A research team from the University of Illinois has built
a better plant: one that has the ability to produce more leaves and fruit and does not require extra fertilizer.
The team used a computer model that mimics the process of evolution and they are the first to stimulate every step of the photosynthesis process.
Photosynthesis is how plants algae and phytoplankton convert light energy into chemical energy Photosynthesis, for the most plant takes place in the plant’s leaves and involves an elaborate array of chemical reactions requiring dozens of protein enzymes and other chemical components.
“The question we wanted to ask, was, ‘Can we do better than the plant, in terms of productivity?’ ” said principal investigator Steve Long, a professor of plant biology and crop sciences at the University of Illinois.
The researchers knew that is was not feasible to tackle this question with experiments on actual plants; with more than 100 proteins are involved in photosynthesis, testing one protein at a time would require an enormous investment of time and money.
“But now that we have the photosynthetic process ‘in silico,’ we can test all possible permutations on the supercomputer,” he said.
The first step was to build a reliable model of photosynthesis, one that would accurately mimic the photosynthetic response to changes in the environment. Xin-Guang Zhu is a research scientist at the center and in plant biology and worked with Long and Eric de Sturler, formerly a specialist in computational mathematics in computer sciences at Illinois, to realize this model.
When the relative abundance of each of the proteins involved in photosynthesis had been determined, the researchers were able to create a series of linked differential equations, each mimicking a single photosynthetic step.
Next, the team tested and adjusted the model until it successfully predicted the outcome of experiments conducted on real leaves, including their dynamic response to environmental variation.
The model was programmed to randomly alter levels of individual enzymes in the photosynthetic process.
The researchers then asked a simple question: “Can we do a better job than the plant in the way this fixed amount of nitrogen is invested in the different photosynthetic proteins?”
The team used “evolutionary algorithms,” which mimic evolution by selecting for desirable traits; the model hunted for enzymes that, if increased, would enhance plant productivity.
If higher concentrations of an enzyme relative to others improved photosynthetic efficiency, the model used the results of that experiment as a parent for the next generation of tests.
Several proteins were identified that could, if present in higher concentrations relative to others, greatly enhance the productivity of the plant. The team’s findings are consistent with results from other researchers, who found that increases in one of these proteins in transgenic plants increased productivity.
“By rearranging the investment of nitrogen, we could almost double efficiency,” Long said.
One question stood out as a result of the research; why haven’t plants already evolved to be as efficient as possible?
“The answer may lie in the fact that evolution selects for survival and fecundity, while we were selecting for increased productivity,” he said. The changes suggested in the model might undermine the survival of a plant living in the wild, he said, “but our analyses suggest they will be viable in the farmer’s field.”