For a typical MALDI analysis, solutions of a sample (pure or a mixture; ~10 µM) and matrix (~10 mM) are pre-mixed and a small volume (~1 µl) is applied directly to the sample plate. (The matrix is selected such that it has a large extinction coefficient at the emission wavelength of the laser.) The solvent is generally allowed to evaporate at room temperature and pressure to yield a heterogeneous crystalline surface. Inside the mass spectrometer the laser is pulsed onto the crystalline surface and the matrix immediately sublimes, concomitantly desorbing and ionizing the analyte molecules. The m/z values for the analyte ions are then measured. The MALDI mass spectrum is a plot of intensities on the ordinate axis and the corresponding mass/charge values on the x-axis. The intensity scale is the relative abundance of ions, but generally the region below about m/z 500 is not shown because it is saturated with signals from matrix-derived ions. MALDI mass spectra of pure compounds are normally dominated by a single ion corresponding to the protonated molecule; multiply charged ions are rare, except for very large molecules and even then they are usually of low relative abundance. MALDI spectra of mixtures typically show multiple ions corresponding to the protonated forms of some if not all of the molecular components present in the sample. It is noteworthy that peak heights for equimolar loadings of different analytes may vary significantly. The proclivity of MALDI to yield singly charged ions is in contrast to electrospray and offers significant advantages in quantification, especially for mixtures.
Characteristically, there is substantial variability in the noise level, baseline and peak intensities in a collection of MALDI spectra generated from the same sample. Variations in ion current are observed with consecutive laser shots fired at the same position on the target surface (shot-to-shot reproducibility), across different locations on the target surface (region-to-region reproducibility) and between identical loadings of the same sample onto different targets (sample-to-sample reproducibility). To minimize this variability, multiple spectra are usually acquired from different locations across the target surface and these are averaged (or added) to yield a more representative spectrum.
Fluctuations in laser power and changes in detector response alter signal intensity, but the primary contributor to variability is heterogeneous incorporation of the analyte into the co-crystallized matrix–analyte complex. This results in ‘hot-spots’ on the target surface where the ratio of analyte to matrix is optimal and where the analyte signal is high relative to other locations. This variability can be circumvented, at least in part, by pre-mixing the sample and matrix solutions and by facilitating faster crystallization times. Faster crystallization generates smaller crystals and a more homogeneous incorporation of the analytes into the crystalline lattice. For example, when 2,5-dihydroxybenzoic acid (DHB) is allowed to crystallize slowly (i.e. from predominantly aqueous solutions at room temp and pressure) large needle-like crystals form and sample incorporation is highly variable. When crystallization is rapid (i.e. when the matrix is prepared in a volatile solvent and/or the target is dried at elevated temperature and/or reduced pressure) the resulting crystals are small and crystallization of the analyte–matrix is much more uniform [2
Competitive ionization/ion suppression is an additional factor that can obliterate any attempt to quantify by MALDI, especially in complex samples. In a mixture, some analytes will have higher affinities for charge than others (e.g. R-terminated peptides > K-terminated peptides) and will more successfully compete for the available protons [3
]. Therefore, when quantifying across a series of samples it is essential to keep the sample composition (or sample matrix) constant. Sample preparation methods should aim to reduce the complexity of the sample, thereby minimizing the background and eliminating potentially interfering peaks, but at the same time, these methods must be highly reproducible and minimize the potential to introduce contaminants that result in higher variability and adversely influence signal intensity (i.e. ion suppression). Although ion suppression is not unique to MALDI, in electrospray LC-MS applications online separation helps minimize the potential for other sample components to influence the ion current of the target analyte. In contrast, few quantitative MALDI applications employ ‘online’ separation of the analytes; rather, multiple analytes are present on the target at the same time and actively compete for the available charge for each desorption/ionization event (i.e. laser shot).
There are, however, several very positive attributes of MALDI, not the least of which is its sensitivity. There have been several estimates of the amount of material required to generate a spectrum, but it is clear that attomoles or less are sufficient to generate a good quality spectrum [4
]. A quick survey of the literature also illustrates the remarkable versatality of this ionization method: i.e. thermally labile, low mass analytes; involatile, high mass biopolymers; even alkanes and polyethylenes [5
] can all be ionized by MALDI. Additional advantages of the approach include the ability to analyse complex mixtures, the potential for high-throughput, the speed of the analysis, ease of automation and the low cost per analysis.
In summary, MALDI offers some important attributes, but its application to quantitative analysis requires careful optimization of the experimental parameters and a good understanding of how confounding factors could compromise a study. In particular, sample preparation (e.g. choice of matrix compound, concentration, solvents and crystallization conditions) is critical and must be optimized in order to reduce the variability introduced during this step. It is also important to acquire and average many single-shot spectra from several positions within a given sample spot to gain representative sample data. Ideally, the laser power should be automatically adjusted to limit the acceptable analyte and internal standard signal intensity to below saturation, but above background noise. Consequently, criteria for spectral acceptance based on minimum and maximum peak height and the signal-to-noise ratio should be established and adhered to before the spectra are averaged.