ReCodLiver0.9: Overcoming Challenges in Genome-Scale Metabolic Reconstruction of a Non-model Species

• Published in: Frontiers in Molecular Biosciences
• Main Authors: Hanna, Eileen Marie, Zhang, Xiaokang, Eide, Marta, Fallahi, Shirin, Furmanek, Tomasz, Yadetie, Fekadu, Zielinski, Daniel Craig, Goksøyr, Anders, Jonassen, Inge
• Other Authors: Norges ForskningsrÃ¥d
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: Frontiers Media SA 2020
• Subjects: atlantic cod; Gadus morhua
• Online Access: http://dx.doi.org/10.3389/fmolb.2020.591406; https://www.frontiersin.org/articles/10.3389/fmolb.2020.591406/full

The availability of genome sequences, annotations, and knowledge of the biochemistry underlying metabolic transformations has led to the generation of metabolic network reconstructions for a wide range of organisms in bacteria, archaea, and eukaryotes. When modeled using mathematical representations, a reconstruction can simulate underlying genotype-phenotype relationships. Accordingly, genome-scale metabolic models (GEMs) can be used to predict the response of organisms to genetic and environmental variations. A bottom-up reconstruction procedure typically starts by generating a draft model from existing annotation data on a target organism. For model species, this part of the process can be straightforward, due to the abundant organism-specific biochemical data. However, the process becomes complicated for non-model less-annotated species. In this paper, we present a draft liver reconstruction, ReCodLiver0.9, of Atlantic cod ( Gadus morhua ), a non-model teleost fish, as a practicable guide for cases with comparably few resources. Although the reconstruction is considered a draft version, we show that it already has utility in elucidating metabolic response mechanisms to environmental toxicants by mapping gene expression data of exposure experiments to the resulting model.