New & Noteworthy

Finally, Microbes Get the Recognition They Deserve

April 15, 2013

Anyone reading the SGD blog knows that the yeast Saccharomyces cerevisiae is an amazing little organism. Not only does it give us bread, wine and beer, but it also is an invaluable tool in understanding human biology. It has helped us better understand cancer, Alzheimer’s, and lots of other diseases, not to mention basic biological processes like gene regulation and cell cycle control. This little one celled beast is the rock star of biology!

And now, finally, government is starting to take notice. In a 58-0 vote, the Oregon House recently decided that yeast should be the official state microbe. If the Senate and the governor agree, then yeast will be getting the recognition it deserves. Take that, C. elegans, Drosophila, and all of you other model organisms!

Unfortunately, this recognition is not for yeast’s scientific value. Craft beer making is huge in Oregon, and designating yeast as the official state microbe is a way of celebrating this important state industry. Given all of yeast’s other important contributions to the well-being of us all, this feels a bit like celebrating Hugh Jackman for his role as Wolverine in X-Men while ignoring his roles on Broadway or his role as Jean Valjean in Les Miserables. Yes, he was great in X-Men, but that is an incomplete picture of him as an actor. Same thing with yeast.

Yeast should be celebrated for wine and bread, for medicines like anti-malarials and antifungals, for the deep biological understanding it has given us, and even for its possible future as a source for biofuels. Still, this honor is way better than nothing, and at least yeast will be the first microbe officially recognized by a state. Well, it will be if Oregon hurries.

Hawaii is voting on an official state microbe too, Flavobacterium akiainvivens. This bacterium was discovered by a high school student during a science fair project and is only found in the state of Hawaii. The Oregon senate should vote soon, or yeast will be the second officially recognized microbe.

Of course, the bill could die in the Senate. This is what happened in Wisconsin back in 2009 when their House passed a bill making Lactococcus lactis the official state microbe. This bacterium is important for making Wisconsin’s famous cheese but it wasn’t important enough for the Senate to approve it as Wisconsin’s official state microbe. Hopefully Oregon won’t make the same mistake with yeast.

by D. Barry Starr, Ph.D., Director of Outreach Activities, Stanford Genetics

Categories: Research Spotlight

Tags: beer, Saccharomyces cerevisiae

The Indulgent Chaperone

April 01, 2013

When you think of a chaperone, you probably think of a strict adult at the prom who keeps a tight rein on the kids’ behavior.  Well, in nature, a chaperone sometimes has to do the opposite to help new genes form more quickly.  Sometimes the chaperone has to give the gene a longer leash to explore lots of different possibilities.

See, in theory, it is pretty easy to make a new gene.  A cell accidentally makes an extra copy of an existing gene and this gene is then free to mutate into something new.  A few mutations later and you have a new gene.

Turns out this is probably trickier than it sounds.  First off, having an extra copy of a gene can cause problems.  And second, getting to a new function is no walk in the park either.  It usually takes a few sequential mutations to get there and, with proteins being such persnickety things, many of the intermediates along the way end up being unstable. 

One way a cell might deal with these issues is to bring in a chaperone that lets the gene tolerate more mutations.  Chaperones are proteins that help stabilize other proteins, often under trying conditions like high temperature.  They coddle the protein and keep it stable so that it can still do its job.  In addition, chaperones can also cause a protein to relocate to different parts of the cell.

So the idea is that if a duplicated gene gains a mutation that lets its protein interact with a chaperone, the protein may get more stability from that interaction or may be rerouted to where it won’t do any harm. Because the chaperone buffers the possible harmful effects for the cell, the gene is free to explore more different intermediates on the way to its new function.

A new study out in GENETICS by Lachowiec and coworkers lends support to this “capacitor hypothesis.”  The authors used both Arabidopsis and Saccharomyces cerevisiae to show that genes whose proteins interact with the chaperone Hsp90 evolved more quickly than closely related genes that did not.  This strongly supports the idea that chaperones can encourage new functions in duplicated genes.

The authors first looked at a couple of closely related transcription factors from Arabidopsis, BES1 and BZR1.  Using a specific inhibitor of HSP90 called geldanamycin (GdA), they were able to show that BES1 was a client of HSP90 but BZR1 was not.  They then created a phylogenetic tree of Arabidopsis BZR/BEH gene family and, by determining the ratio of non-synonymous to synonymous changes, found that BES1 had a higher rate of mutation.  One explanation is that the stabilizing/relocalizing influence of HSP90 allowed BES1 to tolerate more mutations.

This result was an excellent first step in showing that the capacitor hypothesis may be true in some cases, but it is limited by being based on a single pair of proteins.  To broaden their findings, Lachowiec and coworkers took advantage of the vast knowledge about Hsp90 interactions in Saccharomyces cerevisiae to look at many more genes.

At first this didn’t work out that well.  The authors looked at a data set of yeast proteins that interacted with Hsp90 (encoded in yeast by the HSP82 and HSC82 genes) and, after removing any co-chaperones from the set, found no difference in the rate of evolution between those proteins that interacted with Hsp90 and those that did not.  But as the authors note, this isn’t surprising as so many other factors play a role in the rate of evolution too.

To refine their analysis, they mimicked their BES1/BZR1 study and focused on pairs of closely related proteins where one interacted with Hsp90 and the other did not.  They found that proteins that interacted with Hsp90 had a “longer branch length” than did their close relatives that did not interact.  In other words, Hsp90 appeared to help along the formation of a new gene.

The authors then went back to Arabidopsis and showed that BZR and BES1 were found in distinct but overlapping parts of the cell.  This lends credence to the idea that chaperones cause proteins to localize to different parts of the cell. 

So it looks like an important function of chaperones may be to shepherd new gene formation.  They are more like a 1960’s version of a chaperone…they let duplicated genes make lots of mistakes on their way to discovering who they really are.

by D. Barry Starr, Ph.D., Director of Outreach Activities, Stanford Genetics

Categories: Research Spotlight

Tags: chaperones, evolution, Saccharomyces cerevisiae

Thinking Inside the Box (or Mitochondrion)

March 28, 2013

The mantra in real estate is that location is everything. The same may be true for some cases of bioengineering. You may not get the best yield unless a whole pathway is in the right cellular compartment.

This is what Avalos and coworkers found for synthesizing branched chain alcohols in the yeast Saccharomyces cerevisiae. These scientists were able to increase yield by 260% by putting the whole pathway of enzymes into the mitochondrion. This is way better than anything anyone else has been able to achieve.

This matters because branched alcohols like isobutanol may prove to be better biofuels than ethanol. We can get more energy out of isobutanol than we can out of ethanol…it has more bang for the buck. Good idea in theory, but producing large quantities of isobutanol has not worked too well in practice.

Yeast is just not very good at making these alcohols, and efforts to improve yields have been anything but inspiring so far. Overexpressing the enzymes in the metabolic pathways that generate isobutanol increased yield by only about 10%. Unfortunately, 10% of almost nothing is still pretty close to nothing.

One of the key metabolic pathways involved in generating isobutanol and other branched chain alcohols is split between the mitochondria and the cytoplasm. Normally, the valine biosynthesis pathway converts pyruvate to valine and alpha-ketoisovalerate in the mitochondria; then those two intermediates, after transport to the cytoplasm, are further converted to isobutanol by the Erlich pathway for valine degradation. Avalos and coworkers reasoned that the failure to increase yield might be because of some rate limiting step in getting the intermediates from the mitochondria to the cytoplasm. And it looks like they may have been right.

They compared the effects of overexpressing the pathway enzymes in the cytoplasm and mitochondria and found the mitochondrial approach won hands down. Overexpression in the cytoplasm bumped yield up 10% while overexpression bumped it up 260%. And this increase wasn’t just for isobutanol. Yields of two other energy rich alcohols, isopentanol and 2-methyl-1-butanol, also went up significantly.

Part of the explanation almost certainly has to do with transport of intermediates between the mitochondrion and the cytoplasm, but that may not be the whole story. The mitochondrion might be a useful environment for other reasons too. For example, its smaller volume means an increase in the concentration of reactants, and its higher pH, lower oxygen content, and more reducing redox potential may be better for certain reactions. It also contains many key intermediates like heme, steroids, biotin and so on.

On the way to improving isobutanol yield, these scientists made it easier for others to test whether moving their pathway to the mitochondria can help increase the yield of their favorite metabolite. Avalos and coworkers created a system of plasmids that easily allows researchers to attach the N-terminal mitochondrial localization signal from Cox4p, subunit IV of the yeast cytochrome c oxidase, to genes of their choice. This will make it much simpler to test whether a pathway’s yield is enhanced by moving it into the mitochondrion.

These results show there is more to increasing yield than overexpression or codon optimization. Sometimes scientists need to take a good hard look at their particular pathway and think outside of the box for new ways to optimize yield. Or sometimes they just need to think within the box that is the mitochondrion.

by D. Barry Starr, Ph.D., Director of Outreach Activities, Stanford Genetics

Categories: Research Spotlight

Tags: biofuel, mitochondria, Saccharomyces cerevisiae

Hate the CIN, Love the CINner

March 21, 2013

At first our favorite small eukaryote, S. cerevisiae, might not seem like a great model for cancer studies. After all, budding yeast can’t tell us anything about some of the pathways that go wrong in cancer, like growth factor signaling. And it clearly can’t help explain what happens in specific tissues of the human body. But in other ways, it actually turns out to be a great model.

For example, all the details of cell cycle control were originally worked out in yeast.  And now a whole new batch of genes has been found that influence a phenomenon, chromosome instability (CIN), that is important in both yeast and cancer cells.

As the name implies, chromosomes are unstable in cells suffering from CIN. Big chunks of DNA are lost, or break off and fuse to different chromosomes, turning the genome into an aneuploid mess. And this mess has consequences.

CIN can cause new mutations or make old ones have a stronger effect.  Eventually these mutations can affect genes that are important for keeping a cell’s growth in line.  Once these are compromised, a tumor cell is born. 

Since CIN is pretty common in yeast, we might be able to better understand it in cancer cells by studying it in yeast. The Hieter lab at the University of British Columbia has come up with a powerful screen to get yeast to confess why it CINs. 

A previous study from the group set the stage by finding a large group of mutants that have CIN phenotypes, implying that those genes are involved in keeping chromosome structure stable. In a new paper in G3: Genes, Genomes, Genetics, van Pel et al. uncovered the network of interactions among the genes in this set, using synthetic genetic array (SGA) technology. And they confirmed that the human homologs of some of these genes interact in the same way as in yeast, making them potential targets for cancer therapies.

The idea behind SGA studies is that if two proteins are involved in the same process, then a strain carrying mutations in both of their genes will be much worse off than a strain carrying either single mutation. In the worst case, the double mutant will be dead. This is known as a synthetic lethal interaction.

Yeast is a great model for doing these sorts of studies on a very large scale.  We can construct networks showing how lots of different genes interact, and most importantly, find the genes that are central to many interactions.   These “hubs” are likely to be the key players in those processes.

The researchers looked specifically for interactions between genes that are involved with CIN in yeast and are also similar to human cancer-related genes. They came up with various interaction hubs that will be interesting research subjects for a long time to come. In this study, they focused on one of these: genes involved with the DNA replication fork.

One of these in particular, CTF4, is a hub for both physical and genetic interactions. Unfortunately, Ctf4p doesn’t look like a good target for chemotherapy. It’s thought to act as a scaffold, and lacks any known activity that could potentially be inhibited by a drug. However, the interaction network around CTF4 that van Pel et al. uncovered suggests another way to target this hub. If a gene that interacts with CTF4 itself has a synthetic lethal interaction with another gene, and we could re-create the synthetic lethal phenotype in a cancer cell, we might be able to knock out the whole process. And that is just what they found in human cells.

First the authors identified a couple of human genes that were predicted from the yeast screen to be close to human CTF4 in the interaction network and to have a synthetic lethal interaction with each other. They then lowered the expression of one using small interfering RNA (siRNA), and reduced the activity of the other with a known inhibitor. Neither treatment alone had much effect, but combining them significantly reduced cell viability.

Since cancer cells frequently carry mutations in CIN genes, it should be possible to create a synthetic lethal interaction, guided by the yeast interaction network, where one partner is mutated in cancer cells (equivalent to using siRNA in this study) and the other partner is inhibited with a drug. Since it relies on a cancer-specific mutation, this approach has the potential to selectively target cancer cells while not disturbing normal cells, the ultimate goal for chemotherapy.

by Maria Costanzo, Ph.D., Senior Biocurator, SGD

Categories: Research Spotlight, Yeast and Human Disease

Tags: cancer, DNA replication, Saccharomyces cerevisiae, yeast model for human disease

Old Genes, New Tricks

March 14, 2013

You can’t teach an old dog new tricks, or so the saying goes. But imagine you found that your old dog knew a complicated trick and had been doing it all her life, right under your nose, without your ever noticing it! You’d be surprised – about as surprised as the Hinnebusch group at NIH when they discovered that some long-studied S. cerevisiae genes had an unexpected trick of their own.

They were working on the VPS* (vacuolar protein sorting) genes. While known for a very long time to be important in protein trafficking within the cell, Gaur and coworkers found that two of these genes, VPS15 and VPS34, play an important role in RNA polymerase II (pol II) transcription elongation too. Now there is an unexpected new trick…like your dog learning to use a litter box!

There had been a few hints in recent years that the VPS genes, especially VPS15 and VPS34, might have something to do with transcription. Following up on these, the researchers tested whether vps15 and vps34 null mutants were sensitive to the drugs 6-azauracil and mycophenolic acid. Sensitivity to these drugs is a hallmark of known transcription elongation factors. Sure enough, they were as sensitive as a mutant in SPT4, encoding a known transcription elongation factor. Further experiments with reporter genes and pol II occupancy studies showed that pol II had trouble getting all the way to the end of its transcripts in the vps mutant strains.

There was a bit of genetic interaction evidence that had suggested that there might be a connection between VPS15, VPS34, and the NuA4 histone acetyltransferase complex. This is important, since NuA4 is known to modify chromatin to help transcription elongation. Looking more closely, the researchers found that Vps34p and Vps15p were needed for recruitment of NuA4 to an actively transcribing reporter gene.

Other lines of investigation all pointed to the conclusion that these VPS proteins have a role in transcription. They were required for positioning of several transcribing genes at the nuclear pore, could be cross-linked to the coding sequences of transcribing genes, and could be seen localizing at nucleus-vacuole junctions near nuclear pores.

One appealing hypothesis to explain this has to do with what both genes actually do. Vps34p synthesizes phosphatidylinositol 3-phosphate (PI(3)P) in membranes, while Vps15p is a protein kinase required for Vps34p function. The idea is that when Vps15p and Vps34p produce PI(3)P at the nuclear pore near transcribing genes, this recruits the NuA4 complex and other transcription cofactors that can bind phosphoinositides like PI(3)P. There are hints that this mechanism may also be at work in mammalian and plant cells.

There’s a lot more work to be done to nail down the exact role of these proteins in transcription. But this story is a good reminder to researchers that new and interesting discoveries may always be hiding in plain sight.

* These genes were also called VPL for Vacuolar Protein Localization and VPT for Vacuolar Protein Targeting

by Maria Costanzo, Ph.D., Senior Biocurator, SGD

Categories: Research Spotlight

Tags: RNA polymerase II, Saccharomyces cerevisiae, transcription, VPS genes

Cancerous Avalanche

March 05, 2013

Cancer often gets going with chromosome instability.  Basically a cell gets a mutation that causes its chromosomes to mutate at a higher rate.  Now it and any cells that come from it build mutations faster and faster until they hit on the right combination to make the cell cancerous.  An accelerating avalanche of mutations has led to cancer.

There are plenty of obvious candidates for the genes that start these avalanches: genes like those involved in segregating chromosomes and repairing DNA, for example.  But there are undoubtedly sleeper genes that no one has really thought of.  In a new study out in GENETICS, Minaker and coworkers have used the yeast S. cerevisiae to identify three of these genes — GPN1 (previously named NPA3), GPN2, and GPN3.

A mutation in any one of these genes leads to chromosomal problems.  For example, mutations in GPN1 and GPN2 cause defects in sister chromatid cohesion and mutations in GPN3 confer a visible chromosome transmission defect.  All of the mutants also show increased sensitivity to hydroxyurea and ultraviolet light, two potent mutagens.  And if two of the genes are mutated at once, these defects become more severe.  Clearly, mutating GPN1, GPN2, and/or GPN3 leads to an increased risk for even more mutations!

What makes this surprising is what these genes actually do in a cell.  They are responsible for getting RNA polymerase II (RNAPII) and RNA polymerase III (RNAPIII) into the nucleus and assembled properly.  This was known before for GPN1, but here the authors show that in gpn2 and gpn3 mutants, RNAPII and RNAPIII subunits also fail to get into the nucleus. Genetic and physical interactions between all three GPN proteins suggest that they work together in overlapping ways to get enough RNAPII and RNAPIII chugging away in the nucleus.

So it looks like having too little RNAPII and RNAPIII in the nucleus causes chromosome instability. This is consistent with previous work that shows that mutations in many of the RNAPII subunits have similar effects.  Still, these genes would not be the first ones most scientists would look at when trying to find causes of chromosomal instability. Score another point for unbiased screens in yeast leading to a better understanding of human disease.

by D. Barry Starr, Ph.D., Director of Outreach Activities, Stanford Genetics

Categories: Research Spotlight, Yeast and Human Disease

Tags: cancer, chromosome instability, RNA polymerase II, RNA polymerase III, Saccharomyces cerevisiae

Crowdsourcing Genetic Disease

February 28, 2013

Remember when sequencing the human genome was going to help us better understand and treat complex diseases like Type 2 diabetes or Parkinson’s? Well, ten years later, we’re still waiting.

Sure we’ve made some progress. Using genome wide association studies (GWAS), scientists have uncovered markers here and there that explain a bit about how a genetic disease is inherited. But despite a seemingly never-ending stream of these assays, scientists simply can’t explain all of the genetics behind most of these diseases.

So now scientists need to try to explain this missing heritability. If they can find out why they aren’t getting the answers they need from GWAS, then maybe they can restructure these assays to give better results.

As usual, when things get dicey genetically, scientists turn to the yeast Saccharomyces cerevisiae to help sort things out. And in a new study out in Nature, Bloom and coworkers have done just that.

In this study, they mated a laboratory and a wine strain of yeast to get 1,008 test subjects from their progeny. They extensively genotyped each of these 1008 and came up with a colony size assay that allowed them to determine how well each strain grew under various conditions. They settled on 46 different traits to study genetically.

What they found was that none of these traits was determined by a single gene. In fact, they found that each of the 46 different traits had between 5 and 29 different loci associated with it, with a median of 12 loci. This tells us that at least in yeast, many genetic loci each contribute a bit to the final phenotype. And if this is true in people, it could be a major factor behind the missing heritability in GWAS.

If a trait is dependent on many genetic loci that each have a small effect, then researchers need large populations in order to tease them out. In fact, when Bloom and coworkers restricted their population to 100 strains, they could only detect a subset of the genetic loci. For example, the number of loci went from 16 to 2 when they looked at growth in E6 berbamine.

So it may be that scientists are missing loci in GWAS because there are simply too few participants in their assays. If true, then the obvious answer is to increase the size of the populations being studied. Thank goodness DNA technologies get cheaper every year!

Of course as the authors themselves remind us, we do need to keep in mind that humans are a bit more complex than yeast. There may be other reasons that we aren’t turning up the genetic loci involved in various traits. It may be that we can’t as accurately measure the phenotypes in humans or that human traits are more complicated than the yeast ones studied. Another possibility is that in humans, there are more rare alleles that can contribute to a given trait. These would be very hard to find in any population studies like GWAS.

Still, this study at the very least tells us that larger populations will undoubtedly uncover more loci involved in human disease. Thank you again yeast.

by D. Barry Starr, Ph.D., Director of Outreach Activities, Stanford Genetics

Categories: Research Spotlight, Yeast and Human Disease

Tags: GWAS, model organism, Saccharomyces cerevisiae

Puzzling Out Gene Expression

February 21, 2013

Have you ever put together a million piece puzzle that was all blue? That is sort of what it sometimes feels like figuring out how genes are turned on or off, up or down.

There are hundreds or even thousands of proteins called transcription factors (TFs) controlling gene expression. And there is a seemingly simple but frustratingly opaque string of DNA letters dictating which TFs are involved at a particular gene. Figuring out which sets of proteins bind where to control a gene’s expression can be a baffling ordeal.

Up until now most of the ways of identifying which TFs are bound at which genes have been incredibly labor intensive to do on a large scale. With all of the current techniques, researchers need to construct sets of reagents before they even get started. For example, to be able to immunoprecipitate TFs along with the DNA sequences they bind, you need to insert epitope tags in all the TF genes so an antibody can pull them down. Other techniques are just as involved.

What the field needs is a quick and dirty way to find where TFs bind in the genome. And now they just might have one.

In a new study, Mirzaei and coworkers used a modification of the well-known technique mass spectrometry (mass spec) to identify TFs that bind to a specific piece of DNA. With this technique, called selected reaction monitoring, the mass spec looks only for specific peptide sequences. This not only makes it much more sensitive and reproducible than ordinary mass spec, but it should also be relatively straightforward to do if a lab has access to the right sort of mass spec. They haven’t worked out all the bugs and it is definitely still a work in progress, but the technique looks promising.

Mirzaei and coworkers set up assays to detect 464 yeast proteins that are known or suspected to be involved in regulating RNA polymerase II transcription. Then they tested their assay on a 642 base pair piece of DNA known to contain signals that affect the levels of FLO11 transcription. They found fifteen proteins (out of the 222 they searched) that bound this piece of DNA. Of these, only one, Msn1p, had been previously identified as regulating the FLO11 gene. The other fourteen had not been found in any previous assays.

The authors next showed that two of these fourteen proteins, Mot3p and Azf1p, represented real regulators of the FLO11 gene. For example, deletion of MOT3 led to a threefold increase in FLO11 expression under certain conditions. And when AZF1 was deleted, FLO11 could not be activated under a different set of conditions. So Mot3p looks like a repressor of FLO11 and Azf1p looks like an activator.

This was a great proof of principle experiment, but much more work needs to be done before this will become a standard assay in the toolkit of scientists studying gene expression. They need to figure out why some known regulators of FLO11 (Flo8p, Ste12p, and Gcn4p) were missed in the assay and whether the other twelve proteins they discovered play a role in the regulation of the FLO11 gene.

Having said this, it is still important to note that even this early stage model of the assay identified two proteins that scientists did not know controlled FLO11 gene expression. At the very least this is a quick and easy way to quickly identify candidates for gene expression. We may not be able to use it to see the whole picture on the puzzle, but it will at least get us a good start on it.

by D. Barry Starr, Ph.D., Director of Outreach Activities, Stanford Genetics

Categories: Research Spotlight

Tags: RNA polymerase II, Saccharomyces cerevisiae, transcription

The Rhythm of Ribosomes

February 13, 2013

We all know that some people march to the beat of a different drummer. But now we’re finding out that mRNAs also have their own particular rhythms as they move along the ribosome.

It’s long been known that some codons just work better than others. They are translated faster and more accurately mostly because they interact more strongly with their tRNAs and because there are more of their specific tRNAs around. So why hasn’t evolution gotten rid of all the “slow” codons? With only optimal codons, translation could move at a marching beat all the time.

One idea has been that a few pauses every now and then are a good thing. For example, maybe slowing down translation at the end of a stretch coding for a discrete protein domain gives that domain time to fold properly. This would make it less likely for the polypeptide chain to end up tangled, or misfolded. Great thought, but even when researchers looked in multiple organisms, they couldn’t find a consistent correlation between codons used and protein structure. Until now, that is.

In a recent study published in Nature Structural and Molecular Biology, Pechmann and Frydman took a novel approach to this question. They derived a new formula to measure codon optimality. Using it they found that codon usage was highly conserved between even distantly related species, and that this conservation reflected the domain structure of the particular protein a ribosome was translating.

First, the authors came up with a more accurate way of classifying codons as optimal or non-optimal. They took advantage of the huge amount of data available for S. cerevisiae and included a lot more of it in the calculation, such as the abundance of hundreds of mRNAs and their level of ribosome association. They also took into account competition between tRNAs based on supply and demand, something that the previous studies had not done.

Once they developed this new translational efficiency scale, they applied it to ten other yeast species – from closely related budding yeasts all the way out to the evolutionarily distant Schizosaccharomyces pombe. The authors found that positions of optimal and non-optimal codons were indeed highly conserved across the yeasts. And codon optimality was highly correlated with protein structure.

One of the better examples of this is alpha helices. These protein domains form while still inside the ribosomal tunnel. The authors found that the mRNA regions coding alpha helices use a characteristic pattern of optimal and non-optimal codons to encode the first turn of the helix. They theorize that this sets the rhythm for folding the rest of the helix. Other structural elements are coded by distinct codon signatures too.

This isn’t just interesting basic research. It has some far-reaching practical implications too.

When using yeast to make some sort of industrial product, the thought has been to use as many optimal codons as possible. This has not always worked out, and now we may know why. A gene that tailors the codon usage to the rhythm of the protein structure is probably the best way to make a lot of correctly folded protein.

And the factory isn’t the only place where this kind of information will come in handy. Protein misfolding is the known or suspected culprit in a whole slew of human neurodegenerative diseases such as Alzheimer’s, ALS, Huntington’s chorea, and Parkinson’s disease. A better understanding of its causes might give us insights into managing those diseases.

Who knew in 1971 that translation actually is a rhythmic dance?

by Maria Costanzo, Ph.D., Senior Biocurator, SGD

Categories: Research Spotlight

Tags: evolution, protein folding, ribosome, Saccharomyces cerevisiae, translation

Giving the Keys Back to the Cell

February 06, 2013

When someone has a bit too much to drink, it is a good idea to take away their car keys. This keeps them safe until they can drive again. But the next morning, that hung over person needs to get their keys back so they can get to work.

Cells sometimes face a similar situation. Instead of being drunk though, cells have something go wrong while they are growing and dividing. When this happens, the cell stops the cell cycle at the next checkpoint, fixes what is wrong, and then starts the cell cycle back up again where it left off.

Scientists have learned a lot about how the keys are taken from cells, but not a whole lot about how they get them back. Fong and coworkers help to rectify this situation in a new study out in GENETICS. There they identified proteins key to releasing a yeast cell from its S-phase checkpoint.

If a cell’s DNA is damaged while it is growing and dividing, replication is slowed at the S-phase checkpoint. This gives the cell a chance to fix the DNA before it is copied. The authors found that in the absence of the DIA2 gene, yeast cells had trouble getting replication up and running again. This implies that this gene is required for yeast to overcome the S-phase checkpoint. The cell needs DIA2 to get its keys back.

Dia2p is an F-box protein involved in identifying certain proteins for destruction. It is one of several interchangeable subunits that provide specificity to the SCF ubiquitin ligase complex. The idea would be that Dia2p is important for degrading the “keeper of the keys,” the protein responsible for stopping the cell cycle in the S-phase.

To test whether Dia2p is important for checkpoint recovery, Fong and coworkers first activated the S-phase checkpoint by adding the DNA damaging agent MMS. Then they removed the MMS and measured how long it took the cells to finish copying their DNA. The dia2Δ mutant was significantly slower than wild type.

Given that Dia2p is involved in ubiquitin-mediated degradation, the authors reasoned that it may help a cell get out of S-phase arrest by degrading a protein that was keeping it there. To find this “keeper of the keys,” Fong and coworkers looked for mutations that rescued dia2Δ cells in the presence of high levels of MMS. The idea is that if they knock out the gene that is keeping the dia2Δ cells arrested, then the cells could overcome the block caused by the MMS.

One of the genes that came up in the screen was MRC1. To confirm that Dia2p and Mrc1p work together in releasing a yeast cell from the S-phase checkpoint, the authors constructed a double mutant carrying dia2Δ and a mutant version of MRC1, mrc1AQ, that they knew was checkpoint defective. Indeed, the double mutant behaved like wild type in their checkpoint recovery assay. Since the mutant Mrc1-AQp could not keep cells at the checkpoint, there was no need for Dia2p to target it for degradation. The double mutant cell never let go of its keys.

The simplest model to explain what happens in wild type is that when its DNA is damaged, a cell is prevented from progressing through S-phase by Mrc1p. Then when the DNA is repaired, Dia2p, providing specificity to the SCF ubiquitin ligase complex, targets Mrc1p for degradation. The cell is now released, allowing the cell cycle to continue.

The authors did a lot more work that we won’t go into here, but suffice it to say that Dia2p and Mrc1p are not the only players involved in releasing a cell from the S-phase checkpoint. There were other genes, both identified and unidentified, that came up in their screen. These will need to be studied as well.

And this isn’t all just interesting from a scientific standpoint. Many cancer treatments work by damaging the cancer cell’s DNA while it is growing and dividing. A better understanding of how cells are arrested and released may lead to better cancer treatments.

by D. Barry Starr, Ph.D., Director of Outreach Activities, Stanford Genetics

Categories: Research Spotlight, Yeast and Human Disease

Tags: DNA replication checkpoint, Saccharomyces cerevisiae

Next