Chapter 1
Contemporary Protein Analysis by Ion Mobility Mass Spectrometry

Johannes P.C. Vissers and James I. Langridge

Waters Corporation, Wilmslow, UK

1.1 Introduction

The use of ion mobility as an analytical technique to detect and separate biomolecules dates back to the break of the century with the application of the method for proteomics (Valentine et al. 2006; McLean et al. 2005; Gabryelski and Froese 2003), glycomics (Taraszka et al. 2001; Jin et al. 2005; Hoaglund et al. 1997), and metabolomics (Dwivedi et al. 2008). It is a technique that separates gas-phase ions based upon their mobility in a buffer gas. This separation is related to ion size, shape, as well as m/z, and charge. The basis for separation by traditional drift tube ion mobility at a low electric limit can be derived from the Mason-Schamp equation:

where K = drift velocity vd/electric field strength E, µ = reduced mass of the ion (neutral given by (mneutralmion)/(mneutral + mion), kB = Boltzmann constant, T = temperature, z = charge state of the analyte ion, e = charge on an electron, N = number density of the drift gas, and O = average collision cross section. The hyphenation of ion mobility spectrometry (IMS) with MS is often referred to as ion mobility-mass spectrometry (IM-MS). The most common mass analyzer coupled with IMS comprises a time-of-flight (TOF) instrument due to the inherent high sampling rate, although other mass detection systems have been described (Kanu et al. 2008). Four different methods of ion mobility separation are currently used in combination with MS, including drift-time ion mobility spectrometry (DTIMS), aspiration ion mobility spectrometry (AIMS), differential mobility spectrometry (DMS), also called field-asymmetric waveform ion mobility spectrometry (FAIMS), and traveling-wave ion mobility spectrometry (TWIMS). A description of these methods is beyond the scope of this chapter, particularly since they have been reviewed in great detail elsewhere (Kanu et al. 2008; Lanucara et al. 2014).

The innovative demonstration of protein conformer separation by means of IMS by Clemmer et al. 1995 has prompted instrumental IM-MS designs and the broader application of IMS as an analytical tool. The designs by Pringle et al. 2007 and Baker et al. 2007, both orthogonal acceleration time-of-flight (oa-TOF) based IM-MS platform, but utilizing different IMS geometries, have been commercialized and applied for numerous applications and include drug metabolism/metabolites (Dear et al. 2010), lipids (Kliman et al. 2011), trace impurities (Eckers et al. 2007), carbohydrates (Vakhrushev et al. 2008, Schenauer et al. 2009), macromolecular protein species and viruses (Ruotolo et al. 2005, Bereszczak et al. 2014), metal-based anticancer drugs (Williams et al. 2009), and PEGylated conjugates (Bagal et al. 2008). In this chapter, the application of IMS for the identification, quantification, and characterization of proteins is illustrated by application examples that demonstrate the benefits of integrating IMS into the analytical schema in terms of increased resolution and sensitivity, as well as those obtained from collision cross section measurements.

1.2 Traveling-Wave Ion Mobility Mass Spectrometry

The principle of TWIMS is briefly discussed as it forms the basis of subsequent sections. A schematic of the device is shown in Figure 1.1. Details can be found in the papers of Pringle et al. 2007 and Giles et al. 2004. Ions are formed by electrospray ionization (ESI) in the source and subsequently pass through a quadrupole for mass selection before injection into the ion mobility cell. Unlike our other instruments, which use a uniform electric field across the cell for ion mobility experiments, so-called drift tube IMS, this device uses traveling-wave (T-wave) technology. The T-wave cell consists of a stacked-ring radio frequency (RF) ion guide, which incorporates a repeating sequence of transient voltages applied to the ring electrodes. These voltage pulses result in a traveling electric field that propels ions through the background gas present in the mobility cell. The total time taken for an ion to drift through the cell depends on its mobility, as well as the wave period and height, and the gas pressure. Ions with high mobility are better able to keep up with traveling waves and are pushed more quickly through the cell. Ions with low mobility crest over the waves more often and have to wait for subsequent waves to push them forward, resulting in longer drift times. To measure an arrival time distribution (ATD), ions are gated into the mobility cell using an up-front stacked-ring RF device that traps ions before releasing them into the IMS cell. The oa-TOF pulses in an asynchronous manner, sending ions that have exited the mobility cell into the TOF mass analyzer and finally to the detector. The sum of all detected ions is the ion mobility chromatogram, or mobilogram. Selecting a peak in the ion mobility chromatogram displays the underlying TOF mass spectrum. Resolution enhancements to the device are recently described (Giles et al. 2011).

Figure 1.1 Triwave ion mobility optics detail comprising a trap, helium cell, ion mobility separator and transfer.

(Source: Williams et al. 2012. Reproduced with permission of GIT.)

1.3 IM-MS and LC-IM-MS Analysis of Simple and Complex Mixtures

1.3.1 Cross Section and Structure

By measuring the mobility of an ion, information about the rotationally averaged collision cross section, which is given by shape and size, can be determined. The relationship between the mobility of an ion and its collision cross section has been derived in detail using kinetic theory (Mason and McDaniel 1988). When all experimental IM parameter values are held constant, a dependence of the ion mobility constant results only from the average cross section with K ~ 1/O (1996; Bowers et al./>; Henderson et al. 1999; Verbeck et al. 2002), where K = drift velocity vd/electric field strength E and O = average collision cross section. A detailed description of kinetic theory is beyond the scope of this discussion. Ruotolo et al. 2005 were among the first describing the use of IM-MS to decipherer protein complex structure. The analysis of the Trp RNA-binding attenuation protein (TRAP) provided compelling evidence that many features of protein assemblies, including quaternary structure, can be preserved in the absence of solvent molecules. The researchers made use of TWIMS coupled to a modified TOF mass spectrometer to measure the CCS of four charge states of an 11-mer complex, demonstrating that the lowest charge state exhibited the largest CCS, with a value in close agreement to that estimated for a ring structure determined by X-ray crystallography. To investigate the sensitivity of the various conformers to changes in internal energy, they examined collision cross sections of the apo TRAP complex as a function of activation energy by manipulating their acceleration in the atmospheric pressure interface of the instrument, shown in Figure 1.2. The experiment illustrated that when an internal energy is imparted to 22+ ions, an expansion of the collapsed state occurred, while for 19+ ions they could partially drive the structural transitions observed for the ring structure as a function of protein charge state. IM-MS has proved to be extremely useful for the structural analysis of proteins and protein assemblies as illustrated in a number of recent reviews (Lanucara et al. 2014; Zhong et al. 2012; Uetrecht et al. 2010; Snijder and Heck 2014).

Figure 1.2 Ion mobility data for selected charge states of apo-TRAP (19+, 21+, and 22+) as a function of activation energy (175, 125, and 50 V) applied in the high-pressure, sampling cone region of the instrument. The light gray and dark gray dashed lines represent the collision cross sections for collapsed and ring structures. (

(Source: Ruotolo et al. 2005. Reproduced with permission of The American Association for the Advancement of Science.)

Collision cross section measurements and structure IM-MS experiments are not restricted to the analysis of large molecules but have been applied to other molecule classes and applications as well. For example, Valentine et al. 1999 used IMS to measure collision cross sections for 660 peptide ions generated by tryptic digestion proteins. Measured cross sections were compiled into a database that contains peptide molecular weight and sequence information and can be used to generate average intrinsic contributions to cross section for different amino acid residues. This was achieved by relating unknown contributions of individual residues to the sequences and cross sections of database peptides. Size parameters were combined with information about amino acid composition to calculate cross sections for database peptides. Figures 1.3(a) and (b) summarize the work showing cross sections as a function of molecular weight for the singly and doubly charged database peptides, respectively (Valentine et al. 1999). A strong correlation of increasing cross section with increasing molecular weight was observed, suggesting that (predicted) cross section can be used as an additional search parameter for peptide identification. A follow-up study proposed that the method that employs intrinsic amino acid size parameters to obtain ion mobility predictions can be used to rank candidate peptide ion...