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Future directions for electrospray ionization for biological analysis using mass spectrometry
 
Richard D. Smith
Pacific Northwest National Laboratory, Richland, WA, USA
BioTechniques, Vol. 41, No. 2, August 2006, pp. 147–148
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When John Fenn and coworkers first realized Malcolm Dole's dream of electrospray ionization (ESI) (1), the broad impact it would ultimately have was not obvious to most researchers working in the (admittedly much smaller) field at the time (2). Indeed, between his first publication in 1984 and ground breaking report in 1988 that described ESI-mass spectrometry (ESI-MS) as a tool for analyzing large proteins (3), my laboratory was one of the very few (and perhaps the only?) working with ESI-MS (4). After Fenn's 1988 seminal publication, the MS community broadly recognized the potential of ESI-MS for providing the long sought effective interface between liquid chromatography (LC) separations and MS that would allow a large range of previously intractable biomolecules to be studied.

Over the last 20+ years, the range and types of ESI-MS applications has expanded in a breathtaking fashion to include essentially every class of biomolecules and, for example, the characterization of extremely large noncovalently associated protein complexes. As a result of its sensitivity, now broad availability, and applicability, ESI-MS has become a dominant analytical tool for areas of biological research such as proteomics, which is the study of the array of proteins in an organism, tissue, or cell at a given time. Its ability to broadly measure biological macromolecules, especially proteins, can play an important role in delineating complex cellular networks and pathways, as well as in a range of other applications, such as candidate biomarker discovery efforts.

In this context it is fair to ask, what's next? Will ESI be displaced by some other method of ionization or LC-MS interfacing? Are there important new developments still to come? Of course, the possibility of completely new approaches—”disruptive” new technologies that revolutionize how we work—should never be excluded. By their nature, one cannot predict such developments, but we can more reasonably speculate on, and more reliably predict, the impact of more evolutionary developments that arise from the naturally selective process of on-going focused efforts. I believe that such forces, involving ESI driven by the need for more sensitive and better quantitative measurements, are now at play in ways that will greatly expand its utility for biological applications.

The need for greater sensitivity to better detect, identify, and quantify biomolecules in proteomics is essentially open-ended; every improvement enables new applications. For example, the ability to make comprehensive proteomic measurements generally depends on the sample size, as well as on both the sensitivity and dynamic range of measurements. Improvements in measurement sensitivity can enable different approaches (e.g., for characterizing microdissected cells, microbiopsies, or even single cells), while extensions to the range of measurable protein abundances can facilitate identification of disease specific biomarkers (e.g., from blood) and provide the basis for new clinical assays. However, it is often necessary to resort to a “divide and conquer” sample fractionation strategy to obtain sufficient depth of proteome coverage (i.e., measurement dynamic range). Indeed, the real limitations to achieving sufficient depth with present proteome measurements are essentially derived from considerations associated with the amount of sample available and the sensitivity of the measurements methods. When the sample size is very small, and fractionation steps, etc., must be either minimized or eliminated to conserve the sample, measurement sensitivity becomes the limiting factor.

The overall sensitivity of ESI-MS is limited by factors that include both ionization efficiency and ion transmission efficiency into and through the MS analyzer. At the liquid flow rates of conventional LC separations, ESI-MS response typically appears concentration-sensitive rather than mass-sensitive; that is, increasing the flow rate does not greatly increase the signal (5). However, as flow rates are lowered, the smaller charged droplets generated by an electrospray result in increased ionization efficiency (i.e., transfer of an ion from solution to the gas phase) and also permit the ESI emitter to be positioned closer to the MS inlet to allow more efficient transport to the MS analyzer, both of which provide increased sensitivity (6,7). For example, ESI-MS analyses that used flow rates of approximately 20 nL/min demonstrated significantly increased sensitivity (8) compared with flow rates typically applied with LC separations (7). The overall predicted efficiency for converting analyte ions from solution to gas phase approaches 100% when both the liquid flow rate and analyte concentration are sufficiently low (9). Additionally, smaller inner diameter (i.d.) columns with lower flow rates provide higher sensitivity than larger i.d. columns with higher flow rates (10). As ionization efficiencies are increased to produce nano-electrosprays, detection biases are also decreased since undesired matrix effects and/or ionization suppression effects are either reduced or eliminated, which can significantly improve quantitation. The use of 10 µm i.d. silica-based monolithic LC columns (11) providing flow rates on the order of 10 nL/min (i.e., nano-flow) has been shown to both increase sensitivity and improve quantitation.

Comparisons of the relative abundances of different proteins, and quantitative approaches in general, are improved by minimizing variations in ESI response. An advantage of low flow rate separations is that compound-to-compound variations in MS response are minimized, thus providing an improved basis for label-free quantitative measurements. In label-free analyses, LC-MS peak intensities for the same species are compared among different analyses (12), often following normalization to attempt to account for variations in sample quantity and/or instrument performance between analyses. These types of analyses are very sensitive to differences in ionization efficiencies between different species, ionization suppression, matrix effects in ESI that cause nonlinear responses with abundance, and to different detection efficiencies for different species (13). Analyses performed with even the smallest column bore diameter commonly used for capillary LC can result in significant compound-to-compound variations and nonlinear ESI-MS responses, particularly at higher concentrations. Under these conditions, differences in LC-MS peak intensities may not correctly reflect changes in abundance.

Present MS instrumentation is increasingly able to make the most of nanoLC-nanoESI performance. Early ESI-MS instruments suffered due to inefficient ion transmission to the detector. Generally, the greatest ion losses occur in higher pressure regions of the MS (i.e., closest to the ESI source). By using collisional focusing at pressures of <10−2 Torr in radio frequency (RF) ion guides (14), >50% ion transmission efficiency can now be achieved, which means a well-designed mass spectrometer can have overall ion transmission and detection efficiencies in its intermediate-to-lower pressure regions that significantly exceed 10%. The electrodynamic ion funnel has proven highly effective for minimizing loses through the first MS vacuum stage (typically at a pressure of 1–5 Torr) (15); ion transmission efficiency through the funnel is essentially 100% over a wide mass-to-charge ratio (m/z) range. As a result, the extent to which ions are efficiently utilized in analyses is then dictated by the type of instrument and operational details; for example, Belov et al. (16) showed overall ion utilization (from ionization through detection) of 7%–10% that provided low zeptomole detection limits for proteins analyzed by Fourier-transform ion cyclotron resonance (FTICR) instrumentation. Another improvement has derived from the use of automated gain control (AGC) with ion trapping instrumentation, which constrains ion populations in ion traps (e.g., quadrupole and FTICR) to levels that maintain the desired mass measurement accuracy. The greatest sensitivity for these instruments is obtained for LC separation fractions that provide the lowest signal intensities (where accumulation times are longest). Highly abundant species tend to shorten useful accumulation times and thus preclude detection of otherwise detectable low abundance species in the same spectrum. Since the present maximum ion transmission rates from an ESI source (>108 charge/s) can exceed FTICR capacity by >100-fold, potentially useful signal is often wasted. Application of the dynamic range enhancement applied to mass spectrometry (DREAMS) method is a powerful tactic for overcoming wasted signal (17). With DREAMS, a normal mass spectrum is followed by a spectrum in which the most abundant ions detected in the previous spectrum are removed. As a result, the overall dynamic range can be extended by >10-fold, which in turn provides large increases in proteome coverage.

Finally, I believe that the ultimate limitations for ESI-MS analyses stem from the number of ions that can be analyzed in a given time frame. Too few ions, even for the most effective analyzers, limit the quality of the data in addition to the depth and speed of the analysis. New developments, such as multi-emitter nanoESI sources (18), can potentially increase the dynamic range of measurements and indirectly provide higher analysis throughput. Perhaps more importantly, such approaches present opportunities for greatly enhancing the quantitative value of measurements, but at higher and easier to use liquid flow rates. Such developments will continue to expand the role of ESI-MS in biological research and, increasingly, extend its use in important clinical applications.

Acknowledgments

I thank the U.S. Department of Energy (DOE) Office of Biological and Environmental Research for long-term research support, as well as the National Institutes of Health, through the National Center for Research Resources (RR018522) for support of my research.

References
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