Abstract
AbstractPESI-MS enables with its greatly simplified handling and fast result delivery the application field for high-throughput use in routine settings. In health care and research, pre-analytical errors often remain undetected and disrupt diagnosis, treatment, clinical studies and biomarker validations incurring high costs. This proof-of-principle study investigates the suitability of PESI-MS for robust, routine sample quality evaluation.One of the most common pre-analytical quality issues in blood sampling are prolonged transportations times from bedside to laboratory promptly changing the metabolome. Here, human blood (n=50) was processed immediately or with a time delay of 3 h. The developed sample preparation method delivers ready-to-measure extracts in <8 min. PESI-MS spectra were measured in both ionization modes in 2 min from as little as 2 µl plasma allowing 3 replicate measurements. The mass spectra contained 1200 stable features covering a broad chemical space covering major metabolic classes (e.g. fatty acids, lysolipids, lipids). The time delay of 3 h was predictable by using 18 features with AUC > 0.95 with various machine learning and was robust against loss of single features.Our results serve as first proof of principle for the unique advantages of PESI-MS in sample quality assessments. The results pave the way towards a fully automated, cost-efficient, user-friendly, robust and fast quality assessment of human blood samples from minimal sample amounts.Graphical abstract
Publisher
Cold Spring Harbor Laboratory
Cited by
1 articles.
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