Biochemical reaction networks

  • Article
    | Open Access

    Glycomics can uncover important molecular changes but measured glycans are highly interconnected and incompatible with common statistical methods, introducing pitfalls during analysis. Here, the authors develop an approach to identify glycan dependencies across samples to facilitate comparative glycomics.

    • Bokan Bao
    • , Benjamin P. Kellman
    •  & Nathan E. Lewis
  • Article
    | Open Access

    The interplay between human diet and the gut microbiome is complex. Here, the authors present a model of human-microbiome interaction that can predict how phenolic compounds are metabolized by the human gut microbiome, identifying diet-specific metabolites in children of varied clinical conditions.

    • Telmo Blasco
    • , Sergio Pérez-Burillo
    •  & Francisco J. Planes
  • 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

    Biochemistry combined with biophysical measurements and mathematical modeling offer insight into the mechanism by which the cotranslational chaperone, nascent polypeptide-associated complex (NAC), modulates substrate selection by signal recognition particle (SRP) and reduces aberrant, nonspecific targeting of ribosomes to the ER.

    • Hao-Hsuan Hsieh
    • , Jae Ho Lee
    •  & Shu-ou Shan
  • Article
    | Open Access

    Correlation network inference is typically based on the significance of the correlation coefficients, but this procedure is not guaranteed to capture biological mechanisms. Here, the authors develop a cutoff selection algorithm that maximizes the overlap between inferred networks and prior knowledge.

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

    Antibiotics targeting cell wall synthesis display an unexplained gap between in vivo efficacy and in vitro binding affinity for their target. Here, Piepenbreier et al. develop a model for bacterial cell wall biosynthesis, show how it is affected by antibiotics, and use it to predict in vivo efficacy of antibiotics.

    • Hannah Piepenbreier
    • , Angelika Diehl
    •  & Georg Fritz
  • Article
    | Open Access

    Metabolic rewiring is a feature of many cancers. Here, the authors combine control theory and flux correlation analysis to study the transition of healthy metabolic networks to cancer states, and find that cancer metabolism is characterized by more streamlined flux distributions.

    • Jean-Marc Schwartz
    • , Hiroaki Otokuni
    •  & Jose C. Nacher
  • Article
    | Open Access

    Untargeted metabolomics detects large numbers of metabolites but their annotation remains challenging. Here, the authors develop a metabolic reaction network-based recursive algorithm that expands metabolite annotation by taking advantage of the mass spectral similarity of reaction-paired neighbor metabolites.

    • Xiaotao Shen
    • , Ruohong Wang
    •  & Zheng-Jiang Zhu
  • Article
    | Open Access

    In considering cross-feeding among microbes within communities, it is typically assumed that metabolic secretions are costly to produce. However, Pacheco et al. use metabolic models to show that ‘costless’ secretions could be common in some environments and important for structuring interactions among microbes.

    • Alan R. Pacheco
    • , Mauricio Moel
    •  & Daniel Segrè
  • Article
    | Open Access

    Interventions in metabolic networks can improve microbes for chemical production. Here, the authors develop a tool to identify metabolic valves that can decouple growth and production to systematically improve the rate and yield of biochemical production processes.

    • Naveen Venayak
    • , Axel von Kamp
    •  & Radhakrishnan Mahadevan
  • 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

    In silico models of cells can provide insight into the causes and effects of disease states and reduce the need for in vivo studies. Here, the authors present a kinetic model of hepatocyte metabolism including energy, carbohydrate, lipid and nitrogen metabolism and hormonal and allosteric regulation of enzymatic activity.

    • Nikolaus Berndt
    • , Sascha Bulik
    •  & Hermann-Georg Holzhütter
  • Article
    | Open Access

    Biochemical processes require both high sensitivity and low fluctuation which is incompatible with the fluctuation dissipation theorem. Here Fei et al. model biochemical oscillators to show how free energy dissipation leads to both a suppression of phase fluctuation and an enhancement of phase sensitivity.

    • Chenyi Fei
    • , Yuansheng Cao
    •  & Yuhai Tu
  • Article
    | Open Access

    Existing pathway design tools make use of existing reactions from databases or successively apply retrosynthetic rules. novoStoic provides an integrated optimization-based framework combining known reactions with novel steps in pathway design allowing for constraints on thermodynamic feasibility, product yield, pathway length and number of novel steps.

    • Akhil Kumar
    • , Lin Wang
    •  & Costas D. Maranas
  • Article
    | Open Access

    Exploiting synthetic lethality is a promising approach for cancer therapy. Here, the authors present an approach to identifying such interactions by finding genetic minimal cut sets (gMCSs) that block cancer proliferation, and apply it to study the lethality of RRM1 inhibition in multiple myeloma.

    • Iñigo Apaolaza
    • , Edurne San José-Eneriz
    •  & Francisco J. Planes
  • Article
    | Open Access

    Coupling of growth and product synthesis is an important principle in metabolic engineering, but its range of applicability is unclear. Here, the authors use a dedicated computational framework to study the feasibility of coupling the production of metabolites to growth in the genome-scale metabolic models of five production organisms, and show that coupling can be achieved for most metabolites.

    • Axel von Kamp
    •  & Steffen Klamt
  • Article
    | Open Access

    Growth-coupled designs for chemical production are limited by native metabolic networks’ optimality for growth. Here, the authors introduce pathway orthogonality as a measure of the independence of biomass and chemical production pathways, identify metabolic valves that allow substrate utilization to be switched between the two, and demonstrate advantages of orthogonal designs.

    • Aditya Vikram Pandit
    • , Shyam Srinivasan
    •  & Radhakrishnan Mahadevan
  • 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

    The rat is a widely-used model for human biology, but we must be aware of metabolic differences. Here, the authors reconstruct the genome-scale metabolic network of the rat, and after reconciling it with an improved human metabolic model, demonstrate the power of the models to integrate toxicogenomics data, providing species-specific biomarker predictions in response to a panel of drugs.

    • Edik M. Blais
    • , Kristopher D. Rawls
    •  & Jason A. Papin
  • 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

    Building multi-component enzymatic processes in one pot is challenged by the inherent complexity of each biochemical system. Here, the authors use online mass spectroscopy and engineering systems theory to achieve forward design of a ten-membered reaction cascade.

    • Christoph Hold
    • , Sonja Billerbeck
    •  & Sven Panke