High-Throughput Proteomic Analysis of Stored Red Blood Cells from Non-Domestic Cat Species

Importance of High-Throughput Proteomic Analysis in Zoo Medicine

Blood transfusions are critical interventions for anemic exotic felids but carry risks when donor and recipient blood types do not match. Detailed proteomic profiling of stored red blood cells (RBCs) from diverse non-domestic cat species can inform safe transfusion practices and optimize storage protocols for emergency clinical use in zoological institutions.

Objectives and Study Overview

This study evaluated the integrity and reproducibility of proteomic signatures in stored RBCs from 36 individuals across 18 non-domestic cat species. Key aims included assessment of protein degradation over 0, 7, 14, and 28 days of refrigerated storage and demonstration of a high-throughput, automated workflow suitable for routine veterinary use.

Methodology

Fresh blood was collected under approved protocols, aliquoted, and stored at 4 °C for specified durations. RBCs were pelleted and frozen at –80 °C prior to analysis. A bottom-up proteomic approach was implemented using an automated sample preparation platform for lysis, reduction, alkylation, digestion with trypsin, and cleanup without manual intervention. Peptide mixtures were analyzed with capillary flow LC-MS/MS employing a 26-minute gradient, enabling throughput of over 50 samples per day. Data-dependent acquisition (DDA) was performed at 60 K resolution for MS1 and dynamic exclusion for MS2. Spectra were searched against a Feliformia UniProt database with SEQUEST, INFERYS rescoring, and Percolator validation.

Used Instrumentation

• Thermo Scientific AccelerOme automated sample preparation platform
• Thermo Scientific UltiMate 3000 RSLCnano system with EASY-Spray PepMap C18 column (2 µm, 150 µm × 15 cm)
• Thermo Scientific Orbitrap Exploris 480 mass spectrometer with FAIMS Pro interface

Main Results and Discussion

The workflow consistently identified over 2 000 unique peptides mapping to approximately 500 protein groups per sample, despite the dominance of hemoglobin in RBCs. Missed cleavage rates were low and quantitative reproducibility was high across all storage time points. Protein group and peptide identifications showed minimal variation between days 0, 7, 14, and 28, indicating the robustness of the automated workflow and the stability of the RBC proteome under these conditions.

Benefits and Practical Applications

• Automated sample preparation minimizes hands-on time, operator variability, and training requirements.
• High throughput supports rapid turnaround for emergency transfusion scenarios.
• Reproducible data quality enables reliable monitoring of protein changes during storage.
• Label-free quantification offers cost-effective analysis without the need for isotopic reagents.

Future Trends and Possibilities

Advancements may include deeper proteome coverage through longer gradients or complementary fractionation, integration of targeted assays for key RBC biomarkers, and extension to other exotic species. Development of cross-species proteomic reference libraries could further improve transfusion matching. Coupling automated workflows with real-time data analysis and AI-driven interpretation may enhance clinical decision-making in zoo medicine.

Conclusion

The described high-throughput proteomic workflow provides a robust, reproducible, and efficient solution for profiling stored red blood cells from non-domestic cat species. Its implementation can support safer transfusion practices and better emergency preparedness in zoological settings, advancing veterinary transfusion medicine.

References

No additional references were provided in the original text.