Translation Initiation is Controlled by RNA Folding Kinetics via a Ribosome Drafting Mechanism

Predicting synthetic mRNA stability using massively parallel kinetic measurements, biophysical modeling, and machine learning

mRNA degradation is a central process that affects all gene expression levels, though it remains challenging to predict the stability of a mRNA from its sequence, due to the many coupled interactions that control degradation rate. Here, we carried out massively parallel kinetic decay measurements on over 50,000 bacterial mRNAs, using a learn-by-design approach to develop and validate a predictive sequence-to-function model of mRNA stability. mRNAs were designed to systematically vary translation rates, secondary structures, sequence compositions, G-quadruplexes, i-motifs, and RppH activity, resulting in mRNA half-lives from about 20 seconds to 20 minutes. We combined biophysical models and machine learning to develop steady-state and kinetic decay models of mRNA stability with high accuracy and generalizability, utilizing transcription rate models to identify mRNA isoforms and translation rate models to calculate ribosome protection. Overall, the developed model quantifies the key interactions that collectively control mRNA stability in bacterial operons and predicts how changing mRNA sequence alters mRNA stability, which is important when studying and engineering bacterial genetic systems.

Establishing a High-Yield Chloroplast Cell-Free System for Prototyping Genetic Parts

Plastid engineering offers the potential to carry multigene traits in plants; however, it requires reliable genetic parts to balance expression. The difficulty of chloroplast transformation and slow plant growth makes it challenging to build plants just to characterize genetic parts. To address these limitations, we developed a high-yield cell-free system from Nicotiana tabacum chloroplast extracts for prototyping genetic parts. Our cell-free system uses combined transcription and translation driven by T7 RNA polymerase and works with plasmid or linear template DNA. To develop our system, we optimized lysis, extract preparation procedures (e.g., runoff reaction, centrifugation, and dialysis), and the physiochemical reaction conditions. Our cell-free system can synthesize 34 ± 1 μg/mL luciferase in batch reactions and 60 ± 4 μg/mL in semicontinuous reactions. We apply our batch reaction system to test a library of 103 ribosome binding site (RBS) variants and rank them based on cell-free gene expression. We observe a 1300-fold dynamic range of luciferase expression when normalized by maximum mRNA expression, as assessed by the malachite green aptamer. We also find that the observed normalized gene expression in chloroplast extracts and the predictions made by the RBS Calculator are correlated. We anticipate that chloroplast cell-free systems will increase the speed and reliability of building genetic systems in plant chloroplasts for diverse applications.

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.

Pre-optimization and one-step preparation of cascade enzymes system with broad substrates by model guidance: Application of chiral L-norvaline and L-phenylglycine biosynthesis

Cascade biocatalyst systems with catalytic promiscuity can be used for synthesis of a class of chiral chemicals but the optimization of these systems by model guidance is poorly explored. In this study, a cascade system with broad substrate spectrum was characterized and simulated by kinetic model with substrates of DL-Norvaline (DL-Nor) and DL-Phenylglycine (DL-Phg) as examples. To evaluate the optimal cascade system, maximum accumulation of intermediate products and conversion rate in the process were investigated by simultaneous solution of the rate equations for varying enzyme quantities. According to the simulation results, the cascade system was optimized by regulating the expression of D-amino acid oxidase and formate dehydrogenase and was prepared by one-step. The conversion efficiency of DL-Nor and DL-Phg have been significantly improved compared with that of before optimization. Moreover, the total of L-Nor and L-Phg were reached 498.2 mM and 79.5 mM through a gradient fed-batch conversion strategy, respectively.

Synonymous edits in the Escherichia coli genome have substantial and condition-dependent effects on fitness

CRISPR-Cas-based genome editing is widely used in bacteria at scales ranging from construction of individual mutants to massively parallel libraries. This procedure relies on guide RNA-directed cleavage of the genome followed by repair with a template that introduces a desired mutation along with synonymous "immunizing" mutations to prevent re-cleavage of the genome after editing. Because the immunizing mutations do not change the protein sequence, they are often assumed to be neutral. However, synonymous mutations can change mRNA structures in ways that alter levels of the encoded proteins. We have tested the assumption that immunizing mutations are neutral by constructing a library of over 50,000 edits that consist of only synonymous mutations in Escherichia coli. Thousands of edits had substantial effects on fitness during growth of E. coli on acetate, a poor carbon source that is toxic at high concentrations. The percentage of high-impact edits varied considerably between genes and at different positions within genes. We reconstructed clones with high-impact edits and found that 69% indeed had significant effects on growth in acetate. Interestingly, fewer edits affected fitness during growth in glucose, a preferred carbon source, suggesting that changes in protein expression caused by synonymous mutations may be most important when an organism encounters challenging conditions. Finally, we showed that synonymous edits can have widespread effects; a synonymous edit at the 5' end of ptsI altered expression of hundreds of genes. Our results suggest that the synonymous immunizing edits introduced during CRISPR-Cas-based genome editing should not be assumed to be innocuous.

Lipid membrane remodeling and metabolic response during isobutanol and ethanol exposure in Zymomonas mobilis

BACKGROUND

Recent engineering efforts have targeted the ethanologenic bacterium Zymomonas mobilis for isobutanol production. However, significant hurdles remain due this organism's vulnerability to isobutanol toxicity, adversely affecting its growth and productivity. The limited understanding of the physiological impacts of isobutanol on Z. mobilis constrains our ability to overcome these production barriers.

RESULTS

We utilized a systems-level approach comprising LC-MS/MS-based lipidomics, metabolomics, and shotgun proteomics, to investigate how exposure to ethanol and isobutanol impact the lipid membrane composition and overall physiology of Z. mobilis. Our analysis revealed significant and distinct alterations in membrane phospholipid and fatty acid composition resulting from ethanol and isobutanol exposure. Notably, ethanol exposure increased membrane cyclopropane fatty acid content and expression of cyclopropane fatty acid (CFA) synthase. Surprisingly, isobutanol decreased cyclopropane fatty acid content despite robust upregulation of CFA synthase. Overexpression of the native Z. mobilis' CFA synthase increased cyclopropane fatty acid content in all phospholipid classes and was associated with a significant improvement in growth rates in the presence of added ethanol and isobutanol. Heterologous expression of CFA synthase from Clostridium acetobutylicum resulted in a near complete replacement of unsaturated fatty acids with cyclopropane fatty acids, affecting all lipid classes. However, this did not translate to improved growth rates under isobutanol exposure. Correlating with its greater susceptibility to isobutanol, Z. mobilis exhibited more pronounced alterations in its proteome, metabolome, and overall cell morphology-including cell swelling and formation of intracellular protein aggregates -when exposed to isobutanol compared to ethanol. Isobutanol triggered a broad stress response marked by the upregulation of heat shock proteins, efflux transporters, DNA repair systems, and the downregulation of cell motility proteins. Isobutanol also elicited widespread dysregulation of Z. mobilis' primary metabolism evidenced by increased levels of nucleotide degradation intermediates and the depletion of biosynthetic and glycolytic intermediates.

CONCLUSIONS

This study provides a comprehensive, systems-level evaluation of the impact of ethanol and isobutanol exposure on the lipid membrane composition and overall physiology of Z. mobilis. These findings will guide engineering of Z. mobilis towards the creation of isobutanol-tolerant strains that can serve as robust platforms for the industrial production of isobutanol from lignocellulosic sugars.

Toolbox of Characterized Genetic Parts for Staphylococcus aureus

Staphylococcus aureus is an important clinical bacterium prevalent in human-associated microbiomes and the cause of many diseases. However, S. aureus has been intractable to synthetic biology approaches due to limited characterized genetic parts for this nonmodel Gram-positive bacterium. Moreover, genetic manipulation of S. aureus has relied on cumbersome and inefficient cloning strategies. Here, we report the first standardized genetic parts toolbox for S. aureus, which includes characterized promoters, ribosome binding sites, terminators, and plasmid replicons from a variety of bacteria for precise control of gene expression. We established a standard relative expression unit (REU) for S. aureus using a plasmid reference and characterized genetic parts in standardized REUs using S. aureus ATCC 12600. We constructed promoter and terminator part plasmids that are compatible with an efficient Type IIS DNA assembly strategy to effectively build multipart DNA constructs. A library of 24 constitutive promoters was built and characterized in S. aureus, which showed a 380-fold activity range. This promoter library was also assayed in Bacillus subtilis (122-fold activity range) to demonstrate the transferability of the constitutive promoters between these Gram-positive bacteria. By applying an iterative design-build-test-learn cycle, we demonstrated the use of our toolbox for the rational design and engineering of a tetracycline sensor in S. aureus using the PXyl-TetO aTc-inducible promoter that achieved 25.8-fold induction. This toolbox greatly expands the growing number of genetic parts for Gram-positive bacteria and will allow researchers to leverage synthetic biology approaches to study and engineer cellular processes in S. aureus.

Synthetic Homoserine Lactone Sensors for Gram-Positive Bacillus subtilis Using LuxR-Type Regulators

A universal biochemical signal for bacterial cell-cell communication could facilitate programming dynamic responses in diverse bacterial consortia. However, the classical quorum sensing paradigm is that Gram-negative and Gram-positive bacteria generally communicate via homoserine lactones (HSLs) or oligopeptide molecular signals, respectively, to elicit population responses. Here, we create synthetic HSL sensors for Gram-positive Bacillus subtilis 168 using allosteric LuxR-type regulators (RpaR, LuxR, RhlR, and CinR) and synthetic promoters. Promoters were combinatorially designed from different sequence elements (-35, -16, -10, and transcriptional start regions). We quantified the effects of these combinatorial promoters on sensor activity and determined how regulator expression affects its activation, achieving up to 293-fold activation. Using the statistical design of experiments, we identified significant effects of promoter regions and pairwise interactions on sensor activity, which helped to understand the sequence-function relationships for synthetic promoter design. We present the first known set of functional HSL sensors (≥20-fold dynamic range) in B. subtilis for four different HSL chemical signals: p-coumaroyl-HSL, 3-oxohexanoyl-HSL, n-butyryl-HSL, and n-(3-hydroxytetradecanoyl)-HSL. This set of synthetic HSL sensors for a Gram-positive bacterium can pave the way for designable interspecies communication within microbial consortia.

Development of modular expression across phylogenetically distinct diazotrophs

Diazotrophic bacteria can reduce atmospheric nitrogen into ammonia enabling bioavailability of the essential element. Many diazotrophs closely associate with plant roots increasing nitrogen availability, acting as plant growth promoters. These associations have the potential to reduce the need for costly synthetic fertilizers if they could be engineered for agricultural applications. However, despite the importance of diazotrophic bacteria, genetic tools are poorly developed in a limited number of species, in turn narrowing the crops and root microbiomes that can be targeted. Here, we report optimized protocols and plasmids to manipulate phylogenetically diverse diazotrophs with the goal of enabling synthetic biology and genetic engineering. Three broad-host-range plasmids can be used across multiple diazotrophs, with the identification of one specific plasmid (containing origin of replication RK2 and a kanamycin resistance marker) showing the highest degree of compatibility across bacteria tested. We then demonstrated modular expression by testing seven promoters and eleven ribosomal binding sites using proxy fluorescent proteins. Finally, we tested four small molecule inducible systems to report expression in three diazotrophs and demonstrated genome editing in Klebsiella michiganensis M5al.

ONE-SENTENCE SUMMARY

In this study, broad-host plasmids and synthetic genetic parts were leveraged to enable expression tools in a library of diazotrophic bacteria.

Cell-free biosynthesis combined with deep learning accelerates de novo-development of antimicrobial peptides

Bioactive peptides are key molecules in health and medicine. Deep learning holds a big promise for the discovery and design of bioactive peptides. Yet, suitable experimental approaches are required to validate candidates in high throughput and at low cost. Here, we established a cell-free protein synthesis (CFPS) pipeline for the rapid and inexpensive production of antimicrobial peptides (AMPs) directly from DNA templates. To validate our platform, we used deep learning to design thousands of AMPs de novo. Using computational methods, we prioritized 500 candidates that we produced and screened with our CFPS pipeline. We identified 30 functional AMPs, which we characterized further through molecular dynamics simulations, antimicrobial activity and toxicity. Notably, six de novo-AMPs feature broad-spectrum activity against multidrug-resistant pathogens and do not develop bacterial resistance. Our work demonstrates the potential of CFPS for high throughput and low-cost production and testing of bioactive peptides within less than 24 h.

Genetic and functional basis of the reduction effect in bacteriophage ΦX174

The ΦX174 reduction effect describes a plasmid-based inhibitory phenomenon that mimics the superinfection inhibition found in wild phage populations. In this effect, when a portion of the ΦX174 genome - the 3' end of the pilot protein gene (H), the 5' end of the replication gene (A), and the H-A intergenic region - is present on a plasmid in the host cell, almost complete protection from phage infection occurs. Here we demonstrate that only the phage pilot protein H portion of the plasmid is sufficient for the observed inhibition, that protein synthesis is necessary for inhibition to occur, that inserting the entire H gene in the plasmid may also impart a blocking effect, and that partial to complete recovery from this inhibition is possible with minimal viral evolution.

Signal Amplification for Cell-Free Biosensors, an Analog-to-Digital Converter

Toehold switches are biosensors useful for the detection of endogenous and environmental RNAs. They have been successfully engineered to detect virus RNAs in cell-free gene expression reactions. Their inherent sequence programmability makes engineering a fast and predictable process. Despite improvements in the design, toehold switches suffer from leaky translation in the OFF state, which compromises the fold change and sensitivity of the biosensor. To address this, we constructed and tested signal amplification circuits for three toehold switches triggered by Dengue and SARS-CoV-2 RNAs and an artificial RNA. The serine integrase circuit efficiently contained leakage, boosted the expression fold change from OFF to ON, and decreased the detection limit of the switches by 3-4 orders of magnitude. Ultimately, the integrase circuit converted the analog switches' signals into digital-like output. The circuit is broadly useful for biosensors and eliminates the hard work of designing and testing multiple switches to find the best possible performer.

Development of an aminotransferase-driven biocatalytic cascade for deracemization of d,l-phosphinothricin

2-oxo-4-[(hydroxy)(methyl)phosphinoyl]butyric acid (PPO) is the essential precursor keto acid for the asymmetric biosynthesis of herbicide l-phosphinothricin (l-PPT). Developing a biocatalytic cascade for PPO production with high efficiency and low cost is highly desired. Herein, a d-amino acid aminotransferase from Bacillus sp. YM-1 (Ym DAAT) with high activity (48.95 U/mg) and affinity (Km  = 27.49 mM) toward d-PPT was evaluated. To circumvent the inhibition of by-product d-glutamate (d-Glu), an amino acceptor (α-ketoglutarate) regeneration cascade was constructed as a recombinant Escherichia coli (E. coli D), by coupling Ym d-AAT, d-aspartate oxidase from Thermomyces dupontii (TdDDO) and catalase from Geobacillus sp. CHB1. Moreover, the regulation of the ribosome binding site was employed to overcome the limiting step of expression toxic protein TdDDO in E. coli BL21(DE3). The aminotransferase-driven whole-cell biocatalytic cascade (E. coli D) showed superior catalytic efficiency for the synthesis of PPO from d,l-phosphinothricin (d,l-PPT). It revealed the production of PPO exhibited high space-time yield (2.59 g L-1  h-1 ) with complete conversion of d-PPT to PPO at high substrate concentration (600 mM d,l-PPT) in 1.5 L reaction system. This study first provides the synthesis of PPO from d,l-PPT employing an aminotransferase-driven biocatalytic cascade.

Quintuply orthogonal pyrrolysyl-tRNA synthetase/tRNAPyl pairs

Mutually orthogonal aminoacyl transfer RNA synthetase/transfer RNA pairs provide a foundation for encoding non-canonical amino acids into proteins, and encoded non-canonical polymer and macrocycle synthesis. Here we discover quintuply orthogonal pyrrolysyl-tRNA synthetase (PylRS)/pyrrolysyl-tRNA (tRNAPyl) pairs. We discover empirical sequence identity thresholds for mutual orthogonality and use these for agglomerative clustering of PylRS and tRNAPyl sequences; this defines numerous sequence clusters, spanning five classes of PylRS/tRNAPyl pairs (the existing classes +N, A and B, and newly defined classes C and S). Most of the PylRS clusters belong to classes that were unexplored for orthogonal pair generation. By testing pairs from distinct clusters and classes, and pyrrolysyl-tRNAs with unusual structures, we resolve 80% of the pairwise specificities required to make quintuply orthogonal PylRS/tRNAPyl pairs; we control the remaining specificities by engineering and directed evolution. Overall, we create 924 mutually orthogonal PylRS/tRNAPyl pairs, 1,324 triply orthogonal pairs, 128 quadruply orthogonal pairs and 8 quintuply orthogonal pairs. These advances may provide a key foundation for encoded polymer synthesis.

Characterizing a Propionate Sensor in E. coli Nissle 1917

Short-chain fatty acids (SCFAs) are commonly found in the large intestine, but generally not in the small intestine, and influence microbiome composition and host physiology. Thus, synthetic biologists are interested in developing engineered probiotics capable of in situ detection of SCFAs as biogeography or disease sensors. One SCFA, propionate, is both sensed and consumed by E. coli. Here, we utilize the E. coli transcription factor PrpR, sensitive to the propionate-derived metabolite (2S,3S)-2-methylcitrate, and its cognate promoter PprpBCDE to detect extracellular propionate with the probiotic chassis bacterium E. coli Nissle 1917. We identify that PrpR-PprpBCDE displays stationary phase leakiness and transient bimodality, and we explain these observations through evolutionary rationales and deterministic modeling, respectively. Our results will help researchers build biogeographically sensitive genetic circuits.

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.

Protocol to develop a synthetic biology toolkit for the non-model bacterium R. palustris

Numerous biology tools are developed to work for model organisms, which, however, do not work effectively in non-model organisms. Here, we present a protocol for developing a synthetic biology toolkit for Rhodopseudomonas palustris CGA009, a non-model bacterium with unique metabolic properties. We describe steps for introducing and characterizing biological devices in non-model bacteria, such as the utilization of fluorescence markers and RT-qPCR. This protocol may also be applicable for other non-model organisms. For complete details on the use and execution of this protocol, please refer to Immethun et al..¹.

Standard Intein Gene Expression Ramps (SIGER) for Protein-Independent Expression Control

Coordination of multigene expression is one of the key challenges of metabolic engineering for the development of cell factories. Constraints on translation initiation and early ribosome kinetics of mRNA are imposed by features of the 5'UTR in combination with the start of the gene, referred to as the "gene ramp", such as rare codons and mRNA secondary structures. These features strongly influence the translation yield and protein quality by regulating the ribosome distribution on mRNA strands. The utilization of genetic expression sequences, such as promoters and 5'UTRs in combination with different target genes, leads to a wide variety of gene ramp compositions with irregular translation rates, leading to unpredictable levels of protein yield and quality. Here, we present the Standard Intein Gene Expression Ramp (SIGER) system for controlling protein expression. The SIGER system makes use of inteins to decouple the translation initiation features from the gene of a target protein. We generated sequence-specific gene expression sequences for two inteins (DnaB and DnaX) that display defined levels of protein expression. Additionally, we used inteins that possess the ability to release the C-terminal fusion protein in vivo to avoid the impairment of protein functionality by the fused intein. Overall, our results show that SIGER systems are unique tools to mitigate the undesirable effects of gene ramp variation and to control the relative ratios of enzymes involved in molecular pathways. As a proof of concept of the potential of the system, we also used a SIGER system to express two difficult-to-produce proteins, GumM and CBM73.

Modelling ribosome kinetics and translational control on dynamic mRNA

The control of protein synthesis and the overall levels of various proteins in the cell is critical for achieving homoeostasis. Regulation of protein levels can occur at the transcriptional level, where the total number of messenger RNAs in the overall transcriptome are controlled, or at the translational level, where interactions of proteins and ribosomes with the messenger RNA determine protein translational efficiency. Although transcriptional control of mRNA levels is the most commonly used regulatory control mechanism in cells, positive-sense single-stranded RNA viruses often utilise translational control mechanisms to regulate their proteins in the host cell. Here I detail a computational method for stochastically simulating protein synthesis on a dynamic messenger RNA using the Gillespie algorithm, where the mRNA is allowed to co-translationally fold in response to ribosome movement. Applying the model to the test case of the bacteriophage MS2 virus, I show that the models ability to accurately reproduce experimental measurements of coat protein production and translational repression of the viral RNA dependant RNA polymerase at high coat protein concentrations. The computational techniques reported here open up the potential to examine the infection dynamics of a ssRNA virus in a host cell at the level of the genomic RNA, as well as examine general translation control mechanisms present in polycistronic mRNAs.

Mechanisms governing codon usage bias and the implications for protein expression in the chloroplast of Chlamydomonas reinhardtii

Chloroplasts possess a considerably reduced genome that is decoded via an almost minimal set of tRNAs. These features make an excellent platform for gaining insights into fundamental mechanisms that govern protein expression. Here, we present a comprehensive and revised perspective of the mechanisms that drive codon selection in the chloroplast of Chlamydomonas reinhardtii and the functional consequences for protein expression. In order to extract this information, we applied several codon usage descriptors to genes with different expression levels. We show that highly expressed genes strongly favor translationally optimal codons, while genes with lower functional importance are rather affected by directional mutational bias. We demonstrate that codon optimality can be deduced from codon-anticodon pairing affinity and, for a small number of amino acids (leucine, arginine, serine, and isoleucine), tRNA concentrations. Finally, we review, analyze, and expand on the impact of codon usage on protein yield, secondary structures of mRNA, translation initiation and termination, and amino acid composition of proteins, as well as cotranslational protein folding. The comprehensive analysis of codon choice provides crucial insights into heterologous gene expression in the chloroplast of C. reinhardtii, which may also be applicable to other chloroplast-containing organisms and bacteria.

Increasing the Thermodynamic Driving Force of the Phosphofructokinase Reaction in Clostridium thermocellum

The ability to control the distribution of thermodynamic driving force throughout a metabolic pathway is likely to be an important tool for metabolic engineering. The phosphofructokinase reaction is a key enzyme in Embden-Mayerhof-Parnas glycolysis and therefore improving the thermodynamic driving force of this reaction in C. thermocellum is believed to enable higher product titers.

Automated model-predictive design of synthetic promoters to control transcriptional profiles in bacteria

Transcription rates are regulated by the interactions between RNA polymerase, sigma factor, and promoter DNA sequences in bacteria. However, it remains unclear how non-canonical sequence motifs collectively control transcription rates. Here, we combine massively parallel assays, biophysics, and machine learning to develop a 346-parameter model that predicts site-specific transcription initiation rates for any σ70 promoter sequence, validated across 22132 bacterial promoters with diverse sequences. We apply the model to predict genetic context effects, design σ70 promoters with desired transcription rates, and identify undesired promoters inside engineered genetic systems. The model provides a biophysical basis for understanding gene regulation in natural genetic systems and precise transcriptional control for engineering synthetic genetic systems.

Design of 5′-UTR to Enhance Keratinase Activity in Bacillus subtilis

Keratinase is an important industrial enzyme, but its application performance is limited by its low activity. A rational design of 5′-UTRs that increases translation efficiency is an important approach to enhance protein expression. Herein, we optimized the 5′-UTR of the recombinant keratinase KerZ1 expression element to enhance its secretory activity in Bacillus subtilis WB600 through Spacer design, RBS screening, and sequence simplification. First, the A/U content in Spacer was increased by the site-directed saturation mutation of G/C bases, and the activity of keratinase secreted by mutant strain B. subtilis WB600-SP was 7.94 times higher than that of KerZ1. Subsequently, the keratinase activity secreted by the mutant strain B. subtilis WB600-SP-R was further increased to 13.45 times that of KerZ1 based on the prediction of RBS translation efficiency and the multi-site saturation mutation screening. Finally, the keratinase activity secreted by the mutant strain B. subtilis WB600-SP-R-D reached 204.44 KU mL−1 by reducing the length of the 5′ end of the 5′-UTR, which was 19.70 times that of KerZ1. In a 5 L fermenter, the keratinase activity secreted by B. subtilis WB600-SP-R-D after 25 h fermentation was 797.05 KU mL−1, which indicated its high production intensity. Overall, the strategy of this study and the obtained keratinase mutants will provide a good reference for the expression regulation of keratinase and other industrial enzymes.

Mitochondrial mRNA localization is governed by translation kinetics and spatial transport

For many nuclear-encoded mitochondrial genes, mRNA localizes to the mitochondrial surface co-translationally, aided by the association of a mitochondrial targeting sequence (MTS) on the nascent peptide with the mitochondrial import complex. For a subset of these co-translationally localized mRNAs, their localization is dependent on the metabolic state of the cell, while others are constitutively localized. To explore the differences between these two mRNA types we developed a stochastic, quantitative model for MTS-mediated mRNA localization to mitochondria in yeast cells. This model includes translation, applying gene-specific kinetics derived from experimental data; and diffusion in the cytosol. Even though both mRNA types are co-translationally localized we found that the steady state number, or density, of ribosomes along an mRNA was insufficient to differentiate the two mRNA types. Instead, conditionally-localized mRNAs have faster translation kinetics which modulate localization in combination with changes to diffusive search kinetics across metabolic states. Our model also suggests that the MTS requires a maturation time to become competent to bind mitochondria. Our work indicates that yeast cells can regulate mRNA localization to mitochondria by controlling mitochondrial volume fraction (influencing diffusive search times) and gene translation kinetics (adjusting mRNA binding competence) without the need for mRNA-specific binding proteins. These results shed light on both global and gene-specific mechanisms that enable cells to alter mRNA localization in response to changing metabolic conditions.

Deciphering the Rules of Ribosome Binding Site Differentiation in Context Dependence

The ribosome binding site (RBS) is a crucial element regulating translation. However, the activity of RBS is poorly predictable, because it is strongly affected by the local possible secondary structure, that is, context dependence. By the Flowseq technique, over 20 000 RBS variants were sorted and sequenced, and the translation of multiple genes under the same RBS was quantitatively characterized to evaluate the context dependence of each RBS variant in E. coli. Two regions, (-7 to -2) and (-17 to -12), of RBS were predicted with a higher possibility to pair with each other to slow down the translation initiation. Associations between phenotypes and the intrinsic factors suspected to affect translation efficiency and context dependence of the RBS, including nucleotide bias at each position, free energy, and conservation, were disentangled. The results showed that translation efficiency was influenced more significantly by conservation of the SD region (-16 to -8), while an AC-rich spacer region (-7 to -1) was associated with low context dependence. We confirmed these characteristics using a series of synthesized RBSs. The average correlation between multiple reporters was significantly higher for RBSs with an AC-rich spacer (0.714) compared with a GU-rich spacer (0.286). Overall, we proposed general design criteria to improve programmability and minimize context dependence of RBS. The characteristics unraveled here can be adapted to other bacteria for fine-tuning target-gene expression.

Characterizing and Improving pET Vectors for Cell-free Expression

Cell-free protein synthesis (CFPS) is an in vitro process that enables diverse applications in research, biomanufacturing, point-of-care diagnostics, therapeutics, and education using minimal laboratory equipment and reagents. One of the major limitations of CFPS implementation is its sensitivity to plasmid type. Specifically, plasmid templates based on commonly used vector backbones such as the pET series of bacterial expression vectors result in the inferior production of proteins. To overcome this limitation, we have evaluated the effect of expression cassette elements present in the pET30 vector on protein production across three different CFPS systems: NEBExpress, PURExpress, and CFAI-based E. coli extracts. Through the systematic elimination of genetic elements within the pET30 vector, we have identified elements that are responsible for the poor performance of pET30 vectors in the various CFPS systems. As a result, we demonstrate that through the removal of the lac operator (lacO) and N-terminal tags included in the vector backbone sequence, a pET vector can support high titers of protein expression when using extract-based CFPS systems. This work provides two key advances for the research community: 1) identification of vector sequence elements that affect robust production of proteins; 2) evaluation of expression across three unique CFPS systems including CFAI extracts, NEBexpress, and PURExpress. We anticipate that this work will improve access to CFPS by enabling researchers to choose the correct expression backbone within the context of their preferred expression system.

Machine Learning Guided Batched Design of a Bacterial Ribosome Binding Site

Optimization of gene expression levels is an essential part of the organism design process. Fine control of this process can be achieved by engineering transcription and translation control elements, including the ribosome binding site (RBS). Unfortunately, the design of specific genetic parts remains challenging because of the lack of reliable design methods. To address this problem, we have created a machine learning guided Design-Build-Test-Learn (DBTL) cycle for the experimental design of bacterial RBSs to demonstrate how small genetic parts can be reliably designed using relatively small, high-quality data sets. We used Gaussian Process Regression for the Learn phase of the cycle and the Upper Confidence Bound multiarmed bandit algorithm for the Design of genetic variants to be tested in vivo. We have integrated these machine learning algorithms with laboratory automation and high-throughput processes for reliable data generation. Notably, by Testing a total of 450 RBS variants in four DBTL cycles, we have experimentally validated RBSs with high translation initiation rates equaling or exceeding our benchmark RBS by up to 34%. Overall, our results show that machine learning is a powerful tool for designing RBSs, and they pave the way toward more complicated genetic devices.

Binding of 30S Ribosome Induces Single-stranded Conformation Within and Downstream of the Expression Platform in a Translational Riboswitch

Translational riboswitches are bacterial gene regulatory elements found in the 5'-untranslated region of mRNAs. They operate through a conformational refolding reaction that is triggered by a concentration change of a modulating small molecular ligand. The translation initiation region (TIR) is either released from or incorporated into base pairing interactions through the conformational switch. Hence, initiation of translation is regulated by the accessibility of the Shine-Dalgarno sequence and start codon. Interaction with the 30S ribosome is indispensable for the structural switch between functional OFF and ON states. However, on a molecular level it is still not fully resolved how the ribosome is accommodated near or at the translation initiation region in the context of translational riboswitches. The standby model of translation initiation postulates a binding site where the mRNA enters the ribosome and where it resides until the initiation site becomes unstructured and accessible. We here investigated the adenine-sensing riboswitch from Vibrio vulnificus. By application of a ¹⁹F labelling strategy for NMR spectroscopy that utilizes ligation techniques to synthesize differentially ¹⁹F labelled riboswitch molecules we show that nucleotides directly downstream of the riboswitch domain are first involved in productive interaction with the 30S ribosomal subunit. Upon the concerted action of ligand and the ribosomal protein rS1 the TIR becomes available and subsequently the 30S ribosome can slide towards the TIR. It will be interesting to see whether this is a general feature in translational riboswitches or if riboswitches exist where this region is structured and represent yet another layer of regulation.

Removing the Obstacle to (-)-Menthol Biosynthesis by Building a Microbial Cell Factory of (+)-cis-Isopulegone from (-)-Limonene

Microbial synthesis of plant-based (-)-menthol is of great interest because of its high demand (≈30 kiloton per year) as well as unique odor and cooling characteristics. However, this remains a great challenge due to the yet unfilled gap between (-)-limonene and (+)-cis-isopulegone. Herein, the first artificial and effective system was developed for (+)-cis-isopulegone biosynthesis from (-)-limonene by recruiting two bacterial enzymes to replace their inefficient counterparts from Mentha piperita, limonene-3-hydroxylase, and isopiperitenol dehydrogenase. A cofactor self-regenerative recombinant Escherichia coli strain was constructed by introducing a formate dehydrogenase for nicotinamide adenine dinucleotide phosphate (NADPH) regeneration and an engineered microbial isopiperitenol dehydrogenase. The production of (+)-cis-isopulegone (up to 281.2 mg L^-1 ) was improved by 36 times compared with that of the initial strain. This work lays a reliable foundation for the microbial synthesis of (-)-menthol.

Synthetic Biology Tool Development Advances Predictable Gene Expression in the Metabolically Versatile Soil Bacterium Rhodopseudomonas palustris

Harnessing the unique biochemical capabilities of non-model microorganisms would expand the array of biomanufacturing substrates, process conditions, and products. There are non-model microorganisms that fix nitrogen and carbon dioxide, derive energy from light, catabolize methane and lignin-derived aromatics, are tolerant to physiochemical stresses and harsh environmental conditions, store lipids in large quantities, and produce hydrogen. Model microorganisms often only break down simple sugars and require low stress conditions, but they have been engineered for the sustainable manufacture of numerous products, such as fragrances, pharmaceuticals, cosmetics, surfactants, and specialty chemicals, often by using tools from synthetic biology. Transferring complex pathways has proven to be exceedingly difficult, as the cofactors, cellular conditions, and energy sources necessary for this pathway to function may not be present in the host organism. Utilization of unique biochemical capabilities could also be achieved by engineering the host; although, synthetic biology tools developed for model microbes often do not perform as designed in other microorganisms. The metabolically versatile Rhodopseudomonas palustris CGA009, a purple non-sulfur bacterium, catabolizes aromatic compounds derived from lignin in both aerobic and anaerobic conditions and can use light, inorganic, and organic compounds for its source of energy. R. palustris utilizes three nitrogenase isozymes to fulfill its nitrogen requirements while also generating hydrogen. Furthermore, the bacterium produces two forms of RuBisCo in response to carbon dioxide/bicarbonate availability. While this potential chassis harbors many beneficial traits, stable heterologous gene expression has been problematic due to its intrinsic resistance to many antibiotics and the lack of synthetic biology parts investigated in this microbe. To address these problems, we have characterized gene expression and plasmid maintenance for different selection markers, started a synthetic biology toolbox specifically for the photosynthetic R. palustris, including origins of replication, fluorescent reporters, terminators, and 5′ untranslated regions, and employed the microbe’s endogenous plasmid for exogenous protein production. This work provides essential synthetic biology tools for engineering R. palustris’ many unique biochemical processes and has helped define the principles for expressing heterologous genes in this promising microbe through a methodology that could be applied to other non-model microorganisms.

Polyrotaxanes and the pump paradigm

The year 2022 marks the 30th anniversary of the first reports of polyrotaxanes in the scientific literature.

Vectorial channeling as a mechanism for translational control by functional prions and condensates

Translation of messenger RNA (mRNA) is regulated through a diverse set of RNA-binding proteins. A significant fraction of RNA-binding proteins contains prion-like domains which form functional prions. This raises the question of how prions can play a role in translational control. Local control of translation in dendritic spines by prions has been invoked in the mechanism of synaptic plasticity and memory. We show how channeling through diffusion and processive translation cooperate in highly ordered mRNA/prion aggregates as well as in less ordered mRNA/protein condensates depending on their substructure. We show that the direction of translational control, whether it is repressive or activating, depends on the polarity of the mRNA distribution in mRNA/prion assemblies which determines whether vectorial channeling can enhance recycling of ribosomes. Our model also addresses the effect of changes of substrate concentration in assemblies that have been suggested previously to explain translational control by assemblies through the introduction of a potential of mean force biasing diffusion of ribosomes inside the assemblies. The results from the model are compared with the experimental data on translational control by two functional RNA-binding prions, CPEB involved in memory and Rim4 involved in gametogenesis.

Metabolic Engineering of Escherichia coli for Production of α-Santalene, a Precursor of Sandalwood Oil

α-Santalene belongs to a class of natural compounds with many physiological functions and medical applications. Advances in metabolic engineering enable non-native hosts (e.g., Escherichia coli) to produce α-santalene, the precursor of sandalwood oil. However, imbalances in enzymatic activity often result in a metabolic burden on hosts and repress the synthetic capacity of the desired product. In this work, we manipulated ribosome binding sites (RBSs) to optimize an α-santalene synthetic operon in E. coli, and the best engineered E. coli NA-IS_3D strain could produce α-santalene at a titer of 412 mg·L^-1. Concerning the observation of the inverse correlation between indole synthesis and α-santalene production, this study speculated that indole-associated amino acid metabolism would be competitive to the synthesis of α-santalene rather than indole toxicity itself. The deletion of tnaA could lead to a 1.5-fold increase in α-santalene production to a titer of 599 mg·L^-1 in E. coli tnaA^- NA-IS_3D. Our results suggested that the optimization of RBS sets of the synthetic module and attenuation of the competitive pathway are promising approaches for improving the production of terpenoids including α-santalene.

Importance of the 5' regulatory region to bacterial synthetic biology applications

The field of synthetic biology is evolving at a fast pace. It is advancing beyond single-gene alterations in single hosts to the logical design of complex circuits and the development of integrated synthetic genomes. Recent breakthroughs in deep learning, which is increasingly used in de novo assembly of DNA components with predictable effects, are also aiding the discipline. Despite advances in computing, the field is still reliant on the availability of pre-characterized DNA parts, whether natural or synthetic, to regulate gene expression in bacteria and make valuable compounds. In this review, we discuss the different bacterial synthetic biology methodologies employed in the creation of 5' regulatory regions - promoters, untranslated regions and 5'-end of coding sequences. We summarize methodologies and discuss their significance for each of the functional DNA components, and highlight the key advances made in bacterial engineering by concentrating on their flaws and strengths. We end the review by outlining the issues that the discipline may face in the near future.

Tuning Cell-Free Composition Controls the Time Delay, Dynamics, and Productivity of TX-TL Expression

The composition of cell-free expression systems (TX-TL) is adjusted by adding macromolecular crowding agents and salts. However, the effects of these cosolutes on the dynamics of individual gene expression processes have not been quantified. Here, we carry out kinetic mRNA and protein level measurements on libraries of genetic constructs using the common cosolutes PEG-8000, Ficoll-400, and magnesium glutamate. By combining these measurements with biophysical modeling, we show that cosolutes have differing effects on transcription initiation, translation initiation, and translation elongation rates with trade-offs between time delays, expression tunability, and maximum expression productivity. We also confirm that biophysical models can predict translation initiation rates in TX-TL using Escherichia coli lysate. We discuss how cosolute composition can be tuned to maximize performance across different cell-free applications, including biosensing, diagnostics, and biomanufacturing.

A 68-codon genetic code to incorporate four distinct non-canonical amino acids enabled by automated orthogonal mRNA design

Orthogonal (O) ribosome-mediated translation of O-mRNAs enables the incorporation of up to three distinct non-canonical amino acids (ncAAs) into proteins in Escherichia coli (E. coli). However, the general and efficient incorporation of multiple distinct ncAAs by O-ribosomes requires scalable strategies for both creating efficiently and specifically translated O-mRNAs, and the compact expression of multiple O-aminoacyl-tRNA synthetase (O-aaRS)/O-tRNA pairs. We automate the discovery of O-mRNAs that lead to up to 40 times more protein, and are up to 50-fold more orthogonal, than previous O-mRNAs; protein yields from our O-mRNAs match or exceed those from wild-type mRNAs. These advances enable a 33-fold increase in yield for incorporating three distinct ncAAs. We automate the creation of operons for O-tRNA genes, and develop operons for O-aaRS genes. Combining our advances creates a 68-codon, 24-amino-acid genetic code to efficiently incorporate four distinct ncAAs into a single protein in response to four distinct quadruplet codons.

Identification of New Chromosomal Loci Involved in com Genes Expression and Natural Transformation in the Actinobacterial Model Organism Micrococcus luteus

Historically, Micrococcus luteus was one of the first organisms used to study natural transformation, one of the main routes of horizontal gene transfer among prokaryotes. However, little is known about the molecular basis of competence development in M. luteus or any other representative of the phylum of high-GC Gram-positive bacteria (Actinobacteria), while this means of genetic exchange has been studied in great detail in Gram-negative and low-GC Gram-positive bacteria (Firmicutes). In order to identify new genetic elements involved in regulation of the comEA-comEC competence operon in M. luteus, we conducted random chemical mutagenesis of a reporter strain expressing lacZ under the control of the comEA-comEC promoter, followed by the screening of dysregulated mutants. Mutants with (i) upregulated com promoter under competence-repressing conditions and (ii) mutants with a repressed com promoter under competence-inducing conditions were isolated. After genotype and phenotype screening, the genomes of several mutant strains were sequenced. A selection of putative com-influencing mutations was reinserted into the genome of the M. luteus reporter strain as markerless single-nucleotide mutations to confirm their effect on com gene expression. This strategy revealed mutations affecting com gene expression at genetic loci different from previously known genes involved in natural transformation. Several of these mutations decreased transformation frequencies by several orders of magnitude, thus indicating significant roles in competence development or DNA acquisition in M. luteus. Among the identified loci, there was a new locus containing genes with similarity to genes of the tad clusters of M. luteus and other bacteria.

Quantitative Control for Stoichiometric Protein Synthesis

Bacterial protein synthesis rates have evolved to maintain preferred stoichiometries at striking precision, from the components of protein complexes to constituents of entire pathways. Setting relative protein production rates to be well within a factor of two requires concerted tuning of transcription, RNA turnover, and translation, allowing many potential regulatory strategies to achieve the preferred output. The last decade has seen a greatly expanded capacity for precise interrogation of each step of the central dogma genome-wide. Here, we summarize how these technologies have shaped the current understanding of diverse bacterial regulatory architectures underpinning stoichiometric protein synthesis. We focus on the emerging expanded view of bacterial operons, which encode diverse primary and secondary mRNA structures for tuning protein stoichiometry. Emphasis is placed on how quantitative tuning is achieved. We discuss the challenges and open questions in the application of quantitative, genome-wide methodologies to the problem of precise protein production. Expected final online publication date for the Annual Review of Microbiology, Volume 75 is October 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Sigma factor dependent translational activation in Bacillus subtilis

Sigma factors are an important class of bacterial transcription factors that lend specificity to RNA polymerases by binding to distinct promoter elements for genes in their regulons. Here we show that activation of the general stress sigma factor, σB, in Bacillus subtilis paradoxically leads to dramatic induction of translation for a subset of its regulon genes. These genes are translationally repressed when transcribed by the housekeeping sigma factor, σA, owing to extended RNA secondary structures as determined in vivo using DMS-MaPseq. Transcription from σB-dependent promoters ablates the secondary structures and activates translation, leading to dual induction. Translation efficiencies between σB- and σA-dependent RNA isoforms can vary by up to 100-fold, which in multiple cases exceeds the magnitude of transcriptional induction. These results highlight the role of long-range RNA folding in modulating translation and demonstrate that a transcription factor can regulate protein synthesis beyond its effects on transcript levels.

Metabolic engineering strategy for synthetizing trans-4-hydroxy-L-proline in microorganisms

Trans-4-hydroxy-L-proline is an important amino acid that is widely used in medicinal and industrial applications, particularly as a valuable chiral building block for the organic synthesis of pharmaceuticals. Traditionally, trans-4-hydroxy-L-proline is produced by the acidic hydrolysis of collagen, but this process has serious drawbacks, such as low productivity, a complex process and heavy environmental pollution. Presently, trans-4-hydroxy-L-proline is mainly produced via fermentative production by microorganisms. Some recently published advances in metabolic engineering have been used to effectively construct microbial cell factories that have improved the trans-4-hydroxy-L-proline biosynthetic pathway. To probe the potential of microorganisms for trans-4-hydroxy-L-proline production, new strategies and tools must be proposed. In this review, we provide a comprehensive understanding of trans-4-hydroxy-L-proline, including its biosynthetic pathway, proline hydroxylases and production by metabolic engineering, with a focus on improving its production.

Parallel reaction pathways accelerate folding of a guanine quadruplex

G-quadruplexes (G4s) are four-stranded, guanine-rich nucleic acid structures that can influence a variety of biological processes such as the transcription and translation of genes and DNA replication. In many cases, a single G4-forming nucleic acid sequence can adopt multiple different folded conformations that interconvert on biologically relevant timescales, entropically stabilizing the folded state. The coexistence of different folded conformations also suggests that there are multiple pathways leading from the unfolded to the folded state ensembles, potentially modulating the folding rate and biological activity. We have developed an experimental method for quantifying the contributions of individual pathways to the folding of conformationally heterogeneous G4s that is based on mutagenesis, thermal hysteresis kinetic experiments and global analysis, and validated our results using photocaged kinetic NMR experiments. We studied the regulatory Pu22 G4 from the c-myc oncogene promoter, which adopts at least four distinct folded isomers. We found that the presence of four parallel pathways leads to a 2.5-fold acceleration in folding; that is, the effective folding rate from the unfolded to folded ensembles is 2.5 times as large as the rate constant for the fastest individual pathway. Since many G4 sequences can adopt many more than four isomers, folding accelerations of more than an order of magnitude are possible via this mechanism.

An Automated Model Test System for Systematic Development and Improvement of Gene Expression Models

Gene expression models greatly accelerate the engineering of synthetic metabolic pathways and genetic circuits by predicting sequence-function relationships and reducing trial-and-error experimentation. However, developing models with more accurate predictions remains a significant challenge. Here we present a model test system that combines advanced statistics, machine learning, and a database of 9862 characterized genetic systems to automatically quantify model accuracies, accept or reject mechanistic hypotheses, and identify areas for model improvement. We also introduce model capacity, a new information theoretic metric for correct cross-data-set comparisons. We demonstrate the model test system by comparing six models of translation initiation rate, evaluating 100 mechanistic hypotheses, and uncovering new sequence determinants that control protein expression levels. We then applied these results to develop a biophysical model of translation initiation rate with significant improvements in accuracy. Automated model test systems will dramatically accelerate the development of gene expression models, and thereby transition synthetic biology into a mature engineering discipline.

Engineering sensitivity and specificity of AraC-based biosensors responsive to triacetic acid lactone and orsellinic acid

We previously described the design of triacetic acid lactone (TAL) biosensor ‘AraC-TAL1’, based on the AraC regulatory protein. Although useful as a tool to screen for enhanced TAL biosynthesis, this variant shows elevated background (leaky) expression, poor sensitivity and relaxed inducer specificity, including responsiveness to orsellinic acid (OA). More sensitive biosensors specific to either TAL or OA can aid in the study and engineering of polyketide synthases that produce these and similar compounds. In this work, we employed a TetA-based dual-selection to isolate new TAL-responsive AraC variants showing reduced background expression and improved TAL sensitivity. To improve TAL specificity, OA was included as a ‘decoy’ ligand during negative selection, resulting in the isolation of a TAL biosensor that is inhibited by OA. Finally, to engineer OA-specific AraC variants, the iterative protein redesign and optimization computational framework was employed, followed by 2 rounds of directed evolution, resulting in a biosensor with 24-fold improved OA/TAL specificity, relative to AraC-TAL1.

Pairs of amino acids at the P- and A-sites of the ribosome predictably and causally modulate translation-elongation rates

Variation in translation-elongation kinetics along a transcript's coding sequence plays an important role in the maintenance of cellular protein homeostasis by regulating co-translational protein folding, localization, and maturation. Translation-elongation speed is influenced by molecular factors within mRNA and protein sequences. For example, the presence of proline in the ribosome's P- or A-site slows down translation, but the effect of other pairs of amino acids, in the context of all 400 possible pairs, has not been characterized. Here, we study Saccharomyces cerevisiae using a combination of bioinformatics, mutational experiments, and evolutionary analyses, and show that many different pairs of amino acids and their associated tRNA molecules predictably and causally encode translation rate information when these pairs are present in the A- and P-sites of the ribosome independent of other factors known to influence translation speed including mRNA structure, wobble base pairing, tripeptide motifs, positively charged upstream nascent chain residues, and cognate tRNA concentration. The fast-translating pairs of amino acids that we identify are enriched four-fold relative to the slow-translating pairs across Saccharomyces cerevisiae's proteome, while the slow-translating pairs are enriched downstream of domain boundaries. Thus, the chemical identity of amino acid pairs contributes to variability in translation rates, elongation kinetics are causally encoded in the primary structure of proteins, and signatures of evolutionary selection indicate their potential role in co-translational processes.

A deep learning approach to programmable RNA switches

Engineered RNA elements are programmable tools capable of detecting small molecules, proteins, and nucleic acids. Predicting the behavior of these synthetic biology components remains a challenge, a situation that could be addressed through enhanced pattern recognition from deep learning. Here, we investigate Deep Neural Networks (DNN) to predict toehold switch function as a canonical riboswitch model in synthetic biology. To facilitate DNN training, we synthesize and characterize in vivo a dataset of 91,534 toehold switches spanning 23 viral genomes and 906 human transcription factors. DNNs trained on nucleotide sequences outperform (R2 = 0.43-0.70) previous state-of-the-art thermodynamic and kinetic models (R2 = 0.04-0.15) and allow for human-understandable attention-visualizations (VIS4Map) to identify success and failure modes. This work shows that deep learning approaches can be used for functionality predictions and insight generation in RNA synthetic biology.

Modeling Loop Composition and Ion Concentration Effects in RNA Hairpin Folding Stability

The ability to accurately predict RNA hairpin structure and stability for different loop sequences and salt conditions is important for understanding, modeling, and designing larger RNA folds. However, traditional RNA secondary structure models cannot treat loop-sequence and ionic effects on RNA hairpin folding. Here, we describe a general, three-dimensional (3D) conformation-based computational method for modeling salt concentration-dependent conformational distributions and the detailed 3D structures for a set of three RNA hairpins that contain a variable, 15-nucleotide loop sequence. For a given RNA sequence, the new, to our knowledge, method integrates a Vfold2D two-dimensional structure folding model with IsRNA coarse-grained molecular dynamics 3D folding simulations and Monte Carlo tightly bound ion estimations of ion-mediated electrostatic interactions. The model predicts free-energy landscapes for the different RNA hairpin-forming sequences with variable salt conditions. The theoretically predicted results agree with the experimental fluorescence measurements, validating the strategy. Furthermore, the theoretical model goes beyond the experimental results by enabling in-depth 3D structural analysis, revealing energetic mechanisms for the sequence- and salt-dependent folding stability. Although the computational framework presented here is developed for RNA hairpin systems, the general method may be applied to investigate other RNA systems, such as multiway junctions or pseudoknots in mixed metal ion solutions.

The Ongoing Quest to Crack the Genetic Code for Protein Production

Understanding the genetic design principles that determine protein production remains a major challenge. Although the key principles of gene expression were discovered 50 years ago, additional factors are still being uncovered. Both protein-coding and non-coding sequences harbor elements that collectively influence the efficiency of protein production by modulating transcription, mRNA decay, and translation. The influences of many contributing elements are intertwined, which complicates a full understanding of the individual factors. In natural genes, a functional balance between these factors has been obtained in the course of evolution, whereas for genetic-engineering projects, our incomplete understanding still limits optimal design of synthetic genes. However, notable advances have recently been made, supported by high-throughput analysis of synthetic gene libraries as well as by state-of-the-art biomolecular techniques. We discuss here how these advances further strengthen understanding of the gene expression process and how they can be harnessed to optimize protein production.

Plasmid Design for Tunable Two-Enzyme Co-Expression Promotes Whole-Cell Production of Cellobiose

Catalyst development for biochemical cascade reactions often follows a "whole-cell-approach" in which a single microbial cell is made to express all required enzyme activities. Although attractive in principle, the approach can encounter limitations when efficient overall flux necessitates precise balancing between activities. This study shows an effective integration of major design strategies from synthetic biology to a coherent development of plasmid vectors, enabling tunable two-enzyme co-expression in E. coli, for whole-cell-production of cellobiose. An efficient transformation of sucrose and glucose into cellobiose by a parallel (countercurrent) cascade of disaccharide phosphorylases requires the enzyme co-expression to cope with large differences in specific activity of cellobiose phosphorylase (14 U mg^-1 ) and sucrose phosphorylase (122 U mg^-1 ). Mono- and bicistronic co-expression strategies controlling transcription, transcription-translation coupling or plasmid replication are analyzed for effect on activity and stable producibility of the whole-cell-catalyst. A key role of bom (basis of mobility) for plasmid stability dependent on the ori is reported and the importance of RBS (ribosome binding site) strength is demonstrated. Whole cell catalysts show high specific rates (460 µmol cellobiose min^-1  g^-1 dry cells) and performance metrics (30 g L^-1 ; ∼82% yield; 3.8 g L^-1 h^-1 overall productivity) promising for cellobiose production.

Fully biological production of adipic acid analogs from branched catechols

Microbial production of adipic acid from lignin-derived monomers, such as catechol, is a greener alternative to the petrochemical-based process. Here, we produced adipic acid from catechol using catechol 1,2-dioxygenase (CatA) and a muconic acid reductase (MAR) in Escherichia coli. As the reaction progressed, the pH of the media dropped from 7 to 4-5 and the muconic acid isomerized from the cis,cis (ccMA) to the cis,trans (ctMA) isomer. Feeding experiments suggested that cells preferentially uptook ctMA and that MAR efficiently reduced all muconic isomers to adipic acid. Intrigued by the substrate promiscuity of MAR, we probed its utility to produce branched chiral diacids. Using branched catechols likely found in pretreated lignin, we found that while MAR fully reduced 2-methyl-muconic acid to 2-methyl-adipic acid, MAR reduced only one double bond in 3-substituted muconic acids. In the future, MAR's substrate promiscuity could be leveraged to produce chiral-branched adipic acid analogs to generate branched, nylon-like polymers with reduced crystallinity.