Multi-Molecular Hyperspectral PRM-SRS Imaging

Abstract

Lipids play crucial roles in many biological processes under physiological and pathological conditions. Mapping spatial distribution and examining metabolic dynamics of different lipids in cells and tissues in situ are critical for understanding aging and diseases. Commonly used imaging methods, including mass spectrometry-based technologies or labeled imaging techniques, tend to disrupt the native environment of cells/tissues and have limited spatial or spectral resolution, while traditional optical imaging techniques still lack the capacity to distinguish chemical differences between lipid subtypes. To overcome these limitations, we developed a new hyperspectral imaging platform that integrates a Penalized Reference Matching algorithm with Stimulated Raman Scattering (PRM-SRS) microscopy. With this new approach, we directly visualized and identified multiple lipid species in cells and tissues in situ with high chemical specificity and subcellular resolution. High density lipoprotein (HDL) particles containing non-esterified cholesterol was observed in the kidney, indicating that these pools of cholesterol are ectopic deposits, or have yet to be enriched. We detected a higher Cholesterol to phosphatidylethanolamine (PE) ratio inside the granule cells of hippocampal samples in old mice, suggesting altered membrane lipid synthesis and metabolism in aging brains. PRM-SRS imaging also revealed subcellular distributions of sphingosine and cardiolipin in the human brain sample. Compared with other techniques, PRM-SRS demonstrates unique advantages, including faster data processing and direct user-defined visualization with enhanced chemical specificity for distinguishing clinically relevant lipid subtypes in different organs and species. Our method has broad applications in multiplexed cell and tissue imaging.

Pre-processing for precise super-resolution multimodal image analysis

“…In addition, the denoising and drift correction process is also applicable and essential to other image analysis processes. Recently, we have developed a PRM-SRS method to visualize multiple lipid subtype distribution from hyperspectral images [12]. In addition, we have used DO-SRS and multimodal imaging approaches for studying metabolic changes induced by aging [2,8,[13][14][15], disease [2,16], nanoparticle based drug delivery [17], and dietary conditions [14,18].…”

Advanced ratiometric image analysis for super-resolution hyperspectral SRS microscopy

“…Progressing further by augmenting the number of channels transformed into super-resolution images enables the application of the PRM-SRS [8] method. This offers a visual representation of the distribution of various lipid subtypes within the hyperspectral images.…”

“…Moreover, the precision in unmixing molecular components is enhanced based on their spectral shape. If utilized to probe metabolic activity alterations due to disease, aging, or dietary changes [8][9][10][11][12][13][14][15][16], this modality is poised to play an instrumental role in elucidating solutions connected to pathways involving multiple chemical components at the nanoscopic level. From the selected super-resolution images in hyperspectral image stack, intensity ratios can be imaged.…”

Subcellular resolution DO-SRS and 2PEF imaging of metabolic dynamics regulated by L-methionine in amyotrophic lateral sclerosis

“…Future study utilizing super-resolution deconvolution algorithms can significantly enhance spatial resolution of imaging in every single channel (from ~300 nm to ~80 nm) [20,21]. Multimodal images can also be collected in a hyperspectral manner, and a recently developed molecular detection program based on penalized reference matching method can also be applied for multiplex hyperspectral imaging of various biomolecules [22]. Together, more biomolecules and their biological significance in ALS under excess L-methionine regulation can be investigated in a greater depth.…”