New & Noteworthy
May 8, 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.
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
March 5, 2013
Cancer often gets going with chromosome instability. Basically a cell gets a mutation that causes its chromosomes to mutate at a higher rate. Now it and any cells that come from it build mutations faster and faster until they hit on the right combination to make the cell cancerous. An accelerating avalanche of mutations has led to cancer.
There are plenty of obvious candidates for the genes that start these avalanches: genes like those involved in segregating chromosomes and repairing DNA, for example. But there are undoubtedly sleeper genes that no one has really thought of. In a new study out in GENETICS, Minaker and coworkers have used the yeast S. cerevisiae to identify three of these genes — GPN1 (previously named NPA3), GPN2, and GPN3.
A mutation in any one of these genes leads to chromosomal problems. For example, mutations in GPN1 and GPN2 cause defects in sister chromatid cohesion and mutations in GPN3 confer a visible chromosome transmission defect. All of the mutants also show increased sensitivity to hydroxyurea and ultraviolet light, two potent mutagens. And if two of the genes are mutated at once, these defects become more severe. Clearly, mutating GPN1, GPN2, and/or GPN3 leads to an increased risk for even more mutations!
What makes this surprising is what these genes actually do in a cell. They are responsible for getting RNA polymerase II (RNAPII) and RNA polymerase III (RNAPIII) into the nucleus and assembled properly. This was known before for GPN1, but here the authors show that in gpn2 and gpn3 mutants, RNAPII and RNAPIII subunits also fail to get into the nucleus. Genetic and physical interactions between all three GPN proteins suggest that they work together in overlapping ways to get enough RNAPII and RNAPIII chugging away in the nucleus.
So it looks like having too little RNAPII and RNAPIII in the nucleus causes chromosome instability. This is consistent with previous work that shows that mutations in many of the RNAPII subunits have similar effects. Still, these genes would not be the first ones most scientists would look at when trying to find causes of chromosomal instability. Score another point for unbiased screens in yeast leading to a better understanding of human disease.
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.
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.