Flooding and power outages caused havoc on the battered land when Hurricane Maria made landfall in September 2017, destroying Dominica, St. Croix, and Puerto Rico. This led to the polluting of waterways with untreated human waste and harmful microbes.
Amy Pruden, a professor of civil and environmental engineering at Virginia Tech, organized a group of academics, including Maria Virginia Riquelme and William Rhoads, who were post-doctoral scholars at the time, to travel to Puerto Rico six months after the terrible Category 5 hurricane.
The 3.4 million residents of the American island territory in the northeastern Caribbean Sea were in dire straits due to the devastation. Researchers had a unique chance to examine how the widespread destruction of wastewater infrastructure may have facilitated the spread of antibiotic resistance, a rising worldwide public health problem.
In a study published in American Chemical Society’s Journal of Environmental Science & Technology, Virginia Tech researchers and international collaborators have further developed an innovative antibiotic resistance surveillance approach by applying DNA sequencing techniques to detect the spread of disease in watersheds impacted by large-scale storms.
“This study is a critical step toward establishing a unified and comprehensive surveillance approach for antibiotic resistance in watersheds,” said Pruden, the W. Thomas Rice Professor of Civil and Environmental Engineering. “Ideally, it can be applied as a baseline to track disturbances and public health concerns associated with future storms.”
Over the past decade, Pruden, a microbiologist and environmental engineer, has worked with her students using next-generation DNA sequencing, a specialty of Pruden’s, to examine Legionella strains as they operate before, during, after, and outside of Legionnaires’ disease outbreaks in various towns and cities across the country, including Flint, Michigan.
This study is a critical step toward establishing a unified and comprehensive surveillance approach for antibiotic resistance in watersheds. Ideally, it can be applied as a baseline to track disturbances and public health concerns associated with future storms.
Professor W. Thomas Rice
With RAPID funding from the National Science Foundation and collaborating with principal investigator Christina Bandoragoda, research scientist at the University of Washington with expertise in watershed modeling and geospatial analysis, Virginia Tech researchers teamed up with Graciela Ramirez Toro, professor and director of the Centro de Educación, Conservación e Interpretación Ambiental, and her research group at the local Interamerican University in San German, Puerto Rico.
They discovered three sampling locations in watersheds with various levels of wastewater input and land-use patterns that were perfect for identifying geographic trends in the distribution of bacterial genes that produce antibiotic resistance.
Pruden’s doctoral student and first author of the paper Benjamin Davis used a method called shotgun metagenomic DNA sequencing to detect antibiotic resistance genes in river water samples from three watersheds, including samples collected by hiking to far upstream pristine reaches of the watersheds and downstream of three wastewater treatment plants. Metagenomics is the study of genetic material recovered directly from environmental samples.
Data analysis showed that, in contrast to genes that particularly corresponded with human fecal markers, two anthropogenic antibiotic resistance markers DNA sequences linked to human influences on the watershed correlated with a different group of antibiotic resistance genes.
A high diversity of genes affecting resistance to clinically significant antibiotics, such as beta lactams and aminoglycosides, were found in the watershed samples, with a distinct demarcation between wastewater treatment plant influence and levels being elevated downstream of wastewater treatment plants.
Some of the beta lactam resistance genes found in the area were linked to fatal antibiotic-resistant diseases and displayed evidence of being able to hop between bacterial strains. Furthermore, anthropogenic antibiotic resistance markers were found to be more reliable predictors of beta lactam resistance genes than human fecal markers.
Although baseline levels of antibiotic resistance genes in Puerto Rican watersheds prior to Hurricane Maria are unknown, surveillance methodologies like these could be used to assess future impacts of major storms on the spread of antibiotic resistance, the researchers said.
The identification of single gene targets, such as the anthropogenic antibiotic resistance markers, makes watershed surveillance of antibiotic resistance much more accessible. However, many international communities won’t likely have access to sophisticated metagenomic-based monitoring tools in the near future.
And such genes can be quantified directly by quantitative polymerase chain reaction, yielding cost-effective, rapid results in less than a day.
