RT Journal Article
SR Electronic
T1 Unlocking Elementary Conversion Modes: ecmtool unveils all capabilities of metabolic networks
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2020.06.06.137554
DO 10.1101/2020.06.06.137554
A1 Tom J. Clement
A1 Erik B. Baalhuis
A1 Bas Teusink
A1 Frank J. Bruggeman
A1 Robert Planqué
A1 Daan H. de Groot
YR 2020
UL http://biorxiv.org/content/early/2020/10/17/2020.06.06.137554.abstract
AB The metabolic capabilities of cells determine their biotechnological potential, fitness in ecosystems, pathogenic threat levels, and function in multicellular organisms. Their comprehensive experimental characterisation is generally not feasible, particularly for unculturable organisms. In principle, the full range of metabolic capabilities can be computed from an organism’s annotated genome using metabolic network reconstruction. However, current computational methods cannot deal with genome-scale metabolic networks. Part of the problem is that these methods aim to enumerate all metabolic pathways, while computation of all (elementally balanced) conversions between nutrients and products would suffice. Indeed, the elementary conversion modes (ECMs, defined by Urbanczik and Wagner) capture the full metabolic capabilities of a network, but the use of ECMs has not been accessible, until now. We extend and explain the theory of ECMs, implement their enumeration in ecmtool, and illustrate their applicability. This work contributes to the elucidation of the full metabolic footprint of any cell.Competing Interest StatementThe authors have declared no competing interest.