Scientists are coopting the power of cheap, fast DNA sequencing as an environmental sensor for infectious pathogens that can spread through a community. They hope that the approach can provide earlier warning of disease outbreak.
In a project dubbed the Disease Weather Map, Eric Schadt and colleagues at Pacific Biosciences, a sequencing startup in Menlo Park, California, are using the technology to monitor viruses from a number of locations around the Bay Area, including sewage stations, toilet handles, and the mouths of its own employees.
The pilot project, which Schadt presented last week at the Personal Genomes conference in Cold Spring Harbor, New York, is still in its early days–it’s not yet clear how broadly or densely scientists would need to sample the environment to identify warning signs earlier than existing monitoring methods, such as doctor’s reports and tests that involve growing the pathogens in the lab. But they have shown that it’s feasible to collect, sequence, and analyze genomic samples collected from the environment in a single day.
“The idea is to build a real-time weather map of disease by sampling different locations, like airports, BART, or emergency rooms, and use it to measure pathogen flux over time,” says Schadt. “If we can identify the influx of something like H1N1 into a community very early, then maybe we can mobilize resources to react, like getting supplies of Tamiflu.” He hopes ultimately to be able to combine the virus data with mapping software to create a picture of the pathogens in a particular neighborhood.
Schadt, who became chief scientific officer at Pacific Biosciences last year, envisioned the project as a way to harness the speed of the company’s novel sequencing technology. For scientists to act fast enough to protect public health, they need to be able to sequence and analyze virus data extremely quickly. Last spring, Pacific Biosciences collaborated with the New York Department of Health to show that the company’s sequencing technology could be used to sequence and analyze different strains of influenza A virus in a single day.
Public health agencies, such as state health departments and the Centers for Disease Control, currently use a combination of approaches to detect outbreaks, relying on doctors’ reports, molecular testing, and a new generation of Internet-based tools. Google Flu Trends, for example, predicts flu outbreaks based on the number of people searching for information on the flu. But none of these approaches monitor the environment, rather than people, for pathogens. Scientists hope this approach will be able to detect the signs of outbreak earlier than existing methods–before a significant number of people get sick–allowing cities and states to better prepare for potential outbreaks or even prevent them. “This is probably the wave of the future in terms of where we want surveillance to go,” says John Brownstein, a researcher at Children’s Hospital Boston and creator of HealthMap, an Internet-based disease-surveillance tool.
For the pilot project, researchers at Pacific Biosciences took samples from common areas at the company headquarters, such as handles from doors, toilets, and refrigerators, once a week for a month. They also took cheek swabs from employee volunteers twice a month for 2.5 months.
The researchers found multiple influenza strains in a number of people and on surfaces, including the H1N1 virus linked to last year’s swine flu pandemic. It’s not yet clear how predictive the approach can be, but researchers did see hints of its potential. One week into the study, Schadt says, a number of volunteers failed to show up for testing because they were out sick. Almost all of those who did show up turned out to test positive for H1N1, and the virus was present all over the office surfaces.