Mapping metabolic changes by noninvasive, multiparametric, high-resolution imaging using endogenous contrast

Zhiyi Liu,Dimitra Pouli,C. Alonzo,A. Varone,Sevasti Karaliota,K. Quinn,K. Münger,Katia P. Karalis,I. Georgakoudi

Published 2018 in Science Advances

ABSTRACT

Two-photon imaging provides noninvasive, label-free, quantitative assays of metabolic changes at the single-cell or tissue level. Monitoring subcellular functional and structural changes associated with metabolism is essential for understanding healthy tissue development and the progression of numerous diseases, including cancer, diabetes, and cardiovascular and neurodegenerative disorders. Unfortunately, established methods for this purpose either are destructive or require the use of exogenous agents. Recent work has highlighted the potential of endogenous two-photon excited fluorescence (TPEF) as a method to monitor subtle metabolic changes; however, mechanistic understanding of the connections between the detected optical signal and the underlying metabolic pathways has been lacking. We present a quantitative approach to detecting both functional and structural metabolic biomarkers noninvasively, relying on endogenous TPEF from two coenzymes, NADH (reduced form of nicotinamide adenine dinucleotide) and FAD (flavin adenine dinucleotide). We perform multiparametric analysis of three optical biomarkers within intact, living cells and three-dimensional tissues: cellular redox state, NADH fluorescence lifetime, and mitochondrial clustering. We monitor the biomarkers in cells and tissues subjected to metabolic perturbations that trigger changes in distinct metabolic processes, including glycolysis and glutaminolysis, extrinsic and intrinsic mitochondrial uncoupling, and fatty acid oxidation and synthesis. We demonstrate that these optical biomarkers provide complementary insights into the underlying biological mechanisms. Thus, when used in combination, these biomarkers can serve as a valuable tool for sensitive, label-free identification of changes in specific metabolic pathways and characterization of the heterogeneity of the elicited responses with single-cell resolution.

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