New & Noteworthy
November 9, 2016
Like a ruined cookie with too much salt, a cell can go haywire when it has too many copies of certain genes. And of course, cells can deal perfectly well with too many copies of other genes. Just like adding too many chocolate chips to your cookies might make an even better cookie!
Finding out which genes are like salt and which ones are like chocolate chips is of more than just general biological interest. It might help us to explain why cancer happens and to possibly find better treatments.
As you probably know, cancer cells are pretty messed up genetically. Their DNA is littered with mutations, rearrangements and somatic copy number amplifications (SCNAs).
A big reason for this genetic jumble is early DNA changes that increase the rate of mutations in a cell. This “mutator” trait makes a cell more likely to stumble on the mutations it needs to grow out of control or refuse to die.
In their new study in GENETICS, Ang and coworkers set out to find genes that can cause a mutator phenotype when they are part of a SCNA. In other words, which genes lead to an increased mutation rate when expressed at a higher level.
This is important because there are so many SCNAs in a typical cancer cell that it can be hard to figure out which ones matter and which ones don’t (or to put it into cancer parlance, to tell the drivers from the passengers). And despite all of the CRISPR hoopla and other mammalian resources, it would still be a very long process to find “dosage mutator” genes in cell culture and/or living animals.
Which is why Ang and coworkers used our favorite workhorse, the yeast Saccharomyces cerevisiae, to find genes that may cause an increased mutation rate when overexpressed.
The assay is conceptually simple. Yeast that have a functioning CAN1 gene do not survive in the presence of the drug canavanine. So these researchers looked for cells that did better in the presence canavanine when overexpressing a single gene. Presumably, they are surviving because that extra gene resulted in the CAN1 gene being mutated more often because of an increased mutation rate.
They found 37 genes that fit the bill, 18 of which that were involved in biological pathways known to affect genome stability. Combining this with previous studies that looked at gene deletions, this brings the grand total of suspected yeast mutator genes to 210.
Most of these 210 were identified because of mutations that made them stop working which can make figuring out why they cause the mutator phenotype relatively simple. For example, if a mutation kills a gene responsible for fixing DNA mistakes, then you are going to get more DNA mistakes in that cell. It is a little trickier to understand how extra copies of a gene might cause an increased mutation rate.
Ang and coworkers focused on trying to figure out the mechanism behind their top 5 dosage mutator genes: PIF1, MPH1, UBP12, RRM3, and DNA2. Since 4/5 of these code for helicases, they first checked to see if just being a helicase is enough to be a dosage mutator gene. It isn’t.
In the next set of experiments, they wanted to determine if the five strains, each overexpressing one of these five genes, had a higher mutation rate by the same mechanism. They tested this by determining the sensitivity of these 5 strains to 3 different DNA damaging agents. The idea is that if they share the same mechanism, they should have the same sensitivity profiles to each of these agents. They did not.
For example, overexpressing MPH1 resulted in a higher sensitivity to all three agents while overexpressing UBP12 only increased sensitivity to two of them. So each strain probably has an increased mutation rate for a different reason.
They next wanted to see if the increased mutation rate was due to a loss or gain of function. They did this by comparing the profiles of strains either deleted for or overexpressing the dosage mutator genes. The idea is that if overexpression leads to a loss of function, then deleting and overexpressing the genes should have the same profile. The three they could test like this did not.
The authors conclude from this that the increased mutation rate for MPH1, UBP12, and RRM3 is most likely due to the gain of an inappropriate function as opposed to a loss of function. In a final set of experiments, Ang and coworkers focused on what that new function might be in their strongest mutant, MPH1.
First they showed that of the three activities associated with Mph1p, only DNA binding and not its ATPase or helicase activities were important for it causing an increased mutation rate when overexpressed. From this they reasoned that perhaps Mph1p was displacing some other important DNA binding protein and that it was this displacement that was causing the increased mutation rate.
Through a set of experiments we don’t have time to go into here, they provided evidence that Mph1p was outcompeting the flap endonuclease Rad27p for DNA binding. This makes some sense as previous work had shown that deleting RAD27 causes mutation rates to go way up. So too much Mph1p keeps Rad27p from getting to where it needs to be with the end result being an increased mutation rate.
All this MPH1 work may have important implications in some human cancers. Nonsense or missense mutations in FANCM, the human homolog of MPH1, are known to make people more likely to get cancer. And there are examples of cancers where FANCM is overexpressed. Perhaps that overexpression results in an increased mutation rate in these cancers.
Yet again yeast is giving researchers new targets for, and new ways to think about, human disease. Thanks, yeast, for finding all of these mutator genes for us to investigate further! #APOYG!
by Barry Starr, Ph.D., Director of Outreach Activities, Stanford Genetics
October 24, 2016
Looking for human disease-related information in SGD? There is so much to find! Active areas of curation at SGD include yeast-human homology, alleles and phenotype variants, functional complementation relationships, and disease associations. There are plenty of ways to find this information on our website, and it takes just 90 seconds to learn how – what are you waiting for?
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October 17, 2016
I may be a little late to the game, but over the last few weeks I have started consuming episodes of Game of Thrones voraciously. It is such a fun show to watch! And this isn’t the only HBO show I enjoy. Veep, Silicon Valley, and Last Week Tonight with John Oliver all have my attention as well.
You might say that I need HBO, because without it I can’t get my fill of these shows. (Well, there are other routes, but HBO or HBO GO are the easiest). My over watching of these shows has made me dependent on HBO.
Something similar can happen in cancers. Sometimes a key player in keeping a cell cancerous is an overexpressed gene. And just like my binging of Game of Thrones makes me dependent on HBO, so this overexpressed gene (the TV show) makes the cancer cell dependent on another gene (HBO).
Both of these genes are involved in DNA repair and damaging them means the cell builds up mutations. Making lots of DNA mistakes is a good thing for cancers but only up to a point. Too much damage and the cancer cell dies.
What this means is that these cancer cells are now more dependent on other DNA repair genes. Which means these other DNA repair genes are now targets to go after to selectively kill the cancer cells.
For cancer cells lacking BRCA1 or BRCA2 function, research has shown that these cells are now dependent on a second gene, PARP1. If PARP1 expression is turned down, normal cells survive but BRCA1/BRCA2-dependent cancers die. So, we can kill cancer cells, or end their TV show watching, by going after PARP1, their HBO.
Finding these sorts of genes is not easy unless, of course, you turn to our favorite lab workhorse, the yeast Saccharomyces cerevisiae. Given all of the genetic techniques and tools available with this yeast, it is possible to quickly do a synthetic dosage lethality assay – to look for genes that are lethal only in combination with deleting your gene of interest.
This is just what Reid and coworkers did in a new study just out in GENETICS for CKS1B, a gene that is amplified and overexpressed in many cases of breast, lung, and liver cancers. And they found a more “druggable” target to go after, the kinase PLK1 (the human homolog of yeast CDC5). PLK1 even comes with its own kinase inhibitor, Volasertib.
Reid and coworkers transformed a low copy plasmid containing the CKS1 gene, the yeast homolog of CKS1B, under the control of the galactose promoter into two different yeast strain libraries. The first screen used 9600 yeast deletion strains, each with a single gene deleted in either a MATa or MATα strain. The second screen used strains with temperature sensitive mutants of essential genes. They now looked to see which yeast strains did poorly or couldn’t survive when they were overexpressing CSK1 in the presence of galactose.
In the end they came up with 44 different genes that, when deleted or weakened, had a severe effect on the growth of yeast that overexpressed CKS1. Given that CKS1 plays an important role in cell cycle progression, they focused on the 15 genes that affect mitotic progression. Eventually, through a set of experiments that I don’t have time to go into here, they settled in on CDC5, a polo-like kinase involved in both mitotic entry and exit.
The next step was to see if what they learned about in yeast has any bearing on cancer. It did.
First Reid and coworkers looked at a variety of cancer cells in The Cancer Genome Atlas (TCGA) and found that it was very rare for both PLK1 and CKS1B to be overexpressed in the same cancer at the same time. Next they looked at a data set of short hairpin RNA (shRNA) knockdowns of ~16,000 human genes and found that knocking down PLK1 had negative effects on cancers overexpressing CKS1B. These are consistent with the two genes having a synthetic lethal relationship.
They then took eight breast cancer lines where the shRNA against PLK1 had a negative effect on growth and tested the effects of targeting PLK1 on apoptosis. Did decreasing expression of PLK1 in cells that overexpress CKS1B cause an increase in apoptosis in their hands?
The short answer is yes. They repeated the experiments with the shRNA and also tested the PLK1-specific kinase inhibitor Volasertib and found that both treatments increased apoptosis in CKS1B overexpressing cancer cells. It looks like they may have uncovered a way to go after a subset of cancers using yeast!
Which shouldn’t surprise us. Yeast and other model organisms have been teaching us about cancer at least since the days when Hartwell, Hunt and Nurse first identified cyclins and CDKs (for which they got the 2001 Nobel Prize in Physiology or Medicine), and will continue to school us for years to come.
Hopefully researchers will continue to turn to yeast to continue to better understand and find new treatments for cancer. Yeast has so much more to teach us! #APOYG!
by Barry Starr, Ph.D., Director of Outreach Activities, Stanford Genetics
October 3, 2016
Dr. Yoshinori Ohsumi has won the 2016 Nobel Prize in Physiology or Medicine for his groundbreaking work on autophagy in yeast. This is the process whereby cells recycle their worn out parts or where a cell, like Mobius, the snake eating its own tail, eats less essential bits of itself to stay alive during times of starvation. Think Scarlett O’Hara using her drapes as a dress in Gone With the Wind (or Carol Burnett’s hilarious parody).
Like many, many Nobel Prizes in the past, Ohsumi’s work uncovered basic biological properties using a model organism. In this case he used our favorite lab workhorse, the yeast Saccharomyces cerevisiae, to piece together the steps involved in the recycling of a cell’s own internal structures.
And like many other basic biological studies, this one has important medical applications. In this case the two most obvious are chemotherapy resistance and amyloid-β aggregation in Alzheimer’s disease, but it isn’t restricted to just these two. For example, a specialized form of autophagy that targets damaged mitochondria, mitophagy, may not be working well in people with Parkinson’s disease.
The key to Ohsumi’s work was finding a way to disrupt this process in yeast so that he could find the important genes underlying autophagy using the awesome power of yeast genetics (#APOYG!). It turns out that this is trickier than it might seem because yeast and their autophagosomes, the little vesicles that surround and encase the bits to be degraded, are very small and so hard to see. In fact, they are so small that there was some question about whether yeast even had this process!
If yeast did, then it would take place in the vacuole, the recycling center in yeast. The equivalent organelle in people is the lysosome.
To see if autophagy happens in yeast, Ohsumi starved yeast that had vacuoles but couldn’t digest anything. The idea was that there would be a buildup of autophagosomes in the vacuole because the yeast would be desperately trying to eat itself but had no way to digest what it ate. He indeed saw that these poor yeast developed huge vacuoles bloated with autophagosomes.
Dr. Yoshinori Ohsumi now had the makings of a yeast screen! “All” he had to do was to look for mutants that didn’t form giant vacuoles under these conditions with the logic being that if you knocked out autophagy, you wouldn’t get a buildup of autophagosomes.
The rest, as they say, is history. Ohsumi and his lab managed to tease out the subtleties of this vital cellular process using good old baker’s yeast. What other nuggets of knowledge about ourselves will we pry out of this most useful of eukaryotes? I can’t wait to see what it reveals about us next!
Other Nobel Prizes have been awarded in recent years for work in yeast:
- Leland H. Hartwell, R. Timothy (Tim) Hunt, and Paul M. Nurse won the 2001 Nobel Prize in Physiology or Medicine for their discoveries of “key regulators of the cell cycle”.
- Roger D. Kornberg won the 2006 Nobel Prize in Chemistry “for his studies of the molecular basis of eukaryotic transcription”.
- Elizabeth H. Blackburn, Carol W. Greider, and Jack W. Szostak won the 2009 Nobel Prize in Physiology or Medicine “for the discovery of how chromosomes are protected by telomeres and the enzyme telomerase”.
- James E. Rothman, Randy W. Schekman, and Thomas C. Südhof won the 2013 Nobel Prize in Physiology or Medicine “for their discoveries of machinery regulating vesicle traffic, a major transport system in our cells”.
by Barry Starr, Ph.D., Director of Outreach Activities, Stanford Genetics