Progress 09/01/20 to 04/30/22
Outputs
Target Audience:Hazardous marine toxin, especially domoic acid, poses the greatest threat to the shellfish industry, which can cost hundreds of millions of dollars' loss and damage marine ecosystem. However, traditional laboratory chemical analysis methods are ill suited for detecting domoic acid in shellfish as they are expensive, time-consuming, and incapable of on-site testing. The overarching goal of this USDA SBIR project is to develop a portable, ultra-sensitive, cost-effective biosensing technique to detect, track and predict the threat of domoic acid, which will minimize the economic loss to the shellfish industry. The technology developed through this project will provide an easily accessible, affordable, near-real-time monitoring technique for domoic acid that can benefit the coastal community, including industries, government agencies, and academia. The target customers of the proposed domoic acid biosensors include multiple end-users in the coastal community: Private testing companies such as Marshfield Food Safety and Certified Laboratories, Inc., which test the food samples sent by the seafood distribution companies. These laboratories would benefit from our biosensors because the new biosensor technology would significant reduce the labor, utility and material cost by 95%. These laboratories are bought from biotechnology equipment manufacturers such as Renishaw Diagnostics (Table.5). Table.5 List of large laboratory facilities and biotechnology equipment distributors Laboratory Facilities Biotechnology Companies Marshfield Food Safety Renishaw Diagnostics Certified Laboratories, Inc. Qiagen ABC Research Laboratories Neogen Silliker Life Technologies IEH Laboratories & Consulting Group ABSCIEX Northeast Laboratory Services DuPont Seafood processing plants, rather than having to send their samples in an environment controlled box to a lab and then wait a few days to get the results, now could take the measurements themselves. Instead of having to let a whole batch sit while they are waiting for the results from the lab, they would be able to take the measurements, verify the quality of the product and then ship the batch out to their customers. This would allow them to test more frequently thus minimizing their risk of the FDA mandating a costly recall. Government Agencies: FDA and USDA regulate the seafood industry. One of the requirements is for a company to have a Hazard Analysis Critical Care Point (HACCP) plan. This plan outlines how processing plants are going to ensure that their processes kill any contaminants. When the FDA performs their yearly inspection of these plants, they look at the HACCP and often test a product that has gone through the processes to prove that it is indeed safe. In this case, the FDA and USDA would benefit from our biosensors to perform a rapid, accurate, on-site verification of a plant's processes. Department of Agriculture and Department of Fish and Wildlife regularly test crabs and clams along the coast to monitor domoic acid. Depending on the results, they decide whether and how much can be harvested. These tests need to be conducted frequently to ensure that they catch any outbreaks before the infected food is put into our food supply. By providing them our technology, we allow them to test more frequently and more cost effectively with essentially immediate results. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?One postdoc scholar One PhD student How have the results been disseminated to communities of interest?Wang, A.X., 2022, March. Diatom photonic crystal biosensors: materials, applications, and fusion with machine learning. InFrontiers in Biological Detection: From Nanosensors to Systems XIV(p. PC1197907). SPIE. What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
Presented through this work, a simplistic approach to quantitatively assess the presence of a representative marine neurotoxin, Domoic acid (DA) from spiked water and crab meat samples is presented. DA sensing was performed based on surface-enhanced Raman scattering (SERS) using silver nanoparticle enriched diatomaceous earth --- a biological photonic crystal material in nature. Distinctive optical features of the quasi-ordered pore patterns in diatom skeleton with sporadic yet uniform functionalization of silver nanoparticles act as excellent SERS substrates with improved DA signals. Utilizing the measurement results, a standard calibration curve between SERS signal intensity and DA concentration was developed. The calibration curve was later utilized to predict the DA concentration from spiked Dungeness crab meat samples. SERS based quantitative assessment was further complemented with principal component analysis and partial least square regression studies. Additionally, high performance liquid chromatography - mass spectrometry as performed to validate the potential of the study for real time testing. The tested methodology aims to bring forth a sensitive yet simple, economical and an extraction free routine to assess biotoxin presence in sea food samples onsite.
Publications
- Type:
Journal Articles
Status:
Other
Year Published:
2022
Citation:
Quantitative Sensing of Domoic Acid from Shell Fish using Biological Photonic Crystal Enhanced SERS Substrates
Manuscript under preparation
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Progress 09/01/20 to 08/31/21
Outputs
Target Audience:
Nothing Reported
Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?The research project provides the research training for one PhD student, one visiting student, and one research scientist in materials synthesis, SERS sensing, and data analysis. How have the results been disseminated to communities of interest?One article is published in Biosensors. One manuscript is currently under review, and one manuscript is under preparation. What do you plan to do during the next reporting period to accomplish the goals? Milestone 1: Acquiring the SERS spectra of various marine toxin, especially domoic acid using a portable Raman spectrometer SERS spectra of marine toxin in water or seawater have been reported using regular Raman microscope, which can only serve as a laboratory analysis technique. In this project, we will develop a scalable production method of diatomaceous earth microfluidic channel devices using metal template printing. We will also use portable Raman spectrometers at Dr. Wang's group to acquire the SERS spectra of marine toxins at various concentrations. In the meanwhile, the SERS spectra of common interference chemicals such as lipid, protein, amino acids, fatty acids, and glucosamine found in shellfish meat will also be acquired. The results will be used as training data for the machine-learning algorithm to improve the specificity and quantification accuracy. Milestone 2: Test the sensitivity and specificity of marine toxin from real shellfish samples with machine-learning algorithm Step 1: We will mix domoic acid as the representative marine toxin with Dungeness crab meat and perform TLC-SERS detection using the diatomaceous earth micro-fluid channel devices. The objective is to determine the detection limit (expected to be 1ppm) and obtain quantitative sensing results using the QPCA-SVR machine-learning method. Step 2: We will do blind test of Dungeness crab samples supplied by West Coast Seafood Processors Association (WCSPA) and compare the results measured by GC-MS. We will test the sensitivity, selectivity and quantification in the context of real seafood complexity. Milestone 3: Conduct on-site testing at Charleston, Ore., seafood processor Step 1: Develop a full set of tool kit for on-site testing: a lithium battery bank will be bought to power the portable Raman spectrometer. 20 diatomaceous biosensor chips will be prepared with pre-deposited NPs and will be packaged in plastic bags. Organic solvent will be contained in secured containers. The machine-learning algorithm written by Matlab language will automatically collect the data from the portable Raman spectrometer and analyze the data. Step 2: We will conduct on-site testing at Charleston, Ore., seafood processor through the coordination of WCSPA. Multiple on-site testing will be scheduled according to the spike level of domoic acid as well as the growth cycles and harvest seasons of shellfish.
Impacts
What was accomplished under these goals?
Fabrication of uniform thin layer chromatography in tandem with surface-enhanced Raman scattering (TLC-SERS) substrates We fabricated TLC-SERS substrates by in-situ growth silver nanoparticles (Ag NPs) on diatomite biosilica layer via electroless reaction. The fabricated TLC-SERS substrates contain uniform and high density Ag NPs on the diatomite surface, which significantly enhanced the SERS signals, which were evaluated using R6G as a molecular probe at a concentration of 10-5 M. The enhancement factor (EF) of the Ag NPs on the diatomite biosilica substrate was on the order of 1011. A low concentration of R6G at10-14 M was successfully detected. To confirm the uniformity, SERS mapping results shows stable signals with variation less than 10%. Furthermore, the substrate was applied to separate and detect multiple chemical compounds in a complex mixture solution. The TLC-SERS mapping results clearly distinguish the separated target molecules after TLC development and demonstrate improved specificity. Therefore, we conclude that such TLC-SERS substrates can be particularly useful for real-world sample sensing, such as monitoring marine toxins from shell fish meat. Develop machine vision analysis for multiplex TLC-SERS sensing TLC-SERS still faces significant challenges of multiplex sensing from complex mixtures due to the imperfect separation by TLC and the resulting interference of SERS detection. In this project, we propose a multiplex TLC-SERS sensing method of complex mixtures by machine vision analysis of the scanning image. The measurement was conducted based on the same type of TLC-SERS substrates, which can simultaneously perform TLC separation and SERS sensing on the same platform. Mixture solution are separated by TLC followed by 1-D SERS scanning of the entire TLC plate, which generates TLC-SERS images of all target substances along the chromatography path. Benefited from the comprehensive spatial and spectral information of the TLC-SERS image, the proposed machine vision method conducts a holistic analysis by the kernel algorithm based on the image matching between the extracted template image from pure substances and the mixture TLC-SERS image. Our experimental results of 300 ppm mixtures show that the image matching algorithm can achieve high accuracy even though the target substances have certain overlaps along the TLC path and a large dynamic range of the SERS signals. Negative control testing confirms excellent specificity of the machine vision method. It also shows high sensitivity when the mixture concentration is much lower (1ppm) than those used to obtain the image templates. Last but not the least, the machine vision analysis does not require any manual interference and is fully objective and intelligent, which is highly essential for rapid, on-site detection of complex mixtures. We envision that the proposed machine vision analysis of the TLC-SERS imaging can achieve objective, accurate, and efficient multiplex sensing of trace level of target substances that can play pivotal roles in many applications such as food safety, environmental protection, forensics, and public health. Point-of-care (POC) SERS sensing of toxins directly from water solution We also developed a rapid POC SERS sensing technique with ultra-high sensitivity to detect toxins using a portable Raman spectrometer and principal component analysis -partial lest squire regress (PCA-PLSR) model. The SERS substrates were fabricated via in situ growth of AgNPs on diatomaceous earth films. We achieved an ultra-high sensitivity down to 10 part-per-trillion (ppt) fentanyl in artificially contaminated tap water within 2 min in the lab. The PCA-PLSR model predicted the concentration of fentanyl with good R2 values for both training and testing data sets. Furthermore, our SERS substrates exhibited a strong sensing capability of fentanyl in sewage water and detected fentanyl in water from a local wastewater treatment plant. The experimental results show that the concentration of fentanyl in the sewage water was about 800 ppt with a high R2 value. We also tested the fentanyl concentration through high performance liquid chromatography - mass spectrometry (HPLC-MS). The result is consistent with our portable SERS's but only provided a range below 1 part-per-billion (ppb) since the concentration was below the detection limit of HPLC-MS for fentanyl. In addition, we further demonstrated the validity of our SERS sensing technique by comparing SERS results from multiple sewage water treatment plants, and the results are consistent with the public health data from our local health authority. Therefore, we proved that our SERS substrates, when working together with a portable Raman spectrometer and chemometric analysis algorithm, can help an ultra-sensitive sensing technique function at a sub-part-per-billion level to detect the trace level of fentanyl from sewage water, which is crucial to assess public health.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
Zhang, B., Hou, X., Zhen, C. and Wang, A.X., 2021. Sub-Part-Per-Billion Level Sensing of Fentanyl Residues from Wastewater Using Portable Surface-Enhanced Raman Scattering Sensing. Biosensors, 11(10), p.370.
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