QUANTITATIVE EVALUATION OF AFFIMER AND MOLECULAR IMPRINTED POLYMER AFFINITY GLYCOPROTEINS ANALYSIS BY MULTIPLE REACTION MONITORING LC-MS/MS

Significance of the Topic

Accurate quantification of glycoprotein isoforms is essential for disease biomarker discovery and validation. Bottom-up LC-MS workflows face challenges such as glycan heterogeneity, incomplete proteolysis, and low analyte concentrations. Affinity capture using engineered Affimer proteins and molecularly imprinted polymers (MIPs) offers selective enrichment to improve sensitivity and specificity in complex biological samples.

Objectives and Study Overview

This study evaluates the performance of Affimers and MIPs for enrichment of model glycoproteins and viral antigens. Key aims include:

• Comparing capture efficiency against conventional antibodies
• Assessing quantitative performance on carcinoembryonic antigen (CEA), CA-125, and SARS-CoV-2 Spike protein
• Optimizing on-bead deglycosylation and digestion workflows for bottom-up LC-MS/MS

Methodology and Instrumentation

The protocol involved:

• Immobilization of Affimer reagents, MIPs, and antibodies on magnetic beads via biotin-streptavidin or amine coupling
• On-bead sample treatment: denaturation (RapiGest SF), reduction (DTT), alkylation (IAA), PNGase F deglycosylation, and trypsin digestion
• Peptide separation by reversed-phase UPLC and detection by ESI-MRM on a Xevo TQ-XS tandem quadrupole MS
• Data acquisition and processing using TargetLynx and Skyline software

Main Results and Discussion

• Affinity enrichment of CEA with PNGase F treatment yielded over 10^5 fold increase in MRM signal compared to non-deglycosylated samples
• CA-125 analysis demonstrated 10 to 50 times signal enhancement, though epitope heterogeneity limited further optimization
• MIP-based capture of SARS-CoV-2 Spike protein provided selective and quantitative response with linearity across tested concentrations
• Non-specific binding was mitigated by optimized blocking agents and support selection
• Similar binding affinities were observed for Affimers, MIPs, and antibodies, with independent method tuning required for each

Benefits and Practical Applications

Affinity-based enrichment with Affimers and MIPs enables:

• Improved sensitivity for low-abundance glycoprotein biomarkers
• Reduced matrix interference in complex samples such as plasma
• Compatibility with automated workflows and potential online integration
• Flexibility for both labeled and unlabeled target proteins

Future Trends and Opportunities

Potential developments include:

• Integration of affinity capture into online 2D-LC-MS platforms for high throughput
• Design of multiplexed MIP and Affimer panels targeting diverse biomolecules
• Advances in polymer and binding protein engineering to broaden target specificity
• Application to emerging viral pathogens and novel disease biomarkers

Conclusion

Engineered Affimer proteins and molecularly imprinted polymers represent robust alternatives to antibodies for glycoprotein and viral antigen enrichment. Optimized on-bead deglycosylation and proteolysis enhance bottom-up LC-MS/MS sensitivity, and both reagent classes can be seamlessly integrated into automated and high-throughput analytical pipelines.

References

1. Shamsuddin SH, Jayne DG, Tomlinson DC, McPherson MJ, Millner PA. Selection and characterisation of Affimers specific for CEA recognition. Sci Rep. 2021;11(1):744.
2. Bossi A, Bonini F, Turner AP, Piletsky SA. Molecularly imprinted polymers for the recognition of proteins: the state of the art. Biosens Bioelectron. 2007;22(6):1131-1137.
3. Van Puyvelde J, et al. Cov2MS: An Automated and Quantitative Matrix-Independent Assay for Mass Spectrometric Measurement of SARS-CoV-2 Nucleocapsid Protein. Anal Chem. 2022;94(50):17379-17387.
4. MacLean B, Tomazela DM, Shulman N, et al. Skyline: an open source document editor for creating and analyzing targeted proteomics experiments. Bioinformatics. 2010;26(7):966-968.
5. Manufacturer protocols and product information for Affimer, MIP, RapiGest SF, Xevo TQ-XS, ACQUITY UPLC, and TargetLynx.