Composite score analysis for unsupervised comparison and network visualization of metabolomics data

Allergic inflammation triggers dyslipidemia via IgG signalling

BACKGROUND

Allergic diseases begin early in life and are often chronic, thus creating an inflammatory environment that may precede or exacerbate other pathologies. In this regard, allergy has been associated to metabolic disorders and with a higher risk of cardiovascular disease, but the underlying mechanisms remain incompletely understood.

METHODS

We used a murine model of allergy and atherosclerosis, different diets and sensitization methods, and cell-depleting strategies to ascertain the contribution of acute and late phase inflammation to dyslipidemia. Untargeted lipidomic analyses were applied to define the lipid fingerprint of allergic inflammation at different phases of allergic pathology. Expression of genes related to lipid metabolism was assessed in liver and adipose tissue at different times post-allergen challenge. Also, changes in serum triglycerides (TGs) were evaluated in a group of 59 patients ≥14 days after the onset of an allergic reaction.

RESULTS

We found that allergic inflammation induces a unique lipid signature that is characterized by increased serum TGs and changes in the expression of genes related to lipid metabolism in liver and adipose tissue. Alterations in blood TGs following an allergic reaction are independent of T-cell-driven late phase inflammation. On the contrary, the IgG-mediated alternative pathway of anaphylaxis is sufficient to induce a TG increase and a unique lipid profile. Lastly, we demonstrated an increase in serum TGs in 59 patients after undergoing an allergic reaction.

CONCLUSION

Overall, this study reveals that IgG-mediated allergic inflammation regulates lipid metabolism.

An Integrative Approach to Elucidate Mechanisms Underlying the Pharmacokinetic Goldenseal-Midazolam Interaction: Application of In Vitro Assays and Physiologically Based Pharmacokinetic Models to Understand Clinical Observations

The natural product goldenseal is a clinical inhibitor of CYP3A activity, as evidenced by a 40%-60% increase in midazolam area under the plasma concentration versus time curve (AUC) after coadministration with goldenseal. The predominant goldenseal alkaloids berberine and (-)-β-hydrastine were previously identified as time-dependent CYP3A inhibitors using human liver microsomes. Whether these alkaloids contribute to the clinical interaction, as well as the primary anatomic site (hepatic vs. intestinal) and mode of CYP3A inhibition (reversible vs. time-dependent), remain uncharacterized. The objective of this study was to mechanistically assess the pharmacokinetic goldenseal-midazolam interaction using an integrated in vitro-in vivo-in silico approach. Using human intestinal microsomes, (-)-β-hydrastine was a more potent time-dependent inhibitor of midazolam 1'-hydroxylation than berberine (KI and kinact: 8.48 μM and 0.041 minutes-1, respectively, vs. >250 μM and ∼0.06 minutes-1, respectively). Both the AUC and Cmax of midazolam increased by 40%-60% after acute (single 3-g dose) and chronic (1 g thrice daily × 6 days) goldenseal administration to healthy adults. These increases, coupled with a modest or no increase (≤23%) in half-life, suggested that goldenseal primarily inhibited intestinal CYP3A. A physiologically based pharmacokinetic interaction model incorporating berberine and (-)-β-hydrastine successfully predicted the goldenseal-midazolam interaction to within 20% of that observed after both chronic and acute goldenseal administration. Simulations implicated (-)-β-hydrastine as the major alkaloid precipitating the interaction, primarily via time-dependent inhibition of intestinal CYP3A, after chronic and acute goldenseal exposure. Results highlight the potential interplay between time-dependent and reversible inhibition of intestinal CYP3A as the mechanism underlying natural product-drug interactions, even after acute exposure to the precipitant. SIGNIFICANCE STATEMENT: Natural products can alter the pharmacokinetics of an object drug, potentially resulting in increased off-target effects or decreased efficacy of the drug. The objective of this work was to evaluate fundamental mechanisms underlying the clinically observed goldenseal-midazolam interaction. Results support the use of an integrated approach involving established in vitro assays, clinical evaluation, and physiologically based pharmacokinetic modeling to elucidate the complex interplay between multiple phytoconstituents and various pharmacokinetic processes driving a drug interaction.

Integrative analysis of microbiota and metabolomics in chromium-exposed silkworm (Bombyx mori) midguts based on 16S rDNA sequencing and LC/MS metabolomics

The gut microbiota, a complex ecosystem integral to host wellbeing, is modulated by environmental triggers, including exposure to heavy metals such as chromium. This study aims to comprehensively explore chromium-induced gut microbiota and metabolomic shifts in the quintessential lepidopteran model organism, the silkworm (Bombyx mori). The research deployed 16S rDNA sequence analysis and LC/MS metabolomics in its experimental design, encompassing a control group alongside low (12 g/kg) and high (24 g/kg) feeding chromium dosing regimens. Considerable heterogeneity in microbial diversity resulted between groups. Weissella emerged as potentially resilient to chromium stress, while elevated Propionibacterium was noted in the high chromium treatment group. Differential analysis tools LEfSe and random forest estimation identified key species like like Cupriavidus and unspecified Myxococcales, offering potential avenues for bioremediation. An examination of gut functionality revealed alterations in the KEGG pathways correlated with biosynthesis and degradation, suggesting an adaptive metabolic response to chromium-mediated stress. Further results indicated consequential fallout in the context of metabolomic alterations. These included an uptick in histidine and dihydropyrimidine levels under moderate-dose exposure and a surge of gentisic acid with high-dose chromium exposure. These are critical players in diverse biological processes ranging from energy metabolism and stress response to immune regulation and antioxidative mechanisms. Correlative analyses between bacterial abundance and metabolites mapped noteworthy relationships between marker bacterial species, such as Weissella and Pelomonas, and specific metabolites, emphasizing their roles in enzyme regulation, synaptic processes, and lipid metabolism. Probiotic bacteria showed robust correlations with metabolites implicated in stress response, lipid metabolism, and antioxidant processes. Our study reaffirms the intricate ties between gut microbiota and metabolite profiles and decodes some systemic adaptations under heavy-metal stress. It provides valuable insights into ecological and toxicological aspects of chromium exposure that can potentially influence silkworm resilience.

Co-consuming green tea with raloxifene decreases raloxifene systemic exposure in healthy adult participants

Green tea is a popular beverage worldwide. The abundant green tea catechin (-)-epigallocatechin gallate (EGCG) is a potent in vitro inhibitor of intestinal UDP-glucuronosyltransferase (UGT) activity (Ki  ~2 μM). Co-consuming green tea with intestinal UGT drug substrates, including raloxifene, could increase systemic drug exposure. The effects of a well-characterized green tea on the pharmacokinetics of raloxifene, raloxifene 4'-glucuronide, and raloxifene 6-glucuronide were evaluated in 16 healthy adults via a three-arm crossover, fixed-sequence study. Raloxifene (60 mg) was administered orally with water (baseline), with green tea for 1 day (acute), and on the fifth day after daily green tea administration for 4 days (chronic). Unexpectedly, green tea decreased the geometric mean green tea/baseline raloxifene AUC0-96h ratio to ~0.60 after both acute and chronic administration, which is below the predefined no-effect range (0.75-1.33). Lack of change in terminal half-life and glucuronide-to-raloxifene ratios indicated the predominant mechanism was not inhibition of intestinal UGT. One potential mechanism includes inhibition of intestinal transport. Using established transfected cell systems, a green tea extract normalized to EGCG inhibited 10 of 16 transporters tested (IC50 , 0.37-12 μM). Another potential mechanism, interruption by green tea of gut microbe-mediated raloxifene reabsorption, prompted a follow-up exploratory clinical study to evaluate the potential for a green tea-gut microbiota-drug interaction. No clear mechanisms were identified. Overall, results highlight that improvements in current models and methods used to predict UGT-mediated drug interactions are needed. Informing patients about the risk of co-consuming green tea with raloxifene may be considered.

Metabolic profiling and transcriptome analysis provide insights into the accumulation of flavonoids in chayote fruit during storage

Chayote (Sechium edulel) fruits are rich in flavonoids, folate, and low-calorie food. However, studies about the flavonoids and the corresponding regulatory mechanism of flavonoid synthesis in chayote fruits was still unclear. In present study, an integrated transcriptome and metabolite analysis of chayote fruits at three different storage stages were conducted to explore the flavonoid compositions and gene expression associated with flavonoid synthesis. Through the UPLC-MS/MS analysis, a total of 57 flavonoid compounds were detected. Of these, 42 flavonoid glycosides were significantly differential accumulation in chayote fruits at three different storage stages. Many genes associated with flavonoid synthesis were differentially expressed in chayote fruits at three different storage stages through RNA-seq analysis, including structural genes and some TFs. There was a high correlation between RNA-seq analysis and metabolite profiling, and the expression level of candidate genes in the flavonoid synthesis pathway were consistent with the dynamic changes of flavonoids. In addition, one R2R3-MYB transcription factor, FSG0057100, was defined as the critical regulatory gene of flavonoid synthesis. Furthermore, exogenous application of phenylalanine increased the total content of flavonoids and promoted some flavonoid biosynthesis-related gene expression in chayote fruits. The above results not only make us better understand the molecular mechanism of flavonoid synthesis in chayote fruits, but also contribute to the promotion and application of chayote products.

Metabolomics-Driven Mining of Metabolite Resources: Applications and Prospects for Improving Vegetable Crops

Vegetable crops possess a prominent nutri-metabolite pool that not only contributes to the crop performance in the fields, but also offers nutritional security for humans. In the pursuit of identifying, quantifying and functionally characterizing the cellular metabolome pool, biomolecule separation technologies, data acquisition platforms, chemical libraries, bioinformatics tools, databases and visualization techniques have come to play significant role. High-throughput metabolomics unravels structurally diverse nutrition-rich metabolites and their entangled interactions in vegetable plants. It has helped to link identified phytometabolites with unique phenotypic traits, nutri-functional characters, defense mechanisms and crop productivity. In this study, we explore mining diverse metabolites, localizing cellular metabolic pathways, classifying functional biomolecules and establishing linkages between metabolic fluxes and genomic regulations, using comprehensive metabolomics deciphers of the plant’s performance in the environment. We discuss exemplary reports covering the implications of metabolomics, addressing metabolic changes in vegetable plants during crop domestication, stage-dependent growth, fruit development, nutri-metabolic capabilities, climatic impacts, plant-microbe-pest interactions and anthropogenic activities. Efforts leading to identify biomarker metabolites, candidate proteins and the genes responsible for plant health, defense mechanisms and nutri-rich crop produce are documented. With the insights on metabolite-QTL (mQTL) driven genetic architecture, molecular breeding in vegetable crops can be revolutionized for developing better nutritional capabilities, improved tolerance against diseases/pests and enhanced climate resilience in plants.

Label compliance for ingredient verification: regulations, approaches, and trends for testing botanical products marketed for "immune health" in the United States

During the COVID-19 pandemic, the botanical product market saw a consumer interest increase in immune health supplements. While data are currently insufficient to support public health guidance for using foods and dietary supplements to prevent or treat COVID-19 and other immune disorders, consumer surveys indicate that immune support is the second-most cited reason for supplement use in the United States. Meanwhile, consumers showed increased attention to dietary supplement ingredient labels, especially concerning authenticity and ingredient claims. Top-selling botanical ingredients such as elderberry, turmeric, and functional mushrooms have been increasingly marketed toward consumers to promote immune health, but these popular products succumb to adulteration with inaccurate labeling due to the intentional or unintentional addition of lower grade ingredients, non-target plants, and synthetic compounds, partially due to pandemic-related supply chain issues. This review highlights the regulatory requirements and recommendations for analytical approaches, including chromatography, spectroscopy, and DNA approaches for ingredient claim verification. Demonstrating elderberry, turmeric, and functional mushrooms as examples, this review aims to provide industrial professionals and scientists an overview of current United States regulations, testing approaches, and trends for label compliance verification to ensure the safety of botanical products marketed for "immune health."

The Metabolomic Profile in Amyotrophic Lateral Sclerosis Changes According to the Progression of the Disease: An Exploratory Study

Amyotrophic lateral sclerosis (ALS) is a multifactorial neurodegenerative pathology of the upper or lower motor neuron. Evaluation of ALS progression is based on clinical outcomes considering the impairment of body sites. ALS has been extensively investigated in the pathogenetic mechanisms and the clinical profile; however, no molecular biomarkers are used as diagnostic criteria to establish the ALS pathological staging. Using the source-reconstructed magnetoencephalography (MEG) approach, we demonstrated that global brain hyperconnectivity is associated with early and advanced clinical ALS stages. Using nuclear magnetic resonance (¹H-NMR) and high resolution mass spectrometry (HRMS) spectroscopy, here we studied the metabolomic profile of ALS patients' sera characterized by different stages of disease progression-namely early and advanced. Multivariate statistical analysis of the data integrated with the network analysis indicates that metabolites related to energy deficit, abnormal concentrations of neurotoxic metabolites and metabolites related to neurotransmitter production are pathognomonic of ALS in the advanced stage. Furthermore, analysis of the lipidomic profile indicates that advanced ALS patients report significant alteration of phosphocholine (PCs), lysophosphatidylcholine (LPCs), and sphingomyelin (SMs) metabolism, consistent with the exigency of lipid remodeling to repair advanced neuronal degeneration and inflammation.

Metabolomics Analysis and Antioxidant Potential of Endophytic Diaporthe fraxini ED2 Grown in Different Culture Media

Endophytic fungi are a promising source of bioactive metabolites with a wide range of pharmacological activities. In the present study, MS-based metabolomics was conducted to study the metabolomes variations of endophytic Diaporthe fraxini ED2 grown in different culture media. Total phenolic content (TPC), total flavonoid content (TFC), 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging, 2,2-azinobis(3-ethylbenzothiazoline-6-sulfonic acid (ABTS), and ferric reducing antioxidant power (FRAP) assays were conducted to assess the antioxidant potential of the fungal extracts. Multivariate data analysis (MVDA) was employed in data analysis and interpretation to elucidate the complex metabolite profile. The supplemented culture medium of D. fraxini fungal extract stimulated the production of metabolites not occurring in the normal culture medium. Antioxidant activity studies revealed the potential of supplemented cultured fungal extract of D. fraxini as a source of antioxidants. The present findings highlight that fungal culture medium supplementation is an effective approach to unravelling the hidden metabolome in plant-associated fungal diversity.

Principal component analysis technique for early fault detection

Online condition monitoring and predictive maintenance are crucial for the safe operation of equipments. This paper highlights an unsupervised statistical algorithm based on principal component analysis (PCA) for the predictive maintenance of industrial induced draft (ID) fan. The high vibration issues in ID fans cause the failure of the impellers and, sometimes, the complete breakdown of the fan-motor system. The condition monitoring system of the equipment should be reliable and avoid such a sudden breakdown or faults in the equipment. The proposed technique predicts the fault of the ID fan-motor system, being applicable for other rotating industrial equipment, and also for which the failure data, or historical data, is not available. The major problem in the industry is the monitoring of each and every machinery individually. To avoid this problem, three identical ID fans are monitored together using the proposed technique. This helps in the prediction of the faulty part and also the time left for the complete breakdown of the fan-motor system. This helps in forecasting the maintenance schedule for the equipment before breakdown. From the results, it is observed that the PCA-based technique is a good fit for early fault detection and getting alarmed under fault condition as compared with the conventional methods, including signal trend and fast Fourier transform (FFT) analysis.

Elevated serum phosphatidylcholine (16:1/22:6) levels promoted by fish oil and vitamin D3 are highly correlated with biomarkers of non-alcoholic fatty liver disease in Chinese subjects

Phosphatidylcholine (16:1/22:6) was associated with improving inflammation and lipid metabolism.

Chemometric-Guided Approaches for Profiling and Authenticating Botanical Materials

Botanical supplements with broad traditional and medicinal uses represent an area of growing importance for American health management; 25% of U.S. adults use dietary supplements daily and collectively spent over $9. 5 billion in 2019 in herbal and botanical supplements alone. To understand how natural products benefit human health and determine potential safety concerns, careful in vitro, in vivo, and clinical studies are required. However, botanicals are innately complex systems, with complicated compositions that defy many standard analytical approaches and fluctuate based upon a plethora of factors, including genetics, growth conditions, and harvesting/processing procedures. Robust studies rely upon accurate identification of the plant material, and botanicals' increasing economic and health importance demand reproducible sourcing, as well as assessment of contamination or adulteration. These quality control needs for botanical products remain a significant problem plaguing researchers in academia as well as the supplement industry, thus posing a risk to consumers and possibly rendering clinical data irreproducible and/or irrelevant. Chemometric approaches that analyze the small molecule composition of materials provide a reliable and high-throughput avenue for botanical authentication. This review emphasizes the need for consistent material and provides insight into the roles of various modern chemometric analyses in evaluating and authenticating botanicals, focusing on advanced methodologies, including targeted and untargeted metabolite analysis, as well as the role of multivariate statistical modeling and machine learning in phytochemical characterization. Furthermore, we will discuss how chemometric approaches can be integrated with orthogonal techniques to provide a more robust approach to authentication, and provide directions for future research.

Advancements in capturing and mining mass spectrometry data are transforming natural products research

Covering: 2016 up to 2021Mass spectrometry (MS) is an essential technology in natural products research with MS fragmentation (MS/MS) approaches becoming a key tool. Recent advancements in MS yield dense metabolomics datasets which have been, conventionally, used by individual labs for individual projects; however, a shift is brewing. The movement towards open MS data (and other structural characterization data) and accessible data mining tools is emerging in natural products research. Over the past 5 years, this movement has rapidly expanded and evolved with no slowdown in sight; the capabilities of today vastly exceed those of 5 years ago. Herein, we address the analysis of individual datasets, a situation we are calling the '2021 status quo', and the emergent framework to systematically capture sample information (metadata) and perform repository-scale analyses. We evaluate public data deposition, discuss the challenges of working in the repository scale, highlight the challenges of metadata capture and provide illustrative examples of the power of utilizing repository data and the tools that enable it. We conclude that the advancements in MS data collection must be met with advancements in how we utilize data; therefore, we argue that open data and data mining is the next evolution in obtaining the maximum potential in natural products research.

Relationship between amniotic fluid metabolic profile with fetal gender, maternal age, and gestational week

BACKGROUND

Amniotic fluid (AF) provides vital information on fetal development, which is also valuable in identifying fetal abnormalities during pregnancy. However, the relationship between the metabolic profile of AF in the second trimester of a normal pregnancy with several maternal-fetal parameters remains poorly understood, which therefore limits its application in clinical practice. The aim of this study was to explore the association between the metabolic profile of AF with fetal gender, maternal age, and gestational week using an untargeted metabolomics method.

METHODS

A total of 114 AF samples were analyzed in this study. Clinical data on fetal gender, maternal age, and gestational week of these samples were collected. Samples were analyzed by gas chromatography/time-of-flight-mass spectrometry (GC-TOF/MS). Principal component analysis(PCA), orthogonal partial least square discrimination analysis(OPLS-DA) or partial least square discrimination analysis (PLS-DA) were conducted to compare metabolic profiles, and differential metabolites were obtained by univariate analysis.

RESULTS

Both PCA and OPLS-DA demonstrated no significant separation trend between the metabolic profiles of male and female fetuses, and there were only 7 differential metabolites. When the association between the maternal age on AF metabolic profile was explored, both PCA and PLS-DA revealed that the maternal age in the range of 21 to 40 years had no significant effect on the metabolic profile of AF, and only four different metabolites were found. There was no significant difference in the metabolic profiles of AF from fetuses of 17-22 weeks, and 23 differential metabolites were found.

CONCLUSIONS

In the scope of our study, there was no significant correlation between the AF metabolic profile and the fetal gender, maternal age and gestational week of a small range. Nevertheless, few metabolites appeared differentially expressed.

Assessing Transporter-Mediated Natural Product-Drug Interactions Via In vitro-In Vivo Extrapolation: Clinical Evaluation With a Probe Cocktail

The botanical natural product goldenseal can precipitate clinical drug interactions by inhibiting cytochrome P450 (CYP) 3A and CYP2D6. Besides P-glycoprotein, effects of goldenseal on other clinically relevant transporters remain unknown. Established transporter-expressing cell systems were used to determine the inhibitory effects of a goldenseal extract, standardized to the major alkaloid berberine, on transporter activity. Using recommended basic models, the extract was predicted to inhibit the efflux transporter BCRP and uptake transporters OATP1B1/3. Using a cocktail approach, effects of the goldenseal product on BCRP, OATP1B1/3, OATs, OCTs, MATEs, and CYP3A were next evaluated in 16 healthy volunteers. As expected, goldenseal increased the area under the plasma concentration-time curve (AUC_0-inf ) of midazolam (CYP3A; positive control), with a geometric mean ratio (GMR) (90% confidence interval (CI)) of 1.43 (1.35-1.53). However, goldenseal had no effects on the pharmacokinetics of rosuvastatin (BCRP and OATP1B1/3) and furosemide (OAT1/3); decreased metformin (OCT1/2, MATE1/2-K) AUC_0-inf (GMR, 0.77 (0.71-0.83)); and had no effect on metformin half-life and renal clearance. Results indicated that goldenseal altered intestinal permeability, transport, and/or other processes involved in metformin absorption, which may have unfavorable effects on glucose control. Inconsistencies between model predictions and pharmacokinetic outcomes prompt further refinement of current basic models to include differential transporter expression in relevant organs and intestinal degradation/metabolism of the precipitant(s). Such refinement should improve in vitro-in vivo prediction accuracy, contributing to a standard approach for studying transporter-mediated natural product-drug interactions.

Identification of adulteration in botanical samples with untargeted metabolomics

Adulteration remains an issue in the dietary supplement industry, including botanical supplements. While it is common to employ a targeted analysis to detect known adulterants, this is difficult when little is known about the sample set. With this study, untargeted metabolomics using liquid chromatography coupled to ultraviolet-visible spectroscopy (LC-UV) or high-resolution mass spectrometry (LC-MS) was employed to detect adulteration in botanical dietary supplements. A training set was prepared by combining Hydrastis canadensis L. with a known adulterant, Coptis chinensis Franch., in ratios ranging from 5 to 95% adulteration. The metabolomics datasets were analyzed using both unsupervised (principal component analysis and composite score) and supervised (SIMCA) techniques. Palmatine, a known H. canadensis metabolite, was quantified as a targeted analysis comparison. While the targeted analysis was the most sensitive method tested in detecting adulteration, statistical analyses of the untargeted metabolomics datasets detected adulteration of the goldenseal samples, with SIMCA providing the greatest discriminating potential. Graphical abstract.