Automated Isotopic Profile Deconvolution for High Resolution Mass Spectrometric data (APGC-QToF) from Biological Matrices.

An isotopic profile matching algorithm, isotopic profile deconvoluted chromatogram (IPDC), was developed to screen for a wide variety of organic compounds in high-resolution mass spectrometry (HRMS) data acquired from instruments with resolution power as low as 22,000 FWHM. The algorithm initiates the screening process by generating a series of C/Br/Cl/S isotopic patterns consistent with the profiles of approximately three million molecular formulas for compounds with potentially persistent, bioaccumulative, and toxic (PBT) properties. To evaluate this algorithm, HRMS data were screened using these seed profiles to isolate relevant chlorinated and/or brominated compounds. Data reduction techniques included mass defect filtering and retention time prediction from estimated boiling points predicted using molecular formulas and reasonable elemental conformations. A machine learning classifier was also developed using spectrometric and chromatographic variables to minimize false positives. A scoring system was developed to rank candidate molecular formulas for an isotopic feature. The IPDC algorithm was applied to a Lake Michigan lake trout extract analyzed by Atmospheric Pressure Gas Chromatography-Quadrupole Time-of-Flight (APGC-QToF) mass spectrometry in positive and negative modes. The IPDC algorithm detected isotopic features associated with legacy contaminants and a series of unknown halogenated features. The IPDC algorithm resolved 313 and 855 halogenated features in positive and negative modes, respectively in Lake Michigan Lake trout.