Social Networking's Newest Friend: Genomics
The first large-scale study to combine genome sequencing and social-network analysis solves a mysterious TB outbreak.
It was the baby’s case that first caught people’s attention: an infant in a medium-sized community in British Columbia that was diagnosed with tuberculosis in July 2006. When public health workers took a deeper look at the community’s medical records, they found a number of additional cases suggestive of an outbreak. By December 2008, 41 cases had been identified, bumping up the region’s annual incidence rate by a factor of 10.
Officials at the BC Centre for Disease Control (BCCDC) were faced with the question at the heart of any outbreak: what was the source? Had the bacteria that cause TB mutated to become more infectious? Or was there some change in the community that made the microbes more likely to spread?
The answer would be crucial in focusing public health efforts to stop it. Traditional methods for analyzing transmission patterns created only a hazy picture. Molecular analysis of specimens collected from patients suggested everyone was infected with the same strain. “Based on the information we had, we couldn’t really figure out who was giving it to whom,” says Patrick Tang, a medical microbiologist at the BCCDC.
So Tang and collaborators combined two tools to create a much clearer picture of the outbreak: social-network analysis, which has become increasingly common in tracking infectious disease over the last decade, and whole-genome sequencing—an analysis of the microbe’s entire DNA sequence. The latter, which has been applied to outbreaks in only a few cases to date, allows much more precise tracing of infections than traditional molecular techniques, which look at only a few spots in the genome.
“For the first time, we can paint a really detailed picture of the relationships between people in the community and a really detailed picture of the relationships between the bacteria themselves,” says Jennifer Gardy, head of the BCCDC’s Genome Research Laboratory and lead author on the study. “We can reconstruct the path an organism took throughout a population.”
Researchers sequenced the genomes of 36 bacterial samples collected from patients. They used specialized algorithms to compare individual mutations that arose in the microbes’ DNA as they spread. The analysis, published today in the New England Journal of Medicine, revealed that there were actually two different lineages of the microbe, pointing to two different outbreaks spreading independently of one another. These findings suggested that an environmental factor lay at the heart of the outbreak, rather than a genetic one.

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