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      Open and reusable annotated mass spectrometry dataset of a chemodiverse collection of 1,600 plant extracts

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          Abstract

          As privileged structures, natural products often display potent biological activities. However, the discovery of novel bioactive scaffolds is often hampered by the chemical complexity of the biological matrices they are found in. Large natural extract collections are thus extremely valuable for their chemical novelty potential but also complicated to exploit in the frame of drug-discovery projects. In the end, it is the pure chemical substances that are desired for structural determination purposes and bioactivity evaluation. Researchers interested in the exploration of large and chemodiverse extract collections should thus establish strategies aiming to efficiently tackle such chemical complexity and access these structures. Establishing carefully crafted digital layers documenting the spectral and chemical complexity as well as bioactivity results of natural extracts collections can help prioritize time-consuming but mandatory isolation efforts. In this note, we report the results of our initial exploration of a collection of 1,600 plant extracts in the frame of a drug-discovery effort. After describing the taxonomic coverage of this collection, we present the results of its liquid chromatography high-resolution mass spectrometric profiling and the exploitation of these profiles using computational solutions. The resulting annotated mass spectral dataset and associated chemical and taxonomic metadata are made available to the community, and data reuse cases are proposed. We are currently continuing our exploration of this plant extract collection for drug-discovery purposes (notably looking for novel antitrypanosomatids, anti-infective and prometabolic compounds) and ecometabolomics insights. We believe that such a dataset can be exploited and reused by researchers interested in computational natural products exploration.

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          Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking.

          The potential of the diverse chemistries present in natural products (NP) for biotechnology and medicine remains untapped because NP databases are not searchable with raw data and the NP community has no way to share data other than in published papers. Although mass spectrometry (MS) techniques are well-suited to high-throughput characterization of NP, there is a pressing need for an infrastructure to enable sharing and curation of data. We present Global Natural Products Social Molecular Networking (GNPS; http://gnps.ucsd.edu), an open-access knowledge base for community-wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. In GNPS, crowdsourced curation of freely available community-wide reference MS libraries will underpin improved annotations. Data-driven social-networking should facilitate identification of spectra and foster collaborations. We also introduce the concept of 'living data' through continuous reanalysis of deposited data.
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            A Cross-platform Toolkit for Mass Spectrometry and Proteomics

            Mass-spectrometry-based proteomics has become an important component of biological research. Numerous proteomics methods have been developed to identify and quantify the proteins in biological and clinical samples 1 , identify pathways affected by endogenous and exogenous perturbations 2 , and characterize protein complexes 3 . Despite successes, the interpretation of vast proteomics datasets remains a challenge. There have been several calls for improvements and standardization of proteomics data analysis frameworks, as well as for an application-programming interface for proteomics data access 4,5 . In response, we have developed the ProteoWizard Toolkit, a robust set of open-source, software libraries and applications designed to facilitate proteomics research. The libraries implement the first-ever, non-commercial, unified data access interface for proteomics, bridging field-standard open formats and all common vendor formats. In addition, diverse software classes enable rapid development of vendor-agnostic proteomics software. Additionally, ProteoWizard projects and applications, building upon the core libraries, are becoming standard tools for enabling significant proteomics inquiries.
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              MZmine 2: Modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data

              Background Mass spectrometry (MS) coupled with online separation methods is commonly applied for differential and quantitative profiling of biological samples in metabolomic as well as proteomic research. Such approaches are used for systems biology, functional genomics, and biomarker discovery, among others. An ongoing challenge of these molecular profiling approaches, however, is the development of better data processing methods. Here we introduce a new generation of a popular open-source data processing toolbox, MZmine 2. Results A key concept of the MZmine 2 software design is the strict separation of core functionality and data processing modules, with emphasis on easy usability and support for high-resolution spectra processing. Data processing modules take advantage of embedded visualization tools, allowing for immediate previews of parameter settings. Newly introduced functionality includes the identification of peaks using online databases, MSn data support, improved isotope pattern support, scatter plot visualization, and a new method for peak list alignment based on the random sample consensus (RANSAC) algorithm. The performance of the RANSAC alignment was evaluated using synthetic datasets as well as actual experimental data, and the results were compared to those obtained using other alignment algorithms. Conclusions MZmine 2 is freely available under a GNU GPL license and can be obtained from the project website at: http://mzmine.sourceforge.net/. The current version of MZmine 2 is suitable for processing large batches of data and has been applied to both targeted and non-targeted metabolomic analyses.
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                Author and article information

                Contributors
                Journal
                Gigascience
                Gigascience
                gigascience
                GigaScience
                Oxford University Press
                2047-217X
                18 January 2023
                2023
                18 January 2023
                : 12
                : giac124
                Affiliations
                Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva , 1211 Geneva, Switzerland
                School of Pharmaceutical Sciences, University of Geneva , 1211 Geneva, Switzerland
                Department of Biology, University of Fribourg , 1700 Fribourg, Switzerland
                Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva , 1211 Geneva, Switzerland
                School of Pharmaceutical Sciences, University of Geneva , 1211 Geneva, Switzerland
                Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva , 1211 Geneva, Switzerland
                School of Pharmaceutical Sciences, University of Geneva , 1211 Geneva, Switzerland
                Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva , 1211 Geneva, Switzerland
                School of Pharmaceutical Sciences, University of Geneva , 1211 Geneva, Switzerland
                Faculty of Pharmaceutical Sciences, Tokushima Bunri University , 770-8514 Tokushima, Japan
                Institute of Biology, University of Neuchâtel , 2000 Neuchâtel, Switzerland
                Department of Biology, University of Fribourg , 1700 Fribourg, Switzerland
                Institute of Biology, University of Neuchâtel , 2000 Neuchâtel, Switzerland
                Direction Scientifique Naturactive, Pierre Fabre Medicament , 81100 Castres, France
                Green Mission Pierre Fabre, Institut de Recherche Pierre Fabre , 31562 Toulouse, France
                Green Mission Pierre Fabre, Institut de Recherche Pierre Fabre , 31562 Toulouse, France
                Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva , 1211 Geneva, Switzerland
                School of Pharmaceutical Sciences, University of Geneva , 1211 Geneva, Switzerland
                Author notes
                Correspondence address. Pierre-Marie Allard, Department of Biology, University of Fribourg, Chemin du Musée 10, 1700 Fribourg, Switzerland. E-mail: pierre-marie.allard@ 123456unifr.ch
                Author information
                https://orcid.org/0000-0003-3389-2191
                https://orcid.org/0000-0002-3648-7362
                https://orcid.org/0000-0002-1630-8697
                https://orcid.org/0000-0003-0443-9902
                https://orcid.org/0000-0002-7271-3128
                https://orcid.org/0000-0001-8095-6026
                https://orcid.org/0000-0002-3279-9190
                https://orcid.org/0000-0002-7677-7700
                https://orcid.org/0000-0002-2952-6271
                https://orcid.org/0000-0002-6222-9228
                https://orcid.org/0000-0002-0125-952X
                Article
                giac124
                10.1093/gigascience/giac124
                9845059
                36649739
                525d39b0-49dd-4cb9-b701-74db37befed2
                © The Author(s) 2023. Published by Oxford University Press GigaScience.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 18 May 2022
                : 15 September 2022
                : 29 November 2022
                Page count
                Pages: 9
                Funding
                Funded by: National Science Foundation, DOI 10.13039/100000001;
                Award ID: N°CRSII5_189921/1
                Categories
                Data Note
                AcademicSubjects/SCI00960
                AcademicSubjects/SCI02254
                AcademicSubjects/SCI00960
                AcademicSubjects/SCI02254

                plant extracts collection,metabolomics,drug discovery,lc-ms,natural products,mass spectrometry,chemodiversity,open science,biodiversity digitization

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