Sample-directed pseudotargeted method for the metabolic profiling analysis of rice seeds based on liquid chromatography with mass spectrometry

Development of analytical protocol for the investigation of transformation products of pre-harvest fungicides in fruits using LC-MS/MS methods

Chemical protection of plants is critical to permit all-year-long availability of plant products. These chemical agents are transformed both biotically and abiotically after spraying. Our purpose was to develop a workflow which is suitable to investigate those transformation products from plant matrices. Two field trials were set up in two years in two different plant matrices (apples, cherries) to develop a workflow to map the transformation products (TP) of three selected pre-harvest fungicides (boscalid, fluopyram, pyraclostrobin) in the fruits. Modified QuEChERS extraction method was applied for the extraction of TPs from the fruit matrices. We used liquid chromatograph-mass spectrometers to identify and confirm the transformation products of fungicides. LC-QTOF-MS method was suitable to map the key fragmentation routes of parent fungicides. Based on fragmentation pathways, MRM (multiple-reaction monitoring) transitions of fungicide-metabolites mentioned in the literature were predicted. HPLC-QTRAP-MS in target mode was successfully applied to monitor trace level of metabolites and in some cases their isomers. For confirmation of the identified metabolites, LC-QTOF-MS was used. Five earlier-documented as well as one novel transformation product (deschloro-FLP) were found in the investigated fruit samples, the latter has not been reported in plant matrices so far. Area-normalisation method was used to follow the relative concentration of the transformation products in the fruits as a function of time.

Bridging Targeted and Untargeted Mass Spectrometry-Based Metabolomics via Hybrid Approaches

This mini-review aims to discuss the development and applications of mass spectrometry (MS)-based hybrid approaches in metabolomics. Several recently developed hybrid approaches are introduced. Then, the overall workflow, frequently used instruments, data handling strategies, and applications are compared and their pros and cons are summarized. Overall, the improved repeatability and quantitative capability in large-scale MS-based metabolomics studies are demonstrated, in comparison to either targeted or untargeted metabolomics approaches alone. In summary, we expect this review to serve as a first attempt to highlight the development and applications of emerging hybrid approaches in metabolomics, and we believe that hybrid metabolomics approaches could have great potential in many future studies.

Development of a plasma pseudotargeted metabolomics method based on ultra-high-performance liquid chromatography-mass spectrometry

Untargeted methods are typically used in the detection and discovery of small organic compounds in metabolomics research, and ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) is one of the most commonly used platforms for untargeted metabolomics. Although they are non-biased and have high coverage, untargeted approaches suffer from unsatisfying repeatability and a requirement for complex data processing. Targeted metabolomics based on triple-quadrupole mass spectrometry (TQMS) could be a complementary tool because of its high sensitivity, high specificity and excellent quantification ability. However, it is usually applicable to known compounds: compounds whose identities are known and/or are expected to be present in the analyzed samples. Pseudotargeted metabolomics merges the advantages of untargeted and targeted metabolomics and can act as an alternative to the untargeted method. Here, we describe a detailed protocol of pseudotargeted metabolomics using UHPLC-TQMS. An in-depth, untargeted metabolomics experiment involving multiple UHPLC-HRMS runs with MS at different collision energies (both positive and negative) is performed using a mixture obtained using small amounts of the analyzed samples. XCMS, CAMERA and Multiple Reaction Monitoring (MRM)-Ion Pair Finder are used to find and annotate peaks and choose transitions that will be used to analyze the real samples. A set of internal standards is used to correct for variations in retention time. High coverage and high-performance quantitative analysis can be realized. The entire protocol takes ~5 d to complete and enables the simultaneously semiquantitative analysis of 800-1,300 metabolites.

Impact of Crossing Parent and Environment on the Metabolite Profiles of Progenies Generated from a Low Phytic Acid Rice ( Oryza sativa L.) Mutant

The low phytic acid ( lpa) rice mutant Os-lpa-MH86-1, exhibiting a mutation-induced metabolite signature (i.e., increased levels of sugars, sugar alcohols, amino acids, phytosterols, and biogenic amines), was crossed with two commercial wild-type cultivars. The resulting progenies of generation F₈ harvested at three independent field trials were subjected to a GC/MS-based metabolite profiling approach. Statistical assessments via multivariate and univariate analyses demonstrated that the environment had a strong impact on the metabolite profiles of the resulting progenies. In addition, the metabolites of homozygous lpa progenies were significantly influenced by the lipid profiles of the wild-type cultivars employed as the crossing parents. However, for each individual field trial, both the lpa trait and the mutation-specific metabolite signature were consistently expressed in the homozygous lpa mutant progenies of the two crosses. The data underline that cross-breeding can be employed as a tool to generate lpa progeny rice seeds stably exhibiting the mutation-induced metabolic traits.