A critical analysis of codon optimization in human therapeutics

NeuralCodOpt: Codon optimization for the development of DNA vaccines

Inefficient gene translation, driven by organisms' codon preferences, is an emerging research area since this results in sluggish processes and diminished protein yields. Our research culminates in deriving efficient, optimized codon sequences by considering organism-specific Relative Codon Adaptiveness (RCA) ranges. In this research work, we have developed a novel algorithm, Neural Codon Optimization (NeuralCodOpt), to automate the process of codon optimization tailored to a specific organism and input sequence. Our algorithm has two main parts: the target Codon Adaptation Index generation using K-Means and the automation of sequence optimization using reinforcement learning. This algorithm has been tested across a set of 130 species, yielding highly optimal results that are quite significant compared to the previous works. NeuralCodOpt has shown a high accuracy of 86.7%, which would substantially contribute to Deoxyribonucleic Acid (DNA) vaccines by improving the efficiency of DNA expression vectors. These vectors are crucial in DNA vaccination and gene therapy as they enhance protein expression levels. By further incorporating it into plasmid construction, the translational efficiency of DNA vaccines will be significantly improved.

Spike protein-related proteinopathies: A focus on the neurological side of spikeopathies

BACKGROUND

The spike protein (SP) is an outward-projecting transmembrane glycoprotein on viral surfaces. SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2), responsible for COVID-19 (Coronavirus Disease 2019), uses SP to infect cells that express angiotensin converting enzyme 2 (ACE2) on their membrane. Remarkably, SP has the ability to cross the blood-brain barrier (BBB) into the brain and cause cerebral damage through various pathomechanisms. To combat the COVID-19 pandemic, novel gene-based products have been used worldwide to induce human body cells to produce SP to stimulate the immune system. This artificial SP also has a harmful effect on the human nervous system.

STUDY DESIGN

Narrative review.

OBJECTIVE

This narrative review presents the crucial role of SP in neurological complaints after SARS-CoV-2 infection, but also of SP derived from novel gene-based anti-SARS-CoV-2 products (ASP).

METHODS

Literature searches using broad terms such as "SARS-CoV-2", "spike protein", "COVID-19", "COVID-19 pandemic", "vaccines", "COVID-19 vaccines", "post-vaccination syndrome", "post-COVID-19 vaccination syndrome" and "proteinopathy" were performed using PubMed. Google Scholar was used to search for topic-specific full-text keywords.

CONCLUSIONS

The toxic properties of SP presented in this review provide a good explanation for many of the neurological symptoms following SARS-CoV-2 infection and after injection of SP-producing ASP. Both SP entities (from infection and injection) interfere, among others, with ACE2 and act on different cells, tissues and organs. Both SPs are able to cross the BBB and can trigger acute and chronic neurological complaints. Such SP-associated pathologies (spikeopathies) are further neurological proteinopathies with thrombogenic, neurotoxic, neuroinflammatory and neurodegenerative potential for the human nervous system, particularly the central nervous system. The potential neurotoxicity of SP from ASP needs to be critically examined, as ASPs have been administered to millions of people worldwide.

Self-Amplifying RNA: Advantages and Challenges of a Versatile Platform for Vaccine Development

Self-amplifying RNA is synthetic nucleic acid engineered to replicate within cells without generating viral particles. Derived from alphavirus genomes, saRNA retains the non-structural elements essential for replication while replacing the structural elements with an antigen of interest. By enabling efficient intracellular amplification, saRNA offers a promising alternative to conventional mRNA vaccines, enhancing antigen expression while requiring lower doses. However, this advantage comes with challenges. In this review, we highlight the key limitations of saRNA technology and explore potential strategies to overcome them. By identifying these challenges, we aim to provide insights that can guide the future design of saRNA-based therapeutics, extending their potential beyond vaccine applications.

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.

Non-Viral RNA Therapies for Non-Small Cell Lung Cancer and Their Corresponding Clinical Trials

Ribonucleic acid (RNA)-based therapies represent a promising class of drugs for the treatment of non-small cell lung cancer (NSCLC) due to their ability to modulate gene expression. Therapies leveraging small interfering RNA (siRNA), messenger RNA (mRNA), microRNA (miRNA), and antisense oligonucleotides (ASOs) offer various advantages over conventional treatments, including the ability to target specific genetic mutations and the potential for personalized medicine approaches. However, the clinical translation of these therapeutics for the treatment of NSCLC faces challenges in delivery due to their immunogenicity, negative charge, and large size, which can be mitigated with delivery platforms. In this review, we provide a description of the pathophysiology of NSCLC and an overview of RNA-based therapeutics, specifically highlighting their potential application in the treatment of NSCLC. We discuss relevant classes of RNA and their therapeutic potential for NSCLC. We then discuss challenges in delivery and non-viral delivery strategies such as lipid- and polymer-based nanoparticles that have been developed to address these issues in preclinical models. Furthermore, we provide a summary table of clinical trials that leverage RNA therapies for NSCLC [which includes their National Clinical Trial (NCT) numbers] to highlight the current progress in NSCLC. We also discuss how these NSCLC therapies can be integrated with existing treatment modalities to enhance their efficacy and improve patient outcomes. Overall, we aim to highlight non-viral strategies that tackle RNA delivery challenges while showcasing RNA's potential as a next-generation therapy for NSCLC treatment.

CodonTransformer: a multispecies codon optimizer using context-aware neural networks

Degeneracy in the genetic code allows many possible DNA sequences to encode the same protein. Optimizing codon usage within a sequence to meet organism-specific preferences faces combinatorial explosion. Nevertheless, natural sequences optimized through evolution provide a rich source of data for machine learning algorithms to explore the underlying rules. Here, we introduce CodonTransformer, a multispecies deep learning model trained on over 1 million DNA-protein pairs from 164 organisms spanning all domains of life. The model demonstrates context-awareness thanks to its Transformers architecture and to our sequence representation strategy that combines organism, amino acid, and codon encodings. CodonTransformer generates host-specific DNA sequences with natural-like codon distribution profiles and with minimum negative cis-regulatory elements. This work introduces the strategy of Shared Token Representation and Encoding with Aligned Multi-masking (STREAM) and provides a codon optimization framework with a customizable open-access model and a user-friendly Google Colab interface.

The advent of clinical self-amplifying RNA vaccines

Self-amplifying RNA (saRNA) technology is an emerging platform for vaccine development, offering significant advantages over conventional mRNA vaccines. By enabling intracellular amplification of RNA, saRNA facilitates robust antigen expression at lower doses, thereby enhancing both immunogenicity and cost-effectiveness. This review examines the latest advancements in saRNA vaccine development, highlighting its applications in combating infectious diseases. This includes viral pathogens such as SARS-CoV-2, influenza, and emerging zoonotic threats. We discuss the design and optimization of saRNA vectors to maximize antigen expression while minimizing adverse immune responses. Recent studies demonstrating the safety, efficacy, and scalability of saRNA-based vaccines in clinical settings are also discussed. We address challenges related to delivery systems, stability, and manufacturing, along with novel strategies being developed to mitigate these challenges. As the global demand for rapid, flexible, and scalable vaccine platforms grows, saRNA presents a promising solution with enhanced potency and durability. This review emphasizes the transformative potential of saRNA vaccines to shape the future of immunization strategies, particularly in response to pandemics and other global health threats.

Association Analysis of ENPP1 Tissue Expression, Polymorphism, and Growth Traits in Xiangsu Pigs

Background: Pigs are vital agricultural animals, with growth traits serving as key indicators of their quality. Methods: In this study, we examined the mRNA expression of ENPP1 as a candidate gene in heart, liver, spleen, lungs, and kidneys at 3 days and 6 months of age by real-time polymerase chain reaction method and single-nucleotide polymorphism (SNP) loci in 165 Xiangsu pigs by Sanger sequencing. Results: The expression of ENPP1 in different tissues of Xiangsu pigs at different stages was significantly different, and it had high conservation in different species.. Sequence alignment with reference data identified five SNP sites: g.64275T→C and g.64429G→A in intron 19, g.64850T→C and g.64911G→A in intron 20, and g.64527T→C in exon 20. Association analysis revealed that g.64275T→C, g.64429G→A, and g.64527T→C significantly influence the growth performance of Xiangsu pigs (p < 0.05). Conclusions: These findings suggest that ENPP1 polymorphisms are closely associated with growth traits in Xiangsu pigs and may provide valuable insights for molecular breeding of this breed.

Research progress of mosquito-borne virus mRNA vaccines

In recent years, mRNA vaccines have emerged as a leading technology for preventing infectious diseases due to their rapid development and high immunogenicity. These vaccines encode viral antigens, which are translated into antigenic proteins within host cells, inducing both humoral and cellular immune responses. This review systematically examines the progress in mRNA vaccine research for major mosquito-borne viruses, including dengue virus, Zika virus, Japanese encephalitis virus, Chikungunya virus, yellow fever virus, Rift Valley fever virus, and Venezuelan equine encephalitis virus. Enhancements in mRNA vaccine design, such as improvements to the 5' cap structure, 5'UTR, open reading frame, 3'UTR, and polyadenylation tail, have significantly increased mRNA stability and translation efficiency. Additionally, the use of lipid nanoparticles and polymer nanoparticles has greatly improved the delivery efficiency of mRNA vaccines. Currently, mRNA vaccines against mosquito-borne viruses are under development and clinical trials, showing promising protective effects. Future research should continue to optimize vaccine design and delivery systems to achieve broad-spectrum and long-lasting protection against various mosquito-borne virus infections.

Influence of Nucleophosmin (NPM1) Genotypes on Outcome of Patients With AML: An AIEOP-BFM and COG-SWOG Intergroup Collaboration

PURPOSE

Several genomic subsets of NPM1 mutations with varying sequences (type A, B, D, etc) have been identified. Despite molecular heterogeneity, NPM1 mutations cumulatively portend a more favorable outcome, but biology and prognostic implications of different genomic subsets have not been extensively studied. In this multicentric study, we investigated the impact of NPM1 genotypes on patient's outcomes and interrogated the underlying biology of the different subtypes.

MATERIALS AND METHODS

Of more than 4,000 patients enrolled in multiple pediatric cooperative (AIEOP, BFM, ELAM02, NOPHO, DCOG, and COG trials), or adult (SWOG) trials, 348 pediatric and 75 adult AML patients with known NPM1 genotype and available outcome were selected for this study. Diverse NPM1 variants were correlated with the probabilities of overall survival (OS) and event-free survival. Nuclear localization and translational efficiency of the NPM1 variants was studied.

RESULTS

Evaluation of clinical outcome on the basis of NPM1 genotypes showed that patients with type A, B, and other rare variants had similarly favorable outcomes, whereas those with type D had a significantly worse outcome (OS of 63% for type D v 86% for type non-D, P = .005). Multivariate analysis confirmed type D as an independent prognostic factor associated with inferior OS (hazard ratio, 3; P = .005). In vitro, we demonstrated that in type D versus type A synonymous variants, codon optimality plays major roles in determining gene expression levels, and translation efficiency, which resulted in a more expressed NPM1-D mRNA and protein, mediating peculiar mitochondrial gene expression.

CONCLUSION

The evaluation of specific NPM1 genotypes identified AML patients with type D mutations being significantly associated with inferior outcomes, suggesting a reclassification of D cases to higher-risk groups.

Less is more: slow-codon windows enhance eGFP mRNA resilience against RNA interference

Extensive efforts have been devoted to enhancing the translation efficiency of mRNA delivered to mammalian cells via codon optimization. However, the impact of codon choice on mRNA stability remains underexplored. In this study, we investigated the influence of codon usage on mRNA degradation kinetics in cultured human cell lines using live-cell imaging on single-cell arrays. By measuring mRNA lifetimes at the single-cell level for synthetic mRNA constructs, we confirmed that mRNAs containing slowly translated codon windows have shorter lifetimes. Unexpectedly, these mRNAs did not exhibit decreased stability in the presence of small interfering RNA (siRNA) compared with the unmutated sequence, suggesting an interference of different concurrent degradation mechanisms. We employed stochastic simulations to predict ribosome density along the open reading frame, revealing that the ribosome densities correlated with mRNA stability in a cell-type- and codon-position-specific manner. In summary, our results suggest that the effect of codon choice and its influence on mRNA lifetime is context-dependent with respect to cell type, codon position and RNA interference.

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.

mRNA Vaccines: Design Principles, Mechanisms, and Manufacturing-Insights From COVID-19 as a Model for Combating Infectious Diseases

The full approval of two SARS-CoV-2 mRNA vaccines, Comirnaty and Spikevax, has greatly accelerated the development of numerous mRNA vaccine candidates targeting infectious diseases and cancer. mRNA vaccines provide a rapid, safe, and versatile manufacturing process while eliciting strong humoral and cellular immune responses, making them particularly beneficial for addressing emerging pandemics. Recent advancements in modified nucleotides and lipid nanoparticle delivery systems have further emphasized the potential of this vaccine platform. Despite these transformative opportunities, significant improvements are needed to enhance vaccine efficacy, stability, and immunogenicity. This review outlines the fundamentals of mRNA vaccine design, the manufacturing process, and administration strategies, along with various optimization approaches. It also offers a comprehensive overview of the mRNA vaccine candidates developed since the onset of the COVID-19 pandemic, the challenges posed by emerging SARS-CoV-2 variants, and current strategies to address these variants. Finally, we discuss the potential of broad-spectrum and combined mRNA vaccines and examine the challenges and future prospects of the mRNA vaccine platform.

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.

DNA vaccines as promising immuno-therapeutics against cancer: a new insight

Cancer is one of the leading causes of mortality around the world and most of our conventional treatments are not efficient enough to combat this deadly disease. Harnessing the power of the immune system to target cancer cells is one of the most appealing methods for cancer therapy. Nucleotide-based cancer vaccines, especially deoxyribonucleic acid (DNA) cancer vaccines are viable novel cancer treatments that have recently garnered significant attention. DNA cancer vaccines are made of plasmid molecules that encode tumor-associated or tumor-specific antigens (TAAs or TSAs), and possibly some other immunomodulatory adjuvants such as pro-inflammatory interleukins. Following the internalization of plasmids into cells, their genes are expressed and the tumor antigens are loaded on major histocompatibility molecules to be presented to T-cells. After the T-cells have been activated, they will look for tumor antigens and destroy the tumor cells upon encountering them. As with any other treatment, there are pros and cons associated with using these vaccines. They are relatively safe, usually well-tolerated, stable, easily mass-produced, cost-effective, and easily stored and transported. They can induce a systemic immune response effective on both the primary tumor and metastases. The main disadvantage of DNA vaccines is their poor immunogenicity. Several approaches including structural modification, combination therapy with conventional and novel cancer treatments (such as chemotherapy, radiotherapy, and immune checkpoint blockade (ICB)), and the incorporation of adjuvants into the plasmid structure have been studied to enhance the vaccine's immunogenicity and improve the clinical outcome of cancer patients. In this review, we will discuss some of the most promising optimization strategies and examine some of the important trials regarding these vaccines.

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.

Vector-Free Deep Tissue Targeting of DNA/RNA Therapeutics via Single Capacitive Discharge Conductivity-Clamped Gene Electrotransfer

Viral vector and lipid nanoparticle based gene delivery have limitations around spatiotemporal control, transgene packaging size, and vector immune reactivity, compromising translation of nucleic acid (NA) therapeutics. In the emerging field of DNA and particularly RNA-based gene therapies, vector-free delivery platforms are identified as a key unmet need. Here, this work addresses these challenges through gene electrotransfer (GET) of "naked" polyanionic DNA/mRNA using a single needle form-factor which supports "electro-lens" based compression of the local electric field, and local control of tissue conductivity, enabling single capacitive discharge minimal charge gene delivery. Proof-of-concept studies for "single capacitive discharge conductivity-clamped gene electrotransfer" (SCD-CC-GET) deep tissue delivery of naked DNA and mRNA in the mouse hindlimb skeletal muscle achieve stable (>18 month) expression of luciferase reporter synthetic DNA, and mRNA encoding the reporter yield rapid onset (<3 h) high transient expression for several weeks. Delivery of DNAs encoding secreted alkaline phosphatase and Cal/09 influenza virus hemagglutinin antigen generate high systemic circulating recombinant protein levels and antibody titres. The findings support adoption of SCD-CC-GET for vaccines and immunotherapies, and extend the utility of this technology to meet the demand for efficient vector-free, precision, deep tissue delivery of NA therapeutics.

Expression and purification of recombinant tilapia lake virus segment 4 protein and its in-vitro biological activity for potential use in vaccine development

Tilapia lake virus (TiLV) disease is highly contagious and causes substantial mortality in tilapia. Currently, no effective treatments or commercial vaccines are available to prevent TiLV infection. In this study, TiLV segment 4 (S4) was cloned into the pET28a(+)vector and transformed into Escherichia coli BL21(DE3). Codon optimization was performed to enhance TiLV S4 protein expression, and a range of expression conditions were tested, including various inducers and postinduction temperatures and times for both soluble and insoluble protein expression. The recombinant TiLV S4 protein was purified using affinity chromatography. The optimal conditions for recombinant TiLV S4 expression were achieved via induction using 0.1 mM galactose at 37 °C for 1 h postinduction. The insoluble protein was denatured using 6 M urea and subsequently purified to yield a protein concentration of approximately 250 mg/L. Dot blot immunodetection assays confirmed consistent interactions between the purified TiLV S4 protein and the sera from infected fish and rabbit anti-TiLV antibodies. By identifying the optimal growth conditions and production factors for the recombinant protein, our study offers valuable information for the large-scale production of the TiLV S4 protein, which signals an important step forward in TiLV vaccine development.

mRNA cancer vaccines from bench to bedside: a new era in cancer immunotherapy

Harnessing the power of the immune system to target cancer cells is one of the most appealing approaches for cancer therapy. Among these immunotherapies, messenger ribonucleic acid (mRNA) cancer vaccines are worthy of consideration, as they have demonstrated promising results in clinical trials. These vaccines have proven to be safe and well-tolerated. They can be easily mass-produced in a relatively short time and induce a systemic immune response effective against both the primary tumor and metastases. Transcripts encoding immunomodulatory molecules can also be incorporated into the mRNA, enhancing its efficacy. On the other hand, there are some challenges associated with their application, including mRNA instability, insufficient uptake by immune cells, and intrinsic immunogenicity, which can block mRNA translation. Many innovations have been suggested to overcome these obstacles, including structural modification (such as 5' cap modification), optimizing delivery vehicles (especially dendritic cells (DCs) and nanoparticles), and using antigens that can enhance immunogenicity by circumventing tolerance mechanisms. A popular approach is to combine mRNA cancer vaccines with traditional and novel cancer treatments like chemotherapy, radiotherapy, and immune checkpoint blockade (ICB). They are most efficacious when combined with other therapies like ICBs. There is still a long way to go before these vaccines enter the standard of care for cancer patients, but with the incredible pace of development in this field, their clinical application will soon be witnessed. This review highlights the recent advances and challenges of mRNA cancer vaccines. Finally, some of the most prominent clinical applications of these vaccines will be reviewed.

A comparative guide to expression systems for phage lysin production

Phage lysins, bacteriophage-encoded enzymes tasked with degrading their host's cell wall, are increasingly investigated and engineered as novel antibacterials across diverse applications. Their rapid action, tuneable specificity, and low likelihood of resistance development make them particularly interesting. Despite numerous application-focused lysin studies, the art of their recombinant production remains relatively undiscussed. Here, we provide an overview of the available expression systems for phage lysin production and discuss key considerations guiding the choice of a suitable recombinant host. We systematically surveyed recent literature to evaluate the hosts used in the lysin field and cover various recombinant systems, including the well-known bacterial host Escherichia coli or yeast Saccharomyces cerevisiae, as well as plant, mammalian, and cell-free systems. Careful analysis of the limited studies expressing lysins in various hosts suggests a host-dependent effect on activity. Nonetheless, the multitude of available expression systems should be further leveraged to accommodate the growing interest in phage lysins and their expanding range of applications.

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.

Codon optimality modulates cellular stress and innate immune responses triggered by exogenous RNAs

The COVID-19 mRNA vaccines demonstrated the power of mRNA medicines. Despite advancements in sequence design, evidence regarding the preferential use of synonymous codons on cellular stress and innate immune responses is lacking. To this end, we developed a proprietary codon optimality matrix to re-engineer the coding sequences of three luciferase reporters. We demonstrate that optimal mRNAs elicited dramatic increases in luciferase activities compared to non-optimal sequences. Notably, transfecting an optimal RNA affects the translation of other RNAs in the cell including control transcripts in dual luciferase assays. This held true in multiple cell lines and for an unrelated reporter. Further, non-optimal mRNAs preferentially activated innate immune pathways and the phosphorylation of the translation initiation factor eIF2α, a central event of the integrated stress response. Using nucleoside-modified or circular RNAs partially or fully abrogated these responses. Finally, we show that circularizing RNAs enhances both RNA lifespan and durability of protein expression. Our results show that RNA sequence, composition, and structure all govern RNA translatability. However, we also show that RNA sequences with poor codon optimality are immunogenic and induce cellular stress. Hence, RNA sequence engineering, chemical, and topological modifications must all be combined to elicit favorable therapeutic outcomes.

Advances of computational methods enhance the development of multi-epitope vaccines

Vaccine development is one of the most promising fields, and multi-epitope vaccine, which does not need laborious culture processes, is an attractive alternative to classical vaccines with the advantage of safety, and efficiency. The rapid development of algorithms and the accumulation of immune data have facilitated the advancement of computer-aided vaccine design. Here we systemically reviewed the in silico data and algorithms resource, for different steps of computational vaccine design, including immunogen selection, epitope prediction, vaccine construction, optimization, and evaluation. The performance of different available tools on epitope prediction and immunogenicity evaluation was tested and compared on benchmark datasets. Finally, we discuss the future research direction for the construction of a multiepitope vaccine.

The current status and development forecasts of vaccines for aquaculture and its effects on bacterial and viral diseases

The aquaculture sector predicts protein-rich meals by 2040 and has experienced significant economic shifts since 2000. However, challenges emanating from disease control measures, brood stock improvement, feed advancements, hatchery technology, and water quality management due to environmental fluctuations have been taken as major causative agents for hindering the sector's growth. For the past years, aquatic disease prevention and control have principally depended on the use of various antibiotics, ecologically integrated control, other immunoprophylaxis mechanisms, and chemical drugs, but the long-term use of chemicals such as antibiotics not only escalates antibiotic-resistant bacteria and genes but also harms the fish and the environments, resulting in drug residues in aquatic products, severely obstructing the growth of the aquaculture sector. The field of science has opened new avenues in basic and applied research for creating and producing innovative and effective vaccines and the enhancement of current vaccines to protect against numerous infectious diseases. Recent advances in vaccines and vaccinology could lead to novel vaccine candidates that can tackle fish diseases, including parasitic organism agents, for which the current vaccinations are inadequate. In this review, we study and evaluate the growing aquaculture production by focusing on the current knowledge, recent progress, and prospects related to vaccinations and immunizations in the aquaculture industry and their effects on treating bacterial and viral diseases. The subject matter covers a variety of vaccines, such as conventional inactivated and attenuated vaccines as well as advanced vaccines, and examines their importance in real-world aquaculture scenarios. To encourage enhanced importation of vaccines for aquaculture sustainability and profitability and also help in dealing with challenges emanating from diseases, national and international scientific and policy initiatives need to be informed about the fundamental understanding of vaccines.

Current landscape of cystic fibrosis gene therapy

Cystic fibrosis is a life-threatening disease that is caused by mutations in CFTR, a gene which encodes an ion channel that supports proper function of several epithelial tissues, most critically the lung. Without CFTR, airway barrier mechanisms are impaired, allowing for chronic, recurrent infections that result in airway remodeling and deterioration of lung structure and function. Small molecule modulators can rescue existing, defective CFTR protein; however, they still leave a subset of people with CF with no current disease modifying treatments, aside from lung transplantation. Gene therapy directed to the lung is a promising strategy to modify CF disease in the organ most associated with morbidity and mortality. It is accomplished through delivery of a CFTR transgene with an airway permissive vector. Despite more than three decades of research in this area, a lung directed gene therapy has yet to be realized. There is hope that with improved delivery vectors, sufficient transduction of airway cells can achieve therapeutic levels of functional CFTR. In order to do this, preclinical programs need to meet a certain level of CFTR protein expression in vitro and in vivo through improved transduction, particularly in relevant airway cell types. Furthermore, clinical programs must be designed with sensitive methods to detect CFTR expression and function as well as methods to measure meaningful endpoints for lung structure, function and disease. Here, we discuss the current understanding of how much and where CFTR needs to be expressed, the most advanced vectors for CFTR delivery and clinical considerations for detecting CFTR protein and function in different patient subsets.

Personalized mRNA vaccines in glioblastoma therapy: from rational design to clinical trials

Glioblastomas (GBMs) are the most common and aggressive malignant brain tumors, presenting significant challenges for treatment due to their invasive nature and localization in critical brain regions. Standard treatment includes surgical resection followed by radiation and adjuvant chemotherapy with temozolomide (TMZ). Recent advances in immunotherapy, including the use of mRNA vaccines, offer promising alternatives. This review focuses on the emerging use of mRNA vaccines for GBM treatment. We summarize recent advancements, evaluate current obstacles, and discuss notable successes in this field. Our analysis highlights that while mRNA vaccines have shown potential, their use in GBM treatment is still experimental. Ongoing research and clinical trials are essential to fully understand their therapeutic potential. Future developments in mRNA vaccine technology and insights into GBM-specific immune responses may lead to more targeted and effective treatments. Despite the promise, further research is crucial to validate and optimize the effectiveness of mRNA vaccines in combating GBM.

Construction and in vitro characterisation of virus-vectored immunocontraceptive candidates derived from felid alphaherpesvirus 1

There is a pressing need for effective feral cat management globally due to overabundant feline populations, disease transmission and their destructive impact on biodiversity. Virus-vectored immunocontraception (VVIC) is an attractive method for cat population management. Virus-vectored immunocontraceptives could be self-disseminating through horizontal transmission of the VVIC in feral cat populations, or they may be modified to act as non-transmissible vaccine-type immunocontraceptives for delivery to individual cats. These later constructs may be particularly attractive for use in owned (pet) cats and stray cats but could also be used for feral cats that are caught, vaccinated, and released. Here, we report the construction of three felid alphaherpesvirus 1 (FHV-1) derived immunocontraceptive candidates containing genes that encode for feline zona pellucida subunit 3 (ZP3) and gonadotropin-releasing hormone (GnRH). Two of the vaccine candidates were engineered to include disruptions to the thymidine kinase viral virulence gene to reduce the ability of the vaccines to be horizontally transmitted. Analysis of in vitro growth characteristics and protein expression are reported, and their potential for use as a population management tool for cats is discussed.

Unleashing the potential of mRNA therapeutics for inherited neurological diseases

Neurological monogenic loss-of-function diseases are hereditary disorders resulting from gene mutations that decrease or abolish the normal function of the encoded protein. These conditions pose significant therapeutic challenges, which may be resolved through the development of innovative therapeutic strategies. RNA-based technologies, such as mRNA replacement therapy, have emerged as promising and increasingly viable treatments. Notably, mRNA therapy exhibits significant potential as a mutation-agnostic approach that can address virtually any monogenic loss-of-function disease. Therapeutic mRNA carries the information for a healthy copy of the defective protein, bypassing the problem of targeting specific genetic variants. Moreover, unlike conventional gene therapy, mRNA-based drugs are delivered through a simplified process that requires only transfer to the cytoplasm, thereby reducing the mutagenic risks related to DNA integration. Additionally, mRNA therapy exerts a transient effect on target cells, minimizing the risk of long-term unintended consequences. The remarkable success of mRNA technology for developing coronavirus disease 2019 vaccines has rekindled interest in mRNA as a cost-effective method for delivering therapeutic proteins. However, further optimization is required to enhance mRNA delivery, particularly to the CNS, while minimizing adverse drug reactions and toxicity. In this comprehensive review, we delve into past, present and ongoing applications of mRNA therapy for neurological monogenic loss-of-function diseases. We also discuss the promises and potential challenges presented by mRNA therapeutics in this rapidly advancing field. Ultimately, we underscore the full potential of mRNA therapy as a game-changing therapeutic approach for neurological disorders.

CodonBERT large language model for mRNA vaccines

mRNA-based vaccines and therapeutics are gaining popularity and usage across a wide range of conditions. One of the critical issues when designing such mRNAs is sequence optimization. Even small proteins or peptides can be encoded by an enormously large number of mRNAs. The actual mRNA sequence can have a large impact on several properties, including expression, stability, immunogenicity, and more. To enable the selection of an optimal sequence, we developed CodonBERT, a large language model (LLM) for mRNAs. Unlike prior models, CodonBERT uses codons as inputs, which enables it to learn better representations. CodonBERT was trained using more than 10 million mRNA sequences from a diverse set of organisms. The resulting model captures important biological concepts. CodonBERT can also be extended to perform prediction tasks for various mRNA properties. CodonBERT outperforms previous mRNA prediction methods, including on a new flu vaccine data set.

An important consideration when expressing mAbs in Escherichiacoli

Monoclonal antibodies (mAbs) are a driving force in the biopharmaceutical industry. Therapeutic mAbs are usually produced in mammalian cells, but there has been a push towards the use of alternative production hosts, such as Escherichia coli. When the genes encoding for a mAb heavy and light chains are codon-optimized for E. coli expression, a truncated form of the heavy chain can form along with the full-length product. In this work, the role of codon optimization in the formation of a truncated product was investigated. This study used the amino acid sequences of several therapeutic mAbs and multiple optimization algorithms. It was found that several algorithms incorporate sequences that lead to a truncated product. Approaches to avoid this truncated form are discussed.

Dominant B cell-T cell epitopes instigated robust immune response in-silico against Scrub Typhus

Scrub typhus, a potentially life-threatening infectious disease, is attributed to bacteria Orientia tsutsugamushi (O. tsutsugamushi). The transmission of this illness to humans occurs through the bite of infected chiggers, which are the larval forms of mites belonging to the genus Leptotrombidium. In this research, we developed a subunit vaccine specifically designed to target outer membrane proteins. Immunodominant cytotoxic T-lymphocytes (CTLs), B- lymphocytes (BCLs), and major histocompatibility complex (MHC)- II epitopes were identified using machine learning and bioinformatics approaches. These epitopes were arranged in different combinations with the help of suitable linkers like AAY, KK, GPGPG and adjuvant (cholera toxin B) that resulted in a vaccine construct. Physiochemical properties were assessed, where the predicted solubility (0.571) was higher than threshold value. Tertiary structure was predicted using I-TASSER web server and evaluated using Ramachandran plot (94 % residues in most favourable region) and z-score (-6.04), which had shown the structure to have good stability and residue arrangement. Molecular docking with immune receptors, Toll-like receptor (TLR)-2 and -4 showed good residue interaction with 13 and 5 hydrogen bonds respectively. Molecular dynamics simulations of receptor-ligand complex provided the idea about the strong interaction having 1.524751 × 10-5 eigenvalue. Amino acid sequence of vaccine was converted to nucleotide sequence and underwent codon optimization. The optimized codon sequence was used for in-silico cloning, which provided idea about the possibility of synthesis of vaccine using E. coli as host. Overall, this study provided a promising blueprint for a scrub typhus vaccine, although experimental validation is needed for confirmation. Furthermore, it is crucial to acknowledge that while bioinformatics provides valuable insights, in-vitro and in-vivo studies are imperative for a comprehensive evaluation of vaccine candidate. Thus, the integration of computational predictions with empirical research is essential to validate the efficacy, safety, and real-world applicability of the designed vaccine against Scrub Typhus. Nevertheless, the findings are good to carry forward for in-vitro and in-vivo investigations.

Vaccine design and development: Exploring the interface with computational biology and AI

Computational biology involves applying computer science and informatics techniques in biology to understand complex biological data. It allows us to collect, connect, and analyze biological data at a large scale and build predictive models. In the twenty first century, computational resources along with Artificial Intelligence (AI) have been widely used in various fields of biological sciences such as biochemistry, structural biology, immunology, microbiology, and genomics to handle massive data for decision-making, including in applications such as drug design and vaccine development, one of the major areas of focus for human and animal welfare. The knowledge of available computational resources and AI-enabled tools in vaccine design and development can improve our ability to conduct cutting-edge research. Therefore, this review article aims to summarize important computational resources and AI-based tools. Further, the article discusses the various applications and limitations of AI tools in vaccine development.

Emerging mRNA Technology for Liver Disease Therapy

Liver diseases have consistently posed substantial challenges to global health. It is crucial to find innovative methods to effectively prevent and treat these diseases. In recent times, there has been an increasing interest in the use of mRNA formulations that accumulate in liver tissue for the treatment of hepatic diseases. In this review, we start by providing a detailed introduction to the mRNA technology. Afterward, we highlight types of liver diseases, discussing their causes, risks, and common therapeutic strategies. Additionally, we summarize the latest advancements in mRNA technology for the treatment of liver diseases. This includes systems based on hepatocyte growth factor, hepatitis B virus antibody, left-right determination factor 1, human hepatocyte nuclear factor α, interleukin-12, methylmalonyl-coenzyme A mutase, etc. Lastly, we provide an outlook on the potential of mRNA technology for the treatment of liver diseases, while also highlighting the various technical challenges that need to be addressed. Despite these difficulties, mRNA-based therapeutic strategies may change traditional treatment methods, bringing hope to patients with liver diseases.

A comprehensive comparison of DNA and RNA vaccines

Nucleic acid technology has revolutionized vaccine development, enabling rapid design and production of RNA and DNA vaccines for prevention and treatment of diseases. The successful deployment of mRNA and plasmid DNA vaccines against COVID-19 has further validated the technology. At present, mRNA platform is prevailing due to its higher efficacy, while DNA platform is undergoing rapid evolution because it possesses unique advantages that can potentially overcome the problems associated with the mRNA platform. To help understand the recent performances of the two vaccine platforms and recognize their clinical potentials in the future, this review compares the advantages and drawbacks of mRNA and DNA vaccines that are currently known in the literature, in terms of development timeline, financial cost, ease of distribution, efficacy, safety, and regulatory approval of products. Additionally, the review discusses the ongoing clinical trials, strategies for improvement, and alternative designs of RNA and DNA platforms for vaccination.

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.

Non-viral delivery of RNA for therapeutic T cell engineering

Adoptive T cell transfer has shown great success in treating blood cancers, resulting in a growing number of FDA-approved therapies using chimeric antigen receptor (CAR)-engineered T cells. However, the effectiveness of this treatment for solid tumors is still not satisfactory, emphasizing the need for improved T cell engineering strategies and combination approaches. Currently, CAR T cells are mainly manufactured using gammaretroviral and lentiviral vectors due to their high transduction efficiency. However, there are concerns about their safety, the high cost of producing them in compliance with current Good Manufacturing Practices (cGMP), regulatory obstacles, and limited cargo capacity, which limit the broader use of engineered T cell therapies. To overcome these limitations, researchers have explored non-viral approaches, such as membrane permeabilization and carrier-mediated methods, as more versatile and sustainable alternatives for next-generation T cell engineering. Non-viral delivery methods can be designed to transport a wide range of molecules, including RNA, which allows for more controlled and safe modulation of T cell phenotype and function. In this review, we provide an overview of non-viral RNA delivery in adoptive T cell therapy. We first define the different types of RNA therapeutics, highlighting recent advancements in manufacturing for their therapeutic use. We then discuss the challenges associated with achieving effective RNA delivery in T cells. Next, we provide an overview of current and emerging technologies for delivering RNA into T cells. Finally, we discuss ongoing preclinical and clinical studies involving RNA-modified T cells.

Engineered mRNA Delivery Systems for Biomedical Applications

Messenger RNA (mRNA)-based therapeutic strategies have shown remarkable promise in preventing and treating a staggering range of diseases. Optimizing the structure and delivery system of engineered mRNA has greatly improved its stability, immunogenicity, and protein expression levels, which has led to a wider range of uses for mRNA therapeutics. Herein, a thorough analysis of the optimization strategies used in the structure of mRNA is first provided and delivery systems are described in great detail. Furthermore, the latest advancements in biomedical engineering for mRNA technology, including its applications in combatting infectious diseases, treating cancer, providing protein replacement therapy, conducting gene editing, and more, are summarized. Lastly, a perspective on forthcoming challenges and prospects concerning the advancement of mRNA therapeutics is offered. Despite these challenges, mRNA-based therapeutics remain promising, with the potential to revolutionize disease treatment and contribute to significant advancements in the biomedical field.

Synthetic biology approach revealed enhancement in haeme oxygenase-1 gene expression by codon pair optimization while reduction by codon deoptimization

Haem oxygenase-1 (HO-1) is a ubiquitously expressed gene involved in cellular homoeostasis, and its imbalance in expression results in various disorders. To alleviate such disorders, HO-1 gene expression needs to be modulated. Codon usage bias results from evolutionary forces acting on any nucleotide sequence and determines the gene expression. Like codon usage bias, codon pair bias also exists, playing a role in gene expression. In the present study, HO-1 gene was recoded by manipulating codon and codon pair bias, and four such constructs were made through codon/codon pair deoptimization and codon/codon pair optimization to reduce and enhance the HO-1 gene expression. Codon usage analysis was done for these constructs for four tissues brain, heart, pancreas and liver. Based on codon usage in different tissues, gene expression of these tissues was determined in terms of the codon adaptation index. Based on the codon adaptation index, minimum free energy, and translation efficiency, constructs were evaluated for enhanced or decreased HO-1 expression. The analysis revealed that for enhancing gene expression, codon pair optimization, while for reducing gene expression, codon deoptimization is efficacious. The recoded constructs developed in the study could be used in gene therapy regimens to cure HO-1 over or underexpression-associated disorders.

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.

Influence of Fluorescence Lifetime Selections and Conformational Flexibility on Brightness of FusionRed Variants

Fluorescent proteins (FPs) for bioimaging are typically developed by screening mutant libraries for clones with improved photophysical properties. This approach has resulted in FPs with high brightness, but the mechanistic origins of the improvements are often unclear. We focused on improving the molecular brightness in the FusionRed family of FPs with fluorescence lifetime selections on targeted libraries, with the aim of reducing nonradiative decay rates. Our new variants show fluorescence quantum yields of up to 75% and lifetimes >3.5 ns. We present a comprehensive analysis of these new FPs, including trends in spectral shifts, photophysical data, photostability, and cellular brightness resulting from codon optimization. We also performed all-atom molecular dynamics simulations to investigate the impact of side chain mutations. The trajectories reveal that individual mutations reduce the flexibility of the chromophore and side chains, leading to an overall reduction in nonradiative rates.

Therapeutic potential of combating cancer by restoring wild-type p53 through mRNA nanodelivery

Among the tumor suppressor genes, TP53 is the most frequently mutated in human cancers, and most mutations are missense mutations causing production of mutant p53 (mutp53) proteins. TP53 mutations not only results in loss of function (LOH) as a transcription factor and a tumor suppressor, but also gain wild-type p53 (WTp53)-independent oncogenic functions that enhance cancer metastasis and progression (Yamamoto and Iwakuma, 2018; Zhang et al., 2022). TP53 has extensively been studied as a therapeutic target as well as for drug development and therapies, however with limited success. Achieving targeted therapies for restoration of WTp53 function and depletion or repair of mutant p53 (mutp53) will have far reaching implication in cancer treatment and therapies. This review briefly discusses the role of p53 mutation in cancer and the therapeutic potential of restoring WTp53 through the advances in mRNA nanomedicine.

Synonymous codon usage regulates translation initiation

Nonoptimal synonymous codons repress gene expression, but the underlying mechanisms are poorly understood. We and others have previously shown that nonoptimal codons slow translation elongation speeds and thereby trigger messenger RNA (mRNA) degradation. Nevertheless, transcript levels are often insufficient to explain protein levels, suggesting additional mechanisms by which codon usage regulates gene expression. Using reporters in human and Drosophila cells, we find that transcript levels account for less than half of the variation in protein abundance due to codon usage. This discrepancy is explained by translational differences whereby nonoptimal codons repress translation initiation. Nonoptimal transcripts are also less bound by the translation initiation factors eIF4E and eIF4G1, providing a mechanistic explanation for their reduced initiation rates. Importantly, translational repression can occur without mRNA decay and deadenylation, and it does not depend on the known nonoptimality sensor, CNOT3. Our results reveal a potent mechanism of regulation by codon usage where nonoptimal codons repress further rounds of translation.

SARS-CoV-2 Vaccination and the Multi-Hit Hypothesis of Oncogenesis

Cancer is a complex and dynamic disease. The "hallmarks of cancer" were proposed by Hanahan and Weinberg (2000) as a group of biological competencies that human cells attain as they progress from normalcy to neoplastic transformation. These competencies include self-sufficiency in proliferative signaling, insensitivity to growth-suppressive signals and immune surveillance, the ability to evade cell death, enabling replicative immortality, reprogramming energy metabolism, inducing angiogenesis, and activating tissue invasion and metastasis. Underlying these competencies are genome instability, which expedites their acquisition, and inflammation, which fosters their function(s). Additionally, cancer exhibits another dimension of complexity: a heterogeneous repertoire of infiltrating and resident host cells, secreted factors, and extracellular matrix, known as the tumor microenvironment, that through a dynamic and reciprocal relationship with cancer cells supports immortality, local invasion, and metastatic dissemination. This staggering intricacy calls for caution when advising all people with cancer (or a previous history of cancer) to receive the COVID-19 primary vaccine series plus additional booster doses. Moreover, because these patients were not included in the pivotal clinical trials, considerable uncertainty remains regarding vaccine efficacy, safety, and the risk of interactions with anticancer therapies, which could reduce the value and innocuity of either medical treatment. After reviewing the available literature, we are particularly concerned that certain COVID-19 vaccines may generate a pro-tumorigenic milieu (i.e., a specific environment that could lead to neoplastic transformation) that predisposes some (stable) oncologic patients and survivors to cancer progression, recurrence, and/or metastasis. This hypothesis is based on biological plausibility and fulfillment of the multi-hit hypothesis of oncogenesis (i.e., induction of lymphopenia and inflammation, downregulation of angiotensin-converting enzyme 2 (ACE2) expression, activation of oncogenic cascades, sequestration of tumor suppressor proteins, dysregulation of the RNA-G quadruplex-protein binding system, alteration of type I interferon responses, unsilencing of retrotransposable elements, etc.) together with growing evidence and safety reports filed to Vaccine Adverse Effects Report System (VAERS) suggesting that some cancer patients experienced disease exacerbation or recurrence following COVID-19 vaccination. In light of the above and because some of these concerns (i.e., alteration of oncogenic pathways, promotion of inflammatory cascades, and dysregulation of the renin-angiotensin system) also apply to cancer patients infected with SARS-CoV-2, we encourage the scientific and medical community to urgently evaluate the impact of both COVID-19 and COVID-19 vaccination on cancer biology and tumor registries, adjusting public health recommendations accordingly.

Prevention of Portal-Tract Fibrosis in Zfyve19-/- Mouse Model with Adeno-Associated Virus Vector Delivering ZFYVE19

Zinc finger FYVE-type containing 19 (ZFYVE19) deficiency, caused by biallelic ZFYVE19 complete loss-of-function variants, is a recently identified chronic hepatobiliary disorder characterized by obvious portal-tract fibrosis, increased numbers of bile ducts with malformations, and abnormal levels of serum markers of hepatobiliary injury. As liver-targeted adeno-associated virus (AAV) gene therapy has been used successfully in hepatobiliary diseases, liver-targeted gene therapy has been explored in a mouse model of this disorder. Three ZFYVE19 AAV vectors (AAV-hZFYVE19, AAV-hZFYVE19-m, and AAV-hZFYVE19-co) were constructed and injected into Zfyve19-/- mice, which were treated with alpha-naphthyl isothiocyanate, a hepatobiliary toxin. Hematoxylin/eosin, immunohistochemical staining, immunofluorescence staining, Sirius Red staining, real-time quantitative PCR, and Western blotting of liver tissue, along with serum hepatobiliary injury marker analyses, were performed to evaluate the effects of gene therapy. AAV-hZFYVE19 decreased serum hepatobiliary injury markers, portal-tract inflammation, ductal hyperplasia, and portal-tract fibrosis in the Zfyve19-/- model mice most substantially at a relatively low dose (1 × 1011 vg/kg), whereas AAV-hZFYVE19 at a higher dose gradually lost the abovementioned benefits and even caused deterioration at the highest dose of 5 × 1012 vg/kg. These observations verified the pathogenicity of ZFYVE19 deficiency and suggested that the ZFYVE19 gene needs to function well at an optimal level of expression; both too low and too high a ZFYVE19 expression may be harmful.

Combination of hydrophobicity and codon usage bias determines sorting of model K+ channel protein to either mitochondria or endoplasmic reticulum

When the K+ channel-like protein Kesv from Ectocarpus siliculosus virus 1 is heterologously expressed in mammalian cells, it is sorted to the mitochondria. This targeting can be redirected to the endoplasmic reticulum (ER) by altering the codon usage in distinct regions of the gene or by inserting a triplet of hydrophobic amino acids (AAs) into the protein's C-terminal transmembrane domain (ct-TMD). Systematic variations in the flavor of the inserted AAs and/or its codon usage show that a positive charge in the inserted AA triplet alone serves as strong signal for mitochondria sorting. In cases of neutral AA triplets, mitochondria sorting are favored by a combination of hydrophilic AAs and rarely used codons; sorting to the ER exhibits the inverse dependency. This propensity for ER sorting is particularly high when a common codon follows a rarer one in the AA triplet; mitochondria sorting in contrast is supported by codon uniformity. Since parameters like positive charge, hydrophobic AAs, and common codons are known to facilitate elongation of nascent proteins in the ribosome the data suggest a mechanism in which local changes in elongation velocity and co-translational folding in the ct-TMD influence intracellular protein sorting.

Targeting the Cancer-Neuronal Crosstalk in the Pancreatic Cancer Microenvironment

Pancreatic ductal adenocarcinoma (PDAC) represents one of the most aggressive solid tumors with a dismal prognosis and an increasing incidence. At the time of diagnosis, more than 85% of patients are in an unresectable stage. For these patients, chemotherapy can prolong survival by only a few months. Unfortunately, in recent decades, no groundbreaking therapies have emerged for PDAC, thus raising the question of how to identify novel therapeutic druggable targets to improve prognosis. Recently, the tumor microenvironment and especially its neural component has gained increasing interest in the pancreatic cancer field. A histological hallmark of PDAC is perineural invasion (PNI), whereby cancer cells invade surrounding nerves, providing an alternative route for metastatic spread. The extent of PNI has been positively correlated with early tumor recurrence and reduced overall survival. Multiple studies have shown that mechanisms involved in PNI are also involved in tumor spread and pain generation. Targeting these pathways has shown promising results in alleviating pain and reducing PNI in preclinical models. In this review, we will describe the mechanisms and future treatment strategies to target this mutually trophic interaction between cancer cells to open novel avenues for the treatment of patients diagnosed with PDAC.

Genes for highly abundant proteins in Escherichia coli avoid 5' codons that promote ribosomal initiation

In many species highly expressed genes (HEGs) over-employ the synonymous codons that match the more abundant iso-acceptor tRNAs. Bacterial transgene codon randomization experiments report, however, that enrichment with such "translationally optimal" codons has little to no effect on the resultant protein level. By contrast, consistent with the view that ribosomal initiation is rate limiting, synonymous codon usage following the 5' ATG greatly influences protein levels, at least in part by modifying RNA stability. For the design of bacterial transgenes, for simple codon based in silico inference of protein levels and for understanding selection on synonymous mutations, it would be valuable to computationally determine initiation optimality (IO) scores for codons for any given species. One attractive approach is to characterize the 5' codon enrichment of HEGs compared with the most lowly expressed genes, just as translational optimality scores of codons have been similarly defined employing the full gene body. Here we determine the viability of this approach employing a unique opportunity: for Escherichia coli there is both the most extensive protein abundance data for native genes and a unique large-scale transgene codon randomization experiment enabling objective definition of the 5' codons that cause, rather than just correlate with, high protein abundance (that we equate with initiation optimality, broadly defined). Surprisingly, the 5' ends of native genes that specify highly abundant proteins avoid such initiation optimal codons. We find that this is probably owing to conflicting selection pressures particular to native HEGs, including selection favouring low initiation rates, this potentially enabling high efficiency of ribosomal usage and low noise. While the classical HEG enrichment approach does not work, rendering simple prediction of native protein abundance from 5' codon content futile, we report evidence that initiation optimality scores derived from the transgene experiment may hold relevance for in silico transgene design for a broad spectrum of bacteria.

AAV-based in vivo gene therapy for neurological disorders

Recent advancements in gene supplementation therapy are expanding the options for the treatment of neurological disorders. Among the available delivery vehicles, adeno-associated virus (AAV) is often the favoured vector. However, the results have been variable, with some trials dramatically altering the course of disease whereas others have shown negligible efficacy or even unforeseen toxicity. Unlike traditional drug development with small molecules, therapeutic profiles of AAV gene therapies are dependent on both the AAV capsid and the therapeutic transgene. In this rapidly evolving field, numerous clinical trials of gene supplementation for neurological disorders are ongoing. Knowledge is growing about factors that impact the translation of preclinical studies to humans, including the administration route, timing of treatment, immune responses and limitations of available model systems. The field is also developing potential solutions to mitigate adverse effects, including AAV capsid engineering and designs to regulate transgene expression. At the same time, preclinical research is addressing new frontiers of gene supplementation for neurological disorders, with a focus on mitochondrial and neurodevelopmental disorders. In this Review, we describe the current state of AAV-mediated neurological gene supplementation therapy, including critical factors for optimizing the safety and efficacy of treatments, as well as unmet needs in this field.

Improved tropoelastin synthesis in the skin by codon optimization and nucleotide modification of tropoelastin-encoding synthetic mRNA

Loss of elastin due to aging, disease, or injury can lead to impaired tissue function. In this study, de novo tropoelastin (TE) synthesis is investigated in vitro and in vivo using different TE-encoding synthetic mRNA variants after codon optimization and nucleotide modification. Codon optimization shows a strong effect on protein synthesis without affecting cell viability in vitro, whereas nucleotide modifications strongly modulate translation and reduce cell toxicity. Selected TE mRNA variants (3, 10, and 30 μg) are then analyzed in vivo in porcine skin after intradermal application. Administration of 30 μg of native TE mRNA with a me1 Ψ modification or 10 and 30 μg of unmodified codon-optimized TE mRNA is required to increase TE protein expression in vivo. In contrast, just 3 μg of a codon-optimized TE mRNA variant with the me1 Ψ modification is able to increase protein expression. Furthermore, skin toxicity is investigated in vitro by injecting 30 μg of mRNA of selected TE mRNA variants into a human full-thickness skin model, and no toxic effects are observed. Thereby, for the first time, an increased dermal TE synthesis by exogenous administration of synthetic mRNA is demonstrated in vivo. Codon optimization of a synthetic mRNA can significantly increase protein expression and therapeutic outcome.