Elucidating genomic gaps using phenotypic profiles

Daniel A. Cuevas, Daniel Garza, Savannah E. Sanchez, Jason Rostron, Chris S. Henry, Veronika Vonstein, Ross A. Overbeek, Anca Segall, Forest Rohwer, Elizabeth A. Dinsdale, Robert A. Edwards

Research output: Contribution to journalArticlepeer-review

Abstract

Advances in genomic sequencing provide the ability to model the metabolism of organisms from their genome annotation. The bioinformatics tools developed to deduce gene function through homology-based methods are dependent on public databases; thus, novel discoveries are not readily extrapolated from current analysis tools with a homology dependence. Multi-phenotype Assay Plates (MAPs) provide a high-throughput method to profile bacterial phenotypes by growing bacteria in various growth conditions, simultaneously. More robust and accurate computational models can be constructed by coupling MAPs with current genomic annotation methods. PMAnalyzer is an online tool that analyzes bacterial growth curves from the MAP system which are then used to optimize metabolic models during in silico growth simulations. Using Citrobacter sedlakii as a prototype, the Rapid Annotation using Subsystem Technology (RAST) tool produced a model consisting of 1,367 enzymatic reactions. After the optimization, 44 reactions were added to, or modified within, the model. The model correctly predicted the outcome on 93% of growth experiments.
Original languageEnglish
Article number210
Number of pages28
JournalF1000Research
Volume3
DOIs
Publication statusPublished - 17 Oct 2016
Externally publishedYes

Keywords

  • high-throughput model
  • reconciliation
  • Elucidating genomic gaps
  • phenotypic profiles

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