July 02, 2018
When someone says they can “read you like a book”, they probably aren’t saying that they know your entire genome sequence. (…or for you Westworld fans, you certainly hope they aren’t saying they’ve got access to the Delos Incorporated “library”!).
But in fact everyone’s genome CAN be thought of as a book, sort of like a giant cookbook. Within your genome are many “recipes” for gene products — DNA sequences that each give instructions on how, when, and where to make a protein or RNA molecule. The recipes of the genome are used to “cook up” a person!
When a parent cell divides and creates another cell, it makes a copy of its genome “cookbook” and passes it down to the new cell. It’s extremely important to make sure that there aren’t any errors in the newly copied text, as mistakes in recipes for crucial enzymes can have disastrous results for the cell. Indeed, our cells (as well as yeast cells, and in fact, all organisms) have enzymes that are dedicated to scrupulously inspecting the new copies of our genome cookbooks that are made during cell division, and then helping to correct any errors.
A certain class of these enzymes are known as DNA mismatch repair (MMR) proteins. These enzymes carefully proofread the newly made copy of the genome, and if something doesn’t match the original version, they will help fix the error.
You might think that having more of these MMR proteins would be a good thing, because there would be more thorough checking and repairing of the new copy of the genome. But the situation isn’t so simple, especially when it comes to human cancer.
Previous studies show that some cancers and cancer predisposition syndromes have less of the MMR proteins. This makes sense because cancers almost always arise due to genome mutations, and it is known that if a cell has less of the error-checking MMR proteins, there are more genome mutations. However, other studies report a puzzling discrepancy: in some cancers, there are in fact MORE of the MMR proteins rather than less!
In their recent GENETICS study, Chakraborty and coworkers decided to investigate this discrepancy further. They analyzed data from two databases of human cancer genome information, The Cancer Genome Atlas (TCGA) and the cBioPortal for Cancer Genomics, specifically looking at how much the genes encoding MMR proteins were turned on or off in cancer.
They observed that many types of human cancer cells make more of two particular MMR proteins: MSH2 and MSH6. It turns out (as it often does!) that our good buddy Saccharomyces cerevisiae has MMR proteins very similar to the human ones, also encoded by genes called MSH2 and MSH6. So Chakraborty and coworkers made yeast cells that overexpress the yeast genes MSH2 and MSH6 and used the awesome power of yeast genetics (and genomics) (#APOYG!) to investigate whether this might lead to cellular and genome changes like those seen in human cancers.
Using various yeast genetic assays to measure rates of genome alterations such as homologous recombination, mutations, and loss of large chromosome regions, Chakraborty et al. observed increased rates for all of these measures of genome instability in cells when both MSH2 and MSH6 were overexpressed, but not for overexpression of either one alone (or of other MMR proteins). So even though there are more of the “good guy” MMR proteins in these cells, this actually ends up making the genome of the cell MORE likely to get damaging mutations of the same types seen in cancer cells.
So why is too much of a good thing such a bad thing in this case? The authors hypothesize that both Msh2p and Msh6p act together as a joined pair to go to the spot where the chromosomal DNA is actively being copied (“replicated”). When they are both overexpressed, too many of the Msh2p-Msh6p pairs can go to the replication spot and actually interfere with the copying process.
It’s as if you were a medieval scribe carefully copying an illuminated manuscript of a genome cookbook, and instead of one supervisor occasionally checking your work, there are a bunch of people constantly looking over your shoulder and maybe even bumping into your arm, causing you to make mistakes in your writing. They may even make you drop the book you’re copying, scattering pages so that you might leave some out or put them back in the wrong order, seriously messing up your work!
Here’s hoping our cells don’t overdo it with their MMR proteins, so that they can be careful with their cookbook copying job and do it “write”!
by Barbara Dunn, Ph.D. and Kevin MacPherson, M.S.
Categories: Research Spotlight
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
March 19, 2014
Life is a set of tradeoffs for people, countries, and even cells. For example, governments need to decide how much money to dedicate to defense and how much to economic growth. Too much on defense and your country fails, because defense spending sucks up so many resources that your country can no longer afford to pay for anything else. And of course if you spend too little on defense, someone who spent a bit more can come and take you over.
No country lives in a vacuum though—how much to spend on defense and how much on growth depends on the country’s situation. If you are the Ewoks living next to an Imperial shield generator, you’d better sacrifice some growth for defense. But once the Death Star has blown up and the Empire is swept away, you probably focus more on growth (until a new Sith lord arrives).
This guns vs. butter debate plays out at the cellular level too when it comes to protecting DNA from mutations. If cells expend too much energy to protect their DNA they sacrifice growth, but if they spend too little, they develop too may harmful mutations to survive. And just like with countries, how much protection a cell’s DNA needs depends on its environment.
If cells need to adapt quickly to a changing environment, a high rate of mutation is favored. These cells are more likely to develop a mutation that gains them an advantage over their slower mutating brethren.
A new study by Herr and coworkers in the latest issue of GENETICS calculates the upper limit of the rate of mutation in a diploid yeast. In other words, they figure out how little “spending” on defense these yeast can get away with and survive.
They find that diploid yeast can deal with a 10-fold higher rate of mutation as compared to haploid yeast. This makes sense, since the extra gene copy afforded by being diploid can mask a recessive lethal mutation, but this study is the first to give this idea hard numbers.
The authors had previously generated a number of mutations in POL3, the yeast gene for DNA polymerase δ, that affect its ability to find and/or fix any mistakes made during DNA replication. The study first focused on two mutations affecting accuracy, pol3-L612G and pol3-L612M, and one mutation affecting proofreading, pol3-01. The accuracy mutations caused about a 10-fold increase in the mutation rate, while the proofreading mutation caused anywhere from a 20-100-fold increase. Neither was enough to seriously affect a diploid’s growth.
The next step was to combine accuracy and proofreading mutations into the same gene to figure out if the combination resulted in a higher mutation rate. The authors suspected that it did when they discovered that even though the heterozygotes were fine, their spores were inviable. The POL3/pol3-01,L212M and POL3/pol3-01,L212G strains sporulated just fine, but none of the spores could germinate and grow.
One way to explain this was that the double mutation increased the error rate to the point that it would kill off haploids but not diploids. By looking at mutations in the hemizygous CAN1 gene they could see that the mutation rate in these diploids was indeed at around the haploid threshold. In terms of the CAN1 gene, this mutation rate was around 1X10-3 can1 mutations/cell division.
They next determined the mutation rate by sequencing the genomes of each mutant as well as the wild type. They found a single T-G mutation in the wild type, 1535 point mutations in POL3/pol3-01,L212M and 1003 mutations in POL3/pol3-01,L212G. From this they calculated a mutation rate of around 3-4X10-6/base pair/generation.
Even though this level of mutation kills haploids but not diploids, this does not mean the diploids escaped unscathed. When the heterozygous diploid colonies were subcloned the resulting colonies were variable in size, indicating that their higher mutation rate was catching up with them. This high mutation rate was making them sick.
Given this result, it wasn’t surprising that diploid homozygotes of each double mutant could not survive—the mutation rate was now too high. The strains homozygous for pol3-01,L212M managed to get to around 1000 cells before petering out. Strains homozygous for pol3-01,L212G did even worse—they only made it to around 10 cells.
In a final set of experiments Herr and coworkers used a variety of other mutations to tweak these mutation rates to find the threshold at which diploids fail to survive. Some of these mutations were in POL3 while others were deletions of the MSH2 and/or DUN1 genes. After testing many different combinations, they found that these yeast did pretty well up to around 1X10-3 can1 mutations/cell division (the haploid threshold rate). Then, from 1X10-3 to 1X10-2 can1 mutations/cell division there began a rapid drop off with little to no growth at the end.
So as might be expected, diploids can deal with a significantly higher mutation rate than can haploids. But even though they can, wild type yeast in the lab still have a very low mutation rate. It is like they are living near the Imperial city planet of Coruscant. They are willing to expend the energy to keep their DNA protected.
by D. Barry Starr, Ph.D., Director of Outreach Activities, Stanford Genetics
Categories: Research Spotlight
March 21, 2013
At first our favorite small eukaryote, S. cerevisiae, might not seem like a great model for cancer studies. After all, budding yeast can’t tell us anything about some of the pathways that go wrong in cancer, like growth factor signaling. And it clearly can’t help explain what happens in specific tissues of the human body. But in other ways, it actually turns out to be a great model.
For example, all the details of cell cycle control were originally worked out in yeast. And now a whole new batch of genes has been found that influence a phenomenon, chromosome instability (CIN), that is important in both yeast and cancer cells.
As the name implies, chromosomes are unstable in cells suffering from CIN. Big chunks of DNA are lost, or break off and fuse to different chromosomes, turning the genome into an aneuploid mess. And this mess has consequences.
CIN can cause new mutations or make old ones have a stronger effect. Eventually these mutations can affect genes that are important for keeping a cell’s growth in line. Once these are compromised, a tumor cell is born.
Since CIN is pretty common in yeast, we might be able to better understand it in cancer cells by studying it in yeast. The Hieter lab at the University of British Columbia has come up with a powerful screen to get yeast to confess why it CINs.
A previous study from the group set the stage by finding a large group of mutants that have CIN phenotypes, implying that those genes are involved in keeping chromosome structure stable. In a new paper in G3: Genes, Genomes, Genetics, van Pel et al. uncovered the network of interactions among the genes in this set, using synthetic genetic array (SGA) technology. And they confirmed that the human homologs of some of these genes interact in the same way as in yeast, making them potential targets for cancer therapies.
The idea behind SGA studies is that if two proteins are involved in the same process, then a strain carrying mutations in both of their genes will be much worse off than a strain carrying either single mutation. In the worst case, the double mutant will be dead. This is known as a synthetic lethal interaction.
Yeast is a great model for doing these sorts of studies on a very large scale. We can construct networks showing how lots of different genes interact, and most importantly, find the genes that are central to many interactions. These “hubs” are likely to be the key players in those processes.
The researchers looked specifically for interactions between genes that are involved with CIN in yeast and are also similar to human cancer-related genes. They came up with various interaction hubs that will be interesting research subjects for a long time to come. In this study, they focused on one of these: genes involved with the DNA replication fork.
One of these in particular, CTF4, is a hub for both physical and genetic interactions. Unfortunately, Ctf4p doesn’t look like a good target for chemotherapy. It’s thought to act as a scaffold, and lacks any known activity that could potentially be inhibited by a drug. However, the interaction network around CTF4 that van Pel et al. uncovered suggests another way to target this hub. If a gene that interacts with CTF4 itself has a synthetic lethal interaction with another gene, and we could re-create the synthetic lethal phenotype in a cancer cell, we might be able to knock out the whole process. And that is just what they found in human cells.
First the authors identified a couple of human genes that were predicted from the yeast screen to be close to human CTF4 in the interaction network and to have a synthetic lethal interaction with each other. They then lowered the expression of one using small interfering RNA (siRNA), and reduced the activity of the other with a known inhibitor. Neither treatment alone had much effect, but combining them significantly reduced cell viability.
Since cancer cells frequently carry mutations in CIN genes, it should be possible to create a synthetic lethal interaction, guided by the yeast interaction network, where one partner is mutated in cancer cells (equivalent to using siRNA in this study) and the other partner is inhibited with a drug. Since it relies on a cancer-specific mutation, this approach has the potential to selectively target cancer cells while not disturbing normal cells, the ultimate goal for chemotherapy.
by Maria Costanzo, Ph.D., Senior Biocurator, SGD
January 30, 2012
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.
Categories: Research Spotlight