Mechanisms of humic acids degradation by white rot fungi explored using ¹H NMR spectroscopy and FTICR mass spectrometry.

Enzymatic activities involved in decay processes of natural aromatic macromolecules, such as humic acids (HA) and lignin by white rot fungi, have been widely investigated. However, the physical and chemical analysis of degradation products of these materials has not been intensively explored. Fourier transform cyclotron resonance mass spectrometry (FTICR MS) and 1H NMR as well as CHNOS and size exclusion chromatography were employed to study the mechanisms of HA degradation by Trametes sp. M23 and Phanerochaete sp. Y6. Size exclusion chromatography analyses demonstrate and provide evidence for HA breakdown into low MW compounds. The 1H NMR analysis revealed oxidation, a decrease in the aromatic content, and an indication of demethylation of the HA during biodegradation. Evidence for oxidation was also obtained using CHNOS. Analysis of FTICR MS results using a new software program developed by our group (David Mass Sort) revealed consecutive series of masses suggesting biochemical degradation trends such as oxidation, aromatic cleavage, and demethylation. These results are in agreement with the 1H NMR analysis and with the suggested role of the ligninolytic system leading to HA degradation

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