New & Noteworthy

Dealing With Alcohol, a Messy Business

September 16, 2014

Variations in MKT1 do not have as profound an effect on alcohol tolerance in yeast as do variations in ALDH2 in people, but MKT1 is definitely a big player. Image from Wikimedia Commons

Different people can respond to alcohol differently because of their genes.  For example, many Asians flush or even become ill from alcohol because of a mutation in their ALDH2 gene. (This is not just a minor annoyance—these unpleasant side effects come with a significant increase in esophageal cancer rates.)

This is a simple example where one gene has a significant effect. But of course, not everything to do with people and alcohol is so simple at the genetic level! 

For example, some people can drink you under the table while others are lightweights.  Some of this has to do with their lifestyle (how often they drink, how much they weigh, etc.), but a lot undoubtedly has to do with the variations they carry in multiple genes.

Well, it turns out this is also the case for yeast (our friend in the alcohol business). A new paper in GENETICS by Lewis and coworkers confirms that different strains of the yeast Saccharomyces cerevisiae tolerate high levels of alcohol differently because of their specific genetics. And at first the response seems…shall we say…incapacitatingly complex.

The results are interesting in that they help parse out how yeast responds to ethanol, but the implications are more far-reaching than that.  This analysis helps to form the framework for investigating how natural variation in gene expression can affect the traits of individuals and their responses to certain environmental stimuli.

Lewis and coworkers used three strains in their study: a lab strain that came from everyone’s favorite workhorse S288c, the strain M22 from a vineyard, and the oak soil strain YPS163.  They had previously shown that thousands of genes in each strain responded differently to 5% ethanol.  In this study they set out to find out what was behind these differences.

First off they wanted to confirm their previous results.  Using six biological replicates, they found that 3,287 genes out of a total of 6,532 were affected in at least one strain when treated for 30 minutes with 5% ethanol.  This is over half the genes in the genome!

To try to get a handle on what is causing such widespread effects, they next performed eQTL mapping in 45 F2 crosses of S288c X M22 and S288c X YPS163 (these particular matings were chosen because much of the variation they saw was in S288c).  This analysis was designed to try to find “hotspots” in the genome:  loci that affected many different transcripts, or that could account for all the variation they saw.

When they did this analysis they found 37 unique hotspots. Each hotspot represented 20-1,200 different transcripts, with a median of 37 transcripts.  Of these, 15 were seen in both crosses, 12 in just the S288c X M22 and 10 in the S288c X YPS163 matings. No silver bullet, but 37 is certainly easier to work with than 3,287!

Lewis and coworkers next set out to find the key gene(s) in the hotspots responsible for affecting multiple transcripts in the presence of ethanol.  Some were easy to find.  For example, HAP1 in S288c and CYS4 in M22 X S288c.  But the big prize in this analysis probably goes to MKT1, which affected over 1,000 transcripts in this study.

Now MKT1 is not one of the usual suspects, in that it is not a transcription factor.  However, MKT1 has been implicated in lots of observed differences between strains, including alcohol tolerance in one Brazilian overproduction strain.  Given this, the authors set out to explore whether there were any differences in Mkt1p activity in response to ethanol in the different strains.

This analysis revealed that Mkt1p localizes to P-bodies upon ethanol stress in S288C but not YPS163. And this wasn’t some general defect in Mkt1p, since it is known to colocalize with P-bodies in both strains in response to hypo-osmotic stress.

With this discovery, things were starting to make a bit more sense!  Since P-bodies are involved in mRNA turnover, it follows that a P-body component might affect so many transcripts. One potential explanation might be that Mkt1p serves as a regulator by translationally silencing specific mRNAs at P-body loci. This would be consistent with its known role in translational regulation of the HO transcript.

This study reveals how difficult it is to get to the bottom of determining exactly how massive differences in gene expression lead to differences in traits.  But it also shows that while daunting, it is doable.  And perhaps yeast can show us how best to interrogate our own differences in gene expression to help figure out why we are the way we are—not only in terms of whether we dance on the tables or fall to the floor after a few drinks, but in many other respects as well.

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

Categories: Research Spotlight

Tags: transcription regulation, Saccharomyces cerevisiae, eQTL mapping, ethanol response

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