Combining extensive single particle tracking microscopy data of endogenous lipid granules in living fission yeast cells with analytical results we show evidence for anomalous diffusion and weak ergodicity breaking. Namely we demonstrate that at short times the granules perform subdiffusion according to the laws of continuous time random walk theory. The associated violation of ergodicity leads to a characteristic turnover between two scaling regimes of the time averaged mean squared displacement. At longer times the granule motion is consistent with fractional Brownian motion. of larger molecules or tracers in living cells [3,[6][7][8][9][10][11][12][13][14][15][16]. While normal diffusion, by virtue of the central limit theorem, is characterized by the universal Gaussian probability density function and therefore uniquely determined by the first and second moments [17], anomalous diffusion of the form (1) is non-universal and may be caused by different stochastic mechanisms. These would give rise to vastly different behavior for diffusional mixing, diffusionlimited reactions, signaling, or regulatory processes. To better understand cellular dynamics, knowledge of the underlying stochastic mechanism is thus imperative.Here we report experimental evidence from extensive single trajectory time series of lipid granule motion in Schizosaccharomyces pombe (S. pombe) fission yeast cells obtained from tracking with optical tweezers (resolving 10 −6 sec to 1 sec) and video microscopy (10 −2 sec to 100 sec). Using complementary analysis tools we demonstrate that at short times the data are described best by continuous time random walk (CTRW) subdiffusion, revealing pronounced features of weak ergodicity breaking in the time averaged mean squared displacement. At longer times the stochastic mechanism is closest to subdiffusive fractional Brownian motion (FBM). The time scales over which this anomalous behavior persists is relevant for biological processes occurring in the cell. Anomalous diffusion may indeed be a good strategy for cellular signaling and reactions [7,8].CTRW and FBM both effect anomalous diffusion of the type (1) [18]. Subdiffusive CTRWs are random walks with finite variance δx 2 of jump lengths, while the waiting times between successive jumps are drawn from a density ψ(t) ≃ τ α /t 1+α with diverging characteristic time [4,17]. Such scale-free behavior results from multiple trapping events in, e.g., comb-like structures [19] or random energy landscapes [20]. Power-law waiting time distributions were also identified for tracer motion in reconstituted actin networks [21]. Subdiffusive FBM is a random process driven by Gaussian noise ξ with longrange correlations, ξ(0)ξ(t) ≃ α(α − 1)t α−2 [22], and it is related to fractional Langevin equations [23]. The finite characteristic time scales associated with FBM contrast the ageing property of the subdiffusive CTRW processes [Supplementary Material (SM)].Single particle tracking microscopy has become a standard tool to probe the motion of individual tracers, espe...

The viscoelastic properties of the cytoplasm of living yeast cells were investigated by studying the motion of lipid granules naturally occurring in the cytoplasm. A large frequency range of observation was obtained by a combination of video-based and laser-based tracking methods. At time scales from 10(-4) to 10(2) s, the granules typically perform subdiffusive motion with characteristics different from previous measurements in living cells. This subdiffusive behavior is thought to be due to the presence of polymer networks and membranous structures in the cytoplasm. Consistent with this hypothesis, we observe that the motion becomes less subdiffusive upon actin disruption.

We demonstrate stable three-dimensional (3D) single-beam optical trapping of gold nanoparticles with diameters between 18 and 254 nm. Three-dimensional power spectral analysis reveals that, for nanoparticles with diameters less than 100 nm, the trap stiffness is proportional to the volume of the particle. For larger particles, the trap stiffness still increases with size, however, less steeply. Finally, we provide numbers for the largest forces exertable on gold nanoparticles.

The absorption of light by plasmonic nanostructures and their associated temperature increase are exquisitely sensitive to the shape and composition of the structure and to the wavelength of light. Therefore, much effort is put into synthesizing novel nanostructures for optimized interaction with the incident light. The successful synthesis and characterization of high quality and biocompatible plasmonic colloidal nanoparticles has fostered numerous and expanding applications, especially in biomedical contexts, where such particles are highly promising for general drug delivery and for tomorrow’s cancer treatment. We review the thermoplasmonic properties of the most commonly used plasmonic nanoparticles, including solid or composite metallic nanoparticles of various dimensions and geometries. Common methods for synthesizing plasmonic particles are presented with the overall goal of providing the reader with a guide for designing or choosing nanostructures with optimal thermoplasmonic properties for a given application. Finally, the biocompatibility and biological tolerance of structures are critically discussed along with novel applications of plasmonic nanoparticles in the life sciences.

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We report the results of single tracer particle tracking by optical tweezers and video microscopy in micellar solutions. From careful analysis in terms of different stochastic models, we show that the polystyrene tracer beads of size 0.52-2.5 µm after short-time normal diffusion turn over to perform anomalous diffusion of the form r 2 (t) t α with α ≈ 0.3. This free anomalous diffusion is ergodic and consistent with a description in terms of the generalized Langevin equation with a power-law memory kernel. With optical tweezers tracking, we unveil a power-law relaxation over several decades in time to the thermal plateau value under the confinement of the harmonic tweezer potential, as predicted previously (Phys. Rev. E 85 021147 (2012)). After the subdiffusive motion in the millisecond range, the motion becomes faster and turns either back to normal Brownian diffusion or to even faster superdiffusion, depending on the size of the tracer beads.

Absorption of electromagnetic irradiation results in significant heating of metallic nanoparticles, an effect which can be advantageously used in biomedical contexts. Also, metallic nanoparticles are presently finding widespread use as handles, contacts, or markers in nanometer scale systems, and for these purposes it is essential that the temperature increase associated with electromagnetic irradiation is not harmful to the environment. Regardless of whether the heating of metallic nanoparticles is desired or not, it is crucial for nanobio assays to know the exact temperature increase associated with electromagnetic irradiation of metallic nanoparticles. We performed direct measurements of the temperature surrounding single gold nanoparticles optically trapped on a lipid bilayer, a biologically relevant matrix. The lipid bilayer had incorporated fluorescent molecules which have a preference for either fluid or gel phases. The heating associated with electromagnetic radiation was measured by visualizing the melted footprint around the irradiated particle. The effect was measured for individual gold nanoparticles of a variety of sizes and for a variety of laser powers. The temperatures were highly dependent on particle size and laser power, with surface temperature increments ranging from a few to hundreds of degrees Celsius. Our results show that by a careful choice of gold nanoparticle size and strength of irradiating electromagnetic field, one can control the exact particle temperature. The method is easily applicable to any type of nanoparticle for which the photothermal effect is sought to be quantified.

An increasing number of experimental studies employ single particle tracking to probe the physical environment in complex systems. We here propose and discuss what we believe are new methods to analyze the time series of the particle traces, in particular, for subdiffusion phenomena. We discuss the statistical properties of mean maximal excursions (MMEs), i.e., the maximal distance covered by a test particle up to time t. Compared to traditional methods focusing on the mean-squared displacement we show that the MME analysis performs better in the determination of the anomalous diffusion exponent. We also demonstrate that combination of regular moments with moments of the MME method provides additional criteria to determine the exact physical nature of the underlying stochastic subdiffusion processes. We put the methods to test using experimental data as well as simulated time series from different models for normal and anomalous dynamics such as diffusion on fractals, continuous time random walks, and fractional Brownian motion.