Two-dimensional gas chromatography time-of-flight mass spectrometry (gcxgc-tof-ms) data analysis for identifying unknown persistent organic pollutants in milk samples

Over the past decade, the Food and Drug Administration (FDA) has been investigating toxic compounds in milk samples. When analyzing milk samples using a two-dimensional gas chromatography coupled to a time-of-flight mass spectrometer (GCxGC-ToF-MS), thousands of compounds may be identified. The FDA targets up to twenty-four compounds. The purpose of this research is to be able to shift through the data and identify non-target compounds that occur across multiple samples as well as identify any patterns that may emerge between the samples’ GCxGC images. To compare compounds, an algorithm was developed that uses the mass spectra data collected to identify undiscovered patterns among the detected peaks, statistical methods were employed to assess data across seventy-two samples based on their GCxGC image. Compound locations are determined relative to the target compounds, being that, over time, the compound retention time locations may shift in the GCxGC image. Overall, the comparison algorithm compared a known non-target compound and identified 77 compounds with similar mass spectra as a ‘match’ with a success rate of 93.5%. Only one compound per sample can be a match. The remaining 6.5% accounted for repeated ‘matches’ from the same sample. When exploring the patterns in the sample, seven of the files featured abundances of non-target compounds that differentiated them from the other samples. Otherwise, based on the relative locations of the target analytes, the remaining samples were found to have little variance between one another. Further research is required to further quantify the profiles of each sample to improve the clustering, however, locations that are important for further investigation were identified and can provide more insight to the FDA of what compounds may potentially need to be monitored and possibly regulated.