Determining Optimal LC-MS/MS MRMs: Sensitivity is NOT Everything!

LC-MS/MS using electrospray ionization (ESI) is a widely used platform for routine target analysis and quantitation. However, one big challenge faced through the use of ESI is the presence of matrix effects. So, what are matrix effects and why are they important? Simply put, when matrix components coelute with the target analytes, they have the potential to enhance or suppress analyte ionization efficiencies which may cause a loss of method precision and accuracy and even result in false positives or negatives. How can we solve this problem? Generally, the approaches can be categorized into 4 main strategies: 1. Sample cleanup to remove the matrix interference; 2. The use of chromatography to resolve the matrix from the analytes; 3. Calibration techniques to compensate for the matrix effects and 4. Modifying detector parameters to reduce interferences.

Sometimes interferences from the sample extracts have similar ions in the MS/MS experiment compared to your target analytes. In this case, choosing a non-interfering MRM (multiple reaction monitoring) transition with less impact is the most effective way to minimize matrix effects without additional sample clean-up or preparation. To demonstrate the effectiveness of this technique, I provided an example of where this strategy was used recently for the analysis of mycotoxins in peanut powder.

Mycotoxins are toxic secondary fungal metabolites and are very harmful to both humans and animals. Peanuts are one of the major food commodities affected by mycotoxins. The following chromatogram shows an example of matrix related interference for HT-2 toxin in peanut powder.  Difficulties with integration were observed by using the primary MRM transition 447.3->285.3 due to an isobaric matrix interference. This was effectively resolved by using a less abundant MRM transition (447.3->345.3) for quantification. In doing so, excellent accuracy and precision were observed. In addition, it saved extra time and cost that would have been needed to improve the sample cleanup and chromatographic separation. However, due to the lower intensity of the second transition (447.3->345.3), sensitivity was reduced and the lower limit of quantitation (LLOQ) had to be adjusted. Applying this approach is an acceptable practice as long as the reduced sensitivity doesn’t affect the ability to reach an LLOQ necessary to meet a regulatory requirement, or data quality objective.

Overall, matrix interferences vary widely in nature, so there is no single approach to cover every scenario. While no method can completely eliminate matrix effects, applying all the tools and resources available to us will aid in finding the best solutions that fit your application to alleviate or minimize the impact of matrix interferences in challenging samples.

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