Stacked Injections of Biphasic Extractions for Improved Metabolomic Coverage and Sample Throughput

Metabolomes of bumble bees reared in common garden conditions suggest constitutive differences in energy and toxin metabolism across populations

Cold tolerance of ectotherms can vary strikingly among species and populations. Variation in cold tolerance can reflect differences in genomes and transcriptomes that confer cellular-level protection from cold; additionally, shifts in protein function and abundance can be altered by other cellular constituents as cold-exposed insects often have shifts in their metabolomes. Even without a cold challenge, insects from different populations may vary in cellular composition that could alter cold tolerance, but investigations of constitutive differences in metabolomes across wild populations remain rare. To address this gap, we reared Bombus vosnesenskii queens collected from Oregon and California (USA) that differ in cold tolerance (CTmin = -6 °C and 0 °C, respectively) in common garden conditions, and measured offspring metabolomes using untargeted LC-MS/MS. Oregon bees had higher levels of metabolites associated with carbohydrate (sorbitol, lactitol, maltitol, and sorbitol-6-phosphate) and amino acid (hydroxyproline, ornithine, and histamine) metabolism. Exogenous metabolites, likely derived from the diet, also varied between Oregon and California bees, suggesting population-level differences in toxin metabolism. Overall, our results reveal constitutive differences in metabolomes for bumble bees reared in common garden conditions from queens collected in different locations despite no previous cold exposure.

Metabolomic Analysis of Polymicrobial Wound Infections and an Associated Adhesive Bandage

Concerns about ion suppression, spectral contamination, or interference have led to avoidance of polymers in mass spectrometry (MS)-based metabolomics. This avoidance, however, has left many biochemical fields underexplored, including wounds, which are often treated with adhesive bandages. Here, we found that despite previous concerns, the addition of an adhesive bandage can still result in biologically informative MS data. Initially, a test LC-MS analysis was performed on a mixture of known chemical standards and a polymer bandage extract. Results demonstrated successful removal of many polymer-associated features through a data processing step. Furthermore, the bandage presence did not interfere with metabolite annotation. This method was then implemented in the context of murine surgical wound infections covered with an adhesive bandage and inoculated with Staphylococcus aureus, Pseudomonas aeruginosa, or a 1:1 mix of these pathogens. Metabolites were extracted and analyzed by LC-MS. On the bandage side, we observed a greater impact of infection on the metabolome. Distance analysis showed significant differences between all conditions and demonstrated that coinfected samples were more similar to S. aureus-infected samples compared to P. aeruginosa-infected samples. We also found that coinfection was not merely a summative effect of each monoinfection. Overall, these results represent an expansion of LC-MS-based metabolomics to a novel, previously under-investigated class of samples, leading to actionable biological information.

Isosteviol Sodium Exerts Anti-Colitic Effects on BALB/c Mice with Dextran Sodium Sulfate-Induced Colitis Through Metabolic Reprogramming and Immune Response Modulation

PURPOSE

Inflammatory bowel diseases (IBDs) are global health problems that are associated with immune regulation, but clinical IBDs treatment is currently inadequate. Effective preventive or therapeutic methods for immune disorders rely on controlling the function of immune cells. Isosteviol sodium (STV-Na) has antioxidant activity, but the therapeutic effect of STV-Na against IBD remain undocumented. Herein, we investigated the therapeutic effect of STV-Na in mice models with IBDs.

METHODS

Mice received 3.5% DSS for 7 days to establish IBD models. Intraperitoneal STV-Na was given 2 days before DSS and lasted for 9 days. Commercially available drugs used in treating IBDs (5-aminosalicylic acid, dexamethasone, and infliximab) were used as positive controls. Samples were collected 7 days after colitis induction. Histopathological score, biochemical parameters, molecular biology methods, and metabolomics were used for evaluating the therapeutic effect of STV-Na.

RESULTS

Our data revealed that STV-Na could significantly alleviate colon inflammation in mice with colitis. Specifically, STV-Na treatment improved body weight loss, increased colon length, decreased histology scores, and restored the hematological parameters of mice with colitis. The untargeted metabolomics analysis revealed that metabolic profiles were restored by STV-Na treatment. Furthermore, STV-Na therapy suppressed the number of CD68 macrophages and F4/80 cell infiltration. And STV-Na suppressed M1 and M2 macrophage numbers along with the mRNA expressions of proinflammatory cytokines. Moreover, STV-Na administration increased the number of regulatory T (Treg) cells while decreasing Th1/Th2/Th17 cell counts in the spleen. Additionally, STV-Na treatment restored intestinal barrier disruption in DSS-triggered colitis tissues by ameliorating the TJ proteins, increasing goblet cell proportions, and mucin protein production, and decreasing the permeability to FITC-dextran, which was accompanied by decreased plasma LPS and DAO contents.

CONCLUSION

These results indicate that STV-Na can ameliorate colitis by modulating immune responses along with metabolic reprogramming, and could therefore be a promising therapeutic strategy for IBDs.

An optimized LC-HRMS untargeted metabolomics workflow for multi-matrices investigations in the three-spined stickleback

Environmental metabolomics has become a growing research field to understand biological and biochemical perturbations of organisms in response to various abiotic or biotic stresses. It focuses on the comprehensive and systematic analysis of a biologic system’s metabolome. This allows the recognition of biochemical pathways impacted by a stressor, and the identification of some metabolites as biomarkers of potential perturbations occurring in a body. In this work, we describe the development and optimization of a complete reliable methodology based on liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS) for untargeted metabolomics studies within a fish model species, the three-spined stickleback (Gasterosteus aculeatus). We evaluated the differences and also the complementarities between four different matrices (brain, gills, liver and whole fish) to obtain metabolome information. To this end, we optimized and compared sample preparation and the analytical method, since the type and number of metabolites detected in any matrix are closely related to these latter. For the sample preparation, a solid-liquid extraction was performed on a low quantity of whole fish, liver, brain, or gills tissues using combinations of methanol/water/heptane. Based on the numbers of features observed in LC-HRMS and on the responses of analytical standards representative of different metabolites groups (amino acids, sugars…), we discuss the influence of the nature, volume, and ratio of extraction solvents, the sample weight, and the reconstitution solvent. Moreover, the analytical conditions (LC columns, pH and additive of mobile phases and ionization modes) were also optimized so as to ensure the maximum metabolome coverages. Thus, two complementary chromatographic procedures were combined in order to cover a broader range of metabolites: a reversed phase separation (RPLC) on a C18 column followed by detection with positive ionization mode (ESI+) and a hydrophilic interaction chromatography (HILIC) on a zwitterionic column followed by detection with negative ionization mode (ESI-). This work provides information on brain, gills, liver, vs the whole body contribution to the stickleback metabolome. These information would help to guide ecotoxicological and biomonitoring studies.

Integration of Untargeted and Pseudotargeted Metabolomics for Authentication of Three Shrimp Species Using UHPLC-Q-Orbitrap

In this work, an untargeted and pseudotargeted metabolomics combination approach was used for authentication of three shrimp species (Litopenaeus vanmamei, Penaeus japonicus, and Penaeus monodon). The monophasic extraction-based untargeted metabolomics approach enabled comprehensive-coverage and high-throughput analysis of shrimp tissue and revealed 26 potential markers. The pseudotargeted metabolomics approach confirmed 21 markers (including 9 key markers), which realized at least putative identification. The 21 confirmed markers, as well as 9 key markers, were used to develop PLS-DA models, correctly classifying 60/60 testing samples. Furthermore, DD-SIMCA and PLS-DA models were integrated based on the 9 key markers, with 59/60 and 20/20 samples of the species that were involved and uninvolved in model training correctly classified. The results demonstrated the potential of this untargeted and pseudotargeted metabolomics combination approach for shrimp species authentication.

Comprehensive Evaluation of Metabolites and Minerals in 6 Microgreen Species and the Influence of Maturity

BACKGROUND

Microgreens are the young leafy greens of many vegetables, herbs, grains, and flowers with potential to promote human health and sustainably diversify the global food system. For successful further integration into the global food system and evaluation of their health impacts, it is critical to elucidate and optimize their nutritional quality.

OBJECTIVES

We aimed to comprehensively evaluate the metabolite and mineral contents of 6 microgreen species, and the influence of maturity on their contents.

METHODS

Plant species evaluated were from the Brassicaceae (arugula, broccoli, and red cabbage), Amaranthaceae (red beet and red amaranth), and Fabaceae (pea) plant families. Nontargeted metabolomics and ionomics analyses were performed to examine the metabolites and minerals, respectively, in each microgreen species and its mature counterpart.

RESULTS

Nontargeted metabolomics analysis detected 3321 compounds, 1263 of which were annotated and included nutrients and bioactive compounds. Ionomics analysis detected and quantified 26 minerals including macrominerals, trace minerals, ultratrace minerals, and other metals. Principal component analysis indicated that microgreens have distinct metabolite and mineral profiles compared with one another and with their mature counterparts. Several compounds were higher (P  < 0.05; fold change ≥2) in microgreens compared with their mature counterparts, whereas some were not different or lower. In many cases, compounds that were higher in microgreens compared with the mature counterpart were also unique to that microgreen species.

CONCLUSIONS

These data provide evidence for the nutritional quality of microgreens, and can inform future research and development aimed at characterizing and optimizing microgreen nutritional quality and health impacts.

Differential Stem Proteomics and Metabolomics Profiles for Four Wheat Cultivars in Response to the Insect Pest Wheat Stem Sawfly

Common wheat (Triticum aestivum L.) is a global staple crop, and insect pests can impact grain yield. The wheat stem sawfly (Cephus cinctus, WSS) is a major wheat pest, and while partial resistance has been deployed by breeding for a solid-stem trait, this trait is affected by environment. Here, a proteomics and metabolomics study was performed on four wheat cultivars to characterize a molecular response to WSS infestation. The cultivars Hatcher (hollow-stem partially tolerant), Conan (semisolid-stem-resistant), and Denali and Reeder (hollow-stem-susceptible) were infested with WSS, and changes in stem proteins and metabolites were characterized using liquid chromatography-mass spectrometry. The proteome was characterized as 1830 proteins that included five major biological processes, including metabolic processes and response to stimuli, and the metabolome (1823 metabolites) spanned eight chemical superclasses, including alkaloids, benzenoids, and lipids. All four varieties had a molecular response to WSS following infestation. Hatcher had the most distinct changes, whereby 62 proteins and 29 metabolites varied in metabolic pathways involving enzymatic detoxification, proteinase inhibition, and antiherbivory compound production via benzoxazinoids, neolignans, and phenolics. Taken together, these data demonstrate variation in the wheat stem molecular response to WSS infestation and support breeding for molecular resistance in hollow-stem cultivars.

(R)-Salbutamol Improves Imiquimod-Induced Psoriasis-Like Skin Dermatitis by Regulating the Th17/Tregs Balance and Glycerophospholipid Metabolism

Psoriasis is a skin disease that is characterized by a high degree of inflammation caused by immune dysfunction. (R)-salbutamol is a bronchodilator for asthma and was reported to alleviate immune system reactions in several diseases. In this study, using imiquimod (IMQ)-induced mouse psoriasis-like dermatitis model, we evaluated the therapeutic effects of (R)-salbutamol in psoriasis in vivo, and explored the metabolic pathway involved. The results showed that, compared with IMQ group, (R)-salbutamol treatment significantly ameliorated psoriasis, reversed the suppressive effects of IMQ on differentiation, extreme keratinocyte proliferation, and infiltration of inflammatory cells. Enzyme-linked immunosorbent assays (ELISA) showed that (R)-salbutamol markedly reduced the plasma levels of IL-17. Cell analysis using flow cytometry showed that (R)-salbutamol decreased the proportion of CD4+ Th17+ T cells (Th17), whereas it increased the percentage of CD25+ Foxp3+ regulatory T cells (Tregs) in the spleens. (R)-salbutamol also decreased the weight ratio of spleen to body. Furthermore, untargeted metabolomics showed that (R)-salbutamol affected three metabolic pathways, including (i) arachidonic acid metabolism, (ii) sphingolipid metabolism, and (iii) glycerophospholipid metabolism. These results demonstrated that (R)-salbutamol can alleviate IMQ-induced psoriasis through regulating Th17/Tregs cell response and glycerophospholipid metabolism. It may provide a new use of (R)-salbutamol in the management of psoriasis.

Integration of lipidomics and metabolomics for in-depth understanding of cellular mechanism and disease progression

Mass spectrometry (MS)-based omics technologies are now widely used to profile small molecules in multiple matrices to confer comprehensive snapshots of cellular metabolic phenotypes. The metabolomes of cells, tissues, and organisms comprise a variety of molecules including lipids, amino acids, sugars, organic acids, and so on. Metabolomics mainly focus on the hydrophilic classes, while lipidomics has emerged as an independent omics owing to the complexities of the organismal lipidomes. The potential roles of lipids and small metabolites in disease pathogenesis have been widely investigated in various human diseases, but system-level understanding is largely lacking, which could be partly attributed to the insufficiency in terms of metabolite coverage and quantitation accuracy in current analytical technologies. While scientists are continuously striving to develop high-coverage omics approaches, integration of metabolomics and lipidomics is becoming an emerging approach to mechanistic investigation. Integration of metabolome and lipidome offers a complete atlas of the metabolic landscape, enabling comprehensive network analysis to identify critical metabolic drivers in disease pathology, facilitating the study of interconnection between lipids and other metabolites in disease progression. In this review, we summarize omics-based findings on the roles of lipids and metabolites in the pathogenesis of selected major diseases threatening public health. We also discuss the advantages of integrating lipidomics and metabolomics for in-depth understanding of molecular mechanism in disease pathogenesis.

Effect of (R)-salbutamol on the switch of phenotype and metabolic pattern in LPS-induced macrophage cells

Evidence demonstrates that M1 macrophage polarization promotes inflammatory disease. Here, we discovered that (R)‐salbutamol, a β₂ receptor agonist, inhibits and reprograms the cellular metabolism of RAW264.7 macrophages. (R)‐salbutamol significantly inhibited LPS‐induced M1 macrophage polarization and downregulated expressions of typical M1 macrophage cytokines, including monocyte chemotactic protein‐1 (MCP‐1), interleukin‐1β (IL‐1β) and tumour necrosis factor α (TNF‐α). Also, (R)‐salbutamol significantly decreased the production of inducible nitric oxide synthase (iNOS), nitric oxide (NO) and reactive oxygen species (ROS), while increasing the reduced glutathione (GSH)/oxidized glutathione (GSSG) ratio. In contrast, (S)‐salbutamol increased the production of NO and ROS. Bioenergetic profiles showed that (R)‐salbutamol significantly reduced aerobic glycolysis and enhanced mitochondrial respiration. Untargeted metabolomics analysis demonstrated that (R)‐salbutamol modulated metabolic pathways, of which three metabolic pathways, namely, (a) phenylalanine metabolism, (b) the pentose phosphate pathway and (c) glycerophospholipid metabolism were the most noticeably impacted pathways. The effects of (R)‐salbutamol on M1 polarization were inhibited by a specific β₂ receptor antagonist, ICI‐118551. These findings demonstrated that (R)‐salbutamol inhibits the M1 phenotype by downregulating aerobic glycolysis and glycerophospholipid metabolism, which may propose (R)‐salbutamol as the major pharmacologically active component of racemic salbutamol for the treatment of inflammatory diseases and highlight the medicinal value of (R)‐salbutamol.

Merging metabolomics and lipidomics into one analytical run

A novel integrated metabolomics/lipidomics workflow is introduced enabling high coverage of polar metabolites and non-polar lipids within one analytical run. Dual HILIC and RP chromatography were combined to high-resolution mass spectrometry. As a major advantage, only one data file per sample was obtained by fully automated simultaneous analysis of two extracts per sample. Hence, the unprecedented high coverage without compromise on analytical throughput was not only obtained by the orthogonality of the chromatographic separations, but also by the implementation of dedicated sample preparation procedures resulting in optimum extraction efficiency for both sub-omes. Thus, the method addressed completely hydrophilic sugars and organic acids next to water-insoluble triglycerides. As for the timing of the dual chromatography setup, HILIC and RP separation were performed consecutively. However, re-equilibration of the HILIC column during elution of RP compounds and vice versa reduced the overall analysis time by one third to 32 min. Application to the Standard Reference Material SRM 1950 - Metabolites in Frozen Human Plasma resulted in >100 metabolite and >380 lipid identifications based on accurate mass implementing fast polarity switching and acquiring data dependent MS2 spectra with the use of automated exclusion lists. Targeted quantification based on external calibrations and 13C labeled yeast internal standards was successfully accomplished for 59 metabolites. Moreover, the potential for lipid quantification was shown integrating non-endogenous lipids as internal standards. In human plasma, concentrations ranging over 4 orders of magnitude (low nM to high μM) were assessed.

Metabolomics and Ionomics of Potato Tuber Reveals an Influence of Cultivar and Market Class on Human Nutrients and Bioactive Compounds

Potato (Solanum tuberosum L.) is an important global food crop that contains phytochemicals with demonstrated effects on human health. Understanding sources of chemical variation of potato tuber can inform breeding for improved health attributes of the cooked food. Here, a comprehensive metabolomics (UPLC- and GC-MS) and ionomics (ICP-MS) analysis of raw and cooked potato tuber was performed on 60 unique potato genotypes that span 5 market classes including russet, red, yellow, chip, and specialty potatoes. The analyses detected 2,656 compounds that included known bioactives (43 compounds), nutrients (42), lipids (76), and 23 metals. Most nutrients and bioactives were partially degraded during cooking (44 out of 85; 52%), however genotypes with high quantities of bioactives remained highest in the cooked tuber. Chemical variation was influenced by genotype and market class. Specifically, ~53% of all detected compounds from cooked potato varied among market class and 40% varied by genotype. The most notable metabolite profiles were observed in yellow-flesh potato which had higher levels of carotenoids and specialty potatoes which had the higher levels of chlorogenic acid as compared to the other market classes. Variation in several molecules with known association to health was observed among market classes and included vitamins (e.g., pyridoxal, ~2-fold variation), bioactives (e.g., chlorogenic acid, ~40-fold variation), medicinals (e.g., kukoamines, ~6-fold variation), and minerals (e.g., calcium, iron, molybdenum, ~2-fold variation). Furthermore, more metabolite variation was observed within market class than among market class (e.g., α-tocopherol, ~1-fold variation among market class vs. ~3-fold variation within market class). Taken together, the analysis characterized significant metabolite and mineral variation in raw and cooked potato tuber, and support the potential to breed new cultivars for improved health traits.