We use next-generation sequencing to characterize environmental microbial communities, describe the functional capacity of these communities, and identify the presence of environmental contaminants, such as pathogenic bacteria and antibiotic resistance genes. We partner with computer scientists from Virginia Tech (throughout the last few words add links to: http://people.cs.vt.edu/lqzhang/, http://people.cs.vt.edu/~heath/) to develop new tools for analyzing sequencing data, with an emphasis on pipelines that facilitate the identification of antibiotic resistance genes from environmental samples. Along with our computer science collaborators, we have developed MetaStorm (link to: http://bench.cs.vt.edu//MetaStorm/), a platform to facilitate the annotation of functional genes and taxonomic identification from metagenomic data sets using user-uploaded databases. In addition, we have developed deepARG (link to: https://bench.cs.vt.edu/deeparg), a machine learning approach to identify antibiotic resistance genes from sequencing data, and nanoARG (https://bench.cs.vt.edu/nanoarg/#/), a tool to facilitate the identification of ARGs from data generated via Oxford nanopore sequencers. These tools have helped us to identify antibiotic resistance genes in drinking water and reclaimed water systems, wastewater treatment plants, surface water, and in manure-treated soils.
Wastewater, reclaimed water, and reuse website
Wastewater treatment plants are a recognized source of antimicrobial resistance (AMR) to the environment and a major focus of my research. To date, my lab’s work has focused on better understanding the effects of conventional wastewater treatment on the dissemination and mitigation of antibiotic resistance genes (ARGs), microbial contaminants, and other contaminants of emerging concern (CECs) on a local, national, and international scale.
In addition to my lab’s work on conventional wastewater treatment I have recognized an increasing paradigm shift towards wastewater reuse (whether it be in the form of reclaimed, indirect potable, or direct potable reuse) and have expanded my research to address AMR and CECs in these systems. It is my belief that characterizing the effect of advanced water reuse treatment technologies is key to proactively addressing human health concerns.
Examples of my work with wastewater related projects includes, but is not limited to:
PIRE, Halting Environmental Antimicrobial Resistance Dissemination (HEARD)– is an ongoing international collaboration that will 1) quantify how wastewater treatment processes affect different aspects of AMR (e.g., the antimicrobial drugs, AMR organisms, and the DNA elements underlying AMR) across a global transect of wastewater treatment plants, 2) determine how the characteristics of wastewater treatment plants and the receiving environment (e.g., river, lake, or pipe network) interact to affect the spread of AMR, and 3) develop and test novel approaches to stop the spread of AMR originating from wastewater treatment plants.
NSF 1438328–goal is to comprehensively understand the interplay between unique water chemistries and microbial communities within recycled water systems. To elucidate these relationships, we constructed a simulated recycled water distribution to study the impacts of carbon levels, disinfectant types, water age, and temperature on microbial regrowth.
Future work on the distribution systems rigs involves a shift from recycled water to indirect/direct potable water through the implementation of advanced oxidation and biologically-active carbon filtration processes. The ultimate goal is to limit the potential for microbial regrowth throughout the simulate distribution systems, thus possibly attenuating the dissemination of antibiotic resistance.
WRF 4536– examines the role of direct potable reuse (i.e. advanced treatment of wastewater to achieve drinking water quality) in contributing to the regrowth of opportunist pathogens and antibiotic resistant bacteria in distribution systems and home plumbing.
WRF U1R16– leverages a collaboration with the Hampton Roads Sanitation District’s (HRSD) Sustainable Water Initiative for Tomorrow (SWIFT) to fill key knowledge gaps related to operational parameters and chemical/microbial CECs.