Comparative Genome-Scale Reconstruction of Gapless Metabolic Networks for Present and Ancestral Species

Abstract

We introduce a novel computational approach, CoReCo, for comparative metabolic reconstruction and provide genome-scale metabolic network models for 49 important fungal species. Leveraging on the exponential growth in sequenced genome availability, our method reconstructs genome-scale gapless metabolic networks simultaneously for a large number of species by integrating sequence data in a probabilistic framework. High reconstruction accuracy is demonstrated by comparisons to the well-curated Saccharomyces cerevisiae consensus model and large-scale knock-out experiments. Our comparative approach is particularly useful in scenarios where the quality of available sequence data is lacking, and when reconstructing evolutionary distant species. Moreover, the reconstructed networks are fully carbon mapped, allowing their use in 13C flux analysis. We demonstrate the functionality and usability of the reconstructed fungal models with computational steady-state biomass production experiment, as these fungi include some of the most important production organisms in industrial biotechnology. In contrast to many existing reconstruction techniques, only minimal manual effort is required before the reconstructed models are usable in flux balance experiments. CoReCo is available at http://esaskar.github.io/CoReCo/.

Whole-genome metabolic model of Trichoderma reesei built by comparative reconstruction

“…Using the homology search results, the probability of observing each enzyme is scored for each species. This score is based on the probabilistic model that takes into account both BLAST and GTG and it has been shown that the inclusion of GTG improves the reconstructions [21]. Previously, the score was computed as an average of these two sources of information.…”

“…In the second phase of the CoReCo algorithm, the metabolic network is reconstructed using an algorithm that creates gapless metabolic networks [21]. The reactions are added to the network in an iterative manner, starting from the highest-scoring reactions, and subsequently adding reactions until the remaining reactions have a score lower than a user-defined threshold .…”

“…Here, genomes of 56 fungi were used as input to CoReCo. This set includes the 49 fungi used in the first CoReCo publication [21]. For the purpose of reconstructing the T. reesei model, we added several Trichoderma genomes into the set of input organisms.…”

“…The CoReCo algorithm [21] automatically reconstructs gapless metabolic models for several related species at once. The CoReCo metabolic model reconstruction pipeline has two parts (see Fig.…”

Metabolic analysis and modeling approaches to drive enveloped viral particles production in the Insect Cell-BaculoVirus Expression System

“…The used systems metabolic engineering strategies may be useful for the construction of versatile B. subtilis cell factories for the production of the other industrially important chemicals. Method: Our CoReCo method [1] reconstructs genome-scale gapless metabolic networks simultaneously for a large number of species by integrating sequence data in a probabilistic framework. Our comparative approach is particularly useful in scenarios where the quality of available sequence data is lacking, and when reconstructing evolutionary distant species, such as genomes assembled from metagenomics data.…”