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RESEARCH PAPER / 2026-04-14

Label free multimodal optical imaging of metabolic heterogeneity in aging by integrating SRS, MPF, FLIM, and SHG

Jang, H., Wu, S., Kim, H., Wei, T.-Y. W., Kang, J., Ataran, A., Gao, F., Skowronska-Krawczyk, D., Margulies, K. B., Javaheri, A., Sun, W., Shyy, J. Y.-J., Seker, E., Shi, L., Shi, L.

University of California San Diego · biorxiv

Abstract

Cellular metabolism is governed by the coordinated organization of macromolecules, including lipids and proteins, together with redox-active cofactors such as NADH and FAD. However, resolving these biochemical features quantitatively and spatially at subcellular resolution remains challenging because no single imaging modality can capture molecular composition, redox state, and tissue architecture simultaneously without labeling. Here, we present MANIFEST (Multi-modAl Nonlinear Imaging with Fluorescence Excitation and Statistical Temporal-resolved spectroscopy), a label-free imaging platform that integrates stimulated Raman scattering (SRS), second harmonic generation (SHG), multiphoton fluorescence (MPF), and fluorescence lifetime imaging microscopy (FLIM). The MANIFEST combines chemical imaging of lipids with autofluorescence- and lifetime-based quantification of NADH and FAD metabolism, enabling spatially resolved analysis of metabolic heterogeneity at organelle and tissue-compartment levels. We apply this framework to four distinct aging or disease models: amyloid-beta-treated tri-cultured brain cells, high-fat diet mouse liver, human non-ischemic cardiomyopathy tissue, and aging mouse retina. Across these systems, MANIFEST reveals disease-associated lipid remodeling, redox imbalance, disrupted metabolic zonation, collagen reorganization, and layer-specific metabolic changes. By integrating complementary nonlinear optical modalities into a single label-free platform, MANIFEST provides a generalizable approach for high-resolution metabolic phenotyping in complex biological systems and offers new opportunities for studying disease mechanisms, aging biology, and metabolism-driven tissue pathology.

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Research summary

The paper presents a novel imaging platform that enables high-resolution metabolic phenotyping in aging and disease models. The integration of multiple imaging modalities to study metabolic heterogeneity in aging provides insights into the biochemical changes associated with aging, which is relevant to understanding the root causes of aging and age-related diseases.

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