Impact of codon optimization on vip3Aa11 gene expression and insecticidal efficacy in maize

Introduction

Codon optimization is critical for high expression of foreign genes in heterologous systems. The vip3Aa11 gene from Bacillus thuringiensis is a promising candidate for controlling Spodoptera frugiperda.

Methods and results

To develop insect-resistant maize, we designed two codon-optimized vip3Aa11 variants (vip3Aa11-m1 and vip3Aa11-m2) based on maize codon usage bias. Both recombinant proteins expressed in Escherichia coli exhibited high insecticidal activity. However, in transgenic maize, Vip3Aa11-m1 exhibited strong insecticidal activity against Spodoptera frugiperda and Spodoptera exigua, while Vip3Aa11-m2 lost activity despite identical amino acid sequences. RT-PCR analysis confirmed that both genes were transcribed correctly, but western blot results demonstrated a smaller product for vip3Aa11-m2, suggesting a translation-level alteration. Segment replacement and point mutation experiments in maize protoplasts demonstrated that the synonymous codon AAT (Asn) at the fourth amino acid position in vip3Aa11-m2 was associated with the production of a truncated protein, suggesting that the AAT codon may influence the selection of the translation initiation site, potentially shifting it to a downstream ATG (Met) codon.

Discussion

These findings not only reveal the critical role of codon context in translation initiation and protein integrity but also provide a novel strategy for optimizing foreign genes in crop improvement, particularly offering valuable insights for engineering insect-resistant maize using Bt genes.

A cobalamin-dependent pathway of choline demethylation from the human gut acetogen Eubacterium limosum

Elevated serum levels of trimethylamine N-oxide (TMAO) are reported to promote the development of atherosclerosis. TMAO is produced by hepatic oxidation of trimethylamine (TMA) produced by the gut microbiome from dietary quaternary amines such as choline. Net TMA production in the gut depends on microbial enzymes that either produce or consume TMA and its precursors. Here we report the elucidation of a novel microbial pathway consuming choline without TMA production. The human gut acetogen Eubacterium limosum grows by demethylating choline to N-N-dimethylaminoethanol. Quantitative mass spectral analysis of the proteome revealed a multi-protein choline to tetrahydrofolate (THF) methyltransferase system present only in choline-grown cells. The components are encoded in a gene cluster on the genome and include MthB, an MttB superfamily member; MthC, homologous to methylotrophic cobalamin-binding proteins; MthA, homologous to cobalamin:THF methyltransferases; and MthK, a protein related to serine kinases. Together, MthB, MthC, and MthA methylate THF with phosphocholine, but not choline or other quaternary amines. MthB specifically methylates Co(I)-MthC with phosphocholine. MthK acts as a bifunctional choline kinase which can utilize ATP or the MthB demethylation product, N,N-dimethylaminoethanol phosphate, to phosphorylate choline. Together, MthK, MthB, MthC, and MthA are proposed to carry out the methylation of THF with choline. These results outline a THF methylation pathway in which choline is first activated with ATP to phosphocholine prior to demethylation to form N,N-dimethylaminoethanol phosphate. The latter can be recycled by MthK to form more phosphocholine without expending additional ATP, thus minimizing energy utilization during choline-dependent acetogenesis.

Comparative Analysis of Codon Optimization Tools: Advancing toward a Multi-Criteria Framework for Synthetic Gene Design

Codon optimization is an essential technique in synthetic biology and biopharmaceutical production, enhancing recombinant protein expression by fine-tuning genetic sequences to match the translational machinery and codon usage preferences of specific host organisms. This study presents a comprehensive comparative analysis of widely used codon optimization tools, focusing on their capacity to reflect host-specific codon biases, design principles, and parameters. Industrially relevant target proteins were evaluated in Escherichia coli, Saccharomyces cerevisiae, and CHO cells, uncovering significant variability in sequence design and clustering patterns across tools. Tools such as JCat, OPTIMIZER, ATGme, and GeneOptimizer demonstrated strong alignment with genome-wide and highly expressed gene-level codon usage, achieving high codon adaptation index (CAI) values and efficient codon-pair utilization. Conversely, tools like TISIGNER and IDT employed different optimization strategies that frequently produced divergent results. Other key parameters, including GC content, mRNA secondary structure stability (ΔG), and codon-pair bias (CPB), were analyzed to elucidate their influence on translational efficiency. While increased GC content enhanced mRNA stability in E. coli, A/T-rich codons in S. cerevisiae minimized secondary structure formation, and moderate GC content in CHO cells balanced mRNA stability and translation efficiency. Our findings highlight the limitations of single-metric approaches and advocate for a multi-criteria framework that integrates CAI, GC content, mRNA folding energy, and codon-pair considerations. This integrative strategy enables the design of tailored genetic sequences that meet host-specific requirements, advancing synthetic gene design for biotechnological innovation and precision biopharmaceutical applications.

Artificial design of the genome: from sequences to the 3D structure of chromosomes

Genome design is the foundation of genome synthesis, which provides a new platform for deepening our understanding of biological systems by exploring the fundamental components and structure of the genome. Artificial genome designs can endow unnatural genomes with desired functions. We provide a comprehensive overview of genome design principles ranging from DNA sequences to the 3D structure of chromosomes. Furthermore, we highlight applications of genome design in gene expression, genome structure, genome function, and biocontainment, and discuss the potential of artificial intelligence (AI) in genome design.

Translation of the downstream ORF from bicistronic mRNAs by human cells: Impact of codon usage and splicing in the upstream ORF

Biochemistry textbooks describe eukaryotic mRNAs as monocistronic. However, increasing evidence reveals the widespread presence and translation of upstream open reading frames preceding the "main" ORF. DNA and RNA viruses infecting eukaryotes often produce polycistronic mRNAs and viruses have evolved multiple ways of manipulating the host's translation machinery. Here, we introduce an experimental model to study gene expression regulation from virus-like bicistronic mRNAs in human cells. The model consists of a short upstream ORF and a reporter downstream ORF encoding a fluorescent protein. We have engineered synonymous variants of the upstream ORF to explore large parameter space, including codon usage preferences, mRNA folding features, and splicing propensity. We show that human translation machinery can translate the downstream ORF from bicistronic mRNAs, albeit reporter protein levels are thousand times lower than those from the upstream ORF. Furthermore, synonymous recoding of the upstream ORF exclusively during elongation significantly influences its own translation efficiency, reveals cryptic splice signals, and modulates the probability of downstream ORF translation. Our results are consistent with a leaky scanning mechanism facilitating downstream ORF translation from bicistronic mRNAs in human cells, offering new insights into the role of upstream ORFs in translation regulation.

Advances in recombinant protein production in microorganisms and functional peptide tags

Recombinant protein production in prokaryotic and eukaryotic cells is a fundamental technology for both research and industry. Achieving efficient protein synthesis is key to accelerating the discovery, characterization, and practical application of proteins. This review focuses on recent advances in recombinant protein production and strategies for more efficient protein production, especially using Escherichia coli and Saccharomyces cerevisiae. Additionally, this review summarizes the development of various functional peptide tags that can be employed for protein production, modification, and purification, including translation-enhancing peptide tags developed by our research group.

An Evaluation of the Cellular and Humoral Response of a Multi-Epitope Vaccine Candidate Against COVID-19 with Different Alum Adjuvants

SARS-CoV-2 (Betacoronavirus pandemicum) is responsible for the disease identified by the World Health Organization (WHO) as COVID-19. We designed "CHIVAX 2.1", a multi-epitope vaccine, containing ten immunogenic peptides with conserved B-cell and T-cell epitopes in the receceptor binding domain (RBD) sequences of different SARS-CoV-2 variants of concern (VoCs). We evaluated the immune response of mice immunized with 20 or 60 µg of the chimeric protein with two different alum adjuvants (Alhydrogel® and Adju-Phos®), plus PHAD®, in a two-immunization regimen (0 and 21 days). Serum samples were collected on days 0, 21, 31, and 72 post first immunization, with antibody titers determined by indirect ELISA, while lymphoproliferation assays and cytokine production were evaluated by flow cytometry. The presence of neutralizing antibodies was assessed by surrogate neutralization assays. Higher titers of total IgG, IgG1, and IgG2a antibodies, as well as increased proliferation rates of specific CD4+ and CD8+ T cells, were observed in mice immunized with 60 μg of protein plus Adju-Phos®/PHAD®. This formulation also generated the highest levels of TNF-α and IFN-γ, in addition to the presence of neutralizing antibodies against Delta and Omicron VoC. These findings indicate the potential of this chimeric multi-epitope vaccine with combined adjuvants as a promising platform against viral infections, eliciting a TH1 or TH1:TH2 balanced cell response.

A statistical-physics approach for codon usage optimisation

The concept of "codon optimisation" involves adjusting the coding sequence of a target protein to account for the inherent codon preferences of a host species and maximise protein expression in that species. However, there is still a lack of consensus on the most effective approach to achieve optimal results. Existing methods typically depend on heuristic combinations of different variables, leaving the user with the final choice of the sequence hit. In this study, we propose a new statistical-physics model for codon optimisation. This model, called the Nearest-Neighbour interaction (NN) model, links the probability of any given codon sequence to the "interactions" between neighbouring codons. We used the model to design codon sequences for different proteins of interest, and we compared our sequences with the predictions of some commercial tools. In order to assess the importance of the pair interactions, we additionally compared the NN model with a simpler method (Ind) that disregards interactions. It was observed that the NN method yielded similar Codon Adaptation Index (CAI) values to those obtained by other commercial algorithms, despite the fact that CAI was not explicitly considered in the algorithm. By utilising both the NN and Ind methods to optimise the reporter protein luciferase, and then analysing the translation performance in human cell lines and in a mouse model, we found that the NN approach yielded the highest protein expression in vivo. Consequently, we propose that the NN model may prove advantageous in biotechnological applications, such as heterologous protein expression or mRNA-based therapies.

Gene doping detection in the era of genomics

Recent progress in gene editing has enabled development of gene therapies for many genetic diseases, but also made gene doping an emerging risk in sports and competitions. By delivery of exogenous transgenes into human body, gene doping not only challenges competition fairness but also places health risk on athletes. World Anti-Doping Agency (WADA) has clearly inhibited the use of gene and cell doping in sports, and many techniques have been developed for gene doping detection. In this review, we will summarize the main tools for gene doping detection at present, highlight the main challenges for current tools, and elaborate future utilizations of high-throughput sequencing for unbiased, sensitive, economic and large-scale gene doping detections. Quantitative real-time PCR assays are the widely used detection methods at present, which are useful for detection of known targets but are vulnerable to codon optimization at exon-exon junction sites of the transgenes. High-throughput sequencing has become a powerful tool for various applications in life and health research, and the era of genomics has made it possible for sensitive and large-scale gene doping detections. Non-biased genomic profiling could efficiently detect new doping targets, and low-input genomics amplification and long-read third-generation sequencing also have application potentials for more efficient and straightforward gene doping detection. By closely monitoring scientific advancements in gene editing and sport genetics, high-throughput sequencing could play a more and more important role in gene detection and hopefully contribute to doping-free sports in the future.

Highly inclined light sheet allows volumetric super-resolution imaging of efflux pumps distribution in bacterial biofilms

Bacterial biofilms are highly complex communities in which isogenic bacteria display different gene expression patterns and organize in a three-dimensional mesh gaining enhanced resistance to biocides. The molecular mechanisms behind such increased resistance remain mostly unknown, also because of the technical difficulties in biofilm investigation at the sub-cellular and molecular level. In this work we focus on the AcrAB-TolC protein complex, a multidrug efflux pump found in Enterobacteriaceae, whose overexpression is associated with most multiple drug resistance (MDR) phenotypes occurring in Gram-negative bacteria. We propose an optical method to quantify the expression level of the AcrAB-TolC pump within the biofilm volume at the sub-cellular level, with single-molecule sensitivity. Through a combination of super-resolution PALM with single objective light sheet and precision genome editing, we can directly quantify the spatial distribution of endogenous AcrAB-TolC pumps expressed in both planktonic bacteria and, importantly, within the bacterial biofilm volume. We observe a gradient of pump density within the biofilm volume and over the course of biofilm maturation. Notably, we propose an optical method that could be broadly employed to achieve volumetric super-resolution imaging of thick samples.

Recombinant multiepitope proteins expressed in Escherichia coli cells and their potential for immunodiagnosis

Recombinant multiepitope proteins (RMPs) are a promising alternative for application in diagnostic tests and, given their wide application in the most diverse diseases, this review article aims to survey the use of these antigens for diagnosis, as well as discuss the main points surrounding these antigens. RMPs usually consisting of linear, immunodominant, and phylogenetically conserved epitopes, has been applied in the experimental diagnosis of various human and animal diseases, such as leishmaniasis, brucellosis, cysticercosis, Chagas disease, hepatitis, leptospirosis, leprosy, filariasis, schistosomiasis, dengue, and COVID-19. The synthetic genes for these epitopes are joined to code a single RMP, either with spacers or fused, with different biochemical properties. The epitopes' high density within the RMPs contributes to a high degree of sensitivity and specificity. The RMPs can also sidestep the need for multiple peptide synthesis or multiple recombinant proteins, reducing costs and enhancing the standardization conditions for immunoassays. Methods such as bioinformatics and circular dichroism have been widely applied in the development of new RMPs, helping to guide their construction and better understand their structure. Several RMPs have been expressed, mainly using the Escherichia coli expression system, highlighting the importance of these cells in the biotechnological field. In fact, technological advances in this area, offering a wide range of different strains to be used, make these cells the most widely used expression platform. RMPs have been experimentally used to diagnose a broad range of illnesses in the laboratory, suggesting they could also be useful for accurate diagnoses commercially. On this point, the RMP method offers a tempting substitute for the production of promising antigens used to assemble commercial diagnostic kits.

A novel in vivo system to study coral biomineralization in the starlet sea anemone, Nematostella vectensis

Coral conservation requires a mechanistic understanding of how environmental stresses disrupt biomineralization, but progress has been slow, primarily because corals are not easily amenable to laboratory research. Here, we highlight how the starlet sea anemone, Nematostella vectensis, can serve as a model to interrogate the cellular mechanisms of coral biomineralization. We have developed transgenic constructs using biomineralizing genes that can be injected into Nematostella zygotes and designed such that translated proteins may be purified for physicochemical characterization. Using fluorescent tags, we confirm the ectopic expression of the coral biomineralizing protein, SpCARP1, in Nematostella. We demonstrate via calcein staining that SpCARP1 concentrates calcium ions in Nematostella, likely initiating the formation of mineral precursors, consistent with its suspected role in corals. These results lay a fundamental groundwork for establishing Nematostella as an in vivo system to explore the evolutionary and cellular mechanisms of coral biomineralization, improve coral conservation efforts, and even develop novel biomaterials.

Decoding cellular mechanism of recombinant adeno-associated virus (rAAV) and engineering host-cell factories toward intensified viral vector manufacturing

Recombinant adeno-associated virus (rAAV) is one of the prominent gene delivery vehicles that has opened promising opportunities for novel gene therapeutic approaches. However, the current major viral vector production platform, triple transfection in mammalian cells, may not meet the increasing demand. Thus, it is highly required to understand production bottlenecks from the host cell perspective and engineer the cells to be more favorable and tolerant to viral vector production, thereby effectively enhancing rAAV manufacturing. In this review, we provided a comprehensive exploration of the intricate cellular process involved in rAAV production, encompassing various stages such as plasmid entry to the cytoplasm, plasmid trafficking and nuclear delivery, rAAV structural/non-structural protein expression, viral capsid assembly, genome replication, genome packaging, and rAAV release/secretion. The knowledge in the fundamental biology of host cells supporting viral replication as manufacturing factories or exhibiting defending behaviors against viral production is summarized for each stage. The control strategies from the perspectives of host cell and materials (e.g., AAV plasmids) are proposed as our insights based on the characterization of molecular features and our existing knowledge of the AAV viral life cycle, rAAV and other viral vector production in the Human embryonic kidney (HEK) cells.

T-FINDER: A highly sensitive, pan-HLA platform for functional T cell receptor and ligand discovery

Effective, unbiased, high-throughput methods to functionally identify both class II and class I HLA-presented T cell epitopes and their cognate T cell receptors (TCRs) are essential for and prerequisite to diagnostic and therapeutic applications, yet remain underdeveloped. Here, we present T-FINDER [T cell Functional Identification and (Neo)-antigen Discovery of Epitopes and Receptors], a system to rapidly deconvolute CD4 and CD8 TCRs and targets physiologically processed and presented by an individual's unmanipulated, complete human leukocyte antigen (HLA) haplotype. Combining a highly sensitive TCR signaling reporter with an antigen processing system to overcome previously undescribed limitations to target expression, T-FINDER both robustly identifies unknown peptide:HLA ligands from antigen libraries and rapidly screens and functionally validates the specificity of large TCR libraries against known or predicted targets. To demonstrate its capabilities, we apply the platform to multiple TCR-based applications, including diffuse midline glioma, celiac disease, and rheumatoid arthritis, providing unique biological insights and showcasing T-FINDER's potency and versatility.

Evaluation of the humoral and mucosal immune response of a multiepitope vaccine against COVID-19 in pigs

Introduction

This study evaluated the immune response to a multiepitope recombinant chimeric protein (CHIVAX) containing B- and T-cell epitopes of the SARS-CoV-2 spike's receptor binding domain (RBD) in a translational porcine model for pre-clinical studies.

Methods

We generated a multiepitope recombinant protein engineered to include six coding conserved epitopes from the RBD domain of the SARS-CoV-2 S protein. Pigs were divided into groups and immunized with different doses of the protein, with serum samples collected over time to determine antibody responses by indirect ELISA and antibody titration. Peptide recognition was also analyzed by Western blotting. A surrogate neutralization assay with recombinant ACE2 and RBDs was performed. Intranasal doses of the immunogen were also prepared and tested on Vietnamese minipigs.

Results

When the immunogen was administered subcutaneously, it induced specific IgG antibodies in pigs, and higher doses correlated with higher antibody levels. Antibodies from immunized pigs recognized individual peptides in the multiepitope vaccine and inhibited RBD-ACE2 binding for five variants of concern (VOC). Comparative antigen delivery methods showed that both, subcutaneous and combined subcutaneous/intranasal approaches, induced specific IgG and IgA antibodies, with the subcutaneous approach having superior neutralizing activity. CHIVAX elicited systemic immunity, evidenced by specific IgG antibodies in the serum, and local mucosal immunity, indicated by IgA antibodies in saliva, nasal, and bronchoalveolar lavage secretions. Importantly, these antibodies demonstrated neutralizing activity against SARS-CoV-2 in vitro.

Discussion

The elicited antibodies recognized individual epitopes on the chimeric protein and demonstrated the capacity to block RBD-ACE2 binding of the ancestral SARS-CoV-2 strain and four VOCs. The findings provide proof of concept for using multiepitope recombinant antigens and a combined immunization protocol to induce a neutralizing immune response against SARS-CoV-2 in the pig translational model for preclinical studies.

Expression, Purification, and Crystallization of the Vγ9Vδ2 T-cell Receptor Recognizing Protein/Peptide Antigens

γδ T cells, especially Vγ9Vδ2 T cells, play an important role in mycobacterial infection. We have identified some Vγ9Vδ2 T cells that recognize protein/peptide antigens derived from mycobacteria, which may induce protective immune responses to mycobacterial infection. To clarify the structural basis of the molecular recognition mechanism, we tried many methods to express the Vγ9Vδ2 T-cell receptor (TCR). The Vγ9Vδ2 TCR was not expressed well in a prokaryotic expression system or a baculovirus expression system, even after extensive optimization. In a mammalian cell expression system, the Vγ9Vδ2 TCR was expressed in the form of a soluble heterodimer, which was suitable for crystal screening. Reduced-temperature cultivation (cold shock) increased the yield of the recombinant TCR. The recombinant purified TCR was used for crystal trials, and crystals that could be used for X-ray diffraction were obtained. Although we have not yet determined the crystal structure of the Vγ9Vδ2 TCR, we have established a procedure for Vγ9Vδ2 TCR expression and purification, which is useful for basic research and potentially for clinical application.

A unifying network modeling approach for codon optimization

MOTIVATION

Synthesizing genes to be expressed in other organisms is an essential tool in biotechnology. While the many-to-one mapping from codons to amino acids makes the genetic code degenerate, codon usage in a particular organism is not random either. This bias in codon use may have a remarkable effect on the level of gene expression. A number of measures have been developed to quantify a given codon sequence's strength to express a gene in a host organism. Codon optimization aims to find a codon sequence that will optimize one or more of these measures. Efficient computational approaches are needed since the possible number of codon sequences grows exponentially as the number of amino acids increases.

RESULTS

We develop a unifying modeling approach for codon optimization. With our mathematical formulations based on graph/network representations of amino acid sequences, any combination of measures can be optimized in the same framework by finding a path satisfying additional limitations in an acyclic layered network. We tested our approach on bi-objectives commonly used in the literature, namely, Codon Pair Bias versus Codon Adaptation Index and Relative Codon Pair Bias versus Relative Codon Bias. However, our framework is general enough to handle any number of objectives concurrently with certain restrictions or preferences on the use of specific nucleotide sequences. We implemented our models using Python's Gurobi interface and showed the efficacy of our approach even for the largest proteins available. We also provided experimentation showing that highly expressed genes have objective values close to the optimized values in the bi-objective codon design problem.

AVAILABILITY AND IMPLEMENTATION

http://alpersen.bilkent.edu.tr/NetworkCodon.zip.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

In silico screening and heterologous expression of soluble dimethyl sulfide monooxygenases of microbial origin in Escherichia coli

Abstract

Sequence-based screening has been widely applied in the discovery of novel microbial enzymes. However, majority of the sequences in the genomic databases were annotated using computational approaches and lacks experimental characterization. Hence, the success in obtaining the functional biocatalysts with improved characteristics requires an efficient screening method that considers a wide array of factors. Recombinant expression of microbial enzymes is often hampered by the undesirable formation of inclusion body. Here, we present a systematic in silico screening method to identify the proteins expressible in soluble form and with the desired biological properties. The screening approach was adopted in the recombinant expression of dimethyl sulfide (DMS) monooxygenase in Escherichia coli. DMS monooxygenase, a two-component enzyme consisting of DmoA and DmoB subunits, was used as a model protein. The success rate of producing soluble and active DmoA is 71% (5 out of 7 genes). Interestingly, the soluble recombinant DmoA enzymes exhibited the NADH:FMN oxidoreductase activity in the absence of DmoB (second subunit), and the cofactor FMN, suggesting that DmoA is also an oxidoreductase. DmoA originated from Janthinobacterium sp. AD80 showed the maximum NADH oxidation activity (maximum reaction rate: 6.6 µM/min; specific activity: 133 µM/min/mg). This novel finding may allow DmoA to be used as an oxidoreductase biocatalyst for various industrial applications. The in silico gene screening methodology established from this study can increase the success rate of producing soluble and functional enzymes while avoiding the laborious trial and error involved in the screening of a large pool of genes available.

Key points

• A systematic gene screening method was demonstrated.

• DmoA is also an oxidoreductase capable of oxidizing NADH and reducing FMN.

• DmoA oxidizes NADH in the absence of external FMN.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00253-022-12008-8.

Pharmacological interventions enhance virus-free generation of TRAC-replaced CAR T cells

Chimeric antigen receptor (CAR) redirected T cells are potent therapeutic options against hematological malignancies. The current dominant manufacturing approach for CAR T cells depends on retroviral transduction. With the advent of gene editing, insertion of a CD19-CAR into the T cell receptor (TCR) alpha constant (TRAC) locus using adeno-associated viruses for gene transfer was demonstrated, and these CD19-CAR T cells showed improved functionality over their retrovirally transduced counterparts. However, clinical-grade production of viruses is complex and associated with extensive costs. Here, we optimized a virus-free genome-editing method for efficient CAR insertion into the TRAC locus of primary human T cells via nuclease-assisted homology-directed repair (HDR) using CRISPR-Cas and double-stranded template DNA (dsDNA). We evaluated DNA-sensor inhibition and HDR enhancement as two pharmacological interventions to improve cell viability and relative CAR knockin rates, respectively. While the toxicity of transfected dsDNA was not fully prevented, the combination of both interventions significantly increased CAR knockin rates and CAR T cell yield. Resulting TRAC-replaced CD19-CAR T cells showed antigen-specific cytotoxicity and cytokine production in vitro and slowed leukemia progression in a xenograft mouse model. Amplicon sequencing did not reveal significant indel formation at potential off-target sites with or without exposure to DNA-repair-modulating small molecules. With TRAC-integrated CAR⁺ T cell frequencies exceeding 50%, this study opens new perspectives to exploit pharmacological interventions to improve non-viral gene editing in T cells.

Low-dose self-amplifying mRNA COVID-19 vaccine drives strong protective immunity in non-human primates against SARS-CoV-2 infection

The coronavirus disease 2019 (COVID-19) pandemic continues to spread globally, highlighting the urgent need for safe and effective vaccines that could be rapidly mobilized to immunize large populations. We report the preclinical development of a self-amplifying mRNA (SAM) vaccine encoding a prefusion stabilized severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike glycoprotein and demonstrate strong cellular and humoral immune responses at low doses in mice and rhesus macaques. The homologous prime-boost vaccination regimen of SAM at 3, 10 and 30 μg induced potent neutralizing antibody (nAb) titers in rhesus macaques following two SAM vaccinations at all dose levels, with the 10 μg dose generating geometric mean titers (GMT) 48-fold greater than the GMT of a panel of SARS-CoV-2 convalescent human sera. Spike-specific T cell responses were observed with all tested vaccine regimens. SAM vaccination provided protective efficacy against SARS-CoV-2 challenge as both a homologous prime-boost and as a single boost following ChAd prime, demonstrating reduction of viral replication in both the upper and lower airways. The SAM vaccine is currently being evaluated in clinical trials as both a homologous prime-boost regimen at low doses and as a boost following heterologous prime.

Self-amplifying mRNA vaccines offer the benefit of driving potent immune responses at low doses, as the mRNA replicates intracellularly. Here, the authors report the preclinical evaluation of a self-amplifying mRNA SARS-CoV-2 vaccine in non-human primates.

Optimal Design of Synthetic DNA Sequences Without Unwanted Binding Sites

Synthesizing DNA molecules by design has become an essential tool in molecular biology and is expected to become ubiquitous in the coming decade. Successful design of a synthetic DNA molecule often requires satisfying multiple objectives, some of which may conflict with others. One particularly important objective is the elimination of unwanted protein binding sites, which may interfere with the desired function of the synthesized molecule. While most design tools offer this fundamental capability, they do not follow a systematic approach that guarantees elimination of all unwanted sites whenever a feasible solution exists. Furthermore, the algorithms these tools use (when published) are often quite naive and inefficient. We present a formal description of the binding site elimination problem and suggest several efficient algorithms that eliminate unwanted patterns with minimum interference to the desired function of the synthesized sequence. These algorithms are simple, efficient, and flexible and, therefore, can be easily incorporated in all existing DNA design tools, enhancing their design capabilities.

Evolution and host adaptability of plant RNA viruses: Research insights on compositional biases

During recent decades, many new emerging or re-emerging RNA viruses have been found in plants through the development of deep-sequencing technology and big data analysis. These findings largely changed our understanding of the origin, evolution and host range of plant RNA viruses. There is evidence that their genetic composition originates from viruses, and host populations play a key role in the evolution and host adaptability of plant RNA viruses. In this mini-review, we describe the state of our understanding of the evolution of plant RNA viruses in view of compositional biases and explore how they adapt to the host. It appears that adenine rich (A-rich) coding sequences, low CpG and UpA dinucleotide frequencies and lower codon usage patterns were found in the vast majority of plant RNA viruses. The codon usage pattern of plant RNA viruses was influenced by both natural selection and mutation pressure, and natural selection mostly from hosts was the dominant factor. The codon adaptation analyses support that plant RNA viruses probably evolved a dynamic balance between codon adaptation and deoptimization to maintain efficient replication cycles in multiple hosts with various codon usage patterns. In the future, additional combinations of computational and experimental analyses of the nucleotide composition and codon usage of plant RNA viruses should be addressed.

Efficient multi-gene expression in cell-free droplet microreactors

Cell-free transcription and translation systems promise to accelerate and simplify the engineering of proteins, biological circuits and metabolic pathways. Their encapsulation on microfluidic platforms can generate millions of cell-free reactions in picoliter volume droplets. However, current methods struggle to create DNA diversity between droplets while also reaching sufficient protein expression levels. In particular, efficient multi-gene expression has remained elusive. We here demonstrate that co-encapsulation of DNA-coated beads with a defined cell-free system allows high protein expression while also supporting genetic diversity between individual droplets. We optimize DNA loading on commercially available microbeads through direct binding as well as through the sequential coupling of up to three genes via a solid-phase Golden Gate assembly or BxB1 integrase-based recombineering. Encapsulation with an off-the-shelf microfluidics device allows for single or multiple protein expression from a single DNA-coated bead per 14 pL droplet. We envision that this approach will help to scale up and parallelize the rapid prototyping of more complex biological systems.

Advances in COVID-19 mRNA vaccine development

To date, the coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has determined 399,600,607 cases and 5,757,562 deaths worldwide. COVID-19 is a serious threat to human health globally. The World Health Organization (WHO) has declared COVID-19 pandemic a major public health emergency. Vaccination is the most effective and economical intervention for controlling the spread of epidemics, and consequently saving lives and protecting the health of the population. Various techniques have been employed in the development of COVID-19 vaccines. Among these, the COVID-19 messenger RNA (mRNA) vaccine has been drawing increasing attention owing to its great application prospects and advantages, which include short development cycle, easy industrialization, simple production process, flexibility to respond to new variants, and the capacity to induce better immune response. This review summarizes current knowledge on the structural characteristics, antigen design strategies, delivery systems, industrialization potential, quality control, latest clinical trials and real-world data of COVID-19 mRNA vaccines as well as mRNA technology. Current challenges and future directions in the development of preventive mRNA vaccines for major infectious diseases are also discussed.

Machine learning discovery of missing links that mediate alternative branches to plant alkaloids

Engineering the microbial production of secondary metabolites is limited by the known reactions of correctly annotated enzymes. Therefore, the machine learning discovery of specialized enzymes offers great potential to expand the range of biosynthesis pathways. Benzylisoquinoline alkaloid production is a model example of metabolic engineering with potential to revolutionize the paradigm of sustainable biomanufacturing. Existing bacterial studies utilize a norlaudanosoline pathway, whereas plants contain a more stable norcoclaurine pathway, which is exploited in yeast. However, committed aromatic precursors are still produced using microbial enzymes that remain elusive in plants, and additional downstream missing links remain hidden within highly duplicated plant gene families. In the current study, machine learning is applied to predict and select plant missing link enzymes from homologous candidate sequences. Metabolomics-based characterization of the selected sequences reveals potential aromatic acetaldehyde synthases and phenylpyruvate decarboxylases in reconstructed plant gene-only benzylisoquinoline alkaloid pathways from tyrosine. Synergistic application of the aryl acetaldehyde producing enzymes results in enhanced benzylisoquinoline alkaloid production through hybrid norcoclaurine and norlaudanosoline pathways.

Producing plant secondary metabolites by microbes is limited by the known enzymatic reactions. Here, the authors apply machine learning to predict missing link enzymes of benzylisoquinoline alkaloid (BIA) biosynthesis in Papaver somniferum, and validate the specialized activities through heterologous production.

Exploiting the Gal4/UAS System as Plant Orthogonal Molecular Toolbox to Control Reporter Expression in Arabidopsis Protoplasts

The ability of protein domains to fold independently from the rest of the polypeptide is the principle governing the generation of fusion proteins with customized functions. A clear example is the split transcription factor system based on the yeast GAL4 protein and its cognate UAS enhancer. The rare occurrence of the UAS element in the transcriptionally sensitive regions of the Arabidopsis genome makes this transcription factor an ideal orthogonal platform to control reporter induction. Moreover, heterodimeric transcriptional complexes can be generated by exploiting posttranslational modifications hampering or promoting the interaction between GAL4-fused transcriptional partners, whenever this leads to the reconstitution of a fully functional GAL4 factor.The assembly of multiple engineered proteins into a synthetic transcriptional complex requires preliminary testing, before its components can be stably introduced into the plant genome. Mesophyll protoplast transformation represents a fast and reliable technique to test and optimize synthetic regulatory modules. Remarkable properties are the possibility to transform different combinations of plasmids (co-transformation) and the physiological resemblance of these isolated cells with the original tissue.Here we describe an extensive protocol to produce and exploit Arabidopsis mesophyll protoplasts to investigate the transcriptional output of GAL4/UAS-based complexes that are sensitive to posttranslational protein modifications.

Tailoring Codon Usage to the Underlying Biology for Protein Expression Optimization

For heterologous gene expression, codon optimization is required to enhance the quality and quantity of the protein product. Recently, we introduced the software tool OCTOPOS. This sequence optimizer combines a detailed mechanistic mathematical modeling of in vivo protein synthesis with a state-of-the-art machine learning algorithm to find the sequence that best serves a user's needs. Here, we briefly describe the algorithm and its implementation as well as its application in practice using OCTOPOS.

Prediction of lipid nanoparticles for mRNA vaccines by the machine learning algorithm

Lipid nanoparticle (LNP) is commonly used to deliver mRNA vaccines. Currently, LNP optimization primarily relies on screening ionizable lipids by traditional experiments which consumes intensive cost and time. Current study attempts to apply computational methods to accelerate the LNP development for mRNA vaccines. Firstly, 325 data samples of mRNA vaccine LNP formulations with IgG titer were collected. The machine learning algorithm, lightGBM, was used to build a prediction model with good performance (R² > 0.87). More importantly, the critical substructures of ionizable lipids in LNPs were identified by the algorithm, which well agreed with published results. The animal experimental results showed that LNP using DLin-MC3-DMA (MC3) as ionizable lipid with an N/P ratio at 6:1 induced higher efficiency in mice than LNP with SM-102, which was consistent with the model prediction. Molecular dynamic modeling further investigated the molecular mechanism of LNPs used in the experiment. The result showed that the lipid molecules aggregated to form LNPs, and mRNA molecules twined around the LNPs. In summary, the machine learning predictive model for LNP-based mRNA vaccines was first developed, validated by experiments, and further integrated with molecular modeling. The prediction model can be used for virtual screening of LNP formulations in the future.

mRNA codon optimization with quantum computers

Reverse translation of polypeptide sequences to expressible mRNA constructs is a NP-hard combinatorial optimization problem. Each amino acid in the protein sequence can be represented by as many as six codons, and the process of selecting the combination that maximizes probability of expression is termed codon optimization. This work investigates the potential impact of leveraging quantum computing technology for codon optimization. A Quantum Annealer (QA) is compared to a standard genetic algorithm (GA) programmed with the same objective function. The QA is found to be competitive in identifying optimal solutions. The utility of gate-based systems is also evaluated using a simulator resulting in the finding that while current generations of devices lack the hardware requirements, in terms of both qubit count and connectivity, to solve realistic problems, future generation devices may be highly efficient.

The MttB superfamily member MtyB from the human gut symbiont Eubacterium limosum is a cobalamin-dependent γ-butyrobetaine methyltransferase

The production of trimethylamine (TMA) from quaternary amines such as l-carnitine or γ-butyrobetaine (4-(trimethylammonio)butanoate) by gut microbial enzymes has been linked to heart disease. This has led to interest in enzymes of the gut microbiome that might ameliorate net TMA production, such as members of the MttB superfamily of proteins, which can demethylate TMA (e.g., MttB) or l-carnitine (e.g., MtcB). Here, we show that the human gut acetogen Eubacterium limosum demethylates γ-butyrobetaine and produces MtyB, a previously uncharacterized MttB superfamily member catalyzing the demethylation of γ-butyrobetaine. Proteomic analyses of E. limosum grown on either γ-butyrobetaine or dl-lactate were employed to identify candidate proteins underlying catabolic demethylation of the growth substrate. Three proteins were significantly elevated in abundance in γ-butyrobetaine-grown cells: MtyB, MtqC (a corrinoid-binding protein), and MtqA (a corrinoid:tetrahydrofolate methyltransferase). Together, these proteins act as a γ-butyrobetaine:tetrahydrofolate methyltransferase system, forming a key intermediate of acetogenesis. Recombinant MtyB acts as a γ-butyrobetaine:MtqC methyltransferase but cannot methylate free cobalamin cofactor. MtyB is very similar to MtcB, the carnitine methyltransferase, but neither was detectable in cells grown on carnitine nor was detectable in cells grown with γ-butyrobetaine. Both quaternary amines are substrates for either enzyme, but kinetic analysis revealed that, in comparison to MtcB, MtyB has a lower apparent K_m for γ-butyrobetaine and higher apparent V_max, providing a rationale for MtyB abundance in γ-butyrobetaine-grown cells. As TMA is readily produced from γ-butyrobetaine, organisms with MtyB-like proteins may provide a means to lower levels of TMA and proatherogenic TMA-N-oxide via precursor competition.

Analysis of 11,430 recombinant protein production experiments reveals that protein yield is tunable by synonymous codon changes of translation initiation sites

Recombinant protein production is a key process in generating proteins of interest in the pharmaceutical industry and biomedical research. However, about 50% of recombinant proteins fail to be expressed in a variety of host cells. Here we show that the accessibility of translation initiation sites modelled using the mRNA base-unpairing across the Boltzmann's ensemble significantly outperforms alternative features. This approach accurately predicts the successes or failures of expression experiments, which utilised Escherichia coli cells to express 11,430 recombinant proteins from over 189 diverse species. On this basis, we develop TIsigner that uses simulated annealing to modify up to the first nine codons of mRNAs with synonymous substitutions. We show that accessibility captures the key propensity beyond the target region (initiation sites in this case), as a modest number of synonymous changes is sufficient to tune the recombinant protein expression levels. We build a stochastic simulation model and show that higher accessibility leads to higher protein production and slower cell growth, supporting the idea of protein cost, where cell growth is constrained by protein circuits during overexpression.

An Integrative Toolbox for Synthetic Biology in Rhodococcus

The development of microbial cell factories requires robust synthetic biology tools to reduce design uncertainty and accelerate the design-build-test-learn process. Herein, we developed a suite of integrative genetic tools to facilitate the engineering of Rhodococcus, a genus of bacteria with considerable biocatalytic potential. We first created pRIME, a modular, copy-controlled integrative-vector, to provide a robust platform for strain engineering and characterizing genetic parts. This vector was then employed to benchmark a series of strong promoters. We found P_M6 to be the strongest constitutive rhodococcal promoter, 2.5- to 3-fold stronger than the next in our study, while overall promoter activities ranged 23-fold between the weakest and strongest promoters during exponential growth. Next, we used an optimized variant of P_M6 to develop hybrid-promoters and integrative vectors to allow for tetracycline-inducible gene expression in Rhodococcus. The best of the resulting hybrid-promoters maintained a maximal activity of ∼50% of P_M6 and displayed an induction factor of ∼40-fold. Finally, we developed and implemented a uLoop-derived Golden Gate assembly strategy for high-throughput DNA assembly in Rhodococcus. To demonstrate the utility of our approaches, pRIME was used to engineer Rhodococcus jostii RHA1 to grow on vanillin at concentrations 10-fold higher than what the wild-type strain tolerated. Overall, this study provides a suite of tools that will accelerate the engineering of Rhodococcus for various biocatalytic applications, including the sustainable production of chemicals from lignin-derived aromatics.

Expression of 42 kDa chitinase of Trichoderma asperellum (Ta-CHI42) from a synthetic gene in Escherichia coli

Chitinases are enzymes that catalyze the degradation of chitin, a major component of the cell walls of pathogenic fungi and cuticles of insects, gaining increasing attention for the control of fungal pathogens and insect pests. Production of recombinant chitinase in a suitable host can result in a more pure product with less processing time and a significantly larger yield than that produced by native microorganisms. The present study aimed to express the synthetic chi42 gene (syncodChi42), which was optimized from the chi42 gene of Trichoderma asperellum SH16, in Escherichia coli to produce 42 kDa chitinase (Ta-CHI42); then determined the activity of this enzyme, characterizations and in vitro antifungal activity as well as its immunogenicity in mice. The results showed that Ta-CHI42 was overexpressed in E. coli. Analysis of the colloidal chitin hydrolytic activity of purified Ta-CHI42 on an agar plate revealed that this enzyme was in a highly active form. This is a neutral chitinase with pH stability in a range of 6-8 and has an optimum temperature of 45°C with thermal stability in a range of 25-35°C. The chitinolytic activity of Ta-CHI42 was almost completely abolished by 5 mM Zn2+ or 1% SDS, whereas it remained about haft under the effect of 1 M urea, 1% Triton X-100 or 5 mM Cu2+. Except for ions such as Mn2+ and Ca2+ at 5 mM that have enhanced chitinolytic activity; 5 mM of Na+, Fe2+ or Mg2+ ions or 1 mM EDTA negatively impacted the enzyme. Ta-CHI42 at 60 U/mL concentration strongly inhibited the growth of the pathogenic fungus Aspergillus niger. Analysis of western blot indicated that the polyclonal antibody against Ta-CHI42 was greatly produced in mice. It can be used to analyze the expression of the syncodChi42 gene in transgenic plants, through immunoblotting assays, for resistance to pathogenic fungi.

Synthetic Biology in Plants, a Boon for Coming Decades

Recently an enormous expansion of knowledge is seen in various disciplines of science. This surge of information has given rise to concept of interdisciplinary fields, which has resulted in emergence of newer research domains, one of them is 'Synthetic Biology' (SynBio). It captures basics from core biology and integrates it with concepts from the other areas of study such as chemical, electrical, and computational sciences. The essence of synthetic biology is to rewire, re-program, and re-create natural biological pathways, which are carried through genetic circuits. A genetic circuit is a functional assembly of basic biological entities (DNA, RNA, proteins), created using typical design, built, and test cycles. These circuits allow scientists to engineer nearly all biological systems for various useful purposes. The development of sophisticated molecular tools, techniques, genomic programs, and ease of nucleic acid synthesis have further fueled several innovative application of synthetic biology in areas like molecular medicines, pharmaceuticals, biofuels, drug discovery, metabolomics, developing plant biosensors, utilization of prokaryotic systems for metabolite production, and CRISPR/Cas9 in the crop improvement. These applications have largely been dominated by utilization of prokaryotic systems. However, newer researches have indicated positive growth of SynBio for the eukaryotic systems as well. This paper explores advances of synthetic biology in the plant field by elaborating on its core components and potential applications. Here, we have given a comprehensive idea of designing, development, and utilization of synthetic biology in the improvement of the present research state of plant system.

Droplet-Based Microfluidic High-Throughput Screening of Enzyme Mutant Libraries Secreted by Yarrowia lipolytica

Yarrowia lipolytica has emerged as an attractive solution for screening enzyme activities thanks to the numerous tools available for heterologous protein production and its strong secretory ability. Nowadays, activity screening for improved enzymes mostly relies on the evaluation of independent clones in microtiter plates. However, even with highly robotized screening facilities, the relatively low throughput and high cost of the technology do not enable the screening of large diversities, which significantly reduce the probability of isolating improved variants. Droplet-based microfluidics is an emerging technology that allows the high-throughput and individual picoliter droplets manipulation and sorting based on enzymatic substrate fluorescence. This technology is an attractive alternative to microtiter plate screenings with higher throughputs and drastic reduction of working volume and cost.Here, we present a droplet-based microfluidic platform for the screening of libraries expressed in the yeast Y. lipolytica, from the generation of a random mutagenesis library of a heterologous enzyme and its expression in Y. lipolytica to the droplet-based microfluidic procedures composed of cell encapsulation and growth and activity screening or sorting of improved clones.

Visualizing endogenous Rho activity with an improved localization-based, genetically encoded biosensor

Rho GTPases are regulatory proteins, which orchestrate cell features such as morphology, polarity and movement. Therefore, probing Rho GTPase activity is key to understanding processes such as development and cell migration. Localization-based reporters for active Rho GTPases are attractive probes to study Rho GTPase-mediated processes in real time with subcellular resolution in living cells and tissue. Until now, relocation Rho biosensors (sensors that relocalize to the native location of active Rho GTPase) seem to have been only useful in certain organisms and have not been characterized well. In this paper, we systematically examined the contribution of the fluorescent protein and Rho-binding peptides on the performance of localization-based sensors. To test the performance, we compared relocation efficiency and specificity in cell-based assays. We identified several improved localization-based, genetically encoded fluorescent biosensors for detecting endogenous Rho activity. This enables a broader application of Rho relocation biosensors, which was demonstrated by using the improved biosensor to visualize Rho activity during several cellular processes, such as cell division, migration and G protein-coupled receptor signaling. Owing to the improved avidity of the new biosensors for Rho activity, cellular processes regulated by Rho can be better understood.

This article has an associated First Person interview with the first author of the paper.

Summary: The dT-2xrGBD location-based Rho biosensor relocalizes more efficiently than other sensors of this type, and this sensor enables the observation of endogenous Rho activity in cultured cells.

TISIGNER.com: web services for improving recombinant protein production

Experiments that are planned using accurate prediction algorithms will mitigate failures in recombinant protein production. We have developed TISIGNER (https://tisigner.com) with the aim of addressing technical challenges to recombinant protein production. We offer three web services, TIsigner (Translation Initiation coding region designer), SoDoPE (Soluble Domain for Protein Expression) and Razor, which are specialised in synonymous optimisation of recombinant protein expression, solubility and signal peptide analysis, respectively. Importantly, TIsigner, SoDoPE and Razor are linked, which allows users to switch between the tools when optimising genes of interest.

EGFR extracellular domain III expressed in Escherichia coli with SEP tag shows improved biophysical and functional properties and generate anti-sera inhibiting cancer cell growth

The epidermal growth factor receptor extracellular domain III (EGFR-ECDIII) protein is a promising target of anti-cancer research, and its production in Escherichia coli would thus represent significant benefits. However, despite its moderate size (19 kDa), the expression of EGFR-ECDIII in E.coli is hampered by the presence of multiple cysteines producing misfolded proteins with incorrect S-S bonds. In our study, we show that a short 12-residue solubility enhancing peptide (SEP) tag containing nine arginines (C9R) attached at the C-terminus of EGFR-ECDIII reduces the inclusion body formation and increases the final yield by six times (20 mg/L). EGFR-ECDIII-C9R purified from the soluble fraction eluted as a sharp single RP-HPLC peak, suggesting a single S-S bond pairing. Biophysical characterization using circular dichroism, fluorescence, and light scattering confirmed its native-like properties together with reversible thermal denaturation. The binding activity of EGFR-ECDIII-C9R to anti-EGFR-VHH7D12, a single-domain antibody with specific binding to the ECDIII, was assessed by sandwich ELISA. Further, we produced anti-EGFR-ECDIII-C9R antisera in mouse models and anti-sera inhibited A431 cancer cells' growth. These results demonstrate that the SEP tag enables the rapid production of the multiple disulfide-bonded EGFR-ECDIII in E. coli having native-like biophysical properties and producing neutralizing antibodies.

Bi-functionalized aminoguanidine-PEGylated periodic mesoporous organosilica nanoparticles: a promising nanocarrier for delivery of Cas9-sgRNA ribonucleoproteine

BACKGROUND

There is a great interest in the efficient intracellular delivery of Cas9-sgRNA ribonucleoprotein complex (RNP) and its possible applications for in vivo CRISPR-based gene editing. In this study, a nanoporous mediated gene-editing approach has been successfully performed using a bi-functionalized aminoguanidine-PEGylated periodic mesoporous organosilica (PMO) nanoparticles (RNP@AGu@PEG1500-PMO) as a potent and biocompatible nanocarrier for RNP delivery.

RESULTS

The bi-functionalized MSN-based nanomaterials have been fully characterized using electron microscopy (TEM and SEM), nitrogen adsorption measurements, thermogravimetric analysis (TGA), X-ray powder diffraction (XRD), Attenuated Total Reflectance-Fourier Transform Infrared Spectroscopy (ATR-FTIR), and dynamic light scattering (DLS). The results confirm that AGu@PEG1500-PMO can be applied for gene-editing with an efficiency of about 40% as measured by GFP gene knockdown of HT1080-GFP cells with no notable change in the morphology of the cells.

CONCLUSIONS

Due to the high stability and biocompatibility, simple synthesis, and cost-effectiveness, the developed bi-functionalized PMO-based nano-network introduces a tailored nanocarrier that has remarkable potential as a promising trajectory for biomedical and RNP delivery applications.

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.

Synonymous but Not Silent: The Codon Usage Code for Gene Expression and Protein Folding

Codon usage bias, the preference for certain synonymous codons, is found in all genomes. Although synonymous mutations were previously thought to be silent, a large body of evidence has demonstrated that codon usage can play major roles in determining gene expression levels and protein structures. Codon usage influences translation elongation speed and regulates translation efficiency and accuracy. Adaptation of codon usage to tRNA expression determines the proteome landscape. In addition, codon usage biases result in nonuniform ribosome decoding rates on mRNAs, which in turn influence the cotranslational protein folding process that is critical for protein function in diverse biological processes. Conserved genome-wide correlations have also been found between codon usage and protein structures. Furthermore, codon usage is a major determinant of mRNA levels through translation-dependent effects on mRNA decay and translation-independent effects on transcriptional and posttranscriptional processes. Here, we discuss the multifaceted roles and mechanisms of codon usage in different gene regulatory processes.

Homogeneous antibody-drug conjugates: DAR 2 anti-HER2 obtained by conjugation on isolated light chain followed by mAb assembly

Despite advances in medical care, cancer remains a major threat to human health. Antibody-drug conjugates (ADCs) are a promising targeted therapy to overcome adverse side effects to normal tissues. In this field, the current challenge is obtaining homogeneous preparations of conjugates, where a defined number of drugs are conjugated to specific antibody sites. Site-directed cysteine-based conjugation is commonly used to obtain homogeneous ADC, but it is a time-consuming and expensive approach due to the need for extensive antibody engineering to identify the optimal conjugation sites and reduction – oxidation protocols are specific for each antibody. There is thus a need for ADC platforms that offer homogeneity and direct applicability to the already approved antibody therapeutics. Here we describe a novel approach to derive homogeneous ADCs with drug-to-antibody ratio of 2 from any human immunoglobulin 1 (IgG₁), using trastuzumab as a model. The method is based on the production of heavy chains (HC) and light chains (LC) in two recombinant HEK293 independent cultures, so the original amino acid sequence is not altered. Isolated LC was effectively conjugated to a single drug-linker (vcMMAE) construct and mixed to isolated HC dimers, in order to obtain a correctly folded ADC. The relevance of the work was validated in terms of ADC homogeneity (HIC-HPLC, MS), purity (SEC-HPLC), isolated antigen recognition (ELISA) and biological activity (HER2-positive breast cancer cells cytotoxicity assays).

Systematic Structure-Based Virtual Screening Approach to Antibody Selection and Design of a Humanized Antibody against Multiple Addictive Opioids without Affecting Treatment Agents Naloxone and Naltrexone

Opioid drug use, especially heroin, is known as a growing national crisis in America. Heroin itself is a prodrug and is converted to the most active metabolite 6-monoacetylmorphine (6-MAM) responsible for the acute toxicity of heroin and then to a relatively less-active metabolite morphine responsible for the long-term toxicity of heroin. Monoclonal antibodies (mAbs) are recognized as a potentially promising therapeutic approach in the treatment of opioid use disorders (OUDs). Due to the intrinsic challenges of discovering an mAb against multiple ligands, here we describe a general, systematic structure-based virtual screening and design approach which has been used to identify a known anti-morphine antibody 9B1 and a humanized antibody h9B1 capable of binding to multiple addictive opioids (including 6-MAM, morphine, heroin, and hydrocodone) without significant binding with currently available OUD treatment agents naloxone, naltrexone, and buprenorphine. The humanized antibody may serve as a promising candidate for the treatment of OUDs. The experimental binding affinities reasonably correlate with the computationally predicted binding free energies. The experimental activity data strongly support the computational predictions, suggesting that the systematic structure-based virtual screening and humanization design protocol is reliable. The general, systematic structure-based virtual screening and design approach will be useful for many other antibody selection and design efforts in the future.

Molecular characterization, pathogen-host interaction pathway and in silico approaches for vaccine design against COVID-19

COVID-19 has forsaken the world because of extremely high infection rates and high mortality rates. At present we have neither medicine nor vaccine to prevent this pandemic. Lockdowns, curfews, isolations, quarantines, and social distancing are the only ways to mitigate their infection. This is badly affecting the mental health of people. Hence, there is an urgent need to address this issue. Coronavirus disease 2019 (COVID-19) is caused by a novel Betacorona virus named SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) which has emerged in the city of Wuhan in China and declared a pandemic by WHO since it affected almost all the countries the world, infected 24,182,030 people and caused 825,798 death as per data are compiled from John Hopkins University (JHU). The genome of SARS-CoV-2 has a single-stranded positive (+) sense RNA of ∼30 kb nucleotides. Phylogenetic analysis reveals that SARS-CoV-2 shares the highest nucleotide sequence similarity (∼79 %) with SARS-CoV. Envelope and nucleocapsids are two evolutionary conserved regions of SARS-CoV-2 having a sequence identity of about 96 % and 89.6 %, respectively as compared to SARS-CoV. The characterization of SARS-CoV-2 is based on polymerase chain reaction (PCR) and metagenomic next-generation sequencing. Transmission of this virus in the human occurs through the respiratory tract and decreases the respiration efficiency of lungs. Humans are generally susceptible to SARS-CoV-2 with an incubation period of 2-14 days. The virus first infects the lower airway and bind with angiotensin-converting enzyme 2 (ACE2) of alveolar epithelial cells. Due to the unavailability of drugs or vaccines, it is very urgent to design potential vaccines or drugs for COVID-19. Reverse vaccinology and immunoinformatic play an important role in designing potential vaccines against SARS-CoV-2. The suitable vaccine selects for SARS-CoV-2 based on binding energy between the target protein and the designed vaccine. The stability and activity of the designed vaccine can be estimated by using molecular docking and dynamic simulation approaches. This review mainly focused on the brief up to date information about COVID-19, molecular characterization, pathogen-host interaction pathways involved during COVID-19 infection. It also covers potential vaccine design against COVID-19 by using various computational approaches. SARS-CoV-2 enters brain tissue through the different pathway and harm human's brain and causes severe neurological disruption.

Use of a small DNA virus model to investigate mechanisms of CpG dinucleotide-induced attenuation of virus replication

Suppression of the CpG dinucleotide is widespread in RNA viruses infecting vertebrates and plants, and in the genomes of retroviruses and small mammalian DNA viruses. The functional basis for CpG suppression in the latter was investigated through the construction of mutants of the parvovirus, minute virus of mice (MVM) with increased CpG or TpA dinucleotides in the VP gene. CpG-high mutants displayed extraordinary attenuation in A9 cells compared to wild-type MVM (>six logs), while TpA elevation showed no replication effect. Attenuation was independent of Toll-like receptor 9 and STING-mediated DNA recognition pathways and unrelated to effects on translation efficiency. While translation from codon-optimized VP RNA was enhanced in a cell-free assay, MVM containing this sequence was highly attenuated. Further mutational analysis indicated that this arose through its increased numbers of CpG dinucleotides (7→70) and separately from its increased G+C content (42.3→57.4 %), which independently attenuated replication. CpG-high viruses showed impaired NS mRNA expression by qPCR and reduced NS and particularly VP protein expression detected by immunofluorescence and replication in A549 cells, effects reversed in zinc antiviral protein (ZAP) knockout cells, even though nuclear relocalization of VP remained defective. The demonstrated functional basis for CpG suppression in MVM and potentially other small DNA viruses and the observed intolerance of CpGs in coding sequences, even after codon optimization, has implications for the use of small DNA virus vectors in gene therapy and immunization.