A systematic assessment of current genome-scale metabolic reconstruction tools

Abstract

Background Several genome-scale metabolic reconstruction software platforms have been developed and are being continuously updated. These tools have been widely applied to reconstruct metabolic models for hundreds of microorganisms ranging from important human pathogens to species of industrial relevance. However, these platforms, as yet, have not been systematically evaluated with respect to software quality, best potential uses and intrinsic capacity to generate high-quality, genome-scale metabolic models. It is therefore unclear for potential users which tool best fits the purpose of their research. Results In this work, we perform a systematic assessment of current genome-scale reconstruction software platforms. To meet our goal, we first define a list of features for assessing software quality related to genome-scale reconstruction. Subsequently, we use the feature list to evaluate the performance of each tool. To assess the similarity of the draft reconstructions to high-quality models, we compare each tool’s output networks with that of the high-quality, manually curated, models of Lactobacillus plantarum and Bordetella pertussis , representatives of gram-positive and gram-negative bacteria, respectively. We additionally compare draft reconstructions with a model of Pseudomonas putida to further confirm our findings. We show that none of the tools outperforms the others in all the defined features. Conclusions Model builders should carefully choose a tool (or combinations of tools) depending on the intended use of the metabolic model. They can use this benchmark study as a guide to select the best tool for their research. Finally, developers can also benefit from this evaluation by getting feedback to improve their software. Electronic supplementary material The online version of this article (10.1186/s13059-019-1769-1) contains supplementary material, which is available to authorized users.

Genome-Scale Metabolic Modeling for Unraveling Molecular Mechanisms of High Threat Pathogens

“…In a very recent publication, this protocol was extended toward developing multi-strain GEMs from a reference model (Norsigian et al, 2020). Different tools and softwares have been developed to facilitate and accelerate metabolic reconstruction process (Hamilton and Reed, 2014;Mendoza et al, 2019). The biochemical databases such as KEGG, BRENDA, and MetaCyc have become remarkable sources in this reconstruction process to obtain collective information on genes, enzymes, reactions, metabolites and pathways (Kanehisa, 2000;Schomburg, 2002;Caspi et al, 2012).…”

The ModelSEED Database for the integration of metabolic annotations and the reconstruction, comparison, and analysis of metabolic models for plants, fungi, and microbes

“…Given the rapid adoption of these models as tools in systems biology, the pace with which new models are produced has grown dramatically, particularly with the emergence of numerous automated model reconstruction pipelines (Mendoza et al 2019). The diversity of resources now producing large numbers of these models has created new challenges due to a lack of standardization in models and their underlying biochemistry, assumptions, and associated data.…”

Suggestions for Standardized Identifiers for Fatty Acyl Compounds in Genome Scale Metabolic Models and Their Application to the WormJam Caenorhabditis elegans Model

“…Typically, GSMs are reconstructed by applying a variety of protocols to resources such as genome annotations and existing pathway reconstructions [2]. Following rigorous manual curation, networks can be used for a range of purposes.…”