Codon bias and heterologous protein expression

Genetic characterization of four bacteriophages of Salmonella enterica derived from different geographic regions in China via genomic comparison

Based on the AT content > GC content in four Salmonella enterica lytic bacteriophage genomes, information entropy analysis revealed that overall nucleotide usage bias is shaped in the gene population. This genetic feature directly contributes to synonymous codons tending toward the A/T end rather than the C/G end. Furthermore, the interplay between the nucleotide composition constraint from the bacteriophage itself and the natural selection caused by outside environments forces our bacteriophages into similar evolutionary trends in terms of overall codon usage patterns. We identified the nucleotide composition constraint which plays an important role in shaping synonymous codon usage patterns including the keto skew at the first codon position, the pyrimidine skew at the second position and the AT skew at the third position. Although the four bacteriophages were isolated from different geographical regions in China, they display similar evolutionary trends in terms of genomic organization and synonymous codon usage, which are strongly influenced by the nucleotide composition constraint of the bacteriophage. The findings of the present study reveal important details of the evolutionary and host-pathogen interactions of Salmonella enterica, which will benefit the efficient utilization of phages for therapeutic and other applications.

Decoding codon usage in human papillomavirus type 59

Human Papillomavirus Type 59 (HPV-59) is a high-risk subtype linked to cervical and other cancers. However, its codon usage patterns remain underexplored despite their importance in understanding viral behavior and vaccine optimization. This study reveals a mild codon usage bias in HPV-59, with a notable preference for A/T-ending codons and 29 favored codons, primarily ending in A or T. Additionally, CpG dinucleotides were significantly underrepresented, potentially aiding immune evasion. Analyses using the Parity Rule 2, Effective Number of Codons plot, and neutrality plot indicate that both mutational pressure and natural selection shape codon usage, with natural selection playing a dominant role. The virus's codon usage moderately aligns with human translational machinery, as shown by the Isoacceptor tRNA pool, Codon Adaptation Index, and Relative Codon Deoptimization Index, reflecting an evolutionary balance between protein synthesis efficiency and host compatibility. These findings provide valuable insights into HPV-59 biology, offering guidance for developing optimized vaccines.

Enhanced production of C50 carotenoid bacterioruberin by metabolically engineered Corynebacterium glutamicum

Bacterioruberin is a red-pigmented C50 carotenoid commonly found in halophilic archaea, known for its strong antioxidant properties. In this study, we demonstrate the complete biosynthesis of bacterioruberin in metabolically engineered Corynebacterium glutamicum overproducing lycopene. To investigate the function of the encoded enzymes, we genetically modified C. glutamicum to produce lycopene and constructed recombinant C. glutamicum strains expressing bacterioruberin biosynthetic genes. The carotenoids produced by the recombinant strains were then analyzed. The pathway comprising the bifunctional lycopene elongase and 1,2-hydratase (lyeJ), carotenoid 3,4-desaturase (crtD), and C50 carotenoid 2'',3''-hydratase (cruF) from "Haloferax marinum" was introduced into the C. glutamicum ΔcrtRYEb strain. The expression of each gene allowed for the identification of bacterioruberin, its known precursors, and previously unidentified precursors. In fed-batch fermentation, a carotenoid titer of 9.74 mg/L with a yield of 0.29 mg/g DCW and a productivity of 0.30 mg/L/h, was achieved. This study is the first to demonstrate that C. glutamicum can accumulate the non-native bacterioruberin instead of its native cyclic C50 carotenoid, decaprenoxanthin.

The curious case of AAV immunology

Immune responses to adeno-associated virus (AAV) have long been perplexing, from its first discovery to the latest clinical trials of recombinant AAV (rAAV) therapy. Wild-type AAV (wtAAV) does not cause any known disease, making it an ideal vector for gene therapy, as viral vectors retain virus-like properties. Although AAV stimulates only a mild immune response compared with other viruses, it is still recognized by the innate immune system and induces adaptive immune responses. B cell responses against both wtAAV and rAAV are robust and can hinder gene therapy applications and prevent redosing. T cell responses can clear transduced cells or establish tolerance against gene therapy. Immune responses to AAV gene therapy are influenced by many factors. Most clinical immunotoxicities that develop in response to gene therapies have emerged as higher doses of AAV vectors have been utilized and were not properly modeled in preclinical animal studies. Thus, several strategies have been undertaken to reduce or mitigate immune responses to AAV. While we have learned a considerable amount about how the immune system responds to AAV gene therapy since the discovery of AAV virus, it still remains a curious case that requires more investigation to fully understand.

Bioluminescent imaging of an oomycete pathogen empowers chemical selections and rational fungicide applications

Fungicides play an indispensable role in ensuring food security. However, rational chemical selection and fungicide precision application guidance remain constrained by the limitations in real-time monitoring of tracking pathogens within plant tissues. In the current study, we generated a genetically stable Phytophthora infestans strain (PiLuc) expressing luciferase gene, which serves as a dual-mode quantification platform for both in vitro and in vivo throughput screening. Consequently, we designed a 96-well plate high-throughput screening system to assess compounds inhibitory efficacy using PiLuc. Crucially, bioluminescence imaging enabled visualization of PiLuc in potato leaves and tubers during early infection stage, which is invisible to the naked eye. Capitalizing on the semi non-destructive and visual advantages, we developed a system for fungicide bioavailability evaluation and dosage-response assessment in tuber tissues, integrating real-time dynamic monitoring of pathogen. The development of bioluminescent imaging of late blight pathogen establishes an enabling platform for high-throughput fungicide screening while improving the precision bioavailability assessments.

Ribo-seq guided design of enhanced protein secretion in Komagataellaphaffii

The production of recombinant proteins requires the precise coordination of various biological processes, including protein synthesis, folding, trafficking, and secretion. The overproduction of a heterologous protein can impose various bottlenecks on these networks. Identifying and alleviating these bottlenecks can guide strain engineering efforts to enhance protein production. The methylotrophic yeast Komagataella phaffii is used for its high capacity to produce recombinant proteins. Here, we use ribosome profiling to identify bottlenecks in protein secretion during heterologous expression of human serum albumin (HSA). Validation of this analysis showed that the knockout of non-essential genes whose gene products target the ER, through co- and post-translational mechanisms, and have high ribosome utilization can increase production of a heterologous protein, HSA. A triple knockout in co-translationally translocated carbohydrate and acetate transporter Gal2p, cell wall maintenance protein Ydr134cp, and the post-translationally translocated cell wall protein Aoa65896.1 increased HSA production by 35 %. This data-driven strain engineering approach uses cell-level information to identify gene targets for phenotype improvement. This specific case identifies hits and creates strains with improved HSA production, with Ribo-seq and bioinformatic analysis to identify non-essential ER targeted proteins that are high ribosome utilizers.

From genetic code to global health: the impact of nucleic acid vaccines on disease prevention and treatment

Vaccinology has revolutionized modern medicine, delivering groundbreaking solutions to prevent and control infectious diseases while pioneering innovative strategies to tackle non-infectious challenges, including cancer. Traditional vaccines faced inherent limitations, driving the evolution of next-generation vaccines such as subunit vaccines, peptide-based vaccines, and nucleic acid-based platforms. Among these, nucleic acid-based vaccines, including DNA and mRNA technologies, represent a major innovation. Pioneering studies in the 1990s demonstrated their ability to elicit immune responses by encoding specific antigens. Recent advancements in delivery systems and molecular engineering have overcome initial challenges, enabling their rapid development and clinical success. This review explores nucleic acid-based vaccines, including chemically modified variants, by examining their mechanisms, structural features, and therapeutic potential, while underscoring their pivotal role in modern immunization strategies and expanding applications across contemporary medicine.

Characterization of oligosaccharides produced by a truncated dextransucrase from Weissella confusa Wcp3a isolated from pozol, a traditional fermented corn beverage

Glucansucrase Dsr_Wcp3a from a Weissella confusa strain discovered in fermented maize (pozol) was produced in E. coli BL21 resulting in three truncated forms of the native enzyme. An important modification of specificity is observed, as the truncated enzymes synthesize low molecular weight dextran from sucrose, probably due to the absence of domains IV and V, compared to the native enzyme which produces high molecular weight dextran. Low molecular weight dextran is obtained from the non-processive addition of glucose molecules to sucrose (FIMOS) and glucose (IMOS), resulting in two gluco-isomalto-oligosaccharide series. The exclusive synthesis of IMOS occurs in reactions where glucose is included as acceptor in reactions with sucrose as glucosyl donor substrate, due to a higher affinity for glucose as acceptor. The truncated forms also synthesize OS with maltose as acceptor.

A deep learning model trained on expressed transcripts across different tissue types reveals cell-type codon-optimization preferences

Species-specific differences in protein translation can affect the design of protein-based drugs. Consequently, efficient expression of recombinant proteins often requires codon optimization. Publicly available optimization tools do not always result in higher expression levels and can lead to protein misfolding and reduced expression. Here, we aimed to develop a novel deep learning (DL) tool using a recurrent neural network (RNN) to define cell type-dependent codon biases. Using gene expression data from three different tissue types (brain, liver, and muscle) and all secretory genes, we trained DL models to predict optimal codon usage. Codon-optimized sequences for test reporter genes exhibited enhanced protein expression compared to their original sequences and those optimized using a publicly available tool. Interestingly, DL models trained on genes expressed in liver cells (hepatocytes) resulted in the highest levels of expression when tested in vitro, irrespective of the cell type. Our findings also demonstrate that DL-based codon optimization algorithms can significantly enhance protein translation, particularly for secretory proteins, which are crucial for therapeutic applications. This research represents a novel approach to codon optimization with broader implications for protein-based pharmaceuticals, vaccine manufacturing, gene therapy, and other recombinant DNA products.

Technological breakthroughs and advancements in the application of mRNA vaccines: a comprehensive exploration and future prospects

mRNA vaccines utilize single-stranded linear DNA as a template for in vitro transcription. The mRNA is introduced into the cytoplasm via the corresponding delivery system to express the target protein, which then performs its relevant biological function. mRNA vaccines are beneficial in various fields, including cancer vaccines, infectious disease vaccines, protein replacement therapy, and treatment of rare diseases. They offer advantages such as a simple manufacturing process, a quick development cycle, and ease of industrialization. Additionally, mRNA vaccines afford flexibility in adjusting antigen designs and combining sequences of multiple variants, thereby addressing the issue of frequent mutations in pathogenic microorganisms. This paper aims to provide an extensive review of the global development and current research status of mRNA vaccines, with a focus on immunogenicity, classification, design, delivery vector development, stability, and biomedical application. Moreover, the study highlights current challenges and offers insights into future directions for development.

Role of nucleotide pair frequency and synonymous codon usage in the evolution of bovine viral diarrhea virus

Synonymous codon usage plays an important role in the adaptation of viruses to their hosts. Bovine viral diarrhea virus (BVDV) relies on a high mutation rate in its genome to achieve the necessary fitness in a particular host. However, the question of which selective forces influence nucleotide pair and synonymous codon usage patterns in different BVDV genotypes remains unresolved. Here, 169 BVDV strains isolated at different times in various countries were analyzed to compare their dinucleotide frequency and synonymous codon usage. Examination of the nucleotide usage pattern in the open reading frame (ORF) of BVDV revealed a significantly higher frequency of purine than pyrimidine, with the highest extent of nucleotide usage bias observed in the first codon position. Moreover, a nucleotide pair bias, especially favoring CpG dinucleotides, was observed in all of the genotypes. Together, the nucleotide composition constraints and nucleotide pair bias appear to have influenced the overall codon usage pattern. Nucleotide pair and synonymous codon usage biases were associated with individual genotypes to different degrees. Of particular note, BVDV-1 exhibited more variation in its nucleotide pair and synonymous codon usage than BVDV-2 and BVDV-3, suggesting that these patterns are shaped both by selection of mutations in the viral genome and translational selection in the host.

Effective Gene Expression Prediction and Optimization from Protein Sequences

High soluble protein expression in heterologous hosts is crucial for various research and applications. Despite considerable research on the impact of codon usage on expression levels, the relationship between protein sequence and expression is often overlooked. In this study, a novel connection between protein expression and sequence is uncovered, leading to the development of SRAB (Strength of Relative Amino Acid Bias) based on AEI (Amino Acid Expression Index). The AEI served as an objective measure of this correlation, with higher AEI values enhancing soluble expression. Subsequently, the pre-trained protein model MP-TRANS (MindSpore Protein Transformer) is developed and fine-tuned using transfer learning techniques to create 88 prediction models (MPB-EXP) for predicting heterologous expression levels across 88 species. This approach achieved an average accuracy of 0.78, surpassing conventional machine learning methods. Additionally, a mutant generation model, MPB-MUT, is devised and utilized to enhance expression levels in specific hosts. Experimental validation demonstrated that the top 3 mutants of xylanase (previously not expressed in Escherichia coli) successfully achieved high-level soluble expression in E. coli. These findings highlight the efficacy of the developed model in predicting and optimizing gene expression based on protein sequences.

Phylogenetic and Functional Diversity of Soluble Di-Iron Monooxygenases

Monooxygenase (MO) enzymes are responsible for the oxidation of hydrocarbons and other compounds in the carbon and nitrogen cycles, are important for the biodegradation of pollutants and can act as biocatalysts for chemical manufacture. The soluble di-iron monooxygenases (SDIMOs) are of interest due to their broad substrate range, high enantioselectivity and ability to oxidise inert substrates such as methane. Here, we re-examine the phylogeny and functions of these enzymes, using recent advances in the field and expansions in sequence diversity in databases to highlight relationships between SDIMOs and revisit their classification. We discuss the impact of horizontal gene transfer on SDIMO phylogeny, the potential of SDIMOs for the biodegradation of pollutants and the importance of heterologous expression as a tool for understanding SDIMO functions and enabling their use as biocatalysts. Our analysis highlights current knowledge gaps, most notably, the unknown substrate ranges and physiological roles of enzymes that have so far only been detected via genome or metagenome sequencing. Enhanced understanding of the diversity and functions of the SDIMO enzymes will enable better prediction and management of biogeochemical processes and also enable new applications of these enzymes for biocatalysis and bioremediation.

Exploring Antibiotic Resistance in Diverse Homologs of the Dihydrofolate Reductase Protein Family through Broad Mutational Scanning

Current antibiotic resistance studies often focus on individual protein variants, neglecting broader protein family dynamics. Dihydrofolate reductase (DHFR), a key antibiotic target, has been extensively studied using deep mutational scanning, yet resistance mechanisms across this diverse protein family remain poorly understood. Using DropSynth, a scalable gene synthesis platform, we designed a library of 1,536 synthetic DHFR homologs representing 778 species of bacteria, archaea, and viruses, including clinically relevant pathogens. A multiplexed in vivo assay tested their ability to restore metabolic function and confer trimethoprim resistance in an E. coli ∆folA strain. Over half of the synthetic homologs rescued the phenotype without supplementation, and mutants with up to five amino acid substitutions increased the rescue rate to 90%, highlighting DHFR's evolutionary resilience. Broad Mutational Scanning (BMS) of homologs and 100,000 mutants provided critical insights into DHFR's fitness landscape and resistance pathways, representing the most extensive analysis of homolog complementation and inhibitor tolerance to date and advancing our understanding of antibiotic resistance mechanisms.

Predicting gene sequences with AI to study codon usage patterns

Selective pressure acts on the codon use, optimizing multiple, overlapping signals that are only partially understood. We trained AI models to predict codons given their amino acid sequence in the eukaryotes Saccharomyces cerevisiae and Schizosaccharomyces pombe and the bacteria Escherichia coli and Bacillus subtilis to study the extent to which we can learn patterns in naturally occurring codons to improve predictions. We trained our models on a subset of the proteins and evaluated their predictions on large, separate sets of proteins of varying lengths and expression levels. Our models significantly outperformed naïve frequency-based approaches, demonstrating that there are learnable dependencies in evolutionary-selected codon usage. The prediction accuracy advantage of our models is greater for highly expressed genes and is greater in bacteria than eukaryotes, supporting the hypothesis that there is a monotonic relationship between selective pressure for complex codon patterns and effective population size. In S. cerevisiae and bacteria, our models were more accurate for longer proteins, suggesting that the learned patterns may be related to cotranslational folding. Gene functionality and conservation were also important determinants that affect the performance of our models. Finally, we showed that using information encoded in homologous proteins has only a minor effect on prediction accuracy, perhaps due to complex codon-usage codes in genes undergoing rapid evolution. Our study employing contemporary AI methods offers a unique perspective and a deep-learning-based prediction tool for evolutionary-selected codons. We hope that these can be useful to optimize codon usage in endogenous and heterologous proteins.

From Sequence to System: Enhancing IVT mRNA Vaccine Effectiveness through Cutting-Edge Technologies

The COVID-19 pandemic has spotlighted the potential of in vitro transcribed (IVT) mRNA vaccines with their demonstrated efficacy, safety, cost-effectiveness, and rapid manufacturing. Numerous IVT mRNA vaccines are now under clinical trials for a range of targets, including infectious diseases, cancers, and genetic disorders. Despite their promise, IVT mRNA vaccines face hurdles such as limited expression levels, nonspecific targeting beyond the liver, rapid degradation, and unintended immune activation. Overcoming these challenges is crucial to harnessing the full therapeutic potential of IVT mRNA vaccines for global health advancement. This review provides a comprehensive overview of the latest research progress and optimization strategies for IVT mRNA molecules and delivery systems, including the application of artificial intelligence (AI) models and deep learning techniques for IVT mRNA structure optimization and mRNA delivery formulation design. We also discuss recent development of the delivery platforms, such as lipid nanoparticles (LNPs), polymers, and exosomes, which aim to address challenges related to IVT mRNA protection, cellular uptake, and targeted delivery. Lastly, we offer insights into future directions for improving IVT mRNA vaccines, with the hope to spur further progress in IVT mRNA vaccine research and development.

Advancing novel veterinary vaccines: From comprehensive antigen and adjuvant design to preparation process optimization

Vaccination stands as the paramount and cost-effective strategy for the prevention and management of animal infectious diseases. With the advances in biological technology, materials science and industrial optimization, substantial progress has been made in the development of innovative veterinary vaccines. A majority of the novel vaccines under current investigation tend to stimulate multiple immune pathways and to achieve long-term resistance against infectious diseases, yet it remains imperative to concentrate research efforts on the efficient utilization of vaccines, mitigating toxic side effects, and ensuring safe production processes. This article presents an overview of research progress in veterinary vaccines, encompassing comprehensive antigen design, adjuvant formulation advancements, preparation process optimization, and rigorous immune efficacy evaluation. It summarizes cutting-edge vaccines derived from in vitro synthesis and in vivo application, emphasizing immunogenic components and immune response mechanisms. It also highlights novel biological adjuvants that enhance immune efficacy, diversify raw materials, and possess targeted functions, while comprehensively exploring advancements in production methodologies and compatible vaccine products. By establishing a foundation for the integrated use of these innovative veterinary vaccines, this work facilitates future interdisciplinary cooperation in their advancement, aiming to accelerate the achievement of herd immunity through concerted efforts.

Newly developed mRNA vaccines induce immune responses in Litopenaeus vannamei shrimps during primary vaccination

White spot syndrome virus (WSSV) causes highly destructive infection in crustacean aquaculture, often resulting in 100% mortality within a week. However, there is lack of studies addressing the safety issues of WSSV vaccines in shrimps. In this study, WSSV VP28 mRNA vaccines were developed using codon deoptimization approach. These vaccines were administered to Litopenaeus vannamei shrimps at various dosages to access their safety and the shrimps' immune responses using quantification PCR (qPCR). The findings of this study indicate that the expression level of codon deoptimized VP28 mRNA vaccines are lower compared to the wild type VP28 vaccines, as observed through a comparison of bioinformatic predictions and experimental results. Additionally, the total haemocyte count (THC) in shrimps injected with codon deoptimized VP28 vaccine was higher than those injected with wild type VP28 vaccines. Furthermore, the expression of immune-related genes differed between codon deoptimized and wild type VP28 vaccines. In summary, the results suggest that 0.01 μg codon deoptimized VP28-D1 mRNA vaccine is the most promising WSSV mRNA vaccine, displaying low pathogenicity and expression in shrimps. To the best of our knowledge, this research represents the first attempt to attenuate WSSV using codon deoptimization method and development of a potential mRNA vaccine for shrimp purpose. The study addresses an important gap in shrimp vaccine research, offering potential solutions for WSSV control in shrimps.

Discovery and investigation of the truncation of the (GGGGS)n linker and its effect on the productivity of bispecific antibodies expressed in mammalian cells

Protein engineering is a powerful tool for designing or modifying therapeutic proteins for enhanced efficacy, increased safety, reduced immunogenicity, and improved delivery. Fusion proteins are an important group of therapeutic compounds that often require an ideal linker to combine diverse domains to fulfill the desired function. GGGGS [(G4S)n] linkers are commonly used during the engineering of proteins because of their flexibility and resistance to proteases. However, unexpected truncation was observed in the linker of a bispecific antibody, which presented challenges in terms of production and quality. In this work, a bispecific antibody containing 5*G4S was investigated, and the truncation position of the linkers was confirmed. Our investigation revealed that codon optimization, which can overcome the negative influence of a high repetition rate and high GC content in the (G4S)n linker, may reduce the truncation rate from 5-10% to 1-5%. Moreover, the probability of truncation when a shortened 3* or 4*G4S linker was used was much lower than that when a 5*G4S linker was used in mammalian cells. In the case of expressing a bispecific antibody, the bioactivity and purity of the product containing a shorter G4S linker were further investigated and are discussed.

Current Non-Viral-Based Strategies to Manufacture CAR-T Cells

The successful application of CAR-T cells in the treatment of hematologic malignancies has fundamentally changed cancer therapy. With increasing numbers of registered CAR-T cell clinical trials, efforts are being made to streamline and reduce the costs of CAR-T cell manufacturing while improving their safety. To date, all approved CAR-T cell products have relied on viral-based gene delivery and genomic integration methods. While viral vectors offer high transfection efficiencies, concerns regarding potential malignant transformation coupled with costly and time-consuming vector manufacturing are constant drivers in the search for cheaper, easier-to-use, safer, and more efficient alternatives. In this review, we examine different non-viral gene transfer methods as alternatives for CAR-T cell production, their advantages and disadvantages, and examples of their applications. Transposon-based gene transfer methods lead to stable but non-targeted gene integration, are easy to handle, and achieve high gene transfer rates. Programmable endonucleases allow targeted integration, reducing the potential risk of integration-mediated malignant transformation of CAR-T cells. Non-integrating CAR-encoding vectors avoid this risk completely and achieve only transient CAR expression. With these promising alternative techniques for gene transfer, all avenues are open to fully exploiting the potential of next-generation CAR-T cell therapy and applying it in a wide range of applications.

Construction of Pseudomonas aeruginosa SDK-6 with synthetic lipase gene cassette and optimization of different parameters using response surface methodology for over-expression of recombinant lipase

Lipases are industrially important enzymes having vast applications in various fields. Cloning and expression of lipase enzyme-encoding genes in suitable host lead to their widespread use in different fields. The present study represents the first attempt towards the expression of the synthetic lipase gene in Pseudomonas aeruginosa. An alkalophilic lipase gene (GenBank accession number: NP_388152) from Bacillus subtilis was synthetically designed and introduced in the pJN105 vector and subsequently cloned in Pseudomonas aeruginosa SDK-6. Agarose gel electrophoresis confirmed the transformation of SDK-6, exhibiting a band difference of ~ 700 bp between native and recombinant pJN105. Further amplification of cloned lipase gene was confirmed using PCR amplification with Lip 1 and Lip 2 primers respectively, followed by restriction analysis. Approximately 15-fold increase in lipase production was observed in recombinant Pseudomonas as compared to the native strain. One factor at a time (OFAT) analysis revealed L-arabinose, inoculum size (0.5%; v/v), and agitation (120 rpm) as significant factors affecting the over-expression of lipase enzyme. Optimization of enzyme induction conditions by central composite design (CCD) led to 1.60-fold increase in the production of lipase at 0.65% (w/v) inducer concentration, OD600-1.075 before induction and 35 °C post induction temperature with overall lipase production of 50.50 IU/mL. Statistical validation of observed value via ANOVA showed an F-value of 138.70 at p < 0.01 with R2 of 0.9921.

Application of immunoinformatics to develop a novel and effective multiepitope chimeric vaccine against Variovorax durovernensis

Bloodstream infections pose a significant public health challenge caused by resistant bacteria such as Variovorax durovernensis, a recently reported Gram-negative bacterium, worsening the burden on healthcare systems. The design of a vaccine using chimeric peptides derived from a representative V. durovernensis strain holds significant promise for preventing disease onset. The current study aimed to employ reverse vaccinology (RV) approaches such as the retrieval of V. durovernensis proteomics data, removal of redundant proteins by CD-HIT, filtering of non-homologous proteins to humans and essential proteins, identification of outer membrane (OM) proteins by CELLO and PSORTb. Following these steps immunoinformatic approaches were applied, such as epitope prediction by IEDB, vaccine design using linkers and adjuvant and analysis of antigenicity, allergenicity, safety and stability. Among the 4208 nonredundant proteins, an OmpA family protein (A0A940EKP4) was designated a potential candidate for the development of a multiepitope vaccine construct. Upon analysis of OM protein, six immunodominant (B cell) epitopes were found on the basis of the chimeric construct following the prediction of CTL stands cytotoxic T lymphocyte and HTL stands helper T lymphocyte epitopes. To ensure comprehensive population coverage globally, the CTL and HTL coverage rates were 58.18 % and 46.56 %, respectively, and 77.23 % overall. By utilizing EAAAK, GPGPG, and AAY linkers, Cholera toxin B subunit adjuvants, and appropriate epitopes were smoothly incorporated into a chimeric vaccine effectively triggering both adaptive and innate immune responses. For example, the administered antigen showed a peak in counts on the fifthday post injection and then gradually declined until the fifteenth day. Elevated levels of several antibodies (IgG + IgM > 700,000; IgM > 600,000; IgG1 + IgG2; IgG1 > 500,000) were observed as decreased in the antigen concentration. Molecular dynamics simulations carried out via iMODS revealed strong correlations between residue pairs, highlighting the stability of the docked complex. The designed vaccine has promising potential in eliciting specific immunogenic responses, thereby facilitating future research for vaccine development against V. durovernensis.

Scaled codon usage similarity index: A comprehensive resource for crop plants

Over the past three decades species-specific codon usage bias has been used to optimize heterologous gene expression in the target host. However, synthesizing codon optimized gene for multiple species is not achievable due to the prohibitive expense of DNA synthesis. To address this challenge, grouping species with similar codon usage can reduce the need for species-specific codon optimised gene synthesis. We introduced Scaled Codon Usage Similarity (SCUS) index to standardize species similarity assessments based on codon usage profiles. By analysing the SCUS index of 77 plant nuclear genomes from 13 families, we identified codon usage patterns and similarities. We developed an online SCUS index database and a Consensus Relative Synonymous Codon Usage (CRSCU) calculator, available at https://pcud.plantcodon.info. The CRSCU calculator helps determine the most suitable codon usage pattern among two or more species. The SCUS index and CRSCU calculator will facilitate the development of multi-species expression systems, enabling the efficient expression of a single synthetic gene across various crop species. This innovation paves the way for cost-effective and efficient heterologous gene expression across diverse crop species.

Metabolic engineering of Mucor circinelloides to improve astaxanthin production

Astaxanthin is a bioactive natural pigment with antioxidant properties. It has extensive applications within the industrial sector as well as in human and animal health. Mucor circinelloides is a zygomycete fungus that accumulates β-carotene as the main carotenoid compound. M. circinelloides is a well-known model organism among Mucorales for studying carotenogenesis in fungi, which makes it a promising candidate for the biotechnological production of carotenoids. In this study, β-carotene hydroxylase (crtR-B) and ketolase (bkt) genes (codon-optimized) were coexpressed from Haematococcus pluvialis in M. circinelloides using two potent promoters gpd1 and zrt1 respectively to generate an astaxanthin-producing biofactory. Following 72 h of cultivation, the recombinant M. circinelloides Mc-57 obtained in this study produced 135 ± 8 µg/g of astaxanthin. This is the highest reported amount in M. circinelloides to date. The mRNA levels of crtR-B and bkt in Mc-57 were assayed using RT-qPCR. These levels showed a 5.7-fold increase at 72 h and a 5.5-fold increase at 24 h, respectively, compared to the control strain. This demonstrated the successful overexpression of both genes, which correlated with the production of astaxanthin in the Mc-57. Moreover, the addition of glutamate (2 g/L) and mevalonate (15 mM) resulted in an increase in astaxanthin production in the recombinant strain. The results showed that the combined addition of these metabolic precursors resulted in 281 ± 20 µg/g of astaxanthin, which is 2.08-fold higher than the control medium (135 ± 8 µg/g). The addition of metabolic precursors also positively impacted the biomass growth of Mc-57, reaching 11.2 ± 0.57 g/L compared to 9.1 ± 0.23 g/L (control medium). The study successfully addressed the challenge of balancing the accumulation of astaxanthin with biomass growth, which has been regarded as common bottleneck in the metabolic engineering of microbial cells. The development of a recombinant fungal strain of M. circinelloides not only increased astaxanthin content. Additionally, it provided a foundation for further improvement of the biotechnological production of astaxanthin in M. circinelloides.

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.

Strangers in a foreign land: 'Yeastizing' plant enzymes

Expressing plant metabolic pathways in microbial platforms is an efficient, cost-effective solution for producing many desired plant compounds. As eukaryotic organisms, yeasts are often the preferred platform. However, expression of plant enzymes in a yeast frequently leads to failure because the enzymes are poorly adapted to the foreign yeast cellular environment. Here, we first summarize the current engineering approaches for optimizing performance of plant enzymes in yeast. A critical limitation of these approaches is that they are labour-intensive and must be customized for each individual enzyme, which significantly hinders the establishment of plant pathways in cellular factories. In response to this challenge, we propose the development of a cost-effective computational pipeline to redesign plant enzymes for better adaptation to the yeast cellular milieu. This proposition is underpinned by compelling evidence that plant and yeast enzymes exhibit distinct sequence features that are generalizable across enzyme families. Consequently, we introduce a data-driven machine learning framework designed to extract 'yeastizing' rules from natural protein sequence variations, which can be broadly applied to all enzymes. Additionally, we discuss the potential to integrate the machine learning model into a full design-build-test cycle.

Tobacco Plant: A Novel and Promising Heterologous Bioreactor for the Production of Recombinant Bovine Chymosin

The natural source of chymosin, a key enzyme in the dairy industry, is insufficient for rapidly growing cheese industries. Large-scale production of recombinant proteins in heterologous hosts provides an efficient alternative solution. Here, the codon-optimized synthetic prochymosin gene, which has a CAI index of 0.926, was subcloned from a cloning vector (pUC57-bCYM) into the pBI121 vector, resulting in the construct named pBI121-bCYM. CAI ranges from 0 to 1 and higher CAI improves gene expression in heterologous hosts. The overexpression of the prochymosin gene was under the control of constitutive CaMV 35S promoter and NOS terminator and was transferred into the tobacco via A. tumefaciens strain LBA4404. Explant type, regeneration method, inoculation temperature, cell density (OD600) of Agrobacterium for inoculation, and acetosyringone concentration were leaf explants, direct somatic embryogenesis, 19 °C, 0.1, and 100 µM, respectively. The successful integration and expression of the prochymosin gene, along with the bioactivity of recombinant chymosin, were confirmed by PCR, RT-PCR, and milk coagulation assay, respectively. Overall, this study reports the first successful overexpression of the codon-optimized prochymosin form of the bovine chymosin enzyme in the tobacco via indirect transformation. Production of recombinant bovine chymosin in plants can be an easy-to-scale-up, safe, and inexpensive platform.

Comparative Analysis of Codon Usage Bias in Six Eimeria Genomes

The codon usage bias (CUB) of genes encoded by different species' genomes varies greatly. The analysis of codon usage patterns enriches our comprehension of genetic and evolutionary characteristics across diverse species. In this study, we performed a genome-wide analysis of CUB and its influencing factors in six sequenced Eimeria species that cause coccidiosis in poultry: Eimeria acervulina, Eimeria necatrix, Eimeria brunetti, Eimeria tenella, Eimeria praecox, and Eimeria maxima. The GC content of protein-coding genes varies between 52.67% and 58.24% among the six Eimeria species. The distribution trend of GC content at different codon positions follows GC1 > GC3 > GC2. Most high-frequency codons tend to end with C/G, except in E. maxima. Additionally, there is a positive correlation between GC3 content and GC3s/C3s, but a significantly negative correlation with A3s. Analysis of the ENC-Plot, neutrality plot, and PR2-bias plot suggests that selection pressure has a stronger influence than mutational pressure on CUB in the six Eimeria genomes. Finally, we identified from 11 to 15 optimal codons, with GCA, CAG, and AGC being the most commonly used optimal codons across these species. This study offers a thorough exploration of the relationships between CUB and selection pressures within the protein-coding genes of Eimeria species. Genetic evolution in these species appears to be influenced by mutations and selection pressures. Additionally, the findings shed light on unique characteristics and evolutionary traits specific to the six Eimeria species.

Transcriptional Dynamics of NRF2 Overexpression and KEAP1-NRF2 Inhibitors in Human Cell Line and Primary Lung Cells

Oxidative stress in the human lung is caused by both internal (e.g., inflammation) and external stressors (smoking, pollution, and infection) to drive pathology in a number of lung diseases. Cellular damage caused by oxidative damage is reversed by several pathways, one of which is the antioxidant response. This response is regulated by the transcriptional factor NRF2, which has the ability to regulate the transcription of more than 250 genes. In disease, this balance is overwhelmed, and the cells are unable to return to homeostasis. Several pharmacological approaches aim to improve the antioxidant capacity by inhibiting the interaction of NRF2 with its key cytosolic inhibitor, KEAP1. Here, we evaluate an alternative approach by overexpressing NRF2 from chemically modified RNAs (cmRNAs). Our results demonstrate successful expression of functional NRF2 protein in human cell lines and primary cells. We establish a kinetic transcriptomic profile to compare antioxidant response gene expression after treatment of primary human bronchial epithelial cells with either KEAP1 inhibitors or cmRNAs. The key gene signature is then applied to primary human lung fibroblasts and alveolar macrophages to uncover transcriptional preferences in each cell system. This study provides a foundation for the understanding of NRF2 dynamics in the human lung and provides initial evidence of alternative ways for pharmacological interference.

Expression and Subcellular Localization of Lanthipeptides in Human Cells

Cyclic peptides, such as most ribosomally synthesized and post-translationally modified peptides (RiPPs), represent a burgeoning area of interest in therapeutic and biotechnological research because of their conformational constraints and reduced susceptibility to proteolytic degradation compared to their linear counterparts. Herein, an expression system is reported that enables the production of structurally diverse lanthipeptides and derivatives in mammalian cells. Successful targeting of lanthipeptides to the nucleus, the endoplasmic reticulum, and the plasma membrane is demonstrated. In vivo expression and targeting of such peptides in mammalian cells may allow for screening of lanthipeptide-based cyclic peptide inhibitors of native, organelle-specific protein-protein interactions in mammalian systems.

Translation Rates and Protein Folding

The mRNA coding sequence defines not only the amino acid sequence of the protein, but also the speed at which the ribosomes move along the mRNA while making the protein. The non-uniform local kinetics - denoted as translational rhythm - is similar among mRNAs coding for related protein folds. Deviations from this conserved rhythm can result in protein misfolding. In this review we summarize the experimental evidence demonstrating how local translation rates affect cotranslational protein folding, with the focus on the synonymous codons and patches of charged residues in the nascent peptide as best-studied examples. Alterations in nascent protein conformations due to disturbed translational rhythm can persist off the ribosome, as demonstrated by the effects of synonymous codon variants of several disease-related proteins. Charged amino acid patches in nascent chains also modulate translation and cotranslational protein folding, and can abrogate translation when placed at the N-terminus of the nascent peptide. During cotranslational folding, incomplete nascent chains navigate through a unique conformational landscape in which earlier intermediate states become inaccessible as the nascent peptide grows. Precisely tuned local translation rates, as well as interactions with the ribosome, guide the folding pathway towards the native structure, whereas deviations from the natural translation rhythm may favor pathways leading to trapped misfolded states. Deciphering the 'folding code' of the mRNA will contribute to understanding the diseases caused by protein misfolding and to rational protein design.

RNA vaccines for cancer: Principles to practice

Vaccines are the most impactful medicines to improve health. Though potent against pathogens, vaccines for cancer remain an unfulfilled promise. However, recent advances in RNA technology coupled with scientific and clinical breakthroughs have spurred rapid discovery and potent delivery of tumor antigens at speed and scale, transforming cancer vaccines into a tantalizing prospect. Yet, despite being at a pivotal juncture, with several randomized clinical trials maturing in upcoming years, several critical questions remain: which antigens, tumors, platforms, and hosts can trigger potent immunity with clinical impact? Here, we address these questions with a principled framework of cancer vaccination from antigen detection to delivery. With this framework, we outline features of emergent RNA technology that enable rapid, robust, real-time vaccination with somatic mutation-derived neoantigens-an emerging "ideal" antigen class-and highlight latent features that have sparked the belief that RNA could realize the enduring vision for vaccines against cancer.

Comparative Analysis of Complete Mitochondrial Genomes of Five Chromodorididae Species (Nudibranchia:Doridina)

Mitochondrial genome is an important molecular marker for exploring the phylogenetic relationships of species and revealing molecular evolution. In the present study, 5 mitogenomes of Chromodorididae (Chromodoris lochi, Chromodoris colemani, Chromodoris elisabethina, Chromodoris annae and Hypselodoris whitei) were systemically investigated. The lengths of the mitogenomes sequences were 14248 bp, 14257 bp, 14252 bp, 14254 bp and 14856 bp, respectively. Most protein-coding genes (PCGs) were initiated with the common ATG codon and terminated with the TAA and TAG. We calculated Ka/Ks values for all 13 PCGs of Chromodorididae species, all ratios were less than 1, indicating selection by purification. Phylogenetic relationships were constructed by Bayesian inference (BI) and maximum likelihood (ML) methods based on all complete genomes of 50 species, primarily from the family Chromodorididae (Doridina) and 2 outgroups. This phylogenetic tree provided further additional references for the classification of the suborder Doridina. Gene rearrangement suggested a more conserved pattern of gene sequences in the superfamily Chromodoridoidea. These results and newly sequenced will contribute to a better understanding of Chromodorididae and provide reference for further phylogenetic studies.

Development of recombinant proteins for vaccine candidates against serotypes O and A of Foot-and-Mouth Disease virus in Bangladesh

Frequent vaccine failure leading to recurrent outbreaks of Foot-and-Mouth Disease (FMD) in livestock populations necessitates the development of a customizable vaccine platform comprising potential antigenic determinants of circulating lineages of FMD viruses. Artificially designed, chimaeric protein-based recombinant vaccines are novel approaches to combat the phylogenetically diverse FMD Virus (FMDV) strains. Among seven recognized serotypes, only serotypes O and A are dominantly circulating in Bangladesh and neighbouring countries of Asia, where transboundary transmission, recurrent outbreaks and emergence of novel lineages of FMDV are highly prevalent. The objective of this study was to develop multi-epitope recombinant proteins, procuring immunogenicity against circulating diverse genotypes of FMDV serotypes O and A. Two chimaeric proteins, named B1 (41.0 kDa) and B3 (39.3 kDa), have been designed to incorporate potential B-cell and T-cell epitopes selected from multiple FMDV strains, including previously reported and newly emerged sub-lineages. After expression, characterization and immunization of guinea pigs with a considerable antigen load of B1 and B3 followed by serological assays revealed the significant protective immunogenicity, developed from the higher (100 µg) doses of both antigens, against most of the currently prevalent serotype O and A strains of FMDV. The efficient expression, antigenic stability, and multivalent immunogenic potency of the chimaeric proteins strongly indicate their credibility as novel vaccine candidates for existing serotypes O and A of FMDV in Bangladesh and surrounding territories.

Optimizing 5'UTRs for mRNA-delivered gene editing using deep learning

mRNA therapeutics are revolutionizing the pharmaceutical industry, but methods to optimize the primary sequence for increased expression are still lacking. Here, we design 5'UTRs for efficient mRNA translation using deep learning. We perform polysome profiling of fully or partially randomized 5'UTR libraries in three cell types and find that UTR performance is highly correlated across cell types. We train models on our datasets and use them to guide the design of high-performing 5'UTRs using gradient descent and generative neural networks. We experimentally test designed 5'UTRs with mRNA encoding megaTALTM gene editing enzymes for two different gene targets and in two different cell lines. We find that the designed 5'UTRs support strong gene editing activity. Editing efficiency is correlated between cell types and gene targets, although the best performing UTR was specific to one cargo and cell type. Our results highlight the potential of model-based sequence design for mRNA therapeutics.

Advances in non-viral mRNA delivery to the spleen

Developing safe and effective delivery strategies for localizing messenger RNA (mRNA) payloads to the spleen is an important goal in the field of genetic medicine. Accomplishing this goal is challenging due to the instability, size, and charge of mRNA payloads. Here, we provide an analysis of non-viral delivery technologies that have been developed to deliver mRNA payloads to the spleen. Specifically, our review begins by outlining the unique anatomy and potential targets for mRNA delivery within the spleen. Next, we describe approaches in mRNA sequence engineering that can be used to improve mRNA delivery to the spleen. Then, we describe advances in non-viral carrier systems that can package and deliver mRNA payloads to the spleen, highlighting key advances in the literature in lipid nanoparticle (LNP) and polymer nanoparticle (PNP) technology platforms. Finally, we provide commentary and outlook on how splenic mRNA delivery may afford next-generation treatments for autoimmune disorders and cancers. In undertaking this approach, our goal with this review is to both establish a fundamental understanding of drug delivery challenges associated with localizing mRNA payloads to the spleen, while also broadly highlighting the potential to use these genetic medicines to treat disease.

Heterologous Expression of Plantaricin 423 and Mundticin ST4SA in Saccharomyces cerevisiae

Antimicrobial peptides or bacteriocins are excellent candidates for alternative antimicrobials, but high manufacturing costs limit their applications. Recombinant gene expression offers the potential to produce these peptides more cost-effectively at a larger scale. Saccharomyces cerevisiae is a popular host for recombinant protein production, but with limited success reported on antimicrobial peptides. Individual recombinant S. cerevisiae strains were constructed to secrete two class IIa bacteriocins, plantaricin 423 (PlaX) and mundticin ST4SA (MunX). The native and codon-optimised variants of the plaA and munST4SA genes were cloned into episomal expression vectors containing either the S. cerevisiae alpha mating factor (MFα1) or the Trichoderma reesei xylanase 2 (XYNSEC) secretion signal sequences. The recombinant peptides retained their activity and stability, with the MFα1 secretion signal superior to the XYNSEC secretion signal for both bacteriocins. An eight-fold increase in activity against Listeria monocytogenes was observed for MunX after codon optimisation, but not for PlaX-producing strains. After HPLC-purification, the codon-optimised genes yielded 20.9 mg/L of MunX and 18.4 mg/L of PlaX, which displayed minimum inhibitory concentrations (MICs) of 108.52 nM and 1.18 µM, respectively, against L. monocytogenes. The yields represent a marked improvement relative to an Escherichia coli expression system previously reported for PlaX and MunX. The results demonstrated that S. cerevisiae is a promising host for recombinant bacteriocin production that requires a simple purification process, but the efficacy is sensitive to codon usage and secretion signals.

Intraspecific and interspecific variations in the synonymous codon usage in mitochondrial genomes of 8 pleurotus strains

In this study, we investigated the codon bias of twelve mitochondrial core protein coding genes (PCGs) in eight Pleurotus strains, two of which are from the same species. The results revealed that the codons of all Pleurotus strains had a preference for ending in A/T. Furthermore, the correlation between codon base compositions and codon adaptation index (CAI), codon bias index (CBI) and frequency of optimal codons (FOP) indices was also detected, implying the influence of base composition on codon bias. The two P. ostreatus species were found to have differences in various base bias indicators. The average effective number of codons (ENC) of mitochondrial core PCGs of Pleurotus was found to be less than 35, indicating strong codon preference of mitochondrial core PCGs of Pleurotus. The neutrality plot analysis and PR2-Bias plot analysis further suggested that natural selection plays an important role in Pleurotus codon bias. Additionally, six to ten optimal codons (ΔRSCU > 0.08 and RSCU > 1) were identified in eight Pleurotus strains, with UGU and ACU being the most widely used optimal codons in Pleurotus. Finally, based on the combined mitochondrial sequence and RSCU value, the genetic relationship between different Pleurotus strains was deduced, showing large variations between them. This research has improved our understanding of synonymous codon usage characteristics and evolution of this important fungal group.

An Integer Linear Programming Model to Optimize Coding DNA Sequences By Joint Control of Transcript Indicators

A Coding DNA Sequence (CDS) is a fraction of DNA whose nucleotides are grouped into consecutive triplets called codons, each one encoding an amino acid. Because most amino acids can be encoded by more than one codon, the same amino acid chain can be obtained by a very large number of different CDSs. These synonymous CDSs show different features that, also depending on the organism the transcript is expressed in, could affect translational efficiency and yield. The identification of optimal CDSs with respect to given transcript indicators is in general a challenging task, but it has been observed in recent literature that integer linear programming (ILP) can be a very flexible and efficient way to achieve it. In this article, we add evidence to this observation by proposing a new ILP model that simultaneously optimizes different well-grounded indicators. With this model, we efficiently find solutions that dominate those returned by six existing codon optimization heuristics.

"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.

Comprehensive Genomics Investigation of Neboviruses Reveals Distinct Codon Usage Patterns and Host Specificity

Neboviruses (NeVs) from the Caliciviridae family have been linked to enteric diseases in bovines and have been detected worldwide. As viruses rely entirely on the cellular machinery of the host for replication, their ability to thrive in a specific host is greatly impacted by the specific codon usage preferences. Here, we systematically analyzed the codon usage bias in NeVs to explore the genetic and evolutionary patterns. Relative Synonymous Codon Usage and Effective Number of Codon analyses indicated a marginally lower codon usage bias in NeVs, predominantly influenced by the nucleotide compositional constraints. Nonetheless, NeVs showed a higher codon usage bias for codons containing G/C at the third codon position. The neutrality plot analysis revealed natural selection as the primary factor that shaped the codon usage bias in both the VP1 (82%) and VP2 (57%) genes of NeVs. Furthermore, the NeVs showed a highly comparable codon usage pattern to bovines, as reflected through Codon Adaptation Index and Relative Codon Deoptimization Index analyses. Notably, yak NeVs showed considerably different nucleotide compositional constraints and mutational pressure compared to bovine NeVs, which appear to be predominantly host-driven. This study sheds light on the genetic mechanism driving NeVs' adaptability, evolution, and fitness to their host species.

Cloning and heterologous expression of Fusarium oxysporum nitrilase gene in Escherichia coli and evaluation in cyanide degradation

Cyanide is widely utilized in the extraction of precious metal extraction even though it has been deemed as the most toxic compound. Fusarium oxysporum has been shown to degrade cyanide through the activity of the Nitrilase enzyme. In this study, the coding sequence of nitrilase gene from F. oxysporum genomic DNA was optimized for cloning and expression in E. coli. The pUC57 containing synthetic optimized nitrilase gene was transferred into E. coli DH5α strain. This nitrilase gene was sub-cloned into pET26b (+) expression vector containing an in-built His-tag at the C-terminal end to facilitate its purification. The recombinant plasmid, pETAM1, was confirmed by PCR, digestion pattern, and sequencing. The recombinant protein was overproduced in E. coli BL21 (DE3). The results of the SDS-PAGE pattern and Western blot analysis confirmed the expression of the expected recombinant protein. For expression optimization of Nitrilase protein, M16 orthogonal experimental design of the Taguchi method was used. The effect of induction time, temperature and IPTG concentration were examined using four levels for each factors. Estimation of the amount of the expressed protein was calculated via densitometry on SDS-PAGE. The enzyme activity and expression in E. coli proved to be successful since there was ammonia production when potassium cyanide and acrylonitrile were used as substrates while the highest enzyme activity of 88% was expressed at 30 °C. The Km and Vm values of the expressed Nitrilase enzyme were determined to be 0.68 mM and 0.48 mM/min respectively.

DERNA Enables Pareto Optimal RNA Design

The design of an RNA sequence v that encodes an input target protein sequence w is a crucial aspect of messenger RNA (mRNA) vaccine development. There are an exponential number of possible RNA sequences for a single target protein due to codon degeneracy. These potential RNA sequences can assume various secondary structure conformations, each with distinct minimum free energy (MFE), impacting thermodynamic stability and mRNA half-life. Furthermore, the presence of species-specific codon usage bias, quantified by the codon adaptation index (CAI), plays a vital role in translation efficiency. While earlier studies focused on optimizing either MFE or CAI, recent research has underscored the advantages of simultaneously optimizing both objectives. However, optimizing one objective comes at the expense of the other. In this work, we present the Pareto Optimal RNA Design problem, aiming to identify the set of Pareto optimal solutions for which no alternative solutions exist that exhibit better MFE and CAI values. Our algorithm DEsign RNA (DERNA) uses the weighted sum method to enumerate the Pareto front by optimizing convex combinations of both objectives. We use dynamic programming to solve each convex combination in O ( | w | 3 ) time and O ( | w | 2 ) space. Compared with a CDSfold, previous approach that only optimizes MFE, we show on a benchmark data set that DERNA obtains solutions with identical MFE but superior CAI. Moreover, we show that DERNA matches the performance in terms of solution quality of LinearDesign, a recent approach that similarly seeks to balance MFE and CAI. We conclude by demonstrating our method's potential for mRNA vaccine design for the SARS-CoV-2 spike protein.

Engineering Saccharomyces cerevisiae for efficient production of recombinant proteins

Saccharomyces cerevisiae is an excellent microbial cell factory for producing valuable recombinant proteins because of its fast growth rate, robustness, biosafety, ease of operability via mature genomic modification technologies, and the presence of a conserved post-translational modification pathway among eukaryotic organisms. However, meeting industrial and market requirements with the current low microbial production of recombinant proteins can be challenging. To address this issue, numerous efforts have been made to enhance the ability of yeast cell factories to efficiently produce proteins. In this review, we provide an overview of recent advances in S. cerevisiae engineering to improve recombinant protein production. This review focuses on the strategies that enhance protein production by regulating transcription through promoter engineering, codon optimization, and expression system optimization. Additionally, we describe modifications to the secretory pathway, including engineered protein translocation, protein folding, glycosylation modification, and vesicle trafficking. Furthermore, we discuss global metabolic pathway optimization and other relevant strategies, such as the disruption of protein degradation, cell wall engineering, and random mutagenesis. Finally, we provide an outlook on the developmental trends in this field, offering insights into future directions for improving recombinant protein production in S. cerevisiae.

Therapeutic synthetic and natural materials for immunoengineering

Immunoengineering is a rapidly evolving field that has been driving innovations in manipulating immune system for new treatment tools and methods. The need for materials for immunoengineering applications has gained significant attention in recent years due to the growing demand for effective therapies that can target and regulate the immune system. Biologics and biomaterials are emerging as promising tools for controlling immune responses, and a wide variety of materials, including proteins, polymers, nanoparticles, and hydrogels, are being developed for this purpose. In this review article, we explore the different types of materials used in immunoengineering applications, their properties and design principles, and highlight the latest therapeutic materials advancements. Recent works in adjuvants, vaccines, immune tolerance, immunotherapy, and tissue models for immunoengineering studies are discussed.

Advancing Cancer Immunotherapy: The Potential of mRNA Vaccines As a Promising Therapeutic Approach

mRNA vaccines have long been recognized for their ability to induce robust immune responses. The discovery that mRNA vaccines may also contribute to antitumor immunity has made them a promising therapeutic approach against cancer. Recent advances in understanding of immune system are precious in developing therapeutic strategies that target pathways involved in tumor survival and progression, leading to the most reliable therapeutic strategies in cancer treatment history. Among all traditional cancer treatments, cancer immunotherapies are less toxic and more effective, even in advanced or recurrent stages of cancer. Recent advancements in genomics and machine learning algorithms give new insight into vaccine development. mRNA vaccines are designed to interfere with stimulator of interferon genes (STING) and tumor‐infiltrating lymphocytes pathways, activating more CD8+ T‐cells involved in destroying tumor cells and inhibiting tumor growth. A stronger immune response can be achieved by incorporating immunological adjuvants alongside mRNA. Nonformulated or vehicle‐based mRNA vaccines, when combined with adjuvants, efficiently express tumor antigens through antigen‐presenting cells and stimulate both innate and adaptive immune responses. Codelivery with additional immunotherapeutic agents, such as checkpoint inhibitors, further enhances the efficacy of mRNA vaccines. This article focuses on the current clinical approaches and challenges to consider when developing mRNA‐based vaccine technology for cancer treatment.

Genetic transformation of the frog-killing chytrid fungus Batrachochytrium dendrobatidis

Batrachochytrium dendrobatidis (Bd), a causative agent of chytridiomycosis, is decimating amphibian populations around the world. Bd belongs to the chytrid lineage, a group of early-diverging fungi that are widely used to study fungal evolution. Like all chytrids, Bd develops from a motile form into a sessile, growth form, a transition that involves drastic changes in its cytoskeletal architecture. Efforts to study Bd cell biology, development, and pathogenicity have been limited by the lack of genetic tools with which to test hypotheses about underlying molecular mechanisms. Here, we report the development of a transient genetic transformation system for Bd. We used electroporation to deliver exogenous DNA into Bd cells and detected transgene expression for up to three generations under both heterologous and native promoters. We also adapted the transformation protocol for selection using an antibiotic resistance marker. Finally, we used this system to express fluorescent protein fusions and, as a proof of concept, expressed a genetically encoded probe for the actin cytoskeleton. Using live-cell imaging, we visualized the distribution and dynamics of polymerized actin at each stage of the Bd life cycle, as well as during key developmental transitions. This transformation system enables direct testing of key hypotheses regarding mechanisms of Bd pathogenesis. This technology also paves the way for answering fundamental questions of chytrid cell, developmental, and evolutionary biology.

A Basic Method for Formulating mRNA-Lipid Nanoparticle Vaccines in the Lab

During recent years, RNA therapeutics have begun to make a substantial impact in the clinic, with the approval of the siRNA-based therapeutic Patisiran in 2018, and of the two mRNA SARS-CoV-2 vaccines, BNT162b2 and mRNA-1273 in 2021. A key to the success of these therapeutics lies in the lipid-based delivery system. The therapeutic RNAs are encapsulated in lipid nanoparticles (LNPs), which protect against enzymatic degradation and efficiently deliver the RNA across the cell membrane into the cytosol. Thereby, the method used for LNP synthesis and its lipid composition are crucial aspects that decide the efficacy of the LNP-RNA hetero system. Here we provide a detailed guide for the simple preparation of LNP-encapsulated mRNA vaccines.

Whole-Body Disposition and Physiologically Based Pharmacokinetic Modeling of Adeno-Associated Viruses and the Transgene Product

To facilitate model-informed drug development (MIDD) of adeno-associated virus (AAV) therapy, here we have developed a physiologically based pharmacokinetic (PBPK) model for AAVs following preclinical investigation in mice. After 2E11 Vg/mouse dose of AAV8 and AAV9 encoding a monoclonal antibody (mAb) gene, whole-body disposition of both the vector and the transgene mAb was evaluated over 3 weeks. At steady-state, the following tissue-to-blood (T/B) concentration ratios were found for AAV8/9: ∼50 for liver; ∼10 for heart and muscle; ∼2 for brain, lung, kidney, adipose, and spleen; ≤1 for bone, skin, and pancreas. T/B values for mAb were compared with the antibody biodistribution coefficients, and five different clusters of organs were identified based on their transgene expression profile. All the biodistribution data were used to develop a novel AAV PBPK model that incorporates: (i) whole-body distribution of the vector; (ii) binding, internalization, and intracellular processing of the vector; (iii) transgene expression and secretion; and (iv) whole-body disposition of the secreted transgene product. The model was able to capture systemic and tissue PK of the vector and the transgene-produced mAb reasonably well. Pathway analysis of the PBPK model suggested that liver, muscle, and heart are the main contributors for the secreted transgene mAb. Unprecedented PK data and the novel PBPK model developed here provide the foundation for quantitative systems pharmacology (QSP) investigations of AAV-mediated gene therapies. The PBPK model can also serve as a quantitative tool for preclinical study design and preclinical-to-clinical translation of AAV-based gene therapies.

Statistical analysis of synonymous and stop codons in pseudo-random and real sequences as a function of GC content

Knowledge of the frequencies of synonymous triplets in protein-coding and non-coding DNA stretches can be used in gene finding. These frequencies depend on the GC content of the genome or parts of it. An example of interest is provided by stop codons. This is relevant for the definition of Open Reading Frames. A generic case is provided by pseudo-random sequences, especially when they code for complex proteins or when they are non-coding and not subject to selection pressure. Here, we calculate, for such sequences and for all 25 known genetic codes, the frequency of each amino acid and stop codon based on their set of codons and as a function of GC content. The amino acids can be classified into five groups according to the GC content where their expected frequency reaches its maximum. We determine the overall Shannon information based on groups of synonymous codons and show that it becomes maximum at a percent GC of 43.3% (for the standard code). This is in line with the observation that in most fungi, plants, and animals, this genomic parameter is in the range from 35 to 50%. By analysing natural sequences, we show that there is a clear bias for triplets corresponding to stop codons near the 5'- and 3'-splice sites in the introns of various clades.