Amino Acid and Anticodon Enhance Metabolic Reaction Rates Weakly but Specifically: Genetic Code World

2007 ◽  
Vol 76 (5) ◽  
pp. 053801 ◽  
Author(s):  
Mikio Shimizu
Amino Acids ◽  
2020 ◽  
Author(s):  
Thomas L. Williams ◽  
Debra J. Iskandar ◽  
Alexander R. Nödling ◽  
Yurong Tan ◽  
Louis Y. P. Luk ◽  
...  

AbstractGenetic code expansion is a powerful technique for site-specific incorporation of an unnatural amino acid into a protein of interest. This technique relies on an orthogonal aminoacyl-tRNA synthetase/tRNA pair and has enabled incorporation of over 100 different unnatural amino acids into ribosomally synthesized proteins in cells. Pyrrolysyl-tRNA synthetase (PylRS) and its cognate tRNA from Methanosarcina species are arguably the most widely used orthogonal pair. Here, we investigated whether beneficial effect in unnatural amino acid incorporation caused by N-terminal mutations in PylRS of one species is transferable to PylRS of another species. It was shown that conserved mutations on the N-terminal domain of MmPylRS improved the unnatural amino acid incorporation efficiency up to five folds. As MbPylRS shares high sequence identity to MmPylRS, and the two homologs are often used interchangeably, we examined incorporation of five unnatural amino acids by four MbPylRS variants at two temperatures. Our results indicate that the beneficial N-terminal mutations in MmPylRS did not improve unnatural amino acid incorporation efficiency by MbPylRS. Knowledge from this work contributes to our understanding of PylRS homologs which are needed to improve the technique of genetic code expansion in the future.


Author(s):  
Ashley M Buckle ◽  
Malcolm Buckle

In addition to the canonical loss-of-function mutations, mutations in proteins may additionally result in gain-of-function through the binary activation of cryptic ‘structural capacitance elements’. Our previous bioinformatic analysis allowed us to propose a new mechanism of protein evolution - structural capacitance – that arises via the generation of new elements of microstructure upon mutations that cause a disorder-to-order (DO) transition in previously disordered regions of proteins. Here we propose that the DO transition is a necessary follow-on from expected early codon-anticodon and tRNA acceptor stem-amino acid usage, via the accumulation of structural capacitance elements - reservoirs of disorder in proteins. We develop this argument further to posit that structural capacitance is an inherent consequence of the evolution of the genetic code.


2020 ◽  
Author(s):  
Tin Yau Pang ◽  
Martin J. Lercher

AbstractA substantial fraction of the bacterial cytosol is occupied by catalysts and their substrates. While a higher volume density of catalysts and substrates might boost biochemical fluxes, the resulting molecular crowding can slow down diffusion, perturb the reactions’ Gibbs free energies, and reduce the catalytic efficiency of proteins. Due to these tradeoffs, dry mass density likely possesses an optimum that facilitates maximal cellular growth and that is interdependent on the cytosolic molecule size distribution. Here, we analyse the balanced growth of a model cell with metabolic and ribosomal reactions, accounting systematically for crowding effects on reaction kinetics. We find that changes in cytosolic density affect biochemical efficiency more strongly for ribosomal reactions than for metabolic reactions, which involve much smaller catalysts and reactants. Accordingly, optimal cytosolic density depends on cellular resource allocation into ribosomal vs. metabolic reactions. A shift in the relative contributions of these sectors to the cellular economy explains the 10% difference in the cytosolic density between E. coli bacteria growing in nutrient-rich and -poor environments. We conclude that cytosolic density variation in E. coli is consistent with an optimality principle of cellular efficiency.Significance statementThe cellular cytosol harbours diverse molecules, whose crowding slows down diffusion and perturbs the chemical equilibrium of biochemical reactions. Reaction rates thus depend not only on the reactants themselves, but also on the background density of other molecules; consequently, maximal cell growth requires an optimal density. Here, we simulate a model cell with crowding-adjusted metabolic reaction kinetics. Its cytosol accommodates two types of reactions: metabolic reactions involving small molecules, and protein production reactions involving much larger molecules. These two cellular subsystems have distinct optimal densities, and a shift in their relative contribution to the cellular biomass explains the 10% difference in the cytosolic density between E. coli bacteria growing in nutrient-rich and -poor environments.


2006 ◽  
Vol 37 (1) ◽  
pp. 83-103 ◽  
Author(s):  
Sávio Torres de Farias ◽  
Carlos Henrique Costa Moreira ◽  
Romeu Cardoso Guimarães

2019 ◽  
Vol 35 (14) ◽  
pp. i548-i557 ◽  
Author(s):  
Markus Heinonen ◽  
Maria Osmala ◽  
Henrik Mannerström ◽  
Janne Wallenius ◽  
Samuel Kaski ◽  
...  

AbstractMotivationMetabolic flux balance analysis (FBA) is a standard tool in analyzing metabolic reaction rates compatible with measurements, steady-state and the metabolic reaction network stoichiometry. Flux analysis methods commonly place model assumptions on fluxes due to the convenience of formulating the problem as a linear programing model, while many methods do not consider the inherent uncertainty in flux estimates.ResultsWe introduce a novel paradigm of Bayesian metabolic flux analysis that models the reactions of the whole genome-scale cellular system in probabilistic terms, and can infer the full flux vector distribution of genome-scale metabolic systems based on exchange and intracellular (e.g. 13C) flux measurements, steady-state assumptions, and objective function assumptions. The Bayesian model couples all fluxes jointly together in a simple truncated multivariate posterior distribution, which reveals informative flux couplings. Our model is a plug-in replacement to conventional metabolic balance methods, such as FBA. Our experiments indicate that we can characterize the genome-scale flux covariances, reveal flux couplings, and determine more intracellular unobserved fluxes in Clostridium acetobutylicum from 13C data than flux variability analysis.Availability and implementationThe COBRA compatible software is available at github.com/markusheinonen/bamfa.Supplementary informationSupplementary data are available at Bioinformatics online.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Florian Kaiser ◽  
Sarah Krautwurst ◽  
Sebastian Salentin ◽  
V. Joachim Haupt ◽  
Christoph Leberecht ◽  
...  

1984 ◽  
Vol 14 (1-4) ◽  
pp. 589-596 ◽  
Author(s):  
Daniel Grafstein

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