Journal
ANALYTICAL CHEMISTRY
Volume 87, Issue 5, Pages 2527-2534Publisher
AMER CHEMICAL SOC
DOI: 10.1021/ac5046752
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Funding
- European Research Council [210356, 185677]
- European Commission [3054940]
- Biotechnology and Biological Sciences Research Council (BBSRC) [BB/L020858/1]
- BBSRC [BB/L020858/1] Funding Source: UKRI
- European Research Council (ERC) [210356] Funding Source: European Research Council (ERC)
- Academy of Medical Sciences (AMS) [AMS-SGCL8-Kinross] Funding Source: researchfish
- Biotechnology and Biological Sciences Research Council [BB/L020858/1] Funding Source: researchfish
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Rapid evaporative ionization mass spectrometry (REIMS) technology allows real time intraoperative tissue classification and the characterization and identification of microorganisms. In order to create spectral libraries for training the classification models, reference data need to be acquired in large quantities as classification accuracy generally improves as a function of number of training samples. In this study, we present an automated high-throughput method for collecting REIMS data from heterogeneous organic tissue. The underlying instrumentation consists of a 2D stage with an additional high-precision z-axis actuator that is equipped with an electrosurgical diathermy-based sampling probe. The approach was validated using samples of human liver with metastases and bacterial strains, cultured on solid medium, belonging to the species P. aeruginosa, B. subtilis, and S. aureus. For both sample types, spatially resolved spectral information was obtained that resulted in clearly distinguishable multivariate clustering between the healthy/cancerous liver tissues and between the bacterial species.
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