Frequency chasing of individual megadalton ions in an Orbitrap analyzer improves precision of analysis in single molecule mass spectrometry

Abstract

To enhance the performance of charge detection mass spectrometry, we investigated the behavior of macromolecular single ions on their paths towards and within the Orbitrap analyzer. We discovered that ions in mass beyond one megadalton reach a plateau of stability and can be successfully trapped for seconds, travelling a path length of multiple kilometers, thereby enabling precise mass analysis with an effective resolution of greater than 100,000 at m/z 35,000. Through monitoring the frequency of individual ions, we show that these high mass ions, rather than being lost from the trap, can gradually lose residual solvent molecules and, in rare cases, a single elementary charge. Our observations highlight the importance of efficient desolvation for optimal charge detection mass spectrometry and inspired us to implement multiple improved data acquisition strategies. We demonstrate that the frequency drift of single ions due to desolvation and charge stripping can be corrected, which improves the effective ion sampling 23-fold and gives a two-fold improvement in mass precision and resolution, as demonstrated in the analysis of various viral particles.

UniDecCD: Deconvolution of Charge Detection-Mass Spectrometry Data

“…Previous publications have shown that the charge uncertainty is most likely due to collisions or dephasing of ions in the Orbitrap from ion−ion repulsion. 11,23 First, we set out to calibrate our Orbitrap mass analyzer for CD-MS data collection. In the Orbitrap, a single ion's image current is directly proportional to its charge, and prior studies have shown that they scale linearly.…”

“…The removal of the charge state uncertainty removed the artifact mass peaks and resulted in a single mass peak for GroEL that matched the conventional native mass spectrum (Figure 1H,C). Even with no charge state uncertainty, the peaks are slightly broader than their conventional native MS counterparts, and we expect that this loss of m/z resolution is due to frequency drifting of ions over the longer transient times used for CD-MS. 23 We then tested UCD on other proteins and protein complexes with known charge states: MSP1D1(−), BSA, and ADH. With UCD deconvolution, we were able to remove the charge uncertainty from the CD-MS spectra and confidently assign single charge states for MSP1D1(−), BSA, and ADH (Figure 2).…”

“…Our overall goal was to use computational deconvolution to reduce the charge uncertainty in CD-MS data. Previous publications have shown that the charge uncertainty is most likely due to collisions or dephasing of ions in the Orbitrap from ion–ion repulsion. , First, we set out to calibrate our Orbitrap mass analyzer for CD-MS data collection. In the Orbitrap, a single ion’s image current is directly proportional to its charge, and prior studies have shown that they scale linearly. , We therefore set out to create a calibration plot, similar to Wörner et al, that would convert a single ion’s intensity to charge.…”

“…Finally, the noise level is measured. In the Orbitrap, the main component of the noise is amplifier electrical noise, , and it is far more abundant than the chemical noise from ions. We tested several different ways to calculate the noise, including the median noise and the precalculated noise included in the Raw file .…”

Assessment of genome packaging in AAVs using Orbitrap-based charge detection mass spectrometry

“…Additionally, as higher mass ions seem to be more prone to peak splitting, such centroids will be removed more frequently in the signal filtering step, biasing the quantification of filled and empty capsids and furthermore, reducing sensitivity for high mass, low abundant ion species. These artifacts can be mitigated by reducing somewhat the transient recording time from 1024 to 512 ms, as demonstrated previously ( 8 ). The effect of a shortened transient time on the mass histogram is also shown in Supplemental Figure 1C, where we can see little to no difference between the unfiltered and filtered datasets, when recording for 512 ms.…”