Automated Sample Preparation Using Andrew+ Pipetting Robot for UPLC-MSE Identification and UPLC-MS/MS Quantification of Bovine Milk Proteins

Importance of the Topic

Milk proteins deliver essential nutrients and functional properties that influence the nutritional value and quality of dairy products. Accurate analysis of these proteins supports quality control in dairy manufacturing, guides the formulation of milk alternatives, and underpins research in food technology.

Objectives and Study Overview

This application note aimed to establish an automated workflow for the identification and quantification of five bovine milk proteins (α-casein, β-casein, κ-casein, α-lactalbumin, β-lactoglobulin). UPLC-MSE was used for peptide discovery, while UPLC-MS/MS in multiple reaction monitoring mode enabled quantification. Automation using the Andrew+ Pipetting Robot and OneLab Software was implemented to enhance throughput and reproducibility.

Methodology and Instrumentation

Sample preparation employed the ProteinWorks Auto-eXpress Digest Kit with RapiGest SF surfactant for rapid tryptic digestion. Progenesis QI for Proteomics and EZInfo facilitated discovery of signature peptides via PCA and OPLS-DA analyses. Quantitative measurements were carried out on a UPLC-MS/MS system in MRM mode. Automated liquid handling protocols were designed and executed in OneLab on the Andrew+ Pipetting Robot.
Instrumentation

• ACQUITY UPLC I-Class PLUS FTN with ACQUITY Premier CSH C18 column
• Xevo G2-XS QTof for MSE analysis
• Xevo TQ-S micro for targeted MS/MS quantification
• Software: MassLynx v4.2, TargetLynx v4.2, Progenesis QI for Proteomics v4.0, EZInfo v3.0, OneLab

Main Results and Discussion

Rapid digestion delivered over 1,000 identified peptides with clear PCA clustering of the five proteins. OPLS-DA and S-plots enabled selection of unique signature peptides for each target protein. Automated calibration series exhibited linear responses with r2 >0.99. Analysis of various commercial milks yielded protein distributions consistent with literature, confirming β-casein as the most abundant.

Benefits and Practical Applications

• Accelerated and complete protein digestion with minimal manual intervention
• Enhanced detection of phosphopeptides via high performance surface technology
• Increased throughput and reduced operator bias through protocol automation
• Reliable quantification across diverse milk matrices including flavored products

Future Trends and Opportunities

This automated proteomic workflow can be extended to alternative dairy and plant-based proteins, supporting emerging product development. Incorporating isotopically labeled internal standards and full validation (matrix effects, recovery) will strengthen quantitative accuracy. Integration with cloud-native informatics will enable real-time data analysis and remote method deployment.

Conclusion

The combination of bottom-up proteomics, UPLC-MSE peptide discovery, UPLC-MS/MS quantification, and automated sample preparation on the Andrew+ Pipetting Robot delivers a robust, high-throughput solution for bovine milk protein analysis. This approach significantly reduces hands-on time while ensuring data quality and consistency, and is adaptable to novel protein matrices.

Reference

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