By utilizing the phenotypic information stored in the GIDEON database, we can begin to make associations between the presence of a gene (COG) within an organism to its expressed phenotype. First, we mapped the organisms found in the GIDEON database to the organisms in the COGs database (see Additional file 1
). Secondly, to quantify the associations between the phenotype of an organism to its genomic content, we calculated the correlation between the measured expression of a certain phenotype to the absence or presence of COGs within an organism. Third, we applied a hypergeometric distribution threshold of 0.01 to filter for significant correlations.
Subsequently, a 0.8 correlation threshold and a 0.9 correlation threshold were used to generate two separate result sets. The 0.8 correlation data set contained 290 association pairs (see Additional file 2
). One hundred random data points were selected from the 0.8 correlation result set for literature validation; these are referred to as annotated pairs (see Additional file 3
). Out of these 100 data points, 66% of the data points had associations confirmed in the scientific literature. For the 0.9 correlation score threshold, 86% (31/36) of the resulting pairs had confirmed associations in the literature (Table ).
Number of validated associations at the 0.8 and 0.9 threshold
Some of the representative association pairs that were verified by the literature are discussed below (Table ). The laboratory conditions are referred to by their GIDEON identifier/phenotypic description (see Additional file 4
), and a COG with a known function is defined as characterized (see Additional file 5
Accuracy of associations confirmed by literature broken down by individual condition. Characterized are those pairs where the COG has a known function. Confirmed are those associations that were verified in the literature.
A) B01/Gram-negative – Among the 66 confirmed associated pairs found in the result set with a threshold score of 0.8, 16 substantiated associations out of a total of 17 annotated COG-phenotype pairs (Table ) are involved in the B01/Gram-negative phenotype. This resulted in 94% accuracy for determining Gram-negative organisms. For the data set with a score of 0.9 correlation criteria, 12 out of 12 total annotated COG-phenotype pairs were verified by the literature.
The outer membrane of the Gram-negative bacteria is a lipid-protein bilayer made up of proteins, phospholipids, and lipopolysaccharides that differentiate it from the thicker cell wall structure of Gram-positive bacteria [11
]. Perhaps unsurprisingly, the confirmed pairs found with the Gram-negative phenotype contained proteins involved with lipid A and lipopolysaccharide biosynthesis and other proteins belonging to the outer membrane of Gram-negative bacteria (Table ).
Overview of representative hits above 0.8
B) B02/Gram-positive – More interestingly, annotated pairs with the B02/Gram-positive phenotype were not just specific to the specialized Gram-positive membrane but also to a variety of conserved genes found only in the Gram-positive bacteria. Of the six proteins with known function found in the 0.8 correlation score data set, 3 pairs were positively confirmed by the scientific literature. In the 0.9 correlation result set, 2 out of 2 (100%) of the characterized pairs were corroborated.
C) B29/Growth on MacConkey Agar – Growth on MacConkey agar is indicative of Gram-negative bacteria that can ferment lactose [12
]. Sixteen (52%) of the associated pairs from the 0.8 correlation data were confirmed, as were 4 (100%) of the associated pairs from the 0.9 correlation set Organisms that were able to grow on MacConkey agar contained proteins involved with the outer membrane of Gram-negative bacteria. Given the use of this test in specifically differentiating those Gram-negatives that can ferment lactose, one would expect this result; however, the proteins associated with growth on MacConkey agar do not overlap with those proteins most associated with the Gram-negative test. This suggests that this method of building associations can be specific to a particular condition.
D) B30/Oxidase – Two characterized COGs were found with a correlation at 0.85 and p < 7.48 × 10-6 to be positively associated with oxidase activity. Both are components of Cbb3-type cytochrome oxidase which is unsurprising since the goal of the oxidase test is to detect the presence of this enzyme. Although this is not a novel finding, it does illustrate that our method is able to pick out known relationships.
E) B31/Catalase – In the catalase test, hydrogen peroxide is added to the media. Those microbes which do not contain the catalase enzyme are unable to break the hydrogen peroxide into oxygen and water and would die. As would be expected, the COGs associated to the B31/Catalase test were usually enzymes that belong to similar regulation pathways as the catalase enzyme. For example, human acyl-CoA hydrolase, one of the COGs found to be positively associated to the catalase phenotype, upregulates peroxisome biogenesis and, in turn, activates catalase activity [13
]. The highest scoring pair was a member of the catalase protein family. For both the 0.8 and 0.9 correlation result sets, the confirmation percentages were 64% and 63% respectively.
F) FAC/L-Arabinose – With a high correlation score of 0.97, 5-keto 4-deoxyuronate isomerase was the only characterized protein family associated with the ability to assimilate arabinose. 5-keto 4-deoxyuronate isomerase, or kduI, is an enzyme involved with pectin degradation and shares the same regulator protein, crp or CAP protein, as the L-Arabinose catabolism pathway [14
G) FAT/Trehalose – The COGs most associated with the capability to metabolize the sugar trehalose were several maltose-related proteins with correlation scores of 0.94. It has previously been shown that addition of trehalose to growth media induces the maltose system verifying both of these associations [16
H) G03/Motile – Finally, the pairs related to the G03/Motile phenotype contain proteins involved with chemotaxis and flagella. The result set with a correlation score above 0.8 contained 17 such proteins, and 100% of these were verified by the literature. Similarly, all 5 proteins from the result set with a 0.9 threshold were also confirmed.
Additionally, the 0.8 and 0.9 correlation score threshold data sets for motility were compared with the KEGG database [17
]. This analysis revealed that 100% of the proteins found to be associated with motility were also annotated as part of the Cell Motility functional classification in the KEGG pathway database.
Prediction of genes associated to phenotypes
After analyzing the accuracy of the data sets, it is also possible to make reasonable hypotheses for COG-phenotype pairs that are characterized but have not yet been confirmed by the biological literature. These COG-phenotype pairs are listed using their GIDEON identifier/description-COG description/protein name. One example is the B31/Catalase-COG1651/Protein-disulfide isomerase (DsbG) pair with a correlation score of 0.91. Dsb proteins are known to oxidize the sulfhydryl groups of periplasmic proteins to disulfide bonds, donating electrons to ubiquinone, and thereby making the electron transport chain the primary source of oxidizing power for sustaining periplasmic sulfhydryl oxidation [19
]. During the stationary phase, electron transport to oxygen is reduced. Bandyopadhyay et al
. suggest a possible complementary role between catalase and the Dsb proteins in maintaining periplasmic sulfhydryl oxidation. It is possible that catalase may be critical in peroxidatically oxidizing ubiquinol or another periplasmic or inner membrane component using H2
as an electron acceptor during the stationary phase when the oxidizing capacity of the electron transport is diminished [21
With a correlation score of 0.95, other possible associations can be made for the FAP/L-Rhamnose phenotype with various phosphotransferase system sorbitol-specific component proteins. Some microbes such as the Klebsiella I-174 organism make exopolysaccharides with a high rhamnose content [22
]. Farres et al
. showed that the addition of sorbitol increased the production and growth of rhamnose over other carbon sources such as sucrose [23
]. This study suggests that proteins involved with sorbitol metabolism and utilization could be linked to rhamnose production.