Mighty Morphing Metabolic Models: Leveraging Manual Curations for Automatic Metabolic Reconstruction of Clades

Genome-scale metabolic models have been employed with great success for phenotypic studies of organisms over the last two decades. The most difficult step in the reconstruction of these models is manual curation; a time-intensive and laborious process of literature review that is nevertheless essential for a high-quality network. Although various methods have been developed to accelerate automated reconstruction, much effort must still be expended to supplement an automatically-generated draft model with manually curated information from the published literature to achieve the quality needed for successful simulation of the metabolic processes of the organism. Here, we are utilizing our tool for likelihood-based gene annotation (King et al., 2018) to create a method that “morphs” a manually curated metabolic model to a draft model of a closely related organism. Our method combines genes from the original, manually curated model with genes from an annotation database to create a final structure that contains gene-associated reactions from both sources. The benefits of such an approach are twofold: 1) the effort and accumulated knowledge that has gone into the construction of the original model is leveraged to create a metabolic model for a closely related organism; 2) starting from an already completed and functioning model allows the user to run simulations at every step as necessary, offering the ability to predict how modifications will affect the performance of the model. We demonstrate our method by applying it on our model of Methanococcus maripaludis (Richards et al., 2016), to create morphed models of three related methanogenic archaea. Model morphing offers a viable alternative to other automated reconstruction methods, particularly for organisms that are evolutionarily dissimilar to those that form the foundation of annotation databases, and provides a faster method to reconstruct a clade of metabolic models for related organisms from a manually curated representative.