Automated in-time derivatization reduces post derivatization degradation for improved GC/MS analysis of sugars, organic acids and amino acids.
This work demonstrates an automated workflow that improves data quality and sample throughput when performing GC/MS analysis of sugars, organic acids and amino acids in metabolomics and similar studies. The quality of results is improved by treating all samples identically following the derivatization step. The protocol and the associated instrumentation can hold and prepare up to 300 samples per batch. Automated sample preparation and handling in this case minimizes sample-to-sample deviations relating to batch derivatization, more specifically to differences in the time spans from sample preparation to injection over the course of the analysis sequence, i.e. between the first and last samples analysed. Using the automated workflow, individual samples are derivatized at a defined point in time before injection into the GC-MS system, significantly reducing metabolite degradation throughout the sequence. Sample RSDs are significantly improved compared to offline batch derivatization. A combination of in-time sample derivatization, precision ‘Accurate add’ reagent transfers, and reduced number of septum punctures results in improved data quality and the automated workflow reduces the required reagent volume and labour time.
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