Non-typhoidal human salmonellosis in Rio Grande do Sul, Brazil: A combined source attribution study of microbial subtyping and outbreak data

Investigating desiccation resistance, post-rehydration growth, and heat tolerance in desiccation-injured cells of Salmonella enterica isolated from the soybean production chain

This study compared the resistance to different desiccation conditions of 190 Salmonella enterica strains previously isolated from the soybean meal production chain and belonging to 23 serovars. Additionally, the post-rehydration growth and heat tolerance of the strains previously exposed to desiccation were determined. Variability in desiccation resistance was observed both within and between serovars. Strains belonging to S. Havana and S. Schwarzengrund serovars were the most resistant, regardless of storage condition. The drying temperature (20 °C and 30 °C) did not influence the desiccation resistance of the Salmonella strains. On the other hand, increasing drying time from 1 to 7 days reduced Salmonella counts. The origin (isolation sources) also influenced the desiccation resistance of the Salmonella strains. The growth of the Salmonella strains after rehydration varied considerably depending on the drying conditions and incubation temperature during cultivation. An increase in the time and temperature of drying led to a reduction in population of most Salmonella strains after rehydration. Salmonella strains previously desiccated also showed differences in the heat tolerance in all temperature-time binomials tested. Some strains were highly resistant to heat tolerance conditions, presenting <1 log CFU/mL reduction from the initial population. The results obtained in this study suggest that the strategies to mitigate Salmonella in low-aw foods must consider the existence of high-stress resistant strains and their multiple-stress adaptability profiles, including effects of processing, food composition, and storage conditions.

Recent Advances in Electrochemical Biosensors for the Detection of Foodborne Pathogens: Current Perspective and Challenges

Foodborne pathogens cause many diseases and significantly impact human health and the economy. Foodborne pathogens mainly include Salmonella spp., Escherichia coli, Staphylococcus aureus, Shigella spp., Campylobacter spp. and Listeria monocytogenes, which are present in agricultural products, dairy products, animal-derived foods and the environment. Various pathogens in many different types of food and water can cause potentially life-threatening diseases and develop resistance to various types of antibiotics. The harm of foodborne pathogens is increasing, necessitating effective and efficient methods for early monitoring and detection. Traditional methods, such as real-time polymerase chain reaction (RT-PCR), enzyme-linked immunosorbent assay (ELISA) and culture plate, are time-consuming, labour-intensive and expensive and cannot satisfy the demands of rapid food testing. Therefore, new fast detection methods are urgently needed. Electrochemical biosensors provide consumer-friendly methods to quickly detect foodborne pathogens in food and the environment and achieve extensive accuracy and reproducible results. In this paper, by focusing on various mechanisms of electrochemical transducers, we present a comprehensive overview of electrochemical biosensors for the detection of foodborne pathogens. Furthermore, the review introduces the hazards of foodborne pathogens, risk analysis methods and measures of control. Finally, the review also emphasizes the recent research progress and solutions regarding the use of electrochemical biosensors to detect foodborne pathogens in food and the environment, evaluates limitations and challenges experienced during the development of biosensors to detect foodborne pathogens and discusses future possibilities.

Comparison of Source Attribution Methodologies for Human Campylobacteriosis

Campylobacter spp. are the most common cause of bacterial gastrointestinal infection in humans both in Denmark and worldwide. Studies have found microbial subtyping to be a powerful tool for source attribution, but comparisons of different methodologies are limited. In this study, we compare three source attribution approaches (Machine Learning, Network Analysis, and Bayesian modeling) using three types of whole genome sequences (WGS) data inputs (cgMLST, 5-Mers and 7-Mers). We predicted and compared the sources of human campylobacteriosis cases in Denmark. Using 7mer as an input feature provided the best model performance. The network analysis algorithm had a CSC value of 78.99% and an F1-score value of 67%, while the machine-learning algorithm showed the highest accuracy (98%). The models attributed between 965 and all of the 1224 human cases to a source (network applying 5mer and machine learning applying 7mer, respectively). Chicken from Denmark was the primary source of human campylobacteriosis with an average percentage probability of attribution of 45.8% to 65.4%, representing Bayesian with 7mer and machine learning with cgMLST, respectively. Our results indicate that the different source attribution methodologies based on WGS have great potential for the surveillance and source tracking of Campylobacter. The results of such models may support decision makers to prioritize and target interventions.

Critically Important Antimicrobial Resistance Trends in Salmonella Derby and Salmonella Typhimurium Isolated from the Pork Production Chain in Brazil: A 16-Year Period

Knowledge about antimicrobial resistance in Salmonella is relevant due to its importance in foodborne diseases. We gathered data obtained over 16 years in the southern Brazilian swine production chain to evaluate the temporal evolution of halo for carbapenem, and the MIC for third-generation cephalosporins, fluoroquinolone, and polymyxin in 278 Salmonella Derby and Typhimurium isolates. All antimicrobial resistance assays were performed in accordance with EUCAST. To assess the diameter halo, we used a mixed linear model, and to assess the MIC, an accelerated failure time model for interval-censored data using an exponential distribution was used. The linear predictor of the models comprised fixed effects for matrix, serovar, and the interaction between year, serovar, and matrix. The observed halo diameter has decreased for ertapenem, regardless of serovars and matrices, and for the serovar Typhimurium it has decreased for three carbapenems. The MIC for ciprofloxacin and cefotaxime increased over 16 years for Typhimurium, and for Derby (food) it decreased. We did not find evidence that the MIC for colistin, ceftazidime, ciprofloxacin (Derby), or cefotaxime (food Typhimurium and animal Derby) has changed over time. This work gave an overview of antimicrobial resistance evolution from an epidemiological point of view and observed that using this approach can increase the sensitivity and timeliness of antimicrobial resistance surveillance.

Emergence, Dissemination and Antimicrobial Resistance of the Main Poultry-Associated Salmonella Serovars in Brazil

Salmonella infects poultry, and it is also a human foodborne pathogen. This bacterial genus is classified into several serovars/lineages, some of them showing high antimicrobial resistance (AMR). The ease of Salmonella transmission in farms, slaughterhouses, and eggs industries has made controlling it a real challenge in the poultry-production chains. This review describes the emergence, dissemination, and AMR of the main Salmonella serovars and lineages detected in Brazilian poultry. It is reported that few serovars emerged and have been more widely disseminated in breeders, broilers, and layers in the last 70 years. Salmonella Gallinarum was the first to spread on the farms, remaining as a concerning poultry pathogen. Salmonella Typhimurium and Enteritidis were also largely detected in poultry and foods (eggs, chicken, turkey), being associated with several human foodborne outbreaks. Salmonella Heidelberg and Minnesota have been more widely spread in recent years, resulting in frequent chicken/turkey meat contamination. A few more serovars (Infantis, Newport, Hadar, Senftenberg, Schwarzengrund, and Mbandaka, among others) were also detected, but less frequently and usually in specific poultry-production regions. AMR has been identified in most isolates, highlighting multi-drug resistance in specific poultry lineages from the serovars Typhimurium, Heidelberg, and Minnesota. Epidemiological studies are necessary to trace and control this pathogen in Brazilian commercial poultry production chains.