Impact of Anodic Respiration on Biopolymer Production and Consequent Membrane Fouling.

Microbial fuel cells (MFCs) have recently been integrated with membrane bioreactors (MBRs) for wastewater treatment and energy recovery. However, the impact of integration of the two reactors on membrane fouling of MBR has not been reported yet. In this study, MFCs equipped with different external resistances (1-10 000 ohm) were operated, and membrane-fouling potentials of the MFC anode effluents were directly measured to study the impact of anodic respiration by exoelectrogens on membrane fouling. It was found that although the COD removal efficiency was comparable, the fouling potential was significantly reduced due to less production of biopolymer (a major foulant) in MFCs equipped with lower external resistance (i.e., with higher current generation) as compared with aerobic respiration. Furthermore, it was confirmed that Geobacter sulfurreducens strain PCA, a dominant exoelectrogen in anode biofilms of MFCs in this study, produced less biopolymer under anodic respiration condition than fumarate (anaerobic) respiration condition, resulting in lower membrane-fouling potential. Taken together, anodic respiration can mitigate membrane fouling of MBR due to lower biopolymer production, suggesting that development of an electrode-assisted MBR (e-MBR) without aeration is feasible.

Screening of peptide ligands for pyrroloquinoline quinone glucose dehydrogenase using antagonistic template-based biopanning.

We have developed a novel method, antagonistic template-based biopanning, for screening peptide ligands specifically recognizing local tertiary protein structures. We chose water-soluble pyrroloquinoline quinone (PQQ) glucose dehydrogenase (GDH-B) as a model enzyme for this screening. Two GDH-B mutants were constructed as antagonistic templates; these have some point mutations to induce disruption of local tertiary structures within the loop regions that are located at near glucose-binding pocket. Using phage display, we selected 12-mer peptides that specifically bound to wild-type GDH-B but not to the antagonistic templates. Consequently, a peptide ligand showing inhibitory activity against GDH-B was obtained. These results demonstrate that the antagonistic template-based biopanning is useful for screening peptide ligands recognizing the specific local tertiary structure of proteins.

In silico panning for a non-competitive peptide inhibitor.

BACKGROUND: Peptide ligands have tremendous therapeutic potential as efficacious drugs. Currently, more than 40 peptides are available in the market for a drug. However, since costly and time-consuming synthesis procedures represent a problem for high-throughput screening, novel procedures to reduce the time and labor involved in screening peptide ligands are required. We propose the novel approach of 'in silico panning' which consists of a two-stage screening, involving affinity selection by docking simulation and evolution of the peptide ligand using genetic algorithms (GAs). In silico panning was successfully applied to the selection of peptide inhibitor for water-soluble quinoprotein glucose dehydrogenase (PQQGDH). RESULTS: The evolution of peptide ligands for a target enzyme was achieved by combining a docking simulation with evolution of the peptide ligand using genetic algorithms (GAs), which mimic Darwinian evolution. Designation of the target area as next to the substrate-binding site of the enzyme in the docking simulation enabled the selection of a non-competitive inhibitor. In all, four rounds of selection were carried out on the computer; the distribution of the docking energy decreased gradually for each generation and improvements in the docking energy were observed over the four rounds of selection. One of the top three selected peptides with the lowest docking energy, 'SERG' showed an inhibitory effect with Ki value of 20 microM. PQQGDH activity, in terms of the Vmax value, was 3-fold lower than that of the wild-type enzyme in the presence of this peptide. The mechanism of the SERG blockage of the enzyme was identified as non-competitive inhibition. We confirmed the specific binding of the peptide, and its equilibrium dissociation constant (KD) value was calculated as 60 microM by surface plasmon resonance (SPR) analysis. CONCLUSION: We demonstrate an effective methodology of in silico panning for the selection of a non-competitive peptide inhibitor from small virtual peptide library. This study is the first to demonstrate the usefulness of in silico evolution using experimental data. Our study highlights the usefulness of this strategy for structure-based screening of enzyme inhibitors.