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Background: Many crucial cellular operations such as metabolism, signalling, and regulations are based on protein-protein interactions. However, the lack of robust protein-protein interaction information is a challenge. One reason for the lack of solid protein-protein interaction information is poor agreement between experimental findings and computational sets that, in turn, comes from huge false positive predictions in computational approaches. Reduction of false positive predictions and enhancing true positive fraction of computationally predicted protein-protein interaction datasets based on highly confident experimental results has not been adequately investigated.

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A concept of unique peptides (CUP) was proposed and implemented to identify whole-cell proteins from tandem mass spectrometry (MS/MS) ion spectra. A unique peptide is defined as a peptide, irrespective of its length, that exists only in one protein of a proteome of interest, despite the fact that this peptide may appear more than once in the same protein. Integrating CUP, a two-step whole-cell protein identification strategy was developed to further increase the confidence of identified proteins. A dataset containing 40,243 MS/MS ion spectra of Saccharomyces cerevisiae and protein identification tools including Mascot and SEQUEST were used to illustrate the proposed concept and strategy. Without implementing CUP, the proteins identified by SEQUEST are 2.26 fold of those identified by Mascot. When CUP was applied, the proteins bearing unique peptides identified by SEQUEST are 3.89 fold of those identified by Mascot. By cross-comparing two sets of identified proteins, only 89 common proteins derived from CUP were found. The key discrepancy between identified proteins was resulted from the filtering criteria employed by each protein identification tool. According to the origin of peptides classified by CUP and the commonality of proteins recognized by protein identification tools, all identified proteins were cross-compared, resulting in four groups of proteins possessing different levels of assigned confidence.

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The Fenton's reagent was applied to decolor and degrade 2,4-dinitrophenol (DNP). Different concentrations of ferrous ion (Fe 2+ ) and hydrogen peroxide (H 2 O 2 ) were dosed to investigate their influences on the removal of DNP. The ADMI color value was adopted as an index to indicate the decoloring performance of the reaction. Low molecular weight of organic acids was monitored, and the role of dissolved oxygen during the DNP degradation was discussed.Results show that due to productions of colored intermediates and the oxalic acid, DNP was quickly removed, followed by the ADMI color value and DOC, respectively. Both initial removal rates of DNP and ADMI color value increased 935

Redox potential, known as oxidation-reduction or oxidoreduction potential (ORP), not only indicates the reduction and oxidation capacity of the environment but also reflects the metabolic activity of microorganisms. Redox potential can be monitored online and controlled in time for more efficient fermentation operation. This chapter reviews the enzymes that modulate intracellular redox potential, the genetically engineered strains that harbor specific redox potential-regulated genes, the approaches that were used to manipulate and control redox potential toward the production of desired metabolites, the role of redox potential in metabolic pathway, and the impact of redox potential on microbial physiology and metabolism. The application of redox potential-controlled ethanol fermentation and the development of three redox potential-controlled fermentation processes are illustrated. In the end, the future perspective of redox potential control is provided.