Microbiome profiling through 16S rRNA gene sequence analysis has proven to be a useful research tool in the study of C. difficile infection (CDI); however, CDI microbiome studies typically report results at the genus level or higher, thus precluding identification of this pathogen relative to other members of the gut microbiota. Accurate identification of C. difficile relative to the overall gut microbiome may be useful in assessments of colonization in research studies or as a prognostic indicator for patients with CDI. To investigate the burden of C. difficile at the species level relative to the overall gut microbiome, we applied a high-resolution method for 16S rRNA sequence assignment to previously published gut microbiome studies of CDI and other patient populations. We identified C. difficile in 131 of 156 index cases of CDI (average abundance 1.78%), and 18 of 211 healthy controls (average abundance 0.008%). We further detected substantial levels of C. difficile in a subset of infants that persisted over the first two to 12 months of life. Correlation analysis of C. difficile burden compared to other detected species demonstrated consistent negative associations with C. scindens and multiple Blautia species. These analyses contribute insight into the relative burden of C. difficile in the gut microbiome for multiple patient populations, and indicate that high-resolution 16S rRNA gene sequence analysis may prove useful in the development and evaluation of new therapies for CDI.

Culture based methods are commonly employed to detect pathogens in food and environmental samples. These methods are time consuming and complex, requiring multiple non-selective and selective enrichment broths, and usually take at least 1 week to recover and identify pathogens. Improving pathogen detection in foods is a primary goal for regulatory agencies and industry. Salmonella detection in food relies on a series of culture steps in broth formulations optimized to resuscitate Salmonella and reduce the abundance of competitive bacteria. Examples of non-selective pre-enrichment broths used to isolate Salmonella from food include Lactose, Universal Pre-enrichment, BPW, and Trypticase Soy broths. Tetrathionate (TT) and Rappaport–Vassiliadis (RV) broths are employed after a 24-h non-selective enrichment to select for Salmonella and hamper the growth of competitive bacteria. In this study, we tested a new formulation of TT broth that lacks brilliant green dye and has lower levels of TT . We employed this TT broth formulation in conjunction with a 6-h non-selective pre-enrichment period and determined that Salmonella recovery was possible one day earlier than standard food culture methods. We tested the shortened culture method in different non-selective enrichment broths, enumerated Salmonella in the non-selective enrichments, and used 16S rRNA gene sequencing to determine the proportional abundances of Salmonella in the TT and RV selective enrichments. Together these data revealed that a 6-h non-selective pre-enrichment reduces the levels of competitive bacteria inoculated into the selective TT and RV broths, enabling the recovery of Salmonella 1 day earlier than standard culture enrichment methods.

Food microbiome composition impacts food safety and quality. The resident microbiota of many food products is influenced throughout the farm to fork continuum by farming practices, environmental factors, and food manufacturing and processing procedures. Currently, most food microbiology studies rely on culture-dependent methods to identify bacteria. However, advances in high-throughput DNA sequencing technologies have enabled the use of targeted 16S rRNA gene sequencing to profile complex microbial communities including non-culturable members. In this study we used 16S rRNA gene sequencing to assess the microbiome profiles of plant and animal derived foods collected at two points in the manufacturing process; post-harvest/pre-retail (cilantro) and retail (cilantro, masala spice mixes, cucumbers, mung bean sprouts, and smoked salmon). Our findings revealed microbiome profiles, unique to each food, that were influenced by the moisture content (dry spices, fresh produce), packaging methods, such as modified atmospheric packaging (mung bean sprouts and smoked salmon), and manufacturing stage (cilantro prior to retail and at retail). The masala spice mixes and cucumbers were comprised mainly of Proteobacteria, Firmicutes, and Actinobacteria. Cilantro microbiome profiles consisted mainly of Proteobacteria, followed by Bacteroidetes, and low levels of Firmicutes and Actinobacteria. The two brands of mung bean sprouts and the three smoked salmon samples differed from one another in their microbiome composition, each predominated by either by Firmicutes or Proteobacteria. These data demonstrate diverse and highly variable resident microbial communities across food products, which is informative in the context of food safety, and spoilage where indigenous bacteria could hamper pathogen detection, and limit shelf life.