Nanoscale roughness affects the activity of enzymes adsorbed on cluster-assembled titania films.

In this study, we investigated how the adsorption properties governed by the nanometer-scale surface morphology of cluster-assembled titanium oxide films influence the catalytic activity of immobilized serine-protease trypsin. We developed an activity assay for the parallel detection of physisorbed enzyme activity and mass density of the adsorbed proteins in microarray format. The method combines a microarray-based technique and advanced quantitative confocal microscopy approaches based on fluorescent labeling of enzymes and covalent labeling of active sites of surface-bound enzymes. The observed diminishing trypsin binding affinity with increasing roughness, as opposed to the steep rise in its saturation uptake, was interpreted as heterogeneous nucleation-driven adsorption of trypsin at the rough nanoporous titania surface. The increase in relative activity of adsorbed trypsin is proportional to the fractional saturation of titania surfaces, expressed as percentage of saturation uptake. In turn, the specific activity, that is, the ratio of active proteins to the absolute number of adsorbed proteins, drops with growing saturation uptake and surface roughness, witnessing a reduction in the accessibility of enzyme active sites. Both geometrical constraints of titania nanopores and the clusterwise adsorption of trypsin were identified as the key factors underpinning the steric hindrance of the immobilized enzyme. These findings are relevant for the optimization of rough nanoporous surfaces as carriers of immobilized enzymes. The proposed activity assay is particularly advantageous in the screening of candidate materials for enzyme immobilization.

Selective modulation of cell response on engineered fractal silicon substrates.

A plethora of work has been dedicated to the analysis of cell behavior on substrates with ordered topographical features. However, the natural cell microenvironment is characterized by biomechanical cues organized over multiple scales. Here, randomly rough, self-affinefractal surfaces are generated out of silicon,where roughness Ra and fractal dimension Df are independently controlled. The proliferation rates, the formation of adhesion structures, and the morphology of 3T3 murine fibroblasts are monitored over six different substrates. The proliferation rate is maximized on surfaces with moderate roughness (Ra ~ 40 nm) and large fractal dimension (Df ~ 2.4); whereas adhesion structures are wider and more stable on substrates with higher roughness (Ra ~ 50 nm) and lower fractal dimension (Df ~ 2.2). Higher proliferation occurson substrates exhibiting densely packed and sharp peaks, whereas more regular ridges favor adhesion. These results suggest that randomly roughtopographies can selectively modulate cell behavior.