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      The mechanism underlying toxicity of a venom peptide against insects reveals how ants are master at disrupting membranes

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          Summary

          Hymenopterans represent one of the most abundant groups of venomous organisms but remain little explored due to the difficult access to their venom. The development of proteo-transcriptomic allowed us to explore diversity of their toxins offering interesting perspectives to identify new biological active peptides. This study focuses on U 9 function, a linear, amphiphilic and polycationic peptide isolated from ant Tetramorium bicarinatum venom. It shares physicochemical properties with M-Tb1a, exhibiting cytotoxic effects through membrane permeabilization. In the present study, we conducted a comparative functional investigation of U 9 and M-Tb1a and explored the mechanisms underlying their cytotoxicity against insect cells. After showing that both peptides induced the formation of pores in cell membrane, we demonstrated that U 9 induced mitochondrial damage and, at high concentrations, localized into cells and induced caspase activation. This functional investigation highlighted an original mechanism of U 9 questioning on potential valorization and endogen activity in T. bicarinatum venom.

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          Highlights

          • U 9 has a significant insecticidal activity and induces a cell swelling phenotype

          • U 9 impacts both metabolism and membrane integrity of cells

          • U 9 causes cell permeabilization through the formation of pores

          • U 9 enters into cells and induces a mitochondria disorganization phenotype

          Abstract

          Toxicology; Entomology; Biochemistry

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          Most cited references88

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          UCSF ChimeraX : Structure visualization for researchers, educators, and developers

          UCSF ChimeraX is the next-generation interactive visualization program from the Resource for Biocomputing, Visualization, and Informatics (RBVI), following UCSF Chimera. ChimeraX brings (a) significant performance and graphics enhancements; (b) new implementations of Chimera's most highly used tools, many with further improvements; (c) several entirely new analysis features; (d) support for new areas such as virtual reality, light-sheet microscopy, and medical imaging data; (e) major ease-of-use advances, including toolbars with icons to perform actions with a single click, basic "undo" capabilities, and more logical and consistent commands; and (f) an app store for researchers to contribute new tools. ChimeraX includes full user documentation and is free for noncommercial use, with downloads available for Windows, Linux, and macOS from https://www.rbvi.ucsf.edu/chimerax.
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            The CCPN data model for NMR spectroscopy: development of a software pipeline.

            To address data management and data exchange problems in the nuclear magnetic resonance (NMR) community, the Collaborative Computing Project for the NMR community (CCPN) created a "Data Model" that describes all the different types of information needed in an NMR structural study, from molecular structure and NMR parameters to coordinates. This paper describes the development of a set of software applications that use the Data Model and its associated libraries, thus validating the approach. These applications are freely available and provide a pipeline for high-throughput analysis of NMR data. Three programs work directly with the Data Model: CcpNmr Analysis, an entirely new analysis and interactive display program, the CcpNmr FormatConverter, which allows transfer of data from programs commonly used in NMR to and from the Data Model, and the CLOUDS software for automated structure calculation and assignment (Carnegie Mellon University), which was rewritten to interact directly with the Data Model. The ARIA 2.0 software for structure calculation (Institut Pasteur) and the QUEEN program for validation of restraints (University of Nijmegen) were extended to provide conversion of their data to the Data Model. During these developments the Data Model has been thoroughly tested and used, demonstrating that applications can successfully exchange data via the Data Model. The software architecture developed by CCPN is now ready for new developments, such as integration with additional software applications and extensions of the Data Model into other areas of research.
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              Version 1.2 of the Crystallography and NMR system.

              Version 1.2 of the software system, termed Crystallography and NMR system (CNS), for crystallographic and NMR structure determination has been released. Since its first release, the goals of CNS have been (i) to create a flexible computational framework for exploration of new approaches to structure determination, (ii) to provide tools for structure solution of difficult or large structures, (iii) to develop models for analyzing structural and dynamical properties of macromolecules and (iv) to integrate all sources of information into all stages of the structure determination process. Version 1.2 includes an improved model for the treatment of disordered solvent for crystallographic refinement that employs a combined grid search and least-squares optimization of the bulk solvent model parameters. The method is more robust than previous implementations, especially at lower resolution, generally resulting in lower R values. Other advances include the ability to apply thermal factor sharpening to electron density maps. Consistent with the modular design of CNS, these additions and changes were implemented in the high-level computing language of CNS.
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                Author and article information

                Contributors
                Journal
                iScience
                iScience
                iScience
                Elsevier
                2589-0042
                08 February 2023
                17 March 2023
                08 February 2023
                : 26
                : 3
                : 106157
                Affiliations
                [1 ]BTSB-UR 7417, Université de Toulouse, Institut National Universitaire Jean-François Champollion, Place de Verdun, 81000 Albi, France
                [2 ]CNRS, UMR Ecologie des Forêts de Guyane, AgroParisTech, CIRAD, INRA, Université de Guyane, Université des Antilles, Campus Agronomique, BP316 97310 Kourou, France
                [3 ]Inserm U1239, NorDiC, Laboratoire de Différenciation et Communication Neuroendocrine, Endocrine et Germinale, Université de Rouen-Normandie, 76000 Rouen, France
                [4 ]Inserm US51, HeRacLeS, Université de Rouen-Normandie, 76000 Rouen, France
                [5 ]Centre de Biophysique Moléculaire, CNRS UPR 4301, Rue Charles Sadron CS-80054, 45071 Orléans, France
                Author notes
                []Corresponding author elsa.bonnafe@ 123456univ-jfc.fr
                [6]

                Lead contact

                Article
                S2589-0042(23)00234-1 106157
                10.1016/j.isci.2023.106157
                9985030
                36879819
                80327537-8a6b-4d28-adab-eb87b135645b
                © 2023.

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 22 November 2022
                : 17 January 2023
                : 2 February 2023
                Categories
                Article

                toxicology,entomology,biochemistry
                toxicology, entomology, biochemistry

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