New & Noteworthy

Transcription Factors: Kings of the Genome Jungle

October 20, 2017


Imagine that Jane is in trouble on the edge of the jungle. She needs to be saved soon or she will be sent back to Europe (which she does not want).

june71

Tarzan got to Jane in time by swinging on vines. Just like Mig1p needs to “swing” on DNA to get to its binding sites in the yeast genome on time. (DisneyClips)

Tarzan knows he can’t get there in time by running along the jungle floor. But of course he has a trick up his sleeve—swinging from vine to vine!

He gets there in time, fends off her would-be kidnappers, and saves the day. All because he transferred from one strand of vine to another instead of “sliding” along the jungle floor.

A new study by Wollman and coworkers shows that at least two transcription factors in Saccharomyces cerevisiae, Mig1p and Msn2p, seem to share a lot in common with Tarzan. In a process termed intersegment transfer, they get to where they need to in the genome by “swinging” from DNA segment to DNA segment instead of just sliding along the DNA.

And transcription factors like these need to get to the right place in time to save the cell from outside threats. Just like Tarzan had to swing from vine to vine to save Jane.

This sort of approach would not necessarily work well with just a single transcription factor with a single DNA binding domain. It would sort of be like a one-armed Tarzan—it is hard to take advantage of swinging from vine to vine without at least two arms!

The authors argue that Mig1p gains its “extra arms” through joining together into a cluster. Now each Mig1p can bind DNA and drag the other transcription factors with them. A neat solution to the one arm problem.

Their basic approach is to use fluorescence microscopy to follow a GFP-Mig1p fusion protein in a single cell, something that has only become possible recently. What they found was that there were two populations of transcription factors—a diffuse set of smaller molecules and distinct, larger clusters made up of multiple Mig1p’s.

The clusters appeared to be the ones doing the work in the nucleus. Kinetic studies showed that they stayed in one place in the nucleus for over 100 seconds which is consistent with the clusters and not the monomers being bound to the DNA.

OK so this transcription factor tends to clump up into clusters and it looks like these clusters are the ones regulating gene expression. They also showed that a second transcription factor, Msn2p, did the same thing.

The authors next set out to see if this approach made sense for genetic regulation by running simulations of Mig1p finding its sites in the nucleus as either monomers or as clusters. It made sense to form clusters.

A lot of previous work has been done in S. cerevisiae in terms of the three dimensional map of the genome and where Mig1p DNA binding sites were located in this mesh of DNA. And in the course of their studies, Wollman and coworkers were able to estimate how many Mig1p molecules were in yeast cells and how many were in clusters.

MultiArmedMonster

This mythical beast is more like a cluster of Mig1p proteins with its multiple arms representing multiple DNA binding domains with which to grab strands of DNA. (Wikimedia Commons)

They now had all the information they needed to run their simulations. When they crunched the numbers, they found that clusters fit their data much better than monomers (R2 = 0.75 vs. R2 < 0).

The final step was to work out what part of Mig1p was involved in forming the clusters. To do this, the authors compared Mig1p and Msn2p, the second transcription factor they studied that also formed into clusters, and looked for structural regions they might have in common.

What they found was both proteins had a highly disordered region. For Mig1p, it was at the C-terminus and for Msn2p it was at the N-terminus.

The hypothesis is that these disordered regions, which are both at the opposite end of the protein from the DNA binding domain, interact and form ordered structures that enable clusters to form.  Wollman and coworkers used circular dichroism to show that when Mig1p was put in conditions that favor cluster formation, there was a transition consistent with unstructured protein becoming structured.

What we seem to have is a cluster of transcription factors connected in the middle with their DNA binding domains pointing out. This rolling cluster can more easily hop from DNA strand to DNA strand to find the right spots to bind.

Without this mechanism, Mig1p couldn’t get to where it needs to in time. It is as if Tarzan had 6-9 arms circling his body so he could get to Jane even more quickly.

With the wide range of tools available and our deep understanding of how yeast works and how a yeast cell is organized, our trusted ally S. cerevisiae again teaches us something fundamental about how our biology works.

Mig1p may be able to swing like Tarzan but it can’t yell like him. Or like Carol Burnett!

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

Categories: Research Spotlight

Tags: free diffusion , MIG1 , intersegment transfer , Saccharomyces cerevisiae , transcription factor

Of Medieval Market Townes and Wasp Guts

February 03, 2016


As market towns like this one were a place where isolated medieval Europeans could find partners to take back home, so to are a wasp’s gut for yeast. Image from Wikimedia Commons.

Back before trains, planes and automobiles, people didn’t get around as much. And for the people of medieval Europe, this could be a real problem genetically.

At this time there were a lot of small, isolated villages scattered across Europe. If people in these villages stayed put, inbreeding might have gotten as bad as the poor Spanish Hapsburgs. Their last king, Charles II, was infertile, riddled with genetic diseases and his royal line died out with him.

One reason (among many) that this didn’t happen to people all over Europe was market towns. These were centrally located places where villagers came to sell goods. And where they also found partners to bring home to freshen up the gene pool.

Turns out that out in the wild, our friend yeast is in an even worse predicament than medieval Europeans. Because they are all clones of each other, they exist in isolated colonies with almost no genetic diversity.

Yeast are also way less mobile than people. They do have spores but these don’t tend to travel very far without help.

And yet, looking at yeast DNA shows that yeast definitely get around. There are all sorts of signs of various DNA mixing over time. So where are all these yeast hooking up?

A new study by Stefanini and coworkers in PNAS suggests that yeasts’ market towns are in the guts of wasps. It is there that various yeasts can meet and mate before heading back to their “villages.”

This makes sense in a lot of ways. First off, as we described in an earlier blog, there is good evidence that yeast winter in wasp guts.

So there are definitely a variety of yeast hanging around for months, waiting for warmer weather. The gut is also the kind of harsh place where spore dissolution, the first step in yeast mating, can happen.

When the authors looked at the yeast isolates from a wasp’s gut they saw a lot more outbreeding compared to other sources. This suggests that a lot of mating is indeed going on there.

The next step was to directly test how much mating can actually happen in a wasp gut. Stefanini and coworkers tested this by having the wasps eat five different yeast strains and then analyzing the isolates genetically over time. They compared the results from this experiment to the amount of mating that happens in wine must and under ideal lab conditions.

What they found was a whole lot of mating going on.

After two months, around 1/3 of the yeast in the wasp’s gut were outcrossed. This is OK but pretty comparable to what is found in wine must.

It was a different story after four months. Now 90% of the yeast were outcrossed. This is an even better result than scientists typically get in the lab. Clearly the wasp gut is a great place for a yeast to find a partner.

The authors also found that the S. paradoxus strain had to mate to survive in the gut. The only time they found this strain in yeast isolates was in hybrids with S. cerevisiae.

The next steps will be to see if this kind of mating actually has a big effect on yeast diversity in the wild. And of course what, if anything, the wasp gets out of hosting these cavorting yeast.

A market town was great for both the town and the visitors. People met up, sold goods, found partners and the towns prospered from all of this traffic. I can’t wait to find out if the wasp/yeast situation is so mutually beneficial as well.

Jerry Lee Lewis has a whole lot of shakin’ going on, just like a wasp’s gut has a whole lot of matin’ going on.

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

Categories: Research Spotlight

Tags: inbreeding , Saccharomyces cerevisiae , mating , Saccharomyces paradoxus , outcrossing

Clearing Customs in the Nucleus

January 06, 2016


Getting through the nuclear pore is like going through customs at the airport. And now we can see the mRNA make this journey in real time. Image from Wikimedia Commons.

Going through customs at the airport is a necessary evil. Once off the plane, you need to stand in line, scan for an open station, have various forms looked over and possibly stamped before you can pass through the airport doors and get into a new country.

And of course if there is anything wrong, you can be sent back to get your papers in order. A pain but it does help protect people.

Things work pretty similarly in the nucleus. The mRNA disembarks off the DNA, gathers up a set of proteins, and heads for the nuclear pore. There its proteins are checked and if everything is in order, it is allowed to proceed to the cytoplasm. And if there are problems, it is denied entry.

A couple of new studies out in the Journal of Cell Biology use imaging microscopy to give us a close up view of the bustling airport that is the nucleus of a yeast cell. It is utterly fascinating.

Both studies showed that mRNAs often hang out at the nuclear envelope, pausing at a nuclear pore and then sometimes moving to a new one. And that factors both in the nuclear pore and bound to the mRNA affect this scanning of the nuclear envelope.

The basic strategy with both studies is to fluorescently label specific mRNAs in a live yeast cell and follow its journey from the nucleus to the cytoplasm. To do this, they also needed to fluorescently label the nuclear pores, the custom stations in the nuclear envelope.

They labeled the mRNA using the bacteriophage PP7 RNA-labeling system. Basically, they load up the untranslated region (UTR) of a specific gene with sequences that form specific loops. Once transcribed, these loops are then bound by fluorescently labeled PP7 coat protein. Now they can track this labeled mRNA.

To more easily track mRNAs, they chose low expressing genes. That way they could follow a single mRNA more easily. They also needed to get rid of the yeast cell wall so they could see inside the cell better.

Overall they found that at least in yeast, the mRNA takes around 200 milliseconds to get exported to the cytoplasm. Very little of this time is spent in the nucleoplasm; the mRNA very quickly makes its way to a nuclear pore.

Once there things slow down. The mRNA stays at a nuclear pore or slides along the nuclear envelope to a different pore in a process the authors call scanning. Eventually the lucky successfully make it through the pore to the cytoplasm where they can seek out a ribosome for translation. Around 90% of the mRNAs they studied made it through.

They had a couple of different ideas about why the mRNA hangs around the nuclear envelope for so long. One is that the extended stay at the pore is to make sure everything is in order with the mRNA. It can’t pass through customs unless all of the right forms have been filled out properly.

Another possibility is that by scanning it is looking for a nuclear pore that is competent for exporting. It has to search for an available customs agent.

Now that the authors had established a system to look at mRNA export, they next set out to see which factors play important roles. As you might guess, mucking with parts of the nuclear pores or the proteins that bind the mRNA can throw a monkey wrench into the process.

In the first study, Smith and coworkers looked at what happens to the process when one of the key mRNA binding proteins, Mex67p is mutated. This protein is known to interact with the nuclear pore.

Losing the nuclear basket means mRNAs fall away from nuclear pores more easily. It is like getting to the head of the line and then having it close for lunch. Image from thornet on flickr.

It has also been proposed that Mex67p is important in making sure the trip through the pore is one way. Once the mRNA goes through, it releases Mex67p which makes the mRNA let go of the cytoplasmic side of the nuclear pore. The imaging studies here confirmed that Mex67p is indeed important for mRNA directionality.

Using a temperature sensitive mutant of Mex67p the researchers found that the mRNA they tracked stayed at the nuclear envelope about three times longer than in a wild type strain. The process was also much less efficient with only 32% making it to the cytoplasm instead of the 90% seen in the wild type strain. And of the 14 mRNAs which failed to make it through the pore, 7 headed back through the pore to the nucleus.

In the second study, Saroufim and coworkers concentrated on a part of the nuclear pore called the nuclear basket. This is the first part of the nuclear pore that the mRNP, the mRNA plus its proteins, encounters.

They found that deleting or mutating two key parts of the nuclear basket, MLP1 and MLP2, made the mRNA linger for a shorter time at the pore. The mRNA no longer scans the nuclear envelope.

But that didn’t mean the mRNA passed through to the cytoplasm more quickly. No, it just tended to fall back into the nucleoplasm and then have to reattach more often.

It is as if you had to deal with a customs agent who keeps sending you back into the airport. Or agents who keep putting up the “Out to Lunch” sign as soon as you get to the head of the line.

These two studies give researchers a way to study mRNA export in live cells in real time. As we piece together which proteins play what role, we will get a better handle on this important part of gene expression.

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

Categories: Research Spotlight

Tags: Saccharomyces cerevisiae , mRNA export , nuclear pore

Pulsating Yeast

November 19, 2015


A glass of tepid water will do little for a sprained ankle. Just like adding activators and repressors to a gene will have little effect. Image from Wikimedia Commons

Sometimes when you get a minor injury, doctors will recommend alternating heat and cold as a therapy. The heat opens things up and the cold shuts them back down again.

Now obviously it would be pretty useless to apply both at the same time. Adding a bit of lukewarm water to an injury is not going to be very helpful at all.

The same thing holds true for many genes. If activators and repressors all turned on at the same time, there wouldn’t be much of an effect on the expression of a gene regulated by both. It is no way to respond to something in the environment!

Instead, if you want a gene to go up and then go back down again, you’d have the activator turn on first, followed by the repressor. Another way to put this is you’d have a pulse where all of the activators activate their genes at once and then stop working followed by a pulse where all of the repressors work at once.

This is exactly what Lin and colleagues found in their recent study in Nature. There they looked at the effect of certain external stimuli on the timing of when the activator Msn2p activated genes and when the repressor Mig1p repressed genes in our favorite yeast S. cerevisiae. These transcription factors coregulate many of the same genes.

The authors found that in the presence of either lowered glucose concentrations or 100 mM NaCl, most of the Msn2p in the cell turned on first followed closely by the Mig1p repressors. In the absence of either stimulus, there was no coordination.

So there does seem to be a carefully choreographed dance between these two transcriptional regulators with these signals. But of course gene regulation is a bit more complex than a sprained ankle.

There may be situations where a cell wants both regulators to do their jobs at the same time. Sometimes lukewarm water may be just what the doctor ordered.

And this is what Lin and colleagues found with 2.5% ethanol. Under this condition, the pulses of the two regulators overlapped—both were on at the same time. Apparently different stimuli call for different responses which means different timing of transcription factor pulses.

The authors next wanted to get at why Mig1p repression lagged behind Msn2p activation. Since both transcription factors can only enter the nucleus and do their job after they lose a few key phosphate groups, the authors reasoned that perhaps Mig1p dephosphorylation lagged behind that of Msn2p.

They decided to look at the PP1 phosphatase, Glc7p, as previous work had shown that it can indirectly regulate both Msn2p and Mig1p. And indeed, when the authors lowered the expression of GLC7, Msn2p and Mig1p no longer pulsed one after the other at lower glucose concentrations. It looks like Glc7p is a key player in controlling the pulsing of these two regulators.

Even though much of this work was done with synthetic promoters with Mig1p and Msn2p binding sites, the results were not restricted to these artificial constructs. Lin and colleagues found that around 30 endogenous targets also responded to lowered glucose concentrations in a coordinated way just like their synthetic construct. Yeast regulates genes by controlling when activators and repressors pulse.

Finally, all of these studies were done using fluorescent proteins and filming single cells in real time. (Is biology cool or what?) This makes sense because subtle signs of synchronization can be lost when averaged over a large population.

Just like a synchronized swim team, yeast regulates genes by controlling when activators and repressors can work. Image from Wikimedia Commons.

This also allowed the authors to investigate what happens in unstimulated cells. In other words, what happens when both regulators enter the nucleus at the same time? Or if a repressor gets in first?

The first thing they found was that even in the absence of stimulation, there were still pulses. So at seemingly random times, suddenly all of the Msn2p would swoop into the nucleus at the same time and then all leave a short time later. Or the same thing would happen with Mig1p.

If by chance the two entered the nucleus at the same time, both the synthetic reporter and an endogenous gene, GSY1, were not activated. But if Msn2p happens to get in there first, both were activated.

And if the repressor Mig1p managed to get into the nucleus at least 4-5 minutes before Msn2p, activation by Msn2p was muted. The presence of Mig1p beforehand seemed to keep Msn2p from activating coregulated genes to as high a level.

Taken together these results confirm that just like a synchronized swim team, yeast regulates genes by controlling when activators and repressors can work. First there is a pulse where the all of the molecules of a certain activator are primed to do their job and then, after a short time, they all stop doing their job. This can then be followed later by a pulse of repressors shutting it all down.

And this isn’t just in yeast either. For example, these kinds of pulses are important in neuroscience as well.

This work suggests that in dissecting regulatory pathways, researchers may need to pay more attention to the timing of pulses. Then they can see that hot followed by cold makes much more sense than both together.

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

Categories: Research Spotlight

Tags: Saccharomyces cerevisiae , transcription regulation

Yeast, the Spam Filter

November 11, 2015


If you don’t have a good spam filter for your email, you may be overwhelmed—just as the sheer number of variants of human genes can be overwhelming. Luckily, yeast can help us filter out the variants that matter. Image by Jean Pierre Gallot via Flickr

Imagine what our email inboxes would look like if we didn’t have spam filters! To find the meaningful emails, we’d have to wade through hundreds of messages about winning lottery tickets, discount medications, and other things that don’t interest us.

When it comes to sorting out meaningful mutations from meaningless variation in human genes, it turns out that our friend S. cerevisiae makes a pretty good spam filter. And as more and more human genomic sequence data are becoming available every day, this is becoming more and more important.

For example, when you look at the sequence of a gene from, say, a cancer cell, you may see many differences from the wild-type gene. How can you tell which changes are significant and which are not?

SuperBud to the rescue! Because many human proteins can work in yeast, simple phenotypes like viability or growth rate can be assayed to test whether variations in human genes affect the function of their gene products. This may be one answer to the increasingly thorny problem of variants of uncertain significance—those dreaded VUS’s.

In a new paper in GENETICS, Hamza and colleagues systematically screened for human genes that can replace their yeast equivalents, and went on to test the function of tumor-specific variants in several selected genes that maintain chromosome stability in S. cerevisiae. This work extends the growing catalog of human genes that can replace yeast genes.

More importantly, it also provides compelling evidence that yeast can help us tell which mutations in a cancer cell are driver mutations, the ones that are involved in tumorigenesis, and which are the passenger mutations, those that are just the consequence of a seriously messed up cell. Talk about a useful filter!

The researchers started by testing systematically for human genes that could complement yeast mutations. Other groups have done similar large-scale screens, but this study had a couple of different twists.

Previous work from the Hieter lab had identified genes in yeast that, when mutated, made chromosomes unstable: the CIN (Chromosome INstability) phenotype. Reduction-of-function alleles of a significant fraction (29%) of essential genes confer a CIN phenotype. The human orthologs of these genes could be important in cancer, since tumor cells often show chromosome rearrangements or loss. 

So in one experiment, Hamza and colleagues focused specifically on the set of CIN genes, starting with a set of 322 pairs of yeast CIN genes and their human homologs. They tested functional complementation by transforming plasmids expressing the human cDNAs into diploid yeast strains that were heterozygous null mutant for the corresponding CIN genes. Since all of the CIN genes were essential, sporulating those diploids would generate inviable spores—unless the human gene could step in and provide the missing function.

In addition to this one-to-one test, the researchers cast a wider net by doing a pool-to-pool transformation. They mixed cultures of diploid heterozygous null mutants in 621 essential yeast genes, and transformed the pooled strains with a mixture of 1010 human cDNAs. This unbiased strategy could identify unrecognized orthologs, or demonstrate complementation between non-orthologous genes.

In combination, these two screens found 65 human cDNAs that complemented null mutations in 58 essential yeast genes. Twenty of these yeast-human gene pairs were previously undiscovered.

The investigators looked at this group of “replaceable” yeast genes as a whole to see whether they shared any characteristics. Most of their gene products localized to the cytoplasm or cytoplasmic organelles rather than to the nucleus. They also tended to have enzymatic activity rather than, for example, regulatory roles. And they had relatively few physical interactions.

So yeast could “receive messages” from human genes, allowing us to see their function in yeast. But could it filter out the meaningful messages—variations that actually affect function—from the spam? 

The authors chose three CIN genes that were functionally complemented by their human orthologs and screened 35 missense mutations that are found in those orthologs in colorectal cancer cells. Four of the human missense variants failed to support the life of the corresponding yeast null mutant, pointing to these mutations as potentially the most significant of the set.

Despite the fact that these mutations block the function of the human proteins, a mutation in one of the yeast orthologs that is analogous to one of these mutations, changing the same conserved residue, doesn’t destroy the yeast protein’s function. This underscores that whenever possible, testing mutations in the context of the entire human protein is preferable to creating disease-analogous mutations in the yeast ortholog.

Another 19 of the missense mutations allowed the yeast mutants to grow, but at a different rate from the wild-type human gene. (Eighteen conferred slower growth, but one actually made the yeast grow faster!)

For those 19 human variants that did support life for the yeast mutants, Hamza and colleagues tested the sensitivity of the complemented strains to MMS and HU, two agents that cause DNA damage. Most of the alleles altered resistance to these chemicals, making the yeast either more or less resistant than did the wild-type human gene. This is consistent with the idea that the cancer-associated mutations in these human CIN gene orthologs affect chromosome dynamics.

As researchers are inundated by a tsunami of genomic data, they may be able to turn to yeast to help discover the mutations that matter for human disease. They can help us separate those emails touting the virtues of Viagra from those not-to-be-missed kitten videos. And when we know which mutations are likely to be important for disease, we’re one step closer to finding ways to alleviate their effects. 

by Maria Costanzo, Ph.D., Senior Biocuration Scientist, SGD

Categories: Research Spotlight Yeast and Human Disease

Tags: chromosome instability , yeast model for human disease , functional complementation , Saccharomyces cerevisiae

Life Needs to be More Like a 1950&#8217;s Chevy

October 21, 2015


Stripped of modern bells and whistles, cars last a lot longer. The same may be true of life. It may last longer when some extra, nonessential genes are removed. Image via Wikimedia Commons

In the old days, a car came with the bare minimum of features to get from point A to point B. The windows rolled down with a crank and it usually had a radio. That was about it.

As the car has evolved, it has gained a huge number of bells and whistles. There are power windows and power brakes, a baffling number of computer-based bonus features, personal wifi hotspots, and so on. All of these have undoubtedly made cars more fun and comfortable to drive. But they have come at a cost. Many cars simply do not last as long as their predecessors because these extras break easily.

Turns out life may be like a modern car. It has lots of nice features that help it to do better in the world. But a lot of these features may shorten its life span.

This point was reinforced in a recent study by McCormick and coworkers. They painstakingly searched through a library of 4,698 single gene deletion strains in S. cerevisiae and found that 238 of these strains were able to produce significantly more buds over their lifetime. Many nonessential genes seem to shorten a yeast’s life.

And boy was it painstaking! Believe it or not, they manually dissected over 2.2 million individual yeast daughter cells to generate these results. Luckily it was worth it, as they found so many interesting things.

First off, many of the genes they found fall into a set of five pathways that includes cytosolic and mitochondrial translation, the SAGA complex, protein mannosylation, the TCA cycle, and proteasomal activity. So there are certain pathways we can target to extend the lifespan of our friend yeast. And even better, yeast may not be the only beneficiary of these studies.

Two of the pathways, cytosolic and mitochondrial translation and the TCA cycle, have also been found to be significant in extending the life of the roundworm C. elegans. These pathways are also shared with humans.

And just because the authors found no overlap with the other three pathways in other beasts doesn’t mean they may not be targets for life extension in them too. It could be that previous screens in C. elegans simply missed genes from these pathways.

It could also be that what is found in yeast may turn out to be important in people but not in C. elegans. For example, the authors failed to find any equivalent to the SAGA complex in C. elegans. Either the roundworm lost this complex during evolution, or the homologs between yeast and C. elegans are so different that they’re unrecognizable. In any event, humans at least do have an equivalent to SAGA, called STAGA.

All of this suggests that there may be common ways to make organisms, including people, live longer, healthier lives. Here’s hoping!

And these five pathways are certainly not the whole story. The majority of the genes McCormick and coworkers identified were not in these five, which means there are probably lots of other ways to get at living longer.

One fascinating example that the authors decided to look at in depth was LOS1. Deleting it had one of the biggest effects on a yeast’s reproductive life span.

At first this seems a little weird, as Los1p exports tRNAs out of the nucleus. As expected, deleting LOS1 led to a buildup in tRNAs in the nucleus. The authors confirmed that this buildup is important by showing that overexpressing MTR10, a gene involved in transporting tRNAs from the cytoplasm to the nucleus, led to a longer lived yeast with a buildup of tRNAs in its nucleus.

The next step was to figure out why having a lot of tRNA in the nucleus makes yeast live longer. It was known previously that Los1p is kept out of the nucleus under glucose starvation conditions. The authors confirmed this result.

Most everyone knows that restricting calorie intake (also called dietary restriction or DR) can extend the lives of most every beast tested so far, including yeast. The authors found that growing a los1 deletion strain at low glucose did not increase the lifespan of this strain any further. It thus appears that an important consequence of DR is keeping Los1p out of the nucleus and thereby increasing the amount of tRNA in the nucleus.

While we don’t know yet exactly why keeping tRNAs in the nucleus helps yeast live longer, it is interesting that the increased lifespan associated with the loss of LOS1 is linked to caloric restriction. Finding a way to inhibit Los1p has to be better than starving yourself!

This study has identified 238 genes to follow up on for future studies. And of course there is a whole class of genes that haven’t yet been investigated—the essential genes! Many of these may be important for extending life too. 

Stripping life down to its bare essentials may help individuals live longer at the expense of being the most fit in terms of survival in the hurly burly world of nature. After all, those “nonessential” genes undoubtedly have a function in helping yeast outcompete their less well-endowed yeast neighbors. Just like those power sliding doors are way better than the manual ones on a minivan.

But if you want a long-lived minivan, get the one with the manual doors. And if you want a long-lived yeast (or person), get rid of some of those nonessential genes that cause you to break down.

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

Categories: Research Spotlight

Tags: aging , Saccharomyces cerevisiae , lifespan

You Can Take Yeast Off of the Grapevine, But…

October 14, 2015


All over the world and through the ages, people have moved from the country into the big city to look for a better life. These folks often find that even though they can adapt to city life and city ways, they still hang on to their core country values. As the old saying goes, “You can take the boy out of the country, but you can’t take the country out of the boy.”

Even when he goes to the city, the country mouse hangs on to his country ways. The same is true for S. cerevisiae—even though it entered the lab, it still clung to genes that were most useful out in the vineyard. Illustration by Arthur Rackham (1912) via Wikimedia Commons

Our friend Saccharomyces cerevisiae didn’t migrate voluntarily into the lab. But it ended up there, and has been as lonely as a new migrant in a big city. 

Which is of course how we need it to be. One of the basic tenets of classical microbiology is that you can’t begin to study an organism until you’ve isolated it in a pure culture.

And studying pure S. cerevisiae has yielded a huge body of knowledge about molecular biology, cell biology, and genetics. But by not studying yeast in the context of its old country home, we may have missed a few things.

In a new article in PLOS ONE, Rossouw and colleagues uncover one of them. S. cerevisiae has a family of FLO genes that promote flocculation, the adherence of yeast cells to each other. It has always been a bit puzzling why a whole family of genes that are pretty much redundant with each other would be maintained through evolution.

When the researchers took S. cerevisiae out of its lab isolation by mixing it with other yeast species, they found that the different flocculation genes actually determine which species it can co-flocculate with. Different Flo proteins prefer different partners. 

This discovery helps us understand the evolution of this gene family and also opens the door to further study of inter-species interactions in the vineyard. And since flocculation is an important property in winemaking and brewing, there could even be tasty practical applications of this knowledge.

The researchers started by surveying 18 non-Saccharomyces yeast strains that are found in vineyards. They looked at the ability of the yeasts to flocculate both as pure strains and when mixed with either of two S. cerevisiae wine strains.

Intriguingly, certain species showed a synergistic effect when mixed with S. cerevisiae, flocculating more than either species on its own. Rossouw and colleagues used microscopy to confirm that the “flocs” did indeed contain both yeast species—a simple observation, since the cells of different species have slightly different shapes.

To test the effects of different FLO genes on co-flocculation, the authors assayed the co-flocculation ability of flo1, flo10, and flo11 deletion mutants as well as Flo1, Flo5, and Flo11 overproducers in individual combinations with six of the non-Saccharomyces yeasts. 

The results showed that Flo1 has general effects on flocculation. Overproduction increased co-flocculation across the board with all the species tested, while deletion of FLO1 consistently decreased it. In contrast, deletion of FLO10 didn’t have much effect on co-flocculation.

It was a different story for Flo5 and Flo11, though. Overproduction of each of these not only affected co-flocculation, but had species-specific or even strain-specific effects. Flo5 overproduction caused a relative increase in co-flocculation with Metchnikowia fructicola and a substantial decrease in co-flocculation with two different strains of Hanseniaspora opuntiae. Flo11 overproduction reduced co-flocculation with one of the Hanseniaspora opuntiae strains but not with the other. 

All of these experiments were done on mixtures of two species at a time. To get S. cerevisiae even further out of the lab, Rossouw and colleagues created a “consortium” of wine yeasts, a mixture of six species that are found in wine must (freshly pressed grapes) at the start of fermentation. They then added the FLO overproducer strains individually to the consortium, to see their effects in a more natural situation.

They let the yeast consortium flocculate, extracted total DNA from the flocculated or supernatant parts of the culture, and then used automated ribosomal intergenic spacer analysis (ARISA) to see which strains had co-flocculated. This technique can determine the relative abundance of different yeast species in a sample by sequencing a particular region of ribosomal DNA.

In this experiment, overexpression of each of the three FLO genes had significant effects on at least one of the species in the consortium. The species composition of the flocculated yeasts was uniquely different, depending on which gene was overexpressed.

The discovery that the flocculation genes have individual effects on association with other species goes a long way towards explaining why S. cerevisiae has maintained this gene family with so many members that apparently have the same function—at least, when you study a pure culture. Differential regulation of the FLO genes could affect the spectrum of other species that our favorite yeast interacts with. 

So, our friend S. cerevisiae didn’t actually get out of the lab in these experiments, but at least it got to rub shoulders with some of its old friends (buds?) from the vineyard. These experiments are a good reminder for researchers to think outside the lab.

And when S. cerevisiae and its friends get together outside the lab, beautiful things can happen. We’ll drink a toast to that!

by Maria Costanzo, Ph.D., Senior Biocuration Scientist, SGD

If yeast could sing about its forced migration to the lab, it might sound like this.

Categories: Research Spotlight

Tags: vineyard , Saccharomyces cerevisiae , flocculation

Unleashing the Awesome Power of Yeast Transcription

October 07, 2015


With the right mutations, yeast can activate transcription over long distances—just as with the right social media, distance is meaningless for finding and organizing like-minded people. Image via Pixabay.com

In the old days, before the internet, planes or even mass publishing, it was hard to spark a quick, worldwide movement. You simply couldn’t reach out to likeminded people who lived far away.

Nowadays things are very different. With the advent of social media, it is now trivially easy to spread the word. Using Twitter and Facebook, organizers can easily and effectively organize people who live on the other side of the world.

In terms of transcription activation, our friend Saccharomyces cerevisiae seems to be stuck in the old world. Its transcription factors can only turn up nearby genes. This is different from most other eukaryotic beasts, where activation at a distance is routine.

Except maybe yeast isn’t as backward as we think. It may be that yeast has the potential to activate transcription at a distance, but keeps that potential locked away.

This idea is supported in a new study out in GENETICS by Reavey and coworkers. These authors found that they could mutate away yeast’s inability to activate transcription at a distance.

In other words, this ability is there but is just prevented from being used. Yeast is keeping social media out of the hands of its genes.

Getting around social media/internet controls is not easy. Pressure might need to be applied at multiple points before people power is finally released through social media. And even when it does happen, it can sometimes be hard to figure out exactly why certain events tipped the balance.

Turns out that both of these are also true for long range transcription activation in yeast. Mutating a single gene was not enough—it took mutations in multiple genes to see any significant effect.

As you can imagine, it would be very tricky to hit all of the right mutations for a polygenic trait in one fell swoop. This is why Reavey and coworkers started their mutant hunt with a strain that could already weakly activate transcription from a distance, a strain in which the SIN4 gene was deleted. Now they just needed additional mutations to make the effect stronger.

In their screen they used a reporter in which the GAL4 upstream activating sequence (UAS) was placed 799 base pairs upstream of the HIS3 reporter. This reporter gives very low levels of activity in a wild type strain. They included a second reporter, the URA3 gene under control of the same upstream sequences, because Reavey and Winston had discovered in previous work using a single reporter that cis acting mutations and chromosomal rearrangements were a frequent source of false positive results.

The researchers put the reporter strain through multiple rounds of mutation with UV light and selection with increasing levels of 3AT, a competitive inhibitor of His3. After each round of selection, they measured mRNA levels for HIS3 and URA3 and chose strains that not only had higher 3AT resistance but also showed more transcription of the reporter genes.  In the end they found three strains that survived in the presence of galactose (to turn on the activator) and 10 mM 3AT.

As expected, each strain had multiple mutations. One strain had acquired mutations in the GRR1 and MOT3 genes. To confirm that these were the most important mutations, Reavey and colleagues engineered a fresh strain with just the original sin4 null mutation and the selected grr1-1 and mot3-1 mutations. The fresh strain completely recapitulated the selected strain, showing that these three mutations could unlock yeast’s potential for long-range transcriptional activation.

It makes sense that a grr1 mutation could affect transcriptional activation. Grr1 is a ubiquitin ligase that destabilizes Med3 (also known as Pdg1), a key component of the Mediator complex involved in transcription activation. The researchers provided evidence that this is how the grr1-1 mutation affects the process, by showing that mutating MED3 mimicked the effects of mutating GRR1.

It’s also not too hard to imagine how a mutation in Mot3, a sequence-specific transcriptional activator, could affect transcriptional activation, presumably by changing the expression of a gene under its control.

If you stay away from social media, you’ll lose opportunities for impromptu pillow fights. Who knows what yeast is missing without long-range transcription activation? Image via Wikimedia Commons

The results were not so clear-cut for two other strains that were selected. They arose from the same lineage, and each had acquired the ptr3-1 mutation on top of the original sin4 null mutation. One strain went on to further pick up the mit1-1 mutation, while the other got an msn2-1 mutation.

Again it isn’t too surprising that mutations in genes that encode sequence-specific transcriptional activators like Mit1 and Msn2 arose in these strains. But the selection of the ptr3 mutation in these lineages is something of a mystery.

It is hard to imagine how the usual job of Ptr3 in nutrient sensing and transport would be involved in keeping long range transcription activation down. Perhaps the researchers have uncovered a novel function for this gene.

And re-creating these two strains only partially restored the levels of transcription activation at a distance that were seen in the original strains. A little genetic detective work showed that a big reason for this was that both of the selected strains had acquired an extra copy of the chromosome that had the HIS3 reporter, chromosome III.

Reavey and colleagues deleted each of their identified genes to see which ones caused their effect through a loss of function mutation. Deleting GRR1, PTR3, and MSN2 all had the same effect as the original isolated mutations.

The same was not true for MOT3 and MIT1. Deleting either gene actually weakens long range transcription activation, suggesting that these two had their effect through gain of function mutations.

Finally, the researchers showed that the increase in long-distance transcriptional activation was not simply due to a general increase in transcription activation in the selected strains, by showing that their mutants did not have increased activity of a reporter with the GAL4 UAS placed 280 base pairs upstream of HIS3. In fact, if anything, the strains showed decreased activation with this reporter.

So this experimental strategy allowed Reavey and coworkers to identify some of the key genes involved in keeping transcription activation at a distance under control in yeast. In particular, they found compelling evidence that the Mediator complex is an important player. But there is still plenty of work to do. For example, which of the genes regulated by Mit1, Msn2, and Mot3 are important in long range activation? And what on Earth is Ptr3 doing in all of this?

The success of this approach also confirms that doing repeated rounds of selection in yeast is a viable way to select multiple mutants and study polygenic traits. This strategy may prove a boon for studying the many human diseases that are the result of polygenic traits.

Not only can we use yeast to uncover its activation potential, but we can also now potentially use it to uncover new treatments for human disease. Unleashing another awesome yeast power… 

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

Categories: Research Spotlight

Tags: transcription , Saccharomyces cerevisiae , polygenic trait

The Latest Buzz on Stressed-Out Mitochondria

September 30, 2015


Stinging wasps get our attention, and with good reason—getting stung hurts a lot! If you see wasps going into a nest within the walls of your house, you’ll likely try to block their access.

Just like wasps who can’t get into their nest, excess mitochondrial precursor proteins that can’t be imported into mitochondria are bad news for the cell—but it’s developed ways to deal with them. Image via Pixabay.com

But this could backfire: instead of being able to peacefully go into their nest, a swarm of angry wasps could be buzzing around looking for trouble. It might get so bad that you’ll need to call in an exterminator to take care of the problem.

Mitochondrial proteins might seem a lot less scary than wasps, but it turns out that they can also cause trouble if they can’t get into mitochondria. In two new letters to Nature, Wrobel and colleagues and Wang and Chen used complementary approaches to ask what happens when dysfunctional mitochondria aren’t able to import all of the proteins that are waiting to get in. 

What they both found was that these piled up proteins cause real problems for the cells. In desperation, the cells slow down protein synthesis to reduce the excess, and also turn to their own exterminator, the proteasome, to keep these proteins under control.

This is a paradigm shift in thinking about how poorly functioning mitochondria cause disease. In the past, almost everyone focused on how damaged mitochondria couldn’t make enough energy for a cell. Now it looks like there are other ways for a nonworking mitochondria to do a cell in. And new targets for scientists to go after in treating mitochondrial disease.

As we all know, mitochondria are the powerhouses of the cell, where energy is generated, and they’re also the site of many other essential biochemical reactions. They’re composed of about 1,000 proteins, and nearly all of those are synthesized in the cytoplasm and then imported into mitochondria by an intricate system of transporters.

In order to find out what happens when these 1,000 proteins don’t get into mitochondria as efficiently as they should, both groups created strains whose mitochondrial import was impaired.

Wrobel and colleagues used the temperature-sensitive mia40-4int mutation, affecting an essential component of the mitochondrial import system. Wang and Chen started with the aac2-A128P mutation in PET9 (which is also known as AAC2), an ADP/ATP carrier of the mitochondrial inner membrane. Overexpression of the aac2-A128P allele causes mitochondrial dysfunction and eventual cell death.

Wrobel and colleagues decided to get a comprehensive look at what happens in the mia40-4int mutant by assaying its transcriptome and proteome, using RNA-seq and stable isotope labelling by amino acids in cell culture (SILAC), respectively. Surprisingly, one of the biggest differences from wild type that they saw in the import-defective mutant was a decrease in cytoplasmic translation. Whether they looked at the mRNAs encoding ribosomal proteins, the proteins themselves, or the polysome content and translational activity of the cells, everything pointed to down-regulation of translation. And at the same time, the proteasome—the molecular machine that breaks down unwanted proteins—was activated.

To verify that what they were seeing wasn’t peculiar to the mia40-4int mutant, Wrobel and colleagues slowed down mitochondrial import in several other ways: using different mia40 mutant alleles, other import mutants, or treatment with a chemical that destroys the mitochondrial membrane potential required for import. Under these different conditions causing the accumulation of mitochondrial precursor proteins in the cytoplasm, they still saw decreased cytoplasmic translation and increased proteasome activity.

Quick, Henry, the Flit!” When mitochondrial precursors start to swarm around the cytoplasm, the cell keeps them under control by activating the proteasome. Upper image, Flit insecticide, by Bullenwächter, lower image, structure of the yeast 26S proteasome by FridoFoe; both via Wikimedia Commons

Wang and Chen took a different approach, looking to see whether over-expression of any other genes could compensate for the lethality of overexpressing the aac2-A128P allele. The researchers transformed the mutant with a library of yeast genes on a multicopy plasmid, and found 40 genes whose expression could keep it alive.

The suppressor genes found by Wang and Chen were all involved in some aspect of synthesis or degradation of cytoplasmic proteins, just like the genes found by Wrobel and colleagues whose expression was altered in the mia40 mutant. And Wang and Chen also verified that these suppressors weren’t specific to the aac2-A128P mutation: they suppressed a variety of other mutations that decreased import.

Both groups observed precursors of mitochondrial proteins accumulating in the cytosol of the mutant strains they studied. Wang and Chen saw a couple other very interesting proteins increase in abundance: Gis2 and Nog2. These proteins are involved in regulating ribosome function, and the researchers speculate that their stabilization during this stress response contributes to the translational down-regulation. Intriguingly, their human orthologs are implicated in neuromuscular degenerative disease.

So, using orthogonal approaches, the two groups converged on the same model: a newly discovered cellular pathway that regulates cytosolic translation and protein degradation in order to deal with the stress of inefficient mitochondrial import. Wrobel and colleagues have named it UPRam, for Unfolded Protein Response activated by mistargeting of proteins, while Wang and Chen call it mPOS, mitochondrial Precursor Over-accumulation Stress.

Before this work, it was unknown whether cytosolic pathways were even affected by mitochondrial dysfunction. Now we know that the cell has a specific response when mitochondrial precursor proteins begin swarming in the cytosol, unable to get into their home: it slows down the production of those proteins and calls in the proteasome exterminator to take care of them.

We usually think of mitochondrial disease symptoms as being caused by the reduced energy generation of sick mitochondria, or by the lack of other key events that happen in mitochondria—for example, the synthesis of the iron-sulfur clusters that some vitally important enzymes need. Now, these findings raise the possibility that proteostatic stress on the cell caused by the accumulation of mitochondrial precursors could also lead to impaired cell function and disease.

Perhaps drugs that inhibited cytoplasmic translation, or activated the proteasome exterminator, would be helpful in reducing the buzzing swarm of mitochondrial precursor proteins. Wouldn’t it be wonderful if this knowledge suggested new avenues of treatment to take some of the sting out of human mitochondrial disease?

by Maria Costanzo, Ph.D., Senior Biocuration Scientist, SGD

Categories: Research Spotlight

Tags: proteostatic stress , mitochondria , Saccharomyces cerevisiae , proteasome

A Scientist Sees Transcription

September 23, 2015


While Horton uses his sensitive ears to hear a single Who, researchers need to use optical tweezers to see a single gene being transcribed. Image by Dave Parker via Flickr

In the classic Dr. Seuss tale Horton Hears a Who, the elephant Horton thinks he hears voices coming from a speck of dust. He gets into all sorts of trouble over this until all the Whos in Whoville prove they are alive when they all shout at once. Now Horton’s jungle compatriots believe him and Horton can hang out with his new friends.

Horton’s companions never get to hear an individual Who. They are not blessed with Horton’s big elephant ears and so have to just hear all the Whos shouting at once.

Up until recently, we have been in the same situation as the kangaroo and everyone else in the jungle when it comes to transcription in a cell. We can use all sorts of tools to get at what goes on when RNA polymerase II (pol II) gets ready and then starts to transcribe a gene, but we can only get an aggregate picture of lots of cells where it is happening. We can’t hear the Mayor of Whoville amidst all of the other Who voices.

In a new study out in Nature, Fazal and coworkers use the equivalent of elephant ears, optical tweezers, to study the initiation of transcription by purified pol II machinery from Saccharomyces cerevisiae on single molecules. And what they find is that at least for one part of the process, our having looked at things in the aggregate may have fooled us about how the process worked. It was important that we be able to pick out individual voices from the cacophony of the crowd.

Not surprisingly, transcribing a gene is tricky work. It is often split into three steps: initiation, elongation, and termination. And each of these can be subdivided further.

Fazal and coworkers focused on transcription initiation. Previous work had suggested that the process goes something like this:

Top image via Wikimedia Commons

Basically, an alphabet soup of general transcription factors and pol II sit down on a promoter. This complex then pries open the DNA and looks for a signal in the DNA to start transcribing. The polymerase then transcribes short transcripts until it shifts into high gear when it escapes the promoter and enters elongation phase.

This theory comes from the study of transcription in bulk. In other words, it derives from looking at many cells all at once or many promoter fragments in a test tube.

Fazal and coworkers set out to look at how well this all holds up when looking at single genes, one at a time. To do this they used a powerful technique called optical tweezers.

Optical tweezers can “see” what is going on with moving enzymes by measuring the change in force that happens when they move. For this study, the preinitiation complex bound to a longish (2.7 kb) piece of DNA was attached to one bead via pol II, the moving enzyme. The other end of the DNA was attached to a second bead. Each bead is then immobilized using lasers (how cool is that!) and the DNA is stretched between the two beads. Watch this video if you want more details on the technique.

Depending on where you attach the DNA to the bead, you can either track polymerase movement or changes in DNA by precisely measuring changes in the forces keeping the beads in place. Using this technique the researchers found that the bulk studies had done pretty well for most every step. Except for the initial transcribing complex.

The earlier studies had suggested that an open complex of around 15 nucleotides was maintained until elongation began. This study showed that in addition to the 15 base pairs, an additional 32 to 140 base pairs (mean of about 70 base pairs) was also opened before productive elongation could begin. And that this whole region was transcribed.

This result paints a very different picture of transcription initiation. Rather than maintaining a constant amount of open DNA, it looks like the DNA opens more and more until the open DNA collapses back down to the 12-14 base pair transcription bubble seen during elongation.

It turns out that this is consistent with some previous work done in both yeast and fruit flies. Using KMnO4, a probe for single stranded DNA, scientists had seen extended regions of open DNA around transcription start sites but had interpreted it as a collection of smaller, opened DNA. In other words, they thought they were seeing different polymerases at different positions along the DNA.

These new results suggest that they may have actually been seeing initial transcribing complexes poised to start processive elongation. Seeing just one complex at a time changed how we interpreted these results.

Fazal and coworkers were also able to see what happened to some of the 98% of preinitiation complexes that failed to get started. Around 20% of them did end up with an extensive region of open DNA of around 94 +/- 36 base pairs but these complexes were independent of transcription, as they didn’t require NTPs.

But since this opening did require dATP, they propose that it was due to the general transcription factor TFIIH, a helicase. It looks like in these failed complexes, TFIIH is opening the DNA without the polymerase being present.

A clearer picture of what might be going on at the promoter of genes starts to emerge from these studies. Once around 15 base pairs of DNA are pried open to form the appropriately named open complex, TFIIH unwinds an additional 70 or so base pairs. The polymerase comes along, transcribing this entire region. The whole 85 or so base pairs stays open during this process.

Eventually the polymerase breaks free and the opened DNA collapses back down to around 12-14 base pairs. Now the polymerase can merrily elongate to its heart’s content. Until of course something happens and it stops…but that is another story. 

Categories: Research Spotlight

Tags: transcription , RNA polymerase II , Saccharomyces cerevisiae , optical tweezers

New SGD Help Video: What is GO?

September 14, 2015


The Gene Ontology (GO) is an integral part of modern biology. It provides a common language that unifies the description of gene products from all organisms, structured in a way that allows very detailed information to be captured while at the same time facilitating broad categorizations. 

Watch our new video for a brief refresher course on GO: what it is, how it’s structured, and why it’s important.

 

Categories: Tutorial

Tags: Gene Ontology , Saccharomyces cerevisiae

Yeast Researchers Turn up the Heat on Essential Genes

September 09, 2015


Looking at the phenotypes—the observable characteristics—of creatures that have mutations in various genes can give important clues to scientists trying to figure out what those genes do. And the ability to systematically mutate thousands of genes in our favorite organism, Saccharomyces cerevisiae, has made it an awesomely powerful genetic system.

Turning up the heat on temperature-sensitive mutant strains is a great way to study essential yeast genes systematically. Image via Wikimedia Commons

But this awesome system has something of an Achilles heel. If you delete an essential gene, defined as a gene necessary for life under standard growth conditions, you end up with an experimental dead end: a dead cell. How then can you study mutant phenotypes for essential genes, which are nearly 20% of the genome?

In a new paper in G3, Kofoed and colleagues address this problem by creating conditional mutations in 600 essential genes. The mutant genes function normally at standard temperatures (25-30° C) but can be inactivated by raising the temperature. This mutant collection covers about half of S. cerevisiae essential genes and gets us much closer to being able to do mutant screens that are truly genome-wide, helping us to discover unexpected connections between genes and pathways or processes.

One popular approach to studying essential genes has been to put them under control of promoters that can be turned down when you add a particular chemical or carbon source. But it can be hard to tease apart the phenotype of down-regulating transcription of your gene of interest from the effects of the other changes that you need to make in order to regulate expression of the construct.

A solution that avoids some of these issues is to use temperature-sensitive (ts) alleles of essential genes. These mutations make the resulting proteins unstable at high temperatures. If you shift a ts strain to high temperature, the mutant protein will stop functioning; by growing the cells at an intermediate temperature, you can often produce a partially active protein that allows slow growth of the strain.

Temperature-sensitive alleles are not nearly as straightforward to create as are deletion mutations. Although newer technologies are helping, it’s still a lot of work. But Kofoed and colleagues took on this challenge. Building on their previous collection of 250 genes, they targeted genes without existing ts alleles to create a mutant collection including a total of 600 genes, about half of yeast’s essential genes.

The researchers used error-prone PCR to introduce mutations into DNA fragments encoding the genes, then transformed the mutagenized fragments into heterozygous diploid cells containing one wild-type copy of the gene and one deletion allele. The flanking sequences of the mutagenized genes targeted them to integrate in place of the deletion allele. Kofoed and colleagues could then sporulate the diploids and screen the haploid progeny for temperature sensitivity.

The genetic background of these strains is S288C, the widely used strain from which the reference genome sequence is derived. Each strain contains a “barcode”, a sequence that can be used to uniquely identify it. In addition to creating new alleles, the authors also used these methods to transfer some previously isolated ts alleles into this same background. 

Kofoed and colleagues validated and stored multiple ts alleles for each gene on their list. Although they chose one allele per gene for inclusion in the collection, the other alleles are available on request and could be very informative for researchers studying those particular genes.

As a test to see whether their collection of 600 genes was biased in any way, the researchers did Gene Ontology (GO) enrichment analysis. This compares the GO terms, representing molecular function, biological process, and subcellular localization, that are associated with the genes in a set. If the genes share related GO terms, that’s an indication that they may be involved in a common process or share the same location.

Most of the time, when scientists do GO enrichment on sets of genes they’ve come up with in an experiment, they’re hoping the genes have significantly shared terms. But in this case, the researchers were happy to find no shared terms, meaning that their collection represented a wide variety of places and roles in the cell.

The mutant strains may be studied individually in classical genetics experiments or the whole set can be tested using robotic manipulation of all the strains at once. Alternatively, the strains can be pooled and grown together in a competitive situation, like a microscopic Survivor show. When the strains are forced to compete for survival, some will prosper and others will die out. Their unique barcode identifiers allow researchers to figure out which strains were the survivors and which got voted out of the chemostat.

So this collection represents an important step in our ability to survey the phenotypes of virtually all genes in the genome. In addition to creating this resource, Kofoed and colleagues provide a summary (in Table S6) of all currently available mutant collections for essential genes. The yeast research community is now poised to turn up the heat on genome-wide mutant screens and make new discoveries about the roles of these essentially important genes.

by Maria Costanzo, Ph.D., Senior Biocuration Scientist, SGD

Categories: Research Spotlight

Tags: mutant collection , community resource , Saccharomyces cerevisiae

Many Modules Make Light(er) Work

August 26, 2015


If you’ve ever put together something from IKEA you know it can be a bear. So many parts need to connect up together perfectly to build that new bookcase—if you tried to do it all at once you’d go crazy.

Complicated tasks are way easier to do if they are broken up into smaller chunks. This is true whether you are building a bookcase or a biochemical pathway. Image via Wikimedia Commons

Luckily the good folks at IKEA try to make it a bit easier (and more tolerable) by splitting the task into smaller, more manageable pieces. You can concentrate on one part without having to worry about the rest. Once that part is done you can work on the next part and so on. In the end you assemble all the pieces together into your new bookcase.

This is the approach Galanie and coworkers took in their recent Science paper where they engineered our favorite yeast S. cerevisiae to make a couple of different opioids. And it is a good thing they broke this problem up, because it was a way bigger undertaking than anything IKEA might have thrown at them. Engineering this yeast strain was a genetic tour de force.

The authors coordinated 21 different genes from mammals, plants, bacteria and yeast to get the opiate precursor thebaine made. And the semisynthetic opiate hydrocodone took an extra two genes for a grand total of 23! Trying to do all of these at once might have been very frustrating. Thank goodness they split this Herculean task into six (or seven for hydrocodone) smaller modules.

The first step was to get yeast to make (S)-reticuline, a key intermediate on the way to useful opiates. This took 4 modules made up of 17 different genes: six from rat, six from plants, four from yeast and one from bacteria.

And of course just putting these into yeast all at once would almost certainly have made a whole lot of nothing. Each gene needed to be selected from the right beast and then optimized to work in the yeast strain. Sometimes this meant picking the right variant from the right plant, and sometimes it meant mutating a gene to make it behave better. This all would have been overwhelming if the task weren’t split into four easier sections.

Even with all of their optimization, this iteration only made about 20 μg/liter of (S)-reticuline. They needed yeast to crank out more of this intermediate, so they designed a fifth module.

As its name implies, this “bottleneck” module was designed to overcome bottlenecks in the first four modules. After it was added to the strain, the yeast managed to make 82 μg/liter. This was something they could work with!

Except now they were stuck. They needed (R)-reticuline instead of the S form, but no one knew how poppies managed this feat. The gene that did this job hadn’t yet been discovered.

So Galanie and coworkers rolled up their sleeves and dug through plant transcriptome databases to find the gene they were looking for. They found a likely candidate, synthesized the gene in order to produce the enzyme, tested whether it could transform the S form of reticuline into the R form in vitro, and found that it could.

They could now make the right intermediate, which meant they could make their final module. As its name implies, this “thebaine” module would finally allow them to make the opiate precursor thebaine in yeast. This module consisted of their recently discovered gene and three other plant genes.

They had finally made thebaine from simple sugars in yeast! Except it didn’t work very well at all. There seemed to be a bottleneck right after the (R)-reticuline stage. Back to the drawing board!

Given where the bottleneck was, the researchers guessed correctly that the culprit was the SalSyn enzyme which converted (R)-reticuline to salutaradine. A Western blot showed three distinct forms of this enzyme in yeast and only one form, the lowest molecular weight one, when it was expressed in tobacco. Clearly something was happening to inactivate this protein in yeast.

A close look at the protein suggested yeast was glycosylating positions that it shouldn’t, and site directed mutagenesis of these sites confirmed this. The glycosylation was causing the protein to be sorted incorrectly so that it couldn’t do its job.

Unfortunately just mutagenizing away the glycosylation sites wasn’t good enough, because this severely affected the enzyme’s ability to do its job. So the researchers created a chimeric protein with parts of another P450 enzyme they knew did great work in yeast. After optimizing its codons for yeast, this chimera performed beautifully.

Now, finally, they had a yeast strain that could make thebaine. Not a lot of it, only around 6.4 μg/liter—but amazing nonetheless.

A yeast strain would have to be millions of times better at making opioids before a Walter White character could turn it into a profitable criminal activity. But the authors advocate for starting an open dialog on synthetic biology issues now, while there’s still time to deliberate. Image by Hecziaa via deviantart.com

A final module was added that consisted of two plant enzymes that converted thebaine to the drug hydrocodone. This monster strain could crank out around 0.3 μg/liter of hydrocodone. Yes, that is as puny as it sounds; one dose of painkiller for an adult would contain 5 mg of hydrocodone.

To be competitive with poppies, they need a 100,000-fold improvement to around 5 mg/liter. In talking with Dr. Smolke, it sounds like this could happen within a couple of years. After scaling up for production, voila! An entirely new source of opiates for pain relief.

Of course the elephant in the room is a Breaking Bad-esque scene where a yeast biologist grabs ahold of an opiate-producing strain and supplies various cartels with illegal drugs. Our Walter White wannabe wouldn’t be able to use the current strain, as he would need thousands of liters of yeast to produce a single dose of Vicodin.

But this scenario will be a real concern in the next few years. Which is why the Smolke lab has crossed every t and dotted every i in setting up and creating this strain. They have made it as difficult as possible for the wrong people to get their hands on it.  

This strain represents a stunning achievement in synthetic biology. Move over poppies, there’s a new opiate producer in town.

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

Categories: Research Spotlight

Tags: pathway engineering , opiate biosynthesis , Saccharomyces cerevisiae , synthetic biology

Ancient Hybridization Causes Revision of Yeast&#8217;s Calendar

August 19, 2015


Just as this monk had trouble pinpointing when Jesus was born, so too did yeast biologists have trouble figuring out when the genome of S. cerevisiae doubled in size. But they had trouble for very different reasons… Image via Wikimedia Commons

Most people assume that Jesus Christ was born around 1 A.D. or 1 B.C. or something like that. After all, that dating system is based on when he was born. 1 A.D. is by definition “the first year of the Lord.”

Now of course no one was actually marking years this way from the get go. In fact, this dating system wasn’t really invented until 525 A.D. by the monk Dionysius Exiguus.

And as can sometimes happen when you look that far back in time, he didn’t quite get the date of Jesus’ birth right. In point of fact, Jesus was most likely born between 4 and 6 B.C.

While not nearly as momentous, yeast biologists may have done something similar with the genome of our friend Saccharomyces cerevisiae. For many years scientists have believed that this yeast underwent a whole genome duplication (WGD) event around 100 million years ago

But if the conclusions reached by Marcet-Houben and Gabaldón in a new PLOS Biology article are correct, then what looks like the WGD event actually happened before there was a S. cerevisiae around to duplicate its genome.

Which would mean that there couldn’t have been a WGD. There is no way for a species to double its genome if it doesn’t yet exist! Instead the authors propose that what looks like a WGD was actually a hybridization of two related yeasts from longer ago than 100 million years.

Once you get past the vocabulary, the idea behind this study is actually pretty easy. Basically, they took pairs of genes that most likely came from a duplication event (ohnologs) and figured out when they diverged away from one another. This is the same idea behind figuring out when chimps and humans shared a common ancestor by comparing homologous genes.

When Marcet-Houben and Gabaldón compared every potential ohnolog in S. cerevisiae, they found that a WGD event could explain the origin of only 15% of these genes. These 15% could be traced back to a time after S. cerevisiae was already around.

The other 85% all looked to have been duplicated before S. cerevisiae yet existed. Which of course means these could not have come from a WGD. A genome that does not yet exist cannot be duplicated. This set of genes must have arisen in a different way.

An origin story that makes more sense than a WGD for these genes is one in which two related species hybridize to form one new species. This kind of thing definitely happens, especially with yeast (and if you like lagers, you can be glad it does!).

Here the idea is that the related species share a subset of their genes from when they had a common ancestor. When these species fuse, the new beast has both sets of genes. A cursory look might suggest that these genes were from a duplication event, especially if there are many large tracts of them. After all, many genes share a lot of homology between species.

It is only with a closer look that you might trace these genes back to a common ancestor that came before the species you are studying even existed. This is, in essence, what Marcet-Houben and Gabaldón found.

From the phylogeny of reference species that they created, the authors were able to get a general idea about which clades these prehybridization species may have come from. The largest peak of duplication from their analysis came from before Saccharomyces split from a clade containing Kluyveromyces, Lachancea, and Eremothecium (KLE). The other major peak came before Saccharomyces separated from a clade that contains Zygosaccharomyces rouxii and Torulaspora delbrueckii (ZT). So the simplest interpretation is that at some point long ago, an ancestor of modern S. cerevisiae was formed from the hybridization of a pre-KLE and a pre-ZT species.

Showing that something like this happened so long ago is fraught with peril. All sorts of things can happen to a genome in more than a hundred million years. And duplicated genes are even trickier because they can mutate at different rates when one copy is gaining a new function. (After all, that is one way that new genes are born.)

So Marcet-Houben and Gabaldón threw everything but the kitchen sink at the genome sequences. They tried at least three different methods for comparing the various sequences, using alternative reference phylogenies and a variety of techniques to show what might happen to their results if genes were mutating at different rates.

With each method they got similar results. Many or even most of the “duplication” events happened before S. cerevisiae was even a species. And on top of all of this they were able to show that they got a similar result when they used a known hybrid, S. pastorianus, and its two founding species, S. cerevisiae and S. eubayanus.

All of this taken together argues that S. cerevisiae did not undergo a WGD in the deep, dark past. Instead, it is the result of two closely related species getting together and creating a new species.

Now this does not necessarily mean there was no WGD in our favorite yeast’s past. There are at least two ways that a hybrid species might have formed, and as you can see in this image from Marcet-Houben and Gabaldón’s article, one of them involves a duplicated genome:

Fig 6. Hybridization scenarios. From Marcet-Houben and Gabaldón (2015), PLOS Biol. 13(8):e1002220.

In the first scenario, shown on the top left, two diploids of different species fuse together to create a yeast with two sets of chromosomes. Eventually, through mutation, translocation, gene loss and whatever other genome sculpting mechanisms are handy, the yeast ends up with double the number of chromosomes of its predecessors.

In the second possibility, shown on the bottom left, two haploids fuse. This fused yeast then undergoes a whole genome duplication and then goes through similar processes as the first model to get to the current genome.

So, although there may have been a WGD, it looks unlikely that it happened to S. cerevisiae. Just as the placement of historic events in our calendar changes when more information is available, the generation of genome sequences for more and more yeast species and new methods for analyzing them are giving us deeper insight into the history of our friend S. cerevisiae.

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

Categories: Research Spotlight

Tags: whole-genome duplication , evolution , Saccharomyces cerevisiae , hybridization

Redesigning Life, Ethically

August 13, 2015


Yeast is an essential ingredient in the recipes for our most delicious food and drink. But now, researchers are working on a recipe for yeast itself! Image by Maria Costanzo

For thousands of years, humans have used yeast as an essential part of recipes for bread, wine, and beer. But now we’re turning the tables on yeast. Instead of creating recipes with yeast, researchers are creating recipes for yeast.

Now of course we have been making minor tweaks here and there for years. But what we’re talking about now is changing out the whole recipe book: creating a whole new genome for S. cerevisiae.

The Synthetic Yeast 2.0 Project (Sc2.0) has the ambitious goal of re-designing and synthesizing the entire yeast genome, some 12 million base pairs. Along with the scientific challenges, the researchers face some tricky ethical issues as well. After all, they’re creating the blueprint for an entire living eukaryotic cell!

Fortunately, the Sc2.0 researchers have thought long and hard about these issues. They’ve issued a statement of ethics and governance in a new article in GENETICS that also reviews the current regulatory and ethical landscape for synthetic biology. The statement by Sliva and colleagues sets the course for Sc2.0 and serves as a model for oversight of other synthetic biology projects.

We wrote about the science in this space before, when the project published its first major milestone, the synthesis of chromosome III. It’s fascinating stuff: the scientists are not only re-synthesizing the genome, but are re-designing it to be leaner and more useful in the lab. They’re adding features like loxP sites that can be used to alter the structure of the genome for evolution experiments, and engineering the tRNA genes so that one codon can be repurposed to code for a novel amino acid.

But even though these are seemingly benign changes to a relatively harmless beast, there are ethical issues inherent in modifying a living organism in such a big way. While the authors focus on Sc2.0, the issues they discuss are relevant to other synthetic biology projects that combine genes from several organisms in novel pathways, such as the efforts to create an opiate biosynthetic pathway in yeast

While we can only touch on the highlights of their statement here, one of the principles most strongly emphasized by Sliva and colleagues is that all Sc2.0 work will be done for peaceful purposes that benefit society. To promote transparency, they are making outreach a priority, engaging with and educating the public about the project. Sc2.0 will be a public resource, with no intellectual property rights or restrictions on data or materials.

The researchers are also committed to safety. They have engineered multiple auxotrophies into all working strains so that they need special media to survive, even though it seems unlikely that an Sc2.0 strain on the loose would be harmful or would have a competitive advantage over wild strains. And although it’s not required for working with organisms like yeast that are classified “Generally Regarded as Safe” by the FDA, all participants in the project receive biosafety training.

Currently, there is relatively little official policy in place for the field of synthetic biology. Two safety measures currently recommended for DNA synthesis companies by the U.S. Department of Health and Human Services are that the companies check that the sequences they synthesize don’t correspond to toxins or harmful organisms, and that they also verify the identities and institutions of their customers. While compliance with these guidelines is voluntary, the Sc2.0 project has decided to support only companies that follow these safety measures.

To ensure that the policies outlined in their Statement of Ethics and Governance are followed, the Sc2.0 project will maintain an Executive Committee comprised of people both internal and external to the project who have broad expertise in policy, ethics, and science. All of the participants in the project are accountable to this committee, which will actively monitor the work to ensure that the guidelines are followed.

It’s obvious that this is no half-baked scheme, but rather an impressively well-planned recipe for cooking up a yeast cell from scratch. But, we expect nothing less from our friend S. cerevisiae and the talented researchers in the yeast community than to be at the forefront of modern science! 

by Maria Costanzo, Ph.D., Senior Biocuration Scientist, SGD

Categories: Research Spotlight

Tags: synthetic biology , Saccharomyces cerevisiae

Private Nurses Help Birth Ribosomal Proteins

August 06, 2015


Some ribosomal proteins need to be closely chaperoned even as they’re being born. Image courtesy of the National Library of Medicine via Wikimedia Commons

Some kids are born troublemakers, wreaking havoc and destruction everywhere they go. They can’t help themselves; it’s in their nature to be that way. But if they have concerned and protective adults in their lives, children can overcome this tendency and grow up to become productive members of society.

Within the cell, ribosomal proteins are problem children. Although they grow up to have essential and productive roles, as newborns they can cause big trouble.

Many of them have highly charged, unstructured regions that give them a tendency to aggregate with other proteins. And they have a complicated journey to adulthood, since ribosome assembly happens in multiple cellular compartments. With an estimated 160,000 ribosomal proteins synthesized every minute in rapidly growing S. cerevisiae cells, these troublemakers could cause major problems if left to their own devices.

To help control this unruly mob, certain proteins in the cell act as designated chaperones for ribosomal proteins. In a new paper in Nature Communications, Pausch and colleagues found that, surprisingly, these specialized nurses catch their client proteins even as they’re being born.  They swaddle them from the first moment they start to emerge as nascent proteins, and keep them from causing any harm until they can be delivered safely to their final destination.

The researchers first looked at the proteins Rrb1 and Sqt1. Previous work had suggested they might act as specific chaperones for the ribosomal proteins Rpl3 and Rpl10, respectively. And Pausch and colleagues confirmed these results, showing that TAP-tagged Rrb1 pulled down only Rpl3 and Sqt1 only pulled down Rpl10. Each of these troublesome tots had its own personal chaperone!

But surprisingly, very little of the protein was needed for these chaperones to keep ahold of their respective charges. When the authors trimmed down the ribosomal proteins to shorter and shorter lengths, they saw that just the N-terminal 15-20 amino acids of each ribosomal protein were necessary and sufficient for interaction with its chaperone.

They decided to use X-ray crystallography to look in detail at the Sqt1-Rpl10 interaction. First they determined the crystal structure of Sqt1 on its own, and found that it forms an eight-bladed WD-repeat beta-propeller, looking much like a round electric fan.  The amino acids positioned on the surface of the blades are negatively charged.

Next, the authors co-crystallized Sqt1 with a peptide corresponding to amino acids 2-15 of Rpl10. The structure showed that the positively charged peptide was cradled in the negatively charged surface.

To test whether these charged residues were important for the interaction, they mutated the charged residues of Sqt1 and of the peptide and combined them in various ways. Sure enough, changing the charged residues of either partner disrupted or diminished the interaction.

The Sqt1 chaperone resembles an electric fan, with eight blades rather than four. Image via Wikimedia Commons

Pausch and colleagues went on to test whether those same charged residues are important in vivo. An sqt1 mutation changing glutamate residue 315 to lysine (E315K), that abolished the Sqt1-Rpl10 interaction in vitro, was lethal for yeast cells, confirming the importance of the interaction.

The researchers also detected many allele-specific genetic interactions between the charged residues of the two proteins, and even found that switching the charges in an interacting pair of amino acids (changing an Sqt1 residue to a positive charge and its Rpl10 binding partner to a negative charge) would improve growth compared to either single mutant.

The lethality of that sqt1-E315K mutation, and even the lethality of an sqt1 null mutation, were weakly suppressed by overproduction of Rpl10. So yeast cells can get by (just barely) with an un-chaperoned Rpl10, as long as there’s enough of it around. This result also confirmed that Rpl10 is the only client of Sqt1.

As yet another verification that Sqt1 acts as a chaperone, the authors looked to see what happens to the Rpl10 protein in sqt1 mutants. If cells carrying wild-type SQT1 are lysed and separated into a pellet and supernatant, most Rpl10 spins down in the pellet but a significant amount is soluble in the supernatant. However, if the cells carry any of several sqt1 mutant alleles that alter the charged residues and diminish the interaction with Rpl10, all of the Rpl10 is found glommed together in the pellet.

The two chaperone-ribosomal protein interactions that Pausch and colleagues investigated, Sqt1-Rpl10 and Rrb1-Rpl3, both involved the extreme N termini of the ribosomal proteins. Previous studies had also shown that two other chaperones for ribosomal proteins, Yar1 and Syo1, also interact with the N termini of their clients. So the authors wondered whether interactions between ribosomal proteins and their chaperones might even start during translation of the ribosomal proteins.

In a final experiment, the researchers treated yeast with cycloheximide to freeze translation and then pulled down each of the four chaperones via affinity tags. Each chaperone specifically pulled down the mRNA encoding its client protein, showing that it was binding to the nascent protein as it first started to emerge from the translating ribosome. 

So this study has defined a new step in ribosomal biogenesis. Certain specific ribosomal proteins are such troublemakers that it’s too dangerous for the cell to just release them into the cytoplasm after they’re translated.

Instead, these bouncing baby proteins are caught by their individual nurses before they’re even fully born, and wrapped up to protect both the ribosomal proteins themselves and the rest of the cell. Since ribosomal biogenesis is highly conserved across species and since defects in it are associated with many different diseases, further study of these cellular midwives could have important implications for human health. Perhaps some gentle guidance could help put wayward ribosomes on the right track.

by Maria Costanzo, Ph.D., Senior Biocuration Scientist, SGD

Categories: Research Spotlight

Tags: Saccharomyces cerevisiae , ribosomal proteins , chaperones

Another Small Victory for Lamarck

July 29, 2015


Yeast gives us an example of an adaptation that is positively Lamarckian! Image of Jean Baptiste de Lamarck via Wikimedia Commons

Examples of various ways that the environment affects gene expression have become so commonplace that new examples don’t make much of a splash anymore. It is as if Lamarck and Darwin had never argued about how natural selection works.

The main reason we aren’t surprised anymore is that we have a pretty good handle on how most of these changes are happening. Something in our environment causes chemical groups to be added or removed from our DNA and/or its associated proteins, causing a change in gene expression. These kinds of epigenetic changes happen a lot and are now seen as the norm.

What doesn’t happen much at all is that the underlying DNA gets changed in a predictable way to change gene expression in response to something in the environment. Which is why a recent study in PNAS by Jack and coworkers makes you stand up and take notice.

In this study the researchers provide evidence that suggests that yeast will expand the number of copies of its rDNA locus to match the level of nutrients in the environment (presumably to make more ribosomes to take advantage of all those nutrients). The yeast is responding to the environment by changing the content of its genome rather than just changing how it is used.

This is big. It is almost as if Lamarck was right about some part of natural selection. Oh wait, that’s exactly what it is! 

What makes this so cool is that it suggests that natural selection doesn’t necessarily just happen when a random genetic variant wins out in a population. Sometimes the environment itself can induce the winning genome change–and these aren’t just epigenetic changes. (Go Lamarck!)

Jack and coworkers focused on the rDNA locus of the yeast Saccharomyces cerevisiae. This is a fairly fluid part of the yeast genome that consists of multiple copies of the 35S and 5S pre-rRNA genes. The average yeast cell has around 180 copies of this locus and there is a normal range of 150-200 per cell. If a yeast somehow ends up with 80 or fewer copies, it quickly increases the number back to that golden 150-200 range via a Fob1 dependent mechanism.

The authors created a strain of yeast that lacked Fob1 and had only 35 tandem repeats in its rDNA region. This strain, rDNA35, could not expand its rDNA unless Fob1 was added back. They now had a strain in which they could test what affected rDNA expansion, by transforming the strain with a plasmid expressing Fob1 and growing the transformants under different conditions.

The most surprising experiment was the final one of the paper. The authors grew the rDNA35 strain in either 2% or 0.5% glucose and found that rDNA amplification was slowed significantly in low glucose. The authors interpret this to mean that the genome change, the expansion of rDNA, is dependent on nutrient availability. A signaling pathway is able to adjust the rate of rDNA expansion.

Yeast will, of course, grow more slowly at low levels of glucose than they will at higher levels. But the authors were able to show that slow growth was not the reason for the slowed expansion of rDNA at low glucose. They were able to separate the two effects by overexpressing Pnc1, a nicotinamidase.

Overexpression of Pnc1 led to a decreased rate of copy number increase even at the higher glucose levels without affecting growth rate. So rDNA expansion can be separated from slow growth under the right conditions. And as you’ll see below, Pnc1 makes perfect sense given how at least part of nutrient level-dependent rDNA amplification works.

In looking for factors that might affect the rate of rDNA expansion, Jack and coworkers focused on the TOR signaling pathway, since previous work had suggested that it might be important in this process and it is known to respond to nutrient availability. The authors confirmed it was a key player by showing that rapamycin, a TOR inhibitor, kept the rDNA35 strain from expanding its rDNA in the presence of FOB1.

Again they ran into the problem of disentangling cell growth and the rDNA expansion, as rapamycin slows cell growth. The next set of experiments showed that the lack of expansion was almost certainly not due to the slower growth rate.

It is known that rapamycin affects histone deacetylases (HDACs) including Sir2. Jack and coworkers found that nicotinamide, a Sir2 inhibitor, increased the rate of expansion of rDNA without affecting growth rate. So rDNA amplification was not dependent on growth rate.

Which brings us back to Pnc1, that enzyme that cleaves nicotinamide! Presumably endogenous levels of nicotinamide are able to inhibit Sir2 and so encourage the rDNA expansion. Overexpressing Pnc1 releases Sir2 which can then impede the expansion of rDNA.

While that was a bit complicated, the idea is simple and potentially profound. Yeast can sense the level of nutrients in their environment at least partially through the TOR signaling pathway and adjust the actual content of their genome accordingly.

The involvement of nicotinamide in this regulatory process makes this result even cooler, as it has important roles in aging and cellular metabolism from yeast to man. For example, it plays a key role in the life extending properties of caloric restriction in yeast and possibly in more complicated eukaryotes as well. (Click here for a fascinating look at NAD, a compound that contains nicotinamide.)

So, in the presence of low nutrient levels, yeast expand their rDNA much more slowly than they would at higher nutrient levels. Yeast can tailor its genome in response to its environment so it can better utilize that environment.

This work raises the fascinating possibility that this process might even happen at genomic regions other than the rDNA locus. Yeast still has plenty of surprises in store—including giving a Lamarck a little boost.

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

Categories: Research Spotlight

Tags: ribosomal DNA amplification , Saccharomyces cerevisiae , nicotinamide , environmental response

Two Tales of Two Tails

July 22, 2015


Tails let animals sense and interact with their environment at a distance from their bodies. It turns out that some proteins use their “tails” in a similar way. Except they take it one step further.

Some mythical creatures have tails that coil around each other. Septin proteins are not all that different! Image via Wikimedia Commons

In addition to sensing the environment, they can also use their tails as sort of fishing poles to catch proteins they need to interact with. And they do this with great specificity…it is like having that perfect lure that always catches one type of fish.

A great example of this is the septin family of proteins which includes many members that are “tailed” proteins. Septins are highly conserved proteins that typically have a globular GTP-binding domain adjacent to an elongated C-terminal extension.

Septins form structures that act as the boundaries between different cellular parts. In budding yeast cells, they form the septum that separates the mother and bud, and recruit the cytokinesis machinery that allows the daughter cell to separate from the mother cell. In larger animals, they can be found in places such as the dendritic spines of neurons, sperm flagella, or cilia. And in humans, septin mutations have been linked to cancer and neurological diseases.

Until now, the details of how septins recruit other proteins to boundary sites have been elusive. But in two new papers in GENETICS, Finnigan and coworkers in the Thorner lab at Berkeley dove into this question and gained real insight into the lures these proteins use.

In their first paper they reported an extremely comprehensive genetic analysis to dissect the functions of two of the least characterized septins, Shs1 and Cdc11. In the second paper they used both genetic and physical methods to show how these septins recruit myosin to the septum to form the contractile ring that pinches off the bud from the mother.

The bottom line: their C-terminal tails are extremely important. They intertwine with other proteins’ tails like love-struck seahorses. And their specificity comes from these same tails—certain tails only coil around other tails.  

The S. cerevisiae genome encodes a family of septins that assemble with each other to form octameric rods that consist of four different septins. The rods have both end-to-end and side-to-side interactions with each other, forming a ladder-like superstructure.

The septins Cdc11 and Shs1 are the most closely related members of the septin family, and the most recently evolved. They cap the ends of the septin rods. In otherwise wild-type cells, Cdc11 is essential for life while Shs1 is not.

Because SHS1 can be deleted without causing a major phenotype, the first step in investigating its function was to find genetic conditions under which its function becomes more obvious. The authors created four different genetic backgrounds in which the function of other septins was compromised by different mutations. Cells that had mutations in both SHS1 and in other septin genes had obvious problems, such as elongated buds or the inability to grow at high temperatures.

Now Finnigan and colleagues were set to do a detailed genetic analysis to figure out what different parts of Shs1 do by testing mutant versions in these different backgrounds. We can’t possibly recapitulate all the results here, but we’ll do our best to cover the highlights.

Almost all septins, whether in yeast or mammals, end with a tail: a long stretch called the C-terminal extension (CTE) that contains sequence patterns characteristic of a coiled-coil structure. The researchers found that the coiled coil regions of Shs1 and Cdc11were essential to their functions. (And no, they didn’t create any mutations by writing their names in the coiled coil sequence!)

Finnigan and colleagues tried swapping CTEs between different septins. When Cdc11 carried the Shs1 CTE and vice versa, the cells grew just fine. However, this swappability didn’t extend to other septins that are positioned internally in the septin rods. The CTEs of the end subunits Cdc11 and Shs1 could be exchanged for each other, but these CTEs only worked when they were on the ends of the rods.

Since coiled coils are often involved in interactions between proteins, Finnigan and colleagues wondered whether the essential function of the Cdc11 and Shs1 CTEs might be to recruit other proteins to the bud neck.

To test this, they searched published data to identify proteins that are well-known to be localized to the bud neck at the time in the cell cycle when septins are present. They found 30 such proteins, and overexpressed GFP-tagged versions of each in a strain where both Cdc11 and Shs1 lacked their CTEs.

Of the 30 proteins, only overexpressed Bni5 suppressed the growth defect of this strain. To test directly whether binding to Bni5 is a critical function of Shs1, Finnigan and colleagues fused the two genes to each other, so that Bni5 replaced the CTE of Shs1. This fusion protein could compensate for the lack of both Cdc11 and Shs1 CTEs.

To confirm that the important function of the CTEs is to hold Bni5 in the right place, they came up with an alternative test using a “nanobody”, which is a very small, very high-affinity single-chain antibody. They replaced the CTE of either Cdc11 or Shs1 with a nanobody that recognized GFP, and expressed a GFP-Bni5 fusion in these strains. In both cases, tethering Bni5 to the septin via the nanobody obviated the need for the CTE.

Finally, the authors asked why it is important for Bni5 to be located on the septin rods. Previous work had suggested that Bni5 recruits Myo1 (myosin), an important component of the contractile ring at the bud neck. They used the same nanobody constructs to test this, simply expressing GFP-Myo1 in the strains where the nanobody replaced the CTEs of Cdc11 or Shs1. Sure enough, tethering Myo1 to the terminal septins eliminated the need for Bni5.

So we now know that tails are absolutely essential for the functions of the alternative terminal septins Shs1 and Cdc11. These fishing poles let them hold on to the Bni5 “bait,” which in turn catches Myo1 to provide the muscle for cytokinesis to occur. Since septins are so highly conserved, it’s probable that these results will be directly applicable to higher organisms: there are mammalian septins that also occupy the end positions of septin rods, analogous to Cdc11 and Shs1. And that’s no fish story!

Not only septins use their tails to fish.

by Maria Costanzo, Ph.D., Senior Biocuration Scientist, SGD

Categories: Research Spotlight

Tags: septins , Saccharomyces cerevisiae , cytokinesis

SGD Help Video: Gene Name Reservation

July 13, 2015


The eminent Drosophila geneticist Michael Ashburner famously said: “Biologists would rather share their toothbrush than share a gene name.” It’s true that assigning names to genes is often a sticky subject.

In the Saccharomyces cerevisiae community we’re very lucky to have well-defined guidelines for genetic nomenclature, an established system for reserving gene names, and criteria for making them “standard,” or official, names. This system was agreed upon by yeast researchers nearly two decades ago and has served the community well.

Take a look at this video to get an overview of how the gene naming system works. And as always, please contact us with any questions or suggestions.

Categories: Tutorial

Tags: Saccharomyces cerevisiae , video , gene nomenclature

The Gift for the Man Who Has Everything

July 08, 2015


Gifts can be hard to buy for some people. They have everything they need and not many outside interests. What to do?

Having trouble finding that personal gift for that impossible to buy for person? How about a vanity protein with their name written right into the amino acid sequence? Image by D. Barry Starr

You could name a star after them or get them some knick knack they don’t need. Or you could design a personalized protein that has their name in it, solve the structure and present them with the picture.

This is what Deiss and coworkers did to celebrate the 50th birthday of their colleague Andrei N. Lupas, a key figure in studying coiled-coil proteins. They created a personalized protein based on Gcn4 from Saccharomyces cerevisiae. And of course Gcn4 is a coiled-coil protein!

Coiled-coil proteins are the perfect clay for biosculpting a personalized protein. They follow a relatively simple set of rules which makes it easy to predict how they will fold. There isn’t much of the “protein folding problem” with these user-friendly proteins.

Basically these proteins consist of repeated 7 amino acid motifs that each form an alpha helix. They have hydrophobic residues down one face of the helix so that they will tend to oligomerize with each other to keep the hydrophobic residues away from the water. These helices spontaneously coil up like a rope (hence their name).

The 7 amino acids of a repeat are usually represented as abcdefg and are arranged in the pattern hxxhcxc, with h being hydrophobic residues, c being charged residues and x being most any other amino acid. So a and d must be hydrophobic, and e and g charged. That’s pretty much it!

Deiss and coworkers used the name Andrei N. Lupas to create a personalized coiled coil. They replaced 12 amino acids in Gcn4 with the amino acids represented by the letters in his name. Well, they were able to do that for most of the letters.

First off, they had to Roman things up a bit and turn the U into a V (there is no amino acid with the single amino acid code U). So here is the amino acid sequence they used and how they lined it up with the 7-amino acid repeats:

In this arrangement, the hydrophobic residues are asparagine, isoleucine, and valine, and the charged residues are aspartic acid, glutamic acid, proline, and serine. Obviously the last two are not optimal, especially the proline. Proline has an especially rigid conformation and is known to wreak havoc with alpha helices.

When the authors analyzed the protein, they found that as predicted, the proline disrupted the part of the alpha helix with which it was associated. But not enough to completely destroy the coiled coil structure. X-ray diffraction showed that this protein was still able to trimerize properly. They had created a distorted but functional personalized protein. What other kind would anyone want!

And it isn’t as if proline is completely absent from the heptad repeats of coiled-coil proteins. A quick search by the authors found two viral fusion proteins, 1ZTM and 3RRT, that could form a trimer even though they too had prolines. In both of these proteins the proline is in the f position.

They also found 4 dimers with a proline in a heptad repeat. In these cases the proline is at b or c. So no known natural coiled-coil proteins have a proline at the e position. Talk about personalized!

How cool is all of this, and who wouldn’t want a protein of their very own? Unfortunately, not everyone can easily have one.

For example, President Barack Obama would have real trouble since there are no amino acids designated with a B or an O and there is no obvious way to transform these letters into ones that are present in the single letter code. Jeb Bush is out too, but maybe we can do something with Hillary Clinton. Let’s see if we can line up the amino acids of her first name to create a personalized Gcn4 just for her.

“HILLARY” isn’t too bad by itself. All the letters are amino acids (yay) and a and d are hydrophobic (isoleucine and alanine). Aspartic acid works very well for e and while probably not perfect, histidine isn’t too bad for g. The tyrosine at position f is not ideal either but is way better than a proline. This thing might replace one heptad repeat in Gcn4 without causing too many problems.

So what about your name? Can you turn yours into a heptad repeat to create your own personalized Gcn4? 

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

Categories: Research Spotlight

Tags: coiled coil , Saccharomyces cerevisiae

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