New & Noteworthy

Esa1p, the Balancing Artist

July 15, 2014

In the art of rock balancing, the artist positions large rocks with exquisite precision. If he or she succeeds, the rocks counterbalance each other and stay in seemingly impossible positions to make a surprising and beautiful sculpture. But a little uneven pressure is enough to make the whole thing collapse.

It turns out that the cellular acetylation state is just as precisely balanced. In a new GENETICS paper, Torres-Machorro and Pillus identify Esa1p, an acetyltransferase, as the balancing artist in Saccharomyces cerevisiae cells.

Acetylation is an important type of protein modification. Histones, the proteins that interact with DNA to provide structure to chromosomes, are acetylated by histone acetyltransferases (HATs) and deacetylated by histone deacetylases (HDACs). Some HATs and HDACs also act on non-histone proteins.

The acetylation state in a cell is a dynamic process.  All those HATs are adding acetyl groups at the same time that HDACs are removing them.  The final level of acetylation depends on the activities of each of these classes of proteins.

Acetylation of histones has been associated with increases in gene expression and deacetylation with decreases.  So to keep gene expression levels in balance, it is very important to keep acetylation balanced as well.  Throwing acetylation patterns just a bit out of whack can have profound consequences on global gene expression that can ultimately lead to cell death. 

The authors focused on one particular HAT, Esa1p, that acetylates histones H4 and H2A and also has non-histone targets. They were intrigued by the fact that yeast cells cannot survive without Esa1p, since no other HAT or HDAC subunit is essential in yeast.

An obvious explanation for lethality is that losing this protein leads to too low a level of acetylation.  They reasoned that if they also knocked out an HDAC, then the overall acetylation levels might increase and so rescue the esa1 null mutant.  And they were right.

Using a plasmid-shuffling method, they created various double mutant strains of esa1 and HDAC genes, and found that a strain that was mutant in esa1 and also in either the SDS3 or DEP1 genes was viable. SDS3 and DEP1 both encode subunits of the Rpd3L HDAC complex.

Torres-Machorro and Pillus next characterized the esa1 sds3 double mutant further.  They found that although the sds3 mutation suppressed the inviability of the esa1 mutant, it did not suppress other phenotypes such as sensitivity to high temperature and DNA damaging agents.

The authors found that the sds3 mutation subtly increased histone H4 acetylation, which was low in the absence of Esa1p.  However, acetylation levels of a different histone, H3, remained high even in the absence of Esa1p. This suggested that the fundamental problem in the esa1 null mutant was an imbalance in the global state of histone acetylation.

To test this hypothesis, the researchers used a variety of different genetic methods to tweak the balance of cellular acetylation in the esa1 sds3 mutant. They created mutations in histones H3 and H4 that made it seem as if acetylation was low or high, and they also mutated other genes for HDAC subunits. It is as if they were passers-by who decided to poke at a balanced rock sculpture to see what it took to bring the whole thing down.

Although the details are too numerous to report here, the results showed that by using these genetic methods to tweak the overall acetylation state of the cell, the fitness of the esa1 sds3 strain could be improved: phenotypes such as slow growth, sensitivity to high temperature or DNA damaging agents, or cell cycle defects were suppressed to some extent by the various manipulations.  This lends support to the hypothesis that Esa1p is the master balancer of acetylation levels in the cell and that this is its essential function.

This balancing act may happen in human cells too. Esa1p has a human ortholog, TIP60, that has been implicated in cancer and other diseases. Like Esa1p, TIP60 is essential and is involved in the DNA damage response.

So yeast teaches us that the acetylation of proteins is balanced on a knife’s edge.  Even the slightest changes can lead to a collapse in global gene regulation, which can have catastrophic effects like cancer. All that we learn about Esa1p, the acetylation balancing artist, may have much broader implications for human health.

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

Categories: Research Spotlight, Yeast and Human Disease

Tags: histone acetylation, Saccharomyces cerevisiae, yeast model for human disease

Adding Introns to Synthetic Biology’s Toolbox

July 03, 2014

As any good handyman knows, the more tools you have in your tool chest, the better the chance that you can find what you need to solve a problem.  The same goes for synthetic biologists.  The more parts they can mix and match, the more likely they are to engineer the exact level of gene expression they need.

In the last few years synthetic biologists have amassed a wide variety of transcription and translation elements that can be combined in different ways to exquisitely tune the level of expression of their gene of interest.  And now, in a new study out in PLOS Genetics, Yofe and coworkers have added introns to the list of parts available for our favorite yeast Saccharomyces cerevisiae.

Yeast isn’t loaded with introns, but it does have a reasonable number that can be co-opted for synthetic biology.  The authors inserted 240 of these introns individually into the same position near the 5’ end of the yellow fluorescent protein (YFP) gene and monitored the level of fluorescence of each individual strain over a 24 hour period.  They chose the 5’ end of the gene because yeast has a bias for introns being located there.

The authors found that these reporters spanned a 100-fold range of gene expression, that every intron caused a decrease in the level of gene expression, and that even though many of these introns respond to environmental stimuli in their natural context, their effect on gene expression here was immune to the environmental changes the authors tested.  Taken together, these results suggest that introns could be used in yeast systems for dampening over-exuberant gene expression in ways that are independent of growth conditions.  If all of this holds up, introns will prove to be very useful tools indeed.

Yofe and coworkers next wanted to use this library to figure out some of the rules for why some introns cause lowered activity compared to others.  The simplest possibility, that longer introns cause a larger decrease in gene expression, turned out not to be true.  There was no correlation between the size of the intron and its effect on the level of fluorescence. 

Next they scanned the sequences of their constructs to look for elements that might increase or decrease splicing efficiency.  These splicing regulatory elements (SREs) are better understood in larger eukaryotes, but there is evidence that they are important in yeast as well.  The authors identified a number of intron splicing enhancers (ISEs) and intron splicing silencers (ISSs) that were highly enriched near the splice sites. 

To confirm that these sequences did in fact affect splicing efficiency (and hence gene expression), they showed that mutating the enhancer motif TTTATGCT to the silencer motif TTTGTGTA in two reporters resulted in a 22% and a 13% decrease in gene expression.  This proof of principle experiment suggests that future synthetic biologists may be able to further tweak the expression of their genes by manipulating these SREs.

In a final set of experiments the authors used the library to identify rules that can be used to predict how inserting various introns into different positions will affect a gene’s activity.  They found that the most important features were the presence of SREs and the RNA structures at the intron-exon junction.  Synthetic biologists should be able to use these rules to intelligently design their reporter systems.

These experiments are the first step towards adding introns to the ever growing set of tools available to synthetic biologists for modulating gene expression.  We are getting closer to figuring out how genes are controlled and being able to use that knowledge to our advantage.  Or to put it another way, we have taken another baby step towards being able to control a gene as well as a yeast cell does.

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

Categories: Research Spotlight

Tags: Saccharomyces cerevisiae, splicing, synthetic biology

Polygamous DNA Replication

June 26, 2014

Once someone is married, there are lots of things that keep them from starting a second marriage at the same time.  Laws, fear of losing the first spouse, social mores and so on all create a situation where the vast majority of people have only a single spouse at any one time. 

As each of these inhibitions is lifted, people will be more or less inclined towards polygamy, depending on who they are and the culture they live in.  For example, if having multiple spouses becomes acceptable socially, then some people might dive right in while others might hold off.

It turns out that origins of replication are similar.  There are many layers of control that keep an origin from firing more than once during any cell cycle.  But just like people and polygamy, when a few inhibitory layers are removed, some origins are more likely to fire more than once in a cell cycle than are others.

In a new study out in PLOS Genetics, Richardson and Li have identified a DNA sequence that makes nearby origins of replication fire more than once during a cell cycle when certain regulatory mechanisms have been disabled.  The authors hypothesize that these reinitiation promoters (RIPs) may be important for promoting genetic diversity by causing genomic duplication of specific regions under certain circumstances. 

This lab had previously shown that the origin ARS317 reinitiates more frequently when global regulation is removed from some key players in initiation: Cdc6p, the Mcm2-7 complex, and the origin recognition complex (ORC).  They disabled the regulation of all three of these by mutating each to prevent their recognition by the master regulator cyclin-dependent kinase (CDK, whose catalytic subunit is Cdc28p). In this study, they identified a second origin, ARS1238, that also reinitiated more often under these conditions.  The authors next set out to identify why these origins reinitiated under these conditions.

The first thing they found was that chromosomal context didn’t matter a whole lot.  Both origins reinitiated at around the same rate when they were in their natural context or when moved to other chromosomes.  The ability to reinitiate must be contained in the sequence of the DNA that was moved.

They next showed through deletion and linker scanning analysis that the two origins both required an AT-rich, ~60 base pair sequence to reinitiate.  This sequence needed to be within around 35-75 base pairs of the origin to promote reinitiation. Not any old stretch of AT-rich DNA would do; a specific DNA sequence was necessary, suggesting that this DNA is not required for reinitiation just because it is more easily unwound. 

These authors have shed light on a key process in the life of a cell—the firing of an origin of replication once and only once during any cell cycle.  It is critical for a cell that origins do not routinely reinitiate to prevent widespread genomic duplications that left unchecked would be very dangerous to the cell.

Richardson and Li have shown that not all origins are created equally, in that some are more likely to reinitiate under certain conditions than are others. If similar regions in mammalian cells turn out to be hotspots for genetic changes in cancers, then scientists may be able to target them to prevent the cancer’s genetic progression.  We may be able to reintroduce laws to keep polygamy at bay.

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

Categories: Research Spotlight

Tags: DNA replication, replication origin, Saccharomyces cerevisiae

Shared Domains and Phosphorylation Sites on Protein Pages

June 24, 2014

We have redesigned the Protein page to include a new tabular display of protein domains. This table provides the identifier for each domain and illustrates the respective locations of the domains within the protein. In addition to this new table, the domains are displayed in an interactive network diagram that presents the proteins that share these domains with your protein of interest (see figure below, left).

Another new feature on the Protein page is the display of phosphorylation sites within the protein’s sequence (as curated by BioGRID). This feature is available for both the reference strain S288C and other commonly used S. cerevisae strains, using the pull-down to select the desired strain view (see figure below, right) .

Left: Proteins (gray circles) that share domains (colored squares) with Fas1p (yellow circle). Right: an example of some of the phosphorylation sites in Swe1p (red residues).

Categories: New Data, Website changes

YGM Early Registration Deadline is Approaching!

June 23, 2014

There are only a few days left to register for the Yeast Genetics Meeting at the early registration rate. After midnight on Thursday, June 26, the fees will increase by $75. Conference housing is filling up fast too. This is a meeting you don’t want to miss, so don’t delay!

Categories: Conferences

Like People, Prions Need Intimate Contact to Spread

June 19, 2014

In the Matrix Trilogy, the delicate balance of a virtual world is upset by a rogue computer program that goes by the name of Agent Smith.  This program finds and touches other agent programs, converting them into copies of itself.  Eventually, all the agent programs are copies of Agent Smith and only the hero Neo can save humanity in an epic battle within the virtual world of the Matrix.

A new study out in GENETICS by Li and Du provides additional evidence that prions in the yeast Saccharomyces cerevisiae work similarly to Agent Smith, in that they spread through a direct contact model.  These prions are proteins that have entered a rogue conformation, and they end up converting all copies of the same protein into a similar rogue conformation.  The proteins change from a hardworking Agent Smith trying to do its job into something that mucks up the working of a cell.  And the results, at least in humans, can be as catastrophic for the cell as Agent Smith was for the Matrix. 

Mad cow disease, for example, is caused by prions converting the prion protein (PrP) in the brain cells of people from a useful conformation to a dangerous one that spreads.  As the conformation spreads throughout the cell, these prions form amyloid fibrils that eventually kill the cell.  When enough brain cells are killed, the person dies.

The authors chose to work in yeast because unlike in people, there are multiple examples of proteins in yeast that can go prion.  The list includes Sup35p, Ure2p, Rnq1p, Swi1p, Cyc8p, Mot3p, Sfp1p, Mod5p and Nup100p.  As you might guess from the sheer number of these prion-ready proteins, prions actually do more than kill a cell in yeast; they can serve useful functions. Scientists have yet to identify any useful functions for the prion form of PrP in people. 

Having multiple prions in a cell allowed Li and Du to perform some experiments to try to distinguish between two models of prion conformation spreading.  In the first, called the cross-seeding model, the prion acts very much like Agent Smith in that it needs to contact a “healthy” protein to convert it into a prion.  In the second model, the titration model, factors in the cell that prevent prion formation are titrated out when prions form.  As the factors are taken out of commission, prions are free to form.

The main evidence in this study that supports the cross-seeding model has to do with the localization of pre-existing prions during the de novo formation of a new prion.  Li and Du found that the prion [SWI+] localized to newly forming [PSI+] prions but not to already formed [PSI+] prions.  This is not the result we would expect if prion formation were due to titrating out of inhibitors of prion formation.  If that were the mechanism, then there would be no reason for [SWI+] to colocalize with newly forming [PSI+]. These experiments are like having a google map of the Matrix where we could see Smiths converting other agents by touch and then moving on and touching other agents.

Work like this is important for helping to find treatments for prion associated diseases and, perhaps, other amyloid fibril forming diseases like Huntington’s or Alzheimer’s.  Scientists need to focus on the amyloid fiber forming proteins themselves instead of trying, for example, to ramp up the activity of factors that inhibit formation.  Scientists probably need to eliminate Agent Smith to prevent the destruction of the Matrix and all of mankind.

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This is how prions turn other proteins into copies of themselves:

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

Categories: Research Spotlight, Yeast and Human Disease

Tags: prions, Saccharomyces cerevisiae

Holding Back the Translation Torrent

June 12, 2014

We all know the story of the little Dutch boy who stuck his finger into a hole in a dike to keep his village from being flooded.  Now, a new study out in Molecular Cell by Pircher and coworkers has identified a novel regulatory mechanism involving a small 18-nucleotide RNA that behaves similarly to this boy.

A big difference in our story is that unlike the broken dike, the “water flow” in yeast cells is usually a good thing.  It is the continuous stream of protein translation that goes through the ribosome. 

When it’s under stress, though, yeast needs to slow down translation in order to make sure that it is making and folding each protein correctly. This gives it a better shot at surviving the stress.  Once the stress is gone, translation can ramp up again. This is where that 18-nt RNA comes in.

This group identified this 18-nt RNA as a ribosome binding RNA in a previous study. Because there are only a couple of known cases where a noncoding RNA (ncRNA) regulates the ribosome directly, Zywicki and colleagues had wanted to see whether this happens in yeast.  They found about 20 ncRNAs that bound to the ribosome, with the most abundant being an 18-nt fragment that corresponded to part of the coding sequence of the TRM10 gene that encodes a tRNA methyltransferase.

In the current study Pircher and coworkers reconfirmed that in yeast cells about 80% of this 18-nt RNA is associated with ribosomes. To verify whether it really bound to the ribosome rather than to the mRNA being translated, they broke apart polysomes with the chelating agent EDTA. This separated the large and small ribosomal subunits from each other and from mRNA.

All of the 18-mer stayed with the large subunit, showing that it really does interact with the ribosome. The researchers also found that under normal conditions it is bound to nontranslating ribosomes, while in stressed cells it shifts to actively translating polysomes.

The mutant phenotype of the trm10 null mutant suggested that the 18-mer might have a role in adapting to stress conditions. This mutant looks normal under standard conditions, but grows slower than wild type when under osmotic stress.

Pircher and colleagues used a clever strategy to find out whether this phenotype was due to the absence of Trm10p or to the absence of the 18-mer. First, they added a stop codon into the TRM10 gene, outside the region encoding the 18-mer. This mutation blocked production of Trm10p, but didn’t affect the 18-mer. The mutant looked just like wild type under osmotic stress conditions, showing that Trm10p isn’t involved in the stress response.

Second, to see directly whether the 18-mer is important, they mutated its sequence by changing some of the codons within it to other, synonymous codons encoding the same amino acid. So the Trm10p derived from this gene was wild-type, although the 18-mer sequence was different.

A couple of mutants of this type both showed the same phenotype of slow growth under osmotic stress. So production of the 18-mer is in fact important for maintaining growth rate under stress conditions. These mutant 18-mers also failed to bind to ribosomes. 

To find out what this little RNA actually does, they used electroporation to load up each cell with about 200,000 molecules of the 18-mer. This was about the same as the number of ribosomes per cell. Translation was almost completely inhibited. When they did the same experiment with an 18-mer with a scrambled sequence, it had no effect.

Further in vitro experiments confirmed the inhibitory effect of the 18-mer on translation, and showed that the inhibited step is translation initiation. It’s not completely clear why slowing down translation promotes cell growth during stress, but the authors speculate that it leads to more accurate translation and protein folding, which improves protein homeostasis and adaptation to stress. It also remains to be determined whether the 18-mer is created by processing of the TRM10 mRNA or is transcribed independently.

This regulatory mechanism is surprising and relatively novel: there are just a couple of known cases of ncRNAs regulating the ribosome directly. But it makes sense that regulating translation in this way allows the cell to react very quickly to changing environmental conditions, without needing to synthesize any new molecules.

Small ncRNAs like microRNAs or small interfering RNAs are emerging as big players in regulation in many organisms. However, miRNAs and siRNAs are not found in S. cerevisiae. But as this study shows, this does not mean that yeast doesn’t use small RNAs for regulation.  And one of the most surprising things about this story is that such a tiny scrap of RNA can regulate the ribosome, with its 5.5 kb of rRNA and 80 proteins. The little Dutch boy’s finger is immense by comparison!

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

Categories: Research Spotlight

Tags: ncRNA, osmotic stress, Saccharomyces cerevisiae, translation

Saddling Mom with the Burden of Old Age

June 05, 2014

In A World Out of Time by Larry Niven, people live forever by teleporting the unfolded protein aggregates associated with aging out of their cells.  Turns out that our very clever yeast Saccharomyces cerevisiae can do the same thing and it doesn’t need a machine.  

Instead of teleporting the aggregates away, yeast saddles the mother cell with them when it buds.  The daughter has now regained her youth and the mother is left to struggle with old age.

In a new study in Science, Hill and coworkers show that the yeast metacaspase gene MCA1 is critical in this process.  But it doesn’t look like it is involved in segregating these bundles to the mother cell.  Instead, it appears to help clear away many of the bundles left in the daughter.   If it were in Niven’s original story, Mca1p might be a little nanobot that chewed up any aggregates the teleporter missed.  

This all makes sense given caspases’ role in multicellular beasts.  There, these executioner proteases chew up cellular proteins during apoptosis, the process of programmed cell death that is a critically important part of development and growth. 

Although apoptosis has been observed in yeast and Mca1p is involved in the process, it has always been a bit of a mystery why a single-celled organism needs a mechanism for suicide.  This study now suggests that yeast’s only caspase, Mca1p, has a role as a healer as well as an executioner. It saves the daughter by degrading and proteolytically clearing away the aggregated bundles clogging up her cell. 

Scientists already knew that HSP104 was a key player in making sure that aggregates stayed with mom.  Hill and coworkers used this fact and performed a genetic interaction screen using HSP104 to identify MCA1 as required to keep protein aggregates out of the daughter in response to a heat shock.  Follow up work confirmed this result by showing that overexpressing MCA1 led to more efficient segregation of aggregates and that deleting it led to poor segregation of aggregates.

Digging deeper, these authors found that this poor segregation was because Mca1p was not eliminating aggregates in the daughter, as opposed to affecting the segregation itself.  They also showed that the protease activity of Mca1p was needed for this effect.

In the final set of experiments we’ll discuss, the authors looked to see what effect MCA1 has on the life span of a yeast cell.  They saw little effect of deleting MCA1 unless a second gene was also deleted: YDJ1, which encodes an HSP40 co-chaperone.  The double deletion mutant yeast were able to divide fewer times before petering out.  Consistent with this, overexpressing MCA1 led to increased life span and this effect was enhanced in the absence of YDJ1.

Finally, cells lived for a shorter time if just the active site of the Mca1p protease was compromised in a ydj1 deletion background.  This again confirms that proteolysis is key to MCA1’s effects on aging. 

So yeast attains eternal youth by both dumping its age-related aggregates on its mother and by using Mca1p to destroy any aggregates that managed to get into the daughter.  The daughter gets a reset until she builds up too many aggregates, in which case she gets saddled with them.

Yeast may be showing us another way to live a longer life.  If we can specifically degrade our aggregates without causing our cells to commit mass suicide, maybe we can extend our lives.  And we don’t even need fancy teleporting machinery; we just need to adapt the molecular machinery yeast is born with.  Feel free to use this idea for a new science fiction story!

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

Categories: Research Spotlight

Tags: ageing, caspase, protein aggregates, Saccharomyces cerevisiae

Professor Jure Piskur, Ph.D. (1960 – 2014)

June 04, 2014

Dr. Jure Piskur, Professor and Carlsberg Foundation Chair in Molecular Food Microbiology at Lund University, sadly passed away on May 18, 2014. Dr. Piskur worked on yeast early in his scientific career, including postdoctoral research in yeast molecular biology at Carlsberg Brewery. From there, he studied Drosophila genes involved in the metabolism of nucleic acid precursors as well as yeast biodiversity and mitochondrial genetics. Most recently, his research focused on genes involved in the metabolism of nucleic acid precursors and “the evolution and molecular mechanisms which reshaped the modern enzymes and yeast genomes.” Dr. Piskur published many scientific papers, many of them represented in SGD. He was also a FEMS Microbiology Reviews Editor and Yeast Research Editorial Board Member. For more information on Dr. Piskur, please view his Lund University profile page.

Categories: News and Views

Create, Analyze, Save: the Power of Gene Lists in YeastMine

May 30, 2014

If you love to make and analyze lists of genes, you will love YeastMine – you can use it to create all kinds of lists! For instance, use a YeastMine template to search for all genes associated with a given GO term or phenotype observable and save these genes as a list. Or, search for all genes that interact with your gene of interest and save that as a gene list.

What’s even more fun is that you can make lists from your lists! For instance, take the list of genes you found to be associated with a given GO term and plug it into a YeastMine query template to find all the genes that interact with your list of genes – then save those genes as a list. The possibilities are endless given the different types of queries you can perform using YeastMine! Who knows what biological connections you will uncover?

Lastly, save your lists for future use by creating a MyMine account – all you need to sign up is an email and a password.

You can find a link to YeastMine in the top right corner of most SGD pages (“YeastMine: Batch Analysis or Advanced Search”) or go to SGD’s purple main menu bar, click on “Analyze” and select “Gene Lists” to go straight to creating a List in YeastMine.

To see how simple it is to save your search results as a List in YeastMine, view this brief tutorial – YeastMine: Saving Search Results as a List. To view other great SGD tutorials, YeastMine and otherwise, visit and “Subscribe” to the Saccharomyces Genome Database Channel on YouTube.

Categories: Tutorial

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