Andréa McCann , Christopher Kune , Raphael La Rocca , Janina Oetjen , Anthony Arguelles Arias , Marc Ongena , Johann Far , Gauthier Eppe , Loic Quinton , Edwin De Pauw
{"title":"结合离子迁移率和MALDI成像质谱法快速可视化脂肽和化合物的潜在生物活性基团","authors":"Andréa McCann , Christopher Kune , Raphael La Rocca , Janina Oetjen , Anthony Arguelles Arias , Marc Ongena , Johann Far , Gauthier Eppe , Loic Quinton , Edwin De Pauw","doi":"10.1016/j.ddtec.2021.08.003","DOIUrl":null,"url":null,"abstract":"<div><p><span><span>Mass spectrometry imaging<span> (MSI) has become a powerful method for mapping metabolite distribution in a tissue. Applied to bacterial colonies<span>, MSI has a bright future, both for the discovery of new bioactive compounds and for a better understanding of bacterial antibiotic resistance mechanisms. Coupled with separation techniques such as </span></span></span>ion mobility mass spectrometry<span> (IM-MS), the identification of metabolites directly on the image is now possible and does not require additional analysis such as HPLC-MS/MS. In this article, we propose to apply a semi-targeted workflow for rapid IM-MSI data analysis focused on the search for bioactive compounds. First, chemically-related compounds showing a repetitive mass unit (i.e. lipids and lipopeptides) were targeted based on the Kendrick mass defect analysis. The detected groups of potentially bioactive compounds were then confirmed by fitting their measured ion moibilites to their measured </span></span><em>m/z</em> values. Using both their <em>m/z</em><span> and ion mobility values, the selected groups of compounds were identified using the available databases and finally their distribution was observed on the image. Using this workflow on a co-culture of bacteria, we were able to detect and localize bioactive compounds involved in the microbial interaction.</span></p></div>","PeriodicalId":36012,"journal":{"name":"Drug Discovery Today: Technologies","volume":"39 ","pages":"Pages 81-88"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.ddtec.2021.08.003","citationCount":"4","resultStr":"{\"title\":\"Rapid visualization of lipopeptides and potential bioactive groups of compounds by combining ion mobility and MALDI imaging mass spectrometry\",\"authors\":\"Andréa McCann , Christopher Kune , Raphael La Rocca , Janina Oetjen , Anthony Arguelles Arias , Marc Ongena , Johann Far , Gauthier Eppe , Loic Quinton , Edwin De Pauw\",\"doi\":\"10.1016/j.ddtec.2021.08.003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p><span><span>Mass spectrometry imaging<span> (MSI) has become a powerful method for mapping metabolite distribution in a tissue. Applied to bacterial colonies<span>, MSI has a bright future, both for the discovery of new bioactive compounds and for a better understanding of bacterial antibiotic resistance mechanisms. Coupled with separation techniques such as </span></span></span>ion mobility mass spectrometry<span> (IM-MS), the identification of metabolites directly on the image is now possible and does not require additional analysis such as HPLC-MS/MS. In this article, we propose to apply a semi-targeted workflow for rapid IM-MSI data analysis focused on the search for bioactive compounds. First, chemically-related compounds showing a repetitive mass unit (i.e. lipids and lipopeptides) were targeted based on the Kendrick mass defect analysis. The detected groups of potentially bioactive compounds were then confirmed by fitting their measured ion moibilites to their measured </span></span><em>m/z</em> values. Using both their <em>m/z</em><span> and ion mobility values, the selected groups of compounds were identified using the available databases and finally their distribution was observed on the image. Using this workflow on a co-culture of bacteria, we were able to detect and localize bioactive compounds involved in the microbial interaction.</span></p></div>\",\"PeriodicalId\":36012,\"journal\":{\"name\":\"Drug Discovery Today: Technologies\",\"volume\":\"39 \",\"pages\":\"Pages 81-88\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.ddtec.2021.08.003\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Drug Discovery Today: Technologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1740674921000202\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Pharmacology, Toxicology and Pharmaceutics\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Drug Discovery Today: Technologies","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1740674921000202","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Pharmacology, Toxicology and Pharmaceutics","Score":null,"Total":0}
Rapid visualization of lipopeptides and potential bioactive groups of compounds by combining ion mobility and MALDI imaging mass spectrometry
Mass spectrometry imaging (MSI) has become a powerful method for mapping metabolite distribution in a tissue. Applied to bacterial colonies, MSI has a bright future, both for the discovery of new bioactive compounds and for a better understanding of bacterial antibiotic resistance mechanisms. Coupled with separation techniques such as ion mobility mass spectrometry (IM-MS), the identification of metabolites directly on the image is now possible and does not require additional analysis such as HPLC-MS/MS. In this article, we propose to apply a semi-targeted workflow for rapid IM-MSI data analysis focused on the search for bioactive compounds. First, chemically-related compounds showing a repetitive mass unit (i.e. lipids and lipopeptides) were targeted based on the Kendrick mass defect analysis. The detected groups of potentially bioactive compounds were then confirmed by fitting their measured ion moibilites to their measured m/z values. Using both their m/z and ion mobility values, the selected groups of compounds were identified using the available databases and finally their distribution was observed on the image. Using this workflow on a co-culture of bacteria, we were able to detect and localize bioactive compounds involved in the microbial interaction.
期刊介绍:
Discovery Today: Technologies compares different technological tools and techniques used from the discovery of new drug targets through to the launch of new medicines.