Rapid transcriptional and metabolic regulation of the deacclimation process in cold acclimated Arabidopsis thaliana

Background: During low temperature exposure, temperate plant species increase their freezing tolerance in a process termed cold acclimation. This is accompanied by dampened oscillations of circadian clock genes and disrupted oscillations of output genes and metabolites. During deacclimation in response to warm temperatures, cold acclimated plants lose freezing tolerance and resume growth and development. While considerable effort has been directed toward understanding the molecular and metabolic basis of cold acclimation, much less information is available about the regulation of deacclimation.Results: We report metabolic (gas chromatography-mass spectrometry) and transcriptional (microarrays, quantitative RT-PCR) responses underlying deacclimation during the first 24 h after a shift of Arabidopsis thaliana (Columbia-0) plants cold acclimated at 4 °C back to warm temperature (20 °C). The data reveal a faster response of the transcriptome than of the metabolome and provide evidence for tightly regulated temporal responses at both levels. Metabolically, deacclimation is associated with decreasing contents of sugars, amino acids, glycolytic and TCA cycle intermediates, indicating an increased need for carbon sources and respiratory energy production for the activation of growth. The early phase of deacclimation also involves extensive down-regulation of protein synthesis and changes in the metabolism of lipids and cell wall components. Hormonal regulation appears particularly important during deacclimation, with extensive changes in the expression of genes related to auxin, gibberellin, brassinosteroid, jasmonate and ethylene metabolism. Members of several transcription factor families that control fundamental aspects of morphogenesis and development are significantly regulated during deacclimation, emphasizing that loss of freezing tolerance and growth resumption are transcriptionally highly interrelated processes. Expression patterns of some clock oscillator components resembled those under warm conditions, indicating at least partial re-activation of the circadian clock during deacclimation.Conclusions: This study provides the first combined metabolomic and transcriptomic analysis of the regulation of deacclimation in cold acclimated plants. The data indicate cascades of rapidly regulated genes and metabolites that underlie the developmental switch resulting in reduced freezing tolerance and the resumption of growth. They constitute a large-scale dataset of genes, metabolites and pathways that are crucial during the initial phase of deacclimation. The data will be an important reference for further analyses of this and other important but under-researched stress deacclimation processes

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

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

Autoinducers act as biological timers in Vibrio harveyi

Quorum sensing regulates cell density-dependent phenotypes and involves the synthesis, excretion and detection of so-called autoinducers. Vibrio harveyi strain ATCC BAA-1116 (recently reclassified as Vibrio campbellii), one of the best-characterized model organisms for the study of quorum sensing, produces and responds to three autoinducers. HAI-1, AI-2 and CAI-1 are recognized by different receptors, but all information is channeled into the same signaling cascade, which controls a specific set of genes. Here we examine temporal variations of availability and concentration of the three autoinducers in V. harveyi, and monitor the phenotypes they regulate, from the early exponential to the stationary growth phase in liquid culture. Specifically, the exponential growth phase is characterized by an increase in AI-2 and the induction of bioluminescence, while HAI-1 and CAI-1 are undetectable prior to the late exponential growth phase. CAI-1 activity reaches its maximum upon entry into stationary phase, while molar concentrations of AI-2 and HAI-1 become approximately equal. Similarly, autoinducer-dependent exoproteolytic activity increases at the transition into stationary phase. These findings are reflected in temporal alterations in expression of the luxR gene that encodes the master regulator LuxR, and of four autoinducer-regulated genes during growth. Moreover, in vitro phosphorylation assays reveal a tight correlation between the HAI-1/AI-2 ratio as input and levels of receptor-mediated phosphorylation of LuxU as output. Our study supports a model in which the combinations of autoinducers available, rather than cell density per se, determine the timing of various processes in V. harveyi populations