By IL-4 in Memory CD8 T Cells Negative Regulation of NKG2D
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PSPC1 Potentiates IGF1R Expression to Augment Cell Adhesion and Motility
1 Supplementary information 2 PSPC1 potentiates IGF1R expression to augment cell 3 adhesion and motility 4 Hsin-Wei Jen1,2 , De-Leung Gu 2, Yaw-Dong Lang 2 and Yuh-Shan Jou 1,2,* 5 1 Graduate Institute of Life Sciences, National Defense Medical Center, Taipei, Taiwan 6 2 Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan 7 * Author to whom correspondence should be addressed 8 Cells 2020, 9, x; doi: FOR PEER REVIEW www.mdpi.com/journal/cells Cells 2020, 9, x FOR PEER REVIEW 2 of 10 9 10 11 Supplementary Figure S1: Expression of IGF1R and integrin in PSPC1-expressing or PSPC1-depleted 12 HCC cells by Western blotting analysis 13 (A) Detection of IGF1R protein levels in three PSPC1-knockdown cells Huh7, HepG2 and Mahlavu. (B) 14 Detection of selected integrin expression in PSPC1-overexpressing or PSPC1-depleted HCC cells by using 15 their total cell lysates immunoblotted with specific integrin antibodies as shown. 16 17 18 Supplementary Figure S2: PSPC1-modulated IGF1R downstream signaling in HCC cells. Cells 2020, 9, x FOR PEER REVIEW 3 of 10 19 (A, B) Immunoblotting of IGF1R expression in PSPC1-overexpressing SK-Hep1 and PLC5 cells 20 treated with IGF1R shRNAs. (C, D) Cell migration and adhesion were measured in PSPC1- 21 knockdown Hep3B cells rescued with exogenous expression of IGF1R. Exogenous expression of 22 IGF1R in PSPC1-knockdown Hep3B cells were then applied for detection of altered AKT/ERK 23 signaling including (E) total PSPC1, IGF1R, AKT, ERK, p-IGF1R, p-AKT(S473), and 24 p-ERK(T202/Y204) as well as altered FAK/Src signaling including (F) total FAK, Src, p-FAK(Y397) 25 and p-Src(Y416) by immunoblotting assay. -
Analysis of Gene Expression Data for Gene Ontology
ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION A Thesis Presented to The Graduate Faculty of The University of Akron In Partial Fulfillment of the Requirements for the Degree Master of Science Robert Daniel Macholan May 2011 ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION Robert Daniel Macholan Thesis Approved: Accepted: _______________________________ _______________________________ Advisor Department Chair Dr. Zhong-Hui Duan Dr. Chien-Chung Chan _______________________________ _______________________________ Committee Member Dean of the College Dr. Chien-Chung Chan Dr. Chand K. Midha _______________________________ _______________________________ Committee Member Dean of the Graduate School Dr. Yingcai Xiao Dr. George R. Newkome _______________________________ Date ii ABSTRACT A tremendous increase in genomic data has encouraged biologists to turn to bioinformatics in order to assist in its interpretation and processing. One of the present challenges that need to be overcome in order to understand this data more completely is the development of a reliable method to accurately predict the function of a protein from its genomic information. This study focuses on developing an effective algorithm for protein function prediction. The algorithm is based on proteins that have similar expression patterns. The similarity of the expression data is determined using a novel measure, the slope matrix. The slope matrix introduces a normalized method for the comparison of expression levels throughout a proteome. The algorithm is tested using real microarray gene expression data. Their functions are characterized using gene ontology annotations. The results of the case study indicate the protein function prediction algorithm developed is comparable to the prediction algorithms that are based on the annotations of homologous proteins. -
Impact of Natural HIV-1 Nef Alleles and Polymorphisms on SERINC3/5 Downregulation
Impact of natural HIV-1 Nef alleles and polymorphisms on SERINC3/5 downregulation by Steven W. Jin B.Sc., Simon Fraser University, 2016 Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science in the Master of Science Program Faculty of Health Sciences © Steven W. Jin 2019 SIMON FRASER UNIVERSITY Spring 2019 Copyright in this work rests with the author. Please ensure that any reproduction or re-use is done in accordance with the relevant national copyright legislation. Approval Name: Steven W. Jin Degree: Master of Science Title: Impact of natural HIV-1 Nef alleles and polymorphisms on SERINC3/5 downregulation Examining Committee: Chair: Kanna Hayashi Assistant Professor Mark Brockman Senior Supervisor Associate Professor Masahiro Niikura Supervisor Associate Professor Ralph Pantophlet Supervisor Associate Professor Lisa Craig Examiner Professor Department of Molecular Biology and Biochemistry Date Defended/Approved: April 25, 2019 ii Ethics Statement iii Abstract HIV-1 Nef is a multifunctional accessory protein required for efficient viral pathogenesis. It was recently identified that the serine incorporators (SERINC) 3 and 5 are host restriction factors that decrease the infectivity of HIV-1 when incorporated into newly formed virions. However, Nef counteracts these effects by downregulating SERINC from the cell surface. Currently, there lacks a comprehensive study investigating the impact of primary Nef alleles on SERINC downregulation, as most studies to date utilize lab- adapted or reference HIV strains. In this thesis, I characterized and compared SERINC downregulation from >400 Nef alleles isolated from patients with distinct clinical outcomes and subtypes. I found that primary Nef alleles displayed a dynamic range of SERINC downregulation abilities, thus allowing naturally-occurring polymorphisms that modulate this activity to be identified. -
Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model
Downloaded from http://www.jimmunol.org/ by guest on September 25, 2021 T + is online at: average * The Journal of Immunology , 34 of which you can access for free at: 2016; 197:1477-1488; Prepublished online 1 July from submission to initial decision 4 weeks from acceptance to publication 2016; doi: 10.4049/jimmunol.1600589 http://www.jimmunol.org/content/197/4/1477 Molecular Profile of Tumor-Specific CD8 Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. Waugh, Sonia M. Leach, Brandon L. Moore, Tullia C. Bruno, Jonathan D. Buhrman and Jill E. Slansky J Immunol cites 95 articles Submit online. Every submission reviewed by practicing scientists ? is published twice each month by Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts http://jimmunol.org/subscription Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html http://www.jimmunol.org/content/suppl/2016/07/01/jimmunol.160058 9.DCSupplemental This article http://www.jimmunol.org/content/197/4/1477.full#ref-list-1 Information about subscribing to The JI No Triage! Fast Publication! Rapid Reviews! 30 days* Why • • • Material References Permissions Email Alerts Subscription Supplementary The Journal of Immunology 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. This information is current as of September 25, 2021. The Journal of Immunology Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. -
Novel Association of Hypertrophic Cardiomyopathy, Sensorineural Deafness, and a Mutation in Unconventional Myosin VI (MYO6)
309 LETTER TO JMG J Med Genet: first published as 10.1136/jmg.2003.011973 on 1 April 2004. Downloaded from Novel association of hypertrophic cardiomyopathy, sensorineural deafness, and a mutation in unconventional myosin VI (MYO6) S A Mohiddin, Z M Ahmed, A J Griffith, D Tripodi, T B Friedman, L Fananapazir, R J Morell ............................................................................................................................... J Med Genet 2004;41:309–314. doi: 10.1136/jmg.2003.011973 amilial hypertrophic cardiomyopathy (FHC) is typically Key points characterised by left ventricular hypertrophy, diastolic Fdysfunction, and hypercontractility, and is often asso- ciated with disabling symptoms, arrhythmias, and sudden N Familial hypertrophic cardiomyopathy (FHC) is typi- death.1 FHC shows both non-allelic and allelic genetic cally confined to a cardiac phenotype and is caused by heterogeneity, and results from any one of more than 100 mutations in genes encoding sarcomeric proteins. mutations in genes encoding sarcomeric proteins.2 Identified Occasionally FHC may be one component of a genes include those encoding b myosin heavy chain, the hereditary multisystem disorder. myosin regulatory and essential light chains, myosin bind- N Sensorineural hearing loss is genetically heteroge- ing protein C, troponin I, troponin C, a cardiac actin, and neous. Mutations in the MYO6 gene, encoding 23 titin. The FHC phenotype is characterised by hypertrophy, unconventional myosin VI, have been found to cause myocyte disarray and fibrosis, and results from the dominant non-syndromic sensorineural hearing loss—that is, negative expression of one of these (mainly missense) sensorineural hearing loss in the absence of any other mutations. The resulting sarcomeric dysfunction leads related clinical features. ultimately, through mechanisms that remain obscure, to pathological left ventricular remodelling. -
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. -
Identification and Validation of a Blood-Based 18-Gene Expression Signature in Colorectal Cancer
Published OnlineFirst March 27, 2013; DOI: 10.1158/1078-0432.CCR-12-3851 Clinical Cancer Imaging, Diagnosis, Prognosis Research Identification and Validation of a Blood-Based 18-Gene Expression Signature in Colorectal Cancer Ye Xu1,4, Qinghua Xu1,6,7, Li Yang1,4, Xun Ye6,7, Fang Liu6,7, Fei Wu6,7, Shujuan Ni1,2,3,5, Cong Tan1,2,3,5, Guoxiang Cai1,4, Xia Meng6,7, Sanjun Cai1,4, and Xiang Du1,2,3,5 Abstract Purpose: The early detection of colorectal cancer (CRC) is crucial for successful treatment and patient survival. However, compliance with current screening methods remains poor. This study aimed to identify an accurate blood-based gene expression signature for CRC detection. Experimental Design: Gene expression in peripheral blood samples from 216 patients with CRC tumors and 187 controls was investigated in the study.Wefirstconductedamicroarrayanalysistoselect candidate genes that were significantly differentially expressed between patients with cancer and con- trols. A quantitative reverse transcription PCR assay was then used to evaluate the expression of selected genes. A gene expression signature was identified using a training set (n ¼ 200) and then validated using an independent test set (n ¼ 160). Results: We identified an 18-gene signature that discriminated the patients with CRC from controls with 92% accuracy, 91% sensitivity, and 92% specificity. The signature performance was further validated in the independent test set with 86% accuracy, 84% sensitivity, and 88% specificity. The area under the receiver operating characteristics curve was 0.94. The signature was shown to be enriched in genes related to immune functions. Conclusions: This study identified an 18-gene signature that accurately discriminated patients with CRC from controls in peripheral blood samples. -
Dynamics of the Linc Complex
DYNAMICS OF THE LINC COMPLEX Loic Gazquez University of Manchester School of Biological Sciences 2017 A thesis submitted to the University of Manchester for the degree of Doctor of Philosophy in the Faculty of Biology, Medicine and Health TABLE OF CONTENTS Table of Contents .................................................................................................................................... 2 Abstract.................................................................................................................................................... 4 Declaration .............................................................................................................................................. 5 Copyright statement ................................................................................................................................ 5 Acknowledgements ................................................................................................................................. 6 I. Introduction .................................................................................................................................. 7 Nuclear Envelope and the LINC complex ................................................................................... 7 I. 1.1. The first LINC component: the SUN ................................................................................ 8 I. 1.2. The second LINC component: the KASH ........................................................................ 8 I. 1.1. Structure -
UNIVERSITY of CALIFORNIA Los Angeles
UNIVERSITY OF CALIFORNIA Los Angeles Integrating molecular phenotypes and gene expression to characterize DNA variants for cardiometabolic traits A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Human Genetics by Alejandra Rodriguez 2018 ABSTRACT OF THE DISSERTATION Integrating molecular phenotypes and gene expression to characterize DNA variants for cardiometabolic traits by Alejandra Rodriguez Doctor of Philosophy in Human Genetics University of California, Los Angeles, 2018 Professor Päivi Elisabeth Pajukanta, Chair In-depth understanding of cardiovascular disease etiology requires characterization of its genetic, environmental, and molecular architecture. Genetic architecture can be defined as the characteristics of genetic variation responsible for broad-sense phenotypic heritability. Massively parallel sequencing has generated thousands of genomic datasets in diverse human tissues. Integration of such datasets using data mining methods has been used to extract biological meaning and has significantly advanced our understanding of the genome-wide nucleotide sequence, its regulatory elements, and overall chromatin architecture. This dissertation presents integration of “omics” data sets to understand the genetic architecture and molecular mechanisms of cardiovascular lipid disorders (further reviewed in Chapter 1). In 2013, Daphna Weissglas-Volkov and coworkers1 published an association between the chromosome 18q11.2 genomic region and hypertriglyceridemia in a genome-wide -
Supplemental Table 1. Complete Gene Lists and GO Terms from Figure 3C
Supplemental Table 1. Complete gene lists and GO terms from Figure 3C. Path 1 Genes: RP11-34P13.15, RP4-758J18.10, VWA1, CHD5, AZIN2, FOXO6, RP11-403I13.8, ARHGAP30, RGS4, LRRN2, RASSF5, SERTAD4, GJC2, RHOU, REEP1, FOXI3, SH3RF3, COL4A4, ZDHHC23, FGFR3, PPP2R2C, CTD-2031P19.4, RNF182, GRM4, PRR15, DGKI, CHMP4C, CALB1, SPAG1, KLF4, ENG, RET, GDF10, ADAMTS14, SPOCK2, MBL1P, ADAM8, LRP4-AS1, CARNS1, DGAT2, CRYAB, AP000783.1, OPCML, PLEKHG6, GDF3, EMP1, RASSF9, FAM101A, STON2, GREM1, ACTC1, CORO2B, FURIN, WFIKKN1, BAIAP3, TMC5, HS3ST4, ZFHX3, NLRP1, RASD1, CACNG4, EMILIN2, L3MBTL4, KLHL14, HMSD, RP11-849I19.1, SALL3, GADD45B, KANK3, CTC- 526N19.1, ZNF888, MMP9, BMP7, PIK3IP1, MCHR1, SYTL5, CAMK2N1, PINK1, ID3, PTPRU, MANEAL, MCOLN3, LRRC8C, NTNG1, KCNC4, RP11, 430C7.5, C1orf95, ID2-AS1, ID2, GDF7, KCNG3, RGPD8, PSD4, CCDC74B, BMPR2, KAT2B, LINC00693, ZNF654, FILIP1L, SH3TC1, CPEB2, NPFFR2, TRPC3, RP11-752L20.3, FAM198B, TLL1, CDH9, PDZD2, CHSY3, GALNT10, FOXQ1, ATXN1, ID4, COL11A2, CNR1, GTF2IP4, FZD1, PAX5, RP11-35N6.1, UNC5B, NKX1-2, FAM196A, EBF3, PRRG4, LRP4, SYT7, PLBD1, GRASP, ALX1, HIP1R, LPAR6, SLITRK6, C16orf89, RP11-491F9.1, MMP2, B3GNT9, NXPH3, TNRC6C-AS1, LDLRAD4, NOL4, SMAD7, HCN2, PDE4A, KANK2, SAMD1, EXOC3L2, IL11, EMILIN3, KCNB1, DOK5, EEF1A2, A4GALT, ADGRG2, ELF4, ABCD1 Term Count % PValue Genes regulation of pathway-restricted GDF3, SMAD7, GDF7, BMPR2, GDF10, GREM1, BMP7, LDLRAD4, SMAD protein phosphorylation 9 6.34 1.31E-08 ENG pathway-restricted SMAD protein GDF3, SMAD7, GDF7, BMPR2, GDF10, GREM1, BMP7, LDLRAD4, phosphorylation -
Mouse Tnik Conditional Knockout Project (CRISPR/Cas9)
https://www.alphaknockout.com Mouse Tnik Conditional Knockout Project (CRISPR/Cas9) Objective: To create a Tnik conditional knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Tnik gene (NCBI Reference Sequence: NM_026910 ; Ensembl: ENSMUSG00000027692 ) is located on Mouse chromosome 3. 33 exons are identified, with the ATG start codon in exon 1 and the TAA stop codon in exon 33 (Transcript: ENSMUST00000160307). Exon 7 will be selected as conditional knockout region (cKO region). Deletion of this region should result in the loss of function of the Mouse Tnik gene. To engineer the targeting vector, homologous arms and cKO region will be generated by PCR using BAC clone RP23-433L13 as template. Cas9, gRNA and targeting vector will be co-injected into fertilized eggs for cKO Mouse production. The pups will be genotyped by PCR followed by sequencing analysis. Note: Mice homozygous for a knock-out allele exhibit impaired postsynaptic signaling and cognitive function. Exon 7 starts from about 12.48% of the coding region. The knockout of Exon 7 will result in frameshift of the gene. The size of intron 6 for 5'-loxP site insertion: 2463 bp, and the size of intron 7 for 3'-loxP site insertion: 12829 bp. The size of effective cKO region: ~631 bp. The cKO region does not have any other known gene. Page 1 of 8 https://www.alphaknockout.com Overview of the Targeting Strategy Wildtype allele gRNA region 5' gRNA region 3' 1 7 33 Targeting vector Targeted allele Constitutive KO allele (After Cre recombination) Legends Exon of mouse Tnik Homology arm cKO region loxP site Page 2 of 8 https://www.alphaknockout.com Overview of the Dot Plot Window size: 10 bp Forward Reverse Complement Sequence 12 Note: The sequence of homologous arms and cKO region is aligned with itself to determine if there are tandem repeats. -
Microarray‑Based Identification of Nerve Growth‑Promoting Genes in Neurofibromatosis Type I
192 MOLECULAR MEDICINE REPORTS 9: 192-196, 2014 Microarray‑based identification of nerve growth‑promoting genes in neurofibromatosis type I YUFEI LIU1*, DONG KANG2*, CHUNYAN LI3, GUANG XU4, YAN TAN5 and JINHONG WANG6 1Department of Pediatric Intensive Care Unit, The First Affiliated Hospital of Jilin University, Changchun, Jilin 130000; 2Huiqiao Department, South Hospital of Southern Medical University, Guangdong 510630; Departments of 3Pediatric Respiratory and 4Infectious Diseases, The First Affiliated Hospital of Jilin University; 5Cancer Biotherapy Center, People's Hospital of Jilin Province, Changchun, Jilin 130000; 6Department of Respiratory, The Third Affiliated Hospital of Southern Medical University, Guangzhou, Guangdong 510630, P.R. China Received May 16, 2013; Accepted October 29, 2013 DOI: 10.3892/mmr.2013.1785 Abstract. As a genetic disease, neurofibromatosis patients, target molecules contributing to nerve growth during type 1 (NF1) is characterized by abnormalities in multiple NF1 development were investigated, which aided in improving tissues derived from the neural crest, including neoplasms in our understanding of this disease, and may provide a novel the ends of the limbs. The exact mechanism of nerve growth direction for nerve repair and regeneration. in NF1 is unclear. In the present study, the gene expression profile of nerves in healthy controls and NF1 patients with Introduction macrodactylia of the fingers or toes were analyzed in order to identify possible genes associated with nerve growth. The Neurofibromatosis is characterized by café-au-lait spots, Whole Human Genome Microarray was selected to screen for iris Lisch nodules and cutaneous or subcutaneous skin different gene expression profiles, and the result was analyzed tumors termedneurofibromas (1).