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Population dynamics and universal statistics of tumor-inhabiting bacteria

Event Type
Mechanical Science and Engineering
2043 Sidney Lu Mechanical Engineering Building
Jun 26, 2024   2:00 pm  
Professor Andrew Mugler, Department of Physics and Astronomy, University of Pittsburgh
Amy Rumsey
Originating Calendar
MechSE Seminars


Bacterial colonization of solid tumors is widespread, but it is not understood how bacteria affect tumor progression, nor how the tumor environment affects bacterial population dynamics. Recent experiments by collaborators, done with barcoded bacteria, show that clone sizes of tumor-inhabiting bacteria in mice exhibit universal statistical patterns. The patterns are robust across experiments and collection times, and unique to bacteria grown in the tumor environment rather than in liquid culture. We develop a mechanistic theory of the microecological dynamics of tumor-inhabiting bacteria that includes an infection bottleneck, local growth constraints, global resource competition, and noise. Our simple physical model captures both the dynamics and the statistics of the experiments, and explains the uniqueness of the observations to the tumor environment.

About the Speaker

The Mugler Group investigates cell behavior using theoretical physics. We rely on a wide range of tools including statistical physics, stochastic modeling, and information theory. We tackle problems that range from the molecular to the multicellular scale, often in collaboration with experimental groups. Current projects include:

Collective sensing. Cells sense chemicals in their environment and also communicate, but the impact of communication on sensing is poorly understood. We are using tools from statistical physics to develop a unified theory of collective sensing.

Metastatic invasion. Cancer metastasis begins when tumor cells invade the surrounding tissue. We are investigating metastatic invasion using theory, simulation, and microfluidic experiments with collaborators.

Long-range signaling. Cellular communities transmit signals over long distances, but noise or defects can cause these signals to die out. We have discovered that these systems are well described by percolation theory, a branch of statistical physics that describes coffee filtering and crack formation.

Criticality in biology. The molecular networks that process information in cells share many properties with critical points from statistical physics, but the implications for cell behavior are poorly understood. We are investigating critical behavior in biochemical networks and comparing our findings to experiments in immune cells.

Host: Professor Bumsoo Han

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