Transmission dynamics of a multidrug-resistant Salmonella typhimurium outbreak in a dairy farm

Genomic Characterization of Salmonella Typhimurium Isolated from Guinea Pigs with Salmonellosis in Lima, Peru

Salmonella enterica subsp. enterica serovar Typhimurium (S. Typhimurium) is one of the most important foodborne pathogens that infect humans globally. The gastrointestinal tracts of animals like pigs, poultry or cattle are the main reservoirs of Salmonella serotypes. Guinea pig meat is an important protein source for Andean countries, but this animal is commonly infected by S. Typhimurium, producing high mortality rates and generating economic losses. Despite its impact on human health, food security, and economy, there is no genomic information about the S. Typhimurium responsible for the guinea pig infections in Peru. Here, we sequence and characterize 11 S. Typhimurium genomes isolated from guinea pigs from four farms in Lima-Peru. We were able to identify two genetic clusters (HC100_9460 and HC100_9757) distinguishable at the H100 level of the Hierarchical Clustering of Core Genome Multi-Locus Sequence Typing (HierCC-cgMLST) scheme with an average of 608 SNPs of distance. All sequences belonged to sequence type 19 (ST19) and HC100_9460 isolates were typed in silico as monophasic variants (1,4,[5],12:i:-) lacking the fljA and fljB genes. Phylogenomic analysis showed that human isolates from Peru were located within the same genetic clusters as guinea pig isolates, suggesting that these lineages can infect both hosts. We identified a genetic antimicrobial resistance cassette carrying the ant(3)-Ia, dfrA15, qacE, and sul1 genes associated with transposons TnAs3 and IS21 within an IncI1 plasmid in one guinea pig isolate, while antimicrobial resistance genes (ARGs) for β-lactam (blaCTX-M-65) and colistin (mcr-1) resistance were detected in Peruvian human-derived isolates. The presence of a virulence plasmid highly similar to the pSLT plasmid (LT2 reference strain) containing the spvRABCD operon was found in all guinea pig isolates. Finally, seven phage sequences (STGP_Φ1 to STGP_Φ7) were identified in guinea pig isolates, distributed according to the genetic lineage (H50 clusters level) and forming part of the specific gene content of each cluster. This study presents, for the first time, the genomic characteristics of S. Typhimurium isolated from guinea pigs in South America, showing particular diversity and genetic elements (plasmids and prophages) that require special attention and also broader studies in different periods of time and locations to determine their impact on human health.

Dairy management practices associated with multi-drug resistant fecal commensals and Salmonella in cull cows: a machine learning approach

Background

Understanding the effects of herd management practices on the prevalence of multidrug-resistant pathogenic Salmonella and commensals Enterococcus spp. and Escherichia coli in dairy cattle is key in reducing antibacterial resistant infections in humans originating from food animals. Our objective was to explore the herd and cow level features associated with the multi-drug resistant, and resistance phenotypes shared between Salmonella, E. coli and Enterococcus spp. using machine learning algorithms.

Methods

Randomly collected fecal samples from cull dairy cows from six dairy farms in central California were tested for multi-drug resistance phenotypes of Salmonella, E. coli and Enterococcus spp. Using data on herd management practices collected from a questionnaire, we built three machine learning algorithms (decision tree classifier, random forest, and gradient boosting decision trees) to predict the cows shedding multidrug-resistant Salmonella and commensal bacteria.

Results

The decision tree classifier identified rolling herd average milk production as an important feature for predicting fecal shedding of multi-drug resistance in Salmonella or commensal bacteria. The number of culled animals, monthly culling frequency and percentage, herd size, and proportion of Holstein cows in the herd were found to be influential herd characteristics predicting fecal shedding of multidrug-resistant phenotypes based on random forest models for Salmonella and commensal bacteria. Gradient boosting models showed that higher culling frequency and monthly culling percentages were associated with fecal shedding of multidrug resistant Salmonella or commensal bacteria. In contrast, an overall increase in the number of culled animals on a culling day showed a negative trend with classifying a cow as shedding multidrug-resistant bacteria. Increasing rolling herd average milk production and spring season were positively associated with fecal shedding of multidrug- resistant Salmonella. Only six individual cows were detected sharing tetracycline resistance phenotypes between Salmonella and either of the commensal bacteria.

Discussion

Percent culled and culling rate reflect the increase in culling over time adjusting for herd size and were associated with shedding multidrug resistant bacteria. In contrast, number culled was negatively associated with shedding multidrug resistant bacteria which may reflect producer decisions to prioritize the culling of otherwise healthy but low-producing cows based on milk or beef prices (with respect to dairy beef), amongst other factors. Using a data-driven suite of machine learning algorithms we identified generalizable and distant associations between antimicrobial resistance in Salmonella and fecal commensal bacteria, that can help develop a producer-friendly and data-informed risk assessment tool to reduce shedding of multidrug-resistant bacteria in cull dairy cows.

Probiotics and potential applications for alternative poultry production systems

Concerns over animal welfare continue to be a critical component of law and policies associated with commercial food animal production. Social and market pressures are the driving forces behind the legislation and result in the change of poultry production management systems. As a result, the movement toward cage-free and aviary-based egg production systems has become standard practices. Cage-based systems being replaced by alternative methods that offer a suitable housing environment to meet or exceed poultry welfare needs and require different management, including the ban of antibiotics in poultry diets. For broiler production, pasture- raised and free-range management systems have become more popular. However, challenges remain from exposure to disease-causing organisms and foodborne pathogens in these environments. Consequently, probiotics can be supplemented in poultry diets as commercial feed additives. The present review discusses the impacts of these probiotics on the performance of alternative poultry production systems for improving food safety and poultry health by mitigating pathogenic organisms and improving egg and meat quality and production.

Drivers of ESBL-producing Escherichia coli dynamics in calf fattening farms: A modelling study

The contribution of bacteria in livestock to the global burden of antimicrobial resistance raises concerns worldwide. However, the dynamics of selection and diffusion of antimicrobial resistance in farm animals are not fully understood. Here, we used veal calf fattening farms as a model system, as they are a known reservoir of Extended Spectrum β-Lactamase-producing Escherichia coli (ESBL-EC). Longitudinal data of ESBL-EC carriage and antimicrobial use (AMU) were collected from three veal calf farms during the entire fattening process. We developed 18 agent-based mechanistic models to assess different hypotheses regarding the main drivers of ESBL-EC dynamics in calves. The models were independently fitted to the longitudinal data using Markov Chain Monte Carlo and the best model was selected. Within-farm transmission between individuals and sporadic events of contamination were found to drive ESBL-EC dynamics on farms. In the absence of AMU, the median carriage duration of ESBL-EC was estimated to be 19.6 days (95% credible interval: [12.7; 33.3]). In the best model, AMU was found to influence ESBL-EC dynamics, by affecting ESBL-EC clearance rather than acquisition. This effect of AMU was estimated to decrease gradually after the end of exposure and to disappear after 62.5 days [50.0; 76.9]. Moreover, using a simulation study, we quantified the efficacy of ESBL-EC mitigation strategies. Decreasing ESBL-EC prevalence by 50% on arrival at the fattening farm reduced prevalence at slaughter age by 33.3%. Completely eliminating the use of selective antibiotics on arrival had a strong effect on average ESBL-EC prevalence (relative reduction of 77.0%), but the effect was mild if this use was only decreased by 50% compared to baseline (relative reduction of 3.3%).

Relationships between Microbial Indicators and Pathogens in Recreational Water Settings

Fecal pollution of recreational waters can cause scenic blight and pose a threat to public health, resulting in beach advisories and closures. Fecal indicator bacteria (total and fecal coliforms, Escherichia coli, and enterococci), and alternative indicators of fecal pollution (Clostridium perfringens and bacteriophages) are routinely used in the assessment of sanitary quality of recreational waters. However, fecal indicator bacteria (FIB), and alternative indicators are found in the gastrointestinal tract of humans, and many other animals and therefore are considered general indicators of fecal pollution. As such, there is room for improvement in terms of their use for informing risk assessment and remediation strategies. Microbial source tracking (MST) genetic markers are closely associated with animal hosts and are used to identify fecal pollution sources. In this review, we examine 73 papers generated over 40 years that reported the relationship between at least one indicator and one pathogen group or species. Nearly half of the reports did not include statistical analysis, while the remainder were almost equally split between those that observed statistically significant relationships and those that did not. Statistical significance was reported less frequently in marine and brackish waters compared to freshwater, and the number of statistically significant relationships was considerably higher in freshwater (p < 0.0001). Overall, significant relationships were more commonly reported between FIB and pathogenic bacteria or protozoa, compared to pathogenic viruses (p: 0.0022⁻0.0005), and this was more pronounced in freshwater compared to marine. Statistically significant relationships were typically noted following wet weather events and at sites known to be impacted by recent fecal pollution. Among the studies that reported frequency of detection, FIB were detected most consistently, followed by alternative indicators. MST markers and the three pathogen groups were detected least frequently. This trend was mirrored by reported concentrations for each group of organisms (FIB > alternative indicators > MST markers > pathogens). Thus, while FIB, alternative indicators, and MST markers continue to be suitable indicators of fecal pollution, their relationship with waterborne pathogens, particularly viruses, is tenuous at best and influenced by many different factors such as frequency of detection, variable shedding rates, differential fate and transport characteristics, as well as a broad range of site-specific factors such as the potential for the presence of a complex mixture of multiple sources of fecal contamination and pathogens.

Application of dynamic modelling techniques to the problem of antibacterial use and resistance: a scoping review

Selective pressure exerted by the widespread use of antibacterial drugs is accelerating the development of resistant bacterial populations. The purpose of this scoping review was to summarise the range of studies that use dynamic models to analyse the problem of bacterial resistance in relation to antibacterial use in human and animal populations. A comprehensive search of the peer-reviewed literature was performed and non-duplicate articles (n = 1486) were screened in several stages. Charting questions were used to extract information from the articles included in the final subset (n = 81). Most studies (86%) represent the system of interest with an aggregate model; individual-based models are constructed in only seven articles. There are few examples of inter-host models outside of human healthcare (41%) and community settings (38%). Resistance is modelled for a non-specific bacterial organism and/or antibiotic in 40% and 74% of the included articles, respectively. Interventions with implications for antibacterial use were investigated in 67 articles and included changes to total antibiotic consumption, strategies for drug management and shifts in category/class use. The quality of documentation related to model assumptions and uncertainty varies considerably across this subset of articles. There is substantial room to improve the transparency of reporting in the antibacterial resistance modelling literature as is recommended by best practice guidelines.

Effects of antimicrobial use in agricultural animals on drug-resistant foodborne salmonellosis in humans: A systematic literature review

Controversy continues concerning antimicrobial use in food animals and its relationship to drug-resistant infections in humans. We systematically reviewed published literature for evidence of a relationship between antimicrobial use in agricultural animals and drug-resistant meat or dairy-borne non-typhoidal salmonellosis in humans. Based on publications from the United States (U.S.), Canada, and Denmark from January 2010 to July 2014, 858 articles received title and abstract review, 104 met study criteria for full article review with 68 retained for which data are presented. Antibiotic exposure in both cattle and humans found an increased likelihood of Salmonella colonization, whereas in chickens, animals not exposed to antibiotics (organic) were more likely to be Salmonella positive and those that had antibiotic exposure were more likely to harbor antimicrobial resistant Salmonella organisms. In swine literature, only tylosin exposure was examined and no correlation was found among exposure, Salmonella colonization, or antimicrobial resistance. No studies that identified farm antimicrobial use also traced antimicrobial-resistant Salmonella from farm to fork.

Progression to multi-scale models and the application to food system intervention strategies

The aim of this article is to discuss how the systems science approach can be used to optimize intervention strategies in food animal systems. It advocates the idea that the challenges of maintaining a safe food supply are best addressed by integrating modeling and mathematics with biological studies critical to formulation of public policy to address these challenges. Much information on the biology and epidemiology of food animal systems has been characterized through single-discipline methods, but until now this information has not been thoroughly utilized in a fully integrated manner. The examples are drawn from our current research. The first, explained in depth, uses clinical mastitis to introduce the concept of dynamic programming to optimize management decisions in dairy cows (also introducing the curse of dimensionality problem). In the second example, a compartmental epidemic model for Johne's disease with different intervention strategies is optimized. The goal of the optimization strategy depends on whether there is a relationship between Johne's and Crohn's disease. If so, optimization is based on eradication of infection; if not, it is based on the cow's performance only (i.e., economic optimization, similar to the mastitis example). The third example focuses on food safety to introduce risk assessment using Listeria monocytogenes and Salmonella Typhimurium. The last example, practical interventions to effectively manage antibiotic resistance in beef and dairy cattle systems, introduces meta-population modeling that accounts for bacterial growth not only in the host (cow), but also in the cow's feed, drinking water and the housing environment. Each example stresses the need to progress toward multi-scale modeling. The article ends with examples of multi-scale systems, from food supply systems to Johne's disease. Reducing the consequences of foodborne illnesses (i.e., minimizing disease occurrence and associated costs) can only occur through an understanding of the system as a whole, including all its complexities. Thus the goal of future research should be to merge disciplines such as molecular biology, applied mathematics and social sciences to gain a better understanding of complex systems such as the food supply chain.

Amelioration of salmonellosis in pre-weaned dairy calves fed Saccharomyces cerevisiae fermentation products in feed and milk replacer

Salmonellosis is an insidious and potentially epidemic problem in pre-weaned dairy calves. Managing this disease, or any other diarrheal disease, is a financial burden to producers. Calf mortalities and medicinal treatments are overt costs of salmonellosis, while hidden costs include hampered weight gains and persistent intestinal colonization of the pathogen. In this study, we examined the anti-Salmonella effects of Saccharomyces cerevisiae fermentation products (SCFP) incorporated into both the milk replacer and the starter grain. In a blinded study, 2-8 day-old calves were fed SCFP (n=20 calves) or an SCFP-free Control (n=20 calves) for two weeks before and three weeks after experimental challenge with Salmonella enterica serotype Typhimurium. Following the challenge, calves were monitored for clinical signs and parameters associated with salmonellosis. Calves were then euthanized and examined for rumen development and intestinal Salmonella colonization. When compared to calves that received milk replacer and feed lacking SCFP, calves fed SCFP had fewer bouts of diarrhea and fever. Rumens from these calves were more developed, as measured by the length of papillae, which is consistent with the enhanced weight gain observed in this treatment group. Additionally, Salmonella intestinal colonization was reduced in SCFP-fed calves and Salmonella fecal shedding disappeared at an earlier stage in these calves. This study revealed that the combination of two proprietary S. cerevisiae fermentation products provide marked benefit for preventing the negative effects of salmonellosis in pre-weaned dairy calves, while also boosting productivity. The mechanism of action needs to be clarified, but it may be related to the observed decrease in colonization by the pathogen and increase in rumen development.

Stochastic modeling of imperfect Salmonella vaccines in an adult dairy herd

Salmonella is a major cause of bacterial foodborne disease. Human salmonellosis results in significant public health concerns and a considerable economic burden. Dairy cattle are recognized as a key source of several Salmonella serovars that are a threat to human health. To lower the risk of Salmonella infection, reduction of Salmonella prevalence in dairy cattle is important. Vaccination as a control measure has been applied for reduction of preharvest Salmonella prevalence on dairy farms. Salmonella vaccines are usually imperfect (i.e., vaccines may provide a partial protection for susceptible animals, reduce the infectiousness and shedding level, shorten the infectious period of infected animals, and/or curb the number of clinical cases), and evaluation of the potential impacts of imperfect Salmonella vaccines at the farm level is valuable to design effective intervention strategies. The objective of this study was to investigate the impact of imperfect Salmonella vaccines on the stochastic transmission dynamics in an adult dairy herd. To this end, we developed a semi-stochastic and individual-based continuous time Markov chain (CTMC) vaccination model with both direct and indirect transmission, and applied the CTMC vaccination model to Salmonella Cerro transmission in an adult dairy herd. Our results show that vaccines shortening the infectious period are most effective in reducing prevalence, and vaccines decreasing host susceptibility are most effective in reducing the outbreak size. Vaccines with multiple moderate efficacies may have the same effectiveness as vaccines with a single high efficacy in reducing prevalence, time to extinction, and outbreak size. Although the environment component has negligible contributions to the prevalence, time to extinction, and outbreak size for Salmonella Cerro in the herd, the relative importance of environment component was not assessed. This study indicates that an effective vaccination program against Salmonella Cerro spread in the herd can be designed with (1) vaccines with a single high efficacy in reducing either the infectious period or susceptibility of the host, or (2) if such single high efficacy vaccines are not available, vaccines with multiple moderate efficacies may be considered instead. These findings are also of general value for designing vaccination program for Salmonella serotypes in livestock.

Spatial and temporal patterns in antimicrobial resistance of Salmonella Typhimurium in cattle in England and Wales

Salmonella is the second most commonly reported human foodborne pathogen in England and Wales, and antimicrobial-resistant strains of Salmonella are an increasing problem in both human and veterinary medicine. In this work we used a generalized linear spatial model to estimate the spatial and temporal patterns of antimicrobial resistance in Salmonella typhimurium in England and Wales. Of the antimicrobials considered we found a common peak in the probability that an S. typhimurium incident will show resistance to a given antimicrobial in late spring and in mid to late autumn; however, for one of the antimicrobials (streptomycin) there was a sharp drop, over the last 18 months of the period of investigation, in the probability of resistance. We also found a higher probability of resistance in North Wales which is consistent across the antimicrobials considered. This information contributes to our understanding of the epidemiology of antimicrobial resistance in Salmonella.

Prevalence, distribution, and diversity of Salmonella enterica in a major produce region of California

A survey was initiated to determine the prevalence of Salmonella enterica in the environment in and around Monterey County, CA, a major agriculture region of the United States. Trypticase soy broth enrichment cultures of samples of soil/sediment (n = 617), water (n = 252), wildlife (n = 476), cattle feces (n = 795), and preharvest lettuce and spinach (n = 261) tested originally for the presence of pathogenic Escherichia coli were kept in frozen storage and later used to test for the presence of S. enterica. A multipathogen oligonucleotide microarray was employed to identify a subset of samples that might contain Salmonella in order to test various culture methods to survey a larger number of samples. Fifty-five of 2,401 (2.3%) samples yielded Salmonella, representing samples obtained from 20 different locations in Monterey and San Benito Counties. Water had the highest percentage of positives (7.1%) among sample types. Wildlife yielded 20 positive samples, the highest number among sample types, with positive samples from birds (n = 105), coyotes (n = 40), deer (n = 104), elk (n = 39), wild pig (n = 41), and skunk (n = 13). Only 16 (2.6%) of the soil/sediment samples tested positive, and none of the produce samples had detectable Salmonella. Sixteen different serotypes were identified among the isolates, including S. enterica serotypes Give, Typhimurium, Montevideo, and Infantis. Fifty-four strains were sensitive to 12 tested antibiotics; one S. Montevideo strain was resistant to streptomycin and gentamicin. Pulsed-field gel electrophoresis (PFGE) analysis of the isolates revealed over 40 different pulsotypes. Several strains were isolated from water, wildlife, or soil over a period of several months, suggesting that they were persistent in this environment.

Mathematical modeling of the transmission and control of foodborne pathogens and antimicrobial resistance at preharvest

Foodborne diseases are a significant health-care and economic burden. Most foodborne pathogens are enteric pathogens harbored in the gastrointestinal tract of farm animals. Understanding the transmission of foodborne pathogens and the dissemination of antimicrobial resistance at the farm level is necessary to design effective control strategies at preharvest. Mathematical models improve our understanding of pathogen dynamics by providing a theoretical framework in which factors affecting transmission and control of the pathogens can be explicitly considered. In this review, we aim to present the principles underlying the mathematical modeling of foodborne pathogens and antimicrobial resistance at the farm level to a broader audience.