Award details

Development of a nanoscale, near-infrared spectroscopy imaging tool for in situ, rapid and label-free analysis of single extracellular vesicles

Reference	BB/X004449/1
Principal Investigator / Supervisor	Dr Wayne Nishio Ayre
Co-Investigators / Co-Supervisors	Professor Aled Clayton, Professor Philip Davies, Dr Bo Hou
Institution	Cardiff University
Department	Dentistry
Funding type	Research
Value (£)	186,993
Status	Current
Type	Research Grant
Start date	01/04/2023
End date	31/03/2024
Duration	12 months

Abstract

EVs are nanosized, cell-derived, lipid vesicles containing proteins, nucleic acids and metabolites that act in local and distant cell communication. They are vital in maintaining homeostasis but are also implicated in pathogenesis; from tropical infections (malaria) through to diseases afflicting ageing populations (cardiovascular disease, cancer). In addition to their utility as disease markers, there are also prospects for their use as medicinal agents. A major piece of the puzzle is missing however, as the heterogeneity of EVs is often overlooked and there is a limited sense of how pathophysiological factors impact this. Technology with sufficient spatial resolution and high throughput to enable in-depth, single vesicle analysis would provide a step-change towards understanding the biological functions of EV populations. Photo-induced Force Microscopy (PiFM) is a powerful technique that enables rapid direct IR-based chemical mapping as a function of phonon energies whilst simultaneously recording topography at <10 nm spatial resolution. Although PiFM can characterise materials in air, aqueous measurements have not been possible as the environmental phonon distribution caused by water molecule vibrations creates high background noise. To realise in situ single EV analysis, a new sensing technology using surface-enhanced infrared absorption and machine learning approaches will be developed. Using world-leading photo/electron lithography facilities, single EVs will be captured and near-IR vibrations will be sensed through micro/nano-fabricated metal strips functionalised with molecular linkers and topological photonics patterns to obtain high spatial and wavelength resolution in aqueous buffers. The background noise will be further suppressed using image processing and machine learning pattern recognition. Proof-of-concept will be demonstrated with artificial lipid vesicles and the technology will be benchmarked against existing techniques using cell-derived EVs.

Summary

Cells release small spheres, known as extracellular vesicles (EVs), which are approximately 1000 times smaller than the width of a human hair (nanoscale). Recent research has shown that these EVs contain a cargo of signalling molecules that can act to either maintain health (e.g. blood vessel formation, immune response) or encourage disease progression (e.g. cancer, Parkinson's disease). As a result, the biological role and therapeutic potential of EVs has gained significant interest. Moreover, the discovery that EVs are present in circulating blood and elevated in certain diseases has also increased their potential use in diagnostics. A major limitation to the evolution of this field of research however has been the limited techniques available to easily analyse EVs. Many of the research techniques to study EVs require specialist equipment and training as well as significant time, sample processing and labelling, which may induce artefacts or bias results. Due to the low abundance of EVs and their contents, many existing techniques also pool thousands to millions of EVs for single analysis, assuming a homogenous population, when in fact studies have shown from a single cell type, several different sub-populations of EVs are present. To truly understand the biological role of EVs in health and disease and their therapeutic and diagnostic potential, a closer look at the heterogeneity of single EVs is needed in a manner that is both high-throughput and label-free whilst simultaneously maintaining EVs in their natural state. IR spectroscopy may offer a solution to this problem. It is based on the fact that molecules vibrate at specific frequencies due to the stretching and bending of the chemical bonds between atoms. When a chemical bond is exposed to an infrared light at the same frequency as it vibrates, the bond will absorb the energy. Although this technique has provided scientists with the ability to study chemical bonds in great detail, only recently has the technology advanced to the point where it can be applied to samples at a nanoscale. This cutting-edge approach, known as photo-induced force microscopy (PiFM), uses an extremely fine tip to measure the vibrational energy of molecules whilst they are excited by infrared light. Such an approach allows the chemical composition and topography of dry samples to be characterised at a nanoscale. However infrared light is highly prone to absorption in water and the movement of EVs due to their surface charge (Brownian motion) would make locating EVs in liquids using PiFM extremely challenging as well as prone to high levels of background noise. These technical challenges will be overcome in this project using two novel approaches. Firstly, IR light with a shorter wavelength, known as near-IR, will be used as it is less affected by water. Secondly, devices with unique surface features and different materials will be manufactured that can amplify the near-IR signal in water. These surfaces will also be chemically functionalised to capture the EVs for easy localisation and analysis with the PiFM. Analysing near-IR absorption is a complex task as this region of the IR spectrum consists of signals arising from combinations of chemical group vibrations as well as overtones (multiples of chemical vibrations). The project will therefore require a simplified model of EVs (empty vesicles composed of lipids, also known as liposomes) and advanced computational techniques (i.e. machine learning) to develop a database of near-IR chemical signals. Once the technology is optimised and refined, it will be validated and tested using cell derived EVs. This project will therefore develop a label-free, non-invasive, rapid technology to analyse the size and chemical composition of EVs in their natural state at a single vesicle level, providing information on the heterogeneity of EV populations and helping discover potential future therapeutic and diagnostic markers.

Committee	Not funded via Committee
Research Topics	X – not assigned to a current Research Topic
Research Priority	X – Research Priority information not available
Research Initiative	UKRI Basic Technologies [2022]
Funding Scheme	X – not Funded via a specific Funding Scheme

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