Extraction of Plant Lipids for LC-MS-Based Untargeted Plant Lipidomics

Overexpression of phosphatidylserine synthase IbPSS1 enhances salt tolerance by stimulating ethylene signaling-dependent lignin synthesis in sweetpotato roots

Phosphatidylserine (PS) is an important lipid signaling required for plant growth regulation and salt stress adaptation. However, how PS positively regulate plant salt tolerance is still largely unknown. In this study, IbPSS1-overexpressed sweetpotato plants that exhibited overproduction of PS was employed to explore the mechanisms underlying the PS stimulation of plant salt tolerance. The results revealed that the IbPSS1-overexpressed sweetpotato accumulated less Na+ in the stem and leaf tissues compared with the wild type plants. Proteomic profile of roots showed that lignin synthesis-related proteins over-accumulated in IbPSS1-overexpressed sweetpotato. Correspondingly, the lignin content was enhanced but the influx of Na + into the stele was significantly blocked in IbPSS1-overexpressed sweetpotato. The results further revealed that ethylene synthesis and signaling related genes were upregulated in IbPSS1-overexpressed sweetpotato. Ethylene imaging experiment revealed the enhancement of ethylene mainly localized in the root stele. Inhibition of ethylene synthesis completely reversed the PS-overproduction induced lignin synthesis and Na+ influx pattern in stele tissues. Taken together, our findings demonstrate a mechanism by which PS regulates ethylene signaling and lignin synthesis in the root stele, thus helping sweetpotato plants to block the loading of Na+ into the xylem and to minimize the accumulation of Na+ in the shoots.

Integrated analyses of ionomics, phytohormone profiles, transcriptomics, and metabolomics reveal a pivotal role of carbon-nano sol in promoting the growth of tobacco plants

BACKGROUND

Carbon nano sol (CNS) can markedly affect the plant growth and development. However, few systematic analyses have been conducted on the underlying regulatory mechanisms in plants, including tobacco (Nicotiana tabacum L.).

RESULTS

Integrated analyses of phenome, ionome, transcriptome, and metabolome were performed in this study to elucidate the physiological and molecular mechanisms underlying the CNS-promoting growth of tobacco plants. We found that 0.3% CNS, facilitating the shoot and root growth of tobacco plants, significantly increased shoot potassium concentrations. Antioxidant, metabolite, and phytohormone profiles showed that 0.3% CNS obviously reduced reactive oxygen species production and increased antioxidant enzyme activity and auxin accumulation. Comparative transcriptomics revealed that the GO and KEGG terms involving responses to oxidative stress, DNA binding, and photosynthesis were highly enriched in response to exogenous CNS application. Differential expression profiling showed that NtNPF7.3/NtNRT1.5, potentially involved in potassium/auxin transport, was significantly upregulated under the 0.3% CNS treatment. High-resolution metabolic fingerprints showed that 141 and 163 metabolites, some of which were proposed as growth regulators, were differentially accumulated in the roots and shoots under the 0.3% CNS treatment, respectively.

CONCLUSIONS

Taken together, this study revealed the physiological and molecular mechanism underlying CNS-mediated growth promotion in tobacco plants, and these findings provide potential support for improving plant growth through the use of CNS.

Integrating multiomics data accelerates elucidation of plant primary and secondary metabolic pathways

Plants are the most important sources of food for humans, as well as supplying many ingredients that are of great importance for human health. Developing an understanding of the functional components of plant metabolism has attracted considerable attention. The rapid development of liquid chromatography and gas chromatography, coupled with mass spectrometry, has allowed the detection and characterization of many thousands of metabolites of plant origin. Nowadays, elucidating the detailed biosynthesis and degradation pathways of these metabolites represents a major bottleneck in our understanding. Recently, the decreased cost of genome and transcriptome sequencing rendered it possible to identify the genes involving in metabolic pathways. Here, we review the recent research which integrates metabolomic with different omics methods, to comprehensively identify structural and regulatory genes of the primary and secondary metabolic pathways. Finally, we discuss other novel methods that can accelerate the process of identification of metabolic pathways and, ultimately, identify metabolite function(s).

The state of the art in plant lipidomics

Lipids are a group of compounds with diverse structures that perform several important functions in plants. To unravel and better understand their in vivo functions, plant biologists have been using various lipidomic technologies including liquid-chromatography (LC)-mass spectrometry (MS). However, there are still significant challenges in LC-MS based plant lipidomics, which need to be addressed. In this review, we provide an overview of the key developments in LC-MS based lipidomic approaches to detect and identify plant lipids with emphasis on areas that can be further improved. Given that the cellular lipidome is estimated to contain hundreds of thousands of lipids,^1,2 many of the lipid structures remain to be discovered. Furthermore, the plant lipidome is considered to be significantly more complex compared to that of mammals. Recent technical developments in mass spectrometry have made the detection of novel lipids possible; hence, approaches that can be used for plant lipid discovery are also discussed.

The presence of oxygenated lipids in plant defense in response to biotic stress: a metabolomics appraisal

Recent lipid-based findings suggest more direct roles for fatty acids and their degradation products in inducing/modulating various aspects of plant defense, e.g. as signaling molecules following stress responses that may regulate plant innate immunity. The synthesis of oxylipins is a highly dynamic process and occurs in both a developmentally regulated mode and in response to abiotic and biotic stresses. This mini-review summarizes the occurrence of free - and oxygenated fatty acid derivatives in plants as part of an orchestrated metabolic defense against pathogen attack. Oxygenated C18 derived polyunsaturated fatty acids were identified by untargeted metabolomics studies of a number of different plant-microbe pathosystems and may serve as potential biomarkers of oxidative stress. Untargeted metabolomics in combination with targeted lipidomics, can uncover previously unrecognized aspects of lipid mobilization during plant defense.

Bioinformatics in Lipidomics: Automating Large-Scale LC-MS-Based Untargeted Lipidomics Profiling with SimLipid Software

Liquid chromatography-mass spectrometry (LC-MS) provides one of the most popular platforms for untargeted plant lipidomics analysis (Shulaev and Chapman, Biochim Biophys Acta 1862(8):786-791, 2017; Rupasinghe and Roessner, Methods Mol Biol 1778:125-135, 2018; Welti et al., Front Biosci 12:2494-506, 2007; Shiva et al., Plant Methods 14:14, 2018). We have developed SimLipid software in order to streamline the analysis of large-volume datasets generated by LC-MS-based untargeted lipidomics methods. SimLipid contains a customizable library of lipid species; graphical user interfaces (GUIs) for visualization of raw data; the identified lipid molecules and their associated mass spectra annotated with fragment ions and parent ions; and detailed information of each identified lipid species all in a single workbench enabling users to rapidly review the results by examining the data for confident identifications of lipid molecular species. In this chapter, we present the functionality of the software and workflow for automating large-scale LC-MS-based untargeted lipidomics profiling.

Plants Metabolome Study: Emerging Tools and Techniques

Metabolomics is now considered a wide-ranging, sensitive and practical approach to acquire useful information on the composition of a metabolite pool present in any organism, including plants. Investigating metabolomic regulation in plants is essential to understand their adaptation, acclimation and defense responses to environmental stresses through the production of numerous metabolites. Moreover, metabolomics can be easily applied for the phenotyping of plants; and thus, it has great potential to be used in genome editing programs to develop superior next-generation crops. This review describes the recent analytical tools and techniques available to study plants metabolome, along with their significance of sample preparation using targeted and non-targeted methods. Advanced analytical tools, like gas chromatography-mass spectrometry (GC-MS), liquid chromatography mass-spectroscopy (LC-MS), capillary electrophoresis-mass spectrometry (CE-MS), fourier transform ion cyclotron resonance-mass spectrometry (FTICR-MS) matrix-assisted laser desorption/ionization (MALDI), ion mobility spectrometry (IMS) and nuclear magnetic resonance (NMR) have speed up precise metabolic profiling in plants. Further, we provide a complete overview of bioinformatics tools and plant metabolome database that can be utilized to advance our knowledge to plant biology.

HILIC-ESI-MS analysis of phosphatidic acid methyl esters artificially generated during lipid extraction from microgreen crops

The uncontrolled activation of endogenous enzymes may introduce both qualitative and quantitative artefacts when lipids are extracted from vegetal matrices. In the present study, a method based on hydrophilic interaction liquid chromatography coupled either to high-resolution/accuracy Fourier-transform mass spectrometry (HILIC-ESI-FTMS) or to linear ion trap multiple stage mass spectrometry (HILIC-ESI-MSn , with n = 2 and 3) with electrospray ionization was developed to unveil one of those artefacts. Specifically, the artificial generation of methyl esters of phosphatidic acids (MPA), catalysed by endogenous phospholipase D (PLD) during lipid extraction from five oleaginous microgreen crops (chia, soy, flax, sunflower and rapeseed), was studied. Phosphatidylcholines (PC) and phosphatidylglycerols (PG) were found to be the most relevant precursors of MPA among glycerophospholipids (GPLs), being involved in a transphosphatidylation process catalysed by PLD and having methanol as a coreactant. The combination of MS2 and MS3 measurements enabled the unambiguous recognition of MPA from their fragmentation pathways, leading to distinguish them from isobaric PA including a further CH2 group on their side chains. PLD was also found to catalyse the hydrolysis of PC and PG to phosphatidic acids (PAs). The described transformations were confirmed by the remarkable decrease of MPA abundance observed when isopropanol, known to inhibit PLD, was tentatively adopted instead of water during the homogenization of microgreens. The unequivocal identification of MPA might be exploited to assess if GPL alterations are actually triggered by endogenous PLD during lipid extractions from specific vegetal tissues.

Mass spectrometry-based forest tree metabolomics

Research in forest tree species has advanced slowly when compared with other agricultural crops and model organisms, mainly due to the long-life cycles, large genome sizes, and lack of genomic tools. Additionally, trees are complex matrices, and the presence of interferents (e.g., oleoresins and cellulose) challenges the analysis of tree tissues with mass spectrometry (MS)-based analytical platforms. In this review, advances in MS-based forest tree metabolomics are discussed. Given their economic and ecological significance, particular focus is given to Pinus, Quercus, and Eucalyptus forest tree species to better understand their metabolite responses to abiotic and biotic stresses in the current climate change scenario. Furthermore, MS-based metabolomics technologies produce large and complex datasets that require expertize to adequately manage, process, analyze, and store the data in dedicated repositories. To ensure that the full potential of forest tree metabolomics data are translated into new knowledge, these data should comply with the FAIR principles (i.e., Findable, Accessible, Interoperable, and Re-usable). It is essential that adequate standards are implemented to annotate metadata from forest tree metabolomics studies as is already required by many science and governmental agencies and some major scientific publishers. © 2019 John Wiley & Sons Ltd. Mass Spec Rev 40:126-157, 2021.

Plant Metabolomics: Evaluation of Different Extraction Parameters for Nontargeted UPLC-ESI-QTOF-Mass Spectrometry at the Example of White Asparagus officinalis

The extraction of metabolites turns out to be one of the most important key factors for nontargeted metabolomics approaches as this step can significantly affects the informative value of the successive measurements. Compared to metabolomics experiments of various matrices of bacterial or mammalian origins, there are only few studies, which focus on different extraction methods for plant metabolomics analyses. In this study, various solvent extraction compositions were compared and assessed using an UPLC-ESI-QTOF-MS strategy. Exemplary, white asparagus ( Asparagus officinalis) were employed as a low-fat-, low-protein-, high-water-content model commodity with the objective of designing an optimal nontargeted extraction protocol for polar and nonpolar metabolites. Furthermore, the influence of acid addition, mechanical cell disruption methods (ball mill, ultrasonic bath, vortex mixer), and extract stability have been systematically scrutinized too. The different extraction protocols were compared based on sum of features, sum of peak intensities, sum of peak areas, as well as by analyzing individual signals of as many different substance groups as possible to obtain a maximum overview.