Cedric Kamaleson

BioE PhD Proposal Presentation

Time and Date | 8:30 AM, February 19, 2025

Location | Parker H. Petit Institute for Bioengineering and Biosciences (IBB), Suddath Seminar Room 1128 

Zoom Link

Advisor:

Dr. Saad Bhamla, Chemical and Biomolecular Engineering, Georgia Institute of Technology

Thesis Committee:

Dr. Audrey Dussutour, Center for Research on Animal Cognition, National Center for Scientific Research (University of Toulouse)

Dr. William Ratcliff, Quantitative Biosciences, Georgia Institute of Technology 

Dr. David Hu, Mechanical Engineering, Georgia Institute of Technology

Dr. Kostas Konstantinidis, Civil and Environmental Engineering, Georgia Institute of Technology

RNA-mediated Unicellular Learning and Cognition

Unicellular organisms, despite lacking neurons, exhibit diverse learning behaviors, including habituation and classical conditioning. While the validity of complex learning in unicellular systems remains debated, compelling evidence suggests that memories can be transferred between these organisms, with growing support for RNA as a molecular engram for memory storage. This proposal aims to elucidate RNA’s role in learning and challenge the cognitive limitations of unicellular organisms, proposing that unicellular learning mechanisms may not only precede but also influence neural-based learning. The ciliate Spirostomum ambiguum serves as an ideal model system, given its well-documented habituation profiles and unicellular architecture, which enables precise molecular investigations of learning without the confounding complexities of multicellular systems. Three interconnected objectives will be pursued to illuminate how cells can learn without neurons. Aim 1 focuses on inducing and molecularly characterizing habituation in S. ambiguum using novel transcriptomic methods, revisiting an outdated correlation between RNA dynamics and habituation with modern approaches to validate RNA's role in learning. Aim 2 challenges the cognitive boundaries of unicellular organisms by testing associative learning in S. ambiguum, demonstrating that the gap in learning capacity between neural and aneural organisms is smaller than previously assumed. Aim 3 explores collective learning mechanisms in swarming populations, investigating the ecological significance of learning for S. ambiguum. By pushing the cognitive boundaries of unicellular systems, this work will help establish S. ambiguum and similar organisms as a reductionist model for behavioral studies, providing insights into fundamental learning mechanisms that may serve as precursors to neural learning in more complex organisms.