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Mass Spectrometry-Based Multi-omics Integration with a Single Set of Samples. | LitMetric

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Article Abstract

Mass spectrometry-based large-scale multi-omics research has proven to be powerful in answering biological questions; nonetheless, it faces many challenges from sample preparation to downstream data integration. To efficiently extract biomolecules of different physicochemical properties, preparation of various sample type needs specific tailoring, especially of difficult ones, such as . In this study, we sought to develop a multi-omics sample preparation method starting with a single set of samples to save time, minimize variability, expand biomolecule coverage, and promote multi-omics integration. We investigated tissue disruption methods to effectively release biomolecules and optimized extraction strategies to achieve broader and more reproducible biomolecule coverage in proteomics, lipidomics, and metabolomics workflows. In our assessment, we also considered speediness and usability of the approaches. The developed method was validated through a study of 16 samples designed to shine light on mitochondrial unfolded protein response (UPRmt), induced by three unique stressors─knocking down electron transfer chain element , mitochondrial ribosome protein S5 , and antibiotic treatment Doxycycline. Our findings suggested that the method achieved great coverage of proteome, lipidome, and metabolome with high reproducibility and validated that all stressors triggered UPRmt in , although generating unique molecular signatures. Innate immune response was activated, and triglycerides were decreased under all three stressor conditions. Additionally, Doxycycline treatment elicited more distinct proteomic, lipidomic, and metabolomic response than the other two treatments. This method has been successfully used to process (data not shown) and can likely be applied to other organisms for multi-omics research.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10863427PMC
http://dx.doi.org/10.1021/acs.analchem.3c00734DOI Listing

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