Use of Deep Sequencing to Evaluate Transitions in Microbial Communities in Stranded .

Deep sequencing technologies can be used to evaluate pathogens in environmental samples. The objective of this study was to use this technology to evaluate samples that were characterized by different stranding times, one classified as short-term stranded (STS) and another classified as long-term stranded (LTS) . Nine replicates of the STS showed a range in Shannon diversity between 3.04 and 3.38, whereas 11 replicates of LTS showed a range between 1.17 and 1.22. Nonmetric multidimensional scaling analysis showed distinct differences between STS and LTS by about 0.5 coordinate units, while variations within replicates ranged by 0.1 coordinate units. Comparison between the two samples showed a greater abundance of species in STS when compared to LTS , with major pathogenic forms observed for (11%), (1.5%), and (0.29%). Additional known human pathogens were observed, including , , and , as well as the presence of gut commensals and fecal coliforms. Overall results show that deep sequencing analysis of these environmental samples was reproducible. Given the abundance of pathogenic bacteria, more research is needed to evaluate the risk of disease transmission as strands and decomposes on coastal beaches.