GEN-MKT-18-7897-A
Nov 18, 2020 | Blogs, Food / Beverage | 0 comments
Read time: 4 Minutes
The COVID-19 pandemic has increased the need to store and transport raw and finished food products in order to sustain the richness of the food supply chain. Therefore, having a robust post-harvest support system that monitors moisture levels and conditions of raw and finished food products is much needed to ensure food safety and security. I think this is a good time to talk about the risk of mycotoxin growth.
Mycotoxins are small, stable metabolites produced by molds and fungi that can contaminate a variety of crops. These naturally produced chemicals can provoke a toxic response when consumed even in low concentrations by both humans and animals.1
The thing to bear in mind is that toxin contamination usually stems from the source, with the 3 main contamination patterns being:
To put it into perspective, a toxin like aflatoxin is classified as a human carcinogen by the International Agency for Research on Cancer (IARC). These toxins typically make their way into our food chain through a pathway like this: ruminants consume feedstuff contaminated with aflatoxin B1 (AFB1), and the toxin metabolizes into aflatoxin M1 (AFM1). The AFM1 that gets excreted into milk is then consumed by humans, thus putting us at risk.
If you’re interested in learning more about the “what” and “how” of mycotoxin analysis, please check out this blog. In this post, I’d like to discuss a robust approach to screening for mycotoxins and their secondary metabolites, starting with shedding some light on masked mycotoxins.
Masked mycotoxinsCommonly studied mycotoxins include aflatoxins (e.g., AFB1), trichothecenes (e.g., DON), fumonisins (e.g., FB1), ochratoxins (OTA) and zearalenone (ZEN), and the 3 main genera of filamentous fungi that produce these toxins are aspergillus, fusarium and penicillium. Many food labs routinely test for mycotoxins, and research on the different types of mycotoxins is widely available and understood. On the flip side, however, there are potentially hundreds, maybe thousands, of other metabolites produced by plant defense mechanisms that can alter or degrade the mycotoxins of which we are aware. This can result in a slew of similar species present in food commodities that are structurally similar to the routinely targeted mycotoxins, but are not included in routine analytical panels. This means, from the perspective of a targeted analytical method, that they are present but unseen, and hence “masked,” and masked mycotoxins are not currently regulated by the same provisions that regulate routinely measured mycotoxins.
A masked mycotoxin can exhibit toxicity that is similar to its parent toxin. For example, the plant might modify the chemical structure of the toxin with a glucose or sulfate moiety, which reduces its toxicity to the plant. The plant itself may now contain only the conjugated form of the toxin, but during human or animal digestion, if the conjugate functional groups are degraded, the original mycotoxin may emerge and expose the consumer to the dangers of the toxin.2
Emerging awareness of the risks posed by these unseen toxins led some researchers to look beyond the targeted methods for the original compounds. Current knowledge of these “emerging mycotoxins” (e.g., NXToxins), as well as masked or other modified forms of mycotoxins, is limited, but the number of compounds that need to be analyzed is increasing rapidly, requiring more comprehensive analytical methods.3
Routine mycotoxin screeningThere is no true silver bullet for tackling the threat of mycotoxins and their metabolites. However, being able to evaluate their presence is key. There are several methods available for detection, all with advantages and limitations. One common technique—enzyme-linked immunosorbent assays (ELISA)—is rapid and easy, but it has poor selectivity sensitivity and specificity, which can be a problem, especially when detecting masked mycotoxins.
Liquid chromatography-tandem mass spectrometry (LC-MS/MS) can help address that gap. Our team at SCIEX has done some extensive work to put together a robust and high-throughput method to quantify 530 mycotoxins, masked mycotoxins and other metabolites.
This method was demonstrated on barley and corn extract using the SCIEX Triple Quad™ 5500+ LC-MS/MS System – QTRAP® Ready, and the results showed:
If you’re interested, you can click here to download the technical note that details this high-throughput mycotoxin analysis.
References
As an analytical strategy, middle-down mass spectrometry (MS) workflows characterize biotherapeutic proteins by analyzing large, digested protein fragments or defined subunits, rather than fully intact proteins (top-down) or digested peptides (bottom-up). A middle-down strategy combines the strengths of top-down and bottom-up approaches by delivering high sequence coverage and structural specificity while maintaining relatively simple sample preparation. In practice, middle-down analysis enables accurate mass measurement, rapid sequence confirmation, and localization of key post-translational modifications (PTMs) on protein subunits that are directly relevant to product quality.
In biopharmaceutical development, sequence variants (SV) are considered an inherent risk of producing complex proteins in living systems. Sequence variants are unintended changes to the amino acid sequence of a biotherapeutic and can be caused by errors in transcription or translation in the host cell, or cell culture and process conditions. Detailed analysis of SVs is important in process and product development to ensure the drug’s safety and efficacy. Even low‑level sequence variants can have significant implications for product quality, safety, and efficacy, making their accurate detection and characterization a critical requirement across development, process optimization, and regulatory submission.
CE‑SDS remains a cornerstone assay for characterizing fragmentation, aggregation, and product‑related impurities in therapeutic proteins. UV detection has been the long‑standing standard. However, it frequently struggles with baseline noise, limited sensitivity for minor fragments, and subjective integration.
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