Integration of curated databases to identify genotype-phenotype associations

Abstract

Background: The ability to rapidly characterize an unknown microorganism is critical in both responding to infectious disease and biodefense. To do this, we need some way of anticipating an organism's phenotype based on the molecules encoded by its genome. However, the link between molecular composition (i.e. genotype) and phenotype for microbes is not obvious. While there have been several studies that address this challenge, none have yet proposed a large-scale method integrating curated biological information. Here we utilize a systematic approach to discover genotype-phenotype associations that combines phenotypic information from a biomedical informatics database, GIDEON, with the molecular information contained in National Center for Biotechnology Information's Clusters of Orthologous Groups database (NCBI COGs).

Results: Integrating the information in the two databases, we are able to correlate the presence or absence of a given protein in a microbe with its phenotype as measured by certain morphological characteristics or survival in a particular growth media. With a 0.8 correlation score threshold, 66% of the associations found were confirmed by the literature and at a 0.9 correlation threshold, 86% were positively verified.

Conclusion: Our results suggest possible phenotypic manifestations for proteins biochemically associated with sugar metabolism and electron transport. Moreover, we believe our approach can be extended to linking pathogenic phenotypes with functionally related proteins.

Figure 1

Diagram of correlation analysis for associating COGs to lab condition phenotypes. The correlation analysis measures the association between a COG's organism profile (presence or absence of an organism) and a lab condition's organism survival profile. Organisms that have a COG (red) are mapped to the organism's response to adverse growth conditions (blue) creating two vectors that are used for the correlation calculation.

Figure 2

Number of COG-phenotype associated pairs in each subset of the 0.8 and 0.9 threshold correlation score data sets. The resulting data sets of the (a) 0.8 correlation threshold and the (b) 0.9 correlation threshold are broken down into four different subsets. Total number (dark blue) is the total number of COG-phenotype associated pairs found at the 0.8 and 0.9 thresholds respectively. Characterized (light purple) refers to those pairs where the COG has a known function. Annotated (blue-green) are those pairs which were selected for literature verification. Finally, confirmed (light blue) are the associations which were validated in the literature. This is shown for each lab indicated by its GIDEON identifier.