Author, as appears in the article.: Seaver, Samuel M D; Sales-Pardo, Marta; Guimera, Roger; Amaral, Luis A Nunes
Department: Enginyeria Química
URV's Author/s: Guimera Manrique, Roger / Sales Pardo, Marta
Keywords: Scale metabolic reconstruction Phosphoenolpyruvate Membrane-transport systems Mechanism Kinetics Growth Genomics Escherichia-coli Capabilities Annotation
Abstract: The ability of microbial species to consume compounds found in the environment to generate commercially-valuable products has long been exploited by humanity. The untapped, staggering diversity of microbial organisms offers a wealth of potential resources for tackling medical, environmental, and energy challenges. Understanding microbial metabolism will be crucial to many of these potential applications. Thermodynamically-feasible metabolic reconstructions can be used, under some conditions, to predict the growth rate of certain microbes using constraint-based methods. While these reconstructions are powerful, they are still cumbersome to build and, because of the complexity of metabolic networks, it is hard for researchers to gain from these reconstructions an understanding of why a certain nutrient yields a given growth rate for a given microbe. Here, we present a simple model of biomass production that accurately reproduces the predictions of thermodynamically-feasible metabolic reconstructions. Our model makes use of only: i) a nutrient's structure and function, ii) the presence of a small number of enzymes in the organism, and iii) the carbon flow in pathways that catabolize nutrients. When applied to test organisms, our model allows us to predict whether a nutrient can be a carbon source with an accuracy of about 90% with respect to in silico experiments. In addition, our model provides excellent predictions of whether a medium will produce more or less growth than another (p<10(-6)) and good predictions of the actual value of the in silico biomass production. Citation: Seaver SMD, Sales-Pardo M, Guimera R, Amaral LAN (2012) Phenomenological Model for Predicting the Catabolic Potential of an Arbitrary Nutrient. PLoS Comput Biol 8(11): e1002762. doi:10.1371/journal.pcbi.1002762
Thematic Areas: Saúde coletiva Psicología Molecular biology Modeling and simulation Medicina ii Medicina i Mathematics, interdisciplinary applications Mathematical & computational biology Matemática / probabilidade e estatística Interdisciplinar Genetics Ensino Engenharias iv Engenharias iii Ecology, evolution, behavior and systematics Ecology Computational theory and mathematics Ciências biológicas ii Ciências biológicas i Ciências agrárias i Ciência da computação Cellular and molecular neuroscience Biotecnología Biodiversidade Biochemical research methods Astronomia / física
licence for use: https://creativecommons.org/licenses/by/3.0/es/
Author's mail: roger.guimera@urv.cat marta.sales@urv.cat
Author identifier: 0000-0002-3597-4310 0000-0002-8140-6525
Record's date: 2024-10-19
Papper version: info:eu-repo/semantics/publishedVersion
Link to the original source: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1002762
Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
Papper original source: Plos Computational Biology. 8 (11): e1002762-
APA: Seaver, Samuel M D; Sales-Pardo, Marta; Guimera, Roger; Amaral, Luis A Nunes (2012). Phenomenological Model for Predicting the Catabolic Potential of an Arbitrary Nutrient. Plos Computational Biology, 8(11), e1002762-. DOI: 10.1371/journal.pcbi.1002762
Article's DOI: 10.1371/journal.pcbi.1002762
Entity: Universitat Rovira i Virgili
Journal publication year: 2012
Publication Type: Journal Publications