Translation rate is controlled by coupled trade-offs between site accessibility, selective RNA unfolding and sliding at upstream standby sites

Rational Design of Untranslated Regions to Enhance Gene Expression

How to improve gene expression by optimizing mRNA structures is a crucial question for various medical and biotechnological applications. Previous efforts focus largely on investigation of the 5' UTR hairpin structures. In this study, we present a rational strategy that enhances mRNA stability and translation by engineering both the 5' and 3' UTR sequences. We have successfully demonstrated this strategy using green fluorescent protein (GFP) as a model in Escherichia coli and across different expression vectors. We further validated it with luciferase and Plasmodium falciparum lactate dehydrogenase (PfLDH). To elucidate the underlying mechanism, we have quantitatively analyzed both protein, mRNA levels and half-life time. We have identified several key aspects of UTRs that significantly influence mRNA stability and protein expression in our system: (1) The optimal length of the single-stranded spacer between the stabilizer hairpin and ribosome binding site (RBS) in the 5' UTR is 25-30 nucleotide (nt) long. An optimal 32% GC content in the spacer yielded the highest levels of GFP protein production. (2) The insertion of a homodimerdizable, G-quadruplex structure containing RNA aptamer, "Corn", in the 3' UTR markedly increased the protein expression. Our findings indicated that the carefully engineered 5' UTRs and 3' UTRs significantly boosted gene expression. Specifically, the inclusion of 5 × Corn in the 3' UTR appeared to facilitate the local aggregation of mRNA, leading to the formation of mRNA condensates. Aside from shedding light on the regulation of mRNA stability and expression, this study is expected to substantially increase biological protein production.

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.

Transfer learning for cross-context prediction of protein expression from 5'UTR sequence

Model-guided DNA sequence design can accelerate the reprogramming of living cells. It allows us to engineer more complex biological systems by removing the need to physically assemble and test each potential design. While mechanistic models of gene expression have seen some success in supporting this goal, data-centric, deep learning-based approaches often provide more accurate predictions. This accuracy, however, comes at a cost - a lack of generalization across genetic and experimental contexts that has limited their wider use outside the context in which they were trained. Here, we address this issue by demonstrating how a simple transfer learning procedure can effectively tune a pre-trained deep learning model to predict protein translation rate from 5' untranslated region (5'UTR) sequence for diverse contexts in Escherichia coli using a small number of new measurements. This allows for important model features learnt from expensive massively parallel reporter assays to be easily transferred to new settings. By releasing our trained deep learning model and complementary calibration procedure, this study acts as a starting point for continually refined model-based sequence design that builds on previous knowledge and future experimental efforts.

Systematic promoter design for plasmid-encoded S-adenosylmethionine sensing systems

S-adenosylmethionine (SAM) is an important biomolecule that mainly acts as a methyl donor and plays many roles in a variety of biological functions. SAM is also required for the biosynthesis of valuable methylated compounds, but its supply is a bottleneck for these biosynthetic pathways. To overcome this bottleneck and to reconfigure SAM homeostasis, a high-throughput sensing system for changes in intracellular SAM availability is required. We constructed a plasmid that can detect the factors that can alter SAM availability using minimal components. It does so by placing a fluorescent protein under a promoter controlled by endogenous MetJ, a transcription factor that represses its own regulons upon binding with SAM. Next, to validate SAM-responsive behavior, we systematically reconstructed 10 synthetic promoters with different positions and with different number of metbox sites. We found that a position between the -35 box and the -10 box was the most effective for repression and that this setup was suitable for detecting the genetic or environmental factors that can deplete and recover the intracellular SAM availability. Overall, the response patterns of the synthetic MetJ-regulated promoters characterized in this study may be useful for the development of better SAM biosensing systems.

Establishing a straightforward I-SceI-mediated recombination one-plasmid system for efficient genome editing in P. putida KT2440

Pseudomonas putida has become an increasingly important chassis for producing valuable bioproducts. This development is not least due to the ever-improving genetic toolbox, including gene and genome editing techniques. Here, we present a novel, one-plasmid design of a critical genetic tool, the pEMG/pSW system, guaranteeing one engineering cycle to be finalized in 3 days. The pEMG/pSW system proved in the last decade to be valuable for targeted genome engineering in Pseudomonas, as it enables the deletion of large regions of the genome, the integration of heterologous gene clusters or the targeted generation of point mutations. Here, to expedite genetic engineering, two alternative plasmids were constructed: (1) The sacB gene from Bacillus subtilis was integrated into the I-SceI expressing plasmid pSW-2 as a counterselection marker to accelerated plasmid curing; (2) double-strand break introducing gene I-sceI and sacB counterselection marker were integrated into the backbone of the original pEMG vector, named pEMG-RIS. The single plasmid of pEMG-RIS allows rapid genome editing despite the low transcriptional activity of a single copy of the I-SceI encoding gene. Here, the usability of the pEMG-RIS is shown in P. putida KT2440 by integrating an expression cassette including an msfGFP gene in 3 days. In addition, a large fragment of 12.1 kb was also integrated. In summary, we present an updated pEMG/pSW genome editing system that allows efficient and rapid genome editing in P. putida. All plasmids designed in this study will be available via the Addgene platform.

From DNA to lytic proteins: transcription and translation of the bacteriophage T5 holin/endolysin operon

The analysis of transcriptional activity of the bacteriophage T5 hol/endo operon conducted in the paper revealed a strong constitutive promoter recognized by E. coli RNA polymerase and a transcription initiation point of the operon. It was also shown that the only translational start codon for holin was a non-canonical TTG. Translation initiation regions (TIRs) of both genes of the operon (hol and endo) were further analyzed using chimeric constructs, in which parts of the hol/endo regulatory regions were fused with the gene of a reporter protein (EGFP). It was found that TIR of hol was 20 times less effective than that of endo. As it turned out, the level of EGFP production was influenced by the composition of the constructs and the type of the hol start codon. Apparently, the translational suppression of holin's accumulation and posttranslational activation of endolysin by Ca2+ are the main factors ensuring the proper timing of the host cell lysis by bacteriophage T5. The approach based on the use of chimeric constructs proposed in the paper can be recommended for studying other native or artificial operons of any complexity: analyzing the impacts of separate DNA regions, as well as their coupled effect, on the processes of transcription and translation of recombinant protein(s).

Kinetics of programmed and spontaneous ribosome sliding along the mRNA

The ribosome can slide along mRNA without establishing codon-anticodon interactions. This movement can be regulated (programmed) by the elements encoded in the mRNA, as observed in bypassing of non-coding gap in gene 60 of bacteriophage T4, or occur spontaneously, such as during traversal by the 70S ribosome of the 3'UTRs or upon re-initiation on bacterial polycistronic genes. In this study, we investigate the kinetic mechanism underlying the programmed and spontaneous ribosome sliding. We show that the translation rate of gene 60 mRNA decreases as the ribosome approaches the take-off site, especially when the KKYK regulatory sequence in the nascent peptide reaches the constriction site in the ribosome exit tunnel. However, efficiency of bypassing increases when the ribosome traverses the gap quickly. With the non-coding gap exceeding the natural 50 nt, the processivity of sliding remains high up to 56 nt, but drops sharply beyond that due to the loss of mRNA elements support. Sliding efficiency is temperature-dependent; while temperature regulates the number of ribosomes initiating programmed bypassing, traversing the long gaps becomes increasingly unfavorable at lower temperatures. This data offers novel insights into the kinetic determinants of programmed and spontaneous ribosome sliding along the mRNA.

Inducible transposon mutagenesis for genome-scale forward genetics

Transposon insertion sequencing (Tn-seq) is a powerful method for genome-scale functional genetics in bacteria. However, its effectiveness is often limited by a lack of mutant diversity, caused by either inefficient transposon delivery or stochastic loss of mutants due to population bottlenecks. Here, we introduce "InducTn-seq", which leverages inducible mutagenesis for temporal control of transposition. InducTn-seq generates millions of transposon mutants from a single colony, enabling the sensitive detection of subtle fitness defects and transforming binary classifications of gene essentiality into a quantitative fitness measurement across both essential and non-essential genes. Using a mouse model of infectious colitis, we show that InducTn-seq bypasses a highly restrictive host bottleneck to generate a diverse transposon mutant population from the few cells that initiate infection, revealing the role of oxygen-related metabolic plasticity in pathogenesis. Overall, InducTn-seq overcomes the limitations of traditional Tn-seq, unlocking new possibilities for genome-scale forward genetic screens in bacteria.

5'UTR G-quadruplex structure enhances translation in size dependent manner

Translation initiation in bacteria is frequently regulated by various structures in the 5' untranslated region (5'UTR). Previously, we demonstrated that G-quadruplex (G4) formation in non-template DNA enhances transcription. In this study, we aim to explore how G4 formation in mRNA (RG4) at 5'UTR impacts translation using a T7-based in vitro translation system and in E. coli. We show that RG4 strongly promotes translation efficiency in a size-dependent manner. Additionally, inserting a hairpin upstream of the RG4 further enhances translation efficiency, reaching up to a 12-fold increase. We find that the RG4-dependent effect is not due to increased ribosome affinity, ribosome binding site accessibility, or mRNA stability. We propose a physical barrier model in which bulky structures in 5'UTR biases ribosome movement toward the downstream start codon, thereby increasing the translation output. This study provides biophysical insights into the regulatory role of 5'UTR structures in in vitro and bacterial translation, highlighting their potential applications in tuning gene expression.

A genetically encoded biosensor to monitor dynamic changes of c-di-GMP with high temporal resolution

Monitoring changes of signaling molecules and metabolites with high temporal resolution is key to understanding dynamic biological systems. Here, we use directed evolution to develop a genetically encoded ratiometric biosensor for c-di-GMP, a ubiquitous bacterial second messenger regulating important biological processes like motility, surface attachment, virulence and persistence. The resulting biosensor, cdGreen2, faithfully tracks c-di-GMP in single cells and with high temporal resolution over extended imaging times, making it possible to resolve regulatory networks driving bimodal developmental programs in different bacterial model organisms. We further adopt cdGreen2 as a simple tool for in vitro studies, facilitating high-throughput screens for compounds interfering with c-di-GMP signaling and biofilm formation. The sensitivity and versatility of cdGreen2 could help reveal c-di-GMP dynamics in a broad range of microorganisms with high temporal resolution. Its design principles could also serve as a blueprint for the development of similar, orthogonal biosensors for other signaling molecules, metabolites and antibiotics.

Utilizing 5' UTR Engineering Enables Fine-Tuning of Multiple Genes within Operons to Balance Metabolic Flux in Bacillus subtilis

The application of synthetic biology tools to modulate gene expression to increase yield has been thoroughly demonstrated as an effective and convenient approach in industrial production. In this study, we employed a high-throughput screening strategy to identify a 5' UTR sequence from the genome of B. subtilis 168. This sequence resulted in a 5.8-fold increase in the expression level of EGFP. By utilizing the 5' UTR sequence to overexpress individual genes within the rib operon, it was determined that the genes ribD and ribAB serve as rate-limiting enzymes in the riboflavin synthesis pathway. Constructing a 5' UTR library to regulate EGFP expression resulted in a variation range in gene expression levels exceeding 100-fold. Employing the same 5' UTR library to regulate the expression of EGFP and mCherry within the operon led to a change in the expression ratio of these two genes by over 10,000-fold. So, employing a 5' UTR library to modulate the expression of the rib operon gene and construct a synthetic rib operon resulted in a 2.09-fold increase in riboflavin production. These results indicate that the 5' UTR sequence identified and characterized in this study can serve as a versatile synthetic biology toolkit for achieving complex metabolic network reconstruction. This toolkit can facilitate the fine-tuning of gene expression to produce target products.

Long-duration environmental biosensing by recording analyte detection in DNA using recombinase memory

Microbial biosensors that convert environmental information into real-time visual outputs are limited in their sensing abilities in complex environments, such as soil and wastewater, due to optical inaccessibility. Biosensors that could record transient exposure to analytes within a large time window for later retrieval represent a promising approach to solve the accessibility problem. Here, we test the performance of recombinase-memory biosensors that sense a sugar (arabinose) and a microbial communication molecule (3-oxo-C12-L-homoserine lactone) over 8 days (~70 generations) following analyte exposure. These biosensors sense the analyte and trigger the expression of a recombinase enzyme which flips a segment of DNA, creating a genetic memory, and initiates fluorescent protein expression. The initial designs failed over time due to unintended DNA flipping in the absence of the analyte and loss of the flipped state after exposure to the analyte. Biosensor performance was improved by decreasing recombinase expression, removing the fluorescent protein output, and using quantitative PCR to read out stored information. Application of memory biosensors in wastewater isolates achieved memory of analyte exposure in an uncharacterized Pseudomonas isolate. By returning these engineered isolates to their native environments, recombinase-memory systems are expected to enable longer duration and in situ investigation of microbial signaling, cross-feeding, community shifts, and gene transfer beyond the reach of traditional environmental biosensors.IMPORTANCEMicrobes mediate ecological processes over timescales that can far exceed the half-lives of transient metabolites and signals that drive their collective behaviors. We investigated strategies for engineering microbes to stably record their transient exposure to a chemical over many generations through DNA rearrangements. We identify genetic architectures that improve memory biosensor performance and characterize these in wastewater isolates. Memory biosensors are expected to be useful for monitoring cell-cell signals in biofilms, detecting transient exposure to chemical pollutants, and observing microbial cross-feeding through short-lived metabolites within cryptic methane, nitrogen, and sulfur cycling processes. They will also enable in situ studies of microbial responses to ephemeral environmental changes, or other ecological processes that are currently challenging to monitor non-destructively using real-time biosensors and analytical instruments.

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.

Essential factors, advanced strategies, challenges, and approaches involved for efficient expression of recombinant proteins in Escherichia coli

Producing recombinant proteins is a major accomplishment of biotechnology in the past century. Heterologous hosts, either eukaryotic or prokaryotic, are used for the production of these proteins. The utilization of microbial host systems continues to dominate as the most efficient and affordable method for biotherapeutics and food industry productions. Hence, it is crucial to analyze the limitations and advantages of microbial hosts to enhance the efficient production of recombinant proteins on a large scale. E. coli is widely used as a host for the production of recombinant proteins. Researchers have identified certain obstacles with this host, and given the growing demand for recombinant protein production, there is an immediate requirement to enhance this host. The following review discusses the elements contributing to the manifestation of recombinant protein. Subsequently, it sheds light on innovative approaches aimed at improving the expression of recombinant protein. Lastly, it delves into the obstacles and optimization methods associated with translation, mentioning both cis-optimization and trans-optimization, producing soluble recombinant protein, and engineering the metal ion transportation. In this context, a comprehensive description of the distinct features will be provided, and this knowledge could potentially enhance the expression of recombinant proteins in E. coli.

On the ever-growing functional versatility of the CRISPR-Cas13 system

CRISPR-Cas systems evolved in prokaryotes to implement a powerful antiviral immune response as a result of sequence-specific targeting by ribonucleoproteins. One of such systems consists of an RNA-guided RNA endonuclease, known as CRISPR-Cas13. In very recent years, this system is being repurposed in different ways in order to decipher and engineer gene expression programmes. Here, we discuss the functional versatility of the CRISPR-Cas13 system, which includes the ability for RNA silencing, RNA editing, RNA tracking, nucleic acid detection and translation regulation. This functional palette makes the CRISPR-Cas13 system a relevant tool in the broad field of systems and synthetic biology.

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.

Ribosome Profiling Methods Adapted to the Study of RNA-Dependent Translation Regulation in Staphylococcus aureus

Noncoding RNAs, including regulatory RNAs (sRNAs), are instrumental in regulating gene expression in pathogenic bacteria, allowing them to adapt to various stresses encountered in their host environments. Staphylococcus aureus is a well-studied model for RNA-mediated regulation of virulence and pathogenicity, with sRNAs playing significant roles in shaping S. aureus interactions with human and animal hosts. By modulating the translation and/or stability of target mRNAs, sRNAs regulate the synthesis of virulence factors and regulatory proteins required for pathogenesis. Moreover, perturbation of the levels of RNA modifications in two other classes of noncoding RNAs, rRNAs, and tRNAs, has been proposed to contribute to stress adaptation. However, the study of how these various factors affect translation regulation has often been restricted to specific genes, using in vivo reporters and/or in vitro translation systems. Genome-wide sequencing approaches offer novel perspectives for studying RNA-dependent regulation. In particular, ribosome profiling methods provide a powerful resource for characterizing the overall landscape of translational regulation, contributing to a better understanding of S. aureus physiopathology. Here, we describe protocols that we have adapted to perform ribosome profiling in S. aureus.

Systematic mining of the human microbiome identifies antimicrobial peptides with diverse activity spectra

Human-associated bacteria secrete modified peptides to control host physiology and remodel the microbiota species composition. Here we scanned 2,229 Human Microbiome Project genomes of species colonizing skin, gastrointestinal tract, urogenital tract, mouth and trachea for gene clusters encoding RiPPs (ribosomally synthesized and post-translationally modified peptides). We found 218 lanthipeptides and 25 lasso peptides, 70 of which were synthesized and expressed in E. coli and 23 could be purified and functionally characterized. They were tested for activity against bacteria associated with healthy human flora and pathogens. New antibiotics were identified against strains implicated in skin, nasal and vaginal dysbiosis as well as from oral strains selectively targeting those in the gut. Extended- and narrow-spectrum antibiotics were found against methicillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococci. Mining natural products produced by human-associated microbes will enable the elucidation of ecological relationships and may be a rich resource for antimicrobial discovery.

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.

5'UTR G-quadruplex structure enhances translation in size dependent manner

Translation initiation in bacteria is frequently regulated by various structures in the 5' untranslated region (5'UTR). Previously, we demonstrated that G-quadruplex (G4) formation in non-template DNA enhances transcription. In this study, we aimed to explore how G4 formation in mRNA (RG4) at 5'UTR impacts translation using a T7-based in vitro translation system and in E. coli. We showed that RG4 strongly promotes translation efficiency in a size-dependent manner. Additionally, inserting a hairpin upstream of the RG4 further enhances translation efficiency, reaching up to a 12-fold increase. We found that the RG4-dependent effect is not due to increased ribosome affinity, ribosome binding site accessibility, or mRNA stability. We proposed a physical barrier model in which bulky structures in 5'UTR prevent ribosome dislodging and thereby increase the translation output. This study provides biophysical insights into the regulatory role of 5'UTR structures in bacterial translation, highlighting their potential applications in tuning gene expression.

Generative and predictive neural networks for the design of functional RNA molecules

RNA is a remarkably versatile molecule that has been engineered for applications in therapeutics, diagnostics, and in vivo information-processing systems. However, the complex relationship between the sequence and structural properties of an RNA molecule and its ability to perform specific functions often necessitates extensive experimental screening of candidate sequences. Here we present a generalized neural network architecture that utilizes the sequence and structure of RNA molecules (SANDSTORM) to inform functional predictions. We demonstrate that this approach achieves state-of-the-art performance across several distinct RNA prediction tasks, while learning interpretable abstractions of RNA secondary structure. We paired these predictive models with generative adversarial RNA design networks (GARDN), allowing the generative modelling of novel mRNA 5' untranslated regions and toehold switch riboregulators exhibiting a predetermined fitness. This approach enabled the design of novel toehold switches with a 43-fold increase in experimentally characterized dynamic range compared to those designed using classic thermodynamic algorithms. SANDSTORM and GARDN thus represent powerful new predictive and generative tools for the development of diagnostic and therapeutic RNA molecules with improved function.

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.

Automated design of protein-binding riboswitches for sensing human biomarkers in a cell-free expression system

Cell-free genetically encoded biosensors have been developed to detect small molecules and nucleic acids, but they have yet to be reliably engineered to detect proteins. Here we develop an automated platform to convert protein-binding RNA aptamers into riboswitch sensors that operate within low-cost cell-free assays. We demonstrate the platform by engineering 35 protein-sensing riboswitches for human monomeric C-reactive protein, human interleukin-32γ, and phage MS2 coat protein. The riboswitch sensors regulate output expression levels by up to 16-fold with input protein concentrations within the human serum range. We identify two distinct mechanisms governing riboswitch-mediated regulation of translation rates and leverage computational analysis to refine the protein-binding aptamer regions, improving design accuracy. Overall, we expand the cell-free sensor toolbox and demonstrate how computational design is used to develop protein-sensing riboswitches with future applications as low-cost medical diagnostics.

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.

Ultradeep characterisation of translational sequence determinants refutes rare-codon hypothesis and unveils quadruplet base pairing of initiator tRNA and transcript

Translation is a key determinant of gene expression and an important biotechnological engineering target. In bacteria, 5'-untranslated region (5'-UTR) and coding sequence (CDS) are well-known mRNA parts controlling translation and thus cellular protein levels. However, the complex interaction of 5'-UTR and CDS has so far only been studied for few sequences leading to non-generalisable and partly contradictory conclusions. Herein, we systematically assess the dynamic translation from over 1.2 million 5'-UTR-CDS pairs in Escherichia coli to investigate their collective effect using a new method for ultradeep sequence-function mapping. This allows us to disentangle and precisely quantify effects of various sequence determinants of translation. We find that 5'-UTR and CDS individually account for 53% and 20% of variance in translation, respectively, and show conclusively that, contrary to a common hypothesis, tRNA abundance does not explain expression changes between CDSs with different synonymous codons. Moreover, the obtained large-scale data provide clear experimental evidence for a base-pairing interaction between initiator tRNA and mRNA beyond the anticodon-codon interaction, an effect that is often masked for individual sequences and therefore inaccessible to low-throughput approaches. Our study highlights the indispensability of ultradeep sequence-function mapping to accurately determine the contribution of parts and phenomena involved in gene regulation.

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.

CRISPR-dCas12a-mediated genetic circuit cascades for multiplexed pathway optimization

The production efficiency of microbial cell factories is sometimes limited by the lack of effective methods to regulate multiple targets in a coordinated manner. Here taking the biosynthesis of glucosamine-6-phosphate (GlcN6P) in Bacillus subtilis as an example, a 'design-build-test-learn' framework was proposed to achieve efficient multiplexed optimization of metabolic pathways. A platform strain was built to carry biosensor signal-amplifying circuits and two genetic regulation circuits. Then, a synthetic CRISPR RNA array blend for boosting and leading (ScrABBLE) device was integrated into the platform strain, which generated 5,184 combinatorial assemblies targeting three genes. The best GlcN6P producer was screened and engineered for the synthesis of valuable pharmaceuticals N-acetylglucosamine and N-acetylmannosamine. The N-acetylglucosamine titer reached 183.9 g liter-1 in a 15-liter bioreactor. In addition, the potential generic application of the ScrABBLE device was also verified using three fluorescent proteins as a case study.

Precision engineering of biological function with large-scale measurements and machine learning

As synthetic biology expands and accelerates into real-world applications, methods for quantitatively and precisely engineering biological function become increasingly relevant. This is particularly true for applications that require programmed sensing to dynamically regulate gene expression in response to stimuli. However, few methods have been described that can engineer biological sensing with any level of quantitative precision. Here, we present two complementary methods for precision engineering of genetic sensors: in silico selection and machine-learning-enabled forward engineering. Both methods use a large-scale genotype-phenotype dataset to identify DNA sequences that encode sensors with quantitatively specified dose response. First, we show that in silico selection can be used to engineer sensors with a wide range of dose-response curves. To demonstrate in silico selection for precise, multi-objective engineering, we simultaneously tune a genetic sensor's sensitivity (EC50) and saturating output to meet quantitative specifications. In addition, we engineer sensors with inverted dose-response and specified EC50. Second, we demonstrate a machine-learning-enabled approach to predictively engineer genetic sensors with mutation combinations that are not present in the large-scale dataset. We show that the interpretable machine learning results can be combined with a biophysical model to engineer sensors with improved inverted dose-response curves.

Initiation at AUGUG and GUGUG sequences can lead to translation of overlapping reading frames in E. coli

During initiation, the ribosome is tasked to efficiently recognize open reading frames (ORFs) for accurate and fast translation of mRNAs. A critical step is start codon recognition, which is modulated by initiation factors, mRNA structure, a Shine Dalgarno (SD) sequence and the start codon itself. Within the Escherichia coli genome, we identified more than 50 annotated initiation sites harboring AUGUG or GUGUG sequence motifs that provide two canonical start codons, AUG and GUG, in immediate proximity. As these sites may challenge start codon recognition, we studied if and how the ribosome is accurately guided to the designated ORF, with a special focus on the SD sequence as well as adenine at the fourth coding sequence position (A4). By in vitro and in vivo experiments, we characterized key requirements for unambiguous start codon recognition, but also discovered initiation sites that lead to the translation of both overlapping reading frames. Our findings corroborate the existence of an ambiguous translation initiation mechanism, implicating a multitude of so far unrecognized ORFs and translation products in bacteria.

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.

Flow-Seq Method: Features and Application in Bacterial Translation Studies

The Flow-seq method is based on using reporter construct libraries, where a certain element regulating the gene expression of fluorescent reporter proteins is represented in many thousands of variants. Reporter construct libraries are introduced into cells, sorted according to their fluorescence level, and then subjected to next-generation sequencing. Therefore, it turns out to be possible to identify patterns that determine the expression efficiency, based on tens and hundreds of thousands of reporter constructs in one experiment. This method has become common in evaluating the efficiency of protein synthesis simultaneously by multiple mRNA variants. However, its potential is not confined to this area. In the presented review, a comparative analysis of the Flow-seq method and other alternative approaches used for translation efficiency evaluation of mRNA was carried out; the features of its application and the results obtained by Flow-seq were also considered.

Functional expression of diverse post-translational peptide-modifying enzymes in Escherichia coli under uniform expression and purification conditions

RiPPs (ribosomally-synthesized and post-translationally modified peptides) are a class of pharmaceutically-relevant natural products expressed as precursor peptides before being enzymatically processed into their final functional forms. Bioinformatic methods have illuminated hundreds of thousands of RiPP enzymes in sequence databases and the number of characterized chemical modifications is growing rapidly; however, it remains difficult to functionally express them in a heterologous host. One challenge is peptide stability, which we addressed by designing a RiPP stabilization tag (RST) based on a small ubiquitin-like modifier (SUMO) domain that can be fused to the N- or C-terminus of the precursor peptide and proteolytically removed after modification. This is demonstrated to stabilize expression of eight RiPPs representative of diverse phyla. Further, using Escherichia coli for heterologous expression, we identify a common set of media and growth conditions where 24 modifying enzymes, representative of diverse chemistries, are functional. The high success rate and broad applicability of this system facilitates: (i) RiPP discovery through high-throughput “mining” and (ii) artificial combination of enzymes from different pathways to create a desired peptide.

A Universal Method for Developing Autoinduction Expression Systems Using AHL-Mediated Quorum-Sensing Circuits

A major challenge in engineering microorganisms for the desirable product is maintaining the rational balance between cell growth and production. Quorum sensing (QS)-based dynamic regulations provide a pathway-independent genetic control technology to rebalance metabolic flux for biomass and product synthesis. However, the lack of a universal method for screening QS elements and the complex design of autoinduction circuits limit their applications in metabolic engineering. Here, we developed a universal method for simple and rapid screening and evaluating various QS systems from Gram-negative bacteria, and the largest library containing 195 combinations of receiving device/signal molecules was constructed and evaluated in Escherichia coli. A simple logical circuit with different inducer synthesis rates was established to dynamically regulate gene expression levels, leading to efficient protein expression and product synthesis. The system was further applied in Pseudomonas putida, which indicated it could be widely accommodated in other microorganisms. Therefore, the method could be used in diverse Gram-negative strains for the desired biosynthesis.

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.

Sorption of Cellulases in Biofilm Enhances Cellulose Degradation by Bacillus subtilis

Biofilm commonly forms on the surfaces of cellulosic biomass but its roles in cellulose degradation remain largely unexplored. We used Bacillus subtilis to study possible mechanisms and the contributions of two major biofilm components, extracellular polysaccharides (EPS) and TasA protein, to submerged biofilm formation on cellulose and its degradation. We found that biofilm produced by B. subtilis is able to absorb exogenous cellulase added to the culture medium and also retain self-produced cellulase within the biofilm matrix. The bacteria that produced more biofilm degraded more cellulose compared to strains that produced less biofilm. Knockout strains that lacked both EPS and TasA formed a smaller amount of submerged biofilm on cellulose than the wild-type strain and also degraded less cellulose. Imaging of biofilm on cellulose suggests that bacteria, cellulose, and cellulases form cellulolytic biofilm complexes that facilitate synergistic cellulose degradation. This study brings additional insight into the important functions of biofilm in cellulose degradation and could potentiate the development of biofilm-based technology to enhance biomass degradation for biofuel production.

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 a New Fluorescent Protein for a Low Limit of Detection Sensing in the Cell-Free System

Cell-free protein synthesis-based biosensors have been developed as highly accurate, low-cost biosensors. However, since most biomarkers exist at low concentrations in various types of biopsies, the biosensor's dynamic range must be increased in the system to achieve low limits of detection necessary while deciphering from higher background signals. Many attempts to increase the dynamic range have relied on amplifying the input signal from the analyte, which can lead to complications of false positives. In this study, we aimed to increase the protein synthesis capability of the cell-free protein synthesis system and the output signal of the reporter protein to achieve a lower limit of detection. We utilized a new fluorescent protein, mNeonGreen, which produces a higher output than those commonly used in cell-free biosensors. Optimizations of DNA sequence and the subsequent cell-free protein synthesis reaction conditions allowed characterizing protein expression variability by given DNA template types, reaction environment, and storage additives that cause the greatest time constraint on designing the cell-free biosensor. Finally, we characterized the fluorescence kinetics of mNeonGreen compared to the commonly used reporter protein, superfolder green fluorescent protein. We expect that this finely tuned cell-free protein synthesis platform with the new reporter protein can be used with sophisticated synthetic gene circuitry networks to increase the dynamic range of a cell-free biosensor to reach lower detection limits and reduce the false-positive proportion.

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.

DeepTESR: A Deep Learning Framework to Predict the Degree of Translational Elongation Short Ramp for Gene Expression Control

Controlling translational elongation is essential for efficient protein synthesis. Ribosome profiling has revealed that the speed of ribosome movement is correlated with translational efficiency in the translational elongation ramp. In this work, we present a new deep learning model, called DeepTESR, to predict the degree of translational elongation short ramp (TESR) from mRNA sequence. The proposed deep learning model exhibited superior performance in predicting the TESR scores for 226 981 TESR sequences, resulting in the mean absolute error (MAE) of 0.285 and a coefficient of determination R² of 0.627, superior to the conventional machine learning models (e.g., MAE of 0.335 and R² of 0.571 for LightGBM). We experimentally validated that heterologous fluorescence expression of proteins with randomly selected TESR was moderately correlated with the predictions. Furthermore, a genome-wide analysis of TESR prediction in the 4305 coding sequences of Escherichia coli showed conserved TESRs over the clusters of orthologous groups. In this sense, DeepTESR can be used to predict the degree of TESR for gene expression control and to decipher the mechanism of translational control with ribosome profiling. DeepTESR is available at https://github.com/fmblab/DeepTESR.

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.

Metabolomics-Driven Identification of the Rate-Limiting Steps in 1-Propanol Production

The concerted effort for bioproduction of higher alcohols and other commodity chemicals has yielded a consortium of metabolic engineering techniques to identify targets to enhance performance of engineered microbial strains. Here, we demonstrate the use of metabolomics as a tool to systematically identify targets for improved production phenotypes in Escherichia coli. Gas chromatography/mass spectrometry (GC/MS) and ion-pair LC-MS/MS were performed to investigate metabolic perturbations in various 1-propanol producing strains. Two initial strains were compared that differ in the expression of the citramalate and threonine pathways, which hold a synergistic relationship to maximize production yields. While this results in increased productivity, no change in titer was observed when the threonine pathway was overexpressed beyond native levels. Metabolomics revealed accumulation of upstream byproducts, norvaline and 2-aminobutyrate, both of which are derived from 2-ketobutyrate (2KB). Eliminating the competing pathway by gene knockouts or improving flux through overexpression of glycolysis gene effectively increased the intracellular 2KB pool. However, the increase in 2KB intracellular concentration yielded decreased production titers, indicating toxicity caused by 2KB and an insufficient turnover rate of 2KB to 1-propanol. Optimization of alcohol dehydrogenase YqhD activity using an ribosome binding site (RBS) library improved 1-propanol titer (g/L) and yield (g/g of glucose) by 38 and 29% in 72 h compared to the base strain, respectively. This study demonstrates the use of metabolomics as a powerful tool to aid systematic strain improvement for metabolically engineered organisms.

PASIV: A Pooled Approach-Based Workflow to Overcome Toxicity-Induced Design of Experiments Failures and Inefficiencies

We present here a newly developed workflow—which we have called PASIV—designed to provide a solution to a practical problem with design of experiments (DoE) methodology: i.e., what can be done if the scoping phase of the DoE cycle is severely hampered by burden and toxicity issues (caused by either the metabolite or an intermediary), making it unreliable or impossible to proceed to the screening phase? PASIV—standing for pooled approach, screening, identification, and visualization—was designed so the (viable) region of interest can be made to appear through an interplay between biology and software. This was achieved by combining multiplex construction in a pooled approach (one-pot reaction) with a viability assay and with a range of bioinformatics tools (including a novel construct matching tool). PASIV was tested on the exemplar of the lycopene pathway—under stressful constitutive expression—yielding a region of interest with comparatively stronger producers.

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.

Design, mutate, screen: Multiplexed creation and arrayed screening of synchronized genetic clocks

A major goal in synthetic biology is coordinating cellular behavior using cell-cell interactions; however, designing and testing complex genetic circuits that function only in large populations remains challenging. Although directed evolution has commonly supplemented rational design methods for synthetic gene circuits, this method relies on the efficient screening of mutant libraries for desired phenotypes. Recently, multiple techniques have been developed for identifying dynamic phenotypes from large, pooled libraries. These technologies have advanced library screening for single-cell, time-varying phenotypes but are currently incompatible with population-level phenotypes dependent on cell-cell communication. Here, we utilize directed mutagenesis and multiplexed microfluidics to develop an arrayed-screening workflow for dynamic, population-level genetic circuits. Specifically, we create a mutant library of an existing oscillator, the synchronized lysis circuit, and discover variants with different period-amplitude characteristics. Lastly, we utilize our screening workflow to construct a transcriptionally regulated synchronized oscillator that functions over long timescales. A record of this paper's transparent peer review process is included in the supplemental information.

Removing the Bottleneck: Introducing cMatch - A Lightweight Tool for Construct-Matching in Synthetic Biology

We present a software tool, called cMatch, to reconstruct and identify synthetic genetic constructs from their sequences, or a set of sub-sequences—based on two practical pieces of information: their modular structure, and libraries of components. Although developed for combinatorial pathway engineering problems and addressing their quality control (QC) bottleneck, cMatch is not restricted to these applications. QC takes place post assembly, transformation and growth. It has a simple goal, to verify that the genetic material contained in a cell matches what was intended to be built - and when it is not the case, to locate the discrepancies and estimate their severity. In terms of reproducibility/reliability, the QC step is crucial. Failure at this step requires repetition of the construction and/or sequencing steps. When performed manually or semi-manually QC is an extremely time-consuming, error prone process, which scales very poorly with the number of constructs and their complexity. To make QC frictionless and more reliable, cMatch performs an operation we have called “construct-matching” and automates it. Construct-matching is more thorough than simple sequence-matching, as it matches at the functional level-and quantifies the matching at the individual component level and across the whole construct. Two algorithms (called CM_1 and CM_2) are presented. They differ according to the nature of their inputs. CM_1 is the core algorithm for construct-matching and is to be used when input sequences are long enough to cover constructs in their entirety (e.g., obtained with methods such as next generation sequencing). CM_2 is an extension designed to deal with shorter data (e.g., obtained with Sanger sequencing), and that need recombining. Both algorithms are shown to yield accurate construct-matching in a few minutes (even on hardware with limited processing power), together with a set of metrics that can be used to improve the robustness of the decision-making process. To ensure reliability and reproducibility, cMatch builds on the highly validated pairwise-matching Smith-Waterman algorithm. All the tests presented have been conducted on synthetic data for challenging, yet realistic constructs - and on real data gathered during studies on a metabolic engineering example (lycopene production).

The context of the ribosome binding site in mRNAs defines specificity of action of kasugamycin, an inhibitor of translation initiation

Several antibiotics targeting the large ribosomal subunit interfere with translation in a context-specific manner, preventing ribosomes from polymerizing specific amino acid sequences. Here, we reveal kasugamycin as a small ribosomal subunit-targeting antibiotic whose action depends on the sequence context of the untranslated messenger RNA (mRNA) segments. We show that kasugamycin-induced ribosomal arrest at the start codons of the genes and the resulting inhibition of gene expression depend on the nature of the mRNA nucleotide immediately preceding the start codon and on the proximity of the stop codon of the upstream cistron. Our findings underlie the importance of mRNA context for the action of protein synthesis inhibitors and might help to guide the development of better antibiotics.

Kasugamycin (KSG) is an aminoglycoside antibiotic widely used in agriculture and exhibits considerable medical potential. Previous studies suggested that KSG interferes with translation by blocking binding of canonical messenger RNA (mRNA) and initiator transfer tRNA (tRNA) to the small ribosomal subunit, thereby preventing initiation of protein synthesis. Here, by using genome-wide approaches, we show that KSG can interfere with translation even after the formation of the 70S initiation complex on mRNA, as the extent of KSG-mediated translation inhibition correlates with increased occupancy of start codons by 70S ribosomes. Even at saturating concentrations, KSG does not completely abolish translation, allowing for continuing expression of some Escherichia coli proteins. Differential action of KSG significantly depends on the nature of the mRNA residue immediately preceding the start codon, with guanine in this position being the most conducive to inhibition by the drug. In addition, the activity of KSG is attenuated by translational coupling as genes whose start codons overlap with the coding regions or the stop codons of the upstream cistrons tend to be less susceptible to drug-mediated inhibition. Altogether, our findings reveal KSG as an example of a small ribosomal subunit-targeting antibiotic with a well-pronounced context specificity of action.