A longitudinal study to examine the influence of farming practices and environmental factors on pathogen prevalence using structural equation modeling.

The contamination of fresh produce with foodborne pathogens has been an on-going concern with outbreaks linked to these commodities. Evaluation of farm practices, such as use of manure, irrigation water source, and other factors that could influence pathogen prevalence in the farming environment could lead to improved mitigation strategies to reduce the potential for contamination events. Soil, water, manure, and compost were sampled from farms in Ohio and Georgia to identify the prevalence of Salmonella, Listeria monocytogenes (Lm), Campylobacter, and Shiga-toxin-producing Escherichia coli (STEC), as well as Arcobacter, an emerging human pathogen. This study investigated agricultural practices to determine which influenced pathogen prevalence, i.e., the percent positive samples. These efforts identified a low prevalence of Salmonella, STEC, and Campylobacter in soil and water (< 10%), preventing statistical modeling of these pathogens. However, Lm and Arcobacter were found in soil (13 and 7%, respectively), manure (49 and 32%, respectively), and water samples (18 and 39%, respectively) at a comparatively higher prevalence, suggesting different dynamics are involved in their survival in the farm environment. Lm and Arcobacter prevalence data, soil chemical characteristics, as well as farm practices and weather, were analyzed using structural equation modeling to identify which factors play a role, directly or indirectly, on the prevalence of these pathogens. These analyses identified an association between pathogen prevalence and weather, as well as biological soil amendments of animal origin. Increasing air temperature increased Arcobacter and decreased Lm. Lm prevalence was found to be inversely correlated with the use of surface water for irrigation, despite a high Lm prevalence in surface water suggesting other factors may play a role. Furthermore, Lm prevalence increased when the microbiome's Simpson's Diversity Index decreased, which occurred as soil fertility increased, leading to an indirect positive effect for soil fertility on Lm prevalence. These results suggest that pathogen, environment, and farm management practices, in addition to produce commodities, all need to be considered when developing mitigation strategies. The prevalence of Arcobacter and Lm versus the other pathogens suggests that multiple mitigation strategies may need to be employed to control these pathogens.

Genetic and resistance phenotypic subtyping of Salmonella Saintpaul isolates from various food sources and humans: Phylogenetic concordance in combinatory analyses.

Bacterial pathogen subtyping for public health traceback of foodborne outbreaks has increasingly produced a number of disparate molecular techniques of varying resolution. Here, we bridge the molecular divide across three methodologies, transform data types for cross-comparison, and test phylogenetic concordance. Single nucleotide polymorphism (SNP) discovery was combined with pulsed-field gel electrophoresis (PFGE) and antimicrobial susceptibility profiles for identifying and differentiating 183 strains of closely related Salmonella enterica serovar Saintpaul isolates from retail meats, produce-associated outbreaks, and clinical sources. Fifty-six SNPs across 30 different genes were identified by comparative genomic analysis. These SNPs stratified general, monophyletic S. Saintpaul serovar specific signatures down to informative strain-specific markers. This SNP panel resulted in 17 distinct genotypes that, in concert with standard PFGE profiling, generated additional discriminatory power among clonal swarms of isolates when the data were transformed into a cross-comparable binary format. In a limited number of cases, antimicrobial susceptibility profiles (ASP) provided additional attributes for some strains when combined similarly. However, as expected from presumably acquired elements, resistant and susceptible populations produced some conflicting signals in most clonal complexes but they remained largely undisruptive to the general concordance. Taken in concert together, the three datasets (SNPs, PFGE,ASP) yielded a matrix of 156 independent phylogenetic characters that were statistically evaluated and found to be largely congruent, resulting in a consistently structured, non-homoplastic, phylogenetic signal and tree topology.

Single nucleotide polymorphism (SNP)-based differentiation of Shigella isolates by pyrosequencing.

Analysis of single nucleotide polymorphisms (SNPs) is an important genetic tool that provides molecular markers for rapid differentiation of closely related strains. We have applied SNP discovery and analysis for distinguishing each of the four Shigella serogroups (Boydii, Dysenteriae, Flexneri, and Sonnei) and for discriminating individual strains within the same serogroup by using 24 SNPs selected from nine genes. Five SNPs were identified from sequence analysis of two housekeeping genes (gapA and thrB) used previously in our lab to differentiate Shigella isolates into distinct lineages. The remaining 19 SNPs were identified by in silico analyses of eight Shigella genomes and are within the genes lpxC, sanA, yaaH, ybaP, ygaZ, yhbO, and ynhA. A total of 118 Shigella strains comprising 20 Boydii, 29 Dysenteriae, 42 Flexneri, and 27 Sonnei isolates were analyzed using the SNP typing scheme reported here. The combination of the 24 SNPs resulted in the identification of 26 SNP genotypes among the four Shigella serogroups and also provided some discriminatory resolution among individual strains within the same serogroup. The SNPs presented here should prove useful in identifying Shigella using PCR amplification and rapid sequence typing strategies.

Bacillus alcalophilus peptidoglycan induces IFN-alpha-mediated inhibition of vaccinia virus replication.

Bacterial products such as cell walls (CW) and peptidoglycan (PGN) are known to activate macrophages and NK cells during microbial infections. In this report, we demonstrated that whole CW and PGN of four Gram-positive bacteria are capable of enhancing the anti-poxviral activity of murine macrophage RAW 264.7 cells. Among the major Bacillus alcalophilus CW components, PGN contributes the most to antiviral activity and induces remarkably higher levels of IFN-alpha. Anti-IFN-alpha/beta antibody, but not anti-IFN-gamma, anti-IFN-gamma receptor, or anti-IL-12, reversed the PGN-induced inhibition of vaccinia virus replication and reduced nitric oxide (NO) production. Our data thus suggest that PGN induce antiviral activity through IFN-alpha and to a lesser extent, through NO production.

IL-15 induces IFN-beta and iNOS gene expression, and antiviral activity of murine macrophage RAW 264.7 cells.

The effects of interleukine-15 (IL-15) on macrophage activation and antiviral activity have been investigated in this study. We have provided evidence that IL-15 stimulates murine macrophage RAW 264.7 cells to release nitric oxide (NO) and inhibit vaccinia virus (VV) replication in bystander human 293 cells in a dose-dependent manner. The IL-15-induced antiviral activity was partially mediated by NO, as blocking NO production by NO synthase (iNOS) inhibitor NG-monomethyl-L-arginine acetate (L-NMA) partially restored the virus replication. Interferon-gamma (IFN-gamma) was not detectable by ELISA in the cell supernatant of IL-15-activated macrophages or in the co-cultures of macrophages and infected bystander cells. Neutralizing anti-IFN-gamma, anti-IFN-gamma receptor R2, anti-TNF-alpha, or anti-IL-12 antibodies had no effect on NO production or antiviral activity. In contrast, neutralizing anti-IFN-alpha/beta antibody completely restored the VV replication and reduced the NO level to one third of that in the control. Elevated mRNA levels of IFN-beta and iNOS genes were detected in IL-15-activated RAW 264.7 cells by RT-PCR. Our data suggest that IL-15 is capable of inducing IFN-beta, which could participate in NO-mediated antiviral effect.