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Article

Answer Set Programming for Computing Constraints-Based Elementary Flux Modes: Application to Escherichia coli Core Metabolism

1
LRI, Université Paris-Saclay, CNRS, 91405 Orsay, France
2
Department of Chemical and Biological Engineering, Center for Biofilm Engineering, Microbiology and Immunology, Montana State University, Bozeman, MT 59717, USA
3
INRAE, UR1404, MaIAGE, Université Paris-Saclay, 78350 Jouy-en-Josas, France
*
Author to whom correspondence should be addressed.
Processes 2020, 8(12), 1649; https://doi.org/10.3390/pr8121649
Received: 13 November 2020 / Revised: 4 December 2020 / Accepted: 8 December 2020 / Published: 14 December 2020
Elementary Flux Modes (EFMs) provide a rigorous basis to systematically characterize the steady state, cellular phenotypes, as well as metabolic network robustness and fragility. However, the number of EFMs typically grows exponentially with the size of the metabolic network, leading to excessive computational demands, and unfortunately, a large fraction of these EFMs are not biologically feasible due to system constraints. This combinatorial explosion often prevents the complete analysis of genome-scale metabolic models. Traditionally, EFMs are computed by the double description method, an efficient algorithm based on matrix calculation; however, only a few constraints can be integrated into this computation. They must be monotonic with regard to the set inclusion of the supports; otherwise, they must be treated in post-processing and thus do not save computational time. We present aspefm, a hybrid computational tool based on Answer Set Programming (ASP) and Linear Programming (LP) that permits the computation of EFMs while implementing many different types of constraints. We apply our methodology to the Escherichia coli core model, which contains 226×106 EFMs. In considering transcriptional and environmental regulation, thermodynamic constraints, and resource usage considerations, the solution space is reduced to 1118 EFMs that can be computed directly with aspefm. The solution set, for E. coli growth on O2 gradients spanning fully aerobic to anaerobic, can be further reduced to four optimal EFMs using post-processing and Pareto front analysis. View Full-Text
Keywords: constraints-based elementary flux modes; logic programming; answer set programming; Escherichia coli core metabolism constraints-based elementary flux modes; logic programming; answer set programming; Escherichia coli core metabolism
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MDPI and ACS Style

Mahout, M.; Carlson, R.P.; Peres, S. Answer Set Programming for Computing Constraints-Based Elementary Flux Modes: Application to Escherichia coli Core Metabolism. Processes 2020, 8, 1649. https://doi.org/10.3390/pr8121649

AMA Style

Mahout M, Carlson RP, Peres S. Answer Set Programming for Computing Constraints-Based Elementary Flux Modes: Application to Escherichia coli Core Metabolism. Processes. 2020; 8(12):1649. https://doi.org/10.3390/pr8121649

Chicago/Turabian Style

Mahout, Maxime, Ross P. Carlson, and Sabine Peres. 2020. "Answer Set Programming for Computing Constraints-Based Elementary Flux Modes: Application to Escherichia coli Core Metabolism" Processes 8, no. 12: 1649. https://doi.org/10.3390/pr8121649

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