Computer modelling articles within Nature Communications

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  • Article
    | Open Access

    The development of the human cerebellum is not well understood. Here, the authors analyse a large sample of neuroimaging scans from children and adolescents to develop growth models of the cerebellum which mirror age-related developmental trajectories of behaviour and function.

    • Carolin Gaiser
    • , Rick van der Vliet
    •  & Ryan L. Muetzel

  • Article
    | Open Access

    This work leverages a new diet database and six long term monitoring efforts of 361 taxa to build comparable pre- and post-heatwave ecosystem models. The study provides empirical demonstration of changes in ecosystem-wide patterns of energy flux and biomass in response to marine heatwaves.

    • Dylan G. E. Gomes
    • , James J. Ruzicka
    •  & Joshua D. Stewart

  • Article
    | Open Access

    Little is known about how malaria parasites adapt the speed of their development to their mosquito vectors. Using an evolutionary modelling framework, this study predicts that the metabolic status of mosquitoes shapes the parasites’ life-history strategies and transmission dynamics.

    • Paola Carrillo-Bustamante
    • , Giulia Costa
    •  & Elena A. Levashina

  • Article
    | Open Access

    The detoxification pathway photorespiration has been thought to be photoprotective in dynamic light. The authors report that, instead, growth in dynamic light buffers plants against photorespiratory lesions by reducing photosynthesis and inducing metabolite re-routing.

    • Thekla von Bismarck
    • , Philipp Wendering
    •  & Ute Armbruster

  • Article
    | Open Access

    Mature fields of engineering use physics-based models to design systems that work reliably the first time. Here the authors show how a similar approach can be used to design and build a cellular-scale system, protein synthesis, from scratch.

    • Akshay J. Maheshwari
    • , Jonathan Calles
    •  & Drew Endy

  • Article
    | Open Access

    Here, Seelbinder et al. show high Candida levels in cancer patients’ stool to correlate with greater metabolically flexibility but less robust bacterial communities and, combined with machine learning models to predict Candida levels from bacterial data, suggest that lactate producing bacteria may fuel Candida overgrowth in the gut during dysbiosis.

    • Bastian Seelbinder
    • , Zoltan Lohinai
    •  & Gianni Panagiotou

  • Article
    | Open Access

    HOXA9 plays an important role in acute myeloid leukaemia (AML), but its relevance for other blood malignancies is unclear. Here, the authors show that HOXA9 has a binary switch function that can clinically stratify AML patients, and model how the interactions with JAK2, TET2 and NOTCH impact myeloproliferative neoplasms.

    • Laure Talarmain
    • , Matthew A. Clarke
    •  & Benjamin A. Hall

  • Article
    | Open Access

    Communities of microbes play important roles in natural environments and hold great potential for deploying division-of-labor strategies in synthetic biology and bioproduction. Here, in a community of two competing E. coli strains, the authors show that the relative abundances of the strains can be stabilized and steered dynamically with remarkable precision by coupling the cells to an automated computer-controlled feedback-loop.

    • Joaquín Gutiérrez Mena
    • , Sant Kumar
    •  & Mustafa Khammash

  • Article
    | Open Access

    Genome-scale metabolic models have been widely used for quantitative exploration of the relation between genotype and phenotype. Here the authors present GECKO 2, an automated framework for continuous and version controlled update of enzyme-constrained models of metabolism, producing an interesting catalogue of high-quality models for diverse yeasts, bacteria and human metabolism, aiming to facilitate their use in basic science, metabolic engineering and synthetic biology purposes.

    • Iván Domenzain
    • , Benjamín Sánchez
    •  & Jens Nielsen

  • Article
    | Open Access

    Many diseases are caused by disruptions to the network of biochemical reactions that allow cells to respond to external signals. Here Nilsson et al develop a method to simulate cellular signaling using artificial neural networks to predict cellular responses and activities of signaling molecules.

    • Avlant Nilsson
    • , Joshua M. Peters
    •  & Douglas A. Lauffenburger

  • Article
    | Open Access

    Due to the complexity of the protein secretory pathway, strategy suitable for the production of a certain recombination protein cannot be generalized. Here, the authors construct a proteome-constrained genome-scale protein secretory model for yeast and show its application in the production of different misfolded or recombinant proteins.

    • Feiran Li
    • , Yu Chen
    •  & Jens Nielsen

  • Article
    | Open Access

    Developing predictive methods to identify patients with high risk of severe COVID-19 disease is of crucial importance. Authors show here that by measuring anti-SARS-CoV-2 antibody and cytokine levels at the time of hospital admission and integrating the data by unsupervised hierarchical clustering/machine learning, it is possible to predict unfavourable outcome.

    • Yvonne M. Mueller
    • , Thijs J. Schrama
    •  & Peter D. Katsikis

  • Article
    | Open Access

    Metabolically active organelles compete for cytosolic space and resources during metabolism rewiring. Here, the authors develop a computational model of yeast metabolism and resource allocation to predict condition- and compartment-specific proteome constraints that govern metabolic strategies.

    • Ibrahim E. Elsemman
    • , Angelica Rodriguez Prado
    •  & Bas Teusink

  • Article
    | Open Access

    Ordinary differential equation (ODE) models are widely used to understand multiple processes. Here the authors show how the concept of mini-batch optimization can be transferred from the field of Deep Learning to ODE modelling.

    • Paul Stapor
    • , Leonard Schmiester
    •  & Jan Hasenauer

  • Article
    | Open Access

    Many microbes grow diauxically, utilizing resources one at a time rather than simultaneously. This study developed a minimal model of diauxic microbial communities assembling in a serially diluted culture, providing testable predictions for the assembly of natural as well as synthetic communities of diauxically shifting microorganisms.

    • Zihan Wang
    • , Akshit Goyal
    •  & Sergei Maslov

  • Article
    | Open Access

    Collateral sensitivity-based antibiotic treatments may have the potential to limit the emergence of antimicrobial resistance. Here, the authors use mathematical modelling to study the effects of pathogen- and drug-specific characteristics for different treatment designs on bacterial population dynamics and resistance evolution.

    • Linda B. S. Aulin
    • , Apostolos Liakopoulos
    •  & J. G. Coen van Hasselt

  • Article
    | Open Access

    Cytosolic amino acid concentrations are carefully maintained, but how homeostasis occurs is unclear. Here, the authors show that amino acid transporters primarily determine intracellular amino acid levels and develop a model that predicts a perturbation response similar to experimental data.

    • Gregory Gauthier-Coles
    • , Jade Vennitti
    •  & Stefan Bröer

  • Article
    | Open Access

    Formulating metabolic networks mathematically can help researchers study metabolic diseases and optimize the production of industrially important molecules. Here, the authors propose a framework that allows to model eukaryotic metabolism considering gene expression and thermodynamic constraints.

    • Omid Oftadeh
    • , Pierre Salvy
    •  & Vassily Hatzimanikatis

  • Article
    | Open Access

    A promising strategy to increase product synthesis from bacteria uses inducible systems to switch metabolism to production. Here, the authors use models to show how engineering positive feedback loops into the genetic circuitry creates a switch that requires only temporary induction with a cheap nutrient to switch metabolism irreversibly, and so drastically reduce inducer use and cost.

    • Ahmad A. Mannan
    •  & Declan G. Bates

  • Article
    | Open Access

    Industrial sugarcane ethanol fermentations are accomplished by a microbial community dominated by S. cerevisiae and co-occurring bacteria. Here, the authors investigate how microbial community composition contributes to community function and reveal the role of acetaldehyde in improving yeast growth rate and ethanol production.

    • Felipe Senne de Oliveira Lino
    • , Djordje Bajic
    •  & Morten Otto Alexander Sommer

  • Article
    | Open Access

    Honey bee workers take on different tasks for the colony as they age. Here, the authors develop a method to extract a descriptor of the individuals’ social networks and show that interaction patterns predict task allocation and distinguish different developmental trajectories.

    • Benjamin Wild
    • , David M. Dormagen
    •  & Tim Landgraf

  • Article
    | Open Access

    Boolean Networks are a well-established model of biological networks, but usual interpretations can preclude the prediction of behaviours observed in quantitative systems. The authors introduce Most Permissive Boolean Networks, which are shown not to miss any behaviour achievable by the corresponding quantitative model.

    • Loïc Paulevé
    • , Juri Kolčák
    •  & Stefan Haar

  • Article
    | Open Access

    Successful application of microbial community for bioproduction relies on the selection of appropriate heterotroph and phototroph partners. Here, the authors construct community metabolic models to guide strain selection and experimentally validate metabolic exchanges that sustain the heterotrophs in minimal media.

    • Cristal Zuñiga
    • , Tingting Li
    •  & Karsten Zengler

  • Article
    | Open Access

    Single-cell technologies are increasingly prominent in clinical applications, but predictive modelling with such data in large cohorts has remained computationally challenging. We developed a new algorithm, ‘VoPo’, for predictive modelling and visualization of single cell data for translational applications.

    • Natalie Stanley
    • , Ina A. Stelzer
    •  & Nima Aghaeepour

  • Article
    | Open Access

    Current methods to generate sequence-function data at large scale are either technically complex or limited to specific applications. Here the authors introduce DNA-based phenotypic recording to overcome these limitations and enable deep learning for accurate prediction of function from sequence.

    • Simon Höllerer
    • , Laetitia Papaxanthos
    •  & Markus Jeschek

  • Article
    | Open Access

    Cellular signalling networks provide information to the cell, but the trade-off between accuracy of information transfer and energetic cost of doing so has not been assessed. Here, the authors investigate a MAPK signalling cascade in budding yeast and find that information is maximised per unit energetic cost.

    • Alexander Anders
    • , Bhaswar Ghosh
    •  & Victor Sourjik

  • Article
    | Open Access

    The association between leguminous plants and rhizobial bacteria is a paradigmatic example of a symbiosis driven by metabolic exchanges. Here, diCenzo et al. report the reconstruction and modelling of a genome-scale metabolic network of the plant Medicago truncatula nodulated by the bacterium Sinorhizobium meliloti.

    • George C. diCenzo
    • , Michelangelo Tesi
    •  & Marco Fondi

  • 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

    Macrophage activation is tightly regulated to maintain immune homeostasis, yet activation is also heterogeneous. Here, the authors show that macrophages coordinate activation by partitioning into two phenotypes that can nonlinearly amplify collective inflammatory cytokine production as a function of cell density.

    • Joseph J. Muldoon
    • , Yishan Chuang
    •  & Joshua N. Leonard

  • Article
    | Open Access

    Genome engineering will one day benefit from computational tools that can design genomes with desired functions. Here the authors develop computational design-simulate-test algorithms to design minimal genomes based on the whole-cell model of Mycoplasma genitalium.

    • Joshua Rees-Garbutt
    • , Oliver Chalkley
    •  & Claire Grierson

  • Article
    | Open Access

    Feedback mechanisms for synthetic gene circuits are necessary to provide robustness to external perturbations. Here the authors validate a biomolecular controller based on a sigma and anti-sigma factor to achieve stable gene expression in the face of external disturbances in an in vitro synthetic gene circuit.

    • Deepak K. Agrawal
    • , Ryan Marshall
    •  & Eduardo D Sontag

  • 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

    Membrane proteins have been implicated in cancers, but studying the downstream effects of their perturbation remains challenging. Here, the authors map the membrane protein-regulated network of 15 cancers, a resource for prognostic biomarker development and druggable target identification.

    • Chun-Yu Lin
    • , Chia-Hwa Lee
    •  & Jinn-Moon Yang

  • Article
    | Open Access

    Polycomb and Trithorax group proteins regulate silent and active gene expression states, but also allow poised states in pluripotent cells. Here the authors present a mathematical model that integrates data on Polycomb/ Trithorax biochemistry into a single coherent framework which predicts that poised chromatin is not bivalent as previously proposed, but is bistable, meaning that the system switches frequently between stable active and silent states.

    • Kim Sneppen
    •  & Leonie Ringrose

  • Article
    | Open Access

    Biological complexity has impeded our ability to predict the dynamics of mutualistic interactions. Here, the authors deduce a general rule to predict outcomes of mutualistic systems and introduce an approach that permits making predictions even in the absence of knowledge of mechanistic details.

    • Feilun Wu
    • , Allison J. Lopatkin
    •  & Lingchong You

  • Article
    | Open Access

    The catalytic efficiency of many enzymes is lower than the theoretical maximum. Here, the authors combine genome-scale metabolic modeling with population genetics models to simulate enzyme evolution, and find that strong epistasis limits turnover numbers due to diminishing returns of fitness gains.

    • David Heckmann
    • , Daniel C. Zielinski
    •  & Bernhard O. Palsson

  • Article
    | Open Access

    Tools from statistical physics can be used to investigate a large variety of fields ranging from economics to biology. Here the authors first adapt density-functional theory to predict the distributions of crowds in new environments and then validate their approach using groups of fruit flies.

    • J. Felipe Méndez-Valderrama
    • , Yunus A. Kinkhabwala
    •  & T. A. Arias

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