SuperMix System Fractionation Case Study

Lei Huang¹, Pierre Gagné², Guy G. Poirier², and Xiangming Fang¹

1. GenWay Biotech, Inc. 6777 Nancy Ridge Drive, San Diego, CA 92121
2. CHUL Research Center, Laval University, Ste-Foy (Quebec) Canada G1V 4G2

Human body fluids, such as blood plasma and serum, urine, saliva and CNS fluid, serve as the most important and readily available sources for biomarker discovery. However, novel protein biomarkers are present at a very low concentration in the body fluids samples. As a result, detection of the novel biomarkers is hampered by the "masking" effect caused by a number of highly abundant proteins, and often moderately abundant proteins. For example, 12 most abundant proteins constitute 96% of the bulk mass of the human plasma (Fig.1).

Figure 1. Highly-abundant (HAP)

Moderately-abundant (MAP) and low-abundant (LAP) proteins in human plasma. Relative abundance of HAP, MAP and LAP fractions is shown in percentage of the bulk mass of the proteins from each fraction to the bulk weight of the total plasma protein.

Thus, biomarker detection is significantly facilitated by the removal of 12 most abundant proteins. High-efficiency removal of HAPs was achieved with the original GenWay Seppro^® IgY12 column series, presently marketed as Beckman-Coulter ProteomeLabTM IgY12 system (Beckman-Coulter Product). Numerous studies have demonstrated highly-reproducible separation of twelve HAPs by the IgY12 system (1).

Thus, biomarker detection is significantly facilitated by the removal of 12 most abundant proteins. High-efficiency removal of HAPs was achieved with Beckman-Coulter's ProteomeLab-IgY12 system (Beckman-Coulter Product). Numerous studies have demonstrated highly-reproducible separation of 12 HAPs by the IgY12 system (1, 2). While removal of the HAP fractions enables researchers to analyze more biomarkers than ever, there is still a limitation of how deep one can dig into the proteome. As researchers dig deeper into the human plasma proteome, moderately-abundant protein fraction (MAP) increasingly interferes with such studies. After the removal of 96% of the plasma protein mass (HAP fraction), MAP still constitutes about 98% of the remaining protein mass while majority of novel biomarkers reside in the low-abundant fraction (Fig.1). Thus there is a growing need in the next level of plasma protein fractionation. In response to this need GenWay Biotech developed a new Seppro^® SuperMix System for further fractionation of the MAP and LAP proteins. Current studies by the scientists of Laval University demonstrate effective fractionation of these plasma proteins as an additional step after IgY12-mediated fractionation, which enabled mass spectrometry-assisted identification of 454 plasma proteins using SDS-PAGE coupled with LC-MS/MS identification method.

Materials and Methods

SuperMix LC2 column. The theory behind the SuperMix column is that antibodies can be generated against mixed antigens. The antibody titers correspond to the abundance and the immunogenicity of the proteins (3). Thus, the MAP proteins will cause much higher immune response than lower-abundant proteins. SuperMix LC2 column beads were prepared as follows (Fig. 2). Human plasma samples were partitioned over ProteomeLab-IgY12 system. Chickens were subsequently immunized with the resulting antigen mixture. The generated antibody mixture was affinity purified with F1 proteins and coupled to the microbeads, which were subsequently incorporated into the LC2 column format.

Figure 2. Process of SuperMix Column Production

Shown is how SuperMix column was prepared

Plasma sample fractionation and sample preparation. A human plasma sample (0.5mL) was fractionated over ProteomeLab-IgY12 LC20 column and the resulting flow-through fraction (F1) was further subjected to the SuperMix assisted chromatography. Both SuperMix flow-through (F2) and SuperMix column-bound (eluted) fractions (E2) were subjected to the SDS-PAGE electrophoresis (Fig.3). The gel slices from each lane of the same fraction were combined and digested with trypsin.

Figure 3. Plasma Sample Preparation

A plasma sample was subjected to IgY12-assisted partitioning followed by SuperMix mediated fractionation. SuperMix flow-through (left panel) and SuperMix-2 bound (eluted) fractions (right panel) were subjected to the SDS-PAGE (Sypro Ruby staining). Ten (10) µg of total protein was loaded in each lane. Gel slices from each lane of the same fraction were combined, digested with trypsin and subjected to the conventional LC-MS/MS analysis.

LC-MS/MS analysis of protein digests

Peptide extracts were analyzed using a NanoLC 1100 series system (Agilent Technologies) coupled with a hybrid quadrupole-TOF mass spectrometer (QSTAR xl, MDS Sciex). Dried extracts were resuspended in 20 µL of a 0.1% trifluoroacetic acid (TFA). Chromatographic separation was achieved on a 75 µm ID x 10 cm Biobasic C18 Integrafrit column. Two different elution gradients were used, respectively a 1 hour and 2 hours long, depending on the Sypro Ruby stain intensity of the gel section analyzed. Gel sections of the flow-through fraction which contained a highly complex mixture of peptides were injected twice, using a static exclusion list in the second analysis. All in all, the 30 peptide extracts from the SuperMix eluate fraction required 30 LC-MS/MS runs and a total analysis time of 54 hours; and the 31 peptide extracts from the SuperMix flow-through fraction required 47 LC-MS/MS runs and a total analysis time of 79 hours. The total MS analysis time for both the SuperMix eluate and flow-through fractions was therefore of 133 hours (5.54 days) (Fig.4).

Figure 4. LC-MS/MS analysis of the peptides derived from the plasma protein trypsin digestion

Example shows the spectrum of for a peptide belongs to cholinesterase precursor.

Database searching and criteria for protein identification

All MS/MS spectra were analyzed using Mascot (Matrix Science), Sequest (Thermo Electron) and X! Tandem (www.thegpm.org). All three search engines were set up to search the IPI human database (www.ebi.ac.uk/IPI, version 3.15) modified to include contaminants such as trypsin and IgY (58,152 entries in total). Scaffold (Proteome Software) was used to group and validate MS/MS based peptide and protein identifications. Peptide identifications were accepted if they could be established at greater than 80.0% probability as specified by the PeptideProphet algorithm (4). For the SuperMix eluate and flow-through high-confidence datasets, protein identifications were accepted if they could be established at greater than 95.0% probability and contained at least 2 identified peptides. The SuperMix eluate and flow-through low-confidence datasets contains protein identifications with a probability greater than 80.0% and only 1 identified peptide. Protein probabilities were assigned by the Protein Prophet algorithm (5).

Results

The plasma samples were subjected to IgY12 and SuperMix fractionation consecutively. The resulting protein fractions (flow-through and eluted, column-bound fractions, F2 and E2, respectively) were subjected to SDS-PAGE resolution and isolation followed by trypsin digest and LC-MS/MS analysis. The whole analysis took about 5 days of MS/MS acquisition. In the final analysis of the proteins highly-stringent criteria was applied. It resulted in rigorous but, at the same time, more accurate, selection of positively-identified proteins. Table I shows the selection criteria for positively-identified peptides.

Table I. Selection criteria for positive protein identification

Over the course of this 5.5-day mini-project, 81 proteins from the flow-through fraction were identified with the confidence level >95% and 130 proteins were identified with the confidence level >80%. From the column-bound, eluted fraction, 126 proteins were identified with the confidence level >95% and 198 proteins were identified with the confidence level >80%. For the summary of the results please refer to Table II. of the results please refer to Table II.

Table II. Summary of SuperMix Protein Identification

Conclusions

Independent study conducted in the laboratory of D. Guy G. Poirier at the CHUL Research Center, Laval University demonstrated significant improvement of the protein identification in plasma proteome if SuperMix column is used in addition to the ProteomeLabT-IgY12 system. Coupled use of the IgY12 and SuperMix Systems in separating HAP and MAP from LAP facilitates plasma protein identification 10 fold (if the same identification method is used). Applying about 1/10 of the total protein from each fraction (F2 and E2) of SuperMix column (Fig. 3), total of 531 proteins have been identified over the course of the independent study. This is quite remarkable given the fact that these results were obtained in less than six days of MS/MS acquisition. For comparison, HUPO Pilot Phase, which was conducted by 35 collaborating laboratories, generated a core dataset of 3,020 proteins over 1 year period (6). This new method of plasma proteome fractionation does not only improve the quality of the data but more importantly provides more time-effective and more financially-effective approach to the plasma proteome research. In conclusion, SuperMix System provides a novel tool for digging deeper into the proteome with good confidence and reproducibility.

References

1. Huang, L., Harvie, G., Feitelson, J.S., Gramatikoff, K., Herold, D.A., Allen, D.L., Amunngama, R., Hagler, R.A., Pisano, M.R., Zhang, W.-W., and X. Fang (2005) Immunoaffinity separation of plasma proteins by IgY microbeads: Meeting the needs of proteomic sample preparation and analysis. Proteomics 5, 3314-3328,

2. Liu, T., Qian, W.-J., Mottaz, H.M., Gritsenko, M.A., Norbeck, A.D., Moore, R.J., Purvine, S.O., Camp, D.G., and R.D. Smith. (2006). Evaluation of Multi-Protein Immunoaffinity Subtraction for Plasma Proteomics and Candidate Biomarker Discovery Using Mass Spectrometry. Mol. Cel. Proteom. EPUB.

3. Anderson, N.G., Willis, D.D., Holladay, D.W., Caton, J.E., Holleman, J.W., Eveleigh, J.W., Attrill, J.E., Ball, F.L., and N. L. Anderson. (1975). Analytical Techniques for Cell Fractionation. Analytical Biochemistry 68: 371-393. 4. Omenn, G.S., States, D.J., Adamski, M., Blackwell, T.W., Menon, R., Hermjakob, H., Apweiler, R., Haab, B.B., Simpson, R.J., Eddes, J.S., Kapp, E.A., Moritz, R.L., Chan, D.W., Rai, A.J., Admon, A., Aebersold, R., Eng, J., Hancock, W.S., Hefta, S.A., Meyer, H., Paik, Y.K., Yoo, J.S., Ping, P., Pounds, J., Adkins, J., Qian, X., Wang, R., Wasinger, V., Wu, C.Y., Zhao, X., Zeng, R., Archakov, A., Tsugita, A., Beer, I., Pandey, A., Pisano, M., Andrews, P., Tammen, H., Speicher, D.W., and S.M. Hanash. (2005). Overview of the HUPO Plasma Proteome Project: results from the pilot phase with 35 collaborating laboratories and multiple analytical groups, generating a core dataset of 3020 proteins and a publicly-available database. Proteomics 5: 3226-3245.

4. Keller, A., Nesvizhskii, A.I., Kolker, E., and R.Aebersold (2002). Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search. Anal. Chem. 74, 5383-5392.

5. Nesvizhskii, A.I., Keller, A., Kolker, E., and R. Aebersold (2003). A statistical model for identifying proteins by tandem mass spectrometry. Anal Chem. 75, 4646-4658.

6. Omenn, G.S., States, D.J., Adamski, M., Blackwell, T.W., Menon, R., Hermjakob, H., Apweiler, R., Haab, B.B., Simpson, R.J., Eddes, J.S., Kapp, E.A., Moritz, R.L., Chan, D.W., Rai, A.J., Admon, A., Aebersold, R., Eng, J., Hancock, W.S., Hefta, S.A., Meyer, H., Paik, Y.K., Yoo, J.S., Ping, P., Pounds, J., Adkins, J., Qian, X., Wang, R., Wasinger, V., Wu, C.Y., Zhao, X., Zeng, R., Archakov, A., Tsugita, A., Beer, I., Pandey, A., Pisano, M., Andrews, P., Tammen, H., Speicher, D.W., and S.M. Hanash. (2005). Overview of the HUPO Plasma Proteome Project: results from the pilot phase with 35 collaborating laboratories and multiple analytical groups, generating a core dataset of 3020 proteins and a publicly-available database. Proteomics 5: 3226-3245.

For additional information, please inquire: ssikora@genwaybio.com

Case Study	Protein List of SuperMix Column Eluate
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