In early June 2011, at a bioinformatics conference outside of Cambridge, U.K., University of British Columbia epidemiologist Jennifer Gardy watched a Twitter storm take place. “The world’s tiny population of genomic epidemiologists is sitting in this lecture hall,” she remembers thinking—and they all seemed to be firing off tweets as fast as they could compose them. Just weeks earlier, reports had surfaced that a new and deadly variant of E. coli was infecting people in parts of Germany. While the epidemiologists were gathered together in the hall, researchers from the Beijing Genomics Institute (BGI) announced on Twitter that they had just publicly released an unassembled sequence of the strain’s genome. By sheer coincidence, the geneticists at the conference had just been discussing whole-genome sequencing as a forensic tool in epidemiology. Suddenly, they were handed an open case.
Gardy was sitting in the front row next to the University of Birmingham’s Nick Loman, who helped organize the meeting, the Wellcome Trust conference on Applied Bioinformatics and Public Health Microbiology. “We see the tweet from BGI go up, and Nick immediately grabs it,” Gardy recalls.
Loman sent the data to a server of his that assembles genomes, stitching short reads together into a coherent whole to be analyzed using any number of bioinformatics techniques. He then wrote a blog postand sent a tweet, setting the assembled genome loose online. Over the remainder of the conference, during presentations and on coffee breaks in the lobby, researchers cracked open their personal genomic toolboxes to investigate the genome. They and other researchers from around the world shared and discussed their findings with each other in real time on Twitter. Even after the conference, analyses of the E. coli genome continued to roll in, so prolifically that Loman set up a wiki to collect the information. Less than two months later, Loman and others published a paper based in part on this crowdsourced genomic analysis (N Engl J Med, 365:718-24, 2011).
“Twenty-four hours after the release of the genome, it had been assembled; two days after its dissemination, it had been assigned to an existing sequence type,” the paper read. “Five days after the release of the sequence data, we had designed and released strain-specific diagnostic primer sequences, and within a week, two dozen reports had been filed on an open-source wiki.”
Twitter, at the time, had grown into an established social media platform, but scientists were still warming to the idea of having meaningful technical exchanges using 140-character missives. To some, though, this tool for networking and sharing showed enormous promise for scientific research. Now, scientists in fast-moving and data-driven fields are finding that such online forums enable real-time dissemination of their work. Sharing research on social media also fits with the community’s growing interest in accelerating scientific publishing, as evidenced by a spate of new preprint servers.
“Twitter is the place where I actually hear people discussing science,” says Richard Sever, executive editor at Cold Spring Harbor Perspectives and cofounder of the life-science preprint server bioRxiv. “That’s been an eye-opener for some people. . . . Suddenly, serious people, serious scientists, particularly in genomics, started joining. And serious discussions are happening.”
In early August, Gardy tweeted a question to her nearly 6,000 followers: “If you had to isolate DNA from feces and you were in the middle of Africa with no lab equipment, what would you do?” The question was not hypothetical.
Gardy had just spoken to Jer Thorp, a data scientist who specializes in visualization. Thorp is involved in the Okavango Wilderness Project, and travels with his colleagues along the Okavango River in southwest Africa performing wildlife surveys and taking photographs, as well as measuring the heart rates of team members, all while uploading their data online for others to explore. Thorp was hoping to add genomic data to the project, but getting usable DNA samples with limited power and no access to a laboratory was proving challenging. So he asked Gardy for ideas, and she asked Twitter.
“If I run into a genomics or bioinformatics problem, I know that I can go to Twitter, tweet about it, and because I’ve got enough bioinformaticians and computational biologists following me, probably within a few minutes I’ll get an answer,” she says. Indeed, in response to tweeting about DNA collection in undeveloped Africa, Gardy got responses that ran the gamut from technical (an exchange over storage solutions) to facetious (“really tiny tweezers”) to meta (“probably just tweet asking for help”). But she also got her answer: a fellow genomicist with experience in field sampling knew how to turn a drill into a low-tech centrifuge for extracting a DNA sample.
Gardy relayed the information back to Thorp, who is now testing the idea in the field. If the Okavango team gets the approach to work, they’ll be able to share their data with the same population of genomicists who responded to Gardy’s question.
This type of casual crowdsourcing has become a regular activity for many scientists who have cultivated a responsive Twitter following. “Instead of me sitting here for two days trying to hammer through a bit of R code that is making no sense to me, I can send it out to the community” for a solution, says Gardy. As ecologist Andrea Kirkwood of the University of Ontario Institute of Technology put it, bouncing questions off Twitter “is part of my job. It’s just one tool in my toolkit.”