Study Links Photosynthesis Genes to Marine Virus Fitness

February 4, 2009

(PhysOrg.com) -- A recent Northeastern University study has shown, for the first time, the effect of individual genes on the fitness of a marine species at the ecosystem level. Using his innovative computer simulation model, engineering professor Ferdi Hellweger found that eliminating photosynthesis genes from viruses that attack important marine photosynthetic bacterial organisms will negatively impact the fitness of these viruses, ultimately killing them.

The findings, published in the journal Environmental Microbiology, have led to a new interdisciplinary field called “systems bioecology.” Combining systems biology and ecology, systems bioecology uses computer simulation to better understand the role of individual genes at the ecosystem scale.

With his computer simulation model, Hellweger “knocked out” the photosynthesis genes of cyanophages (viruses that attack marine cyanobacteria species such as Synechococcus and Prochlorococcus) to compare the fitness-level of these viruses to those containing the genes. Simulating a ten-year time span, he found that viruses without the photosynthesis genes were dead while the ones with the genes present survive.

The findings demonstrate that the fitness of cyanophage viruses is positively affected by the presence of photosynthesis genes.

Synechococcus and Prochlorococcus are known to be the most abundant photosynthetic organisms on Earth and play a major role in our carbon and climate cycles and the ocean ecosystem. Thus, finding out what factors influence the fitness and destructive impact of marine viruses on these bacteria is crucial in order to better understand the ecosystem.

The innovative computer simulation model can be expanded and modified using different genes and applying it to different species of other marine bacteria.

“Most of the biological science that comes out today is at the molecular level, but our models have not reached that point,” said Hellweger. “Systems bioecology has the potential for becoming widely used and the ‘method of choice’ for simulation in the post-genomic era.”

Provided by Northeastern University