Quantification of Proteins and Metabolites by Mass Spectrometry without Isotopic Labeling or Spiked Standards

Abstract

A new method is presented for quantifying proteomic and metabolomic profile data by liquid chromatography-mass spectrometry (LC-MS) with electrospray ionization. This biotechnology provides differential expression measurements and enables the discovery of biological markers (biomarkers). Work presented here uses human serum but is applicable to any fluid or tissue. The approach relies on linearity of signal versus molecular concentration and reproducibility of sample processing. There is no use of isotopic labeling or chemically similar standard materials. Linear standard curves are reported for a variety of compounds introduced into human serum. As a measure of analytical reproducibility for proteome and metabolome sampling, median coefficients of variation of 25.7 and 23.8%, respectively, were determined for approximately 3400 molecular ions (not counting their numerous isotopes) from 25 independently processed human serum samples, corresponding to a total of 85000 individual molecular ion measurements.

A proteomic study of serum from children with autism showing differential expression of apolipoproteins and complement proteins

“…41,[53][54][55] In brief, serum was fractioned into proteome and metabolome using a 5-kDa molecular weight cutoff spin filter (Millipore Corp., Bedford, MA, USA). Proteomic analysis was performed on serum proteins > 5000 Da.…”

“…Proprietary MassView software was used to track and quantify molecules for their differential expression. [55][56][57] Identification of proteins was performed based upon the identification of peptides. Peptides of interest (significantly changing in expression level) were linked to tandem mass spectrometry (MS/MS) experiments on quadrupole TOF (Q-TOF) and iontrap mass spectrometers using extra or similar sample material.…”

Label-free quantitation: A new glycoproteomics approach

“…To alleviate much of the variation due to changes in MS response among samples, normalization of data has been applied in proteomics studies [33][34][35][36]. Many proteomics researchers employ a normalization technique that involves dividing intensities of individual peaks by the total intensity from all peaks in the spectrum [33][34][35]; this approach is fundamentally similar to the approach by Wang et al, where spectra are normalized by calculating an intensity ratio for one spectrum versus another by doing pair-wise comparisons of peak intensities, for all the peaks in the spectra [36].…”

“…Many proteomics researchers employ a normalization technique that involves dividing intensities of individual peaks by the total intensity from all peaks in the spectrum [33][34][35]; this approach is fundamentally similar to the approach by Wang et al, where spectra are normalized by calculating an intensity ratio for one spectrum versus another by doing pair-wise comparisons of peak intensities, for all the peaks in the spectra [36]. In the work presented here, this concept of normalization is builtupon to produce a label-free quantitative method for glycopeptide analysis.…”

Quantitative analysis of complex peptide mixtures using FTMS and differential mass spectrometry

“…Label-free methods do not require sample mixing or metabolic labeling, meaning that diverse samples, including human tissues or body fluids, can be analyzed. Lastly, label-free methods permit direct comparison of multiple samples across multiple conditions [13], enabling complex experimental designs.…”