Eldad Kepten

Loss of lamin A function increases chromatin dynamics in the nuclear interior

Chromatin is organized in a highly ordered yet dynamic manner in the cell nucleus, but the principles governing this organization remain unclear. Similarly, it is unknown whether, and how, various proteins regulate chromatin motion and as a result influence nuclear organization. Here by studying the dynamics of different genomic regions in the nucleus of live cells, we show that the genome has highly constrained dynamics. Interestingly, depletion of lamin A strikingly alters genome dynamics, inducing a dramatic transition from slow anomalous diffusion to fast and normal diffusion. In contrast, depletion of LAP2α, a protein that interacts with lamin A and chromatin, has no such effect on genome dynamics. We speculate that chromosomal inter-chain interactions formed by lamin A throughout the nucleus contribute to chromatin dynamics, and suggest that the molecular regulation of chromatin diffusion by lamin A in the nuclear interior is critical for the maintenance of genome organization.

Universal Algorithm for Identification of Fractional Brownian Motion. A Case of Telomere Subdiffusion

We present a systematic statistical analysis of the recently measured individual trajectories of fluorescently labeled telomeres in the nucleus of living human cells. The experiments were performed in the U2OS cancer cell line. We propose an algorithm for identification of the telomere motion. By expanding the previously published data set, we are able to explore the dynamics in six time orders, a task not possible earlier. As a result, we establish a rigorous mathematical characterization of the stochastic process and identify the basic mathematical mechanisms behind the telomere motion. We find that the increments of the motion are stationary, Gaussian, ergodic, and even more chaotic--mixing. Moreover, the obtained memory parameter estimates, as well as the ensemble average mean square displacement reveal subdiffusive behavior at all time spans. All these findings statistically prove a fractional Brownian motion for the telomere trajectories, which is confirmed by a generalized p-variation test. Taking into account the biophysical nature of telomeres as monomers in the chromatin chain, we suggest polymer dynamics as a sufficient framework for their motion with no influence of other models. In addition, these results shed light on other studies of telomere motion and the alternative telomere lengthening mechanism. We hope that identification of these mechanisms will allow the development of a proper physical and biological model for telomere subdynamics. This array of tests can be easily implemented to other data sets to enable quick and accurate analysis of their statistical characteristics.

Improved estimation of anomalous diffusion exponents in single-particle tracking experiments

The mean square displacement is a central tool in the analysis of single-particle tracking experiments, shedding light on various biophysical phenomena. Frequently, parameters are extracted by performing time averages on single-particle trajectories followed by ensemble averaging. This procedure, however, suffers from two systematic errors when applied to particles that perform anomalous diffusion. The first is significant at short-time lags and is induced by measurement errors. The second arises from the natural heterogeneity in biophysical systems. We show how to estimate and correct these two errors and improve the estimation of the anomalous parameters for the whole particle distribution. As a consequence, we manage to characterize ensembles of heterogeneous particles even for rather short and noisy measurements where regular time-averaged mean square displacement analysis fails. We apply this method to both simulations and in vivo measurements of telomere diffusion in 3T3 mouse embryonic fibroblast cells. The motion of telomeres is found to be subdiffusive with an average exponent constant in time. Individual telomere exponents are normally distributed around the average exponent. The proposed methodology has the potential to improve experimental accuracy while maintaining lower experimental costs and complexity.

Guidelines for the Fitting of Anomalous Diffusion Mean Square Displacement Graphs from Single Particle Tracking Experiments

Single particle tracking is an essential tool in the study of complex systems and biophysics and it is commonly analyzed by the time-averaged mean square displacement (MSD) of the diffusive trajectories. However, past work has shown that MSDs are susceptible to significant errors and biases, preventing the comparison and assessment of experimental studies. Here, we attempt to extract practical guidelines for the estimation of anomalous time averaged MSDs through the simulation of multiple scenarios with fractional Brownian motion as a representative of a large class of fractional ergodic processes. We extract the precision and accuracy of the fitted MSD for various anomalous exponents and measurement errors with respect to measurement length and maximum time lags. Based on the calculated precision maps, we present guidelines to improve accuracy in single particle studies. Importantly, we find that in some experimental conditions, the time averaged MSD should not be used as an estimator.

Exploring chromatin organization mechanisms through its dynamic properties

Abstract The organization of the genome in the nucleus is believed to be crucial for different cellular functions. It is known that chromosomes fold into distinct territories, but little is known about the mechanisms that maintain these territories. To explore these mechanisms, we used various live-cell imaging methods, including single particle tracking to characterize the diffusion properties of different genomic regions in live cells. Chromatin diffusion is found to be slow and anomalous; in vast contrast, depletion of lamin A protein significantly increases chromatin motion, and the diffusion pattern of chromatin transforms from slow anomalous to fast normal. More than this, depletion of lamin A protein also affects the dynamics of nuclear bodies. Our findings indicate that chromatin motion is mediated by lamin A and we suggest that constrained chromatin mobility allows to maintain chromosome territories. Thus, the discovery of this function of nucleoplasmic lamin A proteins sheds light on the maintenance mechanism of chromosome territories in the interphase nucleus, which ensures the proper function of the genome.

Estimating the anomalous diffusion exponent for single particle tracking data with measurement errors - An alternative approach

Accurately characterizing the anomalous diffusion of a tracer particle has become a central issue in biophysics. However, measurement errors raise difficulty in the characterization of single trajectories, which is usually performed through the time-averaged mean square displacement (TAMSD). In this paper, we study a fractionally integrated moving average (FIMA) process as an appropriate model for anomalous diffusion data with measurement errors. We compare FIMA and traditional TAMSD estimators for the anomalous diffusion exponent. The ability of the FIMA framework to characterize dynamics in a wide range of anomalous exponents and noise levels through the simulation of a toy model (fractional Brownian motion disturbed by Gaussian white noise) is discussed. Comparison to the TAMSD technique, shows that FIMA estimation is superior in many scenarios. This is expected to enable new measurement regimes for single particle tracking (SPT) experiments even in the presence of high measurement errors.

Direct Transfer of Viral and Cellular Proteins from Varicella-Zoster Virus-Infected Non-Neuronal Cells to Human Axons

Varicella Zoster Virus (VZV), the alphaherpesvirus that causes varicella upon primary infection and Herpes zoster (shingles) following reactivation in latently infected neurons, is known to be fusogenic. It forms polynuclear syncytia in culture, in varicella skin lesions and in infected fetal human ganglia xenografted to mice. After axonal infection using VZV expressing green fluorescent protein (GFP) in compartmentalized microfluidic cultures there is diffuse filling of axons with GFP as well as punctate fluorescence corresponding to capsids. Use of viruses with fluorescent fusions to VZV proteins reveals that both proteins encoded by VZV genes and those of the infecting cell are transferred in bulk from infecting non-neuronal cells to axons. Similar transfer of protein to axons was observed following cell associated HSV1 infection. Fluorescence recovery after photobleaching (FRAP) experiments provide evidence that this transfer is by diffusion of proteins from the infecting cells into axons. Time-lapse movies and immunocytochemical experiments in co-cultures demonstrate that non-neuronal cells fuse with neuronal somata and proteins from both cell types are present in the syncytia formed. The fusogenic nature of VZV therefore may enable not only conventional entry of virions and capsids into axonal endings in the skin by classical entry mechanisms, but also by cytoplasmic fusion that permits viral protein transfer to neurons in bulk.

Uniform Contraction-Expansion Description of Relative Centromere and Telomere Motion

Internal organization and dynamics of the eukaryotic nucleus have been at the front of biophysical research in recent years. It is believed that both dynamics and location of chromatin segments are crucial for genetic regulation. Here we study the relative motion between centromeres and telomeres at various distances and at times relevant for genetic activity. Using live-imaging fluorescent microscopy coupled to stochastic analysis of relative trajectories, we find that the interlocus motion is distance-dependent with a varying fractional memory. In addition to short-range constraining, we also observe long-range anisotropic-enhanced parallel diffusion, which contradicts the expectation for classic viscoelastic systems. This motion is linked to uniform expansion and contraction of chromatin in the nucleus, and leads us to define and measure a new (to our knowledge) uniform contraction-expansion diffusion coefficient that enriches the contemporary picture of nuclear behavior. Finally, differences between loci types suggest that different sites along the genome experience distinctive coupling to the nucleoplasm environment at all scales.

Single-particle tracking for studying the dynamic properties of genomic regions in live cells.

The appropriate functioning of living cells depends on a variety of dynamic processes that necessitate delicate motion, transportation, association, and disassociation in time and space. Different dynamic patterns such as directed motion, normal diffusion, and restricted diffusion take part at different length scales, and their identification serves as a tool for exploring biochemical processes. Here we describe single-particle tracking which is a powerful method that allows the characterization of dynamic processes on the single-molecule or single-particle level with nanometer spatial and sub-second temporal precision. In particular, we describe the cell preparation procedures, microscopy imaging, and image analysis processes for following telomere dynamics in living mammalian cells.

Single-site transcription rates through fitting of ensemble-averaged data from fluorescence recovery after photobleaching: A fat-tailed distribution

The stochastic process of gene expression is commonly controlled at the level of RNA transcription. The synthesis of messenger RNA (mRNA) is a multistep process, performed by RNA polymerase II and controlled by many transcription factors. Although mRNA transcription is intensively studied, real-time in vivo dynamic rates of a single transcribing polymerase are still not available. A popular method for examining transcription kinetics is the fluorescence recovery after photobleaching (FRAP) approach followed by kinetic modeling. Such analysis has yielded a surprisingly broad range of transcription rates. As transcription depends on many variables such as the chromatin state, binding and unbinding of transcription factors, and cell phase, transcription rates are stochastic variables. Thus, the distribution of rates is expected to follow Poissonian statistics, which does not coincide with the wide range of transcription rate results. Here we present an approach for analyzing FRAP data for single-gene transcription. We find that the transcription dynamics of a single gene can be described with a constant rate for all transcribing polymerases, while cell population transcription rates follow a fat-tailed distribution. This distribution suggests a larger probability for extreme rates than would be implied by normal distribution. Our analysis supports experimental results of transcription from two different promoters, and it explains the puzzling observation of extreme average rate values of transcription.