Logic programming-based Minimal Cut Sets reveal consortium-level therapeutic targets for chronic wound infections

Abstract Minimal Cut Sets (MCSs) identify sets of reactions which, when removed from a metabolic network, disable certain cellular functions. The traditional search for MCSs within genome-scale metabolic models (GSMMs) targets cellular growth, identifies reaction sets resulting in a lethal phenotype...

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Main Authors: Maxime Mahout, Ross P. Carlson, Laurent Simon, Sabine Peres
Format: Article
Language:English
Published: Nature Portfolio 2024-04-01
Series:npj Systems Biology and Applications
Online Access:https://doi.org/10.1038/s41540-024-00360-6
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author Maxime Mahout
Ross P. Carlson
Laurent Simon
Sabine Peres
author_facet Maxime Mahout
Ross P. Carlson
Laurent Simon
Sabine Peres
author_sort Maxime Mahout
collection DOAJ
description Abstract Minimal Cut Sets (MCSs) identify sets of reactions which, when removed from a metabolic network, disable certain cellular functions. The traditional search for MCSs within genome-scale metabolic models (GSMMs) targets cellular growth, identifies reaction sets resulting in a lethal phenotype if disrupted, and retrieves a list of corresponding gene, mRNA, or enzyme targets. Using the dual link between MCSs and Elementary Flux Modes (EFMs), our logic programming-based tool aspefm was able to compute MCSs of any size from GSMMs in acceptable run times. The tool demonstrated better performance when computing large-sized MCSs than the mixed-integer linear programming methods. We applied the new MCSs methodology to a medically-relevant consortium model of two cross-feeding bacteria, Staphylococcus aureus and Pseudomonas aeruginosa. aspefm constraints were used to bias the computation of MCSs toward exchanged metabolites that could complement lethal phenotypes in individual species. We found that interspecies metabolite exchanges could play an essential role in rescuing single-species growth, for instance inosine could complement lethal reaction knock-outs in the purine synthesis, glycolysis, and pentose phosphate pathways of both bacteria. Finally, MCSs were used to derive a list of promising enzyme targets for consortium-level therapeutic applications that cannot be circumvented via interspecies metabolite exchange.
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spelling doaj.art-b432f7bfaa3b4c0aa8678e2b38a9c9552024-04-07T11:22:28ZengNature Portfolionpj Systems Biology and Applications2056-71892024-04-0110111310.1038/s41540-024-00360-6Logic programming-based Minimal Cut Sets reveal consortium-level therapeutic targets for chronic wound infectionsMaxime Mahout0Ross P. Carlson1Laurent Simon2Sabine Peres3Université Paris-Saclay, CNRS, Laboratoire Interdisciplinaire des Sciences du NumériqueDepartment of Chemical and Biological Engineering, Center for Biofilm Engineering, Microbiology and Immunology, Montana State UniversityBordeaux-INP, Université BordeauxUMR CNRS 5558, Laboratoire de Biométrie et de Biologie Évolutive, Université Claude Bernard Lyon 1Abstract Minimal Cut Sets (MCSs) identify sets of reactions which, when removed from a metabolic network, disable certain cellular functions. The traditional search for MCSs within genome-scale metabolic models (GSMMs) targets cellular growth, identifies reaction sets resulting in a lethal phenotype if disrupted, and retrieves a list of corresponding gene, mRNA, or enzyme targets. Using the dual link between MCSs and Elementary Flux Modes (EFMs), our logic programming-based tool aspefm was able to compute MCSs of any size from GSMMs in acceptable run times. The tool demonstrated better performance when computing large-sized MCSs than the mixed-integer linear programming methods. We applied the new MCSs methodology to a medically-relevant consortium model of two cross-feeding bacteria, Staphylococcus aureus and Pseudomonas aeruginosa. aspefm constraints were used to bias the computation of MCSs toward exchanged metabolites that could complement lethal phenotypes in individual species. We found that interspecies metabolite exchanges could play an essential role in rescuing single-species growth, for instance inosine could complement lethal reaction knock-outs in the purine synthesis, glycolysis, and pentose phosphate pathways of both bacteria. Finally, MCSs were used to derive a list of promising enzyme targets for consortium-level therapeutic applications that cannot be circumvented via interspecies metabolite exchange.https://doi.org/10.1038/s41540-024-00360-6
spellingShingle Maxime Mahout
Ross P. Carlson
Laurent Simon
Sabine Peres
Logic programming-based Minimal Cut Sets reveal consortium-level therapeutic targets for chronic wound infections
npj Systems Biology and Applications
title Logic programming-based Minimal Cut Sets reveal consortium-level therapeutic targets for chronic wound infections
title_full Logic programming-based Minimal Cut Sets reveal consortium-level therapeutic targets for chronic wound infections
title_fullStr Logic programming-based Minimal Cut Sets reveal consortium-level therapeutic targets for chronic wound infections
title_full_unstemmed Logic programming-based Minimal Cut Sets reveal consortium-level therapeutic targets for chronic wound infections
title_short Logic programming-based Minimal Cut Sets reveal consortium-level therapeutic targets for chronic wound infections
title_sort logic programming based minimal cut sets reveal consortium level therapeutic targets for chronic wound infections
url https://doi.org/10.1038/s41540-024-00360-6
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