Grants

Howard University

To explore how spontaneous, self-organizing processes give rise to goal-oriented behaviors in single-cell organisms by studying the reassembly and mass-sensing behaviors of Physarum polycephalum

  • Amount $1,012,693
  • City Washington, DC
  • Investigator Philip Kurian
  • Year 2022
  • Program Research
  • Sub-program Matter-to-Life

Agency, defined here as purposeful or goal-oriented behavior, is often framed as a distinctive—perhaps even defining—feature of life. Beings have an agenda—whether it be finding food, reproducing, or avoiding environmental danger—and it's difficult to understand how a living creature could consist of inanimate matter passively following physical laws and yet also exhibit behaviors that seem—at least from the outside—to be purposeful. Improving our understanding of how agency emerges in a matter system will advance our understanding of how matter transitions to life. Gaining a scientific foothold on agency, however, is not so simple. One needs a living system that resides in the 'Goldilocks Zone' of complexity: complex enough to exhibit agency and yet simple enough that there's reasonable hope of achieving a mechanistic understanding of the processes underlying behavior. Philip Kurian, a theoretical physicist and founding director of the Quantum Biology Laboratory at Howard University, and Michael Levin, Distinguished Professor of Biology and director of the Tufts Center for Regenerative and Developmental Biology, propose Physarum polycephalum as such a system. Physarum polycephalum, henceforth Physarum, is a multinucleate slime mold with the remarkable ability to reassemble into a single organism after being broken into several fragments. Physarum can also "mass-sense", detect and grow towards the heaviest mass in its local environment. This grant supports research by Kurian and Levin to try to gain a scientific foothold on agency through the study of reassembly and mass-sensing in Physarum. Physarum is a good choice for this project because it is a simple cellular organism with no brain to decode; its behaviors are simple motions whose direct mechanistic causes can plausibly be determined. The project has two related goals: obtaining a corpus of novel data that informs the development of behavior-explaining, predictive models of mass sensing and reassembly in Physarum, and testing a hypothesis about how Physarum coordinates these behaviors—Kurian and Levin speculate they are controlled via superradiance in Physarum's cytoskeletal network. The overall plan is to develop a multi-scale (molecular- to cell-scale) model while also performing experiments to characterize Physarum during its search and mass-sensing activities. Dr. Kurian proposes to refine his existing cytoskeletal-superradiance model to better capture Physarum dynamics; in part by adding additional cytoskeletal components (actin & actomyosin) and in part via iteration of experiment and theory-simulation to pin down various model parameters and to benchmark model predictions against observations. The new model will also account for ultraweak photon emission, weak light associated with the metabolic production of reactive oxygen species. Microscopy imaging will then be used to create spatially- and temporally-resolved 'maps' that characterize Physarum during its reassembly and mass-sensing behaviors. They hypothesize that problem-relevant information is stored in cytoskeletal structure and read out by Physarum using a combination of bioelectric, optical, and calcium-signaling transduction mechanisms. These 'maps' will then be used as a way for researchers to access some of the information thought to be informing Physarum's decision-making processes. They will also use a novel Ultraweak Photon Emission (UPE) detector in order to track UPE as an indicator of metabolic activity. As a final experimental goal, Kurian and Levin will aim to demonstrate that Physarum can reassemble even when cut in to more than eight fragments, the current limit on demonstrated Physarum reintegration; possibly demonstrating reintegration of up to 32 fragments.

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