NanoARG: a web service for detecting and contextualizing antimicrobial resistance genes from nanopore-derived metagenomes.

BACKGROUND: Direct and indirect selection pressures imposed by antibiotics and co-selective agents and horizontal gene transfer are fundamental drivers of the evolution and spread of antibiotic resistance. Therefore, effective environmental monitoring tools should ideally capture not only antibiotic resistance genes (ARGs), but also mobile genetic elements (MGEs) and indicators of co-selective forces, such as metal resistance genes (MRGs). A major challenge towards characterizing the potential human health risk of antibiotic resistance is the ability to identify ARG-carrying microorganisms, of which human pathogens are arguably of greatest risk. Historically, short reads produced by next-generation sequencing technologies have hampered confidence in assemblies for achieving these purposes. RESULTS: Here, we introduce NanoARG, an online computational resource that takes advantage of the long reads produced by nanopore sequencing technology. Specifically, long nanopore reads enable identification of ARGs in the context of relevant neighboring genes, thus providing valuable insight into mobility, co-selection, and pathogenicity. NanoARG was applied to study a variety of nanopore sequencing data to demonstrate its functionality. NanoARG was further validated through characterizing its ability to correctly identify ARGs in sequences of varying lengths and a range of sequencing error rates. CONCLUSIONS: NanoARG allows users to upload sequence data online and provides various means to analyze and visualize the data, including quantitative and simultaneous profiling of ARGs, MRGs, MGEs, and putative pathogens. A user-friendly interface allows users the analysis of long DNA sequences (including assembled contigs), facilitating data processing, analysis, and visualization. NanoARG is publicly available and freely accessible at https://bench.cs.vt.edu/nanoarg .

Monochloramine decay in model and distribution system waters.

Chloramines have long been used to provide a disinfecting residual in distribution systems where it is difficult to maintain a free chlorine residual or where disinfection by-product (DBP) formation is of concern. While chloramines are generally considered less reactive than free chlorine, they are inherently unstable even in the absence of reactive substances. These reactions, often referred to as "auto-decomposition", always occur and hence define the maximum stability of monochloramine in water. The effect of additional reactive material must be measured relative to this basic loss process. A thorough understanding of the auto-decomposition reactions is fundamental to the development of mechanisms that account for reactions with additional substances and to the ultimate formation of DBPs. A kinetic model describing auto-decomposition was recently developed. This model is based on studies of isolated individual reactions and on observations of the reactive ammonia-chlorine system as a whole. The work presented here validates and extends this model for use in waters typical of those encountered in distribution systems and under realistic chloramination conditions. The effect of carbonate and temperature on auto-decomposition is discussed. The influence of bromide and nitrite at representative monochloramine concentrations is also examined, and additional reactions to account for their influence on monochloramine decay are presented to demonstrate the ability of the model to incorporate inorganic demand pathways that occur parallel to auto-decomposition.