دورية أكاديمية
أعرض في EDS

Optimization of fecal sample homogenization for untargeted metabolomics.

التفاصيل البيبلوغرافية
العنوان: Optimization of fecal sample homogenization for untargeted metabolomics.
المؤلفون: Tarazona Carrillo K; Department of Chemistry, University of Alberta, Edmonton, AB, T6G 2G2, Canada., Nam SL; Department of Chemistry, University of Alberta, Edmonton, AB, T6G 2G2, Canada., de la Mata AP; Department of Chemistry, University of Alberta, Edmonton, AB, T6G 2G2, Canada., de Bruin OM; DNA Genotek, Ottawa, ON, Canada., Doukhanine E; DNA Genotek, Ottawa, ON, Canada., Harynuk J; Department of Chemistry, University of Alberta, Edmonton, AB, T6G 2G2, Canada. james.harynuk@ualberta.ca.
المصدر: Metabolomics : Official journal of the Metabolomic Society [Metabolomics] 2023 Aug 11; Vol. 19 (8), pp. 74. Date of Electronic Publication: 2023 Aug 11.
نوع المنشور: Journal Article; Research Support, Non-U.S. Gov't
اللغة: English
بيانات الدورية: Publisher: Springer Country of Publication: United States NLM ID: 101274889 Publication Model: Electronic Cited Medium: Internet ISSN: 1573-3890 (Electronic) Linking ISSN: 15733882 NLM ISO Abbreviation: Metabolomics Subsets: MEDLINE
أسماء مطبوعة: Original Publication: New York : Springer, c2006-
مواضيع طبية MeSH: Metabolomics*/methods , Metabolome*, Reproducibility of Results ; Feces ; Solvents
مستخلص: Introduction: Fecal samples are highly complex and heterogeneous, containing materials at various stages of digestion. The heterogeneity and complexity of feces make stool metabolomics inherently challenging. The level of homogenization influences the outcome of the study, affecting the metabolite profiles and reproducibility; however, there is no consensus on how fecal samples should be prepared to overcome the topographical discrepancy and obtain data representative of the stool as a whole.
Objectives: Various combinations of homogenization conditions were compared to investigate the effects of bead size, addition of solvents and the differences between wet-frozen and lyophilized feces.
Methods: The homogenization parameters were systematically altered to evaluate the solvent usage, bead size, and whether lyophilization is required in homogenization. The metabolic coverage and reproducibility were compared among the different conditions.
Results: The current work revealed that a combination of mechanical and chemical lysis obtained by bead-beating with a mixture of big and small sizes of beads in an organic solvent is an effective way to homogenize fecal samples with adequate reproducibility and metabolic coverage. Lyophilization is required when bead-beating is not available.
Conclusions: A comprehensive and systematical evaluation of various fecal matter homogenization conditions provides a profound understanding for the effects of different homogenization methods. Our findings would be beneficial to assist with standardization of fecal sample homogenization protocol.
(© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)
References: Bliss, D. Z., Savik, K., Jung, H., Jensen, L., LeMoine, M., & Lowry, A. (1999). Comparison of subjective classification of stool consistency and stool water content. Journal of WOCN, 26(3), 137–141. https://doi.org/10.1016/S1071-5754(99)90031-1. (PMID: 10.1016/S1071-5754(99)90031-110711123)
Gangadoo, S., Rajapaksha Pathirannahalage, P., Cheeseman, S., Dang, Y. T. H., Elbourne, A., Cozzolino, D., Latham, K., Truong, V. K., & Chapman, J. (2021). The multiomics analyses of fecal matrix and its significance to coeliac disease gut profiling. International Journal of Molecular Sciences, 22(4), 1965. https://doi.org/10.3390/ijms22041965. (PMID: 10.3390/ijms22041965336711977922330)
Gao, X., Pujos-Guillot, E., & Sébédio, J.-L. (2010). Development of a quantitative metabolomic approach to study clinical human fecal water metabolome based on trimethylsilylation derivatization and GC/MS analysis. Analytical Chemistry, 82(15), 6447–6456. https://doi.org/10.1021/ac1006552. (PMID: 10.1021/ac100655220669995)
Gorzelak, M. A., Gill, S. K., Tasnim, N., Ahmadi-Vand, Z., Jay, M., & Gibson, D. L. (2015). Methods for improving human gut microbiome data by reducing variability through sample processing and storage of stool. PLoS ONE, 10(8), e0134802. https://doi.org/10.1371/journal.pone.0134802. (PMID: 10.1371/journal.pone.0134802262525194529225)
Gratton, J., Phetcharaburanin, J., Mullish, B. H., Williams, H. R. T., Thursz, M., Nicholson, J. K., Holmes, E., Marchesi, J. R., & Li, J. V. (2016). Optimized sample handling strategy for metabolic profiling of human feces. Analytical Chemistry, 88(9), 4661–4668. https://doi.org/10.1021/acs.analchem.5b04159. (PMID: 10.1021/acs.analchem.5b0415927065191)
Heaton, K. W., Radvan, J., Cripps, H., Mountford, R. A., Braddon, F. E., & Hughes, A. O. (1992). Defecation frequency and timing, and stool form in the general population: A prospective study. Gut, 33(6), 818–824. https://doi.org/10.1136/gut.33.6.818. (PMID: 10.1136/gut.33.6.81816241661379343)
Higgins Keppler, E. A., Jenkins, C. L., Davis, T. J., & Bean, H. D. (2018). Advances in the application of comprehensive two-dimensional gas chromatography in metabolomics. TrAC Trends in Analytical Chemistry, 109, 275–286. https://doi.org/10.1016/j.trac.2018.10.015. (PMID: 10.1016/j.trac.2018.10.015)
Karu, N., Deng, L., Slae, M., Guo, A. C., Sajed, T., Huynh, H., Wine, E., & Wishart, D. S. (2018). A review on human fecal metabolomics: Methods, applications and the human fecal metabolome database. Analytica Chimica Acta, 1030, 1–24. https://doi.org/10.1016/j.aca.2018.05.031. (PMID: 10.1016/j.aca.2018.05.03130032758)
Lewis, S. J., & Heaton, K. W. (1997). Stool form scale as a useful guide to intestinal transit time. The Scandinavian Journal of Gastroenterolog, 32(9), 920–924. https://doi.org/10.3109/00365529709011203. (PMID: 10.3109/00365529709011203)
Liang, Y., Dong, T., Chen, M., He, L., Wang, T., Liu, X., Chang, H., Mao, J.-H., Hang, B., Snijders, A. M., & Xia, Y. (2020). Systematic analysis of impact of sampling regions and storage methods on fecal gut microbiome and metabolome profiles. msphere, 5(1), 10–1128. https://doi.org/10.1128/mSphere.00763-19. (PMID: 10.1128/mSphere.00763-19)
Lim, M. Y., Park, Y.-S., Kim, J.-H., & Nam, Y.-D. (2020). Evaluation of fecal DNA extraction protocols for human gut microbiome studies. BMC Microbiology, 20(1), 212. https://doi.org/10.1186/s12866-020-01894-5. (PMID: 10.1186/s12866-020-01894-5326805727367376)
Moosmang, S., Pitscheider, M., Sturm, S., Seger, C., Tilg, H., Halabalaki, M., & Stuppner, H. (2019). Metabolomic analysis—addressing NMR and LC-MS related problems in human feces sample preparation. Clinica Chimica Acta, 489, 169–176. https://doi.org/10.1016/j.cca.2017.10.029. (PMID: 10.1016/j.cca.2017.10.029)
Nam, S. L., de la Mata, A. P., Dias, R. P., & Harynuk, J. J. (2020). Towards standardization of data normalization strategies to improve urinary metabolomics studies by GC×GC-TOFMS. Metabolites, 10(9), 376. https://doi.org/10.3390/metabo10090376. (PMID: 10.3390/metabo10090376329617797570207)
O’Sullivan, V., Madrid-Gambin, F., Alegra, T., Gibbons, H., & Brennan, L. (2018). Impact of sample storage on the NMR fecal water metabolome. ACS Omega, 3(12), 16585–16590. https://doi.org/10.1021/acsomega.8b01761. (PMID: 10.1021/acsomega.8b01761306138076312648)
Rose, C., Parker, A., Jefferson, B., & Cartmell, E. (2015). The characterization of feces and urine: A review of the literature to inform advanced treatment technology. Critical Reviews in Environmental Science and Technology, 45(17), 1827–1879. https://doi.org/10.1080/10643389.2014.1000761. (PMID: 10.1080/10643389.2014.1000761262467844500995)
Santiago, A., Panda, S., Mengels, G., Martinez, X., Azpiroz, F., Dore, J., Guarner, F., & Manichanh, C. (2014). Processing faecal samples: A step forward for standards in microbial community analysis. BMC Microbiology, 14(1), 112. https://doi.org/10.1186/1471-2180-14-112. (PMID: 10.1186/1471-2180-14-112248845244021188)
Singh, R. K., Chang, H.-W., Yan, D., Lee, K. M., Ucmak, D., Wong, K., Abrouk, M., Farahnik, B., Nakamura, M., Zhu, T. H., Bhutani, T., & Liao, W. (2017). Influence of diet on the gut microbiome and implications for human health. Journal of Translational Medicine, 15(1), 73. https://doi.org/10.1186/s12967-017-1175-y. (PMID: 10.1186/s12967-017-1175-y283889175385025)
Smith, L., Villaret-Cazadamont, J., Claus, S. P., Canlet, C., Guillou, H., Cabaton, N. J., & Ellero-Simatos, S. (2020). Important considerations for sample collection in metabolomics studies with a special focus on applications to liver functions. Metabolites, 10(3), 104. https://doi.org/10.3390/metabo10030104. (PMID: 10.3390/metabo10030104321783647142637)
Vernocchi, P., Del Chierico, F., & Putignani, L. (2020). Gut microbiota metabolism and interaction with food components. International Journal of Molecular Sciences, 21(10), 3688. https://doi.org/10.3390/ijms21103688. (PMID: 10.3390/ijms21103688324562577279363)
Vijay, A., & Valdes, A. M. (2022). Role of the gut microbiome in chronic diseases: A narrative review. European Journal of Clinical Nutrition, 76(4), 489–501. https://doi.org/10.1038/s41430-021-00991-6. (PMID: 10.1038/s41430-021-00991-634584224)
Wu, J., Wang, K., Wang, X., Pang, Y., & Jiang, C. (2021). The role of the gut microbiome and its metabolites in metabolic diseases. Protein & Cell, 12(5), 360–373. https://doi.org/10.1007/s13238-020-00814-7. (PMID: 10.1007/s13238-020-00814-7)
Wu, W.-K., Chen, C.-C., Panyod, S., Chen, R.-A., Wu, M.-S., Sheen, L.-Y., & Chang, S.-C. (2019). Optimization of fecal sample processing for microbiome study—The journey from bathroom to bench. Journal of the Formosan Medical Association, 118(2), 545–555. https://doi.org/10.1016/j.jfma.2018.02.005. (PMID: 10.1016/j.jfma.2018.02.00529490879)
Yang, Y., Yin, Y., Chen, X., Chen, C., Xia, Y., Qi, H., Baker, P. N., Zhang, H., & Han, T.-L. (2019). Evaluating different extraction solvents for GC-MS based metabolomic analysis of the fecal metabolome of adult and baby giant pandas. Science Reports, 9(1), 12017. https://doi.org/10.1038/s41598-019-48453-1. (PMID: 10.1038/s41598-019-48453-1)
Zhang, B., Brock, M., Arana, C., Dende, C., Hooper, L., & Raj, P. (2020). Impact of bead-beating intensity on microbiome recovery in mouse and human stool: Optimization of DNA extraction. biorxiv. https://doi.org/10.1101/2020.06.15.151753. (PMID: 10.1101/2020.06.15.151753333982877781331)
فهرسة مساهمة: Keywords: Bead-beating; Feces; GC × GC-TOFMS; Homogenization; Lyophilization; Metabolomics; Microbiome
المشرفين على المادة: 0 (Solvents)
تواريخ الأحداث: Date Created: 20230811 Date Completed: 20230814 Latest Revision: 20230821
رمز التحديث: 20240628
DOI: 10.1007/s11306-023-02036-4
PMID: 37566260
قاعدة البيانات: MEDLINE
الوصف
تدمد:1573-3890
DOI:10.1007/s11306-023-02036-4