Rice University engineer Lauren Stadler and her team compared wastewater ‘snapshots’ to daylong composite samples and found snapshots lead to bias in testing for the presence of antibiotic-resistant genes. Credit: Jeff Fitlow/Rice University
During the COVID-19 pandemic, wastewater monitoring went from zero to hero seemingly overnight. And while most now agree on the importance of the technique, its quick ascent left room for improvement—or at least additional research.
A new study from engineers at Rice University—which has been a foremost leader in wastewater monitoring techniques—found that testing a single sample of wastewater does not tell the whole story. Instead, composite samples taken over 24 hours give a much more accurate representation of the level of antibiotic-resistant genes (ARGs) in wastewater.
“I think it’s intuitive that grabbing a single sample of wastewater is not representative of what flows across the entire day,” said civil and engineering research professor Lauren Stadler, whose lab is responsible for the study. “Wastewater flows and loads vary across the day, due to patterns of water use. While we know this to be true, no one had shown the degree to which antibiotic-resistant genes vary throughout the day.”
For the study, published in Environmental Science & Technology: Water, lead authors Esther Lou and Priyanka Ali collected samples from a Houston-area plant that routinely disinfects wastewater over two campaigns, one in the summer and one in the winter.
The researchers took both “grab” samples—snapshots collected when flow through a wastewater plant is at a minimum—and composite samples every two hours from various stages of the wastewater treatment process. Back in the lab, the researchers ran PCR tests to quantify several clinically relevant genes that confer resistance to fluoroquinolone, carbapenem, ESBL and colistin, as well as a class 1 integron-integrase gene known as a mobile genetic element (for its ability to move within a genome or transfer from one species to another).
According to the findings, levels of antibiotic-resistant RNA concentrations were 10 times higher in composite samples than grabs.
Interestingly, the scientists also found that the vast majority of ARG removal occurred due to biological processes, as opposed to chemical disinfection. In fact, chemical disinfection had the opposite effect. The team observed that chlorination, used as the final disinfectant before the treated wastewater is discharged into the environment, may have selected for antibiotic-resistant organisms.
The takeaway for testers is that snapshots can lead to unintended biases in results, the researchers say.
Since wastewater loads vary throughout the day—as shown—Lou and Ali had to collect the grab samples at a steady pace over 24 hours, forcing the research duo to camp out at the wastewater treatment plant.
Such commitment would not be necessary if real-time wastewater monitoring was a reality, Stadler said, which is one reason why she is working toward that goal.
In November, a separate team at Rice led by Caroline Ajo-Franklin, published a study that showed engineered bacteria can quickly sense and report on the presence of a variety of contaminants. In multiple successful experiments, E. coli was recoded to sense an endocrine disruptor.
Now, thanks to a $2 million grant from the National Science Foundation, Ajo-Franklin, Stadler and collaborators are developing living bacterial sensors that would detect the presence of ARGs and pathogens, including SARS-CoV-2, without pause at different locations within a wastewater system.
“I think the future is these living sensors that can be placed anywhere in the wastewater system and report on what they see in real time,” said Stadler.