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As a make-up for having hardly any time to post during the Week of Science, I have just added a set of four posts of pure science to my blog in rapid succession. On is on something that was already mentioned here, but the others are unrelated to anything on GNXP, so if you want to check them out, you can read them.

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First of all I would like to invite you all to come and check out my new blog, Science, Theory, and Liberty, at Unlike here at GNXP, my week of science is just starting, since I haven’t had much of a chance to post to blogs lately. Since I won’t have access to a computer from Wednesday evening through Saturday night, some of the posting may actually last into early next week. If some people would actually leave some comments on some of my posts, that would be nice.

Now to the content…

As the biological community has become more appreciative of the many roles played by non-coding RNA in the cell, there have been a few key types of RNA for which new functions are being discovered at a rapid pace. One of these is the class of microRNAs, which are short pieces of RNA that fold into stem-loop structures and which are known to regulate gene expression post-transcriptionally by targeting mRNAs.

I was first introduced to this class of RNAs when I worked for a semester on a project that was trying to characterize their mechanism of action. Since then, I have witnessed many discoveries regarding their effects, and I will briefly mention some of the latest ones here:

-Marshall et. al. report on how microRNAs encoded by the Kaposi sarcoma-associated herpesvirus are highly conserved, suggesting that they contribute to the pathogenicity of the virus.
-Linsley et. al. have found that one particular family of microRNAs appears to be involved in blocking cell cycle progression out of the G0 and G1 phases.
-Flynt et. al. discovered that a particular microRNA in zebrafish regulates genes in the well-known Hedgehog developmental signaling pathway, and is involvied in the differentiation of muscle cells
-Presutti et. al. review the types of non-coding RNAs, including microRNAs, present in neurons and some findings regarding their roles in growth and synaptic plasticity.
-In probably the most directly applicable of these studies, Lee et. al. identified a microRNA signature in pancreatic cancer cells.

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…when it specifies a different fold! At least that’s the latest word from Kimchi-Sarfaty et. al., who reported in the Jan 26 issue of Science that a supposedly “silent” mutation in the multidrug resistance gene MDR1 changes the function of the encoded protein. If the authors’ conclusions are correct, this result could radically expand the number of gene variants that have the potential to influence phenotypes, and that’s why I chose to post this one on GNXP. To understand the meaning of this, you have to know something about the genetic code and the subject of protein folding.

As I’m sure most of you know, the amino acid sequence of a protein is specified precisely by the sequence of bases in the DNA of its gene. Each amino acid is specified by three consecutive bases, and since there four possible bases, there are 4^3=64 possible base triples (called codons). Considering that there are 20 amino acids found in proteins, and three codons that act as stop signs, that means there are on average three codons per amino acid. These duplicate codons often differ by a single base, which means that many point mutations even within the coding region of a gene will not alter the protein sequence. Different organisms have clear preferences for what codons they use to specify each amino acid, and while any known life form can recognize them all, the preferred ones are read a little faster (the mechanism for this involves the abundance of the tRNAs that actually do the recognition, though that doesn’t matter for our discussion). It is a piece of cake to determine whether any two variations on a common gene sequence, for example, one from a healthy person and another from someone with a disease, will encode the same exact protein. Ones that do are routinely dismissed as being “silent”, i.e. unable to cause a new phenotype, except in cases where the change is in a regulatory region that controls expression of the gene, splicing, etc.

That brings us to the question of protein folding. It is generally accepted that a protein’s function is intimately related to the three-dimensional shape into which it folds, and that this shape is determined by the sequence of amino acids from which it is made up. Therefore, researchers have assumed (and typically rightfully so) that no matter how you make a given sequence of amino acids, under typical cellular conditions it will fold up into its proper shape and start functioning. The prevailing view also holds that the correct three-dimensional shape is formed because that one has the overall lowest (free) energy of any possible shape.

This energetic criterion cannot be the whole story, because a quick calculation (see Levinthal’s Paradox) shows that a protein could never “visit” all possible shapes in any reasonable amount of time. Therefore, most people studying protein folding believe that protein sequences are optimized not only to dictate the correct fold but to specify a “roadmap” of how to get there, by setting up fast initial interactions among the atoms that “push” the folding in the right direction. However, there has been no good evidence that the final state isn’t a unique energy minimum, regardless of how complex the journey to get there.

Kimchi-Sarfaty et. al. looked at a transmembrane pump called P-glycoprotein (P-gp) that is well-known in the cancer research community for being something that cancer cells turn on to expel the kind of toxic drugs we throw at them. P-gp tends to grab large, greasy molecules, without regard to their precise structure, and use ATP to power their expulsion from the cell, thereby allowing the cell to evade their effects. Several variants of the MDR1 gene, which encodes P-gp, can be seen to specify the exact same sequence of amino acids, except that one of these is encoded by a slightly different set of three bases in each variant. However, the change converts a codon that is common in mammalian cells to one that is rarer, and as mentioned above, the rarer one would be expected to create a slight pause at that point in the synthesis of the protein.

The very surprising result is that the proteins produced from the different variants show a bunch of functional differences, including the affinity with which they bind several drugs, even though they are expressed at the same level and their amino acid sequences were verified to be identical. The authors conclude that the pause induced by the rare codon causes the protein folding (which starts long before the protein is finished) to follow a different pathway. This implies that the rate at which a protein is allowed to fold, and not just the set of final states, is crucial for determining the final shape. For the geneticist, the take-home message here is that a change in a coding sequence should not be dismissed as a possible cause of a phenotypic trait just because it doesn’t alter the protein sequence.

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From Epigenetics News:

Researchers at the Wadsworth Center, the public health laboratory of the New York Sate Department of Health, have shown it is technically feasible to detect DNA methylation using a simple breath test. Dr. Weiguo Han and Dr. Simon D. Spivack have tested seven patients by having them breath into a handheld device for 10 minutes, which forms a condensed vapor, to which the methylation assay is applied. The methylated form of all six tumor suppressor genes could be detected using the simple breath test.

    The DNA is believed to be released when cells turn over, or are damaged, in the lungs and airways, he said. “Although it is not possible to say at this point the precise anatomic origin of the airway-derived DNA being tested, it may be that different patterns of gene methylation will themselves actually map the origin of this DNA to particular regions of the airway,” Spivack said.

The researchers hope that the test can be further developed into a non-invasive test for the early detection of lung cancer.

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I just had a short conversation with one of my professors about one of my most common topics of discussion, namely the role of human understanding in science and engineering. He made a comment like “the most interesting things in the universe are ones we cannot understand”, which seemed like a quite unusual thing to say. For me, there is basically no (intellectual) interest in things that I cannot hope to understand. I think this is part of the reason I am not much interested in the social scene. I insert the word “intellectual” simply to exclude things that are “interesting” solely because the result benefits or harms me personally, or members of the opposite sex I am “interested in” in the sense of attraction.

For me there is an interest, as sort of “beauty”, that is initially present in almost all complex physical systems, and which disappears when they go outside the grasp of understanding. Again, beauty is in quotes because there are things that look beautiful in a non-intellectual way. I was wondering about whether people on here find that interest and understandability also go hand in hand. By “understandable” I don’t mean simple, I just mean something that can be mentally captured in some way other than a series of equations impenetrable to anything but a computer.

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I’m sure Coffee Mug can explain a lot more about the significance of this, but in a new article in Science researchers report fusing a fluorescent protein to a particular potassium channel, known as Kv1.1, and using this to determine the site of synthesis of the channel. The particular type of fluorescent protein they used has one neat property that made this task a lot easier. When synthesized it has a green color, but when excited by UV light in the right way, it becomes red. Therefore, the protein made before and after this “photoconversion” process can be distinguished. It was found that the Kv1.1 that appears in the membrane in dendrites is synthesized locally, within those dendrites, rather than in the cell body. In addition, it was found that activation of the NMDA receptor dramatically decreased the rate of local synthesis of Kv1.1 This effect was found to be dependent on a protein called mTOR, which gets its name from its interaction with the drug rapamycin (which in fact is a well-known immunosuppressant, although it sounds like something you take to keep loud, rhythmic music from making you sick).

What could be the significance of this local down-regulation? Well, those of you with a background in neurophysiology will know that potassium channels hyperpolarize neurons, making them less likely to fire an action potential. Also, NMDA receptors are excitatory and seem to play a role in learning and memory. By shutting off production of potassium channels, the stimulus registered by the NMDA receptor can be reinforced, leading to potentiation of the dendrite’s response.

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The 2006 Nobel Prize in Physiology or Medicine goes to Andrew Z. Fire and Craig C. Mello “for their discovery of RNA interference – gene silencing by double-stranded RNA”. This is the now quite well-known phenomenon of RNA interference (RNAi), in which double-stranded RNA can interact with complementary messenger RNA to block the expression of genes. This discovery was important as it showed how RNA can carry out a specific cellular function without having to be translated into a protein. Since then, there have been many other types of RNAs found to act as gene regulators, including the microRNAs (miRNAs) mentioned by Coffee Mug recently. Some of the protein players involved in RNAi, such as the enzyme Dicer, have been identified, but the mechanisms of action of all these RNAs, especially the more recently discovered types, are still quite uncertain.

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I know this has nothing intrinsically to do with genetics, but it has something to do with cognitive ability testing, which I know is a favorite topic of discussion on GNXP. I was inspired to write a post on this since I am in the process of preparing for the GRE. Among the preparation materials that ETS provides are the distributions of verbal and quantitative test scores by graduate field of study.

Out of curiosity I looked through these, and found some interesting results. In particular, the shape of the distribution of quantitative test scores varies drastically by intended field of study. It is approximately normal for the humanities and some of the biological sciences, but is extremely left-skewed for physics, math and engineering majors, having a peak at around 700 but rising again near a perfect score of 800. In some cases this ceiling effect in quantitative scores is so severe that it’s impossible to score above the 90th percentile!

The verbal scores show a very different pattern. The humanities and social sciences mostly show normal distributions, whereas the hard sciences typically show a bimodal distribution but with a similar mean. There is no evidence, though, in any major for a ceiling effect even remotely resembling that for the quantitative scores. The difference is such that, even though I scored a full 80 points lower on the verbal section than the quantitative section of a practice test, I didn’t see a single major where I would have been at a higher quantitative than verbal percentile. This raises the question of what the verbal test is actually measuring, and why its mean seems to vary so much less by major. One explanation I came up with is that verbal tests measure mostly how much education you have had, and how much reading you have done, rather than intellectual aptitude. This is because they ask you for things like antonyms of quite uncommon words. In any case, I doubt that it measures the type of verbal ability factor that has been shown to trade off with visuospatial ability in many studies, including those assessing gender differences. If it were so, I would expect the scores to vary more, with the less spatially-oriented fields showing more left-skewed distributions. Also, I have always done well on verbal tests although I am predominantly a visuospatial thinker, and have always found analyzing literature to be one of the most difficult tasks. Any thoughts?

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Today on I found metion of this article reporting a study of the effect of breastfeeding on the stress response of children at 10 years of age. The study involved almost 9000 children born in Great Britain in 1970. The occurrence of divorce or separation of the parents was also included in the statistical analysis, along with a few other variables such as maternal age and the sex of the child. As predicted, children whose parents had divorced or separated between when the child was 5 and 10 years old had higher levels of anxiety. In addition, children who had been breast-fed had lower anxiety than those who had been bottle-fed. Interestingly, the effect of parental divorce or separation on anxiety was only significant for the bottle-fed children. Parental separation and divorce were not correlated with breastfeeding themselves, and none of the other variables appeared to mediate the effect of breastfeeding.

I likely wouldn’t have thought anything of this study before, but after reading about methylation of the glucocorticoid receptor gene in rats being affected by maternal behavior (see the “alter their response to stress” link in this old GNXP post), this makes me wonder if a similar effect operates in humans. Although there are many ways to explain the human child study that don’t invoke this type of biochemical process, the pattern of altered responsiveness to an environmental event (parental separation/divorce) would be consistent with some kind of alteration in the stress response pathway itself.

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I just posted this on my own blog last night and thought I’d cross-post it here, as there have been a few posts lately about neurotransmitters, neurons, and behavior.

About a month ago I saw this article about the role of the dopamine transporter in cocaine reward. For those that don’t know, the modified amino acids dopamine, norepinephrine, and serotonin, collectively known as monoamines, are neurotransmitters that are released by specific neurons in the brain and activate receptors on other neurons, sending a message from one cell to another. There are “pumps” in the membranes of the neurons that release these transmitters, which “clean up” the released monoamines so that they don’t keep activating receptors for too long. These pumps are blocked by many psychotherapeutic and recreational drugs, producing a change in brain function. While each neurotransmitter has multiple effects in the brain, the transmitter dopamine in particular is believed to participate in the behavior-reinforcing properties of both natural (food, sex, etc.) and pharmacological (drug) stimuli. Among many scientists dopamine is still believed to be a kind of “pleasure chemical” whose concentration determines the degree of positive subjective sensation produced by the environment, regardless of the specific nature of the stimulus. This idea has been called into question especially lately, though, for a number of reasons, many of which have nothing to do with this article. For instance, the effect of drugs that directly activate dopamine receptors is not euphoric in humans.

The finding that concerns us here is one made by Sora et. al. in 1998. To understand the significance of this study, it is important to know that the stimulant cocaine blocks the transporters (“pumps”) for all three monoamines. Given the assumed responsibility of dopamine for reinforcement, it has long been assumed that the block of the dopamine transporter (DAT) produces the euphoric effect of cocaine by allowing dopamine to sit around and activate its receptors longer. To test this, Sora et. al. deleted (“knocked out”) the gene encoding DAT from mice, and showed that they still prefer to spend time in a chamber in which they have previously received cocaine. This so-called conditioned place preference suggests that cocaine can act as a reward even when it cannot block DAT (because DAT doesn’t exist in these mice). Knocking out the serotonin transporter (SERT) also left cocaine reward intact (This SERT is the same as the 5-HTT mentioned in the Caspi and Moffitt study-geneticists seem to like the name 5-HTT and biochemists SERT, and some use the alternative SLC6A4 occasionally). A follow-up study showed that knocking out both DAT and SERT makes mice that do not prefer an environment they associate with cocaine. Sora et. al. took this to mean that blocking SERT is rewarding as well, which flies in the face of the fact that blocking SERT with drugs like fluoxetine (Prozac) does not produce signs of euphoria. An obvious caveat here is that the brains of DAT knockout mice are flooded with dopamine and the animals are very hyper even when they aren’t on any drugs, so findings may not generalize to normal mice.

The new study by Chen et. al. took a different approach. They found that by mutating part of DAT, they could prevent cocaine from binding to it without breaking the pump. When this mutant DAT was added back into DAT knockout mice, cocaine no longer made the mice hyperactive like normal or DAT knockout mice (paradoxically, it even calmed them) and was not rewarding. This confirms what I–and probably many other researchers–suspected was going on: the mice with DAT knocked out only showed a response to cocaine because it slightly amplified the effect of the high baseline dopamine. Possible explanations are that increased activation of serotonin receptors overcomes some negative feedback mechanism limiting dopamine levels, or that lack of DAT induces a form of plasticity in the reward pathway such that SERT blockade becomes rewarding. This still doesn’t explain other results questioning the idea of dopamine as a “pleasure chemical”, but at least it shows that cocaine, and probably methylphenidate (Ritalin) and amphetamines, do produce their reinforcing effects through inhibition of dopamine reuptake.

*I just corrected the links. For some reason the first time I posted the URLs got all messed up, even though it worked perfectly fine for my own blog when I cut and pasted from the same file on my computer.

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Okay, this is my first post, and I must admit it has no interesting science news in it. However, I think many on here will find this funny.

A few days ago I took a look at Mendel’s Garden #3, and among the featured posts is a discussion of the work of Japanese biologist Susumu Ohno. He took a part of the gene encoding the large subunit of RNA polymerase II and converted it into music, considering both the base sequence itself and the properties (size and charge) of the encoded amino acids. He thought that this piece sounded like a Chopin nocturne, so he took the nocturne and “reverse translated” it to a DNA sequence. He proceeded to demonstrate that this sequence contains a 160-codon open reading frame (see this site for more), and went on to make lots of philosophical speculations about how DNA sequences and music evolve in the same manner. The probability that any given sequence of 160 base triples would start with a start codon and not contain stop codons is a little less than 1/130,000. However, this could be artificially raised by many orders of magnitude by assigning the start and stop codons to sequences of notes that are very frequent and rare, respectively, in the nocturne, which shouldn’t be difficult to find with the right software.

Perhaps most interesting is the musician Colin Angus of the group The Shamen, who teamed up with biologist Ross King to create the piece “S2 Translation” containing the full sequence of a serotonin receptor. The program they used for this, called ProteinMusic, is available as a free download. I got the program and tried some random gene sequences, making sure to trim off any bases before the start codon (ProteinMusic doesn’t do this automatically). The program went straight through the stop codon at the end of the transcript, calling it “Z”. I could not hear any difference in the sound between the actual polypeptide and the 3′ UTR. The poly(A) tail was easy to recognize because of its repetitiveness, but that’s about it. Someone commented that

“It may be possible for somebody who has heard the pattern of a calcium-binding site or an enzyme active site to recognize its occurrence in a novel protein.”

Yeah right. I doubt 1% of bioinformatics scientists could identify the seven transmembrane helices in that serotonin receptor by ear, something that is typically easy to do by eye using hydropathy plots. This isn’t to say that the idea of turning DNA sequences into music isn’t neat in a purely fun sense, just that it doesn’t do anything for science except maybe increase popularity.

• Category: Science 
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