Quantitative analysis of isotope distributions in proteomic mass spectrometry using least-squares Fourier transform convolution.

Quantitative proteomic mass spectrometry involves comparison of the amplitudes of peaks resulting from different isotope labeling patterns, including fractional atomic labeling and fractional residue labeling. We have developed a general and flexible analytical treatment of the complex isotope distributions that arise in these experiments, using Fourier transform convolution to calculate labeled isotope distributions and least-squares for quantitative comparison with experimental peaks. The degree of fractional atomic and fractional residue labeling can be determined from experimental peaks at the same time as the integrated intensity of all of the isotopomers in the isotope distribution. The approach is illustrated using data with fractional (15)N-labeling and fractional (13)C-isoleucine labeling. The least-squares Fourier transform convolution approach can be applied to many types of quantitative proteomic data, including data from stable isotope labeling by amino acids in cell culture and pulse labeling experiments.