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A framework for intelligent data acquisition and real-time database searching for shotgun proteomics.

Graumann J, Scheltema RA, Zhang Y, Cox J, Mann M - Mol. Cell Proteomics (2011)

Bottom Line: Finally, we demonstrate enhanced quantification of SILAC pairs whose ratios were poorly defined in survey spectra.MaxQuant Real-Time is flexible and can be applied to a large number of scenarios that would benefit from intelligent, directed data acquisition.Our framework should be especially useful for new instrument types, such as the quadrupole-Orbitrap, that are currently becoming available.

View Article: PubMed Central - PubMed

Affiliation: Department of Proteomics and Signal Transduction, Max-Planck Institute for Biochemistry, Am Klopferspitz 18, D-82152 Martinsried, Germany.

ABSTRACT
In the analysis of complex peptide mixtures by MS-based proteomics, many more peptides elute at any given time than can be identified and quantified by the mass spectrometer. This makes it desirable to optimally allocate peptide sequencing and narrow mass range quantification events. In computer science, intelligent agents are frequently used to make autonomous decisions in complex environments. Here we develop and describe a framework for intelligent data acquisition and real-time database searching and showcase selected examples. The intelligent agent is implemented in the MaxQuant computational proteomics environment, termed MaxQuant Real-Time. It analyzes data as it is acquired on the mass spectrometer, constructs isotope patterns and SILAC pair information as well as controls MS and tandem MS events based on real-time and prior MS data or external knowledge. Re-implementing a top10 method in the intelligent agent yields similar performance to the data dependent methods running on the mass spectrometer itself. We demonstrate the capabilities of MaxQuant Real-Time by creating a real-time search engine capable of identifying peptides "on-the-fly" within 30 ms, well within the time constraints of a shotgun fragmentation "topN" method. The agent can focus sequencing events onto peptides of specific interest, such as those originating from a specific gene ontology (GO) term, or peptides that are likely modified versions of already identified peptides. Finally, we demonstrate enhanced quantification of SILAC pairs whose ratios were poorly defined in survey spectra. MaxQuant Real-Time is flexible and can be applied to a large number of scenarios that would benefit from intelligent, directed data acquisition. Our framework should be especially useful for new instrument types, such as the quadrupole-Orbitrap, that are currently becoming available.

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Related in: MedlinePlus

Resequencing can be beneficial for peptide identifications.A, Controlled resequencing of peptides with different times shows that re-sequencing of those peptides whose abundance is increased after 15 s yields the best performance. B, Total number of MS/MS scans as a function of resequencing delay. Short delays yield more fragmentation events due to short ion injection times but less identified peptides (panel A), as many highly abundant peptides keep being resequenced.
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Figure 2: Resequencing can be beneficial for peptide identifications.A, Controlled resequencing of peptides with different times shows that re-sequencing of those peptides whose abundance is increased after 15 s yields the best performance. B, Total number of MS/MS scans as a function of resequencing delay. Short delays yield more fragmentation events due to short ion injection times but less identified peptides (panel A), as many highly abundant peptides keep being resequenced.

Mentions: To increase performance we investigated controlled resequencing, where an isotope pattern is resequenced after a limited amount of time. With the employed peak detection algorithms from MaxQuant it is possible to track the isotope pattern of a peptide during its complete elution time and record properties about its lifetime (in the chromatography conditions employed here this is on average 30 s). As mentioned previously, a fragmentation event is triggered early after which the timestamp of the MS/MS experiment is stored for that particular isotope pattern. If the isotope pattern is still present after an empirically determined resequencing delay and its intensity has increased compared with the one associated with the original sequencing event, a new fragmentation event is triggered. The restriction at the intensity level ensures that no fragmentation scans are triggered that are likely to be less successful than the previous. Fig. 2A shows that, based on the number of identified peptides, a re-sequence delay of 15 s is optimal in the context of the employed chromatography conditions. With longer controlled exclusion times less fragmentation scans are recorded (Fig. 2B), which can be attributed to re-sequencing of highly abundant peptides at lower delay times effectively reducing the cycle-time with shorter inject times.


A framework for intelligent data acquisition and real-time database searching for shotgun proteomics.

Graumann J, Scheltema RA, Zhang Y, Cox J, Mann M - Mol. Cell Proteomics (2011)

Resequencing can be beneficial for peptide identifications.A, Controlled resequencing of peptides with different times shows that re-sequencing of those peptides whose abundance is increased after 15 s yields the best performance. B, Total number of MS/MS scans as a function of resequencing delay. Short delays yield more fragmentation events due to short ion injection times but less identified peptides (panel A), as many highly abundant peptides keep being resequenced.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3316723&req=5

Figure 2: Resequencing can be beneficial for peptide identifications.A, Controlled resequencing of peptides with different times shows that re-sequencing of those peptides whose abundance is increased after 15 s yields the best performance. B, Total number of MS/MS scans as a function of resequencing delay. Short delays yield more fragmentation events due to short ion injection times but less identified peptides (panel A), as many highly abundant peptides keep being resequenced.
Mentions: To increase performance we investigated controlled resequencing, where an isotope pattern is resequenced after a limited amount of time. With the employed peak detection algorithms from MaxQuant it is possible to track the isotope pattern of a peptide during its complete elution time and record properties about its lifetime (in the chromatography conditions employed here this is on average 30 s). As mentioned previously, a fragmentation event is triggered early after which the timestamp of the MS/MS experiment is stored for that particular isotope pattern. If the isotope pattern is still present after an empirically determined resequencing delay and its intensity has increased compared with the one associated with the original sequencing event, a new fragmentation event is triggered. The restriction at the intensity level ensures that no fragmentation scans are triggered that are likely to be less successful than the previous. Fig. 2A shows that, based on the number of identified peptides, a re-sequence delay of 15 s is optimal in the context of the employed chromatography conditions. With longer controlled exclusion times less fragmentation scans are recorded (Fig. 2B), which can be attributed to re-sequencing of highly abundant peptides at lower delay times effectively reducing the cycle-time with shorter inject times.

Bottom Line: Finally, we demonstrate enhanced quantification of SILAC pairs whose ratios were poorly defined in survey spectra.MaxQuant Real-Time is flexible and can be applied to a large number of scenarios that would benefit from intelligent, directed data acquisition.Our framework should be especially useful for new instrument types, such as the quadrupole-Orbitrap, that are currently becoming available.

View Article: PubMed Central - PubMed

Affiliation: Department of Proteomics and Signal Transduction, Max-Planck Institute for Biochemistry, Am Klopferspitz 18, D-82152 Martinsried, Germany.

ABSTRACT
In the analysis of complex peptide mixtures by MS-based proteomics, many more peptides elute at any given time than can be identified and quantified by the mass spectrometer. This makes it desirable to optimally allocate peptide sequencing and narrow mass range quantification events. In computer science, intelligent agents are frequently used to make autonomous decisions in complex environments. Here we develop and describe a framework for intelligent data acquisition and real-time database searching and showcase selected examples. The intelligent agent is implemented in the MaxQuant computational proteomics environment, termed MaxQuant Real-Time. It analyzes data as it is acquired on the mass spectrometer, constructs isotope patterns and SILAC pair information as well as controls MS and tandem MS events based on real-time and prior MS data or external knowledge. Re-implementing a top10 method in the intelligent agent yields similar performance to the data dependent methods running on the mass spectrometer itself. We demonstrate the capabilities of MaxQuant Real-Time by creating a real-time search engine capable of identifying peptides "on-the-fly" within 30 ms, well within the time constraints of a shotgun fragmentation "topN" method. The agent can focus sequencing events onto peptides of specific interest, such as those originating from a specific gene ontology (GO) term, or peptides that are likely modified versions of already identified peptides. Finally, we demonstrate enhanced quantification of SILAC pairs whose ratios were poorly defined in survey spectra. MaxQuant Real-Time is flexible and can be applied to a large number of scenarios that would benefit from intelligent, directed data acquisition. Our framework should be especially useful for new instrument types, such as the quadrupole-Orbitrap, that are currently becoming available.

Show MeSH
Related in: MedlinePlus