New & Noteworthy

Alternatives to Whale Puke

May 11, 2012

Scientists are finally on their way to finding an alternative to ambergris like this. Image courtesy of Wikimedia Commons.

Imagine scouring the beaches of the world for balls of whale vomit.  People are willing to do this because finding one is like finding a huge gold nugget.  Perfume companies will pay around $10,000 per pound for this ambergris (which is the more scientific name for the stuff). 

Of course perfume companies would rather have a more reliable and less expensive source for their ambergris.  And it wouldn’t hurt to find one that was a little less ethically troubling than using products from an endangered animal.

Until recently their best bet was a chemical called cis-abienol from balsam firs.  While less murky ethically, this chemical is tricky to harvest and even trickier to synthesize in the lab.  The perfume industry could definitely use an alternative.  And researchers in the Bohlmann lab may be on their way to finding it.

In a recent study from this lab, Zerbe and coworkers used “…metabolite profiling, tissue-specific deep transcriptome sequencing and functional (i.e. biochemical) genomics…” to identify the key enzyme for making cis-abienol in balsam firs.  They next plan to put the gene into yeast and have the yeast crank out this chemical.

Finding the gene was not trivial.  The first thing they did was to identify that most of the cis-abienol was made in the bark and phloem of the balsam fir.  They then sequenced the transcriptome from these sources and looked for likely candidate genes.  For this last step, they used a curated library of 146 known terpene synthases.

They found 4 candidate genes (AbdiTPS1-4) and successfully cloned three of them.  They then went on to express these proteins in E. coli, purify them, and found that AbdiTPS4 catalyzed the synthesis of cis-abienol in vitro. They renamed the gene AbCAS at that point.

According to Dr. Bohlmann, the lab is now testing conditions for getting the enzyme to work in yeast.  If they can pull it off, the perfume industry will finally get a cheap and easy alternative to whale vomit.  Let’s see if they pass any savings down to the consumer…

Take SGD with you wherever you go!

May 7, 2012

The YeastGeome app splash screen on an iPad.

SGD has just released an app for the iPhone, iPad and iPod touch ap(p)tly called “YeastGenome”, containing the latest Saccharomyces cerevisiae information from the database, available now as a free download on iTunes. Search by gene names, gene descriptions or simply browse for quick access to Gene Ontology annotations, mutant phenotypes and protein and genetic interaction data for your favorite genes – all at your fingertips!

Use YeastGenome to:

  • Search using gene name or keywords
  • Browse by genomic feature types
  • Save your favorite genomic features
  • Quickly see fundamental genomic feature information
  • Find Gene Ontology terms, Phenotypes, Interactions, and References associated with genomic features

… with or without an internet connection!

How many ATP-dependent RNA helicases is the S. cerevisiae genome known to encode? Which proteins have a zinc finger motif? Now you can answer these questions and more with the YeastGenome app, whether you’re in line at the supermarket or having lunch with your colleagues or attending a seminar with no wifi-access! Get your friends and colleagues as fired up about The Awesome Power of Yeast as you are – use YeastGenome to email information about genomic features to collaborators and spread the word!

Please read our FAQ or visit iTunes for more information.

When Heat is Not the Burning Issue

May 4, 2012

Just because a mutation looks temperature sensitive, that doesn't mean it is.

When is a temperature sensitive mutation not a temperature sensitive mutation? When the process being studied is affected by temperature too.

Mutations conferring temperature sensitivity – that is, a phenotype that only appears at higher- or lower-than-normal growth temperature due to the loss or alteration of function of a gene product at that temperature – have for decades been an invaluable tool in dissecting many biological processes in yeast and other model organisms. Now there is reason to question whether some temperature sensitive phenotypes might actually be the result of a more complex interaction between multiple genes.

This synthetic genetic interaction is easy to mistake for the effect of a single mutation. A scientist starts out with a mutation that weakens a gene in a certain process. Unfortunately for the scientist, the process being studied is itself weakened by higher temperatures. The effect of the higher temperature combines with the effect of the mutation to shut down the process. The mutation looks temperature sensitive even when it isn’t.

And this does not appear to be merely a theoretical concern. As Paschini and coworkers show in a new study out in GENETICS, something similar may have happened with key mutations used to study telomere function in yeast.

These researchers looked at several mutations but we’ll focus on the work they did with cdc13-1. A key experiment that had been previously done with this mutation dealt with the effects of the loss of cdc13 function in the absence of RAD9.

Basically, researchers had found that prolonged incubation of a cdc13-1/Δrad9 strain at 36° severely compromised viability. These results were used to infer CDC13 function based on its loss at 36°. However, Paschini and coworkers provide compelling data that cdc13-1 behaves equally poorly at 23° and 36°.

First off, they showed that prolonged incubation of wild type yeast at the temperatures used in these studies (36°) resulted in shorter telomeres. They found very little effect on telomere length at 32°.

Next they showed that biochemically, cdc13-1 didn’t behave like a temperature sensitive mutation. Strains with cdc13-1 produced around 4-fold less protein at both 23° and 36° and the protein that was made bound telomeres equally well at both temperatures.

They argue from these two pieces of data that the loss of viability comes from a combination of the compromised cdc13-1 mutation and the effects of higher temperature on telomere function. Something is going on in the rad9 experiment but it is not due to an increased loss of CDC13 function at higher temperatures. There is some other factor involved that is being inhibited.

Of course it could be that cdc13-1 still confers temperature sensitivity, but that they didn’t have the right biochemical assay to see it. To address this issue, they generated five new mutations in cdc13 that behaved more like traditional temperature sensitive mutations.

They focused on one, cdc13-S611L, that was compromised for protein production at temperatures of 32° and above. They then repeated the rad9 double mutant experiment at 32° and 36°. They found that viability was compromised only at 36° even though Cdc13p was equally absent at both 32° and 36°. These results suggest that the loss of viability at 36° is not only the result of cdc13-1.

If this and other results hold up, scientists will need to rethink what previous experiments meant and they may need to modify their models. This should also get other researchers thinking about their temperature sensitive mutations.  It is important to confirm biochemically that a mutation indeed makes a specific gene product temperature sensitive. Because sometimes even if it quacks, it isn’t a duck…

SGD Quarterly Newsletter

April 30, 2012

SGD sends out its quarterly newsletter to colleagues designated as contacts in SGD. An HTML version of the newsletter is available. If you would like to receive this letter in the future please use the Colleague Submission/Update form to let us know.

Idling Transcription Factors

April 24, 2012

Transcription factors may lie in wait on the DNA, waiting for a signal to pounce. Image courtesy of DesktopNexus http://www.desktopnexus.com/.

A new study by Lickwar and coworkers suggests that many transcription factors fidget on and off the DNA, waiting for some signal to get to work.  Once they get that signal, they clamp down and start affecting the activity of nearby genes.

If true this would help explain some perplexing results researchers have been getting with chromosomal immunoprecipitation (ChIP) assays.  Transcription factors appear to be bound at many places where they are not affecting any nearby genes.  Now we might have an idea why.

These researchers came up with this model through the use of an elegant, in vivo competition study.  What they did was to set up a yeast strain that contained two different versions of the transcription factor Rap1p.  One version was tagged with a FLAG epitope and was under the control of RAP1’s endogenous, constitutive promoter.   The other version was tagged with a Myc epitope and was under the control of an inducible promoter.

They started out seeing where Rap1p was bound in the absence of the inducer by using an antibody against FLAG.  This is the equivalent of a typical ChIP experiment.  They found Rap1p was bound in many places throughout the genome including sites where it did not appear to affect any nearby genes.

Then they added the inducer galactose and at various time points repeated the ChIP experiment with antibodies against either FLAG or Myc.  They were basically looking for how quickly the Myc-tagged Rap1p replaced the FLAG-tagged Rap1p with the idea that less stably bound transcription factors would be replaced more quickly.

They indeed found that some sites were better able to withstand the onslaught of Myc-tagged Rap1p.  And more importantly, that these sites were near genes most influenced by Rap1p.  In other words it appears that the more stably bound the Rap1p, the bigger the effect it has on nearby genes.

They then went on to show that more stable binding correlated with lower nucleosome occupancy and stronger in vitro binding.  From this data they propose a model where the level of the effect on transcription is the result of a competition between nucleosome and transcription factor binding.  Stronger transcription factor binding keeps nucleosomes away so transcription can proceed.

They took the model one step further and proposed that transcription factors are idling on the DNA, waiting for a signal to bind more tightly and influence the activity of nearby genes.  In other words, transcription factors are ready to have an effect at a moment’s notice.

This part of the model still has to be proven though.  All that has been shown so far is that a slow off rate is required for effective transcription activation by Rap1p.  What we don’t know is whether this translates to other transcription factors or if idling Rap1p is ever more stably bound.