Environmental engineer Smruthi Karthikeyan had spent just a couple of days working in her new lab at the University of California, San Diego when the state instituted its first coronavirus lockdown in March 2020.
Biologist Rob Knight had hired her as a postdoc to develop new techniques to study how microbes in complex ecosystems shape human health and vice versa. The COVID-19 pandemic quickly put a new spin on that mission.
Soon, the lab pivoted to support the coronavirus response. Infections were outpacing testing capacity in San Diego County, Karthikeyan says. In the meantime, the university wanted to keep the campus open for its 10,000 students who still live on campus and 25,000 workers. There had to be a way to monitor infections without requiring thousands of people to get tested all the time, Karthikeyan and his colleagues thought.
Public health researchers had previously tested wastewater for pathogens as a way to spy on movements of infectious agents in communities. Viruses, bacteria and parasites can show up in stool before people show symptoms, hinting at a looming outbreak. But no one had implemented such a system to track a respiratory virus before, and never on a scale of tens of thousands of people.
Karthikeyan was up for the challenge.
The wastewater monitoring system that Karthikeyan and his colleagues developed and implemented at UC San Diego, reported July 7 at Nature, processes more than 200 samples per day. Previous methods could process a maximum of eight samples, she says. In addition, the system has identified newly spread coronavirus variants up to two weeks earlier than clinical trials and accurately predicted the combination of variants infecting students and staff.
That has given school officials more time to take steps to keep infection rates low. During the study period from November 2020 to September 2021, the proportion of clinical tests that came back positive was less than one percent, Karthikeyan says, dramatically lower than rates in the surrounding area and many other college campuses at the time. .
Among the key players in the team’s monitoring system are 131 robots that collect wastewater samples throughout each day from 360 university buildings. Back at the lab, the samples are analyzed for viral RNA and the results are entered into a publicly available archive. online dashboard created as part of the project.
Karthikeyan’s team is not the only one Using human waste to get ahead of COVID-19. But the scale of the monitoring is “unprecedented,” says Ameet Pinto, an environmental engineer at Georgia Tech in Atlanta. During the study period, Karthikeyan and his colleagues processed a total of nearly 20,000 samples. “That’s amazing,” she says.
A positive result triggers a campus-wide notification via the smartphone app. For dorms, anyone who lives in the building is required to be tested for COVID-19, while it is strongly recommended that anyone who has recently been in the building be tested.
To increase access to testing, the team swapped candy in vending machines for home testing kits and installed testing drop boxes in buildings. Karthikeyan’s team processes the tests and sends the results within a day.
Anyone who tests positive for the coronavirus is moved to a designated isolation dorm or instructed to self-isolate at home if they live off campus. If the coronavirus shows up in the sewage test the next day, the remaining building occupants will be notified to test again.
To find out which variants are causing infections at the university, Karthikeyan’s team created a freely available computational tool called Freyja. It uses a library of genetic markers to identify the relative abundance of known and emerging variants in wastewater. Freyja detected the emerging delta variant on campus 14 days before clinical trials did, Karthikeyan and his colleagues report.
Based on the university’s success, San Diego County officials asked researchers to test a modified version of the at the Point Loma Wastewater Treatment Plant, which serves more than 2.2 million inhabitants, and in 17 public schools. Elementary school students were able to name the robots, calling the machines Sir-Poops-a-Lot, Harry Botter and the Rancid Water, and other silly nicknames, Karthikeyan said with a laugh.
At the county level, the system detected the appearance of the omicron variant 11 days before clinical trials, the team reports in the same study in Nature. A detailed analysis of the public school data has not yet been published.
Karthikeyan and his colleagues’ methods have been adapted by researchers at the state, national, and international levels. For example, him US Centers for Disease Control and Prevention. and the The Food and Drug Administration uses Freyja to track variants in wastewater across the country.
The system is now being used to monitor monkeypox, and the team is working on how it can detect other pathogens that can spread unnoticed. That work has the potential to have a big impact on the epidemiology of wastewater, says Pinto.
Karthikeyan will launch his own lab at Caltech in 2023, where he plans to adapt these tools to monitor groundwater. The communities of microbes that live there can serve as sentinels, signaling disturbances from pollution, climate change and more, she says. “My whole business is looking at a much larger system through a very small lens.”
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