A new synthetic biology approach allows transfer of an entire metabolic pathway from a medicinal plant to a biomass crop.

Artemisinin-based therapies are the only effective treatment for malaria, the most devastating disease in human history. To meet the growing demand for artemisinin and make it accessible to the poorest, an inexpensive and rapidly scalable production platform is urgently needed. Here we have developed a new synthetic biology approach, combinatorial supertransformation of transplastomic recipient lines (COSTREL), and applied it to introduce the complete pathway for artemisinic acid, the precursor of artemisinin, into the high-biomass crop tobacco. We first introduced the core pathway of artemisinic acid biosynthesis into the chloroplast genome. The transplastomic plants were then combinatorially supertransformed with cassettes for all additional enzymes known to affect flux through the artemisinin pathway. By screening large populations of COSTREL lines, we isolated plants that produce more than 120 milligram artemisinic acid per kilogram biomass. Our work provides an efficient strategy for engineering complex biochemical pathways into plants and optimizing the metabolic output. DOI: http://dx.doi.org/10.7554/eLife.13664.00

Ranking ligand affinity for the DNA minor groove by experiment and simulation

The structural and thermodynamic basis for the strength and selectivity of the interactions of minor-groove binders (MGBs) with DNA is not fully understood. In 2003 we reported the first example of a thiazole containing MGB that bound in a phase shifted pattern that spanned 6 base-pairs rather than the usual 4 (for tricyclic distamycin-like compounds). Since then, using DNA footprinting, nuclear magnetic resonance spectroscopy, isothermal titration calorimetry and molecular dynamics, we have established that the flanking bases around the central 4 being read by the ligand have subtle effects on recognition. We have investigated the effect of these flanking sequences on binding and the reasons for the differences and established a computational method to rank ligand affinity against varying DNA sequences

Metabolic Profiling of Heathland Plants in the Diet of Sheep

Little is known about how plant biochemistry influences the grazing behaviour of animals grazing heterogeneous vegetation communities. Furthermore, most biochemical profiles of grassland species are restricted to major nutritional characteristics. Recent developments in analytical techniques have made possible the detailed analysis of minor components, which can potentially affect animal feeding preferences, performance and health. Gas chromatography/time of flight mass spectroscopy (GC/TOF-MS) coupled with automated library annotation is ideally suited to the acquisition of detailed metabolite profiles of plant extracts (Wagner et al., 2003) and can be applied to other matrices such as blood and faeces. In this study GC/TOF-MS was used to identify metabolites within heathland plants, and to investigate which of these metabolites were present and absent within plasma and faeces from sheep consuming mixtures of these plants

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

Integrated pathway modules using time-course metabolic profiles and EST data from Milnesium tardigradum

<p>Abstract</p> <p>Background</p> <p>Tardigrades are multicellular organisms, resistant to extreme environmental changes such as heat, drought, radiation and freezing. They outlast these conditions in an inactive form (tun) to escape damage to cellular structures and cell death. Tardigrades are apparently able to prevent or repair such damage and are therefore a crucial model organism for stress tolerance. Cultures of the tardigrade <it>Milnesium tardigradum</it> were dehydrated by removing the surrounding water to induce tun formation. During this process and the subsequent rehydration, metabolites were measured in a time series by GC-MS. Additionally expressed sequence tags are available, especially libraries generated from the active and inactive state. The aim of this integrated analysis is to trace changes in tardigrade metabolism and identify pathways responsible for their extreme resistance against physical stress.</p> <p>Results</p> <p>In this study we propose a novel integrative approach for the analysis of metabolic networks to identify modules of joint shifts on the transcriptomic and metabolic levels. We derive a tardigrade-specific metabolic network represented as an undirected graph with 3,658 nodes (metabolites) and 4,378 edges (reactions). Time course metabolite profiles are used to score the network nodes showing a significant change over time. The edges are scored according to information on enzymes from the EST data. Using this combined information, we identify a key subnetwork (functional module) of concerted changes in metabolic pathways, specific for de- and rehydration. The module is enriched in reactions showing significant changes in metabolite levels and enzyme abundance during the transition. It resembles the cessation of a measurable metabolism (e.g. glycolysis and amino acid anabolism) during the tun formation, the production of storage metabolites and bioprotectants, such as DNA stabilizers, and the generation of amino acids and cellular components from monosaccharides as carbon and energy source during rehydration.</p> <p>Conclusions</p> <p>The functional module identifies relationships among changed metabolites (e.g. spermidine) and reactions and provides first insights into important altered metabolic pathways. With sparse and diverse data available, the presented integrated metabolite network approach is suitable to integrate all existing data and analyse it in a combined manner.</p

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