An empirical model of aminoacylation kinetics for E. coli class I and II aminoacyl tRNA synthetases.
Efficient functioning of the prokaryotic translational system depends on a steady supply of aminoacylated tRNAs to be delivered to translating ribosomes via ternary complex. As such, tRNA synthetases play a crucial role in maintaining efficient and accurate translation in the cell, as they are respo...
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Public Library of Science (PLoS)
2025-08-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://doi.org/10.1371/journal.pcbi.1013353 |
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| author | Eric C Dykeman |
| author_facet | Eric C Dykeman |
| author_sort | Eric C Dykeman |
| collection | DOAJ |
| description | Efficient functioning of the prokaryotic translational system depends on a steady supply of aminoacylated tRNAs to be delivered to translating ribosomes via ternary complex. As such, tRNA synthetases play a crucial role in maintaining efficient and accurate translation in the cell, as they are responsible for aminoacylating the correct amino acid to its corresponding tRNA. Moreover, the kinetic rate at which they perform this reaction will dictate the overall rate of supply of aminoacylated tRNAs to the ribosome and will have consequences for the average translational speed of ribosomes in the cell. In this work, I develop an empirical kinetic model for the 20 aminoacyl tRNA synthetase enzymes in E. coli enabling the study of the effects of tRNA charging dynamics on translational efficiency. The model is parametrised based on in vitro experimental measurements of substrate Km and kcat values for both pyrophosphate exchange and aminoacylation. The model also reproduces the burst kinetics observed in class I enzymes and the transfer rates measured in single turnover experiments. Stochastic simulation of in vivo translation shows the kinetic model is able to support the tRNA charging demand resulting from translation in exponentially growing E. coli cells at a variety of different doubling times. This work provides a basis for the theoretical study of the amino acid starvation and the stringent response, as well as the complex behaviour of tRNA charging and translational dynamics in response to cellular stresses. |
| format | Article |
| id | doaj-art-7f2ae189936e49b5af7302cb25fb703b |
| institution | Kabale University |
| issn | 1553-734X 1553-7358 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj-art-7f2ae189936e49b5af7302cb25fb703b2025-08-26T05:30:55ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582025-08-01218e101335310.1371/journal.pcbi.1013353An empirical model of aminoacylation kinetics for E. coli class I and II aminoacyl tRNA synthetases.Eric C DykemanEfficient functioning of the prokaryotic translational system depends on a steady supply of aminoacylated tRNAs to be delivered to translating ribosomes via ternary complex. As such, tRNA synthetases play a crucial role in maintaining efficient and accurate translation in the cell, as they are responsible for aminoacylating the correct amino acid to its corresponding tRNA. Moreover, the kinetic rate at which they perform this reaction will dictate the overall rate of supply of aminoacylated tRNAs to the ribosome and will have consequences for the average translational speed of ribosomes in the cell. In this work, I develop an empirical kinetic model for the 20 aminoacyl tRNA synthetase enzymes in E. coli enabling the study of the effects of tRNA charging dynamics on translational efficiency. The model is parametrised based on in vitro experimental measurements of substrate Km and kcat values for both pyrophosphate exchange and aminoacylation. The model also reproduces the burst kinetics observed in class I enzymes and the transfer rates measured in single turnover experiments. Stochastic simulation of in vivo translation shows the kinetic model is able to support the tRNA charging demand resulting from translation in exponentially growing E. coli cells at a variety of different doubling times. This work provides a basis for the theoretical study of the amino acid starvation and the stringent response, as well as the complex behaviour of tRNA charging and translational dynamics in response to cellular stresses.https://doi.org/10.1371/journal.pcbi.1013353 |
| spellingShingle | Eric C Dykeman An empirical model of aminoacylation kinetics for E. coli class I and II aminoacyl tRNA synthetases. PLoS Computational Biology |
| title | An empirical model of aminoacylation kinetics for E. coli class I and II aminoacyl tRNA synthetases. |
| title_full | An empirical model of aminoacylation kinetics for E. coli class I and II aminoacyl tRNA synthetases. |
| title_fullStr | An empirical model of aminoacylation kinetics for E. coli class I and II aminoacyl tRNA synthetases. |
| title_full_unstemmed | An empirical model of aminoacylation kinetics for E. coli class I and II aminoacyl tRNA synthetases. |
| title_short | An empirical model of aminoacylation kinetics for E. coli class I and II aminoacyl tRNA synthetases. |
| title_sort | empirical model of aminoacylation kinetics for e coli class i and ii aminoacyl trna synthetases |
| url | https://doi.org/10.1371/journal.pcbi.1013353 |
| work_keys_str_mv | AT ericcdykeman anempiricalmodelofaminoacylationkineticsforecoliclassiandiiaminoacyltrnasynthetases AT ericcdykeman empiricalmodelofaminoacylationkineticsforecoliclassiandiiaminoacyltrnasynthetases |