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Amphitrite: A program for processing travelling wave ion mobility mass spectrometry data.

Sivalingam GN, Yan J, Sahota H, Thalassinos K - Int J Mass Spectrom (2013)

Bottom Line: We present a novel software package that enables the processing of T-Wave ion mobility data.It can also be used to automatically create a collision cross section (CCS) calibration and apply this to subsequent files of interest.A number of applications of the software, and how it enhances the information content extracted from the raw data, are illustrated using model proteins.

View Article: PubMed Central - PubMed

Affiliation: Institute of Structural and Molecular Biology, Division of Biosciences, University College London, London, UK.

ABSTRACT

Since the introduction of travelling wave (T-Wave)-based ion mobility in 2007 a large number of research laboratories have embraced the technique, particularly those working in the field of structural biology. The development of software to process the data generated from this technique, however, has been limited. We present a novel software package that enables the processing of T-Wave ion mobility data. The program can deconvolute components in a mass spectrum and uses this information to extract corresponding arrival time distributions (ATDs) with minimal user intervention. It can also be used to automatically create a collision cross section (CCS) calibration and apply this to subsequent files of interest. A number of applications of the software, and how it enhances the information content extracted from the raw data, are illustrated using model proteins.

No MeSH data available.


IM-MS analysis of a mixture of BSA, concanavalin A and alcohol dehydrogenase. The mass spectrum was deconvoluted into its component parts (panel C), with the raw arrival time distribution shown in panel B. Using the deconvolution data and CCS calibration (like that shown in Fig. 2), the raw arrival times can be separated and converted into CCS vs. m/z information for each molecular component (panel A). The colouring is consistent between panel A and C (concanavalin A monomer – red, dimer – blue, tetramer – purple, BSA monomer – green, dimer – brown, ADH tetramer – magenta).
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fig0020: IM-MS analysis of a mixture of BSA, concanavalin A and alcohol dehydrogenase. The mass spectrum was deconvoluted into its component parts (panel C), with the raw arrival time distribution shown in panel B. Using the deconvolution data and CCS calibration (like that shown in Fig. 2), the raw arrival times can be separated and converted into CCS vs. m/z information for each molecular component (panel A). The colouring is consistent between panel A and C (concanavalin A monomer – red, dimer – blue, tetramer – purple, BSA monomer – green, dimer – brown, ADH tetramer – magenta).

Mentions: The user then selects peaks corresponding to sequential charge state peaks of a particular species. The mass of the species is calculated using the m/z values of the peak tops. The theoretical m/z values for charge states are calculated (default 1+ to 100+) and are displayed as vertical markers along with the calculated mass and error (Fig. 1D). Both of these features help to ensure that peaks were correctly identified, as incorrect peak picking would result in misaligned theoretical charge states and large mass errors. The user then supplies the charge range to simulate, based on charge state ion peak intensities. After this process has been completed for each species, the program can fit simulated data to the supplied spectrum using least squares optimisation with the result shown in Fig. 1C. If the user then notices that a species was missed, it can be added to the simulation by following the steps described above. The data simulation algorithm can identify and deconvolve overlapping peaks and peak shoulders (see examples in Fig. 4C). An additional benefit of this feature is that it allows one to estimate the integrals of individual species with small mass differences, which can provide a more accurate measure of the peak intensity for overlapping peaks.


Amphitrite: A program for processing travelling wave ion mobility mass spectrometry data.

Sivalingam GN, Yan J, Sahota H, Thalassinos K - Int J Mass Spectrom (2013)

IM-MS analysis of a mixture of BSA, concanavalin A and alcohol dehydrogenase. The mass spectrum was deconvoluted into its component parts (panel C), with the raw arrival time distribution shown in panel B. Using the deconvolution data and CCS calibration (like that shown in Fig. 2), the raw arrival times can be separated and converted into CCS vs. m/z information for each molecular component (panel A). The colouring is consistent between panel A and C (concanavalin A monomer – red, dimer – blue, tetramer – purple, BSA monomer – green, dimer – brown, ADH tetramer – magenta).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4375678&req=5

fig0020: IM-MS analysis of a mixture of BSA, concanavalin A and alcohol dehydrogenase. The mass spectrum was deconvoluted into its component parts (panel C), with the raw arrival time distribution shown in panel B. Using the deconvolution data and CCS calibration (like that shown in Fig. 2), the raw arrival times can be separated and converted into CCS vs. m/z information for each molecular component (panel A). The colouring is consistent between panel A and C (concanavalin A monomer – red, dimer – blue, tetramer – purple, BSA monomer – green, dimer – brown, ADH tetramer – magenta).
Mentions: The user then selects peaks corresponding to sequential charge state peaks of a particular species. The mass of the species is calculated using the m/z values of the peak tops. The theoretical m/z values for charge states are calculated (default 1+ to 100+) and are displayed as vertical markers along with the calculated mass and error (Fig. 1D). Both of these features help to ensure that peaks were correctly identified, as incorrect peak picking would result in misaligned theoretical charge states and large mass errors. The user then supplies the charge range to simulate, based on charge state ion peak intensities. After this process has been completed for each species, the program can fit simulated data to the supplied spectrum using least squares optimisation with the result shown in Fig. 1C. If the user then notices that a species was missed, it can be added to the simulation by following the steps described above. The data simulation algorithm can identify and deconvolve overlapping peaks and peak shoulders (see examples in Fig. 4C). An additional benefit of this feature is that it allows one to estimate the integrals of individual species with small mass differences, which can provide a more accurate measure of the peak intensity for overlapping peaks.

Bottom Line: We present a novel software package that enables the processing of T-Wave ion mobility data.It can also be used to automatically create a collision cross section (CCS) calibration and apply this to subsequent files of interest.A number of applications of the software, and how it enhances the information content extracted from the raw data, are illustrated using model proteins.

View Article: PubMed Central - PubMed

Affiliation: Institute of Structural and Molecular Biology, Division of Biosciences, University College London, London, UK.

ABSTRACT

Since the introduction of travelling wave (T-Wave)-based ion mobility in 2007 a large number of research laboratories have embraced the technique, particularly those working in the field of structural biology. The development of software to process the data generated from this technique, however, has been limited. We present a novel software package that enables the processing of T-Wave ion mobility data. The program can deconvolute components in a mass spectrum and uses this information to extract corresponding arrival time distributions (ATDs) with minimal user intervention. It can also be used to automatically create a collision cross section (CCS) calibration and apply this to subsequent files of interest. A number of applications of the software, and how it enhances the information content extracted from the raw data, are illustrated using model proteins.

No MeSH data available.