A lab engineered strain of yeast may make low alcohol, great tasting beer a reality.

Let’s face it: low alcohol beer just doesn’t taste that great.  This is because the alcohol is either diluted or removed chemically after fermentation.  Both methods wreak havoc with a beer’s flavor.

Dr. John Morrissey of University College Cork is trying to change this.  His lab is working to generate a strain of yeast that turns some but not all of its sugar into alcohol.  That way the beer process is the same, just with less alcohol at the end.

This is different from stopping fermentation early.  In that case there are still sugars in the final product which ruin a beer’s taste even more than removing the alcohol!  Here the same amount of sugars are used up, it is just that only part of that energy has gone into making the alcohol.  Same sugar content, less alcohol.

Although we don’t have all the details because of intellectual property issues, what we do know is that he compared the genomes of yeast species that make a lot of alcohol and those that don’t.  In an email he stated that he focused on genes that would affect carbon metabolism without perturbing redox balance in a significant way.  Presumably he then swapped the appropriate genes between strains and created his low alcohol strain.

This is not only a godsend for low alcohol beer, but it may be useful for other fermentation processes as well.  For example, maybe something similar can be done for low or no alcohol wines which, apparently, are even less tasty than low alcohol beer.  Designated drivers everywhere will be thanking Dr. Morrissey profusely if he can make decent tasting, low alcohol drinks a reality.

And apparently it isn’t just designated drivers that want this stuff.  Judging by recent upticks in sales of the relatively low quality low alcohol beers currently on the market, there is definitely a market out there for such beverages.  A cool science project, decent low alcohol beer and nice profits to boot!  Who could ask for more? 

How beer is made, from Modern Marvels, www.history.com

LiftOver files that allow conversion of chromosomal coordinates between different S. cerevisiae genome versions are also now available for download via the genome_releases link in the sequence directory.

It took just a few months to go from one cell to many. Image adapted from Ratcliff, et al (PMID: 22307617).

Some people might think that the transition from single-celled creatures to multi-cellular ones must have been tough.  After all, single celled organisms ruled the world for the first one or two billion years of life here on Earth. 

And yet, all multi-celled beasts didn’t evolve from the same ancestor.  Current theories are that multicellularity evolved dozens of times over the ages.  In fact, all of the transitional stages of multicellular life can be seen in the volvocine green algae species around today.  So maybe it isn’t so tricky after all.

Using a very clever screen in yeast, Ratcliff and coworkers have shown that they can get crude multicellular life to evolve in the lab.  Basically they only let the yeast that settled easily to the bottom of a shaking flask go on to reproduce.  Within 60 or so days, they had the beautiful, snowflake-like, multicellular beasts made up of multiple yeast cells shown in the image to the right.

Of course multicellular is more than having a bunch of cells stuck together.  Heck, yeast do that now in something called flocs.  No, to be multicellular, these yeast need to reproduce in a way that generates new multicellular yeast and to have specialized cells.  The snowflake yeast from this experiment did both.

These yeast did not reproduce by creating sperm and eggs that combine to generate progeny.  Instead they reproduced more like a lot of plants do.  They produced smaller versions of themselves which then went on to grow to “adulthood.”  Multicellular life gave birth to more multicellular life.

Cells within these snowflakes were also willing to die for the common good.  For example, the cell where the juvenile snowflake was attached would undergo apoptosis so the juvenile could be released.  No single-celled organism would willingly take that kind of hit for other cells.

So it looks like these researchers managed to evolve multicellular organisms from single-celled ones in just a few months.  Pretty amazing what can be learned from yeast!

Of course some care is needed here.  Yeast actually evolved from a multicellular ancestor so some sort of memory of multicellular life may still be lurking in its genes.  If true, this might make the transition from one to many simpler in yeast than in other single-celled organisms. 

This is why the researchers plan to try similar experiments with single celled organisms that have been single cells throughout their evolutionary life.  Then they’ll have an even better idea about how easy the “one to many cells” transition is.

Multicellular yeast having babies.

A new study by Finnigan and coworkers provides an important counterpunch to this argument.  These authors resurrected ancient proteins and showed that an increase in complexity can come from much more common, loss of function mutations.  Time for the deniers to find a new argument…

Making Molecular Machines

Proton pumps like this one may be easier to evolve than scientists first thought.

Finnigan and coworkers focused on the evolution of a protein called vacuolar H+ -ATPase or V-ATPase for short.  Like other molecular machines, this proton pump consists of many different proteins all working together in a coordinated fashion.  One key part of this machine is a rotary ring called V₀.  (This would be the ring of C proteins in the image to the right.)

In most eukaryotes, V₀ is made up of five identical subunits (called Vma3) and one subunit called Vma16.  In fungi, a third protein, Vma11, has replaced one of the Vma3 subunits.  In other words, the fungal version is a bit more complex than other eukaryotic versions.

Current theories are that these three proteins all arose through gene duplication.  Duplication of the Vma3 gene first led to the Vma16 gene and then later in fungi, Vma3 duplicated again this time becoming Vma11.  Yeast V-ATPase absolutely requires Vma11 to function and other eukaryotic Vma3 family members cannot replace Vma11.

Using the 139 family members of the Vma family available in GenBank, members of the Thornton and Stevens lab recreated the ancestral proteins that existed before and after the Vma11 gene duplication event.  Before the arrival of Vma11, there were only two proteins which the authors have named Anc.3-11 and Anc.16.  Anc.3-11 presumably has functions of both Vma3 and Vma11.  After the gene duplication event, there were three ancient proteins: Anc.3, Anc.11, and Anc.16.

Using these ancient proteins, the authors first showed that Anc.3-11 could substitute for either Vma3 or Vma11 in yeast. It could even partially rescue a yeast strain that lacked both of the other genes.  They then showed Anc.16 could replace Vma16 and most importantly, that the two ancient proteins could replace the three modern ones.  They reconstructed an ancient molecular machine that works.

The next step was to figure out what happened after Anc.3-11 duplicated again and the two genes began to evolve into the separate proteins, Anc.3 and Anc.11.  Again using the GenBank sequences, the authors predicted that two single mutations were an initial step on the way to the separation of Anc.3-11 activities into the Anc3 and the Anc11 proteins. 

The authors engineered each mutation independently into the Anc.3-11 protein and found that one mutation made Anc.3-11 more like Anc.3 and the other made Anc.3-11 more like Anc.11.  The complex now required all three Anc proteins instead of just the two for maximal activity.  The authors had recapitulated the first evolutionary steps that led to the formation of the three subunit V₀ rotary ring.

Finally the authors showed that each of these mutations were loss of function mutations.  The Anc.3-11 protein has two different interfaces that interact with Anc.16.  The first mutation weakened one interface on Anc.3 and the second mutation weakened the other interface on Anc.11 causing both proteins to now be required to reconstitute the ring.  The added complexity arose from a combination of gene duplication and relatively common loss of function mutations.

DNA repair at the end of S phase may be more error prone.

Variation in the DNA that results in natural selection does not come about randomly. Where a piece of DNA is in the genome and how it is used affects its chances for being mutated. The end result is that the genomes we see today are the product of these nonrandom mutation rates.

One of the first places this became apparent was in transcribed genes. Scientists found that the transcribed strand of active genes has fewer mutations than the nontranscribed strand. They found the major reason for this was transcription-coupled repair.

Now in a new study in yeast, Agier and Fischer have shown that when a piece of DNA is replicated affects its chance of being mutated too. They compared the genomes of 39 different strains of Saccharomyces cerevisiae and found that late replicating DNA is 1.3 times more likely to be mutated compared to early replicating DNA. This is consistent with a recent study by Chen and coworkers that showed a similar result in the human genome.

This means that if a piece of DNA happens to be further away from an origin of replication, it will build up more mutations over time. And while a 1.3 fold increase in mutation rate might seem small, it is predicted to have a significant impact on genomic variation and natural selection on an evolutionary time scale.

There are a number of potential models for why late replicating DNA is more likely to be mutated. One hypothesis is that cells use different repair mechanisms at different times during S phase: cells in early S-phase repair replication errors with relatively error-free repair mechanisms like template switching with newly formed sister chromatids, while cells in late S-phase tend to rely on more error-prone translesion repair pathways.

Other possible models rely on potential differences between the cellular environment in early and late S-phase. They include altered metabolism, increased presence of single stranded DNA, or even a slow decrease in DNA repair as S-phase progresses. The researchers do not know which, if any, of these mechanisms is responsible for the change in mutation rate.

It may even be that different mechanisms are responsible in yeast and humans. Agier and Fischer found that in yeast, the leading strand had higher rates of substitution towards C and A than did the lagging strand. Chen et. al. found the opposite to be true in human cells. Either they use different mechanisms or similar mechanisms can end up with opposite results.

These findings suggest that the genomes observed today are at least partly the result of the nonrandom nature of neutral mutations. Highly expressed genes near an origin of replication are much less likely to be mutated than are genes with low expression more distant from an origin of replication.

And there are other known and yet to be discovered ways that certain DNA ends up more mutated than other DNAs. Just like in real estate, the key to mutation rate is location, location, location.

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More ORFs than previously thought are interacting with ribosomes.

As scientists peer ever more deeply into a cell, the picture of how things work becomes more and more complicated.  This was true when scientists took a hard look at transcription and gene regulation and found lots of little RNAs scurrying around the cell, regulating genes.  And it now appears to be true for what is being translated and how translation is regulated.

In a new study, Brar and coworkers used ribosome profiling to explore what happens in yeast cells during meiosis at the level of translation.  What they found was that a whole lot more was being translated (or at the very least gumming up the translation machinery) than anyone expected. They also found that translation is as finely regulated as is transcription. 

And this doesn’t just happen in yeast.  The same group has also generated similar findings in mice embryos as well.  Results with human cells should be right around the corner…

Ribosome Profiling

In ribosome profiling, scientists determine what RNAs are contained in a ribosome at a given time point.  The basic idea is that they isolate ribosomes, treat them with nucleases and then harvest the associated 30-35 nucleotide long mRNAs.  They then sequence all of the isolated RNAs and identify where they came from.

Like lots of biology these days, this technique has only become possible with the advent of cheap, robust sequencing.  In fact, the size of these sequences is ideal for modern sequencing techniques.

Researchers in the Weissman lab are finding all sorts of interesting things using this new tool.  For example, in meiosis they were better able to determine which proteins are involved at various stages of meiosis, to see how involved “untranslated” mRNA leaders are in translation, and to identify smaller, previously ignored transcripts associated with ribosomes.  In this post we’ll just focus on the last point but encourage the reader to learn about the study’s other findings here.

Of Shorter ORFs

Ribosome profiling has revealed that a lot more is being translated in yeast than the standard set of genes identified in the Saccharomyces Genome Database (SGD).  For example, Brar and coworkers found that the mRNA of many open reading frames (ORFs) shorter than the usual 250 or so base pairs were associated with the ribosomes.  Shorter ORFs like these aren’t routinely thought of as genes and so have not been extensively studied.

However, given how many of these ORFs were associated with ribosomes, scientists probably should start paying more attention now.  Even before meiosis, 5% of the ribosomes tested in yeast contained RNAs from these shorter ORFs.  Once meiosis kicked in, the number went up to an astonishing 30%.

Since scientists have only just started to focus on them, it isn’t surprising they don’t know how many of these smaller ORFs are translated into smaller peptides.  Or what any of these peptides that do get translated might be doing in a cell.

In a recent study, Kondo and coworkers have shown that one of these ORFs is translated into a peptide and proposed it affects how the transcription regulator Shavenbaby works in Drosophila.  Work similar to this will need to get underway before we have a good handle on what exactly is going on with these shorter ORFs.

Whatever they turn out to do, these small ORFs will probably change what we consider to be a gene.  Again.  The cell just keeps getting more and more complicated! 

Lengthy but informative lecture on ribosome profiling.