Title
「Model-driven investigation of ribosome dynamics」 ポスター🔗
Lecturer
Dr. Saori Uematsu（Cornell University・M.D.,Ph.D.）
Date, Time & Venue
15:00-16:00, November 20 , 2025 Seminar Room A , 2nd floor the Building G , Medical Campus
Abstract
Translation, the decoding of mRNA to synthesize proteins, is fundamental to cellular homeostasis and function. Ribosome profiling (Ribo-seq), which measures ribosome-protected footprints genome-wide, has revealed that ribosomes traverse mRNAs at highly heterogeneous speeds; they pause at specific positions and can even collide after prolonged stalling. However, Ribo-seq is a static snapshot of ribosome occupancy rather than direct decoding speeds, and gene-level read counts can be inflated by pausing, obscuring true protein output. These features hinder our understanding of complex ribosome behaviors and our ability to link ribosome behavior to protein synthesis.
In this talk, I will present mathematical and computational models that quantitatively connect codon sequences, ribosome densities, elongation kinetics, and protein production rates. I developed a TASEP-grounded deep learning framework that infers position-specific elongation speeds from Ribo-seq-derived density. A stochastic simulation converts these speeds into actionable metrics such as protein production rates and collision propensity, which could be used for codon optimization. To extend analysis to mRNAs lacking Ribo-seq, I fine-tuned a codon language model to predict ribosome density from sequences only.
Together, the proposed framework of a sequence-density-speed-output mapping improves the interpretability of Ribo-seq, laying a foundation for rational, ribosome-aware codon optimization.
Contact
Division of Integrated Life Science, Department of Gene Mechanisms,
Laboratory of Cell Cycle Regulation
Center for Living Systems Information Science 【CeLiSIS】
Kazuhiro Aoki（aoki.kazuhiro.6v@kyoto-u.ac.jp）
