Biosensing using antibody-modulated motility of actin filaments on myosin-coated surfaces.

Motor proteins, such as myosin and kinesin, are biological molecular motors involved in force generation and intracellular transport within living cells. The characteristics of molecular motors, i.e., their motility over long distances, their capacity of transporting cargoes, and their very efficient energy consumption, recommend them as potential operational elements of a new class of dynamic nano-devices, with potential applications in biosensing, analyte concentrators, and biocomputation. A possible design of a biosensor based on protein molecular motor comprises a surface with immobilized motors propelling cytoskeletal filaments, which are decorated with antibodies, presented as side-branches. Upon biomolecular recognition of these branches by secondary antibodies, the 'extensions' on the cytoskeletal filaments can achieve considerable lengths (longer than several diameters of the cytoskeletal filament carrier), thus geometrically impairing or halting motility. Because the filaments are several micrometers long, this sensing mechanism converts an event in the nanometer range, i.e., antibody-antigen sizes, into an event in the micrometer range: the visualization of the halting of motility of microns-long cytoskeletal filaments. Here we demonstrate the proof of concept of a sensing system comprising heavy-mero-myosin immobilized on surfaces propelling actin filaments decorated with actin antibodies, whose movement is halted upon the recognition with secondary anti-actin antibodies. Because antibodies to the actin-myosin system are involved in several rare diseases, the first possible application for such a device may be their prognosis and diagnosis. The results also provide insights into guidelines for designing highly sensitive and very fast biosensors powered by motor proteins.

Polymer surface properties control the function of heavy meromyosin in dynamic nanodevices.

The actin-myosin system, responsible for muscle contraction, is also the force-generating element in dynamic nanodevices operating with surface-immobilized motor proteins. These devices require materials that are amenable to micro- and nano-fabrication, but also preserve the bioactivity of molecular motors. The complexity of the protein-surface systems is greatly amplified by those of the polymer-fluid interface; and of the structure and function of molecular motors, making the study of these interactions critical to the success of molecular motor-based nanodevices. We measured the density of the adsorbed motor protein (heavy meromyosin, HMM) using quartz crystal microbalance; and motor bioactivity with ATPase assay, on a set of model surfaces, i.e., nitrocellulose, polystyrene, poly(methyl methacrylate), and poly(butyl methacrylate), poly(tert-butyl methacrylate). A higher hydrophobicity of the adsorbing material translates in a higher total number of HMM molecules per unit area, but also in a lower uptake of water, and a lower ratio of active per total HMM molecules per unit area. We also measured the motility characteristics of actin filaments on the model surfaces, i.e., velocity, smoothness and deflection of movement, determined via in vitro motility assays. The filament velocities were found to be controlled by the relative number of active HMM per total motors, rather than their absolute surface density. The study allowed the formulation of the general engineering principles for the selection of polymeric materials for the manufacturing of dynamic nanodevices using protein molecular motors.

Fungi use efficient algorithms for the exploration of microfluidic networks.

Fungi, in particular, basidiomycetous fungi, are very successful in colonizing microconfined mazelike networks (for example, soil, wood, leaf litter, plant and animal tissues), a fact suggesting that they may be efficient solving agents of geometrical problems. We therefore evaluated the growth behavior and optimality of fungal space-searching algorithms in microfluidic mazes and networks. First, we found that fungal growth behavior was indeed strongly modulated by the geometry of microconfinement. Second, the fungus used a complex growth and space-searching strategy comprising two algorithmic subsets: 1) long-range directional memory of individual hyphae and 2) inducement of branching by physical obstruction. Third, stochastic simulations using experimentally measured parameters showed that this strategy maximizes both survival and biomass homogeneity in microconfined networks and produces optimal results only when both algorithms are synergistically used. This study suggests that even simple microorganisms have developed adequate strategies to solve nontrivial geometrical problems.