Improving heterologous membrane protein production in Escherichia coli by combining transcriptional tuning and codon usage algorithms

Development of a Transcriptional Biosensor for Hydrogen Sulfide that Functions under Aerobic and Anaerobic Conditions

Hydrogen sulfide (H 2 S) is a gaseous gut metabolite with disputed effects on gastrointestinal health. Monitoring H 2 S concentration in the gut would provide insight into its role in disease, but is complicated by sulfide's reactivity and volatility. Here we develop a transcriptional sulfide biosensor in E. coli . The sensor relies on enzymatic oxidation of sulfide catalyzed by a sulfide:quinone reductase (Sqr) to polysulfides, which bind to the repressor SqrR, triggering unbinding from the promoter and transcription of the reporter. Through promoter engineering and improving soluble SqrR expression, we optimized the system to provide an operational range of 50 µM - 750 µM and dynamic range of 18 aerobically. To enable sensing in anaerobic environments, we identified an Sqr from Wolinella succinogenes that uses menaquinone, facilitating reoxidation through the anaerobic electron transport chain by fumarate or nitrate. Use of this homolog resulted in an anaerobic H 2 S response up to 750 µM. This sensor could ultimately enable spatially and temporally resolved measurements of H 2 S in the gastrointestinal tract to elucidate the role of this metabolite in disease, and potentially as a non-invasive diagnostic.

NERVE 2.0: boosting the new enhanced reverse vaccinology environment via artificial intelligence and a user-friendly web interface

BACKGROUND

Vaccines development in this millennium started by the milestone work on Neisseria meningitidis B, reporting the invention of Reverse Vaccinology (RV), which allows to identify vaccine candidates (VCs) by screening bacterial pathogens genome or proteome through computational analyses. When NERVE (New Enhanced RV Environment), the first RV software integrating tools to perform the selection of VCs, was released, it prompted further development in the field. However, the problem-solving potential of most, if not all, RV programs is still largely unexploited by experimental vaccinologists that impaired by somehow difficult interfaces, requiring bioinformatic skills.

RESULTS

We report here on the development and release of NERVE 2.0 (available at: https://nerve-bio.org ) which keeps the original integrative and modular approach of NERVE, while showing higher predictive performance than its previous version and other web-RV programs (Vaxign and Vaxijen). We renewed some of its modules and added innovative ones, such as Loop-Razor, to recover fragments of promising vaccine candidates or Epitope Prediction for the epitope prediction binding affinities and population coverage. Along with two newly built AI (Artificial Intelligence)-based models: ESPAAN and Virulent. To improve user-friendliness, NERVE was shifted to a tutored, web-based interface, with a noSQL-database to consent the user to submit, obtain and retrieve analysis results at any moment.

CONCLUSIONS

With its redesigned and updated environment, NERVE 2.0 allows customisable and refinable bacterial protein vaccine analyses to all different kinds of users.

Strategies to overcome the challenges of low or no expression of heterologous proteins in Escherichia coli

Protein expression is a critical process in diverse biological systems. For Escherichia coli, a widely employed microbial host in industrial catalysis and healthcare, researchers often face significant challenges in constructing recombinant expression systems. To maximize the potential of E. coli expression systems, it is essential to address problems regarding the low or absent production of certain target proteins. This article presents viable solutions to the main factors posing challenges to heterologous protein expression in E. coli, which includes protein toxicity, the intrinsic influence of gene sequences, and mRNA structure. These strategies include specialized approaches for managing toxic protein expression, addressing issues related to mRNA structure and codon bias, advanced codon optimization methodologies that consider multiple factors, and emerging optimization techniques facilitated by big data and machine learning.

"Metabolic burden" explained: stress symptoms and its related responses induced by (over)expression of (heterologous) proteins in Escherichia coli

BACKGROUND

Engineering bacterial strains to redirect the metabolism towards the production of a specific product has enabled the development of industrial biotechnology. However, rewiring the metabolism can have severe implications for a microorganism, rendering cells with stress symptoms such as a decreased growth rate, impaired protein synthesis, genetic instability and an aberrant cell size. On an industrial scale, this is reflected in processes that are not economically viable.

MAIN TEXT

In literature, most stress symptoms are attributed to "metabolic burden", however the actual triggers and stress mechanisms involved are poorly understood. Therefore, in this literature review, we aimed to get a better insight in how metabolic engineering affects Escherichia coli and link the observed stress symptoms to its cause. Understanding the possible implications that chosen engineering strategies have, will help to guide the reader towards optimising the envisioned process more efficiently.

CONCLUSION

This review addresses the gap in literature and discusses the triggers and effects of stress mechanisms that can be activated when (over)expressing (heterologous) proteins in Escherichia coli. It uncovers that the activation of the different stress mechanisms is complex and that many are interconnected. The reader is shown that care has to be taken when (over)expressing (heterologous) proteins as the cell's metabolism is tightly regulated.

The Causes for Genomic Instability and How to Try and Reduce Them Through Rational Design of Synthetic DNA

Genetic engineering has revolutionized our ability to manipulate DNA and engineer organisms for various applications. However, this approach can lead to genomic instability, which can result in unwanted effects such as toxicity, mutagenesis, and reduced productivity. To overcome these challenges, smart design of synthetic DNA has emerged as a promising solution. By taking into consideration the intricate relationships between gene expression and cellular metabolism, researchers can design synthetic constructs that minimize metabolic stress on the host cell, reduce mutagenesis, and increase protein yield. In this chapter, we summarize the main challenges of genomic instability in genetic engineering and address the dangers of unknowingly incorporating genomically unstable sequences in synthetic DNA. We also demonstrate the instability of those sequences by the fact that they are selected against conserved sequences in nature. We highlight the benefits of using ESO, a tool for the rational design of DNA for avoiding genetically unstable sequences, and also summarize the main principles and working parameters of the software that allow maximizing its benefits and impact.

Design of an effective small expression tag to enhance GPCR production in E. coli-based cell-free and whole cell expression systems

G protein-coupled receptors (GPCRs) play crucial roles in sensory, immune, and tumor metastasis processes, making them valuable targets for pharmacological and sensing applications in various industries. However, most GPCRs have low production yields in Escherichia coli (E. coli) expression systems. To overcome this limitation, we introduced AT10 tag, an effective fusion tag that could significantly enhance expression levels of various GPCRs in E. coli and its derived cell-free protein synthesis (CFPS) system. This AT10 tag consisted of an A/T-rich gene sequence designed via optimization of translation initiation rate. It is translated into a short peptide sequence of 10 amino acids at the N-terminus of GPCRs. Additionally, effector proteins could be utilized to suppress cytotoxicity caused by membrane protein expression, further boosting GPCR production in E. coli. Enhanced expression of various GPCRs using this AT10 tag is a promising approach for large-scale production of functional GPCRs in E. coli-based CFPS and whole cell systems, enabling their potential utilization across a wide range of industrial applications.

Maximizing Heterologous Expression of Engineered Type I Polyketide Synthases: Investigating Codon Optimization Strategies

Type I polyketide synthases (T1PKSs) hold enormous potential as a rational production platform for the biosynthesis of specialty chemicals. However, despite great progress in this field, the heterologous expression of PKSs remains a major challenge. One of the first measures to improve heterologous gene expression can be codon optimization. Although controversial, choosing the wrong codon optimization strategy can have detrimental effects on the protein and product levels. In this study, we analyzed 11 different codon variants of an engineered T1PKS and investigated in a systematic approach their influence on heterologous expression in Corynebacterium glutamicum, Escherichia coli, and Pseudomonas putida. Our best performing codon variants exhibited a minimum 50-fold increase in PKS protein levels, which also enabled the production of an unnatural polyketide in each of these hosts. Furthermore, we developed a free online tool (https://basebuddy.lbl.gov) that offers transparent and highly customizable codon optimization with up-to-date codon usage tables. In this work, we not only highlight the significance of codon optimization but also establish the groundwork for the high-throughput assembly and characterization of PKS pathways in alternative hosts.

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

BACKGROUND

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

RESULTS

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

CONCLUSIONS

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

A Machine Learning Method for Genome Engineering Design Tool Attribution

As the ability to engineer biological systems improves with increasingly advanced technology, the risk of accidental or intentional release of a dangerous genetically modified organism becomes greater. It is important that authorities can carry out attribution for the source of a genetically modified biological agent release. In the absence of evidence that ties a release directly to the individuals responsible, attribution can be carried out in part by discovering the in silico tools used to design the engineered genetic components, which can leave a signature in the DNA of the organism. Previous attribution methods have focused on identifying the laboratory of origin of an engineered organism using machine learning on plasmid signatures. The next logical step is to address attribution using signatures from the tools that are used to create the engineered modifications. A random forest classifier was developed that discriminates between design tools used to optimize coding regions for incorporation into the genome of another organism. To this end, tens of thousands of genes were optimized with 4 different codon optimization methods and relevant features from these sequences were generated for a machine learning classifier. This method achieves more than 97% accuracy in predicting which tools were used to design codon optimized genes for expression in other organisms. The methods presented here lay the groundwork for the creation of effective organism engineering attribution techniques. Such methods can act both as deterrents for future attempts at creating dangerous organisms as well as tools for forensic science.

Engineering the biological conversion of formate into crotonate in Cupriavidus necator

To advance the sustainability of the biobased economy, our society needs to develop novel bioprocesses based on truly renewable resources. The C1-molecule formate is increasingly proposed as carbon and energy source for microbial fermentations, as it can be efficiently generated electrochemically from CO2 and renewable energy. Yet, its biotechnological conversion into value-added compounds has been limited to a handful of examples. In this work, we engineered the natural formatotrophic bacterium C. necator as cell factory to enable biological conversion of formate into crotonate, a platform short-chain unsaturated carboxylic acid of biotechnological relevance. First, we developed a small-scale (150-mL working volume) cultivation setup for growing C. necator in minimal medium using formate as only carbon and energy source. By using a fed-batch strategy with automatic feeding of formic acid, we could increase final biomass concentrations 15-fold compared to batch cultivations in flasks. Then, we engineered a heterologous crotonate pathway in the bacterium via a modular approach, where each pathway section was assessed using multiple candidates. The best performing modules included a malonyl-CoA bypass for increasing the thermodynamic drive towards the intermediate acetoacetyl-CoA and subsequent conversion to crotonyl-CoA through partial reverse β-oxidation. This pathway architecture was then tested for formate-based biosynthesis in our fed-batch setup, resulting in a two-fold higher titer, three-fold higher productivity, and five-fold higher yield compared to the strain not harboring the bypass. Eventually, we reached a maximum product titer of 148.0 ± 6.8 mg/L. Altogether, this work consists in a proof-of-principle integrating bioprocess and metabolic engineering approaches for the biological upgrading of formate into a value-added platform chemical.

Multiplex genome engineering in Clostridium beijerinckii NCIMB 8052 using CRISPR-Cas12a

Clostridium species are re-emerging as biotechnological workhorses for industrial acetone-butanol-ethanol production. This re-emergence is largely due to advances in fermentation technologies but also due to advances in genome engineering and re-programming of the native metabolism. Several genome engineering techniques have been developed including the development of numerous CRISPR-Cas tools. Here, we expanded the CRISPR-Cas toolbox and developed a CRISPR-Cas12a genome engineering tool in Clostridium beijerinckii NCIMB 8052. By controlling the expression of FnCas12a with the xylose-inducible promoter, we achieved efficient (25-100%) single-gene knockout of five C. beijerinckii NCIMB 8052 genes (spo0A, upp, Cbei_1291, Cbei_3238, Cbei_3832). Moreover, we achieved multiplex genome engineering by simultaneously knocking out the spo0A and upp genes in a single step with an efficiency of 18%. Finally, we showed that the spacer sequence and position in the CRISPR array can affect the editing efficiency outcome.

Experimental characterization of de novo proteins and their unevolved random-sequence counterparts

De novo gene emergence provides a route for new proteins to be formed from previously non-coding DNA. Proteins born in this way are considered random sequences and typically assumed to lack defined structure. While it remains unclear how likely a de novo protein is to assume a soluble and stable tertiary structure, intersecting evidence from random sequence and de novo-designed proteins suggests that native-like biophysical properties are abundant in sequence space. Taking putative de novo proteins identified in human and fly, we experimentally characterize a library of these sequences to assess their solubility and structure propensity. We compare this library to a set of synthetic random proteins with no evolutionary history. Bioinformatic prediction suggests that de novo proteins may have remarkably similar distributions of biophysical properties to unevolved random sequences of a given length and amino acid composition. However, upon expression in vitro, de novo proteins exhibit moderately higher solubility which is further induced by the DnaK chaperone system. We suggest that while synthetic random sequences are a useful proxy for de novo proteins in terms of structure propensity, de novo proteins may be better integrated in the cellular system than random expectation, given their higher solubility.

Genetic Engineering of Escherichia coli BL21 (DE3) with a codon-optimized insecticidal toxin complex gene tccZ

A toxin complex consists of a high-molecular-weight group of toxins that exhibits insecticidal activity against insect pests. These toxins are a promising alternative to Bacillus thuringiensis (Bt) toxins that have been extensively utilized in insect pest control. Herein, a codon-optimized insecticidal gene (tccZ) (381 bp) identified in Pantoea ananatis strain MHSD5 (a bacterial endophyte previously isolated from Pellaea calomelanos) was ligated into the pET SUMO expression vector and expressed in Escherichia coli BL21 (DE3). We report the success of cloning the tccZ gene into the pET SUMO vector and ultimately the transformation into E. coli BL21 (DE3) competent cells. However, despite conducting a time course of expression as well as isopropyl β-d-1-thiogalactopyranoside (IPTG) dosage optimization to determine optimal conditions for expression, TccZ protein expression could not be detected on Stain-Free and Coomassie-stained SDS-PAGE gels.

Metabolic engineering of Clostridium autoethanogenum for ethyl acetate production from CO

Background

Ethyl acetate is a bulk chemical traditionally produced via energy intensive chemical esterification. Microbial production of this compound offers promise as a more sustainable alternative process. So far, efforts have focused on using sugar-based feedstocks for microbial ester production, but extension to one-carbon substrates, such as CO and CO2/H2, is desirable. Acetogens present a promising microbial platform for the production of ethyl esters from these one-carbon substrates.

Results

We engineered the acetogen C. autoethanogenum to produce ethyl acetate from CO by heterologous expression of an alcohol acetyltransferase (AAT), which catalyzes the formation of ethyl acetate from acetyl-CoA and ethanol. Two AATs, Eat1 from Kluyveromyces marxianus and Atf1 from Saccharomyces cerevisiae, were expressed in C. autoethanogenum. Strains expressing Atf1 produced up to 0.2 mM ethyl acetate. Ethyl acetate production was barely detectable (< 0.01 mM) for strains expressing Eat1. Supplementation of ethanol was investigated as potential boost for ethyl acetate production but resulted only in a 1.5-fold increase (0.3 mM ethyl acetate). Besides ethyl acetate, C. autoethanogenum expressing Atf1 could produce 4.5 mM of butyl acetate when 20 mM butanol was supplemented to the growth medium.

Conclusions

This work offers for the first time a proof-of-principle that autotrophic short chain ester production from C1-carbon feedstocks is possible and offers leads on how this approach can be optimized in the future.

Expanding the genetic engineering toolbox for the metabolically flexible acetogen Eubacterium limosum

Acetogenic bacteria are an increasingly popular choice for producing fuels and chemicals from single carbon (C1) substrates. Eubacterium limosum is a promising acetogen with several native advantages, including the ability to catabolize a wide repertoire of C1 feedstocks and the ability to grow well on agar plates. However, despite its promise as a strain for synthetic biology and metabolic engineering, there are insufficient engineering tools and molecular biology knowledge to leverage its native strengths for these applications. To capitalize on the natural advantages of this organism, here we extended its limited engineering toolbox. We evaluated the copy number of three common plasmid origins of replication and devised a method of controlling copy number and heterologous gene expression level by modulating antibiotic concentration. We further quantitatively assessed the strength and regulatory tightness of a panel of promoters, developing a series of well-characterized vectors for gene expression at varying levels. In addition, we developed a black/white colorimetric genetic reporter assay and leveraged the high oxygen tolerance of E. limosum to develop a simple and rapid transformation protocol that enables benchtop transformation. Finally, we developed two new antibiotic selection markers—doubling the number available for this organism. These developments will enable enhanced metabolic engineering and synthetic biology work with E. limosum.

Functional expression and regulation of eukaryotic cytochrome P450 enzymes in surrogate microbial cell factories

Cytochrome P450 (CYP) enzymes play crucial roles during the evolution and diversification of ancestral monocellular eukaryotes into multicellular eukaryotic organisms due to their essential functionalities including catalysis of housekeeping biochemical reactions, synthesis of diverse metabolites, detoxification of xenobiotics, and contribution to environmental adaptation. Eukaryotic CYPs with versatile functionalities are undeniably regarded as promising biocatalysts with great potential for biotechnological, pharmaceutical and chemical industry applications. Nevertheless, the modes of action and the challenges associated with these membrane-bound proteins have hampered the effective utilization of eukaryotic CYPs in a broader range. This review is focused on comprehensive and consolidated approaches to address the core challenges in heterologous expression of membrane-bound eukaryotic CYPs in different surrogate microbial cell factories, aiming to provide key insights for better studies and applications of diverse eukaryotic CYPs in the future. We also highlight the functional significance of the previously underrated cytochrome P450 reductases (CPRs) and provide a rational justification on the progression of CPR from auxiliary redox partner to function modulator in CYP catalysis.

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

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

A Hyperthermoactive-Cas9 Editing Tool Reveals the Role of a Unique Arsenite Methyltransferase in the Arsenic Resistance System of Thermus thermophilus HB27

Arsenic detoxification systems can be found in a wide range of organisms, from bacteria to humans. In a previous study, we discovered an arsenic-responsive transcriptional regulator in the thermophilic bacterium Thermus thermophilus HB27 (TtSmtB). Here, we characterize the arsenic resistance system of T. thermophilus in more detail. We employed TtSmtB-based pulldown assays with protein extracts from cultures treated with arsenate and arsenite to obtain an S-adenosyl-l-methionine (SAM)-dependent arsenite methyltransferase (TtArsM). In vivo and in vitro analyses were performed to shed light on this new component of the arsenic resistance network and its peculiar catalytic mechanism. Heterologous expression of TtarsM in Escherichia coli resulted in arsenite detoxification at mesophilic temperatures. Although TtArsM does not contain a canonical arsenite binding site, the purified protein does catalyze SAM-dependent arsenite methylation with formation of monomethylarsenites (MMAs) and dimethylarsenites (DMAs). In addition, in vitro analyses confirmed the unique interaction between TtArsM and TtSmtB. Next, a highly efficient ThermoCas9-based genome-editing tool was developed to delete the TtArsM-encoding gene on the T. thermophilus genome and to confirm its involvement in the arsenite detoxification system. Finally, the TtarsX efflux pump gene in the T. thermophilus ΔTtarsM genome was substituted by a gene encoding a stabilized yellow fluorescent protein (sYFP) to create a sensitive genome-based bioreporter system for the detection of arsenic ions.

Comprehensive Genome Engineering Toolbox for Microalgae Nannochloropsis oceanica Based on CRISPR-Cas Systems

Microalgae can produce industrially relevant metabolites using atmospheric CO₂ and sunlight as carbon and energy sources, respectively. Developing molecular tools for high-throughput genome engineering could accelerate the generation of tailored strains with improved traits. To this end, we developed a genome editing strategy based on Cas12a ribonucleoproteins (RNPs) and homology-directed repair (HDR) to generate scarless and markerless mutants of the microalga Nannochloropsis oceanica. We also developed an episomal plasmid-based Cas12a system for efficiently introducing indels at the target site. Additionally, we exploited the ability of Cas12a to process an associated CRISPR array to perform multiplexed genome engineering. We efficiently targeted three sites in the host genome in a single transformation, thereby making a major step toward high-throughput genome engineering in microalgae. Furthermore, a CRISPR interference (CRISPRi) tool based on Cas9 and Cas12a was developed for effective downregulation of target genes. We observed up to 85% reduction in the transcript levels upon performing CRISPRi with dCas9 in N. oceanica. Overall, these developments substantially accelerate genome engineering efforts in N. oceanica and potentially provide a general toolbox for improving other microalgal strains.

From the notebook to recombinant protein production in Escherichia coli: Design of expression vectors and gene cloning

Research in recombinant protein expression in microorganism hosts spans half a century. The field has evolved from mostly trial-and-error approaches to more rational strategies, including careful design of the expression vectors and the coding sequence for the protein of interest. It is important to reflect on many aspects about vector construction, such as codon usage, integration site, coding sequence mutagenesis and many others. In this chapter, we overview methods and considerations to generate a suitable construct and anticipate possible experimental roadblocks.

Exploring Codon Adjustment Strategies towards Escherichia coli-Based Production of Viral Proteins Encoded by HTH1, a Novel Prophage of the Marine Bacterium Hypnocyclicus thermotrophus

Marine viral sequence space is immense and presents a promising resource for the discovery of new enzymes interesting for research and biotechnology. However, bottlenecks in the functional annotation of viral genes and soluble heterologous production of proteins hinder access to downstream characterization, subsequently impeding the discovery process. While commonly utilized for the heterologous expression of prokaryotic genes, codon adjustment approaches have not been fully explored for viral genes. Herein, the sequence-based identification of a putative prophage is reported from within the genome of Hypnocyclicus thermotrophus, a Gram-negative, moderately thermophilic bacterium isolated from the Seven Sisters hydrothermal vent field. A prophage-associated gene cluster, consisting of 46 protein coding genes, was identified and given the proposed name Hypnocyclicus thermotrophus phage H1 (HTH1). HTH1 was taxonomically assigned to the viral family Siphoviridae, by lowest common ancestor analysis of its genome and phylogeny analyses based on proteins predicted as holin and DNA polymerase. The gene neighbourhood around the HTH1 lytic cassette was found most similar to viruses infecting Gram-positive bacteria. In the HTH1 lytic cassette, an N-acetylmuramoyl-L-alanine amidase (Amidase_2) with a peptidoglycan binding motif (LysM) was identified. A total of nine genes coding for enzymes putatively related to lysis, nucleic acid modification and of unknown function were subjected to heterologous expression in Escherichia coli. Codon optimization and codon harmonization approaches were applied in parallel to compare their effects on produced proteins. Comparison of protein yields and thermostability demonstrated that codon optimization yielded higher levels of soluble protein, but codon harmonization led to proteins with higher thermostability, implying a higher folding quality. Altogether, our study suggests that both codon optimization and codon harmonization are valuable approaches for successful heterologous expression of viral genes in E. coli, but codon harmonization may be preferable in obtaining recombinant viral proteins of higher folding quality.

Genetic and metabolic engineering challenges of C1-gas fermenting acetogenic chassis organisms

Unabated mining and utilisation of petroleum and petroleum resources and their conversion to essential fuels and chemicals have drastic environmental consequences, contributing to global warming and climate change. In addition, fossil fuels are finite resources, with a fast-approaching shortage. Accordingly, research efforts are increasingly focusing on developing sustainable alternatives for chemicals and fuels production. In this context, bioprocesses, relying on microorganisms, have gained particular interest. For example, acetogens use the Wood-Ljungdahl pathway to grow on single carbon C1-gases (CO2 and CO) as their sole carbon source and produce valuable products such as acetate or ethanol. These autotrophs can, therefore, be exploited for large-scale fermentation processes to produce industrially relevant chemicals from abundant greenhouse gases. In addition, genetic tools have recently been developed to improve these chassis organisms through synthetic biology approaches. This review will focus on the challenges of genetically and metabolically modifying acetogens. It will first discuss the physical and biochemical obstacles complicating successful DNA transfer in these organisms. Current genetic tools developed for several acetogens, crucial for strain engineering to consolidate and expand their catalogue of products, will then be described. Recent tool applications for metabolic engineering purposes to allow redirection of metabolic fluxes or production of non-native compounds will lastly be covered.

DNA Chisel, a versatile sequence optimizer

MOTIVATION

Accounting for biological and practical requirements in DNA sequence design often results in challenging optimization problems. Current software solutions are problem-specific and hard to combine.

RESULTS

DNA Chisel is an easy-to-use, easy-to-extend sequence optimization framework allowing to freely define and combine optimization specifications via Python scripts or Genbank annotations.

AVAILABILITY AND IMPLEMENTATION

The framework is available as a web application (https://cuba.genomefoundry.org/sculpt_a_sequence) or open-source Python library (see at https://github.com/Edinburgh-Genome-Foundry/DNAChisel for code and documentation).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

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.

Computational Tools for Discovering and Engineering Natural Product Biosynthetic Pathways

Natural products (NPs), also known as secondary metabolites, are produced in bacteria, fungi, and plants. NPs represent a rich source of antibacterial, antifungal, and anticancer agents. Recent advances in DNA sequencing technologies and bioinformatics unveiled nature's great potential for synthesizing numerous NPs that may confer unprecedented structural and biological features. However, discovering novel bioactive NPs by genome mining remains a challenge. Moreover, even with interesting bioactivity, the low productivity of many NPs significantly limits their practical applications. Here we discuss the progress in developing bioinformatics tools for efficient discovery of bioactive NPs. In addition, we highlight computational methods for optimizing the productivity of NPs of pharmaceutical importance.

Efficient Cas9-based genome editing of Rhodobacter sphaeroides for metabolic engineering

Background

Rhodobacter sphaeroides is a metabolically versatile bacterium that serves as a model for analysis of photosynthesis, hydrogen production and terpene biosynthesis. The elimination of by-products formation, such as poly-β-hydroxybutyrate (PHB), has been an important metabolic engineering target for R. sphaeroides. However, the lack of efficient markerless genome editing tools for R. sphaeroides is a bottleneck for fundamental studies and biotechnological exploitation. The Cas9 RNA-guided DNA-endonuclease from the type II CRISPR-Cas system of Streptococcus pyogenes (SpCas9) has been extensively employed for the development of genome engineering tools for prokaryotes and eukaryotes, but not for R. sphaeroides.

Results

Here we describe the development of a highly efficient SpCas9-based genomic DNA targeting system for R. sphaeroides, which we combine with plasmid-borne homologous recombination (HR) templates developing a Cas9-based markerless and time-effective genome editing tool. We further employ the tool for knocking-out the uracil phosphoribosyltransferase (upp) gene from the genome of R. sphaeroides, as well as knocking it back in while altering its start codon. These proof-of-principle processes resulted in editing efficiencies of up to 100% for the knock-out yet less than 15% for the knock-in. We subsequently employed the developed genome editing tool for the consecutive deletion of the two predicted acetoacetyl-CoA reductase genes phaB and phbB in the genome of R. sphaeroides. The culturing of the constructed knock-out strains under PHB producing conditions showed that PHB biosynthesis is supported only by PhaB, while the growth of the R. sphaeroides ΔphbB strains under the same conditions is only slightly affected.

Conclusions

In this study, we combine the SpCas9 targeting activity with the native homologous recombination (HR) mechanism of R. sphaeroides for the development of a genome editing tool. We further employ the developed tool for the elucidation of the PHB production pathway of R. sphaeroides. We anticipate that the presented work will accelerate molecular research with R. sphaeroides.

Smoothing membrane protein structure determination by initial upstream stage improvements

Membrane proteins (MP) constitute 20–30% of all proteins encoded by the genome of various organisms and perform a wide range of essential biological functions. However, despite they represent the largest class of protein drug targets, a relatively small number high-resolution 3D structures have been obtained yet. Membrane protein biogenesis is more complex than that of the soluble proteins and its recombinant biosynthesis has been a major drawback, thus delaying their further structural characterization. Indeed, the major limitation in structure determination of MP is the low yield achieved in recombinant expression, usually coupled to low functionality, pinpointing the optimization target in recombinant MP research. Recently, the growing attention that have been dedicated to the upstream stage of MP bioprocesses allowed great advances, permitting the evolution of the number of MP solved structures. In this review, we analyse and discuss effective solutions and technical advances at the level of the upstream stage using prokaryotic and eukaryotic organisms foreseeing an increase in expression yields of correctly folded MP and that may facilitate the determination of their three-dimensional structure. A section on techniques used to protein quality control and further structure determination of MP is also included. Lastly, a critical assessment of major factors contributing for a good decision-making process related to the upstream stage of MP is presented.

Modular Engineering of Biomass Degradation Pathways

Production of fuels and chemicals from renewable lignocellulosic feedstocks is a promising alternative to petroleum-derived compounds. Due to the complexity of lignocellulosic feedstocks, microbial conversion of all potential substrates will require substantial metabolic engineering. Non-model microbes offer desirable physiological traits, but also increase the difficulty of heterologous pathway engineering and optimization. The development of modular design principles that allow metabolic pathways to be used in a variety of novel microbes with minimal strain-specific optimization will enable the rapid construction of microbes for commercial production of biofuels and bioproducts. In this review, we discuss variability of lignocellulosic feedstocks, pathways for catabolism of lignocellulose-derived compounds, challenges to heterologous engineering of catabolic pathways, and opportunities to apply modular pathway design. Implementation of these approaches will simplify the process of modifying non-model microbes to convert diverse lignocellulosic feedstocks.

Improved protein production and codon optimization analyses in Escherichia coli by bicistronic design

Different codon optimization algorithms are available that aim at improving protein production by optimizing translation elongation. In these algorithms, it is generally not considered how the altered protein coding sequence will affect the secondary structure of the corresponding RNA transcript, particularly not the effect on the 5'-UTR structure and related ribosome binding site availability. This is a serious drawback, because the influence of codon usage on mRNA secondary structures, especially near the start of a gene, may strongly influence translation initiation. In this study, we aim to reduce the effect of codon usage on translation initiation by applying a bicistronic design (BCD) element. Protein production of several codon-optimized gene variants is tested in parallel for a BCD and a standard monocistronic design (MCD). We demonstrate that these distinct architectures can drastically change the relative performance of different codon optimization algorithms. We conclude that a BCD is indispensable in future studies that aim to reveal the impact of codon optimization and codon usage correlations. Furthermore, irrespective of the algorithm used, using a BCD does improve protein production compared with an MCD. The overall highest expression from BCDs for both GFP and RFP is at least twofold higher than the highest levels found for the MCDs, while for codon variants having very low expression from the MCD, even 10-fold to 100-fold increases in expression were achieved by the BCD. This shows the great potential of the BCD element for recombinant protein production.