New & Noteworthy

Passing the Hog: How a Long Noncoding RNA Helps Yeast Respond to Salt

February 25, 2014

Most people know that Incans relied on human runners to get messages across their empire.  Basically they had runners stationed at various places and one runner would hand the message off to the next.  This relayed message could then quickly travel across the country.

As shown in a new study by Nadal-Ribelles and coworkers, it turns out that something similar happens in yeast when the CDC28 gene is turned up in response to high salt.  In this case, the runner is the stress activated protein kinase (SAPK) Hog1p and it is stationed at the 3’ end of the gene.  When the cell is subjected to high salt, the message is relayed from the 3’ end of the CDC28 gene to its 5’ end by the Hog1p kinase.  The end result is about a 2-fold increase in the amount of Cdc28p made, which allows the cell to enter the cell cycle more quickly after the salty insult.

Unlike the Incans who had their paths all set up in front of them, poor Hog1p has to build its own path.  It does this by activating a promoter at the 3’ end of the CDC28 gene that produces an antisense long noncoding RNA (lncRNA) that is needed for the transfer of the Hog1p.  It is as if our Incan runner had to build a bridge over a gorge to send his message.

This mechanism isn’t peculiar to the CDC28 gene either.  The authors in this study directly show that something similar happens with a second salt sensitive gene, MMF1.  And they show that a whole lot more lncRNAs are induced by high salt in yeast as well.

Nadal-Ribelles and coworkers started off by identifying coding and noncoding regions of the yeast genome that respond positively to high salt.  The authors found that 343 coding regions and 173 noncoding regions were all induced at 0.4 M NaCl.   Both coding and noncoding regions required the SAPK Hog1p for activation. 

The authors next focused on CDC28 and its associated antisense lncRNA.  After adding high salt, Nadal-Ribelles and coworkers found that Hog1p was both at the start and end of the CDC28 gene – as would be expected, since both CDC28 and the antisense lncRNA required this kinase for transcriptional activation. 

Things got interesting when they were able to prevent the lncRNA from being made.  When they did this, Hog1p was missing from both the 5′ and 3′ ends of the CDC28 gene and as expected, activation was compromised.  But Nadal-Ribelles and coworkers showed that expressing the lncRNA from a plasmid did not allow for CDC28 activation. It appears that where the lncRNA is made is just as important as whether it is made.

Through a set of clever experiments, the authors showed that not only does the lncRNA need to be made in the right place, but it needs to be activated in the right way.  When they set up a system where the lncRNA was induced in the right place using a Gal4-VP16 activator, CDC28 was not induced by high salt.  A closer look showed that this was most likely due to a lack of Hog1p at the start of the CDC28 gene.

The situation was different when they activated the lncRNA with a Gal4-Msn2p activator which uses Hog1p to increase expression.  In this case, CDC28 now responded to high salt and Hog1p was present at both the start and end of the CDC28 gene.  But this activation went away if they added a terminator which prevented the full length lncRNA from being made. 

Phew, that was a lot!  What it means is that for there to be a Hog1p at the business end of the CDC28 gene, there needs to be one at the 3’ end.  It also means that for the Hog1p to get to the start of the CDC28 gene, the antisense lncRNA needs to be made.

This would all make sense if maybe the lncRNA was involved in DNA looping, which could get the Hog1p from the end of CDC28 to the start where it can do some good.  Nadal-Ribelles and coworkers showed that this indeed was the case, as CDC28 activation required SSU72, a key looping gene.  When there was no Ssu72p in a cell, salt induction of CDC28 was severely compromised.

So it looks like an antisense lncRNA in yeast is being used as part of a looping mechanism to provide the cell with a quick way to start dividing once it has dealt with its environmental insult.  The authors show that yeast that can properly induce their CDC28 gene enter the cell cycle around 20 minutes faster than yeast that cannot induce the gene.  The cells are poised for a quick recovery.

And this is almost certainly not merely a yeast phenomenon.  Some recent work in mammalian cells has implicated lncRNAs in recruiting proteins involved in controlling gene activity through a looping mechanism as well (reviewed here).  Now that the same thing has been found in yeast, scientists can bring to bear all the powerful tools available to dissect out the mechanism(s) of lncRNA action.  And that’s far from a loopy idea…

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

Categories: Research Spotlight

Tags: DNA looping, lncRNA, Saccharomyces cerevisiae, transcription

Yeast, Smarter than a Train Wreck

January 30, 2014

Imagine you run a railroad that has a single track. You need for trains to run in both directions to get your cargo where it needs to go.

One way to regulate this might be to have the trains just go whenever and count on collisions as a way to regulate traffic. Talk about a poor business model! Odds are your company would quickly go bankrupt.

Another, more sane possibility is to somehow keep the trains from running into each other. Maybe you schedule them so their paths never cross. Or maybe you have small detours where a train can wait while the other passes. Anything is better than regulation by wreckage!

Turns out that at least in some cases, nature is a better business person than many people previously thought. Instead of trains on a track, nature needs to deal with nearby genes that point towards one another, so-called convergent genes. If both genes are expressed, then the RNA polymerases will barrel towards one another and could collide.

A new study in PLoS Genetics by Wang and coworkers shows just how big a deal this issue is for our favorite yeast Saccharomyces cerevisiae. An analysis of this yeast’s genome showed that not only did 20% of its genes fit the convergent definition but that in many cases, each gene in a pair influenced the expression of the other gene. Their expression was negatively correlated: when one of the pair was turned up, the other went down, and vice versa.

One way these genes might regulate one another is the collision model. When expression of one gene is turned up and a lot of RNA polymerases are barreling down the tracks, they would crash into and derail any polymerases coming from the opposite direction. A prediction of this model is that orientation and location matter.  In other words, the negative regulation would work only in cis, not in trans.  Surprisingly, the authors show that this is clearly not the case.

Focusing on four different gene pairs, Wang and coworkers showed that if the genes in a pair were physically separated from one another, their expression was still negatively correlated.  This was true if they just flipped one of the genes so the two genes were pointed in the same direction, and it was still true if they moved one gene to a different chromosome.  Clearly, collisions were not the only way these genes regulated one another.

Using missense and deletion mutation analysis, the authors showed that neither the proteins from these genes nor the coding sequence itself was required for this regulation.  Instead, the key player was the overlapping 3’ untranslated regions (UTRs) of the transcripts.  The authors hypothesize that the regulation is happening via an anti-sense mechanism using the complementary portions of the 3’ UTRs.

This anti-sense mechanism may be S. cerevisiae’s answer to RNAi, which it lost at some point in its evolutionary history.  Given the importance of RNA-mediated regulation of gene expression in other organisms, perhaps it shouldn’t be surprising that yeast has come up with another way to use RNA.  

Instead of RNAi, it relies on genomic structure and overlapping 3’ UTRs to regulate genes.  This may be a bit more cumbersome than RNAi, but at least yeast came up with a more clever system than polymerase collisions to regulate gene expression.  

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

Categories: Research Spotlight

Tags: RNA polymerase II, Saccharomyces cerevisiae, transcription, UTR

The Brazor of Biology

January 08, 2014

The janitor on the U.S. comedy series Scrubs is always coming up with terrible inventions. One of his worst was the knife-wrench. It is what it sounds like—a tool with a knife at one end and a wrench at the other.

Of course not all dual purpose tools have to be so useless.  Imagine a tool like the one at the right with a razor at one end and a toothbrush on the other.  Now you can easily brush your teeth and shave in the shower or at your bathroom sink (as long as you are careful not to cut your cheek).

Turns out that biology has these dual purpose tools too except that they are almost always more useful.  For example, Lahudkar and coworkers show in the most recent issue of GENETICS that Cet1p doesn’t just help out with capping mRNA.  No, these authors found that it also helps clear RNA polymerase II (RNA pol II) away from promoters.  And what’s most interesting is that this second function has little to do with its job in mRNA capping.

Basically the two functions are probably in the same protein because they both happen in the same place, at the start site of a promoter.  Just like our brazor is useful because both jobs happen in the bathroom.

The first step was to show that in the absence of Cet1p, RNA pol II was more likely to be found near the start of transcription.  The authors showed that this was the case by using a temperature sensitive mutant of Cet1p and a chromatin immunoprecipitation (ChIP) assay targeted at RNA pol II—there was more RNA pol II crowded near the promoter at the nonpermissive temperature. 

The next set of experiments showed that merely messing with the cap is not sufficient to cause the polymerase to pause. Lahudkar and coworkers found that RNA pol II occupancy was unchanged in strains carrying mutations in STO1 (also known as CBP80) or CEG1, two components of the capping machinery. Cet1p apparently has a separate, unrelated function in helping to clear polymerases away from the start site of transcription.

The final set of experiments showed that the unpausing activity of Cet1p was found in a different part of the protein from its capping function.  Cet1p be can be broadly divided into three regions—a poorly characterized N-terminal domain (amino acids 1-204), a Ceg1p interaction domain (aa 205-266), and a triphosphatase domain (aa 265-549).  The last two domains are critical to its capping function.

Lahudkar and coworkers found that deleting the 1-204 aa domain from Cet1p caused polymerase stalling at the promoter without affecting its capping ability.  And conversely, that when they impaired the ability of Cet1p to perform its capping function while retaining its 1-204 aa domain, RNA pol II escaped the promoter at the same rate as it did in the presence of wild type Cet1p.  A final experiment showed that just expressing the first 300 amino acids of Cet1p was sufficient to get the polymerases moving. 

All in all these experiments provide strong evidence that Cet1p has two separate functions—an enzymatic role in capping mRNA and an unrelated activity that helps clear RNA pol II from the regions around the promoters of genes.  Which all goes to show that even when you think you have a handle on a protein, it can still surprise you with something new.  Turn it around and you just might find a toothbrush at the end.

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

Categories: Research Spotlight

Tags: bifunctional protein, mRNA capping, Saccharomyces cerevisiae, transcription

Keeping the Noise Down

May 08, 2013

When you get down to a single cell, things can get really noisy. Instead of the nice, smoothed over data that you see in populations, you see some variation from cell to cell. This is even if all the cells are identical genetically.

Of course this makes perfect sense if you think about it. Part of the variation comes from slightly different environments. Conditions at the bottom of the flask are bound to be different from those at the top! This goes by the name of extrinsic noise.

Another source of variation has to do with levels of reactants within the cell and the chances that they encounter each other so they can react. These effects can be especially pronounced when there aren’t a lot of reactants around. This goes by the name intrinsic noise.

One process with a lot of noise is gene regulation. It is often affected by minor fluctuations in the environment and there are usually just one or two copies of the gene itself. This is the perfect recipe for noise.

The noisiness of gene expression can be split into two steps. One, called burst frequency, reflects how often RNA polymerase sits down and starts transcribing a gene. The second, burst size, has to do with how many proteins are produced each time a gene is turned on.

Of these two processes, the most sensitive to noise is usually burst frequency. A transcription factor (TF) has to find the promoter of the gene it is supposed to turn on and then bring the polymerase over to that gene. This is dependent on the amount of TF in a cell and the number of TF binding sites on the DNA. What this means is that most of the time, genes with low levels of expression tend to be very noisy.

There are some situations, though, where it is very important to have low expression and low noise: for example, where a cell needs at least a few copies of a protein, but can’t tolerate too many. For most promoters, low levels of expression mean high noise, which in turn means there will be some cells that lack this key protein entirely. But a new study out in PLOS Biology shows one way that a promoter can have the best of both worlds.

In this study, Carey and coworkers examined the noisiness of sixteen different naturally occurring promoters in the yeast S. cerevisiae, controlled by the TF Zap1p. This is a great system because the activity of Zap1p is determined by the concentration of zinc in the medium. This means the authors were able to look at the noisiness of these promoters under a broad range of gene activities.

Their research yields a treasure trove of information about the noisiness of these promoters at varying levels of expression. As we might predict, noise decreased at most (11/13) of the reporter genes as more active Zap1p was around. This makes sense, as cell to cell variability will decrease as genes are turned on more often. Higher burst frequency means less noise.

The opposite was true for most (2/3) of the reporters repressed by Zap1p. As more Zap1p was around, transcription of the reporter gene became less frequent, which meant that the noise effects became more prominent.

One of the more interesting findings in this study focused on an exception to this rule. The ZRT2 promoter showed a bimodal expression pattern, as it was activated at low levels of zinc and repressed at high levels. What makes it so interesting is that its noise level stays fairly constant.

As the zinc concentration increases and activity goes up, the noise goes down. This is what we would expect. But when zinc levels get high enough so that the gene is repressed, the noise levels do not increase. They stay similar to the levels seen with the activated gene.

The authors show that this promoter is repressed differently than the other two repressed promoters, ADH1 and ADH3. These promoters are repressed by decreasing the burst frequency: they fire less often when repressed. In contrast, the ZRT2 promoter fires at the same activated rate when repressed, but yields less protein with each firing: repression decreases burst size.

So this is how a cell can manage to get a gene turned on at low levels more or less uniformly through a cell’s population. If it can create a situation where the gene fires a lot but very little protein is made with each firing, then the cell will have relatively constant but low levels of that protein.

This study also provides a new tool for dissecting how a TF affects the expression of a gene. If a repressor decreases expression without an increase in noise, then it is probably affecting burst size. If on the other hand the noise goes up as expression goes down, then the repressor is affecting burst frequency.

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

Categories: Research Spotlight

Tags: cellular noise, RNA polymerase II, Saccharomyces cerevisiae, transcription

Old Genes, New Tricks

March 14, 2013

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

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

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

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

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

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

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

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

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

Categories: Research Spotlight

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

Puzzling Out Gene Expression

February 21, 2013

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

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

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

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

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

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

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

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

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

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

Categories: Research Spotlight

Tags: RNA polymerase II, Saccharomyces cerevisiae, transcription

When Polymerases Collide

October 25, 2012

Lots of recent studies are showing that transcription happens over way more DNA than anyone previously thought. For example, the ENCODE project has shown that most of a genome gets transcribed into RNA in humans, fruit flies and nematodes. This transcriptional exuberance was recently confirmed in the yeast S. cerevisiae as well.

There is also a whole lot of antisense transcription going on. Taken together, these two observations suggest that there are lots of opportunities for two polymerases to run headlong into each other. And this could be a big problem if polymerases can’t easily get past one another.

Imagine that the two polymerases clash in the middle of some essential gene. If they can’t somehow resolve this situation, the gene would effectively be shut off. Bye bye cell!

Of course this is all theoretical at this point. After all, smaller polymerases like those from T3 and T4 bacteriophages manage to sneak past one another. It looks like this isn’t the case for RNA polymerase II (RNAPII), though.

As a new study by Hobson and coworkers in Molecular Cell shows, when two yeast RNAPII molecules meet in a head on collision on the same piece of DNA, they have real trouble getting past each other. This is true both in vitro and in vivo.

For the in vivo experiments, the authors created a situation where they could easily monitor the amount of transcription close in and far away from a promoter in yeast. Basically they pointed two inducible promoters, from the GAL10 and GAL7 genes, at one another and eliminated any transcription terminators between them. They also included G-less cassettes (regions encoding guanine-free RNA) at different positions relative to the GAL10 promoter, so that they could use RNAse T1 (which cleaves RNA at G residues) to look at how much transcription starts out and how much makes it to the end.

When they just turned on the GAL10 promoter, they saw equal amounts of transcription from both the beginning and the end of the GAL10 transcript. But when they turned on both GAL10 and GAL7, they saw only 21% of the more distant G-less cassette compared to the one closer to the GAL10 promoter.

They interpret this result as meaning the two polymerases have run into each other and stalled between the two promoters. And their in vitro data backs this up.

Using purified elongation complexes, they showed that when two polymerases charge at each other on the same template, transcripts of intermediate length are generated. They again interpret this as the polymerases stopping dead in their tracks once they run into one another. Consistent with this, they showed that these stalled polymerases are rock stable using agarose gel electrophoresis.

Left unchecked, polymerases that can’t figure out how to get past one another would obviously be bad for a cell. Even if it were a relatively rare occurrence, eventually two polymerases would clash somewhere important, with the end result being a dead cell. So how do cells get around this thorny problem?

One way is to get rid of the polymerases. The lab previously showed that if a polymerase is permanently stalled because of some irreparable DNA lesion, the cell ubiquitinates the polymerase and targets it for destruction. In this study they used ubiquitin mutants to show that the same system can work at these paused polymerases too. Ubiquitylation-compromised yeast took longer to clear the polymerases than did their wild type brethren.

The authors think that this isn’t the only mechanism by which polymerases break free though. They are actively seeking factors that can help resolve these crashed polymerases. It will be interesting to see what cool way the cell has devised to resolve this dilemma.

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

Categories: Research Spotlight

Tags: RNA polymerase II, Saccharomyces cerevisiae, transcription, ubiquitin-mediated degradation

Yeast with Sticking Power

July 16, 2012

Most strains of Saccharomyces cerevisiae don’t stick together very well. And hardly any of them form biofilms. But it would be very useful to have a better understanding of why some strains like to stick together and others do not. 

Stickiness helps in any process where you want the yeast to do something and then get rid of it. An obvious example is ethanol production either for energy or to make our beer and wine. After sticky yeast are done with their job of making the alcohol, they simply fall to the bottom of the fermentor or float on the surface in a biofilm (the “flor”). This makes the step of separating the yeast from the finished product that much easier.

Understanding more details of yeast stickiness would also be useful for studying harmful yeast. Adhesion to other cells and to substrates is an important factor in pathogenesis. It would be nice to investigate this phenomenon in the more tractable brewer’s yeast.

The Ibeas lab has decided to figure out why most strains of S. cerevisiae can’t flocculate by comparing one of the few that can (the “flor” strain used to make sherry) to a reference strain that can’t.  They previously showed that a key gene in the process, FLO11 (also known as MUC1), is expressed at much higher levels in flor.  They were also able to show that a large part of this increased expression comes from a 111 base pair deletion in the FLO11 promoter in this particular strain.

In a recent paper in GENETICS, Barrales and coworkers set out to investigate why the loss of these 111 base pairs leads to increased gene expression.  They were able to conclude that the deletion does not significantly affect histone occupancy at the promoter.  What they could see was that histone placement was affected and that PHO23 may play a significant role in this.

The researchers had previously shown that the histone deacetylase complex (HDAC) Rpd3L was important for maximal FLO11 activity.  They next wanted to determine if this complex was the major player in explaining the increased activity of the 111 bp deletion FLO11 promoter (Δ111) over the wild type (WT) one.  They did this by comparing the level of mRNA made by each promoter in strains lacking either the Pho23p or the Rpd3p subunits of the Rpd3L complex.  They found that the Δ111 construct was much more severely compromised by the loss of PHO23 than was the WT one.  (A bit confusingly, neither was much affected by the loss of RPD3.) 

Given that PHO23 is part of a complex that affects chromatin, the next thing the researchers did was look at the histones in and around both FLO11 promoters.  They found that PHO23 was involved in maintaining an open chromatin structure at the FLO11 promoter but that deleting the 111 base pairs didn’t affect this process significantly.

Where they started to see subtle differences was when they looked at histone placement as opposed to occupancy.  Using micrococcal nuclease protection to map chromatin structure, they found a number of differences between the two promoters, centered on the deletion and the TATA box, and deleting PHO23 affected the two promoters in different ways.

It appears that FLO11 is upregulated in the flor strain because the deletion of 111 base pairs leads to an altered chromatin structure.  The next steps will be to figure out what this means and then to use that knowledge to create stickier yeast. We’ll end up with a better understanding of transcriptional regulation and adhesion, and beer and wine makers may end up with even better self separating yeast.

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

Categories: Research Spotlight

Tags: biofilm, flocculation, Saccharomyces cerevisiae, transcription

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