A consensus orthogonal partial least squares discriminant analysis (OPLS-DA) strategy for multiblock Omics data fusion

Comparative evaluating laser ionization and iKnife coupled with rapid evaporative ionization mass spectrometry and machine learning for geographical authentication of Larimichthys crocea

Larimichthys crocea (LYC) holds significant economic value as a marine fish species. However, inaccuracies in labeling its origin can adversely affect consumer interests. Herein, a laser assisted rapid evaporative ionization mass spectrometry (LA-REIMS) and machine learning (ML) was developed for geographical authentication. When compared to iKnife, the LA demonstrated to be superior owing to reduced thermal damage to sample tissue, enhanced automation, and ease of use. Analysis of LYC from six distinct geographical origins across China revealed a total of 798 ions, which were then subjected to six classifiers to establish ML models. Following hyperparameter optimization and feature engineering, the Chi2(15%)-KNN model exhibited the highest training and testing accuracy, achieving 98.4 ± 0.9% and 98.5 ± 1.4%, respectively. This LA-REIMS/ML methodology offers a rapid, accurate, and intelligent solution for tracing the origin of LYC, thereby providing valuable technical support for the establishment of traceability systems in the aquatic product industry.

UPLC-ESI-MS/MS strategy to analyze fatty acids composition and lipid profiles of Pacific saury (Cololabis saira)

The Pacific saury (Cololabis saira) is a highly nutritious deep-sea fish, rich in omega-3 polyunsaturated fatty acids (n-3 PUFAs). This study comprehensively investigated fatty acids composition and lipid profiles of different parts of Pacific saury based on an untargeted lipidomic strategy. Results suggested that the crude fat content of meat, head and viscera were 5.81%, 10.90%, and 19.46%, respectively. The contents of PUFAs were 41.08%, 34.96% and 33.14%, respectively. Among them, the n-3 PUFAs in the head (34.58%) were significantly higher than meat (29.40%) and viscera (27.95%). Moreover, 5752 lipid molecules were identified, where glycerophospholipids (GP) were the most numerous lipid type (45.58%), with phosphatidylcholine (PC) being main differential subclass. PC (20:3_22:6) was the most abundant molecule in the head (14.59%) and meat (19.60%). Head_vs_viscera group had higher characteristic PC abundance. This study will provide a theoretical basis for the physiological activity and lipid high-value utilization of Pacific saury.

Preliminary study on the geographical origin of Chinese 'Cuiguan' pears using integrated stable isotope and multi-element analyses

Distinguish the geographical origin of the pear is important due to the increasingly valued brand protection and reducing the potential food safety risks. In this study, the profiles of stable isotopes (δ13C, δ15N, δ2H, δ18O) and the contents of 16 elements in pear peer from four production areas were analyzed. The δ13C, δ15N, δ2H, δ18O and 12 elements were significantly different (p < 0.05) in the four production areas. Chemometrics analysis including principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA) and linear discriminant analysis (LDA) were exploited for geographical origin classification of samples. OPLS-DA analysis showed that crucial variables (δ13C, δ18O, δ2H, Ni, Cd, Ca, δ15N, Sr and Ga) are more relevant for the discrimination of the samples. OPLS-DA achieved pear origin accuracy rates of 87.76 % by combining stable isotope ratios and elemental contents. LDA had a higher accuracy rate than OPLS-DA, and the LDA analysis showed that the original discrimination rate reached to 100 %, while the cross-validated rate reached to 95.7 %. These studies indicated that this method could be used to assess the geographical discrimination of pear from different producing areas and could potentially control the fair trade of pear in fruit markets.

Oleanolic acid alleviating ischemia-reperfusion injury in rat severe steatotic liver via KEAP1/NRF2/ARE

Severe steatosis in donor livers is contraindicated for transplantation due to the high risk of ischemia-reperfusion injury (IRI). Although Ho-1 gene-modified bone marrow mesenchymal stem cells (HO-1/BMMSCs) can mitigate IRI, the role of gut microbiota and metabolites in this protection remains unclear. This study aimed to explore how gut microbiota and metabolites contribute to HO-1/BMMSCs-mediated protection against IRI in severe steatotic livers. Using rat models and cellular models (IAR20 and THLE-2 cells) of steatotic liver IRI, this study revealed that ischemia-reperfusion led to significant liver and intestinal damage, heightened immune responses, impaired liver function, and altered gut microbiota and metabolite profiles in rats with severe steatosis, which were partially reversed by HO-1/BMMSCs transplantation. Integrated microbiome and metabolome analyses identified gut microbial metabolite oleanolic acid as a potential protective agent against IRI. Experimental validation showed that oleanolic acid administration alone alleviated IRI and inhibited ferroptosis in both rat and cellular models. Network pharmacology and molecular docking implicated KEAP1/NRF2 pathway as a potential target of oleanolic acid. Indeed, OA experimentally upregulated NRF2 activity, which underlies its inhibition of ferroptosis and protection against IRI. The gut microbial metabolite OA protects against IRI in severe steatotic liver by promoting NRF2 expression and activity, thereby inhibiting ferroptosis.

Insight into the compositional variation of volatile and polar compounds of Radix Bupleuri from different processing technologies by GC-MS and UHPLC-Q-TOF/MS metabolomics

INTRODUCTION

Insight into comparing key active ingredients of Radix Bupleuri (RB) based on different processing technologies is a key step to reveal the material basis of drug efficacy and a challenging task for developing traditional Chinese medicine (TCM).

OBJECTIVE

This work aims to establish a comprehensive comparative analysis method of TCM and its processed products, which can be used to analyze the changing trend of active components of RB before and after processing.

METHODS

First, RB was processed with rice vinegar, rice wine, and honey. Then, ultra-high-performance liquid chromatography (UHPLC) and gas chromatography (GC) coupled with mass spectrometry (MS) technology as well as multiple statistical analyses were used to comprehensively evaluate the compositional variation of polar and volatile compounds in RB under different processing processes. Meanwhile, in UHPLC-MS, a sequential window acquisition of all theoretical fragment ion spectral and information-dependent acquisition mutual authentication (SIMA) was developed.

RESULTS

A total of 30 polar components and 33 volatile components were identified as chemical markers (mainly type II saikosaponins, terpenes, and fatty acid esters). These may be the material basis for giving unique pharmacological activities to RB and its processed products.

CONCLUSIONS

These findings provided a solid foundation for the differentiated clinical application of RB, and the SIMA method held great potential for achieving accurate analysis of TCM processing ingredients.

Lycium barbarum polysaccharides regulate the gut microbiota to modulate metabolites in high-fat diet-induced obese rats

Lycium Barbarum Polysaccharides (LBP) can benefit lipid parameters such as total cholesterol, triglyceride, and high-density lipoprotein levels and upregulate the level of Firmicutes, increase the diversity of gut microbiota and reduce metabolic disorders, finally relieving weight gain of obese rats. But it cannot reverse the outcome of obesity. Over 30 differential metabolites and four pathways are altered by LBP.

Synergistic Biocontrol and Growth Promotion in Strawberries by Co-Cultured Trichoderma harzianum TW21990 and Burkholderia vietnamiensis B418

This study aimed to investigate the efficiency of the secondary metabolites (SMs) produced by a co-culture of Trichoderma harzianum TW21990 and Burkholderia vietnamiensis B418 in the control of Colletotrichum siamense CM9. A fermentation filtrate of B418 + TW21990 co-culture (BT21) produced a notable increase in the inhibition rate of CM9 compared to those of TW21990 and B418 monocultures, which reached 91.40% and 80.46% on PDA plates and strawberry leaves, respectively. The BT21 fermentation broth exhibited high control efficiency on strawberry root rot of 68.95% in a pot experiment, which was higher than that in the monocultures and fluazinam treatment. In addition, BT21 treatment promoted strawberry root development, improved antioxidative enzyme activities in the leaves and roots, and enhanced the total chlorophyll content of the strawberry leaves. UHPLC-MS/MS analysis of fermentation filtrates was performed to elucidate SM variations, revealing 478 and 795 metabolites in BT21 co-culture in positive and negative ion modes, respectively. The metabolomic profiles suggested abundant SMs with antagonistic capabilities and growth-promoting effects: 3-(propan-2-yl)-octahydropyrrolo [1,2-a]pyrazine-1,4-dione (cyclo(L-Pro-L-Val)), 3-[(4-hydroxyphenyl)methyl]-octahydropyrrolo[1,2-a]pyrazine-1,4-dione (cyclo(L-Pro-L-Tyr)), 3-indoleacetic acid (IAA), 2-hydroxycinnamic acid, 4-aminobutyric acid (GABA), bafilomycin B1, and DL-indole-3-lactic acid (ILA) were significantly enhanced in the co-culture. Overall, this study demonstrates that a co-culture strategy is efficient for inducing bioactive SMs in T. harzianum and B. vietnamiensis, which could be exploited as a novel approach for developing biocontrol consortia.

Immune signature of patients with cardiovascular disease predicts increased risk for a severe course of COVID-19

Severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) infection can lead to life-threatening clinical manifestations. Patients with cardiovascular disease (CVD) are at higher risk for severe courses of COVID-19. So far, however, there are hardly any strategies for predicting the course of SARS-CoV-2 infection in CVD patients at hospital admission. Thus, we investigated whether this prediction is achievable by prospectively analysing the blood immunophenotype of 94 nonvaccinated participants, including uninfected and acutely SARS-CoV-2-infected CVD patients and healthy donors, using a 36-colour spectral flow cytometry panel. Unsupervised data analysis revealed little differences between healthy donors and CVD patients, whereas the distribution of the cell populations changed dramatically in SARS-CoV-2-infected CVD patients. The latter had more mature NK cells, activated monocyte subsets, central memory CD4+ T cells, and plasmablasts but fewer dendritic cells, CD16+ monocytes, innate lymphoid cells, and CD8+ T-cell subsets. Moreover, we identified an immune signature characterised by CD161+ T cells, intermediate effector CD8+ T cells, and natural killer T (NKT) cells that is predictive for CVD patients with a severe course of COVID-19. Thus, intensified immunophenotype analyses can help identify patients at risk of severe COVID-19 at hospital admission, improving clinical outcomes through specific treatment.

An exploratory metabolomic study reveals the Dipsacus asper-Achyranthes bidentate herb pair against osteoarthritis by modulating imbalance in polyunsaturated fatty acids and energy metabolism

Osteoarthritis (OA) is a degenerative joint disease primarily affecting the cartilage. The therapeutic potential of the Dipsacus asper-Achyranthes bidentate herb pair for OA has been acknowledged, yet its precise mechanism remains elusive. In this study, we conducted a comprehensive analysis of metabolomic changes and therapeutic outcomes in osteoarthritic rats, employing a gas chromatography-mass spectrometry-based metabolomics approach in conjunction with histopathological and biochemical assessments. The rats were divided into six groups: control, model, positive control, Dipsacus asper treated, Achyranthes bidentata treated, and herb pair treated groups. Compared to the model group, significant reductions in levels of tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), interleukin-6 (IL-6), and iNOS were observed in the treated groups. Multivariate statistical analyses were employed to investigate metabolite profile changes in serum samples and identify potential biomarkers, revealing 45 differential biomarkers, with eighteen validated using standard substances. These analytes exhibited excellent linearity across a wide concentration range (R2>0.9990), with intra- and inter-day precision RSD values below 4.69% and 4.83%, respectively. Recoveries of the eighteen analytes ranged from 93.97% to 106.59%, with RSD values under 5.72%, underscoring the method's reliability. Treatment with the herbal pair effectively restored levels of unsaturated fatty acids such as linoleic acid and arachidonic acid, along with glucogenic amino acids. Additionally, levels of phosphoric acid and citric acid were reversed, indicating restoration of energy metabolism. Collectively, these findings highlight the utility of metabolomic analysis in evaluating therapeutic efficacy and elucidating the underlying molecular mechanisms of herb pairs in OA treatment.

Correlation between climatic environment and characteristic components of 14 kinds of huajiao by thermal analysis techniques, GC-MS and HS-IMS

Huajiao (Zanthoxylum bungeanum Maxim.) is extensively cultivated in various countries, including China, Korea, and India, owing to its adaptability to diverse environments. This study comprehensively analyzed the volatile substance composition of 14 varieties of red huajiao with distinct geographical origins. Thermal analysis methods, gas chromatography-mass spectrometry (GC-MS), and headspace-ion mobility chromatography (HS-IMS) were employed to evaluate the total volatile substance composition and content. The study revealed minor variations in water content, volatile matter content, and fractions among the geographically sourced huajiao samples. Utilizing correlation analysis based on GC-MS and orthogonal partial least squares discriminant analysis (OPLS-DA) with HS-IMS, a robust classification method for the 14 types of huajiao was developed. Applying the variable importance in the projection (VIP) method, seven distinctive components were identified as potential markers for distinguishing the geographical origins of red huajiao. By integrating climatic and topographical factors of the 14 huajiao varieties, the correlation analysis of GC-MS, and OPLS-DA classification outcomes from HS-IMS elucidated the influence of geo-environmental factors on huajiao components and contents. This research provides insights into the impact of diverse geographic environments on the constituents and characteristics of huajiao. It offers valuable guidance for selecting optimal cultivation locations to enhance huajiao quality, aiding consumers in making informed choices.

Region-Specific Effects of Metformin on Gut Microbiome and Metabolome in High-Fat Diet-Induced Type 2 Diabetes Mouse Model

The glucose-lowering drug metformin alters the composition of the gut microbiome in patients with type 2 diabetes mellitus (T2DM) and other diseases. Nevertheless, most studies on the effects of this drug have relied on fecal samples, which provide limited insights into its local effects on different regions of the gut. Using a high-fat diet (HFD)-induced mouse model of T2DM, we characterize the spatial variability of the gut microbiome and associated metabolome in response to metformin treatment. Four parts of the gut as well as the feces were analyzed using full-length sequencing of 16S rRNA genes and targeted metabolomic analyses, thus providing insights into the composition of the microbiome and associated metabolome. We found significant differences in the gut microbiome and metabolome in each gut region, with the most pronounced effects on the microbiomes of the cecum, colon, and feces, with a significant increase in a variety of species belonging to Akkermansiaceae, Lactobacillaceae, Tannerellaceae, and Erysipelotrichaceae. Metabolomics analysis showed that metformin had the most pronounced effect on microbiome-derived metabolites in the cecum and colon, with several metabolites, such as carbohydrates, fatty acids, and benzenoids, having elevated levels in the colon; however, most of the metabolites were reduced in the cecum. Thus, a wide range of beneficial metabolites derived from the microbiome after metformin treatment were produced mainly in the colon. Our study highlights the importance of considering gut regions when understanding the effects of metformin on the gut microbiome and metabolome.

Multivariate curve resolution-based data fusion approaches applied in 1H NMR metabolomic analysis of healthy cohorts

BACKGROUND

Metabolomics plays a critical role in deciphering metabolic alterations within individuals, demanding the use of sophisticated analytical methodologies to navigate its intricate complexity. While many studies focus on single biofluid types, simultaneous analysis of multiple matrices enhances understanding of complex biological mechanisms. Consequently, the development of data fusion methods enabling multiblock analysis becomes essential for comprehensive insights into metabolic dynamics.

RESULTS

This study introduces a novel guideline for jointly analyzing diverse metabolomic datasets (serum, urine, metadata) with a focus on metabolic differences between groups within a healthy cohort. The guideline presents two fusion strategies, 'Low-Level data fusion' (LLDF) and 'Mid-Level data fusion' (MLDF), employing a sequential application of Multivariate Curve Resolution with Alternating Least Squares (MCR-ALS), linking the outcomes of successive analyses. MCR-ALS is a versatile method for analyzing mixed data, adaptable at various stages of data processing-encompassing resonance integration, data compression, and exploratory analysis. The LLDF and MLDF strategies were applied to 1H NMR spectral data extracted from urine and serum samples, coupled with biochemical metadata sourced from 145 healthy volunteers.

SIGNIFICANCE

Both methodologies effectively integrated and analysed multiblock datasets, unveiling the inherent data structure and variables associated with discernible factors among healthy cohorts. While both approaches successfully detected sex-related differences, the MLDF strategy uniquely revealed components linked to age. By applying this analysis, we aim to enhance the interpretation of intricate biological mechanisms and uncover variations that may not be easily discernible through individual data analysis.

LC-MS metabolomics analysis of serum metabolites during neoadjuvant chemoradiotherapy in locally advanced rectal cancer

BACKGROUND

This study aimed to investigate the serum metabolite profiles during neoadjuvant chemoradiotherapy (NCRT) in locally advanced rectal cancer (LARC) using liquid chromatography-mass spectrometry (LC-MS) metabolomics analysis.

METHODS

60 serum samples were collected from 20 patients with LARC before, during, and after radiotherapy. LC-MS metabolomics analysis was performed to identify the metabolite variations. Functional annotation was applied to discover altered metabolic pathways. The key metabolites were screened and their ability to predict sensitivity to radiotherapy was calculated using random forests and ROC curves.

RESULTS

The results showed that NCRT led to significant changes in the serum metabolite profiles. The serum metabolic profiles showed an apparent separation between different time points and different sensitivity groups. Moreover, the functional annotation showed that the differential metabolites were associated with a series of important metabolic pathways. Pre-radiotherapy (3Z,6Z)-3,6-Nonadiena and pro-radiotherapy 1-Hydroxyibuprofen showed good predictive performance in discriminating the sensitive and non-sensitive group to NCRT, with an AUC of 0.812 and 0.75, respectively. Importantly, the combination of different metabolites significantly increased the predictive ability.

CONCLUSION

This study demonstrated the potential of LC-MS metabolomics for revealing the serum metabolite profiles during NCRT in LARC. The identified metabolites may serve as potential biomarkers and therapeutic targets for the management of this disease. Furthermore, the understanding of the affected metabolic pathways may help design more personalized therapeutic strategies for LARC patients.

Impact of chronic exposure to field level glyphosate on the food consumption, survival, gene expression, gut microbiota, and metabolomic profiles of honeybees

Glyphosate (GLY) is among the most widely used pesticides in the world. However, there are a lot of unknowns about chronic exposure to GLY's effects on Honeybee (HB) behavior and physiology. To address this, we carried out five experiments to study the impact of chronic exposure to 5 mg/kg GLY on sugar consumption, survival, gene expression, gut microbiota, and metabolites of HB workers. Our results find a significant decrease in sugar consumption and survival probability of HB after chronic exposure to GLY. Further, genes associated with immune response, energy metabolism, and longevity were conspicuously altered. In addition, a total of seven metabolites were found to be differentially expressed in the metabolomic profiles, mainly related the sucrose metabolism. There was no significant difference in the gut microbiota. Results suggest that chronic exposure to field-level GLY altered the health of HB and the intricate toxic mechanisms. Our data provided insights into the chronic effects of GLY on HB behavior in food intake and health, which represents the field conditions where HB are exposed to pesticides over extended periods.

Identifying Anti-NSCLC Bioactive Compounds in Scutellaria via 2D NMR-Based Metabolomic Analysis of Pharmacologically Classified Crude Extracts

We presented a strategy utilizing 2D NMR-based metabolomic analysis of crude extracts, categorized by different pharmacological activities, to rapidly identify the primary bioactive components of TCM. It was applied to identify the potential bioactive components from Scutellaria crude extracts that exhibit anti-non-small cell lung cancer (anti-NSCLC) activity. Four Scutellaria species were chosen as the study subjects because of their close phylogenetic relationship, but their crude extracts exhibit significantly different anti-NSCLC activity. Cell proliferation assay was used to assess the anti-NSCLC activity of four species of Scutellaria. 1H-13C HSQC spectra were acquired for the chemical profiling of these crude extracts. Based on the pharmacological classification (PCA, OPLS-DA and univariate hypothesis test) were performed to identify the bioactive constituents in Scutellaria associated with the anti-NSCLC activity. As a result, three compounds, baicalein, wogonin and scutellarin were identified as bioactive compounds. The anti-NSCLC activity of the three potential active compounds were further confirmed via cell proliferation assay. The mechanism of the anti-NSCLC activity by these active constituents was further explored via flow cytometry and western blot analyses. This study demonstrated 2D NMR-based metabolomic analysis of pharmacologically classified crude extracts to be an efficient approach to the identification of active components of herbal medicine.

Let-7 microRNA targets BmCentrin to modulate the development and functionality of the middle silk gland in the silkworm, Bombyx mori

The silk gland of the silkworm Bombyx mori serves as a valuable model for investigating the morphological structure and physiological functions of organs. Previous studies have demonstrated the notable regulatory role of let-7 microRNA in the silk gland, but its specific molecular mechanism remains to be elucidated across different segments of this organ. In this study, we further investigated the functional mechanism of let-7 in the middle silk gland (MSG). The MSG of a let-7 knockout strain was analyzed using a combined proteomic and metabolomic technique, revealing the enrichment of differential proteins and metabolites in the DNA synthesis and energy metabolism pathways. BmCentrin was identified as a novel target gene of let-7 in the MSG, and its downregulation inhibited the proliferation of BmN4-SID1 cells, which is exactly opposite to the role of let-7 in these cells. CRISPR/Cas9 genome editing and transgenic technologies were employed to manipulate BmCentrin in the MSG. Knockout of BmCentrin led to severe MSG atrophy, whereas the overexpression of BmCentrin resulted in beaded MSG. Further measurements of these knockout or overexpression strains revealed significant changes in the expression levels of sericin protein genes, the weight of the cocoon and the mechanical properties of the silk. Investigating the biological role of BmCentrin in the silk gland offers valuable insights for elucidating the molecular mechanisms by which let-7 controls silk gland development and silk protein synthesis in the silkworm.

Advancements in metabolomics research in benign gallbladder diseases: A review

The burgeoning field of metabolomics has piqued the interest of researchers in the context of benign gallbladder diseases, which include conditions such as gallbladder polyps, gallstones, and cholecystitis, which are common digestive system disorders. As metabolomics continues to advance, researchers have increasingly focused their attention on its applicability in the study of benign gallbladder diseases to provide new perspectives for diagnostic, therapeutic, and prognostic evaluation. This comprehensive review primarily describes the techniques of liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry, and nuclear magnetic resonance and their respective applications in the study of benign gallbladder disease. Metabolomics has made remarkable progress in various aspects of these diseases, ranging from early diagnosis, etiological research, assessment of disease progression and prognosis, and optimization of therapeutic strategies. However, challenges remain in the field of metabolomics in the study of benign gallbladder diseases. These include issues related to data processing and analysis, biomarker discovery and validation, interdisciplinary research integration, and the advancement of personalized medicine. This article attempts to summarize research findings to date, highlight future research directions, and provide a reference point for metabolomics research in benign gallbladder disease.

Photoperiod-Dependent Nutrient Accumulation in Rice Cultivated in Plant Factories: A Comparative Metabolomic Analysis

Plant factories offer a promising solution to some of the challenges facing traditional agriculture, allowing for year-round rapid production of plant-derived foods. However, the effects of conditions in plant factories on metabolic nutrients remain to be explored. In this study, we used three rice accessions (KongYu131, HuangHuaZhan, and Kam Sweet Rice) as objectives, which were planted in a plant factory with strict photoperiods that are long-day (12 h light/12 h dark) or short-day (8 h light/16 h dark). A total of 438 metabolites were detected in the harvested rice grains. The difference in photoperiod leads to a different accumulation of metabolites in rice grains. Most metabolites accumulated significantly higher levels under the short-day condition than the long-day condition. Differentially accumulated metabolites were enriched in the amino acids and vitamin B6 pathway. Asparagine, pyridoxamine, and pyridoxine are key metabolites that accumulate at higher levels in rice grains harvested from the short-day photoperiod. This study reveals the photoperiod-dependent metabolomic differences in rice cultivated in plant factories, especially the metabolic profiling of taste- and nutrition-related compounds.

Combined pesticides in field doses weaken honey bee (Apis cerana F.) flight ability and analyses of transcriptomics and metabolomics

Imidacloprid, chlorpyrifos, and glyphosate rank among the most extensively employed pesticides worldwide. The effects of these pesticides and their combined on the flight capability of Apis cerana, and the potential underlying mechanisms remain uncertain. To investigate these effects, we carried out flight mill, transcriptome, and metabolome experiments. Our findings reveal that individual acute oral treatments with pesticides, specifically 20 μL of 10 ng/g imidacloprid (0.2 ng per bee), 30 ng/g chlorpyrifos (0.6 ng per bee), and 60 ng/g glyphosate (1.2 ng per bee), did not impact the flight capability of the bees. However, when bees were exposed to a combination of two or three pesticides, a notable reduction in flight duration and distance was observed. In the transcriptomic and metabolomic analyses, we identified 307 transcripts and 17 metabolites that exhibited differential expression following exposure to combined pesticides, primarily associated with metabolic pathways involved in energy regulation. Our results illuminate the intricate effects and potential hazards posed by combined pesticide exposures on bee behavior. These findings offer valuable insights into the synergistic potential of pesticide combinations and their capacity to impair bee behavior. Understanding these complex interactions is essential for comprehending the broader consequences of pesticide formulations on honey bee populations.

Analysis of the mechanism of curcumin against osteoarthritis using metabolomics and transcriptomics

Curcumin, a polyphenolic compound derived from the turmeric plant (Curcuma longa), has been extensively studied for its anti-inflammatory and anti-proliferative properties. The safety and efficacy of curcumin have been thoroughly validated. Nevertheless, the underlying mechanism for treating osteoarthritis remains ambiguous. This study aims to reveal the potential mechanism of curcumin in treating osteoarthritis by using metabolomics and transcriptomics. Firstly, we validated the effect of curcumin on inflammatory factors in human articular chondrocytes. Secondly, we explored the cellular metabolism mechanism of curcumin against osteoarthritis using cell metabolomics. Thirdly, we assessed the differences in gene expression of human articular chondrocytes through transcriptomics. Lastly, to evaluate the essential targets and elucidate the potential mechanism underlying the therapeutic effects of curcumin in osteoarthritis, we conducted a screening of the proteins within the shared pathway of metabolomics and transcriptomics. Our results demonstrated that curcumin significantly decreased the levels of inflammatory markers, such as IL-β, IL-6, and TNF-α, in human articular chondrocytes. Cell metabolomics identified 106 differential metabolites, including beta-aminopropionitrile, 3-amino-2-piperidone, pyrrole-2-carboxaldehyde, and various other components. The transcriptomic analysis yielded 1050 differential mRNAs. Enrichment analysis showed that the differential metabolites and mRNAs were significantly enriched in seven pathways, including glycine, serine, and threonine metabolism; pentose and glucuronate interconversions; glycerolipid metabolism; histidine metabolism; mucin-type o-glycan biosynthesis; inositol phosphate metabolism; and cysteine and methionine metabolism. A total of 23 key targets were identified to be involved in these pathways. We speculate that curcumin may alleviate osteoarthritis by targeting key proteins involved in glycine, serine, and threonine metabolism; inhibiting pyruvate production; and modulating glycolysis.

Key components, formation pathways, affecting factors, and emerging analytical strategies for edible mushrooms aroma: A review

Aroma is one of the decisive factors affecting the quality and consumer acceptance of edible mushrooms. This review summarized the key components and formation pathways of edible mushroom aroma. It also elaborated on the affecting factors and emerging analytical strategies of edible mushroom aroma. A total of 1308 volatile organic compounds identified in edible mushrooms, 61 were key components. The formation of these compounds is closely related to fatty acid metabolism, amino acid metabolism, lentinic acid metabolism, and terpenoid metabolism. The aroma profiles of edible mushrooms were affected by genetic background, preharvest factors, and preservation methods. Molecular sensory science and omics techniques are emerging analytical strategies to reveal aroma information of edible mushrooms. This review would provide valuable data and insights for future research on edible mushroom aroma.

Integrative metabolomic and transcriptomic analyses reveals the accumulation patterns of key metabolites associated with flavonoids and terpenoids of Gynostemma pentaphyllum (Thunb.) Makino

Gynostemma pentaphyllum (Thunb.) Makino (G. pentaphyllum) is a medicinal and edible plant with multiple functions of liver protection, anti-tumor, anti-inflammation, balancing blood sugar and blood lipids. The nutritional value of the G. pentaphyllum plant is mainly due to its rich variety of biologically active substances, such as flavonoids, terpenes and polysaccharides. In this study, we performed a comprehensive analysis combining metabolomics and root, stem and leaf transcriptomic data of G. pentaphyllum. We used transcriptomics and metabolomics data to construct a dynamic regulatory network diagram of G. pentaphyllum flavonoids and terpenoids, and screened the transcription factors involved in flavonoids and terpenoids, including basic helix-loop-helix (bHLH), myb-related, WRKY, AP2/ERF. Transcriptome analysis results showed that among the DEGs related to the synthesis of flavonoids and terpenoids, dihydroflavonol 4-reductase (DFR) and geranylgeranyl diphosphate synthases (GGPPS) were core genes. This study presents a dynamic image of gene expression in different tissues of G. pentaphyllum, elucidating the key genes and metabolites of flavonoids and terpenoids. This study is beneficial to a deeper understanding of the medicinal plants of G. pentaphyllum, and also provides a scientific basis for further regulatory mechanisms of plant natural product synthesis pathways and drug development.

Comparative physiology and transcriptome response patterns in cold-tolerant and cold-sensitive varieties of Solanum melongena

BACKGROUND

Climate change has led to severe cold events, adversely impacting global crop production. Eggplant (Solanum melongena L.), a significant economic crop, is highly susceptible to cold damage, affecting both yield and quality. Unraveling the molecular mechanisms governing cold resistance, including the identification of key genes and comprehensive transcriptional regulatory pathways, is crucial for developing new varieties with enhanced tolerance.

RESULTS

In this study, we conducted a comparative analysis of leaf physiological indices and transcriptome sequencing results. The orthogonal partial least squares discriminant analysis (OPLS-DA) highlighted peroxidase (POD) activity and soluble protein as crucial physiological indicators for both varieties. RNA-seq data analysis revealed that a total of 7024 and 6209 differentially expressed genes (DEGs) were identified from variety "A" and variety "B", respectively. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment of DEGs demonstrated that the significant roles of starch and sucrose metabolism, glutathione metabolism, terpenoid synthesis, and energy metabolism (sucrose and starch metabolism) were the key pathways in eggplant. Weighted gene co-expression network analysis (WGCNA) shown that the enrichment of numerous cold-responsive genes, pathways, and soluble proteins in the MEgrep60 modules. Core hub genes identified in the co-expression network included POD, membrane transporter-related gene MDR1, abscisic acid-related genes, growth factor enrichment gene DELLA, core components of the biological clock PRR7, and five transcription factors. Among these, the core transcription factor MYB demonstrated co-expression with signal transduction, plant hormone, biosynthesis, and metabolism-related genes, suggesting a pivotal role in the cold response network.

CONCLUSION

This study integrates physiological indicators and transcriptomics to unveil the molecular mechanisms responsible for the differences in cold tolerance between the eggplant cold-tolerant variety "A" and the cold-sensitive variety "B". These mechanisms include modulation of reactive oxygen species (ROS), elevation in osmotic carbohydrate and free proline content, and the expression of terpenoid synthesis genes. This comprehensive understanding contributes valuable insights into the molecular underpinnings of cold stress tolerance, ultimately aiding in the improvement of crop cold tolerance.

Pulchinenoside B4 ameliorates oral ulcers in rats by modulating gut microbiota and metabolites

Pulchinenoside B4, a natural saponin monomer from the Pulsatilla plant, plays an important role as an immunomodulator in the treatment of acute inflammation. Oral ulcer (OU) is a common ulcerative injury disease that occurs in the oral mucosa, including mucosal ulceration and abnormalities of lips and tongue. A close correlation exists between gut microbiota and circulating metabolites in patients with OU. However, the correlation between gut microbiota and serum metabolomics is not clear. Therefore, this study aimed to explore the changes in gut microbiota and metabolites in OU. The 16S ribosomal RNA (16S rRNA) gene sequencing was used to detect the changes in the composition of gut microbiota in OU rat model. Moreover, the endogenous small metabolites were explored by collecting the non-targeted serum metabolomics data. A total of 34 OU-related biomarkers were identified, mainly related to fatty acid metabolism and inflammatory pathways. The administration of B4 effectively reduced the occurrence of OU and restored the levels of multiple endogenous biomarkers and key gut microbial species to the normal level. This study demonstrated that the gut microbiota and metabolites were altered in the OU rat model, which were significantly restored to the normal level by B4, thereby showing good application prospects in the treatment of OU. KEY POINTS: • The first investigating the correlation between OU and gut microbiota. • A close correlation between metabolites and gut microbiota in OU disease was successfully identified. • Pulchinenoside B4 ameliorates oral ulcers in rats by modulating gut microbiota and metabolites.

LC-HRMS-Driven Computational Toolbox to Assess Extraction Protocols Dedicated to Untargeted Analysis: How to Ease Analyzing Pesticide-Contaminated Soils?

Metabolomics is a powerful approach that allows for high throughput analysis and the acquisition of large biochemical data. Nonetheless, it still faces several challenging requirements, such as the development of optimal extraction and analytical methods able to respond to its high qualitative and quantitative requisites. Hence, the objective of the present article is to suggest a LC-HRMS-based untargeted profiling approach aiming to provide performant tools that help assess the performance and the quality of extraction methods. It is applied in a herbicide-contaminated soil metabolomics context. The trifactorial experimental design consists of 150 samples issued from five different extraction protocols, two types of soils, and three contamination conditions (contaminated soils with two different formulated herbicides against uncontaminated soils). Four performance and quality criteria are investigated using adapted LC-HRMS-driven computational tools. First, 861 metabolic features are annotated, and then the width of metabolome coverage and quantitative performance of the five different extraction protocols are assessed in all samples using various optimized configurations of heatmaps as well as van Krevelen diagrams. Then, the reproducibility of LC-HRMS profiles issued from the five extractions is studied by two different approaches: Euclidean distances and relative standard deviations. The two methods are examined and compared. Their advantages and limitations are thus discussed. After, the capacity of the different extractions to discriminate between contaminated and uncontaminated soils will be evaluated using orthogonal projections to latent structures-discriminant analysis. Different data scaling parameters are tested, and the results are explored and discussed. All of the suggested computational and visualization tools are performed using public-access platforms or open-source software. They can be readapted by metabolomics developers and users according to their study contexts and fields of application.

Wekemo Bioincloud: A user-friendly platform for meta-omics data analyses

The increasing application of meta-omics approaches to investigate the structure, function, and intercellular interactions of microbial communities has led to a surge in available data. However, this abundance of human and environmental microbiome data has exposed new scalability challenges for existing bioinformatics tools. In response, we introduce Wekemo Bioincloud-a specialized platform for -omics studies. This platform offers a comprehensive analysis solution, specifically designed to alleviate the challenges of tool selection for users in the face of expanding data sets. As of now, Wekemo Bioincloud has been regularly equipped with 22 workflows and 65 visualization tools, establishing itself as a user-friendly and widely embraced platform for studying diverse data sets. Additionally, the platform enables the online modification of vector outputs, and the registration-independent personalized dashboard system ensures privacy and traceability. Wekemo Bioincloud is freely available at https://www.bioincloud.tech/.

Molecular and metabolic insights into purplish leaf coloration through the investigation of two mulberry (Morus alba) genotypes

BACKGROUND

Leaf coloration in plants, attributed to anthocyanin compounds, plays a crucial role in various physiological functions, and also for pharmaceutical and horticultural uses. However, the molecular mechanisms governing leaf coloration and the physiological significance of anthocyanins in leaves remain poorly understood.

RESULTS

In this study, we investigated leaf color variation in two closely related mulberry genotypes, one with purplish-red young leaves (EP) and another with normal leaf color (EW). We integrated transcriptomic and metabolomic approaches to gain insights into the metabolic and genetic basis of purplish-red leaf development in mulberry. Our results revealed that flavonoid biosynthesis, particularly the accumulation of delphinidin-3-O-glucoside, is a key determinant of leaf color. Additionally, the up-regulation of CHS genes and transcription factors, including MYB family members, likely contributes to the increased flavonoid content in purplish-red leaves.

CONCLUSION

These findings enhance our understanding of the molecular mechanisms responsible for the purplish coloration observed in mulberry leaves and also offer supporting evidence for the hypothesis that anthocyanins serve a protective function in plant tissues until the processes of light absorption and carbon fixation reach maturity, thereby ensuring a balanced equilibrium between energy capture and utilization.

Mixture effects of pharmaceuticals carbamazepine, diclofenac and venlafaxine on Mytilus galloprovincialis mussel probed by metabolomics and proteogenomics combined approach

Exposure to single molecules under laboratory conditions has led to a better understanding of the mechanisms of action (MeOAs) and effects of pharmaceutical active compounds (PhACs) on non-target organisms. However, not taking the co-occurrence of contaminants in the environment and their possible interactions into account may lead to underestimation of their impacts. In this study, we combined untargeted metabolomics and proteogenomics approaches to assess the mixture effects of diclofenac, carbamazepine and venlafaxine on marine mussels (Mytilus galloprovincialis). Our multi-omics approach and data fusion strategy highlighted how such xenobiotic cocktails induce important cellular changes that can be harmful to marine bivalves. This response is mainly characterized by energy metabolism disruption, fatty acid degradation, protein synthesis and degradation, and the induction of endoplasmic reticulum stress and oxidative stress. The known MeOAs and molecular signatures of PhACs were taken into consideration to gain insight into the mixture effects, thereby revealing a potential additive effect. Multi-omics approaches on mussels as sentinels offer a comprehensive overview of molecular and cellular responses triggered by exposure to contaminant mixtures, even at environmental concentrations.

Identifying subgroups of childhood obesity by using multiplatform metabotyping

Introduction: Obesity results from an interplay between genetic predisposition and environmental factors such as diet, physical activity, culture, and socioeconomic status. Personalized treatments for obesity would be optimal, thus necessitating the identification of individual characteristics to improve the effectiveness of therapies. For example, genetic impairment of the leptin-melanocortin pathway can result in rare cases of severe early-onset obesity. Metabolomics has the potential to distinguish between a healthy and obese status; however, differentiating subsets of individuals within the obesity spectrum remains challenging. Factor analysis can integrate patient features from diverse sources, allowing an accurate subclassification of individuals. Methods: This study presents a workflow to identify metabotypes, particularly when routine clinical studies fail in patient categorization. 110 children with obesity (BMI > +2 SDS) genotyped for nine genes involved in the leptin-melanocortin pathway (CPE, MC3R, MC4R, MRAP2, NCOA1, PCSK1, POMC, SH2B1, and SIM1) and two glutamate receptor genes (GRM7 and GRIK1) were studied; 55 harboring heterozygous rare sequence variants and 55 with no variants. Anthropometric and routine clinical laboratory data were collected, and serum samples processed for untargeted metabolomic analysis using GC-q-MS and CE-TOF-MS and reversed-phase U(H)PLC-QTOF-MS/MS in positive and negative ionization modes. Following signal processing and multialignment, multivariate and univariate statistical analyses were applied to evaluate the genetic trait association with metabolomics data and clinical and routine laboratory features. Results and Discussion: Neither the presence of a heterozygous rare sequence variant nor clinical/routine laboratory features determined subgroups in the metabolomics data. To identify metabolomic subtypes, we applied Factor Analysis, by constructing a composite matrix from the five analytical platforms. Six factors were discovered and three different metabotypes. Subtle but neat differences in the circulating lipids, as well as in insulin sensitivity could be established, which opens the possibility to personalize the treatment according to the patients categorization into such obesity subtypes. Metabotyping in clinical contexts poses challenges due to the influence of various uncontrolled variables on metabolic phenotypes. However, this strategy reveals the potential to identify subsets of patients with similar clinical diagnoses but different metabolic conditions. This approach underscores the broader applicability of Factor Analysis in metabotyping across diverse clinical scenarios.

Rapid authentication of red wine by MALDI-MS combined with DART-MS

A simple, rapid and high-throughput approach was developed for authentication of red wine for the first time, by combining spectral results from matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) and direct analysis in real time mass spectrometry (DART-MS). By coupling with orthogonal partial least squares discrimination analysis (OPLS-DA), this approach enabled successful classification of 535 wines from 8 countries, with the correct classification rates of 100% on the calibration set and over 90% on the validation set for almost all countries, and 26 potential characteristic markers selected. Compared to one single technique, this approach allowed detection of more compound ions, and with better fitting and predictive performances. The satisfactory differentiation results of vintages and grape varieties further verified the robustness of the approach. This study demonstrated the feasibility of combining multiple mass spectrometric techniques for wine analysis, which can be extended to other fields or to combinations of other analytical techniques.

Metabolome subtyping reveals multi-omics characteristics and biological heterogeneity in major psychiatric disorders

Growing evidence suggests that major psychiatric disorders (MPDs) share common etiologies and pathological processes. However, the diagnosis is currently based on descriptive symptoms, which ignores the underlying pathogenesis and hinders the development of clinical treatments. This highlights the urgency of characterizing molecular biomarkers and establishing objective diagnoses of MPDs. Here, we collected untargeted metabolomics, proteomics and DNA methylation data of 327 patients with MPDs, 131 individuals with genetic high risk and 146 healthy controls to explore the multi-omics characteristics of MPDs. First, differential metabolites (DMs) were identified and we classified MPD patients into 3 subtypes based on DMs. The subtypes showed distinct metabolomics, proteomics and DNA methylation signatures. Specifically, one subtype showed dysregulation of complement and coagulation proteins, while the DNA methylation showed abnormalities in chemical synapses and autophagy. Integrative analysis in metabolic pathways identified the important roles of the citrate cycle, sphingolipid metabolism and amino acid metabolism. Finally, we constructed prediction models based on the metabolites and proteomics that successfully captured the risks of MPD patients. Our study established molecular subtypes of MPDs and elucidated their biological heterogeneity through a multi-omics investigation. These results facilitate the understanding of pathological mechanisms and promote the diagnosis and prevention of MPDs.

1H NMR Metabolomics on Pigs' Liver Exposed to Antibiotics Administration: An Explorative Study

An untargeted Nuclear Magnetic Resonance (NMR) spectroscopy-based metabolomics approach was applied as a first attempt to explore the metabolome of pigs treated with antibiotics. The final goal was to investigate the possibility of discriminating between antibiotic-treated (TX group) and untreated pigs (CTRL group), with the further perspective of identifying the authentication tools for antibiotic-free pork supply chains. In particular, 41 samples of pig liver were subjected to a biphasic extraction to recover both the polar and the non-polar metabolites, and the 1H NMR spectroscopy analysis was performed on the two separate extracts. Unsupervised (principal component analysis) and supervised (orthogonal partial least squares discriminant analysis) multivariate statistical analysis of 1H NMR spectra data in the range 0-9 ppm provided metabolomic fingerprinting useful for the discrimination of pig livers based on the antibiotic treatment to which they were exposed. Moreover, within the signature patterns, significant discriminating metabolites were identified among carbohydrates, choline and derivatives, amino acids and some lipid-class molecules. The encouraging findings of this exploratory study showed the feasibility of the untargeted metabolomic approach as a novel strategy in the authentication framework of pork supply chains and open a new horizon for a more in-depth investigation.

Metabolomics insights into the effects of pre-pregnancy lead exposure on bone metabolism in pregnant rats

Today's women of childbearing age with a history of high lead (Pb) exposure in childhood have large Pb body burdens, which increases Pb release during pregnancy by promoting bone Pb mobilisation. The purpose of this study was to investigate the metabolic mechanisms underlying bone Pb mobilisation and explore the bone metabolism-related pathways during pregnancy. Drinking water containing 0.05% sodium acetate or Pb acetate was provided to weaned female rats for 4 weeks followed by a 4-week washout period, and then rats were co-caged with healthy males of the same age until pregnancy. Blood and bone tissues of the female rats were collected at gestational day (GD) 3 (early pregnancy), GD 10 (middle pregnancy), and GD 17 (late pregnancy), respectively. Pb and calcium concentrations, biomarkers for bone turnover, bone microstructure, serum metabolomics, and metabolic indicators were intensively analyzed. The results demonstrated that pre-pregnancy Pb exposure elevated blood lead levels (BLLs) at GD17, accompanied by a negative correlation between BLLs and trabecular bone Pb levels. Meanwhile, Pb-exposed rats had low bone mass and aberrant bone architecture with a larger number of mature osteoclasts (OCs) compared to the control group. Moreover, the metabolomics uncovered that Pb exposure caused mitochondrial dysfunction, such as enhanced oxidative stress and inflammatory response, and suppressed energy metabolism. Additionally, the levels of ROS, MDA, IL-1β, and IL-18 involved in redox and inflammatory pathways of bone tissues were significantly increased in the Pb-exposed group, while antioxidant SOD and energy metabolism-related indicators including ATP levels, Na+-K+-ATPase, and Ca2+-Mg2+-ATPase activities were significantly decreased. In conclusion, pre-pregnancy Pb exposure promotes bone Pb mobilisation and affects bone microstructure in the third trimester of pregnancy, which may be attributed to OC activation and mitochondrial dysfunction.

Modeling of soluble solid content of PE-packaged blueberries based on near-infrared spectroscopy with back propagation neural network and partial least squares (BP-PLS) algorithm

Blueberries are a nutritious and popular berry worldwide. The physical and chemical properties of blueberries constantly change through the cycle of the supply chain (from harvest to sale). The purpose of this study was to develop a rapid method for detecting the properties of packaged blueberries based on near-infrared (NIR) spectroscopy. NIR was applied to quantitatively determine the soluble solid content (SSC) of polyethylene (PE)-packaged blueberries. An orthogonal partial least squares discriminant analysis model was established to show the correlation between spectral data and the measured SSC. Multiplicative scattering correction, standard normal variable, Savitzky-Golay convolution first derivative, and normalization (Normalize) were used for spectra preprocessing. Uninformative variables elimination, competitive adaptive reweighted sampling, and iteratively retaining informative variables were jointly used for wavelength optimization. NIR-based SSC prediction models for unpacked blueberries and PE-packaged blueberries were developed using partial least squares (PLS). The prediction model for PE-packaged samples (RP 2 = 0.876, root mean square error of prediction [RMSEP] = 0.632) had less precision than the model for unpacked samples (RP 2 = 0.953, RMSEP = 0.611). To reduce the effect of PE, the back propagation (BP) neural network and PLS were combined into the BP-PLS algorithm based on the residual learning algorithm. The model of BP-PLS (RP 2 = 0.947, RMSEP = 0.414) was successfully developed to improve the prediction accuracy of SSC for PE-packaged blueberries. The results suggested a promising way of using the BP-PLS method in tandem with NIR for the rapid detection of the SSC of PE-packaged blueberries. PRACTICAL APPLICATION: Most of the NIR-based research used unpacked blueberries as samples, while the use of packaged blueberries would provide researchers with a better understanding of the crucial factors at different phases of the blueberry supply chain (from harvest to sale). To meet market demands and minimize losses, NIR spectroscopy has been proven to be a rapid and nondestructive method for the determination of the SSC of PE-packaged blueberries. This study provides an effective method for monitoring the properties of blueberries in the entire supply chain.

Untargeted metabolomics analysis on kidney tissues from mice reveals potential hypoxia biomarkers

Chronic hypoxia may have a huge impact on the cardiovascular and renal systems. Advancements in microscopy, metabolomics, and bioinformatics provide opportunities to identify new biomarkers. In this study, we aimed at elucidating the metabolic alterations in kidney tissues induced by chronic hypoxia using untargeted metabolomic analyses. Reverse phase ultrahigh performance liquid chromatography-mass spectroscopy/mass spectroscopy (RP-UPLC-MS/MS) and hydrophilic interaction liquid chromatography (HILIC)-UPLC-MS/MS methods with positive and negative ion mode electrospray ionization were used for metabolic profiling. The metabolomic profiling revealed an increase in metabolites related to carnitine synthesis and purine metabolism. Additionally, there was a notable increase in bilirubin. Heme, N-acetyl-L-aspartic acid, thyroxine, and 3-beta-Hydroxy-5-cholestenoate were found to be significantly downregulated. 3-beta-Hydroxy-5-cholestenoate was downregulated more significantly in male than female kidneys. Trichome Staining also showed remarkable kidney fibrosis in mice subjected to chronic hypoxia. Our study offers potential intracellular metabolite signatures for hypoxic kidneys.

Investigation of the Mechanism of Action of Periploca forrestii Schltr. Extract on Adjuvant Collagen Rats Based on UPLC-Q-Orbitrap-HRMS Non-Targeted Lipidomics

Periploca forrestii Schltr. (P. forrestii) is a classical medicinal plant and is commonly used in traditional medicine for the treatment of rheumatoid arthritis, soft tissue injuries, and traumatic injuries. The aim of this study was to evaluate the anti-arthritic effects of three fractions of P. forrestii alcoholic extracts (PAE), P. forrestii water extracts (PWE), and total flavonoids from P. forrestii (PTF) on Freund's complete adjuvant (FCA)-induced arthritis in rats, and to use a non-targeted lipidomic method to investigate the mechanism of action of the three fractions of P. forrestii in the treatment of rheumatoid arthritis. To assess the effectiveness of anti-rheumatoid arthritis, various indicators were measured, including joint swelling, histopathological changes in the joints, serum cytokines (tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), interleukin-6 (IL-6)), and the joint inflammatory substance prostaglandin E2 (PGE2). Finally, ultra-performance liquid chromatography-quadrupole-orbitrap-high-resolution mass spectrometry (UPLC-Q-Orbitrap-HRMS) was used to determine the non-targeted lipid histology of the collected rat serum and urine samples to investigate the possible mechanism of action. PWE, PAE, and PTF were all effective in treating FCA-induced rheumatoid arthritis. The administered groups all reduced joint swelling and lowered serum inflammatory factor levels in rats. In the screening of lipid metabolite differences between serum and urine of the rat model group and the normal group, a total of 52 different metabolites were screened, and the levels of lipid metabolites in PWE, PAE, and PTF were significantly higher than those in the normal group after administration. In addition, PWE, PAE, and PTF may have significant therapeutic effects on FCA-induced arthritis by modulating nicotinic acid, nicotinamide, and histidine metabolic pathways.

Combined analysis of the proteome and metabolome provides insight into microRNA-1174 function in Aedes aegypti mosquitoes

BACKGROUND

Pathogenic viruses can be transmitted by female Aedes aegypti (Ae. aegypti) mosquitoes during blood-meal acquisition from vertebrates. Silencing of mosquito- and midgut-specific microRNA (miRNA) 1174 (miR-1174) impairs blood intake and increases mortality. Determining the identity of the proteins and metabolites that respond to miR-1174 depletion will increase our understanding of the molecular mechanisms of this miRNA in controlling blood-feeding and nutrient metabolism of mosquitoes.

METHODS

Antisense oligonucleotides (antagomirs [Ant]) Ant-1174 and Ant-Ct were injected into female Ae. aegypti mosquitoes at 12-20 h posteclosion, and depletion of miR-1174 was confirmed by reverse transcription quantitative real-time PCR (RT-qPCR). Ant-1174-injected and control mosquitoes were collected before the blood meal at 72 h post-injection for tandem mass tag-based proteomic analysis and liquid chromatography-tandom mass spectrometry non-target metabolomic analysis to identify differentially expressed proteins and metabolites, respectively. RNA interference (RNAi) using double-stranded RNA (dsRNA) injection was applied to investigate the biological roles of these differentially expressed genes. The RNAi effect was verified by RT-qPCR and western blotting assays. Triglyceride content and ATP levels were measured using the appropriate assay kits, following the manufacturers' instructions. Statistical analyses were conducted with GraphPad7 software using the Student's t-test.

RESULTS

Upon depletion of mosquito- and midgut-specific miR-1174, a total of 383 differentially expressed proteins (DEPs) were identified, among which 258 were upregulated and 125 were downregulated. Functional analysis of these DEPs using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment suggested that miR-1174 plays important regulatory roles in amino acid metabolism, nucleotide metabolism, fatty acid metabolism and sugar metabolism pathways. A total of 292 differential metabolites were identified, of which 141 were upregulated and 151 were downregulated. Integrative analysis showed that the associated differential proteins and metabolites were mainly enriched in a variety of metabolic pathways, including glycolysis, citrate cycle, oxidative phosphorylation and amino acid metabolism. Specifically, the gene of one upregulated protein in miR-1174-depleted mosquitoes, purine nucleoside phosphorylase (PNP; AAEL002269), was associated with the purine, pyrimidine and niacin-nicotinamide metabolism pathways. PNP knockdown seriously inhibited blood digestion and ovary development and increased adult mortality. Mechanically, PNP depletion led to a significant downregulation of the vitellogenin gene (Vg); in addition, some important genes in the ecdysone signaling and insulin-like peptide signaling pathways related to ovary development were affected.

CONCLUSIONS

This study demonstrates differential accumulation of proteins and metabolites in miR-1174-depleted Ae. aegypti mosquitoes using proteomic and metabolomic techniques. The results provide functional evidence for the role of the upregulated gene PNP in gut physiological activities. Our findings highlight key molecular changes in miR-1174-depleted Ae. aegypti mosquitoes and thus provide a basis and novel insights for increased understanding of the molecular mechanism involved in a lineage-specific miRNA in mosquito vectors.

Tracing the geographical origin of tobacco at two spatial scales by stable isotope and element analyses with chemometrics

Tobacco is a widely cultivated cash crop, but it is often smuggled and sold illegally. Unfortunately, there is currently no way to verify the origin of tobacco in China. In an effort to address this issue, we conducted a study using stable isotopes and elements from 176 tobacco samples at both provincial and municipal scales. Our findings revealed significant differences in δ¹³C, K, Cs, and ^208/206Pb at the provincial-level, and Sr, Se, and Pb at the municipal level. We created a heat map at the municipal level, which showed a similar cluster classification to geographic grouping and provided an initial assessment of tobacco origins. Using OPLS-DA modeling, we achieved a 98.3% accuracy rate for the provincial scale and 97.6% for the municipal scale. It is worth noting that the importance of rankings of variables varied depending on the spatial scale of the evaluation. This study offers the first traceability fingerprint dataset of tobacco and has the potential to combat mislabeling and fraudulent conduct by identifying the geographical origin of tobacco.

Transcriptomic and Metabolomic Analyses Provide Insights into the Pathogenic Mechanism of the Rice False Smut Pathogen Ustilaginoidea virens

Rice false smut, caused by the fungal pathogen Ustilaginoidea virens, is a worldwide rice fungal disease. However, the molecular mechanism of the pathogenicity of the fungus U. virens remains unclear. To understand the molecular mechanism of pathogenesis of the fungus U. virens, we performed an integrated analysis of the transcriptome and metabolome of strongly (S) and weakly (W) virulent strains both before and after the infection of panicles. A total of 7932 differential expressed genes (DEGs) were identified using transcriptome analysis. Gene ontology (GO) and metabolic pathway enrichment analysis indicated that amino acid metabolism, autophagy-yeast, MAPK signaling pathway-yeast, and starch and sucrose metabolism were closely related to the pathogenicity of U. virens. Genes related to pathogenicity were significantly upregulated in the strongly virulent strain, and were ATG, MAPK, STE, TPS, and NTH genes. However, genes involved in the negative regulation of pathogenesis were significantly downregulated and contained TOR kinase, TORC1, and autophagy-related protein genes. Metabolome analysis identified 698 differentially accumulated metabolites (DAMs), including 13 categories of organic acids and derivatives, lipids and lipid-like molecules, organoheterocyclic compounds. The significantly enriched pathways of DAMs mainly included amino acids and carbohydrates, and they accumulated after infection by the S strain. To understand the relevance of DEGs and DAMs in the pathogenicity of U. virens, transcriptomic and metabolomic data were integrated and analyzed. These results further confirmed that the pathogenesis of U. virens was regulated by DEGs and DAMs related to these four pathways, involving arginine and proline metabolism, lysine biosynthesis, alanine, aspartate and glutamate metabolism, and starch and sugar metabolism. Therefore, we speculate that the pathogenicity of U. virens is closely related to the accumulation of amino acids and carbohydrates, and to the changes in the expression of related genes.

High-quality genome assembly and multi-omics analysis of pigment synthesis pathway in Auricularia cornea

Owing to its great market potential for food and health care, white Auricularia cornea, a rare edible fungus, has received increased attention in recent years. This study presents a high-quality genome assembly of A. cornea and multi-omics analysis of its pigment synthesis pathway. Continuous Long Reads libraries, combined with Hi-C-assisted assembly were used to assemble of white A. cornea. Based on this data, we analyzed the transcriptome and metabolome of purple and white strains during the mycelium, primordium, and fruiting body stages. Finally, we obtained the genome of A.cornea assembled from 13 clusters. Comparative and evolutionary analysis suggests that A.cornea is more closely related to Auricularia subglabra than to Auricularia heimuer. The divergence of white/purple A.cornea occurred approximately 40,000 years ago, and there were numerous inversions and translocations between homologous regions of the two genomes. Purple strain synthesized pigment via the shikimate pathway. The pigment in the fruiting body of A. cornea was γ-glutaminyl-3,4-dihydroxy-benzoate. During pigment synthesis, α-D-glucose-1P, citrate, 2-Oxoglutarate, and glutamate were four important intermediate metabolites, whereas polyphenol oxidase and other 20 enzyme genes were the key enzymes. This study sheds light on the genetic blueprint and evolutionary history of the white A.cornea genome, revealing the mechanism of pigment synthesis in A.cornea. It has important theoretical and practical implications for understanding the evolution of basidiomycetes, molecular breeding of white A.cornea, and deciphering the genetic regulations of edible fungi. Additionally, it provides valuable insights for the study of phenotypic traits in other edible fungi.

Deciphering the contribution of microbial biomass to the properties of dissolved and particulate organic matter in anaerobic digestates

The recalcitrant structures either from substrate or microbial biomass contained in digestates after anaerobic digestion (AD) highly influence digestate valorization. To properly assess the microbial biomass contribution to the digested organic matter (OM), a combination of characterization methods and the use of various substrate types in anaerobic continuous reactors was required. The use of totally biodegradable substrates allowed detecting soluble microbial products via fluorescence spectroscopy at emission wavelengths of 420 and 460 nm while the protein-like signature was enhanced by the whey protein. During reactors' operation, a transfer of complex compounds to the dissolved OM from the particulate OM was observed through fluorescence applied on biochemical fractionation. Consequently, the fluorescence complexity index of the dissolved OM increased from 0.59-0.60 to 1.06-1.07, whereas it decreased inversely for the extractable soluble from the particulate OM from 1.16-1.19 to 0.42-0.54. Accordingly, fluorescence regional integration showed differences among reactors based on visual inspection and orthogonal partial latent structures (OPLS) analysis. Similarly, the impact of the substrate type and operation time on the particulate OM was revealed by ¹³C nuclear magnetic resonance using OPLS, providing a good model (R²X = 0.93 and Q² = 0.8) with a clear time-trend. A high signal resonated at ∼30 ppm attributed to CH₂-groups in the aliphatic chain of lipid-like structure besides carbohydrates intensities at 60-110 ppm distinguished the reactor fed with whey protein from the other, which was mostly biomass related. Indeed, this latter displayed a higher presence of peptidoglycan (δH/C: 1.6-2.0/20-25 ppm) derived from microbial biomass by ¹H-¹³C heteronuclear single-quantum coherence (HSQC) nuclear magnetic resonance. Interestingly, the sample distribution obtained by non-metric multidimensional scaling of bacterial communities resembled the attained using ¹³C NMR properties, opening new research perspectives. Overall, this study discloses the microbial biomass contribution to digestates composition to improve the OM transformation mechanism knowledge.

Orthogonal cytokine engineering enables novel synthetic effector states escaping canonical exhaustion in tumor-rejecting CD8+ T cells

To date, no immunotherapy approaches have managed to fully overcome T-cell exhaustion, which remains a mandatory fate for chronically activated effector cells and a major therapeutic challenge. Understanding how to reprogram CD8+ tumor-infiltrating lymphocytes away from exhausted effector states remains an elusive goal. Our work provides evidence that orthogonal gene engineering of T cells to secrete an interleukin (IL)-2 variant binding the IL-2Rβγ receptor and the alarmin IL-33 reprogrammed adoptively transferred T cells to acquire a novel, synthetic effector state, which deviated from canonical exhaustion and displayed superior effector functions. These cells successfully overcame homeostatic barriers in the host and led-in the absence of lymphodepletion or exogenous cytokine support-to high levels of engraftment and tumor regression. Our work unlocks a new opportunity of rationally engineering synthetic CD8+ T-cell states endowed with the ability to avoid exhaustion and control advanced solid tumors.

Multi-omics joint analysis reveals how Streptomyces albidoflavus OsiLf-2 assists Camellia oleifera to resist drought stress and improve fruit quality

Camellia oleifera (C. oleifera) is a unique edible oil crop in China cultivated in the hilly southern mountains. Although C. oleifera is classified as a drought-tolerant tree species, drought remains the main factor limiting the growth of C. oleifera in summer and autumn. Using endophytes to improve crop drought tolerance is one effective strategy to meet our growing food crop demand. In this study, we showed that endophyte Streptomyces albidoflavus OsiLf-2 could mitigate the negative impact of drought stress on C. oleifera, thus improving seed, oil, and fruit quality. Microbiome analysis revealed that OsiLf-2 treatment significantly affected the microbial community structure in the rhizosphere soil of C. oleifera, decreasing both the diversity and abundance of the soil microbe. Likewise, transcriptome and metabolome analyses found that OsiLf-2 protected plant cells from drought stress by reducing root cell water loss and synthesizing osmoregulatory substances, polysaccharides, and sugar alcohols in roots. Moreover, we observed that OsiLf-2 could induce the host to resist drought stress by increasing its peroxidase activity and synthesizing antioxidants such as cysteine. A multi-omics joint analysis of microbiomes, transcriptomes, and metabolomes revealed OsiLf-2 assists C. oleifera in resisting drought stress. This study provides theoretical and technical support for future research on endophytes application to enhance the drought resistance, yield, and quality of C. oleifera.

Characterization of donkey-meat flavor profiles by GC–IMS and multivariate analysis

The distinctive flavor compounds of donkey meat are unknown. Accordingly, in the present study, the volatile compounds (VOCs) in the meat from SanFen (SF) and WuTou (WT) donkeys were comprehensively analyzed by gas chromatography–ion mobility spectrometry (GC-IMS) combined with multivariate analysis. A total of 38 VOCs, of which 33.33% were ketones, 28.89% were alcohols, 20.00% were aldehydes, and 2.22% were heterocycles, were identified. Ketones and alcohols were significantly more abundant for SF than for WT, whereas aldehydes showed the opposite trend. The donkey meats from the two strains were well differentiated using topographic plots, VOC fingerprinting, and multivariate analysis. A total of 17 different VOCs were identified as potential markers for distinguishing the different strains, including hexanal-m, 3-octenal, oct-1-en-3-ol, and pentanal-d. These results indicate that GC–IMS combined with multivariate analysis is a convenient and powerful method for characterizing and discriminating donkey meat.

Detection of metabolic syndrome with ATR-FTIR spectroscopy and chemometrics in blood plasma

Metabolic Syndrome (MetS) is a constellation of 3 or more risk factor (abdominal obesity, high triglycerides, low HDL-c, high blood pressure, and elevated blood glucose) for atherosclerotic cardiovascular disease. Considering these systemic metabolic changes in the biochemical pathways of all biomolecules, Attenuated Total Reflection-Fourier Transform Infrared (ATR-FTIR) spectroscopy is a rapid, low-cost, and reagent-free alternative technique capable of identifying spectral biomarkers that differentiate subjects with MetS from control. In this study, plasma samples from 74 subjects (14 MetS, 60 control) were analyzed on the ATR-FTIR spectrophotometer. The objective was to differentiate subjects with MetS from control with supervised chemometrics modeling (Orthogonal Partial Least Squares-Discriminant Analysis, OPLS-DA). Additionally, the inflammatory status of subjects with MetS and control (supervised by C-reactive protein - CRP, leptin, and cell-free DNA - cfDNA) was verified. The OPLS-DA model achieved 100% sensitivity and specificity in cross-validation. For 1 latent variable (93.4% of variance), RMSECV < 0.002, PRESS CV < 0.0001, and R² > 0.9999 was obtained. Significant spectrochemical differences (p < 0.05) were found between MetS and control subjects in the following biomolecular regions (cm^-1): 1717-1703 [ν(CO) and δ(NH)], 1166-1137 [ν(C-OH) + ν(CO) and ν(CC) + δ(OH) + ν(CO)], 1113-1040 [ν(PO₂^-) and ν(C-OH)], and 1027-1008 [ν(CO) and v(CH₂OH)]. In the OPLS-DA model loadings, amide I [1720-1600 cm^-1, ν(CO)] and amide II [1570-1480 cm^-1, δ(NH) + ν(CH)] had significantly greater weight than all other regions. There was a significant difference in inflammatory status between MetS patient and control (p < 0.05 for CRP and leptin, and p < 0.01 for cfDNA).

Flavor substances of low-valued red swamp crayfish (Procambarus clarkii) hydrolysates derived from double enzymatic systems

To make better use of low-valued crayfish (Procambarus clarkii), double enzymatic systems containing endopeptidase and Flavourzyme® were applied to investigate their effect on the physicochemical properties and volatile substances of low-valued crayfish. The results demonstrated that the double enzymatic hydrolysis had a positive effect on reduced bitterness and increased umami. Among them, the highest degree of hydrolysis (31.67 %) was obtained using trypsin and Flavourzyme® (TF), which showed 96.32 % of peptides with molecular weight < 0.5 kDa and 101.99 mg/g of free amino acids. The quality and quantity analysis showed that the types and relative contents of volatile compounds especially benzaldehyde, 1-octen-3-ol, nonanal, hexanal, 2-nonanone, 2-undecanonewere increased in the double enzymatic hydrolysis. In addition, the increase of esters and pyrazines was also found in gas chromatography-ion mobility spectrometry (GC-IMS). The results indicated that different enzymatic systems could be performed to enhance the flavor substances of low-valued crayfish. In conclusion, double enzymatic hydrolysis may be used as an advisable technique to promote the high-value utilization of low-valued crayfish and provides valuable information for the shrimp products requiring enzymatic hydrolysis.

A Comprehensive Analysis to Elucidate the Effects of Spraying Mineral Elements on the Accumulation of Flavonoids in Epimedium sagittatum during the Harvesting Period

The harvesting period is a critical period for the accumulation of flavonoids in the leaves of the important medicinal plant Epimedium sagittatum. In this study, we conducted an experiment on E. sagittatum leaves sprayed with mineral elements with the aim of improving the quality of the herbal leafage during the harvesting period. We elucidated the changes in flavonoids (icariin, epimedin A, epimedin B, and epimedin C) in E. sagittatum leaves. The sum of main flavonoids content reached a maximum (11.74%) at 20 days after the high-concentration Fe²⁺ (2500 mg·L^-1) treatment. We analyzed the FT-IR spectra characteristics of E. sagittatum leaf samples using the FT-IR technique, and constructed an OPLS-DA model and identified characteristic peaks to achieve differentiated identification of E. sagittatum. Further, widely untargeted metabolomic analysis identified different classes of metabolites. As the most important characteristic flavonoids, the relative contents of icariin, icaritin, icariside I, and icariside II were found to be up-regulated by high-Fe²⁺ treatment. Our experimental results demonstrate that high-concentration Fe²⁺ treatment is an effective measure to increase the flavonoids content in E. sagittatum leaves during the harvesting period, which can provide a scientific basis for the improvement of E. sagittatum leaf cultivation agronomic measures.

Metabolomics-Based Profiling via a Chemometric Approach to Investigate the Antidiabetic Property of Different Parts and Origins of Pistacia lentiscus L

Pistacia lentiscus L. is a medicinal plant that grows spontaneously throughout the Mediterranean basin and is traditionally used to treat diseases, including diabetes. The aim of this work consists of the evaluation of the α-glucosidase inhibitory effect (i.e., antidiabetic activity in vitro) of different extracts from the leaves, stem barks and fruits of P. lentiscus harvested on mountains and the littoral of Tizi-Ouzou in Algeria. Metabolomic profiling combined with a chemometric approach highlighted the variation of the antidiabetic properties of P. lentiscus according to the plant's part and origin. A multiblock OPLS analysis showed that the metabolites most involved in α-glucosidase inhibition activity were mainly found in the stem bark extracts. The highest inhibitory activity was found for the stem bark extracts, with averaged inhibition percentage values of 84.7% and 69.9% for the harvested samples from the littoral and mountain, respectively. On the other hand, the fruit extracts showed a lower effect (13.6%) at both locations. The UHPLC-ESI-HRMS characterization of the metabolites most likely responsible for the α-glucosidase-inhibitory activity allowed the identification of six compounds: epigallocatechin(4a>8)epigallocatechin (two isomers), (epi)gallocatechin-3'-O-galloyl-(epi)gallocatechin (two isomers), 3,5-O-digalloylquinic acid and dihydroxy benzoic acid pentoside.

Metabolomics analysis reveals the accumulation patterns of flavonoids and phenolic acids in quinoa (Chenopodium quinoa Willd.) grains of different colors

Quinoa grains are gaining increasing popularity owing to their high nutritional merits. However, only limited information is available on the metabolic profiles of quinoa grains. In this study, we determined the metabolic profiles of black, red, and white quinoa grains via an ultraperformance liquid chromatography-electrospray ionization-tandem mass spectrometry (UPLC-ESI-MS/MS)-based metabolomics. A total of 689 metabolites were identified, among which 251, 182, and 317 metabolites displayed different accumulation patterns in the three comparison groups (Black vs Red, Black vs White, and Red vs White), respectively. In particular, flavonoid and phenolic acid contents displayed considerable differences, with 22 flavonoids, 5 phenolic acids, and 1 betacyanin being differentially accumulated among the three quinoa cultivars. Additionally, correlation analysis showed that flavonoids and phenolic acids could act as betanin co-pigments in quinoa grains. In conclusion, this study provides comprehensive insights into the adequate utilization and development of novel quinoa-based functional foods.