(176u) Raps: Rapid Annotation of Photosynthetic Systems

Large-scale bioproduction requires comprehensive modeling efforts. However, the construction and validation of models is a complex and extensive process. Moreover, model construction has recently become a significant bottleneck in deriving value from genomic information. While some model organisms, including E. coli and yeast, have strong and diverse communities devoted to continually improving models, not all organisms have such a research effort behind them. The work done on these model organisms benefits the larger community of researchers studying genomes because many annotations are based on homology to these model systems, but photosynthetic species like algae or cyanobacteria have unique traits and metabolic functions which are not usually captured by comparing DNA sequences to heterotrophic bacteria. Instead, manual curation of these features is required, an arduous process that requires significant time and effort. In order to reduce repetitive curation tasks and make better use of existing genome scale models, we have developed an automated pipeline focused specifically on rapid annotation of photosynthetic organisms. Our method leverages previous genomic annotations and metabolic models, and standardizes reaction names and metabolic abbreviations. The output of our algorithm is a first draft genome-scale metabolic model which can then be used for flux balance analysis.