Serum and plasma proteomics face unique challenges due to the presence of extremely high-abundance proteins (e.g., albumin, immunoglobulins), which account for over 90% of total protein content. These proteins mask low-abundance targets, limiting the identification to only a few hundred proteins using standard workflows. Specialized blood proteomics methods are essential to achieve deeper protein coverage and detect disease-relevant biomarkers.

Common strategies include:

• High-abundance protein depletion, which can increase depth but risks co-depletion and reduced reproducibility;

• Fractionation-based proteomics, which improves coverage but is labor-intensive;

• Magnetic bead-based enrichment, which selectively captures low-abundance proteins while preserving sample integrity.

MetwareBio uses a magnetic bead-assisted low-abundance protein enrichment workflow specifically optimized for serum and plasma proteomics.

Bead-based enrichment selectively enhances signals from low-abundance proteins without removing major proteins, avoiding unintended co-depletion. Compared to immunodepletion, it offers higher reproducibility, simplified handling, and better performance in large-scale plasma biomarker discovery studies.

Label-free DIA (Data-Independent Acquisition) provides unbiased sampling by fragmenting all precursors across the m/z range, ensuring consistent quantification even in complex blood matrices. Unlike DDA, which may miss low-abundance proteins due to stochastic precursor selection, DIA improves reproducibility and data completeness, making it ideal for serum and plasma biomarker quantification.

MetwareBio’s platform combines DIA with ion mobility separation (TIMS) to generate four-dimensional proteomics data: retention time, mass-to-charge (m/z), ion mobility, and intensity. This 4D label-free DIA approach enhances peptide separation and quantification, especially for co-eluting proteins in plasma and serum samples, increasing accuracy in low-abundance biomarker detection.

We implement a comprehensive QC pipeline, including peptide reproducibility analysis, coefficient of variation (CV) filtering, and batch effect correction. This ensures high-quality data across clinical cohorts, longitudinal time points, or multi-batch serum/plasma sample sets.

Yes. Our workflow enables quantitative profiling of clinically relevant plasma and serum proteins, including inflammatory cytokines, complement proteins, coagulation factors, and metabolic biomarkers. We also support target validation and follow-up analysis for clinical research and translational biomarker studies.