Automated Mass Spectral Deconvolution and Identification System for GC-MS Screening for Drugs, Poisons, and Metabolites in Urine

Abstract

Abstract Background: The challenge in systematic toxicological analysis using gas chromatography and/or liquid chromatography coupled to mass spectrometry is to identify compounds of interest from background noise. The large amount of spectral information collected in one full-scan MS run demands the use of automated evaluation of recorded data files. We evaluated the applicability of the freeware deconvolution software AMDIS (Automated Mass Spectral Deconvolution and Identification System) for GC-MS–based systematic toxicological analysis in urine for increasing the speed of evaluation and automating the daily routine workload. Methods: We prepared a set of 111 urine samples for GC-MS analysis by acidic hydrolysis, liquid-liquid extraction, and acetylation. After analysis, the resulting data files were evaluated manually by an experienced toxicologist and automatically using AMDIS with deconvolution and identification settings previously optimized for this type of analysis. The results by manual and AMDIS evaluation were then compared. Results: The deconvolution settings for the AMDIS evaluation were successfully optimized to obtain the highest possible number of components. Identification settings were evaluated and chosen for a compromise between most identified targets and general number of hits. With the use of these optimized settings, AMDIS-based data analysis was comparable or even superior to manual evaluation and reduced by half the overall analysis time. Conclusions: AMDIS proved to be a reliable and powerful tool for daily routine and emergency toxicology. Nevertheless, AMDIS can identify only targets present in the user-defined target library and may therefore not indicate unknown compounds that might be relevant in clinical and forensic toxicology.