STEM I

STEM is a course taught by Dr. Crowthers! In this class we complete multiple major projects including our 6-month independent science fair project. We begin the process in the early summer, with brainstorming sessions and structured idea investigation.

Development of a Novel Point of Care Allergen Detection System

My project aimed to determine the feasibility of Raman Spectroscopy as an accessible solution to cross-contamination in public dining.

Abstract

8.6% of emergency room visits in the last year were attributed to allergy related concerns. Food-based allergies are a growing problem because of the dangers posed by their ability to induce anaphylaxis and similar negative reactions. Although precautions are taken to reduce the likelihood of food contamination, these precautions often fail to effectively protect people with allergen sensitivities. As a result, there is an increasingly important need for point-of-care devices for consumer use. Raman spectroscopy is a viable method of allergenic contaminant detection in food samples, therefore reducing a consumer’s likelihood of undergoing an allergic response. Raw tree nut samples, heat treated samples, and contaminated samples were processed under a Raman spectroscope. Heat treatment was applied to ensure the accuracy of allergen detection. one a miniaturized Raman spectroscope was engineered for point-of-care testing. It was determined that Raman Spectroscopy could detect tree nut and peanut allergens despite any contamination or reduction of immunoreactivity. Additionally, a miniaturized Raman spectroscope device could be used to detect allergens easily and accurately in a sample. These findings indicate that such a device could be used for an allergy-sensitive person when there is a risk of contaminated food; therefore, decreasing the likelihood of harmful reactions. Since Raman spectroscopy can be used for more than just food-based molecules, this can be further expanded to detect molds, parasites, pesticides, and other contaminants that could negatively impact one’s health. The portability of this device also has larger implications for point-of-care health care devices that utilize Raman Spectroscopy.

Keywords: Allergens, rapid detection, point of care treatment, Raman Spectroscopy

Problem Statement

Around 8.6% of the ER visits in the last year were attributed to food allergy related concerns (Wood et al., 2014). That number totals to around 123 MILLION PEOPLE in the United States alone, People with food allergies worry about cross-contamination in their day-to-day life. Food allergen cross-contamination in public dining setting is a serious safety concern for people with food allergies. The Centers for Disease Control & Prevention reported that the prevalence of food allergy in children increased by 50 percent between 1997 and 2011. Accurate and rapid detection of food allergens is an important unmet public health need that can help effective prevent the incidence of food allergy in our increasingly global society.

Project Objectives

1. To determine the utility of vibrational spectroscopy for allergen detection, specific to the detection of peanut/tree nut allergens in prepared food
2. To build a portable Raman Spectroscope and spectral database for food allergen identification

Access my research documents here!

Background

Process

Experimental Equipment and Materials
The primary phase of this project utilized the Horiba XplorA Raman microscope for spectroscopic data collection. Samples were processed using a 785nm laser, with 600 grating at 25% power. Each sample was collected 10 times with an acquisition time of 20 seconds. The samples used in these experiments were tree nuts and common household staples, including pasta sauce, peanut butter, and granola bars.
Sample Preparation
There were three levels of sample preparation to best determine the impacts of heat treatment on samples. The first round of testing was conducted with food grade peanuts and almonds, both raw and treated with heat. Almonds and peanuts were placed in boiling water for two minutes to replicate the effects of heat used in restaurant kitchens. Samples were then allowed to airdry for a 24-hour period and then packaged in miniature test tubes for transportation to the lab. The second round of tests were conducted on peanut butter, Nutella, and the skins of both almonds and peanuts. Name brand peanut butter and Nutella were spread onto a glass slide for analysis.
Sample Collection
The Raman microscope was initially calibrated with a silicone piece to ensure the spectral results were not impacted by sampling error. The samples were placed on a sterile glass slide in a thin layer to increase visibility on the collected spectra. A 785nm laser was used for sample collection with an acquisition time of 20 seconds, repeated 10 times per sample.

Figure 1: Baseline adjusted and averaged Raman Spectra of pasta sauce, contaminated sauce, and peanuts.

Figure 2: Baseline adjusted Raman spectra of a peanut butter bar and powdered peanuts with significant peaks at 849, 950, 1005, 1076, 1120, 1262, 1305, 1340, 1445, 1610, and 1750 cm^-1.

Figure 3: Raman Spectra of various heat-treated peanut samples, with significant peaks closely aligned with those of Figure 4.

Figure 4: : Raman spectra of ten varied peanut species indicating common identification bands among species (Farber et. Al, 2020).

Analysis

We obtained near-identical spectra for samples with varying amounts of peanuts, indicating that the method used in this project thus far is replicable with various samples. Additionally, those peaks align with the peaks found by Farber et. Al in their study of oleic acids in various species of peanuts. Farber et. Al utilized Raman spectroscopy to analyze ten different species of peanuts to understand more about their oleic acid levels and nematode resistance. This alignment indicates that not only does the spectroscopic method used here yield consistent results amongst samples, but it also matches up with previous work of other researchers who used different samples and different methods. In addition, the accuracy of the immunoreactivity trial further establishes Raman spectroscopy as a more accurate method of allergen detection. Our third and fourth trials, composing of a controlled variable of generic brand pasta sauce, varying samples with the presence of peanuts and a granola bar, indicated that allergens can be detected despite amounts of other functional groups like lipids and carbohydrates which had the possibility of drowning out the peaks associated with the allergens.

Discussions

Despite the successes noted in the data collected, a major issue occurred when interpreting raw spectral results. When conducting traditional Raman spectroscopy, the initial spectra obtained are often difficult to read due to high levels of fluorescence and noise in the spectra. To effectively analyze the peaks found in our samples, we needed to baseline adjust the spectra. In order to do so, a python program was written using the BaselineRemoval open library which extends the NumPy library. The adjustment methods of Zhangfit, ImodPoly and ModPoly were used on all processed spectra, with a polynomial degree of 5. Another issue that arose after data collection was the conducting of statistical tests. When spectra is collected, it is typically collected as a two column .txt file, however, most literature simply plots the spectra based on the points collected. Therefore, when attempting to compare the spectra obtained in this study with previous work, it was necessary to complete an image error analysis. The Scikit open library was used and modified in order to evaluate for the Mean Standard Error (MSE) between the images produced in this project and those previously conducted. The MSE between samples of this study was highly significant with MSE values under 0.5, while the MSE values evaluating the error between our spectra and other people’s spectra were slightly higher but remained statistically significant between 0.75 and 1.4. The difference in error can be attributed to the differences in graph formatting, i.e., grid lines, trendlines, etc. The work completed in this study reinforces previous spectral compositions of peanuts and further extends those compositions into a method for allergen detection. As further research is done on portable spectrometers, the findings of this project thus far could serve as evidence for using spectroscopy as a more effective and accessible allergen detection method.