Correlated peptides for quantitative mass spectrometry

1. A method of identifying signature peptides for quantifying a polypeptide in a sample, comprising:

acquiring mass spectrometry (MS) data on multiple candidate peptides derived from the polypeptide in multiple samples,

wherein acquiring MS data comprises operating a mass spectrometer;

using the MS data to calculate correlation values for pairwise comparisons among the multiple candidate peptides;

eliminating candidate peptides containing a methionine amino acid residue; and

identifying highly correlated peptides among the multiple candidate peptides without methionine,

wherein the highly correlated peptides have mean or median correlation values ranked in the top 80% among the multiple candidate peptides without methionine, and

wherein the highly correlated peptides are identified as the signature peptides for quantifying the polypeptide.

2. The method of claim 1 , wherein the MS data is collected by a targeted acquisition method.

3. The method of claim 1 , wherein the MS data is collected by a data independent acquisition method.

4. The method of claim 1 , wherein the correlation values are coefficient of determination (r 2 ) values.

5. The method of claim 1 , wherein the multiple candidate peptides are derived by proteolysis or chemical cleavage of the polypeptide.

6. The method of claim 1 , wherein the sample is derived from food, water, cheek swab, blood, serum, plasma, urine, saliva, semen, cells, tissue, tumor, or a combination thereof.

7. The method of claim 1 , further comprising ranking the correlation values of the multiple candidate peptides.

8. The method of claim 1 , wherein the highly correlated peptides have mean or median correlation values ranked in the top 70% among the multiple candidate peptides without methionine.

9. The method of claim 1 , wherein the multiple candidate peptides are obtained from a data-dependent MS screen, data-independent MS data, targeted peptides data, MS spectral database, or proteotypic peptide prediction, or a combination thereof.

10. The method of claim 1 , further comprising eliminating candidate peptides that satisfy one or more of the following criteria:

i. not previously detected by MS;

ii. not unique to the polypeptide;

iii. absent from the polypeptide's mature form;

iv. containing an uncleaved protease recognition site;

v. susceptible to post-translational modification (PTM);

vi. containing asparagine and/or cysteine residues;

vii. sensitive to endogenous proteases;

viii. having m/z values lower than an m/z bottom cutoff value;

ix. having m/z values higher than an m/z top cutoff value; and

x. having signal intensities lower than an intensity bottom cutoff value in the acquired MS data.

11. The method of claim 1 , wherein the identified signature peptides have signal intensities more than 20 times the background noise intensity value in the acquired MS data.

12. The method of claim 1 , wherein the highly correlated peptides have mean or median correlation values ranked in the top 60% among the multiple candidate peptides without methionine.

13. The method of claim 1 , wherein the highly correlated peptides have mean or median correlation values ranked in the top 50% among the multiple candidate peptides without methionine.

14. The method of claim 1 , wherein the highly correlated peptides have mean or median correlation values ranked in the top 40% among the multiple candidate peptides without methionine.

15. A method of identifying signature peptides for quantifying a polypeptide in a sample, comprising:

acquiring mass spectrometry (MS) data on multiple candidate peptides derived from the polypeptide in multiple samples,

wherein acquiring MS data comprises operating a mass spectrometer;

using the MS data to calculate correlation values for pairwise comparisons among the multiple candidate peptides;

eliminating candidate peptides containing a methionine amino acid residue;

ranking the mean or median correlation values of the multiple candidate peptides; and

identifying highly correlated peptides among the multiple candidate peptides without methionine,

wherein the highly correlated peptides have mean or median correlation values ranked in the top 10 among the multiple candidate peptides without methionine, and

wherein the highly correlated peptides are identified as the signature peptides for quantifying the polypeptide.

16. The method of claim 15 , wherein the highly correlated peptides have mean or median correlation values ranked in the top 6 among the multiple candidate peptides without methionine.

17. A method of quantifying a polypeptide in a sample, comprising:

acquiring mass spectrometry (MS) data on multiple candidate peptides derived from the polypeptide in multiple samples;

using the MS data to calculate correlation values for pairwise comparisons among the multiple candidate peptides;

eliminating candidate peptides containing a methionine amino acid residue;

identifying highly correlated peptides among the multiple candidate peptides without methionine,

wherein the highly correlated peptides have mean or median correlation values ranked in the top 80% among the multiple candidate peptides without methionine, and

wherein the highly correlated peptides are identified as signature peptides for quantifying the polypeptide;

cleaving the polypeptide in the sample to yield the signature peptides;

analyzing the sample on a mass spectrometer;

detecting MS signals of the signature peptides; and

quantifying the polypeptide based on the detected MS signals of the signature peptides.

18. The method of claim 17 , further comprising spiking the sample with an internal standard and detecting MS signals of the internal standard.

19. The method of claim 18 , wherein the internal standard comprises the signature peptide labeled with a stable isotope.

20. The method of claim 18 , further comprising normalizing the signature peptide's MS signals to the internal standard's MS signals.