Mouse Population-Guided Resequencing Reveals That Variants in CD44 Contribute to Acetaminophen-Induced Liver Injury in Humans
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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. -
FHL3 Contributes to EMT and Chemotherapy Resistance Through Inhibiting Ubiquitination of Slug and Activating Tgfβ/Smad-Independent Pathways in Gastric Cancer
FHL3 Contributes to EMT and Chemotherapy Resistance Through Inhibiting Ubiquitination of Slug and Activating TGFβ/Smad-Independent Pathways in Gastric Cancer Guodong Cao First Aliated Hospital of Anhui Medical University Pengping Li Hangzhou Xiaoshan No 1 People's Hospital Qiang Sun Xuzhou Medical University Sihan Chen First Aliated Hospital of Anhui Medical University Xin Xu First Aliated Hospital of Anhui Medical University Xiaobo He First Aliated Hospital of Anhui Medical University Zhenyu Wang Hangzhou Xiaoshan No 1 People's Hospital Peng Chen First Aliated Hospital of Anhui Medical University Maoming Xiong ( [email protected] ) First Aliated Hospital of Anhui Medical University Bo Chen First Aliated Hospital of Anhui Medical University Research Keywords: EMT, Chemotherapy resistance, FHL3, Ubiquitination, Gastric cancer Posted Date: October 9th, 2020 DOI: https://doi.org/10.21203/rs.3.rs-87249/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. ReLoaadd iFngu l[Ml LaitchJeanxs]/ejax/output/CommonHTML/jax.js Page 1/28 Loading [MathJax]/jax/output/CommonHTML/jax.js Page 2/28 Abstract Background: Gastric cancer presents high risk of metastasis and chemotherapy resistance. Hence, the mechanistic understanding of the tumor metastasis and chemotherapy resistance is quietly important. Methods: TCGA database and clinical samples are used for exploring the role of FHL3 in disease progression and prognosis. The roles of FHL3 in metastasis and chemotherapy resistance are explored in vitro and in vivo by siRNA or shRNA treatment. Finally, we explore the FHL3-mediated EMT and chemotherapy resistance. Results: mRNA and protein level of FHL3 is signicantly up-regulated in gastric cancer tissues when compares with it in adjacent tissue. -
Urabe VK, Et Al. Influences on U2 Snrna Structure U2
bioRxiv preprint doi: https://doi.org/10.1101/2021.07.05.451154; this version posted July 6, 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. Urabe VK, et al. Influences on U2 snRNA structure U2 snRNA structure is influenced by SF3A and SF3B proteins but not by SF3B inhibitors Veronica K. Urabe1, Meredith Stevers1, Arun K. Ghosh3 and Melissa S. Jurica1,2 * 1Department of Molecular Cell and Developmental Biology and 2Center for Molecular Biology of RNA, University of California, Santa Cruz, California, United States of America 3Department of Chemistry and Department of Medicinal Chemistry, Purdue University, West Lafayette, Indiana United States of America *Corresponding author E-mail: [email protected] (MSJ) bioRxiv preprint doi: https://doi.org/10.1101/2021.07.05.451154; this version posted July 6, 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. Urabe VK, et al. Influences on U2 snRNA structure Abstract U2 snRNP is an essential component of the spliceosome. It is responsible for branch point recognition in the spliceosome A-complex via base-pairing of U2 snRNA with an intron to form the branch helix. Small molecule inhibitors target the SF3B component of the U2 snRNP and interfere with A-complex formation during spliceosome assembly. -
In Vivo Studies Using the Classical Mouse Diversity Panel
The Mouse Diversity Panel Predicts Clinical Drug Toxicity Risk Where Classical Models Fail Alison Harrill, Ph.D The Hamner-UNC Institute for Drug Safety Sciences 0 The Importance of Predicting Clinical Adverse Drug Reactions (ADR) Figure: Cath O’Driscoll Nature Publishing 2004 Risk ID PGx Testing 1 People Respond Differently to Drugs Pharmacogenetic Markers Identified by Genome-Wide Association Drug Adverse Drug Risk Allele Reaction (ADR) Abacavir Hypersensitivity HLA-B*5701 Flucloxacillin Hepatotoxicity Allopurinol Cutaneous ADR HLA-B*5801 Carbamazepine Stevens-Johnson HLA-B*1502 Syndrome Augmentin Hepatotoxicity DRB1*1501 Ximelagatran Hepatotoxicity DRB1*0701 Ticlopidine Hepatotoxicity HLA-A*3303 Average preclinical populations and human hepatocytes lack the diversity to detect incidence of adverse events that occur only in 1/10,000 people. Current Rodent Models of Risk Assessment The Challenge “At a time of extraordinary scientific progress, methods have hardly changed in several decades ([FDA] 2004)… Toxicologists face a major challenge in the twenty-first century. They need to embrace the new “omics” techniques and ensure that they are using the most appropriate animals if their discipline is to become a more effective tool in drug development.” -Dr. Michael Festing Quantitative geneticist Toxicol Pathol. 2010;38(5):681-90 Rodent Models as a Strategy for Hazard Characterization and Pharmacogenetics Genetically defined rodent models may provide ability to: 1. Improve preclinical prediction of drugs that carry a human safety risk 2. -
TFEB Regulates Murine Liver Cell Fate During Development and Regeneration ✉ Nunzia Pastore 1,2 , Tuong Huynh1,2, Niculin J
ARTICLE https://doi.org/10.1038/s41467-020-16300-x OPEN TFEB regulates murine liver cell fate during development and regeneration ✉ Nunzia Pastore 1,2 , Tuong Huynh1,2, Niculin J. Herz1,2, Alessia Calcagni’ 1,2, Tiemo J. Klisch1,2, Lorenzo Brunetti 3,4, Kangho Ho Kim5, Marco De Giorgi6, Ayrea Hurley6, Annamaria Carissimo7, Margherita Mutarelli7, Niya Aleksieva 8, Luca D’Orsi7, William R. Lagor6, David D. Moore 5, ✉ Carmine Settembre7,9, Milton J. Finegold10, Stuart J. Forbes8 & Andrea Ballabio 1,2,7,9 1234567890():,; It is well established that pluripotent stem cells in fetal and postnatal liver (LPCs) can differentiate into both hepatocytes and cholangiocytes. However, the signaling pathways implicated in the differentiation of LPCs are still incompletely understood. Transcription Factor EB (TFEB), a master regulator of lysosomal biogenesis and autophagy, is known to be involved in osteoblast and myeloid differentiation, but its role in lineage commitment in the liver has not been investigated. Here we show that during development and upon regen- eration TFEB drives the differentiation status of murine LPCs into the progenitor/cho- langiocyte lineage while inhibiting hepatocyte differentiation. Genetic interaction studies show that Sox9, a marker of precursor and biliary cells, is a direct transcriptional target of TFEB and a primary mediator of its effects on liver cell fate. In summary, our findings identify an unexplored pathway that controls liver cell lineage commitment and whose dysregulation may play a role in biliary cancer. 1 Jan and Dan Duncan Neurological Research Institute, Texas Children Hospital, Houston, TX 77030, USA. 2 Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA. -
Examination of the Transcription Factors Acting in Bone Marrow
THESIS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY (PHD) Examination of the transcription factors acting in bone marrow derived macrophages by Gergely Nagy Supervisor: Dr. Endre Barta UNIVERSITY OF DEBRECEN DOCTORAL SCHOOL OF MOLECULAR CELL AND IMMUNE BIOLOGY DEBRECEN, 2016 Table of contents Table of contents ........................................................................................................................ 2 1. Introduction ............................................................................................................................ 5 1.1. Transcriptional regulation ................................................................................................... 5 1.1.1. Transcriptional initiation .................................................................................................. 5 1.1.2. Co-regulators and histone modifications .......................................................................... 8 1.2. Promoter and enhancer sequences guiding transcription factors ...................................... 11 1.2.1. General transcription factors .......................................................................................... 11 1.2.2. The ETS superfamily ..................................................................................................... 17 1.2.3. The AP-1 and CREB proteins ........................................................................................ 20 1.2.4. Other promoter specific transcription factor families ................................................... -
Bioinformatic Analysis of Structure and Function of LIM Domains of Human Zyxin Family Proteins
International Journal of Molecular Sciences Article Bioinformatic Analysis of Structure and Function of LIM Domains of Human Zyxin Family Proteins M. Quadir Siddiqui 1,† , Maulik D. Badmalia 1,† and Trushar R. Patel 1,2,3,* 1 Alberta RNA Research and Training Institute, Department of Chemistry and Biochemistry, University of Lethbridge, 4401 University Drive, Lethbridge, AB T1K 3M4, Canada; [email protected] (M.Q.S.); [email protected] (M.D.B.) 2 Department of Microbiology, Immunology and Infectious Disease, Cumming School of Medicine, University of Calgary, 3330 Hospital Drive, Calgary, AB T2N 4N1, Canada 3 Li Ka Shing Institute of Virology, University of Alberta, Edmonton, AB T6G 2E1, Canada * Correspondence: [email protected] † These authors contributed equally to the work. Abstract: Members of the human Zyxin family are LIM domain-containing proteins that perform critical cellular functions and are indispensable for cellular integrity. Despite their importance, not much is known about their structure, functions, interactions and dynamics. To provide insights into these, we used a set of in-silico tools and databases and analyzed their amino acid sequence, phylogeny, post-translational modifications, structure-dynamics, molecular interactions, and func- tions. Our analysis revealed that zyxin members are ohnologs. Presence of a conserved nuclear export signal composed of LxxLxL/LxxxLxL consensus sequence, as well as a possible nuclear localization signal, suggesting that Zyxin family members may have nuclear and cytoplasmic roles. The molecular modeling and structural analysis indicated that Zyxin family LIM domains share Citation: Siddiqui, M.Q.; Badmalia, similarities with transcriptional regulators and have positively charged electrostatic patches, which M.D.; Patel, T.R. -
Supplementary Table S1. Upregulated Genes Differentially
Supplementary Table S1. Upregulated genes differentially expressed in athletes (p < 0.05 and 1.3-fold change) Gene Symbol p Value Fold Change 221051_s_at NMRK2 0.01 2.38 236518_at CCDC183 0.00 2.05 218804_at ANO1 0.00 2.05 234675_x_at 0.01 2.02 207076_s_at ASS1 0.00 1.85 209135_at ASPH 0.02 1.81 228434_at BTNL9 0.03 1.81 229985_at BTNL9 0.01 1.79 215795_at MYH7B 0.01 1.78 217979_at TSPAN13 0.01 1.77 230992_at BTNL9 0.01 1.75 226884_at LRRN1 0.03 1.74 220039_s_at CDKAL1 0.01 1.73 236520_at 0.02 1.72 219895_at TMEM255A 0.04 1.72 201030_x_at LDHB 0.00 1.69 233824_at 0.00 1.69 232257_s_at 0.05 1.67 236359_at SCN4B 0.04 1.64 242868_at 0.00 1.63 1557286_at 0.01 1.63 202780_at OXCT1 0.01 1.63 1556542_a_at 0.04 1.63 209992_at PFKFB2 0.04 1.63 205247_at NOTCH4 0.01 1.62 1554182_at TRIM73///TRIM74 0.00 1.61 232892_at MIR1-1HG 0.02 1.61 204726_at CDH13 0.01 1.6 1561167_at 0.01 1.6 1565821_at 0.01 1.6 210169_at SEC14L5 0.01 1.6 236963_at 0.02 1.6 1552880_at SEC16B 0.02 1.6 235228_at CCDC85A 0.02 1.6 1568623_a_at SLC35E4 0.00 1.59 204844_at ENPEP 0.00 1.59 1552256_a_at SCARB1 0.02 1.59 1557283_a_at ZNF519 0.02 1.59 1557293_at LINC00969 0.03 1.59 231644_at 0.01 1.58 228115_at GAREM1 0.01 1.58 223687_s_at LY6K 0.02 1.58 231779_at IRAK2 0.03 1.58 243332_at LOC105379610 0.04 1.58 232118_at 0.01 1.57 203423_at RBP1 0.02 1.57 AMY1A///AMY1B///AMY1C///AMY2A///AMY2B// 208498_s_at 0.03 1.57 /AMYP1 237154_at LOC101930114 0.00 1.56 1559691_at 0.01 1.56 243481_at RHOJ 0.03 1.56 238834_at MYLK3 0.01 1.55 213438_at NFASC 0.02 1.55 242290_at TACC1 0.04 1.55 ANKRD20A1///ANKRD20A12P///ANKRD20A2/// -
Human Transcription Factor Protein-Protein Interactions in Health and Disease
HELKA GÖÖS GÖÖS HELKA Recent Publications in this Series 45/2019 Mgbeahuruike Eunice Ego Evaluation of the Medicinal Uses and Antimicrobial Activity of Piper guineense (Schumach & Thonn) 46/2019 Suvi Koskinen AND DISEASE IN HEALTH INTERACTIONS PROTEIN-PROTEIN FACTOR HUMAN TRANSCRIPTION Near-Occlusive Atherosclerotic Carotid Artery Disease: Study with Computed Tomography Angiography 47/2019 Flavia Fontana DISSERTATIONES SCHOLAE DOCTORALIS AD SANITATEM INVESTIGANDAM Biohybrid Cloaked Nanovaccines for Cancer Immunotherapy UNIVERSITATIS HELSINKIENSIS 48/2019 Marie Mennesson Kainate Receptor Auxiliary Subunits Neto1 and Neto2 in Anxiety and Fear-Related Behaviors 49/2019 Zehua Liu Porous Silicon-Based On-Demand Nanohybrids for Biomedical Applications 50/2019 Veer Singh Marwah Strategies to Improve Standardization and Robustness of Toxicogenomics Data Analysis HELKA GÖÖS 51/2019 Iryna Hlushchenko Actin Regulation in Dendritic Spines: From Synaptic Plasticity to Animal Behavior and Human HUMAN TRANSCRIPTION FACTOR PROTEIN-PROTEIN Neurodevelopmental Disorders 52/2019 Heini Liimatta INTERACTIONS IN HEALTH AND DISEASE Efectiveness of Preventive Home Visits among Community-Dwelling Older People 53/2019 Helena Karppinen Older People´s Views Related to Their End of Life: Will-to-Live, Wellbeing and Functioning 54/2019 Jenni Laitila Elucidating Nebulin Expression and Function in Health and Disease 55/2019 Katarzyna Ciuba Regulation of Contractile Actin Structures in Non-Muscle Cells 56/2019 Sami Blom Spatial Characterisation of Prostate Cancer by Multiplex -
SF3B2-Mediated RNA Splicing Drives Human Prostate Cancer Progression
Published OnlineFirst August 20, 2019; DOI: 10.1158/0008-5472.CAN-18-3965 Cancer Molecular Cell Biology Research SF3B2-Mediated RNA Splicing Drives Human Prostate Cancer Progression Norihiko Kawamura1,2, Keisuke Nimura1, Kotaro Saga1, Airi Ishibashi1, Koji Kitamura1,3, Hiromichi Nagano1, Yusuke Yoshikawa4, Kyoso Ishida1,5, Norio Nonomura2, Mitsuhiro Arisawa4, Jun Luo6, and Yasufumi Kaneda1 Abstract Androgen receptor splice variant-7 (AR-V7) is a General RNA splicing SF3B2 complex-mediated alternative RNA splicing constitutively active AR variant implicated in U2 castration-resistant prostate cancers. Here, we show U2 snRNA that the RNA splicing factor SF3B2, identified by 3’ 3’ in silico and CRISPR/Cas9 analyses, is a critical 5’ 3’ splice site 5’ SF3B7 AR-V7 5’ A U2AF2 AGA Exon ? determinant of expression and is correlated SF3B6(p14) SF3B4 SF3B1 SF3B4 SF3B1 with aggressive cancer phenotypes. Transcriptome SF3B5 SF3B2 SF3B3 SF3B2 SF3B3 and PAR-CLIP analyses revealed that SF3B2 con- SF3A3 SF3B2 complex SF3A3 SF3A1 SF3A1 SF3b complex trols the splicing of target genes, including AR, to AR pre-mRNA drive aggressive phenotypes. SF3B2-mediated CE3 aggressive phenotypes in vivo were reversed by AR-V7 mRNA AR mRNA AR-V7 knockout. Pladienolide B, an inhibitor of CE3 a splicing modulator of the SF3b complex, sup- Drive malignancy pressed the growth of tumors addicted to high While the SF3b complex is critical for general RNA splicing, SF3B2 promotes inclusion of the target exon through recognizing a specific RNA motif. SF3B2 expression. These findings support the idea © 2019 American Association for Cancer Research that alteration of the splicing pattern by high SF3B2 expression is one mechanism underlying prostate cancer progression and therapeutic resistance. -
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. -
Full-Length Cdna, Expression Pattern and Association Analysis of the Porcine FHL3 Gene
1473 Asian-Aust. J. Anim. Sci. Vol. 20, No. 10 : 1473 - 1477 October 2007 www.ajas.info Full-length cDNA, Expression Pattern and Association Analysis of the Porcine FHL3 Gene Bo Zuo*, YuanZhu Xiong, Hua Yang and Jun Wang Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture & Key Lab of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, College of Animal Science and Veterinary Medicine, Huazhong Agricultural University, Wuhan, 430070, P. R. China ABSTRACT : Four-and-a-half LIM-only protein 3 (FHL3) is a member of the LIM protein superfamily and can participate in mediating protein-protein interaction by binding one another through their LIM domains. In this study, the 5'- and 3'- cDNA ends were characterized by RACE (Rapid Amplification of the cDNA Ends) methodology in combination with in silica cloning based on the partial cDNA sequence obtained. Bioinformatics analysis showed FHL3 protein contained four LIM domains and four LIM zinc-binding domains. In silica mapping assigned this gene to the gene cluster MTF1-INPP5B-SF3A3-FHL3-CGI-94 on pig chromosome 6 where several QTL affecting intramuscular fat and eye muscle area had previously been identified. Transcription of the FHL3 gene was detected in spleen, liver, kidney, small intestine, skeletal muscle, fat and stomach, with the greatest expression in skeletal muscle. The A/G polymorphism in exon II was significantly associated with birth weight, average daily gain before weaning, drip loss rate, water holding capacity and intramuscular fat in a Landrace-derived pig population. Together, the present study provided the useful information for further studies to determine the roles of FHL3 gene in the regulation of skeletal muscle cell growth and differentiation in pigs.