Lawrence J. Herskowitz

Effects of surface passivation on gliding motility assays.

In this study, we report differences in the observed gliding speed of microtubules dependent on the choice of bovine casein used as a surface passivator. We observed differences in both speed and support of microtubules in each of the assays. Whole casein, comprised of αs1, αs2, β, and κ casein, supported motility and averaged speeds of 966±7 nm/s. Alpha casein can be purchased as a combination of αs1 and αs2 and supported gliding motility and average speeds of 949±4 nm/s. Beta casein did not support motility very well and averaged speeds of 870±30 nm/s. Kappa casein supported motility very poorly and we were unable to obtain an average speed. Finally, we observed that mixing alpha, beta, and kappa casein with the proportions found in bovine whole casein supported motility and averaged speeds of 966±6 nm/s.

Effect of 2H and 18O water isotopes in kinesin-1 gliding assay

We show for the first time the effects of heavy-hydrogen water (2H2O) and heavy-oxygen water (H218O) on the gliding speed of microtubules on kinesin-1 coated surfaces. Increased fractions of isotopic waters used in the motility solution decreased the gliding speed of microtubules by a maximum of 21% for heavy-hydrogen and 5% for heavy-oxygen water. We also show that gliding microtubule speed returns to its original speed after being treated with heavy-hydrogen water. We discuss possible interpretations of these results and the importance for future studies of water effects on kinesin and microtubules. We also discuss the implication for using heavy waters in biomolecular devices incorporating molecular motors.

Open-Source Stochastic Simulation for Modeling Kinesin-1 Kinetics

Kinesin-1 (conventional kinesin) is a homodimeric motor protein important for axonal transport. It has been well studied through ensemble and single-molecule assays. However, the enzymatic stepping cycle is complex, with many rate constants that are modulated by interaction of the two motor domains. This makes it difficult to predict how changes in a given rate constant may affect observable properties such as processivity, velocity, or stall force. We have written a simulation of kinesin walking using a Stochastic Simulation Algorithm. The model allows for interactions between the heads, and includes states that are not considered part of the normal cycle. This adds to the complexity of the model but also allows for probing rare events, such as those that lead to a finite processivity. Also included are rate constant dependencies on force and concentrations of ATP, ADP, and Pi, which may provide insight into other processes under investigation, such as kinesin backstepping. We intend to use the simulation to aid in interpreting our own gliding motility assay results and to place upper and lower limits on values for rate constants. Our source and executable codes will be freely available.Acknowledgements: This work was supported by the DTRA CB Basic Research Program under Grant No. HDTRA1-09-1-008.