Abstract
Introduction
Intestinal microbiota and metabolites play important roles for further improvement of animal production. Metabolomics of shrimp intestine to understand roles and their relationship to the host is hampered by the lack of metabolome profiling method.
Objectives
This study aims to develop extraction and analytical methods to allow accurate metabolic analysis in shrimp intestine.
Methods
Conditions for extraction and LC-HRMS/MS analysis were optimized.
Results
Extraction with ethyl acetate:acetone (15:2 v/v) acidified with 0.5% acetic acid, elution with acetonitrile:water acidified with 0.01% acetic acid for 25 min, and mass fragmentation at 15% HCD were the optimal conditions, yielding the highest signal intensity and numbers of putative metabolites.
Conclusion
Our method enabled in-depth study for shrimp-microbial interaction at metabolite level.
References
Deda, O., Chatziioannou, A. C., Fasoula, S., Palachanis, D., Raikos, Ν, Theodoridis, G. A., et al. (2017). Sample preparation optimization in fecal metabolic profiling. Journal of Chromatography B, 1047, 115–123. https://doi.org/10.1016/j.jchromb.2016.06.047.
FAO. (2018). The state of world fisheries and aquaculture 2018—Meeting the sustainable development goals. Rome, Licence: CC BY-NC-SA 3.0 IGO.
Guo, A. C., Jewison, T., Wilson, M., Liu, Y., Knox, C., Djoumbou, Y., et al. (2013). ECMDB: The E. coli metabolome database. Nucleic Acids Research, 41, D625–D630. https://doi.org/10.1093/nar/gks992.
Hanning, I., & Diaz-Sanchez, S. (2015). The functionality of the gastrointestinal microbiome in non-human animals. Microbiome, 3, 51. https://doi.org/10.1186/s40168-015-0113-6.
Huttenhower, C., Gevers, D., Knight, R., Abubucker, S., Badger, J. H., Chinwalla, A. T., et al. (2012). Structure, function and diversity of the healthy human microbiome. Nature, 486, 207–214. https://doi.org/10.1038/nature11234.
Kanehisa, M., & Goto, S. (2000). KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Research, 28, 27–30. https://doi.org/10.1093/nar/28.1.27.
Karasov, W. H., & Douglas, A. E. (2013). Comparative digestive physiology. Comprehensive Physiology, 3, 741–783. https://doi.org/10.1002/cphy.c110054.
Levy, M., Thaiss, C. A., & Elinav, E. (2016). Metabolites: Messengers between the microbiota and the immune system. Genes & Development, 30, 1589–1597. https://doi.org/10.1101/gad.284091.116.
Masson, P., Alves, A. C., Ebbels, T. M. D., Nicholson, J. K., & Want, E. J. (2010). Optimization and evaluation of metabolite extraction protocols for untargeted metabolic profiling of liver samples by UPLC-MS. Analytical Chemistry, 82, 7779–7786. https://doi.org/10.1021/ac101722e.
Mongkol, P., Bunphimpapha, P., Rungrassamee, W., Arayamethakorn, S., Klinbunga, S., Menasveta, P., et al. (2018). Bacterial community composition and distribution in different segments of the gastrointestinal tract of wild-caught adult Penaeus monodon. Aquaculture Research, 49, 378–392. https://doi.org/10.1111/are.13468.
Pence, H. E., & Williams, A. (2010). ChemSpider: An online chemical information resource. Journal of Chemical Education, 87, 1123–1124. https://doi.org/10.1021/ed100697w.
Rhoades, S. D., & Weljie, A. M. (2016). Comprehensive optimization of LC-MS metabolomics methods using design of experiments (COLMeD). Metabolomics: Official Journal of the Metabolomic Society. https://doi.org/10.1007/s11306-016-1132-4.
Römisch-Margl, W., Prehn, C., Bogumil, R., Röhring, C., Suhre, K., & Adamski, J. (2012). Procedure for tissue sample preparation and metabolite extraction for high-throughput targeted metabolomics. Metabolomics, 8, 133–142. https://doi.org/10.1007/s11306-011-0293-4.
Rungrassamee, W., Klanchui, A., Maibunkaew, S., Chaiyapechara, S., Jiravanichpaisal, P., & Karoonuthaisiri, N. (2014). Characterization of intestinal bacteria in wild and domesticated adult black tiger shrimp (Penaeus monodon). PLoS ONE, 9, e91853. https://doi.org/10.1371/journal.pone.0091853.
Schock, T. B., Duke, J., Goodson, A., Weldon, D., Brunson, J., Leffler, J. W., et al. (2013). Evaluation of Pacific white shrimp (Litopenaeus vannamei) health during a superintensive aquaculture growout using NMR-based metabolomics. PLoS ONE, 8, e59521–e59521. https://doi.org/10.1371/journal.pone.0059521.
Stentiford, G. D., Neil, D. M., Peeler, E. J., Shields, J. D., Small, H. J., Flegel, T. W., et al. (2012). Disease will limit future food supply from the global crustacean fishery and aquaculture sectors. Journal of Invertebrate Pathology, 110, 141–157. https://doi.org/10.1016/j.jip.2012.03.013.
Sumner, L. W., Amberg, A., Barrett, D., Beale, M. H., Beger, R., Daykin, C. A., et al. (2007). Proposed minimum reporting standards for chemical analysis Chemical Analysis Working Group (CAWG) metabolomics standards initiative (MSI). Metabolomics, 3, 211–221. https://doi.org/10.1007/s11306-007-0082-2.
Thaiss, C. A., Zmora, N., Levy, M., & Elinav, E. (2016). The microbiome and innate immunity. Nature, 535, 65–74. https://doi.org/10.1038/nature18847.
Wishart, D. S., Tzur, D., Knox, C., Eisner, R., Guo, A. C., Young, N., et al. (2007). HMDB: The human metabolome database. Nucleic Acids Research, 35, D521–D526. https://doi.org/10.1093/nar/gkl923.
Yoshii, K., Hosomi, K., Sawane, K., & Kunisawa, J. (2019). Metabolism of dietary and microbial vitamin B family in the regulation of host immunity. Frontiers in Nutrition. https://doi.org/10.3389/fnut.2019.00048.
Zhu, N., Wang, J., Yu, L., Zhang, Q., Chen, K., & Liu, B. (2019). Modulation of growth performance and intestinal microbiota in chickens fed plant extracts or virginiamycin. Frontiers in Microbiology. https://doi.org/10.3389/fmicb.2019.01333.
Acknowledgements
We thank Dr. Sage Chaiyapechara and staffs at Aquaculture Service Development Research Team, BIOTEC, Thailand for their assistance with black tiger shrimp sample collection in this study. This work was financially supported by the National Center for Genetic Engineering and Biotechnology (Thailand) (P-16-52214), International Foundation for Science under the collaborative research Grant agreement No J-3-B-6003-1 and the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant agreement No 734486 (SAFE-Aqua). We are grateful to Dr. Nitsara Karoonuthaisiri for her mentorship and advice on this manuscript and we thank Dr. Tanaporn Uengwetwanit for her assistance with manuscript preparation.
Author information
Authors and Affiliations
Contributions
WR and UU conceived and designed research. SA collected shrimp intestine samples. UU, PJ and SP conducted experiment, analytical tools and data analysis. UU, SP and WR wrote the manuscript. All authors read and approved the manuscript.
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interests.
Research involving animal rights
All applicable international, national, and/or institutional guidelines for the care and use of animals were followed.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
Below is the link to the electronic supplementary material.
Supplementary material 1 (TIF 1002 kb)
Supplementary Figure 1. Optimization of extraction solvents. Comparison of (A) base peak chromatogram obtained from negative ESI mode, (B) from positive ESI mode, (C) a number of peaks, (D) a number of putative metabolites and (E) compound class of six different extraction solvents.
Supplementary material 2 (TIF 526 kb)
Supplementary Figure 2. Optimization of acidity in mobile phase system. Comparison of (A) base peak chromatograms obtained from negative ESI mode, (B) from positive ESI mode, (C) a number of peaks and (D) a number of putative metabolites of four different acidities in mobile phase system.
Supplementary material 3 (TIF 294 kb)
Supplementary Figure 3. Comparison of three different gradient patterns for elution system. (A) Base peak chromatograms obtained from negative ESI mode, (B) a number of peaks and (C) a number of putative metabolites were shown in each bar graph.
Supplementary material 4 (TIF 278 kb)
Supplementary Figure 4. Optimization of four different higher-energy collisional dissociation (HCD) energy. (A) Base peak chromatograms obtained from negative ESI mode, (B) from positive ESI mode, (C) a number of peak and (D) a number of putative metabolites.
Supplementary material 5 (TIF 1570 kb)
Supplementary Figure 5. Comparison of full scan parameters (i.e., AGC target and intensity threshold) for mass acquisitions. (A) Base peak chromatograms obtained from positive ESI mode, (B) a number of peak and (C) a number of putative metabolites of three different full scan parameter conditions.
Supplementary material 6 (TIF 790 kb)
Supplementary Figure 6. Base peak chromatograms of shrimp intestine extracts (six replicates) obtained from positive ESI mode at retention time (A) 2-23 min, (C) 12-16 min and (E) 16-20 min, and negative mode at retention time (B) 2-23 min, (D) 8-12 min and (F) 20-24 min.
Supplementary material 7 (TIF 690 kb)
Supplementary Figure S7. Metabolite identification using authentic standards namely, (A) phenylalanine in positive mode, (B) phenylalanine in negative mode, (C) tryptophan in positive mode and (D) tryptophan in negative mode.
Supplementary material 8 (XLSX 10 kb)
Supplementary Table 1. Three different gradient elution system used for optimization in this study.
Supplementary material 9 (XLSX 99 kb)
Supplementary Table 2. Metabolite profiles of shrimp intestines (validation set) in both positive and negative ESI modes.
Rights and permissions
About this article
Cite this article
Uawisetwathana, U., Plaisen, S., Arayamethakorn, S. et al. Optimization of metabolite extraction and analytical methods from shrimp intestine for metabolomics profile analysis using LC-HRMS/MS. Metabolomics 17, 8 (2021). https://doi.org/10.1007/s11306-020-01768-x
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s11306-020-01768-x