We demonstrate the quantification capability and robustness of a new integrated liquid chromatography-mass spectrometry (LC-MS)
approach for large-scale profiling of proteins and metabolites. This approach to determine differential expression relies
on linearity of signal vs molecular concentration using electrospray ionization LC-MS, reproducibility of sample processing,
a novel normalization strategy and associated data analysis software. No isotopic tagging or spiking of internal standards
is required. The method is general and applicable to the proteome and metabolome from all biological fluids and tissues. Small
or large numbers of samples can be profiled in a single experiment. Differential profiling of 6000 molecular ions per sample
by one-dimensional chromatography LC-MS and 30,000 molecular ions per sample by two-dimensional chromatography LC-MS is demonstrated
using rheumatoid arthritis patient samples compared with control samples. A new approach to peptide identification is described
that involves building libraries of previously identified peptides, circumventing the need to acquire MS/MS data during profiling.
Robustness of the platform was tested by repeating sample preparation and LC-MS differential expression analysis after 10
mo, using independent serum aliquots stored at − 80�C. To the best of our knowledge, this is the first demonstration of long-term
robustness of a platform for quantitative proteomics and metabolomics.