NMR methods for unravelling the spectra of complex mixtures

New insights on the degradation of polystyrene and polypropylene by larvae of the superworm Zophobas atratus and gut bacterial consortium enrichments obtained under different culture conditions

This study aims to deepen knowledge of the biodegradation of plastics, focusing on polypropylene (PP) fabric from surgical masks and polystyrene (PS) by larvae of Zophobas atratus as well as of specialized bacterial consortia from their gut, which were obtained in different enrichment conditions (aerobic, anaerobic, presence or absence of combined nitrogen). Plastics ingested by larvae obtained in Spain did not show any signs of oxidation but only limited depolymerization, preferably from the lowest molecular weight chains. Gut microbiota composition changed as an effect of plastic feeding. Such differences were more evident in bacterial enrichment cultures, where the polymer type influenced the composition more than by culture conditions, with an increase in the presence of nitrogen-fixers in anaerobic conditions. PS and PP degradation by different enrichment cultures was confirmed under aerobic and anaerobic conditions by respirometry tests, with anaerobic conditions favouring a more active plastic degradation. In addition, exposure to selected bacterial consortia in aerobiosis induced limited surface oxidation of PS. This possibly indicates that different biochemical routes are being utilized in the anaerobic gut and in aerobic conditions to degrade the polymer.

Individualization of petrol sources by high field nuclear magnetic resonance spectroscopy

In the forensic science context petrol is considered the most common fire accelerant. However, the identification and classification of petrol sources through the years has been proven to be a challenge in the investigation of fire related incidents. This research explored the possibility of identification and classification of petrol sources using high field NMR spectroscopy. In this study, 1H NMR profiling, using specific pulse sequences to analyse neat aliquot petrol samples of different brands collected at different times across the UK and Ireland is shown, for the first time, to provide a diagnostic 'fingerprint' with specific chemical compounds that can be used for identification and classification of petrol samples. This enables linkage of unknown petrol samples to a source and in addition provides a tool which allows exclusion of potential petrol sources. A new, innovative method using 1H selTOCSY is described for the individualization and classification of petrol samples through the identification of olefinic markers in the samples. Those markers were identified as (i) 3-methyl-1-butene, (ii) a mixture of 1-pentene and 3-methyl-1-butene, (iii) 2-methyl-2-butene and (iv) a mixture of cis and trans-2-pentene.

Recent Advancement in NMR Based Plant Metabolomics: Techniques, Tools, and Analytical Approaches

Plant metabolomics, a rapidly advancing field within plant biology, is dedicated to comprehensively exploring the intricate array of small molecules in plant systems. This entails precisely gathering comprehensive chemical data, detecting numerous metabolites, and ensuring accurate molecular identification. Nuclear magnetic resonance (NMR) spectroscopy, with its detailed chemical insights, is crucial in obtaining metabolite profiles. Its widespread application spans various research disciplines, aiding in comprehending chemical reactions, kinetics, and molecule characterization. Biotechnological advancements have further expanded NMR's utility in metabolomics, particularly in identifying disease biomarkers across diverse fields such as agriculture, medicine, and pharmacology. This review covers the stages of NMR-based metabolomics, including historical aspects and limitations, with sample preparation, data acquisition, spectral processing, analysis, and their application parts.

Analysis of complex mixtures with benchtop nuclear magnetic resonance: Solvent suppression with T2 and diffusion filters

Benchtop nuclear magnetic resonance (NMR) spectrometers are being employed in a wide variety of applications from undergraduate teaching and research in academia to quality control and process monitoring in industrial settings. Incorporating benchtop NMR in some of these applications presents opportunities for new practical uses of the technology and challenges that truly test the capabilities of compact NMR spectrometers. For instance, the use of protonated solvents in manufacturing or process monitoring requires separating and quantitating the analyte signals of interest from the strong (overwhelming) response from the solvents. Furthermore, due to the lower field strength available with permanent magnet spectrometers, the NMR spectra of complex mixtures can be more difficult to analyze due to partial or complete signal overlap. To address some of these challenges and to extend the range of applications of benchtop NMR, we investigate NMR techniques that enable quantitative analysis of different components in mixtures. These pulse sequences can be used to suppress one or multiple solvent peaks, to filter out signals by spin-spin relaxation time (T2), or to separate signal components by a molecule's diffusion coefficient (NMR diffusometry). In this paper, we discuss quantitative analysis of excipients in buffers for therapeutic proteins to highlight the usefulness of these NMR pulse sequences in the analysis of complex samples with benchtop NMR spectrometers.

Background signal suppression by opposite polarity subtraction for targeted DNP NMR spectroscopy on mixture samples

A novel method for background signal suppression is introduced to improve the selectivity of dynamic nuclear polarization (DNP) NMR spectroscopy in the study of target molecules within complex mixtures. The method uses subtraction between positively and negatively enhanced DNP spectra, leading to an improved contrast factor, which is the ratio between the target and background signal intensities. The proposed approach was experimentally validated using a reverse-micelle system that confines the target molecules together with the polarizing agent, OX063 trityl. A substantial increase in the contrast factor was observed, and the contrast factor was optimized through careful selection of the DNP build-up time. A simulation study based on the experimental results provides insights into a strategy for choosing the appropriate DNP build-up time and the corresponding selectivity of the method. Further analysis revealed a broad applicability of the technique, encompassing studies from large biomolecules to surface-modified polymers, depending on the nuclear spin diffusion rate with a range of gyromagnetic ratios.

Magnetstein: An Open-Source Tool for Quantitative NMR Mixture Analysis Robust to Low Resolution, Distorted Lineshapes, and Peak Shifts

1H NMR spectroscopy is a powerful tool for analyzing mixtures including determining the concentrations of individual components. When signals from multiple compounds overlap, this task requires computational solutions. They are typically based on peak-picking and the comparison of obtained peak lists with libraries of individual components. This can fail if peaks are not sufficiently resolved or when peak positions differ between the library and the mixture. In this paper, we present Magnetstein, a quantification algorithm rooted in the optimal transport theory that makes it robust to unexpected frequency shifts and overlapping signals. Thanks to this, Magnetstein can quantitatively analyze difficult spectra with the estimation trueness an order of magnitude higher than that of commercial tools. Furthermore, the method is easier to use than other approaches, having only two parameters with default values applicable to a broad range of experiments and requiring little to no preprocessing of the spectra.

Review on NMR as a tool to analyse natural products extract directly: Molecular structure elucidation and biological activity analysis

INTRODUCTION

Natural products, the small organic molecules produced by plants, microbes and invertebrates, often present in the form of a mixture, this leads to the structural characterisation of natural extracts often requiring time-consuming multistep purification procedures. Nuclear magnetic resonance (NMR) technology is traditionally utilised as a tool for the structural elucidation of pure compounds. Contemporarily, an up-to-date trend in the application of NMR in natural product research is shifting to the direct NMR analysis of crude mixtures, to obtain molecular structure and biological activity information without performing cumbersome separation.

OBJECTIVE

To review works of literature on the evolution, principle and progress of NMR technologies for analysing mixtures, we focus on the successful application of NMR technologies in direct analysis of natural product extracts.

METHODOLOGY

Based on our research experience, academic tracking and extensive literature search, which involved, but not limited to, the use of various databases, like Web of Knowledge and PubMed. The keywords used, in various combinations, to retrieve recent literature on the successful application of NMR technologies to sheer natural product extracts, and excluded artificially natural product mixture and biofluid.

RESULTS

NMR technologies for direct natural extracts analysis, including two-dimensional J-resolved spectroscopy (2D-JRES), pure shift NMR, diffusion-ordered NMR spectroscopy (DOSY), statistical correlation spectroscopy (STOCSY), concentration-ordered NMR spectroscopy (CORDY), saturation transfer difference (STD) and water-ligand observed via gradient spectroscopy (WaterLOGSY) were illustrated.

CONCLUSIONS

By these methods, molecular structure and biological activity information will be directly obtained from NMR analysis of natural products extract, aiming to save experimental time and expenses.

Solution-State 2D NMR Spectroscopy of Mixtures HyperpolarizedUsing Optically Polarized Crystals

The HYPNOESYS method (Hyperpolarized NOE System), which relies on the dissolution of optically polarized crystals, has recently emerged as a promising approach to enhance the sensitivity of NMR spectroscopy in the solution state. However, HYPNOESYS is a single-shot method that is not generally compatible with multidimensional NMR. Here we show that 2D NMR spectra can be obtained from HYPNOESYS-polarized samples, using single-scan acquisition methods. The approach is illustrated with a mixture of terpene molecules and a benchtop NMR spectrometer, paving the way to a sensitive, information-rich and affordable analytical method.

Machine learning-assisted structure annotation of natural products based on MS and NMR data

Covering: up to March 2023Machine learning (ML) has emerged as a popular tool for analyzing the structures of natural products (NPs). This review presents a summary of the recent advancements in ML-assisted mass spectrometry (MS) and nuclear magnetic resonance (NMR) data analysis to establish the chemical structures of NPs. First, ML-based MS/MS analyses that rely on library matching are discussed, which involves the utilization of ML algorithms to calculate similarity, predict the MS/MS fragments, and form molecular fingerprint. Then, ML assisted MS/MS structural annotation without library matching is reviewed. Furthermore, the cases of ML algorithms in assisting structural studies of NPs based on NMR are discussed from four perspectives: NMR prediction, functional group identification, structural categorization and quantum chemical calculation. Finally, the review concludes with a discussion of the challenges and the trends associated with the structural establishment of NPs based on ML algorithms.

Exploring Proton-Only NMR Experiments and Filters for Daphnia In Vivo: Potential and Limitations

Environmental metabolomics provides insight into how anthropogenic activities have an impact on the health of an organism at the molecular level. Within this field, in vivo NMR stands out as a powerful tool for monitoring real-time changes in an organism's metabolome. Typically, these studies use 2D ¹³C-¹H experiments on ¹³C-enriched organisms. Daphnia are the most studied species, given their widespread use in toxicity testing. However, with COVID-19 and other geopolitical factors, the cost of isotope enrichment increased ~6-7 fold over the last two years, making ¹³C-enriched cultures difficult to maintain. Thus, it is essential to revisit proton-only in vivo NMR and ask, "Can any metabolic information be obtained from Daphnia using proton-only experiments?". Two samples are considered here: living and whole reswollen organisms. A range of filters are tested, including relaxation, lipid suppression, multiple-quantum, J-coupling suppression, 2D ¹H-¹H experiments, selective experiments, and those exploiting intermolecular single-quantum coherence. While most filters improve the ex vivo spectra, only the most complex filters succeed in vivo. If non-enriched organisms must be used, then, DREAMTIME is recommended for targeted monitoring, while IP-iSQC was the only experiment that allowed non-targeted metabolite identification in vivo. This paper is critically important as it documents not just the experiments that succeed in vivo but also those that fail and demonstrates first-hand the difficulties associated with proton-only in vivo NMR.

Effect of sweeteners and carbonation on aroma partitioning and release in beverage systems

The effect of monosaccharides (glucose, fructose and galactose) and disaccharides (sucrose and lactose) at 10, 20 and 30 % w/v on the in-vitro aroma partitioning of C₄ - C₁₀ aldehydes and ethyl esters, as well as limonene (concentration of aroma compounds at 1 μg mL^-1), was studied using atmospheric pressure chemical ionisation-mass spectrometry. An increase in sugar concentration from 0 to 30 % w/v resulted in a significant increase in partitioning under static headspace conditions for the majority of the compounds (p < 0.05), an effect generally not observed when 10 % w/v sucrose was substituted with low-calorie sweeteners (p > 0.05). The complexity of the system was increased to model a soft drink design - comprising water, sucrose (10, 20 and 30 % w/v), acid (0.15 % w/v), carbonation (∼7.2 g/L CO₂) and aroma compounds representative of an apple style flavouring, namely ethyl butanoate and hexanal (10 μg mL^-1 each). Although the addition of sucrose had no significant in-vivo effect, carbonation significantly decreased breath-by-breath (in-vivo) aroma delivery (p < 0.05). To understand the physical mechanisms behind aroma release from the beverage matrix, the effect of sucrose on the kinetics of the matrix components was explored. An increase in sucrose concentration from 0 to 30 % w/v resulted in a significant decrease in water activity (p < 0.05), which accounted for the significantly slower rate of self-diffusion of aroma compounds (p < 0.05), measured using diffusion-ordered spectroscopy-nuclear magnetic resonance spectroscopy. No significant effect of sucrose on carbon dioxide volume flux was found (p > 0.05).

Unsupervised Analysis of Small Molecule Mixtures by Wavelet-Based Super-Resolved NMR

Resolving small molecule mixtures by nuclear magnetic resonance (NMR) spectroscopy has been of great interest for a long time for its precision, reproducibility, and efficiency. However, spectral analyses for such mixtures are often highly challenging due to overlapping resonance lines and limited chemical shift windows. The existing experimental and theoretical methods to produce shift NMR spectra in dealing with the problem have limited applicability owing to sensitivity issues, inconsistency, and/or the requirement of prior knowledge. Recently, we resolved the problem by decoupling multiplet structures in NMR spectra by the wavelet packet transform (WPT) technique. In this work, we developed a scheme for deploying the method in generating highly resolved WPT NMR spectra and predicting the composition of the corresponding molecular mixtures from their 1H NMR spectra in an automated fashion. The four-step spectral analysis scheme consists of calculating the WPT spectrum, peak matching with a WPT shift NMR library, followed by two optimization steps in producing the predicted molecular composition of a mixture. The robustness of the method was tested on an augmented dataset of 1000 molecular mixtures, each containing 3 to 7 molecules. The method successfully predicted the constituent molecules with a median true positive rate of 1.0 against the varying compositions, while a median false positive rate of 0.04 was obtained. The approach can be scaled easily for much larger datasets.

NMR methods for the analysis of mixtures

NMR spectroscopy is a powerful approach for the analysis of mixtures. Its usefulness arises in large part from the vast landscape of methods, and corresponding pulse sequences, that have been and are being designed to tackle the specific properties of mixtures of small molecules. This feature article describes a selection of methods that aim to address the complexity, the low concentrations, and the changing nature that mixtures can display. These notably include pure-shift and diffusion NMR methods, hyperpolarisation methods, and fast 2D NMR methods such as ultrafast 2D NMR and non-uniform sampling. Examples or applications are also described, in fields such as reaction monitoring and metabolomics, to illustrate the relevance and limitations of different methods.

Analysis of Small-Molecule Mixtures by Super-Resolved 1H NMR Spectroscopy

Analysis of small molecules is essential to metabolomics, natural products, drug discovery, food technology, and many other areas of interest. Current barriers preclude from identifying the constituent molecules in a mixture as overlapping clusters of NMR lines pose a major challenge in resolving signature frequencies for individual molecules. While homonuclear decoupling techniques produce much simplified pure shift spectra, they often affect sensitivity. Conversion of typical NMR spectra to pure shift spectra by signal processing without a priori knowledge about the coupling patterns is essential for accurate analysis. We developed a super-resolved wavelet packet transform based 1H NMR spectroscopy that can be used in high-throughput studies to reliably decouple individual constituents of small molecule mixtures. We demonstrate the efficacy of the method on the model mixtures of saccharides and amino acids in the presence of significant noise.

NMR-Based Approaches in the Study of Foods

In this review, the three different NMR-based approaches usually used to study foodstuffs are described, reporting specific examples. The first approach starts with the food of interest that can be investigated using different complementary NMR methodologies to obtain a comprehensive picture of food composition and structure; another approach starts with the specific problem related to a given food (frauds, safety, traceability, geographical and botanical origin, farming methods, food processing, maturation and ageing, etc.) that can be addressed by choosing the most suitable NMR methodology; finally, it is possible to start from a single NMR methodology, developing a broad range of applications to tackle common food-related challenges and different aspects related to foods.

Filtering the NMR Spectra of Mixtures by Coordination to Paramagnetic Cu2

The paramagnetic spin relaxation (PSR) filter allows the selective NMR signal suppression of components in mixtures according to their complexation ability to a paramagnetic ion. It relies on the faster relaxation of nuclei in paramagnetic environments and thus is complementary to classical diffusion and relaxation filters. So far, the PSR filter has established Gd³⁺ as the sole PSR agent, restricting the paramagnetic filtering repertoire. Herein, we present Cu²⁺ as a robust PSR agent with characteristic filtering properties. While Gd³⁺ depends on unspecific ion-pair interactions with anionic components, Cu²⁺ stands out for filtering species via ordered coordination complexes. An evaluation of the paramagnetic effect of Cu²⁺ over more than 50 small molecules and polymers has unveiled different sensitivities to Cu²⁺ (especially high for pyridines, diamines, polyamines, and amino alcohols) and precise filtering conditions for mixtures (¹H, COSY, and HMQC) that were challenged with a test bed of commercial drugs. The advantage of integrating Cu²⁺ and Gd³⁺ for the stepwise PSR filtering of complex mixtures is also shown.

Examples Showing the Utility of Doping Experiments in 1H NMR Analysis of Mixtures

Here we provide examples that demonstrate the value of using properly designed and easily performed doping experiments to give insights about the nature of the analyte(s) present in a ¹H NMR sample. Two mixtures, the first quite complex and the second far less so, have been chosen: (i) the crude pyrolysate from reaction of butyric acid in (supercritical) water at 600 °C and (ii) a mixture of two basic amines. In the former, 13 distinct carbonyl-containing compounds, ranging in relative concentration of nearly 2 orders of magnitude, were positively identified. The latter highlights the advantage of using a doping experiment as opposed to merely comparing the spectra from two separate samples containing the same analyte.

Recent Advances in Spectroscopic Techniques for the Analysis of Microplastics in Food

Microplastic pollution has become a worldwide concern in aquatic and terrestrial environments. Microplastics could also enter the food chain, causing potential harm to human health. To facilitate the risk assessment of microplastics to humans, it is critically important to have a reliable analytical technique to detect, quantify, and identify microplastics of various materials, sizes, and shapes from environmental, agricultural, and food matrices. Spectroscopic techniques, mainly vibrational spectroscopy (Raman and infrared), are commonly used techniques for microplastic analysis. This review focuses on recent advances of these spectroscopic techniques for the analysis of microplastics in food. The fundamental, recent technical advances of the spectroscopic techniques and their advantages and limitations were summarized. The food sample pretreatment methods and recent applications for detecting and quantifying microplastics in different types of food were reviewed. In addition, the current technical challenges and future research directions were discussed. It is anticipated that the advances in instrument development and methodology innovation will enable spectroscopic techniques to solve critical analytical challenges in microplastic analysis in food, which will facilitate the reliable risk assessment.

Sphingomyelin nanosystems loaded with uroguanylin and etoposide for treating metastatic colorectal cancer

Colorectal cancer is the third most frequently diagnosed cancer malignancy and the second leading cause of cancer-related deaths worldwide. Therefore, it is of utmost importance to provide new therapeutic options that can improve survival. Sphingomyelin nanosystems (SNs) are a promising type of nanocarriers with potential for association of different types of drugs and, thus, for the development of combination treatments. In this work we propose the chemical modification of uroguanylin, a natural ligand for the Guanylyl Cyclase (GCC) receptor, expressed in metastatic colorectal cancer tumors, to favour its anchoring to SNs (UroGm-SNs). The anti-cancer drug etoposide (Etp) was additionally encapsulated for the development of a combination strategy (UroGm-Etp-SNs). Results from in vitro studies showed that UroGm-Etp-SNs can interact with colorectal cancer cells that express the GCC receptor and mediate an antiproliferative response, which is more remarkable for the drugs in combination. The potential of UroGm-Etp-SNs to treat metastatic colorectal cancer cells was complemented with an in vivo experiment in a xenograft mice model.

Evaluation of the Rotating-Frame Relaxation (T1ρ) Filter and Its Application in Metabolomics as an Alternative to the Transverse Relaxation (T2) Filter

Nuclear magnetic resonance (NMR)-based metabolomic studies commonly involve the use of T2 filter pulse sequences to eliminate or attenuate the broad signals from large molecules and improve spectral resolution. In this paper, we demonstrate that the T1ρ filter-based pulse sequence represents an interesting alternative because it allows the stability and the reproducibility needed for statistical analysis. The integrity of the samples and the stability of the instruments were assessed for different filter durations and amplitudes. We showed that the T1ρ filter pulse sequence did not induce sample overheating for a filter duration of up to 500 ms. The reproducibility was evaluated and compared with the T2 filter in serum and liver samples. The implementation is relatively simple and provides the same statistical and analytical results as those obtained with the standard filters. Regarding tissues analysis, because the duration of the filter is the same as that of the spin-lock, the synchronization of the echo delays with the magic angle spinning (MAS) rate is no longer necessary as for T2 filter-based sequences. The results presented in this article aim at establishing a new protocol to improve metabolomic studies and pave the way for future developments on T1ρ alternative filters, in liquid and HR-MAS NMR experiments.

Matrix-Assisted DOSY for Analysis of Indole Alkaloid Mixtures

Diffusion-ordered spectroscopy (DOSY) is a powerful tool for investigating mixtures and identifying peaks of chemical components. However, similar diffusion coefficients of the components, particularly for complex mixtures that contain crowded resonances, limit resolution and restrict application of the DOSY technique. In this paper, matrix-assisted DOSY were used to explore whether the diffusion resolution of a complex model involving indole alkaloid mixtures can be realized. Furthermore, we investigated the influence of different factors on the separation effect. The results showed that the changes in diffusion coefficient differences were achieved more obviously when using sodium dodecyl sulfate (SDS) micelles as the matrix. In addition, we also found that increasing the concentration of SDS can improve the resolution of the DOSY spectrum. Finally, after investigating the influence factors and NMR conditions, we demonstrated the applications of the SDS-assisted DOSY on analyzing the total alkaloid extract of Alstonia Mairei, and the virtual separation of mixtures was achieved.

Amino Acid Ionic Liquids Catalyzed d-Glucosamine into Pyrazine Derivatives: Insight from NMR Spectroscopy

Using environment-friendly catalysts to convert biomass into compounds with high values is one of the central topics of green chemistry. In this work, [Ch][Pro] (cholinium as the cation and l-proline as the anion) ionic liquid was synthesized and applied as a model catalyst in the production of deoxyfructosazine (DOF) and fructosazine (FZ) from d-glucosamine (GlcNH₂). The ¹³C NMR chemical shift titration experiments and the diffusion-ordered NMR spectroscopy (DOSY) measurements showed that, when the [Ch][Pro] interacted with GlcNH₂, the l-proline anion ([Pro]^-) played a major catalytic role instead of cholinium cation ([Ch]⁺). The effects of the reaction temperature and the amount of [Ch][Pro] on the product yields were surveyed. The experimental results showed that the highest DOF yield (33.78%) was obtained after 30 min at 100 °C when the molar ratio of [Ch][Pro]/GlcNH₂ was 1. Moreover, in situ ¹H NMR and in situ ¹³C NMR experiments were applied to monitor the reaction process with [Ch][Pro] as the catalyst. The reactive intermediate, dihydrofructosazine, was clearly detected by these in situ techniques. Accordingly, a possible reaction pathway was proposed. By applying other amino acids as the anions, we also prepared five other [Ch][AA] ionic liquids, and they showed different catalytic activities and selectivity in the GlcNH₂ self-condensation reaction.

Circulating Metabolites as Potential Biomarkers for Neurological Disorders-Metabolites in Neurological Disorders

There are, still, limitations to predicting the occurrence and prognosis of neurological disorders. Biomarkers are molecules that can change in different conditions, a feature that makes them potential tools to improve the diagnosis of disease, establish a prognosis, and monitor treatments. Metabolites can be used as biomarkers, and are small molecules derived from the metabolic process found in different biological media, such as tissue samples, cells, or biofluids. They can be identified using various strategies, targeted or untargeted experiments, and by different techniques, such as high-performance liquid chromatography, mass spectrometry, or nuclear magnetic resonance. In this review, we aim to discuss the current knowledge about metabolites as biomarkers for neurological disorders. We will present recent developments that show the need and the feasibility of identifying such biomarkers in different neurological disorders, as well as discuss relevant research findings in the field of metabolomics that are helping to unravel the mechanisms underlying neurological disorders. Although several relevant results have been reported in metabolomic studies in patients with neurological diseases, there is still a long way to go for the clinical use of metabolites as potential biomarkers in these disorders, and more research in the field is needed.

In Vitro-In Silico Modeling Approach to Rationally Designed Simple and Versatile Drug Delivery Systems

Rational design and development of a nanosystem usually relies on empirical approaches as well as a fair degree of serendipity. Understanding how nanosystems behave at the molecular level is of great importance for potential biomedical applications. In this work, we describe a nanosystem composed of two natural compounds, vitamin E and sphingomyelin, prepared by spontaneous emulsification (vitamin E-sphingomyelin nanosystems (VSNs)). Extensive characterization revealed suitable physicochemical properties, very high biocompatibility in vitro and in vivo, and colloidal stability during storage and in biological media, all relevant properties for clinical translation. We have additionally pursued a computational approach to gain an improved understanding of the assembling, structure, dynamics, and drug-loading capacity of VSNs, using both small molecules and biomolecules (resveratrol, curcumin, gemcitabine, and two peptides). The spontaneous formation of compartmentalized VSNs starting from completely disassembled molecules, observed here for the first time, was accurately assessed from the computational molecular dynamics trajectories. We describe here a synergistic in silico/in vitro approach showing the predictive power of computational simulations for VSNs' structural characterization and description of internal interaction mechanisms responsible for the association of bioactive molecules, representing a paradigm shift in the rational design of nanotechnologies as drug delivery systems for advanced personalized medicine.

Genome mining as a biotechnological tool for the discovery of novel marine natural products

Compared to terrestrial environments, the oceans harbor a variety of environments, creating higher biodiversity, which gives marine natural products a high occurrence of significant biology and novel chemistry. However, traditional bioassay-guided isolation and purification strategies are severely limiting the discovery of additional novel natural products from the ocean. With an increasing number of marine microorganisms being sequenced, genome mining is gradually becoming a powerful tool to retrieve novel marine natural products. In this review, we have summarized genome mining approaches used to analyze key enzymes of biosynthetic pathways and predict the chemical structure of new gene clusters by introducing successful stories that used genome mining strategy to identify new marine-derived compounds. Furthermore, we also put forward challenges for genome mining techniques and their proposed solutions. The detailed analysis of the genome mining strategy will help researchers to understand this novel technique and its application. With the development of a genome sequence, genome mining strategies will be applied more widely, which will drive rapid development in the field of marine natural product development.

Simultaneous determination of artemisinin and its analogs and flavonoids in Artemisia annua crude extracts with the use of NMR spectroscopy

Artemisia annua is a promising and potent antimalarial herbal drug. This activity has been ascribed to its component artemisinin, a sesquiterpene lactone. The ability to determine artemisinin and its known analogs in plant extracts is an especially difficult task because the compounds are present in low concentrations, are thermolabile, and lack ultraviolet or fluorescent chromophores. We report herein a facile and rapid 1-D ¹ H, 1-D total correlation spectroscopy, 2-D ¹ H-¹³ C heteronuclear single quantum coherence, and ¹ H-¹³ C heteronuclear multiple bond correlation nuclear magnetic resonance techniques for the simultaneous identification and quantification of artemisinin and five of its analogs along with five flavonoids, an aromatic ketone, and camphor (in total, 13 compounds) in crude diethyl ether A. annua extract without the need of laborious isolation of the individual analytes. The above method was validated in terms of precision, linearity, and limit of detection. The analytical results were found to be in excellent agreement with those obtained with the use of the time consuming high-performance liquid chromatography with diode-array detection and liquid chromatography with tandem mass spectrometry for the compounds that standards were available.

Metabolomic tools used in marine natural product drug discovery

Introduction: The marine environment is a very promising resource for natural product research, with many of these reaching the market as new drugs, especially in the field of cancer therapy as well as the drug discovery pipeline for new antimicrobials. Exploitation for bioactive marine compounds with unique structures and novel bioactivity such as the isoquinoline alkaloid; trabectedin, the polyether macrolide; halichondrin B, and the peptide; dolastatin 10, requires the use of analytical techniques, which can generate unbiased, quantitative, and qualitative data to benefit the biodiscovery process. Metabolomics has shown to bridge this understanding and facilitate the development of new potential drugs from marine sources and particularly their microbial symbionts.Areas covered: In this review, articles on applied secondary metabolomics ranging from 1990-2018 as well as to the last quarter of 2019 were probed to investigate the impact of metabolomics on drug discovery for new antibiotics and cancer treatment.Expert opinion: The current literature review highlighted the effectiveness of metabolomics in the study of targeting biologically active secondary metabolites from marine sources for optimized discovery of potential new natural products to be made accessible to a R&D pipeline.

Improving the Sensitivity of FESTA Methods for the Analysis of Fluorinated Mixtures

The analysis of complex mixtures is an important but often intractable problem. When species contain sparse fluorine atoms, NMR spectra of fluorine-containing spin systems can be efficiently extracted from an intact mixture using the recently proposed FESTA (Fluorine-Edited Selective TOCSY Acquisition) methodology. Here an alternative approach to the existing selective reverse INEPT FESTA (SRI-FESTA) experiment is described, based on the use of a modulated spin echo for the initial excitation. MODO-FESTA (modulated echo FESTA) is simpler and has a significant sensitivity advantage over SRI-FESTA. Comparisons are presented of the relative sensitivity and spectral purity of the two types of methods.

Metabolomics in the Context of Plant Natural Products Research: From Sample Preparation to Metabolite Analysis

Plant-derived natural products have long been considered a valuable source of lead compounds for drug development. Natural extracts are usually composed of hundreds to thousands of metabolites, whereby the bioactivity of natural extracts can be represented by synergism between several metabolites. However, isolating every single compound from a natural extract is not always possible due to the complex chemistry and presence of most secondary metabolites at very low levels. Metabolomics has emerged in recent years as an indispensable tool for the analysis of thousands of metabolites from crude natural extracts, leading to a paradigm shift in natural products drug research. Analytical methods such as mass spectrometry (MS) and nuclear magnetic resonance (NMR) are used to comprehensively annotate the constituents of plant natural products for screening, drug discovery as well as for quality control purposes such as those required for phytomedicine. In this review, the current advancements in plant sample preparation, sample measurements, and data analysis are presented alongside a few case studies of the successful applications of these processes in plant natural product drug discovery.

Enhancing benchtop NMR spectroscopy by means of sample shifting

Benchtop NMR sensitivity enhancement by cyclic, mechanical shifting of a sample to preserve high nuclear spin polarization.

NMR-based metabolomics and fluxomics: developments and future prospects

Recent NMR developments are acting as game changers for metabolomics and fluxomics – a critical and perspective review.

NMR analysis of the Fischer-Tropsch wastewater: Combination of 1D selective gradient TOCSY, 2D DOSY and qNMR

The Fischer-Tropsch (FT) process is a practical approach to convert synthesis gas (CO and H₂) into hydrocarbons and oxygenates, and these product mixtures are usually well-characterized. However, the analysis of Fischer-Tropsch waste water (FTW) is still somewhat underdeveloped and the exact composition of FTW remains unclear. Herein, various qualitative NMR techniques, especially diffusion-ordered spectroscopy (DOSY) and one dimension (1D) selective gradient total correlation spectroscopy (SelTOCSY) were strategically applied in the analysis of FTW. The NMR results show that the DOSY technique can pseudo-separate most of components in complex mixtures over the diffusion dimension. The SelTOCSY technique is used as a supporting method in the cases where the DOSY technique cannot clearly distinguish overlapped signals. Moreover, the quantitative ¹H NMR (qNMR) was further used to quantify the components of the sample. These routine and advanced qualitative and quantitative NMR technique utilized here provide a fast, effective and feasible method for the identification of complex mixtures in FTW, which might be a powerful and fast alternative to gas chromatography or high performance liquid chromatography for FTW research.

1H HR-MAS NMR spectroscopy to study the metabolome of the protozoan parasite Giardia lamblia

Knowledge of the metabolic profile and exchange processes in the protozoan parasite Giardia lamblia is of importance for a better understanding of the biochemical processes and for the development of drugs to control diseases caused by G. lamblia. In the current paper, ¹H High Resolution Magic Angle Spinning (HR-MAS) NMR spectroscopy was directly applied to G. lamblia trophozoite suspensions to analyze the detectable small metabolites with a minimum of intervention. Thirty-one components were identified with main contributions from amino acids such as alanine and ornithine. The reproducibility, variability, and stability of the metabolites were investigated. Citrulline was found to be formed as an intermediate and citrulline levels depended on the stage of cell growth. Glucose-1-phosphate was found to be formed in relatively high amounts after cell harvesting if enzymes were not inactivated. In addition, the metabolic footprint of Giardia trophozoites, i.e. changes in the culture medium induced by G. lamblia, was investigated by liquid state NMR spectroscopy of culture media before and after inoculation. A quantitative comparison of the NMR spectra revealed component changes in the culture media during growth. The results suggested that not glucose but rather arginine serves as main energy supply. Biochemical functions of intracellular components and their metabolic exchange with the culture medium are discussed. The results provide an important basis for the design of HR-MAS NMR based metabolomic studies of G. lamblia in particular and any protozoan parasite samples in general.

Exploring the Role of Solvent on Carbohydrate-Aryl Interactions by Diffusion NMR-Based Studies

Carbohydrate-protein interactions play an important role in many molecular recognition processes. An exquisite combination of multiple factors favors the interaction of the receptor with one specific type of sugar, whereas others are excluded. Stacking CH-aromatic interactions within the binding site provide a relevant contribution to the stabilization of the resulting sugar-protein complex. Being experimentally difficult to detect and analyze, the key CH-π interaction features have been very often dissected using a variety of techniques and simple model systems. In the present work, diffusion NMR spectroscopy has been employed to separate the components of sugar mixtures in different solvents on the basis of their differential ability to interact through CH-π interactions with one particular aromatic cosolute in solution. The experimental data show that the properties of the solvent did also influence the diffusion behavior of the sugars present in the mixture, inhibiting or improving their separation. Overall, the results showed that, for the considered monosaccharide derivatives, their diffusion coefficient values and, consequently, their apparent molecular sizes and/or shapes depend on the balance between solute/cosolute as well as solute/solvent interactions. Thus, in certain media and in the presence of the aromatic cosolute, the studied saccharides that are more suited to display CH-π interactions exhibited a lower diffusion coefficient than the noncomplexing sugars in the mixture. However, when dissolved in another medium, the interaction with the solvent strongly competes with that of the aromatic cosolute.

Metabolomics applied to diabetes-lessons from human population studies

The 'classical' distribution of type 2 diabetes (T2D) across the globe is rapidly changing and it is no longer predominantly a disease of middle-aged/elderly adults of western countries, but it is becoming more common through Asia and the Middle East, as well as increasingly found in younger individuals. This global altered incidence of T2D is most likely associated with the spread of western diets and sedentary lifestyles, although there is still much debate as to whether the increased incidence rates are due to an overconsumption of fats, sugars or more generally high-calorie foods. In this context, understanding the interactions between genes of risk and diet and how they influence the incidence of T2D will help define the causative pathways of the disease. This review focuses on the use of metabolomics in large cohort studies to follow the incidence of type 2 diabetes in different populations. Such approaches have been used to identify new biomarkers of pre-diabetes, such as branch chain amino acids, and associate metabolomic profiles with genes of known risk in T2D from large scale GWAS studies. As the field develops, there are also examples of meta-analysis across metabolomics cohort studies and cross-comparisons with different populations to allow us to understand how genes and diet contribute to disease risk. Such approaches demonstrate that insulin resistance and T2D have far reaching metabolic effects beyond raised blood glucose and how the disease impacts systemic metabolism.

Capturing "Extraordinary" Soft-Assembled Charge-Like Polypeptides as a Strategy for Nanocarrier Design

The rational design of nanomedicines is a challenging task given the complex architectures required for the construction of nanosized carriers with embedded therapeutic properties and the complex interface of these materials with the biological environment. Herein, an unexpected charge-like attraction mechanism of self-assembly for star-shaped polyglutamates in nonsalty aqueous solutions is identified, which matches the ubiquitous "ordinary-extraordinary" phenomenon previously described by physicists. For the first time, a bottom-up methodology for the stabilization of these nanosized soft-assembled star-shaped polyglutamates is also described, enabling the translation of theoretical research into nanomaterials with applicability within the drug-delivery field. Covalent capture of these labile assemblies provides access to unprecedented architectures to be used as nanocarriers. The enhanced in vitro and in vivo properties of these novel nanoconstructs as drug-delivery systems highlight the potential of this approach for tumor-localized as well as lymphotropic delivery.

Advanced solvent signal suppression for the acquisition of 1D and 2D NMR spectra of Scotch Whisky

A simple and robust solvent suppression technique that enables acquisition of high-quality 1D 1 H nuclear magnetic resonance (NMR) spectra of alcoholic beverages on cryoprobe instruments was developed and applied to acquire NMR spectra of Scotch Whisky. The method uses 3 channels to suppress signals of water and ethanol, including those of 13 C satellites of ethanol. It is executed in automation allowing high throughput investigations of alcoholic beverages. On the basis of the well-established 1D nuclear Overhauser spectroscopy (NOESY) solvent suppression technique, this method suppresses the solvent at the beginning of the pulse sequence, producing pure phase signals minimally affected by the relaxation. The developed solvent suppression procedure was integrated into several homocorrelated and heterocorrelated 2D NMR experiments, including 2D correlation spectroscopy (COSY), 2D total correlation spectroscopy (TOCSY), 2D band-selective TOCSY, 2D J-resolved spectroscopy, 2D 1 H, 13 C heteronuclear single-quantum correlation spectroscopy (HSQC), 2D 1 H, 13 C HSQC-TOCSY, and 2D 1 H, 13 C heteronuclear multiple-bond correlation spectroscopy (HMBC). A 1D chemical-shift-selective TOCSY experiments was also modified. The wealth of information obtained by these experiments will assist in NMR structure elucidation of Scotch Whisky congeners and generally the composition of alcoholic beverages at the molecular level.

PALMA, an improved algorithm for DOSY signal processing

NMR is a tool of choice for the measurement of diffusion coefficients of species in solution.

Novel selective TOCSY method enables NMR spectral elucidation of metabolomic mixtures

Complex mixture analysis is routinely encountered in NMR-based investigations. With the aim of component identification, spectral complexity may be addressed chromatographically or spectroscopically, the latter being favored to reduce sample handling requirements. An attractive experiment is selective total correlation spectroscopy (sel-TOCSY), which is capable of providing tremendous spectral simplification and thereby enhancing assignment capability. Unfortunately, isolating a well resolved resonance is increasingly difficult as the complexity of the mixture increases and the assumption of single spin system excitation is no longer robust. We present TOCSY optimized mixture elucidation (TOOMIXED), a technique capable of performing spectral assignment particularly in the case where the assumption of single spin system excitation is relaxed. Key to the technique is the collection of a series of 1D sel-TOCSY experiments as a function of the isotropic mixing time (τ_m), resulting in a series of resonance intensities indicative of the underlying molecular structure. By comparing these τ_m-dependent intensity patterns with a library of pre-determined component spectra, one is able to regain assignment capability. After consideration of the technique's robustness, we tested TOOMIXED firstly on a model mixture. As a benchmark we were able to assign a molecule with high confidence in the case of selectively exciting an isolated resonance. Assignment confidence was not compromised when performing TOOMIXED on a resonance known to contain multiple overlapping signals, and in the worst case the method suggested a follow-up sel-TOCSY experiment to confirm an ambiguous assignment. TOOMIXED was then demonstrated on two realistic samples (whisky and urine), where under our conditions an approximate limit of detection of 0.6mM was determined. Taking into account literature reports for the sel-TOCSY limit of detection, the technique should reach on the order of 10μM sensitivity. We anticipate this technique will be highly attractive to various analytical fields facing mixture analysis, including metabolomics, foodstuff analysis, pharmaceutical analysis, and forensics.

Isotope-filtered nD NMR spectroscopy of complex mixtures to unravel the molecular structures of phenolic compounds in tagged soil organic matter

Unravelling structures of molecules contained in complex, chromatographically inseparable mixtures is a challenging task. Due to the number of overlapping resonances in NMR spectra of these mixtures, unambiguous chemical shift correlations attributable to individual molecules cannot be achieved and thus their structure determination is elusive by this technique. Placing a tag carrying an NMR active nucleus onto a subset of molecules enables (i) to eliminate signals from the non-tagged molecules, and (ii) to obtain a set of correlated chemical shifts and coupling constants belonging to a single molecular type. This approach provides an opportunity for structure determination without the need for compound separation. Focusing on the most abundant functional groups of natural organic matter molecules, the carboxyl and hydroxyl groups were converted into esters and ethers, respectively by introducing (13)CH3O groups. A set of (13)C-filtered nD NMR experiments was designed yielding structures/structural motives of tagged molecules. The relative sensitivity of these experiments was compared and a step-by-step guide how to use these experiments to analyse the structures of methylated phenolics is provided. The methods are illustrated using an operational fraction of soil organic matter, fulvic acid isolated from a Scottish peat bog. Analysis of 33 structures identified in this sample revealed a correlation between the position of the methoxy cross-peaks in the (1)H, (13)C HSQC spectra and the compound type. This information enables profiling of phenolic compounds in natural organic matter without the need to acquire a full set of experiments described here or access to high field cryoprobe NMR spectrometers.

Silica sol assisted chromatographic NMR spectroscopy for resolution of trans- and cis-isomers

Chromatographic NMR spectroscopy can separate the mixtures of species with significantly different molecular size, but generally fails for isomeric species. Herein, we reported the resolution of trans- and cis-isomers and their structural analogue, which are different in molecular shapes, but similar in mass, were greatly enhanced in the presence of silica sol. The mixtures of maleic acid, fumaric acid and succinic acid, and the mixtures of trans- and cis-1,2-cyclohexanedicarboxylic acids, were distinguished by virtue of their different degrees of interaction with silica sol. Moreover, we found mixed solvents could improve the spectral resolution of DOSY spectra of mixtures.

Advanced tools in marine natural drug discovery

Marine natural products (MNPs) remain promising drug sources with several marine-derived drugs having been successfully approved. Nevertheless, it is never a smooth sailing to seek bioactive compounds from marine environments, during which many challenges are need to be faced to, for example, discovering unique marine resources, reviving unculturable organisms outside the marine environment, distinguishing novel compounds from the known ones, and disclosing the function of MNPs and optimizing their pharmacological use. Herein we review some advanced techniques and methodologies that can be employed to deal with above challenges with the intent of inspiring the forthcoming efforts in MNPs discovery pipelines.