SERUM PROTEOMICS OF COVID-19 SAMPLES ANALYSED BY LIQUID CHROMATOGRAPHY AND SELECT SERIESTM CYCLICTM ION MOBILITY MASS SPECTROMETER

Significance of the Topic

Clinical proteomic profiling of serum samples from COVID-19 patients provides molecular insights into host responses and disease severity, aiding biomarker discovery for patient stratification and therapeutic monitoring.

Objectives and Study Overview

This pilot study compared the serum proteomes of patients with mild versus severe COVID-19 by applying a data-independent acquisition method on pooled, undepleted samples using cyclic ion mobility mass spectrometry. A small-scale quality control was established alongside severity-based pooling to identify differentially regulated proteins.

Methodology

• Sample pools were created from a Manchester biobank cohort of over 400 hospitalized adults, categorized into mild and severe groups; a composite QC pool was also prepared.
• Undepleted serum underwent surfactant-assisted reduction, alkylation, and overnight tryptic digestion, followed by dilution for LC injection.
• Reversed-phase UPLC employed an ACQUITY Premier CSH C18 column with a 5–35% acetonitrile gradient over 20 min at 150 μL/min and 55 °C.

Instrumentation

• Waters ACQUITY Premier UPLC system with ACQUITY Premier CSH™ C18 1.7 μm, 2.1 × 100 mm column.
• SELECT SERIES Cyclic Ion Mobility Spectrometer in HDMSE mode (20–46 eV elevated energy, 2.2 kV capillary voltage, m/z 50–1990).
• Data processed using Progenesis QI for Proteomics and ProteinLynx Global Server; statistical analyses performed in MetaboAnalyst 5.0 and TIBCO Spotfire.

Key Results and Discussion

• Unsupervised principal component analysis revealed clear differentiation between severe and mild pools based on proteomic profiles.
• A total of 268 protein groups were quantified, with 96% of peptide measurements within ±3 ppm of theoretical mass.
• C-reactive protein showed significant upregulation in severe cases, reflecting acute inflammation.
• Glutathione peroxidase levels were markedly reduced in severe patients, indicating elevated oxidative stress.

Benefits and Practical Applications

This streamlined workflow on undepleted serum offers a reproducible, high-throughput platform for rapid biomarker discovery without extensive sample fractionation, supporting clinical decision-making and monitoring of COVID-19 severity.

Future Trends and Opportunities

Expanding to individual-sample analyses with richer clinical metadata will refine biomarker validation. Integrating cyclic ion mobility with advanced bioinformatics and machine learning is expected to enhance diagnostic precision and uncover novel therapeutic targets.

Conclusion

This study demonstrates that cyclic ion mobility mass spectrometry can effectively distinguish COVID-19 severity through serum proteome signatures, highlighting potential inflammatory and oxidative stress biomarkers and paving the way for broader clinical adoption.

References

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