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Antimicrobial Resistance

Emerging contaminants, including pharmaceuticals such as antibiotics, may accumulate in our water resources with largely unknown impacts.  In my research, we focus on antibiotic resistance genes (ARGs) as the contaminant of interest, bringing in environmental engineering tools to understand their fate and transport in the environment as well as to assess water treatment options. Our research suggests that standard pathogen inactivation imposed by water and wastewater treatment may not be sufficient.

  • Convergence at the Interfaces of Policy, Data Science, Environmental Engineering and Science to Combat Antimicrobial Resistance (CIP-CAR) NSF NRT.  This is a National Science Foundation funded Research Traineeship (NRT) that brings together PhD students across disciplines to help develop science-based policy to combat the spread of antimicrobial resistance as a pressing societal challenge. Trainees engage in transdisciplinary team-based research incorporating data analytics, environmental science and engineering, environmental chemistry, stakeholder engagement, public health, and policy to advance DNA sequencing of wastewater as a powerful tool to identify forms of AMR circulating in the community and inform environmental and public health policy, practice, and interventions. Trainees gain skills in science communication and ethical stakeholder engagement, learning how to tap into the power of artificial intelligence and other powerful data analytics approaches to inform effective solutions to pressing societal challenges. Trainees that complete the program will be poised as future leaders in government, industry, academia, and non-governmental organizations.

  • 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.

Opportunistic Pathogens in Drinking Water, e.g., Legionella pneumophila

Opportunistic pathogens (OPs) are the leading cause of tap-water associated disease and death in the US and many parts of the world.  Examples include Legionella pneumophila (the causative agent of Legionnaires’ Disease), nontuberculous mycobacteria (NTM, agent of nontuberculous lung disease), and Pseudomonas aeruginosa (commonly a multi-antibiotic resistant pathogen responsible for skin, blood, and ear infections). OPs are very challenging to address because they establish as part of the microbial ecology of drinking water distribution system and premise plumbing biofilms.  The Safe Drinking Water Act does not adequately address OPs because it is designed to provide barriers to fecal pathogens, which are not natural inhabitants of the drinking water environment.  In partnership with Prof. Marc Edwards, Pruden’s research is focused on advancing an understanding of the microbial ecology of these organisms, combining culture-, PCR- and metagenomic approaches.  Pruden was a co-author on the US National Academies of Science Engineering and Medicine Report on Management of Legionella in Water Systems.

Metagenomic Analysis of Microbial Communities in Environmental Systems

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: 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:, 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:, a machine learning approach to identify antibiotic resistance genes from sequencing data, and 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 and Water Reuse

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. A premise of my research is that characterizing the effect of advanced water reuse treatment technologies is key to proactively addressing human health concerns.

Examples of my work with wastewater and water reuse related projects includes, but is not limited to:

  • US Bureau of Reclamation partnership with Hampton Roads Sanitation District.  My role in the research is to track the composition of microbial communities through various water reuse treatment train configurations and relate them to treatment performance.  We also track ARGs to calculate removal rates and determine which processes most effectively attenuate concerns related to AMR.

Currently Funded Research Projects




PI (Co-PIs)



Advancing Comprehensive Wastewater Surveillance of Endemic and Emerging Pathogens Across Multiple Microbial Domains through Strain-resolved Metagenomics

US Centers for Disease Control

Pruden 40% (Vikesland, Zhang)



NRT: HDR: Convergence at the Interfaces of Policy, Data Science, and Environmental Science and Engineering to Combat Antimicrobial Resistance (CIP-CAR)

National Science Foundation Research Traineeship (NRT)

Pruden 20% (Krometis, Drape, Shenk, Zhang)



Ensuring the Sustainability of Indirect Potable Reuse and Aquifer Recharge

US Bureau of Reclamation

Pruden 60% (Widdowson, Bott, Novak)



Frameworks: Developing CyberInfrastructure for Antibiotic Resistance Risk Surveillance (CI-4WARS)


Zhang 25% (Pruden, Vikesland, Butt)



Continued Virginia Tech HRSD SWIFT Collaboration: AOP-BAC/GAC Pilot/Demo, Soil Aquifer Treatment, and 1,4-Dioxane Studies

Hampton Roads Sanitation District

Pruden 60%




NNCI: National Center for Earth and Environmental Nanotechnology Infrastructure (NanoEarth)

NSF- National Nanotechnology Coordinated Infrastructure (NNCI)

Murayama (Pruden 5%)

$3.0 M


The Spread of Antimicrobial Resistance through the Atmosphere.


Marr (Pruden 40%, Ogejo, Isaacman-van Wertz)



Project 5052: Standardizing Methods with QA/QC Standards for Investigating the Occurrence and Removal of Antibiotic Resistant Bacteria/Antibiotic Resistance Genes (ARB/ARGs) in Surface Water, Wastewater, and Recycled Water

Water Research Foundation

Pruden 80% (Heath, Harwood (USF))



Project 4961: The Use of Next Generation Sequencing (NGS) Technologies and Metagenomics

Approaches to Evaluate Water and Wastewater Quality Monitoring and Treatment


Water Research Foundation

Pruden 35% (Zhang, Heath, Vikesland, Marr, Garner)



Project 4813: Critical Evaluation and Assessment of Health and Environmental Risks from Antibiotic Resistance in Reuse and Wastewater

Water Research Foundation 

Hamilton, Pruden (42%), Garner, Ashbolt, Medema