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.