Mass-Remainder Analysis (MARA): An Improved Method for Elemental Composition Assignment in Petroleomics.

Abstract

Data processing and visualization methods have an important role in the mass spectrometric study of crude oils and other natural samples. The recently invented data mining procedure, Mass-Remainder Analysis (MARA), was further developed for use in petroleomics. MARA is based on the calculation of the remainder after dividing by the exact mass of a base unit, in petroleomics by the mass of the CH2 group. The two key steps in the MARA algorithm are the separation of the monoisotopic peaks from the other isotopic peaks and the subsequent intensity correction. The effectiveness of our MARA method was demonstrated on the analysis of lubricating mineral oil and crude oil samples by ultra-high-resolution Fourier transform ion cyclotron resonance mass spectrometry experiments. MARA is able to handle a huge portion of the overlapped peaks even in a moderate resolution mass spectrum. With use of MARA, effective chemical composition assignment and visual representation were achieved for complex mass spectra recorded by a time-of-flight analyzer with a limited resolution of 40 000 at m/ z 400. In the absence of an ultra-high-resolution mass analyzer, MARA can provide a closer look on the mass spectral peaks, like a digital zoom in a simple camera.