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Metabolomics investigates global metabolic alterations associated with chemical, biological, physiological, or pathological processes. These metabolic changes are measured with various analytical platforms including liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS) and nuclear magnetic resonance spectroscopy (NMR). While LC-MS methods are becoming increasingly popular in the field of metabolomics (accounting for more than 70% of published metabolomics studies to date), there are considerable benefits and advantages to NMR-based methods for metabolomic studies. In fact, according to PubMed, more than 926 papers on NMR-based metabolomics were published in 2021—the most ever published in a given year. This suggests that NMR-based metabolomics continues to grow and has plenty to offer to the scientific community. This perspective outlines the growing applications of NMR in metabolomics, highlights several recent advances in NMR technologies for metabolomics, and provides a roadmap for future advancements.

Solid-phase microextraction (SPME) was coupled to gas chromatography mass spectrometry (GC-MS) and a method optimized to quantitatively and qualitatively measure a large array of volatile metabolites in alfalfa glandular trichomes isolated from stems, trichome-free stems, and leaves as part of a non-targeted metabolomics approach. Major SPME extraction parameters optimized included SPME fiber composition, extraction temperature, and extraction time. The optimized SPME method provided the most chemically diverse coverage of alfalfa volatile and semi-volatile metabolites using a DVB/CAR/PDMS fiber, extraction temperature of 60 °C, and an extraction time of 20 min. Alfalfa SPME-GC-MS profiles were processed using automated peak deconvolution and identification (AMDIS) and quantitative data extraction software (MET-IDEA). A total of 87 trichome, 59 stem, and 99 leaf volatile metabolites were detected after background subtraction which removed contaminants present in ambient air and associated with the fibers and NaOH/EDTA buffer solution containing CaCl2. Thirty-seven volatile metabolites were detected in all samples, while 15 volatile metabolites were uniquely detected only in glandular trichomes, 9 only in stems, and 33 specifically in leaves as tissue specific volatile metabolites. Hierarchical cluster analysis (HCA) and principal component analysis (PCA) of glandular trichomes, stems, and leaves showed that the volatile metabolic profiles obtained from the optimized SPME-GC-MS method clearly differentiated the three tissues (glandular trichomes, stems, and leaves), and the biochemical basis for this differentiation is discussed. Although optimized using plant tissues, the method can be applied to other types of samples including fruits and other foods.

Viruses are obligate intracellular symbionts. Plant viruses are often discovered and studied as pathogenic parasites that cause diseases in agricultural plants. However, here it is shown that viruses can extend survival of their hosts under conditions of abiotic stress that could benefit hosts if they subsequently recover and reproduce. Various plant species were inoculated with four different RNA viruses, Brome mosaic virus (BMV), Cucumber mosaic virus (CMV), Tobacco mosaic virus and Tobacco rattle virus. The inoculated plants were stressed by withholding water. The onset of drought symptoms in virus-infected plants was compared with that in the plants that were inoculated with buffer (mock-inoculated plants). Metabolite profiling analysis was conducted and compared between mock-inoculated and virus-infected plants before and after being subjected to drought stress. In all cases, virus infection delayed the appearance of drought symptoms. Beet plants infected with CMV also exhibited significantly improved tolerance to freezing. Metabolite profiling analysis showed an increase in several osmoprotectants and antioxidants in BMV-infected rice and CMV-infected beet plants before and after drought stress. These results indicate that virus infection improves plant tolerance to abiotic stress, which correlates with increased osmoprotectant and antioxidant levels in infected plants.

Integrated metabolomics and transcriptomics of Medicago truncatula seedling border cells and root tips revealed substantial metabolic differences between these distinct and spatially segregated root regions. Large differential increases in oxylipin-pathway lipoxygenases and auxin-responsive transcript levels in border cells corresponded to differences in phytohormone and volatile levels compared with adjacent root tips. Morphological examinations of border cells revealed the presence of significant starch deposits that serve as critical energy and carbon reserves, as documented through increased β-amylase transcript levels and associated starch hydrolysis metabolites. A substantial proportion of primary metabolism transcripts were decreased in border cells, while many flavonoid- and triterpenoid-related metabolite and transcript levels were increased dramatically. The cumulative data provide compounding evidence that primary and secondary metabolism are differentially programmed in border cells relative to root tips. Metabolic resources normally destined for growth and development are redirected toward elevated accumulation of specialized metabolites in border cells, resulting in constitutively elevated defense and signaling compounds needed to protect the delicate root cap and signal motile rhizobia required for symbiotic nitrogen fixation. Elevated levels of 7,4′-dihydroxyflavone were further increased in border cells of roots exposed to cotton root rot (Phymatotrichopsis omnivora), and the value of 7,4′-dihydroxyflavone as an antimicrobial compound was demonstrated using in vitro growth inhibition assays. The cumulative and pathway-specific data provide key insights into the metabolic programming of border cells that strongly implicate a more prominent mechanistic role for border cells in plant-microbe signaling, defense, and interactions than envisioned previously.

Influenza is a persistent public health concern worldwide. The elucidation of influenza A virus (IAV)–host interactions and the identification of host factors that regulate IAV infection would be beneficial for combating and treating the disease. Ceramides, comprising a host sphingolipid family, have been shown to regulate virus infections. However, the effect of IAV on individual ceramides remains unknown. This study aimed to investigate the changes in ceramide species during the infection of human lung epithelial A549 cells and human primary tracheal epithelial cells with IAV. We established a method utilizing UHPLC-MS analysis to measure individual ceramides (C14- to C26-ceramide). The results indicate that two main ceramide species, C16- and C24-ceramide, constitute approximately 80% of the ceramide population in human respiratory epithelial cells. Following IAV infection, these ceramides were found to undergo a shift in abundance, with a reduction in C16-ceramide and an increase in C24-ceramide, under various infection conditions. Primarily, IAV infection led to an increase in multiple long-chain ceramides. These findings could provide details for understanding how the ceramide system is disrupted during influenza virus infection and to further support the ongoing efforts to understand influenza–host interactions.

The utility of metabolomics is well documented; however, its full scientific promise has not yet been realized due to multiple technical challenges. These grand challenges include accurate chemical identification of all observable metabolites and the limiting depth-of-coverage of current metabolomics methods. Here, we report a combinatorial solution to aid in both grand challenges using UHPLC-trapped ion mobility spectrometry coupled to tandem mass spectrometry (UHPLC-TIMS-TOF-MS). TIMS offers additional depth-of-coverage through increased peak capacities realized with the multi-dimensional UHPLC-TIMS separations. Metabolite identification confidence is simultaneously enhanced by incorporating orthogonal collision cross section (CCS) data matching. To facilitate metabolite identifications, we created a CCS library of 146 plant natural products. This library was generated using TIMS with N2 drift gas to record the TIMSCCSN2 of plant natural products with a high degree of reproducibility; i.e., average RSD = 0.10%. The robustness of TIMSCCSN2 data matching was tested using authentic standards spiked into complex plant extracts, and the precision of CCS measurements were determined to be independent of matrix affects. The utility of the UHPLC-TIMS-TOF-MS/MS in metabolomics was then demonstrated using extracts from the model legume Medicago truncatula and metabolites were confidently identified based on retention time, accurate mass, molecular formula, and CCS.

Aluminum (Al) toxicity is the major stress in acidic soil that comprises about 50% of the world's arable land. The complex molecular mechanisms of Al toxicity have yet to be fully determined. As a barrier to Al entrance, plant cell membranes play essential roles in plant interaction with Al, and lipid composition and membrane integrity change significantly under Al stress. Here, we show that phospholipase Dγs (PLDγs) are induced by Al stress and contribute to Al-induced membrane lipid alterations. RNAi suppression of PLDγ resulted in a decrease in both PLDγ1 and PLDγ2 expression and an increase in Al resistance. Genetic disruption of PLDγ1 also led to an increased tolerance to Al while knockout of PLDγ2 did not. Both RNAi-suppressed and pldγ1-1 mutants displayed better root growth than wild-type under Al stress conditions, and PLDγ1-deficient plants had less accumulation of callose, less oxidative damage, and less lipid peroxidation compared to wild-type plants. Most phospholipids and glycolipids were altered in response to Al treatment of wild-type plants, whereas fewer changes in lipids occurred in response to Al stress in PLDγ mutant lines. Our results suggest that PLDγs play a role in membrane lipid modulation under Al stress and that high activities of PLDγs negatively modulate plant tolerance to Al.

Exine, the outer plant pollen wall, has elaborate species-specific patterns, provides a protective barrier for male gametophytes, and serves as a mediator of strong and species-specific pollen-stigma adhesion. Exine is made of sporopollenin, a material remarkable for its strength, elasticity, and chemical durability. The chemical nature of sporopollenin, as well as the developmental mechanisms that govern its assembly into diverse patterns in different species, are poorly understood. Here, we describe a simple yet effective genetic screen in Arabidopsis (Arabidopsis thaliana) that was undertaken to advance our understanding of sporopollenin synthesis and exine assembly. This screen led to the recovery of mutants with a variety of defects in exine structure, including multiple mutants with novel phenotypes. Fifty-six mutants were selected for further characterization and are reported here. In 14 cases, we have mapped defects to specific genes, including four with previously demonstrated or suggested roles in exine development (MALE STERILITY2, CYP703A2, ANTHER-SPECIFIC PROTEIN6, TETRAKETIDE α-PYRONE REDUCTASE/DIHYDROFLAVONOL-4-REDUCTASE-LIKE1), and a number of genes that have not been implicated in exine production prior to this screen (among them, fatty acid ω-hydroxylase CYP704B1, putative glycosyl transferases At1g27600 and At1g33430,4-coumaratecoenzyme A ligase 4CL3, polygalacturonase QUARTET3, novel gene At5g58100, and nucleotide-sugar transporter At5g65000). Our study illustrates that morphological screens of pollen can be extremely fruitful in identifying previously unknown exine genes and lays the foundation for biochemical, developmental, and evolutionary studies of exine production.

There is a general consensus that supports the need for standardized reporting of metadata or information describing large-scale metabolomics and other functional genomics data sets. Reporting of standard metadata provides a biological and empirical context for the data, facilitates experimental replication, and enables the re-interrogation and comparison of data by others. Accordingly, the Metabolomics Standards Initiative is building a general consensus concerning the minimum reporting standards for metabolomics experiments of which the Chemical Analysis Working Group (CAWG) is a member of this community effort. This article proposes the minimum reporting standards related to the chemical analysis aspects of metabolomics experiments including: sample preparation, experimental analysis, quality control, metabolite identification, and data pre-processing. These minimum standards currently focus mostly upon mass spectrometry and nuclear magnetic resonance spectroscopy due to the popularity of these techniques in metabolomics. However, additional input concerning other techniques is welcomed and can be provided via the CAWG on-line discussion forum at http://msi-workgroups.sourceforge.net/ or http://Msi-workgroups-feedback@lists.sourceforge.net. Further, community input related to this document can also be provided via this electronic forum.