1,299 research outputs found
Requirements for efficient cell-type proportioning: regulatory timescales, stochasticity and lateral inhibition
The proper functioning of multicellular organisms requires the robust
establishment of precise proportions between distinct cell-types. This
developmental differentiation process typically involves intracellular
regulatory and stochastic mechanisms to generate cell-fate diversity as well as
intercellular mechanisms to coordinate cell-fate decisions at tissue level. We
thus surmise that key insights about the developmental regulation of cell-type
proportion can be captured by the modeling study of clustering dynamics in
population of inhibitory-coupled noisy bistable systems. This general class of
dynamical system is shown to exhibit a very stable two-cluster state, but also
frustrated relaxation, collective oscillations or steady-state hopping which
prevents from timely and reliably reaching a robust and well-proportioned
clustered state. To circumvent these obstacles or to avoid fine-tuning, we
highlight a general strategy based on dual-time positive feedback loops, such
as mediated through transcriptional versus epigenetic mechanisms, which
improves proportion regulation by coordinating early and flexible lineage
priming with late and firm commitment. This result sheds new light on the
respective and cooperative roles of multiple regulatory feedback, stochasticity
and lateral inhibition in developmental dynamics
Stochastic timing in gene expression for simple regulatory strategies
Timing is essential for many cellular processes, from cellular responses to
external stimuli to the cell cycle and circadian clocks. Many of these
processes are based on gene expression. For example, an activated gene may be
required to reach in a precise time a threshold level of expression that
triggers a specific downstream process. However, gene expression is subject to
stochastic fluctuations, naturally inducing an uncertainty in this
threshold-crossing time with potential consequences on biological functions and
phenotypes. Here, we consider such "timing fluctuations", and we ask how they
can be controlled. Our analytical estimates and simulations show that, for an
induced gene, timing variability is minimal if the threshold level of
expression is approximately half of the steady-state level. Timing fuctuations
can be reduced by increasing the transcription rate, while they are insensitive
to the translation rate. In presence of self-regulatory strategies, we show
that self-repression reduces timing noise for threshold levels that have to be
reached quickly, while selfactivation is optimal at long times. These results
lay a framework for understanding stochasticity of endogenous systems such as
the cell cycle, as well as for the design of synthetic trigger circuits.Comment: 10 pages, 5 figure
Emergence of Noise-Induced Oscillations in the Central Circadian Pacemaker
Computational modeling and experimentation explain how intercellular coupling and intracellular noise can generate oscillations in a mammalian neuronal network even in the absence of cell-autonomous oscillators
Functional roles for noise in genetic circuits
The genetic circuits that regulate cellular functions are subject to stochastic fluctuations, or βnoiseβ, in the levels of their components. Noise, far from just a nuisance, has begun to be appreciated for its essential role in key cellular activities. Noise functions in both microbial and eukaryotic cells, in multicellular development, and in evolution. It enables coordination of gene expression across large regulons, as well as probabilistic differentiation strategies that function across cell populations. At the longest timescales, noise may facilitate evolutionary transitions. Here we review examples and emerging principles that connect noise, the architecture of the gene circuits in which it is present, and the biological functions it enables. We further indicate some of the important challenges and opportunities going forward
Using movies to analyse gene circuit dynamics in single cells
Many bacterial systems rely on dynamic genetic circuits to control crucial biological processes. A major goal of systems biology is to understand these behaviours in terms of individual genes and their interactions. However, traditional techniques based on population averages 'wash out' crucial dynamics that are either unsynchronized between cells or are driven by fluctuations, or 'noise', in cellular components. Recently, the combination of time-lapse microscopy, quantitative image analysis and fluorescent protein reporters has enabled direct observation of multiple cellular components over time in individual cells. In conjunction with mathematical modelling, these techniques are now providing powerful insights into genetic circuit behaviour in diverse microbial systems
Persistent Cell-Autonomous Circadian Oscillations in Fibroblasts Revealed by Six-Week Single-Cell Imaging of PER2::LUC Bioluminescence
Biological oscillators naturally exhibit stochastic fluctuations in period and amplitude due to the random nature of molecular reactions. Accurately measuring the precision of noisy oscillators and the heterogeneity in period and strength of rhythmicity across a population of cells requires single-cell recordings of sufficient length to fully represent the variability of oscillations. We found persistent, independent circadian oscillations of clock gene expression in 6-week-long bioluminescence recordings of 80 primary fibroblast cells dissociated from PER2::LUC mice and kept in vitro for 6 months. Due to the stochastic nature of rhythmicity, the proportion of cells appearing rhythmic increases with the length of interval examined, with 100% of cells found to be rhythmic when using 3-week windows. Mean period and amplitude are remarkably stable throughout the 6-week recordings, with precision improving over time. For individual cells, precision of period and amplitude are correlated with cell size and rhythm amplitude, but not with period, and period exhibits much less cycle-to-cycle variability (CV 7.3%) than does amplitude (CV 37%). The time series are long enough to distinguish stochastic fluctuations within each cell from differences among cells, and we conclude that the cells do exhibit significant heterogeneity in period and strength of rhythmicity, which we measure using a novel statistical metric. Furthermore, stochastic modeling suggests that these single-cell clocks operate near a Hopf bifurcation, such that intrinsic noise enhances the oscillations by minimizing period variability and sustaining amplitude
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