Proteins are dynamically regulated by a myriad of post-translational modifications (PTMs) that control their stability, conformation, activity, subcellular localization, and local interactions. Capturing the precise composition of these various modification states, or proteoforms, is a principal objective of top-down proteomics (TDP). By ionizing intact proteoforms and combining measurements of precursor ion and fragment ion masses, the position, stoichiometry, and combination of PTMs can be determined. Despite the highly valuable measurements that TDP can provide, it is typically less sensitive than corresponding peptide-level analysis, with many reports utilizing input material in the microgram to milligram range. Contributing to this lack of sensitivity is the risk of sample loss due to nonspecific binding to surfaces during sample preparation. The most widely employed sample preparation approaches for TDP either require high sample input (e.g., precipitation and ultrafiltration) or fail to effectively remove surfactants (e.g., solid-phase extraction). These limitations have hindered advancement of targeted TDP applications involving immunoprecipitation and other enrichment strategies. Bead-assisted protein aggregation, also referred to as single-pot, solid-phase-enhanced sample preparation (SP3), has emerged as a popular sample preparation strategy for bottom-up proteomic workflows, but has only been used in TDP with high concentrations of formic acid (40%) or a secondary ion exchange chromatography cleanup step. We envisioned a magnetic bead-based protein cleanup approach that proceeds directly to MS analysis with a judicious choice of bead surface chemistry and elution conditions. Here we report a sample preparation method using hydroxyl-functionalized magnetic beads that proceeds directly to MS analysis. Applied to SDS-containing HeLa lysate, hydroxyl beads with 0.5% TFA recovery identified as many proteins as methanol-chloroform-water precipitation (231 vs 228), spanning the same ranges of mass, isoelectric point, hydrophobicity, and cellular compartment, with comparable precursor intensity at a modest cost in precursor signal-to-noise.
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Feltenstein et al. (2026) studied this question.
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