Year-Long Metagenomic Study of River Microbiomes Across Land Use and Water Quality.

Select bacteria, such as Escherichia coli or coliforms, have been widely used as sentinels of low water quality; however, there are concerns regarding their predictive accuracy for the protection of human and environmental health. To develop improved monitoring systems, a greater understanding of bacterial community structure, function, and variability across time is required in the context of different pollution types, such as agricultural and urban contamination. Here, we present a year-long survey of free-living bacterial DNA collected from seven sites along rivers in three watersheds with varying land use in Southwestern Canada. This is the first study to examine the bacterial metagenome in flowing freshwater (lotic) environments over such a time span, providing an opportunity to describe bacterial community variability as a function of land use and environmental conditions. Characteristics of the metagenomic data, such as sequence composition and average genome size (AGS), vary with sampling site, environmental conditions, and water chemistry. For example, AGS was correlated with hours of daylight in the agricultural watershed and, across the agriculturally and urban-affected sites, k-mer composition clustering corresponded to nutrient concentrations. In addition to indicating a community shift, this change in AGS has implications in terms of the normalization strategies required, and considerations surrounding such strategies in general are discussed. When comparing abundances of gene functional groups between high- and low-quality water samples collected from an agricultural area, the latter had a higher abundance of nutrient metabolism and bacteriophage groups, possibly reflecting an increase in agricultural runoff. This work presents a valuable dataset representing a year of monthly sampling across watersheds and an analysis targeted at establishing a foundational understanding of how bacterial lotic communities vary across time and land use. The results provide important context for future studies, including further analyses of watershed ecosystem health, and the identification and development of biomarkers for improved water quality monitoring systems.

Genomic analysis identifies targets of convergent positive selection in drug-resistant Mycobacterium tuberculosis.

M. tuberculosis is evolving antibiotic resistance, threatening attempts at tuberculosis epidemic control. Mechanisms of resistance, including genetic changes favored by selection in resistant isolates, are incompletely understood. Using 116 newly sequenced and 7 previously sequenced M. tuberculosis whole genomes, we identified genome-wide signatures of positive selection specific to the 47 drug-resistant strains. By searching for convergent evolution--the independent fixation of mutations in the same nucleotide position or gene--we recovered 100% of a set of known resistance markers. We also found evidence of positive selection in an additional 39 genomic regions in resistant isolates. These regions encode components in cell wall biosynthesis, transcriptional regulation and DNA repair pathways. Mutations in these regions could directly confer resistance or compensate for fitness costs associated with resistance. Functional genetic analysis of mutations in one gene, ponA1, demonstrated an in vitro growth advantage in the presence of the drug rifampicin.