Integrated Raman spectroscopy and mass spectrometry for heterospectral tissue imaging

Student thesis: Doctoral ThesisDoctor of Philosophy

Abstract

Many diseases are characterised by changes in molecular composition. For instance, lipids are essential molecules in cells that have important roles in structure, function, and biological pathways regulation. However, current optical techniques cannot directly analyse the complex lipidome in tissues, limiting our understanding of lipid involvement in health and disease. This thesis investigates the capability of vibrational Raman Spectroscopy to identify individual lipids in complex tissue matrices, by combining Raman Spectroscopy with desorption electrospray ionisation (DESI) - mass spectrometry imaging in an integrated instrument. To complement the molecular analysis for in situ measurements of bulk tissues, the thesis also explore a polarised Raman needle probe for rapid bulk structural and molecular tissue analysis. The first technique combines Raman Spectroscopy and DESI-mass spectrometry imaging to enable Raman spectroscopic identification of specific tissue lipids. A custom-developed computational pipeline was used to extract lipidomic information from optical vibrational spectra, enabling the identification of different lipid classes and species. This is demonstrated in transient cerebral ischemia-reperfusion injury in a murine model of ischemic stroke. Furthermore, I deployed the approach in a handheld fibre-optic Raman probe and demonstrated real-time classification of bulk brain tissues based on specific lipid abundances. To complement the technique for structural analysis, I developed a polarised Raman needle probe to characterise biomolecules, providing both chemical and structural information relevant to biomedical research and diseases where tissues show disorganisation. This thesis contributes to the development of a new type of biomedical Raman Spectroscopy that enable real-time lipidomics using Raman scattered light. The polarised Raman system provides enhanced chemical and structural information, addressing the need for alternative techniques to capture biochemical structure involvement in health and disease.
Date of Award1 May 2024
Original languageEnglish
Awarding Institution
  • King's College London
SupervisorMads Bergholt (Supervisor), Tom Vercauteren (Supervisor) & Vincenzo Abbate (Supervisor)

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