Development and validation of a random forest algorithm for source attribution of animal and human Salmonella Typhimurium and monophasic variants of S. Typhimurium isolates in England and Wales utilising whole genome sequencing data.

Source attribution has traditionally involved combining epidemiological data with different pathogen characterisation methods, including 7-gene multi locus sequence typing (MLST) or serotyping, however, these approaches have limited resolution. In contrast, whole genome sequencing data provide an overview of the whole genome that can be used by attribution algorithms. Here, we applied a random forest (RF) algorithm to predict the primary sources of human clinical Salmonella Typhimurium (S. Typhimurium) and monophasic variants (monophasic S. Typhimurium) isolates. To this end, we utilised single nucleotide polymorphism diversity in the core genome MLST alleles obtained from 1,061 laboratory-confirmed human and animal S. Typhimurium and monophasic S. Typhimurium isolates as inputs into a RF model. The algorithm was used for supervised learning to classify 399 animal S. Typhimurium and monophasic S. Typhimurium isolates into one of eight distinct primary source classes comprising common livestock and pet animal species: cattle, pigs, sheep, other mammals (pets: mostly dogs and horses), broilers, layers, turkeys, and game birds (pheasants, quail, and pigeons). When applied to the training set animal isolates, model accuracy was 0.929 and kappa 0.905, whereas for the test set animal isolates, for which the primary source class information was withheld from the model, the accuracy was 0.779 and kappa 0.700. Subsequently, the model was applied to assign 662 human clinical cases to the eight primary source classes. In the dataset, 60/399 (15.0%) of the animal and 141/662 (21.3%) of the human isolates were associated with a known outbreak of S. Typhimurium definitive type (DT) 104. All but two of the 141 DT104 outbreak linked human isolates were correctly attributed by the model to the primary source classes identified as the origin of the DT104 outbreak. A model that was run without the clonal DT104 animal isolates produced largely congruent outputs (training set accuracy 0.989 and kappa 0.985; test set accuracy 0.781 and kappa 0.663). Overall, our results show that RF offers considerable promise as a suitable methodology for epidemiological tracking and source attribution for foodborne pathogens.

Geographical and temporal distribution of multidrug-resistant Salmonella Infantis in Europe and the Americas.

Recently emerged S. Infantis strains carrying resistance to several commonly used antimicrobials have been reported from different parts of the globe, causing human cases of salmonellosis and with occurrence reported predominantly in broiler chickens. Here, we performed phylogenetic and genetic clustering analyses to describe the population structure of 417 S. Infantis originating from multiple European countries and the Americas collected between 1985 and 2019. Of these, 171 were collected from 56 distinct premises located in England and Wales (E/W) between 2009 and 2019, including isolates linked to incursions of multidrug-resistant (MDR) strains from Europe associated with imported poultry meat. The analysis facilitated the comparison of isolates from different E/W sources with isolates originating from other countries. There was a high degree of congruency between the outputs of different types of population structure analyses revealing that the E/W and central European (Germany, Hungary, and Poland) isolates formed several disparate groups, which were distinct from the cluster relating to the United States (USA) and Ecuador/Peru, but that isolates from Brazil were closely related to the E/W and the central European isolates. Nearly half of the analysed strains/genomes (194/417) harboured the IncFIB(pN55391) replicon typical of the "parasitic" pESI-like megaplasmid found in diverse strains of S. Infantis. The isolates that contained the IncFIB(pN55391) replicon clustered together, despite originating from different parts of the globe. This outcome was corroborated by the time-measured phylogeny, which indicated that the initial acquisition of IncFIB(pN55391) likely occurred in Europe in the late 1980s, with a single introduction of IncFIB(pN55391)-carrying S. Infantis to the Americas several years later. Most of the antimicrobial resistance (AMR) genes were identified in isolates that harboured one or more different plasmids, but based on the short-read assemblies, only a minority of the resistance genes found in these isolates were identified as being associated with the detected plasmids, whereas the hybrid assemblies comprising the short and long reads demonstrated that the majority of the identified AMR genes were associated with IncFIB(pN55391) and other detected plasmid replicon types. This finding underlies the importance of applying appropriate methodologies to investigate associations of AMR genes with bacterial plasmids.

Bayesian Source Attribution of Salmonella Typhimurium Isolates From Human Patients and Farm Animals in England and Wales.

The purpose of the study was to apply a Bayesian source attribution model to England and Wales based data on Salmonella Typhimurium (ST) and monophasic variants (MST), using different subtyping approaches based on sequence data. The data consisted of laboratory confirmed human cases and mainly livestock samples collected from surveillance or monitoring schemes. Three different subtyping methods were used, 7-loci Multi-Locus Sequence Typing (MLST), Core-genome MLST, and Single Nucleotide Polymorphism distance, with the impact of varying the genetic distance over which isolates would be grouped together being varied for the latter two approaches. A Bayesian frequency matching method, known as the modified Hald method, was applied to the data from each of the subtyping approaches. Pigs were found to be the main contributor to human infection for ST/MST, with approximately 60% of human cases attributed to them, followed by other mammals (mostly horses) and cattle. It was found that the use of different clustering methods based on sequence data had minimal impact on the estimates of source attribution. However, there was an impact of genetic distance over which isolates were grouped: grouping isolates which were relatively closely related increased uncertainty but tended to have a better model fit.

Seascape Genomics of the Sugar Kelp Saccharina latissima along the North Eastern Atlantic Latitudinal Gradient.

Temperature is one of the most important range-limiting factors for many seaweeds. Driven by the recent climatic changes, rapid northward shifts of species' distribution ranges can potentially modify the phylogeographic signature of Last Glacial Maximum. We explored this question in detail in the cold-tolerant kelp species Saccharina latissima, using microsatellites and double digest restriction site-associated DNA sequencing ( ddRAD-seq) derived single nucleotide polymorphisms (SNPs) to analyze the genetic diversity and structure in 11 sites spanning the entire European Atlantic latitudinal range of this species. In addition, we checked for statistical correlation between genetic marker allele frequencies and three environmental proxies (sea surface temperature, salinity, and water turbidity). Our findings revealed that genetic diversity was significantly higher for the northernmost locality (Spitsbergen) compared to the southern ones (Northern Iberia), which we discuss in light of the current state of knowledge on phylogeography of S. latissima and the potential influence of the recent climatic changes on the population structure of this species. Seven SNPs and 12 microsatellite alleles were found to be significantly associated with at least one of the three environmental variables. We speculate on the putative adaptive functions of the genes associated with the outlier markers and the importance of these markers for successful conservation and aquaculture strategies for S. latissima in this age of rapid global change.

Population genomics of the introduced and cultivated Pacific kelp Undaria pinnatifida: Marinas-not farms-drive regional connectivity and establishment in natural rocky reefs.

Ports and farms are well-known primary introduction hot spots for marine non-indigenous species (NIS). The extent to which these anthropogenic habitats are sustainable sources of propagules and influence the evolution of NIS in natural habitats was examined in the edible seaweed Undaria pinnatifida, native to Asia and introduced to Europe in the 1970s. Following its deliberate introduction 40 years ago along the French coast of the English Channel, this kelp is now found in three contrasting habitat types: farms, marinas and natural rocky reefs. In the light of the continuous spread of this NIS, it is imperative to better understand the processes behind its sustainable establishment in the wild. In addition, developing effective management plans to curtail the spread of U. pinnatifida requires determining how the three types of populations interact with one another. In addition to an analysis using microsatellite markers, we developed, for the first time in a kelp, a ddRAD-sequencing technique to genotype 738 individuals sampled in 11 rocky reefs, 12 marinas, and two farms located along ca. 1,000 km of coastline. As expected, the RAD-seq panel showed more power than the microsatellite panel for identifying fine-grained patterns. However, both panels demonstrated habitat-specific properties of the study populations. In particular, farms displayed very low genetic diversity and no inbreeding conversely to populations in marinas and natural rocky reefs. In addition, strong, but chaotic regional genetic structure, was revealed, consistent with human-mediated dispersal (e.g., leisure boating). We also uncovered a tight relationship between populations in rocky reefs and those in nearby marinas, but not with nearby farms, suggesting spillover from marinas into the wild. At last, a temporal survey spanning 20 generations showed that wild populations are now self-sustaining, albeit there was no evidence for local adaptation to any of the three habitats. These findings highlight that limiting the spread of U. pinnatifida requires efficient management policies that also target marinas.