Objective 1: Identify the environmental drivers impacting the presence and variability of Salmonella enterica serotypes and other common food borne pathogens within local, natural, multi-use poultry production systems. Objective 2: Determine the linkage between phenotypes and genotypes of Salmonella enterica to find markers associated with colonization or invasion in chickens, as well as patterns of antibiotic resistances present in the poultry production environment. Objective 3: Test mixtures of Salmonella enterica serotypes that vary in their ability to invade and colonize hens to determine the ability of commensal-like serotypes reduce the ability of pathogenic serotypes to colonize and persist. This information will be used to assess and improve vaccination strategies and reduce the use of antibiotics. Objective 4: Determine the impact of infectious dosage of the various Salmonella enterica isolates on their ability to colonize and persist in egg-laying hens to facilitate their detection and reduction in poultry.
Reducing pathogenic Salmonella enterica in eggs and poultry products is facilitated by generating research that bridges the gap between laboratory and field application. This project focuses on small farms and associated processing facilities, their management practices, and characteristics of Salmonella enterica in these environments. This research will investigate which contributes more to pathogenic Salmonella enterica on-farm, namely environmental factors and management practices versus the genetics of the pathogen. Focusing on local farms facilitates access, consistent sampling schedules and communication with participating farmers. Additional experimentation will focus on the interaction between types of Salmonella enterica that rarely cause disease with those that frequently cause disease. Specifically, we will address how the farm-prevalent serovar Kentucky impacts recovery of invasive serovar Enteritidis from internal organs of hens. Expected outcomes for regulatory agencies, the poultry industry and the consumer include: 1) data-supported approaches for identifying risks associated with contamination of end products; 2) tools that facilitate characterization of Salmonella serovars and how mixtures correlate to epidemiological trends; 3) correlation of genomic markers to antimicrobial resistances present between and within Salmonella serovars; and 4) identification of best practices that help the producer raising smaller flocks reduce pathogens in consumer products. A summary meeting will be held with participating farmers to inform them of results in a confidential setting, and how results might be used to advise management practices such as the decision to vaccinate and to raise mixed species of animals on-farm.
ARS researchers in Athens, Georgia, and Gainesville, Florida, find a genomic nucleotide motif that appears to distinguish Salmonella enterica from other eubacteria. Previous research had identified that single nucleotide (homopolymer) strings of adenines and thymines (specifically, AAAAAAAA or TTTTTTTT, and longer strings) might be prone to spontaneous mutation in Salmonella enterica. To characterize these motifs further, homopolymers were catalogued within the genomes of serotypes Typhimurium, Gallinarum, and Enteritidis. The prototypical reference strain for all foodborne Salmonella is Typhimurium LT2, and it had a total of 298 AT homopolymers that were present at close to the same percentage within genes and outside of genes. After analyzing other gram-positive and gram-negative pathogens, AT homopolymers appear to be a motif that varies greatly between different bacterial genera that are separated by evolutionary lineage and disease-causing potential. Results suggest that analysis of AT homopolymers is an efficient way to identify genes undergoing natural mutation across serotypes of Salmonella enterica; in addition, patterns of homopolymers may be prognostic for disease-causing potential of eubacteria. ARS researchers in Athens, Georgia, develop foodborne-pathogen predictive models for pastured, poultry-based management systems. Pastured poultry flocks are exposed to numerous environmental variables, and thus there is great interest in understanding which variables affect the safety of the poultry products throughout the poultry production chain. Previous work in our lab developed Listeria spp. and Salmonella enterica predictive models, and these models are being expanded to include (1) Campylobacter data and (2) using pathogen-specific microbiome 16S sequence data. The use of sequence data, as opposed to the cultural recovery data, allowed us to include microbial taxa relative abundance data in the models, expanding on the potential meteorological and farm management predicting variables currently employed. Preliminary results suggest that several environmental factors may be predictive of Campylobacter prevalence in both pre-harvest (fecal) and post-harvest (final product, whole-carcass rinses) samples, and that microbiome 16S sequence data shows the potential to greatly expand the utility of these models.
1. Low-dose infection of the egg-laying hen with Salmonella enterica serotype Enteritidis has risk for egg contamination as much or more than somewhat higher doses. Salmonella enterica serovar Enteritidis is the leading cause of salmonellosis in people, and modeling of infections in chickens is used to identify intervention strategies. To address a lack of information on the impact of low dose infections impacting organ invasion in the hen at lay, ARS researchers in Athens, Georiga, conducted two experiments in triplicate. Experiment A hens were infected intramuscularly with 1,000, 100,000, and 10,000,000 cells, and hens in Experiment B were infected orally with 5000 cells with 4 strains from different genomic clades. Results from sampling the liver, spleen, ovarian pedicle, and paired ceca indicated that dosages of 1000 cells in both experiments produced positive samples. The kinetics of infection appeared to differ between low and high dosages suggestive of a J-curve response, which meant a very small dose of 1000 cells has potential to result in more positive organs than a somewhat higher dose of 100,000 cells. Thus, the risk for hens becoming orally infected and producing eggs contaminated by Salmonella enterica serotype Enteritidis is still present even as the number of bacterial cells in the poultry environment is decreased.
2. Application of predictive algorithms throughout the pastured poultry farm-to-fork continuum was effective for predicting Salmonella spp. prevalence. In order to predict the prevalence of Salmonella during pastured poultry production, ARS researchers in Athens, Georgia, used random forest modeling in combination with questionnaire-based farm-management data and meteorological data for the origin farms. The predictive modeling showed that years farming, broiler flock age, and dominant feed components were major farm management drivers for Salmonella prevalence in preharvest samples, while dominant feed components was the most relevant drivers of Salmonella prevalence in post-harvest samples. Average temperature, humidity and high wind gust speeds prior to sampling were the meteorological variables that most closely correlated to Salmonella prevalence in preharvest samples. These data provide stakeholders with target variables to monitor to determine potential Salmonella food safety risks within their management systems.
Rothrock Jr, M.J., Locatelli, A., Feye, K.M., Caudill, A.J., Guard, J.Y., Hiett, K., Ricke, S.C. 2019. A microbiomic analysis of a pasture-raised broiler flock elucidates foodborne pathogen ecology along the farm-to-fork continuum. Frontiers in Veterinary Science. 6:260.
Hwang, D., Rothrock Jr, M.J., Pang, H., Kumar, G., Mishra, A. 2020. Farm management practices that affect the prevalence of Salmonella in pastured poultry farms. LWT - Food Science and Technology. v. 127. https://doi.org/10.1016/j.lwt.2020.109423.
Guard, J.Y., Rothrock Jr, M.J., Jones, D.R., Gast, R.K. 2020. Low dose infection of hens in lay with Salmonella enterica serovar Enteritidis from different genomic clades. Avian Diseases. 64(1):7-15. https://doi.org/10.1637/0005-2086-64.1.7.
Hwang, D., Rothrock Jr, M.J., Pang, H., Guo, M., Mishra, A. 2020. Predicting Salmonella prevalence associated with meteorological factors in pastured poultry farms in southeastern United States. Science of the Total Environment. 713. https://doi.org/10.1016/j.scitotenv.2019.136359.