Researchers Trace Evolution of Cystic Fibrosis Infection

A collaboration between researchers at Harvard Medical School and Children’s Hospital Boston studying an infectious outbreak in cystic fibrosis patients has yielded important new information regarding how an infection spreads and how antibiotic resistance develops.

The scientists, using DNA sequencing technology, were able to retrace the evolution of specific bacteria and identify 17 adaptive genes that increase bacterial survival.

Cystic fibrosis is a life-threatening genetic disease that causes mucus to build up in the lungs and other organs, thereby facilitating bacterial infection. In the 1990s, a rare strain of bacteria later named Burkholderia dolosa infected a closed group of 39 cystic fibrosis patients at Children’s Hospital Boston. The clinic had the foresight to collect 112 samples of bacteria from 14 of these infected people. Roy Kishony, professor of systems biology at Harvard Medical School, had the original idea to use the data to study the spread of infections.

Jean-Baptiste Michel, Kishony’s former graduate student and now a post-doctoral fellow at Harvard Medical School, and Tami D. Lieberman, a research assistant and graduate student in systems biology, co-wrote the paper with Kishony that appeared in Nature Genetics.

“Once we had this wealth of data, we tried to understand and use that data to interpret how the epidemic spread and what genes were in selection,” Lieberman said.

Whole genome sequencing allows scientists to study how one strain of bacteria evolved over time in multiple infected patients during the outbreak. This research successfully sequenced the genomes and mapped their changes to identify genes that faced the greatest selective pressure, or how the bacteria evolved when challenged by both human defenses and medical treatment.

The team’s findings could help better define a pathogen’s strengths and weaknesses or potential targets for new therapies. Their innovative methodology can also be applied to other epidemics such as E. coli infections.

Kishony said that this large scale study “was only possible due to the close collaboration among the best people from the clinical side and basic research, bringing in backgrounds in mathematics, physics, and biology.”