Trichoderma-Plant Root Colonization: Escaping Early Plant Defense Responses and Activation of the Antioxidant Machinery for Saline Stress Tolerance

Trichoderma spp. are versatile opportunistic plant symbionts which can colonize the apoplast of plant roots. Microarrays analysis of Arabidopsis thaliana roots inoculated with Trichoderma asperelloides T203, coupled with qPCR analysis of 137 stress responsive genes and transcription factors, revealed wide gene transcript reprogramming, proceeded by a transient repression of the plant immune responses supposedly to allow root colonization. Enhancement in the expression of WRKY18 and WRKY40, which stimulate JA-signaling via suppression of JAZ repressors and negatively regulate the expression of the defense genes FMO1, PAD3 and CYP71A13, was detected in Arabidopsis roots upon Trichoderma colonization. Reduced root colonization was observed in the wrky18/wrky40 double mutant line, while partial phenotypic complementation was achieved by over-expressing WRKY40 in the wrky18 wrky40 background. On the other hand increased colonization rate was found in roots of the FMO1 knockout mutant. Trichoderma spp. stimulate plant growth and resistance to a wide range of adverse environmental conditions. Arabidopsis and cucumber (Cucumis sativus L.) plants treated with Trichoderma prior to salt stress imposition show significantly improved seed germination. In addition, Trichoderma treatment affects the expression of several genes related to osmo-protection and general oxidative stress in roots of both plants. The MDAR gene coding for monodehydroascorbate reductase is significantly up-regulated and, accordingly, the pool of reduced ascorbic acid was found to be increased in Trichoderma treated plants. 1-Aminocyclopropane-1-carboxylate (ACC)-deaminase silenced Trichoderma mutants were less effective in providing tolerance to salt stress, suggesting that Trichoderma, similarly to ACC deaminase producing bacteria, can ameliorate plant growth under conditions of abiotic stress, by lowering ameliorating increases in ethylene levels as well as promoting an elevated antioxidative capacity

TargetSearch - a Bioconductor package for the efficient preprocessing of GC-MS metabolite profiling data

Background: Metabolite profiling, the simultaneous quantification of multiple metabolites in an experiment, is becoming increasingly popular, particularly with the rise of systems-level biology. The workhorse in this field is gas-chromatography hyphenated with mass spectrometry (GC-MS). The high-throughput of this technology coupled with a demand for large experiments has led to data pre-processing, i.e. the quantification of metabolites across samples, becoming a major bottleneck. Existing software has several limitations, including restricted maximum sample size, systematic errors and low flexibility. However, the biggest limitation is that the resulting data usually require extensive hand-curation, which is subjective and can typically take several days to weeks. Results: We introduce the TargetSearch package, an open source tool which is a flexible and accurate method for pre-processing even very large numbers of GC-MS samples within hours. We developed a novel strategy to iteratively correct and update retention time indices for searching and identifying metabolites. The package is written in the R programming language with computationally intensive functions written in C for speed and performance. The package includes a graphical user interface to allow easy use by those unfamiliar with R. Conclusions: TargetSearch allows fast and accurate data pre-processing for GC-MS experiments and overcomes the sample number limitations and manual curation requirements of existing software. We validate our method by carrying out an analysis against both a set of known chemical standard mixtures and of a biological experiment. In addition we demonstrate its capabilities and speed by comparing it with other GC-MS pre-processing tools. We believe this package will greatly ease current bottlenecks and facilitate the analysis of metabolic profiling data

A Metabolomic Approach to the Study of Wine Micro-Oxygenation

Wine micro-oxygenation is a globally used treatment and its effects were studied here by analysing by untargeted LC-MS the wine metabolomic fingerprint. Eight different procedural variations, marked by the addition of oxygen (four levels) and iron (two levels) were applied to Sangiovese wine, before and after malolactic fermentation

Advances in structure elucidation of small molecules using mass spectrometry

The structural elucidation of small molecules using mass spectrometry plays an important role in modern life sciences and bioanalytical approaches. This review covers different soft and hard ionization techniques and figures of merit for modern mass spectrometers, such as mass resolving power, mass accuracy, isotopic abundance accuracy, accurate mass multiple-stage MS(n) capability, as well as hybrid mass spectrometric and orthogonal chromatographic approaches. The latter part discusses mass spectral data handling strategies, which includes background and noise subtraction, adduct formation and detection, charge state determination, accurate mass measurements, elemental composition determinations, and complex data-dependent setups with ion maps and ion trees. The importance of mass spectral library search algorithms for tandem mass spectra and multiple-stage MS(n) mass spectra as well as mass spectral tree libraries that combine multiple-stage mass spectra are outlined. The successive chapter discusses mass spectral fragmentation pathways, biotransformation reactions and drug metabolism studies, the mass spectral simulation and generation of in silico mass spectra, expert systems for mass spectral interpretation, and the use of computational chemistry to explain gas-phase phenomena. A single chapter discusses data handling for hyphenated approaches including mass spectral deconvolution for clean mass spectra, cheminformatics approaches and structure retention relationships, and retention index predictions for gas and liquid chromatography. The last section reviews the current state of electronic data sharing of mass spectra and discusses the importance of software development for the advancement of structure elucidation of small molecules

Group‑wise ANOVA simultaneous component analysis for designed omics experiments

Modern omics experiments pertain not only to the measurement of many variables but also follow complex experimental designs where many factors are manipulated at the same time. This data can be conveniently analyzed using multivariate tools like ANOVA-simultaneous component analysis (ASCA) which allows interpretation of the variation induced by the different factors in a principal component analysis fashion. However, while in general only a subset of the measured variables may be related to the problem studied, all variables contribute to the final model and this may hamper interpretatio

The transcription factor PHR1 regulates lipid remodeling and triacylglycerol accumulation in Arabidopsis thaliana during phosphorus starvation.

Lipid remodeling is one of the most dramatic metabolic responses to phosphorus (P) starvation. It consists of the degradation of phospholipids to release the phosphate needed by the cell and the accumulation of glycolipids to replace phospholipids in the membranes. It is shown that PHR1, a well-described transcriptional regulator of P starvation of the MYB family, largely controls this response. Glycerolipid composition and the expression of most lipid-remodeling gene transcripts analysed were altered in the phr1 mutant under phosphate starvation in comparison to wild-type plants. In addition to these results, the lipidomic characterization of wild-type plants showed two novel features of the lipid response to P starvation for Arabidopsis. Triacylglycerol (TAG) accumulates dramatically under P starvation (by as much as ~20-fold in shoots and ~13-fold in roots), a response known to occur in green algae but hardly known in plants. Surprisingly, there was an increase in phosphatidylglycerol (PG) in P-starved roots, a response that may be adaptive as it was suppressed in the phr1 mutant