Using Raman Spectroscopy and Surface-enhanced Raman Spectroscopy to Detect Cholesterol Disorders

Disease detection is a hot topic in spectroscopic circles, including how new diagnostic tools can be used to detect diseases in patients. To advance this research, researchers are using Raman spectroscopy and surface-enhanced Raman spectroscopy (SERS) to quantify intracellular cholesterol (1).

Cholesterol is required in the human body for it to function properly. However, having too much cholesterol under certain conditions can lead to severe health complications, including heart disease, kidney disease, Niemann-Pick disease type C (NPC), and polycystic ovary syndrome (2). Accurate methods for intracellular cholesterol measurement are critical for understanding cell physiology and diagnosing metabolic disorders (1).

Cholesterol plaque in artery with human heart anatomy. 3D illustration. | Image Credit: © Rasi - stock.adobe.com

In this study, researchers Caterina Dallari and Martino Calamai and their team from the European Laboratory for Non-Linear Spectroscopy (LENS) and the National Institute of Optics at the National Research Council in Italy focused on assessing changes in cholesterol levels in human fibroblasts enriched with cholesterol-methyl-β-cyclodextrin (1). The team was able to demonstrate in their study that Raman spectroscopy and SERS were sensitive enough to detect specific cholesterol signals. Out of the two techniques, it was determined that SERS was more effective because the technique was able to deliver precise differentiation between fibroblast populations from various NPC patients, outperforming standard fluorescence imaging methods like filipin III labeling (1).

NPC is characterized by excessive cholesterol buildup in lysosomes, impairing cellular function (1,3). It is a rare neurodegenerative disease that damages the nervous system over time (3). In their study, the researchers found that when bolstered by gold nanoparticles (AuNPs), SERS could determine the extent of cholesterol accumulation in fibroblasts from different NPC patients (1). The specificity of AuNPs’ trafficking to lysosomes—NPC’s primary site of cholesterol storage—helped amplify SERS’s sensitivity (1).

The AuNPs played a critical role in this study. These nanoparticles, used as signal enhancers in SERS, were internalized by cells and localized in lysosomes (1). Their specific lysosomal accumulation aligned perfectly with NPC fibroblasts’ pathological hallmark—cholesterol storage in these compartments (1). By amplifying the Raman signals, the AuNPs enabled unparalleled accuracy in cholesterol detection, establishing SERS as a powerful tool for biomedical applications (1).

Another technique used for this type of analysis is fluorescence imaging with filipin III, and the researchers showed how SERS improves on this method. Filipin III helps provide a generalized view of cholesterol accumulation, but it lacked the sensitivity to differentiate subtle variations across patient-derived fibroblast populations (1). Filipin III yields a strong fluorescence signal when bound to cholesterol in biological systems. In contrast, SERS delivered precise, label-free analysis, which allows scientists to gain a better understanding of intracellular cholesterol dynamics (1).

The study also showed how SERS is superior to Raman spectroscopy for this analysis. Unlike Raman spectroscopy, SERS can accomplish two important things essential in cholesterol-related dynamics. First, SERS can reliably detect cholesterol in normal fibroblasts (wild-type) (1). Second, SERS can distinguish between the cholesterol levels in fibroblasts from different NPC patients (1).

SERS is a sensitive, label-free tool to use for evaluating intracellular cholesterol content. The researchers demonstrate its effectiveness in this study while showing how it can contribute to the development of optical detection systems for ex-vivo screening and monitoring cholesterol-related diseases (1). Beyond NPC, SERS (and Raman spectroscopy to a lesser extent) holds promise for broader applications in diagnosing and studying metabolic disorders where cholesterol dysregulation is a key factor (1).

Future research may explore the application of these techniques in other lipid-related disorders and further refine the use of nanoparticles for enhanced diagnostic capabilities (1). By advancing our ability to measure and understand intracellular cholesterol, this research represents a significant step toward improving the diagnosis and treatment of metabolic diseases, offering hope to patients affected by conditions like NPC.

References

1. Baria, E.; Dallari, C.; Mattii, F.; et al. Evaluating Pathological Levels of Intracellular Cholesterol through Raman and Surface-enhanced Raman Spectroscopies. Sci. Rep. 2024, 14, 28566. DOI: 10.1038/s41598-024-76621-5
2. Penn Medicine, High Cholesterol. Penn Medicine.org. Available at: https://www.pennmedicine.org/for-patients-and-visitors/patient-information/conditions-treated-a-to-z/high-cholesterol#:~:text=Cholesterol%20is%20a%20fat%20(also,%2C%20stroke%2C%20and%20other%20problems. (accessed 2024-11-22).
3. Alzheimer Society, Niemann-Pick Disease Type C. Alzheimer.ca. Available at: https://alzheimer.ca/en/about-dementia/other-types-dementia/rare-types-dementia/niemann-pick-disease-type-c#:~:text=Occupational%20and%20physical%20therapies%20may,from%20the%20progression%20of%20NPC. (accessed 2024-11-22).