Source Attribution of Salmonella in Macadamia Nuts to Animal and Environmental Reservoirs in Queensland, Australia

Effects of Substrate Composition on the Growth Traits of Grafted Seedling in Macadamia (Macadamia integrifolia) Nuts

Macadamia nut plantings in China are expanding year by year. In order to breed and promote superior varieties, this study analyzed the effects of different rootstocks and scions on the survival rate of grafted seedlings, and then selected the best substrate composition for plant growth. The results showed that the survival rate of the HAES788 variety as rootstock and Guire No. 1 as scion was the highest, reaching 96%. The optimal grafting time in December was better than that in March. Furthermore, among 16 substrate formulations, T12, T13, T15, and T16 had advantages of agglomerated soil and more well-developed root systems compared to the CK made of loess. The plant height, stem diameter, leaf length, leaf width, and dry weight of the aboveground and underground parts of the grafted seedlings planted in these substrate formulations were significantly higher than those plants planted in the CK. In addition, the substrate formulations T12, T13, T15, and T16 significantly improved the organic matter, total nitrogen, and total potassium content of the substrate soils, but little improvement was observed for total phosphorus content after 13 months. Overall, macadamia grafting times are best in December, with HAES788 and Guire No. 1 being the best rootstock and scion. The optimal substrate formulations are T12, T13, T15, and T16. This study provides a solid foundation for the production of high-quality macadamia plants.

A machine learning approach to identifying Salmonella stress response genes in isolates from poultry processing

We explored the potential of machine learning to identify significant genes associated with Salmonella stress response during poultry processing using whole genome sequencing (WGS) data. The Salmonella isolates (n = 177) used in this study were obtained from various chicken sources (skin before chiller, chicken carcass before chiller, frozen chicken, and post-chill chicken carcass). Six machine learning algorithms (random forest, neural network, cost-sensitive learning, logit boost, and support vector machine linear and radial kernels) were trained on Salmonella WGS data, and model fit was assessed using standard evaluation metrics such as the area under the receiver operating characteristic (AUROC) curve and confusion matrix statistics. All models achieved high performances based on the AUROC metric, with logit boost showing the best performance with an AUROC score of 0.904, sensitivity of 0.889, and specificity of 0.920. The significant genes identified included ybtX, which encodes a Yersiniabactin-associated zinc transporter, and the transferase-encoding genes yccK and thiS. Additionally, genes coding for cold (cspA, cspD, and cspE) and heat shock (rpoH and rpoE) responses were identified. Other significant genes included those involved in lipopolysaccharide biosynthesis (irp1, waaD, rfc, and rfbX), DNA repair and replication (traI), biofilm formation (ccdA and fyuA), and cellular metabolism (irtA).

A Preliminary Investigation of Salmonella Populations in Indigenous Portuguese Layer Hen Breeds

The sustainability of agroecological systems, biodiversity protection, animal welfare, and consumer demand for higher quality products from alternative and extensive farming methods have reinforced interest in local breeds that are well adapted to low-input environments. However, food safety needs to be safeguarded to reinforce consumer confidence. The aim of this study was to conduct a preliminary investigation on the occurrence of Salmonella spp. in eggshells, hen's cloaca, and litter materials from autochthonous Portuguese laying hens raised in a semi-extensive system for small-scale production. A total of 279 samples from 31 flocks belonging to 12 farms were obtained, with 63 samples from the "Preta Lusitânica" breed, and 72 samples each from the remaining autochthonous breeds, namely, "Branca", "Amarela", and "Pedrês Portuguesa". None (0%) of the samples analyzed were positive for Salmonella spp. To the best of our knowledge, these are the first results of Salmonella evaluation from hen's cloaca, eggshells, and litter materials in autochthonous Portuguese chickens, suggesting that a semi-extensive production system can contribute to better food security and a lower risk to public health and the environment.

The Rise of Non-typhoidal Salmonella Infections in India: Causes, Symptoms, and Prevention

Non-typhoidal Salmonella infections (NTS) are a growing concern in India, posing a significant health risk to the population. These infections are becoming more common at worrisome rates, primarily because of inadequate surveillance. Salmonella non-typhoidal causes severe gastroenteritis and can even cause invasive infections, such as bacteremia, and focal infections, such as meningitis and septic arthritis, and is acquired through contaminated food and water sources. From moderate to severe, the symptoms might vary. Certain serovars exhibit a stronger propensity for specific syndromes, with serious infections more commonly observed in vulnerable populations. Consuming contaminated food, using inadequate sanitation procedures while handling meat from animals slaughtered, and contaminated water supplies are some of the causes of these diseases. Proper food and water treatment, better sanitary facilities, public awareness campaigns, and adherence to food safety laws are all part of prevention measures. The issue of antimicrobial resistance further emphasizes the necessity for prudent antibiotic usage. The Indian government has put in place programs including public awareness campaigns, better sanitary facilities, and stricter food safety laws. In the future, efforts should, however, concentrate on improving laws, boosting hygienic practices, and funding the development of new medicines and vaccines. These actions will lessen the burden of NTS infections in India by assisting in their prevention and management. This review aims to understand the reasons for this growing tendency, which is essential for creating efficient control and prevention strategies.

Phenotypic and genotypic characterization of antibiotic resistance of Salmonella Heidelberg in the south of Brazil

Salmonella is the main human pathogen present in the poultry chain. Salmonella Heidelberg is one of the most important serovars for public health since it has been frequently isolated in broiler chickens from different countries and may present multidrug resistance (MDR). This study was carried out with 130 S. Heidelberg isolates collected from pre-slaughter broiler farms in 2019 and 2020 in 18 cities from three Brazilian states to study relevant aspects regarding their genotypic and phenotypic resistance. The isolates were tested and identified using somatic and flagellar antiserum (0:4, H:2, and H:r), and an antimicrobial susceptibility test (AST) was performed against 11 antibiotics for veterinary use. The strains were typed by Enterobacterial Repetitive Intergenic Consensus (ERIC)-PCR, and representatives of the main clusters of the identified profiles were sequenced by Whole Genome Sequencing (WGS). AST results showed that all isolates were resistant to sulfonamide, 54 % (70/130) were resistant to amoxicillin, and only one was sensitive to tetracycline. Twelve isolates (15.4 %) were MDR. The dendrogram obtained from the ERIC-PCR showed that the strains were grouped into 27 clusters with similarity above 90 %, with some isolates showing 100 % similarity but with different phenotypic profiles of antimicrobial resistance. Identical strains collected on the same farm on other dates were identified, indicating that they were residents. WGS identified 66 antibiotic-resistance genes. The sul2 (present in all sequenced samples) and tet(A) genes were highlighted and validated in the experimental analysis. The fosA7 gene was also identified in all sequenced samples, but resistance was not observed in the phenotypic test, possibly due to the heteroresistance of the S. Heidelberg strains evaluated. Considering that chicken meat is one of the most consumed meats in the world, the data obtained in the present study can corroborate the mapping of the origin and trends of antimicrobial resistance.

Evaluation of irish consumers' knowledge of salmonellosis and food-handling practices

Salmonella is one of numerous food-borne pathogens that could possibly pose a major threat to global food safety. Salmonella is primarily associated with foods such as poultry, eggs, vegetables, and some dairy products. However, infected food handlers and faecal contaminated environments are also significant sources and reservoirs of this pathogen. This study comprehensively evaluated the Irish consumers' food safety knowledge by exploring their knowledge level, practices and attitudes regarding raw meat handling, cross-contamination while handling different types of food products, and knowledge of Salmonella risk and associated food-handling practices. The online SurveyMonkey tool was used to distribute a quantitative survey titled "Evaluation of Knowledge and Food-handling practices of Irish Consumers" from July to November 2020 and generated a total of 1916 responses. Results indicated that 79.9% of the studied Irish population had a good knowledge of salmonellosis and risk perception related to food handling practices. Knowledge of cross-contamination, hygienic practices and pathogens associated with poultry were also considered high. However, knowledge of meat handling was low at 44.9%. It was also observed that age, gender, marital status, gross annual income, and nationality were influential factors regarding the food safety knowledge of consumers, while age, marital status and gender indicated significant differences regarding awareness of correct food hygiene practices.

Rural Raccoons (Procyon lotor) Not Likely to Be a Major Driver of Antimicrobial Resistant Human Salmonella Cases in Southern Ontario, Canada: A One Health Epidemiological Assessment Using Whole-Genome Sequence Data

Non-typhoidal Salmonella infections represent a substantial burden of illness in humans, and the increasing prevalence of antimicrobial resistance among these infections is a growing concern. Using a combination of Salmonella isolate short-read whole-genome sequence data from select human cases, raccoons, livestock and environmental sources, and an epidemiological framework, our objective was to determine if there was evidence for potential transmission of Salmonella and associated antimicrobial resistance determinants between these different sources in the Grand River watershed in Ontario, Canada. Logistic regression models were used to assess the potential associations between source type and the presence of select resistance genes and plasmid incompatibility types. A total of 608 isolates were obtained from the following sources: humans (n = 58), raccoons (n = 92), livestock (n = 329), and environmental samples (n = 129). Resistance genes of public health importance, including blaCMY−2, were identified in humans, livestock, and environmental sources, but not in raccoons. Most resistance genes analyzed were significantly more likely to be identified in livestock and/or human isolates than in raccoon isolates. Based on a 3,002-loci core genome multi-locus sequence typing (cgMLST) scheme, human Salmonella isolates were often more similar to isolates from livestock and environmental sources, than with those from raccoons. Rare instances of serovars S. Heidelberg and S. Enteritidis in raccoons likely represent incidental infections and highlight possible acquisition and dissemination of predominantly poultry-associated Salmonella by raccoons within these ecosystems. Raccoon-predominant serovars were either not identified among human isolates (S. Agona, S. Thompson) or differed by more than 350 cgMLST loci (S. Newport). Collectively, our findings suggest that the rural population of raccoons on swine farms in the Grand River watershed are unlikely to be major contributors to antimicrobial resistant human Salmonella cases in this region.

Source attribution of salmonellosis by time and geography in New South Wales, Australia

BACKGROUND

Salmonella is a major cause of zoonotic illness around the world, arising from direct or indirect contact with a range of animal reservoirs. In the Australian state of New South Wales (NSW), salmonellosis is believed to be primarily foodborne, but the relative contribution of animal reservoirs is unknown.

METHODS

The analysis included 4543 serotyped isolates from animal reservoirs and 30,073 serotyped isolates from domestically acquired human cases in NSW between January 2008 and August 2019. We used a Bayesian source attribution methodology to estimate the proportion of foodborne Salmonella infections attributable to broiler chickens, layer chickens, ruminants, pigs, and an unknown or unsampled source. Additional analyses included covariates for four time periods and five levels of rurality.

RESULTS

A single serotype, S. Typhimurium, accounted for 65-75% of included cases during 2008-2014 but < 50% during 2017-2019. Attribution to layer chickens was highest during 2008-2010 (48.7%, 95% CrI 24.2-70.3%) but halved by 2017-2019 (23.1%, 95% CrI 5.7-38.9%) and was lower in the rural and remote populations than in the majority urban population. The proportion of cases attributed to the unsampled source was 11.3% (95% CrI 1.2%-22.1%) overall, but higher in rural and remote populations. The proportion of cases attributed to pork increased from approximately 20% in 2009-2016 to approximately 40% in 2017-2019, coinciding with a rise in cases due to Salmonella ser. 4,5,12:i:-.

CONCLUSION

Layer chickens were likely the primary reservoir of domestically acquired Salmonella infections in NSW circa 2010, but attribution to the source declined contemporaneously with increased vaccination of layer flocks and tighter food safety regulations for the handling of eggs.

Multistate Outbreak of Salmonella enterica Serovar Heidelberg with Unidentified Source, Australia, 2018-2019

We report a multistate Salmonella enterica serovar Heidelberg outbreak in Australia during 2018-2019. Laboratory investigation of cases reported across 5 jurisdictions over a 7-month period could not identify a source of infection but detected indicators of severity and invasiveness. The hospitalization rate of 36% suggested a moderately severe clinical picture.

Occurrence of Salmonella enterica in grey-headed flying foxes from New South Wales

Salmonella enterica and Campylobacter jejuni are significant foodborne zoonotic pathogens causing gastroenteritis in humans. Domestic animals are commonly implicated as reservoirs of S. enterica and C. jejuni, but both are also detected in wild animals. Salmonella enterica serovar Typhimurium is the most common cause of human salmonellosis in Australia; however, Salmonella enterica serovar Wangata is associated with sporadic human outbreaks in New South Wales and wild animals may be a potential reservoir. To determine if wild grey-headed flying foxes (GHFF; Pteropus poliocephalus) are reservoirs of Salmonella and Campylobacter, faecal samples were collected from three GHFF colonies in New South Wales and cultured for the presence of Salmonella and Campylobacter. One Salmonella isolate was cultured from 254 GHFF faecal samples (0.39%). Whole genome sequencing was used to genetically characterise the Salmonella isolate and perform phylogenetic analysis. The GHFF isolate was determined to be Salmonella Typhimurium ST19. The GHFF isolate carried a virulence plasmid and other virulence factors, but did not exhibit antimicrobial resistance. Phylogenetic analysis determined that the GHFF isolate was most closely related to a cluster of six isolates: four from human salmonellosis cases in Queensland and two from Australian livestock. Neither Campylobacter nor Salmonella Wangata were cultured from the 254 GHFF faecal samples. This study concluded that wild GHFF in New South Wales are not major reservoirs for Salmonella, and the zoonotic risks associated with S. enterica carriage by urban GHFF are low for the general public.

Salmonella, Food Safety and Food Handling Practices

Salmonellosis is the second most reported gastrointestinal disorder in the EU resulting from the consumption of Salmonella-contaminated foods. Symptoms include gastroenteritis, abdominal cramps, bloody diarrhoea, fever, myalgia, headache, nausea and vomiting. In 2018, Salmonella accounted for more than half of the numbers of foodborne outbreak illnesses reported in the EU. Salmonella contamination is mostly associated with produce such as poultry, cattle and their feeds but other products such as dried foods, infant formula, fruit and vegetable products and pets have become important. Efforts aimed at controlling Salmonella are being made. For example, legislation and measures put in place reduced the number of hospitalizations between 2014 and 2015. However, the number of hospitalizations started to increase in 2016. This calls for more stringent controls at the level of government and the private sector. Food handlers of "meat processing" and "Ready to Eat" foods play a crucial role in the spread of Salmonella. This review presents an updated overview of the global epidemiology, the relevance of official control, the disease associated with food handlers and the importance of food safety concerning salmonellosis.

Application of Whole-Genome Sequences and Machine Learning in Source Attribution of Salmonella Typhimurium

Prevention of the emergence and spread of foodborne diseases is an important prerequisite for the improvement of public health. Source attribution models link sporadic human cases of a specific illness to food sources and animal reservoirs. With the next generation sequencing technology, it is possible to develop novel source attribution models. We investigated the potential of machine learning to predict the animal reservoir from which a bacterial strain isolated from a human salmonellosis case originated based on whole-genome sequencing. Machine learning methods recognize patterns in large and complex data sets and use this knowledge to build models. The model learns patterns associated with genetic variations in bacteria isolated from the different animal reservoirs. We selected different machine learning algorithms to predict sources of human salmonellosis cases and trained the model with Danish Salmonella Typhimurium isolates sampled from broilers (n = 34), cattle (n = 2), ducks (n = 11), layers (n = 4), and pigs (n = 159). Using cgMLST as input features, the model yielded an average accuracy of 0.783 (95% CI: 0.77-0.80) in the source prediction for the random forest and 0.933 (95% CI: 0.92-0.94) for the logit boost algorithm. Logit boost algorithm was most accurate (valid accuracy: 92%, CI: 0.8706-0.9579) and predicted the origin of 81% of the domestic sporadic human salmonellosis cases. The most important source was Danish produced pigs (53%) followed by imported pigs (16%), imported broilers (6%), imported ducks (2%), Danish produced layers (2%), Danish produced cattle and imported cattle (<1%) while 18% was not predicted. Machine learning has potential for improving source attribution modeling based on sequence data. Results of such models can inform risk managers to identify and prioritize food safety interventions.