Zusammenfassung: | |
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.
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Lizenzbestimmungen: | CC BY 4.0 Unported - https://creativecommons.org/licenses/by/4.0 |
Publikationstyp: | Article |
Publikationsstatus: | publishedVersion |
Erstveröffentlichung: | 2024 |
Schlagwörter (englisch): | Codon, Fluorescence, Protein Biosynthesis, Ribosomes, RNA, Messenger, Enzymes, Signal processing, amino acid, guanosine triphosphatase, messenger RNA, transfer RNA, messenger RNA, Biomolecular process, Case-studies, Enzyme reaction, Fluorescence intensities, Hidden information, Monitoring time, Single molecule, Stochasticity, Time trace, Time-dependent signals, biochemical analysis, biochemical reaction, biomolecular process stochasticity, chromophore assisted light inactivation, codon position, codon usage, cost effectiveness analysis, decomposing bulk signal, elongation rate, ensemble fluorescence signature, enzyme mechanism, Escherichia coli, feasibility study, fluorescence analysis, fluorescence intensity, fluorescence signature, fluorescence signature decomposition, growth, hidden information, hydrolysis, kinetics, least square analysis, magnitude estimation method, Markov chain, model parameterization, molecular biology, noise, probability, regularization parameters, thermal fluctuation, time dependent signal, transition rate, translation dynamics, translation elongation cycle, codon, fluorescence, genetics, metabolism, protein synthesis, ribosome, Fluorescence |
Fachliche Zuordnung (DDC): | 570 | Biowissenschaften, Biologie, 004 | Informatik, 610 | Medizin, Gesundheit |
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