Raman spectroscopy is a remarkable analytical technique that has transformed the way we understand and study molecular composition and structures. But what makes it so special? Let's take a closer look at the Raman effect and how it works.
First, its existence is thanks to the work of the Indian physicist, Sir Chandrasekhara Venkata Raman (pictured right), who first published the effect in 1928. The Raman Effect (or Raman Shift) is named after him. It occurs by the inelastic scattering of light molecules. Inelastic scattering does not conserve the energy of the light, which leads to a change in the light’s wavelength. Sir C. V. Raman won the 1930 Physics Nobel Prize for his work on this [1].
The Raman effect is a rare type of inelastic scattering that occurs when light interacts with matter. In fact, it's so rare that only 1 in 100 million incidents of light scattering exhibit this effect! But when it does happen, it's broken down into two sub-types based on how the frequency of the light changes: Stokes and anti-Stokes.
When a molecule absorbs energy from a photon of light, the frequency of the light decreases, and this is known as the Stokes shift. Conversely, when energy is given by a molecule, the frequency of the light detected is higher than it was at the source, and this is known as the anti-Stokes shift. These shifts in light frequency are unique identifiers of the rotational and vibrational states of particular molecules [2].
This is where Raman spectroscopy comes in. By measuring the number of shifts in the frequency of scattered light over a range of wavelengths, scientists can identify the composition of a sample and gain insights into its molecular structure. Much like a compositional and structural fingerprint for your sample. This is called a spectrum (plural spectra). For example, in bone, we can use spectra to understand collagen order (Amide I), mineral crystallinity(half-width intensity of V1PO4), and mineral substitution (V1CO3: V1PO4 which is carbonate: phosphate) ratios. More detail will be given later on bone Raman spectroscopy, but changes in the ratios can suggest deteriorating bone health.
The best part is that Raman spectroscopy is becoming extremely useful to the biomedical field because it is:
Quick
Little to no sample preparation is required
Hydrated samples OK
All states of matter (gases, liquids, solids, etc.) OK
Non-destructive
Non-invasive (OK to use on bodies)
Requires NO dyes or labels
Relatively inexpensive
Compatible with other techniques
The ease of use and potential for clinical application make Raman spectroscopy attractive compared to complementary and similar techniques like Fourier-transform Infrared Spectroscopy (FTIR). Additionally, the versatility of Raman spectroscopy to combine with a range of other technologies lets us create powerful analytical tools. This has led to over 25 variations of the technique, which can be overwhelming for those new to the field. But let's focus on some of the main types.
Spontaneous Raman spectroscopy is used more often for very fast imaging, such as live-cell imaging combined with confocal scanning laser microscopy (CSLM). This allows us to capture single-cell spatial information and fluctuations of molecules near real-time. However, the Raman effect is rare, and as a result, the spectra generated by spontaneous Raman spectroscopy are weak and noisy. This can make it difficult to accurately identify and analyze the molecules and orientations present in a sample [3]. Raman labels, such as R-dots, are developing to improve the applicability of this method. Raman labels attach to specific molecules with the help of antibodies, for example, to increase the signal of those molecules in the spectra [4].
Other techniques use multiple lasers to increase the incidence of the Raman effect and generate stronger, clearer signals. This leads to better molecular detection.
Stimulated Raman Scattering (SRS) utilizes multiple lasers that can enhance the Raman effect signal by a whopping 1000 to 1 million times. There are two main types of SRS, which are divided by the type of Raman shift they measure: Stokes or Anti-Stokes. Coherent Raman Scattering (CRS) measures Stokes and coherent anti-Stokes Raman scattering (CARS) measures anti-Stokes.
CRS is the go-to for quantitative compositional analysis, but it comes with a bit of a catch. The detectors are more complex and collection times are a bit longer. However, we use this often in bone studies to better understand how our cell activity influences our mechanical properties through tissue changes.
CARS is a better tool for studying complex biological tissue structures like collagen, where orientation can give us important insights into the structure and function of the tissue. This is because CARS performs at higher wavelengths and captures vibrational and orientation information better. It has simpler detectors but the signal requires more post-processing of the data.
Some other common variations of Raman spectroscopy are surface-enhanced Raman scattering (SERS) and tip-enhanced Raman scattering (TERS). Both SERS and TERS rely on inducing plasmonic resonance using the original light beam. This means the electrons are energized at the surface of the sample, which enhances the interaction between the light and the sample. This significantly boosts the rate of the Raman effect. SERS and TERS techniques offer nanometer resolution because they aren't limited by light resolution limits. However, both SERS and TERS require more preparation, so they may not be as straightforward as other Raman spectroscopy techniques, particularly in biomedical and clinical applications.
But to this point, I have not mentioned many downsides to Raman spectroscopy and it does have them just like any technique does. The good news is that we have a workaround for most of them in newer variations of Raman spectroscopy. Most of the drawbacks of Raman come back to the low strength of the Raman effect but they include:
Can have a high noise-to-signal ratio*
Autofluorescence can overwhelm the Raman effect**
High laser powers can burn your samples ***
Generally cannot analyze pure metals and alloys
* Variations of Raman spectroscopy can boost the signal drastically
**Autofluorescence can be minimized with different laser wavelengths
***Laser power can be reduced to prevent burning samples
Biomedical Examples
*Note: The majority of biological samples will have ~90% of their fingerprint spectra peaks between 300-1800 cm-1 and the rest between 2700-3300 cm-1 [3].
Drug delivery is an application of great interest. Imagine being able to tell if a molecule is being released and delivered effectively from a skin patch, or if the patch has less of the drug in it. But that's not all. If we know the molecules that change as a result of the drug, we can measure them in living tissue using Raman spectroscopy. This is a far more preferable approach than relying on tissue samples taken from trial participants, which can give an incomplete picture of the drug's activity. By avoiding this step, we can improve our understanding of the patch's delivery and efficacy while saving study participants from unnecessary pain.
Tissue quality can be measured with Raman spectroscopy for disease diagnosis and progression. For example, imagine a tiny fiber-optic Raman spectroscopy probe inside a needle that can 'read' muscles when it is in a body. This little probe was able to distinguish diseased mice from healthy ones and even track the progression of debilitating conditions like amyotrophic lateral sclerosis (ALS) and Duchenne muscular dystrophy (DMD). Improved diagnosis and monitoring of ALS and DMD could make all the difference in clinical trials aimed at improving patient outcomes [5].
So whether you're a researcher in the lab or just a curious science enthusiast, the world of Raman spectroscopy is full of exciting possibilities. By Raman spectroscopy with other advanced techniques, we're able to explore the molecular world like never before and uncover new insights into the workings of our bodies.
References
[1] The Nobel Prize in Physics 1930 [Internet]. NobelPrize.org. 2023.
[2] Unal M, Ahmed R, Mahadevan-Jansen A, Nyman JS. Compositional assessment of bone by Raman spectroscopy. Analyst [Internet]. 2021 Dec 6;146(24):7464–90. Available from: http://dx.doi.org/10.1039/d1an01560e
[3] Jones RR, Hooper DC, Zhang L, Wolverson D, Valev VK. Raman Techniques: Fundamentals and Frontiers. Nanoscale Res Lett [Internet]. 2019 Jul 12;14(1):231. Available from: http://dx.doi.org/10.1186/s11671-019-3039-2
[4] Chen C, Zhao Z, Qian N, Wei S, Hu F, Min W. Multiplexed live-cell profiling with Raman probes. Nat Commun [Internet]. 2021 Jun 7;12(1):3405. Available from: http://dx.doi.org/10.1038/s41467-021-23700-0
[5] Plesia M, Stevens OA, Lloyd GR, Kendall CA, Coldicott I, Kennerley AJ, et al. In Vivo Fiber Optic Raman Spectroscopy of Muscle in Preclinical Models of Amyotrophic Lateral Sclerosis and Duchenne Muscular Dystrophy. ACS Chem Neurosci [Internet]. 2021 May 19;12(10):1768–76. Available from: http://dx.doi.org/10.1021/acschemneuro.0c00794
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