New & Noteworthy

Yeast, the Spam Filter

November 11, 2015

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Imagine what our email inboxes would look like if we didn’t have spam filters! To find the meaningful emails, we’d have to wade through hundreds of messages about winning lottery tickets, discount medications, and other things that don’t interest us.

When it comes to sorting out meaningful mutations from meaningless variation in human genes, it turns out that our friend S. cerevisiae makes a pretty good spam filter. And as more and more human genomic sequence data are becoming available every day, this is becoming more and more important.

For example, when you look at the sequence of a gene from, say, a cancer cell, you may see many differences from the wild-type gene. How can you tell which changes are significant and which are not?

SuperBud to the rescue! Because many human proteins can work in yeast, simple phenotypes like viability or growth rate can be assayed to test whether variations in human genes affect the function of their gene products. This may be one answer to the increasingly thorny problem of variants of uncertain significance—those dreaded VUS’s.

In a new paper in GENETICS, Hamza and colleagues systematically screened for human genes that can replace their yeast equivalents, and went on to test the function of tumor-specific variants in several selected genes that maintain chromosome stability in S. cerevisiae. This work extends the growing catalog of human genes that can replace yeast genes.

More importantly, it also provides compelling evidence that yeast can help us tell which mutations in a cancer cell are driver mutations, the ones that are involved in tumorigenesis, and which are the passenger mutations, those that are just the consequence of a seriously messed up cell. Talk about a useful filter!

The researchers started by testing systematically for human genes that could complement yeast mutations. Other groups have done similar large-scale screens, but this study had a couple of different twists.

Previous work from the Hieter lab had identified genes in yeast that, when mutated, made chromosomes unstable: the CIN (Chromosome INstability) phenotype. Reduction-of-function alleles of a significant fraction (29%) of essential genes confer a CIN phenotype. The human orthologs of these genes could be important in cancer, since tumor cells often show chromosome rearrangements or loss. 

So in one experiment, Hamza and colleagues focused specifically on the set of CIN genes, starting with a set of 322 pairs of yeast CIN genes and their human homologs. They tested functional complementation by transforming plasmids expressing the human cDNAs into diploid yeast strains that were heterozygous null mutant for the corresponding CIN genes. Since all of the CIN genes were essential, sporulating those diploids would generate inviable spores—unless the human gene could step in and provide the missing function.

In addition to this one-to-one test, the researchers cast a wider net by doing a pool-to-pool transformation. They mixed cultures of diploid heterozygous null mutants in 621 essential yeast genes, and transformed the pooled strains with a mixture of 1010 human cDNAs. This unbiased strategy could identify unrecognized orthologs, or demonstrate complementation between non-orthologous genes.

In combination, these two screens found 65 human cDNAs that complemented null mutations in 58 essential yeast genes. Twenty of these yeast-human gene pairs were previously undiscovered.

The investigators looked at this group of “replaceable” yeast genes as a whole to see whether they shared any characteristics. Most of their gene products localized to the cytoplasm or cytoplasmic organelles rather than to the nucleus. They also tended to have enzymatic activity rather than, for example, regulatory roles. And they had relatively few physical interactions.

So yeast could “receive messages” from human genes, allowing us to see their function in yeast. But could it filter out the meaningful messages—variations that actually affect function—from the spam? 

The authors chose three CIN genes that were functionally complemented by their human orthologs and screened 35 missense mutations that are found in those orthologs in colorectal cancer cells. Four of the human missense variants failed to support the life of the corresponding yeast null mutant, pointing to these mutations as potentially the most significant of the set.

Despite the fact that these mutations block the function of the human proteins, a mutation in one of the yeast orthologs that is analogous to one of these mutations, changing the same conserved residue, doesn’t destroy the yeast protein’s function. This underscores that whenever possible, testing mutations in the context of the entire human protein is preferable to creating disease-analogous mutations in the yeast ortholog.

Another 19 of the missense mutations allowed the yeast mutants to grow, but at a different rate from the wild-type human gene. (Eighteen conferred slower growth, but one actually made the yeast grow faster!)

For those 19 human variants that did support life for the yeast mutants, Hamza and colleagues tested the sensitivity of the complemented strains to MMS and HU, two agents that cause DNA damage. Most of the alleles altered resistance to these chemicals, making the yeast either more or less resistant than did the wild-type human gene. This is consistent with the idea that the cancer-associated mutations in these human CIN gene orthologs affect chromosome dynamics.

As researchers are inundated by a tsunami of genomic data, they may be able to turn to yeast to help discover the mutations that matter for human disease. They can help us separate those emails touting the virtues of Viagra from those not-to-be-missed kitten videos. And when we know which mutations are likely to be important for disease, we’re one step closer to finding ways to alleviate their effects. 

by Maria Costanzo, Ph.D., Senior Biocuration Scientist, SGD

Categories: Research Spotlight, Yeast and Human Disease

Tags: chromosome instability, functional complementation, Saccharomyces cerevisiae, yeast model for human disease

Life Needs to be More Like a 1950’s Chevy

October 21, 2015

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In the old days, a car came with the bare minimum of features to get from point A to point B. The windows rolled down with a crank and it usually had a radio. That was about it.

As the car has evolved, it has gained a huge number of bells and whistles. There are power windows and power brakes, a baffling number of computer-based bonus features, personal wifi hotspots, and so on. All of these have undoubtedly made cars more fun and comfortable to drive. But they have come at a cost. Many cars simply do not last as long as their predecessors because these extras break easily.

Turns out life may be like a modern car. It has lots of nice features that help it to do better in the world. But a lot of these features may shorten its life span.

This point was reinforced in a recent study by McCormick and coworkers. They painstakingly searched through a library of 4,698 single gene deletion strains in S. cerevisiae and found that 238 of these strains were able to produce significantly more buds over their lifetime. Many nonessential genes seem to shorten a yeast’s life.

And boy was it painstaking! Believe it or not, they manually dissected over 2.2 million individual yeast daughter cells to generate these results. Luckily it was worth it, as they found so many interesting things.

First off, many of the genes they found fall into a set of five pathways that includes cytosolic and mitochondrial translation, the SAGA complex, protein mannosylation, the TCA cycle, and proteasomal activity. So there are certain pathways we can target to extend the lifespan of our friend yeast. And even better, yeast may not be the only beneficiary of these studies.

Two of the pathways, cytosolic and mitochondrial translation and the TCA cycle, have also been found to be significant in extending the life of the roundworm C. elegans. These pathways are also shared with humans.

And just because the authors found no overlap with the other three pathways in other beasts doesn’t mean they may not be targets for life extension in them too. It could be that previous screens in C. elegans simply missed genes from these pathways.

It could also be that what is found in yeast may turn out to be important in people but not in C. elegans. For example, the authors failed to find any equivalent to the SAGA complex in C. elegans. Either the roundworm lost this complex during evolution, or the homologs between yeast and C. elegans are so different that they’re unrecognizable. In any event, humans at least do have an equivalent to SAGA, called STAGA.

All of this suggests that there may be common ways to make organisms, including people, live longer, healthier lives. Here’s hoping!

And these five pathways are certainly not the whole story. The majority of the genes McCormick and coworkers identified were not in these five, which means there are probably lots of other ways to get at living longer.

One fascinating example that the authors decided to look at in depth was LOS1. Deleting it had one of the biggest effects on a yeast’s reproductive life span.

At first this seems a little weird, as Los1p exports tRNAs out of the nucleus. As expected, deleting LOS1 led to a buildup in tRNAs in the nucleus. The authors confirmed that this buildup is important by showing that overexpressing MTR10, a gene involved in transporting tRNAs from the cytoplasm to the nucleus, led to a longer lived yeast with a buildup of tRNAs in its nucleus.

The next step was to figure out why having a lot of tRNA in the nucleus makes yeast live longer. It was known previously that Los1p is kept out of the nucleus under glucose starvation conditions. The authors confirmed this result.

Most everyone knows that restricting calorie intake (also called dietary restriction or DR) can extend the lives of most every beast tested so far, including yeast. The authors found that growing a los1 deletion strain at low glucose did not increase the lifespan of this strain any further. It thus appears that an important consequence of DR is keeping Los1p out of the nucleus and thereby increasing the amount of tRNA in the nucleus.

While we don’t know yet exactly why keeping tRNAs in the nucleus helps yeast live longer, it is interesting that the increased lifespan associated with the loss of LOS1 is linked to caloric restriction. Finding a way to inhibit Los1p has to be better than starving yourself!

This study has identified 238 genes to follow up on for future studies. And of course there is a whole class of genes that haven’t yet been investigated—the essential genes! Many of these may be important for extending life too. 

Stripping life down to its bare essentials may help individuals live longer at the expense of being the most fit in terms of survival in the hurly burly world of nature. After all, those “nonessential” genes undoubtedly have a function in helping yeast outcompete their less well-endowed yeast neighbors. Just like those power sliding doors are way better than the manual ones on a minivan.

But if you want a long-lived minivan, get the one with the manual doors. And if you want a long-lived yeast (or person), get rid of some of those nonessential genes that cause you to break down.

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

Categories: Research Spotlight

Tags: aging, lifespan, Saccharomyces cerevisiae

You Can Take Yeast Off of the Grapevine, But…

October 14, 2015

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All over the world and through the ages, people have moved from the country into the big city to look for a better life. These folks often find that even though they can adapt to city life and city ways, they still hang on to their core country values. As the old saying goes, “You can take the boy out of the country, but you can’t take the country out of the boy.”

Our friend Saccharomyces cerevisiae didn’t migrate voluntarily into the lab. But it ended up there, and has been as lonely as a new migrant in a big city. 

Which is of course how we need it to be. One of the basic tenets of classical microbiology is that you can’t begin to study an organism until you’ve isolated it in a pure culture.

And studying pure S. cerevisiae has yielded a huge body of knowledge about molecular biology, cell biology, and genetics. But by not studying yeast in the context of its old country home, we may have missed a few things.

In a new article in PLOS ONE, Rossouw and colleagues uncover one of them. S. cerevisiae has a family of FLO genes that promote flocculation, the adherence of yeast cells to each other. It has always been a bit puzzling why a whole family of genes that are pretty much redundant with each other would be maintained through evolution.

When the researchers took S. cerevisiae out of its lab isolation by mixing it with other yeast species, they found that the different flocculation genes actually determine which species it can co-flocculate with. Different Flo proteins prefer different partners. 

This discovery helps us understand the evolution of this gene family and also opens the door to further study of inter-species interactions in the vineyard. And since flocculation is an important property in winemaking and brewing, there could even be tasty practical applications of this knowledge.

The researchers started by surveying 18 non-Saccharomyces yeast strains that are found in vineyards. They looked at the ability of the yeasts to flocculate both as pure strains and when mixed with either of two S. cerevisiae wine strains.

Intriguingly, certain species showed a synergistic effect when mixed with S. cerevisiae, flocculating more than either species on its own. Rossouw and colleagues used microscopy to confirm that the “flocs” did indeed contain both yeast species—a simple observation, since the cells of different species have slightly different shapes.

To test the effects of different FLO genes on co-flocculation, the authors assayed the co-flocculation ability of flo1, flo10, and flo11 deletion mutants as well as Flo1, Flo5, and Flo11 overproducers in individual combinations with six of the non-Saccharomyces yeasts. 

The results showed that Flo1 has general effects on flocculation. Overproduction increased co-flocculation across the board with all the species tested, while deletion of FLO1 consistently decreased it. In contrast, deletion of FLO10 didn’t have much effect on co-flocculation.

It was a different story for Flo5 and Flo11, though. Overproduction of each of these not only affected co-flocculation, but had species-specific or even strain-specific effects. Flo5 overproduction caused a relative increase in co-flocculation with Metchnikowia fructicola and a substantial decrease in co-flocculation with two different strains of Hanseniaspora opuntiae. Flo11 overproduction reduced co-flocculation with one of the Hanseniaspora opuntiae strains but not with the other. 

All of these experiments were done on mixtures of two species at a time. To get S. cerevisiae even further out of the lab, Rossouw and colleagues created a “consortium” of wine yeasts, a mixture of six species that are found in wine must (freshly pressed grapes) at the start of fermentation. They then added the FLO overproducer strains individually to the consortium, to see their effects in a more natural situation.

They let the yeast consortium flocculate, extracted total DNA from the flocculated or supernatant parts of the culture, and then used automated ribosomal intergenic spacer analysis (ARISA) to see which strains had co-flocculated. This technique can determine the relative abundance of different yeast species in a sample by sequencing a particular region of ribosomal DNA.

In this experiment, overexpression of each of the three FLO genes had significant effects on at least one of the species in the consortium. The species composition of the flocculated yeasts was uniquely different, depending on which gene was overexpressed.

The discovery that the flocculation genes have individual effects on association with other species goes a long way towards explaining why S. cerevisiae has maintained this gene family with so many members that apparently have the same function—at least, when you study a pure culture. Differential regulation of the FLO genes could affect the spectrum of other species that our favorite yeast interacts with. 

So, our friend S. cerevisiae didn’t actually get out of the lab in these experiments, but at least it got to rub shoulders with some of its old friends (buds?) from the vineyard. These experiments are a good reminder for researchers to think outside the lab.

And when S. cerevisiae and its friends get together outside the lab, beautiful things can happen. We’ll drink a toast to that!

by Maria Costanzo, Ph.D., Senior Biocuration Scientist, SGD

If yeast could sing about its forced migration to the lab, it might sound like this.

Categories: Research Spotlight

Tags: flocculation, Saccharomyces cerevisiae, vineyard

Unleashing the Awesome Power of Yeast Transcription

October 07, 2015

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In the old days, before the internet, planes or even mass publishing, it was hard to spark a quick, worldwide movement. You simply couldn’t reach out to likeminded people who lived far away.

Nowadays things are very different. With the advent of social media, it is now trivially easy to spread the word. Using Twitter and Facebook, organizers can easily and effectively organize people who live on the other side of the world.

In terms of transcription activation, our friend Saccharomyces cerevisiae seems to be stuck in the old world. Its transcription factors can only turn up nearby genes. This is different from most other eukaryotic beasts, where activation at a distance is routine.

Except maybe yeast isn’t as backward as we think. It may be that yeast has the potential to activate transcription at a distance, but keeps that potential locked away.

This idea is supported in a new study out in GENETICS by Reavey and coworkers. These authors found that they could mutate away yeast’s inability to activate transcription at a distance.

Categories: Research Spotlight

Tags: polygenic trait, Saccharomyces cerevisiae, transcription

The Latest Buzz on Stressed-Out Mitochondria

September 30, 2015

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Stinging wasps get our attention, and with good reason—getting stung hurts a lot! If you see wasps going into a nest within the walls of your house, you’ll likely try to block their access.

But this could backfire: instead of being able to peacefully go into their nest, a swarm of angry wasps could be buzzing around looking for trouble. It might get so bad that you’ll need to call in an exterminator to take care of the problem.

Mitochondrial proteins might seem a lot less scary than wasps, but it turns out that they can also cause trouble if they can’t get into mitochondria. In two new letters to Nature, Wrobel and colleagues and Wang and Chen used complementary approaches to ask what happens when dysfunctional mitochondria aren’t able to import all of the proteins that are waiting to get in. 

What they both found was that these piled up proteins cause real problems for the cells. In desperation, the cells slow down protein synthesis to reduce the excess, and also turn to their own exterminator, the proteasome, to keep these proteins under control.

This is a paradigm shift in thinking about how poorly functioning mitochondria cause disease. In the past, almost everyone focused on how damaged mitochondria couldn’t make enough energy for a cell. Now it looks like there are other ways for a nonworking mitochondria to do a cell in. And new targets for scientists to go after in treating mitochondrial disease.

As we all know, mitochondria are the powerhouses of the cell, where energy is generated, and they’re also the site of many other essential biochemical reactions. They’re composed of about 1,000 proteins, and nearly all of those are synthesized in the cytoplasm and then imported into mitochondria by an intricate system of transporters.

In order to find out what happens when these 1,000 proteins don’t get into mitochondria as efficiently as they should, both groups created strains whose mitochondrial import was impaired.

Wrobel and colleagues used the temperature-sensitive mia40-4int mutation, affecting an essential component of the mitochondrial import system. Wang and Chen started with the aac2-A128P mutation in PET9 (which is also known as AAC2), an ADP/ATP carrier of the mitochondrial inner membrane. Overexpression of the aac2-A128P allele causes mitochondrial dysfunction and eventual cell death.

Wrobel and colleagues decided to get a comprehensive look at what happens in the mia40-4int mutant by assaying its transcriptome and proteome, using RNA-seq and stable isotope labelling by amino acids in cell culture (SILAC), respectively. Surprisingly, one of the biggest differences from wild type that they saw in the import-defective mutant was a decrease in cytoplasmic translation. Whether they looked at the mRNAs encoding ribosomal proteins, the proteins themselves, or the polysome content and translational activity of the cells, everything pointed to down-regulation of translation. And at the same time, the proteasome—the molecular machine that breaks down unwanted proteins—was activated.

To verify that what they were seeing wasn’t peculiar to the mia40-4int mutant, Wrobel and colleagues slowed down mitochondrial import in several other ways: using different mia40 mutant alleles, other import mutants, or treatment with a chemical that destroys the mitochondrial membrane potential required for import. Under these different conditions causing the accumulation of mitochondrial precursor proteins in the cytoplasm, they still saw decreased cytoplasmic translation and increased proteasome activity.

Wang and Chen took a different approach, looking to see whether over-expression of any other genes could compensate for the lethality of overexpressing the aac2-A128P allele. The researchers transformed the mutant with a library of yeast genes on a multicopy plasmid, and found 40 genes whose expression could keep it alive.

The suppressor genes found by Wang and Chen were all involved in some aspect of synthesis or degradation of cytoplasmic proteins, just like the genes found by Wrobel and colleagues whose expression was altered in the mia40 mutant. And Wang and Chen also verified that these suppressors weren’t specific to the aac2-A128P mutation: they suppressed a variety of other mutations that decreased import.

Both groups observed precursors of mitochondrial proteins accumulating in the cytosol of the mutant strains they studied. Wang and Chen saw a couple other very interesting proteins increase in abundance: Gis2 and Nog2. These proteins are involved in regulating ribosome function, and the researchers speculate that their stabilization during this stress response contributes to the translational down-regulation. Intriguingly, their human orthologs are implicated in neuromuscular degenerative disease.

So, using orthogonal approaches, the two groups converged on the same model: a newly discovered cellular pathway that regulates cytosolic translation and protein degradation in order to deal with the stress of inefficient mitochondrial import. Wrobel and colleagues have named it UPRam, for Unfolded Protein Response activated by mistargeting of proteins, while Wang and Chen call it mPOS, mitochondrial Precursor Over-accumulation Stress.

Before this work, it was unknown whether cytosolic pathways were even affected by mitochondrial dysfunction. Now we know that the cell has a specific response when mitochondrial precursor proteins begin swarming in the cytosol, unable to get into their home: it slows down the production of those proteins and calls in the proteasome exterminator to take care of them.

We usually think of mitochondrial disease symptoms as being caused by the reduced energy generation of sick mitochondria, or by the lack of other key events that happen in mitochondria—for example, the synthesis of the iron-sulfur clusters that some vitally important enzymes need. Now, these findings raise the possibility that proteostatic stress on the cell caused by the accumulation of mitochondrial precursors could also lead to impaired cell function and disease.

Perhaps drugs that inhibited cytoplasmic translation, or activated the proteasome exterminator, would be helpful in reducing the buzzing swarm of mitochondrial precursor proteins. Wouldn’t it be wonderful if this knowledge suggested new avenues of treatment to take some of the sting out of human mitochondrial disease?

by Maria Costanzo, Ph.D., Senior Biocuration Scientist, SGD

Categories: Research Spotlight

Tags: mitochondria, proteasome, proteostatic stress, Saccharomyces cerevisiae

A Scientist Sees Transcription

September 23, 2015

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In the classic Dr. Seuss tale Horton Hears a Who, the elephant Horton thinks he hears voices coming from a speck of dust. He gets into all sorts of trouble over this until all the Whos in Whoville prove they are alive when they all shout at once. Now Horton’s jungle compatriots believe him and Horton can hang out with his new friends.

Horton’s companions never get to hear an individual Who. They are not blessed with Horton’s big elephant ears and so have to just hear all the Whos shouting at once.

Up until recently, we have been in the same situation as the kangaroo and everyone else in the jungle when it comes to transcription in a cell. We can use all sorts of tools to get at what goes on when RNA polymerase II (pol II) gets ready and then starts to transcribe a gene, but we can only get an aggregate picture of lots of cells where it is happening. We can’t hear the Mayor of Whoville amidst all of the other Who voices.

In a new study out in Nature, Fazal and coworkers use the equivalent of elephant ears, optical tweezers, to study the initiation of transcription by purified pol II machinery from Saccharomyces cerevisiae on single molecules. And what they find is that at least for one part of the process, our having looked at things in the aggregate may have fooled us about how the process worked. It was important that we be able to pick out individual voices from the cacophony of the crowd.

Not surprisingly, transcribing a gene is tricky work. It is often split into three steps: initiation, elongation, and termination. And each of these can be subdivided further.

Fazal and coworkers focused on transcription initiation. Previous work had suggested that the process goes something like this:

Top image via Wikimedia Commons

Basically, an alphabet soup of general transcription factors and pol II sit down on a promoter. This complex then pries open the DNA and looks for a signal in the DNA to start transcribing. The polymerase then transcribes short transcripts until it shifts into high gear when it escapes the promoter and enters elongation phase.

This theory comes from the study of transcription in bulk. In other words, it derives from looking at many cells all at once or many promoter fragments in a test tube.

Fazal and coworkers set out to look at how well this all holds up when looking at single genes, one at a time. To do this they used a powerful technique called optical tweezers.

Optical tweezers can “see” what is going on with moving enzymes by measuring the change in force that happens when they move. For this study, the preinitiation complex bound to a longish (2.7 kb) piece of DNA was attached to one bead via pol II, the moving enzyme. The other end of the DNA was attached to a second bead. Each bead is then immobilized using lasers (how cool is that!) and the DNA is stretched between the two beads. Watch this video if you want more details on the technique.

Depending on where you attach the DNA to the bead, you can either track polymerase movement or changes in DNA by precisely measuring changes in the forces keeping the beads in place. Using this technique the researchers found that the bulk studies had done pretty well for most every step. Except for the initial transcribing complex.

The earlier studies had suggested that an open complex of around 15 nucleotides was maintained until elongation began. This study showed that in addition to the 15 base pairs, an additional 32 to 140 base pairs (mean of about 70 base pairs) was also opened before productive elongation could begin. And that this whole region was transcribed.

This result paints a very different picture of transcription initiation. Rather than maintaining a constant amount of open DNA, it looks like the DNA opens more and more until the open DNA collapses back down to the 12-14 base pair transcription bubble seen during elongation.

It turns out that this is consistent with some previous work done in both yeast and fruit flies. Using KMnO₄, a probe for single stranded DNA, scientists had seen extended regions of open DNA around transcription start sites but had interpreted it as a collection of smaller, opened DNA. In other words, they thought they were seeing different polymerases at different positions along the DNA.

These new results suggest that they may have actually been seeing initial transcribing complexes poised to start processive elongation. Seeing just one complex at a time changed how we interpreted these results.

Fazal and coworkers were also able to see what happened to some of the 98% of preinitiation complexes that failed to get started. Around 20% of them did end up with an extensive region of open DNA of around 94 +/- 36 base pairs but these complexes were independent of transcription, as they didn’t require NTPs.

But since this opening did require dATP, they propose that it was due to the general transcription factor TFIIH, a helicase. It looks like in these failed complexes, TFIIH is opening the DNA without the polymerase being present.

A clearer picture of what might be going on at the promoter of genes starts to emerge from these studies. Once around 15 base pairs of DNA are pried open to form the appropriately named open complex, TFIIH unwinds an additional 70 or so base pairs. The polymerase comes along, transcribing this entire region. The whole 85 or so base pairs stays open during this process.

Eventually the polymerase breaks free and the opened DNA collapses back down to around 12-14 base pairs. Now the polymerase can merrily elongate to its heart’s content. Until of course something happens and it stops…but that is another story. 

Categories: Research Spotlight

Tags: optical tweezers, RNA polymerase II, Saccharomyces cerevisiae, transcription

Yeast Researchers Turn up the Heat on Essential Genes

September 09, 2015

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Looking at the phenotypes—the observable characteristics—of creatures that have mutations in various genes can give important clues to scientists trying to figure out what those genes do. And the ability to systematically mutate thousands of genes in our favorite organism, Saccharomyces cerevisiae, has made it an awesomely powerful genetic system.

But this awesome system has something of an Achilles heel. If you delete an essential gene, defined as a gene necessary for life under standard growth conditions, you end up with an experimental dead end: a dead cell. How then can you study mutant phenotypes for essential genes, which are nearly 20% of the genome?

In a new paper in G3, Kofoed and colleagues address this problem by creating conditional mutations in 600 essential genes. The mutant genes function normally at standard temperatures (25-30° C) but can be inactivated by raising the temperature. This mutant collection covers about half of S. cerevisiae essential genes and gets us much closer to being able to do mutant screens that are truly genome-wide, helping us to discover unexpected connections between genes and pathways or processes.

One popular approach to studying essential genes has been to put them under control of promoters that can be turned down when you add a particular chemical or carbon source. But it can be hard to tease apart the phenotype of down-regulating transcription of your gene of interest from the effects of the other changes that you need to make in order to regulate expression of the construct.

A solution that avoids some of these issues is to use temperature-sensitive (ts) alleles of essential genes. These mutations make the resulting proteins unstable at high temperatures. If you shift a ts strain to high temperature, the mutant protein will stop functioning; by growing the cells at an intermediate temperature, you can often produce a partially active protein that allows slow growth of the strain.

Temperature-sensitive alleles are not nearly as straightforward to create as are deletion mutations. Although newer technologies are helping, it’s still a lot of work. But Kofoed and colleagues took on this challenge. Building on their previous collection of 250 genes, they targeted genes without existing ts alleles to create a mutant collection including a total of 600 genes, about half of yeast’s essential genes.

The researchers used error-prone PCR to introduce mutations into DNA fragments encoding the genes, then transformed the mutagenized fragments into heterozygous diploid cells containing one wild-type copy of the gene and one deletion allele. The flanking sequences of the mutagenized genes targeted them to integrate in place of the deletion allele. Kofoed and colleagues could then sporulate the diploids and screen the haploid progeny for temperature sensitivity.

The genetic background of these strains is S288C, the widely used strain from which the reference genome sequence is derived. Each strain contains a “barcode”, a sequence that can be used to uniquely identify it. In addition to creating new alleles, the authors also used these methods to transfer some previously isolated ts alleles into this same background. 

Kofoed and colleagues validated and stored multiple ts alleles for each gene on their list. Although they chose one allele per gene for inclusion in the collection, the other alleles are available on request and could be very informative for researchers studying those particular genes.

As a test to see whether their collection of 600 genes was biased in any way, the researchers did Gene Ontology (GO) enrichment analysis. This compares the GO terms, representing molecular function, biological process, and subcellular localization, that are associated with the genes in a set. If the genes share related GO terms, that’s an indication that they may be involved in a common process or share the same location.

Most of the time, when scientists do GO enrichment on sets of genes they’ve come up with in an experiment, they’re hoping the genes have significantly shared terms. But in this case, the researchers were happy to find no shared terms, meaning that their collection represented a wide variety of places and roles in the cell.

The mutant strains may be studied individually in classical genetics experiments or the whole set can be tested using robotic manipulation of all the strains at once. Alternatively, the strains can be pooled and grown together in a competitive situation, like a microscopic Survivor show. When the strains are forced to compete for survival, some will prosper and others will die out. Their unique barcode identifiers allow researchers to figure out which strains were the survivors and which got voted out of the chemostat.

So this collection represents an important step in our ability to survey the phenotypes of virtually all genes in the genome. In addition to creating this resource, Kofoed and colleagues provide a summary (in Table S6) of all currently available mutant collections for essential genes. The yeast research community is now poised to turn up the heat on genome-wide mutant screens and make new discoveries about the roles of these essentially important genes.

by Maria Costanzo, Ph.D., Senior Biocuration Scientist, SGD

Categories: Research Spotlight

Tags: community resource, mutant collection, Saccharomyces cerevisiae

Many Modules Make Light(er) Work

August 26, 2015

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If you’ve ever put together something from IKEA you know it can be a bear. So many parts need to connect up together perfectly to build that new bookcase—if you tried to do it all at once you’d go crazy.

Luckily the good folks at IKEA try to make it a bit easier (and more tolerable) by splitting the task into smaller, more manageable pieces. You can concentrate on one part without having to worry about the rest. Once that part is done you can work on the next part and so on. In the end you assemble all the pieces together into your new bookcase.

This is the approach Galanie and coworkers took in their recent Science paper where they engineered our favorite yeast S. cerevisiae to make a couple of different opioids. And it is a good thing they broke this problem up, because it was a way bigger undertaking than anything IKEA might have thrown at them. Engineering this yeast strain was a genetic tour de force.

The authors coordinated 21 different genes from mammals, plants, bacteria and yeast to get the opiate precursor thebaine made. And the semisynthetic opiate hydrocodone took an extra two genes for a grand total of 23! Trying to do all of these at once might have been very frustrating. Thank goodness they split this Herculean task into six (or seven for hydrocodone) smaller modules.

The first step was to get yeast to make (S)-reticuline, a key intermediate on the way to useful opiates. This took 4 modules made up of 17 different genes: six from rat, six from plants, four from yeast and one from bacteria.

And of course just putting these into yeast all at once would almost certainly have made a whole lot of nothing. Each gene needed to be selected from the right beast and then optimized to work in the yeast strain. Sometimes this meant picking the right variant from the right plant, and sometimes it meant mutating a gene to make it behave better. This all would have been overwhelming if the task weren’t split into four easier sections.

Even with all of their optimization, this iteration only made about 20 μg/liter of (S)-reticuline. They needed yeast to crank out more of this intermediate, so they designed a fifth module.

As its name implies, this “bottleneck” module was designed to overcome bottlenecks in the first four modules. After it was added to the strain, the yeast managed to make 82 μg/liter. This was something they could work with!

Except now they were stuck. They needed (R)-reticuline instead of the S form, but no one knew how poppies managed this feat. The gene that did this job hadn’t yet been discovered.

So Galanie and coworkers rolled up their sleeves and dug through plant transcriptome databases to find the gene they were looking for. They found a likely candidate, synthesized the gene in order to produce the enzyme, tested whether it could transform the S form of reticuline into the R form in vitro, and found that it could.

They could now make the right intermediate, which meant they could make their final module. As its name implies, this “thebaine” module would finally allow them to make the opiate precursor thebaine in yeast. This module consisted of their recently discovered gene and three other plant genes.

They had finally made thebaine from simple sugars in yeast! Except it didn’t work very well at all. There seemed to be a bottleneck right after the (R)-reticuline stage. Back to the drawing board!

Given where the bottleneck was, the researchers guessed correctly that the culprit was the SalSyn enzyme which converted (R)-reticuline to salutaradine. A Western blot showed three distinct forms of this enzyme in yeast and only one form, the lowest molecular weight one, when it was expressed in tobacco. Clearly something was happening to inactivate this protein in yeast.

A close look at the protein suggested yeast was glycosylating positions that it shouldn’t, and site directed mutagenesis of these sites confirmed this. The glycosylation was causing the protein to be sorted incorrectly so that it couldn’t do its job.

Unfortunately just mutagenizing away the glycosylation sites wasn’t good enough, because this severely affected the enzyme’s ability to do its job. So the researchers created a chimeric protein with parts of another P450 enzyme they knew did great work in yeast. After optimizing its codons for yeast, this chimera performed beautifully.

Now, finally, they had a yeast strain that could make thebaine. Not a lot of it, only around 6.4 μg/liter—but amazing nonetheless.

A final module was added that consisted of two plant enzymes that converted thebaine to the drug hydrocodone. This monster strain could crank out around 0.3 μg/liter of hydrocodone. Yes, that is as puny as it sounds; one dose of painkiller for an adult would contain 5 mg of hydrocodone.

To be competitive with poppies, they need a 100,000-fold improvement to around 5 mg/liter. In talking with Dr. Smolke, it sounds like this could happen within a couple of years. After scaling up for production, voila! An entirely new source of opiates for pain relief.

Of course the elephant in the room is a Breaking Bad-esque scene where a yeast biologist grabs ahold of an opiate-producing strain and supplies various cartels with illegal drugs. Our Walter White wannabe wouldn’t be able to use the current strain, as he would need thousands of liters of yeast to produce a single dose of Vicodin.

But this scenario will be a real concern in the next few years. Which is why the Smolke lab has crossed every t and dotted every i in setting up and creating this strain. They have made it as difficult as possible for the wrong people to get their hands on it.  

This strain represents a stunning achievement in synthetic biology. Move over poppies, there’s a new opiate producer in town.

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

Categories: Research Spotlight

Tags: opiate biosynthesis, pathway engineering, Saccharomyces cerevisiae, synthetic biology

Ancient Hybridization Causes Revision of Yeast’s Calendar

August 19, 2015

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Most people assume that Jesus Christ was born around 1 A.D. or 1 B.C. or something like that. After all, that dating system is based on when he was born. 1 A.D. is by definition “the first year of the Lord.”

Now of course no one was actually marking years this way from the get go. In fact, this dating system wasn’t really invented until 525 A.D. by the monk Dionysius Exiguus.

And as can sometimes happen when you look that far back in time, he didn’t quite get the date of Jesus’ birth right. In point of fact, Jesus was most likely born between 4 and 6 B.C.

While not nearly as momentous, yeast biologists may have done something similar with the genome of our friend Saccharomyces cerevisiae. For many years scientists have believed that this yeast underwent a whole genome duplication (WGD) event around 100 million years ago. 

But if the conclusions reached by Marcet-Houben and Gabaldón in a new PLOS Biology article are correct, then what looks like the WGD event actually happened before there was a S. cerevisiae around to duplicate its genome.

Which would mean that there couldn’t have been a WGD. There is no way for a species to double its genome if it doesn’t yet exist! Instead the authors propose that what looks like a WGD was actually a hybridization of two related yeasts from longer ago than 100 million years.

Once you get past the vocabulary, the idea behind this study is actually pretty easy. Basically, they took pairs of genes that most likely came from a duplication event (ohnologs) and figured out when they diverged away from one another. This is the same idea behind figuring out when chimps and humans shared a common ancestor by comparing homologous genes.

When Marcet-Houben and Gabaldón compared every potential ohnolog in S. cerevisiae, they found that a WGD event could explain the origin of only 15% of these genes. These 15% could be traced back to a time after S. cerevisiae was already around.

The other 85% all looked to have been duplicated before S. cerevisiae yet existed. Which of course means these could not have come from a WGD. A genome that does not yet exist cannot be duplicated. This set of genes must have arisen in a different way.

An origin story that makes more sense than a WGD for these genes is one in which two related species hybridize to form one new species. This kind of thing definitely happens, especially with yeast (and if you like lagers, you can be glad it does!).

Here the idea is that the related species share a subset of their genes from when they had a common ancestor. When these species fuse, the new beast has both sets of genes. A cursory look might suggest that these genes were from a duplication event, especially if there are many large tracts of them. After all, many genes share a lot of homology between species.

It is only with a closer look that you might trace these genes back to a common ancestor that came before the species you are studying even existed. This is, in essence, what Marcet-Houben and Gabaldón found.

From the phylogeny of reference species that they created, the authors were able to get a general idea about which clades these prehybridization species may have come from. The largest peak of duplication from their analysis came from before Saccharomyces split from a clade containing Kluyveromyces, Lachancea, and Eremothecium (KLE). The other major peak came before Saccharomyces separated from a clade that contains Zygosaccharomyces rouxii and Torulaspora delbrueckii (ZT). So the simplest interpretation is that at some point long ago, an ancestor of modern S. cerevisiae was formed from the hybridization of a pre-KLE and a pre-ZT species.

Showing that something like this happened so long ago is fraught with peril. All sorts of things can happen to a genome in more than a hundred million years. And duplicated genes are even trickier because they can mutate at different rates when one copy is gaining a new function. (After all, that is one way that new genes are born.)

So Marcet-Houben and Gabaldón threw everything but the kitchen sink at the genome sequences. They tried at least three different methods for comparing the various sequences, using alternative reference phylogenies and a variety of techniques to show what might happen to their results if genes were mutating at different rates.

With each method they got similar results. Many or even most of the “duplication” events happened before S. cerevisiae was even a species. And on top of all of this they were able to show that they got a similar result when they used a known hybrid, S. pastorianus, and its two founding species, S. cerevisiae and S. eubayanus.

All of this taken together argues that S. cerevisiae did not undergo a WGD in the deep, dark past. Instead, it is the result of two closely related species getting together and creating a new species.

Now this does not necessarily mean there was no WGD in our favorite yeast’s past. There are at least two ways that a hybrid species might have formed, and as you can see in this image from Marcet-Houben and Gabaldón’s article, one of them involves a duplicated genome:

In the first scenario, shown on the top left, two diploids of different species fuse together to create a yeast with two sets of chromosomes. Eventually, through mutation, translocation, gene loss and whatever other genome sculpting mechanisms are handy, the yeast ends up with double the number of chromosomes of its predecessors.

In the second possibility, shown on the bottom left, two haploids fuse. This fused yeast then undergoes a whole genome duplication and then goes through similar processes as the first model to get to the current genome.

So, although there may have been a WGD, it looks unlikely that it happened to S. cerevisiae. Just as the placement of historic events in our calendar changes when more information is available, the generation of genome sequences for more and more yeast species and new methods for analyzing them are giving us deeper insight into the history of our friend S. cerevisiae.

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

Categories: Research Spotlight

Tags: evolution, hybridization, Saccharomyces cerevisiae, whole-genome duplication

Redesigning Life, Ethically

August 13, 2015

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For thousands of years, humans have used yeast as an essential part of recipes for bread, wine, and beer. But now we’re turning the tables on yeast. Instead of creating recipes with yeast, researchers are creating recipes for yeast.

Now of course we have been making minor tweaks here and there for years. But what we’re talking about now is changing out the whole recipe book: creating a whole new genome for S. cerevisiae.

The Synthetic Yeast 2.0 Project (Sc2.0) has the ambitious goal of re-designing and synthesizing the entire yeast genome, some 12 million base pairs. Along with the scientific challenges, the researchers face some tricky ethical issues as well. After all, they’re creating the blueprint for an entire living eukaryotic cell!

Fortunately, the Sc2.0 researchers have thought long and hard about these issues. They’ve issued a statement of ethics and governance in a new article in GENETICS that also reviews the current regulatory and ethical landscape for synthetic biology. The statement by Sliva and colleagues sets the course for Sc2.0 and serves as a model for oversight of other synthetic biology projects.

We wrote about the science in this space before, when the project published its first major milestone, the synthesis of chromosome III. It’s fascinating stuff: the scientists are not only re-synthesizing the genome, but are re-designing it to be leaner and more useful in the lab. They’re adding features like loxP sites that can be used to alter the structure of the genome for evolution experiments, and engineering the tRNA genes so that one codon can be repurposed to code for a novel amino acid.

But even though these are seemingly benign changes to a relatively harmless beast, there are ethical issues inherent in modifying a living organism in such a big way. While the authors focus on Sc2.0, the issues they discuss are relevant to other synthetic biology projects that combine genes from several organisms in novel pathways, such as the efforts to create an opiate biosynthetic pathway in yeast. 

While we can only touch on the highlights of their statement here, one of the principles most strongly emphasized by Sliva and colleagues is that all Sc2.0 work will be done for peaceful purposes that benefit society. To promote transparency, they are making outreach a priority, engaging with and educating the public about the project. Sc2.0 will be a public resource, with no intellectual property rights or restrictions on data or materials.

The researchers are also committed to safety. They have engineered multiple auxotrophies into all working strains so that they need special media to survive, even though it seems unlikely that an Sc2.0 strain on the loose would be harmful or would have a competitive advantage over wild strains. And although it’s not required for working with organisms like yeast that are classified “Generally Regarded as Safe” by the FDA, all participants in the project receive biosafety training.

Currently, there is relatively little official policy in place for the field of synthetic biology. Two safety measures currently recommended for DNA synthesis companies by the U.S. Department of Health and Human Services are that the companies check that the sequences they synthesize don’t correspond to toxins or harmful organisms, and that they also verify the identities and institutions of their customers. While compliance with these guidelines is voluntary, the Sc2.0 project has decided to support only companies that follow these safety measures.

To ensure that the policies outlined in their Statement of Ethics and Governance are followed, the Sc2.0 project will maintain an Executive Committee comprised of people both internal and external to the project who have broad expertise in policy, ethics, and science. All of the participants in the project are accountable to this committee, which will actively monitor the work to ensure that the guidelines are followed.

It’s obvious that this is no half-baked scheme, but rather an impressively well-planned recipe for cooking up a yeast cell from scratch. But, we expect nothing less from our friend S. cerevisiae and the talented researchers in the yeast community than to be at the forefront of modern science! 

by Maria Costanzo, Ph.D., Senior Biocuration Scientist, SGD

Categories: Research Spotlight

Tags: Saccharomyces cerevisiae, synthetic biology

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