In addition to protein identification, it is possible to obtain quantification data from LC-MS/MS proteomic analyses. Except in special cases of targeted proteomics, the quantification obtained is always relative. That is, for each protein, we obtain a ratio between different groups/conditions to be compared. 

Two quantification methods are possible : 

Chemical labeling with TMT (Tandem Mass Tag) 

With this method, peptides from each sample are labeled with a chemical compound tagged with stable isotopes. Each sample receives a different label, and then the samples are combined and injected together into the mass spectrometer, which generates MS1 and MS2 spectra as in a simple identification analysis. However, during fragmentation, the different tags generate reporter ions (one for each sample). Thus, the MS2 spectra contain the fragments for identifying the peptide it contains as well as a group of reporter ions whose intensities provide the quantification of this peptide in each sample. 

This method can be used in two different contexts: 

  • For experiments with 18 samples or less: TMT labeling can be used to combine samples and then fractionate them (usually 12 fractions obtained by high pH fractionation) to obtain better proteome coverage. 
  • On the contrary, for experiments with a very large number of samples, TMT labeling can be used to multiplex the analyses (up to 17 samples + 1 normalization control in the same injection). 

However, this method has two disadvantages: it is quite expensive (TMT labeling kit), and it can generate ratio compression. 

Label-Free Quantification (LFQ) 

This is the simplest method. Samples are treated separately and injected one after the other into the mass spectrometer. 

Depending on the experiments and instruments, we use two different signal acquisition strategies called DDA (Data Dependent Acquisition) or DIA (Data Independent Acquisition). DDA acquisition provides higher-quality spectra (necessary, for example, for the analysis of post-translational modifications), while DIA analysis generally allows for more comprehensive proteome coverage. 

After analysis, signal processing software allows us to obtain quantification values by reconstituting and integrating the peak area of each peptide elution in each sample. 

This method has the advantage of being less expensive than the labeling method, and it also allows for the handling of experiments containing hundreds of samples. Bioinformatic processing methods then allow for data normalization between different injections.