Elucidation of the Function of Type 1 Human Methionine Aminopeptidase During Cell Cycle Progression
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Supplementary Materials: Evaluation of Cytotoxicity and Α-Glucosidase Inhibitory Activity of Amide and Polyamino-Derivatives of Lupane Triterpenoids
Supplementary Materials: Evaluation of cytotoxicity and α-glucosidase inhibitory activity of amide and polyamino-derivatives of lupane triterpenoids Oxana B. Kazakova1*, Gul'nara V. Giniyatullina1, Akhat G. Mustafin1, Denis A. Babkov2, Elena V. Sokolova2, Alexander A. Spasov2* 1Ufa Institute of Chemistry of the Ufa Federal Research Centre of the Russian Academy of Sciences, 71, pr. Oktyabrya, 450054 Ufa, Russian Federation 2Scientific Center for Innovative Drugs, Volgograd State Medical University, Novorossiyskaya st. 39, Volgograd 400087, Russian Federation Correspondence Prof. Dr. Oxana B. Kazakova Ufa Institute of Chemistry of the Ufa Federal Research Centre of the Russian Academy of Sciences 71 Prospeсt Oktyabrya Ufa, 450054 Russian Federation E-mail: [email protected] Prof. Dr. Alexander A. Spasov Scientific Center for Innovative Drugs of the Volgograd State Medical University 39 Novorossiyskaya st. Volgograd, 400087 Russian Federation E-mail: [email protected] Figure S1. 1H and 13C of compound 2. H NH N H O H O H 2 2 Figure S2. 1H and 13C of compound 4. NH2 O H O H CH3 O O H H3C O H 4 3 Figure S3. Anticancer screening data of compound 2 at single dose assay 4 Figure S4. Anticancer screening data of compound 7 at single dose assay 5 Figure S5. Anticancer screening data of compound 8 at single dose assay 6 Figure S6. Anticancer screening data of compound 9 at single dose assay 7 Figure S7. Anticancer screening data of compound 12 at single dose assay 8 Figure S8. Anticancer screening data of compound 13 at single dose assay 9 Figure S9. Anticancer screening data of compound 14 at single dose assay 10 Figure S10. -
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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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, -
Sequences in the Cytoplasmic Tail of SARS-Cov-2 Spike Facilitate Expression at the Cell Surface and Syncytia Formation
bioRxiv preprint doi: https://doi.org/10.1101/2020.10.12.335562; this version posted May 3, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Sequences in the cytoplasmic tail of SARS-CoV-2 Spike facilitate expression at the cell surface and syncytia formation Jerome Cattin-Ortolá1,2, Lawrence Welch1,2, Sarah L. Maslen1, J. Mark Skehel1, Guido Papa1, Leo C. James1 and Sean Munro1* 1: MRC Laboratory oF Molecular Biology Francis Crick Avenue Cambridge CB2 0QH UK 2: Denotes equal contribution * Corresponding author: Email: [email protected] 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.10.12.335562; this version posted May 3, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Abstract The Spike (S) protein of SARS-CoV-2 binds ACE2 to direct fusion with host cells. S comprises a large external domain, a transmembrane domain (TMD) and a short cytoplasmic tail. Understanding the intracellular trafficking of S is relevant to SARS-CoV-2 infection, and to vaccines expressing full-length S from mRNA or adenovirus vectors. We have applied proteomics to identify cellular factors that interact with the cytoplasmic tail of S. -
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. -
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 -
Methionine Aminopeptidase Emerging Role in Angiogenesis
Chapter 2 Methionine Aminopeptidase Emerging role in angiogenesis Joseph A. Vetro1, Benjamin Dummitt2, and Yie-Hwa Chang2 1Department of Pharmaceutical Chemistry, University of Kansas, 2095 Constant Ave., Lawrence, KS 66047, USA. 2Edward A. Doisy Department of Biochemistry and Molecular Biology, St. Louis University Health Sciences Center, 1402 S. Grand Blvd., St. Louis, MO 63104, USA. Abstract: Angiogenesis, the formation of new blood vessels from existing vasculature, is a key factor in a number of vascular-related pathologies such as the metastasis and growth of solid tumors. Thus, the inhibition of angiogenesis has great potential as a therapeutic modality in the treatment of cancer and other vascular-related diseases. Recent evidence suggests that the inhibition of mammalian methionine aminopeptidase type 2 (MetAP2) catalytic activity in vascular endothelial cells plays an essential role in the pharmacological activity of the most potent small molecule angiogenesis inhibitors discovered to date, the fumagillin class. Methionine aminopeptidase (MetAP, EC 3.4.11.18) catalyzes the non-processive, co-translational hydrolysis of initiator N-terminal methionine when the second residue of the nascent polypeptide is small and uncharged. Initiator Met removal is a ubiquitous and essential modification. Indirect evidence suggests that removal of initiator Met by MetAP is important for the normal function of many proteins involved in DNA repair, signal transduction, cell transformation, secretory vesicle trafficking, and viral capsid assembly and infection. Currently, much effort is focused on understanding the essential nature of methionine aminopeptidase activity and elucidating the role of methionine aminopeptidase type 2 catalytic activity in angiogenesis. In this chapter, we give an overview of the MetAP proteins, outline the importance of initiator Met hydrolysis, and discuss the possible mechanism(s) through which MetAP2 inhibition by the fumagillin class of angiogenesis inhibitors leads to cytostatic growth arrest in vascular endothelial cells. -
Arxiv:2007.15681V2 [Cs.CL] 9 Nov 2020 Method by a Large Margin
COVID-19 therapy target discovery with context-aware literature mining Matej Martinc1;2, Blaˇz Skrljˇ 1;2, Sergej Pirkmajer3, Nada Lavraˇc1;2;4, Bojan Cestnik5;1, Martin Marzidovˇsek1;2, and Senja Pollak2 1 JoˇzefStefan International Postgraduate School, Ljubljana, Slovenia 2 JoˇzefStefan Institute, Ljubljana, Slovenia 3 Institute of Pathophysiology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia 4 University of Nova Gorica, Vipava, Slovenia 5 Temida d.o.o, Ljubljana, Slovenia The final reviewed publication was published in Proceedings of the 23rd International Conference on Discovery Science (DS 2020), Thessaloniki, Greece, October 19{21, 2020 and is available online at https://doi.org/ 10.1007/978-3-030-61527-7 8. Abstract. The abundance of literature related to the widespread COVID- 19 pandemic is beyond manual inspection of a single expert. Develop- ment of systems, capable of automatically processing tens of thousands of scientific publications with the aim to enrich existing empirical evidence with literature-based associations is challenging and relevant. We propose a system for contextualization of empirical expression data by approxi- mating relations between entities, for which representations were learned from one of the largest COVID-19-related literature corpora. In order to exploit a larger scientific context by transfer learning, we propose a novel embedding generation technique that leverages SciBERT language model pretrained on a large multi-domain corpus of scientific publications and fine-tuned for domain adaptation on the CORD-19 dataset. The con- ducted manual evaluation by the medical expert and the quantitative evaluation based on therapy targets identified in the related work suggest that the proposed method can be successfully employed for COVID-19 therapy target discovery and that it outperforms the baseline FastText arXiv:2007.15681v2 [cs.CL] 9 Nov 2020 method by a large margin. -
Supplementary Table 9. Functional Annotation Clustering Results for the Union (GS3) of the Top Genes from the SNP-Level and Gene-Based Analyses (See ST4)
Supplementary Table 9. Functional Annotation Clustering Results for the union (GS3) of the top genes from the SNP-level and Gene-based analyses (see ST4) Column Header Key Annotation Cluster Name of cluster, sorted by descending Enrichment score Enrichment Score EASE enrichment score for functional annotation cluster Category Pathway Database Term Pathway name/Identifier Count Number of genes in the submitted list in the specified term % Percentage of identified genes in the submitted list associated with the specified term PValue Significance level associated with the EASE enrichment score for the term Genes List of genes present in the term List Total Number of genes from the submitted list present in the category Pop Hits Number of genes involved in the specified term (category-specific) Pop Total Number of genes in the human genome background (category-specific) Fold Enrichment Ratio of the proportion of count to list total and population hits to population total Bonferroni Bonferroni adjustment of p-value Benjamini Benjamini adjustment of p-value FDR False Discovery Rate of p-value (percent form) Annotation Cluster 1 Enrichment Score: 3.8978262119731335 Category Term Count % PValue Genes List Total Pop Hits Pop Total Fold Enrichment Bonferroni Benjamini FDR GOTERM_CC_DIRECT GO:0005886~plasma membrane 383 24.33290978 5.74E-05 SLC9A9, XRCC5, HRAS, CHMP3, ATP1B2, EFNA1, OSMR, SLC9A3, EFNA3, UTRN, SYT6, ZNRF2, APP, AT1425 4121 18224 1.18857065 0.038655922 0.038655922 0.086284383 UP_KEYWORDS Membrane 626 39.77128335 1.53E-04 SLC9A9, HRAS, -
Human Methionine Aminopeptidase 2/ METAP2 Antibody Antigen Affinity-Purified Polyclonal Sheep Igg Catalog Number: AF3795
Human Methionine Aminopeptidase 2/ METAP2 Antibody Antigen Affinity-purified Polyclonal Sheep IgG Catalog Number: AF3795 DESCRIPTION Species Reactivity Human Specificity Detects human Methionine Aminopeptidase 2/METAP2 in direct ELISAs and Western blots. In direct ELISAs, less than 1% crossreactivity with recombinant human METAP1 is observed. Source Polyclonal Sheep IgG Purification Antigen Affinitypurified Immunogen S. frugiperda insect ovarian cell line Sf 21derived recombinant human Aminopeptidase 2/METAP2 Ala2Tyr478 Accession # P50579 Formulation Lyophilized from a 0.2 μm filtered solution in PBS with Trehalose. See Certificate of Analysis for details. *Small pack size (SP) is supplied either lyophilized or as a 0.2 μm filtered solution in PBS. APPLICATIONS Please Note: Optimal dilutions should be determined by each laboratory for each application. General Protocols are available in the Technical Information section on our website. Recommended Sample Concentration Western Blot 1 µg/mL See Below Immunoprecipitation 25 µg/mL Conditioned cell culture medium spiked with Recombinant Human Methionine Aminopeptidase 2/METAP2 (Catalog # 3795ZN), see our available Western blot detection antibodies DATA Western Blot Detection of Human Methionine Aminopeptidase 2 by Western Blot. Western blot shows lysates of COLO 205 human colorectal adenocarcinoma cell line, LS180 human colorectal adenocarcinoma cell line, and HT29 human colon adenocarcinoma cell line. PVDF membrane was probed with 1 µg/mL of Sheep Anti Human Methionine Aminopeptidase 2 Antigen Affinitypurified Polyclonal Antibody (Catalog # AF3795) followed by HRP conjugated AntiSheep IgG Secondary Antibody (Catalog # HAF016). A specific band was detected for Methionine Aminopeptidase 2 at approximately 70 kDa (as indicated). This experiment was conducted under reducing conditions and using Immunoblot Buffer Group 8. -
Development and Validation of a Protein-Based Risk Score for Cardiovascular Outcomes Among Patients with Stable Coronary Heart Disease
Supplementary Online Content Ganz P, Heidecker B, Hveem K, et al. Development and validation of a protein-based risk score for cardiovascular outcomes among patients with stable coronary heart disease. JAMA. doi: 10.1001/jama.2016.5951 eTable 1. List of 1130 Proteins Measured by Somalogic’s Modified Aptamer-Based Proteomic Assay eTable 2. Coefficients for Weibull Recalibration Model Applied to 9-Protein Model eFigure 1. Median Protein Levels in Derivation and Validation Cohort eTable 3. Coefficients for the Recalibration Model Applied to Refit Framingham eFigure 2. Calibration Plots for the Refit Framingham Model eTable 4. List of 200 Proteins Associated With the Risk of MI, Stroke, Heart Failure, and Death eFigure 3. Hazard Ratios of Lasso Selected Proteins for Primary End Point of MI, Stroke, Heart Failure, and Death eFigure 4. 9-Protein Prognostic Model Hazard Ratios Adjusted for Framingham Variables eFigure 5. 9-Protein Risk Scores by Event Type This supplementary material has been provided by the authors to give readers additional information about their work. Downloaded From: https://jamanetwork.com/ on 10/02/2021 Supplemental Material Table of Contents 1 Study Design and Data Processing ......................................................................................................... 3 2 Table of 1130 Proteins Measured .......................................................................................................... 4 3 Variable Selection and Statistical Modeling ........................................................................................ -
Common Genetic Aberrations Associated with Metabolic Interferences in Human Type-2 Diabetes and Acute Myeloid Leukemia: a Bioinformatics Approach
International Journal of Molecular Sciences Article Common Genetic Aberrations Associated with Metabolic Interferences in Human Type-2 Diabetes and Acute Myeloid Leukemia: A Bioinformatics Approach Theodora-Christina Kyriakou 1, Panagiotis Papageorgis 1,2 and Maria-Ioanna Christodoulou 3,* 1 Tumor Microenvironment, Metastasis and Experimental Therapeutics Laboratory, Basic and Translational Cancer Research Center, Department of Life Sciences, European University Cyprus, Nicosia 2404, Cyprus; [email protected] (T.-C.K.); [email protected] (P.P.) 2 European University Cyprus Research Center, Nicosia 2404, Cyprus 3 Tumor Immunology and Biomarkers Laboratory, Basic and Translational Cancer Research Center, Department of Life Sciences, European University Cyprus, Nicosia 2404, Cyprus * Correspondence: [email protected] Abstract: Type-2 diabetes mellitus (T2D) is a chronic metabolic disorder, associated with an increased risk of developing solid tumors and hematological malignancies, including acute myeloid leukemia (AML). However, the genetic background underlying this predisposition remains elusive. We herein aimed at the exploration of the genetic variants, related transcriptomic changes and disturbances in metabolic pathways shared by T2D and AML, utilizing bioinformatics tools and repositories, as well as publicly available clinical datasets. Our approach revealed that rs11709077 and rs1801282, on PPARG, rs11108094 on USP44, rs6685701 on RPS6KA1 and rs7929543 on AC118942.1 comprise Citation: Kyriakou, T.-C.; common SNPs susceptible to the two diseases and, together with 64 other co-inherited proxy SNPs, Papageorgis, P.; Christodoulou, M.-I. may affect the expression patterns of metabolic genes, such as USP44, METAP2, PPARG, TIMP4 and Common Genetic Aberrations RPS6KA1, in adipose tissue, skeletal muscle, liver, pancreas and whole blood. -
Osthole Attenuates APP-Induced Alzheimer's Disease Through Up-Regulating Mirna-101A-3P
Life Sciences 225 (2019) 117–131 Contents lists available at ScienceDirect Life Sciences journal homepage: www.elsevier.com/locate/lifescie Osthole attenuates APP-induced Alzheimer's disease through up-regulating T miRNA-101a-3p ⁎ Ying Lin1, Xicai Liang1, Yingjia Yao, Honghe Xiao, Yue Shi, Jingxian Yang Liaoning University of Traditional Chinese Medicine, Dalian, Liaoning 116600, China ARTICLE INFO ABSTRACT Keywords: Aim: Alzheimer's disease (AD) is a slowly progressing neurodegenerative disorder that attributed to the increase Alzheimer's disease of amyloid precursor protein (APP). Recently, evidence indicates that microRNA alterations are involved in the Osthole development of AD. In this paper, we demonstrated whether osthole could delay the occurrence of AD by Microarray regulating miRNA. MicroRNA-101a-3p Methods: Microarray was used to discover differential miRNAs in AD. The target genes regulated by miRNA were Amyloid precursor protein predicted by databases; The protective effects of osthole on APP/PS1 mice were determined by Morris Water Maze, H&E and Nissl staining; The APP-SH-SY5Y cells were transfected with miRNA-101a-3p inhibitor, the expression of miRNA-101a-3p and APP mRNA in APP/PS1 mice and APP-SH-SY5Y cells were detected by RT- PCR; And western blot and ICC staining were used to detect the APP and Aβ proteins expression. Key findings: MiRNA-101a-3p was the osthole-mediated miRNA in AD and APP is the target gene. Osthole could increase the learning and memory ability in APP/PS1 mice and inhibit APP mRNA/protein expression by up- regulating miRNA-101a-3p. For exploring the underlying mechanism, miR-101a-3p inhibitor was transfected into the APP-SH-SY5Y cells.