Quantitative analysis and modeling of redox networks in biology

A scientific and cultural revolution occurred with the sequencing of the human genome. The information provided by this accomplishment has provided tools for researchers to test new ideas in silico and on the bench. In redox biology many of the genes, transcripts, proteins, and redox active species have been well characterized. However, the vast majority have not been quantitated in an absolute manner. This is a necessary step to provide the tools for mathematical modeling and systems biology approaches for predicting changes in the cellular redox environment and the biochemical and biological consequences. Here we demonstrate techniques for the absolute quantitation of human catalase, glutathione peroxidase, peroxiredoxin, thioredoxin, and superoxide dismutase within cells. These techniques can be parsed into two groups: detection of activity and detection of total amount of species. Methods for the absolute quantitation of active catalase, peroxiredoxins, and superoxide dismutase have been developed by utilizing specific characteristics of each enzyme. Catalase generates oxygen in the presence of hydrogen peroxide that can easily be detected with a Clark electrode (oxygen monitor); the data are fit to a single-exponential to determine the observed pseudo-first-order rate constant. From this the effective number of fully active catalase enzymes in the sample can be determined. Peroxiredoxin in the disulfide state can be reduced by thioredoxin; thioredoxin from E. coli loses fluorescence upon oxidation. The loss of fluorescence over time is mathematically fit to a single-exponential to determine the observed pseudo first-order rate constant from which the number of active enzymes can be determined. Using an inhibition assay to detect superoxide dismutase activity along with the rate constants at which superoxide reacts with the dismutase and the competing superoxide-reacting-indicator-molecule, the concentration of active superoxide dismutase can be determined. To detect the total amount of protein of an enzyme in a biological sample, an immunoassay was first implemented. This method utilized Bio-Plex® beads from Bio-Rad; however, it was problematic because the antibodies applied did not perform satisfactorily not allowing sufficient signal-to-noise to be deployed. Quantitative mass spectrometry was then implemented to detect total catalase, glutathione peroxidase 1, peroxiredoxin 2, and thioredoxin 1 in human red blood cells. With the absolute concentration of these enzymes and proteins along with data for oxygen consumption rates and peroxisomal hydrogen peroxide concentration for several cell lines, we hypothesize that a reasonable model of hydrogen peroxide and superoxide flux can be constructed. Quantitative data such as these provide the foundation for the new redox biology of the 21st century. Presented here is a roadmap for the obligatory first steps to dissect quantitatively the cellular and tissue metabolic pathways and redox networks that are the basis of all of biology.