%MinMax: A versatile tool for calculating and comparing synonymous codon usage and its impact on protein folding

Profiling expression strategies for a type III polyketide synthase in a lysate-based, cell-free system

Some of the most metabolically diverse species of bacteria (e.g., Actinobacteria) have higher GC content in their DNA, differ substantially in codon usage, and have distinct protein folding environments compared to tractable expression hosts like Escherichia coli. Consequentially, expressing biosynthetic gene clusters (BGCs) from these bacteria in E. coli often results in a myriad of unpredictable issues with regard to protein expression and folding, delaying the biochemical characterization of new natural products. Current strategies to achieve soluble, active expression of these enzymes in tractable hosts can be a lengthy trial-and-error process. Cell-free expression (CFE) has emerged as a valuable expression platform as a testbed for rapid prototyping expression parameters. Here, we use a type III polyketide synthase from Streptomyces griseus, RppA, which catalyzes the formation of the red pigment flaviolin, as a reporter to investigate BGC refactoring techniques. We applied a library of constructs with different combinations of promoters and rppA coding sequences to investigate the synergies between promoter and codon usage. Subsequently, we assess the utility of cell-free systems for prototyping these refactoring tactics prior to their implementation in cells. Overall, codon harmonization improves natural product synthesis more than traditional codon optimization across cell-free and cellular environments. More importantly, the choice of coding sequences and promoters impact protein expression synergistically, which should be considered for future efforts to use CFE for high-yield protein expression. The promoter strategy when applied to RppA was not completely correlated with that observed with GFP, indicating that different promoter strategies should be applied for different proteins. In vivo experiments suggest that there is correlation, but not complete alignment between expressing in cell free and in vivo. Refactoring promoters and/or coding sequences via CFE can be a valuable strategy to rapidly screen for catalytically functional production of enzymes from BCGs, which advances CFE as a tool for natural product research.

Codon-optimization in gene therapy: promises, prospects and challenges

Codon optimization has evolved to enhance protein expression efficiency by exploiting the genetic code's redundancy, allowing for multiple codon options for a single amino acid. Initially observed in E. coli, optimal codon usage correlates with high gene expression, which has propelled applications expanding from basic research to biopharmaceuticals and vaccine development. The method is especially valuable for adjusting immune responses in gene therapies and has the potenial to create tissue-specific therapies. However, challenges persist, such as the risk of unintended effects on protein function and the complexity of evaluating optimization effectiveness. Despite these issues, codon optimization is crucial in advancing gene therapeutics. This study provides a comprehensive review of the current metrics for codon-optimization, and its practical usage in research and clinical applications, in the context of gene therapy.

Modifications of the 5' region of the CASPONTM tag's mRNA further enhance soluble recombinant protein production in Escherichia coli

BACKGROUND

Escherichia coli is one of the most commonly used host organisms for the production of biopharmaceuticals, as it allows for cost-efficient and fast recombinant protein expression. However, challenging proteins are often produced with low titres or as inclusion bodies, and the manufacturing process needs to be developed individually for each protein. Recently, we developed the CASPONTM technology, a generic fusion tag-based platform process for high-titer soluble expression including a standardized downstream processing and highly specific enzymatic cleavage of the fusion tag. To assess potential strategies for further improvement of the N-terminally fused CASPONTM tag, we modified the 5'UTR and 5' region of the tag-coding mRNA to optimize the ribosome-mRNA interactions.

RESULTS

In the present work, we found that by modifying the 5'UTR sequence of a pET30acer plasmid-based system, expression of the fusion protein CASPONTM-tumour necrosis factor α was altered in laboratory-scale carbon-limited fed-batch cultivations, but no significant increase in expression titre was achieved. Translation efficiency was highest for a construct carrying an expression enhancer element and additionally possessing a very favourable interaction energy between ribosome and mRNA (∆Gtotal). However, a construct with comparatively low transcriptional efficiency, which lacked the expression enhancer sequence and carried the most favourable ∆Gtotal tested, led to the highest recombinant protein formation alongside the reference pET30a construct. Furthermore, we found, that by introducing synonymous mutations within the nucleotide sequence of the T7AC element of the CASPONTM tag, utilizing a combination of rare and non-rare codons, the free folding energy of the nucleotides at the 5' end (-4 to + 37) of the transcript encoding the CASPONTM tag increased by 6 kcal/mol. Surprisingly, this new T7ACrare variant led to improved recombinant protein titres by 1.3-fold up to 5.3-fold, shown with three industry-relevant proteins in lab-scale carbon limited fed-batch fermentations under industrially relevant conditions.

CONCLUSIONS

This study reveals some of the complex interdependencies between the ribosome and mRNA that govern recombinant protein expression. By modifying the 5'UTR to obtain an optimized interaction energy between the mRNA and the ribosome (ΔGtotal), transcript levels were changed, highlighting the different translation efficiencies of individual transcripts. It was shown that the highest recombinant titre was not obtained by the construct with the most efficient translation but by a construct with a generally high transcript amount coupled with a favourable ΔGtotal. Furthermore, an unexpectedly high potential to enhance expression by introducing silent mutations including multiple rare codons into the 5'end of the CAPONTM tag's mRNA was identified. Although the titres of the fusion proteins were dramatically increased, no formation of inclusion bodies or negative impact on cell growth was observed. We hypothesize that the drastic increase in titre is most likely caused by better ribosomal binding site accessibility. Our study, which demonstrates the influence of changes in ribosome-mRNA interactions on protein expression under industrially relevant production conditions, opens the door to the applicability of the new T7ACrare tag in biopharmaceutical industry using the CASPONTM platform process.

Profiling Expression Strategies for a Type III Polyketide Synthase in a Lysate-Based, Cell-free System

Some of the most metabolically diverse species of bacteria (e.g., Actinobacteria) have higher GC content in their DNA, differ substantially in codon usage, and have distinct protein folding environments compared to tractable expression hosts like Escherichia coli. Consequentially, expressing biosynthetic gene clusters (BGCs) from these bacteria in E. coli frequently results in a myriad of unpredictable issues with protein expression and folding, delaying the biochemical characterization of new natural products. Current strategies to achieve soluble, active expression of these enzymes in tractable hosts, such as BGC refactoring, can be a lengthy trial-and-error process. Cell-free expression (CFE) has emerged as 1) a valuable expression platform for enzymes that are challenging to synthesize in vivo, and as 2) a testbed for rapid prototyping that can improve cellular expression. Here, we use a type III polyketide synthase from Streptomyces griseus, RppA, which catalyzes the formation of the red pigment flaviolin, as a reporter to investigate BGC refactoring techniques. We synergistically tune promoter and codon usage to improve flaviolin production from cell-free expressed RppA. We then assess the utility of cell-free systems for prototyping these refactoring tactics prior to their implementation in cells. Overall, codon harmonization improves natural product synthesis more than traditional codon optimization across cell-free and cellular environments. Refactoring promoters and/or coding sequences via CFE can be a valuable strategy to rapidly screen for catalytically functional production of enzymes from BCGs. By showing the coordinators between CFE versus in vivo expression, this work advances CFE as a tool for natural product research.

An exploratory in silico comparison of open-source codon harmonization tools

BACKGROUND

Not changing the native constitution of genes prior to their expression by a heterologous host can affect the amount of proteins synthesized as well as their folding, hampering their activity and even cell viability. Over the past decades, several strategies have been developed to optimize the translation of heterologous genes by accommodating the difference in codon usage between species. While there have been a handful of studies assessing various codon optimization strategies, to the best of our knowledge, no research has been performed towards the evaluation and comparison of codon harmonization algorithms. To highlight their importance and encourage meaningful discussion, we compared different open-source codon harmonization tools pertaining to their in silico performance, and we investigated the influence of different gene-specific factors.

RESULTS

In total, 27 genes were harmonized with four tools toward two different heterologous hosts. The difference in %MinMax values between the harmonized and the original sequences was calculated (ΔMinMax), and statistical analysis of the obtained results was carried out. It became clear that not all tools perform similarly, and the choice of tool should depend on the intended application. Almost all biological factors under investigation (GC content, RNA secondary structures and choice of heterologous host) had a significant influence on the harmonization results and thus must be taken into account. These findings were substantiated using a validation dataset consisting of 8 strategically chosen genes.

CONCLUSIONS

Due to the size of the dataset, no complex models could be developed. However, this initial study showcases significant differences between the results of various codon harmonization tools. Although more elaborate investigation is needed, it is clear that biological factors such as GC content, RNA secondary structures and heterologous hosts must be taken into account when selecting the codon harmonization tool.

In silico methods for predicting functional synonymous variants

Single nucleotide variants (SNVs) contribute to human genomic diversity. Synonymous SNVs are previously considered to be "silent," but mounting evidence has revealed that these variants can cause RNA and protein changes and are implicated in over 85 human diseases and cancers. Recent improvements in computational platforms have led to the development of numerous machine-learning tools, which can be used to advance synonymous SNV research. In this review, we discuss tools that should be used to investigate synonymous variants. We provide supportive examples from seminal studies that demonstrate how these tools have driven new discoveries of functional synonymous SNVs.

Synonymous and Nonsynonymous Substitutions in Dictyostelium discoideum Ammonium Transporter amtA Are Necessary for Functional Complementation in Saccharomyces cerevisiae

Ammonium transporters are present in all three domains of life. They have undergone extensive horizontal gene transfer (HGT), gene duplication, and functional diversification and therefore offer an excellent paradigm to study protein evolution. We attempted to complement a mep1Δmep2Δmep3Δ strain of Saccharomyces cerevisiae (triple-deletion strain), which otherwise cannot grow on ammonium as a sole nitrogen source at concentrations of <3 mM, with amtA of Dictyostelium discoideum, an orthologue of S. cerevisiae MEP2. We observed that amtA did not complement the triple-deletion strain of S. cerevisiae for growth on low-ammonium medium. We isolated two mutant derivatives of amtA (amtA M1 and amtA M2) from a PCR-generated mutant plasmid library that complemented the triple-deletion strain of S. cerevisiae. amtA M1 bears three nonsynonymous and two synonymous substitutions, which are necessary for its functionality. amtA M2 bears two nonsynonymous substitutions and one synonymous substitution, all of which are necessary for functionality. Interestingly, AmtA M1 transports ammonium but does not confer methylamine toxicity, while AmtA M2 transports ammonium and confers methylamine toxicity, demonstrating functional diversification. Preliminary biochemical analyses indicated that the mutants differ in their conformations as well as their mechanisms of ammonium transport. These intriguing results clearly point out that protein evolution cannot be fathomed by studying nonsynonymous and synonymous substitutions in isolation. The above-described observations have significant implications for various facets of biological processes and are discussed in detail. IMPORTANCE Functional diversification following gene duplication is one of the major driving forces of protein evolution. While the role of nonsynonymous substitutions in the functional diversification of proteins is well recognized, knowledge of the role of synonymous substitutions in protein evolution is in its infancy. Using functional complementation, we isolated two functional alleles of the D. discoideum ammonium transporter gene (amtA), which otherwise does not function in S. cerevisiae as an ammonium transporters. One of them is an ammonium transporter, while the other is an ammonium transporter that also confers methylammonium (ammonium analogue) toxicity, suggesting functional diversification. Surprisingly, both alleles require a combination of synonymous and nonsynonymous substitutions for their functionality. These results bring out a hitherto-unknown pathway of protein evolution and pave the way for not only understanding protein evolution but also interpreting single nucleotide polymorphisms (SNPs).

Implementing computational methods in tandem with synonymous gene recoding for therapeutic development

Synonymous gene recoding, the substitution of synonymous variants into the genetic sequence, has been used to overcome many production limitations in therapeutic development. However, the safety and efficacy of recoded therapeutics can be difficult to evaluate because synonymous codon substitutions can result in subtle, yet impactful changes in protein features and require sensitive methods for detection. Given that computational approaches have made significant leaps in recent years, we propose that machine-learning (ML) tools may be leveraged to assess gene-recoded therapeutics and foresee an opportunity to adapt codon contexts to enhance some powerful existing tools. Here, we examine how synonymous gene recoding has been used to address challenges in therapeutic development, explain the biological mechanisms underlying its effects, and explore the application of computational platforms to improve the surveillance of functional variants in therapeutic design.

The Influence of the Nucleotide Composition of Genes and Gene Regulatory Elements on the Efficiency of Protein Expression in Escherichia coli

Recombinant proteins expressed in Escherichia coli are widely used in biochemical research and industrial processes. At the same time, achieving higher protein expression levels and correct protein folding still remains the key problem, since optimization of nutrient media, growth conditions, and methods for induction of protein synthesis do not always lead to the desired result. Often, low protein expression is determined by the sequences of the expressed genes and their regulatory regions. The genetic code is degenerated; 18 out of 20 amino acids are encoded by more than one codon. Choosing between synonymous codons in the coding sequence can significantly affect the level of protein expression and protein folding due to the influence of the gene nucleotide composition on the probability of formation of secondary mRNA structures that affect the ribosome binding at the translation initiation phase, as well as the ribosome movement along the mRNA during elongation, which, in turn, influences the mRNA degradation and the folding of the nascent protein. The nucleotide composition of the mRNA untranslated regions, in particular the promoter and Shine-Dalgarno sequences, also affects the efficiency of mRNA transcription, translation, and degradation. In this review, we describe the genetic principles that determine the efficiency of protein production in Escherichia coli.

A Short Tale of the Origin of Proteins and Ribosome Evolution

Proteins are the workhorses of the cell and have been key players throughout the evolution of all organisms, from the origin of life to the present era. How might life have originated from the prebiotic chemistry of early Earth? This is one of the most intriguing unsolved questions in biology. Currently, however, it is generally accepted that amino acids, the building blocks of proteins, were abiotically available on primitive Earth, which would have made the formation of early peptides in a similar fashion possible. Peptides are likely to have coevolved with ancestral forms of RNA. The ribosome is the most evident product of this coevolution process, a sophisticated nanomachine that performs the synthesis of proteins codified in genomes. In this general review, we explore the evolution of proteins from their peptide origins to their folding and regulation based on the example of superoxide dismutase (SOD1), a key enzyme in oxygen metabolism on modern Earth.

Protocol to identify host-viral protein interactions between coagulation-related proteins and their genetic variants with SARS-CoV-2 proteins

Here, we describe a bioinformatics pipeline that evaluates the interactions between coagulation-related proteins and genetic variants with SARS-CoV-2 proteins. This pipeline searches for host proteins that may bind to viral protein and identifies and scores the protein genetic variants to predict the disease pathogenesis in specific subpopulations. Additionally, it is able to find structurally similar motifs and identify potential binding sites within the host-viral protein complexes to unveil viral impact on regulated biological processes and/or host-protein impact on viral invasion or reproduction. For complete details on the use and execution of this protocol, please refer to Holcomb et al. (2021).

Engineering a tunable bicistronic TetR autoregulation expression system in Gluconobacter oxydans

Acetic acid bacteria are well-known for their ability to incompletely oxidize their carbon sources. Many of the products of these oxidations find industrial uses. Metabolic engineering of acetic acid bacteria would improve production efficiency and yield by allowing controllable gene expression. However, the molecular tools necessary for regulating gene expression have only recently started being explored. To this end the ability of the activation-dependent P_lux system and two constitutive repression P_tet systems were examined for their ability to modulate gene expression in Gluconobacter oxydans. The activation-dependent P_lux system increased gene expression approximately 5-fold regardless of the strength of the constitutive promoter used to express the luxR transcriptional activator. The P_tet system was tunable and had a nearly 20-fold induction when the tetR gene was expressed from the strong constitutive promoters P₀₁₆₉ and P₂₆₄, but only had a 4-fold induction when a weak constitutive promoter (P₄₅₂) was used for tetR expression. However, the P_tet system was somewhat leaky when uninduced. To mitigate this background activity, a bicistronic TetR expression system was constructed. Based on molecular modeling, this system is predicted to have low background activity when not induced with anhydrotetracycline. The bicistronic system was inducible up to >3,000-fold and was highly tunable with almost no background expression when uninduced, making this bicistronic system potentially useful for engineering G. oxydans and possibly other acetic acid bacteria. These expression systems add to the newly growing repertoire of suitable regulatable promoter systems in acetic acid bacteria.

A Review: Machine Learning for Combinatorial Optimization Problems in Energy Areas

Combinatorial optimization problems (COPs) are a class of NP-hard problems with great practical significance. Traditional approaches for COPs suffer from high computational time and reliance on expert knowledge, and machine learning (ML) methods, as powerful tools have been used to overcome these problems. In this review, the COPs in energy areas with a series of modern ML approaches, i.e., the interdisciplinary areas of COPs, ML and energy areas, are mainly investigated. Recent works on solving COPs using ML are sorted out firstly by methods which include supervised learning (SL), deep learning (DL), reinforcement learning (RL) and recently proposed game theoretic methods, and then problems where the timeline of the improvements for some fundamental COPs is the layout. Practical applications of ML methods in the energy areas, including the petroleum supply chain, steel-making, electric power system and wind power, are summarized for the first time, and challenges in this field are analyzed.

CHARMING: Harmonizing synonymous codon usage to replicate a desired codon usage pattern

There is a growing appreciation that synonymous codon usage, although historically regarded as phenotypically silent, can instead alter a wide range of mechanisms related to functional protein production, a term we use here to describe the net effect of transcription (mRNA synthesis), mRNA half-life, translation (protein synthesis) and the probability of a protein folding correctly to its active, functional structure. In particular, recent discoveries have highlighted the important role that sub-optimal codons can play in modifying co-translational protein folding. These results have drawn increased attention to the patterns of synonymous codon usage within coding sequences, particularly in light of the discovery that these patterns can be conserved across evolution for homologous proteins. Because synonymous codon usage differs between organisms, for heterologous gene expression it can be desirable to make synonymous codon substitutions to match the codon usage pattern from the original organism in the heterologous expression host. Here we present CHARMING (for Codon HARMonizING), a robust and versatile algorithm to design mRNA sequences for heterologous gene expression and other related codon harmonization tasks. CHARMING can be run as a downloadable Python script or via a web portal at http://www.codons.org.

Efficient expression of a cnidarian peptide-gated ion channel in mammalian cells

Hydra Na+ channels (HyNaCs) are peptide-gated ion channels of the DEG/ENaC gene family that are directly activated by neuropeptides of the Hydra nervous system. They have previously been successfully characterized in Xenopus oocytes. To establish their expression in mammalian cells, we transiently expressed heteromeric HyNaC2/3/5 in human HEK 293 and monkey COS-7 cells. We found that the expression of HyNaC2/3/5 using native cDNAs was inefficient and that codon optimization strongly increased protein expression and current amplitude in patch-clamp experiments. We used the improved expression of codon-optimized channel subunits to perform Ca2+ imaging and to demonstrate their glycosylation pattern. In summary, we established efficient expression of a cnidarian ion channel in mammalian cell lines.

Cholesterol Is a Dose-Dependent Positive Allosteric Modulator of CCR3 Ligand Affinity and G Protein Coupling

Cholesterol as an allosteric modulator of G protein-coupled receptor (GPCR) function is well documented. This quintessential mammalian lipid facilitates receptor–ligand interactions and multimerization states. Functionally, this introduces a complicated mechanism for the homeostatic modulation of GPCR signaling. Chemokine receptors are Class A GPCRs responsible for immune cell trafficking through the binding of endogenous peptide ligands. CCR3 is a CC motif chemokine receptor expressed by eosinophils and basophils. It traffics these cells by transducing the signal stimulated by the CC motif chemokine primary messengers 11, 24, and 26. These behaviors are close to the human immunoresponse. Thus, CCR3 is implicated in cancer metastasis and inflammatory conditions. However, there is a paucity of experimental evidence linking the functional states of CCR3 to the molecular mechanisms of cholesterol–receptor cooperativity. In this vein, we present a means to combine codon harmonization and a maltose-binding protein fusion tag to produce CCR3 from E. coli. This technique yields ∼2.6 mg of functional GPCR per liter of minimal media. We leveraged this protein production capability to investigate the effects of cholesterol on CCR3 function in vitro. We found that affinity for the endogenous ligand CCL11 increases in a dose-dependent manner with cholesterol concentration in both styrene:maleic acid lipid particles (SMALPs) and proteoliposomes. This heightened receptor activation directly translates to increased signal transduction as measured by the GTPase activity of the bound G-protein α inhibitory subunit 3 (Gα_i3). This work represents a critical step forward in understanding the role of cholesterol-GPCR allostery in regulation of signal transduction.

Gene variants of coagulation related proteins that interact with SARS-CoV-2

Thrombosis is a recognized complication of Coronavirus disease of 2019 (COVID-19) and is often associated with poor prognosis. There is a well-recognized link between coagulation and inflammation, however, the extent of thrombotic events associated with COVID-19 warrants further investigation. Poly(A) Binding Protein Cytoplasmic 4 (PABPC4), Serine/Cysteine Proteinase Inhibitor Clade G Member 1 (SERPING1) and Vitamin K epOxide Reductase Complex subunit 1 (VKORC1), which are all proteins linked to coagulation, have been shown to interact with SARS proteins. We computationally examined the interaction of these with SARS-CoV-2 proteins and, in the case of VKORC1, we describe its binding to ORF7a in detail. We examined the occurrence of variants of each of these proteins across populations and interrogated their potential contribution to COVID-19 severity. Potential mechanisms, by which some of these variants may contribute to disease, are proposed. Some of these variants are prevalent in minority groups that are disproportionally affected by severe COVID-19. Therefore, we are proposing that further investigation around these variants may lead to better understanding of disease pathogenesis in minority groups and more informed therapeutic approaches.

Assessing optimal: inequalities in codon optimization algorithms

BACKGROUND

Custom genes have become a common resource in recombinant biology over the last 20 years due to the plummeting cost of DNA synthesis. These genes are often "optimized" to non-native sequences for overexpression in a non-native host by substituting synonymous codons within the coding DNA sequence (CDS). A handful of studies have compared native and optimized CDSs, reporting different levels of soluble product due to the accumulation of misfolded aggregates, variable activity of enzymes, and (at least one report of) a change in substrate specificity. No study, to the best of our knowledge, has performed a practical comparison of CDSs generated from different codon optimization algorithms or reported the corresponding protein yields.

RESULTS

In our efforts to understand what factors constitute an optimized CDS, we identified that there is little consensus among codon-optimization algorithms, a roughly equivalent chance that an algorithm-optimized CDS will increase or diminish recombinant yields as compared to the native DNA, a near ubiquitous use of a codon database that was last updated in 2007, and a high variability of output CDSs by some algorithms. We present a case study, using KRas4B, to demonstrate that a median codon frequency may be a better predictor of soluble yields than the more commonly utilized CAI metric.

CONCLUSIONS

We present a method for visualizing, analyzing, and comparing algorithm-optimized DNA sequences for recombinant protein expression. We encourage researchers to consider if DNA optimization is right for their experiments, and work towards improving the reproducibility of published recombinant work by publishing non-native CDSs.

Ribosome occupancy profiles are conserved between structurally and evolutionarily related yeast domains

Motivation

Protein synthesis is a non-equilibrium process, meaning that the speed of translation can influence the ability of proteins to fold and function. Assuming that structurally similar proteins fold by similar pathways, the profile of translation speed along an mRNA should be evolutionarily conserved between related proteins to direct correct folding and downstream function. The only evidence to date for such conservation of translation speed between homologous proteins has used codon rarity as a proxy for translation speed. There are, however, many other factors including mRNA structure and the chemistry of the amino acids in the A- and P-sites of the ribosome that influence the speed of amino acid addition.

Results

Ribosome profiling experiments provide a signal directly proportional to the underlying translation times at the level of individual codons. We compared ribosome occupancy profiles (extracted from five different large-scale yeast ribosome profiling studies) between related protein domains to more directly test if their translation schedule was conserved. Our analysis reveals that the ribosome occupancy profiles of paralogous domains tend to be significantly more similar to one another than to profiles of non-paralogous domains. This trend does not depend on domain length, structural classes, amino acid composition or sequence similarity. Our results indicate that entire ribosome occupancy profiles and not just rare codon locations are conserved between even distantly related domains in yeast, providing support for the hypothesis that translation schedule is conserved between structurally related domains to retain folding pathways and facilitate efficient folding.

Availability and implementation

Python3 code is available on GitHub at https://github.com/DanNissley/Compare-ribosome-occupancy.

Supplementary information

Supplementary data are available at Bioinformatics online.

A Modelling Framework Linking Resource-Based Stochastic Translation to the Optimal Design of Synthetic Constructs

Simple Summary

In synthetic biology, it is commonplace to design and insert gene expression constructs into cells for the production of useful proteins. In order to maximise production yield, it is useful to predict the performance of these “engineered cells” in advance of conducting experiments. This is typically a complex task, which in recent years has motivated the use of “whole-cell models” (WCMs) that act as computational tools for predicting different aspects of cell growth. Many useful WCMs exist, however a common problem is their over-simplification of ribosome movement on mRNA transcripts during translation. WCMs typically don’t consider that, for constructs with inefficient (“slow”) codons, ribosomes can stall and form “traffic jams”, thereby becoming unavailable for translation of other proteins. To more accurately address these scenarios, we have built a computational framework that combines whole-cell modelling with a detailed account of ribosome movement on mRNA. We show how our framework can be used to link the modular design of a gene expression construct (via its promoter, ribosome binding site and codon composition) to protein yield during continuous cell culture, with a particular focus on how the optimal design can change over time in the presence or absence of “slow” codons.

Abstract

The effect of gene expression burden on engineered cells has motivated the use of “whole-cell models” (WCMs) that use shared cellular resources to predict how unnatural gene expression affects cell growth. A common problem with many WCMs is their inability to capture translation in sufficient detail to consider the impact of ribosomal queue formation on mRNA transcripts. To address this, we have built a “stochastic cell calculator” (StoCellAtor) that combines a modified TASEP with a stochastic implementation of an existing WCM. We show how our framework can be used to link a synthetic construct’s modular design (promoter, ribosome binding site (RBS) and codon composition) to protein yield during continuous culture, with a particular focus on the effects of low-efficiency codons and their impact on ribosomal queues. Through our analysis, we recover design principles previously established in our work on burden-sensing strategies, namely that changing promoter strength is often a more efficient way to increase protein yield than RBS strength. Importantly, however, we show how these design implications can change depending on both the duration of protein expression, and on the presence of ribosomal queues.

Synonymous variants in holoprosencephaly alter codon usage and impact the Sonic Hedgehog protein

Synonymous single nucleotide variants (sSNVs) have been implicated in various genetic disorders through alterations of pre-mRNA splicing, mRNA structure and miRNA regulation. However, their impact on synonymous codon usage and protein translation remains to be elucidated in clinical context. Here, we explore the functional impact of sSNVs in the Sonic Hedgehog (SHH) gene, identified in patients affected by holoprosencephaly, a congenital brain defect resulting from incomplete forebrain cleavage. We identified eight sSNVs in SHH, selectively enriched in holoprosencephaly patients as compared to healthy individuals, and systematically assessed their effect at both transcriptional and translational levels using a series of in silico and in vitro approaches. Although no evidence of impact of these sSNVs on splicing, mRNA structure or miRNA regulation was found, five sSNVs introduced significant changes in codon usage and were predicted to impact protein translation. Cell assays demonstrated that these five sSNVs are associated with a significantly reduced amount of the resulting protein, ranging from 5% to 23%. Inhibition of the proteasome rescued the protein levels for four out of five sSNVs, confirming their impact on protein stability and folding. Remarkably, we found a significant correlation between experimental values of protein reduction and computational measures of codon usage, indicating the relevance of in silico models in predicting the impact of sSNVs on translation. Considering the critical role of SHH in brain development, our findings highlight the clinical relevance of sSNVs in holoprosencephaly and underline the importance of investigating their impact on translation in human pathologies.

Potential impact on coagulopathy of gene variants of coagulation related proteins that interact with SARS-CoV-2

Thrombosis has been one of the complications of the Coronavirus disease of 2019 (COVID-19), often associated with poor prognosis. There is a well-recognized link between coagulation and inflammation, however, the extent of thrombotic events associated with COVID-19 warrants further investigation. Poly(A) Binding Protein Cytoplasmic 4 (PABPC4), Serine/Cysteine Proteinase Inhibitor Clade G Member 1 (SERPING1) and Vitamin K epOxide Reductase Complex subunit 1 (VKORC1), which are all proteins linked to coagulation, have been shown to interact with SARS proteins. We computationally examined the interaction of these with SARS-CoV-2 proteins and, in the case of VKORC1, we describe its binding to ORF7a in detail. We examined the occurrence of variants of each of these proteins across populations and interrogated their potential contribution to COVID-19 severity. Potential mechanisms by which some of these variants may contribute to disease are proposed. Some of these variants are prevalent in minority groups that are disproportionally affected by severe COVID-19. Therefore, we are proposing that further investigation around these variants may lead to better understanding of disease pathogenesis in minority groups and more informed therapeutic approaches.

Author summary

Increased blood clotting, especially in the lungs, is a common complication of COVID-19. Infectious diseases cause inflammation which in turn can contribute to increased blood clotting. However, the extent of clot formation that is seen in the lungs of COVID-19 patients suggests that there may be a more direct link. We identified three human proteins that are involved indirectly in the blood clotting cascade and have been shown to interact with proteins of SARS virus, which is closely related to the novel coronavirus. We examined computationally the interaction of these human proteins with the viral proteins. We looked for genetic variants of these proteins and examined how these variants are distributed across populations. We investigated whether variants of these genes could impact severity of COVID-19. Further investigation around these variants may provide clues for the pathogenesis of COVID-19 particularly in minority groups.

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

Improved 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.

Optimised red- and green-fluorescent proteins for live cell imaging in the industrial enzyme-producing fungus Trichoderma reesei

The filamentous fungus Trichoderma reesei is a major source of cellulolytic enzymes in biofuel production. Despite its economic relevance, our understanding of its secretory pathways is fragmentary. A major challenge is to visualise the dynamic behaviour of secretory vesicles in living cells. To this end, we establish a location juxtaposing the succinate dehydrogenase locus as a "soft-landing" site for controlled expression of 4 green-fluorescent and 5 red-fluorescent protein-encoding genes (GFPs, RFPs). Quantitative and comparative analysis of their fluorescent signals in living cells demonstrates that codon-optimised monomeric superfolder GFP (TrmsGFP) and codon-optimised mCherry (TrmCherry) combine highest signal intensity with significantly improved signal-to-noise ratios. Finally, we show that integration of plasmid near the sdi1 locus does not affect secretion of cellulase activity in RUT-C30. The molecular and live cell imaging tools generated in this study will help our understanding the secretory pathway in the industrial fungus T. reesei.

Characteristics analysis of the complete Wurfbainia villosa chloroplast genome

Wurfbainia villosa, which belongs to the huge family Zingiberaceae, is used in the clinic for the treatment of spleen and stomach diseases in southern China. The complete chloroplast genome of W. villosa was sequenced and analyzed using next-generation sequencing technology in the present work. The results showed that the W. villosa chloroplast genome is a circular molecule with 163,608 bp in length. It harbors a pair of inverted repeat regions (IRa and IRb) of 29,820 bp in length, which separate the large single copy (LSC, 88,680 bp) region and the small single copy (SSC, 15,288 bp) region. After annotation, 134 genes were identified in this plastome in total, comprising of 87 protein-coding genes, 38 transfer RNA genes, 8 ribosomal RNA genes and one pseudogene (ycf1). Codon usage, RNA editing sites and single/long sequence repeats were investigated to understand the structural characteristics of the W. villosa chloroplast genome. Furthermore, IR contraction and expansion were analyzed by comparison of complete chloroplast genomes of W. villosa and four other Zingiberaceae species. Finally, a phylogeny study based on the chloroplast genome of W. villosa, along with that of 15 different species, was conducted to further investigate the relationship among these lineages. Overally, our results represented the first insight into the chloroplast genome of W. villosa, and could serve as a significant reference for species identification, genetic diversity analysis and phylogenetic research between W. villosa and other species within Zingiberaceae.

Codon Harmonization of a Kir3.1-KirBac1.3 Chimera for Structural Study Optimization

The expression of functional, folded, and isotopically enriched membrane proteins is an enduring bottleneck for nuclear magnetic resonance (NMR) studies. Indeed, historically, protein yield optimization has been insufficient to allow NMR analysis of many complex Eukaryotic membrane proteins. However, recent work has found that manipulation of plasmid codons improves the odds of successful NMR-friendly protein production. In the last decade, numerous studies showed that matching codon usage patterns in recombinant gene sequences to those in the native sequence is positively correlated with increased protein yield. This phenomenon, dubbed codon harmonization, may be a powerful tool in optimizing recombinant expression of difficult-to-produce membrane proteins for structural studies. Here, we apply this technique to an inward rectifier K⁺ Channel (Kir) 3.1-KirBac1.3 chimera. Kir3.1 falls within the G protein-coupled inward rectifier K⁺ (GIRK) channel family, thus NMR studies may inform on the nuances of GIRK gating action in the presence and absence of its G Protein, lipid, and small molecule ligands. In our hands, harmonized plasmids increase protein yield nearly two-fold compared to the traditional ‘fully codon optimized’ construct. We then employ a fluorescence-based functional assay and solid-state NMR correlation spectroscopy to show the final protein product is folded and functional.

Synonymous codon substitutions perturb cotranslational protein folding in vivo and impair cell fitness

In the cell, proteins are synthesized from N to C terminus and begin to fold during translation. Cotranslational folding mechanisms are therefore linked to elongation rate, which varies as a function of synonymous codon usage. However, synonymous codon substitutions can affect many distinct cellular processes, which has complicated attempts to deconvolve the extent to which synonymous codon usage can promote or frustrate proper protein folding in vivo. Although previous studies have shown that some synonymous changes can lead to different final structures, other substitutions will likely be more subtle, perturbing predominantly the protein folding pathway without radically altering the final structure. Here we show that synonymous codon substitutions encoding a single essential enzyme lead to dramatically slower cell growth. These mutations do not prevent active enzyme formation; instead, they predominantly alter the protein folding mechanism, leading to enhanced degradation in vivo. These results support a model in which synonymous codon substitutions can impair cell fitness by significantly perturbing cotranslational protein folding mechanisms, despite the chaperoning provided by the cellular protein homeostasis network.

Pervasive Strong Selection at the Level of Codon Usage Bias in Drosophila melanogaster

Codon usage bias (CUB), where certain codons are used more frequently than expected by chance, is a ubiquitous phenomenon and occurs across the tree of life. The dominant paradigm is that the proportion of preferred codons is set by weak selection. While experimental changes in codon usage have at times shown large phenotypic effects in contrast to this paradigm, genome-wide population genetic estimates have supported the weak selection model. Here we use deep genomic population sequencing of two Drosophila melanogaster populations to measure selection on synonymous sites in a way that allowed us to estimate the prevalence of both weak and strong purifying selection. We find that selection in favor of preferred codons ranges from weak (|Nes| ∼ 1) to strong (|Nes| > 10), with strong selection acting on 10-20% of synonymous sites in preferred codons. While previous studies indicated that selection at synonymous sites could be strong, this is the first study to detect and quantify strong selection specifically at the level of CUB. Further, we find that CUB-associated polymorphism accounts for the majority of strong selection on synonymous sites, with secondary contributions of splicing (selection on alternatively spliced genes, splice junctions, and spliceosome-bound sites) and transcription factor binding. Our findings support a new model of CUB and indicate that the functional importance of CUB, as well as synonymous sites in general, have been underestimated.

Protein surface charge effect on 3D domain swapping in cells for c-type cytochromes

Many c-type cytochromes (cyts) can form domain-swapped oligomers. The positively charged Hydrogenobacter thermophilus (HT) cytochrome (cyt) c₅₅₂ forms domain-swapped oligomers during expression in the Escherichia coli (E. coli) expression system, but the factors influencing the oligomerization remain unrevealed. Here, we found that the dimer of the negatively charged Shewanella violacea (SV) cyt c₅ exhibits a domain-swapped structure, in which the N-terminal helix is exchanged between protomers, similar to the structures of the HT cyt c₅₅₂ and Pseudomonas aeruginosa (PA) cyt c₅₅₁ domain-swapped dimers. Positively charged horse cyt c and HT cyt c₅₅₂ domain swapped during expression in E. coli, whereas negatively charged PA cyt c₅₅₁ and SV cyt c₅ did not. Oligomers were formed during expression in E. coli for HT cyt c₅₅₂ attached to either a co- or post-translational signal peptide for transportation through the cytoplasm membrane, but not for PA cyt c₅₅₁ attached to either signal peptide. HT cyt c₅₅₂ formed oligomers in E. coli in the presence and absence of rare codons. More oligomers were obtained from the in vitro folding of horse cyt c and HT cyt c₅₅₂ by the addition of negatively charged liposomes during folding, whereas the amount of oligomers for the in vitro folding of PA cyt c₅₅₁ and SV cyt c₅ did not change significantly by the addition. These results indicate that the protein surface charge affects the oligomerization of c-type cyts in cells; positively charged c-type cyts assemble on a negatively charged membrane, inducing formation of domain-swapped oligomers during folding.

Assessing cell-specific effects of genetic variations using tRNA microarrays

Background

By definition, effect of synonymous single-nucleotide variants (SNVs) on protein folding and function are neutral, as they alter the codon and not the encoded amino acid. Recent examples indicate tissue-specific and transfer RNA (tRNA)-dependent effects of some genetic variations arguing against neutrality of synonymous SNVs for protein biogenesis.

Results

We performed systematic analysis of tRNA abunandance across in various models used in cystic fibrosis (CF) research and drug development, including Fischer rat thyroid (FRT) cells, patient-derived primary human bronchial epithelia (HBE) from lung biopsies, primary human nasal epithelia (HNE) from nasal curettage, intestinal organoids, and airway progenitor-directed differentiation of human induced pluripotent stem cells (iPSCs). These were compared to an immortalized CF bronchial cell model (CFBE41o⁻) and two widely used laboratory cell lines, HeLa and HEK293. We discovered that specific synonymous SNVs exhibited differential effects which correlated with variable concentrations of cognate tRNAs.

Conclusions

Our results highlight ways in which the presence of synonymous SNVs may alter local kinetics of mRNA translation; and thus, impact protein biogenesis and function. This effect is likely to influence results from mechansistic analysis and/or drug screeining efforts, and establishes importance of cereful model system selection based on genetic variation profile.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5864-1) contains supplementary material, which is available to authorized users.

Optimizing the dynamics of protein expression

Heterologously expressed genes require adaptation to the host organism to ensure adequate levels of protein synthesis, which is typically approached by replacing codons by the target organism’s preferred codons. In view of frequently encountered suboptimal outcomes we introduce the codon-specific elongation model (COSEM) as an alternative concept. COSEM simulates ribosome dynamics during mRNA translation and informs about protein synthesis rates per mRNA in an organism- and context-dependent way. Protein synthesis rates from COSEM are integrated with further relevant covariates such as translation accuracy into a protein expression score that we use for codon optimization. The scoring algorithm further enables fine-tuning of protein expression including deoptimization and is implemented in the software OCTOPOS. The protein expression score produces competitive predictions on proteomic data from prokaryotic, eukaryotic, and human expression systems. In addition, we optimized and tested heterologous expression of manA and ova genes in Salmonella enterica serovar Typhimurium. Superiority over standard methodology was demonstrated by a threefold increase in protein yield compared to wildtype and commercially optimized sequences.

Re-introducing non-optimal synonymous codons into codon-optimized constructs enhances soluble recovery of recombinant proteins from Escherichia coli

Gene synthesis services have largely superseded traditional PCR methods for the generation of cDNAs destined for bacterial expression vectors. This, in turn, has increased the application of codon-optimized cDNAs where codons rarely used by Escherchia coli are replaced with common synonymous codons to accelerate translation of the target. A markedly accelerated rate of expression often results in a significant uplift in the levels of target protein but a substantial proportion of the enhanced yield can partition to the insoluble fraction rendering a significant portion of the gains unavailable for native purification. We have assessed several expression attenuation strategies for their utility in the manipulation of the soluble fraction towards higher levels of soluble target recovery from codon optimized systems. Using a set of human small GTPases as a case study, we compare the degeneration of the T7 promoter sequence, the use of alternative translational start codons and the manipulation of synonymous codon usage. Degeneration of both the T7 promoter and the translational start codon merely depressed overall expression and did not increase the percentage of product recovered in native purification of the soluble fraction. However, the selective introduction of rare non-optimal codons back into the codon-optimized sequence resulted in significantly elevated recovery of soluble targets. We propose that slowing the rate of extension during translation using a small number of rare codons allows more time for the co-translational folding of the nascent polypeptide. This increases the proportion of the target recovered in the soluble fraction by immobilized metal affinity chromatography (IMAC). Thus, a "de-optimization" of codon-optimized cDNAs, to attenuate or pause the translation process, may prove a useful strategy for improved recombinant protein production.

A New Look at Codon Usage and Protein Expression

%MinMax, a model of intra-gene translational elongation rate, relies on codon usage frequencies. Historically, %MinMax has used tables that measure codon usage bias for all genes in an organism, such as those found at HIVE-CUT. In this paper, we provide evidence that codon usage bias based on all genes is insufficient to accurately measure absolute translation rate. We show that alternative "High-ϕ" codon usage tables, generated by another model (ROC-SEMPPR), are a promising alternative. By creating a hybrid model, future codon usage analyses and their applications (e.g., codon harmonization) are likely to more accurately measure the "tempo" of translation elongation. We also suggest a High-ϕ alternative to the Codon Adaptation Index (CAI), a classic metric of codon usage bias based on highly expressed genes. Significantly, our new alternative is equally well correlated with empirical data as traditional CAI without using experimentally determined expression counts as input.

Applications of Protein Engineering and Directed Evolution in Plant Research

Engineered proteins can be used to optimize desired traits in plants; even though recent advances have resulted in new application areas, certain methodological challenges remain.

Folding up and Moving on-Nascent Protein Folding on the Ribosome

All cellular proteins are synthesized by the ribosome, an intricate molecular machine that translates the information of protein coding genes into the amino acid alphabet. The linear polypeptides synthesized by the ribosome must generally fold into specific three-dimensional structures to become biologically active. Folding has long been recognized to begin before synthesis is complete. Recently, biochemical and biophysical studies have shed light onto how the ribosome shapes the folding pathways of nascent proteins. Here, we discuss recent progress that is beginning to define the role of the ribosome in the folding of newly synthesized polypeptides.

Codon usage clusters correlation: towards protein solubility prediction in heterologous expression systems in E. coli

Production of soluble recombinant proteins is crucial to the development of industry and basic research. However, the aggregation due to the incorrect folding of the nascent polypeptides is still a mayor bottleneck. Understanding the factors governing protein solubility is important to grasp the underlying mechanisms and improve the design of recombinant proteins. Here we show a quantitative study of the expression and solubility of a set of proteins from Bizionia argentinensis. Through the analysis of different features known to modulate protein production, we defined two parameters based on the %MinMax algorithm to compare codon usage clusters between the host and the target genes. We demonstrate that the absolute difference between all %MinMax frequencies of the host and the target gene is significantly negatively correlated with protein expression levels. But most importantly, a strong positive correlation between solubility and the degree of conservation of codons usage clusters is observed for two independent datasets. Moreover, we evince that this correlation is higher in codon usage clusters involved in less compact protein secondary structure regions. Our results provide important tools for protein design and support the notion that codon usage may dictate translation rate and modulate co-translational folding.

Considerations in the Use of Codon Optimization for Recombinant Protein Expression

Codon optimization is a gene engineering approach that is commonly used for enhancing recombinant protein expression. This approach is possible because (1) degeneracy of the genetic code enables most amino acids to be encoded by multiple codons and (2) different mRNAs encoding the same protein can vary dramatically in the amount of protein expressed. However, because codon optimization potentially disrupts overlapping information encoded in mRNA coding regions, protein structure and function may be altered. This chapter discusses the use of codon optimization for various applications in mammalian cells as well as potential consequences, so that informed decisions can be made on the appropriateness of using this approach in each case.