An open source LABVIEW platform for simulating image series of fluorescent microtubules in gliding assays

We describe an open-source LabVIEW software platform for generating simulated images of microtubules in gliding motility assays. We describe how the software works and how to obtain the software

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

We show here the effects of heavy-hydrogen water (^2^H~2~O) and heavy-oxygen water (H~2~^18^O) 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 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 biomolecular devices incorporating molecular motors

Speed effects in gliding motility assays due to surface passivation, water isotope, and osmotic stress.

The molecular motor kinesin-1, an ATPase, and the substrate it walks along, microtubules, are vital components of eukaryotic cells. Kinesin converts chemical energy to linear motion as its two motor domains step along microtubules in a process similar to how we walk. Cells create systems of microtubules that direct the motion of kinesin. This directed motion allows kinesin to transport various cargos inside cells.

During the stepping process, the kinesin motor domains bind and unbind from their binding sites on the microtubules. Binding and unbinding rates of biomolecules are highly dependent on hydration and exclusion of water from the binding interface. Osmotic stress will likely strongly affect the binding and unbinding rates for kinesin and thus offers a tool to specifically probe those steps. We will report the effects of different osmolytes on microtubule speed and other observables in the gliding motility assay.

Kinesin’s kinetic core cycle hydrolyzes ATP with the help of a water molecule. Any modification to the water molecules the kinesin is in will change how ATP hydrolyzes and will ultimately affect how kinesin moves along microtubules. We will report preliminary results showing how kinesin is affected when the solvent it is in is changed from light water to heavy water.
 
When used in a surface assay or in devices, the kinesin and microtubule system is also dependent on substrate passivation. Kinesin motor domains do not transport microtubules in the gliding motility assay if kinesin is added to a glass microscope slide that has not been functionalized. Functionalization of the glass slides and slips is typically performed with bovine milk proteins called caseins. Bovine casein is a globular protein that can be broken up into four constituents: αs1, αs2, β, and κ. Each casein constituent affects how kinesin adheres to the glass and ultimately the speed at which microtubules are observed to glide at. Building on the work of Verma et.al., we have found that each constituent individually produces different outcomes in gliding assays. We will present these findings and discuss implications they have for use of gliding assays to study kinesin and use of kinesin-microtubule system in microdevices. 

[1] Chaen, S, N Yamamoto, I Shirakawa, and H Sugi. 2001. Effect of deuterium oxide on actomyosin motility in vitro. _Biochimica et biophysica acta_ 1506, no. 3: 218-23. 
[2] Vivek Verma, William O Hancock, Jeffrey M Catchmark, "The role of casein in supporting the operation of surface bound kinesin," _J. Biol. Eng._ 2008; 2: 14.

Acknowledgements: This work was supported by the DTRA CB Basic Research Program under Grant No. HDTRA1-09-1-008.
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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

Osmotic stress and water isotope effects in kinesin-1 gliding motility assays

The osmotic pressure and kinetic properties of water play important roles in biomolecular interactions. As pointed out by Parsegian, Rand, and Rau, these crucial roles are often overlooked[1]. In some fields, osmotic stress and isotope effects have been exploited for probing the role water plays in binding interactions of biomolecules. To our knowledge, there have been no studies of osmotic stress and water isotope effects for kinesin, and only a handful for myosin. We're currently using the gliding motility assay to see whether we can extract new information about kinesin-1 / microtubule interactions by changing osmotic stress and water isotopes. We will describe our open-source, automated analysis platform for extracting microtubule gliding speeds from image series. We will also show our preliminary analyses of the changes seen in gliding assays when done in heavy water (either heavy-hydrogen or heavy-oxygen) or osmolytes (betaine). We will discuss whether osmotic stress and isotopes, particularly heavy-oxygen water, might be an important tool for probing effects of water on binding interactions between kinesin and microtubules. We will also discuss potential applications of deuterium water for stabilizing microtubules and kinesin for lab or device applications.
[1] Parsegian, V. A., Rand, R. P., & Rau, D. C. (1995). Macromolecules and water: probing with osmotic stress. Methods in Enzymology, 259.

This work was supported by the DTRA CB Basic Research Program under Grant No. HDTRA1-09-1-008 in collaboration with Dr. Susan Atlas lab (UNM).
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Kinetic and statistical mechanical modeling of DNA unzipping and kinesin mechanochemistry

This thesis explores two topics. The first is shotgun DNA mapping (SDM). Ability to map polymerases and nucleosomes on chromatin is important for understanding the impact of chromatin remodeling on key cellular processes. Current methods have produced a wealth of information that demonstrates this importance, but key information is elusive in these methods. We are pursuing a new single-molecule chromatin mapping method based on unzipping native chromatin molecules with optical tweezers. The first step we are taking towards this ability is SDM. This is the ability to identify the genomic location of a random DNA fragment based on its naked DNA unzipping forces compared with simulated unzipping forces of a published genome. We show that ∼32 separate experimental unzipping curves for pBR322 were correctly matched to their simulated unzipping curves hidden in a background of the ∼2700 sequences neighboring XhoI sites in the S. cerevisiae (yeast) genome. We describe this method and characterize its robustness as well as discuss future applications. The second topic is a discrete state model for kinesin-1's processivity. Kinesin-1 is a homodimeric molecular motor protein that uses ATP and a hand-over-hand motion to transport cargo along microtubules. Minimal kinetic models are often developed to both explain kinesin's hand-over-hand forward-stepping behavior and to infer important kinetic rate constants from experimental data. These minimal models are often limited to a handful of two-headed states on a core cycle. However, it is not always clear how to evolve these core-cycle models to explain more complex behavior. We have developed a kinetic model without a pre-defined core cycle. Our model includes 80 two-headed states and permits transitions between any two states that differ by a single catalytic or binding event. We constrain the rate constants as much as possible by published rates and mechanical strain in the kinesin neck linkers and their docking state. We present a model for neck-linker modulation of head and nucleotide binding and unbinding rates. We show that our model reproduces generally-accepted experimental results. The core cycles that emerge are slightly different than those seen in previous experiments. We also explore how processivity and speed change with neck linker length

A Discrete State Model for Kinesin-1 with Rate Constants Modulated by Neck Linker Tension

Kinesin-1 is a homodimeric molecular motor protein that uses ATP and a hand-over-hand motion to transport cargo along microtubules. How kinesin converts chemical energy into directed motion is a question that has been actively studied since its discovery. Even at the most coarse-grained level of chemical kinetics, understanding is still lacking. Minimal kinetic models are often developed to both explain kinesin’s hand-over-hand forward-stepping behavior and to infer important kinetic rate constants from experimental data. These minimal models are often limited to a handful of two-headed states on a core cycle and have been essential for the current level of understanding. However, it is not always clear how to evolve these core-cycle models to explain more complex behavior such as non-processive motion. We have taken a different approach and have developed a kinetic model without a pre-defined core cycle. Our model includes 80 two-headed states and permits transitions between any two states that differ by a single catalytic or binding event. We constrain the rate constants as much as possible by published experimental data. We define many of the remaining unknown rate constants based on mechanical strain in the kinesin neck linkers and their docking state. We present a one-dimensional model for neck-linker modulation of head binding and unbinding rates and nucleotide binding and unbinding rates. We show that our model reproduces a run length (processivity) and run time in the range of experimental results. The core cycles that emerge are slightly different than those commonly discussed. We also explore how processivity and speed change with neck linker length. Our modeling applications are available as LabVIEW open-source code and compiled executables for PCs, which will allow other research groups to adapt the model and rate constants and may aid in general understanding of molecular motor behavior

(Corrected) Osmotic stress and water isotope effects in kinesin-1 gliding motility assays

The osmotic pressure and kinetic properties of water play important roles in biomolecular interactions. As pointed out by Parsegian, Rand, and Rau, these crucial roles are often overlooked[1]. In some fields, osmotic stress and isotope effects have been exploited for probing the role water plays in binding interactions of biomolecules. To our knowledge, there have been no studies of osmotic stress and water isotope effects for kinesin, and only a handful for myosin. We're currently using the gliding motility assay to see whether we can extract new information about kinesin-1 / microtubule interactions by changing osmotic stress and water isotopes. We will describe our open-source, automated analysis platform for extracting microtubule gliding speeds from image series. We will also show our preliminary analyses of the changes seen in gliding assays when done in heavy water (either heavy-hydrogen or heavy-oxygen) or osmolytes (betaine). We will discuss whether osmotic stress and isotopes, particularly heavy-oxygen water, might be an important tool for probing effects of water on binding interactions between kinesin and microtubules. We will also discuss potential applications of deuterium water for stabilizing microtubules and kinesin for lab or device applications.
[1] Parsegian, V. A., Rand, R. P., & Rau, D. C. (1995). Macromolecules and water: probing with osmotic stress. Methods in Enzymology, 259.

This work was supported by the DTRA CB Basic Research Program under Grant No. HDTRA1-09-1-008 in collaboration with Dr. Susan Atlas lab (UNM).

CORRECTIONS: At the workshop, Erik Schaffer pointed out to us that some of our speed differences (casein data) were surely due to microscope increasing in temperature. I’ve edited the poster to correct for this. Thanks, Erik