ArticleInternational journal of microbiology2025
Multiparametric Optimization of Data-Dependent Acquisition Towards More Holistic Bacterial Metabolite Coverage Through Molecular Networking.
Article in International journal of microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Prokaryotic organisms rely on a limited array of metabolites for survival, which varies according to their natural environment. For example, soil-borne bacteria produce diverse metabolites, such as antibiotics, to thrive in their competitive surroundings, inhibiting the growth of nearby competing bacteria. The structural diversity of these compounds offers great analytical challenges, since there is no universal acquisition setting that can be applied to achieve their comprehensive coverage. Therefore, the use of a single experimental setup inevitably hinders the comprehensive metabolite coverage, which would affect the outputs. To address this, we propose employing a design of experiment (DoE) approach through the central composite design (CCD) to enhance the metabolite detection and broaden the coverage of the data-dependent acquisition (DDA) mode of the UHPLC-qTOF-MS technique. Our study reveals that altering collision energy significantly enhances metabolite coverage compared to adjusting the DDA threshold of detection. Furthermore, the ability of global natural product social (GNPS)-based molecular network models to annotate metabolites is greatly influenced by data acquisition settings, particularly affecting MS
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