Editorial: Noncanonical functions of Aminoacyl-tRNA synthetases
Bibliographic record
Abstract
Editorial on the Research Topic Noncanonical functions of aminoacyl-tRNA synthetasesAminoacyl-tRNA synthetases (aaRS) catalyze the first step of protein synthesis by attaching amino acids to tRNAs.During this key step, aminoacyl-tRNA synthetases further ensure the correct interpretation of the genetic code by providing the ribosome with the building blocks for proteins (Woese et al., 2000).However, this well-studied and strictly conserved "canonical" function of aaRS does not encompass the whole complexity of this ancient protein family.During evolution, aaRS have been co-opted, copied, extended, and mutated to fulfill additional functions (Guo and Schimmel, 2013;Sun et al., 2016;Zhang et al., 2021).In addition, alternatives to aaRS have also been found, as prokaryotes often do not contain a full set of aaRS for all the 20 proteinogenic amino acids that are shared between all living beings.In this issue, the non-canonical functions of aaRS are discussed and showcased across different kingdoms.In addition to the non-canonical use of aaRS, alternative pathways of tRNA aminoacylation are also discussed.Together, they paint a picture of the versatility of aaRS and the creativity of nature in making use of them.Mukai et al. demonstrate alternative pathways to encode cysteine in prokaryotes and find that they are far more widespread than previously assumed.Cysteine incorporation can occur as a two-step mechanism, which has also been described for other amino acids.However, the aminoacylation of tRNAs with, for example, glutamine, relies on the relaxed specificity of the aaRSs which recognizes a chemically very similar amino acid, glutamate.The prokaryote thereby effectively "saves" the addition of a designated aaRS.Cysteine incorporation on the other hand requires a specialized aaRSs, which attaches a phosphoserine to tRNA, which is then modified to a cysteine (Mukai et al., 2021).Mukai et al. explore how common this mode is by using bioinformatical techniques and gain surprising insights into the creativity of interpreting a shared genetic code across species.In contrast, Krahn et al. take the opposite direction.Instead of looking into different ways in which the same amino acid can be attached to a tRNA, they explore how to get the most use out of aaRS, which is by copying them (Krahn et al., 2022).Discussing the most extreme form of co-opting, which is to make a copy and use it for an alternative function, they explore the potential of aaRS-like proteins in alternative functions (or even in the same).AaRS are mostly thought of as single-copy genes to keep evolutionary pressure high, as misacylation
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.029 | 0.018 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".