Longitudinal Approaches for Metagenomic Characterization of the Puget Sound for Environmental Health Surveillance

Abstract

The marine environment is the largest, most diverse and influential ecosystem on Earth. Still largely unexplored, the foundation for further ocean exploration begins with the most abundant and productive life forms in the ocean, the microbial communities. Microbes are essential to all life and play an intimate role in ecosystem function and environmental health. Microbial diversity and community function are important metrics that can be used to monitor and predict environmental changes. Standard lab techniques used for environmental microbial assessment are limited in scope and high-throughput, comprehensive approaches offer a tremendous opportunity to expand our estimates and monitoring of microbial diversity. Metagenomic profiling offers a sensitive approach to evaluate intact community genomes for the novel detection and characterization of microbial populations. Its gene-based, population level surveillance provides advanced insight into uncultured organisms broadening our understanding of microbial environments, community composition and functional potential. In addition to ecological relevance, metagenomic surveillance creates translational research opportunities for monitoring environmentally hosted human health determinants. The objective of this study was to further define the Puget Sound metagenome by expanding our assessment of coastal areas and their environmental signals of human impact and environmental health relevance. This is the second metagenomic study of the Puget Sound, and includes the addition and characterization of seven metagenomes, comprising a total of 14 samples from 10 different locations including a proximal wastewater treatment plant that discharges effluent into the Puget Sound. This longitudinal study uses 454 next generation sequencing, field metadata, and bioinformatic analysis to profile the surface water bacterial communities of the Puget Sound, both temporally and spatially, to characterize community composition, functional potential, and human health determinants. Our results revealed the high reproducibility and discriminatory capabilities of metagenomic profiling. Repeat samples taken approximately a year apart exhibited highly similar composition, while repeat samples taken during different seasons displayed considerable compositional differences suggesting that environmental conditions influence taxonomic relative abundance. Comparative analysis of all metagenomes exposed significant differences in both microbial diversity and human health determinants across a gradient of anthropogenic impact. These results demonstrate our improved characterization of the Puget Sound Metagenome and build capacity toward future bioinformatic applications in environmental monitoring and public health decision-making.