Stochastic modelling articles within Nature Communications

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  • Article
    | Open Access

    To understand why genetically identical cells die at different times the authors measured damage dynamics in individual cells. They report lifespan variation comes not from initial conditions but from stochastic accumulation of damage that saturates repair systems.

    • Yifan Yang
    • , Omer Karin
    •  & Uri Alon

  • Article
    | Open Access

    Deep learning (DL) can be used to automatically extract complex features from dynamic systems. Here, the authors combine high-content imaging, DL and mechanistic models to extract and explain drug-induced morphological changes in the growth of the fungus responsible for Asian soybean rust.

    • Henry Cavanagh
    • , Andreas Mosbach
    •  & Robert G. Endres

  • Article
    | Open Access

    The true number of infections from SARS-Cov-2 is unknown and believed to exceed the reported numbers by several fold. National testing policies, in particular, can strongly affect the proportion of undetected cases. Here, the authors propose a method that reconstructs incidence profiles within minutes, solely from publicly available, time-stamped viral genomes.

    • Maureen Rebecca Smith
    • , Maria Trofimova
    •  & Max von Kleist

  • Article
    | Open Access

    How to infer transient cells and cell-fate transitions from snap-shot single cell transcriptome dataset remains a major challenge. Here the authors present a multiscale approach to construct single-cell dynamical manifold, quantify cell stability, and compute transition trajectory and probability between cell states.

    • Peijie Zhou
    • , Shuxiong Wang
    •  & Qing Nie

  • Article
    | Open Access

    Evolutionary steering uses therapies to control tumour evolution by exploiting trade-offs. Here, using a barcoding approach applied to large cell populations, the authors explore evolutionary steering in lung cancer cells treated with EGFR inhibitors.

    • Ahmet Acar
    • , Daniel Nichol
    •  & Andrea Sottoriva

  • Article
    | Open Access

    Cell fate commitment is understood in terms of bistable regulatory circuits with hysteresis, but inherent stochasticity in gene expression is incompatible with hysteresis. Here, the authors quantify how, under slow dynamics, the dependency of the non-stationary solutions on the initial state of the cells can lead to transient hysteresis.

    • M. Pájaro
    • , I. Otero-Muras
    •  & A. A. Alonso

  • Article
    | Open Access

    We know that variations in cell cycle duration between cells naturally occur but the mechanisms are largely unknown. Here, using lineage tracking, hierarchical clustering and Monte Carlo methods, the authors show that large differences in granddaughter cell cycle duration are driven by asymmetric divisions.

    • Ulrich Berge
    • , Daria Bochenek
    •  & Ruth Kroschewski

  • Article
    | Open Access

    Phenotypic cell-to-cell variability contributes to fractional killing, but the mechanisms are incompletely understood. Here the authors show that mitochondrial density correlates with cell survival in response to TRAIL, and that variable effective concentrations of Bax/Bak contribute to the effect.

    • Luís C. Santos
    • , Robert Vogel
    •  & Pablo Meyer

  • Article
    | Open Access

    Noisy gene expression leading to phenotypic variability can help organisms to survive in changing environments. Here, Patange et al. show that noisy expression of a stress response regulator, RpoS, allows E. coli cells to modulate their growth rates to survive future adverse environments.

    • Om Patange
    • , Christian Schwall
    •  & James C. W. Locke

  • Article
    | Open Access

    The drivers of growth rate variability in bacteria are yet unknown. Here, the authors present a theory to predict the growth dynamics of individual cells and use a stochastic cell model integrating metabolism, gene expression and replication to identify the processes that underlie growth variation.

    • Philipp Thomas
    • , Guillaume Terradot
    •  & Andrea Y. Weiße

  • Article
    | Open Access

    For various organisms, mRNA and protein copy numbers scale with cell volume. Here, the authors show that this result emerges naturally when ribosomes and RNAPs limit expression. Furthermore, the authors show that within their model this result breaks down for a sufficiently high volume/DNA ratio.

    • Jie Lin
    •  & Ariel Amir

  • Article
    | Open Access

    The intractability of most stochastic models of gene regulatory networks (GRNs) limits their utility. Here, the authors present a linear-mapping approximation mapping models onto simpler ones, giving approximate but accurate analytic or semi- analytic solutions for a wide range of model GRNs.

    • Zhixing Cao
    •  & Ramon Grima

  • Article
    | Open Access

    Mitochondrial populations in cells may consist of heteroplasmic mixtures of mtDNA types, and their evolution through development, aging and generations is central to genetic diseases. Here the authors dissect these population dynamics using a large mouse-based data set to characterise the dynamics of heteroplasmy mean and variance throughout life and across generations.

    • Joerg P. Burgstaller
    • , Thomas Kolbe
    •  & Iain G. Johnston

  • Article
    | Open Access

    Innate immunity combines intra- and intercellular signalling to develop responses that limit pathogen spread. Here the authors analyse feedback and feedforward loops connecting IRF3, NF-κB and STAT pathways, and suggest they allow coordinating cell fate decisions in cellular populations in response to the virus-mimicking agent poly(I:C).

    • Maciej Czerkies
    • , Zbigniew Korwek
    •  & Tomasz Lipniacki

  • Article
    | Open Access

    A unified framework to understand gene expression noise is still lacking. Here the authors derive a universal theorem relating the biological noise with dynamics of birth and death processes and present a model of transcription dynamics, allowing analytical prediction of the dependence of mRNA noise on mRNA lifetime variability.

    • Seong Jun Park
    • , Sanggeun Song
    •  & Jaeyoung Sung

  • Article
    | Open Access

    Noisy gene expression can cause stochasticity in the expression of plant traits. Here, Araújo et al. use a dual reporter system of protein expression in Arabidopsis to show that expression noise is lowest in stomata relative to other tissues and that leaf cells are coupled with respect to noise.

    • Ilka Schultheiß Araújo
    • , Jessica Magdalena Pietsch
    •  & Martin Hülskamp

  • Article
    | Open Access

    The bacteriophage lambda and its hostEscherichia coli provide a model system to study cell-fate decisions. Here, Trinh et al. develop a four-colour fluorescence system at the single-cell/single-virus/single-viral-DNA level and find phages cooperate during lysogenization and compete during lysis.

    • Jimmy T. Trinh
    • , Tamás Székely
    •  & Lanying Zeng

  • Article
    | Open Access

    Why do populations of highly similar T cells have heterogeneous division destinies in response to antigenic stimulus? Here the authors develop a multiplex-dye assay and a mathematical framework to test clonal heterogeneity and show distinction in division destiny is a result of inter-clonal variability as lineage imprinting ensures clones share similar proliferation fates.

    • J. M. Marchingo
    • , G. Prevedello
    •  & K. R. Duffy

  • Article
    | Open Access

    Cells must function despite the noisiness of their processes by tolerating or reducing such variability. Here, the authors combine experiment and modelling to show that a network motif that mediates network-dosage compensation also reduces noise in network output, suggesting that noise is tuneable.

    • Weilin Peng
    • , Ruijie Song
    •  & Murat Acar

  • Article
    | Open Access

    Cell-to-cell variability in viral infection means that cell population measurements may not be an accurate representation of the process. Using both experimental and modelling approaches the authors confirm this notion showing that influenza virus infections are variable processes affected by intrinsic and extrinsic noise.

    • Frank S. Heldt
    • , Sascha Y. Kupke
    •  & Timo Frensing

  • Article
    | Open Access

    GALgenes enhance their own transcription via the transcription factor Gal4p, and the number of Galp4 sites in a promoter is expected to strengthen the feedback. In this study, Hsuet al. show that instead the feedback loops are activated by genes that have frequent bursts of expression and fast RNA decay kinetics.

    • Chieh Hsu
    • , Simone Scherrer
    •  & Attila Becskei

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