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      Proteopeptidomic, Functional and Immunoreactivity Characterization of Bothrops moojeni Snake Venom: Influence of Snake Gender on Venom Composition

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          Abstract

          Venom composition varies across snakes from all taxonomic levels and is influenced by the snakes’ age, habitat, diet, and sexual dimorphism. The present study reports the first in-depth investigation of venom composition in male and female Bothrops moojeni ( B. moojeni) snakes (BmooM and BmooF, respectively) through three proteomics approaches associated with functional, cytotoxic, and immunoreactivity characterization. Compared with BmooM venom, BmooF venom exhibited weaker hyaluronidase, metalloproteinase, and phospholipase activity; stronger recognition by anti-bothropic serum; 1.4-fold stronger cytotoxicity; and greater number of peptides. The increased L-amino acid oxidase expression probably accounted for the stronger immunoreactivity and cytotoxicity of BmooF venom. BmooF and BmooM venom shared only 19% peptides. Some venom components were gender-specific, such as phospholipases B, phospholipase inhibitor, and hyaluronidases in BmooM, and cysteine-rich secretory proteins in BmooF. In conclusion, we describe herein the first proteomics study of B. moojeni snake venom and an in-depth characterization of gender-specific differences in venom composition. Altogether, our findings not only stress the importance of considering the snake’s gender during antivenom production, but also help to identify new potential drugs and biotechnological tools.

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          Most cited references41

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          PEAKS: powerful software for peptide de novo sequencing by tandem mass spectrometry.

          A number of different approaches have been described to identify proteins from tandem mass spectrometry (MS/MS) data. The most common approaches rely on the available databases to match experimental MS/MS data. These methods suffer from several drawbacks and cannot be used for the identification of proteins from unknown genomes. In this communication, we describe a new de novo sequencing software package, PEAKS, to extract amino acid sequence information without the use of databases. PEAKS uses a new model and a new algorithm to efficiently compute the best peptide sequences whose fragment ions can best interpret the peaks in the MS/MS spectrum. The output of the software gives amino acid sequences with confidence scores for the entire sequences, as well as an additional novel positional scoring scheme for portions of the sequences. The performance of PEAKS is compared with Lutefisk, a well-known de novo sequencing software, using quadrupole-time-of-flight (Q-TOF) data obtained for several tryptic peptides from standard proteins. Copyright 2003 John Wiley & Sons, Ltd.
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            Direct analysis of protein complexes using mass spectrometry.

            We describe a rapid, sensitive process for comprehensively identifying proteins in macromolecular complexes that uses multidimensional liquid chromatography (LC) and tandem mass spectrometry (MS/MS) to separate and fragment peptides. The SEQUEST algorithm, relying upon translated genomic sequences, infers amino acid sequences from the fragment ions. The method was applied to the Saccharomyces cerevisiae ribosome leading to the identification of a novel protein component of the yeast and human 40S subunit. By offering the ability to identify >100 proteins in a single run, this process enables components in even the largest macromolecular complexes to be analyzed comprehensively.
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              The One Hour Yeast Proteome*

              We describe the comprehensive analysis of the yeast proteome in just over one hour of optimized analysis. We achieve this expedited proteome characterization with improved sample preparation, chromatographic separations, and by using a new Orbitrap hybrid mass spectrometer equipped with a mass filter, a collision cell, a high-field Orbitrap analyzer, and, finally, a dual cell linear ion trap analyzer (Q-OT-qIT, Orbitrap Fusion). This system offers high MS2 acquisition speed of 20 Hz and detects up to 19 peptide sequences within a single second of operation. Over a 1.3 h chromatographic method, the Q-OT-qIT hybrid collected an average of 13,447 MS1 and 80,460 MS2 scans (per run) to produce 43,400 (x̄) peptide spectral matches and 34,255 (x̄) peptides with unique amino acid sequences (1% false discovery rate (FDR)). On average, each one hour analysis achieved detection of 3,977 proteins (1% FDR). We conclude that further improvements in mass spectrometer scan rate could render comprehensive analysis of the human proteome within a few hours.
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                Author and article information

                Journal
                Toxins (Basel)
                Toxins (Basel)
                toxins
                Toxins
                MDPI
                2072-6651
                26 April 2018
                May 2018
                : 10
                : 5
                : 177
                Affiliations
                [1 ]Laboratory of Toxinology, Department of Clinical Analysis, Toxicology and Food Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo—USP, Ribeirão Preto, SP 14040-903, Brazil; tassiarcosta@ 123456yahoo.com.br
                [2 ]GIGA Proteomics Facility, GIGA Institute, University of Liège, 4000 Liège, Belgium; d.baiwir@ 123456uliege.be
                [3 ]Laboratory of Mass Spectrometry, Department of Chemistry, University of Liège, 4000 Liège, Belgium; e.depauw@ 123456ulg.ac.be (E.D.P.); loic.quinton@ 123456ulg.ac.be (L.Q.)
                Author notes
                [* ]Correspondence: fernandagamorim@ 123456gmail.com (F.G.A.); suvilela@ 123456usp.br (S.V.S.); Fax: +55-16-3315-4725
                [†]

                Current address: Fernanda Gobbi Amorim and Suely Vilela Sampaio, Departamento de Análises Clínicas, Toxicológicas e Bromatológicas, Faculdade de Ciências Farmacêuticas de Ribeirão Preto, Universidade de São Paulo—USP, Av. do Café s/no. Campus Universitário, Ribeirão Preto, SP 14040-903, Brazil.

                Author information
                https://orcid.org/0000-0003-1453-3185
                https://orcid.org/0000-0002-1622-0118
                https://orcid.org/0000-0001-8153-9590
                Article
                toxins-10-00177
                10.3390/toxins10050177
                5983233
                29701671
                a994a57c-2db6-44d0-a8ac-f39d858cfb01
                © 2018 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 11 April 2018
                : 23 April 2018
                Categories
                Article

                Molecular medicine
                proteome,bothrops moojeni,toxins,venomics
                Molecular medicine
                proteome, bothrops moojeni, toxins, venomics

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