Skip to main content
SpringerLink
Log in

Application of chemometric methods to the analysis of multimodal chemical images of biological tissues

  • Research Paper
  • Published:
Analytical and Bioanalytical Chemistry Aims and scope Submit manuscript

Abstract

Current histology techniques, such as tissue staining or histochemistry protocols, provide very limited chemical information about the tissues. Chemical imaging technologies such as infrared, Raman, and mass spectrometry imaging, are powerful analytical techniques with a huge potential in describing the chemical composition of sample surfaces. In this work, three images of the same tissue slice using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry, infrared microspectroscopy, and an RGB picture from a conventional hematoxylin/eosin (H/E) staining are simultaneously analyzed. These fused images were analyzed by multivariate curve resolution-alternating least squares (MCR-ALS), which provided, for each component, its distribution within the tissue surface, its IR spectrum fingerprint, its characteristic mass values, and the contribution of the RGB channels of the H/E staining. Compared with the individual analysis of each of the images alone, the fusion of the three images showed the relationship between the different types of chemical/biological information and enabled a better interpretation of the tissue under study. In addition, the least-squares projection of the MCR-ALS resolved spectra of components at low spatial resolution onto the IR and RBG images at high spatial resolution, provided a better delimitation of the sample constituents on the image, giving a more precise description of their distribution on the investigated tissue. The application of this procedure can be of interest in different research areas in which a good description of the spatial distribution of the chemical constituents of the samples is needed, such as in biomedicine, food, or environmental research.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Underwood JCE. More than meets the eye: the changing face of histopathology. Histopathology. 2017;70:4–9. https://doi.org/10.1111/his.13047.

    Article  PubMed  Google Scholar 

  2. Feldman AT, Wolfe D. Tissue processing and hematoxylin and eosin staining. Methods Mol Biol. 2014;1180:31–43. https://doi.org/10.1007/978-1-4939-1050-2_3.

    Article  CAS  PubMed  Google Scholar 

  3. Meguro R, Asano Y, Odagiri S, Li C, Iwatsuki H, Shoumura K. Nonheme-iron histochemistry for light and electron microscopy: a historical, theoretical and technical review. Arch Histol Cytol. 2007;70:1–19. https://doi.org/10.1679/aohc.70.1.

    Article  CAS  PubMed  Google Scholar 

  4. Meloan SN, Puchtler H. Chemical mechanisms of staining methods: Von Kossa’s technique: what von Kossa really wrote and a modified reaction for selective demonstration of inorganic phosphates. J Histotechnol. 1985;8:11–3. https://doi.org/10.1179/his.1985.8.1.11.

    Article  Google Scholar 

  5. Ramos-Vara JA. Principles and methods of immunohistochemistry, in: methods Mol. Biol., Humana Press Inc.; 2017, pp. 115–128. https://doi.org/10.1007/978-1-4939-7172-5_5.

  6. Beesley J. Histopathology: advances in research and techniques. Immunotherapy. 2011;3:825–8.

    Article  Google Scholar 

  7. Bunaciu AA, Hoang VD, Aboul-Enein HY. Vibrational micro-spectroscopy of human tissues analysis: review. Crit Rev Anal Chem. 2017;47:194–203. https://doi.org/10.1080/10408347.2016.1253454.

    Article  CAS  PubMed  Google Scholar 

  8. Pahlow S, Weber K, Popp J, Wood BR, Kochan K, Rüther A, et al. Application of vibrational spectroscopy and imaging to point-of-care medicine: a review. Appl Spectrosc. 2018;72:52–84. https://doi.org/10.1177/0003702818791939.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Lyng FM, Ramos IRM, Ibrahim O, Byrne HJ. Vibrational microspectroscopy for cancer screening. Appl Sci. 2015;5:23–35. https://doi.org/10.3390/app5010023.

    Article  Google Scholar 

  10. Harrison JP, Berry D. Vibrational spectroscopy for imaging single microbial cells in complex biological samples. Front Microbiol. 2017;8. https://doi.org/10.3389/fmicb.2017.00675.

  11. Türker-Kaya S, Huck CW. A review of mid-infrared and near-infrared imaging: principles, concepts and applications in plant tissue analysis. Molecules. 2017;22. https://doi.org/10.3390/molecules22010168.

  12. Fu X, Ying Y. Food safety evaluation based on near infrared spectroscopy and imaging: a review. Crit Rev Food Sci Nutr. 2016;56:1913–24. https://doi.org/10.1080/10408398.2013.807418.

    Article  CAS  PubMed  Google Scholar 

  13. Buchberger AR, DeLaney K, Johnson J, Li L. Mass spectrometry imaging: a review of emerging advancements and future insights. Anal Chem. 2018;90:240–65. https://doi.org/10.1021/acs.analchem.7b04733.

    Article  CAS  PubMed  Google Scholar 

  14. Norris JL, Caprioli RM. Imaging mass spectrometry: a new tool for pathology in a molecular age. Proteomics Clin Appl. 2013;7:733–8. https://doi.org/10.1002/prca.201300055.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Nilsson A, Goodwin RJA, Shariatgorji M, Vallianatou T, Webborn PJH, Andrén PE. Mass spectrometry imaging in drug development. Anal Chem. 2015;87:1437–55. https://doi.org/10.1021/ac504734s.

    Article  CAS  PubMed  Google Scholar 

  16. Tauler R. Multivariate curve resolution applied to second order data. Chemom Intell Lab Syst. 1995;30:133–46. https://doi.org/10.1016/0169-7439(95)00047-X.

    Article  CAS  Google Scholar 

  17. Bedia C, Tauler R, Jaumot J. Compression strategies for the chemometric analysis of mass spectrometry imaging data. J Chemom. 2016;30. https://doi.org/10.1002/cem.2821.

  18. Bedia C, Tauler R, Jaumot J. Analysis of multiple mass spectrometry images from different Phaseolus vulgaris samples by multivariate curve resolution. Talanta. 2017;175:557–65. https://doi.org/10.1016/j.talanta.2017.07.087.

    Article  CAS  PubMed  Google Scholar 

  19. Olmos V, Benítez L, Marro M, Loza-Alvarez P, Piña B, Tauler R, et al. Relevant aspects of unmixing/resolution analysis for the interpretation of biological vibrational hyperspectral images. TrAC - Trends Anal Chem. 2017;94:130–40. https://doi.org/10.1016/j.trac.2017.07.004.

    Article  CAS  Google Scholar 

  20. Piqueras S, Bedia C, Beleites C, Krafft C, Popp J, Maeder M, et al. Handling different spatial resolutions in image fusion by multivariate curve resolution-alternating least squares for incomplete image multisets. Anal Chem. 2018. https://doi.org/10.1021/acs.analchem.8b00630.

  21. Neumann EK, Comi TJ, Spegazzini N, Mitchell JW, Rubakhin SS, Gillette MU, et al. Multimodal chemical analysis of the brain by high mass resolution mass spectrometry and infrared spectroscopic imaging. Anal Chem. 2018;90:11572–80. https://doi.org/10.1021/acs.analchem.8b02913.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Martínez-Aranda A, Hernández V, Guney E, Muixí L, Foj R, Baixeras N, et al. FN14 and GRP94 expression are prognostic/predictive biomarkers of brain metastasis outcome that open up new therapeutic strategies. Oncotarget. 2015;6:44254–73. https://doi.org/10.18632/oncotarget.5471.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Eilers PHC. A perfect smoother. Analytical Chemistry. 2003;75 p3631–6. https://doi.org/10.1021/ac034173t.

  24. Gorrochategui E, Jaumot J, Tauler R. ROIMCR: a powerful analysis strategy for LC-MS metabolomic datasets. BMC Bioinformatics. 2019;20:256. https://doi.org/10.1186/s12859-019-2848-8.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Bedia C, Tauler R, Jaumot J. Compression strategies for the chemometric analysis of mass spectrometry imaging data. J Chemom. 2016;30:575–88. https://doi.org/10.1002/cem.2821.

    Article  CAS  Google Scholar 

  26. Dieterle F, Ross A, Schlotterbeck G, Senn H. Probabilistic quotient normalization as robust method to account for dilution of complex biological mixtures. Application in1H NMR metabonomics. Anal Chem. 2006;78:4281–90. https://doi.org/10.1021/ac051632c.

    Article  CAS  PubMed  Google Scholar 

  27. Jaumot J, de Juan A, Tauler R. MCR-ALS GUI 2.0: new features and applications. Chemom Intell Lab Syst. 2015;140:1–12. https://doi.org/10.1016/J.CHEMOLAB.2014.10.003.

    Article  CAS  Google Scholar 

  28. Zemski Berry KA, Hankin JA, Barkley RM, Spraggins JM, Caprioli RM, Murphy RC. MALDI Imaging of Lipid Biochemistry in Tissues by Mass Spectrometry. n.d.. https://doi.org/10.1021/cr200280p.

  29. Lipidmaps. (n.d.) lipidmaps.org.

  30. Larkin PJ. Infrared and raman spectroscopy : principles and spectral interpretation. Elsevier; 2011.

  31. de Juan A, Tauler R. Data fusion by multivariate curve resolution, in: data Handl. Sci Technol, Elsevier Ltd. 2019;205–233. https://doi.org/10.1016/B978-0-444-63984-4.00008-9.

  32. Piqueras S, Duponchel L, Tauler R, De Juan A. Resolution and segmentation of hyperspectral biomedical images by multivariate curve resolution-alternating least squares. Anal Chim Acta. 2011;705:182–92. https://doi.org/10.1016/j.aca.2011.05.020.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

This work was supported by Generalitat de Catalunya (Suport a les activitats de Grups de Recerca, 2017 SGR 753), Spanish Ministry of Science and Innovation (Project CEX2018-000794-S), and FIS-PI14/00336 - FIS-PI18/00916 Grants, from the I+D+I National Plan, with the financial support from ISCIII-Subdirección General de Evaluación and the Fondo Europeo de Desarrollo Regional (FEDER).

Author information

Authors and Affiliations

  1. Institute of Environmental Assessment and Water Research (IDAEA-CSIC), 08034, Barcelona, Spain

    Carmen Bedia & Romà Tauler

  2. Department of Experimental and Health Sciences, Universitat Pompeu Fabra, 08003, Barcelona, Spain

    Àngels Sierra

Authors
  1. Carmen Bedia
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Àngels Sierra
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Romà Tauler
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Carmen Bedia.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Published in the topical collection Euroanalysis XX with guest editor Sibel A. Ozkan.

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

ESM 1

(PDF 812 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bedia, C., Sierra, À. & Tauler, R. Application of chemometric methods to the analysis of multimodal chemical images of biological tissues. Anal Bioanal Chem 412, 5179–5190 (2020). https://doi.org/10.1007/s00216-020-02595-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00216-020-02595-8

Keywords

Search

Navigation