The evolutionary dynamics of functional modules and the extraordinary plasticity of regulons: the Escherichia coli perspective

Abstract

Using profiles of phylogenetic profiles (P-cubic) we compared the evolutionary dynamics of different kinds of functional associations. Ordered from most to least evolutionarily stable, these associations were genes in the same operons, genes whose products participate in the same biochemical pathway, genes coding for physically interacting proteins and genes in the same regulons. Regulons showed the most plastic functional interactions with evolutionary stabilities barely better than those of unrelated genes. Further regulon analyses showed that global regulators contain less evolutionarily stable associations than local regulators. Genes co-repressed by global regulators had a higher evolutionary conservation than genes co-activated by global regulators. However, the reverse was true for genes co-repressed and co-activated by local regulators. Of all the regulon-related associations, the relationship between regulators and their target genes showed the most evolutionary stability. Different negative data sets built to contrast against each of the analysed kinds of modules also differed in evolutionary conservation revealing further underlying genome organization. Applying P-cubic analyses to other genomes might help visualize genome organization, understand the evolutionary importance and plasticity of functional associations and compare the quality of data sets expected to reflect functional interactions, such as those coming from high-throughput experiments.

The EcoCyc Database

“…EcoCyc has been used as a gold-standard dataset for the development of genome-context methods for predicting gene function [14, 15], operon-prediction methods [16, 17], prediction of promoters and transcription start sites [18, 19], regulatory network reconstruction [20], and the prediction of functional and direct protein-protein interactions [21, 22, 23]. The EcoCyc metabolic data have been used for studies concerning predicted metabolic networks and growth prediction [24, 25], and for model checking of a symbiotic bacteria’s metabolic network [26].…”

The loose evolutionary relationships between transcription factors and other gene products across prokaryotes

“…Using a web-based tool [ 8 ], we selected a non-redundant genome dataset filtered using a genomic similarity score [ 3 , 8 , 9 ] chosen to keep the equivalent of one genome per represented species ( G S S a =0.90) out of the 2733 prokaryotic genomes available at the RefSeq database [ 10 ] ( ftp://ftp.ncbi.nih.gov/genomes/Bacteria/ ) by the end of December 2013. We further filtered this non-redundant genome dataset to keep genomes longer than 2.5 Mbp, with at least 80 genes coding for transcription factors other than sigma factors.…”

“…Profiles of phylogenetic profiles (p-cubic) [ 3 , 5 ], are graphs representing the proportion of genes left at different thresholds of MI. Briefly, these graphs are anti-cumulative plots showing the decline in the proportion of pairs of genes left at increasing MI thresholds.…”

“…Using data derived from literature on experimentally determined molecular interactions, previous work suggested that gene and gene product relationships brought about through transcriptional co-regulation in Escherichia coli K12 MG1655, have loose evolutionary conservation [ 1 – 3 ]. Such results suggest that transcriptional regulation might evolve quickly, an idea that gains support from other results, such as those suggesting that at least half of the transcription factors (TFs) present in E. coli might come from horizontal gene transfer [ 4 ].…”

“…Profiles of phylogenetic profiles, p-cubic, can provide information about the quality of functional interaction datasets [ 5 ], and about the evolutionary conservation of known functional interactions [ 3 ]. As mentioned in the paragraph above, the work on evolutionary conservation has relied on experimentally determined interactions, such as those gathered in knowledge databases like RegulonDB [ 6 ] and EcoCyc [ 7 ].…”