High-throughput functional annotation of natural products by integrated activity profiling.

Determining mechanism of action (MOA) is one of the biggest challenges in natural products discovery. Here, we report a comprehensive platform that uses Similarity Network Fusion (SNF) to improve MOA predictions by integrating data from the cytological profiling high-content imaging platform and the gene expression platform Functional Signature Ontology, and pairs these data with untargeted metabolomics analysis for de novo bioactive compound discovery. The predictive value of the integrative approach was assessed using a library of target-annotated small molecules as benchmarks. Using Kolmogorov-Smirnov (KS) tests to compare in-class to out-of-class similarity, we found that SNF retains the ability to identify significant in-class similarity across a diverse set of target classes, and could find target classes not detectable in either platform alone. This confirmed that integration of expression-based and image-based phenotypes can accurately report on MOA. Furthermore, we integrated untargeted metabolomics of complex natural product fractions with the SNF network to map biological signatures to specific metabolites. Three examples are presented where SNF coupled with metabolomics was used to directly functionally characterize natural products and accelerate identification of bioactive metabolites, including the discovery of the azoxy-containing biaryl compounds parkamycins A and B. Our results support SNF integration of multiple phenotypic screening approaches along with untargeted metabolomics as a powerful approach for advancing natural products drug discovery.

Structural elucidation of 14-membered ring macrolide antibiotics using electrospray ionization tandem mass spectrometry and density functional theory calculations.

RATIONALE: Macrolides are critical antibiotics featuring a macrocyclic lactone core with deoxy sugars. Understanding their gas-phase fragmentation is challenging but essential for improving structural elucidation in mass spectrometry, which has implications for drug discovery and development. METHODS: We used electrospray ionization collision-induced dissociation tandem mass spectrometry (ESI-CID-MS) combined with quantum chemical calculations to investigate the fragmentation pathways of erythromycin A and roxithromycin. This approach helps elucidate the preferred fragmentation routes influenced by protonation sites. RESULTS: Macrolides showed similar fragmentation patterns, including sequential losses of saccharide or amino sugar units and dehydration from the macrocycle core. Multiple competitive pathways were observed, influenced by protonation sites. Computational studies confirmed the most favorable protonation sites and their impact on fragmentation, providing insights into key diagnostic product ions. Subsequent fragments involved rearrangement pathways such as alkene formation and cleavages via remote hydrogen transfers and pericyclic reactions. CONCLUSIONS: Our integrated approach offers a comprehensive understanding of macrolide fragmentation, enhancing structural elucidation and potential applications in drug development. This study advances mass spectrometry analysis of macrolides, contributing to pharmaceutical research by integrating orthogonal annotation methods and fragmentation studies.

Evaluation of Ion Mobility Spectrometry for Improving Constitutional Assignment in Natural Product Mixtures.

The comprehensive chemical characterization of biological samples remains a central challenge in the field of natural products. Conventional workflows using liquid chromatography (LC)-coupled high-resolution tandem mass spectrometry (MS/MS or MS2) allow the detection of relevant small molecules while providing diagnostic fragment ions for their structural assignment. Still, many natural product extracts are of a molecular complexity that challenges the resolving power of modern LC-MS2 pipelines. In this study, we examined the effect of integrating ion mobility spectrometry (IMS) to our LC-MS2 platform for the characterization of natural product mixtures. IMS provides an additional axis of separation in the gas phase as well as experimental collision cross-sectional (CCS) values. We analyzed a mixture of 20 commercial standards at 2 concentration ranges, either solubilized in solvent or spiked into an actinobacterial extract. Data were acquired in positive ion mode using both data-dependent acquisition (DDA) and data-independent acquisition (DIA) MS2 fragmentation approaches and assessed for both chemical coverage and spectral quality. IMS-DIA identified the largest number of standards in the spiked extract at the lower concentration of standards (17), followed by IMS-DDA (10), DDA (8), and DIA (6). In addition, we examined how these data sets performed in the Global Natural Products Social Molecular Networking (GNPS) platform. Overall, integrating IMS increased both metabolite detection and the quality of MS2 spectra, particularly for samples analyzed in DIA mode.

Characterization of aporphine alkaloids by electrospray ionization tandem mass spectrometry and density functional theory calculations.

RATIONALE: Aporphine alkaloids represent a large group of isoquinoline natural products with important roles in biological and biomedical areas. Their characterization by electrospray ionization tandem mass spectrometry (ESI-MS/MS) can contribute to their rapid identification in complex biological matrices. METHODS: We report the fragmentation of protonated 7,7-dimethylaporphine alkaloids by ESI-MS/MS, and the putative annotation of aporphine alkaloids in plant extracts. We used low- and high-resolution MS/MS analyses to rationalize the fragmentation pathways, and employed the B3LYP/6-31 + G(d,p) density functional theory (DFT) model to provide thermochemical parameters and to obtain the reactive sites. RESULTS: DFT calculations of a set of 7,7-dimethylaporphine alkaloids suggested the heterocyclic amino group as the most basic site due to the proton affinity of the nitrogen atom. Collision-induced dissociation experiments promoted • OCH3 elimination instead of the expected neutral loss of the heterocyclic amino group, pointing to the [M - 15 + H]•+ ion as the diagnostic fragment for 7,7-dimethylaporphine alkaloids. The analysis of plant extracts led to the annotation of 25 aporphine alkaloids. Their fragmentation initiated with the loss of the amino group followed by formation of a cyclic carbocation. Further reactions derived from consecutive charge-remote and/or charge-induced fragmentations of the substituents attached to the aromatic system. The mechanisms were re-examined based on plausible gas-phase ion chemistry reactions. CONCLUSIONS: Taken together, the diagnostic product ions and the series of radical and neutral eliminations provided information about the location of methylenedioxy, aromatic methoxy, and vicinal methoxy and hydroxy groups in aporphine alkaloids, assisting their characterization via MS/MS.

Naturally occurring fluorescence in frogs.

Fluorescence, the absorption of short-wavelength electromagnetic radiation reemitted at longer wavelengths, has been suggested to play several biological roles in metazoans. This phenomenon is uncommon in tetrapods, being restricted mostly to parrots and marine turtles. We report fluorescence in amphibians, in the tree frog Hypsiboas punctatus, showing that fluorescence in living frogs is produced by a combination of lymph and glandular emission, with pigmentary cell filtering in the skin. The chemical origin of fluorescence was traced to a class of fluorescent compounds derived from dihydroisoquinolinone, here named hyloins. We show that fluorescence contributes 18-29% of the total emerging light under twilight and nocturnal scenarios, largely enhancing brightness of the individuals and matching the sensitivity of night vision in amphibians. These results introduce an unprecedented source of pigmentation in amphibians and highlight the potential relevance of fluorescence in visual perception in terrestrial environments.

Mass Spectral Similarity Networking and Gas-Phase Fragmentation Reactions in the Structural Analysis of Flavonoid Glycoconjugates.

Flavonoids represent an important class of natural products with a central role in plant physiology and human health. Their accurate annotation using untargeted mass spectrometry analysis still relies on differentiating similar chemical scaffolds through spectral matching to reference library spectra. In this work, we combined molecular network analysis with rules for fragment reactions and chemotaxonomy to enhance the annotation of similar flavonoid glyconjugates. Molecular network topology progressively propagated the flavonoid chemical functionalization according to collision-induced dissociation (CID) reactions, as the following chemical attributes: aglycone nature, saccharide type and number, and presence of methoxy substituents. This structure-based distribution across the spectral networks revealed the chemical composition of flavonoids across intra- and interspecies and guided the putatively assignment of 64 isomers and isobars in the Chrysobalanaceae plant species, most of which are not accurately annotated by automated untargeted MS2 matching. These proof of concept results demonstrate how molecular networking progressively grouped structurally related molecules according to their product ion scans, abundances, and ratios. The approach can be extrapolated to other classes of metabolites sharing similar structures and diagnostic fragments from tandem mass spectrometry.

Dereplication of Flavonoid Glycoconjugates from Adenocalymma imperatoris-maximilianii by Untargeted Tandem Mass Spectrometry-Based Molecular Networking.

The interpretation of large datasets acquired using high performance liquid chromatography coupled with tandem mass spectrometry represents one of the major challenges in natural products research. Here we propose the use of molecular networking to rapid identify the known secondary metabolites from untargeted MS/MS analysis of Adenocalymma imperatoris-maximilianii plant extracts. The leaves, stems and roots of A. imperatoris-maximilianii were extracted using different solvents according to Snyder selectivity triangle. The samples were analyzed by HPLC coupled with ion trap mass spectrometer in a collision-induced dissociation MS/MS configuration in both positive and negative electrospray ionization modes. Molecular networking simultaneously organized the spectra by cosine similarity. The chemical identification was performed based on the systematic study of the main fragmentation pathways observed for the resulting network. The untargeted tandem mass spectrometry-based molecular networking allowed for the identification of 63 metabolites, mainly mono-, di- and tri-, C- and/or O-glycosyl flavones. Molecular networking was capable not only to dereplicate known flavonoids, but also to point out related prenyl derivatives, described for the first time in Adenocalymma species. The gas-phase reaction route to form the characteristic [M-H2O-(30/60/90)]+ fragments in C-glycosyl flavones was suggested as sequential sugar ring opening followed by retro-aldol elimination involving aldose-ketose isomerization. The use of molecular networking with LC-CID-MS/MS assisted the identification of various isomeric and isobaric flavonoid glycoconjugates by establishing clusters according to the fragmentation similarities. Additionally, the proposed cross-ring sugar cleavages can contribute to the identification of C-glycosides by MS/MS analysis.

Partial least squares model and design of experiments toward the analysis of the metabolome of Jatropha gossypifolia leaves: Extraction and chromatographic fingerprint optimization.

A major challenge in metabolomic studies is how to extract and analyze an entire metabolome. So far, no single method was able to clearly complete this task in an efficient and reproducible way. In this work we proposed a sequential strategy for the extraction and chromatographic separation of metabolites from leaves Jatropha gossypifolia using a design of experiments and partial least square model. The effect of 14 different solvents on extraction process was evaluated and an optimized separation condition on liquid chromatography was estimated considering mobile phase composition and analysis time. The initial conditions of extraction using methanol and separation in 30 min between 5 and 100% water/methanol (1:1 v/v) with 0.1% of acetic acid, 20 µL sample volume, 3.0 mL min(-1) flow rate and 25°C column temperature led to 107 chromatographic peaks. After the optimization strategy using i-propanol/chloroform (1:1 v/v) for extraction, linear gradient elution of 60 min between 5 and 100% water/(acetonitrile/methanol 68:32 v/v with 0.1% of acetic acid), 30 µL sample volume, 2.0 mL min(-1) flow rate, and 30°C column temperature, we detected 140 chromatographic peaks, 30.84% more peaks compared to initial method. This is a reliable strategy using a limited number of experiments for metabolomics protocols.

Metabolomics method to comprehensively analyze amino acids in different domains.

Amino acids play essential roles in both metabolism and the proteome. Many studies have profiled free amino acids (FAAs) or proteins; however, few have connected the measurement of FAA with individual amino acids in the proteome. In this study, we developed a metabolomics method to comprehensively analyze amino acids in different domains, using two examples of different sample types and disease models. We first examined the responses of FAAs and insoluble-proteome amino acids (IPAAs) to the Myc oncogene in Tet21N human neuroblastoma cells. The metabolic and proteomic amino acid profiles were quite different, even under the same Myc condition, and their combination provided a better understanding of the biological status. In addition, amino acids were measured in 3 domains (FAAs, free and soluble-proteome amino acids (FSPAAs), and IPAAs) to study changes in serum amino acid profiles related to colon cancer. A penalized logistic regression model based on the amino acids from the three domains had better sensitivity and specificity than that from each individual domain. To the best of our knowledge, this is the first study to perform a combined analysis of amino acids in different domains, and indicates the useful biological information available from a metabolomics analysis of the protein pellet. This study lays the foundation for further quantitative tracking of the distribution of amino acids in different domains, with opportunities for better diagnosis and mechanistic studies of various diseases.

LC-MS/DIA-based strategy for comprehensive flavonoid profiling: an Ocotea spp. applicability case.

We introduce a liquid chromatography - mass spectrometry with data-independent acquisition (LC-MS/DIA)-based strategy, specifically tailored to achieve comprehensive and reliable glycosylated flavonoid profiling. This approach facilitates in-depth and simultaneous exploration of all detected precursors and fragments during data processing, employing the widely-used open-source MZmine 3 software. It was applied to a dataset of six Ocotea plant species. This framework suggested 49 flavonoids potentially newly described for these plant species, alongside 45 known features within the genus. Flavonols kaempferol and quercetin, both exhibiting O-glycosylation patterns, were particularly prevalent. Gas-phase fragmentation reactions further supported these findings. For the first time, the apigenin flavone backbone was also annotated in most of the examined Ocotea species. Apigenin derivatives were found mainly in the C-glycoside form, with O. porosa displaying the highest flavone : flavonol ratio. The approach also allowed an unprecedented detection of kaempferol and quercetin in O. porosa species, and it has underscored the untapped potential of LC-MS/DIA data for broad and reliable flavonoid profiling. Our study annotated more than 50 flavonoid backbones in each species, surpassing the current literature.

Exploration of associations among dietary tryptophan, microbiome composition and function, and symptom severity in irritable bowel syndrome.

BACKGROUND: Imbalance of the tryptophan (TRP) pathway may influence symptoms among patients with irritable bowel syndrome (IBS). This study explored relationships among different components that contribute to TRP metabolism (dietary intake, stool metabolite levels, predicted microbiome metabolic capability) in females with IBS and healthy controls (HCs). Within the IBS group, we also investigated relationships between TRP metabolic determinants, Bifidobacterium abundance, and symptoms of IBS. METHODS: Participants with IBS (Rome III) and HCs completed a 28-day diary of gastrointestinal symptoms and a 3-day food record for TRP intake. They provided a stool sample for shotgun metagenomics, 16 S rRNA analyses, and quantitative measurement of TRP by mass spectrometry. RESULTS: Our cohort included 115 females, 69 with IBS and 46 HCs, with a mean age of 28.5 years (SD 7.4). TRP intake (p = 0.71) and stool TRP level (p = 0.27) did not differ between IBS and HC. Bifidobacterium abundance was lower in the IBS group than in HCs (p = 0.004). Predicted TRP metabolism gene content was higher in IBS than HCs (FDR-corrected q = 0.006), whereas predicted biosynthesis gene content was lower (q = 0.045). Within the IBS group, there was no association between symptom severity and TRP intake or stool TRP, but there was a significant interaction between Bifidobacterium abundance and TRP intake (q = 0.029) in predicting stool character. CONCLUSIONS: Dietary TRP intake, microbiome composition, and differences in TRP metabolism constitute a complex interplay of factors that could modulate IBS symptom severity.

Mitochondrial Inorganic Polyphosphate (polyP) Is a Potent Regulator of Mammalian Bioenergetics in SH-SY5Y Cells: A Proteomics and Metabolomics Study.

Inorganic polyphosphate (polyP) is an ancient, ubiquitous, and well-conserved polymer which is present in all the studied organisms. It is formed by individual subunits of orthophosphate which are linked by structurally similar bonds and isoenergetic to those found in ATP. While the metabolism and the physiological roles of polyP have already been described in some organisms, including bacteria and yeast, the exact role of this polymer in mammalian physiology still remains poorly understood. In these organisms, polyP shows a co-localization with mitochondria, and its role as a key regulator of the stress responses, including the maintenance of appropriate bioenergetics, has already been demonstrated by our group and others. Here, using Wild-type (Wt) and MitoPPX (cells enzymatically depleted of mitochondrial polyP) SH-SY5Y cells, we have conducted a comprehensive study of the status of cellular physiology, using proteomics and metabolomics approaches. Our results suggest a clear dysregulation of mitochondrial physiology, especially of bioenergetics, in MitoPPX cells when compared with Wt cells. Moreover, the effects induced by the enzymatic depletion of polyP are similar to those present in the mitochondrial dysfunction that is observed in neurodegenerative disorders and in neuronal aging. Based on our findings, the metabolism of mitochondrial polyP could be a valid and innovative pharmacological target in these conditions.

Effects of myocardial ischemia/reperfusion injury on plasma metabolomic profile during aging.

BACKGROUND: Heart disease is a frequent cause of hospitalization and mortality for elderly patients. A common feature of both heart disease and aging itself is the involvement of metabolic organ alterations ultimately leading to changes in circulating metabolite levels. However, the specific contribution of aging and ischemic injury to the metabolic dysregulation occurring in older adults with ischemic heart disease is still unknown. AIM: To evaluate the effects of aging and ischemia/reperfusion (I/R) injury on plasma metabolomic profiling in mice. METHODS: Young and aged mice were subjected to a minimally invasive model of I/R injury or sham operation. Complete evaluation of cardiac function and untargeted plasma metabolomics analysis were performed. RESULTS: We confirmed that aged mice from the sham group had impaired cardiac function and augmented left ventricular (LV) dimensions compared to young sham-operated mice. Further, we found that ischemic injury did not drastically reduce LV systolic/diastolic function and dyssynchrony in aged compared to young mice. Using an untargeted metabolomics approach focused on aqueous metabolites, we found that ischemic injury does not affect the plasma metabolomic profile either in young or old mice. Our data also demonstrate that age significantly affects circulating metabolite levels (predominantly amino acids, phospholipids and organic acids) and perturbs several pathways involved in amino acid, glucid and nucleic acid metabolism as well as pyridoxal-5'-phosphate salvage pathway in both sham and ischemic mice. CONCLUSIONS: Our approach increases our understanding of age-associated plasma metabolomic signatures in mice with and without heart disease excluding confounding factors related to metabolic comorbidities.

Effect of a Flaxseed Lignan Intervention on Circulating Bile Acids in a Placebo-Controlled Randomized, Crossover Trial.

Plant lignans and their microbial metabolites, e.g., enterolactone (ENL), may affect bile acid (BA) metabolism through interaction with hepatic receptors. We evaluated the effects of a flaxseed lignan extract (50 mg/day secoisolariciresinol diglucoside) compared to a placebo for 60 days each on plasma BA concentrations in 46 healthy men and women (20-45 years) using samples from a completed randomized, crossover intervention. Twenty BA species were measured in fasting plasma using LC-MS. ENL was measured in 24-h urines by GC-MS. We tested for (a) effects of the intervention on BA concentrations overall and stratified by ENL excretion; and (b) cross-sectional associations between plasma BA and ENL. We also explored the overlap in bacterial metabolism at the genus level and conducted in vitro anaerobic incubations of stool with lignan substrate to identify genes that are enriched in response to lignan metabolism. There were no intervention effects, overall or stratified by ENL at FDR < 0.05. In the cross-sectional analysis, irrespective of treatment, five secondary BAs were associated with ENL excretion (FDR < 0.05). In vitro analyses showed positive associations between ENL production and bacterial gene expression of the bile acid-inducible gene cluster and hydroxysteroid dehydrogenases. These data suggest overlap in community bacterial metabolism of secondary BA and ENL.

Plant Metabolomics Using NMR Spectroscopy.

The major goal in plant metabolomics is to study complex extracts for the purposes of metabolic exploration and natural products discovery. To achieve this goal, plant metabolomics relies on accurate and selective acquisition of all possible chemical information, which includes maximization of the number of detected metabolites and their correct molecular assignment. Nuclear magnetic resonance (NMR) spectroscopy has been recognized as a powerful platform for obtaining the metabolite profiles of plant extracts. In this chapter, we provide a workflow for targeted and untargeted metabolite profiling of plant extracts using both 1D and 2D NMR methods. The protocol includes sample preparation, instrument operation, data processing, multivariate analysis, biomarker elucidation, and metabolite quantitation. It also addresses the annotation of plant metabolite peaks considering NMR's capabilities to cover a broad range of metabolites and elucidate structures for unknown compounds.

Dereplication of Natural Products Using GC-TOF Mass Spectrometry: Improved Metabolite Identification by Spectral Deconvolution Ratio Analysis.

Dereplication based on hyphenated techniques has been extensively applied in plant metabolomics, thereby avoiding re-isolation of known natural products. However, due to the complex nature of biological samples and their large concentration range, dereplication requires the use of chemometric tools to comprehensively extract information from the acquired data. In this work we developed a reliable GC-MS-based method for the identification of non-targeted plant metabolites by combining the Ratio Analysis of Mass Spectrometry deconvolution tool (RAMSY) with Automated Mass Spectral Deconvolution and Identification System software (AMDIS). Plants species from Solanaceae, Chrysobalanaceae and Euphorbiaceae were selected as model systems due to their molecular diversity, ethnopharmacological potential, and economical value. The samples were analyzed by GC-MS after methoximation and silylation reactions. Dereplication was initiated with the use of a factorial design of experiments to determine the best AMDIS configuration for each sample, considering linear retention indices and mass spectral data. A heuristic factor (CDF, compound detection factor) was developed and applied to the AMDIS results in order to decrease the false-positive rates. Despite the enhancement in deconvolution and peak identification, the empirical AMDIS method was not able to fully deconvolute all GC-peaks, leading to low MF values and/or missing metabolites. RAMSY was applied as a complementary deconvolution method to AMDIS to peaks exhibiting substantial overlap, resulting in recovery of low-intensity co-eluted ions. The results from this combination of optimized AMDIS with RAMSY attested to the ability of this approach as an improved dereplication method for complex biological samples such as plant extracts.