A cycling state that can lead to glassy dynamics in intracellular transport

Power-law dwell times have been observed for molecular motors in living cells, but the origins of these trapped states are not known. We introduce a minimal model of motors moving on a two-dimensional network of filaments, and simulations of its dynamics exhibit statistics comparable to those observed experimentally. Analysis of the model trajectories, as well as experimental particle tracking data, reveals a state in which motors cycle unproductively at junctions of three or more filaments. We formulate a master equation for these junction dynamics and show that the time required to escape from this vortex-like state can account for the power-law dwell times. We identify trends in the dynamics with the motor valency for further experimental validation. We demonstrate that these trends exist in individual trajectories of myosin II on an actin network. We discuss how cells could regulate intracellular transport and, in turn, biological function, by controlling their cytoskeletal network structures locally

Entropy Production Rate is Maximized in Non-Contractile Actomyosin

The actin cytoskeleton is an active semi-flexible polymer network whose non-equilibrium properties coordinate both stable and contractile behaviors to maintain or change cell shape. While myosin motors drive the actin cytoskeleton out-of-equilibrium, the role of myosin-driven active stresses in the accumulation and dissipation of mechanical energy is unclear. To investigate this, we synthesize an actomyosin material in vitro whose active stress content can tune the network from stable to contractile. Each increment in activity determines a characteristic spectrum of actin filament fluctuations which is used to calculate the total mechanical work and the production of entropy in the material. We find that the balance of work and entropy does not increase monotonically and, surprisingly, the entropy production rate is maximized in the non-contractile, stable state. Our study provides evidence that the origins of system entropy production and activity-dependent dissipation arise from disorder in the molecular interactions between actin and myosinComment: 31 pages, 5 figure

Dynamics and Selective Remodeling of the DNA-binding Domains of RPA

Replication protein A (RPA) coordinates important DNA metabolic events by stabilizing single-stranded DNA (ssDNA) intermediates, activating the DNA-damage response and handing off ssDNA to the appropriate downstream players. Six DNA-binding domains (DBDs) in RPA promote high-affinity binding to ssDNA yet also allow RPA displacement by lower affinity proteins. We generated fluorescent versions of Saccharomyces cerevisiae RPA and visualized the conformational dynamics of individual DBDs in the context of the full-length protein. We show that both DBD-A and DBD-D rapidly bind to and dissociate from ssDNA while RPA remains bound to ssDNA. The recombination mediator protein Rad52 selectively modulates the dynamics of DBD-D. These findings reveal how RPA-interacting proteins with lower ssDNA binding affinities can access the occluded ssDNA and remodel individual DBDs to replace RPA

Nurses' perceptions of aids and obstacles to the provision of optimal end of life care in ICU

Contains fulltext : 172380.pdf (publisher's version ) (Open Access

Estimating the Cholesterol Affinity of Integral Membrane Proteins from Experimental Data

The cholesterol affinities of many integral plasma membrane proteins have been estimated by molecular computation. However, these values lack experimental confirmation. We therefore developed a simple mathematical model to extract sterol affinity constants and stoichiometries from published isotherms for the dependence of the activity of such proteins on the membrane cholesterol concentration. The binding curves for these proteins are sigmoidal, with strongly lagged thresholds attributable to competition for the cholesterol by bilayer phospholipids. The model provided isotherms that matched the experimental data using published values for the sterol association constants and stoichiometries of the phospholipids. Three oligomeric transporters were found to bind cholesterol without cooperativity, with dimensionless association constants of 35 for Kir3.4* and 100 for both Kir2 and a GAT transporter. (The corresponding ΔG° values were −8.8, −11.4, and −11.4 kJ/mol, respectively). These association constants are significantly lower than those for the phospholipids, which range from ∼100 to 6000. The BK channel, the nicotinic acetylcholine receptor, and the M192I mutant of Kir3.4* appear to bind multiple cholesterol molecules cooperatively (n = 2 or 4), with subunit affinities of 563, 950, and 700, respectively. The model predicts that the three less avid transporters are approximately half-saturated in their native plasma membranes; hence, they are sensitive to variations in cholesterol in vivo. The more avid proteins would be nearly saturated in vivo. The method can be applied to any integral protein or other ligands in any bilayer for which there are reasonable estimates of the sterol affinities and stoichiometries of the phospholipids

Improved Statistical Methods Enable Greater Sensitivity in Rhythm Detection for Genome-Wide Data

Robust methods for identifying patterns of expression in genome-wide data are important for generating hypotheses regarding gene function. To this end, several analytic methods have been developed for detecting periodic patterns. We improve one such method, JTK_CYCLE, by explicitly calculating the null distribution such that it accounts for multiple hypothesis testing and by including non-sinusoidal reference waveforms. We term this method empirical JTK_CYCLE with asymmetry search, and we compare its performance to JTK_CYCLE with Bonferroni and Benjamini-Hochberg multiple hypothesis testing correction, as well as to five other methods: cyclohedron test, address reduction, stable persistence, ANOVA, and F24. We find that ANOVA, F24, and JTK_CYCLE consistently outperform the other three methods when data are limited and noisy; empirical JTK_CYCLE with asymmetry search gives the greatest sensitivity while controlling for the false discovery rate. Our analysis also provides insight into experimental design and we find that, for a fixed number of samples, better sensitivity and specificity are achieved with higher numbers of replicates than with higher sampling density. Application of the methods to detecting circadian rhythms in a metadataset of microarrays that quantify time-dependent gene expression in whole heads of Drosophila melanogaster reveals annotations that are enriched among genes with highly asymmetric waveforms. These include a wide range of oxidation reduction and metabolic genes, as well as genes with transcripts that have multiple splice forms.</p

Improved Statistical Methods Enable Greater Sensitivity in Rhythm Detection for Genome-Wide Data

<div><p>Robust methods for identifying patterns of expression in genome-wide data are important for generating hypotheses regarding gene function. To this end, several analytic methods have been developed for detecting periodic patterns. We improve one such method, JTK_CYCLE, by explicitly calculating the null distribution such that it accounts for multiple hypothesis testing and by including non-sinusoidal reference waveforms. We term this method empirical JTK_CYCLE with asymmetry search, and we compare its performance to JTK_CYCLE with Bonferroni and Benjamini-Hochberg multiple hypothesis testing correction, as well as to five other methods: cyclohedron test, address reduction, stable persistence, ANOVA, and F24. We find that ANOVA, F24, and JTK_CYCLE consistently outperform the other three methods when data are limited and noisy; empirical JTK_CYCLE with asymmetry search gives the greatest sensitivity while controlling for the false discovery rate. Our analysis also provides insight into experimental design and we find that, for a fixed number of samples, better sensitivity and specificity are achieved with higher numbers of replicates than with higher sampling density. Application of the methods to detecting circadian rhythms in a metadataset of microarrays that quantify time-dependent gene expression in whole heads of Drosophila melanogaster reveals annotations that are enriched among genes with highly asymmetric waveforms. These include a wide range of oxidation reduction and metabolic genes, as well as genes with transcripts that have multiple splice forms.</p></div

Annotation terms identified by DAVID as enriched for rhythmic genes.

<p>Rhythmic genes shown are those that are identified with eJTK_aby4 with a Benjamini-Hochberg adjusted <i>p</i>-value less than 0.05. The terms shown are those identified by the DAVID web tool [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004094#pcbi.1004094.ref051" target="_blank">51</a>, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004094#pcbi.1004094.ref052" target="_blank">52</a>] as enriched with a Benjamini-Hochberg adjusted <i>p</i>-value less than 0.05. (A) The individual annotation terms are shown with their adjusted <i>p</i>-values and phase distributions. The red numbers refer to the number of genes in that annotation term with that phase. The horizontal axis of A is the same as that of B. (B) Total phase distribution of the cycling genes. (C) Total asymmetry distribution of the cycling genes.</p

JTK_CYCLE compares all possible pair relations for a time series to those for a reference waveform.

<p>(A) JTK_CYCLE tests for pairwise agreement between a reference (blue) and a signal (cyan) time series. Three discordant pairwise relationships are indicated by red lines. (B) The previous implementation compared a time series to a set of phase-shifted cosines. (C) We add a set of asymmetric waveforms to the reference. An example is shown here with the same phases as in A.</p