Multimodal Optical Imaging Platform for Studying Cellular Metabolism

Optical imaging technologies are critical in biomedical studies for their ability to obtain both morphological and functional information from biological specimens at high spatial resolution. These optical processes exploit various light-molecule interactions, such as scattering, absorption, emission, and harmonic generation, between photons and the molecules within cells, tissues, or organs. While conventional biomedical imaging has historically focused on applying a single modality, recent research has shown that these diverse techniques provide complementary insights, and their combined outputs offer a more comprehensive understanding of molecular changes in aging processes and disease development and fundamentals in cell biology. In the past decades, label-free optical imaging methods have advanced, enabling detailed exploration of cellular and subcellular environments. For instance, multiphoton fluorescence (MPF) not only facilitates targeted protein imaging but also quantifies metabolic activity through autofluorescent coenzymes, achieving high penetration depth and spatial resolution. Second Harmonic Generation (SHG) is used to image structures like collagen in the extracellular matrix, while Stimulated Raman Scattering (SRS) maps chemical bonds and molecular composition in situ with subcellular resolution. We have developed a multimodal imaging platform that combines MPF, SHG, and SRS modalities. The integration of these modalities into a single platform enables the acquisition of multifaceted information from the same localization within cells, tissues, organs, or even bodies, facilitating a more detailed exploration of the intricate relationships between cellular metabolism, extracellular matrix structure, and molecular composition. This multimodal system offers subcellular resolution, deep tissue penetration, in situ live-cell/tissue imaging, as well as label-free detection and instantaneous coregistration without the need for position adjustments, device switching, or postanalysis alignment. Here, we present a protocol for label-free imaging with this multimodal platform and demonstrate its application in characterizing cellular metabolism, and molecular heterogeneity in cells and tissues for studying aging and diseases.