Analytical challenges and solutions for performing metabolomic analysis of root exudates
TL;DR: The assessment of root exudates calls for the development of hyphenated analytical methodologies, as well as efforts to consolidate data-preprocessing workflows.
About: This article is published in Trends in Environmental Analytical Chemistry.The article was published on 2021-05-15 and is currently open access. It has received 22 citations till now.
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TL;DR: In this article , the authors integrate the interrelationship between agronomic traits, rhizosphere microbial population and metabolic processes in roots, following seed treatment with either arbuscular mycorrhizal fungi (AMF) or Plant Growth-Promoting Rhizobacteria (PGPR).
Abstract: Abstract Seed inoculation with beneficial microorganisms has gained importance as it has been proven to show biostimulant activity in plants, especially in terms of abiotic/biotic stress tolerance and plant growth promotion, representing a sustainable way to ensure yield stability under low input sustainable agriculture. Nevertheless, limited knowledge is available concerning the molecular and physiological processes underlying the root‐inoculant symbiosis or plant response at the root system level. Our work aimed to integrate the interrelationship between agronomic traits, rhizosphere microbial population and metabolic processes in roots, following seed treatment with either arbuscular mycorrhizal fungi (AMF) or Plant Growth‐Promoting Rhizobacteria (PGPR). To this aim, maize was grown under open field conditions with either optimal or reduced nitrogen availability. Both seed treatments increased nitrogen uptake efficiency under reduced nitrogen supply revealed some microbial community changes among treatments at root microbiome level and limited yield increases, while significant changes could be observed at metabolome level. Amino acid, lipid, flavone, lignan, and phenylpropanoid concentrations were mostly modulated. Integrative analysis of multi‐omics datasets (Multiple Co‐Inertia Analysis) highlighted a strong correlation between the metagenomics and the untargeted metabolomics datasets, suggesting a coordinate modulation of root physiological traits.
9 citations
TL;DR: Genomic selection (GS) as mentioned in this paper is the application of genomic markers to predict phenotypic traits in a breeding population, offering the possibility of rapid genetic improvement, making GS especially attractive for modifying traits of long-lived species.
8 citations
TL;DR: In this article , a systematic evaluation on the performance of direct introduction ESI and matrix assisted laser desorption ionization (MALDI) coupled with FTICR MS applied to the analysis of root exudates (RE), a complex mixture of metabolites released from plant root tips and containing a relatively high salt concentration.
4 citations
TL;DR: In this paper, the authors acknowledge the financial support of the Spanish Ministry of Science, Innovation and Universities under Project CTM2017-91355-EXP and Project CEX2018-000794-S under the Beatriu de Pinos 2018 grant-programme (MSCA grant agreement number 801370) for the funding.
4 citations
TL;DR: In this paper , the root exudation changes of two aquatic plants (Lemna minor and Salvinia natans) upon micropollutants exposure (10, 100 and 1000 μg/L mixes containing naproxen, diclofenac, carbamazepine, and benzotriazole).
4 citations
References
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TL;DR: An LC/MS-based data analysis approach, XCMS, which incorporates novel nonlinear retention time alignment, matched filtration, peak detection, and peak matching, and is demonstrated using data sets from a previously reported enzyme knockout study and a large-scale study of plasma samples.
Abstract: Metabolite profiling in biomarker discovery, enzyme substrate assignment, drug activity/specificity determination, and basic metabolic research requires new data preprocessing approaches to correlate specific metabolites to their biological origin. Here we introduce an LC/MS-based data analysis approach, XCMS, which incorporates novel nonlinear retention time alignment, matched filtration, peak detection, and peak matching. Without using internal standards, the method dynamically identifies hundreds of endogenous metabolites for use as standards, calculating a nonlinear retention time correction profile for each sample. Following retention time correction, the relative metabolite ion intensities are directly compared to identify changes in specific endogenous metabolites, such as potential biomarkers. The software is demonstrated using data sets from a previously reported enzyme knockout study and a large-scale study of plasma samples. XCMS is freely available under an open-source license at http://metlin...
3,963 citations
TL;DR: A new generation of a popular open-source data processing toolbox, MZmine 2 is introduced, suitable for processing large batches of data and has been applied to both targeted and non-targeted metabolomic analyses.
Abstract: Mass spectrometry (MS) coupled with online separation methods is commonly applied for differential and quantitative profiling of biological samples in metabolomic as well as proteomic research. Such approaches are used for systems biology, functional genomics, and biomarker discovery, among others. An ongoing challenge of these molecular profiling approaches, however, is the development of better data processing methods. Here we introduce a new generation of a popular open-source data processing toolbox, MZmine 2. A key concept of the MZmine 2 software design is the strict separation of core functionality and data processing modules, with emphasis on easy usability and support for high-resolution spectra processing. Data processing modules take advantage of embedded visualization tools, allowing for immediate previews of parameter settings. Newly introduced functionality includes the identification of peaks using online databases, MSn data support, improved isotope pattern support, scatter plot visualization, and a new method for peak list alignment based on the random sample consensus (RANSAC) algorithm. The performance of the RANSAC alignment was evaluated using synthetic datasets as well as actual experimental data, and the results were compared to those obtained using other alignment algorithms. MZmine 2 is freely available under a GNU GPL license and can be obtained from the project website at: http://mzmine.sourceforge.net/
. The current version of MZmine 2 is suitable for processing large batches of data and has been applied to both targeted and non-targeted metabolomic analyses.
2,884 citations
TL;DR: By completely re-implementing the MetaboAnalyst suite using the latest web framework technologies, the server has been able to substantially improve its performance, capacity and user interactivity.
Abstract: MetaboAnalyst (www.metaboanalyst.ca) is a web server designed to permit comprehensive metabolomic data analysis, visualization and interpretation. It supports a wide range of complex statistical calculations and high quality graphical rendering functions that require significant computational resources. First introduced in 2009, MetaboAnalyst has experienced more than a 50X growth in user traffic (>50 000 jobs processed each month). In order to keep up with the rapidly increasing computational demands and a growing number of requests to support translational and systems biology applications, we performed a substantial rewrite and major feature upgrade of the server. The result is MetaboAnalyst 3.0. By completely re-implementing the MetaboAnalyst suite using the latest web framework technologies, we have been able substantially improve its performance, capacity and user interactivity. Three new modules have also been added including: (i) a module for biomarker analysis based on the calculation of receiver operating characteristic curves; (ii) a module for sample size estimation and power analysis for improved planning of metabolomics studies and (iii) a module to support integrative pathway analysis for both genes and metabolites. In addition, popular features found in existing modules have been significantly enhanced by upgrading the graphical output, expanding the compound libraries and by adding support for more diverse organisms.
2,404 citations
TL;DR: A detailed protocol for gas chromatography mass spectrometry (GC-MS)-based metabolite profiling that offers a good balance of sensitivity and reliability, being considerably more sensitive than NMR and more robust than liquid chromatography–linked mass spectromaetry.
Abstract: The concept of metabolite profiling has been around for decades, but technical innovations are now enabling it to be carried out on a large scale with respect to the number of both metabolites measured and experiments carried out. Here we provide a detailed protocol for gas chromatography mass spectrometry (GC-MS)-based metabolite profiling that offers a good balance of sensitivity and reliability, being considerably more sensitive than NMR and more robust than liquid chromatography-linked mass spectrometry. We summarize all steps from collecting plant material and sample handling to derivatization procedures, instrumentation settings and evaluating the resultant chromatograms. We also define the contribution of GC-MS-based metabolite profiling to the fields of diagnostics, gene annotation and systems biology. Using the protocol described here facilitates routine determination of the relative levels of 300-500 analytes of polar and nonpolar extracts in approximately 400 experimental samples per week per machine.
1,623 citations
TL;DR: In this paper, physiological factors of plants that may govern plant-microbe interactions, focusing on root physiology and the role of root exudates, are discussed, and a possible sequence of events governing rhizobiome assembly is elaborated.
1,023 citations