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

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.

"Organ-in-a-Column" Coupled On-line with Liquid Chromatography-Mass Spectrometry.

Organoids, i.e., laboratory-grown organ models developed from stem cells, are emerging tools for studying organ physiology, disease modeling, and drug development. On-line analysis of organoids with mass spectrometry would provide analytical versatility and automation. To achieve these features with robust hardware, we have loaded liquid chromatography column housings with induced pluripotent stem cell (iPSC) derived liver organoids and coupled the "organ-in-a-column" units on-line with liquid chromatography-mass spectrometry (LC-MS). Liver organoids were coloaded with glass beads to achieve an even distribution of organoids throughout the column while preventing clogging. The liver organoids were interrogated "on column" with heroin, followed by on-line monitoring of the drug's phase 1 metabolism. Enzymatic metabolism of heroin produced in the "organ-in-a-column" units was detected and monitored using a triple quadrupole MS instrument, serving as a proof-of-concept for on-line coupling of liver organoids and mass spectrometry. Taken together, the technology allows direct integration of liver organoids with LC-MS, allowing selective and automated tracking of drug metabolism over time.

Nuclear Magnetic Resonance Spectroscopy to Identify Metabolite Biomarkers of Nonresponsiveness to Targeted Therapy in Glioblastoma Tumor Stem Cells.

Glioblastoma is the most common and malignant brain tumor, and current therapies confer only modest survival benefits. A major obstacle is our ability to monitor treatment effect on tumors. Current imaging modalities are ambiguous, and repeated biopsies are not encouraged. To scout for markers of treatment response, we used NMR spectroscopy to study the effects of a survivin inhibitor on the metabolome of primary glioblastoma cancer stem cells. Applying high resolution NMR spectroscopy (1H resonance frequency: 800.03 MHz) to just 3 million cells per sample, we achieved sensitive and high resolving determinations of, e.g., amino acids, nucleosides, and constituents of the citric acid cycle. For control samples that were cultured, prepared, and measured at varying dates, peak area relative standard deviations were 15-20%. Analyses of unfractionated lysates were performed for straightforward compound identification with COLMAR and HMDB databases. Principal component analysis revealed that citrate levels were clearly upregulated in nonresponsive cells, while lactate levels substantially decreased following treatment for both responsive and nonresponsive cells. Hence, lactate and citrate may be potential markers of successful drug uptake and poor response to survivin inhibitors, respectively. Our metabolomics approach provided alternative biomarker candidates compared to spectrometry-based proteomics, underlining benefits of complementary methodologies. These initial findings make a foundation for exploring in vivo MR spectroscopy (MRS) of brain tumors, as citrate and lactate are MRS-visible. In sum, NMR metabolomics is a tool for addressing glioblastoma.

Ultracentrifugation versus kit exosome isolation: nanoLC-MS and other tools reveal similar performance biomarkers, but also contaminations.

AIM: For isolation of exosomes, differential ultracentrifugation and an isolation kit from a major vendor were compared. MATERIALS & METHODS: 'Case study' exosomes isolated from patient-derived cells from glioblastoma multiforme and a breast cancer cell line were analyzed. RESULTS: Transmission electron microscopy, dynamic light scattering, western blotting, and so forth, revealed comparable performance. Potential protein biomarkers for both diseases were also identified in the isolates using nanoLC-MS. Western blotting and nanoLC-MS also revealed negative exosome markers regarding both isolation approaches. CONCLUSION: The two isolation methods had an overall similar performance, but we hesitate to use the term 'exosome isolation' as impurities may be present with both isolation methods. NanoLC-MS can detect disease biomarkers in exosomes and is useful for critical assessment of exosome enrichment procedures.