A computational screen for alternative genetic codes in over 250,000 genomes
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Evaluation Summary:
The Codetta method developed by Shulgina and Eddy is a powerful approach for inferring codon reassignment by comparative analysis of bacterial and archaeal genomes. Given the rapid advances of genomic and metagenomic sequencing, this will be an important tool for elucidating the genetic codes employed by prokaryotes.
(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)
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Abstract
The genetic code has been proposed to be a ‘frozen accident,’ but the discovery of alternative genetic codes over the past four decades has shown that it can evolve to some degree. Since most examples were found anecdotally, it is difficult to draw general conclusions about the evolutionary trajectories of codon reassignment and why some codons are affected more frequently. To fill in the diversity of genetic codes, we developed Codetta, a computational method to predict the amino acid decoding of each codon from nucleotide sequence data. We surveyed the genetic code usage of over 250,000 bacterial and archaeal genome sequences in GenBank and discovered five new reassignments of arginine codons (AGG, CGA, and CGG), representing the first sense codon changes in bacteria. In a clade of uncultivated Bacilli, the reassignment of AGG to become the dominant methionine codon likely evolved by a change in the amino acid charging of an arginine tRNA. The reassignments of CGA and/or CGG were found in genomes with low GC content, an evolutionary force that likely helped drive these codons to low frequency and enable their reassignment.
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Evaluation Summary:
The Codetta method developed by Shulgina and Eddy is a powerful approach for inferring codon reassignment by comparative analysis of bacterial and archaeal genomes. Given the rapid advances of genomic and metagenomic sequencing, this will be an important tool for elucidating the genetic codes employed by prokaryotes.
(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)
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Reviewer #1 (Public Review):
The genetic code is not a "universal code", but alters in some organisms and organelles. Shulgina and Eddy developped a computational method, termed Codetta, to predict genetic code alteration from the input nucleotide sequences using a probabilistic modeling approach. The basic idea is not novel, yet, the present model differed from previous approaches by taking advantage of the extensive profile HMMs from the Pfam database. Codetta works fairly well in assigning and detecting possible codon reassignment in archaeal and bacterial genome sequences. This bioinformatic prediction should provide a plausible starting point for further experimental validations. Generally, this reviewer finds the research content presented here is well conducted and well written.
Major comments:
In the Introduction, the authors …
Reviewer #1 (Public Review):
The genetic code is not a "universal code", but alters in some organisms and organelles. Shulgina and Eddy developped a computational method, termed Codetta, to predict genetic code alteration from the input nucleotide sequences using a probabilistic modeling approach. The basic idea is not novel, yet, the present model differed from previous approaches by taking advantage of the extensive profile HMMs from the Pfam database. Codetta works fairly well in assigning and detecting possible codon reassignment in archaeal and bacterial genome sequences. This bioinformatic prediction should provide a plausible starting point for further experimental validations. Generally, this reviewer finds the research content presented here is well conducted and well written.
Major comments:
In the Introduction, the authors extensively review historical findings of non-stardard genetic codes. In my point of view, however, tRNA modifications play a major roles in reassigning the genetic code. It would be good to revise the introductory part including a role of tRNA modification.
The authors first validate Codetta's performance by predicting the codon decoding of 462 yeast species. Among them, the authors further analyzed S. malanga in which two tRNAs possibly responsible for Ser and Leu are encoded. They just confirm expression and aminoacylation by acid-urea Northern blotting, but they did not demonstrate they are actually Ser-tRNA and Leu-tRNA. To determine the species of amino acid attached to a specific tRNA, there are several methods. After deacylation reaction, total tRNA can be charged with Ser or Leu in the presence of S100 fraction of cell lysate. Then, you can detect the acylated band of the target tRNA by acid-urea northern blotting. Otherwise, MS-based proteomic analysis of cell lysate would be much easier to demonstrate the dual assignment in this yeast species.
In general, MetRS strictly recognizes anticodon sequence of tRNAMet for methionylation. If the authors' hypothesis is true, the anticodon-recognition domains of MetRSs in these species might be different from those of E. coli MetRS. It would be worth investigating and discussing to support their speculation.
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Reviewer #2 (Public Review):
There are many known cases of small variations in the genetic code where one or more codons have bee reassigned in a particular group of organisms. This paper gives a method for scanning genome data to identify cases where a codon has been reassigned. It is tested by comparison with known code variants and also shown to identify several previously unknown cases. It promises to be a useful tool in the future.
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