Quantitative proteomics using isobaric labeling typically involves sample 
digestion, peptide-level labeling and 2D LC-MS/MS. Proteomic analysis of complex 
samples can potentially be performed more comprehensively with GeLC-MS/MS. 
However, combining this approach with peptide-level labeling of multiple in-gel 
digests from entirely sectioned gel lanes can introduce many points of variation 
and adversely affect the final quantitative accuracy. Alternatively, samples 
labeled with isobaric tags at the protein level can be combined and analyzed by 
GeLC-MS/MS as a single gel lane. A caveat to this strategy is that only lysine 
residues are labeled, which might limit protein digestion and quantitation of 
peptides. Here we have compared a protein-level labeling GeLC-MS/MS strategy 
with a peptide-level labeling 2D LC-MS/MS approach, using mouse hippocampus 
synaptosomes and isobaric tandem mass tags. Protein-level labeling enabled the 
identification of 3 times more proteins (697 versus 241) than did peptide-level 
labeling, and importantly for quantitation, twice as many proteins with labeled 
peptides (480 versus 232) were identified. Preliminary in silico analysis also 
suggested the alternative use of Asp-N to trypsin to circumvent the interference 
of lysine labeling on protein digestion. Use of Asp-N resulted in the effective 
analysis of fewer peptides than with trypsin for the protein-level approach 
(1677 versus 3131), but yielded a similar quantitative proteomic coverage in 
terms of both peptides (1150 versus 1181) and proteins (448 versus 480). Taken 
together, these experiments demonstrate that protein-level labeling combined 
with GeLC-MS/MS is an effective strategy for the multiplexed quantitation of 
synaptosomal preparations, and may also be applicable to samples of a similar 
proteomic complexity and dynamic range of protein abundance.