title: Minimal metabolic pathway structure is consistent with associated biomolecular interactions.
abstract: Pathways are a universal paradigm for functionally describing cellular processes. Even though advances in high-throughput data generation have transformed biology, the core of our biological understanding, and hence data interpretation, is still predicated on human-defined pathways. Here, we introduce an unbiased, pathway structure for genome-scale metabolic networks defined based on principles of parsimony that do not mimic canonical human-defined textbook pathways. Instead, these minimal pathways better describe multiple independent pathway-associated biomolecular interaction datasets suggesting a functional organization for metabolism based on parsimonious use of cellular components. We use the inherent predictive capability of these pathways to experimentally discover novel transcriptional regulatory interactions in Escherichia coli metabolism for three transcription factors, effectively doubling the known regulatory roles for Nac and MntR. This study suggests an underlying and fundamental principle in the evolutionary selection of pathway structures; namely, that pathways may be minimal, independent, and segregated.
authors.affiliation: Department of Bioengineering, University of California San Diego, La Jolla, CA, USA.
authors.forename: Aarash
authors.initials: A
authors.lastname: Bordbar
authors.affiliation: Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA, USA.
authors.forename: Harish
authors.initials: H
authors.lastname: Nagarajan
authors.affiliation: Department of Bioengineering, University of California San Diego, La Jolla, CA, USA Department of Pediatrics, University of California San Diego School of Medicine, La Jolla, CA, USA Wyss Institute for Biologically Inspired Engineering and Department of Genetics, Harvard Medical School, Boston, MA, USA.
authors.forename: Nathan E
authors.initials: NE
authors.lastname: Lewis
authors.affiliation: Department of Bioengineering, University of California San Diego, La Jolla, CA, USA.
authors.forename: Haythem
authors.initials: H
authors.lastname: Latif
authors.affiliation: Department of Bioengineering, University of California San Diego, La Jolla, CA, USA.
authors.forename: Ali
authors.initials: A
authors.lastname: Ebrahim
authors.affiliation: Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA, USA.
authors.forename: Stephen
authors.initials: S
authors.lastname: Federowicz
authors.affiliation: Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA, USA.
authors.forename: Jan
authors.initials: J
authors.lastname: Schellenberger
authors.affiliation: Department of Bioengineering, University of California San Diego, La Jolla, CA, USA Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA, USA Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Lyngby, Denmark palsson@ucsd.edu.
authors.forename: Bernhard O
authors.initials: BO
authors.lastname: Palsson
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D004926:Escherichia coli / Q000235:genetics* / Q000378:metabolism; D029968:Escherichia coli Proteins / Q000235:genetics*; D015964:Gene Expression Regulation, Bacterial; D016678:Genome; D006801:Humans; D053858:Metabolic Networks and Pathways; D008957:Models, Genetic
chemical_list: D029968:Escherichia coli Proteins
keywords: constraint‐based modeling; genetic interactions; pathway analysis; protein‐protein interactions; transcriptional regulatory networks