Proteomic Analysis of Blastema Formation in Regenerating Axolotl Limbs Nandini Rao Indiana University - Purdue University Indianapolis
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MARK4 with an Alzheimer's Disease-Related Mutation Promotes
bioRxiv preprint doi: https://doi.org/10.1101/2020.05.20.107284; this version posted May 23, 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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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. MARK4 with an Alzheimer’s disease-related mutation promotes tau hyperphosphorylation directly and indirectly and exacerbates neurodegeneration Toshiya Obaa, Taro Saitoa,b, Akiko Asadaa,b, Sawako Shimizua, Koichi M. Iijimac,d and Kanae Andoa,b, * aGraduate School of Science, Tokyo Metropolitan University, Tokyo 192-0397, Japan, bDepartment of Biological Sciences, School of Science, Tokyo Metropolitan University, Tokyo 192-0397, Japan, cDepartment of Alzheimer’s Disease Research, National Center for Geriatrics and Gerontology, Obu, Aichi 474-8511, Japan, dDepartment of Experimental Gerontology, Graduate School of Pharmaceutical Sciences, Nagoya City University, Nagoya, Aichi 467-8603, Japan *Corresponding author Kanae Ando, Ph.D. E-mail: [email protected] Running title: Mutant MARK4 enhances phospho-tau accumulation Abstract Accumulation of the microtubule-associated protein tau is associated with Alzheimer’s disease (AD). In AD brain, tau is abnormally phosphorylated at many sites, and phosphorylation at Ser262 and Ser356 play critical roles in tau accumulation and toxicity. Microtubule-affinity regulating kinase 4 (MARK4) phosphorylates tau at those sites, and a double de novo mutation in the linker region of MARK4, ΔG316E317InsD, is associated with an elevated risk of AD. However, it remains unclear how this mutation affects phosphorylation, aggregation, and accumulation of tau and tau-induced neurodegeneration. Here, we report that MARK4ΔG316E317D increases the abundance of highly phosphorylated, insoluble tau species and exacerbates neurodegeneration via Ser262/356-dependent and -independent mechanisms. -
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. -
Datasheet Blank Template
SAN TA C RUZ BI OTEC HNOL OG Y, INC . CWC15 (C-8): sc-514479 BACKGROUND APPLICATIONS CWC15 (CWC15 spliceosome-associated protein), also known as ORF5, Cwf15, CWC15 (C-8) is recommended for detection of CWC15 of mouse, rat and C11orf5 or HSPC14, is a 229 amino acid protein involved in pre-mRNA splicing. human origin by Western Blotting (starting dilution 1:100, dilution range The gene encoding CWC15 maps to human chromosome 11q21. With approx - 1:100- 1:1000), immunoprecipitation [1-2 µg per 100-500 µg of total protein imately 135 million base pairs and 1,400 genes, chromosome 11 makes up (1 ml of cell lysate)], immunofluorescence (starting dilution 1:50, dilution around 4% of human genomic DNA and is considered a gene and disease as- range 1:50- 1:500) and solid phase ELISA (starting dilution 1:30, dilution sociation dense chromosome. The chromosome 11 encoded Atm gene is impor - range 1:30-1:3000). tant for regulation of cell cycle arrest and apoptosis following double strand Suitable for use as control antibody for CWC15 siRNA (h): sc-97055, CWC15 DNA breaks. Atm mutation leads to the disorder known as ataxia-telang iecta - siRNA (m): sc-142639, CWC15 shRNA Plasmid (h): sc-97055-SH, CWC15 sia. The blood disorders sickle cell anemia and thalassemia are caused by β shRNA Plasmid (m): sc-142639-SH, CWC15 shRNA (h) Lentiviral Particles: HBB gene mutations. Wilms’ tumors, WAGR syndrome and Denys-Drash syn - sc- 97055-V and CWC15 shRNA (m) Lentiviral Particles: sc-142639-V. drome are associated with mutations of the WT1 gene. -
Multiple Activities of Arl1 Gtpase in the Trans-Golgi Network Chia-Jung Yu1,2 and Fang-Jen S
© 2017. Published by The Company of Biologists Ltd | Journal of Cell Science (2017) 130, 1691-1699 doi:10.1242/jcs.201319 COMMENTARY Multiple activities of Arl1 GTPase in the trans-Golgi network Chia-Jung Yu1,2 and Fang-Jen S. Lee3,4,* ABSTRACT typical features of an Arf-family GTPase, including an amphipathic ADP-ribosylation factors (Arfs) and ADP-ribosylation factor-like N-terminal helix and a consensus site for N-myristoylation (Lu et al., proteins (Arls) are highly conserved small GTPases that function 2001; Price et al., 2005). In yeast, recruitment of Arl1 to the Golgi as main regulators of vesicular trafficking and cytoskeletal complex requires a second Arf-like GTPase, Arl3 (Behnia et al., reorganization. Arl1, the first identified member of the large Arl family, 2004; Setty et al., 2003). Yeast Arl3 lacks a myristoylation site and is an important regulator of Golgi complex structure and function in is, instead, N-terminally acetylated; this modification is required for organisms ranging from yeast to mammals. Together with its effectors, its recruitment to the Golgi complex by Sys1. In mammalian cells, Arl1 has been shown to be involved in several cellular processes, ADP-ribosylation-factor-related protein 1 (Arfrp1), a mammalian including endosomal trans-Golgi network and secretory trafficking, lipid ortholog of yeast Arl3, plays a pivotal role in the recruitment of Arl1 droplet and salivary granule formation, innate immunity and neuronal to the trans-Golgi network (TGN) (Behnia et al., 2004; Panic et al., development, stress tolerance, as well as the response of the unfolded 2003b; Setty et al., 2003; Zahn et al., 2006). -
A Feed-Forward Cycle
GMJ.2020;9:e1681 www.gmj.ir Received 2019-08-08 Revised 2019-11-11 Accepted 2019-11-24 Tau Abnormalities and Autophagic Defects in Neurodegenerative Disorders; A Feed-forward Cycle Nastaran Samimi 1, 2, Akiko Asada 3, 4, Kanae Ando 3, 4 1 Noncommunicable Diseases Research Center, Fasa University of Medical Sciences, Fasa, Iran 2 Department of Brain and Cognitive Sciences, Cell Science Research Center, Royan Institute for Stem Cell Biology and Technology, ACECR, Tehran, Iran 3 Department of Biological Sciences, School of Science, Tokyo Metropolitan University, Tokyo, Japan 4 Graduate School of Science, Tokyo Metropolitan University, Tokyo, Japan Abstract Abnormal deposition of misfolded proteins is a neuropathological characteristic shared by many neurodegenerative disorders including Alzheimer’s disease (AD). Generation of excessive amounts of aggregated proteins and impairment of degradation systems for misfolded proteins such as autophagy can lead to accumulation of proteins in diseased neurons. Molecules that contribute to both these effects are emerging as critical players in disease pathogenesis. Furthermore, impairment of autophagy under disease conditions can be both a cause and a consequence of abnormal protein accumulation. Specifically, disease-causing proteins can impair autophagy, which further enhances the accumulation of abnormal proteins. In this short review, we focus on the relationship between the microtubule-associated protein tau and autophagy to highlight a feed-forward mechanism in disease pathogenesis. [GMJ.2020;9:e1681] DOI:10.31661/gmj.v9i0.1681 Keywords: Neurodegenerative Diseases; Tauopathy; Autophagy; Microtubule Binding Pro- tein; Tau; Phosphorylation; Vesicle Trafficking Tau phosphorylation in physiology and dis- However, tau detaches from microtubules and ease misfolds to form insoluble filaments in neuro- isfolded tau protein is deposited in a fibrillary tangles in the brains of patients with Mgroup of neurodegenerative diseases tauopathies [4-9]. -
Differential RNA Packaging Into Small Extracellular Vesicles by Neurons
Luo et al. Cell Commun Signal (2021) 19:75 https://doi.org/10.1186/s12964-021-00757-4 RESEARCH Open Access Diferential RNA packaging into small extracellular vesicles by neurons and astrocytes Xuan Luo1, Renée Jean‑Toussaint1, Ahmet Sacan2 and Seena K. Ajit1* Abstract Background: Small extracellular vesicles (sEVs) mediate intercellular communication by transferring RNA, proteins, and lipids to recipient cells. These cargo molecules are selectively loaded into sEVs and mirror the physiological state of the donor cells. Given that sEVs can cross the blood–brain barrier and their composition can change in neurologi‑ cal disorders, the molecular signatures of sEVs in circulation can be potential disease biomarkers. Characterizing the molecular composition of sEVs from diferent cell types is an important frst step in determining which donor cells contribute to the circulating sEVs. Methods: Cell culture supernatants from primary mouse cortical neurons and astrocytes were used to purify sEVs by diferential ultracentrifugation and sEVs were characterized using nanoparticle tracking analysis, transmission electron microscopy and western blot. RNA sequencing was used to determine diferential expression and loading patterns of miRNAs in sEVs released by primary neurons and astrocytes. Motif analysis was conducted on enriched miRNAs in sEVs and their respective donor cells. Results: Sequencing total cellular RNA, and miRNAs from sEVs isolated from culture media of postnatal mouse corti‑ cal neurons and astrocytes revealed a distinct profle between sEVs and their corresponding cells. Though the total number of detected miRNAs in astrocytes was greater than neurons, neurons expressed more sEV‑associated miRNAs than astrocytes. Only 20.7% of astrocytic miRNAs were loaded into sEVs, while 41.0% of neuronal miRNAs were loaded into sEVs, suggesting diferences in the cellular sorting mechanisms. -
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. -
Novel Mechanisms of Pten Dysfunction in Pten Hamartoma Tumor Syndromes
NOVEL MECHANISMS OF PTEN DYSFUNCTION IN PTEN HAMARTOMA TUMOR SYNDROMES DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Marcus G. Pezzolesi, B.S. ***** The Ohio State University 2008 Dissertation Committee: Approved by Professor Allan J. Yates, Advisor Professor Charis Eng, Co-Advisor _________________________________ Professor Wolfgang Sadee Advisor Integrated Biomedical Science Professor Michael C. Ostrowski Graduate Program Professor Lawrence S. Kirschner Professor Lei Shen ABSTRACT Phosphatase and tensin homolog deleted on chromosome ten (PTEN) encodes a tumor suppressor phosphatase frequently mutated in both sporadic and heritable forms of human cancer. Germline mutations in PTEN are associated with a number of heritable cancer syndromes referred to as the PTEN hamartoma tumor syndromes (PHTS) and includes both Cowden syndrome (CS) and Bannayan-Riley-Ruvalcaba syndrome (BRRS). Data from our laboratory suggests that alternate mechanisms of PTEN deregulation are likely to, at least in part, contribute to dysfunction in patients with these syndromes, particularly in those for whom germline mutations have yet to be identified. To better understand the mechanism(s) underlying dysregulation of PTEN in these syndromes, we employed a series of genetic and biochemical approaches aimed at investigating novel mechanisms involved in the regulation and deregulation of PTEN. Using a haplotype-based approach, we identified specific haplotypes and rare alleles within the PTEN locus that contribute to disease susceptibility and the phenotypic complexity of this syndrome. Within a haplotype block associated with PTEN-mutation negative patients, we identified a canonical E-box sequence located upstream of PTEN’s minimal promoter. -
A Genome-Wide Scan for Candidate Lethal Variants in Thoroughbred Horses
bioRxiv preprint doi: https://doi.org/10.1101/2020.05.04.077008; this version posted May 4, 2020. 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 4.0 International license. A genome-wide scan for candidate lethal variants in Thoroughbred horses. Evelyn T. Todd1*, Peter C. Thomson1, Natasha A. Hamilton2, Rachel A. Ang1, Gabriella Lindgren3,4, Åsa Viklund3, Susanne Eriksson3, Sofia Mikko3, Eric Strand5 and Brandon D. Velie1. 1 School of Life and Environmental Sciences, The University of Sydney, NSW 2006, Australia. 2 Racing Australia Equine Genetics Research Centre, Racing Australia, NSW 2000, Australia. 3Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden. 4Livestock Genetics, Department of Biosystems, KU Leuven, Leuven, Belgium. 5Department of Companion Animal Clinical Sciences, Faculty of Veterinary Medicine, Norwegian University of Life Sciences, Oslo, Norway. *Correspondence and requests for materials should be addressed to Evelyn T. Todd (email: [email protected]) 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.05.04.077008; this version posted May 4, 2020. 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 4.0 International license. 1 Abstract 2 Recessive lethal variants often segregate at low frequencies in animal populations, such that two 3 randomly selected individuals are unlikely to carry the same mutation. -
Association of Gene Ontology Categories with Decay Rate for Hepg2 Experiments These Tables Show Details for All Gene Ontology Categories
Supplementary Table 1: Association of Gene Ontology Categories with Decay Rate for HepG2 Experiments These tables show details for all Gene Ontology categories. Inferences for manual classification scheme shown at the bottom. Those categories used in Figure 1A are highlighted in bold. Standard Deviations are shown in parentheses. P-values less than 1E-20 are indicated with a "0". Rate r (hour^-1) Half-life < 2hr. Decay % GO Number Category Name Probe Sets Group Non-Group Distribution p-value In-Group Non-Group Representation p-value GO:0006350 transcription 1523 0.221 (0.009) 0.127 (0.002) FASTER 0 13.1 (0.4) 4.5 (0.1) OVER 0 GO:0006351 transcription, DNA-dependent 1498 0.220 (0.009) 0.127 (0.002) FASTER 0 13.0 (0.4) 4.5 (0.1) OVER 0 GO:0006355 regulation of transcription, DNA-dependent 1163 0.230 (0.011) 0.128 (0.002) FASTER 5.00E-21 14.2 (0.5) 4.6 (0.1) OVER 0 GO:0006366 transcription from Pol II promoter 845 0.225 (0.012) 0.130 (0.002) FASTER 1.88E-14 13.0 (0.5) 4.8 (0.1) OVER 0 GO:0006139 nucleobase, nucleoside, nucleotide and nucleic acid metabolism3004 0.173 (0.006) 0.127 (0.002) FASTER 1.28E-12 8.4 (0.2) 4.5 (0.1) OVER 0 GO:0006357 regulation of transcription from Pol II promoter 487 0.231 (0.016) 0.132 (0.002) FASTER 6.05E-10 13.5 (0.6) 4.9 (0.1) OVER 0 GO:0008283 cell proliferation 625 0.189 (0.014) 0.132 (0.002) FASTER 1.95E-05 10.1 (0.6) 5.0 (0.1) OVER 1.50E-20 GO:0006513 monoubiquitination 36 0.305 (0.049) 0.134 (0.002) FASTER 2.69E-04 25.4 (4.4) 5.1 (0.1) OVER 2.04E-06 GO:0007050 cell cycle arrest 57 0.311 (0.054) 0.133 (0.002) -
Natural Genetic Variation Screen in Drosophila Identifies
INVESTIGATION Natural Genetic Variation Screen in Drosophila Identifies Wnt Signaling, Mitochondrial Metabolism, and Redox Homeostasis Genes as Modifiers of Apoptosis Rebecca A. S. Palu,*,1 Elaine Ong,* Kaitlyn Stevens,* Shani Chung,* Katie G. Owings,* Alan G. Goodman,†,‡ and Clement Y. Chow*,2 *Department of Human Genetics, University of Utah School of Medicine, Salt Lake City, UT 84112, †School of Molecular Biosciences, and ‡Paul G. Allen School for Global Animal Health, Washington State University College of Veterinary Medicine, Pullman, WA 99164 ORCID IDs: 0000-0001-9444-8815 (R.A.S.P.); 0000-0001-6394-332X (A.G.G.); 0000-0002-3104-7923 (C.Y.C.) ABSTRACT Apoptosis is the primary cause of degeneration in a number of neuronal, muscular, and KEYWORDS metabolic disorders. These diseases are subject to a great deal of phenotypic heterogeneity in patient apoptosis populations, primarily due to differences in genetic variation between individuals. This creates a barrier to Drosophila effective diagnosis and treatment. Understanding how genetic variation influences apoptosis could lead to genetic variation the development of new therapeutics and better personalized treatment approaches. In this study, we modifier genes examine the impact of the natural genetic variation in the Drosophila Genetic Reference Panel (DGRP) on two models of apoptosis-induced retinal degeneration: overexpression of p53 or reaper (rpr). We identify a number of known apoptotic, neural, and developmental genes as candidate modifiers of degeneration. We also use Gene Set Enrichment Analysis (GSEA) to identify pathways that harbor genetic variation that impact these apoptosis models, including Wnt signaling, mitochondrial metabolism, and redox homeostasis. Fi- nally, we demonstrate that many of these candidates have a functional effect on apoptosis and degener- ation. -
Supplementary Materials
Supplementary materials Supplementary Table S1: MGNC compound library Ingredien Molecule Caco- Mol ID MW AlogP OB (%) BBB DL FASA- HL t Name Name 2 shengdi MOL012254 campesterol 400.8 7.63 37.58 1.34 0.98 0.7 0.21 20.2 shengdi MOL000519 coniferin 314.4 3.16 31.11 0.42 -0.2 0.3 0.27 74.6 beta- shengdi MOL000359 414.8 8.08 36.91 1.32 0.99 0.8 0.23 20.2 sitosterol pachymic shengdi MOL000289 528.9 6.54 33.63 0.1 -0.6 0.8 0 9.27 acid Poricoic acid shengdi MOL000291 484.7 5.64 30.52 -0.08 -0.9 0.8 0 8.67 B Chrysanthem shengdi MOL004492 585 8.24 38.72 0.51 -1 0.6 0.3 17.5 axanthin 20- shengdi MOL011455 Hexadecano 418.6 1.91 32.7 -0.24 -0.4 0.7 0.29 104 ylingenol huanglian MOL001454 berberine 336.4 3.45 36.86 1.24 0.57 0.8 0.19 6.57 huanglian MOL013352 Obacunone 454.6 2.68 43.29 0.01 -0.4 0.8 0.31 -13 huanglian MOL002894 berberrubine 322.4 3.2 35.74 1.07 0.17 0.7 0.24 6.46 huanglian MOL002897 epiberberine 336.4 3.45 43.09 1.17 0.4 0.8 0.19 6.1 huanglian MOL002903 (R)-Canadine 339.4 3.4 55.37 1.04 0.57 0.8 0.2 6.41 huanglian MOL002904 Berlambine 351.4 2.49 36.68 0.97 0.17 0.8 0.28 7.33 Corchorosid huanglian MOL002907 404.6 1.34 105 -0.91 -1.3 0.8 0.29 6.68 e A_qt Magnogrand huanglian MOL000622 266.4 1.18 63.71 0.02 -0.2 0.2 0.3 3.17 iolide huanglian MOL000762 Palmidin A 510.5 4.52 35.36 -0.38 -1.5 0.7 0.39 33.2 huanglian MOL000785 palmatine 352.4 3.65 64.6 1.33 0.37 0.7 0.13 2.25 huanglian MOL000098 quercetin 302.3 1.5 46.43 0.05 -0.8 0.3 0.38 14.4 huanglian MOL001458 coptisine 320.3 3.25 30.67 1.21 0.32 0.9 0.26 9.33 huanglian MOL002668 Worenine