Carlos Pérez-López , Ester Sánchez-Jiménez , Joaquin Abian , Damià Barceló , Antonio Ginebreda , Montserrat Carrascal
{"title":"Aquasearch:通过基于maldi - tof的污水分析增强绿色环境蛋白质组学","authors":"Carlos Pérez-López , Ester Sánchez-Jiménez , Joaquin Abian , Damià Barceló , Antonio Ginebreda , Montserrat Carrascal","doi":"10.1016/j.greeac.2025.100205","DOIUrl":null,"url":null,"abstract":"<div><div>Recently, environmental proteomics has revealed its potential to find biomarkers for human health, as part of wastewater-based epidemiology. However, current analytical strategies for conducting environmental proteomics studies face challenges, including high instrumental costs and the time required for sample management. These costs can become even higher when analysis must be repeated due to experimental issues. Therefore, using MALDI-TOF is proposed as a viable and cost-effective method for the initial screening of environmental proteomics samples, allowing for preliminary sample characterization and ensuring sample quality. MALDI-TOF represents a greener alternative compared to other proteomic techniques, as its faster analysis times and reduced reagent and energy consumption contribute to lower environmental impact. However, the signals obtained from MALDI-TOF analysis must be further analyzed to achieve peptide identification and protein inference. In this work, we present Aquasearch, a novel software application designed to identify protein biomarkers from MALDI-TOF raw data. Aquasearch incorporates a comprehensive database of tryptic peptides derived from previously identified biomarkers by our research group. We have validated the effectiveness and accuracy of this tool in identifying protein biomarkers through the analysis of a set of wastewater samples. Additionally, this information was utilized in multisampling, allowing the unsupervised clustering of samples with similar proteomic profiles. Overall, Aquasearch facilitates the initial screening of proteomics samples using a straightforward approach and ensures the effectiveness of subsequent in-depth analyses. Aquasearch and its source code are available at <span><span>https://github.com/cplqam/IDAEA-IIBB_Aquasearch</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":100594,"journal":{"name":"Green Analytical Chemistry","volume":"12 ","pages":"Article 100205"},"PeriodicalIF":6.2000,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Aquasearch: Enhancing green environmental proteomics via MALDI-TOF-based sewage water profiling\",\"authors\":\"Carlos Pérez-López , Ester Sánchez-Jiménez , Joaquin Abian , Damià Barceló , Antonio Ginebreda , Montserrat Carrascal\",\"doi\":\"10.1016/j.greeac.2025.100205\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Recently, environmental proteomics has revealed its potential to find biomarkers for human health, as part of wastewater-based epidemiology. However, current analytical strategies for conducting environmental proteomics studies face challenges, including high instrumental costs and the time required for sample management. These costs can become even higher when analysis must be repeated due to experimental issues. Therefore, using MALDI-TOF is proposed as a viable and cost-effective method for the initial screening of environmental proteomics samples, allowing for preliminary sample characterization and ensuring sample quality. MALDI-TOF represents a greener alternative compared to other proteomic techniques, as its faster analysis times and reduced reagent and energy consumption contribute to lower environmental impact. However, the signals obtained from MALDI-TOF analysis must be further analyzed to achieve peptide identification and protein inference. In this work, we present Aquasearch, a novel software application designed to identify protein biomarkers from MALDI-TOF raw data. Aquasearch incorporates a comprehensive database of tryptic peptides derived from previously identified biomarkers by our research group. We have validated the effectiveness and accuracy of this tool in identifying protein biomarkers through the analysis of a set of wastewater samples. Additionally, this information was utilized in multisampling, allowing the unsupervised clustering of samples with similar proteomic profiles. Overall, Aquasearch facilitates the initial screening of proteomics samples using a straightforward approach and ensures the effectiveness of subsequent in-depth analyses. 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Aquasearch: Enhancing green environmental proteomics via MALDI-TOF-based sewage water profiling
Recently, environmental proteomics has revealed its potential to find biomarkers for human health, as part of wastewater-based epidemiology. However, current analytical strategies for conducting environmental proteomics studies face challenges, including high instrumental costs and the time required for sample management. These costs can become even higher when analysis must be repeated due to experimental issues. Therefore, using MALDI-TOF is proposed as a viable and cost-effective method for the initial screening of environmental proteomics samples, allowing for preliminary sample characterization and ensuring sample quality. MALDI-TOF represents a greener alternative compared to other proteomic techniques, as its faster analysis times and reduced reagent and energy consumption contribute to lower environmental impact. However, the signals obtained from MALDI-TOF analysis must be further analyzed to achieve peptide identification and protein inference. In this work, we present Aquasearch, a novel software application designed to identify protein biomarkers from MALDI-TOF raw data. Aquasearch incorporates a comprehensive database of tryptic peptides derived from previously identified biomarkers by our research group. We have validated the effectiveness and accuracy of this tool in identifying protein biomarkers through the analysis of a set of wastewater samples. Additionally, this information was utilized in multisampling, allowing the unsupervised clustering of samples with similar proteomic profiles. Overall, Aquasearch facilitates the initial screening of proteomics samples using a straightforward approach and ensures the effectiveness of subsequent in-depth analyses. Aquasearch and its source code are available at https://github.com/cplqam/IDAEA-IIBB_Aquasearch.