258 research outputs found
Multiplexing Biochemical Signals
In this paper we show that living cells can multiplex biochemical signals,
i.e. transmit multiple signals through the same signaling pathway
simultaneously, and yet respond to them very specifically. We demonstrate how
two binary input signals can be encoded in the concentration of a common
signaling protein, which is then decoded such that each of the two output
signals provides reliable information about one corresponding input. Under
biologically relevant conditions the network can reach the maximum amount of
information that can be transmitted, which is 2 bits.Comment: 4 pages, 4 figure
Anisotropic coarse-grained statistical potentials improve the ability to identify native-like protein structures
We present a new method to extract distance and orientation dependent
potentials between amino acid side chains using a database of protein
structures and the standard Boltzmann device. The importance of orientation
dependent interactions is first established by computing orientational order
parameters for proteins with alpha-helical and beta-sheet architecture.
Extraction of the anisotropic interactions requires defining local reference
frames for each amino acid that uniquely determine the coordinates of the
neighboring residues. Using the local reference frames and histograms of the
radial and angular correlation functions for a standard set of non-homologue
protein structures, we construct the anisotropic pair potentials. The
performance of the orientation dependent potentials was studied using a large
database of decoy proteins. The results demonstrate that the new distance and
orientation dependent residue-residue potentials present a significantly
improved ability to recognize native folds from a set of native and decoy
protein structures.Comment: Submitted to "The Journal of Chemical Physics
Phylogeography and Symbiotic Effectiveness of Rhizobia Nodulating Chickpea (Cicer arietinum L.) in Ethiopia
Chickpea (Cicer arietinum L.) used to be considered a restrictive host that nodulated and fixed nitrogen only with Mesorhizobium
ciceri and M.mediterraneum. Recent analysis revealed that chickpea can also establish effective symbioseswith strains of several
other Mesorhizobium species such as M. loti, M. haukuii, M. amorphae, M. muleiense, etc. These strains vary in their nitrogen
fixation potential inviting further exploration. We characterized newly collected mesorhizobial strains isolated from various
locations in Ethiopia to evaluate genetic diversity, biogeographic structure and symbiotic effectiveness. Symbiotic effectiveness
was evaluated in Leonard Jars using a locally released chickpea cultivar “Nattoli”. Most of the new isolates belonged to a clade
related to M. plurifarium, with very few sequence differences, while the total collection of strains contained three additional
mesorhizobial genospecies associated with M. ciceri, M. abyssinicae and an unidentified Mesorhizobium species isolated from a
wild host in Eritrea. The four genospecies identified represented a subset of the eight major Mesorhizobium clades recently
reported for Ethiopia based on metagenomic data. All Ethiopian strains had nearly identical symbiotic genes that grouped them in
a single cluster with M. ciceri, M. mediterraneum and M. muleiense, but not with M. plurifarium. Some phylogeographic
structure was observed, with elevation and geography explaining some of the genetic differences among strains, but the relation
between genetic identity and symbiotic effectiveness was observed to be weak
Symbiotic interactions between chickpea (Cicer arietinum L.) genotypes and Mesorhizobium strains
Legume genotype (GL) x rhizobium genotype (GR) interaction in chickpea was studied using a genetically diverse set of
accessions and rhizobium strains in modified Leonard Jars. A subset of effective GL x GR combinations was subsequently
evaluated in a pot experiment to identify combinations of chickpea genotypes and rhizobium strains with stable and superior symbiotic performance. A linear mixed model was employed to analyse the occurrence of GL x GR interaction and an additive main effects and multiplicative interaction (AMMI) model was used to study patterns in the performance of genotype-strain combinations.We found statistically significant interaction in jars in terms of symbiotic effectiveness that was entirely due to the
inclusion of one of the genotypes, ICC6263. No interaction was found in a subsequent pot experiment. The presence of two genetic groups (Kabuli and Desi genepools) did not affect interaction with Mesorhizobium strains. With the exception of a negative interaction with genotype ICC6263 in the jar experiment, the type strain Mesorhizobium ciceri LMG 14989 outperformed or equalled other strains on all chickpea genotypes in both jar and pot experiments. Similar to earlier reports in common bean, our results suggest that efforts to findmore effective strains may be more rewarding than aiming for identification of superior combinations of strains and genotypes
Regulatory control and the costs and benefits of biochemical noise
Experiments in recent years have vividly demonstrated that gene expression
can be highly stochastic. How protein concentration fluctuations affect the
growth rate of a population of cells, is, however, a wide open question. We
present a mathematical model that makes it possible to quantify the effect of
protein concentration fluctuations on the growth rate of a population of
genetically identical cells. The model predicts that the population's growth
rate depends on how the growth rate of a single cell varies with protein
concentration, the variance of the protein concentration fluctuations, and the
correlation time of these fluctuations. The model also predicts that when the
average concentration of a protein is close to the value that maximizes the
growth rate, fluctuations in its concentration always reduce the growth rate.
However, when the average protein concentration deviates sufficiently from the
optimal level, fluctuations can enhance the growth rate of the population, even
when the growth rate of a cell depends linearly on the protein concentration.
The model also shows that the ensemble or population average of a quantity,
such as the average protein expression level or its variance, is in general not
equal to its time average as obtained from tracing a single cell and its
descendants. We apply our model to perform a cost-benefit analysis of gene
regulatory control. Our analysis predicts that the optimal expression level of
a gene regulatory protein is determined by the trade-off between the cost of
synthesizing the regulatory protein and the benefit of minimizing the
fluctuations in the expression of its target gene. We discuss possible
experiments that could test our predictions.Comment: Revised manuscript;35 pages, 4 figures, REVTeX4; to appear in PLoS
Computational Biolog
From compact to fractal crystalline clusters in concentrated systems of monodisperse hard spheres
We address the crystallization of monodisperse hard spheres in terms of the
properties of finite- size crystalline clusters. By means of large scale
event-driven Molecular Dynamics simulations, we study systems at different
packing fractions {\phi} ranging from weakly supersaturated state points to
glassy ones, covering different nucleation regimes. We find that such regimes
also result in different properties of the crystalline clusters: compact
clusters are formed in the classical-nucleation-theory regime ({\phi} \leq
0.54), while a crossover to fractal, ramified clusters is encountered upon
increasing packing fraction ({\phi} \geq 0.56), where nucleation is more
spinodal-like. We draw an analogy between macroscopic crystallization of our
clusters and percolation of attractive systems to provide ideas on how the
packing fraction influences the final structure of the macroscopic crystals. In
our previous work (Phys. Rev. Lett., 106, 215701, 2011), we have demonstrated
how crystallization from a glass (at {\phi} > 0.58) happens via a gradual
(many-step) mechanism: in this paper we show how the mechanism of gradual
growth seems to hold also in super-saturated systems just above freezing
showing that static properties of clusters are not much affected by dynamics.Comment: Soft Matter, 201
Consistency, variability, and predictability of on-farm nutrient responses in four grain legumes across east and west Africa
Open Access Article; Published online: 26 May 2023Grain legumes are key components of sustainable production systems in sub-Saharan Africa, but wide-spread nutrient deficiencies severely restrict yields. Whereas legumes can meet a large part of their nitrogen (N) requirement through symbiosis with N2-fixing bacteria, elements such as phosphorus (P), potassium (K) and secondary and micronutrients may still be limiting and require supplementation. Responses to P are generally strong but variable, while evidence for other nutrients tends to show weak or highly localised effects. Here we present the results of a joint statistical analysis of a series of on-farm nutrient addition trials, implemented across four legumes in four countries over two years. Linear mixed models were used to quantify both mean nutrient responses and their variability, followed by a random forest analysis to determine the extent to which such variability can be explained or predicted by geographic, environmental or farm survey data. Legume response to P was indeed variable, but consistently positive and we predicted application to be profitable for 67% of farms in any given year, based on prevailing input costs and grain prices. Other nutrients did not show significant mean effects, but considerable response variation was found. This response heterogeneity was mostly associated with local or temporary factors and could not be explained or predicted by spatial, biophysical or management factors. An exception was K response, which displayed appreciable spatial variation that could be partly accounted for by spatial and environmental covariables. While of apparent relevance for targeted recommendations, the minor amplitude of expected response, the large proportion of unexplained variation and the unreliability of the predicted spatial patterns suggests that such data-driven targeting is unlikely to be effective with current data
Generic mechanism for generating a liquid-liquid phase transition
Recent experimental results indicate that phosphorus, a single-component
system, can have two liquid phases: a high-density liquid (HDL) and a
low-density liquid (LDL) phase. A first-order transition between two liquids of
different densities is consistent with experimental data for a variety of
materials, including single-component systems such as water, silica and carbon.
Molecular dynamics simulations of very specific models for supercooled water,
liquid carbon and supercooled silica, predict a LDL-HDL critical point, but a
coherent and general interpretation of the LDL-HDL transition is lacking. Here
we show that the presence of a LDL and a HDL can be directly related to an
interaction potential with an attractive part and two characteristic
short-range repulsive distances. This kind of interaction is common to other
single-component materials in the liquid state (in particular liquid metals),
and such potentials are often used to decribe systems that exhibit a density
anomaly. However, our results show that the LDL and HDL phases can occur in
systems with no density anomaly. Our results therefore present an experimental
challenge to uncover a liquid-liquid transition in systems like liquid metals,
regardless of the presence of the density anomaly.Comment: 5 pages, 3 ps Fig
Homogeneous Bubble Nucleation driven by local hot spots: a Molecular Dynamics Study
We report a Molecular Dynamics study of homogenous bubble nucleation in a
Lennard-Jones fluid. The rate of bubble nucleation is estimated using
forward-flux sampling (FFS). We find that cavitation starts with compact
bubbles rather than with ramified structures as had been suggested by Shen and
Debenedetti (J. Chem. Phys. 111:3581, 1999). Our estimate of the
bubble-nucleation rate is higher than predicted on the basis of Classical
Nucleation Theory (CNT). Our simulations show that local temperature
fluctuations correlate strongly with subsequent bubble formation - this
mechanism is not taken into account in CNT
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