Sample preparation issues in NMR-based plant metabolomics: optimisation for Vitis wood samples

Exploring the complementarity of fast multipulse and multidimensional NMR methods for metabolomics: a chemical ecology case study

This study investigates the potential and complementarity of high-throughput multipulse and multidimensional NMR methods for metabolomics. Through a chemical ecology case study, three methods are investigated, offering a continuum of methods with complementary features in terms of resolution, sensitivity and experiment time. Ultrafast 2D COSY, adiabatic INEPT and SYMAPS HSQC are shown to provide a very good classification ability, comparable to the reference 1D 1H NMR method. Moreover, a detailed analysis of discriminant buckets upon supervised statistical analysis shows that all methods are highly complementary, since they are able to highlight discriminant signals that could not be detected by 1D 1H NMR. In particular, fast 2D methods appear very efficient to discriminate signals located in highly crowded regions of the 1H spectrum. Overall, the combination of these recent methods within a single NMR metabolomics workflow allows to maximize the accessible metabolic information, and also raises exciting challenges in terms of NMR data analysis for chemical ecology.

Twenty Years of 1H NMR Plant Metabolomics: A Way Forward toward Assessment of Plant Metabolites for Constitutive and Inducible Defenses to Biotic Stress

Metabolomics has become an important tool in elucidating the complex relationship between a plant genotype and phenotype. For over 20 years, nuclear magnetic resonance (NMR) spectroscopy has been known for its robustness, quantitative capabilities, simplicity, and cost-efficiency. 1H NMR is the method of choice for analyzing a broad range of relatively abundant metabolites, which can be used for both capturing the plant chemical profile at one point in time and understanding the pathways that underpin plant defense. This systematic Review explores how 1H NMR-based plant metabolomics has contributed to understanding the role of various compounds in plant responses to biotic stress, focusing on both primary and secondary metabolites. It clarifies the challenges and advantages of using 1H NMR in plant metabolomics, interprets common trends observed, and suggests guidelines for method development and establishing standard procedures.

Metabolite Profiling of Conifer Needles: Tracing Pollution and Climate Effects

In the face of escalating environmental challenges, understanding the intricate relationship between plant metabolites, pollution stress, and climatic conditions is of paramount importance. This study aimed to conduct a comprehensive analysis of metabolic variations generated through 1H and 13C NMR measurements in evergreen needles collected from different regions with varying pollution levels. Multivariate analyses were employed to identify specific metabolites responsive to pollution stress and climatic factors. Air pollution indicators were assessed through ANOVA and Pearson correlation analyses. Our results revealed significant metabolic changes attributed to geographical origin, establishing these conifer species as potential indicators for both air pollution and climatic conditions. High levels of air pollution correlated with increased glucose and decreased levels of formic acid and choline. Principal component analysis (PCA) unveiled a clear species separation, largely influenced by succinic acid and threonine. Discriminant analysis (DA) confirmed these findings, highlighting the positive correlation of glucose with pollution grade. Beyond pollution assessment, these metabolic variations could have ecological implications, impacting interactions and ecological functions. Our study underscores the dynamic interplay between conifer metabolism, environmental stressors, and ecological systems. These findings not only advance environmental monitoring practices but also pave the way for holistic research encompassing ecological and physiological dimensions, shedding light on the multifaceted roles of metabolites in conifer responses to environmental challenges.

From sample preparation to NMR-based metabolic profiling in food commodities: The case of table olives

INTRODUCTION

Nuclear magnetic resonance (NMR)-based metabolic profiling has been widely used in food and plant sciences. Despite its simplicity and inherent reproducibility, the determination of the appropriate pre-processing procedures greatly affects the obtained metabolic profile.

OBJECTIVES

The current study represents a detailed guide of use for untargeted NMR-based metabolic profiling of table olives (Olea europaea L.).

METHODS

Greek Kalamon table olives from different geographical origins were selected as reference materials. Differently treated samples were extracted using different solvents and/or solvent systems. Chemical profiles were evaluated with high-performance thin layer chromatography (HPTLC). Different deuterated solvents and sample concentrations were evaluated for the recording of optimal quality spectra.

RESULTS

The methanol extract of freeze-dried table olives was found to contain the most representative secondary metabolites, in higher concentrations, as well. The optimal deuterated solvent for the NMR analysis was methanol-d₄ , while final sample concentration should be within the range of 10 to 15 mg/mL. Multivariate data analysis was also used to estimate and confirm the variation and clustering caused by different characteristics of the samples.

CONCLUSIONS

Results of the present study make evident the necessity for thorough planning and method development prior to any extensive metabolomic study based on NMR spectroscopy. Pre-processing and sample preparation stages seemed to greatly affect the metabolic profile and spectral quality in the case of table olives, which by extrapolation could apply to other food commodities. Nevertheless, the nature of the samples must be fully described in general, in order to proceed to solid conclusions.

The exposome paradigm to predict environmental health in terms of systemic homeostasis and resource balance based on NMR data science

The environment, from microbial ecosystems to recycled resources, fluctuates dynamically due to many physical, chemical and biological factors, the profile of which reflects changes in overall state, such as environmental illness caused by a collapse of homeostasis. To evaluate and predict environmental health in terms of systemic homeostasis and resource balance, a comprehensive understanding of these factors requires an approach based on the "exposome paradigm", namely the totality of exposure to all substances. Furthermore, in considering sustainable development to meet global population growth, it is important to gain an understanding of both the circulation of biological resources and waste recycling in human society. From this perspective, natural environment, agriculture, aquaculture, wastewater treatment in industry, biomass degradation and biodegradable materials design are at the forefront of current research. In this respect, nuclear magnetic resonance (NMR) offers tremendous advantages in the analysis of samples of molecular complexity, such as crude bio-extracts, intact cells and tissues, fibres, foods, feeds, fertilizers and environmental samples. Here we outline examples to promote an understanding of recent applications of solution-state, solid-state, time-domain NMR and magnetic resonance imaging (MRI) to the complex evaluation of organisms, materials and the environment. We also describe useful databases and informatics tools, as well as machine learning techniques for NMR analysis, demonstrating that NMR data science can be used to evaluate the exposome in both the natural environment and human society towards a sustainable future.

Targeted Drug Delivery for Sustainable Crop Protection: Transport and Stability of Polymeric Nanocarriers in Plants

Spraying of agrochemicals (pesticides, fertilizers) causes environmental pollution on a million-ton scale. A sustainable alternative is target-specific, on-demand drug delivery by polymeric nanocarriers. Trunk injections of aqueous nanocarrier dispersions can overcome the biological size barriers of roots and leaves and allow distributing the nanocarriers through the plant. To date, the fate of polymeric nanocarriers inside a plant is widely unknown. Here, the in planta conditions in grapevine plants are simulated and the colloidal stability of a systematic series of nanocarriers composed of polystyrene (well-defined model) and biodegradable lignin and polylactic-co-glycolic acid by a combination of different techniques is studied. Despite the adsorption of carbohydrates and other biomolecules onto the nanocarriers' surface, they remain colloidally stable after incubation in biological fluids (wood sap), suggesting a potential transport via the xylem. The transport is tracked by fluorine- and ruthenium-labeled nanocarriers inside of grapevines by 19 F-magnetic resonance imaging or induced coupled plasma - optical emission spectroscopy. Both methods show that the nanocarriers are transported inside of the plant and proved to be powerful tools to localize nanomaterials in plants. This study provides essential information to design nanocarriers for agrochemical delivery in plants to sustainable crop protection.

Wood profiling by non-targeted high-resolution mass spectrometry: Part 1, Metabolite profiling in Cedrela wood for the determination of the geographical origin

The determination of the geographical origin of wood can be highly relevant for several reasons: On the one hand, it can help to prevent illegal logging and timber trade, on the other hand, it is of special interest for archaeological artefacts made of wood, as well as for a variety of biological questions. For this reason, different extraction methods were first tested for the analysis of polar and non-polar metabolites using liquid chromatography coupled electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-ESI-QTOF-MS). A two-phase extraction with chloroform, methanol and water proved to be particularly successful. Subsequently, cedrela (Cedrela odorata) samples from South America were measured to distinguish geographic origin. Using multivariate data analysis, numerous origin-dependent differences could be extracted. The identification of the marker substances indicated that several metabolic pathways were affected by the geographical influences, some of them probably indicating pest infections.

Rapid identification model based on decision tree algorithm coupling with 1H NMR and feature analysis by UHPLC-QTOFMS spectrometry for sandalwood

Sandalwood is one of the most valuable woods in the world. However, today's counterfeits are widespread, it is difficult to distinguish authenticity. In this paper, similar genus (Dalbergia and Pterocarpus) and confused species (Gluta sp.) of sandalwood were quickly and efficiently identified. Rapid identification model based on ¹H NMR and decision tree (DT) algorithm was firstly developed for the identification of sandalwood, and the accuracy was improved by introducing the AdaBoost algorithm. The accuracy of the final model was above 95%. And the feature components between different species of sandalwood were further explored using UHPLC-QTOFMS and NMR spectrometry. The results showed that 183 compounds were identified, among which 99 were known components, 84 were unknown components. The ¹H NMR and ¹³C NMR signals of 505 samples were assigned, among them, 14 compounds were attributed, characteristic chemical shift intervals with great differences in the model were analysed. Furthermore, the fragmentation pattern of different compounds from sandalwood, in both positive and negative ion ESI modes, was summarized. The results showed a potential and rapid tool based on DT, NMR spectroscopy and UHPLC-QTOFMS, which had performed great potential for rapid identification and feature analysis of sandalwood.

Optimizing 1D 1H-NMR profiling of plant samples for high throughput analysis: extract preparation, standardization, automation and spectra processing

INTRODUCTION

Proton nuclear magnetic resonance spectroscopy (1H-NMR)-based metabolomic profiling has a range of applications in plant sciences.

OBJECTIVES

The aim of the present work is to provide advice for minimizing uncontrolled variability in plant sample preparation before and during NMR metabolomic profiling, taking into account sample composition, including its specificity in terms of pH and paramagnetic ion concentrations, and NMR spectrometer performances.

METHODS

An automation of spectrometer preparation routine standardization before NMR acquisition campaign was implemented and tested on three plant sample sets (extracts of durum wheat spikelet, Arabidopsis leaf and root, and flax leaf, root and stem). We performed 1H-NMR spectroscopy in three different sites on the wheat sample set utilizing instruments from two manufacturers with different probes and magnetic field strengths. The three collections of spectra were processed separately with the NMRProcFlow web tool using intelligent bucketing, and the resulting buckets were subjected to multivariate analysis.

RESULTS

Comparability of large- (Arabidopsis) and medium-size (flax) datasets measured at 600 MHz and from the wheat sample set recorded at the three sites (400, 500 and 600 MHz) was exceptionally good in terms of spectral quality. The coefficient of variation of the full width at half maximum (FWHM) and the signal-to-noise ratio (S/N) of two selected peaks was comprised between 5 and 10% depending on the size of sample set and the spectrometer field. EDTA addition improved citrate and malate resonance patterns for wheat sample sets. A collection of 22 samples of wheat spikelet extracts was used as a proof of concept and showed that the data collected at the three sites on instruments of different field strengths and manufacturers yielded the same discrimination pattern of the biological groups.

CONCLUSION

Standardization or automation of several steps from extract preparation to data reduction improves data quality for small to large collections of plant samples of different origins.

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.

Plant metabolism as studied by NMR spectroscopy

The study of plant metabolism impacts a broad range of domains such as plant cultural practices, plant breeding, human or animal nutrition, phytochemistry and green biotechnologies. Plant metabolites are extremely diverse in terms of structure or compound families as well as concentrations. This review attempts to illustrate how NMR spectroscopy, with its broad variety of experimental approaches, has contributed widely to the study of plant primary or specialized metabolism in very diverse ways. The review presents recent developments of one-dimensional and multi-dimensional NMR methods to study various aspects of plant metabolism. Through recent examples, it highlights how NMR has proved to be an invaluable tool for the global characterization of sample composition within metabolomic studies, and shows some examples of use for targeted phytochemistry, with a special focus on compound identification and quantitation. In such cases, NMR approaches are often used to provide snapshots of the plant sample composition. The review also covers dynamic aspects of metabolism, with a description of NMR techniques to measure metabolic fluxes - in most cases after stable isotope labelling. It is mainly intended for NMR specialists who would be interested to learn more about the potential of their favourite technique in plant sciences and about specific details of NMR approaches in this field. Therefore, as a practical guide, a paragraph on the specific precautions that should be taken for sample preparation is also included. In addition, since the quality of NMR metabolic studies is highly dependent on approaches to data processing and data sharing, a specific part is dedicated to these aspects. The review concludes with perspectives on the emerging methods that could change significantly the role of NMR in the field of plant metabolism by boosting its sensitivity. The review is illustrated throughout with examples of studies selected to represent diverse applications of liquid-state or HR-MAS NMR.

Combined Application of UHPLC-QTOF/MS, HPLC-ELSD and 1 H-NMR Spectroscopy for Quality Assessment of DA-9801, A Standardised Dioscorea Extract

INTRODUCTION

DA-9801, a standardised 50% aqueous ethanolic extract of a mixture of Dioscorea japonica and D. nipponica, is a botanical drug candidate for the treatment of diabetic neuropathy, which finished its US phase II clinical trials recently. An advanced quality control method is needed for further development of DA-9801, considering its high contents of both primary and secondary metabolites.

OBJECTIVE

Development of a quality assessment strategy for DA-9801, based on the combination of UHPLC-QTOF/MS, HPLC-ELSD, and ¹ H-NMR spectroscopy.

METHODS

The method was developed and tested with 15 batch products of DA-9801. The steroidal saponins of DA-9801 were tentatively identified by UHPLC-QTOF/MS and were quantified with the validated HPLC-ELSD method. Primary metabolites of DA-9801 were identified and profiled using ¹ H-NMR spectrometry. The batch-to-batch equivalence of DA-9801 was tested with the ¹ H-NMR spectra using spectral binning, correlation analysis, and principal component analysis.

RESULTS

Six major saponins of DA-9801 were tentatively identified by UHPLC-QTOF/MS. Among them, protodioscin and dioscin were quantified by the validated HPLC-ELSD method. Twenty-six metabolites were identified in ¹ H-NMR spectra. The similarity between DA-9801 batches could be evaluated with the NMR spectra of DA-9801. The ¹ H-NMR method also revealed that two Dioscorea species contributed distinct amino acids to the contents of DA-9801.

CONCLUSION

This study validates the effectiveness of UHPLC-QTOF/MS, HPLC-ELSD, and ¹ H NMR-combined method for quality control of DA-9801 and its crude materials. Copyright © 2016 John Wiley & Sons, Ltd.

Bridging the gap between comprehensive extraction protocols in plant metabolomics studies and method validation

It is vital to pay much attention to the design of extraction methods developed for plant metabolomics, as any non-extracted or converted metabolites will greatly affect the overall quality of the metabolomics study. Method validation is however often omitted in plant metabolome studies, as the well-established methodologies for classical targeted analyses such as recovery optimization cannot be strictly applied. The aim of the present study is to thoroughly evaluate state-of-the-art comprehensive extraction protocols for plant metabolomics with liquid chromatography-photodiode array-accurate mass mass spectrometry (LC-PDA-amMS) by bridging the gap with method validation. Validation of an extraction protocol in untargeted plant metabolomics should ideally be accomplished by validating the protocol for all possible outcomes, i.e. for all secondary metabolites potentially present in the plant. In an effort to approach this ideal validation scenario, two plant matrices were selected based on their wide versatility of phytochemicals: meadowsweet (Filipendula ulmaria) for its polyphenols content, and spicy paprika powder (from the genus Capsicum) for its apolar phytochemicals content (carotenoids, phytosterols, capsaicinoids). These matrices were extracted with comprehensive extraction protocols adapted from literature and analysed with a generic LC-PDA-amMS characterization platform that was previously validated for broad range phytochemical analysis. The performance of the comprehensive sample preparation protocols was assessed based on extraction efficiency, repeatability and intermediate precision and on ionization suppression/enhancement evaluation. The manuscript elaborates on the finding that none of the extraction methods allowed to exhaustively extract the metabolites. Furthermore, it is shown that depending on the extraction conditions enzymatic degradation mechanisms can occur. Investigation of the fractions obtained with the different extraction methods revealed a low resolving power for phytochemicals for all methods. Nevertheless, an overall good repeatability was observed for all extraction methods, which is essential to allow direct comparison between samples. In summary, no single procedure outperforms the others and compromises will have to be made during method selection.

Nuclear Magnetic Resonance (NMR) Spectroscopy For Metabolic Profiling of Medicinal Plants and Their Products

NMR spectroscopy has multidisciplinary applications, including excellent impact in metabolomics. The analytical capacity of NMR spectroscopy provides information for easy qualitative and quantitative assessment of both endogenous and exogenous metabolites present in biological samples. The complexity of a particular metabolite and its contribution in a biological system are critically important for understanding the functional state that governs the organism's phenotypes. This review covers historical aspects of developments in the NMR field, its applications in chemical profiling, metabolomics, and quality control of plants and their derived medicines, foods, and other products. The bottlenecks of NMR in metabolic profiling are also discussed, keeping in view the future scope and further technological interventions.

An efficient high throughput metabotyping platform for screening of biomass willows

Future improvement of woody biomass crops such as willow and poplar relies on our ability to select for metabolic traits that sequester more atmospheric carbon into biomass, or into useful products to replace petrochemical streams. We describe the development of metabotyping screens for willow, using combined 1D 1H-NMR-MS. A protocol was developed to overcome 1D 1H-NMR spectral alignment problems caused by variable pH and peak broadening arising from high organic acid levels and metal cations. The outcome was a robust method to allow direct statistical comparison of profiles arising from source (leaf) and sink (stem) tissues allowing data to be normalised to a constant weight of the soluble metabolome. We also describe the analysis of two willow biomass varieties, demonstrating how fingerprints from 1D 1H-NMR-MS vary from the top to the bottom of the plant. Automated extraction of quantitative data of 56 primary and secondary metabolites from 1D 1H-NMR spectra was realised by the construction and application of a Salix metabolite spectral library using the Chenomx software suite. The optimised metabotyping screen in conjunction with automated quantitation will enable high-throughput screening of genetic collections. It also provides genotype and tissue specific data for future modelling of carbon flow in metabolic networks.