Use of 3-nitrobenzonitrile as an additive for improved sensitivity in sonic-spray ionization mass spectrometry

Sonic-spray ionization (SSI) has been shown to produce gas-phase ions for a wide range of compounds, without the application of voltage or a laser. However, it remains to be shown that it can also provide similar sensitivities to those obtained by electrospray ionization mass spectrometry (ESI-MS).

Here we report on an attempt to further improve the sensitivity of SSI-MS, more specifically a version of SSI that is referred to as Venturi easy ambient sonic-spray ionization (V-EASI) MS, by adding a signal-enhancing additive to the sample solution. The additive used is 3-nitrobenzonitrile (3-NBN), which has recently been used with success in a new ionization approach named matrix-assisted ionization vacuum. In order to conduct this study we have analyzed a range of compounds, including peptides, metalloproteins, and some organometalloids. During the V-EASI-MS analyses molecular ion and protonated molecule signal intensities as well as their corresponding signal-to-noise (S/N) ratios, obtained in the presence and absence of the 3-NBN, were compared.

The 3-NBN-assisted V-EASI-MS approach developed here provides significant improvement in sensitivity relative to conventional V-EASI-MS for almost all compounds tested. More specifically, for peptides a 1.6- to 4-fold enhancement was realized, for proteins the enhancements were from 2- to 5-fold, and for some metalloid species enhancements reached up to 10-fold. However, optimum additive concentration and ion transfer capillary temperature were found to be compound-dependent and thus require optimization in order for maximum enhancements to be achieved. In most cases the 3-NBN-assisted V-EASI-MS approach provides comparable sensitivities and S/N ratios to ESI-MS on the same ion trap mass spectrometer.

The use of 3-NBN with V-EASI-MS gives rise to a novel 3-NBN-assisted MS technique, which has demonstrated considerable signal enhancement for most of the compounds analyzed, thus improving its competitiveness towards the well-established and dominating ESI-MS technique.