Yeast cells approach a mating partner by polarizing along a gradient of mating pheromones that are secreted by cells of the opposite mating type. The Bar1 protease is secreted by a-cells and, paradoxically, degrades the α-factor pheromones which are produced by cells of the opposite mating type and trigger mating in a-cells. This degradation may assist in the recovery from pheromone signaling but has also been shown to play a positive role in mating. Previous studies suggested that widely diffusing protease can bias the pheromone gradient towards the closest secreting cell. Here, we show that restricting the Bar1 protease to the secreting cell itself, preventing its wide diffusion, facilitates discrimination between equivalent mating partners. This may be mostly relevant during spore germination, where most mating events occur in nature.

To find out the evolutionary relationships among different tRNA sequences of 21 amino acids, 22 networks are constructed. One is constructed from whole tRNAs, and the other 21 networks are constructed from the tRNAs which carry the same amino acids. A new method is proposed such that the alignment scores of any two amino acids groups are determined by the average degree and the average clustering coefficient of their networks. The anticodon feature of isolated tRNA and the phylogenetic trees of 21 group networks are discussed. We find that some isolated tRNA sequences in 21 networks still connect with other tRNAs outside their group, which reflects the fact that those tRNAs might evolve by intercrossing among these 21 groups. We also find that most anticodons among the same cluster are only one base different in the same sites when S ≥ 70, and they stay in the same rank in the ladder of evolutionary relationships. Those observations seem to agree on that some tRNAs might mutate from the same ancestor sequences based on point mutation mechanisms.

Here we consider a reaction diffusion system of three plankton populations, a zooplankton feeding on two phytoplankton populations, in two different settings. Firstly, the two phytoplanktons are both non-toxic and both enhance the growth of the grazing zooplankton. Secondly, we assume that one of the phytoplankton releases toxin and thereby inhibits the growth of the zooplankton. Our analytic and numerical study shows that the spatiotemporal distribution of the plankton species is uniform when both phytoplankton populations are non-toxic. However, in the presence of toxin-producing phytoplankton, the biomass distribution of all the plankton populations becomes inhomogeneous.

During bacterial chemotaxis, a cell acquires information about its environment by sampling changes in the local concentration of a chemoattractant, and then uses that information to bias its motion relative to the source of the chemoattractant. The trajectory of a chemotaxing bacteria is thus a spatial manifestation of the information gathered by the cell. Here we show that a recently developed approach for computing spatial information using Fourier coefficient probabilities, the k-space information (kSI), can be used to quantify the information in such trajectories. The kSI is shown to capture expected responses to gradients of a chemoattractant. We then extend the k-space approach by developing an experimental probability distribution (EPD) that is computed from chemotactic trajectories collected under a reference condition. The EPD accounts for connectivity and other constraints that the nature of the trajectories imposes on the k-space computation. The EPD is used to compute the spatial information from any trajectory of interest, relative to the reference condition. The EPD-based spatial information also captures the expected responses to gradients of a chemoattractant, although the results differ in significant ways from the original kSI computation. In addition, the entropy calculated from the EPD provides a useful measure of trajectory space. The methods developed are highly general, and can be applied to a wide range of other trajectory types as well as non-trajectory data.

In biological systems, regulation plays an important role in keeping metabolite concentrations within physiological ranges. To study the dynamical implications of self-regulation, we consider a functional form used in genetic networks and couple it to a mechanism associated with chemical self-replication. For the two-variable minimal model, we find that activation can yield chemical toggles similar to those reported for gene repression in E. coli as well as more complex dynamics.

The ATP synthase consists of two opposing rotary motors, F0 and F1, coupled to each other. When the F1 motor is not coupled to the F0 motor, it can work in the direction hydrolyzing ATP, as a nanomotor called F1-ATPase. It has been reported that the stiffness of the protein varies nonlinearly with increasing load. The nonlinearity has an important effect on the rotating rate of the F1-ATPase. Here, considering the nonlinearity of the γ shaft stiffness for the F1-ATPase, a nonlinear chemo-mechanical coupled dynamic model of F1 motor is proposed. Nonlinear vibration frequencies of the γ shaft and their changes along with the system parameters are investigated. The nonlinear stochastic response of the elastic γ shaft to thermal excitation is analyzed. The results show that the stiffness nonlinearity of the γ shaft causes an increase of the vibration frequency for the F1 motor, which increases the motor’s rotation rate. When the concentration of ATP is relatively high and the load torque is small, the effects of the stiffness nonlinearity on the rotating rates of the F1 motor are obvious and should be considered. These results are useful for improving calculation of the rotating rate for the F1 motor and provide insight about the stochastic wave mechanics of F1-ATPase.

Osteoporosis is a systemic skeletal disorder associated with reduced bone mineral density and the consequent high risk of bone fractures. Current practice relates osteoporosis largely with absolute mass loss. The assessment of variations in chemical composition in terms of the main elements comprising the bone mineral and its effect on the bone’s quality is usually neglected. In this study, we evaluate the ratio of the main elements of bone mineral, calcium (Ca), and phosphorus (P), as a suitable in vitro biomarker for induced osteoporosis. The Ca/P concentration ratio was measured at different sites of normal and osteoporotic rabbit bones using two spectroscopic techniques: Auger electron spectroscopy (AES) and energy-dispersive X-ray spectroscopy (EDX). Results showed that there is no significant difference between samples from different genders or among cortical bone sites. On the contrary, we found that the Ca/P ratio of trabecular bone sections is comparable to cortical sections with induced osteoporosis. Ca/P ratio values are positively related to induced bone loss; furthermore, a different degree of correlation between Ca and P in cortical and trabecular bone is evident. This study also discusses the applicability of AES and EDX to the semiquantitative measurements of bone mineral’s main elements along with the critical experimental parameters.

Transcription factors (TFs) bind to specific DNA sequences to induce or repress gene expression. Expression levels can be tuned by changing TF concentrations, but the precision of such tuning is limited, since the fraction of time a TF occupies its binding site is subject to stochastic fluctuations. Bicoid (Bcd) is a TF that patterns the early Drosophila embryo by establishing an anterior-to-posterior concentration gradient and activating specific gene targets (“gap genes”) in a concentration-dependent manner. Recently, the Bcd gradient and its in-vivo diffusion were quantified in live embryos, raising a quandary: the precision by which the Bcd target genes are defined (one-cell resolution) appeared to exceed the physical limits set by the stochastic binding of Bcd to DNA. We hypothesize that early readout of Bcd could account for the observed precision. Specifically, we consider the possibility that gap genes begin to be expressed earlier than typically measured experimentally, at a time when the distance between the nuclei is large. At this time, the difference in Bcd concentration between adjacent nuclei is large, enabling better tolerance for measurement imprecision. We show that such early decoding can indeed increase the accuracy of gap-gene expression, and that the initial pattern can be stabilized during subsequent divisions.

As brain ventricles lose their ability to regulate the cerebrospinal fluid (CSF) pressure, serious brain conditions collectively named hydrocephalus can appear. By modelling ventricular dynamics with the laws of physics, dynamical instabilities are evidenced, caused by either CSF transport dysregulations or abnormal properties of the elasticity of the ependyma. We show that these instabilities would lead, in most cases, to dilation of the ventricles, establishing a close connection to hydrocephalus, or in some other cases to a ventricular contraction as observed in the slit ventricle syndrome. Signs seem to indicate the possibility of phase transitions occurring as a result of these instabilities, which might have important clinical consequences, such as the inability to recover a healthy state. Even so, our dynamical approach could allow the development of a unified view of these complex intracranial conditions along with a classification that might be clinically relevant.

An active particle can convert its internal energy into mechanical work. We study a generalized energy-depot model of an overdamped active particle in a ratchet potential. Using well-known biological parameters for kinesin-1 and modeling ATP influx as a pulsed energy supply, we apply our model to the molecular motor system. We find that our simple model can capture the essential properties of the kinesin motor such as forward stepping, stalling, backward stepping, dependence on ATP concentration, and stall force. Our model might be quite universal in the sense that it is able to describe dynamics of various types of motors as long as realistic parameters for each motor species are adopted.

Double-stranded DNA in many bacterial viruses (phage) is strongly confined, which results in internal genome pressures of tens of atmospheres. This pressure is strongly dependent on local ion concentration and distribution within the viral capsid. Here, we have used electron energy loss spectroscopy (EELS), energy-filtered TEM (EFTEM) and X-ray energy dispersive spectroscopy to provide such chemical information from the capsid and the phage tail through which DNA is injected into the cell. To achieve this, we have developed a method to prepare thin monolayers of self-supporting virus/buffer films, suitable for EELS and EFTEM analysis. The method is based on entrapment of virus particles at air–liquid interfaces; thus, the commonly used method of staining by heavy metal salts can be avoided, eliminating the risk for chemical artifacts. We found that Mg2 +  concentration was approximately 2–4 times higher in the DNA-filled capsid than in the surrounding TM buffer (containing 10 mM Mg2 + ). Furthermore, we also analyzed the DNA content inside the phage tail by mapping phosphorus and magnesium.

This study demonstrates an application of distance-based numerical measures to the phase space of time series signals, in order to obtain a temporal analysis of complex dynamical systems. This method is capable of detecting alterations appearing in the characters of the deterministic dynamical systems and provides a simple tool for the real-time analysis of time series data obtained from a complex dynamical system even with black box functionality. The study presents a possible application of the method in the dynamical transition analysis of real EEG records from epilepsy patients.

Using a simple example of biological macromolecules which are partitioned between bulk solution and membrane, we investigate T.L. Hill’s phenomenological nanothermodynamics for small systems. By introducing a system size-dependent equilibrium constant for the bulk-membrane partition, we obtain Hill’s results on differential and integral chemical potentials μ and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$\hat{\mu}$\end{document} from computations based on standard Gibbsian equilibrium statistical mechanics. It is shown that their difference can be understood from an equilibrium re-partitioning between bulk and membrane fractions upon a change in the system’s size; it is closely related to the system’s fluctuations and inhomogeneity. These results provide a better understanding of nanothermodynamics and clarify its logical relation with the theory of statistical mechanics.

The spectroscopic signatures of solvated anions and cations, in the O-H stretch region of water, are studied using the POLIR potential. Shifts in the spectra are shown to correlate very well with the distribution of a particular hydrogen bond angle for the waters in the first solvation shell. The results indicate that the spectral shifts might be predicted from MD simulations in a computationally convenient fashion, avoiding an explicit calculation of the spectra, as first suggested by Sharp et al. (J Chem Phys 114(4):1791–1796, 2001).

The complex behavior of liquid water, along with its anomalies and their crucial role in the existence of life, continue to attract the attention of researchers. The anomalous behavior of water is more pronounced at subfreezing temperatures and numerous theoretical and experimental studies are directed towards developing a coherent thermodynamic and dynamic framework for understanding supercooled water. The existence of a liquid–liquid critical point in the deep supercooled region has been related to the anomalous behavior of water. However, the experimental study of supercooled water at very low temperatures is hampered by the homogeneous nucleation of the crystal. Recently, water confined in nanoscopic structures or in solutions has attracted interest because nucleation can be delayed. These systems have a tremendous relevance also for current biological advances; e.g., supercooled water is often confined in cell membranes and acts as a solvent for biological molecules. In particular, considerable attention has been recently devoted to understanding hydrophobic interactions or the behavior of water in the presence of apolar interfaces due to their fundamental role in self-assembly of micelles, membrane formation and protein folding. This article reviews and compares two very recent computational works aimed at elucidating the changes in the thermodynamic behavior in the supercooled region and the liquid–liquid critical point phenomenon for water in contact with hydrophobic environments. The results are also compared to previous reports for water in hydrophobic environments.

A qualitative model of the nucleation of stable bubbles in water at room temperature is suggested. This model is completely based on the property of the affinity of water at the nanometer scale; it is shown that under certain conditions the extent of disorder in a liquid starts growing, which results in a spontaneous decrease of the local density of the liquid and in the formation of nanometer-sized voids. These voids can serve as nuclei for the following generation of the so-called bubstons (the abbreviation for bubbles, stabilized by ions). The model of charging the bubstons by the ions, which are capable of adsorption, and the screening by a cloud of counter-ions, which are incapable of adsorption, is analyzed. It was shown that, subject to the charge of bubston, two regimes of such screening can be realized. At low charge of bubston the screening is described in the framework of the known linearized Debye–Huckel approach, when the sign of the counter-ion cloud preserves its sign everywhere in the liquid surrounding the bubston, whereas at large charge this sign is changed at some distance from the bubston surface. This effect provides the mechanism of the emergence of two types of compound particles having the opposite polarity, which leads to the aggregation of such compound particles by a ballistic kinetics.

Proton transfer to and from water is critical to the function of water in many settings. However, it has been challenging to model. Here, we present proof-of-principle for an efficient yet robust model based on Lewis-inspired submolecular particles with interactions that deviate from Coulombic at short distances to take quantum effects into account. This “LEWIS” model provides excellent correspondence with experimental structures for water molecules and water clusters in their neutral, protonated and deprotonated forms; reasonable values for the proton affinities of water and hydroxide; a good value for the strength of the hydrogen bond in the water dimer; the correct order of magnitude for the stretch and bend force constants of water; and the expected time course for Grotthuss transport in water chains.

Water molecules play critical roles in many biological functions, such as protein dynamics, enzymatic activities, and cellular responses. Previous nuclear magnetic resonance and neutron scattering studies have shown that water molecules bind to specific sites on surfaces and form localized clusters. However, most current experimental techniques cannot measure dynamic behaviors of ordered water molecules on cell-size (10 μm) scale. Recently, the long-distance effect of structured water has been demonstrated by Pollack and his colleagues. Namely, there is a structured water layer near the hydrophilic surface that can exclude solutes (Zheng et al, Adv Colloid Interface Sci 127:19–27, 2006; Pollack 2006, Adv Colloid Interface Sci 103:173–196, 2003). The repelling forces of water clusters inside this exclusion region are investigated in this study. With a laser tweezers system, we found the existence of an unexpected force fields inside the solute-free exclusion zone near a Nafion surface. Our results suggest that the water clusters could transduce mechanical signals on the micrometer range within the exclusion zone. This unexpected inhomogeneous force field near the hydrophilic surface would provide a new insight into cellular activities, leading to a potential new physical chemistry mechanism for cell biology.

Archaerhodopsin-3 (AR3) is a light-driven proton pump from Halorubrum sodomense, but little is known about its photocycle. Recent interest has focused on AR3 because of its ability to serve both as a high-performance, genetically-targetable optical silencer of neuronal activity and as a membrane voltage sensor. We examined light-activated structural changes of the protein, retinal chromophore, and internal water molecules during the photocycle of AR3. Low-temperature and rapid-scan time-resolved FTIR-difference spectroscopy revealed that conformational changes during formation of the K, M, and N photocycle intermediates are similar, although not identical, to bacteriorhodopsin (BR). Positive/negative bands in the region above 3,600 cm − 1, which have previously been assigned to structural changes of weakly hydrogen bonded internal water molecules, were substantially different between AR3 and BR. This included the absence of positive bands recently associated with a chain of proton transporting water molecules in the cytoplasmic channel and a weakly hydrogen bonded water (W401), which is part of a hydrogen-bonded pentagonal cluster located near the retinal Schiff base. However, many of the broad IR continuum absorption changes below 3,000 cm − 1 assigned to networks of water molecules involved in proton transport through cytoplasmic and extracellular portions in BR were very similar in AR3. This work and subsequent studies comparing BR and AR3 structural changes will help identify conserved elements in BR-like proton pumps as well as bioengineer AR3 to optimize neural silencing and voltage sensing.

Nowadays, biologists can explore the cell at the nanometre level. They discover an unsuspected world, amazingly overcrowded, complex and heterogeneous, in which water, also, is complex and heterogeneous. In the cell, statistical phenomena, such as diffusion, long considered as the main transport for water soluble substances, must be henceforth considered as inoperative to orchestrate cell activity. Results at this level are not yet numerous enough to give an exact representation of the cell machinery; however, they are sufficient to cease reasoning in terms of statistics (diffusion, law of mass action, pH, etc.) and encourage cytologists and biochemists to prospect thoroughly the huge panoply of the biophysical properties of macromolecule-water associations at the nanometre level. Our main purpose, here, is to discuss some of the more common misinterpretations due to the ignorance of these properties, and expose briefly the bases for a better approach of the cell machinery. Giorgio Careri, who demonstrated the correlation between proton currents at the surface of lysozyme and activity of this enzyme was one of the pioneers of this approach.

Fully understanding the structure of water is a crucial point in biophysics because this liquid is essential in the operation of the engines of life. Many of its amazing anomalies seem to be tailored to support biological processes and, during about a century, several models have been developed to describe the water structuring. In particular, a theory assumes that water is a mixture of domains constituted by two distinct and inter-converting structural species, the low-density water (LDW) and the high-density water (HDW). According to this theory, by using some particular solutes or changing the water temperature, it should be possible to modify the equilibrium between the two species, changing in this way the water behavior in specific biological processes, as in governing the shape and stability of the structures of proteins. In this work, we assess the possibility of obtaining information on the structures induced in water by specific salts or by temperature by measuring the delayed luminescence (DL) of some salt solutions and of water in the super-cooled regime. Previous works have demonstrated that the delayed luminescence of a system is correlated with its dynamic ordered structures. The results show significant DL signals only when the formation of LDW domains is expected. The measurement reveals a similar activation energy for the domains both in aqueous salt solutions and super-cooled water. It is worth noting that the time trend of DL signals suggests the existence of structures unusually long-lasting in time, up to the microsecond range.