Reticulum-Resident Peptidases Activities of Cytosolic And
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Functional Proteomic Profiling of Secreted Serine Proteases In
www.nature.com/scientificreports OPEN Functional Proteomic Profling of Secreted Serine Proteases in Health and Infammatory Bowel Disease Received: 24 November 2017 Alexandre Denadai-Souza1, Chrystelle Bonnart1, Núria Solà Tapias1, Marlène Marcellin2, Accepted: 30 April 2018 Brendan Gilmore3, Laurent Alric4, Delphine Bonnet1, Odile Burlet-Schiltz2, Morley D. Hollenberg5, Published: xx xx xxxx Nathalie Vergnolle1,5 & Céline Deraison1 While proteases are essential in gastrointestinal physiology, accumulating evidence indicates that dysregulated proteolysis plays a pivotal role in the pathophysiology of infammatory bowel disease (IBD). Nonetheless, the identity of overactive proteases released by human colonic mucosa remains largely unknown. Studies of protease abundance have primarily investigated expression profles, not taking into account their enzymatic activity. Herein we have used serine protease-targeted activity- based probes (ABPs) coupled with mass spectral analysis to identify active forms of proteases secreted by the colonic mucosa of healthy controls and IBD patients. Profling of (Pro-Lys)-ABP bound proteases revealed that most of hyperactive proteases from IBD secretome are clustered at 28-kDa. We identifed seven active proteases: the serine proteases cathepsin G, plasma kallikrein, plasmin, tryptase, chymotrypsin-like elastase 3 A, and thrombin and the aminopeptidase B. Only cathepsin G and thrombin were overactive in supernatants from IBD patient tissues compared to healthy controls. Gene expression analysis highlighted the transcription of genes encoding these proteases into intestinal mucosae. The functional ABP-targeted proteomic approach that we have used to identify active proteases in human colonic samples bears directly on the understanding of the role these enzymes may play in the pathophysiology of IBD. Te degradome represents almost 2% of protein coding genes in the human genome, with at least 588 genes cod- ing for proteases. -
The Global Architecture Shaping the Heterogeneity and Tissue-Dependency of the MHC Class I Immunopeptidome Is Evolutionarily Conserved
bioRxiv preprint doi: https://doi.org/10.1101/2020.09.28.317750; this version posted September 29, 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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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. The Global Architecture Shaping the Heterogeneity and Tissue-Dependency of the MHC Class I Immunopeptidome is Evolutionarily Conserved Authors Peter Kubiniok†1, Ana Marcu†2,3, Leon Bichmann†2,4, Leon Kuchenbecker4, Heiko Schuster1,5, David Hamelin1, Jérome Despault1, Kevin Kovalchik1, Laura Wessling1, Oliver Kohlbacher4,7,8,9,10 Stefan Stevanovic2,3,6, Hans-Georg Rammensee2,3,6, Marian C. Neidert11, Isabelle Sirois1, Etienne Caron1,12* Affiliations *Corresponding and Leading author: Etienne Caron ([email protected]) †Equal contribution to this work 1CHU Sainte-Justine Research Center, Montreal, QC H3T 1C5, Canada 2Department of Immunology, Interfaculty Institute for Cell Biology, University of Tübingen, Tübingen, Baden-Württemberg, 72076, Germany. 3Cluster of Excellence iFIT (EXC 2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Tübingen, Baden-Württemberg, 72076, Germany. 4Applied Bioinformatics, Dept. of Computer Science, University of Tübingen, Tübingen, Baden- Württemberg, 72074, Germany. 5Immatics Biotechnologies GmbH, Tübingen, 72076, Baden-Württemberg, Germany. 6DKFZ Partner Site Tübingen, German Cancer Consortium (DKTK), Tübingen, Baden- Württemberg, 72076, Germany. 7Institute for Bioinformatics and Medical Informatics, -
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. -
Serine Proteases with Altered Sensitivity to Activity-Modulating
(19) & (11) EP 2 045 321 A2 (12) EUROPEAN PATENT APPLICATION (43) Date of publication: (51) Int Cl.: 08.04.2009 Bulletin 2009/15 C12N 9/00 (2006.01) C12N 15/00 (2006.01) C12Q 1/37 (2006.01) (21) Application number: 09150549.5 (22) Date of filing: 26.05.2006 (84) Designated Contracting States: • Haupts, Ulrich AT BE BG CH CY CZ DE DK EE ES FI FR GB GR 51519 Odenthal (DE) HU IE IS IT LI LT LU LV MC NL PL PT RO SE SI • Coco, Wayne SK TR 50737 Köln (DE) •Tebbe, Jan (30) Priority: 27.05.2005 EP 05104543 50733 Köln (DE) • Votsmeier, Christian (62) Document number(s) of the earlier application(s) in 50259 Pulheim (DE) accordance with Art. 76 EPC: • Scheidig, Andreas 06763303.2 / 1 883 696 50823 Köln (DE) (71) Applicant: Direvo Biotech AG (74) Representative: von Kreisler Selting Werner 50829 Köln (DE) Patentanwälte P.O. Box 10 22 41 (72) Inventors: 50462 Köln (DE) • Koltermann, André 82057 Icking (DE) Remarks: • Kettling, Ulrich This application was filed on 14-01-2009 as a 81477 München (DE) divisional application to the application mentioned under INID code 62. (54) Serine proteases with altered sensitivity to activity-modulating substances (57) The present invention provides variants of ser- screening of the library in the presence of one or several ine proteases of the S1 class with altered sensitivity to activity-modulating substances, selection of variants with one or more activity-modulating substances. A method altered sensitivity to one or several activity-modulating for the generation of such proteases is disclosed, com- substances and isolation of those polynucleotide se- prising the provision of a protease library encoding poly- quences that encode for the selected variants. -
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 -
The Tumor Suppressor Notch Inhibits Head and Neck Squamous Cell
The Texas Medical Center Library DigitalCommons@TMC The University of Texas MD Anderson Cancer Center UTHealth Graduate School of The University of Texas MD Anderson Cancer Biomedical Sciences Dissertations and Theses Center UTHealth Graduate School of (Open Access) Biomedical Sciences 12-2015 THE TUMOR SUPPRESSOR NOTCH INHIBITS HEAD AND NECK SQUAMOUS CELL CARCINOMA (HNSCC) TUMOR GROWTH AND PROGRESSION BY MODULATING PROTO-ONCOGENES AXL AND CTNNAL1 (α-CATULIN) Shhyam Moorthy Shhyam Moorthy Follow this and additional works at: https://digitalcommons.library.tmc.edu/utgsbs_dissertations Part of the Biochemistry, Biophysics, and Structural Biology Commons, Cancer Biology Commons, Cell Biology Commons, and the Medicine and Health Sciences Commons Recommended Citation Moorthy, Shhyam and Moorthy, Shhyam, "THE TUMOR SUPPRESSOR NOTCH INHIBITS HEAD AND NECK SQUAMOUS CELL CARCINOMA (HNSCC) TUMOR GROWTH AND PROGRESSION BY MODULATING PROTO-ONCOGENES AXL AND CTNNAL1 (α-CATULIN)" (2015). The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences Dissertations and Theses (Open Access). 638. https://digitalcommons.library.tmc.edu/utgsbs_dissertations/638 This Dissertation (PhD) is brought to you for free and open access by the The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences at DigitalCommons@TMC. It has been accepted for inclusion in The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences Dissertations and Theses (Open Access) by an authorized administrator of DigitalCommons@TMC. For more information, please contact [email protected]. THE TUMOR SUPPRESSOR NOTCH INHIBITS HEAD AND NECK SQUAMOUS CELL CARCINOMA (HNSCC) TUMOR GROWTH AND PROGRESSION BY MODULATING PROTO-ONCOGENES AXL AND CTNNAL1 (α-CATULIN) by Shhyam Moorthy, B.S. -
REVIEW ARTICLE High Molecular Mass Intracellular Proteases
Biochem J. (1989) 263, 625-633 (Printed in Great Britain) 625 REVIEW ARTICLE High molecular mass intracellular proteases A. Jennifer RIVETT Department of Biochemistry, University of Leicester, Leicester LE'l 7RH, U.K. INTRODUCTION demonstrated that intracellular proteolysis is not re- Many of the well-characterized proteolytic enzymes, stricted to the lysosomes. Since a large proportion of and particularly those for which X-ray structures are intracellular protein breakdown, especially the degra- now available, are small monomeric enzymes often dation of proteins with short half-lives, is now known to having molecular masses in the range of 20-30 kDa. occur by nonlysosomal mechanisms (Mayer & Doherty, Many of them are extracellular enzymes which are easy 1986; Bond & Beynon, 1987; Rechsteiner, 1987; Bohley, to assay and to purify. With a growing awareness of the 1987; Rivett, 1989b; Katunuma & Kominami, 1989; importance of intracellular protein turnover and Knecht & Grisolia, 1989), there is now a greater interest mechanisms of intracellular protein breakdown, interest in nonlysosomal degradation systems and in nonlyso- in the proteases responsible has also increased. Although somal proteinases, many of which have large complex some intracellular proteases, especially those found structures. within the lysosomes in animal cells, are, like extracellular In contrast to the well-known lysosomal proteases, proteases, small and highly active monomeric enzymes, soluble extralysosomal proteases often have multimeric a number of cellular proteases -
Studies of Structure and Function of Tripeptidyl-Peptidase II
Till familj och vänner List of Papers This thesis is based on the following papers, which are referred to in the text by their Roman numerals. I. Eriksson, S.; Gutiérrez, O.A.; Bjerling, P.; Tomkinson, B. (2009) De- velopment, evaluation and application of tripeptidyl-peptidase II se- quence signatures. Archives of Biochemistry and Biophysics, 484(1):39-45 II. Lindås, A-C.; Eriksson, S.; Josza, E.; Tomkinson, B. (2008) Investiga- tion of a role for Glu-331 and Glu-305 in substrate binding of tripepti- dyl-peptidase II. Biochimica et Biophysica Acta, 1784(12):1899-1907 III. Eklund, S.; Lindås, A-C.; Hamnevik, E.; Widersten, M.; Tomkinson, B. Inter-species variation in the pH dependence of tripeptidyl- peptidase II. Manuscript IV. Eklund, S.; Kalbacher, H.; Tomkinson, B. Characterization of the endopeptidase activity of tripeptidyl-peptidase II. Manuscript Paper I and II were published under maiden name (Eriksson). Reprints were made with permission from the respective publishers. Contents Introduction ..................................................................................................... 9 Enzymes ..................................................................................................... 9 Enzymes and pH dependence .............................................................. 11 Peptidases ................................................................................................. 12 Serine peptidases ................................................................................. 14 Intracellular protein -
Modeling of Human M1 Aminopeptidases for in Silico Screening of Potential Plasmodium Falciparum Alanine Aminopeptidase (Pfa-M1) Specific Inhibitors
open access www.bioinformation.net Hypothesis Volume 10(8) Modeling of human M1 aminopeptidases for in silico screening of potential Plasmodium falciparum alanine aminopeptidase (PfA-M1) specific inhibitors Shakti Sahi*, Sneha Rai, Meenakshi Chaudhary & Vikrant Nain* School of Biotechnology, Gautam Buddha University, Greater Noida, 201312, India; Shakti Sahi – Email: [email protected]; Vikrant Nain- Email: [email protected]; Phone: +91-120-234275; +91-120-234283 Fax: +91-120-234205; *Corresponding authors Received June 18, 2014; Accepted June 27, 2014; Published August 30, 2014 Abstract: Plasmodium falciparum alanine M1-aminopeptidase (PfA-M1) is a validated target for anti-malarial drug development. Presence of significant similarity between PfA-M1 and human M1-aminopeptidases, particularly within regions of enzyme active site leads to problem of non-specificity and off-target binding for known aminopeptidase inhibitors. Molecular docking based in silico screening approach for off-target binding has high potential but requires 3D-structure of all human M1-aminopeptidaes. Therefore, in the present study 3D structural models of seven human M1-aminopeptidases were developed. The robustness of docking parameters and quality of predicted human M1-aminopeptidases structural models was evaluated by stereochemical analysis and docking of their respective known inhibitors. The docking scores were in agreement with the inhibitory concentrations elucidated in enzyme assays of respective inhibitor enzyme combinations (r2≈0.70). Further docking analysis of fifteen potential PfA-M1 inhibitors (virtual screening identified) showed that three compounds had less docking affinity for human M1-aminopeptidases as compared to PfA-M1. These three identified potential lead compounds can be validated with enzyme assays and used as a scaffold for designing of new compounds with increased specificity towards PfA-M1. -
IMW 2019 Aminopeptidase Gene Expression Poster
Poster FP-028 Aminopeptidase Gene Expression in Myeloma Nina Nupponen,1 Muntasir Majumder,2 Paul Dowling,3 Juha Lievonen,4 Despina Bazou,5 Ana Slipicevic,1 Raija Silvennoinen,4 Pekka Anttila,4 Peter O`Gorman,5 Fredrik Lehmann,1 and Caroline A. Heckman6 1Oncopeptides AB, Stockholm, Sweden; 2Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland; 3Maynooth University, Dublin, Ireland; 4Department of Hematology, Helsinki University Hospital and Comprehensive Cancer Center, Helsinki, Finland; 5Mater Misericordiae University Hospital, Dublin, Ireland; 6Helsinki University Hospital Cancer Center, Helsinki, Finland INTRODUCTION RESULTS A hallmark of myeloma is high-level production • Aminopeptidase gene expression levels were ranked based on abundance levels in all • We also investigated whether any aminopeptidase could be linked to disease progression and • Ex vivo testing of patient cells with the • Survival analysis revealed patient samples exhibiting 2× or higher LAP3 of immunoglobulins leading to a heavy load on samples (Figure 1A) found no significant difference (Figure 2) aminopeptidase inhibitor tosedostat showed expression had poorer prognosis with a median survival of 6 months that the viability of approximately 30% of from the sampling date (P=0.0001, HR 4.5; 95% CI 1.45-14.05) ( ) protein folding and homeostasis in tumor cells. Aminopeptidases were differentially expressed compared to heathy plasma cells - Expression levels of LAP3, ERAP1, METAP2, and DPP7 (P>0.005) appeared higher in Figure 5 • relapsed myeloma samples was reduced The aminopeptidase gene family catalyze the (Figure 1B) relapsed/refractory multiple myeloma (RRMM) than in newly diagnosed multiple myeloma hydrolysis of amino acid residues from proteins (NDMM) samples (Figure 4) - The majority of the genes in patient samples showed related expression patterns or Figure 5. -
©Ferrata Storti Foundation
Original Articles T-cell/histiocyte-rich large B-cell lymphoma shows transcriptional features suggestive of a tolerogenic host immune response Peter Van Loo,1,2,3 Thomas Tousseyn,4 Vera Vanhentenrijk,4 Daan Dierickx,5 Agnieszka Malecka,6 Isabelle Vanden Bempt,4 Gregor Verhoef,5 Jan Delabie,6 Peter Marynen,1,2 Patrick Matthys,7 and Chris De Wolf-Peeters4 1Department of Molecular and Developmental Genetics, VIB, Leuven, Belgium; 2Department of Human Genetics, K.U.Leuven, Leuven, Belgium; 3Bioinformatics Group, Department of Electrical Engineering, K.U.Leuven, Leuven, Belgium; 4Department of Pathology, University Hospitals K.U.Leuven, Leuven, Belgium; 5Department of Hematology, University Hospitals K.U.Leuven, Leuven, Belgium; 6Department of Pathology, The Norwegian Radium Hospital, University of Oslo, Oslo, Norway, and 7Department of Microbiology and Immunology, Rega Institute for Medical Research, K.U.Leuven, Leuven, Belgium Citation: Van Loo P, Tousseyn T, Vanhentenrijk V, Dierickx D, Malecka A, Vanden Bempt I, Verhoef G, Delabie J, Marynen P, Matthys P, and De Wolf-Peeters C. T-cell/histiocyte-rich large B-cell lymphoma shows transcriptional features suggestive of a tolero- genic host immune response. Haematologica. 2010;95:440-448. doi:10.3324/haematol.2009.009647 The Online Supplementary Tables S1-5 are in separate PDF files Supplementary Design and Methods One microgram of total RNA was reverse transcribed using random primers and SuperScript II (Invitrogen, Merelbeke, Validation of microarray results by real-time quantitative Belgium), as recommended by the manufacturer. Relative reverse transcriptase polymerase chain reaction quantification was subsequently performed using the compar- Ten genes measured by microarray gene expression profil- ative CT method (see User Bulletin #2: Relative Quantitation ing were validated by real-time quantitative reverse transcrip- of Gene Expression, Applied Biosystems). -
Supplemental Table 1
Symbol Gene name MIN6.EXO MIN6.M1 MIN6.M2 MIN6.M3 MIN6.M4 A2m alpha-2-macroglobulin A2m Acat1 acetyl-Coenzyme A acetyltransferase 1 Acat1 Acly ATP citrate lyase Acly Acly Acly Act Actin Act Act Act Act Aga aspartylglucosaminidase Aga Ahcy S-adenosylhomocysteine hydrolase Ahcy Alb Albumin Alb Alb Alb Aldoa aldolase A, fructose-bisphosphate Aldoa Anxa5 Annexin A5 Anxa5 AP1 Adaptor-related protein complex AP1 AP2 Adaptor protein complex AP2 Arf1 ADP-ribosylation factor 1 Arf1 Atp1a1 ATPase Na/K transpoting Atp1a1 ATP1b1 Na/K ATPase beta subunit ATP1b1 ATP6V1 ATPase, H+ transporting.. ATP6V1 ATP6v1 ATP6v1 Banf1 Barrier to autointegration factor Banf1 Basp1 brain abundant, memrane signal protein 1 Basp1 C3 complement C3 C3 C3 C3 C4 Complement C4 C4 C4 C4 Calm2 calmodulin 2 (phosphorylase kinase, delta) Calm2 Capn5 Calpain 5 Capn5 Capn5 Cct5 chaperonin subunit 5 Cct5 Cct8 chaperonin subunit 8 Cct8 CD147 basigin CD147 CD63 CD63 CD63 CD81 CD81 CD81 CD81 CD81 CD81 CD81 CD82 CD82 CD82 CD82 CD90.2 thy1.2 CD90.2 CD98 Slc3a2 CD98 CD98 Cdc42 Cell division cycle 42 Cdc42 Cfl1 Cofilin 1 Cfl1 Cfl1 Chmp4b chromatin modifying protein 4B Chmp4b Chmp5 chromatin modifying protein 5 Chmp5 Clta clathrin, light polypeptide A Clta Cltc Clathrin Hc Cltc Cltc Cltc Cltc Clu clusterin Clu Col16a1 collagen 16a1 Col16a1 Col2 Collagen type II Col2a1 Col2 Col6 Collagen type VI alpha 3 Col6a3 Col6 CpE carboxypeptidase E CpE CpE CpE, CpH CpE CpE Cspg4 Chondroitin sulfate proteoglycan 4 Cspg4 CyCAP Cyclophilin C-associated protein CyCAP CyCAP Dnpep aspartyl aminopeptidase Dnpep Dstn destrin Dstn EDIL3 EGF-like repeat discoidin.