Codon optimization with deep learning to enhance protein expression

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.

Codon optimized influenza H1 HA sequence but not CTLA-4 targeting of HA antigen to enhance the efficacy of DNA vaccines in an animal model

Infections caused by the influenza virus lead to both epidemic and pandemic outbreaks in humans and animals. Owing to their rapid production, safety, and stability, DNA vaccines represent a promising avenue for eliciting immunity and thwarting viral infections. While DNA vaccines have demonstrated substantial efficacy in murine models, their effectiveness in larger animals remains subdued. This limitation may be addressed by augmenting the immunogenicity of DNA-based vaccines. In the investigation here, protein expression was enhanced via codon optimization and then mouse cytotoxic T-lymphocyte antigen 4 (CTLA-4) was harnessed as a modulatory adjunct to bind directly to antigen-presenting cells. Further, the study evaluated the immunogenicity of two variants of the hemagglutinin (HA) antigen, i.e. the full-length and the C-terminal deletion versions. The study findings revealed that the codon-optimized HA gene (pcHA) led to increased protein synthesis, as evidenced by elevated mRNA levels. Codon optimization also significantly bolstered both cellular and humoral immune responses. In cytokine assays, all plasmid constructs, particularly pCTLA4-cHA, induced robust interferon (IFN)-γ production, while interleukin (IL)-4 levels remained uniformly non-significant. Mice immunized with pcHA displayed an augmented presence of IFNγ+ T-cells, underscoring the enhanced potency of the codon-optimized HA vaccine. Contrarily, CTLA-4-fused DNA vaccines did not significantly amplify the immune response.

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.

Design of multivalent-epitope vaccine models directed toward the world's population against HIV-Gag polyprotein: Reverse vaccinology and immunoinformatics

Significant progress has been made in HIV-1 research; however, researchers have not yet achieved the objective of eradicating HIV-1 infection. Accordingly, in this study, eucaryotic and procaryotic in silico vaccines were developed for HIV-Gag polyproteins from 100 major HIV subtypes and CRFs using immunoinformatic techniques to simulate immune responses in mice and humans. The epitopes located in the conserved domains of the Gag polyprotein were evaluated for allergenicity, antigenicity, immunogenicity, toxicity, homology, topology, and IFN-γ induction. Adjuvants, linkers, CTLs, HTLs, and BCL epitopes were incorporated into the vaccine models. Strong binding affinities were detected between HLA/MHC alleles, TLR-2, TLR-3, TLR-4, TLR-7, and TLR-9, and vaccine models. Immunological simulation showed that innate and adaptive immune cells elicited active and consistent responses. The human vaccine model was matched with approximately 93.91% of the human population. The strong binding of the vaccine to MHC/HLA and TLR molecules was confirmed through molecular dynamic stimulation. Codon optimization ensured the successful translation of the designed constructs into human cells and E. coli hosts. We believe that the HIV-1 Gag vaccine formulated in our research can reduce the challenges faced in developing an HIV-1 vaccine. Nevertheless, experimental verification is necessary to confirm the effectiveness of these vaccines in these models.

AntigenBoost: enhanced mRNA-based antigen expression through rational amino acid substitution

Messenger RNA (mRNA) vaccines represent a groundbreaking advancement in immunology and public health, particularly highlighted by their role in combating the COVID-19 pandemic. Optimizing mRNA-based antigen expression is a crucial focus in this emerging industry. We have developed a bioinformatics tool named AntigenBoost to address the challenge posed by destabilizing dipeptides that hinder ribosomal translation. AntigenBoost identifies these dipeptides within specific antigens and provides a range of potential amino acid substitution strategies using a two-dimensional scoring system. Through a combination of bioinformatics analysis and experimental validation, we significantly enhanced the in vitro expression of mRNA-derived Respiratory Syncytial Virus fusion glycoprotein and Influenza A Hemagglutinin antigen. Notably, a single amino acid substitution improved the immune response in mice, underscoring the effectiveness of AntigenBoost in mRNA vaccine design.

Production of recombinant human insulin from a promising Pseudomonas fluorescens cell factory and its kinetic modeling

Insulin intake is recommended for diabetics in addition to a proper diet and lifestyle to maintain adequate blood glucose level. Currently, there is a need for an alternative expression system for insulin production as the current expression systems may not meet the growing demand due to various constraints. Here, we demonstrate the synthesis of human insulin in an unconventional expression system based on Pseudomonas fluorescens, a BSL 1 bacterium. Human insulin was produced in the form of proinsulin fused with fusion protein. Then, the proinsulin fusion protein was purified using Ni-NTA chromatography and converted into human insulin. The physicochemical parameters for producing proinsulin fusion protein are optimized. Glucose and ammonium chloride are determined to be suitable carbon and nitrogen sources, respectively. The validity of insulin and proinsulin fusion protein is assessed using western blot and quantified using ELISA techniques. Up to 145.35 mg/l of the proinsulin fusion protein is achieved at the shake flask level. Further, MALDI-TOF and RP-HPLC analysis of the purified human insulin were observed to be close to the theoretical value and insulin standard, respectively. The expression of the recombinant fusion protein was found to be 214.7 mg/l in a batch bioreactor, a ∼48% enhancement over the shake flask level. Further, kinetic modeling was performed to understand the system regarding growth, substrate utilization and product formation, and to estimate the various kinetic parameters. This study establishes the potential of the P. fluorescens expression system for producing human insulin.

High-level expression of codon-optimized Taq DNA polymerase under the control of rhaBAD promoter

A DNA polymerase from Thermus aquaticus remains the most popular among DNA polymerases. It was widely applied in various fields involving the application of polymerase chain reaction (PCR), implying the high commercial value of this enzyme. For this reason, an attempt to obtain a high yield of Taq DNA polymerase is continuously conducted. In this study, the l-rhamnose-inducible promoter rhaBAD was utilized due to its ability to produce recombinant protein under tight control in E. coli expression system. Instead of full-length Taq polymerase, an N-terminal deletion of Taq polymerase was selected. To obtain a high-level expression, we attempted to optimize the codon by reducing the rare codon and GC content, and in a second attempt, we optimized the culture conditions for protein expression. The production of Taq polymerase using the optimum culture condition improved the level of expression by up to 3-fold. This approach further proved that a high level of recombinant protein expression could be achieved by yielding a purified Taq polymerase of about 8.5 mg/L of culture. This is the first research publication on the production of Taq polymerase with N-terminal deletion in E. coli with the control of the rhaBAD promoter system.

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.

Reverse vaccinology approaches to design a potent multiepitope vaccine against the HIV whole genome: immunoinformatic, bioinformatics, and molecular dynamics approaches

Substantial advances have been made in the development of promising HIV vaccines to eliminate HIV-1 infection. For the first time, one hundred of the most submitted HIV subtypes and CRFs were retrieved from the LANL database, and the consensus sequences of the eleven HIV proteins were obtained to design vaccines for human and mouse hosts. By using various servers and filters, highly qualified B-cell epitopes, as well as HTL and CD8 + epitopes that were common between mouse and human alleles and were also located in the conserved domains of HIV proteins, were considered in the vaccine constructs. With 90% coverage worldwide, the human vaccine model covers a diverse allelic population, making it widely available. Codon optimization and in silico cloning in prokaryotic and eukaryotic vectors guarantee high expression of the vaccine models in human and E. coli hosts. Molecular dynamics confirmed the stable interaction of the vaccine constructs with TLR3, TLR4, and TLR9, leading to a substantial immunogenic response to the designed vaccine. Vaccine models effectively target the humoral and cellular immune systems in humans and mice; however, experimental validation is needed to confirm these findings in silico.

Strategic approaches for designing yeast strains as protein secretion and display platforms

Yeast has been established as a versatile platform for expressing functional molecules, owing to its well-characterized biology and extensive genetic modification tools. Compared to prokaryotic systems, yeast possesses advanced cellular mechanisms that ensure accurate protein folding and post-translational modifications. These capabilities are particularly advantageous for the expression of human-derived functional proteins. However, designing yeast strains as an expression platform for proteins requires the integration of molecular and cellular functions. By delving into the complexities of yeast-based expression systems, this review aims to empower researchers with the knowledge to fully exploit yeast as a functional platform to produce a diverse range of proteins. This review includes an exploration of the host strains, gene cassette structures, as well as considerations for maximizing the efficiency of the expression system. Through this in-depth analysis, the review anticipates stimulating further innovation in the field of yeast biotechnology and protein engineering.

Designing multi-epitope vaccine against human cytomegalovirus integrating pan-genome and reverse vaccinology pipelines

Human cytomegalovirus (HCMV) is accountable for high morbidity in neonates and immunosuppressed individuals. Due to the high genetic variability of HCMV, current prophylactic measures are insufficient. In this study, we employed a pan-genome and reverse vaccinology approach to screen the target for efficient vaccine candidates. Four proteins, envelope glycoprotein M, UL41A, US23, and US28, were shortlisted based on cellular localization, high solubility, antigenicity, and immunogenicity. A total of 29 B-cell and 44 T-cell highly immunogenic and antigenic epitopes with high global population coverage were finalized using immunoinformatics tools and algorithms. Further, the epitopes that were overlapping among the finalized B-cell and T-cell epitopes were linked with suitable linkers to form various combinations of multi-epitopic vaccine constructs. Among 16 vaccine constructs, Vc12 was selected based on physicochemical and structural properties. The docking and molecular simulations of VC12 were performed, which showed its high binding affinity (-23.35 kcal/mol) towards TLR4 due to intermolecular hydrogen bonds, salt bridges, and hydrophobic interactions, and there were only minimal fluctuations. Furthermore, Vc12 eliciting a good response was checked for its expression in Escherichia coli through in silico cloning and codon optimization, suggesting it to be a potent vaccine candidate.

Multi-epitope peptide vaccines targeting dengue virus serotype 2 created via immunoinformatic analysis

The Middle East has witnessed a greater spread of infectious Dengue viruses, with serotype 2 (DENV-2) being the most prevalent form. Through this work, multi-epitope peptide vaccines against DENV-2 that target E and nonstructural (NS1) proteins were generated through an immunoinformatic approach. MHC class I and II and LBL epitopes among NS1 and envelope E proteins sequences were predicted and their antigenicity, toxicity, and allergenicity were investigated. Studies of the population coverage denoted the high prevalence of NS1 and envelope-E epitopes among different countries where DENV-2 endemic. Further, both the CTL and HTL epitopes retrieved from NS1 epitopes exhibited high conservancies' percentages with other DENV serotypes (1, 3, and 4). Three vaccine constructs were created and the expected immune responses for the constructs were estimated using C-IMMSIM and HADDOCK (against TLR 2,3,4,5, and 7). Molecular dynamics simulation for vaccine construct 2 with TLR4 denoted high binding affinity and stability of the construct with the receptor which might foretell favorable in vivo interaction and immune responses.

A Novel Quality Control Strategy for the Preparation of High-Quality Recombinant Allergens in Escherichia coli: A Case Study of Der f 2

INTRODUCTION

Recombinant allergens produced by Escherichia coli (E. coli) system play an important role in the component-resolved diagnostics of allergy and vaccine development. However, incorrect folding of recombinant allergens may affect their application. Therefore, it is very important to monitor the correct folding of recombinant allergens. Currently, there is still a lack of a quality control strategy to solve this problem. In this study, a mite allergen, Der f 2, was taken as an example to establish a novel quality control strategy, which was based on chromatography to isolate the allergen, and on enzyme-linked immunosorbent assay to verify the IgE reactivity of the isolated allergen.

METHODS

The nucleotide sequence encoding Der f 2 was codon-optimized and cloned into pET-28a (+) plasmid. Best conditions for the expression of Der f 2 in E. coli were sought. The inclusion body of Der f 2 was denatured and purified by nickel affinity chromatography. Refolding processes were compared using glutathione redox system. The fully and partially folded proteins were separated by anion exchange chromatography, and the IgE reactivity of the isolated proteins was verified by indirect enzyme-linked immunosorbent assay.

RESULTS

An optimized 387 bp segment of the Der f 2 coding gene was successfully expressed in E. coli. Best induction conditions included preinduction bacterial density with absorbance value at 600 nm was 0.6, 1 mM isopropyl beta-d-thiogalactopyranoside at 28°C for 4 h. The Der f 2 protein after refolding was separated by chromatography and two fractions were obtained. The first fraction was identified as monomer protein and the second as aggregate by size-exclusion chromatography. Indirect enzyme-linked immunosorbent assay also confirmed that the first fraction showed higher IgE reactivity.

CONCLUSION

In this study, a novel quality control strategy based on chromatographic separation and IgE reactivity monitoring was established in the case of mite Der f 2, which systematically evaluated the effectiveness of multiple preparation methods for the first time. It is faster and more convenient when compared with the existing methods such as size-exclusion chromatography. This strategy laid a foundation for the stable application of recombinant allergens produced by E. coli in component-resolved diagnostics and the development of molecular vaccines in the future.

Production of Reverse Transcriptase and DNA Polymerase in Bacterial Expression Systems

DNA amplification and reverse transcription enzymes have proven to be invaluable in fast and reliable diagnostics and research applications because of their processivity, specificity, and robustness. Our study focused on the production of mutant Taq DNA polymerase and mutant M-MLV reverse transcriptase in the expression hosts Vibrio natriegens and Escherichia coli under various expression conditions. We also examined nonspecific extracellular production in V. natriegens. Intracellularly, M-MLV was produced in V. natriegens at the level of 11% of the total cell proteins (TCPs) compared with 16% of TCPs in E. coli. We obtained a soluble protein that accounted for 11% of the enzyme produced in V. natriegens and 22% of the enzyme produced in E. coli. Taq pol was produced intracellularly in V. natriegens at the level of 30% of TCPs compared with 26% of TCPs in E. coli. However, Taq pol was almost non-soluble in E. coli, whereas in V. natriegens, we obtained a soluble protein that accounted for 23% of the produced enzyme. We detected substantial extracellular production of Taq pol. Thus, V. natriegens is a suitable alternative host with the potential for production of recombinant proteins.

Integrating pan-genome and reverse vaccinology to design multi-epitope vaccine against Herpes simplex virus type-1

Herpes simplex virus type-1 (HSV-1), the etiological agent of sporadic encephalitis and recurring oral (sometimes genital) infections in humans, affects millions each year. The evolving viral genome reduces susceptibility to existing antivirals and, thus, necessitates new therapeutic strategies. Immunoinformatics strategies have shown promise in designing novel vaccine candidates in the absence of a clinically licensed vaccine to prevent HSV-1. However, to encourage clinical translation, the HSV-1 pan-genome was integrated with the reverse-vaccinology pipeline for rigorous screening of universal vaccine candidates. Viral targets were screened from 104 available complete genomes. Among 364 proteins, envelope glycoprotein D being an outer membrane protein with a high antigenicity score (> 0.4) and solubility (> 0.6) was selected for epitope screening. A total of 17 T-cell and 4 B-cell epitopes with highly antigenic, immunogenic, non-toxic properties and high global population coverage were identified. Furthermore, 8 vaccine constructs were designed using different combinations of epitopes and suitable linkers. VC-8 was identified as the most potential vaccine candidate regarding chemical and structural stability. Molecular docking revealed high interactive affinity (low binding energy: - 56.25 kcal/mol) of VC-8 with the target elicited by firm intermolecular H-bonds, salt-bridges, and hydrophobic interactions, which was validated with simulations. Compatibility of the vaccine candidate to be expressed in pET-29(a) + plasmid was established by in silico cloning studies. Immune simulations confirmed the potential of VC-8 to trigger robust B-cell, T-cell, cytokine, and antibody-mediated responses, thereby suggesting a promising candidate for the future of HSV-1 prevention.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-024-04022-6.

CodonBERT: a BERT-based architecture tailored for codon optimization using the cross-attention mechanism

MOTIVATION

Due to the varying delivery methods of mRNA vaccines, codon optimization plays a critical role in vaccine design to improve the stability and expression of proteins in specific tissues. Considering the many-to-one relationship between synonymous codons and amino acids, the number of mRNA sequences encoding the same amino acid sequence could be enormous. Finding stable and highly expressed mRNA sequences from the vast sequence space using in silico methods can generally be viewed as a path-search problem or a machine translation problem. However, current deep learning-based methods inspired by machine translation may have some limitations, such as recurrent neural networks, which have a weak ability to capture the long-term dependencies of codon preferences.

RESULTS

We develop a BERT-based architecture that uses the cross-attention mechanism for codon optimization. In CodonBERT, the codon sequence is randomly masked with each codon serving as a key and a value. In the meantime, the amino acid sequence is used as the query. CodonBERT was trained on high-expression transcripts from Human Protein Atlas mixed with different proportions of high codon adaptation index codon sequences. The result showed that CodonBERT can effectively capture the long-term dependencies between codons and amino acids, suggesting that it can be used as a customized training framework for specific optimization targets.

AVAILABILITY AND IMPLEMENTATION

CodonBERT is freely available on https://github.com/FPPGroup/CodonBERT.

Efficient overexpression and purification of severe acute respiratory syndrome coronavirus 2 nucleocapsid proteins in Escherichia coli

The fundamental biology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleocapsid protein (Ncap), its use in diagnostic assays and its potential application as a vaccine component have received considerable attention since the outbreak of the Covid19 pandemic in late 2019. Here we report the scalable expression and purification of soluble, immunologically active, SARS-CoV-2 Ncap in Escherichia coli. Codon-optimised synthetic genes encoding the original Ncap sequence and four common variants with an N-terminal 6His affinity tag (sequence MHHHHHHG) were cloned into an inducible expression vector carrying a regulated bacteriophage T5 synthetic promoter controlled by lac operator binding sites. The constructs were used to express Ncap proteins and protocols developed which allow efficient production of purified Ncap with yields of over 200 mg per litre of culture media. These proteins were deployed in ELISA assays to allow comparison of their responses to human sera. Our results suggest that there was no detectable difference between the 6His-tagged and untagged original Ncap proteins but there may be a slight loss of sensitivity of sera to other Ncap isolates.

In vitro synthesis and biochemical characterization of acyl-homoserine lactone synthase and its deletion mutant

Quorum sensing can induce density-dependent gene expressions that cause various problems. For quorum-sensing inhibition, fundamental solutions such as gene manipulation are required, and acyl-homoserine lactone synthase (AHL synthase), which synthesizes the universal quorum-sensing signal of gram-negative bacteria, can be used as a target. In this study, researchers synthesized His-tagged AHL synthase and its deletion mutant that lacks the active site and compared their biochemical characteristics. His-YpeI, the 6x His-tagged AHL synthase of Serratia fonticola, and His-ΔYpeI, its deletion mutant, were designed, and their property conservation were examined using in silico projection tools. For in vitro synthesis of enzymes, the His-YpeI CFPS template was synthesized by in vitro gene synthesis, and the His-ΔYpeI CFPS template was obtained by deletion PCR. CFPS was performed and the products were purified with the 6x His-tag. The enzymes' properties were compared using an enzymatic assay. The bioinformatic analysis confirmed the conservation of biochemical properties between 6x His-tagged and untagged enzymes, including helix-turn-helix interactions, hydropathy profiles, and tertiary structure between His-YpeI and YpeI and between His-ΔYpeI and ΔYpeI. His-YpeI and His-ΔYpeI synthesized by CFPS were found to have the expected molecular weights and demonstrated distinct differences in enzyme activity. The analyzed enzymatic constants supported a significant decrease in substrate affinity and reaction rate as a result of YpeI's enzyme active site deletion. This result showed that CFPS could be used for in vitro protein synthesis, and quorum sensing could be inhibited at the enzymatic level due to the enzyme active site's deletion mutation.

Immune targeting of filarial glutaredoxin through a multi-epitope peptide-based vaccine: A reverse vaccinology approach

Despite the efforts of global programme to eliminate lymphatic filariasis (GPELF), the threat of lymphatic filariasis (LF) still looms over humanity in terms of long-term disabilities, and morbidities across the globe. In light of this situation, investigators have chosen to focus on the development of immunotherapeutics targeting the physiologically important filarial-specific proteins. Glutaredoxin (16.43 kDa) plays a pivotal role in filarial redox biology, serving as a vital contributor. In the context of the intra-host survival of filarial parasites, this antioxidant helps in mitigating the oxidative stress imposed by the host immune system. Given its significant contribution, the development of a vaccine targeting glutaredoxin holds promise as a new avenue for achieving a filaria-free world. Herein, multi-epitope-based vaccine was designed using advanced immunoinformatics approach. Initially, 4B-cell epitopes and 6 T-cell epitopes (4 MHC I and 2 MHC II) were identified from the 146 amino acid long sequence of glutaredoxin of the human filarid, Wuchereria bancrofti. Subsequent clustering of these epitopes with linker peptides finalized the vaccine structure. To boost TLR-mediated innate immunity, TLR-specific adjuvants were incorporated into the designed vaccine. After that, experimental analyses confirm the designed vaccine, Vac4 as anefficient ligand of human TLR5 to elicit protective innate immunity against filarial glutaredoxin. Immune simulation further demonstrated abundant levels of IgG and IgM as crucial contributors in triggering vaccine-induced adaptive responses in the recipients. Hence, to facilitate the validation of immunogenicity of the designed vaccine, Vac4 was cloned in silico in pET28a(+) expression vector for recombinant production. Taken together, our findings suggest that vaccine-mediated targeting of filarial glutaredoxin could be a future option for intervening LF on a global scale.

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

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

Investigation of CaMV-host co-evolution through synonymous codon pattern

Cauliflower mosaic virus (CaMV) has a double-stranded DNA genome and is globally distributed. The phylogeny tree of 121 CaMV isolates was categorized into two primary groups, with Iranian isolates showing the greatest genetic variations. Nucleotide A demonstrated the highest percentage (36.95%) in the CaMV genome and the dinucleotide odds ratio analysis revealed that TC dinucleotide (1.34 ≥ 1.23) and CG dinucleotide (0.63 ≤ 0.78) are overrepresented and underrepresented, respectively. Relative synonymous codon usage (RSCU) analysis confirmed codon usage bias in CaMV and its hosts. Brassica oleracea and Brassica rapa, among the susceptible hosts of CaMV, showed a codon adaptation index (CAI) value above 0.8. Additionally, relative codon deoptimization index (RCDI) results exhibited the highest degree of deoptimization in Raphanus sativus. These findings suggest that the genes of CaMV underwent codon adaptation with its hosts. Among the CaMV open reading frames (ORFs), genes that produce reverse transcriptase and virus coat proteins showed the highest CAI value of 0.83. These genes are crucial for the creation of new virion particles. The results confirm that CaMV co-evolved with its host to ensure the optimal expression of its genes in the hosts, allowing for easy infection and effective spread. To detect the force behind codon usage bias, an effective number of codons (ENC)-plot and neutrality plot were conducted. The results indicated that natural selection is the primary factor influencing CaMV codon usage bias.

Design of a multi-epitope-based vaccine candidate against Bovine Genital Campylobacteriosis using a reverse vaccinology approach

BACKGROUND

Bovine Genital Campylobacteriosis (BGC), a worldwide distributed venereal disease caused by Campylobacter fetus subsp. venerealis (Cfv), has a relevant negative economic impact in cattle herds. The control of BGC is hampered by the inexistence of globally available effective vaccines. The present in silico study aimed to develop a multi-epitope vaccine candidate against Cfv through reverse vaccinology.

RESULTS

The analysis of Cfv strain NCTC 10354 proteome allowed the identification of 9 proteins suitable for vaccine development. From these, an outer membrane protein, OmpA, and a flagellar protein, FliK, were selected for prediction of B-cell and T-cell epitopes. The top-ranked epitopes conservancy was assessed in 31 Cfv strains. The selected epitopes were integrated to form a multi-epitope fragment of 241 amino acids, which included 2 epitopes from OmpA and 13 epitopes from FliK linked by GPGPG linkers and connected to the cholera toxin subunit B by an EAAAK linker. The vaccine candidate was predicted to be antigenic, non-toxic, non-allergenic, and soluble upon overexpression. The protein structure was predicted and optimized, and the sequence was successfully cloned in silico into a plasmid vector. Additionally, immunological simulations demonstrated the vaccine candidate's ability to stimulate an immune response.

CONCLUSIONS

This study developed a novel vaccine candidate suitable for further in vitro and in vivo experimental validation, which may become a useful tool for the control of BGC.

Codon-optimization in gene therapy: promises, prospects and challenges

Codon optimization has evolved to enhance protein expression efficiency by exploiting the genetic code's redundancy, allowing for multiple codon options for a single amino acid. Initially observed in E. coli, optimal codon usage correlates with high gene expression, which has propelled applications expanding from basic research to biopharmaceuticals and vaccine development. The method is especially valuable for adjusting immune responses in gene therapies and has the potenial to create tissue-specific therapies. However, challenges persist, such as the risk of unintended effects on protein function and the complexity of evaluating optimization effectiveness. Despite these issues, codon optimization is crucial in advancing gene therapeutics. This study provides a comprehensive review of the current metrics for codon-optimization, and its practical usage in research and clinical applications, in the context of gene therapy.

Molecular insights into codon usage analysis of mitochondrial fission and fusion gene: relevance to neurodegenerative diseases

Mitochondrial dysfunction is the leading cause of neurodegenerative disorders like Alzheimer's disease and Parkinson's disease. Mitochondria is a highly dynamic organelle continuously undergoing the process of fission and fusion for even distribution of components and maintaining proper shape, number, and bioenergetic functionality. A set of genes governs the process of fission and fusion. OPA1, Mfn1, and Mfn2 govern fusion, while Drp1, Fis1, MIEF1, and MIEF2 genes control fission. Determination of specific molecular patterns of transcripts of these genes revealed the impact of compositional constraints on selecting optimal codons. AGA and CCA codons were over-represented, and CCC, GTC, TTC, GGG, ACG were under-represented in the fusion gene set. In contrast, CTG was over-represented, and GCG, CCG, and TCG were under-represented in the fission gene set. Hydropathicity analysis revealed non-polar protein products of both fission and fusion gene set transcripts. AGA codon repeats are an integral part of translational regulation machinery and present a distinct pattern of over-representation and under-representation in different transcripts within the gene sets, suggestive of selective translational force precisely controlling the occurrence of the codon. Out of six synonymous codons, five synonymous codons encoding for leucine were used differently in both gene sets. Hence, forces regulating the occurrence of AGA and five synonymous leucine-encoding codons suggest translational selection. A correlation of mutational bias with gene expression and codon bias and GRAVY and AROMA signifies the selection pressure in both gene sets, while the correlation of compositional bias with gene expression, codon bias, protein properties, and minimum free energy signifies the presence of compositional constraints. More than 25% of codons of both gene sets showed a significant difference in codon usage. The overall analysis shed light on molecular features of gene sets involved in fission and fusion.

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.

DNA-Based Nonviral Gene Therapy─Challenging but Promising

Over the past decades, significant progress has been made in utilizing nucleic acids, including DNA and RNA molecules, for therapeutic purposes. For DNA molecules, although various DNA delivery systems have been established, viral vector systems are the go-to choice for large-scale commercial applications. However, viral systems have certain disadvantages such as immune response, limited payload capacity, insertional mutagenesis and pre-existing immunity. In contrast, nonviral systems are less immunogenic, not size limited, safer, and easier for manufacturing compared with viral systems. What's more, nonviral DNA vectors have demonstrated their capacity to mediate specific protein expression in vivo for diverse therapeutic objectives containing a wide range of diseases such as cancer, rare diseases, neurodegenerative diseases, and infectious diseases, yielding promising therapeutic outcomes. However, exogenous plasmid DNA is prone to degrade and has poor immunogenicity in vivo. Thus, various strategies have been developed: (i) designing novel plasmids with special structures, (ii) optimizing plasmid sequences for higher expression, and (iii) developing more efficient nonviral DNA delivery systems. Based on these strategies, many interesting clinical results have been reported. This Review discusses the development of DNA-based nonviral gene therapy, including novel plasmids, nonviral delivery systems, clinical advances, and prospects. These developments hold great potential for enhancing the efficacy and safety of nonviral gene therapy and expanding its applications in the treatment of various diseases.

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.

Introduction to RNA Vaccines Post COVID-19

Available prophylactic vaccines help prevent many infectious diseases that burden humanity. Future vaccinology will likely extend these benefits by more effectively countering newly emerging pathogens, fighting currently intractable infections, or even generating novel treatment modalities for non-infectious diseases. Instead of applying protein antigen directly, RNA vaccines contain short-lived genetic information that guides the expression of protein antigen in the vaccinee, like infection with a recombinant viral vector. Upon decades of research, messenger RNA-lipid nanoparticle (mRNA-LNP) vaccines have proven clinical value in addressing the COVID-19 pandemic as they combine benefits of killed subunit vaccines and live-attenuated vectors, including flexible production, self-adjuvanting effects, and stimulation of humoral and cellular immunity. RNA vaccines remain subject to continued development raising high hopes for broader future application. Their mechanistic versatility promises to make them a key tool of vaccinology and immunotherapy going forward. Here, I briefly review key developments in RNA vaccines and outline the contents of this volume of Methods in Molecular Biology.

Use of Drosophila Transgenics to Identify Functions for Symbiont Effectors

Wolbachia, one of the most successful and studied insect symbionts, and Drosophila, one of the most understood model insects, can be exploited as complementary tools to unravel mechanisms of insect symbiosis. Although Wolbachia itself cannot be grown axenically as clonal isolates or genetically manipulated by standard methods, its reproductive phenotypes, including cytoplasmic incompatibility (CI), have been elucidated using well-developed molecular tools and precise transgenic manipulations available for Drosophila melanogaster. Current research only scratches the surface of how Drosophila can provide a tool for understanding Wolbachia's evolutionary success and the molecular roles of its genetic elements. Here, we briefly outline basic methodologies inherent to transgenic Drosophila systems that have already contributed significant advances in understanding CI, but may be unfamiliar to those who lack experience in Drosophila genetics. In the future, these approaches will continue providing significant insights into Wolbachia that undoubtedly will be extended to other insect symbionts and their biological capabilities.

New insights of flavonoid glycosidases and their application in food industry

Flavonoids are significant natural nutraceuticals and a key component of dietary supplements. Given that flavonoid glycosides are more plentiful in nature and less beneficial to human health than their aglycone counterparts, they serve as potential precursors for flavonoid production. Glycosidases have shown substantial potential within the food industry, particularly in enhancing the organoleptic properties of juice, wine, and tea. When applied to food resources, glycosidases can amplify their biological activities, thereby improving the performance of functional foods. This review provides up-to-date information on flavonoid glycosidases, including their catalytic mechanisms, biochemical properties, and natural sources, as well as their applications within the food industry. The use of flavonoid glycosidases in improving food quality is also reviewed.

Recent advances in biosynthesis of mycotoxin-degrading enzymes and their applications in food and feed

Mycotoxins are secondary metabolites produced by fungi in food and feed, which can cause serious health problems. Bioenzymatic degradation is gaining increasing popularity due to its high specificity, gentle degradation conditions, and environmental friendliness. We reviewed recently reported biosynthetic mycotoxin-degrading enzymes, traditional and novel expression systems, enzyme optimization strategies, food and feed applications, safety evaluation of both degrading enzymes and degradation products, and commercialization potentials. Special emphasis is given to the novel expression systems, advanced optimization strategies, and safety considerations for industrial use. Over ten types of recombinases such as oxidoreductase and hydrolase have been studied in the enzymatic hydrolysis of mycotoxins. Besides traditional expression system of Escherichia coli and yeasts, these enzymes can also be expressed in novel systems such as Bacillus subtilis and lactic acid bacteria. To meet the requirements of industrial applications in terms of degradation efficacy and stability, genetic engineering and computational tools are used to optimize enzymatic expression. Currently, registration and technical difficulties have restricted commercial application of mycotoxin-degrading enzymes. To overcome these obstacles, systematic safety evaluation of both biosynthetic enzymes and their degradation products, in-depth understanding of degradation mechanisms and a comprehensive evaluation of their impact on food and feed quality are urgently needed.

Green Biologics: Harnessing the Power of Plants to Produce Pharmaceuticals

Plants are increasingly used for the production of high-quality biological molecules for use as pharmaceuticals and biomaterials in industry. Plants have proved that they can produce life-saving therapeutic proteins (Elelyso™-Gaucher's disease treatment, ZMapp™-anti-Ebola monoclonal antibodies, seasonal flu vaccine, Covifenz™-SARS-CoV-2 virus-like particle vaccine); however, some of these therapeutic proteins are difficult to bring to market, which leads to serious difficulties for the manufacturing companies. The closure of one of the leading companies in the sector (the Canadian biotech company Medicago Inc., producer of Covifenz) as a result of the withdrawal of investments from the parent company has led to the serious question: What is hindering the exploitation of plant-made biologics to improve health outcomes? Exploring the vast potential of plants as biological factories, this review provides an updated perspective on plant-derived biologics (PDB). A key focus is placed on the advancements in plant-based expression systems and highlighting cutting-edge technologies that streamline the production of complex protein-based biologics. The versatility of plant-derived biologics across diverse fields, such as human and animal health, industry, and agriculture, is emphasized. This review also meticulously examines regulatory considerations specific to plant-derived biologics, shedding light on the disparities faced compared to biologics produced in other systems.

Exploring the whole proteome of monkeypox virus to design B cell epitope-based oral vaccines using immunoinformatics approaches

In the last few months 85,536 cases and 91 deaths were reported for monkeypox disease from 110 and 71 locations from all over the world, correspondingly. The vaccines of other viruses that belong to the Poxviridae family were recommended for monkeypox. There is no licensed vaccine available for monkeypox that originated from monkeypox virus. In the present study, using the reverse vaccinology approach we have performed whole proteome analysis of monkeypox virus to screen out the potential antigenic proteins that can be used as vaccine candidates. We have also designed 12 B cell epitopes-based vaccine candidates using immunoinformatics approach. We have found a total 15 potential antigenic proteins out of which 14 antigens are novel and can be used for further vaccine development against monkeypox. We have performed the physicochemical properties, antigenic, immunogenic and allergenicity prediction of the designed vaccine candidates MPOXVs (MPOXV1-MPOXV12). Further, we have performed molecular docking, in silico immune simulation and cloning of MPOXVs. All MPOXVs are potential vaccine candidate that can potentially activate the innate, cellular, and humoral immune response. However, further experimental validation is required before moving to clinical trials. This is the first oral vaccine reported for monkeypox virus derived from monkeypox proteins.

Molecular cloning, expression, and functional analysis of a putative lectin from the pearl oyster (Pinctada fucata, Gould 1850)

Marine lectins are a group of proteins that possess specific carbohydrate recognition and binding domains. They exhibit various activities, including antimicrobial, antitumor, antiviral, and immunomodulatory effects. In this study, a novel galectin-binding lectin gene named PFL-96 (GenBank: OQ561753.1) was cloned from Pinctada fucata. The PFL-96 gene has an open reading frame of 324 base pairs (bp) and encodes a protein comprising 107 amino acids. The protein has a molecular weight of 11.95 kDa and an isoelectric point of 9.27. It contains an N-terminal signal peptide and a galactose-binding lectin domain. The sequence identity to lectin proteins from fish, echinoderms, coelenterates, and shellfish ranges from 31.90 to 40.00 %. In the phylogenetic analysis, it was found that the PFL-96 protein is closely related to the lectin from Pteria penguin. The PFL-96 recombinant protein exhibited coagulation activity on 2 % rabbit red blood cells at a concentration of ≥8 μg/mL. Additionally, it showed significant hemolytic activity at a concentration of ≥32 μg/mL. The PFL-96 recombinant protein exhibited significant antibacterial activity against Bacillus subtilis, Staphylococcus aureus, Candida albicans, and Vibrio alginolyticus, with minimum inhibitory concentrations (MIC) of 4, 8, 16, and 16 μg/mL, respectively. The minimum bactericidal concentrations (MBC) were determined to be 8, 16, 32, and 32 μg/mL, respectively. Furthermore, the PFL-96 recombinant protein exhibited inhibitory effects on the proliferation of Hela tumor cells, HepG2 tumor cells, and C666-1 tumor cells, with IC50 values of 7.962, 8.007, and 9.502 μg/mL, respectively. These findings suggest that the recombinant protein PFL-96 exhibits significant bioactivity in vitro, contributing to a better understanding of the active compounds found in P. fucata. The present study establishes a fundamental basis for further investigation into the mechanism of action and structural optimization of the recombinant protein PFL-96. The aim is to develop potential candidates for antibacterial and anti-tumor agents.

Harnessing synthetic biology for advancing RNA therapeutics and vaccine design

Recent global events have drawn into focus the diversity of options for combatting disease across a spectrum of prophylactic and therapeutic approaches. The recent success of the mRNA-based COVID-19 vaccines has paved the way for RNA-based treatments to revolutionize the pharmaceutical industry. However, historical treatment options are continuously updated and reimagined in the context of novel technical developments, such as those facilitated through the application of synthetic biology. When it comes to the development of genetic forms of therapies and vaccines, synthetic biology offers diverse tools and approaches to influence the content, dosage, and breadth of treatment with the prospect of economic advantage provided in time and cost benefits. This can be achieved by utilizing the broad tools within this discipline to enhance the functionality and efficacy of pharmaceutical agent sequences. This review will describe how synthetic biology principles can augment RNA-based treatments through optimizing not only the vaccine antigen, therapeutic construct, therapeutic activity, and delivery vector. The enhancement of RNA vaccine technology through implementing synthetic biology has the potential to shape the next generation of vaccines and therapeutics.

Codon optimization of a gene encoding DNA polymerase from Pyrococcus furiosus and its expression in Escherichia coli

BACKGROUND

DNA polymerase is an essential component in PCR assay for DNA synthesis. Improving DNA polymerase with characteristics indispensable for a powerful assay is crucial because it can be used in wide-range applications. Derived from Pyrococcus furiosus, Pfu DNA polymerase (Pfu pol) is one of the excellent polymerases due to its high fidelity. Therefore, we aimed to develop Pfu pol from a synthetic gene with codon optimization to increase its protein yield in Escherichia coli.

RESULTS

Recombinant Pfu pol was successfully expressed and purified with a two-step purification process using nickel affinity chromatography, followed by anion exchange chromatography. Subsequently, the purified Pfu pol was confirmed by Western blot analysis, resulting in a molecular weight of approximately 90 kDa. In the final purification process, we successfully obtained a large amount of purified enzyme (26.8 mg/L). Furthermore, the purified Pfu pol showed its functionality and efficiency when tested for DNA amplification using the standard PCR.

CONCLUSIONS

Overall, a high-level expression of recombinant Pfu pol was achieved by employing our approach in the present study. In the future, our findings will be useful for studies on synthesizing recombinant DNA polymerase in E. coli expression system.

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

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

Artificial intelligence-driven systems engineering for next-generation plant-derived biopharmaceuticals

Recombinant biopharmaceuticals including antigens, antibodies, hormones, cytokines, single-chain variable fragments, and peptides have been used as vaccines, diagnostics and therapeutics. Plant molecular pharming is a robust platform that uses plants as an expression system to produce simple and complex recombinant biopharmaceuticals on a large scale. Plant system has several advantages over other host systems such as humanized expression, glycosylation, scalability, reduced risk of human or animal pathogenic contaminants, rapid and cost-effective production. Despite many advantages, the expression of recombinant proteins in plant system is hindered by some factors such as non-human post-translational modifications, protein misfolding, conformation changes and instability. Artificial intelligence (AI) plays a vital role in various fields of biotechnology and in the aspect of plant molecular pharming, a significant increase in yield and stability can be achieved with the intervention of AI-based multi-approach to overcome the hindrance factors. Current limitations of plant-based recombinant biopharmaceutical production can be circumvented with the aid of synthetic biology tools and AI algorithms in plant-based glycan engineering for protein folding, stability, viability, catalytic activity and organelle targeting. The AI models, including but not limited to, neural network, support vector machines, linear regression, Gaussian process and regressor ensemble, work by predicting the training and experimental data sets to design and validate the protein structures thereby optimizing properties such as thermostability, catalytic activity, antibody affinity, and protein folding. This review focuses on, integrating systems engineering approaches and AI-based machine learning and deep learning algorithms in protein engineering and host engineering to augment protein production in plant systems to meet the ever-expanding therapeutics market.

Molecular and Functional Analyses of Characterized Sesquiterpene Synthases in Mushroom-Forming Fungi

Sesquiterpenes are a type of abundant natural product with widespread applications in several industries. They are biosynthesized by sesquiterpene synthases (STSs). As valuable and abundant biological resources, mushroom-forming fungi are rich in new sesquiterpenes and STSs, which remain largely unexploited. In the present study, we collected information on 172 STSs from mushroom-forming fungi with experimentally characterized products from the literature and sorted them to develop a dataset. Furthermore, we analyzed and discussed the phylogenetic tree, catalytic products, and conserved motifs of STSs. Phylogenetic analysis revealed that the STSs were clustered into four clades. Furthermore, their cyclization reaction mechanism was divided into four corresponding categories. This database was used to predict 12 putative STS genes from the edible fungi Flammulina velutipes. Finally, three FvSTSs were selected to experimentally characterize their functions. FvSTS03 predominantly produced Δ-cadinol and FvSTS08 synthesized β-barbatene as the main product; these findings were consistent with those of the functional prediction analysis. A product titer of 78.8 mg/L β-barbatene was achieved in Saccharomyces cerevisiae via metabolic engineering. Our study findings will help screen or design STSs from fungi with specific product profiles as functional elements for applications in synthetic biology.

The apocarotenoid production in microbial biofactories: An overview

Carotenoids are a vast group of natural pigments that come in a variety of colors ranging from red to orange. Apocarotenoids are derived from these carotenoids, which are hormones, pigments, retinoids, and volatiles employed in the textiles, cosmetics, pharmaceutical, and food industries. Due to the high commercial value and poor natural host abundance, they are significantly undersupplied. Microbes like Saccharomyces cerevisiae and Escherichia coli act as heterologous hosts for apocarotenoid production. This article briefly reviews categories of apocarotenoids, their biosynthetic pathway commencing from the MVA and MEP, its significance, the tool enzymes for apocarotenoid biosynthesis like CCDs, their biotechnological production in microbial factories, and future perspectives.

Synergy between imputed genetic pathway and clinical information for predicting recurrence in early stage non-small cell lung cancer

OBJECTIVE

Lung cancer exhibits unpredictable recurrence in low-stage tumors and variable responses to different therapeutic interventions. Predicting relapse in early-stage lung cancer can facilitate precision medicine and improve patient survivability. While existing machine learning models rely on clinical data, incorporating genomic information could enhance their efficiency. This study aims to impute and integrate specific types of genomic data with clinical data to improve the accuracy of machine learning models for predicting relapse in early-stage, non-small cell lung cancer patients.

METHODS

The study utilized a publicly available TCGA lung cancer cohort and imputed genetic pathway scores into the Spanish Lung Cancer Group (SLCG) data, specifically in 1348 early-stage patients. Initially, tumor recurrence was predicted without imputed pathway scores. Subsequently, the SLCG data were augmented with pathway scores imputed from TCGA. The integrative approach aimed to enhance relapse risk prediction performance.

RESULTS

The integrative approach achieved improved relapse risk prediction with the following evaluation metrics: an area under the precision-recall curve (PR-AUC) score of 0.75, an area under the ROC (ROC-AUC) score of 0.80, an F1 score of 0.61, and a Precision of 0.80. The prediction explanation model SHAP (SHapley Additive exPlanations) was employed to explain the machine learning model's predictions.

CONCLUSION

We conclude that our explainable predictive model is a promising tool for oncologists that addresses an unmet clinical need of post-treatment patient stratification based on the relapse risk while also improving the predictive power by incorporating proxy genomic data not available for specific patients.

Heterologous protein production in filamentous fungi

Filamentous fungi are able to produce a wide range of valuable proteins and enzymes for many industrial applications. Recent advances in fungal genomics and experimental technologies are rapidly changing the approaches for the development and use of filamentous fungi as hosts for the production of both homologous and heterologous proteins. In this review, we highlight the benefits and challenges of using filamentous fungi for the production of heterologous proteins. We review various techniques commonly employed to improve the heterologous protein production in filamentous fungi, such as strong and inducible promoters, codon optimization, more efficient signal peptides for secretion, carrier proteins, engineering of glycosylation sites, regulation of the unfolded protein response and endoplasmic reticulum associated protein degradation, optimization of the intracellular transport process, regulation of unconventional protein secretion, and construction of protease-deficient strains. KEY POINTS: • This review updates the knowledge on heterologous protein production in filamentous fungi. • Several fungal cell factories and potential candidates are discussed. • Insights into improving heterologous gene expression are given.

gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm

The tRNA adaptation index (tAI) is a translation efficiency metric that considers weighted values (S _ij values) for codon-tRNA wobble interaction efficiencies. The initial implementation of the tAI had significant flaws. For instance, generated S _ij weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. Consequently, a species-specific approach (stAI) was developed to overcome those limitations. However, the stAI method employed a hill climbing algorithm to optimize the S _ij weights, which is not ideal for obtaining the best set of S _ij weights because it could struggle to find the global maximum given a complex search space, even after using different starting positions. In addition, it did not perform well in computing the tAI of fungal genomes in comparison with the original implementation. We developed a novel approach named genetic tAI (gtAI) implemented as a Python package (https://github.com/AliYoussef96/gtAI), which employs a genetic algorithm to obtain the best set of S _ij weights and follows a new codon usage-based workflow that better computes the tAI of genomes from the three domains of life. The gtAI has significantly improved the correlation with the codon adaptation index (CAI) and the prediction of protein abundance (empirical data) compared to the stAI.

Application of codon usage and context analysis in genes up- or down-regulated in neurodegeneration and cancer to combat comorbidities

Introduction

Neurodegeneration and cancer present in comorbidities with inverse effects due to the expression of genes and pathways acting in opposition. Identifying and studying the genes simultaneously up or downregulated during morbidities helps curb both ailments together.

Methods

This study examines four genes. Three of these (Amyloid Beta Precursor Protein (APP), Cyclin D1 (CCND1), and Cyclin E2 (CCNE2) are upregulated, and one protein phosphatase 2 phosphatase activator (PTPA) is simultaneously downregulated in both disorders. We investigated molecular patterns, codon usage, codon usage bias, nucleotide bias in the third codon position, preferred codons, preferred codon pairs, rare codons, and codon context.

Results

Parity analysis revealed that T is preferred over A, and G is preferred over C in the third codon position, suggesting composition plays no role in nucleotide bias in both the upregulated and downregulated gene sets and that mutational forces are stronger in upregulated gene sets than in downregulated ones. Transcript length influenced the overall %A composition and codon bias, and the codon AGG exerted the strongest influence on codon usage in both the upregulated and downregulated gene sets. Codons ending in G/C were preferred for 16 amino acids, and glutamic acid-, aspartic acid-, leucine-, valine-, and phenylalanine-initiated codon pairs were preferred in all genes. Codons CTA (Leu), GTA (Val), CAA (Gln), and CGT (Arg) were underrepresented in all examined genes.

Discussion

Using advanced gene editing tools such as CRISPR/Cas or any other gene augmentation technique, these recoded genes may be introduced into the human body to optimize gene expression levels to augment neurodegeneration and cancer therapeutic regimens simultaneously.

Optimization, characterization, comparison of self-assembly VLP of capsid protein L1 in yeast and reverse vaccinology design against human papillomavirus type 52

BACKGROUND

Vaccination is the one of the agendas of many countries to reduce cervical cancer caused by the Human papillomavirus. Currently, VLP-based vaccine is the most potent vaccine against HPV, which could be produced by a variety of expression systems. Our study focuses on a comparison of recombinant protein expression L1 HPV52 using two common yeasts, Pichia pastoris and Hansenula polymorpha that have been used for vaccine production on an industrial scale. We also applied bioinformatics approach using reverse vaccinology to design alternative multi-epitope vaccines in recombinant protein and mRNA types.

RESULTS

Our study found that P. pastoris relatively provided higher level of L1 protein expression and production efficiency compared to H. polymorpha in a batch system. However, both hosts showed self-assembly VLP formation and stable integration during protein induction. The vaccine we have designed exhibited high immune activation and safe in computational prediction. It is also potentially suitable for production in a variety of expression systems.

CONCLUSION

By monitoring the overall optimization parameter assessment, this study can be used as the basis reference for large-scale production of the HPV52 vaccine.

Synonymous Codon Variant Analysis for Autophagic Genes Dysregulated in Neurodegeneration

Neurodegenerative disorders are often a culmination of the accumulation of abnormally folded proteins and defective organelles. Autophagy is a process of removing these defective proteins, organelles, and harmful substances from the body, and it works to maintain homeostasis. If autophagic removal of defective proteins has interfered, it affects neuronal health. Some of the autophagic genes are specifically found to be associated with neurodegenerative phenotypes. Non-functional, mutated, or gene copies having silent mutations, often termed synonymous variants, might explain this. However, these synonymous variant which codes for exactly similar proteins have different translation rates, stability, and gene expression profiling. Hence, it would be interesting to study the pattern of synonymous variant usage. In the study, synonymous variant usage in various transcripts of autophagic genes ATG5, ATG7, ATG8A, ATG16, and ATG17/FIP200 reported to cause neurodegeneration (if dysregulated) is studied. These genes were analyzed for their synonymous variant usage; nucleotide composition; any possible nucleotide skew in a gene; physical properties of autophagic protein including GRAVY and AROMA; hydropathicity; instability index; and frequency of acidic, basic, neutral amino acids; and gene expression level. The study will help understand various evolutionary forces acting on these genes and the possible augmentation of a gene if showing unusual behavior.

Annotation of Potential Vaccine Targets and Designing of mRNA-Based Multi-Epitope Vaccine against Lumpy Skin Disease Virus via Reverse Vaccinology and Agent-Based Modeling

Lumpy skin disease is a fatal emerging disease of cattle, which has started to gain extensive attention due to its rapid incursions across the globe. The disease epidemic causes economic loss and cattle morbidity. Currently, there are no specific treatments and safe vaccines against the lumpy skin disease virus (LSDV) to halt the spread of the disease. The current study uses genome-scan vaccinomics analyses to prioritize promiscuous vaccine candidate proteins of the LSDV. These proteins were subjected to top-ranked B- and T-cell epitope prediction based on their antigenicity, allergenicity, and toxicity values. The shortlisted epitopes were connected using appropriate linkers and adjuvant sequences to design multi-epitope vaccine constructs. Three vaccine constructs were prioritized based on their immunological and physicochemical properties. The model constructs were back-translated to nucleotide sequences and codons were optimized. The Kozak sequence with a start codon along with MITD, tPA, Goblin 5′, 3′ UTRs, and a poly(A) tail sequences were added to design a stable and highly immunogenic mRNA vaccine. Molecular docking followed by MD simulation analysis predicted significant binding affinity and stability of LSDV-V2 construct within bovine immune receptors and predicted it to be the top-ranked candidate to stimulate the humeral and cellular immunogenic responses. Furthermore, in silico restriction cloning predicted feasible gene expression of the LSDV-V2 construct in a bacterial expression vector. It could prove worthwhile to validate the predicted vaccine models experimentally and clinically against LSDV.

Protein-Based Biological Materials: Molecular Design and Artificial Production

Polymeric materials produced from fossil fuels have been intimately linked to the development of industrial activities in the 20th century and, consequently, to the transformation of our way of living. While this has brought many benefits, the fabrication and disposal of these materials is bringing enormous sustainable challenges. Thus, materials that are produced in a more sustainable fashion and whose degradation products are harmless to the environment are urgently needed. Natural biopolymers─which can compete with and sometimes surpass the performance of synthetic polymers─provide a great source of inspiration. They are made of natural chemicals, under benign environmental conditions, and their degradation products are harmless. Before these materials can be synthetically replicated, it is essential to elucidate their chemical design and biofabrication. For protein-based materials, this means obtaining the complete sequences of the proteinaceous building blocks, a task that historically took decades of research. Thus, we start this review with a historical perspective on early efforts to obtain the primary sequences of load-bearing proteins, followed by the latest developments in sequencing and proteomic technologies that have greatly accelerated sequencing of extracellular proteins. Next, four main classes of protein materials are presented, namely fibrous materials, bioelastomers exhibiting high reversible deformability, hard bulk materials, and biological adhesives. In each class, we focus on the design at the primary and secondary structure levels and discuss their interplays with the mechanical response. We finally discuss earlier and the latest research to artificially produce protein-based materials using biotechnology and synthetic biology, including current developments by start-up companies to scale-up the production of proteinaceous materials in an economically viable manner.

Cauliflower mosaic virus: Virus-host interactions and its uses in biotechnology and medicine

Cauliflower mosaic virus (CaMV) was the first discovered plant virus with genomic DNA that uses reverse transcriptase for replication. The CaMV 35S promoter is a constitutive promoter and thus, an attractive driver of gene expression in plant biotechnology. It is used in most transgenic crops to activate foreign genes which have been artificially inserted into the host plant. In the last century, producing food for the world's population while preserving the environment and human health is the main topic of agriculture. The damage caused by viral diseases has a significant negative economic impact on agriculture, and disease control is based on two strategies: immunization and prevention to contain virus spread, so correct identification of plant viruses is important for disease management. Here, we discuss CaMV from different aspects: taxonomy, structure and genome, host plants and symptoms, transmission and pathogenicity, prevention, control and application in biotechnology as well as in medicine. Also, we calculated the CAI index for three ORFs IV, V, and VI of the CaMV virus in host plants, the results of which can be used in the discussion of gene transfer or antibody production to identify the CaMV.