Method for simultaneous calibration of mass spectra and identification of peptides in proteomic analysis

Abstract

The invention relates to a mass spectrometry calibration system that may be performed in real-time using the information contained within a sample without the addition of specific calibrants. When applied to a sample, such as a proteomic sample, the calibration system may identify the exact masses of peptides in the sample. The system involves the use of mathematical algorithms that iteratively estimate the error in the measurement and update the calibration parameters accordingly; thereby resulting in peptide mass identification.

1 . A method of producing a calibrated mass spectrum, comprising:
 a) providing a sample comprising an elemental composition;   b) subjecting the sample to mass spectrometry whereby a mass spectrometry output is obtained;   c) providing input parameters;   d) converting the mass spectrometry output to mass values using the input parameters;   e) estimating error and elemental composition probabilities based on the mass values;   f) updating the input parameters based on the estimated error and elemental composition probabilities;   g) applying the updated input parameters to the mass spectrometry output to produce updated mass values; and   h) repeating steps d through g until convergence is reached,   whereby a calibrated mass spectrum is produced.   
     
     
         2 . The method of  claim 1 , wherein the input parameters are selected from the group consisting of a mass database, initial calibration parameters, an initial error estimate, updated calibration parameters, an updated error estimate, and combinations thereof. 
     
     
         3 . The method of  claim 1 , wherein the mass spectrometry is Fourier transform mass spectrometry. 
     
     
         4 . The method of  claim 1 , wherein the mass spectrometry output comprises cyclotron frequencies. 
     
     
         5 . The method of  claim 1 , wherein the elemental composition probabilities are peptide probabilities. 
     
     
         6 . The method of  claim 1 , wherein the sample is selected from the group consisting of blood, plasma, serum, spinal fluid, urine, sweat, saliva, tears, breast aspirate, prostate fluid, seminal fluid, vaginal fluid, stool, cervical scraping, cytes, amniotic fluid, intraocular fluid, mucous, moisture in breath, animal tissue, cell lysates, tumor tissue, hair, skin, buccal scrapings, nails, bone marrow, cartilage, prions, bone powder, ear wax, and combinations thereof. 
     
     
         7 . The method of  claim 1 , wherein the elemental composition comprises at least one peptide. 
     
     
         8 . The method of  claim 1 , wherein the sample is selected from the group consisting of hydrocarbons, petroleum products, nucleotides, combinatorial samples, polymeric samples, and combinations thereof. 
     
     
         9 . The method of  claim 1 , wherein the sample is a petroleum product. 
     
     
         10 . The method of  claim 1 , wherein the estimating the error and elemental composition probabilities comprises using an Expectation Minimization algorithm. 
     
     
         11 . The method of  claim 1 , wherein the estimating the error and elemental composition probabilities comprises using a spline algorithm. 
     
     
         12 . A mass spectrometry calibration system, comprising:
 a) a mass spectrometry device to analyze a sample and produce a mass spectrometry output; and   b) calibration software configured to:
 i) receive input parameters, 
 ii) convert the mass spectrometry output to mass values using the input parameters, 
 iii) estimate error and elemental composition probabilities based on the mass values, 
 iv) update input parameters based on the estimated error and elemental composition probabilities, 
 v) apply the updated input parameters to the mass spectrometry output to produce updated mass values, and 
 vi) repeat steps ii through v until convergence is reached, 
   whereby a calibrated mass spectrum is produced.   
     
     
         13 . The system of  claim 12 , wherein the input parameters are selected from the group consisting of a mass database, initial calibration parameters, an initial error estimate, updated calibration parameters, an updated error estimate, and combinations thereof. 
     
     
         14 . The system of  claim 12 , wherein the mass spectrometry device is a Fourier transform mass spectrometer. 
     
     
         15 . The system of  claim 12 , wherein the mass spectrometry output comprises cyclotron frequencies. 
     
     
         16 . The system of  claim 12 , wherein the elemental composition probabilities are peptide probabilities. 
     
     
         17 . The system of  claim 12 , wherein the sample is selected from the group consisting of blood, plasma, serum, spinal fluid, urine, sweat, saliva, tears, breast aspirate, prostate fluid, seminal fluid, vaginal fluid, stool, cervical scraping, cytes, amniotic fluid, intraocular fluid, mucous, moisture in breath, animal tissue, cell lysates, tumor tissue, hair, skin, buccal scrapings, nails, bone marrow, cartilage, prions, bone powder, ear wax, and combinations thereof. 
     
     
         18 . The system of  claim 12 , wherein the sample comprises at least one peptide. 
     
     
         19 . The system of  claim 12 , wherein the sample is selected from the group consisting of hydrocarbons, petroleum products, nucleotides, combinatorial samples, polymeric samples, and combinations thereof. 
     
     
         20 . The system of  claim 12 , wherein the sample is a petroleum product. 
     
     
         21 . The system of  claim 12 , wherein the software is configured to estimate the error and the elemental composition probabilities using an Expectation Minimization algorithm. 
     
     
         22 . The system of  claim 12 , wherein the software is configured to estimate the error and the elemental composition probabilities using a spline algorithm. 
     
     
         23 . A computer-readable medium having computer-executable instructions that when executed perform a method, the method comprising:
 a) converting a mass spectrometry output to mass values using input parameters;   b) estimating error and elemental composition probabilities based on the mass values;   c) updating the input parameters based on the estimated error and elemental composition probabilities;   d) applying the updated input parameters to the mass spectrometry output to produce updated mass values; and   e) repeating steps b through d until convergence is reached,   whereby a calibrated mass spectrum is produced.   
     
     
         24 . The computer-readable medium of  claim 23 , wherein the input parameters are selected from the group consisting of a mass database, initial calibration parameters, an initial error estimate, and combinations thereof. 
     
     
         25 . The computer-readable medium of  claim 23 , wherein the estimating the error and the elemental composition probabilities uses an Expectation Minimization algorithm. 
     
     
         26 . The computer-readable medium of  claim 23 , wherein the estimating the error and the elemental composition probabilities uses a spline algorithm. 
     
     
         27 . The computer-readable medium of  claim 23 , wherein the mass spectrometry output is produced by a Fourier transform mass spectrometer. 
     
     
         28 . The computer-readable medium of  claim 23 , wherein the mass spectrometry output comprises cyclotron frequencies. 
     
     
         29 . The computer-readable medium of  claim 23 , wherein the elemental composition probabilities are peptide probabilities.