TRALSPEC-AI |Development and validation of a novel method for the determination of Tropane Alkaloids in Food and Food Products
Lead Research Organisation:
Queen's University Belfast
Department Name: Sch of Biological Sciences
Abstract
Datura spp. is rich in tropane alkaloids (TAs), plant secondary compounds produced in response to environmental stressors. The entire plant is toxic and now invade crops such as maise, millet, amaranth, buckwheat, flax/linseed, sunflowers, sorghum, and soybeans. Recently, many people in Uganda suffered from severe food poisoning illness and fatality due to the consumption of Super Cereal contaminated by TAs. The gold standard methods for detecting and quantifying TAs in foods are time-consuming, laborious, expensive. They require a high level of expertise-- implying that stakeholders, such as the crop producers, cannot use these in quality control of their commodities. Our proposal aims to answer the question: can TA contamination that can poison the consumers be detected and thus prevented using vibrational spectroscopy coupled with data analytics to give accurate and real-time measurements? To answer this question, we aim to develop and validate a novel approach to gold standard methods in quantifying TAs in foods, therefore alerting for toxicity. The methods will be based on validated vibrational spectroscopic (infrared) techniques. Foods with a wide range of TA concentrations will be obtained from the European Union Reference Laboratories. They will be scanned using a benchtop and portable IR instrument. They will use Artificial intelligence (Machine Learning) to analyse the large volume of spectral data, resulting in predictive modelling that will detect concentrations of TAs in scanned foods. The model will be imported into the benchtop and portable IR instruments, thus in a way, automating the TA analysis to give real-time measurements. This is user-friendly and can be used at any stage along the food supply chain. We will compare the results obtained from this novel approach with the gold standard methods (Gas & Liquid chromatography coupled with high-resolution mass spectrometry (MS) or MS/MS).
| Description | After optimising and validating a confirmatory testing method for tropane alkaloids in soybeans, the method was used to measure the levels of atropine and scopolamine in soybean seeds and meals. At least 300 soybean samples from different countries were tested. The results showed that most seeds do not threaten human safety, considering the maximum residue limits for each tropane alkaloid. It was found that no Datura plant - a plant that produces tropane alkaloids - was present in the samples. Therefore, it is possible that the contamination by tropane alkaloids was a result of exposure or contact with Datura plant parts, such as the seeds, instead of mixing with Datura plants. Additionally, a preliminary study was carried out to investigate soybeans' exposure to Datura seeds at different times, which reflects what happens in the harvesting, processing, and storage stages of soybeans. The results showed that the concentration of tropane alkaloids increased in soybeans when exposed to Datura seeds for an extended period. |
| Exploitation Route | The sample preparation optimised and validated in this study for LC-MS/MS in determining atropine and scopolamine is easy to use and cost-efficient. The analysis time in LC-MS/MS lasts less than 10 minutes. Other laboratories can easily adopt this method to study cereal samples other than soybeans. It has been discovered that only a small number of soybean seed samples out of at least 300 different samples collected from various countries worldwide are contaminated by atropine and scopolamine. This means that soybean contamination is not a major concern regarding this contaminant compared to other cereals, as reported by others. It is difficult to find foods and products naturally contaminated with tropane alkaloids at different concentrations, which makes furthering this research a great challenge. Artificial contamination (spiking) of samples using standard solutions of atropine and scopolamine may not be the most reliable solution since it can cause uneven distribution of the solution into powdered or seed samples. However, it is possible to expose any cereal or product to Datura seeds for different periods or mix (grind) Datura seeds at different levels to obtain varying concentrations of atropine and scopolamine in the samples. This way, the samples will be naturally contaminated by tropane alkaloids, which is critical for developing rapid methods for detecting them. |
| Sectors | Agriculture Food and Drink Manufacturing including Industrial Biotechology Other |
| Description | Tralspec-AI aims to develop a quick, cost-effective, and user-friendly method for primary producers and WFP to ensure the safety of their nutrition aids from the presence of tropane alkaloids. Other researchers can also adopt Tralspec-AI's findings to further scientific knowledge in the area of plant toxins. By optimizing and validating the gold-standard method (LC-MS/MS) to quantify atropine and scopolamine, which are frequently linked to food poisoning, we have taken a significant step towards developing a rapid and cost-effective method that is adaptable and easy to implement with minimal training required to operators. Our team faced some challenges in obtaining naturally contaminated samples of tropane alkaloids. However, we discovered a natural way of contaminating the samples that reflects the real-world scenario of cereals during harvest, processing, and storage. This breakthrough method is beneficial in developing rapid methods for detecting tropane alkaloids in cereals and products. Furthermore, our partnership with the WFP is instrumental in obtaining a greater variety of samples, which are essential for the current study. The success of Tralspec-Ai will be invaluable to the WFP's operations and primary producers. It can significantly reduce product recalls and rejections, saving considerable money, time, and energy. We are confident that our project will revolutionize the food industry, making cereal and products safer through our affordable and user-friendly rapid technique. |
| First Year Of Impact | 2023 |
| Sector | Agriculture, Food and Drink,Manufacturing, including Industrial Biotechology |
| Impact Types | Societal Economic |
| Description | Project influence at the international level through partnership with WFP |
| Geographic Reach | Multiple continents/international |
| Policy Influence Type | Contribution to new or improved professional practice |
| Impact | Although the project is ongoing, its outcome will significantly benefit around 4.6 million World Food Programme beneficiaries (WFP) beneficiaries. The project aims to ensure that the foods provided for consumption are safe through the early detection of tropane alkaloids in the raw materials or ingredients of the cereal-based WFP nutrition aids. Tralspec-AI will help avoid recalls or rejection of final products, up to 500 metric tons, thereby saving time, money, and resources for the organization and suppliers. Also, Tralspec-AI will benefit WFP and other stakeholders, producing products in the same food groups for commercial purposes. |
| Title | Dilute-and-shoot technique for atropine and scopolamine analysis on LC-MS/MS |
| Description | This study has revolutionized the extraction of tropane alkaloids from cereal by optimising the ASSET Technology Centre's efficient and cost-effective dilute-and-shoot technique. The solid-liquid extraction (SLE) technique was used to extract cereal samples, and the dilute-and-shoot method was used as a clean-up step. Unlike most studies that use SLE followed by a solid-phase extraction (SPE), which can be expensive and time-consuming, this study's dilute-and-shoot technique does not involve concentration or evaporation of extraction solvent steps. This technique ensures a high yield and recovery rate. The dilute-and-shoot optimization for tropane alkaloids extraction using only 60% organic solvent and non-specialized equipment (a shaker) can extract at least 50 samples at once, making it a highly efficient and cost-effective sample preparation method that can be adopted for other solid samples. |
| Type Of Material | Technology assay or reagent |
| Year Produced | 2023 |
| Provided To Others? | No |
| Impact | Initially developed by the ASSET Technology Centre to extract mycotoxins, Tralspec-Ai has adopted this dilute-and-shoot method to extract tropane alkaloids. Colleagues from our research group at IGFS have published a review of the dilute-and-shoot method, which you can find at https://doi.org/10.1016/j.trac.2021.116284. Compared to other extraction methods involving SPE, concentration, and evaporation steps, the dilute-and-shoot method is a game-changer. It's impactful because after adding the solvent and shaking for a few hours, the supernatant is collected, diluted, and filtered before injection to LC-MS/MS. Also, with brief training, researchers can quickly learn the sample preparation process, making it a practical method for any research group. The data from applying this dilute-and-shoot method to tropane alkaloids in cereals will soon be published. |
| Title | Method validation for the determination of atropine and scopolamine in Soybeans using LC-MS/MS |
| Description | The dataset was obtained by optimising the solid-liquid extraction with dilute-and-shoot to prepare samples for analysis using LC-MS/MS. This confirmatory method is the gold standard method for studying tropane alkaloids. The dataset contains the validation data based on the SANTE guidelines, including linearity, recoveries, precision, limits of detection and quantification (LOQ), and matrix effects. All limits set by the guidelines were successfully met during the method's validation, especially the LOQ, which was 1 ppb, making the method suitable to measure the lowest maximum residue limit set by EFSA for processed cereal-based food intended for children and infants. The recoveries of the extraction method were at least 80% for different concentration levels of atropine and scopolamine, with a minimal relative standard deviation of 10-15%, and also showed linearity of results until 100 ppm. (coefficient of determination > 0.98). The dataset generated in this study also contains the analysis of at least 300 soybean samples collected worldwide. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2024 |
| Provided To Others? | No |
| Impact | The dataset supports the applicability of the dilute-and-shoot technique for extracting tropane alkaloids in complicated matrices, such as soybean seeds and meal. The analysis as a whole derived a huge dataset in a short period. The extraction does not require specialised equipment, only a shaker, and takes 2 hours plus LC analysis of less than 10 mins. |
| Description | Partnership between the United Nations World Food Programme and Queen's University Belfast |
| Organisation | World Food Programme (Italy, Sudan, Senegal) |
| Country | Italy |
| Sector | Charity/Non Profit |
| PI Contribution | The partnership's goal is to guarantee the safety and quality of food aid provided by WFP to people in need. Tralspec-AI's objective is to develop quick, cost-effective, user-friendly, and efficient methods to detect the presence of tropane alkaloids, which have been a major concern for WFP. These alkaloids have been found to contaminate food distributed by WFP to underdeveloped African countries. |
| Collaborator Contribution | The WFP shares the operational challenges and needs with the fellow and PI of Tralspec-AI and shares relevant materials and samples for method development and laboratory investigation. |
| Impact | There have been no outputs since the partnership started except for a continuous conversation regarding operational challenges and how issues can be mitigated. |
| Start Year | 2024 |
| Description | Marie Curie Fellowship Programme at QUB promotional video |
| Form Of Engagement Activity | Engagement focused website, blog or social media channel |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Postgraduate students |
| Results and Impact | The Postdoc Fellow was asked to talk about Tralspec-Ai and the MSCA Fellowship Programme by filming a video for the QUB website. The main objective was to promote the fellow's project and to encourage more researchers to apply for the fellowship through QUB. The video will be available to the public and can be accessed globally by anyone interested with internet access. Additionally, the Postdoc Fellow was invited to speak at information events about the MSCA Fellowship and to write a testimonial for the QUB website. The video was recorded in March 2024 and is currently being prepared for upload on the QUB website. |
| Year(s) Of Engagement Activity | 2024 |
| Description | PhD student visit for 6 months to participate in Tralspec-Ai |
| Form Of Engagement Activity | Participation in an open day or visit at my research institution |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Postgraduate students |
| Results and Impact | A highly skilled PhD student from Thailand, who was in her final year joined us at IGFS for six months to participate in the Tralspec-Ai project and receive training from the Postdoc Fellow. Her contribution to the project was invaluable, especially in the development of the confirmatory method that uses LC-MS/MS. During her time here, the student was involved in sample preparation and extraction, where she played a prominent role in the development and validation of the extraction method and analysis. This required thorough research and discussion on several factors such as the choice of extraction solvent, extraction time, and clean-up. We also optimized the type of column and mobile phases for maximum efficiency. Two different instruments we employed to analyse the extracts, which resulted in huge data that will soon be published. The collaboration between the student and the Postdoc Fellow was highly successful, as it brought out more ideas and plans for Tralspec-Ai. The results obtained from their work were very promising and will undoubtedly contribute to the advancement of the project. |
| Year(s) Of Engagement Activity | 2023 |
| Description | Undergraduate Student from Brazil visiting for 6 weeks |
| Form Of Engagement Activity | Participation in an open day or visit at my research institution |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Undergraduate students |
| Results and Impact | An undergraduate student from Brazil visited Portugal and IGFS through an undergraduate mobility programme she won. The postdoc fellow hosted the student for six weeks. The student was one of the best in her class and very eager to get experience in food safety in preparation for her postgraduate studies. The student was introduced to the Tralspec-Ai project and trained in the laboratory. The student learned to use various laboratory equipment and skills, from the analytical balance, solid-extraction method (sample extraction), and analysis (LC-MS/MS). The student was also given training on LC-MS/MS data processing and analysis. In addition, the student was also allowed to observe other activities/research being conducted in IGFS (using LC-Qtof and GC-MS). |
| Year(s) Of Engagement Activity | 2024 |