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“Poetry in the Genetic Code” — does this mean that Natural Selection is now a poet?

The theme of silent mutations that are not so silent has been addressed here at UD before (e.g., go here). Here’s a piece that elaborates on the significance of this recent finding:

Silent No Longer: Researchers unearth another stratum of meaning in the genetic code
By Ivan Amato

The more scientists study the genetic code, the more it reads like poetry. In a poem, every word, every line break, even every syllable can carry more than a literal meaning. So too can the molecular letters, syllables, and words of the genetic code carry more biologically relevant meanings than they appear to at first.

Now, a cadre of researchers is discovering intriguing depths of meaning in “synonyms” in the genetic code—very short wordlike sequences, or codons, that translate into exactly the same amino acids during the construction of a protein. Scientists are finding that synonymous codons influence the temporal pattern by which a messenger RNA (mRNA) molecule bearing genetic specifications from a cell’s nucleus is translated by machinelike ribosomes into protein molecules.

These punctuations in the RNA-to-protein translation process have unexpected consequences: They can change the timing by which nascent proteins fold as they elongate and peel away from ribosomes. This means that two stretches of mRNA that differ only in synonymous codons can translate into two proteins that have identical amino acid sequences but different three-dimensional shapes. Such differences can convey important, even grave, biological and medical meanings. It’s akin to the way the same hand can fold into an affirming thumbs-up gesture or into a shape involving the middle finger that conveys another sentiment altogether.

“We know that one individual given drug A will have to sleep for three days, but another taking the same drug will suffer no such effect,” notes Michael M. Gottesman, chief of the Laboratory of Cell Biology at the National Cancer Institute (NCI) in Bethesda, Md. He now thinks that such individual differences in response to drug treatments and in susceptibility to diseases could correspond to different synonymous codons that lead to differently folded protein products. Most researchers have assumed that this type of genetic variation is too subtle to matter much. In fact, an often-used moniker for the variation is “silent polymorphism.” Nonsilent polymorphisms are those variations in a gene’s code that do lead to amino acid changes.

Last month, Gottesman and coworkers reported results of their investigation of a silent polymorphism that isn’t so silent (Science, DOI: 10.1126/science.1135308). They found it in the gene that codes for P-glycoprotein (P-gp), a protein that takes residence in cell membranes, where it pumps drug molecules out of the cell. By purging the cell of drugs, this protein renders about half of human cancers resistant to a diversity of drugs.

Gottesman’s group discovered that a silent polymorphism sometimes found in this gene gives rise to a version of P-gp that is less effective at expelling drugs from cells than the “wild type” of the protein. The researchers conjecture that the altered protein function derives from a synonymous codon’s effects on the timing of translation and folding as the P-gp protein is being made and as it insinuates itself into a cell’s membrane. In their studies, the researchers expressed the gene with and without the silent polymorphism in cultured human carcinoma cells, an AIDS-related human cell line, and two lines of cells derived from monkey kidney.

“The beauty of the paper is that it is based on natural examples,” that is, living cells, comments Anton Komar of Cleveland State University. He was one of the first scientists to suggest, in the late 1980s, that silent polymorphisms in genes might have important biological consequences. Previously, Komar and others had found evidence that synonymous codons might affect protein folding, but those studies were done in cell-free test-tube preparations. “Nobody paid attention,” Komar recalls. The consensus view, he points out, has long been that only those polymorphisms that translate into amino acid substitutions in the associated proteins were biologically or medically significant. To Komar, Gottesman’s findings ought to change that view.

“Looking closely at silent polymorphisms could become a vast project now,” Komar says. “We have the whole genome in hand.”

Gottesman was attracted to research into silent polymorphisms three years ago during a discussion with Randall Kincaid, a former immunology lab head at the National Institutes of Health in Bethesda, who now runs Veritas, a biotech company in nearby Rockville. Kincaid mentioned a malaria vaccine project that required him to produce loads of a human protein in a microbial host. The protein, however, kept folding up and aggregating into unusable clumps. Kincaid told Gottesman that to circumvent this protein-folding headache, his team used a genetic engineering technique that involves exchanging some of the codons in the human gene with synonymous codons that are more prevalent in the microbial host used to manufacture the protein in bulk.

During that 2003 discussion, Gottesman says, “a light bulb went off in my head.” For Gottesman, Kincaid’s protein-folding headache sounded like a potential answer to a mystery he and his colleagues had been encountering in their research on P-gp. Listening to Kincaid, Gottesman wondered if the differences in folding that his team had observed stemmed from the silent polymorphisms found in the gene for P-gp.

Silent polymorphisms are among a more general class known as single-nucleotide polymorphisms, or SNPs (pronounced “snips”). SNPs consist of one nucleotide letter substituting for another. In the mRNA transcribed from a gene, every string of three nucleotides constitutes a codon that corresponds to and is ultimately translated into one of 20 amino acids.

For example, the mRNA codon designated UUU (uracil-uracil-uracil) encodes the amino acid phenylalanine, whereas the codon UUA (uracil-uracil-adenine) encodes leucine. Because a leucine replaces a phenylalanine, the polymorphism is nonsilent in this case, and the codons are nonsynonymous. On the other hand, the mRNA codons GGU, GGC, GGA, and GGG all encode glycine. That makes them synonymous codons, and their protein constructs all have the same amino acid sequence.

Gottesman’s group traced one particular silent SNP in the gene for P-gp—in which a GGC codon changes into GGT—to altered protein activity. Both codons correspond to glycine. Using several analytical methods, the researchers concluded that the folding, final shape, and function of P-gp indeed are influenced by silent SNPs.

“These results may not only change our thinking about mechanisms of drug resistance, but may also cause us to reassess our whole understanding of SNPs in general and what role they play in disease,” states NCI Director John E. Niederhuber in a press release.

Komar conjectures that synonymous codons might affect protein folding by tweaking the timing of that folding. In cells, he notes, the concentrations of amino acid-toting transfer RNA (tRNA) molecules, each of which corresponds to a specific mRNA codon, roughly mirror the overall frequencies at which the codons appear.

During protein translation, the mRNA codons sequentially specify which tRNA must come into the ribosome complex to deliver the next amino acid to be stitched onto the growing protein. A polymorphism that substitutes an infrequent codon for a relatively common but synonymous codon ought to result in a delay in translation because there is less of the corresponding amino acid-bearing tRNA around, Komar says. Because of the momentary pause, the growing protein could fold in a different way than if the pause were absent.

The details of the altered folding kinetics remain largely unknown, but recent work by Luda Diatchenko of the University of North Carolina and her colleagues has opened up one route of investigation into those matters (Science 2006, 314, 1930). Like Gottesman’s group, they found that different synonymous codons in a gene can lead to changes in the production of its protein product. The gene Diatchenko’s team studied encodes a neurotransmitter-degrading enzyme called human catechol-O-methyltransferase, or COMT. This enzyme is central to the regulation of pain perception. The COMT gene exists in three common variants, each one consisting of both silent and nonsilent codon changes.

Depending on which variant a person has, he or she is likely to have low, average, or high pain sensitivity. The researchers found that differences in COMT production derive far more from differences in synonymous codons in the COMT gene than in nonsynonymous ones that lead to amino acid changes.

Moreover, Diatchenko and her colleagues were able to relate those codon and clinical differences to the presence or absence of a specific stabilizing loop structure in the mRNA molecules encoding the enzyme. The mRNAs that were more stable yielded COMT activities up to 25 times higher than that associated with the least stable mRNA. The researchers surmise that these stability differences influence either the rate at which the mRNA molecules are degraded or at which they can be translated into protein. Because the more stable mRNAs produce more of the neurotransmitter-degrading enzyme, they ultimately correspond to less pain sensitivity.

“We need to give much more weight to synonymous changes,” Diatchenko concludes. “Now that we know that the difference in COMT expression depends on the secondary structure of mRNA, we can think of targeting this mechanism” to alleviate such conditions as persistent pain, she says.

Confirming that the genetic code has built into it “colons or commas” that influence the kinetics of protein synthesis and folding, Komar notes, is a reminder that the code has yet to be fully decrypted. It’s a molecular poem whose deconstruction must continue. The question now for Komar and others is whether they’ve identified a previously hidden stratum of meaning in the genetic code that will significantly help account for the differences that make individuals unique, in illness and in health.

Chemical & Engineering News
January 22, 2007
Volume 85, Number 04
pp. 38-40

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28 Responses to “Poetry in the Genetic Code” — does this mean that Natural Selection is now a poet?

  1. In the beginning . . .

  2. How can you adhere to materialism with findings like this?

  3. “This means that two stretches of mRNA that differ only in synonymous codons can translate into two proteins that have identical amino acid sequences but different three-dimensional shapes.”

    So synonymous, “neutral” mutations actually have an effect after all? What is to become of neutral theory?

    Somebody please inform Sal and Caligula…. : )

  4. this is just too weird if really ture :-)

    If there really are structures that work like commas, or even “WAIT” functions in a computer, then could alot of this stuff be stored in “Junk DNA”.

    Think about how much typed text is used up by whitespace and punctuation. Could alot of the 97% of non-coding junk actually be providing this kind of structural support of the language?

  5. Is that the sound of iambic pentameter exploding that I hear?

    :smile:

  6. sorry for this note here – I finally found my log in info – i,e, how would I get it if for ex. – I couldn’t remember my user name?

    Can someone help me respond to the charge that retrovirus elements in DNA are DEFINITELY VIRAL remnants?
    ALSO that a mutation making nylon degredation possible is PROOF of evolution. (My thought is that this new acquired characteristic is at the expense of another that is more likely keyed to the organisms survivability.

  7. this is just too weird if really ture

    An example of a deleterious random mutation :-)

  8. Alan, Dr. Dembski wrote a paper on nylonase a while back, I believe. You might try to do some searching for it. Maybe someone on here can point you too it.

    BTW, proof of “evolution” doesn’t carry much meaning around here. If you mean “proof for change”, then sure, it is. If you mean “proof for macroevolutionary, bacteria-to-baboons change”, then no, it was a built-in genetic engineering response to input.

  9. There is abundant evidence that most DNA sequences are poly-functional, and therefore are poly-constrained. This fact has been extensively demonstrated by Trifonov (1989). For example, most human coding sequences encode for two different RNAs, read in opposite direction s(i.e. Both DNA strands are transcribed — Yelin et al., 2003). Some sequences encode for different proteins depending on where translation is initiated and where the reading frame begins (i.e. read-through proteins). Some sequences encode for different proteins based upon alternate mRNA splicing. Some sequences serve simultaneously for protein-encoding and also serve as internal transcriptional promoters. Some sequences encode for both a protein coding, and a protein-binding region. Alu elements and origins-of-replication can be found within functional promoters and within exons. Basically all DNA sequences are constrained by isochore requirements (regional GC content), “word” content (species-specific profiles of di-, tri-, and tetra-nucleotide frequencies), and nucleosome binding sites (i.e. All DNA must condense). Selective condensation is clearly implicated in gene regulation, and selective nucleosome binding is controlled by specific DNA sequence patterns – which must permeate the entire genome. Lastly, probably all sequences do what they do, even as they also affect general spacing and DNA-folding/architecture – which is clearly sequence dependent. To explain the incredible amount of information which must somehow be packed into the genome (given that extreme complexity of life), we really have to assume that there are even higher levels of organization and information encrypted within the genome. For example, there is another whole level of organization at the epigenetic level (Gibbs 2003). There also appears to be extensive sequence dependent three-dimensional organization within chromosomes and the whole nucleus (Manuelides, 1990; Gardiner, 1995; Flam, 1994). Trifonov (1989), has shown that probably all DNA sequences in the genome encrypt multiple “codes” (up to 12 codes).

    –John Sanford
    Genetic Entropy

  10. IT takes great faith to believe that this type of elegance and sophistication at that level is the result of an unguided process. No wonder that materialists don’t want the design hypothesis to even be considered in public schools.

  11. As a side note, Michael M. Gottesman is chief of the Laboratory of Cell Biology at the National Cancer Institute (NCI) in Bethesda, Md.

    He is a Medical Doctor, not an evolutionary biologist:

    Michael M. Gottesman, M.D.

    It might be interesting to see how many evolutionary biologists are on Dr. Gottesman’s staff. See: Laboratory of Cell Biology

  12. [...] William Dembski reports that natural selection is now a poet. [...]

  13. Sal,

    Looking at the listed staff only one other researcher holds an MD the others are PhDs.

  14. - – -
    The Sound of Natural Selection Exploding:

    Which to use?…

    http://www.youtube.com/watch?v=2c8b6p8BCEU

    or a redo..
    http://www.youtube.com/watch?v=8ZyYWSNhFxg

  15. alan:
    There is an overview of viruses and genes here: http://www.panspermia.org/virus.htm

    From the site above: “And it has now been shown that some of the genes that viruses install have a beneficial function for the host. In fact, doctors now use viruses to install genes in the new field of “gene therapy.” Even the virus that causes AIDS, if properly disabled, may become useful this way.” (Two references listes)

    Viruses are a demonstrated tool to introduce new genetic information into a particular genome. Unlike Random Mutation and Natural Selection, they actually can accomplish that purpose.
    Retroviral elements are viral elements incorporated into host DNA.
    I’m not sure what your particular concern is about them, or why you call it a “charge.” Maybe you could be more specific in your question?

  16. Scordova: “As a side note, Michael M. Gottesman is chief of the Laboratory of Cell Biology at the National Cancer Institute (NCI) in Bethesda, Md.

    He is a Medical Doctor, not an evolutionary biologist:”

    Haven’t we established that medical doctors don’t know anything about cell biology? Who does this guy think he is? :)

  17. Late_model wrote:

    Sal,

    Looking at the listed staff only one other researcher holds an MD the others are PhDs.

    I was inquiryt about evolutionary biologists, not so much if they were PhD’s or MD’s. I did not see any evolutionary biologists on the staff.

    Sal

  18. I always thought that “the blind watchmaker” was the poet and natural selection weeded out the “There once was a man from Nantucket” in favor of “Trees” (for example).

    One blind watchmaker, eons of time, plus some culling process-and they just churn until they can churn no more. Sometimes you get butter and sometimes you get comprehensible inhabited universes.

  19. Oops, and sometimes you get “poetry in motion”…

  20. dacook

    I’m glad you brought up viral insertions of beneficial genes. In another thread we were making things up to solve Haldane’s Dilemma. Someone divided natural selection into two parts (hard and soft) and said Haldane uses only hard selection while soft selection has no cost and happens an unknown amount of the time.

    Soft selection was rather a brilliant invention. It works like this – if a creature is missing a beneficial mutation and dies before reproducing, well maybe he was going to die anyway whether or not he had the mutation so even though he is helping to fix the mutation there’s no substitution cost because he would’ve died anyhow. Absolutely brilliant. All one has to do is ignore the fact that creatures WITH the mutation also die because of other factors so it doesn’t become obvious that it’s a self-nullifying mechanism.

    At any rate, I thought I’d solve Haldane’s Dilemma too so I proposed that beneficial genes are spread through a population by kissing. I didn’t yet outline how it works by kissing (I was saving that for my forthcoming book “How I Solved Haldane’s Dilemma”) but since you mentioned the mechanism I might as well ‘fess up. A virus that implants the beneficial gene is passed during the kiss.

  21. That would be the Herpes virus :)

  22. As I’ve been following this thread, I couldn’t help but wonder: when computing the reported DNA difference between humans and chimps (somewhere between 1% and 4%), how are SNPs handled in the counting — are they ignored, and the codons considered identical? I suspect this is one area that will be impacted by this new understanding of the “silent” mutations.

  23. “Poetry in the Genetic Code” — does this mean that Natural Selection is now a poet?

    Are you silly IDers doubting the all-purpose resourcefullness of natural selection? Linguist, poet, creator, engineer, innovator. My goodness, the phrase does just about anything you want it to.

  24. Hmmm, Chemical and Engineering News.

    I had some thoughts trickling thru my mind the other night about pain thresholds related Biblically to Eve. It is a weird thought for most I’m sure.

    But it popped into my mind and this article prompted the thought again. What if birthing pain was genetically related? I realize this is a stretch, no pun intended.

    Embedded in this article posted by Dr. Dembski is this little jewel,

    The gene Diatchenko’s team studied encodes a neurotransmitter-degrading enzyme called human catechol-O-methyltransferase, or COMT. This enzyme is central to the regulation of pain perception. The COMT gene exists in three common variants, each one consisting of both silent and nonsilent codon changes.

    Depending on which variant a person has, he or she is likely to have low, average, or high pain sensitivity. The researchers found that differences in COMT production derive far more from differences in synonymous codons in the COMT gene than in nonsynonymous ones that lead to amino acid changes.

    Put this together with other recent research(Wnt signals – limb regeneration), the “zipcode” pattern of body placement for cell location, body repair, blood clotting and healing proceses.

    Could there be more series of switches, folds, body mapping that can be manipulated to shut off pain in different regions?

    I know this is way out there – speculative. But this new fidning of pain threshold differences in such unexecpted areas should alert us to the fact that it can be controlled subtly instead of direct medical feeds like local or general anesthesia. And if controllable, then shut off completely in specific regions by a “zipcode” process, or blanket altogether.

    What about a switch or synonomous areas that turn pain off for good or minimize the pain? That is three billion happy people. This eliminates mass doses of pain medication for childbirth sometimes which may possibly harm a child.

    If one exerts a “literal” interpretation on Genesis, pain was not intended for childbirth in the beginning, but after sin. Realize this brings all sorts of arguments to the table. I’m not trying to make any, just asking questions that think on these issues. Like if pain associated with childbirth were a single point mutation or larger? In this case, it appears larger areas of concern. And does that point to design that can be tweaked backwards toward a more “original” design?

    Finally, pain is beneficial. But the find in the article made me think a bit on my original thought of what may be “designed pain”.

  25. As I’ve been following this thread, I couldn’t help but wonder: when computing the reported DNA difference between humans and chimps (somewhere between 1% and 4%), how are SNPs handled in the counting — are they ignored, and the codons considered identical? I suspect this is one area that will be impacted by this new understanding of the “silent” mutations.

    The SNPs account for the 1.5% difference. When indels are added the number goest to 5%. Just a rote comparison of base-pair numbers

    Man 3.4 giga base pairs
    Chimp 3.57 giga base pairs indicate a 6% difference.

    See:
    Genbank

    The difference between pan an homo is about 180,000,000 just based on base pair count, and that’s about 6%. This indicates comparisons of nucleotides that are non-coding. I argue the non-coding 6% need to be accounted for.

    Also, see this article from PNAS:

    Divergence between samples of chimpanze and human DNA is 5% counting indels

    Five chimpanzee bacterial artificial chromosome (BAC) sequences
    (described in GenBank) have been compared with the best matching
    regions of the human genome sequence to assay the amount
    and kind of DNA divergence. The conclusion is the old saw that we
    share 98.5% of our DNA sequence with chimpanzee is probably in
    error. For this sample, a better estimate would be that 95% of the
    base pairs are exactly shared between chimpanzee and human
    DNA. In this sample of 779 kb, the divergence due to base
    substitution is 1.4%, and there is an additional 3.4% difference due
    to the presence of indels. The gaps in alignment are present
    in about equal amounts in the chimp and human sequences.
    They occur equally in repeated and nonrepeated sequences, as
    detected by REPEATMASKER (http:ftp.genome.washington.eduRM
    RepeatMasker.html).

  26. Sal, thank you for the reference to PNAS. In the article it’s clear we are still just beginning to understand the differences between us and chimps

    For example, in the last paragraph the author states, “One interesting observation is that the sequence divergence between chimp and human is quite large, in excess of 20% for a few regions… These observations suggest that complex processes, presumably involving repeated sequences and possible conversion events, may occur that will require detailed study to understand. The uncertainty in the estimate of 3.4% indels on Table 1 cannot be directly evaluated. In the first place, the sample of 779 kb is small, and the variation between the different BACs is large. Further, there may be large gaps that were missed as part of chimpanzee BAC sequences that could not be aligned with the human genome.” Based on this, one could predict that the genomic difference between human and chimp will continue to increase in line with continued study.

    And I loved the closing statement of the article: “Nevertheless, the conclusion is clear that comparison of the DNA sequences of closely related species reflects many events of insertion and deletion. It is the result of a major evolutionary process.” (I suspect the author meant “Darwinian evolutionary process” as opposed to anything remotely teleological.)

    Thanks for all your help!

    Eric

    P.S. I still would like to see any reference that can show definitively whether, for purposes of determining similarity of nucleotide sequences, it is assumed that synonymous codons are considered “identical,” thus showing closer similarity between the genomes being compared. I assume the current paradigm would prefer a smaller difference rather than larger, thus a tendency to ignore SNPs since with our past understanding we “know” that synonymous codons make “absolutely no difference at all” (a real science stopper here!). Thankfully, however, the engineering instincts of many scientists motivate them to still figure out those things that Darwinian theories don’t care to explore.

  27. I actually think I know what is going on with the issue raised in this paper… It would seem that the sequence of codons do two things: -

    1- Code for an amino acid
    2- Code for the angle/orientation of the amino acid.

    The second point would explain why two identical amino acids coded for by two ‘supposedly’ functionally identical codon triplets could result in a different folding pattern in the protein.

    So in short, when the TRNA goes into the ribosome, the codon sequence it has can actually rotate the amino acid it codes for as well as bind to the its relevant amino acid.

    Whether this will happen for all codon – amino acid pairs… dunno.

  28. And one more thing. My guess is that the orientation of the amino acids that exit the ribosome affects the 3D structure that then ensues.

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