Identification of Brucella genus and eight Brucella species by Luminex bead-based suspension array.

Globally, unpasteurized milk products are vehicles for the transmission of brucellosis, a zoonosis responsible for cases of foodborne illness in the United States and elsewhere. Existing PCR assays to detect Brucella species are restricted by the resolution of band sizes on a gel or the number of fluorescent channels in a single real-time system. The Luminex bead-based suspension array is performed in a 96-well plate allowing for high throughput screening of up to 100 targets in one sample with easily discernible results. We have developed an array using the Bio-Plex 200 to differentiate the most common Brucella species: B. abortus, B. melitensis, B. suis, B. suis bv5, B. canis, B. ovis, B. pinnipedia, and B. neotomae, as well as Brucella genus. All probes showed high specificity, with no cross-reaction with non-Brucella strains. We could detect pure DNA from B. abortus, B. melitensis, and genus-level Brucella at concentrations of ≤5 fg/µL. Pure DNA from all other species tested positive at concentrations well below 500 fg/µL and we positively identified B. neotomae in six artificially contaminated cheese and milk products. An intra-laboratory verification further demonstrated the assay's accuracy and robustness in the rapid screening (3-4 h including PCR) of DNA.

High-Resolution Microbiome Profiling for Detection and Tracking of Salmonella enterica.

16S rRNA community profiling continues to be a useful tool to study microbiome composition and dynamics, in part due to advances in next generation sequencing technology that translate into reductions in cost. Reliable taxonomic identification to the species-level, however, remains difficult, especially for short-read sequencing platforms, due to incomplete coverage of the 16S rRNA gene. This is especially true for Salmonella enterica, which is often found as a low abundant member of the microbial community, and is often found in combination with several other closely related enteric species. Here, we report on the evaluation and application of Resphera Insight, an ultra-high resolution taxonomic assignment algorithm for 16S rRNA sequences to the species level. The analytical pipeline achieved 99.7% sensitivity to correctly identify S. enterica from WGS datasets extracted from the FDA GenomeTrakr Bioproject, while demonstrating 99.9% specificity over other Enterobacteriaceae members. From low-diversity and low-complexity samples, namely ice cream, the algorithm achieved 100% specificity and sensitivity for Salmonella detection. As demonstrated using cilantro and chili powder, for highly complex and diverse samples, especially those that contain closely related species, the detection threshold will likely have to be adjusted higher to account for misidentifications. We also demonstrate the utility of this approach to detect Salmonella in the clinical setting, in this case, bloodborne infections.