Unveiling Hidden Cellular Architecture: Mapping the intracellular Protein Organization Landscape (iPOL) to define cell states and types

1 Project Summary 2 3 Understanding the spatial and temporal organization of intracellular proteins is critical for advancing 4 biomedical research, particularly in disease diagnostics, personalized medicine, and drug discovery. 5 My research program focuses on detecting and quantitatively characterizing spatial patterns across 6 biological scales, from intracellular to tissue-level organization, to uncover the mechanisms driving 7 these patterns and their roles in both physiological function and disease. We focus on developing 8 computational tools to infer cell types and states from hidden symmetries and intracellular 9 organization. While omics approaches like transcriptomics and proteomics advance molecular 10 characterization, they fail to capture the temporal dynamics of cell state transitions. Additionally, 11 cellular functions are often directly linked to the spatiotemporal organization of intracellular proteins, 12 an aspect not addressed by molecular -omics techniques. To bridge this gap, we propose the 13 "Intracellular Protein Organization Landscape" (iPOL), a quantitative framework that defines 14 and characterizes cell types and states based on their spatial protein organization, rather than 15 molecular composition. iPOL integrates high-resolution imaging, feature extraction, and manifold 16 learning to map cell types in a new "protein organization morphological space." Our research aims to 17 answer three key questions: (1) Can iPOL quantitatively characterize cell state transitions during 18 processes like epithelial-to-mesenchymal transition (EMT)? (2) Does intracellular organization reveal 19 hidden aspects of cell type differentiation? (3) Do intracellular asymmetries encode positional 20 information during development? To address the first question, we will construct the iPOL for EMT in 21 development, wound healing, and cancer metastasis to quantitatively characterize, compare and 22 discover mechanistic differences between the cell state transitions in different biological contexts. To 23 address the next two questions, we will use early development in sea urchin as a model system to 24 interrogate how iPOL can reveal new cell states and spatiotemporal dynamics in their native contexts. 25 The conceptual innovation of this work is the development of iPOL as a novel framework to define 26 cell states and types based on cellular phenotype rather than molecular composition. The technical 27 innovation lies in leveraging higher-order morphological, topological, and symmetry-based metrics 28 to capture complex intracellular structures that more directly reflect cellular function. By integrating 29 spatial and temporal protein localization patterns with molecular data, iPOL offers a transformative 30 perspective on cellular function and behavior, with broad implications for understanding diseased 31 cellular states and advancing medical diagnostics through high-resolution imaging techniques. Project Number: 1R35GM162633-01 | Fiscal Year: 2026 | NIH Institute/Center: National Institute of General Medical Sciences (NIGMS) | Principal Investigator: Tzer Han Tan | Institution: UNIVERSITY OF CALIFORNIA, SAN DIEGO, LA JOLLA, CA | Award Amount: $370,550 | Activity Code: R35 | Study Section: Special Emphasis Panel[ZRG1 CDB-N (55)] View on NIH RePORTER: https://reporter.nih.gov/project-details/11272712