Details
| Original language | English |
|---|---|
| Article number | 1011918 |
| Journal | PLoS Computational Biology |
| Volume | 20 |
| Issue number | 3 |
| Publication status | Published - 5 Mar 2024 |
Abstract
Processive enzymes like polymerases or ribosomes are often studied in bulk experiments by monitoring time-dependent signals, such as fluorescence time traces. However, due to biomolecular process stochasticity, ensemble signals may lack the distinct features of single-molecule signals. Here, we demonstrate that, under certain conditions, bulk signals from processive reactions can be decomposed to unveil hidden information about individual reaction steps. Using mRNA translation as a case study, we show that decomposing a noisy ensemble signal generated by the translation of mRNAs with more than a few codons is an ill-posed problem, addressable through Tikhonov regularization. We apply our method to the fluorescence signatures of in-vitro translated LepB mRNA and determine codon-position dependent translation rates and corresponding state-specific fluorescence intensities. We find a significant change in fluorescence intensity after the fourth and the fifth peptide bond formation, and show that both codon position and encoded amino acid have an effect on the elongation rate. This demonstrates that our approach enhances the information content extracted from bulk experiments, thereby expanding the range of these time- and cost-efficient methods.
ASJC Scopus subject areas
- Agricultural and Biological Sciences(all)
- Ecology, Evolution, Behavior and Systematics
- Mathematics(all)
- Modelling and Simulation
- Environmental Science(all)
- Ecology
- Biochemistry, Genetics and Molecular Biology(all)
- Molecular Biology
- Biochemistry, Genetics and Molecular Biology(all)
- Genetics
- Neuroscience(all)
- Cellular and Molecular Neuroscience
- Computer Science(all)
- Computational Theory and Mathematics
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In: PLoS Computational Biology, Vol. 20, No. 3, 1011918, 05.03.2024.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Decomposing bulk signals to reveal hidden information in processive enzyme reactions
T2 - A case study in mRNA translation
AU - Haase, Nadin
AU - Holtkamp, Wolf
AU - Christ, Simon
AU - Heinemann, Dag
AU - Rodnina, Marina V.
AU - Rudorf, Sophia
N1 - Publisher Copyright: Copyright: © 2024 Haase et al.
PY - 2024/3/5
Y1 - 2024/3/5
N2 - Processive enzymes like polymerases or ribosomes are often studied in bulk experiments by monitoring time-dependent signals, such as fluorescence time traces. However, due to biomolecular process stochasticity, ensemble signals may lack the distinct features of single-molecule signals. Here, we demonstrate that, under certain conditions, bulk signals from processive reactions can be decomposed to unveil hidden information about individual reaction steps. Using mRNA translation as a case study, we show that decomposing a noisy ensemble signal generated by the translation of mRNAs with more than a few codons is an ill-posed problem, addressable through Tikhonov regularization. We apply our method to the fluorescence signatures of in-vitro translated LepB mRNA and determine codon-position dependent translation rates and corresponding state-specific fluorescence intensities. We find a significant change in fluorescence intensity after the fourth and the fifth peptide bond formation, and show that both codon position and encoded amino acid have an effect on the elongation rate. This demonstrates that our approach enhances the information content extracted from bulk experiments, thereby expanding the range of these time- and cost-efficient methods.
AB - Processive enzymes like polymerases or ribosomes are often studied in bulk experiments by monitoring time-dependent signals, such as fluorescence time traces. However, due to biomolecular process stochasticity, ensemble signals may lack the distinct features of single-molecule signals. Here, we demonstrate that, under certain conditions, bulk signals from processive reactions can be decomposed to unveil hidden information about individual reaction steps. Using mRNA translation as a case study, we show that decomposing a noisy ensemble signal generated by the translation of mRNAs with more than a few codons is an ill-posed problem, addressable through Tikhonov regularization. We apply our method to the fluorescence signatures of in-vitro translated LepB mRNA and determine codon-position dependent translation rates and corresponding state-specific fluorescence intensities. We find a significant change in fluorescence intensity after the fourth and the fifth peptide bond formation, and show that both codon position and encoded amino acid have an effect on the elongation rate. This demonstrates that our approach enhances the information content extracted from bulk experiments, thereby expanding the range of these time- and cost-efficient methods.
UR - http://www.scopus.com/inward/record.url?scp=85187145561&partnerID=8YFLogxK
U2 - 10.1101/2023.05.17.541147
DO - 10.1101/2023.05.17.541147
M3 - Article
C2 - 38442108
VL - 20
JO - PLoS Computational Biology
JF - PLoS Computational Biology
SN - 1553-734X
IS - 3
M1 - 1011918
ER -