| Title |
Sequencing Larger Intact Proteins (30-70 kDa) with Activated Ion Electron Transfer Dissociation
|
|---|---|
| Published in |
Journal of the American Society for Mass Spectrometry, October 2017
|
| DOI | 10.1007/s13361-017-1808-7 |
| Pubmed ID | |
| Authors |
Nicholas M. Riley, Michael S. Westphall, Joshua J. Coon |
| Abstract |
The analysis of intact proteins via mass spectrometry can offer several benefits to proteome characterization, although the majority of top-down experiments focus on proteoforms in a relatively low mass range (<30 kDa). Recent studies have focused on improving the analysis of larger intact proteins (up to ~75 kDa), but they have also highlighted several challenges to be addressed. One major hurdle is the efficient dissociation of larger protein ions, which often to do not yield extensive fragmentation via conventional tandem MS methods. Here we describe the first application of activated ion electron transfer dissociation (AI-ETD) to proteins in the 30-70 kDa range. AI-ETD leverages infrared photo-activation concurrent to ETD reactions to improve sequence-informative product ion generation. This method generates more product ions and greater sequence coverage than conventional ETD, higher-energy collisional dissociation (HCD), and ETD combined with supplemental HCD activation (EThcD). Importantly, AI-ETD provides the most thorough protein characterization for every precursor ion charge state investigated in this study, making it suitable as a universal fragmentation method in top-down experiments. Additionally, we highlight several acquisition strategies that can benefit characterization of larger proteins with AI-ETD, including combination of spectra from multiple ETD reaction times for a given precursor ion, multiple spectral acquisitions of the same precursor ion, and combination of spectra from two different dissociation methods (e.g., AI-ETD and HCD). In all, AI-ETD shows great promise as a method for dissociating larger intact protein ions as top-down proteomics continues to advance into larger mass ranges. Graphical Abstract ᅟ. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 20% |
| Poland | 1 | 20% |
| Unknown | 3 | 60% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 60% |
| Scientists | 1 | 20% |
| Science communicators (journalists, bloggers, editors) | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 61 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 23 | 38% |
| Researcher | 7 | 11% |
| Student > Bachelor | 5 | 8% |
| Student > Doctoral Student | 4 | 7% |
| Student > Master | 4 | 7% |
| Other | 8 | 13% |
| Unknown | 10 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 21 | 34% |
| Biochemistry, Genetics and Molecular Biology | 13 | 21% |
| Unspecified | 3 | 5% |
| Agricultural and Biological Sciences | 3 | 5% |
| Psychology | 1 | 2% |
| Other | 2 | 3% |
| Unknown | 18 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 February 2018.
All research outputs
#15,097,241
of 25,382,440 outputs
Outputs from Journal of the American Society for Mass Spectrometry
#2,265
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Outputs of similar age
#172,278
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Outputs of similar age from Journal of the American Society for Mass Spectrometry
#16
of 59 outputs
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