Expanding the Subproteome of the Inner Mitochondria Using Protein Separation Technologies

Currently no single proteomics technology has sufficient analytical power to allow for the detection of an entire proteome of an organelle, cell, or tissue. One approach that can be used to expand proteome coverage is the use of multiple separation technologies especially if there is minimal overlap in the proteins observed by the different methods. Using the inner mitochondrial membrane subproteome as a model proteome, we compared for the first time the ability of three protein separation methods (two-dimensional liquid chromatography using the ProteomeLab™ PF 2D Protein Fractionation System from Beckman Coulter, one-dimensional reversed phase high performance liquid chromatography, and two-dimensional gel electrophoresis) to determine the relative overlap in protein separation for these technologies. Data from these different methods indicated that a strikingly low number of proteins overlapped with less than 24% of proteins common between any two technologies and only 7% common among all three methods. Utilizing the three technologies allowed the creation of a composite database totaling 348 non-redundant proteins. 82% of these proteins had not been observed previously in proteomics studies of this subproteome, whereas 44% had not been identified in proteomics studies of intact mitochondria. Each protein separation method was found to successfully resolve a unique subset of proteins with the liquid chromatography methods being more suited for the analysis of transmembrane domain proteins and novel protein discovery. We also demonstrated that both the one- and two-dimensional LC allowed for the separation of the α-subunit of F1F0 ATP synthase that differed due to a change in pI or hydrophobicity. Currently no single proteomics technology has sufficient analytical power to allow for the detection of an entire proteome of an organelle, cell, or tissue. One approach that can be used to expand proteome coverage is the use of multiple separation technologies especially if there is minimal overlap in the proteins observed by the different methods. Using the inner mitochondrial membrane subproteome as a model proteome, we compared for the first time the ability of three protein separation methods (two-dimensional liquid chromatography using the ProteomeLab™ PF 2D Protein Fractionation System from Beckman Coulter, one-dimensional reversed phase high performance liquid chromatography, and two-dimensional gel electrophoresis) to determine the relative overlap in protein separation for these technologies. Data from these different methods indicated that a strikingly low number of proteins overlapped with less than 24% of proteins common between any two technologies and only 7% common among all three methods. Utilizing the three technologies allowed the creation of a composite database totaling 348 non-redundant proteins. 82% of these proteins had not been observed previously in proteomics studies of this subproteome, whereas 44% had not been identified in proteomics studies of intact mitochondria. Each protein separation method was found to successfully resolve a unique subset of proteins with the liquid chromatography methods being more suited for the analysis of transmembrane domain proteins and novel protein discovery. We also demonstrated that both the one- and two-dimensional LC allowed for the separation of the α-subunit of F1F0 ATP synthase that differed due to a change in pI or hydrophobicity. The eukaryotic proteome is a compilation of proteins that represents the integration of numerous cellular processes that begin with the variable transcription of genes to mRNA. These products are then translated to proteins, which may in turn be potentially co- and/or post-translationally modified to produce an array of proteins (1Roberts G.C. Smith C.W. Alternative splicing: combinatorial output from the genome.Curr. Opin. Chem. Biol. 2002; 6: 375-383Crossref PubMed Scopus (110) Google Scholar, 2Farriol-Mathis N. Garavelli J.S. Boeckmann B. Duvaud S. Gasteiger E. Gateau A. Veuthey A.-L. Bairoch A. Annotation of post-translational modifications in the Swiss-Prot knowledge base.Proteomics. 2004; 4: 1537-1550Crossref PubMed Scopus (92) Google Scholar). Due to the large number of unique protein species produced coupled with differences in their relative abundance, there is as of yet no single proteomics technology that has the analytical capacity or sensitivity to realize the goal of complete proteome coverage. One strategy to maximize proteome coverage is to combine synergistic proteomics technologies, particularly if each technology reveals a unique subset of proteins. Using the inner mitochondrial membrane as a model subproteome, we compared the ability of three protein separation methods (two-dimensional LC (2-DLC 1The abbreviations used are: 2-DLC, two-dimensional LC; IMM, inner mitochondrial membrane; PF2D, ProteomeLab™ PF 2D Protein Fractionation System (Beckman Coulter); 1-DLC, one-dimensional reversed phase HPLC; 2-DE, two-dimensional gel electrophoresis; RP, reversed phase; CF, chromatofocusing; PTM, post-translational modification; 1-D, one-dimensional; Bis-Tris, 2-[bis(2-hydroxyethyl)amino]-2-(hydroxymethyl)propane-1,3-diol. 1The abbreviations used are: 2-DLC, two-dimensional LC; IMM, inner mitochondrial membrane; PF2D, ProteomeLab™ PF 2D Protein Fractionation System (Beckman Coulter); 1-DLC, one-dimensional reversed phase HPLC; 2-DE, two-dimensional gel electrophoresis; RP, reversed phase; CF, chromatofocusing; PTM, post-translational modification; 1-D, one-dimensional; Bis-Tris, 2-[bis(2-hydroxyethyl)amino]-2-(hydroxymethyl)propane-1,3-diol. with the PF2D), one-dimensional reversed phase HPLC (1-DLC; reversed phase high performance liquid chromatography (RP-HPLC)), and two-dimensional gel electrophoresis (2-DE) to determine the relative overlap in protein separation for these technologies. 2-DE, a classical proteomics technology that separates proteins based on their pI and molecular weight, has a practical dynamic range of 104 orders of magnitude (for reviews, see Refs. 3Van den Bergh G. Arckens L. Recent advances in 2D electrophoresis: an array of possibilities.Expert Rev. Proteomics. 2005; 2: 243-252Crossref PubMed Scopus (58) Google Scholar and 4Rabilloud T. Two-dimensional gel electrophoresis in proteomics: old, old fashioned, but it still climbs up the mountains.Proteomics. 2002; 1: 3-10Crossref Scopus (666) Google Scholar). This restricts the analysis of a proteome to the most abundant proteins, and so it often underrepresents proteins with extreme hydrophobicity, mass, or isoelectric point. Another common separation method is 1-DLC, which separates proteins based on hydrophobicity. In proteomics, 1-DLC has primarily been used for peptide separation prior to MS, but it can be used for protein separation prior to enzymatic digestion and analysis by MS (for a review, see Ref. 5Neverova I. Van Eyk J.E. Role of chromatographic techniques in proteomic analysis.J. Chromatogr. B Anal. Technol. Biomed. Life Sci. 2005; 815: 51-63Crossref PubMed Scopus (88) Google Scholar; e.g. see Refs. 6Morris Jr., D.L. Sutton J.N. Harper R.G. Timperman A.T. Reversed-phase HPLC separation of human serum employing a novel saw-tooth gradient: toward multidimensional proteome analysis.J. Proteome Res. 2004; 3: 1149-1154Crossref PubMed Scopus (18) Google Scholar and 7Fujii K. Nakano T. Hike H. Usui F. Bando Y. Tojo H. Nishimura T. Fully automated online multi-dimensional protein profiling system for complex mixtures.J. Chromatogr. A. 2004; 1057: 107-113Crossref PubMed Scopus (33) Google Scholar). 2-DLC traditionally couples a charge-based method (e.g. isoelectric focusing or strong cation exchange) as a first dimension with RP-HPLC as the second dimension thereby increasing the extent of protein fractionation compared with 1-DLC. As with 1-DLC, this method has been used primarily in proteomics for peptide separation; however, it is increasingly being applied to the separation of complex intact protein mixtures (for a review, see Ref. 5Neverova I. Van Eyk J.E. Role of chromatographic techniques in proteomic analysis.J. Chromatogr. B Anal. Technol. Biomed. Life Sci. 2005; 815: 51-63Crossref PubMed Scopus (88) Google Scholar; e.g. see Refs. 8Garbis S. Lubec G. Fountoulakis M. Limitations of current proteomics technologies.J. Chromatogr. A. 2005; 1077: 1-18Crossref PubMed Scopus (180) Google Scholar, 9Baumann M. Meri S. Techniques for studying protein heterogeneity and post-translational modifications.Expert Rev. Proteomics. 2004; 1: 207-217Crossref PubMed Scopus (35) Google Scholar, 10Swanson S.K. Washburn M.P. The continuing evolution of shotgun proteomics.Drug Discov. Today. 2005; 10: 719-725Crossref PubMed Scopus (71) Google Scholar). This increased use is (in part) due to the commercialization of 2-DLC systems, including the PF2D (Beckman Coulter), which is based upon the system developed by Lubman and colleagues (e.g. Refs. 11Wang Y. Wu R. Cho K.R. Shedden K.A. Barder T.J. Lubman D.M. Classification of cancer cell lines using an automated two-dimensional liquid mapping method with hierarchical clustering techniques.Mol. Cell. Proteomics. 2006; 5: 43-52Abstract Full Text Full Text PDF PubMed Scopus (22) Google Scholar, 12Sheng S. Chen D. Van Eyk J.E. Multi-dimensional liquid chromatography separation of intact proteins by chromatographic focusing and reversed phased of the human serum proteome: optimization and protein database.Mol. Cell. Proteomics. 2006; 5: 26-34Abstract Full Text Full Text PDF PubMed Scopus (100) Google Scholar, 13Zheng S. Schneider K.A. Barder T.J. Lubman D.M. Two-dimensional liquid chromatography protein expression mapping for differential proteomic analysis of normal and O157:H7 Escherichia coli.BioTechniques. 2003; 35: 1202-1212Crossref PubMed Scopus (44) Google Scholar, 14Lubman D.M. Kachman M.T. Wang H. Gong S. Yan F. Hamler R.L. O’Neil K.A. Zhu K. Buchanan N.S. Barder T.J. Two-dimensional liquid separations-mass mapping of proteins from human cancer cell lysates.J. Chromatogr. B Anal. Technol. Biomed. Life Sci. 2002; 782: 183-196Crossref PubMed Scopus (115) Google Scholar). The PF2D uses chromatofocusing in the first dimension (separating proteins based on their pI) and reversed phase chromatography in the second dimension. Except for a single report utilizing chromatographic isoelectric focusing (first dimension) to separate peptides prior to a multidimensional protein identification technology experiment (15Chen E.I. Hewel J. Felding-Habermann B. Yates III, J.R. Large scale protein profiling by combination of protein fractionation and multidimensional protein identification technology (MudPIT).Mol. Cell. Proteomics. 2006; 5: 53-56Abstract Full Text Full Text PDF PubMed Scopus (153) Google Scholar) the PF2D has been used exclusively for protein separation. To date, the only comparison of the PF2D with any other protein separation technology examined the rice proteome through a limited comparison between the PF2D and 2-DE (16Komatsu S. Zang N. of two proteomics techniques used to proteins by in Proteome Res. 2006; 5: PubMed Scopus Google Scholar). both the of proteome coverage by PF2D and with other proteins separation method is not the of ATP in the cell, and their has been in different both an and an inner membrane with the of the in the inner mitochondrial membrane To these a of the of this subproteome post-translational modifications is of The human mitochondrial proteome: protein modifications and J. Biol. 2005; PubMed Scopus (71) Google Scholar, J.E. Sci. 2006; 26-34Abstract Full Text Full Text PDF PubMed Scopus Google Scholar, A. M.P. on mitochondrial protein 2005; PubMed Scopus Google Scholar). intact been using different proteomics technologies K. F. A. Zhu H. proteomic analysis of a cell model of Cell. Proteomics. 2004; Full Text Full Text PDF Scopus (110) Google Scholar, E. B. S. of the human mitochondrial 2003; 3: Scopus Google Scholar, E. B. coverage of the human mitochondrial proteome using multidimensional liquid chromatography coupled with Proteome Res. 2004; 3: PubMed Scopus (88) Google Scholar, K. Wu L. D. of mitochondrial proteome from human Cell. Proteomics. 2005; 4: Full Text Full Text PDF PubMed Scopus (100) Google Scholar, Van Eyk J.E. in the Res. 2003; PubMed Scopus Google Scholar, E. 2003; Full Text Full Text PDF PubMed Scopus Google Scholar, T. mitochondrial and for in 2004; PubMed Scopus Google Scholar, J. M. J.R. E. S. M. N. M. analysis of protein and in 2003; Full Text Full Text PDF PubMed Scopus Google Scholar, S. I. J. F. analysis of the mitochondrial inner Biol. Chem. 2003; Full Text Full Text PDF PubMed Scopus Google Scholar, S. the mitochondrial Rev. Proteomics. 2005; 4: Scopus Google these only of the mitochondrial proteins S. J. B. A. M. identification of human mitochondrial genes through 2006; PubMed Scopus Google Scholar). these can a of up to S. J. B. A. M. identification of human mitochondrial genes through 2006; PubMed Scopus Google the number of mitochondrial proteins is not with the mitochondrial from proteomics analysis has been the toward proteins to the and membrane and the of proteins E. B. S. of the human mitochondrial 2003; 3: Scopus Google Scholar, E. 2003; Full Text Full Text PDF PubMed Scopus Google Scholar). To the coverage of the subproteome, S. I. J. F. analysis of the mitochondrial inner Biol. Chem. 2003; Full Text Full Text PDF PubMed Scopus Google Scholar, S. the mitochondrial Rev. Proteomics. 2005; 4: Scopus Google Scholar) used an and demonstrated that there are novel proteins this Using the S. I. J. F. analysis of the mitochondrial inner Biol. Chem. 2003; Full Text Full Text PDF PubMed Scopus Google Scholar, S. the mitochondrial Rev. Proteomics. 2005; 4: Scopus Google Scholar, S. J. B. A. M. identification of human mitochondrial genes through 2006; PubMed Scopus Google Scholar, B. J. E. and of and of and Biol. PubMed Scopus Google Scholar) we the that there be a minimal overlap of observed proteins using three different separation technologies 1-DLC, and thereby proteome coverage. from and the subproteome was to the of B. J. E. and of and of and Biol. PubMed Scopus Google Scholar). was as previously S. the mitochondrial Rev. Proteomics. 2005; 4: Scopus Google Scholar). 2-DE, the proteins by in or in for prior to the and 2-DLC, the proteins in by with and in of PF2D chromatofocusing (Beckman Coulter, 1-DLC the subproteome was in with The subproteome was on or with protein in of for and then a method was applied as for for for to and for using a cell To separate proteins with pI the was in of as for for for to for and for which time to and for in with by in with in a and proteins by or protein was for in prior to gel and by or 2-DE to A. M. M. of proteins Chem. PubMed Scopus Google Scholar). with a Data on a between protein 2-DLC analysis of proteins was on a PF2D (Beckman S. Chen D. Van Eyk J.E. Multi-dimensional liquid chromatography separation of intact proteins by chromatographic focusing and reversed phased of the human serum proteome: optimization and protein database.Mol. Cell. Proteomics. 2006; 5: 26-34Abstract Full Text Full Text PDF PubMed Scopus (100) Google Scholar). The first dimension proteins on the of their pI using a on the from the first dimension and the second dimension RP-HPLC The for digestion with and analysis the PF2D, the first and second in an in the first dimension on a chromatofocusing by two in their and to a from to the was for with a of of protein was the a was the was by the for the was with the of the and and Each from the first dimension or protein was in and by RP-HPLC using in which was and B was in with a of Protein was for an of a 2-DLC and for a composite all pI see for a 1-DLC The reversed phase a of and Protein identification for 2-DE and both LC and was based on MS and gel from two-dimensional to F. identification of proteins from a method for the of to PubMed Scopus Google and prior to enzymatic digestion with modified peptides with by two with In the of the protein from multiple by of from 2-DE gel with of on a MS and then using a or in the with an of a of and a of was for each was using a peptide from LC as previously S. 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Zang N. of two proteomics techniques used to proteins by in Proteome Res. 2006; 5: PubMed Scopus Google Scholar, A. G. A. N. chromatography for proteomic analysis in Chromatogr. B Anal. Technol. Biomed. Life Sci. 2006; PubMed Scopus Google Scholar). more approach be to there is (e.g. protein T. analysis of by two-dimensional liquid chromatography and Chromatogr. A. 2006; PubMed Scopus Google Scholar, K. Barder T.J. Lubman D.M. of low molecular proteins by liquid 2004; PubMed Scopus Google Scholar, E. of proteins in the human serum 2005; Google that the number of proteins in a this allow to be the MS of non-redundant proteins was identified by 2-DLC through analysis of a of proteins identified in more than two (in dimension) that these proteins may a K. J. Lubman D.M. Barder T.J. Protein pI due to modifications in the separation and of Chem. 2005; PubMed Scopus Google Scholar). The α-subunit of F1F0 ATP synthase two second dimension it also has a that These by by for the This that the α-subunit from F1F0 ATP synthase of in whereas a molecular in a the was not identified in the 2-DE analysis to low was by 2-DE the pI of the α-subunit is than the multiple pI observed by 2-DE in the of the first dimension of the The 2-DLC was also in protein also in the of the first dimension but from the second dimension different and analysis that the less of based upon the identification of three unique The both protein and of based upon the of unique The different for that there is a yet 1-DLC, the proteins in with and by reversed phase chromatography using a from to B analysis of identified non-redundant proteins with each between and proteins The α-subunit of F1F0 ATP synthase in reversed phase with to observed by 2-DLC The subproteome database from the three protein separation technologies of a of 348 non-redundant proteins was overlap between the proteins observed by the three different methods and only 24% overlap between any two methods. of the proteins identified only by 2-DLC, and identified only by 1-DLC mass, and This comparison the and of the three protein separation methods. with optimization of and 2-DE is limited with to proteins with extreme mass, hydrophobicity, and it has the of multiple of proteins with differences in molecular or isoelectric the 2-DLC and 1-DLC the of for low proteins and proteins with pI the PF2D the proteins are in the from the first dimension so pI is for this of To date, the of studies using the PF2D LC not this the PF2D an protein compared with the other two methods by to be to protein to proteome coverage. 2-DLC and 1-DLC the the overlap in protein was This may be due to different used in for each 2-DLC a whereas RP-HPLC as as an proteins are to in M. T. proteins and proteomics: PubMed Scopus Google and the of an to the for 1-DLC may increased the identification of of proteins. of the inner mitochondrial membrane and are M. E. I. G. A. of transmembrane in membrane the 10: PubMed Google Scholar) to multiple transmembrane from to not which their These proteins a range of to yet an of hydrophobicity. or protein may be by the in this The detection of this unique of proteins is for in which the goal is to determine which proteins are however, for studies 1-DLC is of limited use due to ability to resolve proteins compared with both LC methods most methods for In this 2-DLC has the analysis of the can the number of are large for the intact mitochondrial This the database produced by and colleagues proteins E. B. S. of the human mitochondrial 2003; 3: Scopus Google Scholar) and that was E. B. coverage of the human mitochondrial proteome using multidimensional liquid chromatography coupled with Proteome Res. 2004; 3: PubMed Scopus (88) Google Scholar) by proteins. This used to resolve mitochondrial protein by and In a separate J. M. J.R. E. S. M. N. M. analysis of protein and in 2003; Full Text Full Text PDF PubMed Scopus Google Scholar) to non-redundant mitochondrial proteins in a from and This database was to non-redundant proteins through the of and human proteins from the Proteome database and mitochondrial proteins from the it was not by the different the separation by The PF2D also based on protein and database proteins of the not previously identified in these The only subproteome database to identified proteins using shotgun digestion and separation by multiple chromatographic S. I. J. F. analysis of the mitochondrial inner Biol. Chem. 2003; Full Text Full Text PDF PubMed Scopus Google Scholar). these proteins prior to separation and there is a of database proteins of not in this database and proteins not observed in any of these of the protein and This is due to both the of the proteins prior to analysis E. B. S. of the human mitochondrial 2003; 3: Scopus Google Scholar, E. 2003; Full Text Full Text PDF PubMed Scopus Google Scholar, J. M. J.R. E. S. M. N. M. analysis of protein and in 2003; Full Text Full Text PDF PubMed Scopus Google Scholar) and the increased power of proteins based on a of The of these proteins observed only using 1-DLC that this is a technology to use for the of novel proteins in a is to that the for is B. J. E. and of and of and Biol. PubMed Scopus Google Scholar) and that the of the proteins that had not been previously are to be with the mitochondria. The a low of overlap between the protein separation methods and coverage of the proteome by using an using the PF2D, a 2-DLC we to a unique subset of proteins not observed by 2-DE or 1-DLC. This may be due to in protein for the PF2D to for 1-DLC was to resolve a unique of proteins with the of the proteins not observed by only observed using the 1-DLC. the the power of different separation technologies and also the that can using different separation methods.

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