Dr. Athanasios Antoulas, a professor at Rice University and fellow at the Max-Planck Society, is combining math and biology by using his matrix pencil method, which he developed as a mathematical tool that allowed him to uncover frequencies from very noisy digital data, to study 12- and 24-hour cycles of genes. This novel approach is opening a new area of study of how gene functions over time influence health and disease.
“Other mathematical methods approached this type of problem by asking, does a specific wave form exist in the data? They were already biased to find a particular type of wave,” said Antoulas. “On the other hand, the method that we proposed asked an unbiased question; what type of wave is present in the data, if any?”
Antoulas, along with Dr. Clifford Dacso, a professor of molecular and cellular biology at the Baylor College of Medicine, applied the mathematical method to analyze gene expression data that had been collected every hour for 36 hours. They looked at more than 18,000 mouse liver genes involved in a variety of cellular processes. This analysis yielded astounding results. Not only did they confirm the 12- and 24-hour cycles, but also that the cycles were independent of each other. The conducted laboratory experiments showing that knocking down genes that follow a 24-hour cycle did not affect the expression pattern of the 12-hour genes.
“By looking at the function of genes over time, as opposed to looking at a single moment, we have uncovered that fundamental cell functions, such as inflammation, stress response, protein quality control and energy supply, follow certain cycles,” said Dacso. “This finding has enormous implications for redefining aspects of human health as controlled by genes.”
Other contributors to this work include Bokai Zhu, Qiang Zhang and Brian York. The authors are affiliated with one or more of the following institutions: Baylor College of Medicine, Rice University and the Max-Planck Institute for the Dynamics of Complex Technical Systems, Germany.
Financial support for this project was provided by the National Institutes of Health (NIDDK), the National Science Foundation, the American Diabetes Association, Kay and Rene Joyce Foundation and the German Science Foundation. Additional support was provided by the Max-Planck Institut für Dynamik Komplexer Technischer Systeme, Center for the Advancement of Science in Space, Brockman Medical Research Foundation, Phillip J. Carroll, Jr Professorship, Joyce Family Foundation, Sonya and William Carpenter and Peter J. Fluor Family Fund.