Comprehensive identification and label-free quantitation of host cell protein contaminants using BioPharma Finder 4.1 software

Importance of the Topic

In biotherapeutic manufacturing, residual host cell proteins (HCPs) represent critical quality attributes that can compromise safety, efficacy, and stability of monoclonal antibodies (mAbs). Regulatory guidelines by ICH Q11 and related standards require robust monitoring and control of HCP levels, typically targeting less than 100 ppm in final drug products.

Objectives and Study Overview

This study aimed to develop and demonstrate a peptide mapping workflow, combined with label-free quantification in Thermo Scientific™ BioPharma Finder™ 4.1 software, to detect, identify, and quantify HCPs in an investigational IgG1 mAb. Two eluates from different stages of Protein A chromatography (early cycles vs. end of column life) were compared to evaluate HCP clearance during downstream processing (DSP).

Methodology and Instrumentation

The experimental workflow involved:

• Expression of IgG1 in CHO cells and purification by Protein A affinity chromatography.
• Reduction, alkylation, and tryptic digestion of mAb fractions.
• Reversed-phase LC separation on an Acclaim™ VANQUISH™ C18 column with a 65-min gradient.
• High-resolution accurate mass MS and data-dependent MS/MS on a Q Exactive™ Plus hybrid quadrupole-Orbitrap.
• Data processing in BioPharma Finder 4.1 for peptide mapping and HCP analysis; searches against the Cricetulus griseus UniProt proteome with stringent mass tolerance (≤20 ppm) and peptide filters (minimum three unique peptides and high structural resolution ≤1.5).
• Label-free quantification by comparing the top three peptide intensities of each HCP against the known IgG1 internal standard.

Main Results and Discussion

Initial searches identified 124 CHO proteins in each run; custom filtering yielded 19 confidently identified HCPs (≥2 unique peptides, high confidence, ASR ≤1.5). Of these, 10 HCPs with ≥3 peptides were quantified. Key findings:

• Protein A cycles reduced most HCP levels by approximately 50% in the late-stage eluate compared to early cycles, demonstrating sustained clearance capacity even after >120 column uses.
• Lipoprotein lipase and other high-abundance HCPs were quantified at low ppm levels, while elongation factor 2 exceeded 1000 ppm, indicating the need for additional polishing steps.
• Absolute label-free quantification provided reliable estimates of HCP abundance across purification stages without requiring isotope standards.

Benefits and Practical Applications

• Offers an unbiased, orthogonal approach to traditional immunoassays for HCP monitoring.
• Integrates HCP analysis into routine peptide mapping workflows, simplifying data handling.
• Supports DSP optimization by quantifying impurity clearance over multiple chromatography cycles.
• Enables rapid method development for QA/QC in biomanufacturing.

Future Trends and Applications

Emerging directions include:

• Expansion of database coverage and spectral libraries to improve low-abundance HCP detection.
• Automation of MS-based HCP workflows for high-throughput process monitoring.
• Integration with multi-attribute methods (MAM) to simultaneously track critical quality attributes.
• Application to other biotherapeutic modalities, such as fusion proteins and gene therapy vectors.

Conclusion

The developed BioPharma Finder 4.1 workflow demonstrated high confidence in both identification and label-free quantification of HCPs throughout Protein A purification of an IgG1 mAb. Custom filtering criteria and high-resolution MS data enabled reliable detection and measurement of trace impurities, supporting process development and quality control in biopharmaceutical manufacturing.

Reference

1. Zuch de Zafra CL, et al. Host cell proteins in biotechnology-derived products: A risk assessment framework. Biotechnol Bioeng. 2015;112:2284–2291.
2. International Conference on Harmonisation. Q11 Development and Manufacture of Drug Substances. 2012.
3. International Conference on Harmonisation. Q6B Specifications: Test Procedures and Acceptance Criteria for Biotech Products. 1999.
4. Liu HF, et al. Recovery and purification process development for monoclonal antibody production. MAbs. 2010;2(5):480–499.
5. Albrecht S, et al. Proteomics in biomanufacturing control: protein dynamics of CHO-K1 cells during apoptosis and necrosis. Biotechnol Bioeng. 2018;115(6):1509–1520.
6. UniProt Consortium. Proteome UP000001075: Cricetulus griseus (Chinese hamster). 2021.
7. Eng JK, et al. Comet: an open-source MS/MS sequence database search tool. Proteomics. 2013;13(21):22–24.
8. Van de Peer Y. Calculate and draw custom Venn diagrams. Bioinformatics and Evolutionary Genomics, UGent/VIB. 2009.
9. Gilgunn S, et al. Identification and tracking of problematic HCPs removed by a synthetic nonwoven media. J Chromatogr A. 2019;1595:28–38.
10. Grossmann J, et al. Implementation of relative and absolute quantification in shotgun proteomics. J Proteomics. 2010;73:1740–1746.