Automated high-throughput proteomic analysis of stored blood cells from a large cohort of non-domestic felids

Introduction: Blood transfusions occur infrequently in non-domestic cats housed at zoos, but remain a necessary, life-saving treatment. For this reason, long-term blood storage for non-domestic felid species is required. Little is known about how long blood can be stored from these species before degradation limits its clinical efficacy, however. Non-targeted proteomics provides a sensitive, unbiased method to look at molecular changes in blood cells that result from prolonged storage. Here, over 500 blood cell samples were analyzed using an automated, high-throughput LC-MSMS and data analysis workflow.

Methods: Blood samples were obtained from 135 non-domestic cats, consisting of 18 different species, housed at US zoos. Fresh, anticoagulated, whole blood samples were aliquoted and stored at 4⁰C in a clinical blood bank refrigerator for 0, 7, 14, or 28 days, after which the red blood cells were pelleted. Pelleted blood cells were then prepared for bottom-up proteomic analysis using the Thermo Scientific™ AccelerOme™ that allowed for hands-off, automated sample preparation of over 500 individual blood cell samples analyzed in triplicate resulting in 1600 injections. A high-throughput (85 samples per day) method on a Thermo Scientific™ Vanquish™ Neo LC at capillary flow rates was used for peptide separation before being analyzed by a Thermo Scientific™ Orbitrap™ Astral™ mass spectrometer in data independent (DIA) acquisition mode. Data analysis was automated using the Thermo Scientific™ Ardia™ Platform via the connection of acquisition using the Thermo Scientific™ Xcalibur™ software to processing by the Thermo Scientific™ Proteome Discoverer™ software. Upon the completion of each injection, result files were automatically uploaded to the Ardia platform by the Xcalibur acquisition software, and analysis by the Proteome Discoverer software was automatically triggered. Proteome Discoverer searches leveraged the CHIMERYS™ algorithm running locally on the Ardia server for both spectral identification and quantification.

Preliminary Data: Each injection resulted in the identification of approximately 1200 to 1500 proteins and 8000 to 12,000 peptide groups. The protein and peptide identification rates were approximately 2.5-fold and 5-fold higher, respectively, than a pilot study that was performed on a Thermo Scientific™ Orbitrap Exploris™ 480 mass spectrometer, despite using a method that was nearly twice as long. The variation in the number of identifications observed here can be attributed to differences in the completeness of the proteomes that were available for each species. However, intensities and identification rates across samples derived from the same species were very consistent, highlighting the robustness of the sample preparation and LC-MS setup used. Label-free relative quantification revealed few changes in protein abundance across storage times, which was consistent with limited metabolic activity due to storage at 4⁰C. Interestingly, numerous peptides showed changes in abundance as storage lengths increased, which could indicate protein degradation or chemical changes that occur during storage.