A nanoscale reciprocating rotary mechanism with coordinated mobility control

Biological molecular motors transform chemical energy into mechanical work by coupling cyclic catalytic reactions to large-scale structural transitions. Mechanical deformation can be surprisingly efficient in realizing such coupling, as demonstrated by the F1FO ATP synthase. Here, we describe a synthetic molecular mechanism that transforms a rotary motion of an asymmetric camshaft into reciprocating large-scale transitions in a surrounding stator orchestrated by mechanical deformation. We design the mechanism using DNA origami, characterize its structure via cryo-electron microscopy, and examine its dynamic behavior using single-particle fluorescence microscopy and molecular dynamics simulations. While the camshaft can rotate inside the stator by diffusion, the stator’s mechanics makes the camshaft pause at preferred orientations. By changing the stator’s mechanical stiffness, we accelerate or suppress the Brownian rotation, demonstrating an allosteric coupling between the camshaft and the stator. Our mechanism provides a framework for manufacturing artificial nanomachines that function because of coordinated movements of their components.

Monitoring of Superparamagnetic Particle Sizes in the Langevin Law Regime

In this work, aqueous solutions of magnetite nanoparticles (NPs) are studied. Magnetite NPs are very useful in biomedicine for magnetic resonance imaging (MRI), for drug delivery therapy, and also for hyperthermia. In order to predict the NP efficiency in these applications, it is crucial to accurately characterize their size distribution and their magnetization. Magnetometry, through the dependence of NP magnetization on the magnetic induction (MB curve), can provide interesting information on these physical properties. In this work, the extraction of the NP size distribution and magnetization from experimental MB curves of aqueous solutions of magnetite NPs is discussed. The results are compared to TEM and XRD characterizations. It is shown that an expression taking into account the size distribution better fits the results than the commonly used simple Langevin function. The size distributions obtained by magnetometry seem comparable to those obtained by TEM measurements. However, a closer look at the results shows some nonnegligible discrepancies: the size distributions obtained by magnetometry vary with the temperature and are closer to the TEM ones at room temperature. Our study suggests that it could be explained by the nonnegligible anisotropy energy of the NPs at low temperature and the lack of NP Brownian rotation below the freezing point of water. This demonstrates that care must be taken when interpreting the results obtained by magnetometry of magnetite NPs: only the size and size distribution obtained at room temperature should be used.

Contribution of brownian rotation and particle assembly polarisation to the particle response in magnetic particle spectrometry

The spectrometry of super-paramagnetic iron-oxide nanoparticles is a central tool for characterising particles that are used in Magnetic Particle Imaging. In Magnetic Particle Imaging, nanoparticles are excited by a magnetic field and the particle response is measured. Until now, the influence of the trajectory sequence on the dynamic particle relaxation has not been scoped. With a multi-dimensional Magnetic Particle Spectrometer, analysing the behaviour of different trajectories on the particles becomes possible. In this paper, the contribution of Brownian rotation and assembly polarisation on the particle signal is being analysed.

Modelling and analysis of bacterial tracks suggest an active reorientation mechanism in Rhodobacter sphaeroides

Most free-swimming bacteria move in approximately straight lines, interspersed with random reorientation phases. A key open question concerns varying mechanisms by which reorientation occurs. We combine mathematical modelling with analysis of a large tracking dataset to study the poorly understood reorientation mechanism in the monoflagellate species Rhodobacter sphaeroides . The flagellum on this species rotates counterclockwise to propel the bacterium, periodically ceasing rotation to enable reorientation. When rotation restarts the cell body usually points in a new direction. It has been assumed that the new direction is simply the result of Brownian rotation. We consider three variants of a self-propelled particle model of bacterial motility. The first considers rotational diffusion only, corresponding to a non-chemotactic mutant strain. Two further models incorporate stochastic reorientations, describing ‘run-and-tumble’ motility. We derive expressions for key summary statistics and simulate each model using a stochastic computational algorithm. We also discuss the effect of cell geometry on rotational diffusion. Working with a previously published tracking dataset, we compare predictions of the models with data on individual stopping events in R. sphaeroides . This provides strong evidence that this species undergoes some form of active reorientation rather than simple reorientation by Brownian rotation.

Modelling and analysis of bacterial tracks suggest an active reorientation mechanism inRhodobacter sphaeroides

Most free-swimming bacteria move in approximately straight lines, interspersed with random reorientation phases. A key open question concerns varying mechanisms by which reorientation occurs. We combine mathematical modelling with analysis of a large tracking dataset to study the poorly-understood reorientation mechanism in the monoflagellate speciesRhodobacter sphaeroides. The flagellum on this species rotates counterclockwise to propel the bacterium, periodically ceasing rotation to enable reorientation. When rotation restarts the cell body usually points in a new direction. It has been assumed that the new direction is simply the result of Brownian rotation. We consider three variants of a self-propelled particle model of bacterial motility. The first considers rotational diffusion only, corresponding to a non-chemotactic mutant strain. A further two models also include stochastic reorientations, describing 'run-and-tumble' motility. We derive expressions for key summary statistics and simulate each model using a stochastic computational algorithm. We also discuss the effect of cell geometry on rotational diffusion. Working with a previously published tracking dataset, we compare predictions of the models with data on individual stopping events inR. sphaeroides. This provides strong evidence that this species undergoes some form of active reorientation rather than simple reorientation by Brownian rotation.