Abstract
BackgroundIn bacteria, genes with related functions—such as those involved in the metabolism of the same compound or in infection processes—are often physically close on the genome and form groups called clusters. The enrichment of such clusters over various distantly related bacteria can be used to predict the roles of genes of unknown function that cluster with characterised genes. There is no obvious rule to define a cluster, given their variability in size and intergenic distances, and the definition of what comprises a “gene”, since genes can gain and lose domains over time. Protein domains can cluster within a gene, or in adjacent genes of related function, and in both cases these are chromosomally clustered. Here, we model the distances between pairs of protein domain coding regions across a wide range of bacteria and archaea via a probabilistic two component mixture model, without imposing arbitrary thresholds in terms of gene numbers or distances.ResultsWe trained our model using matched gene ontology terms to label functionally related pairs and assess the stability of the parameters of the model across 14,178 archaeal and bacterial strains. We found that the parameters of our mixture model are remarkably stable across bacteria and archaea, except for endosymbionts and obligate intracellular pathogens. Obligate pathogens have smaller genomes, and although they vary, on average do not show noticeably different clustering distances; the main difference in the parameter estimates is that a far greater proportion of the genes sharing ontology terms are clustered. This may reflect that these genomes are enriched for complexes encoded by clustered core housekeeping genes, as a proportion of the total genes. Given the overall stability of the parameter estimates, we then used the mean parameter estimates across the entire dataset to investigate which gene ontology terms are most frequently associated with clustered genes.ConclusionsGiven the stability of the mixture model across species, it may be used to predict bacterial gene clusters that are shared across multiple species, in addition to giving insights into the evolutionary pressures on the chromosomal locations of genes in different species.
Highlights
In bacteria, genes with related functions—such as those involved in the metabolism of the same compound or in infection processes—are often physi‐ cally close on the genome and form groups called clusters
We first demonstrated that functionally related pairs of protein domain coding regions are typically found close together on bacterial and archaeal chromosomes compared to pairs of domains that are not functionally related
The second component assumes the existence of an evolutionary pressure to keep protein domains that are functionally related close together on the chromosome and the pairwise distances are modelled as exponentially distributed, with a species-specific rate parameter
Summary
Genes with related functions—such as those involved in the metabolism of the same compound or in infection processes—are often physi‐ cally close on the genome and form groups called clusters. Bacterial and archaeal genomes have a characteristic structural organisation where functionally interacting genes, such as those encoding for the subunits of the same protein complex or involved in the same pathway, physically aggregate in blocks (clusters) on the chromosome. This feature provides an evolutionarily advantage by enabling these cells to regulate and trade these genes as a unit, rather than as a set of independent entities [1]. Bacterial clusters are of pivotal importance in bacterial-induced disease, as observed in Escherichia coli strains that gain the ability to infect humans upon acquisition of DNA segments encoding for enterotoxins and other infection machineries [9]
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