Researchers successfully simulate and boost photosynthesis

In a major breakthrough in plant biology, scientists have succeeded in boosting the photosynthetic efficiency of plants. With new insights, researchers from the University of Illinois built a better plant, one that produces more leaves and fruit without needing extra fertilizer. They accomplished the feat using a computer model that mimics the process of evolution. It is the first model ever to simulate every single step of the photosynthetic process.

The research findings appear in an open access article in Plant Physiology, and will be presented today at the BIO-Asia 2007 Conference in Bangkok, Thailand. The leading researcher, Steve Long, is the deputy director of the Energy Biosciences Institute (EBI) and an affiliate of the Institute for Genomic Biology and the National Center for Supercomputing Applications (NCSA). The EBI is a bioenergy and biofuels research consortium of universities, which recently won $500 million in funding from BP.

The breakthrough has obvious consequences for the future of bioenergy. In a study on the global potential for biomass exports, IEA Bioenergy Task 40 researchers found that the planet can sustain a production of maximum 1300 Exajoules worth of bioenergy by 2050 in an explicitly sustainable way. That is, after meeting all the food, fiber and fodder needs of growing populations and without further deforestation. However, they purposely left advances in plant science out of the equation because they cannot be predicted. The authors referred to the unparalleled possibilities of biotechnology to improve energy crops further: the photosynthetic efficiency of most crops presently is only 0.4%, while the theoretical efficiency is 4.5%. Room for higher productivity is enormous, they state, and the bioenergy potential could thus be substantially higher in the future. It is within this context that the new findings make sense.

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.

Principal investigator Long, who is also a professor of plant biology and crop sciences at the University of Illinois, and collegues asked the following question:

The distribution of resources between enzymes of photosynthetic carbon metabolism might be assumed to have been optimized by natural selection. However, natural selection for survival and fecundity does not necessarily select for maximal photosynthetic productivity. Further, the concentration of a key substrate, atmospheric CO2, has changed more over the past 100 years than the past 25 million years, with the likelihood that natural selection has had inadequate time to reoptimize resource partitioning for this change. Could photosynthetic rate be increased by altered partitioning of resources among the enzymes of carbon metabolism?

It wasn’t feasible to tackle this question with experiments on actual plants. With more than 100 proteins involved in photosynthesis, testing one protein at a time would require an enormous investment of time and money. Therefor they started simulating, and now that they have the photosynthetic process ‘in silico,’ they can test all possible permutations on the supercomputer.

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 NCSA.

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:
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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 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, they could almost double efficiency.

An obvious question that stems from the research is why plant productivity can be increased so much. Why haven’t plants already evolved to be as efficient as possible?

According to Long, the answer may lie in the fact that evolution selects for survival and fecundity, while the scientists were selecting for increased productivity. The changes suggested in the model might undermine the survival of a plant living in the wild, but the researchers' analyses suggest they will be viable in the farmer’s field.


The research was sponsored by the National Science Foundation.

The Energy Biosciences Institute (EBI) is a new research and development organization that will bring advanced knowledge in biology, physical sciences, engineering, and environmental and social sciences to bear on problems related to global energy production, particularly the development of next-generation, carbon-neutral transportation fuels.

EBI represents a collaboration between the University of California, Berkeley, Lawrence Berkeley National Laboratory, the University of Illinois at Urbana-Champaign, and BP, which will support the Institute with a 10-year $500 million grant. EBI's multidisciplinary teams will collectively explore total-system approaches to problems that include the sustainable production of cellulosic biofuels, enhanced biological carbon sequestration, bioprocessing of fossil fuels and biologically-enhanced petroleum recovery.

EBI will educate a new generation of students in all areas of bioenergy, and will serve as a model for large-scale academic-industry collaborations. By partnering with a major energy company, EBI will facilitate and accelerate the translation of basic science and engineering research to improved products and processes for meeting the world's energy needs in the 21st century.

The Institute for Genomic Biology at the University of Illinois at Urbana-Champaign was established in 2003 to advance life science research and stimulate bio-economic development in the state of Illinois. It houses up to 400 researchers in three broad Program Areas: Systems Biology, Cellular and Metabolic Engineering and Genome Technology.

Picture (click to enlarge): 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. Credit: Don Hamerman.

References:
Xin-Guang Zhu, Eric de Sturler and Stephen P. Long, "Optimizing the Distribution of Resources between Enzymes of Carbon Metabolism Can Dramatically Increase Photosynthetic Rate: A Numerical Simulation Using an Evolutionary Algorithm", Plant Physiology, 145:513-526 (2007).

University of Illinois at Urbana-Champaign: "Researchers successfully simulate photosynthesis and design a better leaf" - November 9, 2007.

IEA Bioenerggy Task 40: Edward Smeets, André Faaij,Iris Lewandowski, "A quickscan of global bio-energy potentials to 2050 An analysis of the regional availability of biomass resources for export in relation to the underlying factors" [*.pdf], Copernicus Institute - Department of Science, Technology and Society, Utrecht University, March 2004.