iCN718, an Updated and Improved Genome-Scale Metabolic Network Reconstruction of Acinetobacter baumannii AYE

• Published in: Frontiers in genetics 2018-04, Vol.9, p.121-121
• Main Authors: Norsigian, Charles J, Kavvas, Erol, Seif, Yara, Palsson, Bernhard O, Monk, Jonathan M
• Format: Article
• Language: English
• Subjects: Acinetobacter baumannii; antibiotic resistance; constraint-based modeling; Genetics; genome-scale reconstruction; metabolism
• ISSN: 1664-8021; 1664-8021
• DOI: 10.3389/fgene.2018.00121

has become an urgent clinical threat due to the recent emergence of multi-drug resistant strains. There is thus a significant need to discover new therapeutic targets in this organism. One means for doing so is through the use of high-quality genome-scale reconstructions. Well-curated and accurate genome-scale models (GEMs) of would be useful for improving treatment options. We present an updated and improved genome-scale reconstruction of AYE, named iCN718, that improves and standardizes previous AYE reconstructions. iCN718 has 80% accuracy for predicting gene essentiality data and additionally can predict large-scale phenotypic data with as much as 89% accuracy, a new capability for an reconstruction. We further demonstrate that iCN718 can be used to analyze conserved metabolic functions in the A. baumannii core genome and to build strain-specific GEMs of 74 other strains from genome sequence alone. iCN718 will serve as a resource to integrate and synthesize new experimental data being generated for this urgent threat pathogen.