Simultaneous LC-MS determination of glucose regulatory peptides secreted by stem cell-derived islet organoids.

For studying stem cell-derived islet organoids (SC-islets) in an organ-on-chip (OoC) platform, we have developed a reversed-phase liquid chromatography-tandem mass spectrometry (RPLC-MS/MS) method allowing for simultaneous determination of insulin, somatostatin-14, and glucagon, with improved matrix robustness compared to earlier methodology. Combining phenyl/hexyl-C18 separations using 2.1 mm inner diameter LC columns and triple quadrupole mass spectrometry, identification and quantification were secured with negligible variance in retention time and quantifier/qualifier ratios, negligible levels of carryover (<2%), and sufficient precision (±10% RSD) and accuracy (±15% relative error) with and without use of an internal standard. The obtained lower limits of quantification were 0.2 µg/L for human insulin, 0.1 µg/L for somatostatin-14, and 0.05 µg/L for glucagon. The here-developed RPLC-MS/MS method showed that the SC-islets have an insulin response dependent on glucose concentration, and the SC-islets produce and release somatostatin-14 and glucagon. The RPLC-MS/MS method for these peptide hormones was compatible with an unfiltered offline sample collection from SC-islets cultivated on a pumpless, recirculating OoC (rOoC) platform. The SC-islets background secretion of insulin was not significantly different on the rOoC device compared to a standard cell culture well-plate. Taken together, RPLC-MS/MS method is well suited for multi-hormone measurements of SC-islets on an OoC platform.

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.

Determination of insulin secretion from stem cell-derived islet organoids with liquid chromatography-tandem mass spectrometry.

Organoids are laboratory-grown 3D organ models, mimicking human organs for e.g. drug development and personalized therapy. Islet organoids (typically 100-200 µm), which can be grown from the patient́s own cells, are emerging as prototypes for transplantation-based therapy of diabetes. Selective methods for quantifying insulin production from islet organoids are needed, but sensitivity and carry-over have been major bottlenecks in previous efforts. We have developed a reverse phase liquid chromatography-tandem mass spectrometry (RPLC-MS/MS) method for studying the insulin secretion of islet organoids. In contrast to our previous attempts using nano-scale LC columns, conventional 2.1 mm inner diameter LC column (combined with triple quadrupole mass spectrometry) was well suited for sensitive and selective measurements of insulin secreted from islet organoids with low microliter-scale samples. Insulin is highly prone to carry-over, so standard tubings and injector parts were replaced with shielded fused silica connectors. As samples were expected to be very limited, an extended Box-Behnken experimental design for the MS settings was conducted to maximize performance. The finale method has excellent sensitivity, accuracy and precision (limit of detection: ≤0.2 pg/µL, relative error: ≤±10%, relative standard deviation: <10%), and was well suited for measuring 20 µL amounts of Krebs buffer containing insulin secreted from islet organoids.

"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.

Electromembrane Extraction and Mass Spectrometry for Liver Organoid Drug Metabolism Studies.

Liver organoids are emerging tools for precision drug development and toxicity screening. We demonstrate that electromembrane extraction (EME) based on electrophoresis across an oil membrane is suited for segregating selected organoid-derived drug metabolites prior to mass spectrometry (MS)-based measurements. EME allowed drugs and drug metabolites to be separated from cell medium components (albumin, etc.) that could interfere with subsequent measurements. Multiwell EME (parallel-EME) holding 100 µL solutions allowed for simple and repeatable monitoring of heroin phase I metabolism kinetics. Organoid parallel-EME extracts were compatible with ultrahigh-performance liquid chromatography (UHPLC) used to separate the analytes prior to detection. Taken together, liver organoids are well-matched with EME followed by MS-based measurements.

Electromembrane extraction of sodium dodecyl sulfate from highly concentrated solutions.

This fundamental work investigated the removal of sodium dodecyl sulfate (SDS) from highly concentrated samples by electromembrane extraction (EME). SDS concentrations were in the range of 0.1-1.0% w/v, covering both sub- and super-critical micellar concentrations (CMC). Under optimal conditions, we extracted SDS from 100 µL aqueous sample, through 3 µL supported liquid membrane (SLM) and into 200 µL 10 mM NaOH in water as waste solution. The SLM comprised 1.0% w/w Aliquat 336 in 1-nonanol, and extraction voltage was 5 V. From 0.1% SDS samples, EME removed 100% during 30 minutes operation (100% clearance). SDS concentration above the critical micellar concentration (CMC) challenged the capacity of the system. Thus, to reach 100% clearance from 0.5% samples, we extracted for 120 minutes and replenished the SLM after 60 minutes. Increasing the membrane area of the SLM from 28 mm2 to 43 mm2 provided 100% clearance from 0.5% samples after 30 min EME. Complete clearance of 1.0% SDS samples was not achieved under the tested conditions, and maximal clearance was 60%. Mass balance experiments demonstrated that most of the removed SDS is trapped in the SLM, rather than transferring to the waste solution. For super-CMC samples, aggregation of SDS in the SLM exceeded the SLM capacity and impeded further mass transfer.

Investigating Monoliths (Vinyl Azlactone-co-Ethylene Dimethacrylate) as a Support for Enzymes and Drugs, for Proteomics and Drug-Target Studies.

Prior to mass spectrometry, on-line sample preparation can be beneficial to reduce manual steps, increase speed, and enable analysis of limited sample amounts. For example, bottom-up proteomics sample preparation and analysis can be accelerated by digesting proteins to peptides in an on-line enzyme reactor. We here focus on low-backpressure 100 µm inner diameter (ID) × 160 mm, 180 µm ID × 110 mm or 250 µm ID × 140 mm vinyl azlactone-co-ethylene dimethacrylate [poly(VDM-co-EDMA)] monoliths as supports for immobilizing of additional molecules (i.e., proteases or drugs), as the monolith was expected to have few unspecific interactions. For on-line protein digestion, monolith supports immobilized with trypsin enzyme were found to be suited, featuring the expected characteristics of the material, i.e., low backpressure and low carry-over. Serving as a functionalized sample loop, the monolith units were very simple to connect on-line with liquid chromatography. However, for on-line target deconvolution, the monolithic support immobilized with a Wnt pathway inhibitor was associated with numerous secondary interactions when exploring the possibility of selectively trapping target proteins by drug-target interactions. Our initial observations suggest that (poly(VDM-co-EDMA)) monoliths are promising for e.g., on-line bottom-up proteomics, but not a "fit-for-all" material. We also discuss issues related to the repeatability of monolith-preparations.

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.