LC/MS/MS technique, employing QTOF mass analyzer, was used for comparative metabolomic fingerprinting of seven edible mushroom varieties (P.ostreatus, L.edodes, L.sulphureus, A.campestris, T.clypeatus, T.microcarpus and T.letestui). The aim was to identify biomarkers unique to L.sulphureus which might be responsible for the pharmacological claim of the mushroom by the Kaffa people in Ethiopia. As an outcome of the data mining and pre-treatment step using MarkerviewTM software, positive and negative ionization data matrices of 71,083 and 54,856 peaks, respectively, were obtained. Regardless of the ionization mode, the principal component analysis (PCA) of the data set representing the seven edible mushrooms each in triplicate revealed a unique separate clusters for L.sulphureus, documenting differences in LC-MS profiles associated with the sample. Based on plot profile, only 14 and 27 peaks representing monoisotopic ions unique to L.sulphureus at the positive and negative ionization mode respectively were obtained. All the pre-selected biomarkers were searched from METLIN metabolite database, but only one peak at 13.41 min with m/z of 471.3468 and 469.3348, positive and negative ionization, respectively were tentatively identified as 18α-glycyrrhetinic acid (commonly called Enoxolone). This metabolite was verified by comparing the retention time, MS and MS/MS data spectra of authentic standard and sample obtained from PeakviewTM software. Mass frontier software was used to generate possible fragmentation and rearrangement mechanisms of the parent ion. In conclusion, 18α-glycyrrhetinic acid might be one of the compounds responsible for the biological claim of the local people.
Published in | International Journal of Nutrition and Food Sciences (Volume 4, Issue 2) |
DOI | 10.11648/j.ijnfs.20150402.14 |
Page(s) | 141-153 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2015. Published by Science Publishing Group |
Mushroom, LC-MS/MS, Metabolomics, PCA, Biomarkers, 18α-Glycyrrhetinic Acid
[1] | Abate, D. (1998). Mushroom cultivation a practical approach. Addis Ababa: Berhanena Selam Printing Enterprise. |
[2] | AB SCIEX. (2010). MarkerViewTM software 1.2.1 for metabolomic and biomarker profiling analysis: Reference manual. Ontario, Canda: AB SCIEX Pte. Ltd. |
[3] | AB SCIEX. (2012). PeakView Software version 1.0: Reference manual. Ontario, Canda: AB SCIEX Pte. Ltd. |
[4] | Arase, Y., Ikeda, K., Murashima, V., Chayama, K., Tsubota, A., Koida, I., et al. (1997). The long term efficacy of glycyrrhizin in chronic hepatitis C patients. Cancer, 79, 1494-1500. |
[5] | Baker, M. E. (1994). Licorice and enzymes other than 11β- hydroxysteroid dehydrogenase: An evolutionary perspective. Steriods, 59, 136-141. |
[6] | Barran, J., Langford, D., & Pitzele, B. (1974). Synthesis and biological activities of substituted glycyrrhetic acids. Journal of Medicinal Chemistry, 17, 184-191. |
[7] | Barros, L., Baptista, P., & Ferreira, I. C. (2007). Effect of Lactarius piperatus fruiting body maturity stage on antioxidant activity measured by several biochemical assays. Food and Chemical Toxicololgy, 45, 1731–1737. |
[8] | Berrueta, L. A., Alfonso-Salces, R. M., & Herberger, K. (2007). Supervised pattern recognition in food analysis. Journal of Chromatography A, 1158, 196-214. |
[9] | Cevallos–Cevallos, J. M., Reyes-De-Corcuera, J. I., Etxeberria, E., Danyluk, M. D., & Rodrick, G. E. (2009). Metabolomic analysis in food science: A review. Trends in Food Sciene and Technology, 20, 557-566. |
[10] | Chandler, R. F. (1985). Licorice, more than just a flavour. Canadian Pharmaceutical Journal , 118, 420-424. |
[11] | Chung, W., Lee, S. H., Kim, J., Sung, N., Hwang, B., Lee, S. Y., et al. (2001). Effect of the extracts from Glycyrrhiza uralensis Fisch. on the growth characteristics of human cell lines: antitumor and immune activation activities. Cytotechnology, 37, 55-64. |
[12] | Cragg, G. M., & Newman, D. J. (2005). International collaboration in drug discovery and development from natural sources. Pure and Applied Chemistry, 77, 1923-1942. |
[13] | Crisan, E. V., & Sands, A. (1978). Nutritional value. In S. T. Chang, & W. A. Hayes, The biology and cultivation of edible mushrooms (pp. 137-165). New York: Academic Press. |
[14] | Cui, Q., Lewis, I. A., Hegeman, A. D., et al. (2008). Metabolite identification via the Madison Metabolomics Consortium Database. Nature Biotechnology, 26(2), 162-164. |
[15] | Dunn, W. B., & Ellis, D. I. (2005). Metabolomics: Current analytical platforms and methodologies. Trends in Analytical Chemistry, 24, 285-294. |
[16] | Giavalisco, P., Kohl, K., Hummmel, J., Seiwert, B., & Willmitzer, L. (2009). 13C isotope-labeled metabolomes allowing for improved compound annotation and relative quantification in iquid chromatography-mass spectrometry-based metabolomic research. Analytical Chemistry, 81(15), 6546-6551. |
[17] | Glish, G. L., & Burinsky, D. J. (2008). Hybrid mass spectrometers for tandem mass spectrometry. Journal of the American Society for Mass Spectrometry, 19(2), 161-172. |
[18] | Griffiths, W. J., Koal, T., Wang, M., Kohl, M., Enot, D., & Deigner, H. P. (2010). Targeted metabolomics for biomarker discovery. Angewandte Chemie International Edition, 49 (32), 5426-5445. |
[19] | Go, E. P. (2010). Database resoures in metabolomics: an overview. Journal of Neuroimmune Pharmacology, 5(1), 18-30. |
[20] | Kaddurah-Daouk, R., & Krishnan, K. R. (2008). Metabolomics: A global approach to the study of central nervous system diseases. Neuropsychopharmacology, 34, 173-186. |
[21] | Kelleher, N. L., Lin, H. Y., Valaskovic, G. A., Aaserud, D. J., Fridriksson, E. K., & McLafferty, F. W. (1999). Top down versus bottom up protein characterization by tandem high-resolution mass spectrometry. Journal of the Americal Chemical Society, 121(4), 806-812. |
[22] | Kurasawa, S., Sugahara, T., & Hayashi, J. (1982). Studies on dietary fiber of mushrooms and edible wild plants. Nutrition Reports International, 26, 167-173. |
[23] | Lacorte, S., & Fernandez-Alba, A. R. (2006). Time of flight mass spectrometry applied to the liquid chromatographic analysis of pesticides in water and food. Mass Spectrometry Reviews , 25(6), 866-880. |
[24] | Luo, H., Huang, W., Zhang, Z., Wu, Q., Huang, M., Zhang, D., et al. (2004). 18β-glycyrrhetinic acid-induced apoptosis and relation with intracellular Ca2+ release in human breast carcinoma cells. The Chinese-German Journal of Clinical Oncology, 3, 137-140. |
[25] | Mahato, S., Nandy, A., & Roy, G. (1992). Triterpenoids. Phytochemistry, 31, 2199-2249. |
[26] | Makarov, A., Denisov, E., Kholomeev, A., Baischun, W., Lange, O., Strupat, K., et al. (2006). Performance evaluation of a hybrid linear ion trap/orbitrap mass spectrometer. Analytical Chemistry, 1(78),2113-21120. |
[27] | Manzi, P., Aguzzi, A., Vivanti, V., Paci, M., & Pizzoferrato, L. (2001). Nutritional value of mushrooms widely consumed in Italy. Food Chemistry, 73, 321-325. |
[28] | Nabekura, T., Yamaki, T., Ueno, K., & Kitagawa, S. (2008). Inhibition of p-glycoprotein and multidrug resistance protein 1 by dietary phytochemicals. Cancer Chemotherapy and Pharmacology , 62, 867-873. |
[29] | Oliver, S. G., Winson, M. K., Kell, D. B., & Baganz, F. (1998). Systematic functional analysis of the yeast genome. Trends Biotechnology, 16(10), 373-378. |
[30] | Rosenblum, E. S., Viant, M. R., Braid, B. M., Moore, J. D., Friedman, C. S., & Tjeerdema, R. S. (2005). Characterizing the metabolic actions of natural stresses in the California red abalone, Haliotis rufescens using 1H NMR metabolomics. Metabolomics, 1(2), 199-209. |
[31] | Ryu, S., Choi, S., Lee, S., Lee, C., No, Z., & Ahn, J. (1994). Antitumor triterpenes from medicinal plants. Archives of Pharmacological Research, 17, 375-377. |
[32] | Saito, K., & Matsuda, F. (2010). Metabolomics for functional genomics, systems biology, and biotechnology. Annual Review of Plant Biology, 61, 463-489. |
[33] | Smith, C. A., O'Maille, G., Want, E. J., et al. (2005). METLIN: a metabolite mass spectral database. Therapeutic Drug Monitoring, 27(6), 747-751. |
[34] | Strandberg, T. E., Andersson, S., Järvenpää, A. L., & McKeigue, P. M. (2002). Preterm birth and licorice consumption during pregnancy. American Journal of Epidemology, 156(9), 803-805. |
[35] | Sumner, L. W., Amberg, A., Barrett, D., Beger, R., Beale, M. H., Daykin, C., et al. (2007). Proposed minimum reporting standards for chemical analysis. Metabolomics, 3, 211-221. |
[36] | Theodoridis, G., Gika, H. G., & Wilson, I. D. (2008). LC-MS-based methodology for global metabolite profiling in metabonomics/metabolomics. Trends in Analytical Chemistry, 27(3), 251-260. |
[37] | Vaclavik, L., Schreiber, A., Lacina, O., Cajka, T., & Hajslova, J. (2012). Liquid chromatography–mass spectrometry-based metabolomics for authenticity assessment of fruit juices. Metabolomics, 8, 793-803. |
[38] | Van Rossum, T., Vulto, A., DeMan, R., Brouwer, J., & Schlam, S. (1998). Review article: glycyrrhizin as potential treatment for chronic hepatitis C. Alimentary Pharmacology and Therapeutics, 12, 199-205. |
[39] | Wishart, D. S., Tzur, D., Knox, C., et al. (2007). HMDB: the Human Metabolome Database. Nucleic Acids Research, 35, D521-D526. |
[40] | Wishart, D. S. (2008). Application of metabolomics in drug discovery and development. Drugs in R & D , 9, 307-322. |
[41] | Zhou, B., Xiao, J. F., Tuli, L., & Ressom, H. W. (2012). LC-MS-based metabolomics. Molecular BioSystems , 8, 470–481. |
APA Style
Ashagrie Z. Woldegiorgis, Dawit Abate, Gulelat D. Haki, Gregory R. Ziegler. (2015). LC-MS/MS Based Metabolomics to Identify Biomarkers Unique to Laetiporus sulphureus. International Journal of Nutrition and Food Sciences, 4(2), 141-153. https://doi.org/10.11648/j.ijnfs.20150402.14
ACS Style
Ashagrie Z. Woldegiorgis; Dawit Abate; Gulelat D. Haki; Gregory R. Ziegler. LC-MS/MS Based Metabolomics to Identify Biomarkers Unique to Laetiporus sulphureus. Int. J. Nutr. Food Sci. 2015, 4(2), 141-153. doi: 10.11648/j.ijnfs.20150402.14
AMA Style
Ashagrie Z. Woldegiorgis, Dawit Abate, Gulelat D. Haki, Gregory R. Ziegler. LC-MS/MS Based Metabolomics to Identify Biomarkers Unique to Laetiporus sulphureus. Int J Nutr Food Sci. 2015;4(2):141-153. doi: 10.11648/j.ijnfs.20150402.14
@article{10.11648/j.ijnfs.20150402.14, author = {Ashagrie Z. Woldegiorgis and Dawit Abate and Gulelat D. Haki and Gregory R. Ziegler}, title = {LC-MS/MS Based Metabolomics to Identify Biomarkers Unique to Laetiporus sulphureus}, journal = {International Journal of Nutrition and Food Sciences}, volume = {4}, number = {2}, pages = {141-153}, doi = {10.11648/j.ijnfs.20150402.14}, url = {https://doi.org/10.11648/j.ijnfs.20150402.14}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijnfs.20150402.14}, abstract = {LC/MS/MS technique, employing QTOF mass analyzer, was used for comparative metabolomic fingerprinting of seven edible mushroom varieties (P.ostreatus, L.edodes, L.sulphureus, A.campestris, T.clypeatus, T.microcarpus and T.letestui). The aim was to identify biomarkers unique to L.sulphureus which might be responsible for the pharmacological claim of the mushroom by the Kaffa people in Ethiopia. As an outcome of the data mining and pre-treatment step using MarkerviewTM software, positive and negative ionization data matrices of 71,083 and 54,856 peaks, respectively, were obtained. Regardless of the ionization mode, the principal component analysis (PCA) of the data set representing the seven edible mushrooms each in triplicate revealed a unique separate clusters for L.sulphureus, documenting differences in LC-MS profiles associated with the sample. Based on plot profile, only 14 and 27 peaks representing monoisotopic ions unique to L.sulphureus at the positive and negative ionization mode respectively were obtained. All the pre-selected biomarkers were searched from METLIN metabolite database, but only one peak at 13.41 min with m/z of 471.3468 and 469.3348, positive and negative ionization, respectively were tentatively identified as 18α-glycyrrhetinic acid (commonly called Enoxolone). This metabolite was verified by comparing the retention time, MS and MS/MS data spectra of authentic standard and sample obtained from PeakviewTM software. Mass frontier software was used to generate possible fragmentation and rearrangement mechanisms of the parent ion. In conclusion, 18α-glycyrrhetinic acid might be one of the compounds responsible for the biological claim of the local people.}, year = {2015} }
TY - JOUR T1 - LC-MS/MS Based Metabolomics to Identify Biomarkers Unique to Laetiporus sulphureus AU - Ashagrie Z. Woldegiorgis AU - Dawit Abate AU - Gulelat D. Haki AU - Gregory R. Ziegler Y1 - 2015/03/02 PY - 2015 N1 - https://doi.org/10.11648/j.ijnfs.20150402.14 DO - 10.11648/j.ijnfs.20150402.14 T2 - International Journal of Nutrition and Food Sciences JF - International Journal of Nutrition and Food Sciences JO - International Journal of Nutrition and Food Sciences SP - 141 EP - 153 PB - Science Publishing Group SN - 2327-2716 UR - https://doi.org/10.11648/j.ijnfs.20150402.14 AB - LC/MS/MS technique, employing QTOF mass analyzer, was used for comparative metabolomic fingerprinting of seven edible mushroom varieties (P.ostreatus, L.edodes, L.sulphureus, A.campestris, T.clypeatus, T.microcarpus and T.letestui). The aim was to identify biomarkers unique to L.sulphureus which might be responsible for the pharmacological claim of the mushroom by the Kaffa people in Ethiopia. As an outcome of the data mining and pre-treatment step using MarkerviewTM software, positive and negative ionization data matrices of 71,083 and 54,856 peaks, respectively, were obtained. Regardless of the ionization mode, the principal component analysis (PCA) of the data set representing the seven edible mushrooms each in triplicate revealed a unique separate clusters for L.sulphureus, documenting differences in LC-MS profiles associated with the sample. Based on plot profile, only 14 and 27 peaks representing monoisotopic ions unique to L.sulphureus at the positive and negative ionization mode respectively were obtained. All the pre-selected biomarkers were searched from METLIN metabolite database, but only one peak at 13.41 min with m/z of 471.3468 and 469.3348, positive and negative ionization, respectively were tentatively identified as 18α-glycyrrhetinic acid (commonly called Enoxolone). This metabolite was verified by comparing the retention time, MS and MS/MS data spectra of authentic standard and sample obtained from PeakviewTM software. Mass frontier software was used to generate possible fragmentation and rearrangement mechanisms of the parent ion. In conclusion, 18α-glycyrrhetinic acid might be one of the compounds responsible for the biological claim of the local people. VL - 4 IS - 2 ER -