Sewage-handling robots help UCSD team predict coronavirus outbreaks in San Diego

In earlier days of the COVID-19 pandemic, before diagnostic testing was widely available, it was difficult for public health officials to keep track of the infection’s spread or predict where outbreaks were likely to occur. Attempts to get ahead of the coronavirus that causes the disease are still complicated by the fact that people can be infected and spread the virus even without experiencing symptoms themselves.

When studies emerged showing that people testing positive for the virus — whether symptomatic or not — shed it in their stool, “the sewer seemed like the ‘happening’ place to look for it,” said Smruthi Karthikeyan, an environmental engineer and postdoctoral researcher at the UC San Diego School of Medicine in La Jolla.

From July to November, Karthikeyan and a team led by professor Rob Knight, director of the Center for Microbiome Innovation at UCSD, sampled sewage water to see if they could detect the coronavirus, SARS-CoV-2. They could. But concentrating the wastewater proved to be a slow and laborious multistep process.

But in a paper published March 2 in mSystems, the researchers describe how they have automated wastewater concentration with the help of liquid-handling robots. They demonstrated their system’s robustness by comparing it with existing methods and showing that they can predict coronavirus cases in San Diego by a week with excellent accuracy and three weeks with fair accuracy, just using city sewage.

San Diego County has only one primary wastewater treatment plant, located on the coast in Point Loma. All excrement flushed away by San Diego’s approximately 2.3 million residents, including those on the UC San Diego campus, ends up there.

Seven days a week, Karthikeyan or a colleague have driven to the treatment plant to pick up wastewater samples collected and stored for them by onsite technicians.

“Unfortunately, we can’t just directly test wastewater samples the way we would samples from patient nasal swabs,” Karthikeyan said. “That’s because the samples we get are highly diluted — just think of the number of people contributing to the waste stream, plus all the junk that gets flushed and makes it to the sewer system.”

Back in Knight’s lab at UCSD, the researchers process the sewage using their robotic platform. The system extracts RNA — the genetic material that makes up the genomes of viruses like SARS-CoV-2 — from the samples and runs PCR (polymerase chain reaction) to search for the virus’ signature genes.

The automated, high-throughput system can process 24 samples every 40 minutes. Later the same day, Karthikeyan adds the data to a digital dashboard that tracks new positive cases.

According to Knight, the technique is faster, cheaper and more sensitive than other approaches to wastewater surveillance. The team is able to identify a single coronavirus case in a building of about 500 people.

Wastewater monitoring is a key to UCSD’s ‘Return to Learn’ program

Smruthi Karthikeyan picks up wastewater samples from a collection point on the UC San Diego campus.

(UC San Diego)

The researchers and students in Knight’s lab are no strangers to dealing with stool samples. The team has long been known for its studies of the gut microbiome — the unique communities of microbes that live in our gastrointestinal tracts. People all over the world participate in its research program, The Microsetta Initiative, by mailing their fecal swabs to Knight’s lab. The crowdsourced project has allowed the team to study the many factors that might influence the makeup of a person’s gut microbiome and the many ways it influences our health.

In spring 2020, Knight’s team quickly pivoted its focus to one particular microbe: SARS-CoV-2. Soon the team formed an integral part of UC San Diego’s “Return to Learn” program, which has allowed the university to continue to offer on-campus housing and in-person classes and research opportunities.

With about 10,000 students on campus, the program’s many components have helped UCSD maintain a coronavirus positivity rate of less than 1 percent, much lower than the surrounding community and most college campuses.

Return to Learn relies on three pillars: risk mitigation, viral detection and intervention. Knight’s team and its collaborators play a big role in viral detection on campus. They help screen for the asymptomatic presence of SARS-CoV-2 in students and staff (often self-collected using test kits available from vending machines), on surfaces and in wastewater.

The team continues to collect samples daily from more than 100 wastewater samplers on the UCSD campus.

About a month after the campus detection system went online last summer, a positive case was detected in the Revelle College area one Friday afternoon. The campus community was notified within 14 hours and targeted messages were sent to people associated with the affected buildings, recommending they be tested for the virus as soon as possible. More than 650 people were tested that weekend.

As a result, two asymptomatic people were identified as being positive for the virus. They self-isolated before an outbreak could occur.

An online dashboard tracks wastewater coronavirus detection on the UC San Diego campus and makes it available to the public.

(UC San Diego)

Now, wastewater screening results are available on a public dashboard and positive samples are being sequenced to track the emergence of new SARS-CoV-2 variants.

“We hope wastewater-based epidemiology will become more widely adopted,” Knight said. “Rapid, large-scale infectious-disease early-alert systems could be particularly useful for community surveillance in vulnerable populations and communities with less access to diagnostic testing and fewer opportunities to distance and isolate — during this pandemic and the next.”

This article was originally published by the UC San Diego News Center and is republished here with permission.