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Yeast Study Highlights Differences and Linkages Between Transcriptomic and Proteomic Regulation


A team led by researchers at the Swiss Federal Institute of Technology Zurich and University College London has completed a global proteomic and transcriptomic analysis measuring levels of proteins and RNAs in fission yeast cells in both quiescent and proliferating states.

The study, which was published in the current edition of Cell, is one of the most comprehensive of its kind performed to date and raises a number of interesting questions regarding the mechanisms of cell function, Ruedi Aebersold, an ETH Zurich researcher and study leader, told ProteoMonitor.

For the project, Aebersold and his lab collaborated with University College researcher Jurg Bahler, whose team brought its transcriptomics expertise to the effort. While proteomics has typically been seen as more technically challenging than nucleic acid-based work, in this case the transcriptomic work was as or more demanding than the protein portion of the study, Aebersold said.

"Absolute quantification of transcripts actually is non-trivial," he noted. "We always hear about genomics being so fast and so powerful, but if you really want quantitatively accurate data there are a lot of hoops to go through to calibrate the data from the high-throughput sequencing runs. And actually this was a technically more challenging part than the protein analysis."

For the proteomic portion of the study, the researchers used mass spec analysis on a Thermo Fisher Scientific Orbitrap Velos instrument, applying a workflow based on a method described by Aebersold's group in a 2011 Molecular Systems Biology paper (PM 7/22/2011).

The researchers determined the absolute abundances for 39 proteins via spiked-in reference peptides and then used that data to do proteome-wide quantitation by translating the mass spec intensities of all peptides present to an absolute copy number per cell. In this way they quantified roughly 3,397 proteins in proliferating cells and 2,500 in quiescent cells, correlating these expression levels with measurements of their corresponding transcripts.

The study, Aebersold said, offers a number of insights into cell function and highlights a variety of potential avenues for future research. For instance, he noted, the very small number of transcripts – typically fewer than 10 per cell – compared to the much larger number of proteins – averaging in the thousands of copies per cell – suggests two different modes of regulation at these different levels.

The lower number of transcripts present "means that the transcript regulation is a stochastic domain," Aebersold said. "And this of course has implications for how processes are controlled at the transcriptional level. The protein levels, by contrast, are much higher. The mean is in the range of thousands [per cell], so they are clearly the non-stochastic domain. So the means of regulation are probably completely different."

Despite this likely difference in regulatory mechanisms, Aebersold noted, the study found evidence of great coordination between the two levels. For instance, using their proteomics and transcriptomic data independently, the researchers were able to arrive at roughly matching estimates of the per-cell number of ribosomes – complexes made up of single copies of various proteins and transcripts.

"Things just kind of quantitatively make sense," Aebersold said. "So, of course, you would say, 'Sure, why not?" But the question is: How is this being accomplished? Where is this information located? How does the cell know that there are so many transcripts that should be translated and how many ribosomes it should make?"

"It was a really interesting finding how well-aligned and coordinated these levels are even though they are clearly controlled by different mechanisms," he said.

Also interesting was the difference between the response of transcript levels and protein levels in the cells as they shifted from a proliferating to quiescent state, Aebersold noted. While transcript levels dropped globally, the cells' overall protein numbers remained roughly constant, with some proteins being down-regulated and others experiencing up-regulation.

"With the mRNA virtually everything gets down-regulated with no distinction between functional classes," Aebersold said. "And that is not true on the protein level. Some [proteins] are down-regulated in the resting state and some are not."

He added that in general, proteins that are not down-regulated are the ones the cell expects to use again when it exits the resting state. "So ribosomal [proteins], for instance, stay up, [as do] other classes that could be expected to be needed when the cell needs to get going again," he said.

"The cell through evolution has developed a mechanism that positions it to be ready to get going again when a better environment occurs, and I think it would be really interesting in the future to follow up how this is controlled," Aebersold said. "Where are the decision points? From a mechanistic perspective this raises a lot of questions."

He noted that other researchers have made similar observations regarding single proteins or specific classes of proteins, but that few studies have provided this sort of absolute quantitative data on a global scale.

"Now we have a kind of global look at how the transcriptome and proteome react [under proliferating and quiescent conditions], and I think it opens up questions that will now be picked up on by mechanism-oriented biologists," he said.

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