A team led by researchers at the Swiss Federal Institute of Technology Zurich has devised a mass spec workflow enabling high-throughput absolute quantitation of entire proteomes.
The technique enables the reproducible quantification of a target proteome over multiple states, providing data amenable to the sort of cluster analysis that has been widely used in genomic work like transcriptome profiling but much less used in proteomics, said ETH researcher Ruedi Aebersold, leader of the study.
Using the method, which was described in a paper published this week in Molecular Systems Biology, the scientists quantified 1,680 proteins in the human pathogen Leptospira interrogans at 25 different cellular states, obtaining new insights into proteome changes involved in the organism's pathogen progression and antibiotic defense.
The work represents "the first time that really quantitative measurements on multiple states of a proteome have been done," Aebersold told ProteoMonitor. "This allows us to move proteomics to a similar situation as the genomics community, which with transcript profiling has [been able] to do profiles of tens or even dozens of states and then do cluster analysis," allowing scientists to "get information out of the dataset that's not really apparent from just a single protein but that is from the proteomic pattern as a whole."
The technique uses an initial set of LC-MS/MS runs to experimentally determine the best flying proteotypic peptides for each protein. This allows for a mass inclusion list-driven strategy that focuses MS-sequencing time on only these best flying PTPs, maximizing protein coverage. Quantification of the detected proteins is achieved by correlating the average of the signal intensities of the three best responding peptides per protein with a calibration curve built using a set of isotopically labeled reference peptides.
The quantification provided by the technique is "not super precise" Aebersold noted, estimating that it can detect differences of one-and-a-half-fold and greater, but, he said, "it is very fast" and vastly less expensive than adding heavy-labeled peptides for every protein.
Also key, Aebersold said, is that it provides absolute quantitation, meaning protein copy numbers per cell.
"Most techniques used in proteomics today give you relative quantitation, like from one point to the next a protein is up two-fold or down two-fold," he said. "But if [the expression changes] from 20 to 40 copies per cell, that has different implications than if it were to go from 10,000 to 20,000 copies per cell – for estimating the energy consumption, for instance – so this is additional information."
The method is in principle similar to selected-reaction monitoring, Aebersold said, in that it uses predetermined parameters to guide the mass spectrometer's analysis. Determining these parameters for the L. interrogans study required 28 LC-MS/MS runs, or several days of mass spec work, and these parameters proved transferrable when tried on a different model machine in a different laboratory, he noted.
The great advantage of the technique compared to SRM-MS is its throughput, Aebersold said. While SRM-MS is typically limited to several hundred targeted peptides in a run, the ETH technique can cover thousands of peptides in a run.
It suffers in terms of dynamic range, however. While SRM-MS can cover as many as five orders of dynamic range, the new method can go up to only three or four, making it best suited, Aebersold said, to studying organisms like bacteria that have only moderately complex proteomes.
"Both techniques use the same idea," he said. "You predetermine some peptides that you would like to specifically analyze, but then the two techniques have different performance profiles. One is broad but not as deep and the other is very deep but not as broad."
He noted that another new mass spec technique called SWATH could potentially offer both the breadth of the new method and the depth of SRM-MS. Developed by Aebersold's lab on AB Sciex's TripleTOF 5600 instrument, the method was introduced by AB Sciex at the American Society for Mass Spectrometry's annual meeting in June and has been described in a paper by Aebersold that is currently under review (PM 06/10/2011).
Like SRM-MS, SWATH targets for fragmentation particular precursor ion windows where it expects a peptide of interest to be present and then looks at the level of fragment ions to detect and quantify that peptide.
The difference, Aebersold said, is that, enabled by the speed of the 5600, SWATH selects a wide precursor window of 25 mass units and moves through the entire precursor ion mass range in segmented windows of 25 mass units, allowing it to "basically generate fragment ions from everything that is eluting from the [LC] column."
Then, using the SRMAtlas developed in an effort led by Aebersold and the Institute for Systems Biology's Rob Moritz, researchers search the fragment ion spectra captured by the machine against the reference spectra in the SRMAtlas to make the peptide IDs (PM 09/24/2010).
The unique search strategy is necessary, Aebersold said, because the large composite fragment ion spectra generated by the technique would "choke" a typical search engine.
"So we use the SRM libraries to select and find specific patterns in these composite spectra that correspond to target peptides," he said. "We don't try to explain every spectrum like we would with sequence database searching, we simply want to find patterns that tell us whether or not a particular peptide is present and in what quantity."
According to Aebersold, an initial study using the technique showed it could identify proteins in a complex sample over four orders of magnitude of dynamic range with quantitation equivalent to that provided by SRM-MS.
"In terms of sensitivity of detection, [SWATH is] probably a factor of three or four off from SRM, but it's approaching the performance of SRM," he said..
If the method fulfills this promise it could provide "a further tool" for quantitative measurements on multiple states of a proteome like those described in the MSB paper, Aebersold said, noting that "applying the SWATH technique with the same mindset would probably further increase throughput."
One limitation of SWATH compared to the MSB technique is its reliance on the SRMAtlas, which currently contains reference spectra only for human, mouse, and yeast proteins. For the MSB method, on the other hand, the researchers were able to "generate the reference library basically on the fly," Aebersold said.
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