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Microbial activity of the sediment phase in a 1.5-km-long concrete sewer section with a cement pipe in a 540-mm diameter was investigated in this paper. SEM examinations and elementary composition analyses of the sediment samples have identified the presence of a biofilm layer at the sediment surface. Bacterial counting results with a DNA-staining technique have revealed that the amount of bacteria in this layer was 2.1×1011 cell g−1 dry wt, which is close to that of activated sludge. ATP content in the sewer biofilm was found relatively high, demonstrating that the sewer biofilm is active. Throughout the entire 1.5-km sewer section, the biofilm activity was maintained at almost the same level. Lab-scale sediment oxygen uptake flux (SOUF) tests showed that the shear flow velocity above the sediment phase linearly increases the SOUF, which of the potential value was determined to be 32 g O2 m−2 day−1 at an estimated shear flow velocity of 0.055 m s−1 at 25°C in the sewer line, provided that the mean flow velocity was 1.5 m s−1, and the mean water depth was 220 mm. Such a high SOUF value further endorsed the existence of the active sewer biofilm. [Copyright &y& Elsevier]

Protein-protein interactions are critical determinants in biological systems. Engineered proteins binding to specific areas on protein surfaces could lead to therapeutics or diagnostics for treating diseases in humans. But designing epitope-specific protein-protein interactions with computational atomistic interaction free energy remains a difficult challenge. Here we show that, with the antibody-VEGF (vascular endothelial growth factor) interaction as a model system, the experimentally observed amino acid preferences in the antibody-antigen interface can be rationalized with 3-dimensional distributions of interacting atoms derived from the database of protein structures. Machine learning models established on the rationalization can be generalized to design amino acid preferences in antibody-antigen interfaces, for which the experimental validations are tractable with current high throughput synthetic antibody display technologies. Leave-one-out cross validation on the benchmark system yielded the accuracy, precision, recall (sensitivity) and specificity of the overall binary predictions to be 0.69, 0.45, 0.63, and 0.71 respectively, and the overall Matthews correlation coefficient of the 20 amino acid types in the 24 interface CDR positions was 0.312. The structure-based computational antibody design methodology was further tested with other antibodies binding to VEGF. The results indicate that the methodology could provide alternatives to the current antibody technologies based on animal immune systems in engineering therapeutic and diagnostic antibodies against predetermined antigen epitopes. [ABSTRACT FROM AUTHOR]

Phage display of antibody fragments from natural or synthetic antibody libraries with the single chain constructs combining the variable fragments (scFv) has been one of the most prominent technologies in antibody engineering. However, the nature of the artificial single chain constructs results in unstable proteins expressed on the phage surface or as soluble proteins secreted in the bacterial culture medium. The stability of the variable domain structures can be enhanced with interdomain disulfide bond, but the single chain disulfide-stabilized constructs (sc-dsFv) have yet to be established as a feasible format for bacterial phage display due to diminishing expression levels on the phage surface in known phage display systems. In this work, biological combinatorial searches were used to establish that the c-region of the signal sequence is critically responsible for effective expression and functional folding of the sc-dsFv on the phage surface. The optimum signal sequences increase the expression of functional sc-dsFv by 2 orders of magnitude compared with wild-type signal sequences, enabling the construction of phage-displayed synthetic antivascular endothelial growth factor sc-dsFv libraries. Comparison of the scFv and sc-dsFv variants selected from the phage-displayed libraries for vascular endothelial growth factor binding revealed the sequence preference differences resulting from the interdomain disulfide bond. These results underlie a new phage display format for antibody fragments with all the benefits from the scFv format but without the downside due to the instability of the dimeric interface in scFv. [ABSTRACT FROM AUTHOR]

Structural origin of substrate-enzyme recognition remains incompletely understood. In the model enzyme system of serine protease, canonical anti-parallel β-structure substrate-enzyme complex is the predominant hypothesis for the substrate-enzyme interaction at the atomic level. We used factor Xa (fXa), a key serine protease of the coagulation system, as a model enzyme to test the canonical conformation hypothesis. More than 160 fXa-cleavable substrate phage variants were experimentally selected from three designed substrate phage display libraries. These substrate phage variants were sequenced and their specificities to the model enzyme were quantified with quantitative enzyme-linked immunosorbent assay for substrate phage-enzyme reaction kinetics. At least three substrate-enzyme recognition modes emerged from the experimental data as necessary to account for the sequence-dependent specificity of the model enzyme. Computational molecular models were constructed, with both energetics and pharmacophore criteria, for the substrate-enzyme complexes of several of the representative substrate peptide sequences. In contrast to the canonical conformation hypothesis, the binding modes of the substrates to the model enzyme varied according to the substrate peptide sequence, indicating that an ensemble of binding modes underlay the observed specificity of the model serine protease. [ABSTRACT FROM AUTHOR]