Biochemical networks articles within Nature Communications

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  • Article
    | Open Access

    Aberrant signalling pathway activity is relevant for tumour growth and resistance to therapy, but remains hard to understand and target. Here, the authors develop VESPA, a phosphoproteomics-based machine learning algorithm that can elucidate response and adaptation to drug perturbations in cancer signalling pathways.

    • George Rosenberger
    • , Wenxue Li
    •  & Andrea Califano

  • Article
    | Open Access

    Analysis of newly synthesized proteins upon perturbation can provide detailed insights into immediate proteome remodeling, which drives cellular responses. Here, the authors report an optimized semi-automated workflow for the quantitative analysis of the newly synthesized proteome.

    • Toman Borteçen
    • , Torsten Müller
    •  & Jeroen Krijgsveld

  • Article
    | Open Access

    In this work, Bay et al describe the construction of the first genome-scale metabolic model for the parasitic whipworm, Trichuris muris and use it to identify novel metabolic pathways and predict critical enzymes and essential metabolites for worm survival.

    • Ömer F. Bay
    • , Kelly S. Hayes
    •  & Ian S. Roberts

  • Article
    | Open Access

    The use of automated tools to reconstruct lipid metabolic pathways is not warranted in plants. Here, the authors construct Plant Lipid Module for Arabidopsis rosette using constraint-based modeling, demonstrate its integration in other plant metabolic models, and use it to dissect the genetic architecture of lipid metabolism.

    • Sandra Correa Córdoba
    • , Hao Tong
    •  & Zoran Nikoloski

  • Article
    | Open Access

    Quantifying the contribution of individual molecular components to complex cellular processes is a grand challenge in systems biology. Here, the authors present a general theoretical framework (Functional Decomposition of Metabolism, FDM) to quantify the contribution of every metabolic reaction to metabolic functions, e.g. the synthesis of biomass building blocks.

    • Matteo Mori
    • , Chuankai Cheng
    •  & Terence Hwa

  • Article
    | Open Access

    The authors present a workflow integrating metabolic perturbations with protein structural analysis to identify drug off-targets, demonstrating how combining machine learning methods with mechanistic analyses can benefit off-target identification.

    • Sourav Chowdhury
    • , Daniel C. Zielinski
    •  & Eugene I. Shakhnovich

  • Article
    | Open Access

    At the molecular level, the evolution of life is driven by the generation and diversification of adaptation mechanisms. Here Araujo and Liotta identify definitive and universal structural requirements for adaptation via intermolecular interactions.

    • Robyn P. Araujo
    •  & Lance A. Liotta

  • Article
    | Open Access

    Living things rely on extremely sensitive molecular circuits. Here, authors uncover a universal structural limit on kinetic scheme sensitivity, with implications for gene regulation & the functions of condensates.

    • Jeremy A. Owen
    •  & Jordan M. Horowitz

  • Article
    | Open Access

    Here, the authors present a method to build genetically personalised metabolic models across tissues to estimate individualised reaction fluxes. A fluxome-wide association study in UK Biobank identifies fluxes associated with metabolites and coronary artery disease.

    • Carles Foguet
    • , Yu Xu
    •  & Michael Inouye

  • Article
    | Open Access

    Protein networks have been widely explored but most binding affinities remain unknown, limiting the quantitative interpretation of interactomes. Here the authors measure affinities of 65,000 interactions involving human PDZ domains and target sequence motifs relevant for viral infection and cancer.

    • Gergo Gogl
    • , Boglarka Zambo
    •  & Gilles Travé

  • Article
    | Open Access

    Autophagy can selectively target cargo for degradation. Here the authors map the proximal interactome of ATG8-paralogs LC3B and LC3C uncovering an LC3C-Endocytic-Associated-Pathway that selectively recruits internalized plasma membrane cargo, Met and transferrin receptors, to nascent autophagosomes.

    • Paula P. Coelho
    • , Geoffrey G. Hesketh
    •  & Morag Park

  • 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

    Mechanistic models of how single cells respond to different perturbations can help integrate disparate big data sets or predict response to varied drug combinations. Here the authors develop a scalable, open-source pipeline for constructing and simulating large-scale, single-cell mechanistic models, an important building block for clinically-predictive mechanistic models and interpretable big data integration.

    • Cemal Erdem
    • , Arnab Mutsuddy
    •  & Marc R. Birtwistle

  • Article
    | Open Access

    Stable-isotope tracing allows quantifying metabolic activity by measuring isotopically labeled metabolites, but its metabolome coverage has been limited. Here, the authors develop a global isotope tracing approach with metabolome-wide coverage and use it to characterize metabolic activities in aging Drosophila.

    • Ruohong Wang
    • , Yandong Yin
    •  & Zheng-Jiang Zhu

  • 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

    In E. coli, FtsA and FtsZ control the place and time of cell division. Here, the authors use in vitro experiments to show how FtsA can follow FtsZ treadmilling and that downstream proteins form dynamic copolymers with FtsA to initiate division.

    • Philipp Radler
    • , Natalia Baranova
    •  & Martin Loose

  • Article
    | Open Access

    “Mapping the dark matter of metabolism remains an open challenge that can be addressed globally and systematically by existing computational solutions. Here the authors present ATLASx, a repository of known and predicted enzymatic reaction, connecting millions of compounds to help synthetic biologists and metabolic engineers to design and explore metabolic pathways.”

    • Homa MohammadiPeyhani
    • , Jasmin Hafner
    •  & Vassily Hatzimanikatis

  • 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

    The gut microbiota harbours neuroactive potential with links to neurological disorders. Here, the authors apply global metabolomics with an integrated annotation strategy to comparatively profile fecal, blood serum and cerebral cortical brain tissues of eight-week-old germ-free mice vs. age-matched specific-pathogen-free mice, providing a snapshot of the metabolome status linked to the gut-brain axis.

    • Yunjia Lai
    • , Chih-Wei Liu
    •  & Kun Lu

  • Article
    | Open Access

    Complex biomolecular networks are fundamental to the functioning of living systems, both at the cellular level and beyond. In this paper, the authors develop a systems framework to elucidate the interplay of networks and the spatial localisation of network components.

    • Govind Menon
    •  & J. Krishnan

  • Article
    | Open Access

    Boolean networks allow a simplified representation of interactions. Here, the authors systematically analyze regulation in dozens of biological Boolean networks, finding mathematical regularities that suggest biological systems could be controlled through a relatively small number of components.

    • Enrico Borriello
    •  & Bryan C. Daniels

  • 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

    Evolution selects for the fittest but must operate within the realm of the physically possible. Here, the authors present a theoretical framework that allows them to explore how ten abiotic constraints can shape the operation, regulation, and adaptation of metabolism in E. coli.

    • Amir Akbari
    • , James T. Yurkovich
    •  & Bernhard O. Palsson

  • Article
    | Open Access

    The top down cheminformatics method is usually used for the reconstitution of heterologous pathway to produce plant natural products. Here, the authors report a bottom up computational workflow for the identification of potential products and the enzymes required to make them in a noscapine pathway in yeast.

    • Jasmin Hafner
    • , James Payne
    •  & Christina Smolke

  • Article
    | Open Access

    The SRC Homology 3 (SH3) domains mediate protein–protein interactions (PPIs). Here, the authors assess the SH3-mediated PPIs in yeast, and show that the identity of the protein itself and the position of the SH3 both affect the interaction specificity and thus the PPI-dependent cellular functions.

    • Ugo Dionne
    • , Émilie Bourgault
    •  & Christian R. Landry

  • Article
    | Open Access

    Developing effective drugs for Alzheimer’s disease (AD), the most common cause of dementia, has been difficult because of complicated pathogenesis. Here, the authors report an efficient network-based drug-screening platform developed by integrating mathematical modeling and the pathological features of human cerebral organoids.

    • Jong-Chan Park
    • , So-Yeong Jang
    •  & Inhee Mook-Jung

  • Perspective
    | Open Access

    The IMEx consortium provides one of the largest resources of curated, experimentally verified molecular interaction data. Here, the authors review how IMEx evolved into a fundamental resource for life scientists and describe how IMEx data can support biomedical research.

    • Pablo Porras
    • , Elisabet Barrera
    •  & Sandra Orchard

  • Article
    | Open Access

    The protein translation machinery is the most expensive cellular subsystem in fast growing bacteria. Providing a detailed mechanistic model for this complex system, the authors show that the translation machinery components are expressed such that their combined cost to the cell is minimal.

    • Xiao-Pan Hu
    • , Hugo Dourado
    •  & Martin J. Lercher

  • Article
    | Open Access

    Existing fluorescent protein-based sensor measurements are limited to 4 or fewer simultaneously recorded modalities due to spectral overlap. Here the authors introduce Multiplexed Optical Sensors in Arrayed Islands of Cells (MOSAIC), which enables parallel recording of tens of physiological parameters using dense arrays of cell islands, each expressing a different fluorescent sensor.

    • Christopher A. Werley
    • , Stefano Boccardo
    •  & Adam E. Cohen

  • Article
    | Open Access

    Current machine learning classifiers have been applied to whole-genome sequencing data to identify determinants of antimicrobial resistance, but they lack interpretability. Here the authors present a metabolic machine learning classifier that uses flux balance analysis to estimate the biochemical effects of alleles.

    • Erol S. Kavvas
    • , Laurence Yang
    •  & Bernhard O. Palsson

  • Article
    | Open Access

    Genome-scale models of microbial metabolism largely ignore reaction kinetics. Here, the authors develop a general mathematical framework for modeling cellular growth with explicit non-linear reaction kinetics and use it to glean insights into the principles of cellular resource allocation and growth.

    • Hugo Dourado
    •  & Martin J. Lercher

  • Article
    | Open Access

    Complex diseases often share genetic determinants and symptoms, but the mechanistic basis of disease interactions remains elusive. Here, the authors propose a network topological measure to identify proteins linking complex diseases in the interactome, and identify mediators between COPD and asthma.

    • Enrico Maiorino
    • , Seung Han Baek
    •  & Amitabh Sharma

  • Article
    | Open Access

    The secretory pathway is used in the production of most biopharmaceuticals, but the associated biosynthetic costs are little understood. Here, the authors integrate the core secretory pathway into genome-scale metabolic models of human, mouse, and CHO cells, enabling in silico analysis.

    • Jahir M. Gutierrez
    • , Amir Feizi
    •  & Nathan E. Lewis

  • Article
    | Open Access

    There are many examples of cell populations exhibiting density-dependent collective oscillatory behaviour. Here, the authors show that sustained collective oscillations emerge when cells anticipate variation in signal and attempt to amplify it, a property that can be linked to adaptation.

    • Shou-Wen Wang
    •  & Lei-Han Tang

  • Article
    | Open Access

    Microbial respiration releases carbon from the soil. Here, the authors estimate bacterial carbon use efficiency in soils for over 200 species using constraint-based modeling, incorporate the values into an ecosystem model, and find that shifts in community composition may impact carbon storage.

    • Mustafa Saifuddin
    • , Jennifer M. Bhatnagar
    •  & Adrien C. Finzi

  • Article
    | Open Access

    The fraction of protein-protein interactions (PPIs) that can be disrupted without fitness effect is unknown. Here, the authors model how disease-causing mutations and common mutations carried by healthy people perturb the interactome, and estimate that <20% of human PPIs are completely dispensable.

    • Mohamed Ghadie
    •  & Yu Xia

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