Attractant and Repellent Signaling Conformers of Sensory Rhodopsin−Transducer Complexes†

ABSTRACT: Attractant and repellent signaling conformers of the dual-signaling phototaxis receptor sensory rhodopsin I and its transducer subunit (SRI-HtrI) have recently been distinguished experimentally by the opposite connection of their retinylidene protonated Schiff bases to the outwardly located periplasmic side and inwardly located cytoplasmic side. Here we show that the pKa of the outwardly located Asp76 counterion in the outwardly connected conformer is lowered by ∼1.5 units from that of the inwardly connected conformer. The pK a difference enables quantitative determination of the relative amounts of the two conformers in wild-type cells and behavioral mutants prior to photoexcitation, comparison of their absorption spectra, and determination of their relative signaling efficiency. We have shown that the onephoton excitation of the SRI-HtrI attractant conformer causes a Schiff base connectivity switch from inwardly connected to outwardly connected states in the attractant signaling photoreaction. Conversely, a second near-UV photon drives the complex back to the inwardly connected conformer in the repellent signaling photoreaction. The results suggest a model of the color-discriminating dual-signaling mechanism in which phototaxis responses (his-kinase modulation) result from the photointerconversion of the two oppositely connected SRI-HtrI conformers by one-photon and two-photon activation. Furthermore, we find that the related repellent phototaxis SRII-HtrII receptor complex has an outwardly connecte

Polymer Induced Bundling of F-actin and the Depletion Force

The inert polymer polyethylene glycol (PEG) induces a "bundling" phenomenon in F-actin solutions when its concentration exceeds a critical onset value C_o. Over a limited range of PEG molecular weight and ionic strength, C_o can be expressed as a function of these two variables. The process is reversible, but hysteresis is also observed in the dissolution of the bundles, with ionic strength having a large influence. Additional actin filaments are able to join previously formed bundles. Little, if any, polymer is associated with the bundle structure. Continuum estimates of the Asakura-Oosawa depletion force, Coulomb repulsion, and van der Waals potential are combined for a partial explanation of the bundling effect and hysteresis. Conjectures are presented concerning the apparent limit in bundle size

Frozen steady states in active systems

Even simple active systems can show a plethora of intriguing phenomena and often we find complexity were we would have expected simplicity. One striking example is the occurrence of a quiescent or absorbing state with frozen fluctuations that at first sight seems to be impossible for active matter driven by the incessant input of energy. While such states were reported for externally driven systems through macroscopic shear or agitation, the investigation of frozen active states in inherently active systems like cytoskeletal suspensions or active gels is still at large. Using high density motility assay experiments, we demonstrate that frozen steady states can arise in active systems if active transport is coupled to growth processes. The experiments are complemented by agent-based simulations which identify the coupling between self-organization, growth and mechanical properties to be responsible for the pattern formation process

Deterministic and stochastic descriptions of gene expression dynamics

A key goal of systems biology is the predictive mathematical description of gene regulatory circuits. Different approaches are used such as deterministic and stochastic models, models that describe cell growth and division explicitly or implicitly etc. Here we consider simple systems of unregulated (constitutive) gene expression and compare different mathematical descriptions systematically to obtain insight into the errors that are introduced by various common approximations such as describing cell growth and division by an effective protein degradation term. In particular, we show that the population average of protein content of a cell exhibits a subtle dependence on the dynamics of growth and division, the specific model for volume growth and the age structure of the population. Nevertheless, the error made by models with implicit cell growth and division is quite small. Furthermore, we compare various models that are partially stochastic to investigate the impact of different sources of (intrinsic) noise. This comparison indicates that different sources of noise (protein synthesis, partitioning in cell division) contribute comparable amounts of noise if protein synthesis is not or only weakly bursty. If protein synthesis is very bursty, the burstiness is the dominant noise source, independent of other details of the model. Finally, we discuss two sources of extrinsic noise: cell-to-cell variations in protein content due to cells being at different stages in the division cycles, which we show to be small (for the protein concentration and, surprisingly, also for the protein copy number per cell) and fluctuations in the growth rate, which can have a significant impact.Comment: 23 pages, 5 figures; Journal of Statistical physics (2012

Evolution of Robustness to Noise and Mutation in Gene Expression Dynamics

Phenotype of biological systems needs to be robust against mutation in order to sustain themselves between generations. On the other hand, phenotype of an individual also needs to be robust against fluctuations of both internal and external origins that are encountered during growth and development. Is there a relationship between these two types of robustness, one during a single generation and the other during evolution? Could stochasticity in gene expression have any relevance to the evolution of these robustness? Robustness can be defined by the sharpness of the distribution of phenotype; the variance of phenotype distribution due to genetic variation gives a measure of `genetic robustness' while that of isogenic individuals gives a measure of `developmental robustness'. Through simulations of a simple stochastic gene expression network that undergoes mutation and selection, we show that in order for the network to acquire both types of robustness, the phenotypic variance induced by mutations must be smaller than that observed in an isogenic population. As the latter originates from noise in gene expression, this signifies that the genetic robustness evolves only when the noise strength in gene expression is larger than some threshold. In such a case, the two variances decrease throughout the evolutionary time course, indicating increase in robustness. The results reveal how noise that cells encounter during growth and development shapes networks' robustness to stochasticity in gene expression, which in turn shapes networks' robustness to mutation. The condition for evolution of robustness as well as relationship between genetic and developmental robustness is derived through the variance of phenotypic fluctuations, which are measurable experimentally.Comment: 25 page

Statistical modeling of ground motion relations for seismic hazard analysis

We introduce a new approach for ground motion relations (GMR) in the probabilistic seismic hazard analysis (PSHA), being influenced by the extreme value theory of mathematical statistics. Therein, we understand a GMR as a random function. We derive mathematically the principle of area-equivalence; wherein two alternative GMRs have an equivalent influence on the hazard if these GMRs have equivalent area functions. This includes local biases. An interpretation of the difference between these GMRs (an actual and a modeled one) as a random component leads to a general overestimation of residual variance and hazard. Beside this, we discuss important aspects of classical approaches and discover discrepancies with the state of the art of stochastics and statistics (model selection and significance, test of distribution assumptions, extreme value statistics). We criticize especially the assumption of logarithmic normally distributed residuals of maxima like the peak ground acceleration (PGA). The natural distribution of its individual random component (equivalent to exp(epsilon_0) of Joyner and Boore 1993) is the generalized extreme value. We show by numerical researches that the actual distribution can be hidden and a wrong distribution assumption can influence the PSHA negatively as the negligence of area equivalence does. Finally, we suggest an estimation concept for GMRs of PSHA with a regression-free variance estimation of the individual random component. We demonstrate the advantages of event-specific GMRs by analyzing data sets from the PEER strong motion database and estimate event-specific GMRs. Therein, the majority of the best models base on an anisotropic point source approach. The residual variance of logarithmized PGA is significantly smaller than in previous models. We validate the estimations for the event with the largest sample by empirical area functions. etc

A Minimal Model of Metabolism Based Chemotaxis

Since the pioneering work by Julius Adler in the 1960's, bacterial chemotaxis has been predominantly studied as metabolism-independent. All available simulation models of bacterial chemotaxis endorse this assumption. Recent studies have shown, however, that many metabolism-dependent chemotactic patterns occur in bacteria. We hereby present the simplest artificial protocell model capable of performing metabolism-based chemotaxis. The model serves as a proof of concept to show how even the simplest metabolism can sustain chemotactic patterns of varying sophistication. It also reproduces a set of phenomena that have recently attracted attention on bacterial chemotaxis and provides insights about alternative mechanisms that could instantiate them. We conclude that relaxing the metabolism-independent assumption provides important theoretical advances, forces us to rethink some established pre-conceptions and may help us better understand unexplored and poorly understood aspects of bacterial chemotaxis

Direct Observation of the Myosin Va Recovery Stroke That Contributes to Unidirectional Stepping along Actin

Myosins are ATP-driven linear molecular motors that work as cellular force generators, transporters, and force sensors. These functions are driven by large-scale nucleotide-dependent conformational changes, termed “strokes”; the “power stroke” is the force-generating swinging of the myosin light chain–binding “neck” domain relative to the motor domain “head” while bound to actin; the “recovery stroke” is the necessary initial motion that primes, or “cocks,” myosin while detached from actin. Myosin Va is a processive dimer that steps unidirectionally along actin following a “hand over hand” mechanism in which the trailing head detaches and steps forward ∼72 nm. Despite large rotational Brownian motion of the detached head about a free joint adjoining the two necks, unidirectional stepping is achieved, in part by the power stroke of the attached head that moves the joint forward. However, the power stroke alone cannot fully account for preferential forward site binding since the orientation and angle stability of the detached head, which is determined by the properties of the recovery stroke, dictate actin binding site accessibility. Here, we directly observe the recovery stroke dynamics and fluctuations of myosin Va using a novel, transient caged ATP-controlling system that maintains constant ATP levels through stepwise UV-pulse sequences of varying intensity. We immobilized the neck of monomeric myosin Va on a surface and observed real time motions of bead(s) attached site-specifically to the head. ATP induces a transient swing of the neck to the post-recovery stroke conformation, where it remains for ∼40 s, until ATP hydrolysis products are released. Angle distributions indicate that the post-recovery stroke conformation is stabilized by ≥5 kBT of energy. The high kinetic and energetic stability of the post-recovery stroke conformation favors preferential binding of the detached head to a forward site 72 nm away. Thus, the recovery stroke contributes to unidirectional stepping of myosin Va

Amyloid and tau cerebrospinal fluid biomarkers in HIV infection

<p>Abstract</p> <p>Background</p> <p>Because of the emerging intersections of HIV infection and Alzheimer's disease, we examined cerebrospinal fluid (CSF) biomarkers related of amyloid and tau metabolism in HIV-infected patients.</p> <p>Methods</p> <p>In this cross-sectional study we measured soluble amyloid precursor proteins alpha and beta (sAPPα and sAPPβ), amyloid beta fragment 1-42 (Aβ_1-42), and total and hyperphosphorylated tau (t-tau and p-tau) in CSF of 86 HIV-infected (HIV+) subjects, including 21 with AIDS dementia complex (ADC), 25 with central nervous system (CNS) opportunistic infections and 40 without neurological symptoms and signs. We also measured these CSF biomarkers in 64 uninfected (HIV-) subjects, including 21 with Alzheimer's disease, and both younger and older controls without neurological disease.</p> <p>Results</p> <p>CSF sAPPα and sAPPβ concentrations were highly correlated and reduced in patients with ADC and opportunistic infections compared to the other groups. The opportunistic infection group but not the ADC patients had lower CSF Aβ_1-42in comparison to the other HIV+ subjects. CSF t-tau levels were high in some ADC patients, but did not differ significantly from the HIV+ neuroasymptomatic group, while CSF p-tau was not increased in any of the HIV+ groups. Together, CSF amyloid and tau markers segregated the ADC patients from both HIV+ and HIV- neuroasymptomatics and from Alzheimer's disease patients, but not from those with opportunistic infections.</p> <p>Conclusions</p> <p>Parallel reductions of CSF sAPPα and sAPPβ in ADC and CNS opportunistic infections suggest an effect of CNS immune activation or inflammation on neuronal amyloid synthesis or processing. Elevation of CSF t-tau in some ADC and CNS infection patients without concomitant increase in p-tau indicates neural injury without preferential accumulation of hyperphosphorylated tau as found in Alzheimer's disease. These biomarker changes define pathogenetic pathways to brain injury in ADC that differ from those of Alzheimer's disease.</p