Álvaro Cuadros-Inostroza

Metabolomic and transcriptomic stress response of Escherichia coli.

Environmental fluctuations lead to a rapid adjustment of the physiology of Escherichia coli, necessitating changes on every level of the underlying cellular and molecular network. Thus far, the majority of global analyses of E. coli stress responses have been limited to just one level, gene expression. Here, we incorporate the metabolite composition together with gene expression data to provide a more comprehensive insight on system level stress adjustments by describing detailed time‐resolved E. coli response to five different perturbations (cold, heat, oxidative stress, lactose diauxie, and stationary phase). The metabolite response is more specific as compared with the general response observed on the transcript level and is reflected by much higher specificity during the early stress adaptation phase and when comparing the stationary phase response to other perturbations. Despite these differences, the response on both levels still follows the same dynamics and general strategy of energy conservation as reflected by rapid decrease of central carbon metabolism intermediates coinciding with downregulation of genes related to cell growth. Application of co‐clustering and canonical correlation analysis on combined metabolite and transcript data identified a number of significant condition‐dependent associations between metabolites and transcripts. The results confirm and extend existing models about co‐regulation between gene expression and metabolites demonstrating the power of integrated systems oriented analysis.

High-density kinetic analysis of the metabolomic and transcriptomic response of Arabidopsis to eight environmental conditions

The time-resolved response of Arabidopsis thaliana towards changing light and/or temperature at the transcriptome and metabolome level is presented. Plants grown at 21°C with a light intensity of 150 μE m⁻² sec⁻¹ were either kept at this condition or transferred into seven different environments (4°C, darkness; 21°C, darkness; 32°C, darkness; 4°C, 85 μE m⁻² sec⁻¹; 21 °C, 75 μE m⁻² sec⁻¹; 21°C, 300 μE m⁻² sec⁻¹ ; 32°C, 150 μE m⁻² sec⁻¹). Samples were taken before (0 min) and at 22 time points after transfer resulting in (8×) 22 time points covering both a linear and a logarithmic time series totaling 177 states. Hierarchical cluster analysis shows that individual conditions (defined by temperature and light) diverge into distinct trajectories at condition-dependent times and that the metabolome follows different kinetics from the transcriptome. The metabolic responses are initially relatively faster when compared with the transcriptional responses. Gene Ontology over-representation analysis identifies a common response for all changed conditions at the transcriptome level during the early response phase (5-60 min). Metabolic networks reconstructed via metabolite-metabolite correlations reveal extensive environment-specific rewiring. Detailed analysis identifies conditional connections between amino acids and intermediates of the tricarboxylic acid cycle. Parallel analysis of transcriptional changes strongly support a model where in the absence of photosynthesis at normal/high temperatures protein degradation occurs rapidly and subsequent amino acid catabolism serves as the main cellular energy supply. These results thus demonstrate the engagement of the electron transfer flavoprotein system under short-term environmental perturbations.

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

BackgroundMetabolite 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.ResultsWe 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.ConclusionsTargetSearch 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.

Discrimination of wine attributes by metabolome analysis.

The chemical composition of any wine sample contains numerous small molecules largely derived from three different sources: the grape berry, the yeast strain used for fermentation, and the containers used for wine making and storage. The combined sum of these small molecules present in the wine, therefore, might account for all wine specific features such as cultivar, vintage, origin, and quality. Still, most wine authentication procedures rely either on subjective human measures or if they are based on measurable features, they include a limited number of compounds. In this study, which is based on an untargeted UPLC-FT-ICR-MS-based approach, we provide data, demonstrating that unbiased and objective analytical chemistry in combination with multivariate statistical methods allows to reproducible classify/distinguish wine attributes like variety, origin, vintage, and quality.

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

Highlight This study reveals that the transcription factor PHR1 controls phospholipid/glycolipid substitution during P starvation, and that Arabidopsis accumulates triacylglycerol during P starvation. In roots this phenotype is also under control of PHR1.

Linking gene expression and membrane lipid composition of Arabidopsis.

This work examines the connection between changes in gene expression and changes in membrane lipid composition in Arabidopsis exposed to different light and temperature conditions. Three transcriptional programs identified are shown to be coordinated with changes in specific membrane lipids, further supported by lipidomic analysis of selected knockout lines. Glycerolipid metabolism of plants responds dynamically to changes in light intensity and temperature, leading to the modification of membrane lipid composition to ensure optimal biochemical and physical properties in the new environment. Although multiple posttranscriptional regulatory mechanisms have been reported to be involved in the process, the contribution of transcriptional regulation remains largely unknown. Here, we present an integrative analysis of transcriptomic and lipidomic data, revealing large-scale coordination between gene expression and changes in glycerolipid levels during the Arabidopsis thaliana response to light and temperature stimuli. Using a multivariate regression technique called O2PLS, we show that the gene expression response is strictly coordinated at the biochemical pathway level and occurs in parallel with changes of specific glycerolipid pools. Five interesting candidate genes were chosen for further analysis from a larger set of candidates identified based on their close association with various groups of glycerolipids. Lipidomic analysis of knockout mutant lines of these five genes showed a significant relationship between the coordination of transcripts and glycerolipid levels in a changing environment and the effects of single gene perturbations.

GC-MS metabolic profiling of Cabernet Sauvignon and Merlot cultivars during grapevine berry development and network analysis reveals a stage- and cultivar-dependent connectivity of primary metabolites

Information about the total chemical composition of primary metabolites during grape berry development is scarce, as are comparative studies trying to understand to what extent metabolite modifications differ between cultivars during ripening. Thus, correlating the metabolic profiles with the changes occurring in berry development and ripening processes is essential to progress in their comprehension as well in the development of new approaches to improve fruit attributes. Here, the developmental metabolic profiling analysis across six stages from flowering to fully mature berries of two cultivars, Cabernet Sauvignon and Merlot, is reported at metabolite level. Based on a gas chromatography–mass spectrometry untargeted approach, 115 metabolites were identified and relative quantified in both cultivars. Sugars and amino acids levels show an opposite behaviour in both cultivars undergoing a highly coordinated shift of metabolite associated to primary metabolism during the stages involved in growth, development and ripening of berries. The changes are characteristic for each stage, the most pronounced ones occuring at fruit setting and pre-Veraison. They are associated to a reduction of the levels of metabolites present in the earlier corresponding stage, revealing a required catabolic activity of primary metabolites for grape berry developmental process. Network analysis revealed that the network connectivity of primary metabolites is stage- and cultivar-dependent, suggesting differences in metabolism regulation between both cultivars as the maturity process progresses. Furthermore, network analysis may represent an appropriate method to display the association between primary metabolites during berry developmental processes among different grapevine cultivars and for identifying potential biologically relevant metabolites.

Involvement of the Hexose Transporter Gene LeHT1 and of Sugars in Resistance of Tomato to Tomato Yellow Leaf Curl Virus

Supplementary DataxDownload (.02 MB ) Supplementary DataSupplement Table 2List of ITAG2.3 ID and Mapman pathway of differentially expressed genes from the comparison of non-infected S vs. R plants (S0, R0)xDownload (.18 MB ) Supplement Table 2List of ITAG2.3 ID and Mapman pathway of differentially expressed genes from the comparison of non-infected S vs. R plants (S0, R0)Supplement Table 3List of ITAG2.3 ID and Mapman pathway of differentially expressed genes from the comparison of infected S and R plants (Si, Ri).xDownload (.14 MB ) Supplement Table 3List of ITAG2.3 ID and Mapman pathway of differentially expressed genes from the comparison of infected S and R plants (Si, Ri).Supplement Table 4List of ITAG2.3 ID and Mapman pathway of differentially expressed genes from the comparison of non-infected LeHT1-silenced and non-silenced R plants (R0:TRV-LeHT1, R0)xDownload (.08 MB ) Supplement Table 4List of ITAG2.3 ID and Mapman pathway of differentially expressed genes from the comparison of non-infected LeHT1-silenced and non-silenced R plants (R0:TRV-LeHT1, R0)Supplemental Figure and TablesxDownload (.44 MB ) Supplemental Figure and TablesSupplement Table 6List of ITAG2.3 ID and Mapman pathway of transcripts differential expressed from the comparison of infected and non-infected R, S and LeHT1-silenced R plants (Ri vs. R0, Si vs. S0, RHi vs. RH0)xDownload (.05 MB ) Supplement Table 6List of ITAG2.3 ID and Mapman pathway of transcripts differential expressed from the comparison of infected and non-infected R, S and LeHT1-silenced R plants (Ri vs. R0, Si vs. S0, RHi vs. RH0)Supplement Table 7List of ITAG2.3 ID and Mapman pathway of differentially expressed genes from the comparison of infected LeHT1-silenced and not-silenced R plants (RHi vs. Ri)xDownload (.07 MB ) Supplement Table 7List of ITAG2.3 ID and Mapman pathway of differentially expressed genes from the comparison of infected LeHT1-silenced and not-silenced R plants (RHi vs. Ri)Supplementary DataxDownload (3.35 MB ) Supplementary DataSupplementary DataxDownload (.05 MB ) Supplementary Data

Combined Use of Genome-Wide Association Data and Correlation Networks Unravels Key Regulators of Primary Metabolism in Arabidopsis thaliana

Plant primary metabolism is a highly coordinated, central, and complex network of biochemical processes regulated at both the genetic and post-translational levels. The genetic basis of this network can be explored by analyzing the metabolic composition of genetically diverse genotypes in a given plant species. Here, we report an integrative strategy combining quantitative genetic mapping and metabolite‒transcript correlation networks to identify functional associations between genes and primary metabolites in Arabidopsis thaliana. Genome-wide association study (GWAS) was used to identify metabolic quantitative trait loci (mQTL). Correlation networks built using metabolite and transcript data derived from a previously published time-course stress study yielded metabolite‒transcript correlations identified by covariation. Finally, results obtained in this study were compared with mQTL previously described. We applied a statistical framework to test and compare the performance of different single methods (network approach and quantitative genetics methods, representing the two orthogonal approaches combined in our strategy) with that of the combined strategy. We show that the combined strategy has improved performance manifested by increased sensitivity and accuracy. This combined strategy allowed the identification of 92 candidate associations between structural genes and primary metabolites, which not only included previously well-characterized gene‒metabolite associations, but also revealed novel associations. Using loss-of-function mutants, we validated two of the novel associations with genes involved in tyrosine degradation and in β-alanine metabolism. In conclusion, we demonstrate that applying our integrative strategy to the largely untapped resource of metabolite–transcript associations can facilitate the discovery of novel metabolite-related genes. This integrative strategy is not limited to A. thaliana, but generally applicable to other plant species.