A team featuring Duke Kunshan Professor Huansheng Cao has had research into systems biology, a field that seeks to understand the bigger biological picture, published in the science journal Nature Communications.
Their study addressed the regulation of metabolism in a cell, providing valuable insights that could benefit medical research and other scientific fields.
“The metabolic networks as they stand now are only mathematically represented, lacking biological context and regulation, like a skeleton — a human body stripped of flesh and blood,” said Cao, an assistant professor of environmental science.
“That said, our work is an important step in adding regulatory mechanism to metabolic networks, adding flesh back to the skeleton,” he added.
Cao worked on the study with long time collaborators Gaoyang Li, a professor at Tongji University in China, Li Liu, his research assistant at DKU, and Wei Du, a professor at Jilin University, China.
They combined their biological and computational expertise to develop new ways of representing metabolic networks that will expand understanding of them, and grew bacterial cultures from which they collected biological data to verify their models.
The models address how metabolism – reactions that create energy – are regulated in a cell. They shed light on regulatory mechanisms, the combination of steps that the cell engages in to ensure that biological processes are controlled.
In particular, they improve understanding of global gene regulation and local metabolite/substrate regulation inside a cell. Global gene regulation refers to the process used to control the timing, location and amount in which genes encode enzymes, used to convert substances such as glucose, fatty acids and amino acids into energy. Local metabolites are substances produced to regulate enzyme activities during the metabolic process.
Previous research provided a simple picture of these processes, according to Cao, “like a very basic map”, while his team’s research added more detail, akin to calculating distances between locations.
“This study represents an important step in fundamental research in cellular metabolism and multi-omics integration, which are challenging and unsolved intricate questions,” said Cao.
“Besides, it has potential applications in health research. For example, it can be used for cancer diagnosis to see how cellular metabolism in diseased cells is different or differently regulated from that of normal cells.”
The research team is already using the models developed during the project to understand how Antarctic green alga adapts to extreme climate. Wet lab experiments have been completed and multi-omics data collected for this study.
Further research is now underway to “develop a comprehensive next-generation representation of metabolic networks with full regulation to deduce the operation of cellular metabolism,” said Cao.
He will present the research at the 5th International Conference on Cell and Experimental Biology in Baltimore, United States, next April, an event organized by the United Scientific Group.