A fully automated, high-throughput electro-extraction and analysis workflow for acylcarnitines in human plasma and mouse muscle tissues

BACKGROUND: The labor-intensive and time-consuming nature of sample preparation poses significant challenges for bioanalysis, especially for large-scale samples characterized by limited volumes/mass, and low analyte abundance. Additionally, manual sample processing can compromise reproducibility. To overcome these limitations, automation and high-throughput methodologies are essential, highlighting the need for an automated, high-throughput sample preparation and analysis workflow.

RESULTS: This study presents a fully automated, high-throughput electro-extraction (EE) platform integrated with a CTC PAL3 autosampler and liquid chromatography-mass spectrometry analyzer. The integrated platform underwent qualification, followed by optimization of EE parameters using a Design of Experiment approach. Ten acylcarnitines were selected as model analytes. The optimization models exhibited strong fits (p < 0.006, R2 > 0.91). The optimized platform achieved an enrichment factor of up to 400 (an extraction recovery of up to 99 %) in designed academic samples, and was effectively implemented and evaluated using 20 μL of spiked human plasma samples. To test clinically relevant materials, the platform was utilized to study the effects of muscle tissue isolation speed on acylcarnitine stability, and to examine acylcarnitine abundance across muscle types in progeria (sarcopenia) mouse muscle. We found that the speed of muscle isolation does not affect measured levels of acylcarnitines, and detected higher acylcarnitine abundances are consistent with literature.

SIGNIFICANCE: This study provides an automated, high-throughput, and cost-effective workflow enabling extraction and analysis of 120 samples per day, with a cost of <0.1 Euro per sample. It presents a significant stride towards the creation of fully-automated, high-throughput bioanalysis workflows for large-scale studies involving biomass limited samples in the foreseeable future.