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      Discordant congenital Zika syndrome twins show differential in vitro viral susceptibility of neural progenitor cells

      research-article
      Author(s): 1 , 1 , 1 , 2 , 3 , 1 , 4 , 1 , 1 , 1 , 5 , 1 , 4 , 6 , 4 , 4 , 4 , 5 , 7 , 1 , 1 , 1 , 1 , 1 , 8 , 9 , 10 , 11 , 12 , 1 , 13 , 14 , 15 , 16 , 16 , 3 , 4 , 17 , 18 , 19 , 19 , 4 , 6 , 4 , 1 , 1 ,
      Publication date (Electronic):
      Journal: Nature Communications
      Publisher: Nature Publishing Group UK

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          Abstract

          Congenital Zika syndrome (CZS) causes early brain development impairment by affecting neural progenitor cells (NPCs). Here, we analyze NPCs from three pairs of dizygotic twins discordant for CZS. We compare by RNA-Seq the NPCs derived from CZS-affected and CZS-unaffected twins. Prior to Zika virus (ZIKV) infection the NPCs from CZS babies show a significantly different gene expression signature of mTOR and Wnt pathway regulators, key to a neurodevelopmental program. Following ZIKV in vitro infection, cells from affected individuals have significantly higher ZIKV replication and reduced cell growth. Whole-exome analysis in 18 affected CZS babies as compared to 5 unaffected twins and 609 controls excludes a monogenic model to explain resistance or increased susceptibility to CZS development. Overall, our results indicate that CZS is not a stochastic event and depends on NPC intrinsic susceptibility, possibly related to oligogenic and/or epigenetic mechanisms.

          Abstract

          Zika virus (ZIKV) infection can cause congenital Zika syndrome (CZS), but the underlying mechanisms are poorly understood. Here, the authors generate neural progenitor cells from dizygotic twins with a discordant phenotype regarding CZS and study their response to ZIKV infection.

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          DANN: a deep learning approach for annotating the pathogenicity of genetic variants.

          Daniel Quang, Yifei Chen, Xiaohui Xie (2015)
          Annotating genetic variants, especially non-coding variants, for the purpose of identifying pathogenic variants remains a challenge. Combined annotation-dependent depletion (CADD) is an algorithm designed to annotate both coding and non-coding variants, and has been shown to outperform other annotation algorithms. CADD trains a linear kernel support vector machine (SVM) to differentiate evolutionarily derived, likely benign, alleles from simulated, likely deleterious, variants. However, SVMs cannot capture non-linear relationships among the features, which can limit performance. To address this issue, we have developed DANN. DANN uses the same feature set and training data as CADD to train a deep neural network (DNN). DNNs can capture non-linear relationships among features and are better suited than SVMs for problems with a large number of samples and features. We exploit Compute Unified Device Architecture-compatible graphics processing units and deep learning techniques such as dropout and momentum training to accelerate the DNN training. DANN achieves about a 19% relative reduction in the error rate and about a 14% relative increase in the area under the curve (AUC) metric over CADD's SVM methodology. All data and source code are available at https://cbcl.ics.uci.edu/public_data/DANN/. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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            Congenital Zika virus syndrome in Brazil: a case series of the first 1501 livebirths with complete investigation.

            Giovanny França, Lavinia Schuler-Faccini, Wanderson K. Oliveira … (2016)
            In November, 2015, an epidemic of microcephaly was reported in Brazil, which was later attributed to congenital Zika virus infection. 7830 suspected cases had been reported to the Brazilian Ministry of Health by June 4, 2016, but little is known about their characteristics. We aimed to describe these newborn babies in terms of clinical findings, anthropometry, and survival.
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              Zika Virus NS4A and NS4B Proteins Deregulate Akt-mTOR Signaling in Human Fetal Neural Stem Cells to Inhibit Neurogenesis and Induce Autophagy.

              Qiming Liang, Zhifei Luo, Jianxiong Zeng … (2016)
              The current widespread outbreak of Zika virus (ZIKV) infection has been linked to severe clinical birth defects, particularly microcephaly, warranting urgent study of the molecular mechanisms underlying ZIKV pathogenesis. Akt-mTOR signaling is one of the key cellular pathways essential for brain development and autophagy regulation. Here, we show that ZIKV infection of human fetal neural stem cells (fNSCs) causes inhibition of the Akt-mTOR pathway, leading to defective neurogenesis and aberrant activation of autophagy. By screening the three structural proteins and seven nonstructural proteins present in ZIKV, we found that two, NS4A and NS4B, cooperatively suppress the Akt-mTOR pathway and lead to cellular dysregulation. Corresponding proteins from the closely related dengue virus do not have the same effect on neurogenesis. Thus, our study highlights ZIKV NS4A and NS4B as candidate determinants of viral pathogenesis and identifies a mechanism of action for their effects, suggesting potential targets for anti-ZIKV therapeutic intervention.
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                Author and article information

                Contributors
                Mayana Zatz: mayazatz@usp.br
                Journal
                Journal ID (nlm-ta): Nat Commun
                Journal ID (iso-abbrev): Nat Commun
                Title: Nature Communications
                Publisher: Nature Publishing Group UK (London )
                ISSN (Electronic): 2041-1723
                Publication date (Electronic): 2 February 2018
                Publication date PMC-release: 2 February 2018
                Publication date Collection: 2018
                Volume: 9
                Electronic Location Identifier: 475
                Affiliations
                [1 ]ISNI 0000 0004 1937 0722, GRID grid.11899.38, Department of Genetics and Evolutionary Biology, Human Genome and Stem Cell Research Center, Biosciences Institute, , University of São Paulo (USP), ; São Paulo – SP, 05508-900 Brazil
                [2 ]ISNI 0000 0004 0445 0877, GRID grid.452567.7, Brazilian Biosciences National Laboratory (LNBio), , Brazilian Center for Research in Energy and Materials (CNPEM), ; Campinas – SP, 13083-970 Brazil
                [3 ]ISNI 0000 0001 0514 7202, GRID grid.411249.b, Neuroscience laboratory, Department of Neurology and Neurosurgery, , Federal University of São Paulo—UNIFESP/EPM, ; São Paulo – SP, 04039-002 Brazil
                [4 ]ISNI 0000 0001 1702 8585, GRID grid.418514.d, Butantan Institute, ; São Paulo – SP, 05503-900 Brazil
                [5 ]ISNI 0000 0001 0385 1941, GRID grid.413562.7, Albert Einstein Hospital, ; São Paulo – SP, 05652-900 Brazil
                [6 ]ISNI 0000 0004 1937 0722, GRID grid.11899.38, Department of Biochemistry, Institute of Chemistry, , University of São Paulo (USP), ; São Paulo – SP, 05508-900 Brazil
                [7 ]ISNI 0000 0000 8848 9293, GRID grid.412278.a, Universidade de Mogi das Cruzes, ; Mogi das Cruzes – SP, 08780-911 Brazil
                [8 ]AACD, Recife – PE, 50080-810 Brazil
                [9 ]Rehabilitation Center—Dr. Henrique Santillo, Goiânia – GO, 74653-230 Brazil
                [10 ]ISNI 0000 0001 0670 7996, GRID grid.411227.3, Neuropsychiatry Department and KeizoAsami Laboratory, , Federal University of Pernambuco (UFPE), ; Recife – PE, 50670-901 Brazil
                [11 ]ISNI 0000 0000 9687 399X, GRID grid.411233.6, Department of Pediatrics, , Federal University of Rio Grande do Norte (UFRN), ; Natal– RN, 59010-180 Brazil
                [12 ]ISEA, Campina Grande– PB, 58400-220 Brazil
                [13 ]Department of Biology, Paraíba State University (UEPB), Campina Grande – PB, 58429-500 Brazil
                [14 ]ISNI 0000 0004 0372 8259, GRID grid.8399.b, Federal University of Bahia (UFBA), ; Salvador – BA, 40170-115 Brazil
                [15 ]Infectious pediatric laboratory, Medicine School of Jundiaí, Jundiaí – SP, 13202-550 Brazil
                [16 ]ISNI 0000 0001 2285 6801, GRID grid.411252.1, Division of Immunology and Molecular Biology Laboratory, , Federal University of Sergipe (UFS), ; Aracaju – SP, 49100-000 Brazil
                [17 ]ISNI 0000 0004 1937 0722, GRID grid.11899.38, Heart Institute, Faculty of Medicine, , University of São Paulo (USP), ; São Paulo – SP, 05403-900 Brazil
                [18 ]ISNI 0000 0004 1937 0722, GRID grid.11899.38, Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, , University of São Paulo (USP), ; São Paulo – SP, 05508-900 Brazil
                [19 ]ISNI 0000 0004 1937 0722, GRID grid.11899.38, Vaccine Development Laboratory, Department of Microbiology, Institute of Biomedical Science, , University of São Paulo (USP), ; São Paulo – SP, 05508-900 Brazil
                Author information
                http://orcid.org/0000-0003-0012-4217
                http://orcid.org/0000-0001-5297-9108
                http://orcid.org/0000-0002-6356-2401
                Article
                Publisher ID: 2790
                DOI: 10.1038/s41467-017-02790-9
                PMC ID: 5797251
                PubMed ID: 29396410
                SO-VID: 0bab1869-e562-460d-ba53-0bd6d95c8e2b
                Copyright © © The Author(s) 2018
                License:

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                Date received : 10 October 2017
                Date accepted : 28 December 2017
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                Subject: Article
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                issue-copyright-statement © The Author(s) 2018

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