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Analytical and Bioanalytical Chemistry

, Volume 411, Issue 1, pp 147–156 | Cite as

Nanoparticle microarray for high-throughput microbiome metabolomics using matrix-assisted laser desorption ionization mass spectrometry

  • Rebecca L. Hansen
  • Maria Emilia Dueñas
  • Torey Looft
  • Young Jin LeeEmail author
Paper in Forefront

Abstract

A high-throughput matrix-assisted laser desorption/ionization mass spectrometry (MALDI)-MS-based metabolomics platform was developed using a pre-fabricated microarray of nanoparticles and organic matrices. Selected organic matrices, inorganic nanoparticle (NP) suspensions, and sputter coated metal NPs, as well as various additives, were tested for metabolomics analysis of the turkey gut microbiome. Four NPs and one organic matrix were selected as the optimal matrix set: α-cyano-4-hydroycinnamic acid, Fe3O4 and Au NPs in positive ion mode with 10 mM sodium acetate, and Cu and Ag NPs in negative ion mode with no additive. Using this set of five matrices, over two thousand unique metabolite features were reproducibly detected across intestinal samples from turkeys fed a diet amended with therapeutic or sub-therapeutic antibiotics (200 g/ton or 50 g/ton bacitracin methylene disalicylate (BMD), respectively), or non-amended feed. Among the thousands of unique features, 56 of them were chemically identified using MALDI-MS/MS, with the help of in-parallel liquid chromatography (LC)-MS/MS analysis. Lastly, as a proof of concept application, this protocol was applied to 52 turkey cecal samples at three different time points from the antibiotic feed trial. Statistical analysis indicated variations in the metabolome of turkeys with different ages or treatments.

Graphical abstract

Keywords

Metabolomics MALDI Mass spectrometry Nanoparticles Turkey Microbiome High-throughput 

Notes

Funding information

This work was funded by the United States Department of Agriculture-National Institute of Food and Agriculture (USDA-NIFA).

Compliance with ethical standards

All animal experiments were performed at the National Animal Disease Center (NADC), USDA, Ames, IA, USA, following the ethical guidelines set by the Institutional Animal Care and Use Committee (IACUC) using the approved protocol ARS-2869.

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

216_2018_1436_MOESM1_ESM.pdf (686 kb)
ESM 1 (PDF 685 kb)

References

  1. 1.
    Dettmer K, Aronov PA, Hammock BD. Mass spectrometry-based metabolomics. Mass Spectrom Rev. 2007;26(1):51–78.  https://doi.org/10.1002/mas.20108.CrossRefPubMedPubMedCentralGoogle Scholar
  2. 2.
    Wikoff WR, Anfora AT, Liu J, Schultz PG, Lesley SA, Peters EC, et al. Metabolomics analysis reveals large effects of gut microflora on mammalian blood metabolites. Proc Natl Acad Sci U S A. 2009;106(10):3698–703.  https://doi.org/10.1073/pnas.0812874106.CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Aretz I, Meierhofer D. Advantages and pitfalls of mass spectrometry based metabolome profiling in systems biology. Int J Mol Sci. 2016;17(5).  https://doi.org/10.3390/ijms17050632.
  4. 4.
    Dunn WB, Erban A, Weber RJM, Creek DJ, Brown M, Breitling R, et al. Mass appeal: metabolite identification in mass spectrometry-focused untargeted metabolomics. Metabolomics. 2013;9(1):44–66.  https://doi.org/10.1007/s11306-012-0434-4.CrossRefGoogle Scholar
  5. 5.
    Fagerer SR, Nielsen S, Ibáñez A, Zenobi R. Matrix-assisted laser desorption/ionization matrices for negative mode metabolomics. Eur J Mass Spectrom. 2013;19(1):39–47.  https://doi.org/10.1255/ejms.1209.CrossRefGoogle Scholar
  6. 6.
    Wang J-N, Zhou Y, Zhu T-Y, Wang X, Guo Y-L. Prediction of acute cellular renal allograft rejection by urinary metabolomics using MALDI-FTMS. J Proteome Res. 2008;7(8):3597–601.  https://doi.org/10.1021/pr800092f.CrossRefPubMedGoogle Scholar
  7. 7.
    Korte AR, Stopka SA, Morris N, Razunguzwa T, Vertes A. Large-scale metabolite analysis of standards and human serum by laser desorption ionization mass spectrometry from silicon nanopost arrays. Anal Chem. 2016;88(18):8989–96.  https://doi.org/10.1021/acs.analchem.6b01186.CrossRefPubMedGoogle Scholar
  8. 8.
    Korte AR, Lee YJ. MALDI-MS analysis and imaging of small molecule metabolites with 1, 5-diaminonaphthalene (DAN). J Mass Spectrom. 2014;49(8):737–41.CrossRefGoogle Scholar
  9. 9.
    Shroff R, Svatoš A. Proton sponge: a novel and versatile MALDI matrix for the analysis of metabolites using mass spectrometry. Anal Chem. 2009;81(19):7954–9.  https://doi.org/10.1021/ac901048z.CrossRefPubMedGoogle Scholar
  10. 10.
    Lu M, Yang X, Yang Y, Qin P, Wu X, Cai Z. Nanomaterials as assisted matrix of laser desorption/ionization time-of-flight mass spectrometry for the analysis of small molecules. Nanomaterials. 2017;7(4):87.  https://doi.org/10.3390/nano7040087.CrossRefPubMedCentralGoogle Scholar
  11. 11.
    Chiang C-K, Chen W-T, Chang H-T. Nanoparticle-based mass spectrometry for the analysis of biomolecules. Chem Soc Rev. 2011;40(3):1269–81.  https://doi.org/10.1039/c0cs00050g.CrossRefPubMedGoogle Scholar
  12. 12.
    Yagnik GB, Hansen RL, Korte AR, Reichert MD, Vela J, Lee YJ. Large scale nanoparticle screening for small molecule analysis in laser desorption ionization mass spectrometry. Anal Chem. 2016;88(18):8926–30.  https://doi.org/10.1021/acs.analchem.6b02732.CrossRefPubMedGoogle Scholar
  13. 13.
    Kawasaki H, Ozawa T, Hisatomi H, Arakawa R. Platinum vapor deposition surface-assisted laser desorption/ionization for imaging mass spectrometry of small molecules. Rapid Commun Mass Spectrom. 2012;26(16):1849–58.  https://doi.org/10.1002/rcm.6301.CrossRefPubMedGoogle Scholar
  14. 14.
    Dufresne M, Thomas A, Breault-Turcot J, Masson J-F, Chaurand P. Silver-assisted laser desorption ionization for high spatial resolution imaging mass spectrometry of olefins from thin tissue sections. Anal Chem. 2013;85(6):3318–24.  https://doi.org/10.1021/ac3037415.CrossRefPubMedGoogle Scholar
  15. 15.
    Dufresne M, Masson J-F, Chaurand P. Sodium-doped gold-assisted laser desorption ionization for enhanced imaging mass spectrometry of triacylglycerols from thin tissue sections. Anal Chem. 2016;88(11):6018–25.  https://doi.org/10.1021/acs.analchem.6b01141.CrossRefPubMedGoogle Scholar
  16. 16.
    Medicine FaDACfV (2012) The judicious use of medically important antimicrobial drugs in food-producing animals. Author, Rockville, MD.Google Scholar
  17. 17.
    Hernandez E, Bargiela R, Diez MS, Friedrichs A, Perez-Cobas AE, Gosalbes MJ. Functional consequences of microbial shifts in the human gastrointestinal tract linked to antibiotic treatment and obesity. Gut Microbes. 2013;4.  https://doi.org/10.4161/gmic.25321.
  18. 18.
    Vernocchi P, Del Chierico F, Putignani L. Gut microbiota profiling: metabolomics based approach to unravel compounds affecting human health. Front Microbiol. 2016;7:1144.  https://doi.org/10.3389/fmicb.2016.01144.CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Yan S, Huang J, Chen Z, Jiang Z, Li X, Chen Z. Metabolomics in gut microbiota: applications and challenges. Sci Bull. 2016;61(15):1151–3.  https://doi.org/10.1007/s11434-016-1142-7.CrossRefGoogle Scholar
  20. 20.
    Robichaud G, Garrard KP, Barry JA, Muddiman DC. MSiReader: an open-source Interface to view and analyze high resolving power MS imaging files on Matlab platform. J Am Soc Mass Spectrom. 2013;24(5):718–21.  https://doi.org/10.1007/s13361-013-0607-z.CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Ruttkies C, Schymanski EL, Wolf S, Hollender J, Neumann S. MetFrag relaunched: incorporating strategies beyond in silico fragmentation. J Cheminform. 2016;8(1):3.  https://doi.org/10.1186/s13321-016-0115-9.CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Allen F, Pon A, Wilson M, Greiner R, Wishart D. CFM-ID: a web server for annotation, spectrum prediction and metabolite identification from tandem mass spectra. Nucleic Acids Res. 2014;42(W1):W94–9.  https://doi.org/10.1093/nar/gku436.CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    Yukihira D, Miura D, Saito K, Takahashi K, Wariishi H. MALDI−MS-based high-throughput metabolite analysis for intracellular metabolic dynamics. Anal Chem. 2010;82(10):4278–82.  https://doi.org/10.1021/ac100024w.CrossRefPubMedGoogle Scholar
  24. 24.
    Miura D, Fujimura Y, Tachibana H, Wariishi H. Highly sensitive matrix-assisted laser desorption ionization-mass spectrometry for high-throughput metabolic profiling. Anal Chem. 2010;82(2):498–504.  https://doi.org/10.1021/ac901083a.CrossRefPubMedGoogle Scholar
  25. 25.
    Zhang Y, Wang Y, Guo S, Guo Y, Liu H, Li Z. Ammonia-treated N-(1-naphthyl) ethylenediamine dihydrochloride as a novel matrix for rapid quantitative and qualitative determination of serum free fatty acids by matrix-assisted laser desorption/ionization-Fourier transform ion cyclotron resonance mass spectrometry. Anal Chim Acta. 2013;794:82–9.  https://doi.org/10.1016/j.aca.2013.07.060.CrossRefPubMedGoogle Scholar
  26. 26.
    Chong J, Soufan O, Li C, Caraus I, Li S, Bourque G, et al. MetaboAnalyst 4.0: towards more transparent and integrative metabolomics analysis. Nucleic Acids Res. 2018; gky310-gky310.Google Scholar
  27. 27.
    Lu J, Idris U, Harmon B, Hofacre C, Maurer JJ, Lee MD. Diversity and succession of the intestinal bacterial Community of the Maturing Broiler Chicken. Appl Environ Microbiol. 2003;69(11):6816–24.  https://doi.org/10.1128/AEM.69.11.6816-6824.2003.CrossRefPubMedPubMedCentralGoogle Scholar
  28. 28.
    Scupham AJ. Succession in the intestinal microbiota of preadolescent turkeys. FEMS Microbiol Ecol. 2007;60(1):136–47.  https://doi.org/10.1111/j.1574-6941.2006.00245.x.CrossRefPubMedGoogle Scholar
  29. 29.
    Cheung Lam AH, Sandoval N, Wadhwa R, Gilkes J, Do TQ, Ernst W, et al. Assessment of free fatty acids and cholesteryl esters delivered in liposomes as novel class of antibiotic. BMC Res Notes. 2016;9(1):337.  https://doi.org/10.1186/s13104-016-2138-8.CrossRefPubMedPubMedCentralGoogle Scholar
  30. 30.
    Zheng CJ, Yoo J-S, Lee T-G, Cho H-Y, Kim Y-H, Kim W-G. Fatty acid synthesis is a target for antibacterial activity of unsaturated fatty acids. FEBS Lett. 2005;579(23):5157–62.  https://doi.org/10.1016/j.febslet.2005.08.028.CrossRefPubMedGoogle Scholar
  31. 31.
    Crompton MJ, Dunstan RH, Macdonald MM, Gottfries J, von Eiff C, Roberts TK. Small changes in environmental parameters Lead to alterations in antibiotic resistance, cell morphology and membrane fatty acid composition in Staphylococcus lugdunensis. PLoS One. 2014;9(4):e92296.CrossRefGoogle Scholar
  32. 32.
    Defez R, Esposito R, Angelini C, Bianco C. Overproduction of indole-3-acetic acid in free-living rhizobia induces transcriptional changes resembling those occurring in nodule Bacteroids. Mol Plant-Microbe Interact. 2016;29(6):484–95.  https://doi.org/10.1094/MPMI-01-16-0010-R.CrossRefPubMedGoogle Scholar
  33. 33.
    Matilla MA, Daddaoua A, Chini A, Morel B, Krell T. An auxin controls bacterial antibiotics production. Nucleic Acids Res. 2018; gky766-gky766.Google Scholar
  34. 34.
    Bianco C, Imperlini E, Calogero R, Senatore B, Pucci P, Defez R. Indole-3-acetic acid regulates the central metabolic pathways in Escherichia coli. Microbiology. 2006;152(8):2421–31.CrossRefGoogle Scholar
  35. 35.
    Zelante T, Iannitti Rossana G, Cunha C, De Luca A, Giovannini G, Pieraccini G, et al. Tryptophan catabolites from microbiota engage aryl hydrocarbon receptor and balance mucosal reactivity via Interleukin-22. Immunity. 2013;39(2):372–85.  https://doi.org/10.1016/j.immuni.2013.08.003.CrossRefPubMedGoogle Scholar
  36. 36.
    Taub FE, DeLeo JM, Thompson EB. Sequential comparative hybridizations analyzed by computerized image processing can identify and quantitate regulated RNAs. DNA. 1983;2(4):309–27.  https://doi.org/10.1089/dna.1983.2.309.CrossRefPubMedGoogle Scholar
  37. 37.
    Pollack JR, Perou CM, Alizadeh AA, Eisen MB, Pergamenschikov A, Williams CF, et al. Genome-wide analysis of DNA copy-number changes using cDNA microarrays. Nat Genet. 1999;23:41.CrossRefGoogle Scholar
  38. 38.
    Schäferling M. Methods in molecular biology Vol. 671: Biological microarrays: methods and protocols. Edited by Ali Khademhosseini, Kahp-Yang Suh and Mohammed Zourob. ChemBioChem. 2011;12(10):1602–3.  https://doi.org/10.1002/cbic.201100279.CrossRefGoogle Scholar
  39. 39.
    Hutchens TW, Yip T-T. New desorption strategies for the mass spectrometric analysis of macromolecules. Rapid Commun Mass Spectrom. 1993;7(7):576–80.  https://doi.org/10.1002/rcm.1290070703.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Rebecca L. Hansen
    • 1
  • Maria Emilia Dueñas
    • 1
  • Torey Looft
    • 2
  • Young Jin Lee
    • 1
    Email author
  1. 1.Department of ChemistryIowa State UniversityAmesUSA
  2. 2.United States Department of AgricultureNational Animal Disease CenterAmesUSA

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