Shifts in the Molecular Epidemiology of Campylobacter jejuni Infections in a Sentinel Region of New Zealand following Implementation of Food Safety Interventions by the Poultry Industry

A Systematic Review on the Role of Wildlife as Carriers and Spreaders of Campylobacter spp

Campylobacter spp. are important zoonotic pathogens and can cause one of the main bacterial diarrheal diseases worldwide. Research in the context of infection arising from transmission from other humans and other vertebrates has been extensive. A large fraction of these investigations has focused on domestic animals; however, there are also a number of publications which either totally, or at least in part, consider the role of wild or feral animals as carriers or spreaders of Campylobacter spp. Here, we carry out a systematic review to explore the role played by wild vertebrates as sources of Campylobacter spp. with a compilation of prevalence data for more than 150 species including reptiles, mammals and birds. We found that numerous vertebrate species can act as carriers of Campylobacter species, but we also found that some host specificity may exist, reducing the risk of spread from wildlife to domestic animals or humans.

Transmission dynamics of an antimicrobial resistant Campylobacter jejuni lineage in New Zealand's commercial poultry network

Understanding the relative contribution of different between-farm transmission pathways is essential in guiding recommendations for mitigating disease spread. This study investigated the association between contact pathways linking poultry farms in New Zealand and the genetic relatedness of antimicrobial resistant Campylobacter jejuni Sequence Type 6964 (ST-6964), with the aim of identifying the most likely contact pathways that contributed to its rapid spread across the industry. Whole-genome sequencing was performed on 167C. jejuni ST-6964 isolates sampled from across 30 New Zealand commercial poultry enterprises. The genetic relatedness between isolates was determined using whole genome multilocus sequence typing (wgMLST). Permutational multivariate analysis of variance and distance-based linear models were used to explore the strength of the relationship between pairwise genetic associations among the C. jejuni isolates and each of several pairwise distance matrices, indicating either the geographical distance between farms or the network distance of transportation vehicles. Overall, a significant association was found between the pairwise genetic relatedness of the C. jejuni isolates and the parent company, the road distance and the network distance of transporting feed vehicles. This result suggests that the transportation of feed within the commercial poultry industry as well as other local contacts between flocks, such as the movements of personnel, may have played a significant role in the spread of C. jejuni. However, further information on the historical contact patterns between farms is needed to fully characterise the risk of these pathways and to understand how they could be targeted to reduce the spread of C. jejuni.

Machine learning to predict the source of campylobacteriosis using whole genome data

Campylobacteriosis is among the world's most common foodborne illnesses, caused predominantly by the bacterium Campylobacter jejuni. Effective interventions require determination of the infection source which is challenging as transmission occurs via multiple sources such as contaminated meat, poultry, and drinking water. Strain variation has allowed source tracking based upon allelic variation in multi-locus sequence typing (MLST) genes allowing isolates from infected individuals to be attributed to specific animal or environmental reservoirs. However, the accuracy of probabilistic attribution models has been limited by the ability to differentiate isolates based upon just 7 MLST genes. Here, we broaden the input data spectrum to include core genome MLST (cgMLST) and whole genome sequences (WGS), and implement multiple machine learning algorithms, allowing more accurate source attribution. We increase attribution accuracy from 64% using the standard iSource population genetic approach to 71% for MLST, 85% for cgMLST and 78% for kmerized WGS data using the classifier we named aiSource. To gain insight beyond the source model prediction, we use Bayesian inference to analyse the relative affinity of C. jejuni strains to infect humans and identified potential differences, in source-human transmission ability among clonally related isolates in the most common disease causing lineage (ST-21 clonal complex). Providing generalizable computationally efficient methods, based upon machine learning and population genetics, we provide a scalable approach to global disease surveillance that can continuously incorporate novel samples for source attribution and identify fine-scale variation in transmission potential.

Comparative macrolide use in humans and animals: should macrolides be moved off the World Health Organisation's critically important antimicrobial list?

Macrolide antibiotics are categorized by the WHO as Highest Priority, Critically Important Antimicrobials due to their recommendation as treatment for severe cases of campylobacteriosis in humans; a self-limiting, rarely life-threatening, zoonotic foodborne infection. Low rates of macrolide resistance in Campylobacter jejuni and the availability of alternative treatments have prompted some regulatory schemes to assign macrolides to a lower importance category. Apart from rare, specific infections, macrolides largely play a supportive role to other drug classes in human medicine. By contrast, although the advent of alternative control methods has seen significant reductions in macrolide use in intensive livestock, they still have a crucial role in the treatment/control of respiratory infections and liver abscesses in cattle. Whilst acknowledging that ongoing surveillance is required to reduce the spread of recently emerged, transferable macrolide resistance among Campylobacter, this article recommends that macrolides should be moved to the WHO Highly Important category.

Campylobacter sp.: Pathogenicity factors and prevention methods-new molecular targets for innovative antivirulence drugs?

Infections caused by bacterial species from the genus Campylobacter are one of the four main causes of strong diarrheal enteritis worldwide. Campylobacteriosis, a typical food-borne disease, can range from mild symptoms to fatal illness. About 550 million people worldwide suffer from campylobacteriosis and lethality is about 33 million p.a. This review summarizes the state of the current knowledge on Campylobacter with focus on its specific virulence factors. Using this knowledge, multifactorial prevention strategies can be implemented to reduce the prevalence of Campylobacter in the food chain. In particular, antiadhesive strategies with specific adhesion inhibitors seem to be a promising concept for reducing Campylobacter bacterial load in poultry production. Antivirulence compounds against bacterial adhesion to and/or invasion into the host cells can open new fields for innovative antibacterial agents. Influencing chemotaxis, biofilm formation, quorum sensing, secretion systems, or toxins by specific inhibitors can help to reduce virulence of the bacterium. In addition, the unusual glycosylation of the bacterium, being a prerequisite for effective phase variation and adaption to different hosts, is yet an unexplored target for combating Campylobacter sp. Plant extracts are widely used remedies in developing countries to combat infections with Campylobacter. Therefore, the present review summarizes the use of natural products against the bacterium in an attempt to stimulate innovative research concepts on the manifold still open questions behind Campylobacter towards improved treatment and sanitation of animal vectors, treatment of infected patients, and new strategies for prevention. KEY POINTS: • Campylobacter sp. is a main cause of strong enteritis worldwide. • Main virulence factors: cytolethal distending toxin, adhesion proteins, invasion machinery. • Strong need for development of antivirulence compounds.

Probabilistic model for estimating Listeria monocytogenes concentration in cooked meat products from presence/absence data

A quantitative probabilistic model was developed to estimate the concentration of Listeria monocytogenes in cooked meat products based on presence/absence data and an assumed zero-inflated distribution, i.e. zero-inflated Poisson (ZIP) or zero-inflated Poisson lognormal (ZIPL) distribution. The performance of these two distributions was compared in two data sets (data set A and B), which represented L. monocytogenes prevalence and concentrations in cooked meat products. In this study, L. monocytogenes contamination data consisted of 4.23% (8/189) and 4.17% (5/120) non-zero counts for data set A and B, respectively. The contamination level of L. monocytogenes, determined by the most probable number (MPN) technique, ranged from 3 to 93 MPN/g among 13 positive samples. The goodness-of-fit test indicated that the ZIPL distribution was better than the simpler ZIP distribution, when L. monocytogenes contamination levels on positive cooked meat samples illustrated large heterogeneity. Results obtained from ZIPL distribution showed that the logarithmic mean value of L. monocytogenes positive samples was 1.5 log MPN/g (log σ = 0.4) for data set A and B. This study provides an alternative probabilistic method when only qualitative data is available in Quantitative microbial risk assessment (QMRA), in particular if pathogen concentrations consist of large numbers of zero counts and represent high variability.