This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Selected reaction monitoring (SRM) is a powerful tandem mass spectrometry method that can be used to monitor target peptides within a complex protein digest. The specificity and sensitivity of the approach, as well as its capability to multiplex the measurement of many analytes in parallel, has made it a technology of particular promise for hypothesis driven proteomics. An underappreciated step in the development of an assay to measure many peptides in parallel is the time and effort necessary to establish a usable assay. Here we report the use of shotgun proteomics data to expedite the selection of SRM transitions for target peptides of interest. The use of tandem mass spectrometry data acquired on an LTQ ion trap mass spectrometer can accurately predict which fragment ions will produce the greatest signal in an SRM assay using a triple quadrupole mass spectrometer. Furthermore, we present a scoring routine that can compare the targeted SRM chromatogram data with an MS/MS spectrum acquired by data-dependent acquisition and stored in a library. This scoring routine is invaluable in determining which signal in the chromatogram from a complex mixture best represents the target peptide. These algorithmic developments have been implemented in a software package that is available from the authors upon request.

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
Biotechnology Resource Grants (P41)
Project #
5P41RR011823-14
Application #
7957849
Study Section
Special Emphasis Panel (ZRG1-CB-H (40))
Project Start
2009-09-01
Project End
2010-08-31
Budget Start
2009-09-01
Budget End
2010-08-31
Support Year
14
Fiscal Year
2009
Total Cost
$27,708
Indirect Cost
Name
University of Washington
Department
Biochemistry
Type
Schools of Medicine
DUNS #
605799469
City
Seattle
State
WA
Country
United States
Zip Code
98195
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Hollmann, Taylor; Kim, Tae Kwon; Tirloni, Lucas et al. (2018) Identification and characterization of proteins in the Amblyomma americanum tick cement cone. Int J Parasitol 48:211-224
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