Quantitative chemometric phenotyping of three-dimensional liver organoids by Raman spectral imaging

Journal article

Confocal Raman spectral imaging (RSI) enables high-content, label-free visualization of a wide range of molecules in biological specimens without sample preparation. However, reliable quantification of the deconvoluted spectra is needed. Here we develop an integrated bioanalytical methodology, qRamanomics, to qualify RSI as a tissue phantom calibrated tool for quantitative spatial chemotyping of major classes of biomolecules. Next, we apply qRamanomics to fixed 3D liver organoids generated from stem-cell-derived or primary hepatocytes to assess specimen variation and maturity. We then demonstrate the utility of qRamanomics for identifying biomolecular response signatures from a panel of liver-altering drugs, probing drug-induced compositional changes in 3D organoids followed by in situ monitoring of drug metabolism and accumulation. Quantitative chemometric phenotyping constitutes an important step in developing quantitative label-free interrogation of 3D biological specimens

Authors: LaLone, V; Aizenshtadt, A; Goertz, J; Skottvoll, FS; Mota, MB

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Cell Press
• Journal: Cell Reports: Methods
• Volume: 3
• Issue: 4
• Pages: 100440-100440
• Article number: 100440
• Publication date: 2023-03-31
• DOI: 10.1016/j.crmeth.2023.100440
• EISSN: 2667-2375
• ISSN: 2667-2375
• Language: English
• Keywords: Organoid; Computational biology; Biological specimen; Chromatography; Biomolecule; Raman spectroscopy; Drug discovery; Materials science; Biology; Nanotechnology; Chemistry; Bioanalysis; Quantitative analysis (chemistry); Bioinformatics