Novel software for data analysis of Fourier transform ion cyclotron resonance mass spectra applied to natural organic matter

Natural organic matter (NOM) occurs as an extremely complex mixture of large, charged molecules that are formed by secondary synthesis reactions. Due to their nature, their full characterization is an important challenge to scientists specializing in NOM as well as analytical chemistry. Ultra-high-resolution Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) analysis enables the identification of thousands of masses in a single measurement. A major challenge in the data analysis process of NOM using the FT-ICR MS technique is the need to sort the entire data set and to present it in an accessible mode. Here we present a simple targeted algorithm called the David Mass Sort (DMS) algorithm which facilitates the detection and counting of consecutive series of masses correlated to any selected mass spacing. This program searches for specific mass differences among all of the masses in a single spectrum against all of the masses in the same spectrum. As a representative case, the current study focuses on the analysis of the well-characterized Suwannee River humic and fulvic acid (SRHA and SRFA, respectively). By applying this algorithm, we were able to find and assess the amount of singly and doubly charged molecules. In addition we present the capabilities of the program to detect any series of consecutive masses correlated to specific mass spacing, e.g. COO, H(2), OCH(2) and O(2). Under several limitations, these mass spacings may be correlated to both chemical and biochemical changes which occur simultaneously during the formation and/or degradation of large mixtures of compounds.