Driving SERS into the Clinic

With the discovery of laser and subsequent advancements in laser and detector technology, the previously slow development of Raman spectroscopy moved into a higher gear. Raman spectroscopy has now proven its worth for analyzing biomacromolecules, including proteins and DNA, living cells, tissues, and microorganisms for detection and diagnosis.

Raman scattering, however, is a very weak process in which only one in a million photons is elastically scattered. An additional problem – autofluorescence – hinders the use of the technique in biological applications. Fortunately, in the early 1970s, a novel phenomenon was discovered where molecules in contact with (or in very close proximity to) noble metal surfaces, such as silver and gold, increased Raman scattering by up to 1011 times, which led to the development of surface-enhanced Raman scattering (SERS). In addition to enhanced scattering, SERS effectively quenches autofluorescence.

Although there is a lot of knowledge about SERS analysis of biological structures, in my opinion, there is a gap between research and clinical applications. Moreover, it is not going to be possible to translate the technique into real applications without understanding the needs and processes within a clinical setting.

For example, there are several issues that need careful consideration for sound interpretation of data gathered from a biological SERS experiment. First, the type of SERS substrate needs careful selection for the sample of interest. Should it be a nanostructured surface or colloidal nanoparticles, such as gold (AuNP) or silver nanoparticles (AgNP)? If the sample is a living cell, AuNPs or AgNPs can be a better choice. If the sample is microbiological, a surface or colloidal NP substrate is best.

After choosing the most appropriate substrate, it is important to test for reproducibility and applicability. The obtained spectral information should be evaluated by considering the selective interactions of the functional groups, such as SH and NH2, with the noble metal surfaces, as these interactions define the environment.

For a decade, we have evaluated whether the technique can be used for clinical decision-making. We have analyzed living and dead cells, tissues, and microbiological samples using sample preparation methods developed and tested in our laboratories. We believe more has to be done to explore the potential of the technique because biological samples are not only very complex but also show variations from sample to sample.

Rapid identification of infectious microorganisms is critical for disease intervention in clinics. Although there are many studies demonstrating the proof of concept for utilizing SERS for fast microorganism identification, its capacity to identify them from clinical samples is not yet clear.

The complex nature of biological samples, such as blood and urine, is one of the major obstacles to decreasing the time needed for understanding the status of a sample. For example, in a urine sample, there could be several chemicals, including urea and creatinine, dissolved ions, white and red blood cells, and proteins together with infectious pathogens. These components may interfere with, or hinder, the SERS measurement without proper cleaning or separation, which of course increases analysis time. There are also several questions that need asking to determine the infection status of a urine sample. The first question seems obvious: is the sample infected or not? The numbers of bacteria in 1 mL of urine determine the answer, as only urine samples containing greater than 105 cfu/mL are considered to be infected. Then, we must ask which pathogen(s) is/are present? We then move onto asking if there is a marker that SERS can identify to show whether the urine is infected or not. Can the technique be used for the quantification of bacteria in the sample? Can the technique identify the pathogen?

We already know that SERS can identify bacteria, but further effort is needed to speed up the process from a complex sample. In my opinion, we are not that far from getting positive answers for some of these questions – and that will shorten the time needed to get SERS into a position where it can enhance clinical decision-making.