Stable isotope resolved metabolomics classification of prostate cancer cells using hyperpolarized NMR data.

Metabolic fingerprinting is a strong tool for characterization of biological phenotypes. Classification with machine learning is a critical component in the discrimination of molecular determinants. Cellular activity can be traced using stable isotope labelling of metabolites from which information on cellular pathways may be obtained. Nuclear magnetic resonance (NMR) spectroscopy is, due to its ability to trace labelling in specific atom positions, a method of choice for such metabolic activity measurements. In this study, we used hyperpolarization in the form of dissolution Dynamic Nuclear Polarization (dDNP) NMR to measure signal enhanced isotope labelled metabolites reporting on pathway activity from four different prostate cancer cell lines. The spectra have a high signal-to-noise, with less than 30 signals reporting on 10 metabolic reactions. This allows easy extraction and straightforward interpretation of spectral data. Four metabolite signals selected using a Random Forest algorithm allowed a classification with Support Vector Machines between aggressive and indolent cancer cells with 96.9% accuracy, -corresponding to 31 out of 32 samples. This demonstrates that the information contained in the few features measured with dDNP NMR, is sufficient and robust for performing binary classification based on the metabolic activity of cultured prostate cancer cells.

Stable Isotope-Resolved Analysis with Quantitative Dissolution Dynamic Nuclear Polarization.

Metabolite profiles and their isotopomer distributions can be studied noninvasively in complex mixtures with NMR. The advent of dissolution Dynamic Nuclear Polarization (dDNP) and isotope enrichment add sensitivity and resolution to such metabolic studies. Metabolic pathways and networks can be mapped and quantified if protocols that control and exploit the ex situ signal enhancement are created. We present a sample preparation method, including cell incubation, extraction and signal enhancement, to obtain reproducible and quantitative dDNP (qdDNP) NMR-based stable isotope-resolved analysis. We further illustrate how qdDNP was applied to gain metabolic insights into the phenotype of aggressive cancer cells.

A new sulfated alpha-ionone glycoside from Sonchus erzincanicus Matthews.

Sonchus erzincanicus (Asteraceae) is an endemic species in Turkey, where six Sonchus species grow. In this study, a phytochemical study was performed on the aerial parts of the plant. The study describes the isolation and structure elucidation of five flavonoids and two a-ionone glycosides from S. erzincanicus. The compounds were isolated using several and repeated chromatographic techniques from ethyl acetate and aqueous phases that were partitioned from a methanol extract obtained from the plant. 5,7,3',4'-Tetrahydroxy-3-methoxyflavone (1) and quercetin 3-O-beta-D-glucoside (2) were isolated from the ethyl acetate phase, while corchoionoside C 6'-O-sulfate (3), corchoionoside C (4), luteolin 7-O-glucuronide (5) and luteolin 7-O-beta-D-glucoside (6), apigenin 7-O-glucuronide (7) were isolated from the aqueous phase. Corchoionoside C 6'-O-sulfate (3), isolated for the first time from a natural source, was a new compound. The structures of the compounds were elucidated by means of 1H-NMR, 13C-NMR, 2D-NMR (COSY, HMQC, HMBC) and ESI-MS.

An investigation on the anticandidal activity of some traditional medicinal plants in Turkey.

Methanol and chloroform extracts obtained from eight plant species belonging to six families, which were selected depending on their use in Turkish folk medicine, including Mentha longifolia L. (Labiatae), Mentha piperita L. Hudson (Labiatae), Prongos ferulaceae (Umbelliferae), Galium verum L. (Rubiaceae), Salvia limbata C. A Meyer (Labiatae), Artemisia austriaca Jacq. (Artemiceae), Plantago lanceolata L. (Plantaginaceae) and Urtica dioica L. (Urticaceae) were evaluated for their in vitro anticandidal activity. The anticandidal activity of extracts against 99 human pathogenic clinical isolates belonging to 35 Candida albicans, 33 Candida tropicalis and 31 Candida glabrata and standard strains of Candida spp. (C. albicans ATCC 10231, C. glabrata ATCC 80030 and C. tropicalis ATCC 22019) were tested by disc diffusion method and the active extracts were assayed for the minimal inhibitory concentration (MIC). Chloroform extracts of plants have no inhibitory effect against both clinical and standard strains of Candida spp., whereas methanol extracts exhibited good activity. Among the plants tested, M. piperita showed the highest anticandidal activity with 12.3 mm inhibition zone and 1.25 mg ml(-1) MIC value against C. albicans, M. longifolia, P. lanceolata and A. austriaca also displayed activity against C. albicans and C. tropicalis.