Computational Genomics and Metagenomics

We just published an article, in collaboration with the laboratory of Gabriela Olmedo-Alvarez, trying to solve the phylogeny of Bacillus, which started with a special focus on Bacillus isolated from aquatic environments. The work required solving several little problems just to get those phylogenies, choosing the appropriate genes/proteins for the analyses, thinking of distance measures, etc. All of which I’ll be delighted to write about in later posts. For now, I’ll concentrate on the main finding.

In a previous article, also in collaboration with Gabriela, we had presented several phylogenies all showing that aquatic Bacillus clustered together into a single clade. Given the continuous growth of the public genome databases (see the previous two posts for example), and that Gabriela’s lab continues sequencing aquatic and other interesting Bacillus, we wondered whether the aquatic group would stand to this avalanche of new data. So there we were, choosing Bacillus and checking the data about their places of isolation. As in the previous work, we built a phylogenetic tree based on the 16S rRNA genes, a second one based on the proteins encoded by genes present in all of the genomes under analysis (a core tree), a third tree based on marker genes for phylogenomics published by Jonathan Eisen‘s group, and a hierarchical cluster based on the [dis]similarity of shared proteins between each pair of genomes that we call the Genomic Similarity Score (GSS).

The phylogenetic trees showed a clade of aquatic Bacillus, but several other aquatic Bacillus landed in other clades, thus breaking the pattern previously found. However, the GSS analysis placed the aquatic Bacillus closer together than any of the phylogenetic trees. We were surprised because, in the previous work, the GSS cluster reflected the results of the phylogenetic trees. We therefore started looking for an explanation for this discrepancy.

The phylogenetic trees are restricted to using genes or proteins shared by all the genomes under analysis, while the GSS is not limited, as it uses the similarity of all of the proteins encoded by the genes shared by each pair of genomes. Thus, we thought that there might be more genes shared between organisms of similar environments, than would be expected from their different vertical origins. After all, it is not rare for Bacteria to receive genes via horizontal gene transfer (HGT).

To test for this possibility, we proceeded to make analyses based on gene content as reflected by the classification of their encoded proteins into protein families, and the comparison of such content across organisms. We produced clusters based on gene content and, again, aquatic Bacillus were clustered better than in the phylogenetic trees. Further analyses showed some genes prevailing in groups from each environment. Most of these “environmentally-related” genes were found in strains isolated from soil, and therefore every group had some interesting genes for future studies. Among them we found genes described in previous works as being related to the appropriate environments where we found them to be enriched.

We call this apparent tendency to share more genes than expected from vertical inheritance, perhaps due to environmental constraints, gene content homoplasy.

Main reference:

1. Hernández-González IL, Moreno-Hagelsieb G, Olmedo-Álvarez G (2018) Environmentally-driven gene content convergence and the Bacillus phylogeny. BMC Evol Biol 18: 148.