Periodic Reporting for period 1 - UltraRamanomics (High Content Microanalytical Ramanomics for Ultraquantitative Phenotyping of Individual Stem Cells and Bioengineered Organoids)
Période du rapport: 2020-10-01 au 2022-09-30
Human induced pluripotent stem (hiPS) cell-based organoids have recently emerged as a promising model system to recapitulate the structure and function of actual biological tissues and organs. These 3D self-organized multi-cellular tissue systems bridge the gap from cell to tissue/organ levels, providing bio-relevant model systems with foreseeable utility in drug discovery, regenerative medicine, and the study of disease pathogenesis. However, the increased complexity and unique attributes of each system introduces new challenges in cell culture and experimental reproducibility. While organoids offer profound potential for applications in biological and biomedical research, their scientific value is limited by a lack of correct tissue architecture and maturity of the parenchymal cells. To improve the design and development of organoid-based predictive model system, it is crucial to have a quantitative biochemical and structural analysis technique at single cell resolution in organoids. In UltraRamanomics, I developed a robust quantitatively calibrated bioanalytical platform for high content phenotypic profiling of hiPS cell-derived organoids. This system allows direct structural and quantitative compositional comparison of organoid models in absolute biochemical measurements, thereby addressing the currently unmet analytical need. The platform is based on micro-Raman spectroscopy – enabling direct measurements of the absolute biochemical composition of single-cells and tissue organoids with unprecedented spatial resolution and providing a novel analytical solution to the existing gap in stem cell organoid research.
To develop a strategy for quantitative chemometric unmixing of Raman spectra from organoids, we designed a 3D tissue phantom calibration technology which enables direct simultaneous measurement of absolute local concentrations of the most abundant biomolecular components and sequestered xenobiotics. The poor solubility of lipids in aqueous media was resolved by employing formulated saturated (DPPC) and monounsaturated (POPC) synthetic high-density lipoprotein nanodiscs (sHDLs) of ~10 nm particle diameter. This allowed dissolution of lipids up to 80 mg/mL and facilitated miscibility with other biomolecules at varying concentrations in PBS. The calibration was repeated across concentration ranges for protein, DPPC, POPC, DNA, and glycogen. The complete unit-scaled reference spectral model accurately identified and deconvoluted single-component tissue phantom data with minimal errors using linear combination modelling approaches. Bayesian model fitting enabled accuracy and precision confidence assessments across measured concentration ranges and specificity in complex multi-component mixtures for model validation. The fundamental linear theory presented herein establishes a robust framework for quantitative analysis of 3D biospecimens.
Primary human hepatocyte spheroids (3D PHH) and iPSC-derived hepatocyte-like cell containing organoids (3D iHLC) were generated using modified differentiation protocols to ensure functional maturation. We employed the Raman methodology for high-content quantitative comparison of 3D PHH and 3D iHLC specimens to determine quantitative and qualitative differences between both. UltraRamanomics revealed similar patterns of glycogen accumulation between 3D iHLC and 3D PHH, an important hallmark of hepatocytes functionality and essential for the maintenance of glucose homeostasis. No significant differences were observed in total lipids content. UltraRamanomics revealed lower protein concentration, a marker for functional activity, per iHLC organoids as compared to the benchmark PHH spheroids. Lower protein concentrations were subsequently confirmed by UV-spectroscopy and proteomics.
We also applied the platform for quantitative chemometric phenotyping of 3D PHHs and 3D iHLCs upon exposure to a panel of drugs with reported impact on hepatocytes. 3D PHHs and 3D iHLCs were exposed to 10 µM amiodarone, nilotinib, fluticasone-propionate, ketoconazole, neratinib, and methadone for 48 h prior to analysis. UltraRamanomics elucidated drug-specific compositional changes induced in 3D PHH and 3D iHLC. We observed a drug-specific modulation of lipid content in all treatment groups, with marked increases in the amiodarone- and nilotinib-treated groups. Elevated levels of glycogen, as well as changes in cyt c levels and its co-localization with DNA, proteins, and lipids were seen in drug-treated groups. Among all tested drugs, amiodarone treatment induced the most significant changes in glycogen (increase) and cyt c concentrations (decrease). To the best of our knowledge, amiodarone-induced glycogenosis has not yet been reported.
Beyond biomolecular phenotyping upon drug exposure, UltraRamanomics enables direct measurement of contextual drug and metabolite accumulation within cells. We report the first spectroscopic evidence of xenobiotic deposits of amiodarone and fluticasone detectable by Raman within the 3D biospecimens along with evidence of nilotinib and neratinib accumulation, while no deposits were detected in the ketoconazole or methadone treatment groups. 3D images were generated for to visualize the distribution of drug/metabolite deposits within the spheroids and organoids. To the best of our knowledge, this has not been reported previously.
Primary human hepatocyte spheroids (3D PHH) and iPSC-derived hepatocyte-like cell containing organoids (3D iHLC) were generated using modified differentiation protocols to ensure functional maturation. We employed the Raman methodology for high-content quantitative comparison of 3D PHH and 3D iHLC specimens to determine quantitative and qualitative differences between both. UltraRamanomics revealed similar patterns of glycogen accumulation between 3D iHLC and 3D PHH, an important hallmark of hepatocytes functionality and essential for the maintenance of glucose homeostasis. No significant differences were observed in total lipids content. UltraRamanomics revealed lower protein concentration, a marker for functional activity, per iHLC organoids as compared to the benchmark PHH spheroids. Lower protein concentrations were subsequently confirmed by UV-spectroscopy and proteomics.
We also applied the platform for quantitative chemometric phenotyping of 3D PHHs and 3D iHLCs upon exposure to a panel of drugs with reported impact on hepatocytes. 3D PHHs and 3D iHLCs were exposed to 10 µM amiodarone, nilotinib, fluticasone-propionate, ketoconazole, neratinib, and methadone for 48 h prior to analysis. UltraRamanomics elucidated drug-specific compositional changes induced in 3D PHH and 3D iHLC. We observed a drug-specific modulation of lipid content in all treatment groups, with marked increases in the amiodarone- and nilotinib-treated groups. Elevated levels of glycogen, as well as changes in cyt c levels and its co-localization with DNA, proteins, and lipids were seen in drug-treated groups. Among all tested drugs, amiodarone treatment induced the most significant changes in glycogen (increase) and cyt c concentrations (decrease). To the best of our knowledge, amiodarone-induced glycogenosis has not yet been reported.
Beyond biomolecular phenotyping upon drug exposure, UltraRamanomics enables direct measurement of contextual drug and metabolite accumulation within cells. We report the first spectroscopic evidence of xenobiotic deposits of amiodarone and fluticasone detectable by Raman within the 3D biospecimens along with evidence of nilotinib and neratinib accumulation, while no deposits were detected in the ketoconazole or methadone treatment groups. 3D images were generated for to visualize the distribution of drug/metabolite deposits within the spheroids and organoids. To the best of our knowledge, this has not been reported previously.
Over the past three decades, Raman spectroscopy has emerged as a powerful tool for the analysis of biospecimens, with applications ranging from non-invasive in vivo clinical diagnostics to single-cell analyses. Raman enables label-free non-destructive investigation of a sample’s chemical composition via laser-induced molecular vibrations which scatter light at various wavelengths, providing spectral “fingerprints” which are directly and quantitatively related to the molecular composition of the sample. Coupled to a confocal microscope, micro-Raman offers unprecedented spatial resolution, thereby opening the doors of scientific perception to the unadulterated (label-free, non-destructive) biomolecular realm within living cells and tissues. While quantitation at the single-cell level has been claimed by many research groups, it remains a topic of scepticism throughout the Raman community due to the absence or reliable calibration standards. To address this gap in the field, we developed a novel micro-calibration methodology which enables ultraquantitative micro-Ramanomics: direct simultaneous measurement of absolute local concentrations of the most abundant biomolecular components and sequestered xenobiotics within single eukaryotic cells (i.e. femtograms/femtolitre of protein, lipid, nucleic acid, carbohydrate, and drug throughout single cells). Ultraquantitation provides more in-depth chemotypic characterization of cell populations than previously possible and represents a significant advancement in the field of Raman-based biomedical research but further development of instrumental calibration technology is still necessary to facilitate interlaboratory comparisons of Raman cytometry data and harmonize Ramanomics at the global level. Overall, the UltraRamanomics project provides a holistic answer to the significant and currently unmet need in organoid engineering: quantitative biochemical analysis of organoids at the single- and multi-cellular levels to evaluate and track their functional state.