NYU Abu Dhabi faculty member Kourosh Salehi-Ashtiani, has played a leading role in a noteworthy scientific achievement with the development of the first genome-scale metabolic model of an algal species. A four-year collaborative project supported by 11 experts from a range of international institutions has yielded an interpretive and predictive model that will act as a significant resource in the investigation of algae's potential as a source for biofuel and clean energy.
Most options for biofuel production utilize human or animal food resources, but algae are microorganisms that can be found abundantly in various environments, such as soil or water, and can be cultivated on non-agricultural lands. When nitrogen is removed from the media of these organisms they typically react by accumulating starch and generating lipids, the latter can then be processed into clean fuel.
Unlike conventional maps on the metabolic process, the genome-scale metabolic network of Clamydomonas reinhardtii was reconstructed and developed into a computational model that provides predictive insights on how gene-manipulation can affect factors like growth and lipid production. Another important advancement has been incorporating the characteristics of light consumption into the model to predict the impact of light variation on metabolic processes.
"This model can provide predictions on what would happen if you deleted a certain gene or set of genes," Salehi-Ashtiani said. "We can use this computational model as a predictive tool to simplify the task of conducting an unfeasible number of experiments. It can even help understand the likely impact of the alteration of genes that otherwise might not be experimentally possible."
"Building on an integrated approach that my group and [the study's senior co-author] Jason Papin's group jointly developed several years ago, we have carried out large-scale cloning of the genes that are in the model. This way, the clones and the model provide a set of complementary biological and computational resources that can be applied to biofuel research, for instance by helping with strain optimization, which essentially means generating modified strains of the organism that behaves exactly as you want," he added.
The Clamydomonas reinhardtii species was selected for this project because it has historically been used as a scientific model for understanding processes like photosynthesis, reproduction, and metabolism in microorganisms. Now that the process of developing a genome-scale model has been completed for this algal species, it can be adapted to apply to other algae as well.
Salehi-Ashtiani said he aims to continue his research of Clamydomonas reinhardtii, making his base in Abu Dhabi a central point for driving forward further an international consortium to advancing scientific knowledge on the algal species. He also plans to explore variations of this and other algae that can be found in the UAE environment to study how different environments can lead to different characteristics in an organism.
"I see Abu Dhabi as an environment that is very motivated in exploring new frontiers," Salehi-Ashtiani said. "I hope that we can start collaborative efforts with organizations here in Abu Dhabi to further this research. The potential and level of interest that I see here in developing renewable resources is going to be very important moving forward."
A complete copy of the published research paper can be found in the journal Molecular Systems Biology.
The research team comprised: Roger L. Chang and Bernhard Ø Palsson, University of California, San Diego; Lila Ghamsari, Santhanam Balaji, Yun Shen, and Tong Hao, Center for Cancer Systems Biology, Dana-Farber, Cancer Institute and Harvard Medical School; Ani Manichaikul and Jason A. Papin, University of Virginia; Erik F.Y. Hom, Harvard University; Weiqi Fu, University of Iceland; Kourosh Salehi-Ashtiani, NYU Abu Dhabi and NYU New York. Salehi-Ashtiani and Papin are the senior authors of the study.