Fast, sensitive approach can be used as primary screen on drug-treated primary cells.
Scientists report on the development of a nuclear magnetic resonance (NMR)-based method for screening the metabolomic response of drug-treated mammalian cells to drug therapy. The Sanford-Burnham Medical Research Institute, and Rady Children’s Hospital investigators, say the highly sensitive, fast, and simple method is carried out in 96-well format, and could have particular utility as a method for high-throughput primary screens. The preparation technique takes just five minutes to metabolically inactivate and lyse hundreds of drug-treated samples, and a metabolomic screening of around 100 samples can be carried out in 24 hours.
Giovanni Paternostro, M.D., and colleagues describe their approach, analyze the results of validation studies on drug-treated cancer cell lines, and evaluate the technique for screening a kinase inhibitor library. Their work is described in Nature Communications in a paper titled “Metabolomic high-content nuclear magnetic resonance-based drug screening of a kinase inhibitor library.”
High-throughput screening (HTS) is widely used as a tool in drug discovery, but most screens monitor a single variable, which is often related to activity on a single target, the researchers explain. Although high-content screening (HCS) approaches that provide multivariate readouts are gaining ground, these techniques generally rely on automated digital microscopy.
The technique developed by the Sanford-Burnham researchers involves seeding cells into a 96-well plate and treating them with several drugs. The cells’ metabolism is then quenched using sodium dodecyl sulphate (SDS), and the cells lysed using ultrasonication, in an overall process that takes just five minutes. The entire content of the well, including endo- and exo-metabolome, is then transferred into an NMR tube for analysis.
The team needed to address the relative contribution of the intracellular metabolome to the NMR spectrum acquired on the well content, including both medium and the lysed cell metabolomes. To answer this they generated NMR spectra on the entire content of the well (i.e., both endo- and exo-metabolomes), and also on the exometabolome, the endometabolome, and the medium. They found that major NMR signals arose from the extracellular metabolites, but several signals arising from the intracellular metabolites were also detected, for example glutamate, choline, and phosphocholine. Importantly, they found that spectra acquired on samples containing both endo- and extracellular metabolomes included signals resulting exclusively from the endometabolome—such as phosphocholine and glycerophosphocholine—which didn’t overlap with other extracellular resonances.
The researchers evaluated the sensitivity of the approach for monitoring metabolic changes induced by 24 hours of drug treatment, on both suspension (CCRF-CEM human leukemia cells) and adherent mammalian carcinoma cell lines (human SKOV-3 ovarian cancer cells). The cell lines were treated using either dexamethasone (Dex), rapamycin (Rap) dichloroacetate (DCA), vincristine (Vin), and different doses of L-asparaginase. The resulting spectra, generated using three different 1H NMR pulse sequences, showed that, as expected, the response to drug treatment by the more resistant SKOV-3 cells was far less pronounced compared with the CCRF-CEM cells. Encouragingly, the NMR screening approach could also be applied to detecting metabolic changes in response to forms of intervention, such as the transfection of HeLa cells the microRNAs mir-121 and mir-16. These results indicated that mir-16 induced a greater degree of metabolomic change than mir-121.
Because the developed technique requires just a small amount of cells, the investigators suggest in might have utility in studying drug response directly in primary cells, and so avoid phenotypic changes that can be induced by growth in culture. They evaluated metabolomic changes in cells isolated from bone marrow specimens of an untreated AML patient, in response to treatment with Rap and L-asparaginase, at different doses. In order to specifically highlight metabolic changes in the cells themselves, the NRM spectra acquired on unconditioned medium were compared to those acquired on AML primary cells with and without drug administraton. The resulting spectra clearly showed distinct changes in the metabolome of the primary cells as a result of drug treatment. Further analyses indicated these changes were more pronounced in response to L-asparaginase than for Rap therapy.
The team then moved on to use the approach for carrying out screening of metabolomic response to a kinase inhibitor (KI) library. Multiple rounds of screening on KIs with well-characterized and less well-characterized effects on the metabolome confirmed the utility of the technique for identifying metabolic alterations resulting from inhibitor treatment. More specifically, four hits were validated from their action on the well-characterized lactate to pyruvate ratio parameter.
“We believe that this NMR-based assay might find an immediate relevant application for screening a large number of individual or combinatorial drug interventions, reducing the number of possible drugs to be studied in more detail,” the authors state. “In addition, it might find an immediate relevant application into clinical studies.”
They admit that the main drawback of NMR is the relatively limited number of compounds that can be detected. However, they stress, “although not comprehensive of all metabolites, the wealth of information obtained from the multivariate metabolic readout is of great advantage for drug screening purposes.” The method could therefore represent a valuable high-throughput primary screen, which could then be followed by secondary assays to analyze the exo- and endo-metabolomes of selected hits using combinations of different anaytical platforms.
“There are many other possible applications of this method, for example lactate production and substrate utilization in cancer versus noncancer cells, or gluconeogenesis from different substrates in hepatocytes, relevant to diabetes. Importantly, because the measurements are performed within a global metabolic profile, they can also provide a series of compounds with partially different mechanisms of actions, which can be explored for potential synergies.”