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Apr 13, 2020 | Blogs, Food / Beverage, Life Science Research, Proteomics | 0 comments
About 220 million people worldwide live with a food allergy.1 These numbers, along with the complexity and severity of conditions, continue to rise. In America, there are about 32 million food allergy sufferers—5.6 million of those are children under the age of 18.2.2 That’s 1 out of every 13 children, or about 2 in every classroom. From a financial perspective, the cost of food allergy childcare for US families is up to $25 billion annually.
What is a food allergy?A food allergy is an adverse health effect resulting from a specific immune response that occurs reproducibly from exposure to a given food. Food allergens are proteins that can be tolerated by most people but, in some sensitive individuals, can cause a severe, even life-threatening, reaction known as anaphylaxis.
There is no cure for severe food allergy, so complete avoidance is required. Allergic consumers rely heavily on product labeling to help them do just that. There are more than 170 foods that are reported to cause allergenic reactions. In the US, the 8 major food allergens responsible for most of the severe reactions must be declared: eggs, fish, milk, peanuts, tree nuts, shellfish or crustacean, soy and wheat.2 In the UK this list also includes 6 additional food allergens: celery, lupin, mollusks, mustard, sesame seeds and sulfur dioxide and sulfites.3
Testing is critical to ensure food safetyA study led by Michelle Colgrave and James Broadbent of the Commonwealth Scientific and Industrial Research Organization (CSIRO) found that common methods, such as the antibody-based ELISA, are not always appropriate in complex food matrices. Drawing from their experience with gluten detection using liquid chromatography-mass spectrometry (LC-MS), they developed an alternative, complementary proteomics approach to detect allergenic proteins. This approach could be the first step toward the development of a routine food testing assay.
Colgrave and Broadbent’s study focused on seafood allergy for the following reasons:
From the target groups, 3 types of shrimp and prawns were chosen based on their production worldwide. (Whiteleg shrimp is one of the most commonly caught aquatic species.)
Detecting proteins by their piecesThe analysis followed these steps:
The generic workflow for protein detection and quantification using LC-MSBefore you watch the webinar, here’s a summary of the research approach.
To learn more about their work, watch their webinar by filling out the form on your right, where they describe their ongoing work on the proteome analysis of shellfish. They share data from the initial detection and identification of shellfish proteins by LC-QqTOF, and some early results of targeted allergen analysis using LC-QqQ mass spectrometry. They conclude with their goals for the second phase of the project.
Fill out the form on your right to watch the webinar.
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Regulated laboratories are evolving faster than ever. New analytical modalities, higher sample throughput, increasing regulatory scrutiny, and leaner teams are reshaping how work gets done. At the same time, expectations for data integrity, standardization, and operational efficiency continue to increase complexity and/or scope. In this environment, LC-MS software is no longer simply an instrument control platform—it has become a critical part of a laboratory’s quality management system. The question is no longer whether your lab has changed, but whether your software has evolved to support the way regulated labs operate today, and if they are ready and able to meet the demands, they will face tomorrow.
Analyst software has long been a trusted foundation in regulated LC-MS laboratories—and for many, it still performs reliably today. But regulated environments are evolving faster than ever. As labs transition to Windows 11, strengthen cybersecurity policies, modernize IT infrastructure, and prepare for future compliance expectations, software decisions are no longer just about what works today—they’re about managing tomorrow’s risk. Analyst will not be supported on Windows 11. While some labs may continue operating in unsupported environments temporarily, the bigger question is: when that risk becomes reality, will your lab be reacting under pressure—or executing a planned mitigation strategy with confidence?
As regulatory scrutiny increases and detection requirements tighten, laboratories are facing a new question: How can TFA be measured reliably, sensitively, and at scale?
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