Very interesting open access paper:
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Random thoughts:
If the authors had complete representation in their screens, then they screened about 10 trillion (give or take an order of magnitude) sequences. They identified three sequence families. Let’s call these three sequences (not true, but about as friendly to the ID argument as I can think of), then that is a frequency in sequence space of about 1 in 3 trillion. To make the typing easier, lets round this to 1 in 10^-13.
To make sure we have enough sequences to get at least one of these, we need about 10^15 individual sequences. That is about 50 micrograms, or 1 nanomole, of RNA. If all of this is in, say, 1 liter of soup, then the molar concentration of the RNA mix is 1 nanomolar.
Thus, if aminoacylation can be generalized to all possible RNA catalysts, then a one liter soup of 1 nM RNA should be enough to have a very diverse range of catalysts.
(Someone please check my numbers!)
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It would be interesting to see how the fitness landscape looks for different amino acids. As far as I could gather they only tested aminoacylation of different ribozymes with Tyrosine. Presumably the fitness landscape for other amino acids would not be identical, and the degree of overlap and connectivity between the aminoacylating functions of ribozymes for different amino acids would also have some implications for how likely it is that other functions can evolve if one function has already been found.
Are some of the valleys in the Tyrosine aminoacylating ribozyme landscape, peaks in the leucine ribozyme landscape, for example?
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Hey, turns out I wasn’t the only one pondering the question I alluded to above. Accidentally discovered this article while looking for something else, and immediately recalled this thread.
The authors of the paper @pnelson linked have been doing work to probe exactly the question I posed above.
In this work, we evaluate the evolutionary potential of self-aminoacylating ribozymes to adopt new amino acid substrates. We previously used in vitro selection and high-throughput sequencing to exhaustively search RNA sequence space (21 nt) for self-aminoacylating ribozymes7. These ribozymes were originally selected to react with biotinyl-Tyr(Me)-oxazolone (BYO), a chemically activated amino acid. The 5(4H)-oxazolones and related carboxyanhydrides can be made abiotically under prebiotically plausible conditions 40-48. Three distinct, evolutionarily unrelated catalytic motifs had been discovered from the exhaustive search. Here we determine the co-option potential of these ribozymes, by measuring the activity of all single- and double- mutants of five ribozymes, representing the three catalytic motifs, for six alternative substrates, using a massively parallel assay (k-Seq7, 49). This assay and related techniques leverage high-throughput sequencing to measure the activity of thousands of candidate sequences in a mixed pool50-53. The six substrates (analogs of tryptophan, phenylalanine, leucine, isoleucine, valine, and methionine) represent a range of sizes and biophysical classes (aromatic, aliphatic, sulfur-containing), as well as supposed early (Leu, Ile, Val) and late (Trp, Phe, Met) incorporations into the genetic code54-58. Our findings indicate extensive opportunities for co-option to incorporate new substrates into the system. In addition, we describe two major by-products of evolution of these ribozymes. First, a positive correlation between activity and specificity was observed, indicating that greater specificity would be a byproduct of selection for greater activity. Second, related ribozymes react with biophysically similar amino acids, suggesting that expansion of the code by co-option would incorporate a biophysically similar amino acid into the system, with error minimization arising as a by-product. Such effects could favor the emergence of a complex biochemical system.
Very interesting read with implications for genetic code evolution.
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Funny coincidence? Literally the exact hypothetical example I pose (“Are some of the valleys in the Tyrosine aminoacylating ribozyme landscape, peaks in the leucine ribozyme landscape, for example?”) is mentioned in the discussion:
While the order in which amino acids were incorporated into the genetic code is a subject of debate, the amino acid substrates tested here include those that are generally believed to be early (L, I, V) and late (W, F, M) additions to the code54-58. Interestingly, the aromatic residues were generally preferred by all ribozyme families. While the original selection employed a tyrosine analog, an analogous selection using the leucine analog did not yield new ribozymes, indicating that this preference may be intrinsic. Such a preference is not surprising based on considerations for intermolecular interactions (e.g., p-p stacking) and is supported by an analysis of amino acid preferences among RNA aptamers evolved in vitro72. Thus, in a plausible scenario, self-aminoacylating RNAs that react with ‘early’ amino acid substrates would have promiscuous activity on ‘late’ substrates, allowing co-option of these ribozymes to incorporate new substrates once they become available.
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Why? Their silly metaphor aside, as the authors note at the end of the abstract, “The frustrated nature of the evolutionary network suggests that chance emergence of a ribozyme motif would be more important than optimization by natural selection.”
Why what?
Yes. I think it shows that different but related functions are very interconnected in ribozyme sequence space. Finding a functional sequence is likely to then also provide a sort of network-access to lots of other useful functions. Once you’ve found one functional thing it becomes a sort of springboard to lots of new discoveries. A lot of evolution appears to have this feature.