scholarly journals Note: Integration of trapped ion mobility spectrometry with mass spectrometry

2011 ◽  
Vol 82 (12) ◽  
pp. 126106 ◽  
Author(s):  
F. A. Fernandez-Lima ◽  
D. A. Kaplan ◽  
M. A. Park
Keyword(s):  
Mass Spectrometry ◽  
Ion Mobility Spectrometry ◽  
Ion Mobility ◽  
Trapped Ion ◽  
Trapped Ion Mobility Spectrometry

scholarly journals AlphaTims: Indexing trapped ion mobility spectrometry - time of flight data for fast and easy accession and visualization

2021 ◽  
Author(s):  
Sander Willems ◽  
Eugenia Voytik ◽  
Patricia Skowronek ◽  
Maximilian T Strauss ◽  
Matthias Mann
Keyword(s):  
Mass Spectrometry ◽  
Open Source ◽  
Ion Mobility Spectrometry ◽  
Ion Mobility ◽  
Large Scale ◽  
High Resolution Mass Spectrometry ◽  
Time Of Flight ◽  
Arrival Times ◽  
Trapped Ion ◽  
Trapped Ion Mobility Spectrometry

High resolution mass spectrometry-based proteomics generates large amounts of data, even in the standard liquid chromatography (LC) - tandem mass spectrometry configuration. Adding an ion mobility dimension vastly increases the acquired data volume, challenging both analytical processing pipelines and especially data exploration by scientists. This has necessitated data aggregation, effectively discarding much of the information present in these rich data sets. Taking trapped ion mobility spectrometry (TIMS) on a quadrupole time-of-flight platform (Q-TOF) as an example, we developed an efficient indexing scheme that represents all data points as detector arrival times on scales of minutes (LC), milliseconds (TIMS) and microseconds (TOF). In our open source AlphaTims package, data are indexed, accessed and visualized by a combination of tools of the scientific Python ecosystem. We interpret unprocessed data as a sparse 4D matrix and use just-in-time compilation to machine code with Numba, accelerating our computational procedures by several orders of magnitude while keeping to familiar indexing and slicing notations. For samples with more than six billion detector events, a modern laptop can load and index raw data in about a minute. Loading is even faster when AlphaTims has already saved indexed data in a HDF5 file, a portable scientific standard used in extremely large-scale data acquisition. Subsequently, data accession along any dimension and interactive visualization happen in milliseconds. We have found AlphaTims to be a key enabling tool to explore high dimensional LC-TIMS-QTOF data and have made it freely available as an open-source Python package with a stand-alone graphical user interface at https://github.com/MannLabs/alphatims or as part of the AlphaPept ecosystem.

scholarly journals Trapped Ion Mobility Spectrometry Reduces Spectral Complexity in Mass Spectrometry Based Workflow

2021 ◽  
Author(s):  
Joshua Charkow ◽  
Hannes Rost
Keyword(s):  
Mass Spectrometry ◽  
Ion Mobility Spectrometry ◽  
Ion Mobility ◽  
Peptide Identification ◽  
Peptide Ions ◽  
Trapped Ion ◽  
Data Independent Acquisition ◽  
Window Width ◽  
Trapped Ion Mobility Spectrometry ◽  
Collisional Cross Section

In bottom-up mass spectrometry based proteomics, deep proteome coverage is limited by high cofragmentation rates. This occurs when more than one analyte is isolated by the quadrupole and the subsequent fragmentation event produces fragment ions of heterogeneous origin. One strategy to reduce cofragmentation rates is through effective peptide separation techniques such as chromatographic separation and, the more recently popularized, ion mobility (IM) spectrometry which separates peptides by their collisional cross section. Here we investigate the capability of the Trapped Ion Mobility Spectrometry (TIMS) device to effectively separate peptide ions and quantify the separation power of the TIMS device in the context of a Parallel Accumulation-Serial Fragmentation (PASEF) workflow. We found that TIMS IM separation increases the number of interference-free MS1 features 9.2-fold, while decreasing the average peptide density in precursor spectra 6.5 fold. In a Data Dependent Acquisition (DDA) PASEF workflow, IM separation increased the number of spectra without cofragmentation by a factor of 4.1 and the number of high quality spectra 17-fold. This observed decrease in spectral complexity results in a substantial increase in peptide identification rates when using our data-driven model. In the context of a Data Independent Acquisition (DIA), the reduction in spectral complexity resulting from IM separation is estimated to be equivalent to a 4-fold decrease in isolation window width (from 25Da to 6.5Da). Our study shows that TIMS IM separation dramatically reduces cofragmentation rates leading to an increase in peptide identification rates.

Identification of Lasso Peptide Topologies Using Native Nanoelectrospray Ionization-Trapped Ion Mobility Spectrometry–Mass Spectrometry

2018 ◽  
Vol 90 (8) ◽  
pp. 5139-5146 ◽  
Author(s):  
Kevin Jeanne Dit Fouque ◽  
Javier Moreno ◽  
Julian D. Hegemann ◽  
Séverine Zirah ◽  
Sylvie Rebuffat ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Ion Mobility Spectrometry ◽  
Ion Mobility ◽  
Trapped Ion ◽  
Lasso Peptide ◽  
Trapped Ion Mobility Spectrometry ◽  
Nanoelectrospray Ionization

Tandem‐trapped ion mobility spectrometry/mass spectrometry coupled with ultraviolet photodissociation

2021 ◽  
Vol 35 (22) ◽  
Author(s):  
Fanny C. Liu ◽  
Mark E. Ridgeway ◽  
J. S. Raaj Vellore Winfred ◽  
Nicolas C. Polfer ◽  
Jusung Lee ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Ion Mobility Spectrometry ◽  
Ion Mobility ◽  
Trapped Ion ◽  
Ultraviolet Photodissociation ◽  
Trapped Ion Mobility Spectrometry
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