GC-MS detection of central nervous tissues as TSE risk material in meat products: analytical quality and strategy
2004
Lucker, E. | Biedermann, W. | Lachhab, S. | Truyen, U. | Hensel, A.
allemand. The detection of central nervous system (CNS) tissue (i.e. brain and spinal cord) by the use of GC-MS and certain fatty acids (FAs) as their methyl esters (FAMEs) was previously shown to be a very promising approach towards identification of CNS tissue as a specified risk material (SRM) in meat products, contrasting available immunochemical methods. This GC-MS method promised to allow quantification of CNS material as low as 0.01%. Here, we show that the CNS-relevant FAMEs C22:6, C24:1omega9, C24:1omega7, C24:0 and C24-OH are present in pure muscle and adipose tissue samples in detectable amounts. Thus, limits of detection are not feasible as quality parameters in this analytical GC-MS approach. Instead, cut-off values have to be applied as calculated from the baseline content of the respective FAME in CNS-free samples and its variation for a given statistical security. Furthermore, the FAs used for quantification of the CNS showed distinct differences depending on species and age. This finding is in accordance with previous studies where it had been concluded that species and age differentiation of CNS might be possible with GC-MS. However, it was not taken into account that it also necessitates a strict analytical strategy for quantification of the CNS content: identification of the presence of CNS (step 1); identification of species and age (step 2); and quantification by use of a species- and age-specific CNS calibration (step 3). Differences between the FA content of the CNS used for calibrating and the CNS in the sample will cause up to fivefold deviation from the true CNS content. Our results show that the FA best suited for identification (step 1) and quantification (step 3) purposes is cerebronic acid C24-OH after silylation. Further in-depth studies are needed in order to elucidate variability of brain FA content and to determine analytical limits. However, the present GC-MS approach is already a highly promising supplement to existing immunochemical methods for the detection of traces of CNS material in meat products
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Editeur Springer
ISSN 1618-2642 | 1618-2650Cette notice bibliographique a été fournie par German Federal Institute for Risk Assessment
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