• Animal Bioscience
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• 제37권5호
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• pp.918-928
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• 2024

Objective: The adulteration of raw beef (BMr) with dog meat (DMr) and pork (PMr) becomes a serious problem because it is associated with halal status, quality, and safety of meats. This research aimed to develop an effective authentication method to detect non-halal meats (dog meat and pork) in beef using metabolomics approach. Methods: Liquid chromatography-high resolution mass spectrometry (LC-HRMS) using untargeted approach combined with chemometrics was applied for analysis non-halal meats in BMr. Results: The untargeted metabolomics approach successfully identified various metabolites in BMr DMr, PMr, and their mixtures. The discrimination and classification between authentic BMr and those adulterated with DMr and PMr were successfully determined using partial least square-discriminant analysis (PLS-DA) with high accuracy. All BMr samples containing non-halal meats could be differentiated from authentic BMr. A number of discriminating metabolites with potential as biomarkers to discriminate BMr in the mixtures with DMr and PMr could be identified from the analysis of variable importance for projection value. Partial least square (PLS) and orthogonal PLS (OPLS) regression using discriminating metabolites showed high accuracy (R² >0.990) and high precision (both RMSEC and RMSEE <5%) in predicting the concentration of DMr and PMr present in beef indicating that the discriminating metabolites were good predictors. The developed untargeted LC-HRMS metabolomics and chemometrics successfully identified non-halal meats adulteration (DMr and PMr) in beef with high sensitivity up to 0.1% (w/w). Conclusion: A combination of LC-HRMS untargeted metabolomic and chemometrics promises to be an effective analytical technique for halal authenticity testing of meats. This method could be further standardized and proposed as a method for halal authentication of meats.

• Mass Spectrometry Letters
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• 제11권1호
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• pp.1-5
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• 2020

In this study, some of the recently reported data processing strategies were evaluated and modified based on their capabilities and a brief workflow for data mining was redefined for Q-TOF LC-MS based untargeted metabolomics. Commercial pooled human plasma samples were used for this purpose. An ultrafiltration procedure was applied on sample preparation. Sample set was analyzed through Q-TOF LC/MS. A C18 column (Agilent Zorbax 1.8 µM, 50 × 2.1 mm) was used for chromatographic separation. Raw chromatograms were processed using XCMS - R programming language edition and Isotopologue Parameter Optimization (IPO) was used to optimize XCMS parameters. The raw XCMS table was processed using MS Excel to find reliable and reproducible peaks. Totally 1650 reliable and reproducible potential metabolite peaks were found based on the data processing procedures given in this paper. The redefined dataset was upload into MetaboAnalyst platform and the identified metabolites were matched with 86 metabolic pathways. Thus, two list were obtained and presented in this study as supplement files. The first list is to present the retention times and m/z values of detected metabolite peaks. The second list is the metabolic pathways related with the identified metabolites. The briefly described data processing strategies and dataset presented in this study could be beneficial for the researchers working on untargeted metabolomics for processing their data and validating their results.

• Mass Spectrometry Letters
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• 제11권2호
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• pp.36-40
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• 2020

Untargeted metabolomics is a useful tool for drug development focusing on novel chemotherapeutic and chemopreventative agents against cancer cells. In recent years, quadrupole time of flight liquid chromatography-mass spectrometry (Q-TOF LC/MS)-based untargeted metabolomic approaches have gained importance to evaluate the effect of these agents at the molecular level. The researchers working on cell culture studies still do not apply standardized methodologies on sample preparation for untargeted metabolomics approaches. In this study, the rough and wet lysis techniques performed on MCF-7 breast cancer cells were compared with each other via the Q-TOF LC/MS-based metabolomic approach. The C18 and hydrophilic interaction liquid chromatography (HILIC) columns were used for the separation of the metabolites in MCF-7 cell lysates. 505 peaks were detected through the HILIC column and 551 peaks were found through the C18 column for the wet lysis technique. This situation supported by the base peak chromatograms showed that the wet lysis technique allowed us to extract higher number of non-polar metabolites. Almost equal number of metabolites was found for the C18 and HILIC columns (697 peaks for the HILIC column and 695 peaks for the C18 column) when the rough lysis technique was used. However, the intensities of polar metabolites were higher for the rough lysis technique on base peak chromatograms for both the HILIC and C18 columns. Although cell lysis technique, which is the first step in the sample preparation for cell culture studies, does not cause dramatic differences in the number of the detected metabolite peaks, it affects the polar and non-polar metabolite ratio significantly. Therefore, it must be considered carefully especially for in vitro drug development studies.

• Mass Spectrometry Letters
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• 제11권2호
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• pp.17-24
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• 2020

Metabolomics has become an important research field with many areas of applications ranging from disease biomarker discovery to global biology systems study. A key step in metabolomics is to perform metabolome analysis to obtain quantitative information on metabolic changes among comparative samples. Mass spectrometry (MS) is widely used for highly sensitive detection of many different types of metabolites. In this review, we highlight some of the more commonly used MS techniques for metabolome analysis.

• Journal of Microbiology and Biotechnology
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• 제26권3호
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• pp.572-578
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• 2016

Communication between endothelial cells (ECs) and smooth muscle cells (SMCs) via miR-143/145 clusters is vital to vascular stability. Previous research demonstrates that miR-143/145 released from ECs can regulate SMC proliferation and migration. In addition, a recent study has found that SMCs also have the capability of manipulating EC function via miR-143/145. In the present study, we artificially increased the expression of miR-143/145 in ECs, to mimic a similar change caused by miR-143/145 released by SMCs, and applied untargeted metabolomics analysis, aimed at investigating the consequential effect of miR-143/145 overexpression. Our results showed that miR-143/145 overexpression alters the levels of metabolites involved in energy production, DNA methylation, and oxidative stress. These changed metabolites indicate that metabolic pathways, such as the SAM cycle and TCA cycle, exhibit significant differences from the norm with miR-143/145 overexpression.

• Mass Spectrometry Letters
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• 제9권4호
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• pp.91-94
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• 2018

Bilin tetrapyrroles are metabolic products of the breakdown of porphyrins within a species. In the case of mammals, these bilins are formed by the catabolism of heme and can be utilized as either biomarkers in disease or as an indicator of human waste contamination. Although a small subset of bilin tandem mass spectrometry reports exist, limited data is available in online databases for their fragmentation. The use of fragmentation data is important for metabolomics analyses to determine the identity of compounds detected within a sample. Therefore, in this study, the fragmentation of bilins generated by positive ion mode electrospray ionization is examined by collision-induced dissociation (CID) as a function of collision energy on an FT-ICR MS. The use of the FT-ICR MS allows for high mass accuracy measurements, and thus the formulas of resultant product ions can be ascertained. Based on our observations, fragmentation behavior for hemin, biliverdin and its dimethyl ester, phycocyanobilin, bilirubin, bilirubin conjugate, mesobilirubin, urobilin, and stercobilin are discussed in the context of the molecular structure and collision energy. This report provides insight into the identification of structures within this class of molecules for untargeted analyses.

• Natural Product Sciences
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• 제27권4호
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• pp.257-263
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• 2021

Aster species (Asteraceae) are widely distributed edible and medicinal plants, known to contain various specialized metabolites including polyphenols and saponins. However, systemic analysis on the chemical profiles of these plants have rarely been made. Here we analyzed the phytochemical constituents in leaves of 6 Aster species occurring in Korea, A. ageratoides, A. altaicus var. uchiyamae, A. glehnii, A. hispidus, A. incisus, and A. yomena, by applying a LC-MS/MS-based untargeted metabolomics approach. The analysis revealed that A. ageratoides, A. hispidus, and A. yomena are relatively rich in saponins most of which are expected to be previously unknown.

• Mass Spectrometry Letters
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• 제14권2호
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• pp.42-47
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• 2023

Carthamus tinctorius L. (known as safflower) is a valuable oil plant whose importance is increasing rapidly in the world due to its high adaptation to arid regions. The seeds of this unique plant are especially used in edible oil, soap, paint, varnish and lacquer production. Its flowers are used in vegetable dye production and medicinal purposes beside its features as a coloring and flavoring in food. After the oil is removed, the remaining pulp and plant parts are used as animal feed, and dry straw residues are used as fuel. Beside all these features, its usage as a herbal medicinal plants for various diseases has gained importance on recent years. In this study, it was designed a plant metabolomic approach which transfers all the recent data processing strategies of untargeted metabolomics in clinical applications to the present study. Q-TOF LC/MS-based analysis of the extracts (70% ethanol, hexane, and chloroform) for both seed and flowers was performed using a C18 column (Agilent Zorbax 1.8 µM, 100 × 2.1 mm). Differences were observed in seed and fruit extracts and these differences were visualized using principal component analysis (PCA) plots. The total number and intersections of the peaks in the extracts were visualized using peak count comparison graph. Based on the experimental results, the number of the detected peaks for seeds was higher than the ones for the flowers for all solvent systems to extract the samples.

• Nutrition Research and Practice
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• 제17권6호
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• pp.1238-1254
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• 2023

BACKGROUND/OBJECTIVES: Weight loss via a mobile application (App) or a paper-based diary (Paper) may confer favorable metabolic and anthropometric changes. SUBJECTS/METHODS: A randomized parallel trial was conducted among 57 adults whose body mass indices (BMIs) were 25 kg/m² or greater. Participants randomly assigned to either the App group (n = 30) or the Paper group (n = 27) were advised to record their foods and supplements through App or Paper during the 12-week intervention period. Relative changes of anthropometries and biomarker levels were compared between the 2 intervention groups. Untargeted metabolic profiling was identified to discriminate metabolic profiles. RESULTS: Out of the 57 participants, 54 participants completed the trial. Changes in body weight and BMI were not significantly different between the 2 groups (P = 0.11). However, body fat and low-density lipoprotein (LDL)-cholesterol levels increased in the App group but decreased in the Paper group, and the difference was statistically significant (P = 0.03 for body fat and 0.02 for LDL-cholesterol). In the metabolomics analysis, decreases in methylglyoxal and (S)-malate in pyruvate metabolism and phosphatidylcholine (lecithin) in linoleic acid metabolism from pre- to post-intervention were observed in the Paper group. CONCLUSIONS: In the 12-week randomized parallel trial of weight loss through a App or a Paper, we found no significant difference in change in BMI or weight between the App and Paper groups, but improvement in body fatness and LDL-cholesterol levels only in the Paper group under the circumstances with minimal contact by dietitians or health care providers.

• Journal of Microbiology and Biotechnology
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• 제33권12호
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• pp.1657-1670
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• 2023

This study aimed to evaluate the effects of Limosilactobacillus fermentum and Lactiplantibacillus plantarum isolated from human feces coordinating with inulin on the composition of gut microbiota and metabolic profiles in db/db mice. These supplements were administered to db/db mice for 12 weeks. The results showed that the Lactobacillaceae coordinating with inulin group (LI) exhibited lower fasting blood glucose levels than the model control group (MC). Additionally, LI was found to enhance colon tissue and increase the levels of short-chain fatty acids. 16S rRNA sequencing revealed that the abundance of Corynebacterium and Proteus, which were significantly increased in the MC group compared with NC group, were significantly decreased by the treatment of LI that also restored the key genera of the Lachnospiraceae_NK4A136_group, Lachnoclostridium, Ruminococcus_gnavus_group, Desulfovibrio, and Lachnospiraceae_UCG-006. Untargeted metabolomics analysis showed that lotaustralin, 5-hydroxyindoleacetic acid, and 13(S)-HpODE were increased while L-phenylalanine and L-tryptophan were decreased in the MC group compared with the NC group. However, the intervention of LI reversed the levels of these metabolites in the intestine. Correlation analysis revealed that Lachnoclostridium and Ruminococcus_gnavus_group were negatively correlated with 5-hydroxyindoleacetic acid and 13(S)-HpODE, but positively correlated with L-tryptophan. 13(S)-HpODE was involved in the "linoleic acid metabolism". L-tryptophan and 5-hydroxyindoleacetic acid were involved in "tryptophan metabolism" and "serotonergic synapse". These findings suggest that LI may alleviate type 2 diabetes symptoms by modulating the abundance of Ruminococcus_gnavus_group and Lachnoclostridium to regulate the pathways of "linoleic acid metabolism", "serotonergic synapse", and" tryptophan metabolism". Our results provide new insights into prevention and treatment of type 2 diabetes.