Spatiotemporal dynamics of biological systems: from high-resolution technology to predictive modeling

Microbiome research is entering an era, driven by the rapid advance of AI and data science, in which “what can be predicted from large-scale data” is increasingly regarded as the field's central value. Yet we have not yet reached the stage of truly controlling and predicting host–microbiome interactions.

Behind this gap lies a shortage of ultra-high-resolution observation platforms that connect molecules, cells, and organisms, and the immaturity of theoretical frameworks capable of integrating the complex phenomena revealed by such new observations.

This symposium brings together researchers from Japan and abroad who share this concern, aiming to directly connect next-generation observation technologies — spatiotemporal analysis, omics analysis, automation, long-read sequencing, organoids, and more — with theoretical frameworks centered on complex-systems mathematics and data-driven analysis.

Throughout the history of science, new observation technologies have always opened up new theories and new fields of study. Under the keyword “New tools lead to new science,” this symposium gathers researchers who develop and apply original, state-of-the-art observation technologies for spatiotemporal microbiome analysis — long-read sequencing, spatial omics (spatial transcriptomics, spatial metabolomics, spatial proteomics, and more), automated time-series measurement, live imaging, organoids and synthetic ecosystems — together with specialists in complex-systems mathematics, AI and data science, mathematical modeling, and information science, to explore new research angles and directions that set this work apart from conventional biology.

What distinguishes this symposium is not simply a showcase of new technologies or analytical case studies, but a shared commitment to the fundamental question of what and how we should observe in order to understand and control living systems — directly connecting observation technology with theoretical science. As AI's analytical power advances dramatically, questioning the resolution and design of the observational data itself matters more than ever. The future of microbiome research requires a new academic foundation that goes beyond mere data accumulation and correlation-seeking, cyclically integrating observation, theory, and control.

Through this symposium, we hope to create a new research current that develops microbiome research from an “observational science” into a “controllable, predictable complex-systems science.” We also aim to connect observation technologies and analytical methods uniquely developed in Japan with direct discussion among leading researchers worldwide — strengthening the international reach of Japan-originated research and paving the way for new collaborations and interdisciplinary research.

Co-hosted, on equal footing, by the JST-CREST BioDX project (PI: Wataru Suda) and the ERATO Arita Lipidome Atlas Project (Research Director: Makoto Arita) — bringing together time-axis and space-axis approaches to living systems — and co-organized with RIKEN IMS and the Keio University Bio2Q Center.