{"title":"Metabolite profiling of different solvent extracts of Moringa oleifera seeds and correlation with DPPH radical scavenging activity via 1H NMR-based metabolomics","authors":"Oluwayemisi Juliannah Famurewa, Yarkasuwa Chindo Istifanus, Adamu Mahmoud Auwal","doi":"10.5897/jmsb2023.0029","DOIUrl":"https://doi.org/10.5897/jmsb2023.0029","url":null,"abstract":"In the present study, profiling of the Moringa oleifera seeds metabolome was carried out by employing proton nuclear magnetic resonance (1H NMR) spectroscopy combined with multivariate data analysis (MVDA) of 3 different solvent extracts. The principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA) score plot reveal that methanol extract was discriminated from ethyl acetate and hexane extracts by PC1 while ethyl acetate and hexane extracts were well separated from methanol extract by PC2. The PLS-DA loading plot highlighted the potential metabolites, which are responsible for the group separation observed in the score plot. Further detailed examination of the loading plot shows that methanol extract contains significantly higher amount of vitamins, sterols, amino acids and fatty acids compared to the other extracts. A total of 37 compounds were detected from the 3 different solvents upon which the methanolic extract was identified to contain more metabolites and in a wider range than the other organic solvent extracts. Based on PLS analysis, ergosterol, oleic acid, isoleucine, riboflavin, cholesterol, leucine, ascorbic acid, stigmasterol, tryptophan, choline, histidine and cysteine displayed strong correlation to 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging activity. Hence, this extract would be more appropriate in metabolite extraction for analysis and for therapeutical benefits. Therefore, NMR spectroscopy combined with MVDA in compliment with the right choice of solvent for extraction could be utilized by applicable industries to obtain maximum valued metabolites within a short period of time. Besides having high diversity of metabolites, M. oleifera seeds can serve as potential nutritional source to develop new functional foods, and even as a source of biodiesel. Key words: Moringa oleifera seeds, functional food, biofuel, metabolome, 2,2-diphenyl-1-picrylhydrazyl (DPPH), multivariate data analysis, 1H NMR metabolomics.","PeriodicalId":90225,"journal":{"name":"Journal of metabolomics and systems biology","volume":"215 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136271517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nath Srivastava Rajeshwar, Ara Zeenat, Waliullah Shah, Singh Alka, Raj Saloni, A. M. Abbas, Kumar Garg Ravindra, Roy Raja
{"title":"Taurine is a future biomolecule for potential health benefits: A review","authors":"Nath Srivastava Rajeshwar, Ara Zeenat, Waliullah Shah, Singh Alka, Raj Saloni, A. M. Abbas, Kumar Garg Ravindra, Roy Raja","doi":"10.5897/jmsbs2021.0026","DOIUrl":"https://doi.org/10.5897/jmsbs2021.0026","url":null,"abstract":"","PeriodicalId":90225,"journal":{"name":"Journal of metabolomics and systems biology","volume":"202 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73674345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Gateway between Omics Data and Systems Biology.","authors":"Fabian V Filipp","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Metabolomics captures the cellular chemistry and thereby the ultimate realization of numerous genetic, transcriptional, and enzymatic events. The mechanistic interpretation of small molecules as substrates, intermediates, or products of biochemical action is necessary to place metabolites into the correct physiological context of a system. Therefore, the tight connection between omics technologies and systems biology is vital.</p>","PeriodicalId":90225,"journal":{"name":"Journal of metabolomics and systems biology","volume":"1 1","pages":"1"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3920656/pdf/nihms543997.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32116232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Gateway between Omics Data and Systems Biology.","authors":"F. Filipp","doi":"10.13188/2329-1583.1000003","DOIUrl":"https://doi.org/10.13188/2329-1583.1000003","url":null,"abstract":"Metabolomics captures the cellular chemistry and thereby the ultimate realization of numerous genetic, transcriptional, and enzymatic events. The mechanistic interpretation of small molecules as substrates, intermediates, or products of biochemical action is necessary to place metabolites into the correct physiological context of a system. Therefore, the tight connection between omics technologies and systems biology is vital.","PeriodicalId":90225,"journal":{"name":"Journal of metabolomics and systems biology","volume":"28 1 1","pages":"1"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78870404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Prakriti Mudvari, Kamran Kowsari, Charles Cole, Raja Mazumder, Anelia Horvath
{"title":"Extraction of Molecular Features through Exome to Transcriptome Alignment.","authors":"Prakriti Mudvari, Kamran Kowsari, Charles Cole, Raja Mazumder, Anelia Horvath","doi":"10.13188/2329-1583.1000002","DOIUrl":"https://doi.org/10.13188/2329-1583.1000002","url":null,"abstract":"<p><p>Integrative Next Generation Sequencing (NGS) DNA and RNA analyses have very recently become feasible, and the published to date studies have discovered critical disease implicated pathways, and diagnostic and therapeutic targets. A growing number of exomes, genomes and transcriptomes from the same individual are quickly accumulating, providing unique venues for mechanistic and regulatory features analysis, and, at the same time, requiring new exploration strategies. In this study, we have integrated variation and expression information of four NGS datasets from the same individual: normal and tumor breast exomes and transcriptomes. Focusing on SNPcentered variant allelic prevalence, we illustrate analytical algorithms that can be applied to extract or validate potential regulatory elements, such as expression or growth advantage, imprinting, loss of heterozygosity (LOH), somatic changes, and RNA editing. In addition, we point to some critical elements that might bias the output and recommend alternative measures to maximize the confidence of findings. The need for such strategies is especially recognized within the growing appreciation of the concept of systems biology: integrative exploration of genome and transcriptome features reveal mechanistic and regulatory insights that reach far beyond linear addition of the individual datasets.</p>","PeriodicalId":90225,"journal":{"name":"Journal of metabolomics and systems biology","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2013-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4003560/pdf/nihms520854.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32311628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}