13,669 research outputs found
Bistability: Requirements on Cell-Volume, Protein Diffusion, and Thermodynamics
Bistability is considered wide-spread among bacteria and eukaryotic cells,
useful e.g. for enzyme induction, bet hedging, and epigenetic switching.
However, this phenomenon has mostly been described with deterministic dynamic
or well-mixed stochastic models. Here, we map known biological bistable systems
onto the well-characterized biochemical Schloegl model, using analytical
calculations and stochastic spatio-temporal simulations. In addition to network
architecture and strong thermodynamic driving away from equilibrium, we show
that bistability requires fine-tuning towards small cell volumes (or
compartments) and fast protein diffusion (well mixing). Bistability is thus
fragile and hence may be restricted to small bacteria and eukaryotic nuclei,
with switching triggered by volume changes during the cell cycle. For large
volumes, single cells generally loose their ability for bistable switching and
instead undergo a first-order phase transition.Comment: 23 pages, 8 figure
Entropy production selects nonequilibrium states in multistable systems
Far-from-equilibrium thermodynamics underpins the emergence of life, but how
has been a long-outstanding puzzle. Best candidate theories based on the
maximum entropy production principle could not be unequivocally proven, in part
due to complicated physics, unintuitive stochastic thermodynamics, and the
existence of alternative theories such as the minimum entropy production
principle. Here, we use a simple, analytically solvable, one-dimensional
bistable chemical system to demonstrate the validity of the maximum entropy
production principle. To generalize to multistable stochastic system, we use
the stochastic least-action principle to derive the entropy production and its
role in the stability of nonequilibrium steady states. This shows that in a
multistable system, all else being equal, the steady state with the highest
entropy production is favored, with a number of implications for the evolution
of biological, physical, and geological systems.Comment: 15 pages, 4 figure
Protein connectivity in chemotaxis receptor complexes
The chemotaxis sensory system allows bacteria such as Escherichia coli to swim towards nutrients and away from repellents. The underlying pathway is remarkably sensitive in detecting chemical gradients over a wide range of ambient concentrations. Interactions among receptors, which are predominantly clustered at the cell poles, are crucial to this sensitivity. Although it has been suggested that the kinase CheA and the adapter protein CheW are integral for receptor connectivity, the exact coupling mechanism remains unclear. Here, we present a statistical-mechanics approach to model the receptor linkage mechanism itself, building on nanodisc and electron cryotomography experiments. Specifically, we investigate how the sensing behavior of mixed receptor clusters is affected by variations in the expression levels of CheA and CheW at a constant receptor density in the membrane. Our model compares favorably with dose-response curves from in vivo Förster resonance energy transfer (FRET) measurements, demonstrating that the receptor-methylation level has only minor effects on receptor cooperativity. Importantly, our model provides an explanation for the non-intuitive conclusion that the receptor cooperativity decreases with increasing levels of CheA, a core signaling protein associated with the receptors, whereas the receptor cooperativity increases with increasing levels of CheW, a key adapter protein. Finally, we propose an evolutionary advantage as explanation for the recently suggested CheW-only linker structures
Emulating Human Developmental Stages with Bayesian Neural Networks
We compare the acquisition of knowledge in humans and machines. Research from
the field of developmental psychology indicates, that human-employed hypothesis
are initially guided by simple rules, before evolving into more complex
theories. This observation is shared across many tasks and domains. We
investigate whether stages of development in artificial learning systems are
based on the same characteristics. We operationalize developmental stages as
the size of the data-set, on which the artificial system is trained. For our
analysis we look at the developmental progress of Bayesian Neural Networks on
three different data-sets, including occlusion, support and quantity comparison
tasks. We compare the results with prior research from developmental psychology
and find agreement between the family of optimized models and pattern of
development observed in infants and children on all three tasks, indicating
common principles for the acquisition of knowledge
Noise characteristics of the Escherichia coli rotary motor
The chemotaxis pathway in the bacterium Escherichia coli allows cells to
detect changes in external ligand concentration (e.g. nutrients). The pathway
regulates the flagellated rotary motors and hence the cells' swimming
behaviour, steering them towards more favourable environments. While the
molecular components are well characterised, the motor behaviour measured by
tethered cell experiments has been difficult to interpret. Here, we study the
effects of sensing and signalling noise on the motor behaviour. Specifically,
we consider fluctuations stemming from ligand concentration, receptor switching
between their signalling states, adaptation, modification of proteins by
phosphorylation, and motor switching between its two rotational states. We
develop a model which includes all signalling steps in the pathway, and discuss
a simplified version, which captures the essential features of the full model.
We find that the noise characteristics of the motor contain signatures from all
these processes, albeit with varying magnitudes. This allows us to address how
cell-to-cell variation affects motor behaviour and the question of optimal
pathway design. A similar comprehensive analysis can be applied to other
two-component signalling pathways.Comment: 22 pages, 7 figures, 3 tutorials, supplementary information;
submitted manuscrip
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