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Background: In 2007, a nationwide Salmonella Tennessee outbreak occurred via contaminated peanut butter. Here, we developed a single-nucleotide polymorphism (SNP)-typing method for S. Tennessee to determine the clonal subtypes of S. Tennessee that were associated with the peanut butter outbreak. Methods and results: One seventy-six S. Tennessee isolates from various sources, including humans, animals, food, and the environment, were analyzed by using the SNP technique. Eighty-four representative SNP markers were selected by comparing the sequences of three representative S. Tennessee strains with different multi-locus sequence typing and variable number tandem repeats from our collection. The set of eighty-four SNP markers showed 100% typeability for the 176 strains, with the nucleotide diversity ranging from 0.011 to 0.107 (mean = 0.049 ± 0.018, median = 0.044) for each marker. Among the four clades and nine subtypes generated by the SNP typing, subtype 1, which comprised 142 S. Tennessee strains, was the most predominant. The dominance of single-strain clones in subtype 1 revealed that S. Tennessee is highly clonal regardless of outbreak-association, source, or period of isolation, suggesting the presence of an S. Tennessee strain prototype. Notably, a minimum 18 SNP set was able to determine clonal S. Tennessee strains with similar discrimination power, potentially allowing more rapid and economic strain genotyping for both outbreaks and sporadic cases. Conclusions: The SNP-typing method described here might aid the investigation of the epidemiology and microevolution of pathogenic bacteria by discriminating between outbreak-related and sporadic clinical cases. In addition, this approach enables us to understand the population structure of the bacterial subtypes involved in the outbreak. [ABSTRACT FROM AUTHOR]

Background: Laboratory assays for determining recent HIV-1 infection are an important public health tool for aiding in the estimation of HIV incidence. Some incidence assay analytes are remarkably predictive of time since seroconversion and may be useful for additional applications, such as predicting recent transmission events during HIV outbreaks and informing prevention strategies., Methods: Plasma samples (n = 154) from a recent HIV-1 outbreak in a rural community in Indiana were tested with the customized HIV-1 Multiplex assay, based on the Bio-Rad Bio-Plex platform, which measures antibody response to HIV envelope antigens, gp120, gp160, and gp41. Assay cutoffs for each analyte were established to determine whether an individual seroconverted within 30, 60, or 90 days of the sample collection date. In addition, a novel bioinformatics method was implemented to infer infection dates of persons newly diagnosed with HIV during the outbreak., Results: Sensitivity/specificity of the HIV-1 Multiplex assay for predicting seroconversion within 30, 60, and 90 days, based on a training data set, was 90.5%/95.4%, 94.1%/90%, and 89.4%/82.9%, respectively. Of 154 new diagnoses in Indiana between December 2014 and August 2016, the majority (71%) of recent infections (≤3 months since seroconversion) were identified between February and May 2016. The epidemiologic curve derived from the bioinformatics analysis indicated HIV transmission began as early as 2010, grew exponentially in 2014, and leveled off in April 2015., Conclusions: The HIV-1 Multiplex assay has the potential to identify and monitor trends in recent infection during an epidemic to assess the efficacy of programmatic or treatment interventions.