The robust non-covalent interaction between biotin and streptavidin has proven invaluable for enriching biotinylated proteins in biological systems. This interaction, characterized by its strength, specificity, and sensitivity, makes it an ideal tool for investigating the dynamic and influential cell surface protein signature, or surfaceome. Utilizing biotin labeling in conjunction with MS-based proteomics provides avenues for exploring the surfaceome, laying the foundation for potential therapeutic drug development by targeting disease-specific cell surface antigens.
Traditionally, the enrichment of biotin-tagged proteins involves the use of streptavidin-coated agarose resin, a method known for its robustness, high specificity, and minimal background. However, this procedure, while effective, has limitations in terms of throughput, hindering its applicability in high-throughput clinical sample screening—a growing trend in translational research.
Recognizing the need for automation-friendly sample processing, we performed a series of optimisation studies to benchmark alternative magnetic streptavidin beads from Cytiva, GenScript, and ReSyn. These beads can be adapted to a 96-well sample processing format for both manual and liquid automation robotic platforms. We performed DIA-MS analysis (30-minute analytical nanoLC gradient) to: (i) Benchmark magbeads against agarose-streptavidin beads enrichment, optimizing washing conditions. (ii) Benchmark magbeads against each other for sensitivity, selectivity, and ease of transferability to a high-throughput platform. (iii) Assess ease of handling and selectivity by comparing different magbeads under similar conditions.
For this experiment, we used the U251 malignant glioblastoma tumor cell line, biotin-labeled cell surface proteins (~1 million cells per enrichment) to optimize washing conditions for magbeads and to maximize sensitivity and selectivity. In comparison to agarose beads, both Cytiva and GenScript magnetic beads demonstrated a significant increase (at least 20%) in protein IDs, with a substantial overlap of 60% shared among the three beads. While sensitivity and selectivity were comparable between Cytiva and GenScript, Cytiva beads faced challenges in translating to a 96-well format, resulting in poor reproducibility of protein IDs.
In summary, our findings highlight the promise of magnetic streptavidin beads for increased protein identification and compatible with high-throughput platforms, albeit with challenges such as higher background. Addressing these challenges through optimized washing steps is crucial for harnessing the full potential of magnetic streptavidin beads in high-throughput applications.