title: Genome-scale modelling of microbial metabolism with temporal and spatial resolution.
abstract: Most natural microbial systems have evolved to function in environments with temporal and spatial variations. A major limitation to understanding such complex systems is the lack of mathematical modelling frameworks that connect the genomes of individual species and temporal and spatial variations in the environment to system behaviour. The goal of this review is to introduce the emerging field of spatiotemporal metabolic modelling based on genome-scale reconstructions of microbial metabolism. The extension of flux balance analysis (FBA) to account for both temporal and spatial variations in the environment is termed spatiotemporal FBA (SFBA). Following a brief overview of FBA and its established dynamic extension, the SFBA problem is introduced and recent progress is described. Three case studies are reviewed to illustrate the current state-of-the-art and possible future research directions are outlined. The author posits that SFBA is the next frontier for microbial metabolic modelling and a rapid increase in methods development and system applications is anticipated.
authors.affiliation: Department of Chemical Engineering, University of Massachusetts, Amherst, MA 01003, U.S.A. henson@ecs.umass.edu.
authors.forename: Michael A
authors.initials: MA
authors.lastname: Henson
mesh_terms: D000465:Algorithms; D001419:Bacteria / Q000235:genetics* / Q000254:growth & development / Q000378:metabolism*; D018441:Biofilms / Q000254:growth & development; D016680:Genome, Bacterial / Q000235:genetics*; D023281:Genomics / Q000379:methods*; D053858:Metabolic Networks and Pathways / Q000235:genetics; D055442:Metabolome / Q000235:genetics; D055432:Metabolomics / Q000379:methods*; D008954:Models, Biological; D008957:Models, Genetic
keywords: biofilms; genome-scale reconstructions; metabolic modelling; microbial communities; spatiotemporal models