Sequence-based typing is essential for understanding the epidemiology of Campylobacter infections, a major worldwide cause of bacterial gastroenteritis. We demonstrate the practical and rapid exploitation of whole-genome sequencing to provide routine definitive characterization of Campylobacter jejuni and Campylobacter coli for clinical and public health purposes. Short-read data from 384 Campylobacter clinical isolates collected over 4 months in Oxford, United Kingdom, were assembled de novo . Contigs were deposited at the pubMLST.org /campylobacter website and automatically annotated for 1,667 loci. Typing and phylogenetic information was extracted and comparative analyses were performed for various subsets of loci, up to the level of the whole genome, using the Genome Comparator and Neighbor-net algorithms. The assembled sequences (for 379 isolates) were diverse and resembled collections from previous studies of human campylobacteriosis. Small subsets of very closely related isolates originated mainly from repeated sampling from the same patients and, in one case, likely laboratory contamination. Much of the within-patient variation occurred in phase-variable genes. Clinically and epidemiologically informative data can be extracted from whole-genome sequence data in real time with straightforward, publicly available tools. These analyses are highly scalable, are transparent, do not require closely related genome reference sequences, and provide improved resolution (i) among Campylobacter clonal complexes and (ii) between very closely related isolates. Additionally, these analyses rapidly differentiated unrelated isolates, allowing the detection of single-strain clusters. The approach is widely applicable to analyses of human bacterial pathogens in real time in clinical laboratories, with little specialist training required.

Understanding the structure of a bacterial population is essential in order to understand bacterial evolution. Estimating the core genome (those genes common to all, or nearly all, strains of a species) is a key component of such analyses. The size and composition of the core genome varies by dataset, but we hypothesized that the variation between different collections of the same bacterial species would be minimal. To investigate this, we analyzed the genome sequences of 3,118 pneumococci recovered from healthy individuals in Reykjavik (Iceland), Southampton (United Kingdom), Boston (United States), and Maela (Thailand). The analyses revealed a “supercore” genome (genes shared by all 3,118 pneumococci) of 558 genes, although an additional 354 core genes were shared by pneumococci from Reykjavik, Southampton, and Boston. Overall, the size and composition of the core and pan-genomes among pneumococci recovered in Reykjavik, Southampton, and Boston were similar. Maela pneumococci were distinctly different in that they had a smaller core genome and larger pan-genome. The pan-genome of Maela pneumococci contained several >25 Kb sequence regions (flanked by pneumococcal genes) that were homologous to genomic regions found in other bacterial species. Overall, our work revealed that some subsets of the global pneumococcal population are highly heterogeneous, and our hypothesis was rejected. This is an important finding in terms of understanding genetic variation among pneumococci and is also an essential point of consideration before generalizing the findings from a single dataset to the wider pneumococcal population.

Genomic surveillance of bacterial meningitis pathogens is essential for effective disease control globally, enabling identification of emerging and expanding strains and consequent public health interventions. While there has been a rise in the use of whole genome sequencing, this has been driven predominately by a subset of countries with adequate capacity and resources. Global capacity to participate in surveillance needs to be expanded, particularly in low and middle-income countries with high disease burdens. In light of this, the WHO-led collaboration, Defeating Meningitis by 2030 Global Roadmap, has called for the establishment of a Global Meningitis Genome Partnership that links resources for: N. meningitidis (Nm), S. pneumoniae (Sp), H. influenzae (Hi) and S. agalactiae (Sa) to improve worldwide coordination of strain identification and tracking. Existing platforms containing relevant genomes include: PubMLST: Nm (31,622), Sp (15,132), Hi (1935), Sa (9026); The Wellcome Sanger Institute: Nm (13,711), Sp (> 24,0 0 0), Sa (6200), Hi (1738); and BMGAP: Nm (8785), Hi (2030). A steering group is being established to coordinate the initiative and encourage high-quality data curation. Next steps include: developing guidelines on open-access sharing of genomic data; defining a core set of metadata; and facilitating development of user-friendly interfaces that represent publicly available data.

This human campylobacteriosis sentinel surveillance project was based at two sites in Oxfordshire and North East England chosen (i) to be representative of the English population on the Office for National Statistics urban-rural classification and (ii) to provide continuity with genetic surveillance started in Oxfordshire in October 2003. Between October 2015 and September 2018 epidemiological questionnaires and genome sequencing of isolates from human cases was accompanied by sampling and genome sequencing of isolates from possible food animal sources. The principal aim was to estimate the contributions of the main sources of human infection and to identify any changes over time. An extension to the project focussed on antimicrobial resistance in study isolates and older archived isolates. These older isolates were from earlier years at the Oxfordshire site and the earliest available coherent set of isolates from the national archive at Public Health England (1997/8). The aim of this additional work was to analyse the emergence of the antimicrobial resistance that is now present among human isolates and to describe and compare antimicrobial resistance in recent food animal isolates. Having identified the presence of bias in population genetic attribution, and that this was not addressed in the published literature, this study developed an approach to adjust for bias in population genetic attribution, and an alternative approach to attribution using sentinel types. Using these approaches the study estimated that approximately 70% of Campylobacter jejuni and just under 50% of C. coli infection in our sample was linked to the chicken source and that this was relatively stable over time. Ruminants were identified as the second most common source for C. jejuni and the most common for C. coli where there was also some evidence for pig as a source although less common than ruminant or chicken. These genomic attributions of themselves make no inference on routes of transmission. However, those infected with isolates genetically typical of chicken origin were substantially more likely to have eaten chicken than those infected with ruminant types. Consumption of lamb’s liver was very strongly associated with infection by a strain genetically typical of a ruminant source. These findings support consumption of these foods as being important in the transmission of these infections and highlight a potentially important role for lamb’s liver consumption as a source of Campylobacter infection. Antimicrobial resistance was predicted from genomic data using a pipeline validated by Public Health England and using BIGSdb software. In C. jejuni this showed a nine-fold increase in resistance to fluoroquinolones from 1997 to 2018. Tetracycline resistance was also common, with higher initial resistance (1997) and less substantial change over time. Resistance to aminoglycosides or macrolides remained low in human cases across all time periods. Among C. jejuni food animal isolates, fluoroquinolone resistance was common among isolates from chicken and substantially less common among ruminants, ducks or pigs. Tetracycline resistance was common across chicken, duck and pig but lower among ruminant origin isolates. In C. coli resistance to all four antimicrobial classes rose from low levels in 1997. The fluoroquinolone rise appears to have levelled off earlier and among animals, levels are high in duck as well as chicken isolates, although based on small sample sizes, macrolide and aminoglycoside resistance, was substantially higher than for C. jejuni among humans and highest among pig origin isolates. Tetracycline resistance is high in isolates from pigs and the very small sample from ducks. Antibiotic use following diagnosis was relatively high (43.4%) among respondents in the human surveillance study. Moreover, it varied substantially across sites and was highest among non-elderly adults compared to older adults or children suggesting opportunities for improved antimicrobial stewardship. The study also found evidence for stable lineages over time across human and source animal species as well as some tighter genomic clusters that may represent outbreaks. The genomic dataset will allow extensive further work beyond the specific goals of the study. This has been made accessible on the web, with access supported by data visualisation tools.