Improving the EFMs quality by augmenting their representativeness in LP methods

Abstract

BackgroundAlthough cellular metabolism has been widely studied, its fully comprehension is still a challenge. A main tool for this study is the analysis of meaningful pieces of knowledge called modes and, in particular, specially interesting classes of modes such as pathways and Elementary Flux Modes (EFMs). Its study often has to deal with issues such as the appearance of infeasibilities or the difficulty of finding representative enough sets of modes that are free of repetitions. Mode extraction methods usually incorporate strategies devoted to mitigate this phenomena but they still get a high ratio of repetitions in the set of solutions.ResultsThis paper presents a proposal to improve the representativeness of the full set of metabolic reactions in the set of computed modes by penalizing the eventual high frequency of occurrence of some reactions during the extraction. This strategy can be applied to any linear programming based extraction existent method.ConclusionsOur strategy enhances the quality of a set of extracted EFMs favouring the presence of every reaction in it and improving the efficiency by mitigating the occurrence of repeated solutions. The new proposed strategy can complement other EFMs extraction methods based on linear programming. The obtained solutions are more likely to be diverse using less computing effort and improving the efficiency of the extraction.

Boosting the extraction of elementary flux modes in genome-scale metabolic networks using the linear programming approach

“…In the end, as for any extraction method based on random sampling, it is usually recommended a statistic analysis of the solutions obtained in order to avoid any bias produced by that method (see, e.g. Hidalgo et al , 2018 ; Tabe-Bordbar and Marashi, 2013 ). Therefore, another interesting future work is to carry out that statistic analysis to check the diversity and quality of the EFMs found by EFM-Ta.…”

On the representativeness and stability of a set of EFMs

“…So, even in the few cases in which the whole set E can be computed, it is pretty easy to obtain two subsets of EFMs that are quite different (see Hidalgo et al 2018 ), but it is much harder to elucidate which one is more representative.…”

“…This issue has been previously observed (see Machado et al 2012 , Tabe-Bordbar and Marashi 2013 , Ullah et al 2020 ) and is a severe limitation that affects the usability of these methods. Note that different methods provide subsets that can be different in a statistically significant way ( Hidalgo et al 2018 ), so properties inferred from these EFMs may heavily depend on the method used.…”