By: Nik Bear Brown, Shesh Gupta
The RAMAN Effect project is research to develop machine learning and experiments to show the effectiveness of RAMAN SERS for wastewater epidemiology rather than a technology like PCR. Analyzing the data coming from RAMAN spectra can be done using standard machine learning prediction and accuracy of up to 90% (or even more) can be achieved by building neural network models.
RAMAN SERS versus PCR
Wastewater collection is done at facilities such as dorms, office buildings, apartment buildings, naval ships, prisons, or nursing homes. PCR is a well-established molecular biology technique that only detects known nucleic acids. PCR is better at detecting presence or absence than being a strictly quantitative technique. The PCR test takes a sample of ribonucleic acid (RNA) and “amplifies” it with the help of lab technologies. Amplifying RNA helps to make even small traces of the COVID-19 virus visible in the test sample. Even if you have a small trace of the virus in your system, the PCR test will detect it.
However, PCR technology is not sensitive. The PCR approach has several serious issues. The primary issue is that if one is going to test the wastewater at a facility one wants to test for many more things than COVID-19. Page Break
The most natural technique for wastewater epidemiology is Raman Spectroscopy. Raman Spectroscopy is a non-destructive chemical analysis technique that provides detailed information about chemical structure, phase and polymorphs, crystallinity, and molecular interactions.
In Raman Spectroscopy, a sample is illuminated with a laser beam. Electromagnetic radiation from the illuminated spot is collected with a lens and sent through a monochromator. Elastically scattered radiation at the wavelength corresponding to the laser line (Rayleigh scattering) is filtered out by either a notch filter, edge pass filter, or a band pass filter, while the rest of the collected light is dispersed onto a detector such as a camera.
Raman Spectroscopy can be unbelievably cheap. It can detect bacteria, small molecules, and nucleic acids. Raman Spectrometers have been built using a cell phone and a diode laser.
Further, to enhance the detection of molecules, Surface-Enhanced Raman Spectroscopy (SERS) is typically used. SERS is also capable of simultaneously detecting multiple contaminants of varying polarities and molecular weights, a feat that most existing detection strategies cannot achieve. SERS chips are wafers with nanoparticles with different areas of the chip to detect specific molecules. Chips are about the size of a sim card that can detect around 100 different molecules.