Systematic electron ionization fragmentation studies of steroids have been performed to elucidate and trace their characteristic fragmentation patterns. However, the electron ionization source setting at 70 eV electron energy is much higher than the ionization potential (7-15 eV) of most organic compounds, leading to extensive fragmentation. We present a multifactorial study on optimizing a low-energy electron ionization source to maximize molecular ion formation while minimizing the extent of fragmentation to improve the analytical sensitivity of steroids, especially the more thermolabile ones, while preserving the information that can be extracted from the data.
Twenty-seven steroid reference materials, chosen to cover four main classes of urinary steroids, were considered; gas chromatography/quadrupole time-of-flight (GC/qTOF) analyses were carried out using an Agilent Technologies model 8890 gas chromatograph coupled to an Agilent Technologies model 7250 accurate-mass quadrupole time-of-flight (GC/qTOF) instrument. The effects of electron energy, emission current, and source temperature, as well as their potential interactions on steroid fragmentation pathways, have been assessed in full factorial experimental designs.
Three parameters were specifically evaluated to improve the chromatographic/spectrometric response of the selected steroids: (i) degree of fragmentation; (ii) relative abundance of the molecular ion; and (iii) peak width. The first two were evaluated by screening designs that highlighted collision energy and source temperature as the most influential factors on the analytical responses of the considered steroids, while emission current always showed a non-significant influence. Then, an optimization design was performed to select the final source setting by searching for the combination of factors that minimize peak tailing.
The proposed analytical approach permits a faster selection of optimal experimental conditions for steroidomics analysis using low-energy electron ionization and high-resolution mass spectrometry. The development of these designs of experiments (DoE) in full factorial design (FFD) allowed multiple inputs to be monitored at the same time, highlighting the possible interactions and estimating the effects of a factor in the different levels of the other factors considered.