Mass spectrometry imaging guided molecular networking to expedite discovery and structural analysis of agarwood natural products

Study on the Anti-Inflammatory Mechanism of Coumarins in Peucedanum decursivum Based on Spatial Metabolomics Combined with Network Pharmacology

Peucedanum decursivum (Miq.) Maxim (P. decursivum) is a traditional Chinese medicinal plant with pharmacological effects such as anti-inflammatory and anti-tumor effects, the root of which is widely used as medicine. Determining the spatial distribution and pharmacological mechanisms of metabolites is necessary when studying the effective substances of medicinal plants. As a means of obtaining spatial distribution information of metabolites, mass spectrometry imaging has high sensitivity and allows for molecule visualization. In this study, matrix-assisted laser desorption mass spectrometry (MALDI-TOF-MSI) and network pharmacology were used for the first time to visually study the spatial distribution and anti-inflammatory mechanism of coumarins, which are metabolites of P. decursivum, to determine their tissue localization and mechanism of action. A total of 27 coumarins were identified by MALDI-TOF-MSI, which mainly concentrated in the cortex, periderm, and phloem of the root of P. decursivum. Network pharmacology studies have identified key targets for the anti-inflammatory effect of P. decursivum, such as TNF, PTGS2, and PRAKA. GO enrichment and KEGG pathway analyses indicated that coumarins in P. decursivum mainly participated in biological processes such as inflammatory response, positive regulation of protein kinase B signaling, chemical carcinogenesis receptor activation, pathways in cancer, and other biological pathways. The molecular docking results indicated that there was good binding between components and targets. This study provides a basis for understanding the spatial distribution and anti-inflammatory mechanism of coumarins in P. decursivum.

Utilizing metabolomics and network analysis to explore the effects of artificial production methods on the chemical composition and activity of agarwood

Introduction: Agarwood is a traditional aromatic southern medicine. It has a long history of being used in traditional Chinese aromatherapy to treat insomnia, anxiety and depression. Due to the scarcity of wild resources, people have planted trees successfully and begun to explore various agarwood-inducing techniques. This study comparative analysis of volatile metabolites in agarwood produced by various inducing techniques and its potential sleep-promoting, anti-anxiety and anti-depressant network pharmacological activities. Methods: A total of 23 batches of two types of agarwood were collected, one of which was produced by artificial techniques, including 6 batches of TongTi (TT) agarwood produced by "Agar-Wit" and 6 batches of HuoLao (HL) agarwood produced by "burning, chisel and drilling", while the other was collected from the wild, including 6 batches of BanTou (BT) agarwood with trunks broken due to natural or man-made factors and 5 batches of ChongLou (CL) agarwood with trunks damaged by moth worms. The study employed metabolomics combined with network analysis to compare the differences in volatile metabolites of agarwood produced by four commonly used inducing techniques, and explored their potential roles and possible action targets in promoting sleep, reducing anxiety, and alleviating depression. Results: A total of 147 volatile metabolites were detected in agarwood samples, mainly including small aromatic hydrocarbons, sesquiterpenes and 2-(2-phenylethyl) chromone and their pyrolysis products. The results showed composition of metabolites was minimally influenced by the agarwood induction method. However, their concentrations exhibited significant variations, with 17 metabolites showing major differences. The two most distinct metabolites were 6-methoxy-2-(2-phenylethyl) chromone and 6,7-dimethoxy-2-(2-phenylethyl) chromone. Among the volatile metabolites, 142 showed promising potential in treating insomnia, anxiety, and depression, implicating various biological and signaling pathways, predominantly ALB and TNF targets. The top three active metabolites identified were 2-(2-phenylethyl) chromone, 1,5-diphenylpent-1-en-3-one, and 6-methoxy-2-[2-(4'-methoxyphenyl) ethyl] chromone, with their relative content in the four types of agarwood being TT>HL>CL>BT. Conclusion: The differences in the content of 2-(2-phenylethyl) chromones suggest that they may be responsible for the varying therapeutic activities observed in different types of agarwood aromatherapy. This study offers theoretical support for the selection of agarwood in aromatherapy practices.

Molecular evolution and characterization of type III polyketide synthase gene family in Aquilaria sinensis

2-(2-Phenylethyl) chromone (PEC) and its derivatives are markers of agarwood formation and are also related to agarwood quality. However, the biosynthetic and regulatory mechanisms of PECs still remain mysterious. Several studies suggested that type III polyketide synthases (PKSs) contribute to PEC biosynthesis in Aquilaria sinensis. Furthermore, systematic studies on the evolution of PKSs in A. sinensis have rarely been reported. Herein, we comprehensively analyzed PKS genes from 12 plant genomes and characterized the AsPKSs in detail. A unique branch contained only AsPKS members was identified through evolutionary analysis, including AsPKS01 that was previously indicated to participate in PEC biosynthesis. AsPKS07 and AsPKS08, two tandem-duplicated genes of AsPKS01 and lacking orthologous genes in evolutionary models, were selected for their transient expression in the leaves of Nicotiana benthamiana. Subsequently, PECs were detected in the extracts of N. benthamiana leaves, suggesting that AsPKS07 and AsPKS08 promote PEC biosynthesis. The interaction between the promoters of AsPKS07, AsPKS08 and five basic leucine zippers (bZIPs) from the S subfamily indicated that their transcripts could be regulated by these transcription factors (TFs) and might further contribute to PECs biosynthesis in A. sinensis. Our findings provide valuable insights into the molecular evolution of the PKS gene family in A. sinensis and serve as a foundation for advancing PEC production through the bioengineering of gene clusters. Ultimately, this contribution is expected to shed light on the mechanism underlying agarwood formation.

Tandem mass spectrometry (MS/MS) molecular networking guided profiling of small molecules from Aquilaria sinensis (Lour.) Gilg leaves and their bioactivity evaluation

INTRODUCTION

Agarwood, a fragrant resinous wood mainly formed by Aquilaria spp., is used worldwide as a natural fragrance and traditional medicine. A large amount of Aquilaria sinensis (Lour.) Gilg leaves are underutilised during the process of the agarwood industry, and the development of A. sinensis leaves as tea has recently attracted more and more attention. However, the small molecule profile of A. sinensis leaves and their bioactivities has been rarely reported.

OBJECTIVE

To conduct a rapid untargeted liquid chromatography-mass spectrometry (LC-MS) analysis of A. sinensis leaves with a molecular networking (MN) strategy and evaluate its antioxidant and antidiabetic value.

METHOD

A MN-assisted tandem mass spectrometry (MS/MS) analysis strategy was used to investigate the small molecule profile of A. sinensis leaves. Additionally, the integration of antioxidant and α-glucosidase inhibitory assays with MN analysis was executed to expeditiously characterise the bioactive compounds for potential prospective application.

RESULTS

Five main chemical groups including phenol C-glycosides, organic acids, 2-(2-phenylethyl) chromones, benzophenone O-glycosides and flavonoids were rapidly revealed from the A. sinensis leaves. Eighty-one compounds were provisionally identified by comparing their MS/MS fragments with canonical pathways. The featured xanthone C-glycosides and benzophenone C-glycosides were recognised as the primary components of A. sinensis leaves. Several dimers and a trimer of mangiferin were reported firstly in A. sinensis leaves. Furthermore, 17 and 14 potential bioactive molecules were rapidly annotated from antioxidant and α-glucosidase inhibitory fraction, respectively.

CONCLUSION

Our findings will help expand the utilisation of A. sinensis leaves and thus promote the high-quality development of agarwood industry.

Activity labelled molecular networking fuels the antioxidation active molecules profile of Ginger

Ginger has been used as consumed food spice and folk medicine in daily life for thousands of years in various regions of the world. Considerable antioxidation is one of the major activities for Ginger to exhibit health-promoting effects. In this study, a bioinformatic workflow was developed to generate activity labelled molecular networking (ALMN) to fuel the antioxidation active molecules profile of Ginger. In ALMN, antioxidation activity data, which was defined as correlation (r and p value) between the relative abundance of a molecule in fractions and the activity level of each fraction, was labelled to feature-based molecular network to profile out antioxidation active molecules visually. Fragmentation tree was further computed as a complementary way to conduct high confidence structure annotations of antioxidation active molecules. Consequently, 48 molecules were prioritized as antioxidation active molecules from 11,720 metabolite molecules of Ginger in a systematical way.

Rapid screening and characterization of 2-(2-phenylethyl)chromones in agarwood by UHPLC-Q-Exactive Orbitrap-MS

The purpose of this study is to develop an improved comprehensive data filtering strategy, which was implemented primarily through the Microsoft Office platform's Excel software for rapid screening of potential 2-(2-phenylethyl)chromone (PEC) monomers and their dimers (PEC dimers) obtained from agarwood. A total of 108 PEC monomers and 30 PEC dimers in agarwood were characterized. In conclusion, the results obtained in this work could provide useful information for the future utilization of agarwood. In particular, it is the first time to conduct an in-depth analysis of the MS/MS fragmentation behavior of a large number of PEC monomers and PEC dimers, including the identification of substituent positions of them. The proposed data filtering strategy could improve the comprehensive characterization efficiency of complex components in spices.

Screening of potential chemical marker with interspecific differences in Pterocarpus wood and a spatially-resolved approach to visualize the distribution of the characteristic markers

Profiling the spatial distributions and tissue changes of characteristic compounds with interspecific differences is critical to elucidate the complex species identification during tree species traceability, wood anti-counterfeiting verification and timber trade control. In this research, in order to visualize the spatial position of characteristic compounds in two species with similar morphology (Pterocarpus santalinus and Pterocarpus tinctorius), a high coverage MALDI-TOF-MS imaging method was used to found the mass spectra fingerprints of different wood species. 2-Mercaptobenzothiazole matrix was used to spray wood tissue section to enhance the detection effect of metabolic molecules, and the mass spectrometry imaging data were obtained. Based on this technology, the spatial location of fifteen potential chemical markers with remarkable interspecific differences in 2 Pterocarpus timber species were successfully obtained. Distinct chemical signatures obtained from this method can promote rapid identification at the wood species level. Thus, matrix-assisted laser desorption/time-of-flight/ionization mass spectrometry imaging (MALDI-TOF-MSI) provides a spatial-resolved way for traditional wood morphological classification and breaking through the limitations of traditional wood identification technology.

The Effect of Chinese Agarwood Essential Oil with Cyclodextrin Inclusion against PCPA-Induced Insomnia Rats

OBJECTIVE

To study the extraction process of agarwood active ingredients (AA) and investigate the safety and effectiveness of AA in the treatment of insomnia rats by nasal administration.

METHOD

A β-cyclodextrin (β-CD) inclusion compound (a-β-CD) was prepared from agarwood essential oil (AEO), and the preparation process was optimized and characterized. The safety of AA in nasal mucosa was evaluated through Bufo gargarizans maxillary mucosa and rat nasal mucosa models. Insomnia animal models were replicated by injecting p-chlorophenylalanine (PCPA), conducting behavioral tests, and detecting the expression levels of monoamine neurotransmitters (NE and 5-HT) and amino acids (GABA/Glu) in the rat hypothalamus.

RESULTS

The optimum inclusion process conditions of β-CD were as follows: the feeding ratio was 0.35:1.40 (g:g), the inclusion temperature was 45 °C, the inclusion time was 2 h, and the ICY% and IEO% were 53.78 ± 2.33% and 62.51 ± 3.21%, respectively. The inclusion ratio, temperature, and time are the three factors that have significant effects on the ICY% and IEO% of a-β-CD. AA presented little damage to the nasal mucosa. AA increased the sleep rate, shortened the sleep latency, and prolonged the sleep time of the rats. The behavioral test results showed that AA could ameliorate depression in insomnia rats to a certain extent. The effect on the expression of monoamine neurotransmitters and amino acids in the hypothalamus of rats showed that AA could significantly reduce NE levels and increase the 5-HT level and GABA/Glu ratio in the hypothalamus of insomnia rats.

CONCLUSION

The preparation of a-β-CD from AEO can reduce its irritation, improve its stability, increase its curative effect, and facilitate its storage and transport. AA have certain therapeutic effects on insomnia. The mechanism of their effect on rat sleep may involve regulating the expression levels of monoamine neurotransmitters and amino acids in the hypothalamus.

Mass spectrometry imaging: new eyes on natural products for drug research and development

Natural products (NPs) and their structural analogs represent a major source of novel drug development for disease prevention and treatment. The development of new drugs from NPs includes two crucial aspects. One is the discovery of NPs from medicinal plants/microorganisms, and the other is the evaluation of the NPs in vivo at various physiological and pathological states. The heterogeneous spatial distribution of NPs in medicinal plants/microorganisms or in vivo can provide valuable information for drug development. However, few molecular imaging technologies can detect thousands of compounds simultaneously on a label-free basis. Over the last two decades, mass spectrometry imaging (MSI) methods have progressively improved and diversified, thereby allowing for the development of various applications of NPs in plants/microorganisms and in vivo NP research. Because MSI allows for the spatial mapping of the production and distribution of numerous molecules in situ without labeling, it provides a visualization tool for NP research. Therefore, we have focused this mini-review on summarizing the applications of MSI technology in discovering NPs from medicinal plants and evaluating NPs in preclinical studies from the perspective of new drug research and development (R&D). Additionally, we briefly reviewed the factors that should be carefully considered to obtain the desired MSI results. Finally, the future development of MSI in new drug R&D is proposed.

Discovery of Biomarkers and Potential Mechanisms of Agarwood Incense Smoke Intervention by Untargeted Metabolomics and Network Pharmacology

Background

Agarwood, as a traditional Chinese medicine, has great potential value for the treatment of tranquilization. However, its potential mechanisms and biomarkers are still unclear.

Methods

In this study, ultra-high performance liquid chromatography-quadrupole-Exactive Orbitrap mass spectrometry (UHPLC-Q-Exactive Orbitrap-MS)-based metabonomics was adopted to discover the potential biomarkers in mice after agarwood incense smoke (AIS) intervention. Furthermore, the chemical components in agarwood were identified based on UHPLC-Q-Exactive Orbitrap-MS. The global view of potential compound-target-pathway (C-T-B) network was constructed through network pharmacology to understand the potentially material basis of biomarkers.

Results

Metabolic profiling indicated that the metabolic changed significantly in mice serum after AIS intervention. A total of 18 potential biomarkers closely related to insomnia and emotional disease were identified, mainly involving in tryptophan metabolism, arginine and proline metabolism, cysteine and methionine metabolism and steroid hormone biosynthesis pathways. A total of 138 components in agarwood were identified based on UHPLC-Q-Exactive Orbitrap-MS. The results showed that mainly compounds such as flidersia type 2-(2-phenylethyl) chromones (FTPECs) and sesquiterpenes exerted good docking abilities with key target proteins, which were involved in multiple diseases including depression and hypnosis.

Conclusion

In conclusion, this study enhanced current understanding of the change of metabolic markers after AIS intervention. Meanwhile, it also confirmed the feasibility of combining metabolomics and network pharmacology to identify active components and elucidate the material basis of biomarkers and mechanisms.

The application of mass spectrometry imaging in traditional Chinese medicine: a review

Mass spectrometry imaging is a frontier technique which connects classical mass spectrometry with ion imaging. Various types of chemicals could be visualized in their native tissues using mass spectrometry imaging. Up to now, the most commonly applied mass spectrometry imaging techniques are matrix assisted laser desorption ionization mass spectrometry imaging, desorption electrospray ionization mass spectrometry imaging and secondary ion mass spectrometry imaging. This review gives an introduction to the principles, development and applications of commonly applied mass spectrometry imaging techniques, and then illustrates the application of mass spectrometry imaging in the investigation of traditional Chinese medicine. Recently, mass spectrometry imaging has been adopted to explore the spatial distribution of endogenous metabolites in traditional Chinese medicine. Data collected from mass spectrometry imaging can be further utilized to search for marker components of traditional Chinese medicine, discover new compounds from traditional herbs, and differentiate between medicinal plants that are similar in botanical features. Moreover, mass spectrometry imaging also plays a role in revealing the pharmacological and toxicological mechanisms of traditional Chinese medicine.

Tissue Structure Changes of Aquilaria sinensis Xylem after Fungus Induction

In this study, we analyzed the mechanism and the process of fungal-induced agarwood formation in Aquilaria sinensis and studied the functional changes in the xylem structure after the process. The microscopic structure of the white zone, transition zone, agarwood zone, and decay zone of 12-and 18-months of inoculation A. sinensis xylem was studied. The distribution of nuclei, starch grains, soluble sugars, sesquiterpenes, fungal propagules, and mycelium in xylem tissues was investigated by histochemical analysis. The results show that the process of agarwood formation was accompanied by apoptosis of parenchyma cells such as interxylary phloem, xylem rays, and axial parenchyma. Regular changes in the conversion of starch grains to soluble sugars, the production of sesquiterpenoids, and other characteristic components of agarwood in various types of parenchyma cells were also observed. The material transformation was concentrated in the interxylary phloem, providing a structural and material basis for the formation of agarwood. It is the core part of the production of sesquiterpenoids and other characteristic products of agarwood. Compared with the A. sinensis inoculated for 12 months, the xylem of the A. sinensis inoculated for 18 months was more vigorous. There were no significant differences between the 12 and 18 months of inoculation in terms of sugars and agarwood characteristic products. In production, harvesting after 12 months of inoculation can improve harvesting efficiency.

Tracing the migration and transformation of metabolites in xylem during wood growth by mass spectrometry imaging

MALDI MSI was used to explore the rule of metabolite migration and transformation for the first time. The rules of heartwood formation and resin secretion were visualized and fully explored.

An integrated chemical characterization based on FT-NIR, GC-MS and LC-MS for the comparative metabolite profiling of wild and cultivated agarwood

Agarwood is a well-known and precious traditional Chinese medicine, has been widely applied as drugs and spices for century. The large demand for this material has deeply stimulated the emergence of numerous cultivated products. However, it is difficult to distinguish wild agarwood from cultivated agarwood, and the chemical composition difference between them is not clear. In this study, an integrated method of Fourier transform near-infrared (FT-NIR), gas chromatography-mass spectrometry (GC-MS) and ultraperformance liquid chromatography Quadrupole-Exactive Orbitrap tandem mass spectrometry (UHPLC-Q-Exactive Orbitrap/MS) was developed to explore chemical variation between wild and cultivated agarwood in combination with multivariate statistical analysis. Twenty-four wild and cultivated agarwood samples were collected from different regions. FT-NIR profiles were used to obtain the holistic metabolic characterization in combination with principal component analysis (PCA). A total of seventy-six and seventy-nine metabolites, including volatile components and 2-(2-phenethyl) chromones derivatives, were successfully identified by GC-MS and UHPLC-Q-Exactive Orbitrap/MS, respectively. Thereafter, the orthogonal-partial least square method-discriminant analysis (OPLS-DA) and variable importance in the projection (VIP) were used to screen potential characteristic chemical components (VIP > 1) in wild and cultivated agarwood, respectively. Finally, eight key chemical markers were putatively identified by two techniques to distinguish agarwood from different origins, which can be found that sesquiterpenes, aromatics, terpenoids, 2-(2-phenylethyl) chromones of the flidersia type (FTPECs) and tetrahydro-2-(2-phenylethyl) chromones (THPECs) are the most important metabolites. Summary, this research presented a comprehensive metabolomic variation between wild and cultivated agarwood on the basis of a multi-technology platform, which laid a foundation for distinguishing the two ecotypes of agarwood and was conducive to the quality control of this resource.

Artificial intelligence-guided discovery of anticancer lead compounds from plants and associated microorganisms

Plants and associated microorganisms are essential sources of natural products against human cancer diseases, partly exemplified by plant-derived anticancer drugs such as Taxol (paclitaxel). Natural products provide diverse mechanisms of action and can be used directly or as prodrugs for further anticancer optimization. Despite the success, major bottlenecks can delay anticancer lead discovery and implementation. Recent advances in sequencing and omics-related technology have provided a mine of information for developing new therapeutics from natural products. Artificial intelligence (AI), including machine learning (ML), has offered powerful techniques for extensive data analysis and prediction-making in anticancer leads discovery. This review presents an overview of current AI-guided solutions to discover anticancer lead compounds, focusing on natural products from plants and associated microorganisms.

Combination of untargeted metabolomics approach and molecular networking analysis to identify unique natural components in wild Morchella sp. by UPLC-Q-TOF-MS

Morchella sp. is a typical edible fungus. However, its unique natural products, especially bioactive composition, are rarely reported. In this study, an untargeted metabolomics approach combined with multivariate statistical analysis was employed to screen the differential metabolites in Morchella sp. compared to four other edible fungi. Among the screened 50-top differential metabolites, 18 compounds involving fatty acids and peptides showed higher content in Morchella sp.. A unique peptide of desferriferricrocin was identified. Subsequently, molecular networking analysis revealed three novel homologous compounds of desferriferricrocin, which were annotated as desferriferrichrome, desferriferrichrome C, and a new homolog not previously reported. These results were further verified by quantitative analysis. To the best of our knowledge, this is the first report of four peptides in Morchella sp..

Mass spectrometry imaging for direct visualization of components in plants tissues

Mass spectrometry is considered the most informative technique for components identification and has been widely adopted in plant sciences. However, the spatial distribution of compounds in the plant, which is vital for the exploration of plant physiological mechanisms, is missed in MS analysis. In recent years, mass spectrometry imaging has brought a great breakthrough in plant analysis because it can determine both the molecular compositions and spatial distributions, which is conducive to understand functions and regulation pathways of specific components in plants. Mass spectrometry imaging analysis of plant tissue is toward high sensitivity, high spatial resolution, and even single-cell analysis. Despite many challenges and technical barriers, such as difficulties of sample pretreatment caused by morphological diversity of plant tissues, obstacles for high spatial resolution imaging, and so on, lots of researches have contributed to remarkable progress, including improvement in tissue preparation, matrix innovation, and ionization mode development. This review focuses on the advances of mass spectrometry imaging analysis of plants in the last 5 years, including commonly used ionization techniques, technical advances, and recent applications of mass spectrometry imaging in plants.

The combination of UHPLC-HRMS and molecular networking improving discovery efficiency of chemical components in Chinese Classical Formula

Background

It is essential to identify the chemical components for the quality control methods establishment of Chinese Classical Formula (CCF). However, CCF are complex mixture of several herbal medicines with huge number of different compounds and they are not equal to the combination of chemical components from each herb due to particular formula ratio and preparation techniques. Therefore, it is time-consuming to identify compounds in a CCF by analyzing the LC–MS/MS data one by one, especially for unknown components.

Methods

An ultra-high pressure liquid chromatography-linear ion trap-orbitrap high resolution mass spectrometry (UHPLC-LTQ-Orbitrap-MS/MS) approach was developed to comprehensively profile and characterize multi-components in CCF with Erdong decoction composed of eight herbal medicines as an example. Then the MS data of Erdong decoction was analyzed by MS/MS-based molecular networking and these compounds with similar structures were connected to each other into a cluster in the network map. Then the unknown compounds connected to known compounds in a cluster of the network map were identified due to their similar structures.

Results

Based on the clusters of the molecular networking, 113 compounds were rapidly tentative identification from Erdong decoction for the first time in the negative mode, which including steroidal saponins, triterpenoid saponins, flavonoid O-glycosides and flavonoid C-glycosides. In addition, 10 alkaloids were tentatively identified in the positive mode from Nelumbinis folium by comparison with literatures.

Conclusion

MS/MS-based molecular networking technique is very useful for the rapid identification of components in CCF. In Erdong decoction, this method was very suitable for the identification of major steroidal saponins, triterpenoid saponins, and flavonoid C-glycosides.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13020-021-00459-6.

Chemical similarity methods for analyzing secondary metabolite structures

The relation that exists between the structure of a compound and its function is an integral part of chemoinformatics. The similarity principle states that “structurally similar molecules tend to have similar properties and similar molecules exert similar biological activities”. The similarity of the molecules can either be studied at the structure level or at the descriptor level (properties level). Generally, the objective of chemical similarity measures is to enhance prediction of the biological activities of molecules. In this article, an overview of various methods used to compare the similarity between metabolite structures has been provided, including two-dimensional (2D) and three-dimensional (3D) approaches. The focus has been on methods description; e.g. fingerprint-based similarity in which the molecules under study are first fragmented and their fingerprints are computed, 2D structural similarity by comparing the Tanimoto coefficients and Euclidean distances, as well as the use of physiochemical properties descriptor-based similarity methods. The similarity between molecules could also be measured by using data mining (clustering) techniques, e.g. by using virtual screening (VS)-based similarity methods. In this approach, the molecules with the desired descriptors or /and structures are screened from large databases. Lastly, SMILES-based chemical similarity search is an important method for studying the exact structure search, substructure search and also descriptor similarity. The use of a particular method depends upon the requirements of the researcher.

Reaction Tracking and High-Throughput Screening of Active Compounds in Combinatorial Chemistry by Tandem Mass Spectrometry Molecular Networking

Combinatorial synthesis has been widely used as an efficient strategy to screen for active compounds. Mass spectrometry is the method of choice in the identification of hits resulting from high-throughput screenings due to its high sensitivity, specificity, and speed. However, manual data processing of mass spectrometry data, especially for structurally diverse products in combinatorial chemistry, is extremely time-consuming and one of the bottlenecks in this process. In this study, we demonstrated the effectiveness of a tandem mass spectrometry molecular networking-based strategy for product identification, reaction dynamics monitoring, and active compound targeting in combinatorial synthesis. Molecular networking connects compounds with similar tandem mass spectra into a cluster and has been widely used in natural products analysis. We show that both the expected and side products can be readily characterized using molecular networking based on their mass spectrometry fragmentation patterns. Additionally, time-dependent molecular networking was integrated to track reaction dynamics to determine the optimal reaction time to maximize target product yields. We also present a proof-of-concept experiment that successfully identified and isolated active molecules from a dynamic combinatorial library. These results demonstrated the potential of using molecular networking for identifying, tracking, and high-throughput screening of active compounds in combinatorial synthesis.

Nematode-Trapping Fungi Produce Diverse Metabolites during Predator-Prey Interaction

Nematode-trapping fungi are natural antagonists of nematodes. These predatory fungi are capable of switching their lifestyle from a saprophytic to predatory stage in the presence of nematodes by developing specialized trapping devices to capture and consume nematodes. The biochemical mechanisms of such predator–prey interaction have become increasingly studied given the potential application of nematode-trapping fungi as biocontrol agents, but the involved fungal metabolites remain underexplored. Here, we report a comprehensive liquid–chromatography mass spectrometry (LC–MS) metabolomics study on one hundred wild isolates of nematode-trapping fungi in three different species, Arthrobotrysoligospora, Arthrobotrys thaumasia, and Arthrobotrys musiformis. Molecular networking analysis revealed that the fungi were capable of producing thousands of metabolites, and such chemical diversity of metabolites was notably increased as the fungi switched lifestyle to the predatory stage. Structural annotations by tandem mass spectrometry revealed that those fungal metabolites belonged to various structural families, such as peptide, siderophore, fatty alcohol, and fatty acid amide, and their production exhibited species specificity. Several small peptides (<1.5 kDa) produced by A.musiformis in the predatory stage were found, with their partial amino acid sequences resolved by the tandem mass spectra. Four fungal metabolites (desferriferrichrome, linoleyl alcohol, nonadecanamide, and citicoline) that were significantly enriched in the predatory stage were identified and validated by chemical standards, and their bioactivities against nematode prey were assessed. The availability of the metabolomics datasets will facilitate comparative studies on the metabolites of nematode-trapping fungi in the future.