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In a computer model, researchers at Illinois were
able to simulate the photosynthetic behavior of actual leaves.
Here, a gas exchange system measures the rate of carbon dioxide
and electron transport in intact leaves.
Photo by Don Hamerman
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�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.
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