Label-Free Imaging of Lipid Storage Dynamics in Caenorhabditis elegans using Stimulated Raman Scattering Microscopy.

Lipid metabolism is a fundamental physiological process necessary for cellular and organism health. Dysregulation of lipid metabolism often elicits obesity and many associated diseases including cardiovascular disorders, type II diabetes, and cancer. To advance the current understanding of lipid metabolic regulation, quantitative methods to precisely measure in vivo lipid storage levels in time and space have become increasingly important and useful. Traditional approaches to analyze lipid storage are semi-quantitative for microscopic assessment or lacking spatio-temporal information for biochemical measurement. Stimulated Raman scattering (SRS) microscopy is a label-free chemical imaging technology that enables rapid and quantitative detection of lipids in live cells with a subcellular resolution. As the contrast is exploited from intrinsic molecular vibrations, SRS microscopy also permits four-dimensional tracking of lipids in live animals. In the last decade, SRS microscopy has been widely used for small molecule imaging in biomedical research and overcome the major limitations of conventional fluorescent staining and lipid extraction methods. In the laboratory, we have combined SRS microscopy with the genetic and biochemical tools available to the powerful model organism, Caenorhabditis elegans, to investigate the distribution and heterogeneity of lipid droplets across different cells and tissues and ultimately to discover novel conserved signaling pathways that modulate lipid metabolism. Here, we present the working principles and the detailed setup of the SRS microscope and provide methods for its use in quantifying lipid storage at distinct developmental timepoints of wild-type and insulin signaling deficient mutant C. elegans.

Label-free chemical imaging flow cytometry by high-speed multicolor stimulated Raman scattering.

Combining the strength of flow cytometry with fluorescence imaging and digital image analysis, imaging flow cytometry is a powerful tool in diverse fields including cancer biology, immunology, drug discovery, microbiology, and metabolic engineering. It enables measurements and statistical analyses of chemical, structural, and morphological phenotypes of numerous living cells to provide systematic insights into biological processes. However, its utility is constrained by its requirement of fluorescent labeling for phenotyping. Here we present label-free chemical imaging flow cytometry to overcome the issue. It builds on a pulse pair-resolved wavelength-switchable Stokes laser for the fastest-to-date multicolor stimulated Raman scattering (SRS) microscopy of fast-flowing cells on a 3D acoustic focusing microfluidic chip, enabling an unprecedented throughput of up to ∼140 cells/s. To show its broad utility, we use the SRS imaging flow cytometry with the aid of deep learning to study the metabolic heterogeneity of microalgal cells and perform marker-free cancer detection in blood.