Bacterial bioluminescence onset and quenching: a dynamical model for a quorum sensing-mediated property.

We present an effective dynamical model for the onset of bacterial bioluminescence, one of the most studied quorum sensing-mediated traits. Our model is built upon simple equations that describe the growth of the bacterial colony, the production and accumulation of autoinducer signal molecules, their sensing within bacterial cells, and the ensuing quorum activation mechanism that triggers bioluminescent emission. The model is directly tested to quantitatively reproduce the experimental distributions of photon emission times, previously measured for bacterial colonies of Vibrio jasicida, a luminescent bacterium belonging to the Harveyi clade, growing in a highly drying environment. A distinctive and novel feature of the proposed model is bioluminescence 'quenching' after a given time elapsed from activation. Using an advanced fitting procedure based on the simulated annealing algorithm, we are able to infer from the experimental observations the biochemical parameters used in the model. Such parameters are in good agreement with the literature data. As a further result, we find that, at least in our experimental conditions, light emission in bioluminescent bacteria appears to originate from a subtle balance between colony growth and quorum activation due to autoinducers diffusion, with the two phenomena occurring on the same time scale. This finding is consistent with a negative feedback mechanism previously reported for Vibrio harveyi.

Suppression of Low-Frequency Electronic Noise in Polymer Nanowire Field-Effect Transistors.

The authors report on the reduction of low-frequency noise in semiconductor polymer nanowires with respect to thin-films made of the same organic material. Flicker noise is experimentally investigated in polymer nanowires in the range of 10-10(5) Hz by means of field-effect transistor architectures. The noise in the devices is well described by the Hooge empirical model and exhibits an average Hooge constant, which describes the current power spectral density of fluctuations, suppressed by 1-2 orders of magnitude compared to thin-film devices. To explain the Hooge constant reduction, a resistor network model is developed, in which the organic semiconducting nanostructures or films are depicted through a two-dimensional network of resistors with a square-lattice structure, accounting for the different anisotropy and degree of structural disorder of the active nanowires and films. Results from modeling agree well with experimental findings. These results support enhanced structural order through size-confinement in organic nanostructures as effective route to improve the noise performance in polymer electronic devices.

Early warning signals of desertification transitions in semiarid ecosystems.

The identification of early warning signals for regime shifts in ecosystems is of crucial importance given their impact in terms of economic and social effects. We present here the results of a theoretical study on the desertification transition in semiarid ecosystems under external stress. We performed numerical simulations based on a stochastic cellular automaton model, and we studied the dynamics of the vegetation clusters in terms of percolation theory, assumed as an effective tool for analyzing the geometrical properties of the clusters. Focusing on the role played by the strength of external stresses, measured by the mortality rate m, we followed the progressive degradation of the ecosystem for increasing m, identifying different stages: first, the fragmentation transition occurring at relatively low values of m, then the desertification transition at higher mortality rates, and finally the full desertification transition corresponding to the extinction of the vegetation and the almost complete degradation of the soil, attained at the maximum value of m. For each transition we calculated the spanning probabilities as functions of m and the percolation thresholds according to different spanning criteria. The identification of the different thresholds is proposed as an useful tool for monitoring the increasing degradation of real-world finite-size systems. Moreover, we studied the time fluctuations of the sizes of the biggest clusters of vegetated and nonvegetated cells over the entire range of mortality values. The change of sign in the skewness of the size distributions, occurring at the fragmentation threshold for the biggest vegetation cluster and at the desertification threshold for the nonvegetated cluster, offers new early warning signals for desertification. Other new and robust indicators are given by the maxima of the root-mean-square deviation of the distributions, which are attained respectively inside the fragmentation interval, for the vegetated biggest cluster, and inside the desertification interval, for the nonvegetated cluster.

Microscopic modeling of charge transport in sensing proteins.

: Sensing proteins (receptors) are nanostructures that exhibit very complex behaviors (ions pumping, conformational change, reaction catalysis, etc). They are constituted by a specific sequence of amino acids within a codified spatial organization. The functioning of these macromolecules is intrinsically connected with their spatial structure, which modifications are normally associated with their biological function. With the advance of nanotechnology, the investigation of the electrical properties of receptors has emerged as a demanding issue. Beside the fundamental interest, the possibility to exploit the electrical properties for the development of bioelectronic devices of new generations has attracted major interest. From the experimental side, we investigate three complementary kinds of measurements: (1) current-voltage (I-V) measurements in nanometric layers sandwiched between macroscopic contacts, (2) I-V measurements within an AFM environment in nanometric monolayers deposited on a conducting substrate, and (3) electrochemical impedance spectroscopy measurements on appropriate monolayers of self-assembled samples. From the theoretical side, a microscopic interpretation of these experiments is still a challenging issue. This paper reviews recent theoretical results carried out within the European project, Bioelectronic Olfactory Neuron Device, which provides a first quantitative interpretation of charge transport experiments exploiting static and dynamic electrical properties of several receptors. To this purpose, we have developed an impedance network protein analogue (INPA) which considers the interaction between neighboring amino acids within a given radius as responsible of charge transfer throughout the protein. The conformational change, due to the sensing action produced by the capture of the ligand (photon, odour), induces a modification of the spatial structure and, thus, of the electrical properties of the receptor. By a scaling procedure, the electrical change of the receptor when passing from the native to the active state is used to interpret the macroscopic measurement obtained within different methods. The developed INPA model is found to be very promising for a better understanding of the role of receptor topology in the mechanism responsible of charge transfer. Present results point favorably to the development of a new generation of nano-biosensors within the lab-on-chip strategy.

Distribution of first-return times in correlated stationary signals.

We present an analytical expression for the first return time (FRT) probability density function of a stationary correlated signal. Precisely, we start by considering a stationary discrete-time Ornstein-Uhlenbeck (OU) process with exponential decaying correlation function. The first return time distribution for this process is derived by adopting a well-known formalism typically used in the study of the FRT statistics for nonstationary diffusive processes. Then, by a subordination approach, we treat the case of a stationary process with power-law tail correlation function and diverging correlation time. We numerically test our findings, obtaining in both cases a good agreement with the analytical results. We notice that neither in the standard OU nor in the subordinated case a simple form of waiting time statistics, like stretched-exponential or similar, can be obtained while it is apparent that long time transient may shadow the final asymptotic behavior.

A network model to correlate conformational change and the impedance spectrum of single proteins.

Integrated nanodevices based on proteins or biomolecules are attracting increasing interest in today's research. In fact, it has been shown that proteins such as azurin and bacteriorhodopsin manifest some electrical properties that are promising for the development of active components of molecular electronic devices. Here we focus on two relevant kinds of protein: bovine rhodopsin, prototype of G-protein-coupled-receptor (GPCR) proteins, and the enzyme acetylcholinesterase (AChE), whose inhibition is one of the most qualified treatments of Alzheimer's disease. Both these proteins exert their function starting with a conformational change of their native structure. Our guess is that such a change should be accompanied with a detectable variation of their electrical properties. To investigate this conjecture, we present an impedance network model of proteins, able to estimate the different impedance spectra associated with the different configurations. The distinct types of conformational change of rhodopsin and AChE agree with their dissimilar electrical responses. In particular, for rhodopsin the model predicts variations of the impedance spectra up to about 30%, while for AChE the same variations are limited to about 10%, which supports the existence of a dynamical equilibrium between its native and complexed states.

A novel detection strategy for odorant molecules based on controlled bioengineering of rat olfactory receptor I7.

In this study, we report a dose-dependent detection of odorant molecules in solution by rat olfactory receptor I7 (OR I7) in its membrane fraction. The OR I7 is immobilized on a gold electrode by multilayer bioengineering based on a mixed self-assembled monolayer and biotin/avidin system, which allows for a well-controlled immobilization of the bioreceptor within its lipid environment. The odorant detection is electronically performed in a quantitative manner by electrochemical impedance spectroscopy (EIS) measurements on samples and controls.

Immobilization of rhodopsin on a self-assembled multilayer and its specific detection by electrochemical impedance spectroscopy.

Rhodopsin, the G protein-coupled receptor (GPCR) which mediates the sense of vision, was prepared from calf eyes and used as receptor enriched membrane fraction. In this study it was immobilized onto gold electrode by two different techniques: Langmuir-Blodgett (LB) and a strategy based on a self-assembled multilayer. We demonstrated that Langmuir and LB films of rhodopsin are not stable. Thus, in this study a new protein multilayer was prepared on gold electrode by building up layer-by-layer a self-assembled multilayer. It is composed of a mixed self-assembled monolayer formed by MHDA and biotinyl-PE, followed by a biotin-avidin system which allows binding of biotinylated antibody specific to rhodopsin. The immobilization of rhodopsin in membrane fraction, by the specific antibody bound previously on self-assembled multilayer, was monitored with electrochemical impedance spectroscopy (EIS). In addition, the specificity and sensitivity of this self-assembled multilayer system to the presence of rhodopsin were investigated. No effect was observed when the system was in contact with olfactory receptor I7 in membrane fraction used for control measurements. All these results demonstrate that rhodopsin can be immobilized efficiently, specifically, quantitatively and stably on gold electrode through the self-assembled multilayer.

Resistance and resistance fluctuations in random resistor networks under biased percolation.

We consider a two-dimensional random resistor network (RRN) in the presence of two competing biased processes consisting of the breaking and recovering of elementary resistors. These two processes are driven by the joint effects of an electrical bias and of the heat exchange with a thermal bath. The electrical bias is set up by applying a constant voltage or, alternatively, a constant current. Monte Carlo simulations are performed to analyze the network evolution in the full range of bias values. Depending on the bias strength, electrical failure or steady state are achieved. Here we investigate the steady state of the RRN focusing on the properties of the non-Ohmic regime. In constant-voltage conditions, a scaling relation is found between /(0) and V/V(0), where is the average network resistance, (0) the linear regime resistance, and V0 the threshold value for the onset of nonlinearity. A similar relation is found in constant-current conditions. The relative variance of resistance fluctuations also exhibits a strong nonlinearity whose properties are investigated. The power spectral density of resistance fluctuations presents a Lorentzian spectrum and the amplitude of fluctuations shows a significant non-Gaussian behavior in the prebreakdown region. These results compare well with electrical breakdown measurements in thin films of composites and of other conducting materials.