351 research outputs found
Influence of M-phase chromatin on the anisotropy of microtubule asters
In many eukaryotic cells going through M-phase, a bipolar spindle is formed by microtubules nucleated from centrosomes. These microtubules, in addition to being "captured" by kinetochores, may be stabilized by chromatin in two different ways: short-range stabilization effects may affect microtubules in close contact with the chromatin, while long-range stabilization effects may "guide" microtubule growth towards the chromatin (e.g., by introducing a diffusive gradient of an enzymatic activity that affects microtubule assembly). Here, we use both meiotic and mitotic extracts from Xenopus laevis eggs to study microtubule aster formation and microtubule dynamics in the presence of chromatin. In "low-speed" meiotic extracts, in the presence of salmon sperm chromatin, we find that short-range stabilization effects lead to a strong anisotropy of the microtubule asters. Analysis of the dynamic parameters of microtubule growth show that this anisotropy arises from a decrease in the catastrophe frequency, an increase in the rescue frequency and a decrease in the growth velocity. In this system we also find evidence for long-range "guidance" effects, which lead to a weak anisotropy of the asters. Statistically relevant results on these long-range effects are obtained in "high-speed" mitotic extracts in the presence of artificially constructed chromatin stripes. We find that aster anisotropy is biased in the direction of the chromatin and that the catastrophe frequency is reduced in its vicinity. In this system we also find a surprising dependence of the catastrophe and the rescue frequencies on the length of microtubules nucleated from centrosomes: the catastrophe frequency increase and the rescue frequency decreases with microtubule length
Statistical mechanics for metabolic networks during steady-state growth
Which properties of metabolic networks can be derived solely from
stoichiometric information about the network's constituent reactions?
Predictive results have been obtained by Flux Balance Analysis (FBA), by
postulating that cells set metabolic fluxes within the allowed stoichiometry so
as to maximize their growth. Here, we generalize this framework to single cell
level using maximum entropy models from statistical physics. We define and
compute, for the core metabolism of Escherichia coli, a joint distribution over
all fluxes that yields the experimentally observed growth rate. This solution,
containing FBA as a limiting case, provides a better match to the measured
fluxes in the wild type and several mutants. We find that E. coli metabolism is
close to, but not at, the optimality assumed by FBA. Moreover, our model makes
a wide range of predictions: (i) on flux variability, its regulation, and flux
correlations across individual cells; (ii) on the relative importance of
stoichiometric constraints vs. growth rate optimization; (iii) on quantitative
scaling relations for singe-cell growth rate distributions. We validate these
scaling predictions using data from individual bacterial cells grown in a
microfluidic device at different sub-inhibitory antibiotic concentrations.
Under mild dynamical assumptions, fluctuation-response relations further
predict the autocorrelation timescale in growth data and growth rate adaptation
times following an environmental perturbation.Comment: 12 pages, 4 figure
Intrinsic limits to gene regulation by global crosstalk
Gene regulation relies on the specificity of transcription factor (TF) - DNA
interactions. In equilibrium, limited specificity may lead to crosstalk: a
regulatory state in which a gene is either incorrectly activated due to
noncognate TF-DNA interactions or remains erroneously inactive. We present a
tractable biophysical model of global crosstalk, where many genes are
simultaneously regulated by many TFs. We show that in the simplest regulatory
scenario, a lower bound on crosstalk severity can be analytically derived
solely from the number of (co)regulated genes and a suitable parameter that
describes binding site similarity. Estimates show that crosstalk could present
a significant challenge for organisms with low-specificity TFs, such as
metazoans, unless they use appropriate regulation schemes. Strong cooperativity
substantially decreases crosstalk, while joint regulation by activators and
repressors, surprisingly, does not; moreover, certain microscopic details about
promoter architecture emerge as globally important determinants of crosstalk
strength. Our results suggest that crosstalk imposes a new type of global
constraint on the functioning and evolution of regulatory networks, which is
qualitatively distinct from the known constraints acting at the level of
individual gene regulatory elements
Charge-Induced Fragmentation of Sodium Clusters
The fission of highly charged sodium clusters with fissilities X>1 is studied
by {\em ab initio} molecular dynamics. Na_{24}^{4+} is found to undergo
predominantly sequential Na_{3}^{+} emission on a time scale of 1 ps, while
Na_{24}^{Q+} (5 \leq Q \leq 8) undergoes multifragmentation on a time scale
\geq 0.1 ps, with Na^{+} increasingly the dominant fragment as Q increases. All
singly-charged fragments Na_{n}^{+} up to size n=6 are observed. The observed
fragment spectrum is, within statistical error, independent of the temperature
T of the parent cluster for T \leq 1500 K. These findings are consistent with
and explain recent trends observed experimentally.Comment: To appear in Physical Review Letter
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Noise Underlies Switching Behavior of the Bacterial Flagellum
We report the switching behavior of the full bacterial flagellum system that includes the filament and the motor in wild-type Escherichia coli cells. In sorting the motor behavior by the clockwise bias, we find that the distributions of the clockwise (CW) and counterclockwise (CCW) intervals are either exponential or nonexponential with long tails. At low bias, CW intervals are exponentially distributed and CCW intervals exhibit long tails. At intermediate CW bias (0.5) both CW and CCW intervals are mainly exponentially distributed. A simple model suggests that these two distinct switching behaviors are governed by the presence of signaling noise within the chemotaxis network. Low noise yields exponentially distributed intervals, whereas large noise yields nonexponential behavior with long tails. These drastically different motor statistics may play a role in optimizing bacterial behavior for a wide range of environmental conditions.Molecular and Cellular Biolog
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