[tt] Researchers successfully simulate photosynthesis and design a better leaf

[Brian Atkins]

http://www.news.uiuc.edu/news/07/1109photosynthesis.html

11/9/07

CHAMPAIGN, Ill. — University of Illinois researchers have built a better plant, 
one that produces more leaves and fruit without needing extra fertilizer. The 
researchers accomplished the feat using a computer model that mimics the process 
of evolution. Theirs is the first model to simulate every step of the 
photosynthetic process.

The research findings appear in the October issue of Plant Physiology, and will 
be presented today at the BIO-Asia 2007 Conference in Bangkok, Thailand. The 
research was sponsored by the National Science Foundation.

Photosynthesis converts light energy into chemical energy in plants, algae, 
phytoplankton and some species of bacteria and archaea. Photosynthesis in plants 
involves an elaborate array of chemical reactions requiring dozens of protein 
enzymes and other chemical components. Most photosynthesis occurs in a plant’s 
leaves.

“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.

It wasn’t feasible to tackle this question with experiments on actual plants, 
Long said. With more than 100 proteins 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 researchers first had to build a reliable model of photosynthesis, one that 
would accurately mimic the photosynthetic response to changes in the 
environment. This formidable task relied on the computational resources 
available at the National Center for Supercomputing Applications.

Xin-Guang Zhu, a research scientist at the center and in plant biology, worked 
with Long and Eric de Sturler, formerly a specialist in computational 
mathematics in computer sciences at Illinois, to realize this model.

After determining the relative abundance of each of the proteins involved in 
photosynthesis, the researchers created a series of linked differential 
equations, each mimicking a single photosynthetic step. 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 researchers then programmed the model to randomly alter levels of individual 
enzymes in the photosynthetic process.

Before a crop plant, like wheat, produces grain, most of the nitrogen it takes 
in goes into the photosynthetic proteins of its leaves. Knowing that it was 
undesirable to add more nitrogen to the plants, Long said, the researchers 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?”

Using “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.

This process identified several proteins that could, if present in higher 
concentrations relative to others, greatly enhance the productivity of the 
plant. The new 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.

An obvious question that stems from the research is why plant productivity can 
be increased so much, Long said. 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.”

Long also is the deputy director of the Energy Biosciences Institute and an 
affiliate of the Institute for Genomic Biology and the supercomputing center.

-- 
Brian Atkins
Singularity Institute for Artificial Intelligence
http://www.singinst.org/