484 research outputs found
Simulational study of anomalous tracer diffusion in hydrogels
In this article, we analyze different factors that affect the diffusion
behavior of small tracer particles (as they are used e.g.in fluorescence
correlation spectroscopy (FCS)) in the polymer network of a hydrogel and
perform simulations of various simplified models. We observe, that under
certain circumstances the attraction of a tracer particle to the polymer
network strands might cause subdiffusive behavior on intermediate time scales.
In theory, this behavior could be employed to examine the network structure and
swelling behavior of weakly crosslinked hydrogels with the help of FCS.Comment: 11 pages, 11 figure
The Influence of Transcription Factor Competition on the Relationship between Occupancy and Affinity
Transcription factors (TFs) are proteins that bind to specific sites on the DNA and regulate gene activity. Identifying where TF molecules bind and how much time they spend on their target sites is key to understanding transcriptional regulation. It is usually assumed that the free energy of binding of a TF to the DNA (the affinity of the site) is highly correlated to the amount of time the TF remains bound (the occupancy of the site). However, knowing the binding energy is not sufficient to infer actual binding site occupancy. This mismatch between the occupancy predicted by the affinity and the observed occupancy may be caused by various factors, such as TF abundance, competition between TFs or the arrangement of the sites on the DNA. We investigated the relationship between the affinity of a TF for a set of binding sites and their occupancy. In particular, we considered the case of the transcription factor lac repressor (lacI) in E.coli, and performed stochastic simulations of the TF dynamics on the DNA for various combinations of lacI abundance and competing TFs that contribute to macromolecular crowding. We also investigated the relationship of site occupancy and the information content of position weight matrices (PWMs) used to represent binding sites. Our results showed that for medium and high affinity sites, TF competition does not play a significant role for genomic occupancy except in cases when the abundance of the TF is significantly increased, or when the PWM displays relatively low information content. Nevertheless, for medium and low affinity sites, an increase in TF abundance (for both cognate and non-cognate molecules) leads to an increase in occupancy at several sites. © 2013 Zabet et al
Evolution favors protein mutational robustness in sufficiently large populations
BACKGROUND: An important question is whether evolution favors properties such
as mutational robustness or evolvability that do not directly benefit any
individual, but can influence the course of future evolution. Functionally
similar proteins can differ substantially in their robustness to mutations and
capacity to evolve new functions, but it has remained unclear whether any of
these differences might be due to evolutionary selection for these properties.
RESULTS: Here we use laboratory experiments to demonstrate that evolution
favors protein mutational robustness if the evolving population is sufficiently
large. We neutrally evolve cytochrome P450 proteins under identical selection
pressures and mutation rates in populations of different sizes, and show that
proteins from the larger and thus more polymorphic population tend towards
higher mutational robustness. Proteins from the larger population also evolve
greater stability, a biophysical property that is known to enhance both
mutational robustness and evolvability. The excess mutational robustness and
stability is well described by existing mathematical theories, and can be
quantitatively related to the way that the proteins occupy their neutral
network.
CONCLUSIONS: Our work is the first experimental demonstration of the general
tendency of evolution to favor mutational robustness and protein stability in
highly polymorphic populations. We suggest that this phenomenon may contribute
to the mutational robustness and evolvability of viruses and bacteria that
exist in large populations
Genotype to phenotype mapping and the fitness landscape of the E. coli lac promoter
Genotype-to-phenotype maps and the related fitness landscapes that include
epistatic interactions are difficult to measure because of their high
dimensional structure. Here we construct such a map using the recently
collected corpora of high-throughput sequence data from the 75 base pairs long
mutagenized E. coli lac promoter region, where each sequence is associated with
its phenotype, the induced transcriptional activity measured by a fluorescent
reporter. We find that the additive (non-epistatic) contributions of individual
mutations account for about two-thirds of the explainable phenotype variance,
while pairwise epistasis explains about 7% of the variance for the full
mutagenized sequence and about 15% for the subsequence associated with protein
binding sites. Surprisingly, there is no evidence for third order epistatic
contributions, and our inferred fitness landscape is essentially single peaked,
with a small amount of antagonistic epistasis. There is a significant selective
pressure on the wild type, which we deduce to be multi-objective optimal for
gene expression in environments with different nutrient sources. We identify
transcription factor (CRP) and RNA polymerase binding sites in the promotor
region and their interactions without difficult optimization steps. In
particular, we observe evidence for previously unexplored genetic regulatory
mechanisms, possibly kinetic in nature. We conclude with a cautionary note that
inferred properties of fitness landscapes may be severely influenced by biases
in the sequence data
Transient Phenomena in Gene Expression after Induction of Transcription
When transcription of a gene is induced by a stimulus, the number of its mRNA molecules changes with time. Here we discuss how this time evolution depends on the shape of the mRNA lifetime distribution. Analysis of the statistical properties of this change reveals transient effects on polysomes, ribosomal profiles, and rate of protein synthesis. Our studies reveal that transient phenomena in gene expression strongly depend on the specific form of the mRNA lifetime distribution
Nonidentifiability of the Source of Intrinsic Noise in Gene Expression from Single-Burst Data
Over the last few years, experimental data on the fluctuations in gene activity
between individual cells and within the same cell over time have confirmed that
gene expression is a “noisy” process. This variation is in
part due to the small number of molecules taking part in some of the key
reactions that are involved in gene expression. One of the consequences of this
is that protein production often occurs in bursts, each due to a single promoter
or transcription factor binding event. Recently, the distribution of the number
of proteins produced in such bursts has been experimentally measured, offering a
unique opportunity to study the relative importance of different sources of
noise in gene expression. Here, we provide a derivation of the theoretical
probability distribution of these bursts for a wide variety of different models
of gene expression. We show that there is a good fit between our theoretical
distribution and that obtained from two different published experimental
datasets. We then prove that, irrespective of the details of the model, the
burst size distribution is always geometric and hence determined by a single
parameter. Many different combinations of the biochemical rates for the
constituent reactions of both transcription and translation will therefore lead
to the same experimentally observed burst size distribution. It is thus
impossible to identify different sources of fluctuations purely from protein
burst size data or to use such data to estimate all of the model parameters. We
explore methods of inferring these values when additional types of experimental
data are available
Major decline of hepatitis C virus incidence rate over two decades in a cohort of drug users
Injecting drug users (DU) are at high risk for hepatitis C virus (HCV) and HIV infections. To examine the prevalence and incidence of these infections over a 20-year period (1985–005), the authors evaluated 1276 DU from the Amsterdam Cohort Studies who had been tested prospectively for HIV infection and retrospectively for HCV infection. To compare HCV and HIV incidences, a smooth trend was assumed for both curves over calendar time. Risk factors for HCV seroconversion were determined using Poisson regression. Among ever-injecting DU, the prevalence of HCV antibodies was 84.5% at study entry, and 30.9% were co-infected with HIV. Their yearly HCV incidence dropped from 27.5/100 person years (PY) in the 1980s to 2/100 PY in recent years. In multivariate analyses, ever-injecting DU who currently injected and borrowed needles were at increased risk of HCV seroconversion (incidence rate ratio 29.9, 95% CI 12.6, 70.9) compared to ever-injecting DU who did not currently inject. The risk of HCV seroconversion decreased over calendar time. The HCV incidence in ever-injecting DU was on average 4.4 times the HIV incidence, a pattern seen over the entire study period. The simultaneous decline of both HCV and HIV incidence probably results from reduced risk behavior at the population level
First-passage times in complex scale-invariant media
How long does it take a random walker to reach a given target point? This
quantity, known as a first passage time (FPT), has led to a growing number of
theoretical investigations over the last decade1. The importance of FPTs
originates from the crucial role played by first encounter properties in
various real situations, including transport in disordered media, neuron firing
dynamics, spreading of diseases or target search processes. Most methods to
determine the FPT properties in confining domains have been limited to
effective 1D geometries, or for space dimensions larger than one only to
homogeneous media1. Here we propose a general theory which allows one to
accurately evaluate the mean FPT (MFPT) in complex media. Remarkably, this
analytical approach provides a universal scaling dependence of the MFPT on both
the volume of the confining domain and the source-target distance. This
analysis is applicable to a broad range of stochastic processes characterized
by length scale invariant properties. Our theoretical predictions are confirmed
by numerical simulations for several emblematic models of disordered media,
fractals, anomalous diffusion and scale free networks.Comment: Submitted version. Supplementary Informations available on Nature
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