Modern agriculture has dramatically changed the distribution of animal species on Earth. Changes to host ecology have a major impact on the microbiota, potentially increasing the risk of zoonotic pathogens being transmitted to humans, but the impact of intensive livestock production on host-associated bacteria has rarely been studied. Here, we use large isolate collections and comparative genomics techniques, linked to phenotype studies, to understand the timescale and genomic adaptations associated with the proliferation of the most common food-born bacterial pathogen (Campylobacter jejuni) in the most prolific agricultural mammal (cattle). Our findings reveal the emergence of cattle specialist C. jejuni lineages from a background of host generalist strains that coincided with the dramatic rise in cattle numbers in the 20th century. Cattle adaptation was associated with horizontal gene transfer and significant gene gain and loss. This may be related to differences in host diet, anatomy, and physiology, leading to the proliferation of globally disseminated cattle specialists of major public health importance. This work highlights how genomic plasticity can allow important zoonotic pathogens to exploit altered niches in the face of anthropogenic change and provides information for mitigating some of the risks posed by modern agricultural systems.

Cataloguing the distribution of genes within natural bacterial populations is essential for understanding evolutionary processes and the genetic basis of adaptation. Here we present a pangenomics toolbox, PIRATE (Pangenome Iterative Refinement And Threshold Evaluation), which identifies and classifies orthologous gene families in bacterial pangenomes over a wide range of sequence similarity thresholds. PIRATE builds upon recent scalable software developments to allow for the rapid interrogation of thousands of isolates. PIRATE clusters genes (or other annotated features) over a wide range of amino-acid or nucleotide identity thresholds and uses the clustering information to rapidly classify paralogous gene families into either putative fission/fusion events or gene duplications. Furthermore, PIRATE orders the pangenome using a directed graph, provides a measure of allelic variation and estimates sequence divergence for each gene family. We demonstrate that PIRATE scales linearly with both number of samples and computation resources, allowing for analysis of large genomic datasets, and compares favorably to other popular tools. PIRATE provides a robust framework for analysing bacterial pangenomes, from largely clonal to panmictic species.Availability: PIRATE is implemented in Perl and is freely available under an GNU GPL 3 open source license from https://github.com/SionBayliss/PIRATE. Contact: s.bayliss@bath.ac.uk

Despite overwhelming evidence that variation in intergenic regions (IGRs) in bacteria impacts on phenotypes, most current approaches for analysing pan-genomes focus exclusively on protein-coding sequences. To address this we present Piggy, a novel pipeline that emulates Roary except that it is based only on IGRs. We demonstrate the use of Piggy for pan-genome analyses of Staphylococcus aureus and Escherichia coli using large genome datasets. For S.aureus, we show that highly divergent ("switched") IGRs are associated with differences in gene expression, and we establish a multi-locus reference database of IGR alleles (igMLST;implemented in BIGSdb).

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-22238-5

There are currently no broad estimates of the overall strength and direction of selection operating on intergenic variation in bacteria. Here we address this using large whole genome sequence datasets representing six diverse bacterial species; Escherichia coli , Staphylococcus aureus, Salmonella enterica , Streptococcus pneumoniae , Klebsiella pneumoniae , and Mycobacterium tuberculosis . Excluding M. tuberculosis , we find that a high proportion (62%79%; mean 70%) of intergenic sites are selectively constrained, relative to synonymous sites. Noncoding RNAs tend to be under stronger selective constraint than promoters, which in turn are typically more constrained than rhoindependent terminators. Even when these regulatory elements are excluded, the mean proportion of constrained intergenic sites only falls to 69%; thus our current understanding of the functionality of intergenic regions (IGRs) in bacteria is severely limited. Consistent with a role for positive as well as negative selection on intergenic sites, we present evidence for strong positive selection in Mycobacterium tuberculosis promoters, underlining the key role of regulatory changes as an adaptive mechanism in this highly monomorphic pathogen.