Impact of Internal Fragments on Top-Down Analysis of Intact Proteins by 193 nm UVPD

Abstract

193 nm ultraviolet photodissociation (UVPD) allows high sequence coverage to be obtained for intact proteins using terminal fragments alone. However, internal fragments, those that contain neither N- nor C- terminus, are typically ignored, neglecting their potential to bolster characterization of intact proteins. Here, we explore internal fragments generated by 193 nm UVPD for proteins ranging in size from 17–47 kDa and using the ClipsMS algorithm to facilitate searches for internal fragments. Internal fragments were only retained if identified in multiple replicates in order to reduce spurious assignments and to explore the reproducibility of internal fragments generated by UVPD. Inclusion of internal fragment improved sequence coverage by an average of 18% and 32% for UVPD and HCD, respectively, across all proteins and charge states studied. However, only an average of 18% of UVPD internal fragments were identified in two out of three replicates relative to the average number identified across all replicates for all proteins studied. Conversely, for HCD, an average of 63% of internal fragments were retained across replicates. These trends reflect an increased risk of false-positive identifications and a need for caution when considering internal fragments for UVPD. Additionally, proton-transfer charge reduction (PTCR) reactions were performed following UVPD or HCD to assess the impact on internal fragment identifications, allowing up to 20% more fragment ions to be retained across multiple replicates. At this time, it is difficult to recommend the inclusion of the internal fragment when searching UVPD spectra without further work to develop strategies for reducing the possibilities of false-positive identifications. All mass spectra are available in the public repository jPOST with the accession number JPST001885.

Enhanced Characterization of Histones Using 193 nm Ultraviolet Photodissociation and Proton Transfer Charge Reduction

“…Examining the utility of internal fragment ions for characterization of histone sequences is also an attractive pursuit as they may offer additional support for the presence and localization of certain modifications. However, due to the increased risk of detecting false-positive fragment ion identifications, the use of an internal calibrant during data acquisition (e.g., Easy-IC option on the Fusion Lumos) is essential to ensure high mass accuracy (<2 ppm) of the fragment ions. , Finally, applying UVPD-PTCR to histones with more combinatorial modifications is underway. Demonstrating the probability of reducing ambiguous hits and quantifying PTMs are goals of future studies.…”

Enhancing Top-Down Analysis of Proteins by Combining Ultraviolet Photodissociation (UVPD), Proton-Transfer Charge Reduction (PTCR), and Gas-Phase Fractionation to Alleviate the Impact of Nondissociated Precursor Ions

“…PTCR has been previously been shown to be highly advantageous in countering spectral congestion when performing UVPD 28 while reducing the risk of false positive identifications. 22 Combining PUF + PTCR with additional fractionation of the fragment ion population further increases the signals of fragment ions while improving confidence in identifications. This extra enhancement upon subfractionation of the fragment ion population is attributed to reduced space charging and dephasing of lower abundance ions.…”

“…13,16,18 UVPD generates a variety of fragment ion types (a/x, b/y, and c/ z) 14,19−21 which offers great potential for comprehensive characterization of proteins, yet at the same time results in dense spectra and decreased signal-to-noise because the ion current is dispersed among so many fragmentation pathways. All of these MS/MS methods also produce multiple-generation fragment ions, particularly internal ions, 12,22 that increase in abundance and number when the activation conditions are modified to attain higher energy deposition. 23,24 A common conundrum of top-down analysis is that extensive fragmentation is needed to fully characterize protein sequences, identify mutations, and pinpoint sites of PTMs, yet at the same time the most dense, information-rich spectra often suffer from production of redundant fragment ions in multiple charge states and from overlapping isotope patterns of fragment ions, making them unassignable.…”

“…22,24,26,28,31−33 PTCR has been shown to allow more accurate and reliable deconvolution of internal fragment ions. 22 However, PTCR also may diminish the abundance of fragment ions by diluting their signals across multiple charge states. To counter this issue, ion parking 32 can be performed.…”

“…Addition of supplemental activation to electron-based methods, such as electron transfer higher-energy collisional dissociation (EThCD) or activated ion electron transfer dissociation (AI-ETD), counters the impact of the prevalent charge-reduction/no dissociation pathways, and has improved the ability to sequence and characterize larger proteins. ,, UVPD generates a variety of fragment ion types ( a / x , b / y , and c / z ) ,− which offers great potential for comprehensive characterization of proteins, yet at the same time results in dense spectra and decreased signal-to-noise because the ion current is dispersed among so many fragmentation pathways. All of these MS/MS methods also produce multiple-generation fragment ions, particularly internal ions, , that increase in abundance and number when the activation conditions are modified to attain higher energy deposition. , A common conundrum of top-down analysis is that extensive fragmentation is needed to fully characterize protein sequences, identify mutations, and pinpoint sites of PTMs, yet at the same time the most dense, information-rich spectra often suffer from production of redundant fragment ions in multiple charge states and from overlapping isotope patterns of fragment ions, making them unassignable. Furthermore, achieving the highest sequence coverage to maximize the characterization of large proteins requires significant spectral averaging, a factor that confounds high throughput analysis required for LC time scales.…”