Protein biomarkers are highly desired for early detection, accurate diagnosis, and prognosis of human diseases such as cancer, as well as for monitoring clinical interventions.1
Human plasma (or serum) is a particularly desirable biological fluid for disease biomarker discovery because blood is routinely collected in the clinic, collection is minimally invasive, and established clinical assays are relatively inexpensive. Proteins and metabolites in the blood are thought to be shed by most cells in the body, and changes in the levels of these proteins and metabolites have been hypothesized to potentially reflect most physical conditions.2, 3
Thus, human plasma is a potential treasure-trove of candidate biomarkers that might indicate the onset and progression of most disease states. However, mass spectrometry (MS)-based proteomics analyses of plasma for disease-associated biomarker discovery and validation is extremely challenging due to plasma’s great complexity and wide dynamic range of plasma protein concentrations that span more than 10 orders of magnitude.2
Specifically, the plasma proteome is dominated by a handful of proteins in the mg/mL range and the 20 most-abundant plasma proteins constitute 99% of the total protein mass in plasma.2
But, most disease biomarkers are predicted to be present at low-abundant levels, particularly proteins such as cancer biomarkers that are relatively specifically associated with the tumor. For example, prostate-specific antigen (PSA), carcinoembryonic antigen (CEA), CA125, and other relatively specific known cancer biomarkers are typically present in serum and plasma in the low ng/mL to pg/mL range.2–4
Hence, low-abundant disease biomarkers are often either masked by the abundant proteins or are below detection limits of MS instruments because the abundant proteins limit the volume of plasma that can be injected and analyzed. Therefore, detection of low-abundant proteins requires fractionation strategies that reduce sample complexity and increase the volume of original plasma that analyzed fractions represent. Of course, protein recoveries must remain high and relatively reproducible.
The strategies most commonly employed are to immunodeplete the major plasma proteins and subject the remaining proteome to additional protein- and/or peptide-level fractionation steps prior to nanoLC-MS/MS.5–8
Sequential separation steps should exploit orthogonal physicochemical properties of proteins or peptides. SDS-PAGE and strong cation exchange (SCX) are highly orthogonal to immunodepletion, and reverse-phase nanoLC-MS/MS and have been widely used for intermediate protein and peptide fractionation, respectively. Recently, peptide OFFGEL electrophoresis and high pH RP-HPLC (hpRP-HPLC) have gained attention and showed good performance in terms of separation efficiency and identifications of protein and peptide.9–17
Binary or higher dimensional comparisons of different fractionation approaches prior to LC-MS/MS have been studied by several research groups using samples with different complexities. Peptide OFFGEL electrophoresis has found to be comparable to online SCX separations using low- or medium-complexity samples,18, 19
and appears to outperform offline SCX20
fractionation methods for complex samples. Recently, two independent systematic fractionation comparison studies showed SDS-PAGE was superior to OFFGEL electrophoresis or offline SCX in terms of protein and peptide identifications using honey bee lysates or lung cancer secretomes.22, 23
hpRP-HPLC exploits the same peptide properties (hydrophobicity) as low pH RP-HPLC, thus it seems less orthogonal to low pH RP-HPLC compared with SDS-PAGE, OFFGEL electrophoresis, and SCX. However, it is worth noting that hpRP-HPLC outperformed OFFGEL electrophoresis,19
based on the total number of proteins identified using low- or medium-complexity samples. Taken together, the above studies indicated that 1-D SDS-PAGE, OFFGEL electrophoresis, and hpRP-HPLC are among the highest performance proteome fractionation methods, as at least several studies showed each of these methods yielded the best depth of analysis in specific studies using low- or medium-complexity samples. However, to our knowledge, a side-by-side comparison of these three fractionation methods using a highly complex sample such as human plasma has not been reported.
We previously used a 3-D plasma/serum fractionation strategy for ectopic pregnancy biomarker discovery and verification that combined immunodepletion of 20 abundant proteins, SDS-PAGE, and LC-MS/MS with label-free peptide quantitation.27–29
SDS-PAGE as the second plasma fractionation step provides reasonably reproducible separations and, importantly, can distinguish molecular weight changes in a given protein that may be clinically important for some biomarkers.28
This same method was used for initial small-scale validation of ectopic pregnancy and ovarian cancer biomarkers using multiple reaction monitoring (MRM) with label-free quantitation. 27–29
However, this 3-D strategy with SDS-PAGE as the middle step is not very compatible with stable isotope dilution MRM quantitation or with other peptide-level, stable-isotope-label-based quantitative strategies. Another limitation of the 3-D MRM analysis using 1-D SDS gels as the middle step is that proteins to be quantitated are usually spread over at least three to four fractions and slight gel-to-gel variations in protein migration further increase the number of gel slices that must be analyzed in order to ensure that the proteins of interest are fully quantitated. This spread of peptides to be quantitated among multiple fractions reduces peptide signal intensity, making the peptide harder to detect and quantify, and reduces sample throughput.
In this study, we systematically compared 1-D SDS-PAGE, OFFGEL electrophoresis and hpRP-HPLC as the middle step in 3-D plasma proteome profiling. One goal was to identify a peptide-based method that could be better integrated with stable isotope dilution MRM assays and would have at least a similar depth of analysis to 1-D SDS PAGE. In addition, a peptide-based fractionation method that might prove to be superior to 1-D SDS PAGE for plasma proteome profiling would provide an alternative 3-D strategy for initial plasma biomarker discovery. We selected peptide OFFGEL electrophoresis and peptide hpRP-HPLC as the best peptide fractionation methods for comparison to 1-D SDS gels based on their high performance on less complex samples, as summarized above. Surprisingly, the results show that hpRP-HPLC of depleted plasma tryptic peptides is more efficient at in-depth analysis than either 1-D SDS gels or peptide OFFGEL electrophoresis.