Biochemical networks articles within Nature Communications

Featured

  • Article
    | Open Access

    Bacteria grown on two carbon sources either consume both sources simultaneously or consume them sequentially. Here the authors use a metabolic network model of E. coli to show that optimal protein resource allocation and topological features of the network can explain the choice of carbon acquisition.

    • Xin Wang
    • , Kang Xia
    •  & Chao Tang

  • Article
    | Open Access

    Combination therapy holds great promise, but discovery remains challenging. Here, the authors propose a method to identify efficacious drug combinations for specific diseases, and find that successful combinations tend to target separate neighbourhoods of the disease module in the human interactome.

    • Feixiong Cheng
    • , István A. Kovács
    •  & Albert-László Barabási

  • Article
    | Open Access

    Inferring direct protein−protein interactions (PPIs) and modules in PPI networks remains a challenge. Here, the authors introduce an algorithm to infer potential direct PPIs from quantitative proteomic AP-MS data by identifying enriched interactions of each bait relative to the other baits.

    • Mihaela E. Sardiu
    • , Joshua M. Gilmore
    •  & Michael P. Washburn

  • Article
    | Open Access

    Serine synthesis from glucose is required even when serine is available from the environment. Here, the authors explain this paradox by showing that the enzyme PHGDH enables nucleotide synthesis by coordinating anabolic fluxes related to central carbon metabolism, independent of its role in serine production.

    • Michael A. Reid
    • , Annamarie E. Allen
    •  & Jason W. Locasale

  • 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

    Tumors often exhibit a pH gradient, with an acidic extracellular space and alkaline cytoplasm. Here the authors develop a computational model to show how alkaline pHi supports changes inherent to cancer cell metabolism and acidification disables these adaptations, and demonstrate the effect of acidic pHi on breast cancer cell survival.

    • Erez Persi
    • , Miquel Duran-Frigola
    •  & Eytan Ruppin

  • Article
    | Open Access

    Single cell growth rate variability has been difficult to understand. Here, the authors apply a generalization of flux balance analysis to single cells based on maximum entropy modeling, and find that growth rate fluctuations of E. coli reflect metabolic flux variability and growth sub-optimality, in turn highlighting information costs for growth optimization.

    • Daniele De Martino
    • , Anna MC Andersson
    •  & Gašper Tkačik

  • Article
    | Open Access

    Robust perfect adaptation (RPA), the ability of a system to return to its pre-stimulus state in the presence of a new signal, enables organisms to respond to further changes in stimuli. Here, the authors identify the modular structure of the full set of network topologies that can confer RPA on complex networks.

    • Robyn P. Araujo
    •  & Lance A. Liotta

  • Article
    | Open Access

    Sign epistasis clearly constrains evolution, but its causes are difficult to decipher. Here, the authors study epistasis in a signalling cascade, and arrive at a general criterion and understanding of sign epistasis as arising from the inherent hierarchy between signalling cascade components.

    • Philippe Nghe
    • , Manjunatha Kogenaru
    •  & Sander J. Tans

  • Article
    | Open Access

    IgG glycosylation is an important factor in immune function, yet the molecular details of protein glycosylation remain poorly understood. The data-driven approach presented here uses large-scale plasma IgG mass spectrometry measurements to infer new biochemical reactions in the glycosylation pathway.

    • Elisa Benedetti
    • , Maja Pučić-Baković
    •  & Jan Krumsiek

  • Article
    | Open Access

    Although networks of interacting genes and metabolic reactions are interdependent, they have largely been treated as separate systems. Here the authors apply a statistical framework for interdependent networks to E. coli, and show that it is sensitive to gene and protein perturbations but robust against metabolic changes.

    • David F. Klosik
    • , Anne Grimbs
    •  & Marc-Thorsten Hütt

  • Article
    | Open Access

    Metabolites act as enzyme inhibitors, but their global impact on metabolism has scarcely been considered. Here, the authors generate a human genome-wide metabolite-enzyme inhibition network, and find that inhibition occurs largely due to limited structural diversity of metabolites, leading to a global constraint on metabolism which subcellular compartmentalization minimizes.

    • Mohammad Tauqeer Alam
    • , Viridiana Olin-Sandoval
    •  & Markus Ralser

  • Article
    | Open Access

    Large-scale metabolic models of organisms from microbes to mammals can provide great insight into cellular function, but their analysis remains challenging. Here, the authors provide an approximate analytic method to estimate the feasible solution space for the flux vectors of metabolic networks, enabling more accurate analysis under a wide range of conditions of interest.

    • Alfredo Braunstein
    • , Anna Paola Muntoni
    •  & Andrea Pagnani

  • Article
    | Open Access

    Targeting virulence rather than bacterial growth is less likely to select for antibiotic resistance, but many possible targets function in both processes. Here, the authors reconstruct a genome-scale metabolic network ofP. aeruginosastrain PA14 and update that of strain PAO1, which, together with mutant screens, enable them to identify genes uniquely critical for virulence factor production.

    • Jennifer A. Bartell
    • , Anna S. Blazier
    •  & Jason A. Papin

  • Article
    | Open Access

    Understanding of dysregulation in cancers requires knowledge, beyond cancer genomes, of the interactions of cancer-associated proteins. Here, the authors use high-throughput, time-resolved FRET to map protein–protein interactions to establish a lung cancer protein network, and demonstrate its utility in revealing new oncogenic pathways and connectivity of tumour suppressors with druggable targets.

    • Zenggang Li
    • , Andrei A. Ivanov
    •  & Haian Fu

  • Article
    | Open Access

    Nonlinearity in synthetic molecular circuits is usually achieved by manipulation of network topology or of production kinetics. Here, the authors achieve bistability and other nonlinear behaviours by manipulating the individual degradation rate laws of circuit components using saturable pathways.

    • Kevin Montagne
    • , Guillaume Gines
    •  & Yannick Rondelez

  • Article
    | Open Access

    Translating omics data sets into biological insight is one of the great challenges of our time. Here, the authors make headway by synchronising pairs of omics data types via invariants across conditions and by integrating datasets into a genome-scale model of E. coli metabolism and gene expression.

    • Ali Ebrahim
    • , Elizabeth Brunk
    •  & Bernhard O. Palsson

  • Article
    | Open Access

    Absolute concentration robustness (ACR), independence of the steady-state concentration of a molecule from the environment, is difficult to predict. Here, the authors derive a network structure-based necessary condition for ACR, and suggest that metabolites satisfying the condition are prevalent.

    • Jeanne M. O. Eloundou-Mbebi
    • , Anika Küken
    •  & Zoran Nikoloski

  • Article
    | Open Access

    How genetic diversity generates complex phenotypes along a continuum remains a fundamental question of biology. Here—applying the emerging SWATH proteomics technology—the authors describe a proteome wide association study (PWAS) of Drosophila wing size and identify functional protein clusters associated with this trait.

    • Hirokazu Okada
    • , H. Alexander Ebhardt
    •  & Ernst Hafen

  • Article
    | Open Access

    Microbes survive in dynamic environments by modulating their intracellular metabolism. Here, the authors reveal that mycobacteria employ a rheostat-like mechanism to regulate carbon flux between the oxidative TCA cycle and the glyoxylate shunt during glucose-acetate diauxic shift.

    • Paul Murima
    • , Michael Zimmermann
    •  & John D. McKinney

  • Article
    | Open Access

    Complex networks, including physical, biological and social systems are ubiquitous, but understanding of how to control them is elusive. Here Wang et al. develop a framework based on the concept of attractor networks to facilitate the study of controllability of nonlinear dynamics in complex systems.

    • Le-Zhi Wang
    • , Ri-Qi Su
    •  & Ying-Cheng Lai

  • Article
    | Open Access

    Sigma factors are regulatory proteins that reprogram the bacterial RNA polymerase in response to stress conditions to transcribe certain genes, including those for other sigma factors. Here, Chauhan et al. describe the complete sigma factor regulatory network of the pathogen Mycobacterium tuberculosis.

    • Rinki Chauhan
    • , Janani Ravi
    •  & Maria Laura Gennaro

  • Article
    | Open Access

    Attempts to predict novel use for existing drugs rarely consider information on the impact on the genes perturbed in a given disease. Here, the authors present a novel network-based drug-disease proximity measure that provides insight on gene specific therapeutic effect of drugs and may facilitate drug repurposing.

    • Emre Guney
    • , Jörg Menche
    •  & Albert-László Barábasi

  • Article
    | Open Access

    Infection remains a leading cause of morbidity and mortality in neonates worldwide. Here the authors report disproportionate immune stimulatory, co-inhibitory and metabolic pathway responses that specifically mark bacterial infection and can be used to predict sepsis in neonatal patients at the first clinical signs of infection.

    • Claire L. Smith
    • , Paul Dickinson
    •  & Peter Ghazal

  • Article |

    Identifying functionally important features of complex biological networks is computationally challenging. Ganter et al.develop a probabilistic framework that uses recurrent metabolite patterns to predict the properties and existence of reactions within a genome-scale metabolic network.

    • Mathias Ganter
    • , Hans-Michael Kaltenbach
    •  & Jörg Stelling

  • Article
    | Open Access

    Experience-dependent plasticity and functional adaptation are thought to be restricted to the central nervous and immune systems. This study shows that long-lasting experience-dependent plasticity is a key feature of endocrine cell networks, allowing improved tissue function and hormone output following repeat demand.

    • David J. Hodson
    • , Marie Schaeffer
    •  & Patrice Mollard

Browse broader subjects

Browse Biochemical networks across other nature.com journals