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SI Correction SYSTEMS BIOLOGY Correction to Supporting Information for “miRNA proxy approach issue 23, June 9, 2015, of Proc Natl Acad Sci USA (112:7327–7332; reveals hidden functions of glycosylation,” by Tomasz Kurcon, first published May 26, 2015; 10.1073/pnas.1502076112). Zhongyin Liu, Anika V. Paradkar, Christopher A. Vaiana, Sujeethraj The authors note that Table S1, Table S3, and Table S4 ap- Koppolu, Praveen Agrawal, and Lara K. Mahal, which appeared in peared incorrectly. The SI has been corrected online. Table S1. Classification of miR-200f predicted glycogenes according to the type of glycan synthesized (related to Table S3) N-linked O-linked NC-O-linked GAGs Glycolipid Other/terminal ALG2 C1GALT1 B3GAT1 CSGALNACT2 B3GALT2 B3GALNT2 ALG5 GALNT2 B3GLCT B3GALT6 B3GALNT1 B3GNT1 ALG6 GALNT3 GXYLT1 CHST2 B3GNT4 B3GNT2 ALG8 GALNT4 LARGE CHST7 B3GNT5 FUT2 ALG11 GALNT10 LFNG CHST12 B4GALT6 FUT4 ALG14 GALNT11 OGT CHSY1 GAL3ST1 HAS2 DDOST GALNT12 POFUT1 CHSY3 ST3GAL5 HAS3 DPAGT1 GALNT14 EXTL2 ST3GAL6 ST3GAL2 MGAT2 GALNTL2 HS2ST1 ST6GALNAC3 ST3GAL3 MGAT3 GCNT2 HS3ST1 ST6GALNAC5 ST8SIA2 MGAT4A GCNT4 HS3ST3A1 UGCG ST8SIA4 MGAT4C HS3ST5 HS6ST1 HS6ST2 HS6ST3 NDST3 Count 12 11 7 16 11 11 % Total 17.6 16.2 10.3 23.5 16.2 16.2 miR-200f predicted glycogenes were classified according to the glycan they synthesize using the Kyoto Encyclopedia of Genes and Genomes. The % total represents the distribution of one type of glycan among all predicted targets. GAGs, glycosaminoglycans; NC O-linked, noncanonical O-linked. E4632–E4635 | PNAS | August 18, 2015 | vol. 112 | no. 33 www.pnas.org Downloaded by guest on September 28, 2021 Table S3. miR-200f target glycogene transcript expression profile in MDA-MB-231 cells treated with miR-200a, miR-200b, or scramble mimics miR-200a treatment miR-200b treatment Glycogene Fold change P values Glycogene Fold change P values Glycan type Shared predicted targets MGAT4A 1.06 0.74 MGAT4A 1.17 0.31 N-linked C1GALT1 −1.19 0.050 C1GALT1 −1.10 0.40 O-linked GCNT2 1.04 0.86 GCNT2 1.20 0.36 B3GLCT −1.06 0.69 B3GLCT −1.61 4.18E-03 NC O-linked ST3GAL5 −1.61 6.37E-03 ST3GAL5 −2.13 2.11E-04 Glycolipid ST6GALNAC3 1.62 0.20 ST6GALNAC3 1.11 0.76 B3GNT2 1.07 0.66 B3GNT2 1.22 0.15 Other/terminal miR-200b/-200c/-429 predicted targets MGAT2 −1.08 0.72 MGAT2 1.01 0.98 N-linked MGAT3 −1.86 0.12 MGAT3 1.30 0.15 MGAT4C 1.93 0.20 MGAT4C −1.00 1.00 GALNT2 −1.09 0.52 GALNT2 −1.40 0.022 O-linked GALNT3 1.03 0.71 GALNT3 2.30 4.52E-04 GALNT10 −1.14 0.11 GALNT10 −1.68 1.22E-03 GALNT11 −1.11 0.29 GALNT11 −1.26 0.011 GALNT12 −1.40 7.38E-03 GALNT12 −1.52 6.32E-03 GALNT14 −1.49 0.011 GALNT14 −1.94 5.92E-03 GCNT4 −1.18 0.16 GCNT4 −1.05 0.79 LFNG −1.49 0.21 LFNG −2.14 0.074 NC O-linked CHST12 1.09 0.81 CHST12 1.22 0.66 GAGs CHSY3 1.15 0.36 CHSY3 −1.04 0.68 EXTL2 −1.05 0.78 EXTL2 1.07 0.71 HS3ST1 1.99 0.044 HS3ST1 3.28 0.014 HS3ST3A1 −1.11 0.74 HS3ST3A1 −1.24 0.39 NDST3 −2.87 3.16E-03 NDST3 −6.96 4.58E-04 B3GALNT1 −1.11 0.56 B3GALNT1 −1.16 0.46 Glycolipid ST6GALNAC5 2.23 0.033 ST6GALNAC5 4.79 0.010 B3GNT1 −1.04 0.80 B3GNT1 −1.47 0.039 Other/terminal ST3GAL2 −1.18 0.20 ST3GAL2 −1.59 1.23E-03 ST8SIA4 −1.23 0.013 ST8SIA4 −1.15 0.22 miR−/−200a/-141 predicted targets GALNT4 −1.16 0.20 GALNT4 −1.17 0.077 O-linked OGT −1.09 0.50 OGT −1.02 0.88 NC O-linked POFUT1 −1.00 0.98 POFUT1 −1.01 0.90 B3GALT6 1.05 0.83 B3GALT6 1.00 0.99 GAGs HS6ST1 −1.19 0.46 HS6ST1 −1.14 0.56 HS6ST3 1.13 0.59 HS6ST3 4.37 1.41E-03 B3GNT4 1.29 0.075 B3GNT4 2.42 6.44E-04 Glycolipid B3GNT5 1.25 0.11 B3GNT5 1.70 2.62E-03 ST3GAL6 −1.18 0.30 ST3GAL6 1.01 0.91 ST3GAL3 −1.42 0.051 ST3G AL3 −1.43 0.035 Other/terminal MDA-MB-231 cells were treated with miR-200a, miR-200b. or scramble mimics (50 nM) for 7 d. The qRT-PCR was performed using RT2 Profiler PCR Array Human Glycosylation (Qiagen) or custom primers for genes not repre- sented on the array (Dataset S1). Fold change (miR-treated/scramble) was calculated by taking the average relative expression of miR-treated samples (n = 4 independent experiments, normalized to GAPDH) over the average SI CORRECTION relative expression of the scramble treated cells (n = 4 independent experiments, normalized to GAPDH). Where the fold change was less than 1, the negative inverse is shown. P values for treated vs. scramble were calculated using Student’s t test. Statistically significant (P ≤ 0.05) down-regulation is in bold; up-regulation is underlined. GAGs, glycosaminoglycans; NC O-linked, noncanonical O-linked; See Table S1 for glycan type distribution. *Genes for which luciferase data were obtained (Fig. 1). PNAS | August 18, 2015 | vol. 112 | no. 33 | E4633 Downloaded by guest on September 28, 2021 Table S4. Expression profile of glycogenes not predicted to be targets of the miR-200 family in MDA-MB-231 cells treated with miR-200a, miR-200b, or scramble mimics miR-200a treatment miR-200b treatment Glycogene Fold change P values Glycogene Fold change P values A4GNT −1.41 7.17E-03 A4GNT −1.81 1.14E-03 AGA −1.37 2.50E-03 AGA −1.17 0.24 B3GNT3 13.51 5.78E-06 B3GNT3 67.80 1.35E-05 B3GNT8 −1.14 0.42 B3GNT8 1.01 0.95 B4GALT1 −1.17 0.20 B4GALT1 −1.15 0.16 B4GALT2 1.01 0.97 B4GALT2 −1.02 0.92 B4GALT3 1.21 0.43 B4GALT3 1.32 0.19 B4GALT5 1.11 0.62 B4GALT5 1.61 0.021 C1GALT1C1 −1.01 0.94 C1GALT1C1 1.02 0.80 EDEM1 −1.07 0.59 EDEM1 −1.05 0.65 EDEM2 −1.06 0.60 EDEM2 1.04 0.66 EDEM3 1.02 0.79 EDEM3 −1.10 0.23 FUCA1 −1.09 0.31 FUCA1 −1.12 0.19 FUCA2 −1.09 0.24 FUCA2 −1.03 0.61 FUT8 1.20 0.19 FUT8 −1.07 0.45 FUT11 1.03 0.79 FUT11 1.28 0.12 GALNT1 1.15 0.29 GALNT1 −1.12 0.30 GALNT6 2.14 3.74E-04 GALNT6 1.79 9.89E-05 GALNT7 −1.07 0.60 GALNT7 −1.09 0.39 GALNT8 −1.69 0.21 GALNT8 −2.07 0.18 GALNT9 −2.19 0.12 GALNT9 −1.90 0.17 GALNT13 −1.16 0.024 GALNT13 1.03 0.63 GALNTL1 −1.61 0.013 GALNTL1 −2.02 3.34E-03 GALNTL5 1.41 0.36 GALNTL5 1.08 0.36 GALNTL6 −2.06 0.12 GALNTL6 −3.08 0.048 GANAB −1.01 0.92 GANAB −1.02 0.80 GCNT1 −1.61 8.08E-05 GCNT1 −1.63 3.98E-03 GCNT3 −1.18 0.35 GCNT3 1.49 0.23 GLB1 −1.06 0.73 GLB1 −1.17 0.26 GNPTAB −1.15 0.19 GNPTAB −1.03 0.84 GNPTG −1.15 0.26 GNPTG −1.13 0.22 HEXA −1.11 0.36 HEXA −1.14 0.091 HEXB −1.13 0.24 HEXB −1.17 0.11 MAN1A1 1.09 0.54 MAN1A1 −1.14 0.45 MAN1A2 1.02 0.88 MAN1A2 −1.15 0.25 MAN1B1 −1.06 0.56 MAN1B1 −1.08 0.41 MAN1C1 −1.07 0.76 MAN1C1 −1.39 0.039 MAN2A1 −1.06 0.23 MAN2A1 1.13 0.23 MAN2A2 1.24 0.41 MAN2A2 1.43 0.12 MAN2B1 1.04 0.89 MAN2B1 1.01 0.97 MANBA −1.21 5.54E-04 MANBA −1.22 0.015 MGAT1 1.18 0.36 MGAT1 1.37 0.019 MGAT4B 1.13 0.39 MGAT4B 1.13 0.17 MGAT5 1.27 0.32 MGAT5 1.31 0.25 MGAT5B −1.29 0.15 MGAT5B −2.24 3.69E-03 MGEA5 −1.06 0.58 MGEA5 1.02 0.71 MOGS 1.10 0.63 MOGS 1.32 0.092 NAGPA −1.33 0.32 NAGPA −1.40 0.20 NEU1 −1.08 0.63 NEU1 1.25 0.10 NEU2 1.43 0.24 NEU2 1.62 0.032 NEU3 −1.05 0.63 NEU3 1.24 0.074 NEU4 −1.35 0.51 NEU4 −1.63 0.36 POFUT2 −1.14 0.18 POFUT2 −1.25 0.014 POMGNT1 1.06 0.71 POMGNT1 −1.05 0.59 POMT1 −1.18 0.33 POMT1 −1.07 0.61 POMT2 1.07 0.66 POMT2 1.02 0.85 PRKCSH 1.02 0.86 PRKCSH 1.07 0.39 ST3GAL1 1.19 0.056 ST3GAL1 1.21 0.027 ST6GAL1 −1.60 8.50E-03 ST6GAL1 −2.08 3.80E-04 ST6GALNAC1 4.57 0.044 ST6GALNAC1 9.10 6.11E-03 E4634 | www.pnas.org Downloaded by guest on September 28, 2021 Table S4. Cont. miR-200a treatment miR-200b treatment Glycogene Fold change P values Glycogene Fold change P values ST8SIA3 −1.11 0.91 ST8SIA3 −1.06 0.95 ST8SIA6 −1.72 0.017 ST8SIA6 −3.13 1.77E-03 UGGT1 −1.03 0.87 UGGT1 −1.15 0.30 UGGT2 −1.09 0.44 UGGT2 −1.18 0.093 MDA-MB-231 cells were treated with miR-200a, miR-200b, or scramble mimics (50 nM) for 7 d.
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  • GM2 Gangliosidoses: Clinical Features, Pathophysiological Aspects, and Current Therapies

    GM2 Gangliosidoses: Clinical Features, Pathophysiological Aspects, and Current Therapies

    International Journal of Molecular Sciences Review GM2 Gangliosidoses: Clinical Features, Pathophysiological Aspects, and Current Therapies Andrés Felipe Leal 1 , Eliana Benincore-Flórez 1, Daniela Solano-Galarza 1, Rafael Guillermo Garzón Jaramillo 1 , Olga Yaneth Echeverri-Peña 1, Diego A. Suarez 1,2, Carlos Javier Alméciga-Díaz 1,* and Angela Johana Espejo-Mojica 1,* 1 Institute for the Study of Inborn Errors of Metabolism, Faculty of Science, Pontificia Universidad Javeriana, Bogotá 110231, Colombia; [email protected] (A.F.L.); [email protected] (E.B.-F.); [email protected] (D.S.-G.); [email protected] (R.G.G.J.); [email protected] (O.Y.E.-P.); [email protected] (D.A.S.) 2 Faculty of Medicine, Universidad Nacional de Colombia, Bogotá 110231, Colombia * Correspondence: [email protected] (C.J.A.-D.); [email protected] (A.J.E.-M.); Tel.: +57-1-3208320 (ext. 4140) (C.J.A.-D.); +57-1-3208320 (ext. 4099) (A.J.E.-M.) Received: 6 July 2020; Accepted: 7 August 2020; Published: 27 August 2020 Abstract: GM2 gangliosidoses are a group of pathologies characterized by GM2 ganglioside accumulation into the lysosome due to mutations on the genes encoding for the β-hexosaminidases subunits or the GM2 activator protein. Three GM2 gangliosidoses have been described: Tay–Sachs disease, Sandhoff disease, and the AB variant. Central nervous system dysfunction is the main characteristic of GM2 gangliosidoses patients that include neurodevelopment alterations, neuroinflammation, and neuronal apoptosis. Currently, there is not approved therapy for GM2 gangliosidoses, but different therapeutic strategies have been studied including hematopoietic stem cell transplantation, enzyme replacement therapy, substrate reduction therapy, pharmacological chaperones, and gene therapy.
  • Investigation of the Underlying Hub Genes and Molexular Pathogensis in Gastric Cancer by Integrated Bioinformatic Analyses

    Investigation of the Underlying Hub Genes and Molexular Pathogensis in Gastric Cancer by Integrated Bioinformatic Analyses

    bioRxiv preprint doi: https://doi.org/10.1101/2020.12.20.423656; this version posted December 22, 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. Investigation of the underlying hub genes and molexular pathogensis in gastric cancer by integrated bioinformatic analyses Basavaraj Vastrad1, Chanabasayya Vastrad*2 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2020.12.20.423656; this version posted December 22, 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. Abstract The high mortality rate of gastric cancer (GC) is in part due to the absence of initial disclosure of its biomarkers. The recognition of important genes associated in GC is therefore recommended to advance clinical prognosis, diagnosis and and treatment outcomes. The current investigation used the microarray dataset GSE113255 RNA seq data from the Gene Expression Omnibus database to diagnose differentially expressed genes (DEGs). Pathway and gene ontology enrichment analyses were performed, and a proteinprotein interaction network, modules, target genes - miRNA regulatory network and target genes - TF regulatory network were constructed and analyzed. Finally, validation of hub genes was performed. The 1008 DEGs identified consisted of 505 up regulated genes and 503 down regulated genes.
  • Salmonella Degrades the Host Glycocalyx Leading to Altered Infection and Glycan Remodeling

    Salmonella Degrades the Host Glycocalyx Leading to Altered Infection and Glycan Remodeling

    UC Davis UC Davis Previously Published Works Title Salmonella Degrades the Host Glycocalyx Leading to Altered Infection and Glycan Remodeling. Permalink https://escholarship.org/uc/item/0nk8n7xb Journal Scientific reports, 6(1) ISSN 2045-2322 Authors Arabyan, Narine Park, Dayoung Foutouhi, Soraya et al. Publication Date 2016-07-08 DOI 10.1038/srep29525 Peer reviewed eScholarship.org Powered by the California Digital Library University of California www.nature.com/scientificreports OPEN Salmonella Degrades the Host Glycocalyx Leading to Altered Infection and Glycan Remodeling Received: 09 February 2016 Narine Arabyan1, Dayoung Park2, Soraya Foutouhi1, Allison M. Weis1, Bihua C. Huang1, Accepted: 17 June 2016 Cynthia C. Williams2, Prerak Desai1,†, Jigna Shah1,‡, Richard Jeannotte1,3,§, Nguyet Kong1, Published: 08 July 2016 Carlito B. Lebrilla2,4 & Bart C. Weimer1 Complex glycans cover the gut epithelial surface to protect the cell from the environment. Invasive pathogens must breach the glycan layer before initiating infection. While glycan degradation is crucial for infection, this process is inadequately understood. Salmonella contains 47 glycosyl hydrolases (GHs) that may degrade the glycan. We hypothesized that keystone genes from the entire GH complement of Salmonella are required to degrade glycans to change infection. This study determined that GHs recognize the terminal monosaccharides (N-acetylneuraminic acid (Neu5Ac), galactose, mannose, and fucose) and significantly (p < 0.05) alter infection. During infection, Salmonella used its two GHs sialidase nanH and amylase malS for internalization by targeting different glycan structures. The host glycans were altered during Salmonella association via the induction of N-glycan biosynthesis pathways leading to modification of host glycans by increasing fucosylation and mannose content, while decreasing sialylation.