Development of an Integrated Framework for Minimal Cut Set Enumeration in Constraint-Based Models

Vieira, Vítor; Maia, Paulo; Rocha, Isabel; Rocha, Miguel

doi:10.1007/978-3-319-40126-3_20

Cited by 2 publications

(3 citation statements)

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“…Mixed-integer linear programming was used to find a subset of the MCSs [SGMR17]. The target-specific dual method has previously been used for this task, in a method called MCSEnumerator [vKK14,VMRR16]. As its authors state, not all the EFMs in the dual space result in valid MCSs, but by adding the appropriate constraints, one can remove the redundant results from the ILP's feasible space.…”

Section: Resultsmentioning

confidence: 99%

“…Given the challenges in enumerating all MCSs (in part due to their large number, which can be exponential in the size of the network), some recent work [vKK14,VMRR16] uses Mixed Integer Linear Programming (MILP) formulations to enumerate a subset of the MCSs, in increasing order of size. In some practical applications, quickly obtaining a few MCSs of minimum size may be more desirable than enumerating the complete set.…”

Section: Introductionmentioning

confidence: 99%

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MCS²: Minimal coordinated supports for fast enumeration of minimal cut sets in metabolic networks

Miraskarshahi

Zabeti

Stephen

et al. 2018

Preprint

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Motivation: Constraint-based modeling of metabolic networks helps researchers gain insight into the metabolic processes of many organisms, both prokaryotic and eukaryotic. Minimal Cut Sets (MCSs) are minimal sets of reactions whose inhibition blocks a target reaction in a metabolic network. Most approaches for finding the MCSs in constrained-based models require, either as an intermediate step or as a byproduct of the calculation, the computation of the set of elementary flux modes (EFMs), a convex basis for the valid flux vectors in the network. Recently, Ballerstein et al.[BvKKH11] proposed a method for computing the MCSs of a network without first computing its EFMs, by creating a dual network whose EFMs are a superset of the MCSs of the original network. However, their dual network is always larger than the original network and depends on the target reaction. Here we propose the construction of a different dual network, which is typically smaller than the original network and is independent of the target reaction, for the same purpose. We prove the correctness of our approach, MCS 2 , and describe how it can be modified to compute the few smallest MCSs for a given target reaction. Results: We compare MCS 2 to the method of Ballerstein et al. and two other existing methods. We show that MCS 2 succeeds in calculating the full set of MCSs in many models where other approaches cannot finish within a reasonable amount of time. Thus, in addition to its theoretical novelty, our approach provides a practical advantage over existing methods. Availability: MCS 2 is freely available at https://github.com/RezaMash/MCS under the GNU 3.0 license.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

MCS²: Minimal coordinated supports for fast enumeration of minimal cut sets in metabolic networks

Miraskarshahi

Zabeti

Stephen

et al. 2018

Preprint

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“…Two additional problem formulations are also presented to allow greater flexibility of growth-coupled design strategies based on MCSs. A graphical user interface for the MCS enumeration algorithm was also made available as a plugin for the OptFlux metabolic engineering platform [27].…”

Section: Introductionmentioning

confidence: 99%

Comparison of pathway analysis and constraint-based methods for cell factory design

et al. 2019

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Background Computational strain optimisation methods (CSOMs) have been successfully used to exploit genome-scale metabolic models, yielding strategies useful for allowing compound overproduction in metabolic cell factories. Minimal cut sets are particularly interesting since their definition allows searching for intervention strategies that impose strong growth-coupling phenotypes, and are not subject to optimality bias when compared with simulation-based CSOMs. However, since both types of methods have different underlying principles, they also imply different ways to formulate metabolic engineering problems, posing an obstacle when comparing their outputs. Results In this work, we perform an in-depth analysis of potential strategies that can be obtained with both methods, providing a critical comparison of performance, robustness, predicted phenotypes as well as strategy structure and size. To this end, we devised a pipeline including enumeration of strategies from evolutionary algorithms (EA) and minimal cut sets (MCS), filtering and flux analysis of predicted mutants to optimize the production of succinic acid in Saccharomyces cerevisiae . We additionally attempt to generalize problem formulations for MCS enumeration within the context of growth-coupled product synthesis. Strategies from evolutionary algorithms show the best compromise between acceptable growth rates and compound overproduction. However, constrained MCSs lead to a larger variety of phenotypes with several degrees of growth-coupling with production flux. The latter have proven useful in revealing the importance, in silico, of the gamma-aminobutyric acid shunt and manipulation of cofactor pools in growth-coupled designs for succinate production, mechanisms which have also been touted as potentially useful for metabolic engineering. Conclusions The two main groups of CSOMs are valuable for finding growth-coupled mutants. Despite the limitations in maximum growth rates and large strategy sizes, MCSs help uncover novel mechanisms for compound overproduction and thus, analyzing outputs from both methods provides a richer overview on strategies that can be potentially carried over in vivo. Electronic supplementary material The online version of this article (10.1186/s12859-019-2934-y) contains supplementary material, which is available to authorized users.

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Development of an Integrated Framework for Minimal Cut Set Enumeration in Constraint-Based Models

Cited by 2 publications

References 16 publications

MCS²: Minimal coordinated supports for fast enumeration of minimal cut sets in metabolic networks

MCS²: Minimal coordinated supports for fast enumeration of minimal cut sets in metabolic networks

Comparison of pathway analysis and constraint-based methods for cell factory design

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Development of an Integrated Framework for Minimal Cut Set Enumeration in Constraint-Based Models

Cited by 2 publications

References 16 publications

MCS2: Minimal coordinated supports for fast enumeration of minimal cut sets in metabolic networks

MCS2: Minimal coordinated supports for fast enumeration of minimal cut sets in metabolic networks

Comparison of pathway analysis and constraint-based methods for cell factory design

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MCS²: Minimal coordinated supports for fast enumeration of minimal cut sets in metabolic networks

MCS²: Minimal coordinated supports for fast enumeration of minimal cut sets in metabolic networks