<p>A recent publication highlights a collaborative effort between researchers at <a href="https://www.recetox.muni.cz/en" target="_blank">RECETOX</a>, <a href="t3://page?uid=2" target="_blank">PAL System</a>, and <a href="https://www.thermofisher.com/ch/en/home.html" target="_blank">Thermo Fisher Scientific</a> to improve the efficiency and throughput of GC/MS-based metabolomics.</p> <p>The research, spearheaded by <a href="https://www.muni.cz/en/people/517699-akrem-jbebli" target="_blank">Akrem Jbebli</a> and <a href="https://www.recetox.muni.cz/en/research/principal-investigators/dr-elliott-price" target="_blank">Elliott J. Price</a> at RECETOX, focuses on automating the critical derivatization step required for analyzing polar metabolites and the subsequent injection into the GC/MS system. This new protocol utilizes a Thermo Scientific™ TriPlus™ RSH autosampler (or <a href="t3://page?uid=218" target="_blank">comparable system</a>) to perform sequential methoximation and silylation reactions.</p> <p>By automating these reactions, the researchers achieved significant improvements in several key areas:</p> <p><strong>Increased Throughput</strong>: The automated workflow enables the analysis of approximately 40 samples within a 24-hour period, significantly streamlining the analytical process.</p> <p><strong>Enhanced Reproducibility</strong>: Automation minimizes manual handling errors and ensures consistent reaction conditions, leading to improved reproducibility across a variety of blood matrices, including dried blood spots, serum, and plasma.</p> <p><strong>Broad Metabolite Coverage</strong>: Combined with high-resolution Orbitrap mass spectrometry, the protocol facilitated the identification of over 70 metabolites in each blood matrix.</p> <p>This automated sequential derivatization protocol offers a valuable tool for researchers seeking to enhance the efficiency and reliability of their GC/MS metabolomics workflows.</p> <p>The approach holds promise for applications in various fields, including:</p> <ul> <li>Large-scale metabolomics studies: Enabling faster and more robust analysis of large sample cohorts.</li> <li>Clinical diagnostics: Improving the accuracy and speed of metabolite-based disease diagnostics.</li> <li>Drug discovery and development: Facilitating the identification of drug targets and the study of drug metabolism.</li> </ul>

PFAS are a wide class of ubiquitous chemically persistent environmental pollutants. Here the authors combine nontarget screening with a two-layer network approach to identify large numbers of PFAS fro...