scholarly journals Human Codon Usage: The Genetic Basis of Pathogen Latency

2021 ◽  
Author(s):  
Darja Kanduc
Keyword(s):  
Protein Expression ◽  
Codon Usage ◽  
Genetic Basis ◽  
Codon Optimization ◽  
Quantitative Relationship ◽  
Infectious Agents ◽  
Front Line ◽  
Chronic Infections ◽  
Synonymous Codons ◽  
Definition Of

AbstractInfectious diseases pose two main compelling issues. First, the identification of the molecular factors that allow chronic infections, that is, the often completely asymptomatic coexistence of infectious agents with the human host. Second, the definition of the mechanisms that allow the switch from pathogen dormancy to pathologic (re)activation. Furthering previous studies, the present work (1) analyzes the frequency of occurrence of synonymous codons in coding DNA, that is, codon usage, as a genetic tool that rules protein expression; (2) describes how human codon usage can inhibit protein expression of infectious agents during latency, so that pathogen genes the codon usage of which does not conform to the human codon usage cannot be translated; and (3) frames human codon usage among the front-line instruments of the innate immunity against infections. In parallel, it is shown that, while genetics can account for the molecular basis of pathogen latency, the changes of the quantitative relationship between codon frequencies and isoaccepting tRNAs during cell proliferation offer a biochemical mechanism that explains the pathogen switching to (re)activation. Immunologically, this study warns that using codon optimization methodologies can (re)activate, potentiate, and immortalize otherwise quiescent, asymptomatic pathogens, thus leading to uncontrollable pandemics.

scholarly journals Effects of codon optimization on coagulation factor IX translation and structure: Implications for protein and gene therapies

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Aikaterini Alexaki ◽  
Gaya K. Hettiarachchi ◽  
John C. Athey ◽  
Upendra K. Katneni ◽  
Vijaya Simhadri ◽  
...  
Keyword(s):  
Protein Expression ◽  
Codon Optimization ◽  
Critical Mass ◽  
Coagulation Factor ◽  
Factor Ix ◽  
Gene Therapies ◽  
Synonymous Codons ◽  
Coagulation Factor Ix ◽  
And Function ◽  
The Impact

Abstract Synonymous codons occur with different frequencies in different organisms, a phenomenon termed codon usage bias. Codon optimization, a common term for a variety of approaches used widely by the biopharmaceutical industry, involves synonymous substitutions to increase protein expression. It had long been presumed that synonymous variants, which, by definition, do not alter the primary amino acid sequence, have no effect on protein structure and function. However, a critical mass of reports suggests that synonymous codon variations may impact protein conformation. To investigate the impact of synonymous codons usage on protein expression and function, we designed an optimized coagulation factor IX (FIX) variant and used multiple methods to compare its properties to the wild-type FIX upon expression in HEK293T cells. We found that the two variants differ in their conformation, even when controlling for the difference in expression levels. Using ribosome profiling, we identified robust changes in the translational kinetics of the two variants and were able to identify a region in the gene that may have a role in altering the conformation of the protein. Our data have direct implications for codon optimization strategies, for production of recombinant proteins and gene therapies.

scholarly journals Optimization of Codon Usage Enhances the Immunogenicity of a DNA Vaccine Encoding Mycobacterial Antigen Ag85B

2005 ◽  
Vol 73 (9) ◽  
pp. 5666-5674 ◽  
Author(s):  
Hyun-Jeong Ko ◽  
Sung-Youl Ko ◽  
Yeon-Jeong Kim ◽  
Eun-Gae Lee ◽  
Sang-Nae Cho ◽  
...  
Keyword(s):  
Protein Expression ◽  
Codon Usage ◽  
Dna Vaccine ◽  
Codon Optimization ◽  
Cytotoxic T Cell ◽  
Mycobacterial Antigen ◽  
T Cell Immune Responses ◽  
Aerosol Infection

ABSTRACT In spite of its many other benefits, DNA vaccine is limited in its application by its insufficient immunogenicity. One promising approach for enhancing its immunogenicity is to maximize its expression in the immunized host. In the current study, we investigated whether codon optimization of the mycobacterial antigen Ag85B gene could enhance the expression and immunogenicity of the Ag85B DNA vaccine. We generated a synthetic humanized Ag85B (hAg85B) gene in which codon usage was optimized for expression in human cells. DNA plasmids with codon-optimized hAg85B increased the level of protein expression in vitro and in vivo. DNA vaccine with hAg85B induced stronger Th1-like and cytotoxic T-cell immune responses in BALB/c mice and generated higher protective immunity in a BALB/c mouse model of Mycobacterium tuberculosis aerosol infection than did the DNA vaccine with wild-type Ag85B. Therefore, our results suggest that codon optimization of mycobacterial antigens (e.g., Ag85B) could improve protein expression and thereby enhance the immunogenicity of DNA vaccines against M. tuberculosis.

scholarly journals Codon pair optimization (CPO): a software tool for synthetic gene design based on codon pair bias to improve the expression of recombinant proteins in Pichia pastoris

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Yide Huang ◽  
Ting Lin ◽  
Lingfang Lu ◽  
Fan Cai ◽  
Jie Lin ◽  
...  
Keyword(s):  
Pichia Pastoris ◽  
Protein Expression ◽  
Codon Usage ◽  
Codon Optimization ◽  
Software Tool ◽  
Expression Levels ◽  
Gene Design ◽  
Codon Pair Bias ◽  
Codon Pair ◽  
Synthetic Gene Design

Abstract Background Codon optimization is a common method to improve protein expression levels in Pichia pastoris and the current strategy is to replace rare codons with preferred codons to match the codon usage bias. However, codon-pair contexts have a profound effect on translation efficiency by influencing both translational elongation rates and accuracy. Until now, it remains untested whether optimized genes based on codon pair bias results in higher protein expression levels compared to codon usage bias. Results In this study, an algorithm based on dynamic programming was introduced to develop codon pair optimization (CPO) which is a software tool to provide simple and efficient codon pair optimization for synthetic gene design in Pichia pastoris. Two reporters (MT1-MMP E2C6 and ADAM17 A9B8 scFvs) were employed to test the effects of codon pair bias and CPO optimization on their protein expression levels. Four variants of MT1-MMP E2C6 and ADAM17 A9B8 for each were generated, one variant with the best codon-pair context, one with the worst codon-pair context, one with unbiased codon-pair context, and another optimized based on codon usage. The expression levels of variants with the worst codon-pair context were almost undetectable by Western blot and the variants with the best codon-pair context were expressed well. The expression levels on MT1-MMP E2C6 and ADAM17 A9B8 were more than five times and seven times higher in the optimized sequences based on codon-pair context compared to that based on codon usage, respectively. The results indicated that the codon-pair context-based codon optimization is more effective in enhancing expression of protein in Pichia pastoris. Conclusions Codon-pair context plays an important role on the protein expression in Pichia pastoris. The codon pair optimization (CPO) software developed in this study efficiently improved the protein expression levels of exogenous genes in Pichia pastoris, suggesting gene design based on codon pair bias is an alternative strategy for high expression of recombinant proteins in Pichia pastoris.

scholarly journals ICOR: Improving codon optimization with recurrent neural networks

2021 ◽  
Author(s):  
Rishab Jain ◽  
Aditya Jain ◽  
Elizabeth Mauro ◽  
Kevin LeShane ◽  
Douglas Densmore
Keyword(s):  
Escherichia Coli ◽  
Amino Acids ◽  
Heterologous Expression ◽  
Codon Usage ◽  
Dna Sequences ◽  
Codon Optimization ◽  
Optimization Techniques ◽  
Codon Adaptation Index ◽  
Synonymous Codons ◽  
Adaptation Index

In protein sequences—as there are 61 sense codons but only 20 standard amino acids—most amino acids are encoded by more than one codon. Although such synonymous codons do not alter the encoded amino acid sequence, their selection can dramatically affect the expression of the resulting protein. Codon optimization of synthetic DNA sequences is important for heterologous expression. However, existing solutions are primarily based on choosing high-frequency codons only, neglecting the important effects of rare codons. In this paper, we propose a novel recurrent-neural-network based codon optimization tool, ICOR, that aims to learn codon usage bias on a genomic dataset of Escherichia coli. We compile a dataset of over 7,000 non-redundant, high-expression, robust genes which are used for deep learning. The model uses a bidirectional long short-term memory-based architecture, allowing for the sequential context of codon usage in genes to be learned. Our tool can predict synonymous codons for synthetic genes toward optimal expression in Escherichia coli. We demonstrate that sequential context achieved via RNN may yield codon selection that is more similar to the host genome, therefore improving protein expression more than frequency-based approaches. ICOR is evaluated on 1,481 Escherichia coli genes as well as a benchmark set of 40 select DNA sequences whose heterologous expression has been previously characterized. ICOR's performance across five metrics is compared to that of five different codon optimization techniques. The codon adaptation index -- a metric indicative of high real-world expression -- was utilized as the primary benchmark in this study. ICOR is shown to improve the codon adaptation index by 41.69% and 17.25% compared to the original and Genscript's GenSmart-optimized sequences, respectively. Our tool is provided as an open-source software package that includes the benchmark set of sequences used in this study.

The effect of expression levels on codon usage inPlasmodium falciparum

Parasitology ◽  
2004 ◽  
Vol 128 (3) ◽  
pp. 245-251 ◽  
Author(s):  
L. PEIXOTO ◽  
V. FERNÁNDEZ ◽  
H. MUSTO
Keyword(s):  
Amino Acids ◽  
Plasmodium Falciparum ◽  
Natural Selection ◽  
Codon Usage ◽  
Complete Sequence ◽  
Expression Data ◽  
Expression Levels ◽  
Synonymous Codons ◽  
Translational Selection ◽  
Highly Expressed Genes

The usage of alternative synonymous codons in the completely sequenced, extremely A+T-rich parasitePlasmodium falciparumwas studied. Confirming previous studies obtained with less than 3% of the total genes recently described, we found that A- and U-ending triplets predominate but translational selection increases the frequency of a subset of codons in highly expressed genes. However, some new results come from the analysis of the complete sequence. First, there is more variation in GC3 than previously described; second, the effect of natural selection acting at the level of translation has been analysed with real expression data at 4 different stages and third, we found that highly expressed proteins increment the frequency of energetically less expensive amino acids. The implications of these results are discussed.

scholarly journals Codon usage bias creates a ramp of hydrogen bonding at the 5′-end in prokaryotic ORFeomes

2019 ◽  
Author(s):  
Juan C. Villada ◽  
Maria F. Duran ◽  
Patrick K. H. Lee
Keyword(s):  
Hydrogen Bonding ◽  
Codon Usage ◽  
Codon Usage Bias ◽  
Translation Efficiency ◽  
Molecular Processes ◽  
Molecular Feature ◽  
Web Based ◽  
Synonymous Codons ◽  
Double Stranded Dna ◽  
Codon Positions

Codon usage bias exerts control over a wide variety of molecular processes. The positioning of synonymous codons within coding sequences (CDSs) dictates protein expression by mechanisms such as local translation efficiency, mRNA Gibbs free energy, and protein co-translational folding. In this work, we explore how codon variants affect the position-dependent content of hydrogen bonding, which in turn influences energy requirements for unwinding double-stranded DNA. By analyzing over 14,000 bacterial, archaeal, and fungal ORFeomes, we found that Bacteria and Archaea exhibit an exponential ramp of hydrogen bonding at the 5′-end of CDSs, while a similar ramp was not found in Fungi. The ramp develops within the first 20 codon positions in prokaryotes, eventually reaching a steady carrying capacity of hydrogen bonding that does not differ from Fungi. Selection against uniformity tests proved that selection acts against synonymous codons with high content of hydrogen bonding at the 5′-end of prokaryotic ORFeomes. Overall, this study provides novel insights into the molecular feature of hydrogen bonding that is governed by the genetic code at the 5′-end of CDSs. A web-based application to analyze the position-dependent hydrogen bonding of ORFeomes has been developed and is publicly available (https://juanvillada.shinyapps.io/hbonds/).

scholarly journals Analysis of computational codon usage models and their association with translationally slow codons

2020 ◽  
Author(s):  
Gabriel Wright ◽  
Anabel Rodriguez ◽  
Jun Li ◽  
Patricia L. Clark ◽  
Tijana Milenković ◽  
...  
Keyword(s):  
Codon Usage ◽  
Computational Models ◽  
Selective Pressure ◽  
Synonymous Codon ◽  
Ground Truth ◽  
Protein Translation ◽  
Weak Correlation ◽  
Experimental Conditions ◽  
Synonymous Codons ◽  
Genome Wide

AbstractImproved computational modeling of protein translation rates, including better prediction of where translational slowdowns along an mRNA sequence may occur, is critical for understanding co-translational folding. Because codons within a synonymous codon group are translated at different rates, many computational translation models rely on analyzing synonymous codons. Some models rely on genome-wide codon usage bias (CUB), believing that globally rare and common codons are the most informative of slow and fast translation, respectively. Others use the CUB observed only in highly expressed genes, which should be under selective pressure to be translated efficiently (and whose CUB may therefore be more indicative of translation rates). No prior work has analyzed these models for their ability to predict translational slowdowns. Here, we evaluate five models for their association with slowly translated positions as denoted by two independent ribosome footprint (RFP) count experiments from S. cerevisiae, because RFP data is often considered as a “ground truth” for translation rates across mRNA sequences. We show that all five considered models strongly associate with the RFP data and therefore have potential for estimating translational slowdowns. However, we also show that there is a weak correlation between RFP counts for the same genes originating from independent experiments, even when their experimental conditions are similar. This raises concerns about the efficacy of using current RFP experimental data for estimating translation rates and highlights a potential advantage of using computational models to understand translation rates instead.

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