Session V19: New Frontiers for Biological Physics

Mechanochemistry of Molecular Motors

Molecular motors lie at the heart of biological processes from DNA replication to vesicle transport. We seek to understand the physical mechanisms by which these nanoscale machines convert chemical energy into mechanical work. I will overview our ongoing use of single molecule tracking and manipulation techniques to observe and perturb substeps in the mechanochemical cycles of individual motors, before concentrating on our recent efforts to dissect the structural basis of a ``reverse gear'' in myosin VI. The basic actomyosin motor has been embellished, altered, and re-used many times through the evolution of diverse members of the myosin superfamily. Class VI myosins are highly specialized (-) end directed motors involved in a growing list of functions in animal cells, including endocytosis, cell migration, and maintenance of stereociliar membrane tension. How does myosin VI achieve reverse directionality, despite sharing extensive sequence and structural conservation with (+) end directed myosins? We generated a series of truncated myosin VI constructs and characterized the size and direction of the power stroke for each construct using dual-labeled gliding filament assays and optical trapping. Motors truncated near the end of the converter domain generate (+) end directed motion, whereas longer constructs move toward the (-) end, confirming the importance of a class-specific insert that redirects the lever arm. Our quantitative results suggest a surprising model in which the lever arm rotates $\sim$180$^{\circ}$ during the power stroke. We are currently studying the behavior of engineered myosin VI constructs with artificial lever arms, in order to further challenge and refine our power stroke model.   

Rare returns on lost effort! Dynamic refolding (after unfolding) of protein domains.

Dynamic force loading is an established technique for probing the forward kinetics in unfolding of single protein domains. Examined over several orders of magnitude in force rate, the unfolding forces often exhibit a linear dependence on the logarithm of loading rate, revealing the dynamic truncation of a precipitous activation barrier. The slope and force-rate intercept of the linear response characterize the critical molecular length gained in the barrier transition and the force-free rate of barrier passage. On the other hand, if reversed and probed with negative force rates, refolding of a stretched polypeptide chain has been found to yield a linear relation between the squares of the refolding forces and the logarithms of (reverse) force rates. Revealing here the dynamic elevation of a deep harmonic well that confines the unfolded states, the slope and force-rate intercept of the linear response characterize the effective spring constant of the harmonic well and the unstretched refolding rate. Representing a dynamical corollary to predictions of fluctuation theorems for small systems, the most-frequent amount of mechanical work recovered (from the thermal environment) in refolding increases with each decade reduction in the force-unloading rate and approaches the limit set by near-equilibrium transitions over a logarithmic span related to the free energy of transition.   

Generalization of distance to higher dimensional objects, and its application to protein folding

After a brief biophysical introduction to motivate the problem, I will show how the notion and calculation of distance between two objects can be generalized to the case where the objects are no longer points, but are one-dimensional. Additional concepts such as nonextensibility, curvature constraints, and noncrossing become central to the notion of distance. I will give some analytical and numerical results for specific examples, and I will discuss applications to biopolymers and protein folding.   

Getting into shape: the physics of bacterial morphology

Bacterial cells come in a wide variety of shapes and sizes, with the peptidoglycan cell wall as the primary stress-bearing structure that dictates cell shape. In recent years, cell shape has been shown to play a critical role in regulating many important biological functions including attachment, dispersal, motility, polar differentiation, predation, and cellular differentiation. Though many molecular details of the composition and assembly of the cell wall components are known, how the peptidoglycan network organizes to give the cell shape during normal growth, and how it reorganizes in response to damage or environmental forces have been relatively unexplored. We introduce a quantitative mechanical model of the bacterial cell wall that predicts the response of cell shape to peptidoglycan damage in the rod-shaped Gram-negative bacterium {\it Escherichia coli}. To test these predictions, we use time-lapse imaging experiments to show that damage often manifests as a bulge on the sidewall, coupled to large-scale bending of the cylindrical cell wall around the bulge. The direction of bending confirms the hypothesis of a longitudinal orientation of peptides and a circumferential orientation of glycan strands in the peptidogylcan layer. Our simulations based on our physical model also suggest a surprising robustness of cell shape to damage, allowing cells to grow and maintain their shape even under conditions that limit crosslinking. Finally, we show that many common bacterial cell shapes can be realized within the model via simple spatial patterning of peptidoglycan defects, suggesting that subtle patterning changes could underlie the great diversity of shapes observed in the bacterial kingdom.   

Sensing and Selection in Bacteria

The ability to sense changes in the environment allows bacteria to respond by altering their phenotype, or behavior, to adapt to new conditions. Alternatively, bacteria have the ability to spontaneously change their phenotype, without sensing. Such behavior is known as stochastic switching. By simply observing dividing bacteria, is it possible to tell whether the cells are sensing their environment? This talk presents a theory that can decouple the action of sensing from the action of natural selection using single-cell observation of bacteria.