Transfering Retention Indexes

Gas chromatography (GC) coupled to mass spectroscopy (MS) relies on two cornerstones to identify metabolites in complex samples typically derived from plants. First, the retention index (RI, i.e. Kovats retention index), which is a number derived from the retention time and describes the chromatographic behaviour of the substances in a particular chromatographic setup. Second, the mass spectrum as shown here for Alanine (2TMS). We combine these features for convenience in to a mass spectral tag (MST) and link MSTs to the appropriate analytes.

While for the mass spectral matching differences in the used detector technologies, namely quadrupole, ion trap and time of flight, can be deemed irrelevant, chromatography settings varying between different laboratories such as temperature programming, type of capillary column and choice of column manufacturer heavily affect the empirically determined RI properties. Procedures for the transfer of RI properties between chromatography variants are, therefore, highly relevant for a shared library use. We assessed (Strehmel, N., Hummel, J., Erban, A., Strassburg, K. and Kopka, J. (2008) Retention index thresholds for compound matching in GC-MS metabolite profiling, Journal of Chromatography B, 871, 182-190. http://dx.doi.org/10.1016/j.jchromb.2008.04.042) the accuracy of RI transfer between chromatography variants and found regressions transfering empirical determined RI properties favourable compared to retention indexes estimated from physico chemical properties as described by S. E. Stein and coworkers  Estimation of Kováts Retention Indices Using Group Contributions.

Here I report on the GmdRiTransfer_01 transferring RIs from a  5%-phenyl-95%-dimethylpolysiloxane (VAR5) column towards a 35%-phenyl-65%-dimethylpolysiloxane (MDN35) capillary column. To make things more complicated the retention indexes on the VAR5 variant are based on the n-alkane homolouges while the retention indexes on the MDN35 variant are based on fatty acid methyl esthers (FAME).

The figure above depicts the training data, 899 blue dots represent analytes in the GMD with an VAR5-ALKANE RI (typically applied in the J. Kopka group) and an MDN35 FAME RI (typically utilised in the Willmitzer department). The analyte and spectrum GUIDs (global uniuqe identififiers) in the data files can be resolved using GMDs text search facility, i.e. http://gmd.mpimp-golm.mpg.de/search.aspx?query=F3EF65C6-A321-4F89-A22A-0D587219B60E. The training data are approximated using a logarithmic regression [y = 807112.206965427 * ln(x) - 5440118.048605500] (yellow graph) resulting in an averaged relative error of 5% and 7% (S.D.) and exhibiting a R² = 0,950764659. Finally 2,340 analytes in the GMD laking a empirically determined MDN35 FAME RI were projected from the VAR5 ALKANE variant in to the MDN35 FAME variant (greenish data points).
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