Authors
Anoushka Gupta, Pooja Anantha, Hidenori Koresawa, Heqi Xi, Yu-Hua Beckham Yang, Michael Ka Ho Lee, Katsumasa Fujita, Sui-Seng Tee, Ishan Barman
Published in
Biosensors & bioelectronics. Volume 290. Pages 117994. Dec 15, 2025. Epub Sep 13, 2025.
Abstract
Brown adipose tissue (BAT) plays a pivotal role in energy expenditure and metabolic health, yet the influence of specific sugars like fructose on brown adipocyte development remains poorly understood. Here, we employ high-speed line-illumination Raman imaging, combined with machine learning, to investigate how varying sugar environments - fructose, glucose, or both - impact the differentiation of human brown preadipocytes (HBPs). This label-free, non-destructive method provides spatially-resolved insight into lipid content, composition, and subcellular distribution during adipogenesis. Quantitative ratiometric analysis of Raman spectra reveals that fructose exposure leads to higher lipid unsaturation and esterification, indicative of impaired differentiation. Trajectory inference and unsupervised clustering further identify distinct subpopulations of adipocytes, demonstrating that fructose-treated cells exhibit phenotypes associated with early differentiation stages. Together, our findings reveal a negative regulatory role of fructose in brown adipocyte maturation and highlight Raman imaging as a powerful tool for dissecting metabolic cell states under variable nutrient conditions.
PMID:
40957282
Bibliographic data and abstract were imported from PubMed on 06 Oct 2026.
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