Metabolome Analysis of the Interaction Between Perennial Ryegrass (\u3cem\u3eLolium Perenne\u3c/em\u3e) and the Fungal Endophyte \u3cem\u3eNeotyphodium Lolii\u3c/em\u3e

Perennial ryegrass (Lolium perenne L.) and tall fescue (Festuca arundinacea Schreb.) frequently contain endophytic fungi (Neotyphodium lolii in perennial ryegrass and N. coenophialum in tall fescue). The presence of the endophyte has been shown to improve seedling vigour, persistence and drought tolerance in marginal environments as well as provide protection against some insect pests. Endophyte-infected grasses also produce a wide range of metabolites, including ergopeptine alkaloids, indole-isoprenoid lolitrems, pyrrolizidine alkaloids, and pyrrolopyrazine alkaloids. In contrast to information on alkaloids and animal toxicosis, the beneficial physiological aspects of the endophyte/grass interactions have not been well characterised. The physiological mechanisms which lead to increased plant vigour and enhanced tolerance to abiotic stresses unrelated to the reduction in pest damage to endophyte-infected grasses are unknown. Recent technological advances in metabolomics enable dynamic changes in the metabolome of an organism under varying experimental conditions to be studied. This provides opportunities for the investigation and validation of each and every detected metabolite, investigation of known metabolic pathways through searching of databases of known metabolites, molecular formula determination of unknown metabolites and creation of pathways from novel metabolites

Decision tree supported substructure prediction of metabolites from GC-MS profiles

Gas chromatography coupled to mass spectrometry (GC-MS) is one of the most widespread routine technologies applied to the large scale screening and discovery of novel metabolic biomarkers. However, currently the majority of mass spectral tags (MSTs) remains unidentified due to the lack of authenticated pure reference substances required for compound identification by GC-MS. Here, we accessed the information on reference compounds stored in the Golm Metabolome Database (GMD) to apply supervised machine learning approaches to the classification and identification of unidentified MSTs without relying on library searches. Non-annotated MSTs with mass spectral and retention index (RI) information together with data of already identified metabolites and reference substances have been archived in the GMD. Structural feature extraction was applied to sub-divide the metabolite space contained in the GMD and to define the prediction target classes. Decision tree (DT)-based prediction of the most frequent substructures based on mass spectral features and RI information is demonstrated to result in highly sensitive and specific detections of sub-structures contained in the compounds. The underlying set of DTs can be inspected by the user and are made available for batch processing via SOAP (Simple Object Access Protocol)-based web services. The GMD mass spectral library with the integrated DTs is freely accessible for non-commercial use at http://gmd.mpimp-golm.mpg.de/. All matching and structure search functionalities are available as SOAP-based web services. A XML + HTTP interface, which follows Representational State Transfer (REST) principles, facilitates read-only access to data base entities

Expanding the Repertoire of Natural Product-Inspired Ring Pairs for Molecular Recognition of DNA

A furan amino acid, inspired by the recently discovered proximicin natural products, was incorporated into the scaffold of a DNA-binding hairpin polyamide. While unpaired oligomers of 2,4-disubstituted furan amino acids show poor DNA-binding activity, furan (Fn) carboxamides paired with N-methylpyrrole (Py) and N-methylimidazole (Im) rings demonstrate excellent stabilization of duplex DNA as well as discrimination of noncognate sequences, consistent with function as a Py mimic according to the Py/Im polyamide pairing rules

Treatment response evaluation with (18)F-FDG PET/CT and (18)F-NaF PET/CT in multiple myeloma patients undergoing high-dose chemotherapy and autologous stem cell transplantation.

AIM The aim of this study was to assess the combined use of the radiotracers (18)F-FDG and (18)F-NaF in treatment response evaluation of a group of multiple myeloma (MM) patients undergoing high-dose chemotherapy (HDT) followed by autologous stem cell transplantation (ASCT) by means of static (whole-body) and dynamic PET/CT (dPET/CT). PATIENTS AND METHODS Thirty-four patients with primary, previously untreated MM scheduled for treatment with HDT followed by ASCT were enrolled in the study. All patients underwent PET/CT scanning with (18)F-FDG and (18)F-NaF before and after therapy. Treatment response by means of PET/CT was assessed according to the European Organization for Research and Treatment of Cancer (EORTC) 1999 criteria. The evaluation of dPET/CT studies was based on qualitative evaluation, semi-quantitative (SUV) calculation, and quantitative analysis based on two-tissue compartment modelling and a non-compartmental approach leading to the extraction of fractal dimension (FD). RESULTS An analysis was possible in 29 patients: three with clinical complete response (CR) and 26 with non-CR (13 patients near complete response-nCR, four patients very good partial response-VGPR, nine patients partial response-PR). After treatment, (18)F-FDG PET/CT was negative in 14/29 patients and positive in 15/29 patients, showing a sensitivity of 57.5 % and a specificity of 100 %. According to the EORTC 1999 criteria, (18)F-FDG PET/CT-based treatment response revealed CR in 14 patients ((18)F-FDG PET/CT CR), PR in 11 patients ((18)F-FDG PET/CT PR) and progressive disease in four patients ((18)F-FDG PET/CT PD). In terms of (18)F-NaF PET/CT, 4/29 patients (13.8 %) had a negative baseline scan, thus failed to depict MM. Regarding the patients for which a direct lesion-to-lesion comparison was feasible, (18)F-NaF PET/CT depicted 56 of the 129 (18)F-FDG positive lesions (43 %). Follow-up (18)F-NaF PET/CT showed persistence of 81.5 % of the baseline (18)F-NaF positive MM lesions after treatment, despite the fact that 64.7 % of them had turned to (18)F-FDG negative. Treatment response according to (18)F-NaF PET/CT revealed CR in one patient ((18)F-NaF PET/CT CR), PR in five patients ((18)F-NaF PET/CT PR), SD in 12 patients ((18)F-NaF PET/CT SD), and PD in seven patients ((18)F-NaF PET/CT PD). Dynamic (18)F-FDG and (18)F-NaF PET/CT studies showed that SUVaverage, SUVmax, as well as the kinetic parameters K1, influx and FD from reference bone marrow and skeleton responded to therapy with a significant decrease (p < 0.001). CONCLUSION F-FDG PET/CT demonstrated a sensitivity of 57.7 % and a specificity of 100 % in treatment response evaluation of MM. Despite its limited sensitivity, the performance of (18)F-FDG PET/CT was satisfactory, given that 6/9 false negative patients in follow-up scans (66.7 %) were clinically characterized as nCR, a disease stage with very low tumor mass. On the other hand, (18)F-NaF PET/CT does not seem to add significantly to (18)F-FDG PET/CT in treatment response evaluation of MM patients undergoing HDT and ASCT, at least shortly after therapy

Dissecting Rice Polyamine Metabolism under Controlled Long-Term Drought Stress

A selection of 21 rice cultivars (Oryza sativa L. ssp. indica and japonica) was characterized under moderate long-term drought stress by comprehensive physiological analyses and determination of the contents of polyamines and selected metabolites directly related to polyamine metabolism. To investigate the potential regulation of polyamine biosynthesis at the transcriptional level, the expression of 21 genes encoding enzymes involved in these pathways were analyzed by qRT-PCR. Analysis of the genomic loci revealed that 11 of these genes were located in drought-related QTL regions, in agreement with a proposed role of polyamine metabolism in rice drought tolerance. The cultivars differed widely in their drought tolerance and parameters such as biomass and photosynthetic quantum yield were significantly affected by drought treatment. Under optimal irrigation free putrescine was the predominant polyamine followed by free spermidine and spermine. When exposed to drought putrescine levels decreased markedly and spermine became predominant in all cultivars. There were no correlations between polyamine contents and drought tolerance. GC-MS analysis revealed drought-induced changes of the levels of ornithine/arginine (substrate), substrates of polyamine synthesis, proline, product of a competing pathway and GABA, a potential degradation product. Gene expression analysis indicated that ADC-dependent polyamine biosynthesis responded much more strongly to drought than the ODC-dependent pathway. Nevertheless the fold change in transcript abundance of ODC1 under drought stress was linearly correlated with the drought tolerance of the cultivars. Combining metabolite and gene expression data, we propose a model of the coordinate adjustment of polyamine biosynthesis for the accumulation of spermine under drought conditions

Induced, Imprinted, and Primed Responses to Changing Environments: Does Metabolism Store and Process Information?

Metabolism is the system layer that determines growth by the rate of matter uptake and conversion into biomass. The scaffold of enzymatic reaction rates drives the metabolic network in a given physico-chemical environment. In response to the diverse environmental stresses, plants have evolved the capability of integrating macro- and micro-environmental events to be prepared, i.e., to be primed for upcoming environmental challenges. The hierarchical view on stress signaling, where metabolites are seen as final downstream products, has recently been complemented by findings that metabolites themselves function as stress signals. We present a systematic concept of metabolic responses that are induced by environmental stresses and persist in the plant system. Such metabolic imprints may prime metabolic responses of plants for subsequent environmental stresses. We describe response types with examples of biotic and abiotic environmental stresses and suggest that plants use metabolic imprints, the metabolic changes that last beyond recovery from stress events, and priming, the imprints that function to prepare for upcoming stresses, to integrate diverse environmental stress histories. As a consequence, even genetically identical plants should be studied and understood as phenotypically plastic organisms that continuously adjust their metabolic state in response to their individually experienced local environment. To explore the occurrence and to unravel functions of metabolic imprints, we encourage researchers to extend stress studies by including detailed metabolic and stress response monitoring into extended recovery phases