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Lysosomes are key degradative compartments of the cell. Transport to lysosomes relies on GlcNAc-1-phosphotransferase-mediated tagging of soluble enzymes with mannose 6-phosphate (M6P). GlcNAc-1-phosphotransferase deficiency leads to the severe lysosomal storage disorder mucolipidosis II (MLII). Several viruses require lysosomal cathepsins to cleave structural proteins and thus depend on functional GlcNAc-1-phosphotransferase. We used genome-scale CRISPR screens to identify lysosomal enzyme trafficking factor (LYSET, also named TMEM251) as essential for infection by cathepsin-dependent viruses including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). LYSET deficiency resulted in global loss of M6P tagging and mislocalization of GlcNAc-1-phosphotransferase from the Golgi complex to lysosomes. Lyset knockout mice exhibited MLII-like phenotypes, and human pathogenic LYSET alleles failed to restore lysosomal sorting defects. Thus, LYSET is required for correct functioning of the M6P trafficking machinery and mutations in LYSET can explain the phenotype of the associated disorder.

Ion-ion reactions are valuable tools in mass-spectrometry-based peptide and protein sequencing. To boost the generation of sequence-informative fragment ions from low charge-density precursors, supplemental activation methods, via vibrational and photoactivation, have become widely adopted. However, long-lived radical peptide cations undergo intramolecular hydrogen atom transfer from c-type ions to z • -type ions. Here we investigate the degree of hydrogen transfer for thousands of unique peptide cations where electron transfer dissociation (ETD) was performed and was followed by beam-type collisional activation (EThcD), resonant collisional activation (ETcaD), or concurrent infrared photoirradiation (AI-ETD). We report on the precursor charge density and the local amino acid environment surrounding bond cleavage to illustrate the effects of intramolecular hydrogen atom transfer for various precursor ions. Over 30% of fragments from EThcD spectra comprise distorted isotopic distributions, whereas over 20% of fragments from ETcaD have distorted distributions and less than 15% of fragments derived from ETD and AI-ETD reveal distorted isotopic distributions. Both ETcaD and EThcD give a relatively high degree of hydrogen migration, especially when D, G, N, S, and T residues were directly C-terminal to the cleavage site. Whereas all postactivation methods boost the number of c- and z • -type fragment ions detected, the collision-based approaches produce higher rates of hydrogen migration, yielding fewer spectral identifications when only c- and z • -type ions are considered. Understanding hydrogen rearrangement between c- and z • -type ions will facilitate better spectral interpretation.

Here we report the fragmentation of disulfide linked intact proteins using activated-ion electron transfer dissociation (AI-ETD) for top-down protein characterization. This fragmentation method is then compared to the alternative methods of beam-type collisional activation (HCD), electron transfer dissociation (ETD), and electron transfer and higher-energy collision dissociation (EThcD). We analyzed multiple precursor charge states of the protein standards bovine insulin, α-lactalbumin, lysozyme, β-lactoglobulin, and trypsin inhibitor. In all cases, we found that AI-ETD provides a boost in protein sequence coverage information and the generation of fragment ions from within regions enclosed by disulfide bonds. AI-ETD shows the largest improvement over the other techniques when analyzing highly disulfide linked and low charge density precursor ions. This substantial improvement is attributed to the concurrent irradiation of the gas phase ions while the electron-transfer reaction is taking place, mitigating nondissociative electron transfer, helping unfold the gas phase protein during the electron transfer event, and preventing disulfide bond reformation. We also show that AI-ETD is able to yield comparable sequence coverage information when disulfide bonds are left intact relative to proteins that have been reduced and alkylated. This work demonstrates that AI-ETD is an effective fragmentation method for the analysis of proteins with intact disulfide bonds, dramatically enhancing sequence ion generation and total sequence coverage compared to HCD and ETD.

High-throughput top-down proteomic experiments directly identify proteoforms in complex mixtures, making high quality tandem mass spectra necessary to deeply characterize proteins with many sources of variation. Collision-based dissociation methods offer expedient data acquisition but often fail to extensively fragment proteoforms for thorough analysis. Electron-driven dissociation methods are a popular alternative approach, especially for precursor ions with high charge density. Combining infrared photoactivation concurrent with electron transfer dissociation (ETD) reactions, i.e., activated ion ETD (AI-ETD), can significantly improve ETD characterization of intact proteins, but benefits of AI-ETD have yet to be quantified in high-throughput top-down proteomics. Here, we report the first application of AI-ETD to LC-MS/MS characterization of intact proteins (<20 kDa), highlighting improved proteoform identification the method offers over higher energy-collisional dissociation (HCD), standard ETD, and ETD followed by supplemental HCD activation (EThcD). We identified 935 proteoforms from 295 proteins from human colorectal cancer cell line HCT116 using AI-ETD compared to 1014 proteoforms, 915 proteoforms, and 871 proteoforms with HCD, ETD, and EThcD, respectively. Importantly, AI-ETD outperformed each of the three other methods in MS/MS success rates and spectral quality metrics (e.g., sequence coverage achieved and proteoform characterization scores). In all, this four-method analysis offers the most extensive comparisons to date and demonstrates that AI-ETD both increases identifications over other ETD methods and improves proteoform characterization via higher sequence coverage, positioning it as a premier method for high-throughput top-down proteomics.

Electron transfer dissociation (ETD) is a valuable tool for protein sequence analysis, especially for the fragmentation of intact proteins. However, low product ion signal-to-noise often requires some degree of signal averaging to achieve high quality MS/MS spectra of intact proteins. Here we describe a new implementation of ETD on the newest generation of quadrupole-Orbitrap-linear ion trap Tribrid, the Orbitrap Fusion Lumos, for improved product ion signal-to-noise via ETD reactions on larger precursor populations. In this new high precursor capacity ETD implementation, precursor cations are accumulated in the center section of the high pressure cell in the dual pressure linear ion trap prior to charge-sign independent trapping, rather than precursor ion sequestration in only the back section as is done for standard ETD. This new scheme increases the charge capacity of the precursor accumulation event, enabling storage of approximately 3-fold more precursor charges. High capacity ETD boosts the number of matching fragments identified in a single MS/MS event, reducing the need for spectral averaging. These improvements in intra-scan dynamic range via reaction of larger precursor populations, which have been previously demonstrated through custom modified hardware, are now available on a commercial platform, offering considerable benefits for intact protein analysis and top down proteomics. In this work, we characterize the advantages of high precursor capacity ETD through studies with myoglobin and carbonic anhydrase.

Here we report the first implementation of activated ion electron transfer dissociation (AI-ETD) for top down protein characterization, showing that AI-ETD definitively extends the m/z range over which ETD can be effective for fragmentation of intact proteins. AI-ETD, which leverages infrared photon bombardment concurrent to the ETD reaction to mitigate nondissociative electron transfer, was performed using a novel multipurpose dissociation cell that can perform both beam-type collisional dissociation and ion-ion reactions on an ion trap-Orbitrap hybrid mass spectrometer. AI-ETD increased the number of c- and z-type product ions for all charge states over ETD alone, boosting product ion yield by nearly 4-fold for low charge density precursors. AI-ETD also outperformed HCD, generating more matching fragments for all proteins at all charge states investigated. In addition to generating more unique fragment ions, AI-ETD provided greater protein sequence coverage compared to both HCD and ETD. In all, the effectiveness of AI-ETD across the entirety of the m/z spectrum demonstrates its efficacy for robust fragmentation of intact proteins.