62 May / June 2019
HPLC eluent travels through a spray capillary surrounded by a co-axial flow of nebulising gas, typically heated nitrogen. The liquid is charged by applying an electric field to the capillary, causing a potential difference between the capillary tip and the entrance of the high vacuum region of the MS. The application of a charge results in the generation of a Taylor cone. The surface tension of the eluent holds the liquid in a steady state for a set distance and beyond this an aerosol of charged droplets is formed and ejected towards the electrode of the opposing charge. Currently, there are two generally agreed mechanisms by which ions are formed from the charged liquid droplets: (a) the charged residue model (CRM) [11] ; and (b) the ion evaporation model (IEM) [12]. Both mechanisms have been demonstrated to exist together under the same experimental conditions and depending on the exact LC and MS parameters, one of these mechanisms will tend to be favoured. CRM states that solvent evaporation, often assisted by heat, causes the droplets to diminish in size, reaching a critical diameter or Rayleigh limit. At this point the residual charge on the remaining solvent is no longer stable on the available surface area of the droplet. This results in a Coulombic explosion which ideally would lead to the formation of a single molecule of analyte with a single charge associated with it. IEM proposes that droplets and ions are emitted from a much larger droplet and that this results in a gradual reduction of the size of the main droplet [11,12]. Other models do exist which explain the phenomena of electrospray [13,14,15], but these are generally variants or combinations of the CRM and IEM.
The CRM and IEM form a solid basis for understanding the processes that occur within an ionisation chamber in a mass spectrometer. These models have been further developed to allow a better understanding of the competitive ionisation process that occurs in the presence of co-eluting components. The models also refine some of the original hypothesis of the underlying processes that are occurring. In particular the ion evaporation model has seen development to allow a better comparison with experimental data. Tang and Kebarle [16] further developed the Iribane and Thompson model proposing a model that related the ion evaporation rate to the concentration of the ion in the droplet. This model was further refined by Enke [17] who proposed using the ratio of equilibrium partitioning constants rather than the rate approach. The theory proposed by Enke looks at the competitive nature of the evaporation of the ions from the droplet state into the gas phase. This process is dependent on the concentration of ions at the surface of the droplet, which can be defined as follows;
KA [A+ Where KA Similarly [E+ KE = [E+
]s[X- X-
]s ]i
Representing the equilibrium of the analyte and electrolyte ions between the surface and interior of the droplet and;
[A+ ]s - concentration of ion A+
X- - counterions E+
- electrolyte ions
Q - concentration of the excess charge CA
CE - concentration of analyte at the surface
- concentration of electrolyte at the surface i - bulk concentration
at the surface = [A+ [A+
]s[X- X-
]s ]i ]s = CA
KA KE
/KE -1 + CE /[Q]
Several authors [17,18] have looked at the application of this equation to the effects of mobile phases but it has not been applied to the ion suppression associated with the competitive ions generated from the stationary phase.
Initial studies associated with the coupling of LC to MS suggested that there was little or no requirement for a separation prior to the detector. However, it was soon realised that coelution of components into the detector would result in a distortion of the process by which ions are formed [19,20,21].Since this observation, the phenomenon of ion suppression or enhancement, which is the reduction or increase of signal response from the MS, has become a major concern to analysts. Significant efforts are employed to reduce the number of components that coelute into the MS by pretreating the samples or employing a separation step. This is particularly the case with complex biological and environmental samples where a considerable number of matrix components are present.
Even with extraction and preconcentration procedures, a target analyte extracted from a complex matrix can still be affected by the remaining components of the matrix [22], as well as other sources. This will lead to inaccurate quantification. There are examples in the academic literature that demonstrate matrix-related effects such as with the analysis of morphine [22], and during the analysis of caffeine where a loss of background ESI signal was observed during repeated injections of a pretreated plasma sample [23]. Researchers have been developing protocols evaluating different sample clean-up methods to minimise matrix effects efficiently. This is achieved by taking account of the matrix types and focusing on the removal of the matrix component [24]. A few researchers have also looked at the contribution of other, method-related components to the levels of ion suppression, with the focus being on the contribution of vials, septa and the extraction consumables to the change in the signal intensity [25].
The use of electrospray has radically changed analytical chemistry, chemistry; however, this increase in analytical power has to be respected and understood to be used effectively. It is the responsibility of the separation scientist to ensure that due diligence is applied to the development of the assay, and that the data produced is truly reflective of what is in the original sample. This starts with the approach to sampling, and sample storage, and continues with the choice of an appropriate sample preparation and separation process to ensure that the detector is giving a response that matches the reality.
References
1. J. B. Fenn, ‘Ion Formation from Charged Droplets: Roles of Geometry, Energy, and Time,’ Journal of the American Society for Mass Spectrometry, vol. 4, no. 7, pp. 524-535, 1993.
2. B. X. Huang, H-Y Kim and C. Dass, ‘Probing three-dimensional structure of bovine serum albumin by chemical cross-linking and mass spectrometry,’ Journal of the American Society for Mass Spectrometry, vol. 15, no. 8, pp. 1237-1247, 2004.
3. Hua Xu, Liwen Zhang and Michael A. Freitas, ‘Identification and Characterization of Disulfide Bonds in Proteins and Peptides from Tandem MS Data by Use of the MassMatrix MS/MS Search Engine,’ Journal of Proteome Research, vol. 7, no. 01, pp. 138-144, 2008.
4. Walter L. Siqueira, Weimin Zhang, Eva J. Helmerhorst, Steven P. Gygi and Frank G. Oppenheim, ‘Identification of Protein Components in in vivo Human Acquired Enamel Pellicle Using LC−ESI−MS/MS’.
5. Atsushi Yamamoto, Naoya Kakutani, Kohji Yamamoto, Toshikazu Kamiura and Hidekazu Miyakoda, ‘Steroid Hormone Profiles of Urban
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