Motor proteins, including kinesin, can serve as biological components in engineered nanosystems. A proof-of-principle application is a "smart dust" biosensor for the remote detection of biological and chemical agents. The development of this system requires the integration of a diverse set of technologies, illustrates the complexity of biophysical mechanisms, and enables the formulation of general principles for nanoscale engineering. For example, our most recent work created a molecular system that is capable of dynamically assembling and disassembling its building blocks while retaining its functionality, and demonstrates the possibility of self-healing and adaptation. Optical techniques are a key tool to interrogate and interact with these nanosystems as they enable non-destructive measurements with nanometer precision as well as the control of chemical events at the nanoscale. The presentation will highlight the important contributions of photonics to the study of active nanosystems.
Significant effort has been invested into understanding the dynamics of protein adsorption on surfaces, in particular to predict protein behavior at the specialized surfaces of biomedical technologies like hydrogels, nanoparticles, and biosensors. Recently, the application of fluorescent single molecule imaging to this field has permitted the tracking of individual proteins and their stochastic contribution to the aggregate dynamics of adsorption. However, the interpretation of these results is complicated by (1) the finite time available to observe effectively infinite adsorption timescales and (2) the contribution of photobleaching kinetics to adsorption kinetics. Here, we perform a protein adsorption simulation to introduce specific survival analysis methods that overcome the first complication. Additionally, we collect single molecule residence time data from the adsorption of fibrinogen to glass and use survival analysis to distinguish photobleaching kinetics from protein adsorption kinetics.
KEYWORDS: Super resolution microscopy, Chemical analysis, Sensors, Image processing software, Molecular assembly, Proteins, Glasses, Interfaces, Biosensors, Molecules, Point spread functions, Signal to noise ratio, Detection and tracking algorithms, Charge-coupled devices, Super resolution, Data modeling, Algorithm development, Computer simulations, Microscopy
Super-resolution localization microscopy methods rely on accurate and fast localization algorithms. We introduce a simple algorithm for the localization of imaged objects based on the search of the best-correlated center. This approach yields tracking accuracies that are comparable to those of Gaussian fittings in typical low signal-to-noise ratios, but with 6× faster execution. The algorithm can be adapted to localize objects that do not exhibit radial symmetry or have to be localized in higher dimensional spaces.
Biomolecular motors, such as the motor protein kinesin, are simultaneously objects of scientific inquiry and components
for nanotechnology. The investigation of the properties of a biomolecular motor is challenging, since it is a dynamic
nanoscale object but at the same time soft and fragile. Photonic techniques are well suited to these investigations due to
their compatibility with an aqueous environment and their non-destructive character, however their resolution is often
insufficient. We adapted Fluorescence Interference Contrast (FLIC) microscopy to the imaging of microtubules
transported by kinesin motors (PNAS vol. 103, p. 15812) and achieved nm-resolution in the z-direction. This advance
provided insights into the role of the kinesin tail for the functioning of the motor in vivo, but also enabled us to
determine the "ground clearance" of molecular shuttles powered by kinesin motors. Kinesin-driven molecular shuttles,
in turn, enable the design of highly integrated bionanodevices. Photons are the most suitable tool to communicate with
such devices, since they can address molecules and nanoparticles packaged into the devices without the need for a
physical connection.
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