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Imitating plant evolution proves fruitful

By mimicking plant evolution, a team of researchers has improved upon nature’s design to build a leafy energy-producing powerhouse — or at least a virtual one on a supercomputer.

By mimicking plant evolution, a team of researchers has improved upon nature’s design to build a leafy energy-producing powerhouse — or at least a virtual one on a supercomputer.

Efforts to improve crop yields without resorting to more nitrogen-based fertilizer and a growing interest in plant-based biofuels have combined to make the energy-amassing process of photosynthesis a hot research topic. A big challenge, according to University of Illinois at Urbana-Champaign crop sciences professor Steve Long, is ensuring that enough energy can be produced to yield both food and fuel.

In a study published within the journal Plant Physiology, Long and colleagues have suggested a way forward for both aims by using a supercomputer to design a photosynthetic pathway that is 76 percent more efficient than anything found within natural greenery.

In photosynthesis, all green plants, algae and some microbes use sunlight to convert water and carbon dioxide into oxygen and energy stored as carbohydrates. Some scientists view the pathway as the most important biological process on Earth because it supplies most building materials and all food (either directly or through plant-eating animals). Photosynthesis also counteracts the effect of burning fossil fuels by consuming carbon dioxide.

The carbon-converting prowess of photosynthesis, in fact, is why planting more trees is commonly cited as a way to help mitigate global warming. Understanding the underlying mechanisms of the pathway could help increase wheat and other crop yields, make better use of existing solar energy, and augment the production of corn, switchgrass and other plant-derived biofuels as oil alternatives.

Photosynthesis is inefficient
Over the past half-century, researchers have been able to describe the dozens of enzymes and reactions involved in photosynthesis. “And one of things that’s known about this process is that it’s not very efficient,” Long said. If green plants aren’t optimizing their investment, he thought, might scientists be able to tweak the process to essentially build a better plant?

On a supercomputer, at least, it’s no contest.

Robert Blankenship, a professor of biology and chemistry at Washington University in St. Louis, said he was surprised by the “dramatic” increase in efficiency obtained by Long’s group. “If you could increase carbon fixation by 76 percent (in the real world), that would be a huge deal,” said Blankenship, who wasn’t involved with the study.

At its core, the study consisted of a series of linked differential equations that essentially mimicked each reaction within photosynthesis. The computer-assisted linkup, Blankenship said, allowed the scientists to reconstruct the complicated pathway on the computer and tinker with it in way that would be very difficult to do with real plants. Long’s team determined the starting amounts of each protein from prior studies, and after linking up the equations, kept testing and tweaking the model until it successfully predicted the outcome of experiments performed on living leaves.

“For reactions strung together in a fairly complicated way, it’s very difficult to go in there and say, ‘Maybe we should change this one or that one,’ ” Long said.

An evolutionary algorithm
Instead, his team used an evolutionary algorithm that selected a reaction at random and either increased or decreased the relevant protein by 10 percent. Adjusting the amount of an enzyme effectively changes the rate of its corresponding reaction. Because the reactions were all linked, a relatively minor alteration could impact the entire pathway.

After every round of adjustments, the supercomputer determined whether the virtual plant, given a steady level of nitrogen and overall protein, could fix more or less carbon dioxide per unit of light (the standard measure for photosynthesis efficiency).

“What we find is that 99 times out of 100, we’re actually making it worse, rather than better,” Long said. But that rare improvement could be used to seed the next generation in the plant’s simulated evolution. The computer repeated the process for 1,500 generations, always hunting for the best possible solution. By the time it was finished, the virtual plant’s photosynthesis output had clobbered its real-world competition.

The big question, of course, is whether the tinkering could work within a living plant.

Some independent findings have given Long reason for optimism. One protein whose levels increased significantly within the simulation — inscrutably named sedoheptulose-1,7-bisphosphatase — has been found to aid real plant production when upped experimentally by researchers in England and Japan. “That’s one clue we have. It was striking that the computer actually selected this protein,” Long said.

Boosting virtual plant proteins
For a more efficient plant, in fact, the supercomputer suggested the protein should be increased four-fold. The simulation gave another big boost to a notoriously inefficient but abundant enzyme abbreviated RuBisCO, which Blankenship called the “800 pound gorilla of plant proteins” and a key player in photosynthesis.

A handful of other proteins were significantly increased as well in the virtual plant, whereas most others were increased or decreased by no more than 20 percent to 30 percent. As a start, Long suggested, maybe the half-dozen proteins whose levels were altered the most could be the focus of future genetic engineering. “We view this as a guide,” he said. “These are the best bets.”

If the evolutionary algorithm produced such a clear increase in efficiency, why hasn’t evolution naturally done the same thing?

One reason, Long said, may have to do with a plant’s priorities. Evolution selects for those individuals producing the most viable offspring, which isn’t the same thing as selecting for a photosynthetic superstar. Getting the biggest bang for the buck from photosynthesis may require cutbacks in other plant processes.

Long believes the computer’s simulated shortchanging of some enzymes known to hamper photosynthesis could prove lethal for real plants exposed to high temperatures and drought conditions. Higher photosynthesis efficiency, it seems, may come at the cost of reduced stress tolerance — just one of the many potential pitfalls of messing with Mother Nature that will have to be addressed in the future.

In addition, most vegetation evolved under atmospheric conditions far different from what exists today. Perhaps, Long and his co-authors reasoned in their study, the plants’ photosynthetic cycle simply hasn’t been able to adequately adjust to the spike in atmospheric carbon dioxide levels over the past 150 years.

Nor are green plants the photosynthetic champions of the natural world. That distinction belongs to tiny cyanobacteria and some microalgae, which have generated considerable interest from researchers seeking to harness their long-term potential for producing bioenergy.

Nevertheless, Blankenship said exploring different avenues is likely to be the best strategy, and he lauded Long’s efforts at trying to maximize what nature didn’t necessarily intend. “There’s really no reason to think that we can’t do better,” he said. “You shouldn’t assume that nature is just perfect.”