Andrew Williams reports on Raman spectroscopy methods for health applications
In recent months, several universities and research organisations have made important breakthroughs in the use of Raman spectroscopy (RS) methods for health applications.
So, what did the research entail? And how exactly was RS technology applied in each case?
Mapping human cartilage
One of the most interesting recent initiatives is an Imperial College London project that is using RS to accurately map human cartilage and compare it to engineered cartilage at various stages while it is being grown in the laboratory.
As Mads Sylvest Bergholt, Research Fellow at Imperial College London, explains, RS is a vital tool in the work because it essentially provides a chemical 'fingerprint' of the composition of a sample, as well as some information on the organisation of specific components such as collagen fibre orientation, in the form of a spectrum.
"We can scan a tissue and obtain these spectra for every location in the tissue. In this work, we have imaged bovine cartilage and extracted information about collagen, glycosaminoglycan and water content in the tissues - the three main components of cartilage," he says.
"We found that cartilage was more complex than previously thought, with at least six groups, zones or layers that differ not just by the content of their main components and the orientation of collagen, but also by the presence of other chemical species in the sample. This is in sharp contrast to the currently accepted three zone or layer model in the literature," he adds.
As part of the work, which forms part of the ongoing UK Regenerative Medicine Platform that seeks to apply RS to tissue engineering in an effort to study how well scientists can reproduce native tissue, the team further demonstrated that it could grow tissue-engineered cartilage in the lab and the then use RS to quantitatively characterise its biochemical composition and compare it with native tissue.
In Bergholt's view, one of the main advantages of RS over conventional imaging approaches is the fact that it does not need labelling and therefore requires little or no sample preparation.
"It is also non-destructive and can therefore be used to study live-cells. One can do quantitative analysis since the Raman signal intensity is proportional to the sample concentration," he says.
In addition to using RS as a laboratory based tool for cell and tissue characterisation, the Imperial team has also developed a computational approach to analysing cells volumetrically using Raman microspectroscopy - specifically an alpha300R+ confocal Raman micro-spectroscope produced by German outfit WITec.
According to Molly Stevens, Professor of Biomedical Materials and Regenerative Medicine at ICL, most Raman studies in the literature of cells have been performed by generating conventional 2D images of the biochemical distributions, which 'does not enable accurate quantification since molecules become blurred throughout the depth of the cell.'
"In this work we developed analytical and computational methods, called Quantitative volumetric Raman imaging (qVRI), that allow us to visualise molecules inside cells in 3D using high-resolution Raman microscopy," she says.
"We have integrated qVRI as an important part of our lab and can apply this to study cells and tissue in biomedicine ranging from stem cell research, cancer biology to drug discovery. In the future, this will allow us to better characterise cell systems at the molecular level. Further, we are planning to correlate the qVRI results that we find with various other complementary techniques used in cell biology," she adds.
'Listening' for cancer
Elsewhere, a University of Strathclyde-led project has employed a combination of cutting-edge RS technology and audio signalling software to enable brain surgeons to 'listen' for cancer while carrying out complex operations.
As part of the work, the team took RS measurements with a Horiba LabRam HR800 spectrometer, with an air-cooled CLDS 785nm laser, coupled with a single edge filter.
Spectra were collected with a 0.75 numerical aperture ×60 objective (LUMPlanFLN, Olympus) immersion lens with the confocal hole set to 100 μm for spectral acquisition.
As Dr Matthew Baker, senior lecturer in Chemistry and Director of Knowledge Exchange (PAC) at the University of Strathclyde, explains, the project arose following discussions with neurosurgeons, where it became obvious that the creation of innovative inter-operative diagnostics technology would be a very welcome advance because the complete removal of the brain tumour is 'paramount for the patient.'
"Currently a static image is used, which isn't optimum as brain and patient can move slightly. Colleagues in the field are developing Raman probes that can be used for this purpose but the options for data feedback of where the tumour and non-tumour regions were located were limited to looking at complicated statistical outputs or potentially flashing lights in people's eyes," he says.
"We aimed to use the Raman output to directly control a synthesizer equation to see if the different molecular signal could be turned into different sounds, which it was," he adds.
This Raman spectrum output was then fed directly into a synthesizer equation to produce the tissue sounds that the team has discovered.
"The major advantage of this technique, when combined with Raman probes, is the ability for the surgeon to maintain visual focus on the surgical procedure - as well as its ability to help to provide inter-operative diagnostics, which would hopefully enable more efficient removal of cancerous tumours," he adds.
Analysing status of living cells
Another interesting initiative is currently being coordinated by the Italian National Research Council, which is applying an RS-based approach to complement its ongoing work on the development of so-called memristor (or MEMory ResISTOR) networks.
These state-of-the -art electrical components possess a type of 'memory' that enables them to vary their resistance depending on the amount of voltage that has been applied to them in the past - a function broadly comparable to the learning processes that occur when brain synapses develop variable 'weight' in their connections and repeatedly activate and reinforce the 'right' connections over others.
By combining a Raman spectrometer from Horiba Scientific and a homemade microscope as part of an experimental set-up located in the joint laboratory of the IOM-CNR and the Department of Physics and Geology in the University of Perugia, the team has devised a technique capable of analysing the status of living cells across a large variety of applications, as well investigating the biocompatibility of the memristive surfaces.
"The clear ability of spectroscopy to obtain real-time information on living cells and to characterise their status and their activity has led to its widespread use in recent years," says Silvia Caponi, researcher at the Consiglio Nazionale delle Ricerche (Italian National Research Council).
"The advantage of this technique is that by focusing laser light on the cell we can obtain deep cellular biochemical characterisation," she adds.
The findings will now be used to develop solutions to modern scientific and technological challenges by combining expertise in fields generally considered to be separate, such as electronics and computing architectures on the one hand and neuroscience, nanosciences and bio-electronics on the other.
"These fields are in rapid and astonishing evolution and urgent demand exists for the realisation of platforms for testing models and mechanisms of brain functions, as well as for the ability to develop bio-electronic devices and interfaces that could effectively interchange and transfer data between biological, or neuron, cells and electrical parts," says Caponi.
"This is the main ambitious purpose of the MaDEleNA project, which includes a large group of researchers from different institutions, including IBF-CNR of Trento, CNR- IOM-Perugia, CNR IMEM-Parma and Trento, CIBIO University of Trento and Fondazione Bruno Kessler (Trento)," she adds.
One future application the team imagines is hybrid neuronal-memristor systems, where biological signal transmissions will be mapped by memristor networks - in the process exploiting their ability to interact with the electrical activity of neurons and deepening understanding of how to reproduce biological adaptive or learning mechanisms using artificial components.
"This result would be of great relevance in overcoming the strong limitations of present approaches based on biocompatible electrodes," adds Caponi.