Guillaume Nugue , Michele Martins , Gabriela Vitória , Beatriz Luzia De Mello Lima Guimaraes , Mauricio Quiñones-Vega , Stevens Rehen , Marilia Z. Guimarães , Magno Junqueira
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Given their enhanced relevance, these 3D neurospheres serve as a valuable model for elucidating neurogenesis, differentiation, and neuropathological mechanisms, contributing to the advancement of in vitro neural models and reducing dependency on animal models.</div></div><div><h3>Significance</h3><div>This study evaluates ten protein extraction protocols using TMT 10-plex labeling to optimize proteomic analysis from single neurospheres. It compares cost, protein yield, and the ability to detect differentially expressed proteins, identifying methods like SPEED and S-Trap as efficient for high-throughput studies, while FASP excels in peptide yield. TMT labeling enhances protein identification, particularly for low-abundance proteins, and allows pre-fractionation to maximize analysis from limited samples. However, challenges such as limited PTM analysis and the potential loss of minor proteins highlight the importance of selecting protocols based on specific research goals. This work contributes to optimizing proteomic workflows for in vitro neural models, advancing single-cell analysis with minimal reliance on animal models.</div></div>","PeriodicalId":16891,"journal":{"name":"Journal of proteomics","volume":"313 ","pages":"Article 105368"},"PeriodicalIF":2.8000,"publicationDate":"2024-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimized pipeline for personalized neurobiological insights from single patient-derived Neurospheres\",\"authors\":\"Guillaume Nugue , Michele Martins , Gabriela Vitória , Beatriz Luzia De Mello Lima Guimaraes , Mauricio Quiñones-Vega , Stevens Rehen , Marilia Z. Guimarães , Magno Junqueira\",\"doi\":\"10.1016/j.jprot.2024.105368\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This pipeline presents a refined approach for deriving personalized neurobiological insights from iPSC-derived neurospheres. 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Optimized pipeline for personalized neurobiological insights from single patient-derived Neurospheres
This pipeline presents a refined approach for deriving personalized neurobiological insights from iPSC-derived neurospheres. By employing Tandem Mass Tag (TMT) labeling, we optimized sample pooling and multiplexing for robust comparative analysis across experimental conditions, maximizing data yield per sample. Through single-patient-derived neurospheres—composed of neural progenitor cells, early neurons, and radial glia—this study explores proteomic profiling to mirror the cellular complexity of neurodevelopment more accurately than traditional 2D cultures. Given their enhanced relevance, these 3D neurospheres serve as a valuable model for elucidating neurogenesis, differentiation, and neuropathological mechanisms, contributing to the advancement of in vitro neural models and reducing dependency on animal models.
Significance
This study evaluates ten protein extraction protocols using TMT 10-plex labeling to optimize proteomic analysis from single neurospheres. It compares cost, protein yield, and the ability to detect differentially expressed proteins, identifying methods like SPEED and S-Trap as efficient for high-throughput studies, while FASP excels in peptide yield. TMT labeling enhances protein identification, particularly for low-abundance proteins, and allows pre-fractionation to maximize analysis from limited samples. However, challenges such as limited PTM analysis and the potential loss of minor proteins highlight the importance of selecting protocols based on specific research goals. This work contributes to optimizing proteomic workflows for in vitro neural models, advancing single-cell analysis with minimal reliance on animal models.
期刊介绍:
Journal of Proteomics is aimed at protein scientists and analytical chemists in the field of proteomics, biomarker discovery, protein analytics, plant proteomics, microbial and animal proteomics, human studies, tissue imaging by mass spectrometry, non-conventional and non-model organism proteomics, and protein bioinformatics. The journal welcomes papers in new and upcoming areas such as metabolomics, genomics, systems biology, toxicogenomics, pharmacoproteomics.
Journal of Proteomics unifies both fundamental scientists and clinicians, and includes translational research. Suggestions for reviews, webinars and thematic issues are welcome.