Hnrnp K Co-Immunoprecipitated Transcripts Regulated
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Figure 2S 4 7 A - C 080125 CSCs 080418 CSCs - + IFN-a 48 h + IFN-a 48 h + IFN-a 72 h 6 + IFN-a 72 h 3 5 MRFI 4 2 3 2 1 1 0 0 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 7 B 13 080125 FBS - D 080418 FBS - + IFN-a 48 h 12 + IFN-a 48 h + IFN-a 72 h + IFN-a 72 h 6 080125 FBS 11 10 5 9 8 4 7 6 3 MRFI 5 4 2 3 2 1 1 0 0 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 Molecule Molecule FIGURE 4S FIGURE 5S Panel A Panel B FIGURE 6S A B C D Supplemental Results Table 1S. Modulation by IFN-α of APM in GBM CSC and FBS tumor cell lines. Molecule * Cell line IFN-α‡ HLA β2-m# HLA LMP TAP1 TAP2 class II A A HC§ 2 7 10 080125 CSCs - 1∞ (1) 3 (65) 2 (91) 1 (2) 6 (47) 2 (61) 1 (3) 1 (2) 1 (3) + 2 (81) 11 (80) 13 (99) 1 (3) 8 (88) 4 (91) 1 (2) 1 (3) 2 (68) 080125 FBS - 2 (81) 4 (63) 4 (83) 1 (3) 6 (80) 3 (67) 2 (86) 1 (3) 2 (75) + 2 (99) 14 (90) 7 (97) 5 (75) 7 (100) 6 (98) 2 (90) 1 (4) 3 (87) 080418 CSCs - 2 (51) 1 (1) 1 (3) 2 (47) 2 (83) 2 (54) 1 (4) 1 (2) 1 (3) + 2 (81) 3 (76) 5 (75) 2 (50) 2 (83) 3 (71) 1 (3) 2 (87) 1 (2) 080418 FBS - 1 (3) 3 (70) 2 (88) 1 (4) 3 (87) 2 (76) 1 (3) 1 (3) 1 (2) + 2 (78) 7 (98) 5 (99) 2 (94) 5 (100) 3 (100) 1 (4) 2 (100) 1 (2) 070104 CSCs - 1 (2) 1 (3) 1 (3) 2 (78) 1 (3) 1 (2) 1 (3) 1 (3) 1 (2) + 2 (98) 8 (100) 10 (88) 4 (89) 3 (98) 3 (94) 1 (4) 2 (86) 2 (79) * expression of APM molecules was evaluated by intracellular staining and cytofluorimetric analysis; ‡ cells were treatead or not (+/-) for 72 h with 1000 IU/ml of IFN-α; # β-2 microglobulin; § β-2 microglobulin-free HLA-A heavy chain; ∞ values are indicated as ratio between the mean of fluorescence intensity of cells stained with the selected mAb and that of the negative control; bold values indicate significant MRFI (≥ 2). -
Strategies to Increase ß-Cell Mass Expansion
This electronic thesis or dissertation has been downloaded from the King’s Research Portal at https://kclpure.kcl.ac.uk/portal/ Strategies to increase -cell mass expansion Drynda, Robert Lech Awarding institution: King's College London The copyright of this thesis rests with the author and no quotation from it or information derived from it may be published without proper acknowledgement. END USER LICENCE AGREEMENT Unless another licence is stated on the immediately following page this work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International licence. https://creativecommons.org/licenses/by-nc-nd/4.0/ You are free to copy, distribute and transmit the work Under the following conditions: Attribution: You must attribute the work in the manner specified by the author (but not in any way that suggests that they endorse you or your use of the work). Non Commercial: You may not use this work for commercial purposes. No Derivative Works - You may not alter, transform, or build upon this work. Any of these conditions can be waived if you receive permission from the author. Your fair dealings and other rights are in no way affected by the above. Take down policy If you believe that this document 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 Strategies to increase β-cell mass expansion A thesis submitted by Robert Drynda For the degree of Doctor of Philosophy from King’s College London Diabetes Research Group Division of Diabetes & Nutritional Sciences Faculty of Life Sciences & Medicine King’s College London 2017 Table of contents Table of contents ................................................................................................. -
Correct Setup of the Substantia Nigra Requires Reelin-Mediated Fast, Laterally- Directed Migration of Dopaminergic Neurons
RESEARCH ARTICLE Correct setup of the substantia nigra requires Reelin-mediated fast, laterally- directed migration of dopaminergic neurons Ankita Ravi Vaswani1, Beatrice Weykopf2†, Cathleen Hagemann1, Hans-Ulrich Fried3, Oliver Bru¨ stle2, Sandra Blaess1* 1Neurodevelopmental Genetics, Institute of Reconstructive Neurobiology, University of Bonn School of Medicine & University Hospital Bonn, Bonn, Germany; 2Institute of Reconstructive Neurobiology, University of Bonn School of Medicine & University Hospital Bonn, Bonn, Germany; 3Light Microscope Facility, German Center for Neurodegenerative Diseases, Bonn, Germany Abstract Midbrain dopaminergic (mDA) neurons migrate to form the laterally-located substantia nigra pars compacta (SN) and medially-located ventral tegmental area (VTA), but little is known about the underlying cellular and molecular processes. Here we visualize the dynamic cell morphologies of tangentially migrating SN-mDA neurons in 3D and identify two distinct migration modes. Slow migration is the default mode in SN-mDA neurons, while fast, laterally-directed *For correspondence: migration occurs infrequently and is strongly associated with bipolar cell morphology. Tangential [email protected] migration of SN-mDA neurons is altered in absence of Reelin signaling, but it is unclear whether Reelin acts directly on migrating SN-mDA neurons and how it affects their cell morphology and † Present address: Precision migratory behavior. By specifically inactivating Reelin signaling in mDA neurons we demonstrate its Neurology Program & Advanced direct role in SN-mDA tangential migration. Reelin promotes laterally-biased movements in mDA Center for Parkinson’s Disease neurons during their slow migration mode, stabilizes leading process morphology and increases the Research, Harvard Medical School and Brigham & Women’s probability of fast, laterally-directed migration. -
Watsonjn2018.Pdf (1.780Mb)
UNIVERSITY OF CENTRAL OKLAHOMA Edmond, Oklahoma Department of Biology Investigating Differential Gene Expression in vivo of Cardiac Birth Defects in an Avian Model of Maternal Phenylketonuria A THESIS SUBMITTED TO THE GRADUATE FACULTY In partial fulfillment of the requirements For the degree of MASTER OF SCIENCE IN BIOLOGY By Jamie N. Watson Edmond, OK June 5, 2018 J. Watson/Dr. Nikki Seagraves ii J. Watson/Dr. Nikki Seagraves Acknowledgements It is difficult to articulate the amount of gratitude I have for the support and encouragement I have received throughout my master’s thesis. Many people have added value and support to my life during this time. I am thankful for the education, experience, and friendships I have gained at the University of Central Oklahoma. First, I would like to thank Dr. Nikki Seagraves for her mentorship and friendship. I lucked out when I met her. I have enjoyed working on this project and I am very thankful for her support. I would like thank Thomas Crane for his support and patience throughout my master’s degree. I would like to thank Dr. Shannon Conley for her continued mentorship and support. I would like to thank Liz Bullen and Dr. Eric Howard for their training and help on this project. I would like to thank Kristy Meyer for her friendship and help throughout graduate school. I would like to thank my committee members Dr. Robert Brennan and Dr. Lilian Chooback for their advisement on this project. Also, I would like to thank the biology faculty and staff. I would like to thank the Seagraves lab members: Jailene Canales, Kayley Pate, Mckayla Muse, Grace Thetford, Kody Harvey, Jordan Guffey, and Kayle Patatanian for their hard work and support. -
The Ski Oncoprotein Interacts with Skip, the Human Homolog of Drosophila Bx42
Oncogene (1998) 16, 1579 ± 1586 1998 Stockton Press All rights reserved 0950 ± 9232/98 $12.00 The Ski oncoprotein interacts with Skip, the human homolog of Drosophila Bx42 Richard Dahl, Bushra Wani and Michael J Hayman Department of Microbiology, State University of New York, Stony Brook, New York 11794, USA The v-Ski avian retroviral oncogene is postulated to act Little is known about how Ski functions. Both the as a transcription factor. Since protein ± protein interac- cellular and the viral genes share transforming and tions have been shown to play an important role in the muscle inducing ability. Ski localizes to the nucleus and transcription process, we attempted to identify Ski is observed to associate with chromatin (Barkas et al., protein partners with the yeast two-hybrid system. Using 1986; Sutrave et al., 1990a). Because of its nuclear v-Ski sequence as bait, the human gene skip (Ski localization and its ability to induce expression of Interacting Protein) was identi®ed as encoding a protein muscle speci®c genes in quail cells (Colmenares and which interacts with both the cellular and viral forms of Stavnezer, 1989), Ski has been assumed to be a Ski in the two-hybrid system. Skip is highly homologous transcription factor. Consistent with this assumption, to the Drosophila melanogaster protein Bx42 which is c-Ski has been shown to bind DNA in vitro with the found associated with chromatin in transcriptionally help of an unknown protein factor (Nagase et al., active pus of salivary glands. The Ski-Skip interaction 1990), and has been recently shown to enhance MyoD is potentially important in Ski's transforming activity dependent transactivation of a myosin light chain since Skip was demonstrated to interact with a highly enhancer linked reporter gene in muscle cells (Engert conserved region of Ski required for transforming et al., 1995). -
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. -
A CRISPR-Cas9–Engineered Mouse Model for GPI-Anchor Deficiency Mirrors Human Phenotypes and Exhibits Hippocampal Synaptic Dysfunctions
A CRISPR-Cas9–engineered mouse model for GPI-anchor deficiency mirrors human phenotypes and exhibits hippocampal synaptic dysfunctions Miguel Rodríguez de los Santosa,b,c,d, Marion Rivalane,f, Friederike S. Davidd,g, Alexander Stumpfh, Julika Pitschi,j, Despina Tsortouktzidisi, Laura Moreno Velasquezh, Anne Voigth, Karl Schillingk, Daniele Matteil, Melissa Longe,f, Guido Vogta,c, Alexej Knausd, Björn Fischer-Zirnsaka,c, Lars Wittlerm, Bernd Timmermannn, Peter N. Robinsono,p, Denise Horna, Stefan Mundlosa,c, Uwe Kornaka,c,q, Albert J. Beckeri, Dietmar Schmitzh, York Wintere,f, and Peter M. Krawitzd,1 aInstitute for Medical Genetics and Human Genetics, Charité–Universitätsmedizin Berlin, 13353 Berlin, Germany; bBerlin-Brandenburg School for Regenerative Therapies, Charité-Universitätsmedizin Berlin, 13353 Berlin, Germany; cResearch Group Development and Disease, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany; dInstitute for Genomic Statistics and Bioinformatics, University of Bonn, 53127 Bonn, Germany; eAnimal Outcome Core Facility of the NeuroCure Center, Charité–Universitätsmedizin Berlin, 10117 Berlin, Germany; fInstitute of Cognitive Neurobiology, Humboldt University, 10117 Berlin, Germany; gInstitute of Human Genetics, Faculty of Medicine, University Hospital Bonn, 53127 Bonn, Germany; hNeuroscience Research Center, Charité–Universitätsmedizin Berlin, 10117 Berlin, Germany; iSection for Translational Epilepsy Research, Department of Neuropathology, University Hospital Bonn, 53127 Bonn, Germany; jDepartment of Epileptology, -
An Automated Pipeline for Inferring Variant-Driven Gene
www.nature.com/scientificreports OPEN MAGPEL: an autoMated pipeline for inferring vAriant‑driven Gene PanEls from the full‑length biomedical literature Nafseh Saberian1, Adib Shaf 1, Azam Peyvandipour1 & Sorin Draghici 1,2* In spite of the eforts in developing and maintaining accurate variant databases, a large number of disease‑associated variants are still hidden in the biomedical literature. Curation of the biomedical literature in an efort to extract this information is a challenging task due to: (i) the complexity of natural language processing, (ii) inconsistent use of standard recommendations for variant description, and (iii) the lack of clarity and consistency in describing the variant-genotype-phenotype associations in the biomedical literature. In this article, we employ text mining and word cloud analysis techniques to address these challenges. The proposed framework extracts the variant- gene‑disease associations from the full‑length biomedical literature and designs an evidence‑based variant-driven gene panel for a given condition. We validate the identifed genes by showing their diagnostic abilities to predict the patients’ clinical outcome on several independent validation cohorts. As representative examples, we present our results for acute myeloid leukemia (AML), breast cancer and prostate cancer. We compare these panels with other variant‑driven gene panels obtained from Clinvar, Mastermind and others from literature, as well as with a panel identifed with a classical diferentially expressed genes (DEGs) approach. The results show that the panels obtained by the proposed framework yield better results than the other gene panels currently available in the literature. One crucial step in understanding the biological mechanism underlying a disease condition is to capture the relationship between the variants and the disease risk1. -
Genome-Wide DNA Methylation Analysis of KRAS Mutant Cell Lines Ben Yi Tew1,5, Joel K
www.nature.com/scientificreports OPEN Genome-wide DNA methylation analysis of KRAS mutant cell lines Ben Yi Tew1,5, Joel K. Durand2,5, Kirsten L. Bryant2, Tikvah K. Hayes2, Sen Peng3, Nhan L. Tran4, Gerald C. Gooden1, David N. Buckley1, Channing J. Der2, Albert S. Baldwin2 ✉ & Bodour Salhia1 ✉ Oncogenic RAS mutations are associated with DNA methylation changes that alter gene expression to drive cancer. Recent studies suggest that DNA methylation changes may be stochastic in nature, while other groups propose distinct signaling pathways responsible for aberrant methylation. Better understanding of DNA methylation events associated with oncogenic KRAS expression could enhance therapeutic approaches. Here we analyzed the basal CpG methylation of 11 KRAS-mutant and dependent pancreatic cancer cell lines and observed strikingly similar methylation patterns. KRAS knockdown resulted in unique methylation changes with limited overlap between each cell line. In KRAS-mutant Pa16C pancreatic cancer cells, while KRAS knockdown resulted in over 8,000 diferentially methylated (DM) CpGs, treatment with the ERK1/2-selective inhibitor SCH772984 showed less than 40 DM CpGs, suggesting that ERK is not a broadly active driver of KRAS-associated DNA methylation. KRAS G12V overexpression in an isogenic lung model reveals >50,600 DM CpGs compared to non-transformed controls. In lung and pancreatic cells, gene ontology analyses of DM promoters show an enrichment for genes involved in diferentiation and development. Taken all together, KRAS-mediated DNA methylation are stochastic and independent of canonical downstream efector signaling. These epigenetically altered genes associated with KRAS expression could represent potential therapeutic targets in KRAS-driven cancer. Activating KRAS mutations can be found in nearly 25 percent of all cancers1. -
Mutations in SKI in Shprintzen–Goldberg Syndrome Lead to Attenuated TGF-B Responses Through SKI Stabilization
RESEARCH ARTICLE Mutations in SKI in Shprintzen–Goldberg syndrome lead to attenuated TGF-b responses through SKI stabilization Ilaria Gori1, Roger George2, Andrew G Purkiss2, Stephanie Strohbuecker3, Rebecca A Randall1, Roksana Ogrodowicz2, Virginie Carmignac4, Laurence Faivre4, Dhira Joshi5, Svend Kjær2, Caroline S Hill1* 1Developmental Signalling Laboratory, The Francis Crick Institute, London, United Kingdom; 2Structural Biology Facility, The Francis Crick Institute, London, United Kingdom; 3Bioinformatics and Biostatistics Facility, The Francis Crick Institute, London, United Kingdom; 4INSERM - Universite´ de Bourgogne UMR1231 GAD, FHU-TRANSLAD, Dijon, France; 5Peptide Chemistry Facility, The Francis Crick Institute, London, United Kingdom Abstract Shprintzen–Goldberg syndrome (SGS) is a multisystemic connective tissue disorder, with considerable clinical overlap with Marfan and Loeys–Dietz syndromes. These syndromes have commonly been associated with enhanced TGF-b signaling. In SGS patients, heterozygous point mutations have been mapped to the transcriptional co-repressor SKI, which is a negative regulator of TGF-b signaling that is rapidly degraded upon ligand stimulation. The molecular consequences of these mutations, however, are not understood. Here we use a combination of structural biology, genome editing, and biochemistry to show that SGS mutations in SKI abolish its binding to phosphorylated SMAD2 and SMAD3. This results in stabilization of SKI and consequently attenuation of TGF-b responses, both in knockin cells expressing an SGS mutation and in fibroblasts from SGS patients. Thus, we reveal that SGS is associated with an attenuation of TGF-b- *For correspondence: induced transcriptional responses, and not enhancement, which has important implications for [email protected] other Marfan-related syndromes. Competing interests: The authors declare that no competing interests exist. -
SUPPLEMENTARY MATERIAL Bone Morphogenetic Protein 4 Promotes
www.intjdevbiol.com doi: 10.1387/ijdb.160040mk SUPPLEMENTARY MATERIAL corresponding to: Bone morphogenetic protein 4 promotes craniofacial neural crest induction from human pluripotent stem cells SUMIYO MIMURA, MIKA SUGA, KAORI OKADA, MASAKI KINEHARA, HIROKI NIKAWA and MIHO K. FURUE* *Address correspondence to: Miho Kusuda Furue. Laboratory of Stem Cell Cultures, National Institutes of Biomedical Innovation, Health and Nutrition, 7-6-8, Saito-Asagi, Ibaraki, Osaka 567-0085, Japan. Tel: 81-72-641-9819. Fax: 81-72-641-9812. E-mail: [email protected] Full text for this paper is available at: http://dx.doi.org/10.1387/ijdb.160040mk TABLE S1 PRIMER LIST FOR QRT-PCR Gene forward reverse AP2α AATTTCTCAACCGACAACATT ATCTGTTTTGTAGCCAGGAGC CDX2 CTGGAGCTGGAGAAGGAGTTTC ATTTTAACCTGCCTCTCAGAGAGC DLX1 AGTTTGCAGTTGCAGGCTTT CCCTGCTTCATCAGCTTCTT FOXD3 CAGCGGTTCGGCGGGAGG TGAGTGAGAGGTTGTGGCGGATG GAPDH CAAAGTTGTCATGGATGACC CCATGGAGAAGGCTGGGG MSX1 GGATCAGACTTCGGAGAGTGAACT GCCTTCCCTTTAACCCTCACA NANOG TGAACCTCAGCTACAAACAG TGGTGGTAGGAAGAGTAAAG OCT4 GACAGGGGGAGGGGAGGAGCTAGG CTTCCCTCCAACCAGTTGCCCCAAA PAX3 TTGCAATGGCCTCTCAC AGGGGAGAGCGCGTAATC PAX6 GTCCATCTTTGCTTGGGAAA TAGCCAGGTTGCGAAGAACT p75 TCATCCCTGTCTATTGCTCCA TGTTCTGCTTGCAGCTGTTC SOX9 AATGGAGCAGCGAAATCAAC CAGAGAGATTTAGCACACTGATC SOX10 GACCAGTACCCGCACCTG CGCTTGTCACTTTCGTTCAG Suppl. Fig. S1. Comparison of the gene expression profiles of the ES cells and the cells induced by NC and NC-B condition. Scatter plots compares the normalized expression of every gene on the array (refer to Table S3). The central line -
HCC and Cancer Mutated Genes Summarized in the Literature Gene Symbol Gene Name References*
HCC and cancer mutated genes summarized in the literature Gene symbol Gene name References* A2M Alpha-2-macroglobulin (4) ABL1 c-abl oncogene 1, receptor tyrosine kinase (4,5,22) ACBD7 Acyl-Coenzyme A binding domain containing 7 (23) ACTL6A Actin-like 6A (4,5) ACTL6B Actin-like 6B (4) ACVR1B Activin A receptor, type IB (21,22) ACVR2A Activin A receptor, type IIA (4,21) ADAM10 ADAM metallopeptidase domain 10 (5) ADAMTS9 ADAM metallopeptidase with thrombospondin type 1 motif, 9 (4) ADCY2 Adenylate cyclase 2 (brain) (26) AJUBA Ajuba LIM protein (21) AKAP9 A kinase (PRKA) anchor protein (yotiao) 9 (4) Akt AKT serine/threonine kinase (28) AKT1 v-akt murine thymoma viral oncogene homolog 1 (5,21,22) AKT2 v-akt murine thymoma viral oncogene homolog 2 (4) ALB Albumin (4) ALK Anaplastic lymphoma receptor tyrosine kinase (22) AMPH Amphiphysin (24) ANK3 Ankyrin 3, node of Ranvier (ankyrin G) (4) ANKRD12 Ankyrin repeat domain 12 (4) ANO1 Anoctamin 1, calcium activated chloride channel (4) APC Adenomatous polyposis coli (4,5,21,22,25,28) APOB Apolipoprotein B [including Ag(x) antigen] (4) AR Androgen receptor (5,21-23) ARAP1 ArfGAP with RhoGAP domain, ankyrin repeat and PH domain 1 (4) ARHGAP35 Rho GTPase activating protein 35 (21) ARID1A AT rich interactive domain 1A (SWI-like) (4,5,21,22,24,25,27,28) ARID1B AT rich interactive domain 1B (SWI1-like) (4,5,22) ARID2 AT rich interactive domain 2 (ARID, RFX-like) (4,5,22,24,25,27,28) ARID4A AT rich interactive domain 4A (RBP1-like) (28) ARID5B AT rich interactive domain 5B (MRF1-like) (21) ASPM Asp (abnormal