Tag Archives: degradation

Live: Lecture by Nobel Laurate Avram Hershko

Today I am at the the symposium “Protein Chemistry ‐ Applications to Combat Diseases”, which takes place in Copenhagen a few minutes walk from where I work.

This morning started with a keynote lecture by Nobel Laurate Avram Hershko on regulation of the cell division cycle by ubiquitin‐mediated protein degradation. This post is just a very quick write-up and a few photos made during and immediately after his presentation.

Avram Hershko presenting in Copenhagen

Most of the early work on ubiquitylation was done on model proteins, most of which were extracellular. Interestingly, what spurred Avram Hershko on to study ubiquitylation of physiologically relevant proteins was the early work on cyclin degradation for which Tim Hunt received the Nobel Prize. Tim Hunt speculated speculated that there was a cyclin protease that would break down cyclins. However, Avram Hershko showed in 1991 that cyclins are in fact not degraded by a specific protease, but are rather targeted for proteasomal degradation by a specific ubiquitin ligase. Showed this in JBC papers in 1991 and 1994. One year later his group identified this ubiquitin ligase to be what is now known as the Anaphase Promoting Complex (APC) / Cyclosome (APC/C).

The role of APC/C in ubiquitylation and degradation of cyclins

In addition to being crucial for degradation of cyclins, APC/C is also required for entry into anaphase of the cell cycle (hence the name Anaphase Promoting Complex). This because it is responsible for targeting the securin protein for degradation, which in turns releases separase activity to degrade the cohesin rings that hold together sister chromatids.

Having worked on other cell-cycle proteins for many years, Avram Hershko has in recent years returned his interest to APC/C, more specifically to understand how the inhibition of APC/C is released, which in turn leads to the whole series of events described above.

Release of APC/C from checkpoint inhibition

Analysis: Degradation signals correlate with protein half-life

I yesterday blogged about how the protein half-life data from the O’Shea lab fit well with my earlier analyses of transcriptional regulation during the budding yeast cell cycle and with the just-in-time assembly hypothesis. However, I have now realized that the same data set can be used to test the validity of the sequence-based predictions of protein degradation signals that I relied on for the cell-cycle study.

To this end, I divided the budding yeast proteome into six groups: proteins with a D-box, proteins without a D-box, proteins with a KEN-box, proteins without a KEN-box, proteins with a PEST region, and proteins without a PEST region. For each of these six groups of proteins, I simply plotted the distribution of protein half-lives as a histogram:

The figure shows that for all three degradation signals, proteins with the sequence motif tend to have shorter half-lives than proteins without the motif. These differences are all statistically significant according to the Mann-Whitney U test (D-box, P < 10-6; KEN-box, P < 0.02; PEST region, P < 10-15). It is noteworthy that the KEN-box motif gives a far weaker correlation with protein half-live than the two other degradation signals, as it was also the only degradation signal that did not correlate with transcriptional cell-cycle regulation in budding yeast (see supplementary information of Jensen et al., 2006).

In summary, proteins that contain putative degradation signals have significantly shorter half-lives than proteins that do not contain such signals. The only caveat is that long sequences are more likely to match the sequence motifs, and that O’Shea and colleagues found a negative correlation between sequence length and protein half-life. The correlations described here could thus be a secondary effect; however, it is also possible that the presence of degradation signals in long sequences is the missing explanation for their short half-lives.

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Analysis: Cell-cycle-regulated genes encode short-lived proteins

In relation to an entirely different analysis than the one I will describe here, I downloaded the protein half-life data for budding yeast that was published in PNAS by the O’Shea lab about two years ago:

Quantification of protein half-lives in the budding yeast proteome

A complete description of protein metabolism requires knowledge of the rates of protein production and destruction within cells. Using an epitope-tagged strain collection, we measured the half-life of >3,750 proteins in the yeast proteome after inhibition of translation. By integrating our data with previous measurements of protein and mRNA abundance and translation rate, we provide evidence that many proteins partition into one of two regimes for protein metabolism: one optimized for efficient production or a second optimized for regulatory efficiency. Incorporation of protein half-life information into a simple quantitative model for protein production improves our ability to predict steady-state protein abundance values. Analysis of a simple dynamic protein production model reveals a remarkable correlation between transcriptional regulation and protein half-life within some groups of coregulated genes, suggesting that cells coordinate these two processes to achieve uniform effects on protein abundances. Our experimental data and theoretical analysis underscore the importance of an integrative approach to the complex interplay between protein degradation, transcriptional regulation, and other determinants of protein metabolism.

The idea that transcriptional regulation goes hand-in-hand with protein degradation is fully consistent with the just-in-time assembly hypothesis. I thus examined the distributions of protein half-lives for dynamic (i.e. periodically expressed) and static (i.e. not periodically expressed) proteins:

The histogram suggests that dynamic proteins are shifted towards shorter half-lives relative to static proteins. The difference is indeed statistically significant according to the Mann-Whitney U test (P < 10-4). This result supports the sequence-based observation that dynamic proteins contain more D-box, KEN-box, and PEST degradation signals than static proteins.

I next tested if the half-life of the dynamic proteins varies during the cell cycle by make scatter plot of the protein half-life as function of the time of peak expression for the corresponding mRNA:

There appears to be no correlation. Together, these analyses indicate that dynamic proteins have shorter half-lives than static proteins, irrespective of when in the cell cycle they are expressed.

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