This project focuses on mathematical and biophysical modeling of the mechanisms through which microorganisms such as bacteria regulate the various cellular processes in the cell cycle in a robust and efficient way, focusing on the coupling of DNA replication, division and protein production. The team will construct mathematical models that will elucidate the laws describing microbial growth, and the interplay between size regulation, cell cycle progression and protein production. Moreover, the implications of single-cell variability on the growth of the population as a whole will be studied. Model predictions will be used to design new experiments and will be tested by collaborators. Building on the PI's rich experience in outreach for more than a decade, the PI proposes to develop three important educational programs, each aimed at a different target audience. First, the PI will continue and extend his support to the "Teach" initiative, developing new content for a program which exposes the ethnically diverse K-12 community in Cambridge to STEM content, and in particular the physics of living systems. Within this project, the PI and his group will interact directly with hundreds of seventh graders from the Cambridge public system, exposing them to academic life and to modern science. Second, the PI will collaboration with Harvard's Museum of Natural History, and will take a role in a new exhibit on "Microbial Life: A Universe at the Edge of Sight", where he will present to K-12 teachers. Third, the PI will develop a mentoring program for the Physics Olympiad for high school students in the Boston area, putting special emphasis on female students and students from underrepresented groups. Together, these projects will expose a large number of students and teachers to exciting topics which are not covered in their school curriculum, and will aim at attracting the students into science and research.
The project deals with mathematical modeling of the cell cycle in microbes, focusing on the regulation and coupling of DNA replication, cell division and protein production. These are fundamental processes common to all life forms. One of the proposed approaches is to use Langevin-type equations to produce coarse-grained descriptions of the cell cycle. Such phenomenological models have proven to be extremely useful in the study of cell physiology, and can provide us with important insights into the biological processes. The existence of strong feedback in biological systems, in addition to various sources of stochasticity, leads to significant theoretical challenges, which will be addressed and developed within this proposal. Similarly, the study of population growth involves dealing with subtle correlations between cells in a lineage tree, which is a long-standing, mathematically challenging problem. To these technical difficulties is added to one of a more profound nature: choosing the "correct" minimal model that can capture the essence of the phenomena and yet have predictive power. Deepening our fundamental understanding of the cell cycle will have direct manifestations on a broad spectrum of problems. Developing novel antibiotics will be aided by an improved understanding of the bacterial cell cycle, as well as the proposed study of the effects of single-cell variability on the population growth. In particular, the growth and cell cycle of mycobacteria is an underexplored and poorly understood problem, its advance having significant impact on treatment of M. tuberculosis. Similarly, studying the cell cycle in single-celled microbes will allow us to resolve it at the single-cell level, without the added complication of cell-cell signaling, which will provide us with important insights that might be generalized to growth regulation in mammalian tissues, and its failure during cancer growth. The non-trivial connections between physics, mathematics, engineering and biology appear to hold much promise and will lie at the heart of this research program.
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.
