The 3D OrbiSIMS-label-free metabolic imaging with subcellular lateral resolution and high mass-resolving power.

We report the development of a 3D OrbiSIMS instrument for label-free biomedical imaging. It combines the high spatial resolution of secondary ion mass spectrometry (SIMS; under 200 nm for inorganic species and under 2 µm for biomolecules) with the high mass-resolving power of an Orbitrap (>240,000 at m/z 200). This allows exogenous and endogenous metabolites to be visualized in 3D with subcellular resolution. We imaged the distribution of neurotransmitters-gamma-aminobutyric acid, dopamine and serotonin-with high spectroscopic confidence in the mouse hippocampus. We also putatively annotated and mapped the subcellular localization of 29 sulfoglycosphingolipids and 45 glycerophospholipids, and we confirmed lipid identities with tandem mass spectrometry. We demonstrated single-cell metabolomic profiling using rat alveolar macrophage cells incubated with different concentrations of the drug amiodarone, and we observed that the upregulation of phospholipid species and cholesterol is correlated with the accumulation of amiodarone.

Intracellular Drug Uptake-A Comparison of Single Cell Measurements Using ToF-SIMS Imaging and Quantification from Cell Populations with LC/MS/MS.

ToF-SIMS is a label-free imaging method that has been shown to enable imaging of amiodarone in single rat macrophage (NR8383) cells. In this study, we show that the method extends to three other cell lines relevant to drug discovery: human embryonic kidney (HEK293), cervical cancer (HeLa), and liver cancer (HepG2). There is significant interest in the variation of drug uptake at the single cell level, and we use ToF-SIMS to show that there is great diversity between individual cells and when comparing each of the cell types. These single cell measurements are compared to quantitative measurements of cell-associated amiodarone for the population using LC/MS/MS and cell counting with flow cytometry. NR8383 and HepG2 cells uptake the greatest amount of amiodarone with an average of 2.38 and 2.60 pg per cell, respectively, and HeLa and Hek 293 have a significantly lower amount of amiodarone at 0.43 and 0.36 pg per cell, respectively. The amount of cell-associated drug for the ensemble population measurement (LC/MS/MS) is compared with the ToF-SIMS single cell data: a similar amount of drug was detected per cell for the NR8383, and HepG2 cells at a greater level than that for the HEK293 cells. However, the two techniques did not agree for the HeLa cells, and we postulate potential reasons for this.

High-resolution sub-cellular imaging by correlative NanoSIMS and electron microscopy of amiodarone internalisation by lung macrophages as evidence for drug-induced phospholipidosis.

Correlative NanoSIMS and EM imaging of amiodarone-treated macrophages shows the internalisation of the drug at a sub-cellular level and reveals its accumulation within the lysosomes, providing direct evidence for amiodarone-induced phospholipidosis. Chemical fixation using tannic acid effectively seals cellular membranes aiding intracellular retention of diffusible drugs.

Semiempirical Rules To Determine Drug Sensitivity and Ionization Efficiency in Secondary Ion Mass Spectrometry Using a Model Tissue Sample.

There is an increasing need in the pharmaceutical industry to reduce drug failure at late stage and thus reduce the cost of developing a new medicine. Since most drug targets are intracellular, this requires a better understanding of the drug disposition within a cell. Secondary ion mass spectrometry has been identified as a potentially important technique to do this, as it is label-free and allows imaging in 3D with subcellular resolution and recent studies have shown promise for amiodarone. An important analytical parameter is sensitivity, and we measure this in a bovine liver homogenate reference sample for 20 drugs representing important class types relevant to the pharmaceutical industry. We also measure the sensitivity for pure drug and show, for the first time, that the secondary ion mass spectrometry (SIMS) positive ionization efficiency for small molecules is a simple power-law relationship to the log P value. This discovery will be important for advancing the understanding of the SIMS ionization process in small molecules that has, until now, been elusive. This simple relationship is found to hold true for drug doped in the bovine liver homogenate reference sample, except for fluticasone, nicardipine, and sorafenib which suffer from severe matrix suppression. This relationship provides a simple semiempirical method to determine drug sensitivity for positive secondary ions. Furthermore, we show, on chosen models, how the use of different solvents during sample preparation can affect the ionization of analytes.

Single-Cell Analysis: Visualizing Pharmaceutical and Metabolite Uptake in Cells with Label-Free 3D Mass Spectrometry Imaging.

Detecting metabolites and parent compound within a cell type is now a priority for pharmaceutical development. In this context, three-dimensional secondary ion mass spectrometry (SIMS) imaging was used to investigate the cellular uptake of the antiarrhythmic agent amiodarone, a phospholipidosis-inducing pharmaceutical compound. The high lateral resolution and 3D imaging capabilities of SIMS combined with the multiplex capabilities of ToF mass spectrometric detection allows for the visualization of pharmaceutical compound and metabolites in single cells. The intact, unlabeled drug compound was successfully detected at therapeutic dosages in macrophages (cell line: NR8383). Chemical information from endogenous biomolecules was used to correlate drug distributions with morphological features. From this spatial analysis, amiodarone was detected throughout the cell, with the majority of the compound found in the membrane and subsurface regions and absent in the nuclear regions. Similar results were obtained when the macrophages were doped with amiodarone metabolite, desethylamiodarone. The fwhm lateral resolution measured across an intracellular interface in high lateral resolution ion images was approximately 550 nm. Overall, this approach provides the basis for studying cellular uptake of pharmaceutical compounds and their metabolites on the single cell level.

Lost in Translation (LiT): IUPHAR Review 6.

Translational medicine is a roller coaster with occasional brilliant successes and a large majority of failures. Lost in Translation 1 ('LiT1'), beginning in the 1950s, was a golden era built upon earlier advances in experimental physiology, biochemistry and pharmacology, with a dash of serendipity, that led to the discovery of many new drugs for serious illnesses. LiT2 saw the large-scale industrialization of drug discovery using high-throughput screens and assays based on affinity for the target molecule. The links between drug development and university sciences and medicine weakened, but there were still some brilliant successes. In LiT3, the coverage of translational medicine expanded from molecular biology to drug budgets, with much greater emphasis on safety and official regulation. Compared with R&D expenditure, the number of breakthrough discoveries in LiT3 was disappointing, but monoclonal antibodies for immunity and inflammation brought in a new golden era and kinase inhibitors such as imatinib were breakthroughs in cancer. The pharmaceutical industry is trying to revive the LiT1 approach by using phenotypic assays and closer links with academia. LiT4 faces a data explosion generated by the genome project, GWAS, ENCODE and the 'omics' that is in danger of leaving LiT4 in a computerized cloud. Industrial laboratories are filled with masses of automated machinery while the scientists sit in a separate room viewing the results on their computers. Big Data will need Big Thinking in LiT4 but with so many unmet medical needs and so many new opportunities being revealed there are high hopes that the roller coaster will ride high again.

Characterization of the effect of chronic administration of a calcium-sensing receptor antagonist, ronacaleret, on renal calcium excretion and serum calcium in postmenopausal women.

Ronacaleret is an orally-active calcium-sensing receptor (CaSR) antagonist that has the potential for therapeutic utility in the stimulation of PTH release, notably as a bone anabolic agent comparable to recombinant human PTH(1-34) (rhPTH(1-34)). A recent study has shown that, despite the ability to increase circulating PTH levels in postmenopausal women in a dose-dependent manner, minimal effects of ronacaleret on bone mineral density have been observed. Therefore, the purpose of this study was to characterize the PTH profile as well as calcium metabolism parameters as a marker of PTH biological activity following the administration of ronacaleret or rhPTH(1-34). Administration of ronacaleret led to lower peak levels of PTH than were observed with rhPTH(1-34), however, greater total PTH exposure was observed. Further, chronic administration of either agent was associated with increases in urinary calcium excretion and serum calcium levels, with the magnitude of the changes following ronacaleret significantly greater than that for rhPTH(1-34). The greater magnitude of effects observed with ronacaleret is likely due to the greater total PTH exposure, and is potentially reflective of a state comparable to mild hyperparathyroidism. It is not clear whether the administration of all calcilytics would lead to a similar result, or is due to characteristics specific to ronacaleret.

IUPHAR-DB: the IUPHAR database of G protein-coupled receptors and ion channels.

The IUPHAR database (IUPHAR-DB) integrates peer-reviewed pharmacological, chemical, genetic, functional and anatomical information on the 354 nonsensory G protein-coupled receptors (GPCRs), 71 ligand-gated ion channel subunits and 141 voltage-gated-like ion channel subunits encoded by the human, rat and mouse genomes. These genes represent the targets of approximately one-third of currently approved drugs and are a major focus of drug discovery and development programs in the pharmaceutical industry. IUPHAR-DB provides a comprehensive description of the genes and their functions, with information on protein structure and interactions, ligands, expression patterns, signaling mechanisms, functional assays and biologically important receptor variants (e.g. single nucleotide polymorphisms and splice variants). In addition, the phenotypes resulting from altered gene expression (e.g. in genetically altered animals or in human genetic disorders) are described. The content of the database is peer reviewed by members of the International Union of Basic and Clinical Pharmacology Committee on Receptor Nomenclature and Drug Classification (NC-IUPHAR); the data are provided through manual curation of the primary literature by a network of over 60 subcommittees of NC-IUPHAR. Links to other bioinformatics resources, such as NCBI, Uniprot, HGNC and the rat and mouse genome databases are provided. IUPHAR-DB is freely available at http://www.iuphar-db.org.