PanGene-O-Meter: Intra-Species Diversity Based on Gene-Content

Bacterial genome evolution is shaped to a great extent by horizontal gene transfer, detectable as genes with a presence-absence pattern of variation that does not follow phylogenetic relationships across the majority of the genome. While average nucleotide identity (ANI) is the most common metric to measure bacterial genome similarity, its ability to capture gene-content differences is limited, and its use therefore often misses a major factor for functional variability. Here, we propose a new, orthogonal gene-content-based method to quantify similarity between bacterial genomes, leveraging knowledge of pan-genome structure and relationships between gene orthology groups. Using four large datasets of bacterial genomes, from Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, and Helicobacter pylori, we demonstrate that our method, PanGene-O-Meter, provides a higher level of granularity than ANI when classifying bacterial isolates of the same species. We also show that PanGene-O-Meter is useful for efficient bacterial genomes clustering, allowing for facile selection of one or several representative genomes, effectively de-duplicating a set of genomes by their gene-content. PanGene-O-Meter enhances our understanding of intra-species bacterial diversity and its potential functional consequences, introducing a new and versatile tool for bacterial genomics. PanGene-O-Meter is available at: https://github.com/HaimAshk/PanGene-O-Meter.