Cells experience a wide range of unforeseen challenges in their natural environment. Under these circumstances, change is often not a choice. Cells inevitably find new ways to adapt and survive upon exposure to acute stress. Bacterial cells that are exposed to antibiotics acquire resistance through changes to their DNA sequence. Plants make decisions about their flowering times based on their time of exposure to cold conditions. Cancer cells, when exposed to chemotherapeutic agents, can become resistant, posing a significant challenge to treatment and worsening patient outcomes. In many cases, these adaptive changes are epigenetic - they result in gene expression changes without any alterations to the genetic blueprint. In contrast to genetic mutations, epigenetic changes can be transient, heritable and reversible providing diverse pathways for cellular innovation. The thousands of genes within the nucleus of each cell serve as tunable knobs that can alter cell fitness. We do not understand how cells choose which knobs to turn, and making the wrong choice could prove catastrophic. This NSF-funded research program aims to understand the fundamental rules that shape the inner workings of the cell. This research program captures the chaotic collisions between molecules within a cell which can work in unison to help cells make accurate, adaptive decisions. This project also seeks to broadly impact high school and undergraduate education in Michigan through a unique emphasis on interdisciplinary research and learning.
Understanding the fundamental rules of life that guide cells to make adaptive decisions requires interdisciplinary tools that capture cellular processes across different time and length scales. Because epigenetic changes can occur even without cell division and are not permanent, they lead to a rapid, reversible, and adaptive cellular response that has profound consequences for cell growth and survival. This research uses high-resolution imaging to visualize single molecules in cells, microfluidic platforms to reveal decision making events within individual cells, and automated continuous culture methods to investigate the dynamics of cell populations. The synthesis and integration of these multi-dimensional viewpoints will enable the development of mathematical models with the potential to predict emergent properties of these complex regulatory networks. Ultimately, the outcome of these studies will be a set of rules that define how adaptive epigenetic states, much like genetic mutations, represent evolvable traits in eukaryotic genomes.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
