Synthetic biology challenges long-held hypotheses in translation, codon bias and transcription

Engineering Saccharomyces cerevisiae for efficient production of recombinant proteins

Saccharomyces cerevisiae is an excellent microbial cell factory for producing valuable recombinant proteins because of its fast growth rate, robustness, biosafety, ease of operability via mature genomic modification technologies, and the presence of a conserved post-translational modification pathway among eukaryotic organisms. However, meeting industrial and market requirements with the current low microbial production of recombinant proteins can be challenging. To address this issue, numerous efforts have been made to enhance the ability of yeast cell factories to efficiently produce proteins. In this review, we provide an overview of recent advances in S. cerevisiae engineering to improve recombinant protein production. This review focuses on the strategies that enhance protein production by regulating transcription through promoter engineering, codon optimization, and expression system optimization. Additionally, we describe modifications to the secretory pathway, including engineered protein translocation, protein folding, glycosylation modification, and vesicle trafficking. Furthermore, we discuss global metabolic pathway optimization and other relevant strategies, such as the disruption of protein degradation, cell wall engineering, and random mutagenesis. Finally, we provide an outlook on the developmental trends in this field, offering insights into future directions for improving recombinant protein production in S. cerevisiae.

The Influence of Competing tRNA Abundance on Translation: Quantifying the Efficiency of Sense Codon Reassignment at Rarely Used Codons

A quantitative understanding of how system composition and molecular properties conspire to determine the fidelity of translation is lacking. Our strategy directs an orthogonal tRNA to directly compete against endogenous tRNAs to decode individual targeted codons in a GFP reporter. Sets of directed sense codon reassignment measurements allow the isolation of particular factors contributing to translational fidelity. In this work, we isolated the effect of tRNA concentration on translational fidelity by evaluating reassignment of the 15 least commonly employed E. coli sense codons. Eight of the rarely used codons are reassigned with greater than 20 % efficiency. Both tRNA abundance and codon demand moderately inversely correlate with reassignment efficiency. Furthermore, the reassignment of rarely used codons does not appear to confer a fitness advantage relative to reassignment of other codons. These direct competition experiments also map potential targets for genetic code expansion. The isoleucine AUA codon is particularly attractive for the incorporation of noncanonical amino acids, with a nonoptimized reassignment efficiency of nearly 70 %.

Generation of a novel TRAIL mutant by proline to arginine substitution based on codon bias and its antitumor effects

TNF ligand superfamily member 10 (TRAIL) is a member of the tumor necrosis factor superfamily. The present study was performed in an effort to increase the expression of soluble (s)TRAIL by rebuilding the gene sequence of TRAIL. Three principles based on the codon bias of Escherichia coli were put forward to design the rebuild strategy. Relying on these three principles, a P7R mutation near the N‑terminal region of sTRAIL, named TRAIL‑Mu, was designed. TRAIL‑Mu was subsequently cloned into the PTWIN1 plasmid and expressed in E. coli BL21 (DE3). Using a high‑level expression system and a three‑step purification method, soluble TRAIL‑Mu protein reached ~90% of total cellular protein and purity was >95%, demonstrating success in overcoming inclusion body formation. The cytotoxic effect of TRAIL‑Mu was evaluated by sulforhodamine B assay in the MD‑MB‑231, A549, NCI‑H460 and L02 cell lines. The results demonstrated that TRAIL‑Mu exerted stronger antitumor effects on TRAIL‑sensitive tumor cell lines, and was able to partially reverse the resistance of a TRAIL‑resistant tumor cell line. In addition, TRAIL‑Mu exhibited no notable biological effects in a normal liver cell line. The novel TRAIL variant generated in the present study may be useful for the mass production of this important protein for therapeutic purposes.

Energetic contribution to both acidity and conformational stability in peptide models

The acidity difference of the amide rotamers has been revised for a large set ofN-acetyl amino acids.

Facile synthesis of N-acyl-aminoacyl-pCpA for preparation of mischarged fully ribo tRNA

Chemical synthesis of N-acyl-aminoacyl-pdCpA and its ligation to tRNA(minus CA) is widely used for the preparation of unnatural aminoacyl-tRNA substrates for ribosomal translation. However, the presence of the unnatural deoxyribose can decrease incorporation yield in translation and there is no straightforward method for chemical synthesis of the natural ribo version. Here, we show that pCpA is surprisingly stable to treatment with strong organic bases provided that anhydrous conditions are used. This allowed development of a facile method for chemical aminoacylation of pCpA. Preparative synthesis of pCpA was also simplified by using t-butyl-dithiomethyl protecting group methodology, and a more reliable pCpA postpurification treatment method was developed. Such aminoacyl-pCpA analogues ligated to tRNA(minus CA) transcripts are highly active in a purified translation system, demonstrating utility of our synthetic method.

Measurement of average decoding rates of the 61 sense codons in vivo

Most amino acids can be encoded by several synonymous codons, which are used at unequal frequencies. The significance of unequal codon usage remains unclear. One hypothesis is that frequent codons are translated relatively rapidly. However, there is little direct, in vivo, evidence regarding codon-specific translation rates. In this study, we generate high-coverage data using ribosome profiling in yeast, analyze using a novel algorithm, and deduce events at the A- and P-sites of the ribosome. Different codons are decoded at different rates in the A-site. In general, frequent codons are decoded more quickly than rare codons, and AT-rich codons are decoded more quickly than GC-rich codons. At the P-site, proline is slow in forming peptide bonds. We also apply our algorithm to short footprints from a different conformation of the ribosome and find strong amino acid-specific (not codon-specific) effects that may reflect interactions with the exit tunnel of the ribosome.

DOI:http://dx.doi.org/10.7554/eLife.03735.001

Genes contain the instructions for making proteins from molecules called amino acids. These instructions are encoded in the order of the four building blocks that make up DNA, which are symbolized by the letters A, T, C, and G. The DNA of a gene is first copied to make a molecule of RNA, and then the letters in the RNA are read in groups of three (called ‘codons’) by a cellular machine called a ribosome. ‘Sense codons’ each specify one amino acid, and the ribosome decodes hundreds or thousands of these codons into a chain of amino acids to form a protein. ‘Stop codons’ do not encode amino acids but instead instruct the ribosome to stop building a protein when the chain is completed.

Most proteins are built from 20 different kinds of amino acid, but there are 61 sense codons. As such, up to six codons can code for the same amino acid. The multiple codons for a single amino acid, however, are not used equally in gene sequences—some are used much more often than others.

Now, Gardin, Yeasmin et al. have instantly halted the on-going processes of decoding genes and building proteins in yeast cells. Codons being translated into amino acids are trapped inside the ribosome; and codons that take the longest to decode are trapped most often. By using a computer algorithm, Gardin, Yeasmin et al. were able to measure just how often each kind of sense codon was trapped inside the ribosome and use this as a measure of how quickly each codon is decoded. The more often a given codon is used in a gene sequence, the less likely it was found to be trapped inside the ribosome—which suggests that these codons are decoded quicker than other codons and pass through the ribosome more quickly. Put another way, it appears that genes tend to use the codons that can be read the fastest.

Certain properties of a codon also affected its decoding speed. Codons with more As and Ts, for example, are decoded faster than codons with more Cs and Gs. Furthermore, whenever a chemically unusual amino acid called proline has to be added to a new protein chain, it slowed down the speed at which the protein was built. The method described by Gardin, Yeasmin et al. for peering into a decoding ribosome may now help future studies that aim to answer other questions about how proteins are built.

DOI:http://dx.doi.org/10.7554/eLife.03735.002

A condition-specific codon optimization approach for improved heterologous gene expression in Saccharomyces cerevisiae

BACKGROUND

Heterologous gene expression is an important tool for synthetic biology that enables metabolic engineering and the production of non-natural biologics in a variety of host organisms. The translational efficiency of heterologous genes can often be improved by optimizing synonymous codon usage to better match the host organism. However, traditional approaches for optimization neglect to take into account many factors known to influence synonymous codon distributions.

RESULTS

Here we define an alternative approach for codon optimization that utilizes systems level information and codon context for the condition under which heterologous genes are being expressed. Furthermore, we utilize a probabilistic algorithm to generate multiple variants of a given gene. We demonstrate improved translational efficiency using this condition-specific codon optimization approach with two heterologous genes, the fluorescent protein-encoding eGFP and the catechol 1,2-dioxygenase gene CatA, expressed in S. cerevisiae. For the latter case, optimization for stationary phase production resulted in nearly 2.9-fold improvements over commercial gene optimization algorithms.

CONCLUSIONS

Codon optimization is now often a standard tool for protein expression, and while a variety of tools and approaches have been developed, they do not guarantee improved performance for all hosts of applications. Here, we suggest an alternative method for condition-specific codon optimization and demonstrate its utility in Saccharomyces cerevisiae as a proof of concept. However, this technique should be applicable to any organism for which gene expression data can be generated and is thus of potential interest for a variety of applications in metabolic and cellular engineering.

Differential translation tunes uneven production of operon-encoded proteins

Clustering of functionally related genes in operons allows for coregulated gene expression in prokaryotes. This is advantageous when equal amounts of gene products are required. Production of protein complexes with an uneven stoichiometry, however, requires tuning mechanisms to generate subunits in appropriate relative quantities. Using comparative genomic analysis, we show that differential translation is a key determinant of modulated expression of genes clustered in operons and that codon bias generally is the best in silico indicator of unequal protein production. Variable ribosome density profiles of polycistronic transcripts correlate strongly with differential translation patterns. In addition, we provide experimental evidence that de novo initiation of translation can occur at intercistronic sites, allowing for differential translation of any gene irrespective of its position on a polycistronic messenger. Thus, modulation of translation efficiency appears to be a universal mode of control in bacteria and archaea that allows for differential production of operon-encoded proteins.

Genetically encoded libraries of nonstandard peptides

The presence of a nonproteinogenic moiety in a nonstandard peptide often improves the biological properties of the peptide. Non-standard peptide libraries are therefore used to obtain valuable molecules for biological, therapeutic, and diagnostic applications. Highly diverse non-standard peptide libraries can be generated by chemically or enzymatically modifying standard peptide libraries synthesized by the ribosomal machinery, using posttranslational modifications. Alternatively, strategies for encoding non-proteinogenic amino acids into the genetic code have been developed for the direct ribosomal synthesis of non-standard peptide libraries. In the strategies for genetic code expansion, non-proteinogenic amino acids are assigned to the nonsense codons or 4-base codons in order to add these amino acids to the universal genetic code. In contrast, in the strategies for genetic code reprogramming, some proteinogenic amino acids are erased from the genetic code and non-proteinogenic amino acids are reassigned to the blank codons. Here, we discuss the generation of genetically encoded non-standard peptide libraries using these strategies and also review recent applications of these libraries to the selection of functional non-standard peptides.