A team led by Utrecht University researcher Albert Heck has completed a proteomic comparison of embryonic and human induced pluripotent stem cells.
The study, which was published in the current edition of Molecular Systems Biology, found only a slight difference in protein expression between ES and iPS cells, reinforcing results from a similar effort by the lab of University of Wisconsin-Madison researcher Joshua Coon published in Nature Methods earlier this year (PM 9/16/2011).
The work also lends support to the notion, raised by recent research from the labs of Swiss Federal Institute of Technology Zurich scientist Ruedi Aebersold and Max Planck Institute researcher Matthias Mann that proteomics researchers are approaching the outer limits of the number of different proteins that can be quantitated in a human cell using conventional LC-MS workflows (PM 11/18/2011).
In their study, the Heck researchers identified a total of 10,628 unique proteins, roughly on par with the 10,006 proteins in U2OS cells and 10,255 proteins in HeLa cells that the Aebersold and Mann labs, respectively, identified in a pair of papers published – also in MSB – several weeks ago.
At the time, Aebersold told ProteoMonitor he believed that his team had essentially saturated the proteome accessible via the LC-MS/MS workflow that they used. “That’s not to say that there are not other types of proteins in these cells,” he said. “But we would claim that with this workflow — this particular type of cell lysis, this particular type of digestion, this particular type of LC-MS/MS — we would be unlikely to discover many additional proteins even if we kept sequencing.”
According to Javier Munoz, a postdoctoral research in Heck’s group and first author on the MSB stem cell paper, the Utrecht University researchers also reached saturation of their system.
“We see in our analysis that you don’t get more [protein] identifications by reanalyzing the samples,” he told ProteoMonitor. “It’s interesting that the three studies published at almost the same time, using pretty much the same technique, ended up with more or less the same number of proteins.”
Like Aebersold, Munoz noted that use of different sample-prep techniques and different enzymes to create peptide digests would likely enable access to additional proteins, but, he said, “I think we are pretty close to full proteome coverage. I think we could maybe start to say that this is the number that reflects the total protein content of human cell lines.”
Of the more than 10,000 proteins the researchers quantified, only 58 were significantly differentially regulated in ES and iPS cells. This was fewer than the 293 differentially regulated proteins found in the Coon study, but, Munoz said, this difference is less significant than the larger finding, supported by both studies, that the proteomes of ES and iPS cells are largely the same.
He also noted that there were nine proteins that were found to be differentially regulated in both groups’ work, a discovery that he said “was highly significant statistically.”
Doug Phanstiel, first author on the UW-Madison paper and now a post-doc in Mike Snyder’s lab at Stanford University, agreed with Munoz about the similarity of the groups’ findings
“I think we came to the same conclusion,” he told ProteoMonitor. “The bottom line is that ES cells and IPS cells are incredibly similar at the proteomic level. If you look closely enough, in both papers you can find differences, but the differences are pretty slight, so the functional impact is possibly pretty small.”
The larger number of differences found by the Coon researchers likely stemmed from their use of more replicates. While the Heck lab analyzed three different cell lines in duplicate, the Coon team analyzed four different ES cell lines and four different iPS cell lines in triplicate, for a 24-sample comparison.
“That gave us a lot of statistical power, and that probably explains why we found more differences than they did,” Phanstiel said. He added, though, that the Heck researchers’ use of the significance analysis of microarrays, or SAM, statistical test, “was a nice approach” that let them “detect differences without having to do so many replicates.”
In their study, the Heck team fractionated their samples via strong cation exchange chromatography followed by mass spec analysis on a Thermo Scientific LTQ Orbitrap XL ETD instrument for one set of samples and an LTQ-Orbitrap Velos for another set.
They labeled the samples using an in-house dimethyl labeling chemistry that tags primary amine groups and allows for multiplexing of up to three different samples.
According to Munoz, the Utrecht University and UW-Madison scientists have been in communication regarding their work, and the Heck lab is currently analyzing the Coon team’s data using its own statistical pipeline.
They have also deposited their data into the Stem Cell –Omics Repository, or SCORE, resource that the UW-Madison researchers launched upon publication of their study. The repository is an open-access database for collecting and analyzing quantitative information about pluripotent stem cells, including data on mRNA, protein, and post-translational modifications.
The SCORE initiative “is pretty interesting,” Munoz said, “because previously there was nothing like that really dedicated to the stem cell community. It’s a great idea to have a repository for all the groups working on stem cell proteomics.”
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