Explore the vast range of titles available.

The ecological forces that govern the assembly and stability of the human gut microbiota remain unresolved. We developed a generalizable model‐guided framework to predict higher‐dimensional consortia from time‐resolved measurements of lower‐order assemblages. This method was employed to decipher microbial interactions in a diverse human gut microbiome synthetic community. We show that pairwise interactions are major drivers of multi‐species community dynamics, as opposed to higher‐order interactions. The inferred ecological network exhibits a high proportion of negative and frequent positive interactions. Ecological drivers and responsive recipient species were discovered in the network. Our model demonstrated that a prevalent positive and negative interaction topology enables robust coexistence by implementing a negative feedback loop that balances disparities in monospecies fitness levels. We show that negative interactions could generate history‐dependent responses of initial species proportions that frequently do not originate from bistability. Measurements of extracellular metabolites illuminated the metabolic capabilities of monospecies and potential molecular basis of microbial interactions. In sum, these methods defined the ecological roles of major human‐associated intestinal species and illuminated design principles of microbial communities. Synopsis Analysis of microbial interactions in a synthetic human gut microbiome community shows that pairwise microbial interactions are major drivers of multi‐species community dynamics. The study reveals ecological drivers, metabolite hub species and ecologically sensitive organisms in the network. A data‐driven pipeline is used to construct a predictive dynamic model of a diverse anaerobic human gut microbiome community. Design principles of stable coexistence and history‐dependence are elucidated. Ecological roles and metabolite profiles are analyzed for each organism. The study highlights challenges in using phylogenetic and exo‐metabolomic “signals” to predict microbial interactions and community functions. Graphical Abstract Analysis of microbial interactions in a synthetic human gut microbiome community shows that pairwise microbial interactions are major drivers of multi‐species community dynamics. The study reveals ecological drivers, metabolite hub species and ecologically sensitive organisms in the network.

A central aim of cell biology was to understand the strategy of gene expression in response to the environment. Here, we study gene expression response to metabolic challenges in exponentially growing Escherichia coli using mass spectrometry. Despite enormous complexity in the details of the underlying regulatory network, we find that the proteome partitions into several coarse‐grained sectors, with each sector's total mass abundance exhibiting positive or negative linear relations with the growth rate. The growth rate‐dependent components of the proteome fractions comprise about half of the proteome by mass, and their mutual dependencies can be characterized by a simple flux model involving only two effective parameters. The success and apparent generality of this model arises from tight coordination between proteome partition and metabolism, suggesting a principle for resource allocation in proteome economy of the cell. This strategy of global gene regulation should serve as a basis for future studies on gene expression and constructing synthetic biological circuits. Coarse graining may be an effective approach to derive predictive phenomenological models for other ‘omics’ studies. Synopsis Quantitative relative and absolute protein abundance data allow the use of coarse‐graining analysis to reveal strategies of resource allocation by E. coli . A predictive, mathematical model of the proteome is constructed requiring only a few parameters. Coarse‐graining procedure makes proteomics data amenable to quantitative analysis. Five functionally distinct proteome sectors each exhibit linear relations with the growth rate. A simple flux model captures proteome‐wide responses accurately with few parameters. Proteome economy is shown to be a principle governing global gene regulation. Graphical Abstract Quantitative relative and absolute protein abundance data allow the use of coarse‐graining analysis to reveal strategies of resource allocation by E. coli . A predictive, mathematical model of the proteome is constructed requiring only a few parameters.

Morphogenesis in animal tissues is largely driven by actomyosin networks, through tensions generated by an active contractile process. Although the network components and their properties are known, and networks can be reconstituted in vitro, the requirements for contractility are still poorly understood. Here, we describe a theory that predicts whether an isotropic network will contract, expand, or conserve its dimensions. This analytical theory correctly predicts the behavior of simulated networks, consisting of filaments with varying combinations of connectors, and reveals conditions under which networks of rigid filaments are either contractile or expansile. Our results suggest that pulsatility is an intrinsic behavior of contractile networks if the filaments are not stable but turn over. The theory offers a unifying framework to think about mechanisms of contractions or expansion. It provides the foundation for studying a broad range of processes involving cytoskeletal networks and a basis for designing synthetic networks. Synopsis The contraction or expansion rates of disordered cytoskeletal networks is predicted based on the properties of the filaments, and the molecular motors and crosslinkers that link them. The prediction is calculated analytically for networks made of flexible, semi‐flexible (actin) and rigid (microtubule) filaments. It explains the combined contribution of crosslinkers and motors in producing contraction of actomyosin systems. The theory reveals new conditions to produce contractile or expansile cytoskeletal networks. It unifies previously proposed mechanisms of contraction into a common framework. Graphical Abstract The contraction or expansion rates of disordered cytoskeletal networks is predicted based on the properties of the filaments, and the molecular motors and crosslinkers that link them.

Murine dermis contains functionally and spatially distinct fibroblast lineages that cease to proliferate in early postnatal life. Here, we propose a model in which a negative feedback loop between extracellular matrix (ECM) deposition and fibroblast proliferation determines dermal architecture. Virtual‐tissue simulations of our model faithfully recapitulate dermal maturation, predicting a loss of spatial segregation of fibroblast lineages and dictating that fibroblast migration is only required for wound healing. To test this, we performed in vivo live imaging of dermal fibroblasts, which revealed that homeostatic tissue architecture is achieved without active cell migration. In contrast, both fibroblast proliferation and migration are key determinants of tissue repair following wounding. The results show that tissue‐scale coordination is driven by the interdependence of cell proliferation and ECM deposition, paving the way for identifying new therapeutic strategies to enhance skin regeneration. Synopsis In vivo live imaging of dermal fibroblasts combined with mathematical modeling shows that fibroblast behaviour switching between two distinct states—proliferating and depositing ECM—defines dermal architecture. These findings are relevant for identifying new therapeutic strategies for skin regeneration. Tissue‐scale coordination in murine dermis is driven by the interdependence of cell proliferation and ECM deposition. The tissue architecture is set by a negative feedback loop between ECM deposition/remodelling and proliferation. Fibroblast lineages lose segregation with age. Fibroblast migration is the critical discriminator between dermal development and wound healing. Graphical Abstract In vivo live imaging of dermal fibroblasts combined with mathematical modeling shows that fibroblast behaviour switching between two distinct states—proliferating and depositing ECM—defines dermal architecture. These findings are relevant for identifying new therapeutic strategies for skin regeneration.

Bacteria must constantly adapt their growth to changes in nutrient availability; yet despite large‐scale changes in protein expression associated with sensing, adaptation, and processing different environmental nutrients, simple growth laws connect the ribosome abundance and the growth rate. Here, we investigate the origin of these growth laws by analyzing the features of ribosomal regulation that coordinate proteome‐wide expression changes with cell growth in a variety of nutrient conditions in the model organism Escherichia coli . We identify supply‐driven feedforward activation of ribosomal protein synthesis as the key regulatory motif maximizing amino acid flux, and autonomously guiding a cell to achieve optimal growth in different environments. The growth laws emerge naturally from the robust regulatory strategy underlying growth rate control, irrespective of the details of the molecular implementation. The study highlights the interplay between phenomenological modeling and molecular mechanisms in uncovering fundamental operating constraints, with implications for endogenous and synthetic design of microorganisms. Graphical Abstract Building upon empirical “growth laws”, this Perspective discusses mechanisms that integrate protein synthesis with amino acid flux and metabolic control to guarantee optimal growth irrespective of the nutrient environment.

Understanding how the homeostasis of cellular size and composition is accomplished by different organisms is an outstanding challenge in biology. For exponentially growing Escherichia coli cells, it is long known that the size of cells exhibits a strong positive relation with their growth rates in different nutrient conditions. Here, we characterized cell sizes in a set of orthogonal growth limitations. We report that cell size and mass exhibit positive or negative dependences with growth rate depending on the growth limitation applied. In particular, synthesizing large amounts of “useless” proteins led to an inversion of the canonical, positive relation, with slow growing cells enlarged 7‐ to 8‐fold compared to cells growing at similar rates under nutrient limitation. Strikingly, this increase in cell size was accompanied by a 3‐ to 4‐fold increase in cellular DNA content at slow growth, reaching up to an amount equivalent to ~8 chromosomes per cell. Despite drastic changes in cell mass and macromolecular composition, cellular dry mass density remained constant. Our findings reveal an important role of protein synthesis in cell division control. Synopsis Protein overexpression inverts the well‐known positive relation of cell size and DNA content with growth rate under nutrient limitation, resulting in huge, slowly growing cells with high DNA content, but with remarkably constant cellular dry mass density. Protein overexpression leads to an inverted growth rate dependence of cell size, with slow growing cells being even larger than the fastest growing wild‐type cells cultured in rich media. Decoupled from growth rate, changes in cell size are accompanied by comparable changes in cellular DNA content. Despite profound changes in cell size and macromolecular composition, cellular dry mass density remains remarkably constant, as protein overexpression does not result in molecular crowding. Graphical Abstract Protein overexpression inverts the well‐known positive relation of cell size and DNA content with growth rate under nutrient limitation, resulting in huge, slowly growing cells with high DNA content, but with remarkably constant cellular dry mass density.

Transient versus sustained ERK MAP kinase (MAPK) activation dynamics induce proliferation versus differentiation in response to epidermal (EGF) or nerve (NGF) growth factors in PC‐12 cells. Duration of ERK activation has therefore been proposed to specify cell fate decisions. Using a biosensor to measure ERK activation dynamics in single living cells reveals that sustained EGF/NGF application leads to a heterogeneous mix of transient and sustained ERK activation dynamics in distinct cells of the population, different than the population average. EGF biases toward transient, while NGF biases toward sustained ERK activation responses. In contrast, pulsed growth factor application can repeatedly and homogeneously trigger ERK activity transients across the cell population. These datasets enable mathematical modeling to reveal salient features inherent to the MAPK network. Ultimately, this predicts pulsed growth factor stimulation regimes that can bypass the typical feedback activation to rewire the system toward cell differentiation irrespective of growth factor identity. Synopsis Dynamic manipulation of ERK signaling at the single cell level reveals new features of the MAPK network topology and induces robust signaling responses that rewire cell fate decision independently of growth factor identity. Sustained growth factor stimulation induces heterogeneous ERK dynamics, while pulsed growth factor stimulation homogenizes ERK dynamics in a cell population. Dynamic manipulation of ERK signaling using growth factor pulses in living cells, reveals novel features of MAPK network topology and enhances previous mathematical models of MAPK signaling. Pulsed growth factor stimulation at adequate frequencies predicted by an updated model of MAPK signaling rewires cell fate. Graphical Abstract Dynamic manipulation of ERK signaling at the single cell level reveals new features of the MAPK network topology and induces robust signaling responses that rewire cell fate decision independently of growth factor identity.

The cell cycle is canonically described as a series of four consecutive phases: G1, S, G2, and M. In single cells, the duration of each phase varies, but the quantitative laws that govern phase durations are not well understood. Using time‐lapse microscopy, we found that each phase duration follows an Erlang distribution and is statistically independent from other phases. We challenged this observation by perturbing phase durations through oncogene activation, inhibition of DNA synthesis, reduced temperature, and DNA damage. Despite large changes in durations in cell populations, phase durations remained uncoupled in individual cells. These results suggested that the independence of phase durations may arise from a large number of molecular factors that each exerts a minor influence on the rate of cell cycle progression. We tested this model by experimentally forcing phase coupling through inhibition of cyclin‐dependent kinase 2 (CDK2) or overexpression of cyclin D. Our work provides an explanation for the historical observation that phase durations are both inherited and independent and suggests how cell cycle progression may be altered in disease states. Synopsis Time‐lapse imaging of cell‐cycle phase transitions reveals that phase durations are uncoupled and can be modeled as an Erlang process. Phase coupling can be forced by perturbing a strong cell‐cycle regulator acting on multiple phases. Cell‐cycle phase durations are uncoupled in three human cell lines. Each cell‐cycle phase proceeds like a sequence of memoryless steps that can be modeled as an Erlang process. A “many‐for‐all model”, in which large number of factors each exerting minor influence on phase duration, explains the stochastic but heritable nature of cell cycle progression. Coupling between cell‐cycle phases can be introduced by perturbing a cell‐cycle regulator of multiple phases. Graphical Abstract Time‐lapse imaging of cell‐cycle phase transitions reveals that phase durations are uncoupled and can be modeled as an Erlang process. Phase coupling can be forced by perturbing a strong cell‐cycle regulator acting on multiple phases. This article has been featured on the April cover of the journal.

Fluctuations in intracellular molecule abundance can lead to distinct, coexisting phenotypes in isogenic populations. Although metabolism continuously adapts to unpredictable environmental changes, and although bistability was found in certain substrate‐uptake pathways, central carbon metabolism is thought to operate deterministically. Here, we combine experiment and theory to demonstrate that a clonal Escherichia coli population splits into two stochastically generated phenotypic subpopulations after glucose‐gluconeogenic substrate shifts. Most cells refrain from growth, entering a dormant persister state that manifests as a lag phase in the population growth curve. The subpopulation‐generating mechanism resides at the metabolic core, overarches the metabolic and transcriptional networks, and only allows the growth of cells initially achieving sufficiently high gluconeogenic flux. Thus, central metabolism does not ensure the gluconeogenic growth of individual cells, but uses a population‐level adaptation resulting in responsive diversification upon nutrient changes. Synopsis Upon nutrient change, a homogeneous E. coli  population can split into a growing and a non‐growing persister phenotype. Stochastic variation in metabolic flux is responsible for this responsive diversification. Responsive diversification offers an explanation for lag phases in bacterial cultures Flux‐induced phenotypic bistability generalizes to central metabolism Conditional bet‐hedging balances fast glycolytic growth and ability for gluconeogenic growth Limited carbon influx is a major trigger for persistence Graphical Abstract Upon nutrient change, a homogeneous E. coli  population can split into a growing and a non‐growing persister phenotype. Stochastic variation in metabolic flux is responsible for this responsive diversification.

Treatment of BRAF ‐mutant melanomas with MAP kinase pathway inhibitors is paradigmatic of the promise of precision cancer therapy but also highlights problems with drug resistance that limit patient benefit. We use live‐cell imaging, single‐cell analysis, and molecular profiling to show that exposure of tumor cells to RAF/MEK inhibitors elicits a heterogeneous response in which some cells die, some arrest, and the remainder adapt to drug. Drug‐adapted cells up‐regulate markers of the neural crest (e.g., NGFR), a melanocyte precursor, and grow slowly. This phenotype is transiently stable, reverting to the drug‐naïve state within 9 days of drug withdrawal. Transcriptional profiling of cell lines and human tumors implicates a c‐Jun/ECM/FAK/Src cascade in de‐differentiation in about one‐third of cell lines studied; drug‐induced changes in c‐Jun and NGFR levels are also observed in xenograft and human tumors. Drugs targeting the c‐Jun/ECM/FAK/Src cascade as well as BET bromodomain inhibitors increase the maximum effect ( E max ) of RAF/MEK kinase inhibitors by promoting cell killing. Thus, analysis of reversible drug resistance at a single‐cell level identifies signaling pathways and inhibitory drugs missed by assays that focus on cell populations. Synopsis Responses of BRAF V600E melanoma cells to vemurafenib were studied at the single‐cell level using live‐cell imaging and by transcriptional and biochemical profiling to uncover a slowly dividing, de‐differentiated cell state associated with drug resistance but inhibitable by drug combinations. Cell‐to‐cell variability in BRAF V600E melanomas generates drug‐tolerant subpopulations. The drug‐tolerant, slowly dividing NFGR High state is transiently heritable. Drugs against a proposed c‐Jun/ECM/FAK/Src cascade block acquisition of this phenotype. The NGFR High drug‐tolerant state is also blocked by BET inhibitors in vitro and in vivo . Drugs that block adaptation by cell subpopulations increase cell killing by RAF/MEK inhibitors. LINCS‐compliant data and methods are freely available to enhance reproducibility. Graphical Abstract Responses of BRAF V600E melanoma cells to vemurafenib were studied at the single‐cell level using live‐cell imaging and by transcriptional and biochemical profiling to uncover a slowly dividing, de‐differentiated cell state associated with drug resistance but inhibitable by drug combinations.