Immune system modeling gets boost


Ashley Washburn, October 7, 2016 | View original publication

Immune system modeling gets boost

The immune system is one of biology’s most complex, and scientists are able to study its intricacies only in fragments. A University of Nebraska-Lincoln computational biologist aims to change that by giving scientists a tool to collaboratively create a virtual immune system they can explore and study.

Tomas Helikar, assistant professor of biochemistry, earned a $1.77 million National Institutes of Health Maximizing Investigators’ Research Award, a five-year grant that supports the work of promising researchers. He will use the award to advance his work into immune system modeling to aid researchers and biology education.

A mathematical and computer-based model would help researchers better understand the immune system and diseases, test potential new therapies and accelerate research.

“It’s a very big task,” Helikar said. Several layers of biological organization govern how cells, tissues and systems behave individually and in concert, from metabolic and communication networks to gene regulation. That amounts to millions of interactions.

“To fully understand the immune system, we need to be able to understand this information for each of these cells and the dynamic nature of biological systems across scales,” he said. “Creating a complete virtual immune system is not really possible anytime soon.”

So Helikar is developing a model framework, filling in some known information to demonstrate how researchers can use the model to simulate the immune system and observe multiple layers at once. As scientists add their research, a fuller virtual world of the immune system will develop over time.

Researchers will be able to manipulate the virtual system and observe what happens. For example, they could introduce pathogens or toxins to examine the consequences or insert a drug therapy to test its effect on cells or pathways even beyond those targeted.

“This model is not a crystal ball, where you ask it a question and it gives you a definitive answer,” Helikar said. “It’s meant to help you think about your hypothesis, generate new hypotheses and then test them in the lab. It’s an iterative process.”

The work expands on Helikar’s previous research developing Cell Collective, a web-based computer simulation platform to model biological networks in research as well as life sciences education. The software is designed to be collaborative and is freely available.

As with Cell Collective, the immune system modeling also will help students better learn immunology as a dynamic biological system. Cell Collective allows students to manipulate biological processes in a virtual system to see what happens, a valuable educational aid, Helikar said.

“We don’t have to put a lot of additional resources into developing the model as an educational tool,” he said. “The technology overarches everything because the same software for biomedical research is the software life sciences students can use to learn biology.”

Helikar received the award from NIH’s National Institute of General Medical Sciences under grant number R35 GM119770.

Biochemistry Bioinformatics Biology