An accelerated background subtraction algorithm for processing high-resolution MS data and its application to metabolite identification

Abstract

Background: Metabolite identification without radiolabeled compound is often challenging because of interference of matrix-related components. Results: A novel and an effective background subtraction algorithm (A-BgS) has been developed to process high-resolution mass spectral data that can selectively remove matrix-related components. The use of a graphics processing unit with a multicore central processing unit enhanced processing speed several 1000-fold compared with a single central processing unit. A-BgS algorithm effectively removes background peaks from the mass spectra of biological matrices as demonstrated by the identification of metabolites of delavirdine and metoclopramide. Conclusion: The A-BgS algorithm is fast, user friendly and provides reliable removal of matrix-related ions from biological samples, and thus can be very helpful in detection and identification of in vivo and in vitro metabolites.