Evaluation of Si-Trap™ for Integrated Proteomic, Metabolomic, and Lipidomic Analyses

Multi-omics workflows enable proteins, metabolites, and lipids to be analyzed from the same biological system, providing a more complete view of cellular function. However, many established preparation strategies require separate sample inputs or splitting a single sample into multiple fractions to recover each omics layer. This added handling can increase preparation time, sample loss, and technical variability, making integrated analysis more challenging. To address these limitations, the Si-Trap™ was developed to streamline multi-omics sample preparation by enabling proteomic, metabolomic, and lipidomic analyses within a unified workflow. In collaboration with Proteomics and Metabolomics Facility (ProMeFa), the Si-Trap™ workflow was directly compared to the established ProMeFa multi-omics method using HEK293 cell pellets. The ProMeFa workflow employs water/MTBE/methanol phase separation to recover apolar lipid and polar metabolite fractions, with the remaining protein pellet resuspended in 9 M urea and processed by filter-aided sample preparation (FASP) prior to LC-MS analysis. In contrast, Si-Trap™ uses a 96-well plate format, in which samples are dissolved under detergent-free conditions before the addition of binding and lipid-extraction solutions. Proteins are retained on the trap, while metabolites and lipids are collected in the flow-through. Captured proteins are processed directly on the plate, including in situ reduction and alkylation, followed by proteolytic digestion and peptide elution for LC-MS analysis. Both the Si-Trap™ and ProMeFa workflows yielded broadly comparable results across multi-omics analyses. Proteomic analysis showed that most of the identified proteins were shared between the two workflows, indicating that Si-Trap™ achieved protein recovery comparable to that of the ProMeFa-FASP protocol. These proteins were distributed across major cellular compartments, reflecting broad proteome coverage by both methods. Metabolomic analyses identified similar metabolite classes in both workflows, including amino acids, nucleotides, organic acids, and related small molecules. In lipidomic analyses, both workflows recovered multiple lipid classes, with some workflow-dependent differences in class representation; The Si-Trap™ showed greater relative representation of diacylglycerols, while phosphatidylcholines and phosphatidylethanolamines were more represented in the ProMeFa workflow. The Si-Trap™ workflow integrates proteomic, metabolomic, and lipidomic sample processing within a single platform. In this comparative analysis, Si-Trap™ achieved molecular coverage comparable to the established ProMeFa workflow. Consolidation of sample preparation steps into a single format supports reproducible processing across molecular classes, reduces sample input requirements, and minimizes technical variability. Figure 5. Si-Trap™ demonstrates broad multi-omics coverage and strong signal recovery across metabolomics, proteomics, and lipidomics. Feature intensity distributions and molecular class representation were compared between the ProMeFa multi-omics workflow and Si-Trap™ using HEK293 cell samples. Proteomics (a), metabolomics (b), and lipidomics (c) outputs were evaluated for both workflows. Density plots display global feature intensity distributions, and pie charts summarize detected features by protein localization, metabolite category, or lipid class.