Isotopic Signature Transfer and Mass Pattern Prediction (IsoStamp) for Targeted Mass Spectrometry

Developed by the Bertozzi Group, 2015.


Isotopic signature transfer and mass pattern prediction (IsoStamp) is a computational algorithm for the targeted detection and identification of modified species by mass spectrometry (MS). The IsoStamp algorithm uses predictive pattern matching to produce peak lists of isotopically recoded species. The peak lists are used for the immediate validation of modified species by full scan MS and to guide subsequent inclusion list-driven tandem MS.


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We provide two IsoStamp algorithms with further description and references below.


(1) Graph_Search v1.9: mzXML files in profile mode are processed using a continuous wavelet transform for peak optimization. A graph theoretic algorithm is then applied to predict the presence of patterned species. Graph_Search scores based on the clustered peak shape as compared to a theoretical curve, peak abundance, and charge states.


For references see:

Palaniappan, K. K.; Pitcher, A. A.; Smart, B. P.; Spiciarich, D. R.; Iavarone, A. T.; Bertozzi, C. R. “Isotopic signature transfer and mass pattern prediction (IsoStamp): An enabling technique for chemically-directed proteomics.” ACS Chem. Biol. 2011, 6, 829–836. PDF


Austin Pitcher Thesis PDF


(2) Tag_Finder: mzXML files in centroided mode are processed by comparing grouped spectra to the predicted pattern as a function of mass and charge. Tag_Finder scores on the difference between the predicted and observed peak distribution for tagged vs. untagged species.


MS2_Filter (a component of Tag_Finder): Uses the Tag_Finder pattern matching algorithm and the presence of signature fragment peaks to select tandem MS spectra derived from tagged species. The filtered output file is then used for targeted database searching.


For references see: manuscript in preparation