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At single-cell resolution, Tarkhov et al. delineate stochastic and co-regulated components of epigenetic aging, revealing a simultaneous loss of regulation at the epigenetic and transcriptional levels in aging.

One-shot tissue dynamics reconstruction can infer changes in tissue composition over time, from single-time-point spatial proteomics of human cancers.

Plasmid copy number and gene circuit design together shape how genetic mutations emerge at the phenotypic level in bacteria. Here the authors characterize how the interplay of gene dosage via plasmid copy number and regulatory architecture affect the phenotypic mutation rate.

Vinyard et al. present a generative method to model cell dynamics using neural stochastic differential equations that learn state-dependent drift and diffusion, outperforming existing approaches and enabling perturbation studies of development and disease.

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.

Prior work on antibiotic resistance focused on genetic changes. In this work, authors analysed heterogeneous responses of isogenic bacterial cells to antibiotics, revealing heritable phenotypic resistance that selectively enriches robust lineages in populations.

Replication timing reflects the coordination of origin firing and fork progression to preserve genome integrity. Here, the authors show that a high-resolution model of replication timing captures genomic features linked to replication stress and chromatin structure.

Longevity research aims to extend lifespan and reduce sickspan in aging. Here, the authors show that only interventions that steepen survival curves can compress the sickspan relative to lifespan.

Circadian clocks enable organisms to anticipate daily cycles, while being robust to molecular and environmental noise. Here, Eremina et al. show how the cyanobacterial clock buffers genetic and environmental perturbations through its core phosphorylation loop, and demonstrate that known clock regulators are dispensable for clock robustness.

What makes a transcription factor (TF) binding site “strong”: slow TF dissociation, or fast TF association? Kandavalli et al found that stronger sites had both slower dissociation and faster association compared to weaker sites in vivo.

Clonal hematopoiesis becomes increasingly common with age. Here the authors track stem cell dynamics in monozygotic twins and provide evidence that clonal hematopoiesis in later life reflects weak selection conferred by stem cell variation before birth.

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.

Alternative promoters differ in their expression patterns, whose mechanisms are not well understood. Here the authors show that alternative promoters of a Drosophila embryonic gene hunchback are regulated by different action modes of two enhancers.

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.

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.

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.

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.

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.

One of the underlying causes of aging is the accumulation of senescent cells, but their turnover rates and dynamics during ageing are unknown. Here the authors measure and model senescent cell production and removal and explore implications for mortality.

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.

Here the authors explore the distributional differences expected from distinct biophysical models of transcription and show how measurements from single-cell genomics experiments can shed light on the underlying biological processes.

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.

By inducing changes in surrounding tissue, mutant intestinal stem cells create an unfavourable niche environment that gives them a competitive advantage over non-mutant neighbours.

A longitudinal analysis of viral expansion and clearance rates in 60 individuals sampled daily during acute infection reveals high inter-individual variation in infectious virus shedding, which may contribute to superspreading.

Moving livestock is essential to the industry, but such mobility can spread disease. Considering three livestock diseases in the UK, this study finds that movement controls should be matched to the consequences of a disease and, crucially, that optimal movement bans are often far shorter than allowed under existing policy.

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.

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.

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.

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.

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.

DNA replication in higher eukaryotes is a complex process occurring in a complex genome environment. Here the authors present a model of DNA replication that incorporates random loop chromatin folding and domino-like fork progression reproducing the spatial and temporal characteristics of S-phase.

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.

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.

It is well known that organisms profit from adapting to their environment. A study of stochastic adaptation dynamics shows that this comes at the expense of adaptive speed and accuracy—providing a framework for understanding adaptation in noisy biological systems.

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.

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.

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.

Signalling responses are marked by substantial cell-to-cell variability. Here, the authors propose an information theoretic framework that accounts for multiple inputs and temporal dynamics to analyse how signals flow through shared network components.

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.

Gene regulatory circuits (GRCs) regulate many biological processes including cell cycle, cell differentiation, and phenotypic switching. Stochasticity in the gene expression impacts the dynamics and functions of such GRCs. Vivek Kohar and Mingyang Lu from Jackson Laboratory have developed a systems-biology modeling method stochastic random circuit perturbation (sRACIPE), which takes the GRC topology as the only input, and simulates an ensemble of models with random kinetic parameters at multiple noise levels. Statistical analysis of the generated gene expressions reveals the basin of attraction and stability of various phenotypic states and their changes associated with intrinsic and extrinsic noises. Application of the method to single cell expression data from synthetic circuits and epithelial-mesenchymal transition in squamous cell carcinoma shows its potential in yielding new insights on the structure and function of gene regulatory networks.

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).

By stochastically sampling cells in groups of ten, the authors identify transcriptional programs with strong cell-to-cell expression differences thus allowing them to study endogenous heterogeneities in single cells.

Epigenetic clocks estimate biological age; however, the underlying processes are incompletely understood. Here the authors developed a model that describes methylation changes at the cellular level to provide a biologically interpretable predictor of epigenetic age. They reveal acceleration and bias components, and links with health traits.