The involvement of host immunity in the gut microbiota-mediated colonization resistance to Clostridioides difficile infection (CDI) is incompletely understood. Here, we show that interleukin (IL)-22, ...induced by colonization of the gut microbiota, is crucial for the prevention of CDI in human microbiota-associated (HMA) mice. IL-22 signaling in HMA mice regulated host glycosylation, which enabled the growth of succinate-consuming bacteria Phascolarctobacterium spp. within the gut microbiome. Phascolarctobacterium reduced the availability of luminal succinate, a crucial metabolite for the growth of C. difficile, and therefore prevented the growth of C. difficile. IL-22-mediated host N-glycosylation is likely impaired in patients with ulcerative colitis (UC) and renders UC-HMA mice more susceptible to CDI. Transplantation of healthy human-derived microbiota or Phascolarctobacterium reduced luminal succinate levels and restored colonization resistance in UC-HMA mice. IL-22-mediated host glycosylation thus fosters the growth of commensal bacteria that compete with C. difficile for the nutritional niche.
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FZAB, GEOZS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Extracellular vesicles (EVs) originating from intraluminal vesicles (ILVs) formed within multivesicular bodies (MVBs), often referred to as small EV (sEV) or exosomes, are aberrantly produced by ...cancer cells and regulate the tumor microenvironment. The tyrosine kinase c-Src is upregulated in a wide variety of human cancers and is involved in promoting sEV secretion, suggesting its role in malignant progression. In this study, we found that activated Src liberated synaptosomal-associated protein 23 (SNAP23), a SNARE molecule, from lipid rafts to non-rafts on cellular membrane. We also demonstrated that SNAP23 localized in non-rafts induced cholesterol downregulation and ILV formation, resulting in the upregulation of sEV production in c-Src-transformed cells. Furthermore, the contribution of the SNAP23-cholesterol axis on sEV upregulation was confirmed in pancreatic cancer cells. High SNAP23 expression is associated with poor prognosis in patients with pancreatic cancer. These findings suggest a unique mechanism for the upregulation of sEV production via SNAP23-mediated cholesterol downregulation in Src-activated cancer cells.
•Capillary electrophoresis-mass spectrometry (CE-MS) analysis of charged metabolites.•A sheathless interface can increase the sensitivity of CE-MS.•Different mass spectrometers present advantages and ...disadvantages for CE-MS.•Appropriate sample preparation is necessary for CE-MS-based metabolomics.•It is important for CE-MS to develop software to predict unknown metabolites.
Capillary electrophoresis-mass spectrometry (CE-MS) has emerged as a powerful new tool for comprehensive analysis of charged compounds. In this review, we provide a general description of the application of CE-MS in metabolome analysis, including the separation modes of CE, various interfaces and the mass spectrometers used. We also discuss strategies for sample pretreatment, data processing and peak identification, which are important processes in metabolome analysis. In addition, we highlight a number of new techniques to improve metabolite extraction, peak resolution and sensitivity. Finally, we provide some general conclusions and future perspectives.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Cancer cells alter their metabolism for the production of precursors of macromolecules. However, the control mechanisms underlying this reprogramming are poorly understood. Here we show that ...metabolic reprogramming of colorectal cancer is caused chiefly by aberrant MYC expression. Multiomics-based analyses of paired normal and tumor tissues from 275 patients with colorectal cancer revealed that metabolic alterations occur at the adenoma stage of carcinogenesis, in a manner not associated with specific gene mutations involved in colorectal carcinogenesis. MYC expression induced at least 215 metabolic reactions by changing the expression levels of 121 metabolic genes and 39 transporter genes. Further, MYC negatively regulated the expression of genes involved in mitochondrial biogenesis and maintenance but positively regulated genes involved in DNA and histone methylation. Knockdown of MYC in colorectal cancer cells reset the altered metabolism and suppressed cell growth. Moreover, inhibition of MYC target pyrimidine synthesis genes such as CAD, UMPS, and CTPS blocked cell growth, and thus are potential targets for colorectal cancer therapy.
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BFBNIB, NMLJ, NUK, PNG, SAZU, UL, UM, UPUK
Saliva is a readily accessible and informative biofluid, making it ideal for the early detection of a wide range of diseases including cardiovascular, renal, and autoimmune diseases, viral and ...bacterial infections and, importantly, cancers. Saliva-based diagnostics, particularly those based on metabolomics technology, are emerging and offer a promising clinical strategy, characterizing the association between salivary analytes and a particular disease. Here, we conducted a comprehensive metabolite analysis of saliva samples obtained from 215 individuals (69 oral, 18 pancreatic and 30 breast cancer patients, 11 periodontal disease patients and 87 healthy controls) using capillary electrophoresis time-of-flight mass spectrometry (CE-TOF-MS). We identified 57 principal metabolites that can be used to accurately predict the probability of being affected by each individual disease. Although small but significant correlations were found between the known patient characteristics and the quantified metabolites, the profiles manifested relatively higher concentrations of most of the metabolites detected in all three cancers in comparison with those in people with periodontal disease and control subjects. This suggests that cancer-specific signatures are embedded in saliva metabolites. Multiple logistic regression models yielded high area under the receiver-operating characteristic curves (AUCs) to discriminate healthy controls from each disease. The AUCs were 0.865 for oral cancer, 0.973 for breast cancer, 0.993 for pancreatic cancer, and 0.969 for periodontal diseases. The accuracy of the models was also high, with cross-validation AUCs of 0.810, 0.881, 0.994, and 0.954, respectively. Quantitative information for these 57 metabolites and their combinations enable us to predict disease susceptibility. These metabolites are promising biomarkers for medical screening.
Most cancer cells predominantly produce energy by glycolysis rather than oxidative phosphorylation via the tricarboxylic acid (TCA) cycle, even in the presence of an adequate oxygen supply (Warburg ...effect). However, little has been reported regarding the direct measurements of global metabolites in clinical tumor tissues. Here, we applied capillary electrophoresis time-of-flight mass spectrometry, which enables comprehensive and quantitative analysis of charged metabolites, to simultaneously measure their levels in tumor and grossly normal tissues obtained from 16 colon and 12 stomach cancer patients. Quantification of 94 metabolites in colon and 95 metabolites in stomach involved in glycolysis, the pentose phosphate pathway, the TCA and urea cycles, and amino acid and nucleotide metabolisms resulted in the identification of several cancer-specific metabolic traits. Extremely low glucose and high lactate and glycolytic intermediate concentrations were found in both colon and stomach tumor tissues, which indicated enhanced glycolysis and thus confirmed the Warburg effect. Significant accumulation of all amino acids except glutamine in the tumors implied autophagic degradation of proteins and active glutamine breakdown for energy production, i.e., glutaminolysis. In addition, significant organ-specific differences were found in the levels of TCA cycle intermediates, which reflected the dependency of each tissue on aerobic respiration according to oxygen availability. The results uncovered unexpectedly poor nutritional conditions in the actual tumor microenvironment and showed that capillary electrophoresis coupled to mass spectrometry-based metabolomics, which is capable of quantifying the levels of energy metabolites in tissues, could be a powerful tool for the development of novel anticancer agents that target cancer-specific metabolism.
•High-throughput screening salivary polyamines by MSI-CE-MS/MS was developed.•The choice of BGE and its spacer volume affected peak resolution among samples.•This method enabled screening polyamines ...in 359 salivary samples in 360 min.•This method found N1-acetylspermine a promising biomarker for colorectal cancer.
Polyamine metabolites provide pathophysiological information on disease or therapeutic efficacy, yet rapid screening methods for these biomarkers are lacking. Here, we developed high-throughput polyamine metabolite profiling based on multisegment injection capillary electrophoresis triple quadrupole tandem mass spectrometry (MSI-CE-MS/MS), which allows sequential 40-sample injection followed by electrophoretic separation and specific mass detection. To achieve consecutive analysis of polyamine samples, 1 M formic acid was used as the background electrolyte (BGE). The BGE spacer volume had an apparent effect on peak resolution among samples, and 20 nL was selected as the optimal volume. The use of polyamine isotopomers as the internal standard enabled the correction of matrix effects in MS detection. This method is sensitive, selective and quantitative, and its utility was demonstrated by screening polyamines in 359 salivary samples within 360 min, resulting in discrimination of colorectal cancer patients from noncancer controls.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Tardigrades are microscopic animals that are renowned for their capabilities of tolerating near-complete desiccation by entering an ametabolic state called anhydrobiosis. However, many species also ...show high tolerance against radiation in the active state as well, suggesting cross-tolerance via the anhydrobiosis mechanism. Previous studies utilized indirect DNA damaging agents to identify core components of the cross-tolerance machinery in species with high anhydrobiosis capacities. However, it was difficult to distinguish whether transcriptomic changes were specific to DNA damage or mutual with anhydrobiosis. To this end, we performed transcriptome analysis on bleomycin-exposed Hypsibius exemplaris. We observed induction of several tardigrade-specific gene families, including a previously identified novel anti-oxidative stress family, which may be a core component of the cross-tolerance mechanism. We also identified enrichment of the tryptophan metabolism pathway, for which metabolomic analysis suggested engagement of this pathway in stress tolerance. These results provide several candidates for the core component of cross-tolerance, as well as possible anhydrobiosis machinery.
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FFLJ, NUK, ODKLJ, UL, UM, UPUK
•A double coaxial electrospray ionization sprayer improves the peak resolutions.•This method is highly selective and sensitive for anionic metabolites.•This method is suitable for non-targeted ...analysis of anionic metabolites.
Recently, ion chromatography coupled with mass spectrometry has been used for the determination of anionic metabolites. However, connection with a mass spectrometer in this method is not straightforward because backpressure produced by the addition of a make-up solution often affects the peak resolutions of the target metabolites. To overcome this problem, we developed a capillary ion chromatography-mass spectrometry method utilizing a double coaxial electrospray ionization sprayer. This method was not affected by backpressure and the number of theoretical plates was about three times that of a conventional sprayer. Under optimized conditions, 44 anionic metabolites, including organic acids, sugar phosphates, nucleotides, and cofactors, were successfully separated and selectively detected with a Q Exactive mass spectrometer. The calibration curves of the tested metabolites showed excellent linearity within the range of 1–100,000 nmol/L and the correlation coefficient was greater than 0.991. The detection limits for these metabolites were between 1 and 500 nmol/L (0.4 and 200 fmol). The developed method was applied to the quantitation of anionic metabolites in cultured cancer cell samples with tumor necrosis factor (TNF)-α stimulation. This allowed for the successful determination of 105 metabolites. The levels of tricarboxylic acid cycle intermediates changed significantly after TNF-α stimulation. These results demonstrate that the developed method is a promising new tool for comprehensive analysis of anionic metabolites.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
A sheath‐flow interface is the most common ionization technique in CE‐ESI‐MS. However, this interface dilutes the analytes with the sheath liquid and decreases the sensitivity. In this study, we ...developed a sheathless CE‐MS interface to improve sensitivity. The interface was fabricated by making a small crack approximately 2 cm from the end of a capillary column fixed on a plastic plate, and then covering the crack with a dialysis membrane to prevent metabolite loss during separation. A voltage for CE separation was applied between the capillary inlet and the buffer reservoir. Under optimum conditions, 52 cationic metabolite standards were separated and selectively detected using MS. With a pressure injection of 5 kPa for 15 s (ca. 1.4 nL), the detection limits for the tested compounds were between 0.06 and 1.7 μmol/L (S/N = 3). The method was applied to analysis of cationic metabolites extracted from a small number (12 000) of cancer cells, and the number of peaks detected was about 2.5 times higher than when using conventional sheath‐flow CE‐MS. Because the interface is easy to construct, it is cost‐effective and can be adapted to any commercially available capillaries. This method is a powerful new tool for highly sensitive CE‐MS‐based metabolomic analysis.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK