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Chen XG, Jiang X, Gu J, Xu M, Wu Y, Deng Y, Zhang C, Bonizzoni M, Dermauw W, Vontas J, Armbruster P, Huang X, Yang Y, Zhang H, He W, Peng H, Liu Y, Wu K, Chen J, Lirakis M, Topalis P, Van Leeuwen T, Hall AB, Jiang X, Thorpe C, Mueller RL, Sun C, Waterhouse RM, Yan G, Tu ZJ, Fang X, James AA. Genome sequence of the Asian Tiger mosquito, Aedes albopictus, reveals insights into its biology, genetics, and evolution. Proc Natl Acad Sci U S A 2015; 112:E5907-15. [PMID: 26483478 PMCID: PMC4640774 DOI: 10.1073/pnas.1516410112] [Citation(s) in RCA: 188] [Impact Index Per Article: 20.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The Asian tiger mosquito, Aedes albopictus, is a highly successful invasive species that transmits a number of human viral diseases, including dengue and Chikungunya fevers. This species has a large genome with significant population-based size variation. The complete genome sequence was determined for the Foshan strain, an established laboratory colony derived from wild mosquitoes from southeastern China, a region within the historical range of the origin of the species. The genome comprises 1,967 Mb, the largest mosquito genome sequenced to date, and its size results principally from an abundance of repetitive DNA classes. In addition, expansions of the numbers of members in gene families involved in insecticide-resistance mechanisms, diapause, sex determination, immunity, and olfaction also contribute to the larger size. Portions of integrated flavivirus-like genomes support a shared evolutionary history of association of these viruses with their vector. The large genome repertory may contribute to the adaptability and success of Ae. albopictus as an invasive species.
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Affiliation(s)
- Xiao-Guang Chen
- Department of Pathogen Biology, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou 510515, China;
| | - Xuanting Jiang
- Beijing Genomics Institute-Shenzhen, Shenzhen 518083, China
| | - Jinbao Gu
- Department of Pathogen Biology, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou 510515, China
| | - Meng Xu
- Beijing Genomics Institute-Shenzhen, Shenzhen 518083, China
| | - Yang Wu
- Department of Pathogen Biology, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou 510515, China
| | - Yuhua Deng
- Department of Pathogen Biology, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou 510515, China
| | - Chi Zhang
- Beijing Genomics Institute-Shenzhen, Shenzhen 518083, China
| | - Mariangela Bonizzoni
- Program in Public Health, University of California, Irvine, CA 92697; Department of Biology and Biotechnology, University of Pavia, 27100 Pavia, Italy
| | - Wannes Dermauw
- Laboratory of Agrozoology, Department of Crop Protection, Faculty of Bioscience Engineering, Ghent University, B-9000 Ghent, Belgium
| | - John Vontas
- Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology-Hellas, 73100 Heraklion, Greece; Faculty of Crop Science, Pesticide Science Lab, Agricultural University of Athens, 11855 Athens, Greece
| | - Peter Armbruster
- Department of Biology, Georgetown University, Washington, DC 20057
| | - Xin Huang
- Department of Biology, Georgetown University, Washington, DC 20057
| | - Yulan Yang
- Beijing Genomics Institute-Shenzhen, Shenzhen 518083, China
| | - Hao Zhang
- Department of Pathogen Biology, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou 510515, China
| | - Weiming He
- Beijing Genomics Institute-Shenzhen, Shenzhen 518083, China
| | - Hongjuan Peng
- Department of Pathogen Biology, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou 510515, China
| | - Yongfeng Liu
- Beijing Genomics Institute-Shenzhen, Shenzhen 518083, China
| | - Kun Wu
- Department of Pathogen Biology, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou 510515, China
| | - Jiahua Chen
- Beijing Genomics Institute-Shenzhen, Shenzhen 518083, China
| | - Manolis Lirakis
- Department of Biology, University of Crete, Heraklion, GR-74100, Crete, Greece
| | - Pantelis Topalis
- Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology-Hellas, 73100 Heraklion, Greece
| | - Thomas Van Leeuwen
- Department of Biology and Biotechnology, University of Pavia, 27100 Pavia, Italy; Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, 1090 GE Amsterdam, The Netherlands
| | - Andrew Brantley Hall
- Interdisciplinary PhD Program in Genetics, Bioinformatics, and Computational Biology, Virginia Tech University, Blacksburg, VA 24061; Department of Biochemistry, Fralin Life Science Institute, Virginia Tech University, Blacksburg, VA 24061
| | - Xiaofang Jiang
- Interdisciplinary PhD Program in Genetics, Bioinformatics, and Computational Biology, Virginia Tech University, Blacksburg, VA 24061; Department of Biochemistry, Fralin Life Science Institute, Virginia Tech University, Blacksburg, VA 24061
| | - Chevon Thorpe
- Cellular and Molecular Physiology, Edward Via College of Osteopathic Medicine, Blacksburg, VA 24060
| | | | - Cheng Sun
- Department of Biology, Colorado State University, Fort Collins, CO 80523
| | - Robert Michael Waterhouse
- Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland; Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139; The Broad Institute of MIT and Harvard, Cambridge, MA 02142
| | - Guiyun Yan
- Department of Pathogen Biology, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou 510515, China; Program in Public Health, University of California, Irvine, CA 92697
| | - Zhijian Jake Tu
- Interdisciplinary PhD Program in Genetics, Bioinformatics, and Computational Biology, Virginia Tech University, Blacksburg, VA 24061; Department of Biochemistry, Fralin Life Science Institute, Virginia Tech University, Blacksburg, VA 24061
| | - Xiaodong Fang
- Beijing Genomics Institute-Shenzhen, Shenzhen 518083, China;
| | - Anthony A James
- Departments of Microbiology & Molecular Genetics and Molecular Biology & Biochemistry, University of California, Irvine, CA 92697
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Li H, Shen H, Yan G, Zhang Y, Liu M, Fang P, Yu H, Yang P. Site-specific structural characterization of O-glycosylation and identification of phosphorylation sites of recombinant osteopontin. BIOCHIMICA ET BIOPHYSICA ACTA-PROTEINS AND PROTEOMICS 2014; 1854:581-91. [PMID: 25450502 DOI: 10.1016/j.bbapap.2014.09.025] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/15/2014] [Revised: 08/25/2014] [Accepted: 09/30/2014] [Indexed: 12/21/2022]
Abstract
Osteopontin (OPN) plays a key role in multiple physiological and pathological processes such as cytokine production, mineralization, inflammation, immune responses, and tumorigenesis. Post-translational modifications (PTMs) of OPN significantly affect its structure and biological properties; however, site-specific characterization of O-glycosylation in human OPN has not been reported. In this work, we profiled the overall glycan pattern of human recombinant OPN using a lectin array and completed detailed structural analysis of O-glycopeptides by mass spectrometry (MS). We detected 28 O-glycopeptides from 7 O-glycosylation regions of human OPN, occupied by highly heterogeneous O-glycans. These O-glycans carried, in part, functionally relevant epitopes such as T antigens (Galβ1-3GalNAcα1-), sialyl-Tn antigens, sialyl-T antigens, and sialyl-Le(x/a) antigens [Neuα2-3Galβ1-4(Fucα1-3)GlcNAc/Neuα2-3Galβ1-3(Fucα1-4)GlcNAc]. MS(3) spectra of the generated O-glycopeptides showed cleavages of the peptide backbone and provided essential information on the peptide sequence. Furthermore, 26 phosphorylation sites were identified by reverse-phase liquid chromatography-tandem mass spectrometry (RPLC-MS/MS), including a novel one (Y209). We provide a detailed, site-specific structural characterization of O-glycosylation and identify the phosphorylation sites of OPN. These data lay the foundation for further research into the role of oligosaccharides and phosphorylation of recombinant human OPN. This article is part of a Special Issue entitled: Medical Proteomics.
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Affiliation(s)
- Hong Li
- Department of Chemistry, Fudan University, Shanghai 200032, PR China; Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, PR China
| | - Huali Shen
- Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, PR China
| | - Guoquan Yan
- Department of Chemistry, Fudan University, Shanghai 200032, PR China; Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, PR China
| | - Yang Zhang
- Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, PR China
| | - Mingqi Liu
- Department of Chemistry, Fudan University, Shanghai 200032, PR China; Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, PR China
| | - Pan Fang
- Department of Chemistry, Fudan University, Shanghai 200032, PR China; Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, PR China
| | - Hongxiu Yu
- Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, PR China.
| | - Pengyuan Yang
- Department of Chemistry, Fudan University, Shanghai 200032, PR China; Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, PR China.
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Chen Y, Cao J, Yan G, Lu H, Yang P. Two-step protease digestion and glycopeptide capture approach for accurate glycosite identification and glycoprotein sequence coverage improvement. Talanta 2011; 85:70-5. [PMID: 21645671 DOI: 10.1016/j.talanta.2011.03.029] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2010] [Revised: 03/05/2011] [Accepted: 03/12/2011] [Indexed: 11/27/2022]
Abstract
A novel two-step protease digestion and glycopeptide capture approach has been developed. It is different from traditional tryptic digestion, glycopeptide enriching and identification approach in glycoproteomics. Here, proteins were first digested by Lys-C into relatively large peptides. Glycopeptides among them were selectively captured by hydrazide resin through oxidized glycans. After thorough washing steps, trypsin was used as a second protease to in situ release non-glycosylated part (named as LT-peptides) from glycopeptides. Subsequently, the remaining part of glycopeptides on resin was de-glycosylated by peptide-N-glycosidase F, and collected as DG-peptides. Finally, both LT- and DG-peptides could be analyzed by mass spectrometer, achieving glycoprotein and glycosite identification. The approach was applied to cell lysate after positive validation by a model glycoprotein: 143 N-glycoproteins identified from DG- and LT-fraction both. In those glycoproteins, 189 DG-peptide-revealed N-glycosites got further confirmation by neighboring LT-peptides, which, in the meantime, made 109 glycoproteins get improved sequence coverage with increase even up to 350% (averagely 79.4%). Through controllable release, separate identification and combined interpretation of non-glycopeptides (newly introduced LT-peptides here) and traditional de-glycopeptides, the approach could not only achieve routine N-glycosite identification, but also provide further proofs of N-glycosites and increase glycoprotein sequence coverage.
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Affiliation(s)
- Yaohan Chen
- Department of Chemistry, Fudan University, Shanghai 200433, PR China
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