Retention index thresholds for compound matching in GC–MS metabolite profiling

Abstract

The generation of retention index (RI) libraries is an expensive and time-consuming effort. Procedures for the transfer of RI properties between chromatography variants are, therefore, highly relevant for a shared use. The precision of RI determination and accuracy of RI transfer between 8 method variants employing 5%-phenyl-95%-dimethylpolysiloxane capillary columns was investigated using a series of 9 n-alkanes (C 10–C 36). The precision of the RI determination of 13 exemplary fatty acid methyl esters (C 8 ME–C 30 ME) was 0.22–0.33 standard deviation (S.D.) expressed in RI units in low complexity samples. In the presence of complex biological matrices this precision may deteriorate to 0.75–1.11. Application of the previously proposed Kováts, van den Dool or 3rd–5th order polynomial regression algorithms resulted in similar precision of RI calculation. For transfer of empirical van den Dool-RI properties between the chromatography variants 3rd order regression was found to represent the minimal necessary assumption. The range of typical regression coefficients was r 2 = 0.9988–0.9998 and accuracy of RI prediction between chromatography variants varied between 5.1 and 19.8 (0.29–0.69%) S.D. of residual RI error, RI predicted − RI determined ( n > 64). Accuracy of prediction was enhanced when subsets of chemically similar compound classes were used for regression, for example organic acids and sugars exhibited 0.78 ( n = 29) and 3.74 ( n = 37) S.D. of residual RI error, respectively. In conclusion, we suggest use of percent RI error rather than absolute RI units for the definition of matching thresholds. Thresholds of 0.5–1.0% may apply to most transfers between chromatography variants. These thresholds will not solve all matching ambiguities in complex samples. Therefore, we recommend co-analysis of reference substances with each GC–MS profiling experiment. Composition of these defined reference mixtures may best approximate or mimic the quantitative and qualitative composition of the biological matrix under investigation.