PubMed

ACS Sens. 2023 Jan 4. doi: 10.1021/acssensors.2c02325. Online ahead of print.ABSTRACTSkin metabolites show huge potential for use in clinical diagnostics. However, skin sampling and analysis workflows are tedious and time-consuming. Here, we demonstrate a vending-machine-style skin excretion sensing platform based on hydrogel-assisted sampling of skin metabolites. In this sensing platform, a sampling probe with hydrogel is held by a robotic arm. The robotic arm manoeuvres the probe to press it onto the forearm of a human subject. Due to the highly hydrophilic nature of the hydrogel, water-soluble metabolites─released by skin─are collected into the hydrogel, leaving behind the nonpolar metabolites. The probe is then inserted into a custom-made open port sampling interface coupled to an electrospray ion source of a high-resolution quadrupole-time-of-flight mass spectrometer. Metabolites in the hydrogel are immediately extracted by a solvent liquid junction in the interface and analyzed using the mass spectrometer. The ion current of the target analyte is displayed on a customized graphical user interface, which can also be used to control the key components of the analytical platform. The automated sampling and analysis workflow starts after the user inserts coins or presents an insurance card, presses a button, and extends an arm on the sampling area. The platform relies on low-cost mechanical and electronic modules (a robotic arm, a single-board computer, and two microcontroller boards). The limits of detection for standard analytes─arginine, citrulline, and histidine─embedded in agarose gel beds were 148, 205, and 199 nM, respectively. Various low-molecular-weight metabolites from human skin have been identified with the high-resolution mass spectrometer.PMID:36598150 | DOI:10.1021/acssensors.2c02325

Circ Res. 2023 Jan 4. doi: 10.1161/CIRCRESAHA.122.321923. Online ahead of print.ABSTRACTBACKGROUND: Pulmonary arterial hypertension (PAH) is a complex disease characterized by progressive right ventricular (RV) failure leading to significant morbidity and mortality. Investigating metabolic features and pathways associated with RV dilation, mortality, and measures of disease severity can provide insight into molecular mechanisms, identify subphenotypes, and suggest potential therapeutic targets.METHODS: We collected data from a prospective cohort of PAH participants and performed untargeted metabolomic profiling on 1045 metabolites from circulating blood. Analyses were intended to identify metabolomic differences across a range of common metrics in PAH (eg, dilated versus nondilated RV). Partial least squares discriminant analysis was first applied to assess the distinguishability of relevant outcomes. Significantly altered metabolites were then identified using linear regression, and Cox regression models (as appropriate for the specific outcome) with adjustments for age, sex, body mass index, and PAH cause. Models exploring RV maladaptation were further adjusted for pulmonary vascular resistance. Pathway enrichment analysis was performed to identify significantly dysregulated processes.RESULTS: A total of 117 participants with PAH were included. Partial least squares discriminant analysis showed cluster differentiation between participants with dilated versus nondilated RVs, survivors versus nonsurvivors, and across a range of NT-proBNP (N-terminal probrain natriuretic peptide) levels, REVEAL 2.0 composite scores, and 6-minute-walk distances. Polyamine and histidine pathways were associated with differences in RV dilation, mortality, NT-proBNP, REVEAL score, and 6-minute walk distance. Acylcarnitine pathways were associated with NT-proBNP, REVEAL score, and 6-minute walk distance. Sphingomyelin pathways were associated with RV dilation and NT-proBNP after adjustment for pulmonary vascular resistance.CONCLUSIONS: Distinct plasma metabolomic profiles are associated with RV dilation, mortality, and measures of disease severity in PAH. Polyamine, histidine, and sphingomyelin metabolic pathways represent promising candidates for identifying patients at high risk for poor outcomes and investigation into their roles as markers or mediators of disease progression and RV adaptation.PMID:36597887 | DOI:10.1161/CIRCRESAHA.122.321923

Br J Haematol. 2023 Jan 4. doi: 10.1111/bjh.18633. Online ahead of print.ABSTRACTAutoimmune-responses leading to increased destruction of red blood cells occur in autoimmune haemolytic anaemia (AIHA). The pathophysiology of AIHA is multifactorial and not fully understood, and clinically it remains challenging to manage relapsed and treatment-refractory cases. Rabelo and colleagues conduct metabolomic profiling in plasma of 26 patients with primary warm AIHA, with consideration of haemolytic activity and relapse occurrence. They identify distinct metabolites to be increased in primary warm AIHA patients, thereby providing an encouraging basis for further validation and exploration of metabolomic profiling as a predictive tool for the management of AIHA. Commentary on: Rabelo et al. Metabolomic profile in patients with primary warm autoimmune haemolytic anaemia. Br J Haematol 2022 (Online ahead of print). doi: 10.1111/bjh.18584.PMID:36597858 | DOI:10.1111/bjh.18633

Anal Chem. 2023 Jan 4. doi: 10.1021/acs.analchem.2c01398. Online ahead of print.ABSTRACTRegion of interest (ROI) extraction is a fundamental step in analyzing metabolomic datasets acquired by liquid chromatography-mass spectrometry (LC-MS). However, noises and backgrounds in LC-MS data often affect the quality of extracted ROIs. Therefore, developing effective ROI evaluation algorithms is necessary to eliminate false positives meanwhile keep the false-negative rate as low as possible. In this study, a deep fused filter of ROIs (dffROI) was proposed to improve the accuracy of ROI extraction by combining the handcrafted evaluation metrics with convolutional neural network (CNN)-learned representations. To evaluate the performance of dffROI, dffROI was compared with peakonly (CNN-learned representation) and five handcrafted metrics on three LC-MS datasets and a gas chromatography-mass spectrometry (GC-MS) dataset. Results show that dffROI can achieve higher accuracy, better true-positive rate, and lower false-positive rate. Its accuracy, true-positive rate, and false-positive rate are 0.9841, 0.9869, and 0.0186 on the test set, respectively. The classification error rate of dffROI (1.59%) is significantly reduced compared with peakonly (2.73%). The model-agnostic feature importance demonstrates the necessity of fusing handcrafted evaluation metrics with the convolutional neural network representations. dffROI is an automatic, robust, and universal method for ROI filtering by virtue of information fusion and end-to-end learning. It is implemented in Python programming language and open-sourced at https://github.com/zhanghailiangcsu/dffROI under BSD License. Furthermore, it has been integrated into the KPIC2 framework previously proposed by our group to facilitate real metabolomic LC-MS dataset analysis.PMID:36597722 | DOI:10.1021/acs.analchem.2c01398

Int Nurs Rev. 2023 Jan 3. doi: 10.1111/inr.12816. Online ahead of print.ABSTRACTAIM: To summarize the omics results of symptomatic research that can help nurses identify intervention targets and design precision interventions for pain, mental health, cognitive impairment, sleep disorder, fatigue, lymphedema, and quality of life, so as to provide a comprehensive summary of help and inspire to precision nursing.METHODS: CINAHL, PubMed, Web of Science, and ScienceDirect databases were searched. Retrieval time was from January 2012 to December 2021. Symptomatology research applying omics that can be used to guide nurses in designing targeted interventions was included.RESULTS: Forty-six studies were included in the final review. Symptomatology research that can be integrated with nursing science to develop precision nursing focused on pain, mental health, cognitive impairment, sleep disorder, fatigue, lymphedema, and quality of life. Most studies were related to cognitive impairment (n = 10; 21.74%), pain (n = 9; 19.57%), and mental health (n = 8; 17.39%). Moreover, the included studies involved various omics technologies, such as whole genome, epigenome, transcriptome, proteome, and metabolome.CONCLUSION: The rapid development of various omic technologies promotes symptomatology research, which can help nurses fully understand the information of patients. Phenotypic characteristics and biomarkers shown in symptomatology research help nurses identify intervention targets and develop individualization interventions, so as to prevent and reduce symptoms and improve the quality of life.IMPLICATION FOR NURSING AND HEALTH POLICY: This scoping review is the first synthesis of all peer-reviewed literature to summarize and provide important information and references from the omic results of symptomatology studies to develop precision nursing, highlighting the status and development of precision nursing. Nursing education policies should introduce the development and importance of precision nursing. Further research could consider investing more attention in precision nursing. Nursing researchers can carry out some studies applying omics technology to explore more biomarkers, helping guide the formulation of clinical intervention for symptoms.PMID:36597558 | DOI:10.1111/inr.12816

Food Res Int. 2023 Jan;163:112273. doi: 10.1016/j.foodres.2022.112273. Epub 2022 Nov 30.ABSTRACTDry-cured mackerel is favored by consumers for its suitable salty flavor. Herein, the dynamic changes of volatile compounds and lipids in the mackerel, and the lipidomics based on UPLC-Orbitrap/MS technique during dry-cured processing were investigated. The results showed that endogenous lipases activities in dry-cured mackerel decreased. The dry-cured processing of mackerel had significant effects on its lipid classes and content. The contents of Arachidonic acid (C20:4n6), docosapentaenoic acid (C22:5n3), linoleic acid (LA, C18:2n6), alpha-linolenic acid (C18:3n3), eicosatrienoic acid (C20:3n3) and docosahexaenoic acid (DHA, C22:6n3) increased during dry-cured processing. A total of 38 kinds of volatile compounds were detected in the dry-cured mackerel, 12 of which were derived from fatty acid oxidation. Among 30 lipid metabolites (FC ≥ 2 and VIP > 2), phosphatidylethanolamine (PE, 19:0/22:6) accounted for the highest content, and its difference between three stages was the most obvious. Glycerophospholipid and sphingolipid metabolisms were the most important metabolic pathways involved in dry-cured processing.PMID:36596184 | DOI:10.1016/j.foodres.2022.112273

J Vet Med Sci. 2023 Jan 2. doi: 10.1292/jvms.22-0490. Online ahead of print.ABSTRACTDichlorodiphenyltrichloroethane (DDT) is an organochlorine insecticide used worldwide. Several studies have reported the toxic effects of DDT and its metabolites on steroid hormone biosynthesis; however, its environmental effects are not well understood. This study examined wild rats collected in DDT-sprayed areas of South Africa and quantified plasma metabolites using liquid chromatography quadrupole time-of-flight mass spectrometry (LC-Q-TOF-MS). Fold change analysis of the metabolome revealed the effect of DDT on bile acid biosynthesis. Gene expression of the related enzyme in rat liver samples was also quantified. Significant association was found between DDT and gene expression levels related to constitutive androstane receptor mediated enzymes, such as Cyp2b1 in rat livers. However, our results could not fully demonstrate that enzymes related to bile acid biosynthesis were strongly affected by DDT. The correlation between DDT concentration and gene expression involved in steroid hormone synthesis in testis was also evaluated; however, no significant correlation was found. The disturbance of metabolic enzymes occurred in rat liver in the target area. Our results suggest that DDT exposure affects gene expression in wild rats living in DDT-sprayed areas. Therefore, there is a need for DDT toxicity evaluation in mammals living in DDT-sprayed areas. We could not find an effective biomarker that could reflect the mechanism of DDT exposure; however, this approach can provide new insights for future research to evaluate DDT effects in sprayed areas.PMID:36596564 | DOI:10.1292/jvms.22-0490

J Proteomics. 2022 Dec 31:104808. doi: 10.1016/j.jprot.2022.104808. Online ahead of print.ABSTRACTProteins and translationally modified proteins like phosphoproteins have essential regulatory roles in tumorigenesis. This study attempts to elucidate the dysregulated proteins driving colorectal cancer (CRC). To explore the differential proteins, we performed iTRAQ labeling proteomics and TMT labeling phosphoproteomics analysis of CRC tissues and adjacent non-cancerous tissues. The functions of quantified proteins were analyzed using Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG), and Subcellular localization analysis. Depending on the results, we identified 330 differential proteins and 82 phosphoproteins in CRC. GO and KEGG analyses demonstrated that protein changes were primarily associated with regulating biological and metabolic processes through binding to other molecules. Co-expression relationships between proteomic and phosphoproteomic analysis revealed that TMC5, SMC4, SLBP, VSIG2, and NDRG2 were significantly dysregulated differential proteins. Additionally, based on the predicted co-expression proteins, we identified that the stem-loop binding protein (SLBP) was up-regulated in CRC cells and promoted the proliferation and migration of CRC. This study reports an integrated proteomic and phosphoproteomic analysis of CRC to discern the functional impact of protein alterations and provides a candidate diagnostic biomarker or therapeutic target for CRC. SIGNIFICANCE: Combining one or more high-throughput omics technologies with bioinformatics to analyze biological samples and explore the links between biomolecules and their functions can provide more comprehensive and multi-level insights for disease mechanism research. Proteomics, phosphoproteomics, metabolomics and their combined analysis play an important role in the auxiliary diagnosis, the discovery of biomarkers and novel therapeutic targets for colorectal cancer. In this integrated proteomic and phosphoproteomic analysis, we identified proteins and phosphoproteins in colorectal cancer tissue and analyzed potential mechanisms contributing to progression in colorectal cancer. The results of this study provide a foundation to focus future experiments on the contribution of altered protein and phosphorylation patterns to prevention and treatment of colorectal cancer.PMID:36596410 | DOI:10.1016/j.jprot.2022.104808

Life Sci. 2022 Dec 31:121355. doi: 10.1016/j.lfs.2022.121355. Online ahead of print.ABSTRACTAIMS: This study mainly evaluated the protective mechanism of histidine against the hepatic oxidative stress after high-salt exposure (HSE) through combined analysis of non-targeted metabolomics and biological metabolic networks.MATERIALS AND METHODS: Dahl salt-sensitive (SS) rats were fed with normal-salt diet or HSE ± histidine in addition to drinking water for 14 days. Gas chromatography-mass spectrometry was used to analyze the hepatic metabolites. The metabolic profile was analyzed by SIMCA-14.1, the metabolic correlation network was performed using Gephi-0.9.2, and pathway enrichment was analyzed using MetaboAnalyst 5.0 online website.KEY FINDINGS: Results indicated that HSE disturbed the hepatic metabolic profile, generated abnormal liver metabolism and exacerbated oxidative stress. Histidine supplementation significantly reversed the hepatic metabolic profile. Of note, 14 differential metabolic pathways were enriched after histidine supplementation, most of which played an important role in ameliorating redox and nitric oxide (NO) metabolism. Histidine administration decreased the levels of hydroperoxide and malondialdehyde, and increased the activities of antioxidant enzymes (Catalase, Superoxide Dismutase, Glutathione S-transferase and Glutathione reductases). Histidine effectively enhanced the endogenous synthesis of glutathione by increasing the levels of glutamate and cysteine, thereby enhancing the antioxidant capacity of the glutathione system. After histidine administration, lysine, glutamate, and hypotaurine owned a higher metabolic centrality in the correlation network. In addition, histidine could also effectively increase the endogenous synthesis of NO by enhancing the L-arginine/NO pathway.SIGNIFICANCE: This study offers new insights into the metabolic mechanisms underlying the antioxidant protective effect of histidine on the liver.PMID:36596407 | DOI:10.1016/j.lfs.2022.121355

Int J Biol Macromol. 2022 Dec 31:S0141-8130(22)03239-1. doi: 10.1016/j.ijbiomac.2022.12.318. Online ahead of print.ABSTRACTInulin is a typical kind of fermentable polysaccharide and has emerged as a promising dietary supplement due to its multiple health-promoting effects. This study aimed to unveil the dynamic change pattern of inulin utilizability as a fermentation substrate during gut microbiota development and illuminate its potential association with gut microbiota in Chinese Jinhua native pig models via longitudinal analyses. Herein, fresh feces were collected at one week pre- and post-weaning as well as 3rd month post-weaning, respectively. Targeted metabolomics and in vitro simulated fermentation revealed increasing concentrations of fecal short-chain fatty acids (SCFAs) and elevating utilizability of inulin as a fermentation substrate. Microbiomic analyses demonstrated the conspicuous longitudinal alteration in gut microbial composition and a significant rise in microbial community diversity during gut microbiota development. Furthermore, gut microbial functional analyses showed a remarkable increase in the relative abundances of carbohydrate metabolism pathways, including pentose phosphate pathway, galactose metabolism pathway, butanoate metabolism pathway as well as fructose and mannose metabolism pathway. Notably, relative abundances of bacterial genera Bifidobacterium, Roseburia, Faecalibacterium and Enterococcus displayed significantly positive correlations with the production of microbial fermentation-derived SCFAs. Collectively, these findings offer novel insights into understanding inulin utilizability variations from the perspective of gut microbiota development.PMID:36596372 | DOI:10.1016/j.ijbiomac.2022.12.318

Bioresour Technol. 2022 Dec 31:128567. doi: 10.1016/j.biortech.2022.128567. Online ahead of print.ABSTRACTThe effects and mechanisms of three N-acyl-homoserine lactones (AHLs) (C4-HSL, C6-HSL, and C10-HSL) on responses of biological nitrogen removal (BNR) systems to zinc oxide nanoparticle (NP) shock were investigated. All three AHLs improved the NP-impaired ammonia oxidation rates by up to 50.0 % but inhibited the denitrification process via regulating nitrogen metabolism-related enzyme activities. C4-HSL accelerated the catalase activity by 13.2 %, while C6-HSL and C10-HSL promoted the superoxide dismutase activity by 26.6 % and 18.4 %, respectively, to reduce reactive oxygen species levels. Besides, the enhancements of tryptophan protein and humic acid levels in tightly-bound extracellular polymeric substance by AHLs were vital for NP toxicity attenuation. The metabonomic analysis demonstrated that all three AHLs up-regulated the levels of lipid- and antioxidation-related metabolites to advance the system's resistance to NP shock. The "dual character" of AHLs emphasized the concernment of legitimately employing AHLs to alleviate NP stress for BNR systems.PMID:36596365 | DOI:10.1016/j.biortech.2022.128567

Semin Cancer Biol. 2022 Dec 31:S1044-579X(22)00263-2. doi: 10.1016/j.semcancer.2022.12.009. Online ahead of print.ABSTRACTWith biotechnological advancements, innovative omics technologies are constantly emerging that have enabled researchers to access multi-layer information from the genome, epigenome, transcriptome, proteome, metabolome, and more. A wealth of omics technologies, including bulk and single-cell omics approaches, have empowered to characterize different molecular layers at unprecedented scale and resolution, providing a holistic view of tumor behavior. Multi-omics analysis allows systematic interrogation of various molecular information at each biological layer while posing tricky challenges regarding how to extract valuable insights from the exponentially increasing amount of multi-omics data. Therefore, efficient algorithms are needed to reduce the dimensionality of the data while simultaneously dissecting the mysteries behind the complex biological processes of cancer. Artificial intelligence has demonstrated the ability to analyze complementary multi-modal data streams within the oncology realm. The coincident development of multi-omics technologies and artificial intelligence algorithms has fuelled the development of cancer precision medicine. Here, we present state-of-the-art omics technologies and outline a roadmap of multi-omics integration analysis using an artificial intelligence strategy. The advances made using artificial intelligence-based multi-omics approaches are described, especially concerning early cancer screening, diagnosis, response assessment, and prognosis prediction. Finally, we discuss the challenges faced in multi-omics analysis, with tentative future trends in this field. With the increasing application of artificial intelligence in multi-omics analysis, we anticipate a shifting paradigm in precision medicine becoming driven by artificial intelligence-based multi-omics technology.PMID:36596352 | DOI:10.1016/j.semcancer.2022.12.009

Food Res Int. 2023 Jan;163:112313. doi: 10.1016/j.foodres.2022.112313. Epub 2022 Dec 8.ABSTRACTBlackberry is an economically important shrub species of Rubus in the Rosaceae family. It is rich in phenolic compounds, which have many health effects and pharmaceutical value. The utilization of metabolites from various blackberry tissues is still in the primary stage of development, so investigating the metabolites in various tissues is of practical significance. In this study, nontargeted LC - MS metabolomics was used to identify and measure metabolites in the roots, stems, leaves and fruits (green, red, and black fruits) of blackberry "Chester". We found that 1,427 and 874 metabolites were annotated in the positive and negative ion modes (POS; NEG), respectively. Differentially abundant metabolites (DAMs) between the leaf and root groups were the most abundant (POS: 249; NEG: 141), and the DAMs between the green and red fruit groups were the least abundant (POS: 21; NEG: 14). Moreover, the DAMs in different fruit development stages were far less than those in different tissues. There were significant differences in flavonoid biosynthesis-related pathways among the comparison groups. Trend analysis showed that the profile 10 had the largest number of metabolites. This study provides a scientific basis for the classification and efficient utilization of resources in various tissues of blackberry plants and the directional development of blackberry products.PMID:36596208 | DOI:10.1016/j.foodres.2022.112313

Food Res Int. 2023 Jan;163:112309. doi: 10.1016/j.foodres.2022.112309. Epub 2022 Dec 7.ABSTRACTIncreasing evidence has suggested the mitigatory efficacy of prebiotic inulin on nonalcoholic fatty liver disease (NAFLD), nevertheless, its action mechanisms remain elusive. Herein, inulin consumption effectively ameliorated high-sucrose diet-induced hepatic steatosis and inflammation, and rehabilitated liver lipogenesis regulators, including carbohydrate response element-binding protein, stearoyl-CoA desaturase-1 and peroxisome proliferator-activated receptor alpha. Furthermore, inulin supplementation restored the intestinal barrier integrity and function by up-regulating expressions of tight junction proteins (zonula occludens-1, claudin-1 and occludin). High-throughput sequencing demonstrated that inulin administration regulated the gut microbiota composition, wherein abundance of short-chain fatty acid (SCFA)-producers, including Bifidobacterium, Phascolarctobacterium and Blautia, was significantly enhanced in the inulin-treated rats, conversely, opportunistic pathogens, such as Acinetobacter and Corynebacterium_1, were suppressed. SCFA quantitative analysis showed that dietary inulin suppressed faecal acetate levels, but improved propionate and butyrate concentrations in rats with NAFLD. Functional prediction showed that tryptophan metabolism was one of the key metabolic pathways affected by gut microbiota changes. A targeted metabolomics profiling of tryptophan metabolism demonstrated that inulin intervention up-regulated faecal contents of indole-3-acetic acid and kynurenic acid, whereas down-regulated levels of kynurenine and 5-hydoxyindoleacetic acid in NAFLD rats. Therefore, this study demonstrated that inulin intake alleviated hepatic steatosis likely by regulating the gut microbiota composition and function and restoring the intestinal barrier integrity, which may provide a novel notion for the prevention and treatment of NAFLD in future.PMID:36596207 | DOI:10.1016/j.foodres.2022.112309

Food Res Int. 2023 Jan;163:112287. doi: 10.1016/j.foodres.2022.112287. Epub 2022 Dec 5.ABSTRACTThere is considerable knowledge about plant compounds that produce flavor, scent, and aroma. Aside from the similarities, however, groups of plant-produced nutrients and taste components have little in common with each other. Network analysis holds promise for metabolic gene discovery, which is especially important in plant systems where metabolic networks are not yet fully resolved. To bridge this gap, we propose a joint model of gene regulation and metabolic reactions in two different pepino varieties. Differential metabolomics analysis is carried out for detection of eventual interaction of compound. We adopted a multi-omics approach to profile the transcriptome and metabolome analyze differences in phenolic acids, flavonoids, organic acids, lipids, alkaloids, and sugars between LOF and SRF. The two most predominant classes of metabolites are phenolic acids and lipids in pepino. Overall results show enrichment in most DEGs was carbohydrate and biosynthesis of secondary metabolites pathway. Results of DEMs predominantly comprised N-p-coumaroyl agmatine and tryptamine, and significant differences were observed in their expression between LOF and SRF. Integrated DEMs and DEGs specific networks were constructed by combining two types of networks: transcriptional regulatory networks composed of interactions between DEMs and the regulated genes, and pepino metabolite-metabolite interaction networks. Newly discovered features, such as DEGs (USPA, UBE2 and DELLA) involved in the production of secondary metabolites are found in coregulated gene clusters. Moreover, lipid metabolites were most involved in DEMs correlations by OPLS-DA while identifying a significant number of DEGs co-regulated by SENP1, HMGCS et al. These results further that the metabolite discrepancies result from characterized the nutrients and taste components between two pepino genotype. Among the possible causes of the differences between species in pepino metabolite concentrations is co-regulated by these DEGs, continue to suggest that novel features of metabolite biosynthetic pathway remain to be uncovered. Finally, the integrated metabolome and transcriptome analyses have revealed that many important metabolic pathways are regulated at the transcriptional level. The metabolites content differences observed among varieties of the same species mainly originates from different regulated genes and enzymes expression. Overall, this study provides new insights into the underlying causes of differences in the plant metabolites and suggests that genetic data can be used to improve its nutrients and taste components.PMID:36596193 | DOI:10.1016/j.foodres.2022.112287

Food Res Int. 2023 Jan;163:112275. doi: 10.1016/j.foodres.2022.112275. Epub 2022 Nov 29.ABSTRACTOphiocordyceps sinensis is a traditional medicinal fungus endemic to the alpine and high-altitude areas of the Qinghai-Tibet plateau. The scarcity of the wild resource has led to increased attention to artificially cultivated O. sinensis. However, little is known about the metabolic differences and the regulatory mechanisms between cultivated and wild O. sinensis. This study exploited untargeted metabolomics and transcriptomics to uncover the differences in accumulated metabolites and expressed genes between wild and cultivated O. sinensis. Metabolomics results revealed that 368 differentially accumulated metabolites were mainly enriched in biosynthesis of amino acids, biosynthesis of plant secondary metabolites and purine nucleotide metabolism. Cultivated O. sinensis contained more amino acids and derivatives, carbohydrates and derivatives, and phenolic acids than wild O. sinensis, whereas the contents of most nucleosides and nucleotides in wild O. sinensis were significantly higher than in cultivated O. sinensis. Transcriptome analysis indicated that 4430 annotated differentially expressed genes were identified between two types. Integrated metabolomics and transcriptomics analyses suggested that IMPDH, AK, ADSS, guaA and GUK genes might be related to the synthesis of purine nucleotides and nucleosides. Our findings will provide a new insight into the molecular basis of metabolic variations of this medicinal fungus.PMID:36596185 | DOI:10.1016/j.foodres.2022.112275

Food Res Int. 2023 Jan;163:112228. doi: 10.1016/j.foodres.2022.112228. Epub 2022 Dec 5.ABSTRACTActinidia arguta, an edible berry plant with high nutritional values, has been widely used in Asian countries as a food and traditional medicinal herb. The well-recognized health-promoting properties of A. arguta were associated with its bioactive components in its different botanical parts. To rapidly screen and identify chemical components and simultaneously determine the potential metabolites from different parts of A. arguta, UPLC-Q-TOF-MSE coupled with UNIFI platform and multivariate statistical analysis approach was established in this study. As a result, a total of 107 components were identified from the four different parts of A. arguta, in which 31 characteristic chemical markers were discovered among them, including 12, 8, 6, and 5 compounds from the fruits, leaves, roots, and stems, respectively. These results suggested that the combination of UPLC-Q-TOF-MSE and metabolomic analysis is a powerful method to rapidly screen characteristic markers for the quality control of A. arguta.PMID:36596158 | DOI:10.1016/j.foodres.2022.112228

Food Res Int. 2023 Jan;163:112229. doi: 10.1016/j.foodres.2022.112229. Epub 2022 Nov 24.ABSTRACTChinese flowering cabbage (Brassica campestris L. ssp. chinensis var. utilis Tsen et Lee) is a candidate of selenium (Se) accumulator, but it is not clear whether and how preharvest Se treatment affects its quality after harvest. Here, we showed that preharvest application of 100 μmol/L selenite to roots enhanced storage quality of Chinese flowering cabbage. It increased antioxidant capacity and reduced weight loss, leaf yellowing, and protein degradation after harvest. Furthermore, it increased the activities of antioxidant enzymes such as POD, CAT, GSH-Px, and GR, as well as contents of AsA, GSH, phenolics, and flavonoids during storage. Metabolome analysis revealed that phenolic acids including p-Coumaric acid, caffeic acid, and ferulic acid; flavonoids such as naringenin, eriodictyol, apigenin, quercetin, kaempferol, and their derivatives were notably increased by preharvest selenite treatment. Consistently, the total antioxidant capacity, evaluated by DPPH, ABTS, and FRAP methods, were all markedly enhanced in selenite-treated cabbage compared to the control. Transcriptomics analysis showed that the DEGs induced by selenite were significantly enriched in AsA-GSH metabolisms and phenylpropanoids biosynthesis pathways. Moreover, preharvest selenite treatment significantly up-regulated the expressions of BrGST, BrGSH-Px, BrAPX, BrASO, BrC4H, BrCOMT, BrCHS, and BrFLS during storage. These results suggest that preharvest selenite treatment enhanced quality of cabbage not only by increasing Se biological accumulation, but also through regulating AsA-GSH cycle and increasing phenolics and flavonoids synthesis after harvest. This study provides a novel insight into the effects of preharvest Se treatment on quality of Chinese flowering cabbage during storage.PMID:36596157 | DOI:10.1016/j.foodres.2022.112229

Food Res Int. 2023 Jan;163:112224. doi: 10.1016/j.foodres.2022.112224. Epub 2022 Nov 24.ABSTRACTIn this study, genomics and metabolomics were combined to reveal possible bio-synthetic pathways of core flavor compounds in pickled chayote via lactic acid bacteria (LAB) fermentation. The Lactiplantibacillus plantarum, Levilactobacillus brevis, and Lacticaseibacillus paracasei were selected as core LAB strains with better flavor-producing ability for chayote fermentation. The genomic results showed L. plantarum contained the largest number of metabolism annotated genes, while L. brevis had the fewest. Besides, the largest number of volatile compounds was detected in chayote fermented by L. plantarum, followed by L. brevis and L. paracasei. Some unique odor-active compounds (aldehydes, esters, and alcohols) and taste-active compounds (amino acids and dipeptides) were produced by different LAB strains. Accordingly, phenylalanine metabolic pathway (M00360), amino acid metabolic decomposition pathway (the Ehrlich pathway) and the anabolic pathway (the Harris pathway), and fatty acid biosynthesis pathway (M00061) were the main biosynthesis pathway involved in the flavor formation via LAB fermentation.PMID:36596153 | DOI:10.1016/j.foodres.2022.112224

Food Res Int. 2023 Jan;163:112221. doi: 10.1016/j.foodres.2022.112221. Epub 2022 Nov 24.ABSTRACTSeaweed, an important food resource in several Asian countries, contains various metabolites, including sugars, organic acids, and amino acids; however, their content is affected by prevailing environmental conditions. This review discusses seaweed metabolomics, especially the distribution of primary and functional secondary metabolites (e.g., carotenoids, polyphenols) in seaweed. Additionally, the effects of global warming on seaweed metabolite profile changes are discussed. For example, high temperatures can increase amino acid levels in seaweeds. Overall, understanding the effects of global warming on seaweed metabolite profiles can be useful for evaluating the nutritional composition of seaweeds as food. This review provides an overview of recent applications of metabolomics in seaweed research as well as a perspective on the nutrient content and cultivation of seaweeds under climate change scenarios.PMID:36596150 | DOI:10.1016/j.foodres.2022.112221