Application to Neuroimaging Biomarkers in Alzheimer's
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Cell, Volume 139 Supplemental Data Profiling the Human Protein-DNA
Cell, Volume 139 Supplemental Data Profiling the Human Protein-DNA Interactome Reveals ERK2 as a Transcriptional Repressor of Interferon Signaling Shaohui Hu, Zhi Xie, Akishi Onishi, Xueping Yu, Lizhi Jiang, Jimmy Lin, Hee-sool Rho, Crystal Woodard, Hong Wang, Jun-Seop Jeong, Shunyou Long, Xiaofei He, Herschel Wade, Seth Blackshaw, Jiang Qian, and Heng Zhu Supplemental Experimental Procedures Identifying Tissue-specific Motifs We developed a program to identify tissue-specific motifs. We first defined sets of tissue-specific or tissue-enriched genes by examining their gene expression profiles across multiple tissues (Yu et al., 2006). We then calculated the most over-represented single motifs (8-mers, including a wide character) in the promoters of each set of tissue-specific genes. The program then enumerated all possible combinations of the top n motifs (e.g. n = 100). For each motif pair, the program recorded the occurrence of the motif pair in the promoter sequences. We then calculated the significance score for each motif pair, which was defined as the negative logarithm of the p value, -log(p). The motif pairs with scores above a specified threshold were considered putative TF binding motif pairs in the promoter sequences. With these predicted motif pairs, we could calculate a number of partners for each motif and select a certain number of top non-redundant motifs to be tested in the protein chip experiments. Both the p values for a single motif and those for a motif pair were calculated using hypergeometric distribution. Here, we use a motif pair as an example to show the ij, procedure. -
Investigation of Candidate Genes and Mechanisms Underlying Obesity
Prashanth et al. BMC Endocrine Disorders (2021) 21:80 https://doi.org/10.1186/s12902-021-00718-5 RESEARCH ARTICLE Open Access Investigation of candidate genes and mechanisms underlying obesity associated type 2 diabetes mellitus using bioinformatics analysis and screening of small drug molecules G. Prashanth1 , Basavaraj Vastrad2 , Anandkumar Tengli3 , Chanabasayya Vastrad4* and Iranna Kotturshetti5 Abstract Background: Obesity associated type 2 diabetes mellitus is a metabolic disorder ; however, the etiology of obesity associated type 2 diabetes mellitus remains largely unknown. There is an urgent need to further broaden the understanding of the molecular mechanism associated in obesity associated type 2 diabetes mellitus. Methods: To screen the differentially expressed genes (DEGs) that might play essential roles in obesity associated type 2 diabetes mellitus, the publicly available expression profiling by high throughput sequencing data (GSE143319) was downloaded and screened for DEGs. Then, Gene Ontology (GO) and REACTOME pathway enrichment analysis were performed. The protein - protein interaction network, miRNA - target genes regulatory network and TF-target gene regulatory network were constructed and analyzed for identification of hub and target genes. The hub genes were validated by receiver operating characteristic (ROC) curve analysis and RT- PCR analysis. Finally, a molecular docking study was performed on over expressed proteins to predict the target small drug molecules. Results: A total of 820 DEGs were identified between -
The Metabolic Serine Hydrolases and Their Functions in Mammalian Physiology and Disease Jonathan Z
REVIEW pubs.acs.org/CR The Metabolic Serine Hydrolases and Their Functions in Mammalian Physiology and Disease Jonathan Z. Long* and Benjamin F. Cravatt* The Skaggs Institute for Chemical Biology and Department of Chemical Physiology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States CONTENTS 2.4. Other Phospholipases 6034 1. Introduction 6023 2.4.1. LIPG (Endothelial Lipase) 6034 2. Small-Molecule Hydrolases 6023 2.4.2. PLA1A (Phosphatidylserine-Specific 2.1. Intracellular Neutral Lipases 6023 PLA1) 6035 2.1.1. LIPE (Hormone-Sensitive Lipase) 6024 2.4.3. LIPH and LIPI (Phosphatidic Acid-Specific 2.1.2. PNPLA2 (Adipose Triglyceride Lipase) 6024 PLA1R and β) 6035 2.1.3. MGLL (Monoacylglycerol Lipase) 6025 2.4.4. PLB1 (Phospholipase B) 6035 2.1.4. DAGLA and DAGLB (Diacylglycerol Lipase 2.4.5. DDHD1 and DDHD2 (DDHD Domain R and β) 6026 Containing 1 and 2) 6035 2.1.5. CES3 (Carboxylesterase 3) 6026 2.4.6. ABHD4 (Alpha/Beta Hydrolase Domain 2.1.6. AADACL1 (Arylacetamide Deacetylase-like 1) 6026 Containing 4) 6036 2.1.7. ABHD6 (Alpha/Beta Hydrolase Domain 2.5. Small-Molecule Amidases 6036 Containing 6) 6027 2.5.1. FAAH and FAAH2 (Fatty Acid Amide 2.1.8. ABHD12 (Alpha/Beta Hydrolase Domain Hydrolase and FAAH2) 6036 Containing 12) 6027 2.5.2. AFMID (Arylformamidase) 6037 2.2. Extracellular Neutral Lipases 6027 2.6. Acyl-CoA Hydrolases 6037 2.2.1. PNLIP (Pancreatic Lipase) 6028 2.6.1. FASN (Fatty Acid Synthase) 6037 2.2.2. PNLIPRP1 and PNLIPR2 (Pancreatic 2.6.2. -
Long Noncoding RNA LYPLAL1-AS1 Regulates Adipogenic Differentiation
Yang et al. Cell Death Discovery (2021) 7:105 https://doi.org/10.1038/s41420-021-00500-5 Cell Death Discovery ARTICLE Open Access Long noncoding RNA LYPLAL1-AS1 regulates adipogenic differentiation of human mesenchymal stem cells by targeting desmoplakin and inhibiting the Wnt/β-catenin pathway Yanlei Yang1,2,JunfenFan1,HaoyingXu1,LinyuanFan1,LuchanDeng1,JingLi 1,DiLi1, Hongling Li1, Fengchun Zhang2 and Robert Chunhua Zhao1 Abstract Long noncoding RNAs are crucial factors for modulating adipogenic differentiation, but only a few have been identified in humans. In the current study, we identified a previously unknown human long noncoding RNA, LYPLAL1- antisense RNA1 (LYPLAL1-AS1), which was dramatically upregulated during the adipogenic differentiation of human adipose-derived mesenchymal stem cells (hAMSCs). Based on 5′ and 3′ rapid amplification of cDNA ends assays, full- length LYPLAL1-AS1 was 523 nt. Knockdown of LYPLAL1-AS1 decreased the adipogenic differentiation of hAMSCs, whereas overexpression of LYPLAL1-AS1 enhanced this process. Desmoplakin (DSP) was identified as a direct target of LYPLAL1-AS1. Knockdown of DSP enhanced adipogenic differentiation and rescued the LYPLAL1-AS1 depletion- induced defect in adipogenic differentiation of hAMSCs. Further experiments showed that LYPLAL1-AS1 modulated DSP protein stability possibly via proteasome degradation, and the Wnt/β-catenin pathway was inhibited during 1234567890():,; 1234567890():,; 1234567890():,; 1234567890():,; adipogenic differentiation regulated by the LYPLAL1-AS1/DSP complex. Together, our work provides a new mechanism by which long noncoding RNA regulates adipogenic differentiation of human MSCs and suggests that LYPLAL1-AS1 may serve as a novel therapeutic target for preventing and combating diseases related to abnormal adipogenesis, such as obesity. -
Supp Table 2
Supplementary Table 2 : Transcripts and pathways down-regulated in SLE compared to control renal biopsies Differences in (Log2-transformed, mean-centered) gene expression between lupus and control biopsies were analyzed using a moderated t test with Benjamini-Hochberg correction for multiple comparisons (p value threshold set to 0.05). Pathway analyses were performed using DAVID software. Enrichment scores are –log10 p values, calculated by modified Fisher Exact test by comparing proportions of transcripts belonging to a given pathway in the tested gene list compared to the whole transcriptome.[14, 15] Transcripts Pathways Identifier [Control] [SLE] Gene Symbol Annotation Cluster 1 Enrichment Score: 7.43 Database Pathway Count P_Value Benjamini ILMN_1751607 2.8195102 0.25910223 FOSB SP_PIR_KEYWORDS mitochondrion 52 6.80E-20 2.30E-17 ILMN_1682763 2.1716797 -0.4070203 ALB GOTERM_CC_FAT mitochondrion 60 2.70E-19 7.50E-17 ILMN_1781285 1.7535293 -0.0462692 DUSP1 GOTERM_CC_FAT mitochondrial part 42 7.40E-17 1.50E-14 ILMN_1723522 1.718832 -0.2997489 APOLD1 GOTERM_CC_FAT mitochondrial enveLope 34 3.00E-15 2.80E-13 ILMN_1765232 1.632873 0.14076953 RNLS GOTERM_CC_FAT mitochondrial inner membrane 28 8.40E-14 5.80E-12 ILMN_1662880 1.6177534 -0.1763568 FIS GOTERM_CC_FAT mitochondrial membrane 31 1.50E-13 8.60E-12 ILMN_1813361 1.6158535 0.08449265 ANGPTL7 UP_SEQ_FEATURE tranSit peptide:Mitochondrion 32 3.90E-13 2.80E-10 ILMN_2047618 1.6081884 -0.0522185 KCNE1 GOTERM_CC_FAT organeLLe inner membrane 28 4.80E-13 2.20E-11 ILMN_1711015 1.577714 -0.2619377 -
Changes in Mirna Expression in a Model of Microcephaly Shan Parikh University of Connecticut - Storrs, [email protected]
University of Connecticut OpenCommons@UConn Honors Scholar Theses Honors Scholar Program Spring 5-9-2010 Changes in miRNA Expression in a Model of Microcephaly Shan Parikh University of Connecticut - Storrs, [email protected] Follow this and additional works at: https://opencommons.uconn.edu/srhonors_theses Part of the Cellular and Molecular Physiology Commons, and the Other Physiology Commons Recommended Citation Parikh, Shan, "Changes in miRNA Expression in a Model of Microcephaly" (2010). Honors Scholar Theses. 140. https://opencommons.uconn.edu/srhonors_theses/140 Changes in miRNA expression in a model of Microcephaly Shan Parikh Physiology and Neurobiology Abstract miRNAs function to regulate gene expression through post-transcriptional mechanisms to potentially regulate multiple aspects of physiology and development. Whole transcriptome analysis has been conducted on the citron kinase mutant rat, a mutant that shows decreases in brain growth and development. The resulting differences in RNA between mutant and wild-type controls can be used to identify genetic pathways that may be regulated differentially in normal compared to abnormal neurogenesis. The goal of this thesis was to verify, with quantitative reverse transcriptase polymerase chain reaction (qRT-PCR), changes in miRNA expression in Cit-k mutants and wild types. In addition to confirming miRNA expression changes, bio- informatics software TargetScan 5.1 was used to identify potential mRNA targets of the differentially expressed miRNAs. The miRNAs that were confirmed to change include: rno-miR- 466c, mmu-miR-493, mmu-miR-297a, hsa-miR-765, and hsa-miR-1270. The TargetScan analysis revealed 347 potential targets which have known roles in development. A subset of these potential targets include genes involved in the Wnt signaling pathway which is known to be an important regulator of stem cell development. -
Genomic and Transcriptome Analysis Revealing an Oncogenic Functional Module in Meningiomas
Neurosurg Focus 35 (6):E3, 2013 ©AANS, 2013 Genomic and transcriptome analysis revealing an oncogenic functional module in meningiomas XIAO CHANG, PH.D.,1 LINGLING SHI, PH.D.,2 FAN GAO, PH.D.,1 JONATHAN RUssIN, M.D.,3 LIYUN ZENG, PH.D.,1 SHUHAN HE, B.S.,3 THOMAS C. CHEN, M.D.,3 STEVEN L. GIANNOTTA, M.D.,3 DANIEL J. WEISENBERGER, PH.D.,4 GAbrIEL ZADA, M.D.,3 KAI WANG, PH.D.,1,5,6 AND WIllIAM J. MAck, M.D.1,3 1Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, California; 2GHM Institute of CNS Regeneration, Jinan University, Guangzhou, China; 3Department of Neurosurgery, Keck School of Medicine, University of Southern California, Los Angeles, California; 4USC Epigenome Center, Keck School of Medicine, University of Southern California, Los Angeles, California; 5Department of Psychiatry, Keck School of Medicine, University of Southern California, Los Angeles, California; and 6Division of Bioinformatics, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California Object. Meningiomas are among the most common primary adult brain tumors. Although typically benign, roughly 2%–5% display malignant pathological features. The key molecular pathways involved in malignant trans- formation remain to be determined. Methods. Illumina expression microarrays were used to assess gene expression levels, and Illumina single- nucleotide polymorphism arrays were used to identify copy number variants in benign, atypical, and malignant me- ningiomas (19 tumors, including 4 malignant ones). The authors also reanalyzed 2 expression data sets generated on Affymetrix microarrays (n = 68, including 6 malignant ones; n = 56, including 3 malignant ones). -
I STRUCTURE and FUNCTION of the PALMITOYLTRANSFERASE
STRUCTURE AND FUNCTION OF THE PALMITOYLTRANSFERASE DHHC20 AND THE ACYL COA HYDROLASE MBLAC2 A Dissertation Presented to the Faculty of the Graduate School Of Cornell University In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy By Martin Ian Paguio Malgapo December 2019 i © 2019 Martin Ian Paguio Malgapo ii STRUCTURE AND FUNCTION OF THE PALMITOYLTRANSFERASE DHHC20 AND THE ACYL COA HYDROLASE MBLAC2 Martin Ian Paguio Malgapo, Ph.D. Cornell University 2019 My graduate research has focused on the enzymology of protein S-palmitoylation, a reversible posttranslational modification catalyzed by DHHC palmitoyltransferases. When I started my thesis work, the structure of DHHC proteins was not known. I sought to purify and crystallize a DHHC protein, identifying DHHC20 as the best target. While working on this project, I came across a protein of unknown function called metallo-β-lactamase domain-containing protein 2 (MBLAC2). A proteomic screen utilizing affinity capture mass spectrometry suggested an interaction between MBLAC2 (bait) and DHHC20 (hit) in HEK-293 cells. This finding interested me initially from the perspective of finding an interactor that could help stabilize DHHC20 into forming better quality crystals as well as discovering a novel protein substrate for DHHC20. I was intrigued by MBLAC2 upon learning that this protein is predicted to be palmitoylated by multiple proteomic screens. Additionally, sequence analysis predicts MBLAC2 to have thioesterase activity. Taken together, studying a potential new thioesterase that is itself palmitoylated was deemed to be a worthwhile project. When the structure of DHHC20 was published in 2017, I decided to switch my efforts to characterizing MBLAC2. -
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The Journal of Neuroscience, June 15, 2016 • 36(24):6431–6444 • 6431 Cellular/Molecular Identification of PSD-95 Depalmitoylating Enzymes Norihiko Yokoi,1,3* Yuko Fukata,1,3*,‡ Atsushi Sekiya,1,3 Tatsuro Murakami,1,3 Kenta Kobayashi,2,3 and Masaki Fukata1,3‡ 1Division of Membrane Physiology, Department of Molecular and Cellular Physiology and 2Section of Viral Vector Development, Center for Genetic Analysis of Behavior, National Institute for Physiological Sciences (NIPS), National Institutes of Natural Sciences (NINS), and 3Department of Physiological Sciences, School of Life Science, SOKENDAI (The Graduate University for Advanced Studies), Okazaki, Aichi 444-8787, Japan Postsynaptic density (PSD)-95, the most abundant postsynaptic scaffolding protein, plays a pivotal role in synapse development and function. Continuous palmitoylation cycles on PSD-95 are essential for its synaptic clustering and regulation of AMPA receptor function. However,molecularmechanismsforpalmitatecyclingonPSD-95remainincompletelyunderstood,asPSD-95depalmitoylatingenzymes remain unknown. Here, we isolated 38 mouse or rat serine hydrolases and found that a subset specifically depalmitoylated PSD-95 in heterologous cells. These enzymes showed distinct substrate specificity. ␣/-Hydrolase domain-containing protein 17 members (ABHD17A, 17B, and 17C), showing the strongest depalmitoylating activity to PSD-95, showed different localization from other candi- dates in rat hippocampal neurons, and were distributed to recycling endosomes, the dendritic plasma membrane, and the synaptic fraction. Expression of ABHD17 in neurons selectively reduced PSD-95 palmitoylation and synaptic clustering of PSD-95 and AMPA receptors. Furthermore, taking advantage of the acyl-PEGyl exchange gel shift (APEGS) method, we quantitatively monitored the palmi- ␣ toylation stoichiometry and the depalmitoylation kinetics of representative synaptic proteins, PSD-95, GluA1, GluN2A, mGluR5, G q , and HRas. -
Genetics of Body Fat Distribution: Comparative Analyses in Populations with European, Asian and African Ancestries
G C A T T A C G G C A T genes Review Genetics of Body Fat Distribution: Comparative Analyses in Populations with European, Asian and African Ancestries Chang Sun 1 , Peter Kovacs 1 and Esther Guiu-Jurado 1,2,* 1 Medical Department III–Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, 04103 Leipzig, Germany; [email protected] (C.S.); [email protected] (P.K.) 2 Deutsches Zentrum für Diabetesforschung, 85764 Neuherberg, Germany * Correspondence: [email protected]; Tel.: +49-341-9715895 Abstract: Preferential fat accumulation in visceral vs. subcutaneous depots makes obese individuals more prone to metabolic complications. Body fat distribution (FD) is regulated by genetics. FD patterns vary across ethnic groups independent of obesity. Asians have more and Africans have less visceral fat compared with Europeans. Consequently, Asians tend to be more susceptible to type 2 diabetes even with lower BMIs when compared with Europeans. To date, genome-wide association studies (GWAS) have identified more than 460 loci related to FD traits. However, the majority of these data were generated in European populations. In this review, we aimed to summarize recent advances in FD genetics with a focus on comparisons between European and non-European populations (Asians and Africans). We therefore not only compared FD-related susceptibility loci identified in three ethnicities but also discussed whether known genetic variants might explain the FD pattern heterogeneity across different ancestries. Moreover, we describe several novel candidate genes potentially regulating FD, including NID2, HECTD4 and GNAS, identified in studies with Citation: Sun, C.; Kovacs, P.; Asian populations. -
A SARS-Cov-2 Protein Interaction Map Reveals Targets for Drug Repurposing
Article A SARS-CoV-2 protein interaction map reveals targets for drug repurposing https://doi.org/10.1038/s41586-020-2286-9 A list of authors and affiliations appears at the end of the paper Received: 23 March 2020 Accepted: 22 April 2020 A newly described coronavirus named severe acute respiratory syndrome Published online: 30 April 2020 coronavirus 2 (SARS-CoV-2), which is the causative agent of coronavirus disease 2019 (COVID-19), has infected over 2.3 million people, led to the death of more than Check for updates 160,000 individuals and caused worldwide social and economic disruption1,2. There are no antiviral drugs with proven clinical efcacy for the treatment of COVID-19, nor are there any vaccines that prevent infection with SARS-CoV-2, and eforts to develop drugs and vaccines are hampered by the limited knowledge of the molecular details of how SARS-CoV-2 infects cells. Here we cloned, tagged and expressed 26 of the 29 SARS-CoV-2 proteins in human cells and identifed the human proteins that physically associated with each of the SARS-CoV-2 proteins using afnity-purifcation mass spectrometry, identifying 332 high-confdence protein–protein interactions between SARS-CoV-2 and human proteins. Among these, we identify 66 druggable human proteins or host factors targeted by 69 compounds (of which, 29 drugs are approved by the US Food and Drug Administration, 12 are in clinical trials and 28 are preclinical compounds). We screened a subset of these in multiple viral assays and found two sets of pharmacological agents that displayed antiviral activity: inhibitors of mRNA translation and predicted regulators of the sigma-1 and sigma-2 receptors. -
SPEF2 Functions in Microtubule-Mediated Transport in Elongating Spermatids to Ensure Proper Male Germ Cell Differentiation Mari S
© 2017. Published by The Company of Biologists Ltd | Development (2017) 144, 2683-2693 doi:10.1242/dev.152108 RESEARCH ARTICLE SPEF2 functions in microtubule-mediated transport in elongating spermatids to ensure proper male germ cell differentiation Mari S. Lehti1,2,*, Fu-Ping Zhang2,3,*, Noora Kotaja2,* and Anu Sironen1,‡,§ ABSTRACT 2006, 2002). Mutations in the Spef2 gene (an amino acid substitution Sperm differentiation requires specific protein transport for correct within exon 3 and a nonsense mutation within exon 28) in the big giant sperm tail formation and head shaping. A transient microtubular head (bgh) mouse model caused a primary ciliary dyskinesia (PCD)- structure, the manchette, appears around the differentiating like phenotype, including hydrocephalus, sinusitis and male infertility spermatid head and serves as a platform for protein transport to the (Sironen et al., 2011). Detailed analysis of spermatogenesis in both pig growing tail. Sperm flagellar 2 (SPEF2) is known to be essential for and mouse models revealed axonemal abnormalities, including defects sperm tail development. In this study we investigated the function of in central pair (CP) structure and the complete disorganization of the SPEF2 during spermatogenesis using a male germ cell-specific sperm tail (Sironen et al., 2011). A role of SPEF2 in protein transport Spef2 knockout mouse model. In addition to defects in sperm tail has been postulated owing to its known interaction and colocalization development, we observed a duplication of the basal body and failure with intraflagellar transport 20 (IFT20). During spermatogenesis, in manchette migration resulting in an abnormal head shape. We IFT20 and SPEF2 colocalize in the Golgi complex of late identified cytoplasmic dynein 1 and GOLGA3 as novel interaction spermatocytes and round spermatids and in the manchette and basal partners for SPEF2.