human retinal development and disease. We utilized iPSC organoid models of retinal development to molecularly define developmental alterations in a human model of NRL loss. Consistent with the function of NRL in rod fate specification, human retinal organoids lacking NRL develop S- opsin dominant photoreceptor populations. We report generation of two distinct S-opsin expressing populations in NRL null retinal organoids and identify MEF2C as a candidate regulator of cone development. 1 Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, USA. 2 Waisman Center, University of Wisconsin-Madison, Madison, USA. 3 Department of Ophthalmology, Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, USA. -
Cellular and Molecular Signatures in the Disease Tissue of Early
Cellular and Molecular Signatures in the Disease Tissue of Early Rheumatoid Arthritis Stratify Clinical Response to csDMARD-Therapy and Predict Radiographic Progression Frances Humby1,* Myles Lewis1,* Nandhini Ramamoorthi2, Jason Hackney3, Michael Barnes1, Michele Bombardieri1, Francesca Setiadi2, Stephen Kelly1, Fabiola Bene1, Maria di Cicco1, Sudeh Riahi1, Vidalba Rocher-Ros1, Nora Ng1, Ilias Lazorou1, Rebecca E. Hands1, Desiree van der Heijde4, Robert Landewé5, Annette van der Helm-van Mil4, Alberto Cauli6, Iain B. McInnes7, Christopher D. Buckley8, Ernest Choy9, Peter Taylor10, Michael J. Townsend2 & Costantino Pitzalis1 1Centre for Experimental Medicine and Rheumatology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK. Departments of 2Biomarker Discovery OMNI, 3Bioinformatics and Computational Biology, Genentech Research and Early Development, South San Francisco, California 94080 USA 4Department of Rheumatology, Leiden University Medical Center, The Netherlands 5Department of Clinical Immunology & Rheumatology, Amsterdam Rheumatology & Immunology Center, Amsterdam, The Netherlands 6Rheumatology Unit, Department of Medical Sciences, Policlinico of the University of Cagliari, Cagliari, Italy 7Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow G12 8TA, UK 8Rheumatology Research Group, Institute of Inflammation and Ageing (IIA), University of Birmingham, Birmingham B15 2WB, UK 9Institute of -
G-Protein ␥-Complex Is Crucial for Efficient Signal Amplification in Vision
The Journal of Neuroscience, June 1, 2011 • 31(22):8067–8077 • 8067 Cellular/Molecular G-Protein ␥-Complex Is Crucial for Efficient Signal Amplification in Vision Alexander V. Kolesnikov,1 Loryn Rikimaru,2 Anne K. Hennig,1 Peter D. Lukasiewicz,1 Steven J. Fliesler,4,5,6,7 Victor I. Govardovskii,8 Vladimir J. Kefalov,1 and Oleg G. Kisselev2,3 1Department of Ophthalmology and Visual Sciences, Washington University School of Medicine, St. Louis, Missouri 63110, Departments of 2Ophthalmology and 3Biochemistry and Molecular Biology, Saint Louis University School of Medicine, Saint Louis, Missouri 63104, 4Research Service, Veterans Administration Western New York Healthcare System, and Departments of 5Ophthalmology (Ross Eye Institute) and 6Biochemistry, University at Buffalo/The State University of New York (SUNY), and 7SUNY Eye Institute, Buffalo, New York 14215, and 8Sechenov Institute for Evolutionary Physiology and Biochemistry, Russian Academy of Sciences, Saint Petersburg 194223, Russia A fundamental question of cell signaling biology is how faint external signals produce robust physiological responses. One universal mechanism relies on signal amplification via intracellular cascades mediated by heterotrimeric G-proteins. This high amplification system allows retinal rod photoreceptors to detect single photons of light. Although much is now known about the role of the ␣-subunit of the rod-specific G-protein transducin in phototransduction, the physiological function of the auxiliary ␥-complex in this process remains a mystery. Here, we show that elimination of the transducin ␥-subunit drastically reduces signal amplification in intact mouse rods. The consequence is a striking decline in rod visual sensitivity and severe impairment of nocturnal vision. Our findings demonstrate that transducin ␥-complex controls signal amplification of the rod phototransduction cascade and is critical for the ability of rod photoreceptors to function in low light conditions. -
G Protein-Coupled Receptors
G PROTEIN-COUPLED RECEPTORS Overview:- The completion of the Human Genome Project allowed the identification of a large family of proteins with a common motif of seven groups of 20-24 hydrophobic amino acids arranged as α-helices. Approximately 800 of these seven transmembrane (7TM) receptors have been identified of which over 300 are non-olfactory receptors (see Frederikson et al., 2003; Lagerstrom and Schioth, 2008). Subdivision on the basis of sequence homology allows the definition of rhodopsin, secretin, adhesion, glutamate and Frizzled receptor families. NC-IUPHAR recognizes Classes A, B, and C, which equate to the rhodopsin, secretin, and glutamate receptor families. The nomenclature of 7TM receptors is commonly used interchangeably with G protein-coupled receptors (GPCR), although the former nomenclature recognises signalling of 7TM receptors through pathways not involving G proteins. For example, adiponectin and membrane progestin receptors have some sequence homology to 7TM receptors but signal independently of G-proteins and appear to reside in membranes in an inverted fashion compared to conventional GPCR. Additionally, the NPR-C natriuretic peptide receptor has a single transmembrane domain structure, but appears to couple to G proteins to generate cellular responses. The 300+ non-olfactory GPCR are the targets for the majority of drugs in clinical usage (Overington et al., 2006), although only a minority of these receptors are exploited therapeutically. Signalling through GPCR is enacted by the activation of heterotrimeric GTP-binding proteins (G proteins), made up of α, β and γ subunits, where the α and βγ subunits are responsible for signalling. The α subunit (tabulated below) allows definition of one series of signalling cascades and allows grouping of GPCRs to suggest common cellular, tissue and behavioural responses. -
Bioinformatics Integrated Analysis to Investigate Candidate Biomarkers and Associated Metabolites in Osteosarcoma
Wang et al. Journal of Orthopaedic Surgery and Research (2021) 16:432 https://doi.org/10.1186/s13018-021-02578-0 RESEARCH ARTICLE Open Access Bioinformatics integrated analysis to investigate candidate biomarkers and associated metabolites in osteosarcoma Jun Wang, Mingzhi Gong, Zhenggang Xiong, Yangyang Zhao and Deguo Xing* Abstract Background: This study hoped to explore the potential biomarkers and associated metabolites during osteosarcoma (OS) progression based on bioinformatics integrated analysis. Methods: Gene expression profiles of GSE28424, including 19 human OS cell lines (OS group) and 4 human normal long bone tissue samples (control group), were downloaded. The differentially expressed genes (DEGs) in OS vs. control were investigated. The enrichment investigation was performed based on DEGs, followed by protein–protein interaction network analysis. Then, the feature genes associated with OS were explored, followed by survival analysis to reveal prognostic genes. The qRT-PCR assay was performed to test the expression of these genes. Finally, the OS- associated metabolites and disease-metabolic network were further investigated. Results: Totally, 357 DEGs were revealed between the OS vs. control groups. These DEGs, such as CXCL12, were mainly involved in functions like leukocyte migration. Then, totally, 38 feature genes were explored, of which 8 genes showed significant associations with the survival of patients. High expression of CXCL12, CEBPA, SPARCL1, CAT, TUBA1A, and ALDH1A1 was associated with longer survival time, while high expression of CFLAR and STC2 was associated with poor survival. Finally, a disease-metabolic network was constructed with 25 nodes including two disease-associated metabolites cyclophosphamide and bisphenol A (BPA). BPA showed interactions with multiple prognosis-related genes, such as CXCL12 and STC2. -
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. -
A System-Level, Molecular Evolutionary Analysis of Mam- Malian Phototransduction (Supplementary Material)
A system-level, molecular evolutionary analysis of mam- malian phototransduction (supplementary material) Brandon M Invergo1 , Ludovica Montanucci∗1 , Hafid Laayouni1 and Jaume Bertranpetit1 1IBE-Institute of Evolutionary Biology (UPF-CSIC), CEXS-UPF-PRBB, Barcelona, Catalonia, Spain Email: Brandon Invergo - [email protected]; Ludovica Montanucci∗- [email protected]; Hafid Laayouni - hafi[email protected]; Jaume Bertranpetit - [email protected]; ∗Corresponding author Table S1 - Classifications of the genes Genes were assigned classifications according to their photoreceptor cell-type specificity, the process in which the encoded protein is primarily active, and the general function of the encoded protein. (Note: here "enzyme" specifically refers to enzymes involved in retinoid recycling.) 1 gene cell type process function ABCA4 shared retinoid cycle enzyme AIPL1 shared phototransduction other ARR3 cone phototransduction signal regulator ASCL1 rod development transcription regulation CNGA1 rod phototransduction ion channel CNGA3 cone phototransduction ion channel CNGB1 rod phototransduction ion channel CNGB3 cone phototransduction ion channel CRX shared development transcription regulation GNAT1 rod phototransduction G protein GNAT2 cone phototransduction G protein GNB1 rod phototransduction G protein GNB3 cone phototransduction G protein GNB5 shared phototransduction G protein GNGT1 rod phototransduction G protein GNGT2 cone phototransduction G protein GPSM2 shared phototransduction other GRK1 shared phototransduction -
Comparative Analyses of Gene Copy Number and Mrna Expression in GBM Tumors And
Title page Comparative analyses of gene copy number and mRNA expression in GBM tumors and GBM xenografts J. Graeme Hodgson # *, Ru-Fang Yeh #, Amrita Ray, Nicholas J Wang, Ivan Smirnov, Mamie Yu, Sujatmi Hariono, Joachim Silber, Heidi S. Feiler, Joe W. Gray, Paul T. Spellman, Scott R. Vandenberg, Mitchel S. Berger, C. David James Departments of Neurological Surgery (JGH, IS, MY, SH, JS, SRV, MSB, CDJ), Pathology (SRV), and Epidemiology and Biostatistics (RY) University of California, San Francisco, CA 94143. Life Sciences Division, Lawrence Berkeley National Lab, Berkeley, CA 94720 (AR, NJW, HSF, JWG, PTS) # These authors contributed equally to this work Running title: Genomic analyses of a GBM xenograft tumor panel * Corresponding Author J. Graeme Hodgson Dept. Neurological Surgery UC San Francisco San Francisco, CA 94143-0808 Phone: 415-476-3630 Fax: 415-476-8218 e-mail: [email protected] Abstract Development of model systems that recapitulate the molecular heterogeneity observed amongst GBM tumors will expedite the testing of targeted molecular therapeutic strategies for GBM treatment. In this study, we profiled DNA copy number and mRNA expression in 21 independent GBM tumor lines maintained as subcutaneous xenografts (GBMX), and compared GBMX molecular signatures to those observed in GBM clinical specimens derived from The Cancer Genome Atlas (TCGA). The predominant copy number signature in both tumor groups was defined by chromosome-7-gain/chromosome-10-loss, a poor prognosis genetic signature. We also observed, at frequencies similar to that detected in TCGA GBMs genomic amplification and overexpression of known GBM oncogenes such as EGFR, MDM2, CDK6 and MYCN, and novel genes including NUP107, SLC35E3, MMP1, MMP13 and DDX1. -
CD29 Identifies IFN-Γ–Producing Human CD8+ T Cells with an Increased Cytotoxic Potential
+ CD29 identifies IFN-γ–producing human CD8 T cells with an increased cytotoxic potential Benoît P. Nicoleta,b, Aurélie Guislaina,b, Floris P. J. van Alphenc, Raquel Gomez-Eerlandd, Ton N. M. Schumacherd, Maartje van den Biggelaarc,e, and Monika C. Wolkersa,b,1 aDepartment of Hematopoiesis, Sanquin Research, 1066 CX Amsterdam, The Netherlands; bLandsteiner Laboratory, Oncode Institute, Amsterdam University Medical Center, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands; cDepartment of Research Facilities, Sanquin Research, 1066 CX Amsterdam, The Netherlands; dDivision of Molecular Oncology and Immunology, Oncode Institute, The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands; and eDepartment of Molecular and Cellular Haemostasis, Sanquin Research, 1066 CX Amsterdam, The Netherlands Edited by Anjana Rao, La Jolla Institute for Allergy and Immunology, La Jolla, CA, and approved February 12, 2020 (received for review August 12, 2019) Cytotoxic CD8+ T cells can effectively kill target cells by producing therefore developed a protocol that allowed for efficient iso- cytokines, chemokines, and granzymes. Expression of these effector lation of RNA and protein from fluorescence-activated cell molecules is however highly divergent, and tools that identify and sorting (FACS)-sorted fixed T cells after intracellular cytokine + preselect CD8 T cells with a cytotoxic expression profile are lacking. staining. With this top-down approach, we performed an un- + Human CD8 T cells can be divided into IFN-γ– and IL-2–producing biased RNA-sequencing (RNA-seq) and mass spectrometry cells. Unbiased transcriptomics and proteomics analysis on cytokine- γ– – + + (MS) analyses on IFN- and IL-2 producing primary human producing fixed CD8 T cells revealed that IL-2 cells produce helper + + + CD8 Tcells. -
Identification of NTN4, TRA1, and STC2 As Prognostic Markers in Breast Cancer in a Screen for Signal Sequence Encoding Proteins
Human Cancer Biology Identification of NTN4, TRA1,andSTC2 as Prognostic Markers in Breast Cancer in a Screen for Signal Sequence Encoding Proteins Selma Esseghir,1Alan Kennedy,1Pooja Seedhar,2 Ashutosh Nerurkar,3 Richard Poulsom,2 Jorge S. Reis-Filho,1and Clare M. Isacke1 Abstract Purpose: In a previous screen using a signal-trap library, we identified a number of secreted pro- teins up-regulated in primary tumor cells isolated from invasive breast cancers.The purpose of this study was to assess the expression of these genes in human invasive breast tumors and to deter- mine the significance of their expression for prognosis in breast cancer. Experimental Design: A tissue microarray containing 245 invasive breast tumors from women treated with curative surgery followed by anthracycline-based chemotherapy and hormone ther- apy for the estrogen receptor (ER)^ positive tumors was screened by in situ hybridization with probes against thrombospondin 3 (TSP3), insulin-like growth factor binding protein 7 (IGFBP7), tumor rejection antigen 1 (TRA1), stanniocalcin 2 (STC2),andnetrin4(NTN4). Correlations be- tween categorical variables were done using the m2 test and Fisher’s exact test. Cumulative sur- vival probabilities were calculated using the Kaplan-Meier method and multivariate survival analysis was done with Cox hazard model. A series of breast cancers were also stained with NTN4 antibodies. Results: All five genes examined were expressed in invasive breast tumor cells. NTN4 protein expression was also confirmed by immunohistochemistry.Together, these data validate the design and screening of the signal-trap library. Univariate survival analysis revealed that expressions of TRA1, STC2 ,andNTN4 are correlated with longer disease-free survival and thatTRA1 and NTN4 are associated with longer overall survival. -
1 Supplemental Informations Microarray Method Total RNA Was
Supplemental Informations Microarray method Total RNA was purified using nucleospin RNA L columns (Macherey Nagel, Hoerdt, France) according to the manufacturer’s recommendations. cDNA synthesis and biotin labelling of cRNA were performed using 5 µg total RNA and according to One-Cycle Target Labelling protocol (Affymetrix, Santa Clara, CA). cRNA were hybridized to 12 Mouse Genome 430A GeneChips (1 mouse per chip) and analyzed using a GeneChip 3000 7G scanner and the GeneChip Operative Software v1.1.1 (Affymetrix) at the Gene Expression core facility of the Institute for Biotherapy (Montpellier, France). CEL files were processed using the ChipInspector software (Genomatix, Munich, Germany). ChipInspector uses single probe expression levels as input and map to transcripts probes that uniquely display significant changes. The methods circumvent false negative resulting from low signal probes, annotation errors and errors due to the existence of alternative transcripts. Differentially expressed genes between the AL and MT groups at both time points were identified using a SAM (Significance analysis of Microarrays) one class comparison with the following settings: false discovery rate of 0.5%; minimal probe coverage: 3; minimal fold change threshold of 1.5. Down and up-regulated genes from both datasets (CT4 and CT16) were mapped to the Gene Ontology (GO) biological process terms and calculated as over- represented (z-score) relative to the expected number of regulated genes in each GO category. Cluster 3.0 and Treeview were used to construct the heatmap of the subset of genes regulated in a time dependent manner in the tumor of mice with restricted access to food.