Determinants of translation efficiency and accuracy

Inferring protein from transcript abundances using convolutional neural networks

BACKGROUND

Although transcript abundance is often used as a proxy for protein abundance, it is an unreliable predictor. As proteins execute biological functions and their expression levels influence phenotypic outcomes, we developed a convolutional neural network (CNN) to predict protein abundances from mRNA abundances, protein sequence, and mRNA sequence in Homo sapiens (H. sapiens) and the reference plant Arabidopsis thaliana (A. thaliana).

RESULTS

After hyperparameter optimization and initial data exploration, we implemented distinct training modules for value-based and sequence-based data. By analyzing the learned weights, we revealed common and organism-specific sequence features that influence protein-to-mRNA ratios (PTRs), including known and putative sequence motifs. Adding condition-specific protein interaction information identified genes correlated with many PTRs but did not improve predictions, likely due to insufficient data. The integrated model predicted protein abundance on unseen genes with a coefficient of determination (r2) of 0.30 in H. sapiens and 0.32 in A. thaliana.

CONCLUSIONS

For H. sapiens, our model improves prediction performance by nearly 50% compared to previous sequence-based approaches, and for A. thaliana it represents the first model of its kind. The model's learned motifs recapitulate known regulatory elements, supporting its utility in systems-level and hypothesis-driven research approaches related to protein regulation.

Predicting the translation efficiency of messenger RNA in mammalian cells

The degree to which translational control is specified by mRNA sequence is poorly understood in mammalian cells. Here, we constructed and leveraged a compendium of 3,819 ribosomal profiling datasets, distilling them into a transcriptome-wide atlas of translation efficiency (TE) measurements encompassing >140 human and mouse cell types. We subsequently developed RiboNN, a multitask deep convolutional neural network, and classic machine learning models to predict TEs in hundreds of cell types from sequence-encoded mRNA features, achieving state-of-the-art performance (r=0.79 in human and r=0.78 in mouse for mean TE across cell types). While the majority of earlier models solely considered 5' UTR sequence1, RiboNN integrates contributions from the full-length mRNA sequence, learning that the 5' UTR, CDS, and 3' UTR respectively possess ~67%, 31%, and 2% per-nucleotide information density in the specification of mammalian TEs. Interpretation of RiboNN revealed that the spatial positioning of low-level di- and tri-nucleotide features (i.e., including codons) largely explain model performance, capturing mechanistic principles such as how ribosomal processivity and tRNA abundance control translational output. RiboNN is predictive of the translational behavior of base-modified therapeutic RNA, and can explain evolutionary selection pressures in human 5' UTRs. Finally, it detects a common language governing mRNA regulatory control and highlights the interconnectedness of mRNA translation, stability, and localization in mammalian organisms.

Design of a Multiepitope Pan-Proteomic mRNA Vaccine Construct Against African Swine Fever Virus: A Reverse Vaccinology Approach

African swine fever (ASF), caused by African swine fever virus (ASFV), is a highly contagious disease with devastating effects on the global pig industry. This warrants the development of effective control strategies, such as vaccines. However, previously developed inactivated vaccines have proven ineffective, while live-attenuated vaccines carry inherent safety risks. The use of mRNA vaccines eliminates these risks offering a safe, cost-effective, and efficient vaccine strategy against ASFV. In this study, a reverse vaccinology approach was used to design a multiepitope pan-proteomic mRNA vaccine against ASFV. Various bioinformatics tools were employed to predict epitopes for cytotoxic T lymphocytes, helper T lymphocytes, and B lymphocytes. A 50S ribosomal L7/L12 protein adjuvant, 5' cap, poly(A) tail, signal peptide, and MHC-I-targeting domain were incorporated into the design using appropriate linkers to increase immunogenicity, stability, and recognition efficiency. The physicochemical properties of the final construct were evaluated, and docking analyses were done with Toll-like receptors (TLRs) 3, 4, and 7 to evaluate binding affinity. A molecular dynamics simulation was then performed to determine binding stability, while immune simulations evaluated host's immune response. Based on 100 ASFV proteomes, six epitopes that induce cytotoxic T-cell responses, five epitopes that induce helper T-cell responses, and four epitopes that induce antibody production were predicted. The designed vaccine construct was found to be nonallergenic, antigenic, and stable when bound to TLR4 while the binding pocket analyses of the vaccine construct to TLR3 and TLR7 indicate high translation efficiency. Immune simulations demonstrated successful induction of immune responses and generation of antigen-specific memory cells. In conclusion, this study introduces an mRNA vaccine construct as a potential disease control strategy against ASF for in vitro confirmation.

mRNA vaccine sequence and structure design and optimization: Advances and challenges

Messenger RNA (mRNA) vaccines have emerged as a powerful tool against communicable diseases and cancers, as demonstrated by their huge success during the coronavirus disease 2019 (COVID-19) pandemic. Despite the outstanding achievements, mRNA vaccines still face challenges such as stringent storage requirements, insufficient antigen expression, and unexpected immune responses. Since the intrinsic properties of mRNA molecules significantly impact vaccine performance, optimizing mRNA design is crucial in preclinical development. In this review, we outline four key principles for optimal mRNA sequence design: enhancing ribosome loading and translation efficiency through untranslated region (UTR) optimization, improving translation efficiency via codon optimization, increasing structural stability by refining global RNA sequence and extending in-cell lifetime and expression fidelity by adjusting local RNA structures. We also explore recent advancements in computational models for designing and optimizing mRNA vaccine sequences following these principles. By integrating current mRNA knowledge, addressing challenges, and examining advanced computational methods, this review aims to promote the application of computational approaches in mRNA vaccine development and inspire novel solutions to existing obstacles.

Life History Differences Between Lepidoptera Larvae and Blattodea Nymphs Lead to Different Energy Allocation Strategies and Cellular Qualities

Different life histories result in different strategies to allocate energy in biosynthesis, including growth and reproduction, and somatic maintenance. One of the most notable life history differences between Lepidoptera and Blattodea species is that the former grow much faster than the latter, and during metamorphosis, a large amount of tissue in Lepidoptera species disintegrates. In this review, using Lepidoptera caterpillars and cockroach nymphs as examples, we show that, due to these differences in growth processes, cockroach nymphs spend 20 times more energy on synthesizing one unit of biomass (indirect cost of growth) than butterfly caterpillars. Because of the low indirect cost of growth in caterpillars, the fraction of metabolic energy allocated to growth is six times lower, and that for maintenance is seven times higher in caterpillars, compared to cockroach nymphs, despite caterpillar's higher growth rates. Moreover, due to the higher biosynthetic energy cost in cockroach nymphs, they have better cellular qualities, including higher proteasomal activity for protein quality control and higher resistance to oxidative stress. We also show that under food restriction conditions, the fraction of assimilated energy allocated to growth was reduced by 120% in cockroach nymphs, as they lost body weight under food restriction, while this reduction was only 14% in hornworms, and the body mass increased at a lower rate. Finaly, we discuss future research, especially the difference in adult lifespans associated with the energetic differences.

Protein translation can fluidize bacterial cytoplasm

The cytoplasm of bacterial cells is densely packed with highly polydisperse macromolecules that exhibit size-dependent glassy dynamics. Recent research has revealed that metabolic activities in living cells can counteract the glassy nature of these macromolecules, allowing the cell to maintain critical fluidity for its growth and function. While it has been proposed that the crowded cytoplasm is responsible for this glassy behavior, a detailed analysis of the size-dependent nature of the glassy dynamics and an explanation for how cellular activity induces its fluidization remains elusive. Here, we use a combination of computational models and targeted experiments to show that entropic segregation of the protein synthesis machinery from the chromosomal DNA causes size-dependent spatial organization of molecules within the cell, and the resultant crowding leads to size-dependent glassy dynamics. Furthermore, Brownian dynamics simulations of this in silico system supports a new hypothesis: protein synthesis in living cells contributes to the metabolism-dependent fluidization of the cytoplasm. The main protein synthesis machinery, ribosomes, frequently shift between fast and slow diffusive states. These states correspond to the independent movement of ribosomal subunits and the actively translating ribosome chains called polysomes, respectively. Our simulations demonstrate that the frequent transitions of the numerous ribosomes, which constitute a significant portion of the cell proteome, greatly enhance the mobility of other macromolecules within the bacterial cytoplasm. Considering that ribosomal protein synthesis is the largest consumer of ATP in growing bacterial cells, the translation process can serve as the primary mechanism for fluidizing the cytoplasm in metabolically active cells.

Modeling and measuring how codon usage modulates the relationship between burden and yield during protein overexpression in bacteria

Excess utilization of translational resources is a critical source of burden on cells engineered to over-express exogenous proteins. To improve protein yields and genetic stability, researchers often use codon optimization strategies that improve translational efficiency by matching an exogenous gene's codon usage with that of the host organism's highly expressed genes. Despite empirical data that shows the benefits of codon optimization, little is known quantitatively about the relationship between codon usage bias and the burden imposed by protein overexpression. Here, we develop and experimentally evaluate a stochastic gene expression model that considers the impact of codon usage bias on the availability of ribosomes and different tRNAs in a cell. In agreement with other studies, our model shows that increasing exogenous protein expression decreases production of native cellular proteins in a linear fashion. We also find that the slope of this relationship is modulated by how well the codon usage bias of the exogenous gene and the host's genes match. Strikingly, we predict that an overoptimization domain exists where further increasing usage of optimal codons worsens yield and burden. We test our model by expressing sfGFP and mCherry2 from constructs that have a wide range of codon optimization levels in Escherichia coli . The results agree with our model, including for an mCherry2 gene sequence that appears to lose expression and genetic stability from codon overoptimization. Our findings can be leveraged by researchers to predict and design more optimal cellular systems through the use of more nuanced codon optimization strategies.

Keeping the Distance: Activity Control in Solid-Supported Sucrose Phosphorylase by a Rigid α-Helical Linker of Tunable Spacer Length

Enzyme immobilization into carrier materials has broad importance in biotechnology, yet understanding the catalysis of enzymes bound to solid surfaces remains challenging. Here, we explore surface effects on the catalysis of sucrose phosphorylase through a fusion protein approach. We immobilize the enzyme via a structurally rigid α-helical linker [EA3K] n of tunable spacer length due to the variable number of pentapeptide repeats used (n = 6, 14, 19). Molecular modeling and simulation approaches delineate the conformational space sampled by each linker relative to its His-tag cap used for surface tethering. The population distribution of linker conformers gets broader, with a consequent shift of the enzyme-to-surface distance to larger values (≤15 nm), as the spacer length increases. Based on temperature kinetic studies, we obtain an energetic description of catalysis by the enzyme-to-linker fusions in solution and immobilize on Ni2+-chelate agarose. The solid-supported enzymes involve distinct changes in enthalpy-entropy partitioning within the frame of invariant Gibbs free energy of activation (ΔG ‡ = ∼61 kJ/mol at 30 °C). The entropic contribution (-TΔS ‡) to ΔG ‡ increases with the spacer length, from -16.4 kJ/mol in the linker-free enzyme to +7.9 kJ/mol in the [EA3K]19 linked fusion. The immobilized [EA3K]19 fusion protein is indistinguishable in its catalytic properties from the enzymes in solution, which behave identically regardless of their linker. Enzymes positioned closer to the surface arguably experience a higher degree of molecular organization ("rigidification") that must relax for catalysis through the additional uptake of heat, compensated by a gain in entropy. Increased thermostability of these enzymes (up to 2.8-fold) is consistent with the proposed rigidification effect. Collectively, our study reveals surface effects on the activation parameters of sucrose phosphorylase catalysis and shows their consistent dependence on the length of the surface-tethering linker. The fundamental insight here obtained, together with the successful extension of the principle to a different enzyme (nigerose phosphorylase), suggests that rigid linker-based control of the protein-surface distance can be used as an engineering strategy to optimize the activity characteristics of immobilized enzymes.

Host and structure-specific codon usage of G genotype (VP7) among group A rotaviruses

Rotavirus A (RVA) infects a relatively wide host range. Studying the evolutionary dynamics of viral genomes and the evolution of host adaptations can inform the development of epidemiological models of disease transmission. Moreover, comprehending the adaptive evolution of viruses in the host could provide insights into how viruses promote evolutionary advantages on a larger scale at host level. This study aims to determine whether host specificity in codon usage existed. We used the Clustal W function within MEGA X software to perform sequence alignment, followed by construction of a phylogenetic tree based on the maximum-likelihood method. Additionally, Codon W software and EMBOSS were utilized for analysis of codon usage bias index. We analyzed codon usage bias (CUB) of host-specific G genotype VP7 to elucidate the molecular-dynamic evolutionary pattern and reveal the adaptive evolution of VP7 at the host level. The CUB of RV VP7 exhibits significant difference between human and other species. This bias can be primarily attributed to natural selection. In addition, the β-barrel structural domain, which plays a crucial role in viral transmembrane entry into cells, demonstrates a stronger CUB. Our results provide novel insights into the evolutionary dynamics of RVs, cross-species transmission, and virus-host adaptation.

SARS-CoV-2 Displays a Suboptimal Codon Usage Bias for Efficient Translation in Human Cells Diverted by Hijacking the tRNA Epitranscriptome

Codon bias analysis of SARS-CoV-2 reveals suboptimal adaptation for translation in human cells it infects. The detailed examination of the codons preferentially used by SARS-CoV-2 shows a strong preference for LysAAA, GlnCAA, GluGAA, and ArgAGA, which are infrequently used in human genes. In the absence of an adapted tRNA pool, efficient decoding of these codons requires a 5-methoxycarbonylmethyl-2-thiouridine (mcm5s2) modification at the U34 wobble position of the corresponding tRNAs (tLysUUU; tGlnUUG; tGluUUC; tArgUCU). The optimal translation of SARS-CoV-2 open reading frames (ORFs) may therefore require several adjustments to the host's translation machinery, enabling the highly biased viral genome to achieve a more favorable "Ready-to-Translate" state in human cells. Experimental approaches based on LC-MS/MS quantification of tRNA modifications and on alteration of enzymatic tRNA modification pathways provide strong evidence to support the hypothesis that SARS-CoV-2 induces U34 tRNA modifications and relies on these modifications for its lifecycle. The conclusions emphasize the need for future studies on the evolution of SARS-CoV-2 codon bias and its ability to alter the host tRNA pool through the manipulation of RNA modifications.

DORQ-seq: high-throughput quantification of femtomol tRNA pools by combination of cDNA hybridization and Deep sequencing

Due to its high modification content tRNAs are notoriously hard to quantify by reverse transcription and RNAseq. Bypassing numerous biases resulting from concatenation of enzymatic treatments, we here report a hybrid approach that harnesses the advantages of hybridization-based and deep sequencing-based approaches. The method renders obsolete any RNAseq related workarounds and correction factors that affect accuracy, sensitivity, and turnaround time. Rather than by reverse transcription, quantitative information on the isoacceptor composition of a tRNA pool is transferred to a cDNA mixture in a single step procedure, thereby omitting all enzymatic conversations except for the subsequent barcoding PCR. As a result, a detailed tRNA composition matrix can be obtained from femtomolar amounts of total tRNA. The method is fast, low in cost, and its bioinformatic data workup surprisingly simple. These properties make the approach amenable to high-throughput investigations including clinical samples, as we have demonstrated by application to a collection of variegated biological questions, each answered with novel findings. These include tRNA pool quantification of polysome-bound tRNA, of tRNA modification knockout strains under stress conditions, and of Alzheimer patients' brain tissues.

Compositional Features and Codon Usage Pattern of Genes Associated with Parkinson's Disease

Codon usage bias (CUB) is the phenomenon of non-uniform usage of synonymous codons in which some codons are more used than others and it helps in understanding the molecular organization of genome. Bioinformatic approach was used to analyze the protein-coding sequences of genes associated with Parkinson's disease (PD) to explore compositional features and codon usage pattern as no details work was reported yet. The average improved effective number of codons (Nc) and Nc prime were 42.74 and 44.26 respectively, indicated that CUB was low in these genes. In most of the genes, the overall GC content was almost 50% and GC content at the 1st codon position was the highest while GC content at the 2nd codon position was lowest. Relative synonymous codon usage (RSCU) analysis elucidated over-represented (p > 1.6) and under-represented codons (p < 0.6). The GTG (Val) is the only codon over-represented in all genes. Over-represented codons except (GTG) were A or T ending while under-represented codons (except ACT) were G or C ending. The codons namely TTA (Leu), CTA (Leu), ATC (Ile), ATA (Ile), AGT (Ser), AAC (Asn), TGT (Cys), TGC (Cys), CGC (Arg), AGA (Arg), and AGG (Arg) were absent in SNCA1 to SNCA8 genes. The codon TCG (Ser) was absent in all genes except UCHL1 and PINK1. Correspondence analysis (COA) revealed that the pattern of codon usage differs among genes associated with PD. Neutrality plot analysis indicated some of the points are diagonal distribution suggested that mutation pressure influenced the CUB in genes associated with PD.

Genome-wide impact of codon usage bias on translation optimization in Drosophila melanogaster

Accuracy and efficiency are fundamental to mRNA translation. Codon usage bias is widespread across species. Despite the long-standing association between optimized codon usage and improved translation, our understanding of its evolutionary basis and functional effects remains limited. Drosophila is widely used to study codon usage bias, but genome-scale experimental data are scarce. Using high-resolution mass spectrometry data from Drosophila melanogaster, we show that optimal codons have lower translation errors than nonoptimal codons after accounting for these biases. Genomic-scale analysis of ribosome profiling data shows that optimal codons are translated more rapidly than nonoptimal codons. Although we find no long-term selection favoring synonymous mutations in D. melanogaster after diverging from D. simulans, we identify signatures of positive selection driving codon optimization in the D. melanogaster population. These findings expand our understanding of the functional consequences of codon optimization and serve as a foundation for future investigations.

Using yeasts for the studies of nonfunctional factors in protein evolution

The evolution of protein sequence is driven not only by factors directly related to protein function and shape but also by nonfunctional factors. Such factors in protein evolution might be categorized as those connected to energetic costs, synthesis efficiency, and avoidance of misfolding and toxicity. A common approach to studying them is correlational analysis contrasting them with some characteristics of the protein, like amino acid composition, but these features are interdependent. To avoid possible bias, empirical studies are needed, and not enough work has been done to date. In this review, we describe the role of nonfunctional factors in protein evolution and present an experimental approach using yeast as a suitable model organism. The focus of the proposed approach is on the potential negative impact on the fitness of mutations that change protein properties not related to function and the frequency of mutations that change these properties. Experimental results of testing the misfolding avoidance hypothesis as an explanation for why highly expressed proteins evolve slowly are inconsistent with correlational research results. Therefore, more efforts should be made to empirically test the effects of nonfunctional factors in protein evolution and to contrast these results with the results of the correlational analysis approach.

Engineering a Novel Probiotic Toolkit in Escherichia coli Nissle 1917 for Sensing and Mitigating Gut Inflammatory Diseases

Inflammatory bowel disease (IBD) is characterized by chronic intestinal inflammation with no cure and limited treatment options that often have systemic side effects. In this study, we developed a target-specific system to potentially treat IBD by engineering the probiotic bacterium Escherichia coli Nissle 1917 (EcN). Our modular system comprises three components: a transcription factor-based sensor (NorR) capable of detecting the inflammation biomarker nitric oxide (NO), a type 1 hemolysin secretion system, and a therapeutic cargo consisting of a library of humanized anti-TNFα nanobodies. Despite a reduction in sensitivity, our system demonstrated a concentration-dependent response to NO, successfully secreting functional nanobodies with binding affinities comparable to the commonly used drug Adalimumab, as confirmed by enzyme-linked immunosorbent assay and in vitro assays. This newly validated nanobody library expands EcN therapeutic capabilities. The adopted secretion system, also characterized for the first time in EcN, can be further adapted as a platform for screening and purifying proteins of interest. Additionally, we provided a mathematical framework to assess critical parameters in engineering probiotic systems, including the production and diffusion of relevant molecules, bacterial colonization rates, and particle interactions. This integrated approach expands the synthetic biology toolbox for EcN-based therapies, providing novel parts, circuits, and a model for tunable responses at inflammatory hotspots.

OTUD6 deubiquitination of RPS7/eS7 on the free 40 S ribosome regulates global protein translation and stress

Ribosomes are regulated by evolutionarily conserved ubiquitination/deubiquitination events. We uncover the role of the deubiquitinase OTUD6 in regulating global protein translation through deubiquitination of the RPS7/eS7 subunit on the free 40 S ribosome in vivo in Drosophila. Coimmunoprecipitation and enrichment of monoubiquitinated proteins from catalytically inactive OTUD6 flies reveal RPS7 as the ribosomal substrate. The 40 S protein RACK1 and E3 ligases CNOT4 and RNF10 function upstream of OTUD6 to regulate alkylation stress. OTUD6 interacts with RPS7 specifically on the free 40 S, and not on 43 S/48 S initiation complexes or the translating ribosome. Global protein translation levels are bidirectionally regulated by OTUD6 protein abundance. OTUD6 protein abundance is physiologically regulated in aging and in response to translational and alkylation stress. Thus, OTUD6 may promote translation initiation, the rate limiting step in protein translation, by titering the amount of 40 S ribosome that recycles.

Differentially used codons among essential genes in bacteria identified by machine learning-based analysis

Codon usage bias (CUB), the uneven usage of synonymous codons encoding the same amino acid, differs among genes within and across bacteria genomes. CUB is known to be influenced by gene expression and accordingly, CUB differs between the high-expression and low-expression genes in several bacteria. In this article, we have extended codon usage study considering gene essentiality as a feature. Using machine learning (ML) based approaches, we have analysed Relative Synonymous Codon Usage (RSCU) values between essential and non-essential genes in Escherichia coli and thirty-four other bacterial genomes whose gene essentiality features were available in public databases. We observed significant differences in codon usage patterns between essential and non-essential genes for majority of the bacterial genomes and accordingly, ML based classifiers achieved high area under curve (AUC) scores, with a minimum score of 70.0 across twenty-eight organisms. Further, importance of the codons towards classifying genes found to differ among the codons in each genome. Arg codon CGT and Gly codon GGT were observed to be the most preferred codons among essential genes in Escherichia coli. Interestingly, some of the codons like CGT, ATA, GGT and GGG observed to be contributing consistently towards classifying essential genes across thirty-five bacteria genomes studied. In other hand, codons TGY and CAY encoding amino acids Cys and His respectively were among the least contributing codons towards classification among all these bacteria. This study demonstrates the gene essentiality based differences in synonymous codon usage in bacteria genomes and presents a common codon usage pattern across bacteria.

Orb2 enables rare-codon-enriched mRNA expression during Drosophila neuron differentiation

Regulation of codon optimality is an increasingly appreciated layer of cell- and tissue-specific protein expression control. Here, we use codon-modified reporters to show that differentiation of Drosophila neural stem cells into neurons enables protein expression from rare-codon-enriched genes. From a candidate screen, we identify the cytoplasmic polyadenylation element binding (CPEB) protein Orb2 as a positive regulator of rare-codon-dependent mRNA stability in neurons. Using RNA sequencing, we reveal that Orb2-upregulated mRNAs in the brain with abundant Orb2 binding sites have a rare-codon bias. From these Orb2-regulated mRNAs, we demonstrate that rare-codon enrichment is important for mRNA stability and social behavior function of the metabotropic glutamate receptor (mGluR). Our findings reveal a molecular mechanism by which neural stem cell differentiation shifts genetic code regulation to enable critical mRNA stability and protein expression.

Minimizing IP issues associated with gene constructs encoding the Bt toxin - a case study

BACKGROUND

As part of a publicly funded initiative to develop genetically engineered Brassicas (cabbage, cauliflower, and canola) expressing Bacillus thuringiensis Crystal (Cry)-encoded insecticidal (Bt) toxin for Indian and Australian farmers, we designed several constructs that drive high-level expression of modified Cry1B and Cry1C genes (referred to as Cry1BM and Cry1CM; with M indicating modified). The two main motivations for modifying the DNA sequences of these genes were to minimise any licensing cost associated with the commercial cultivation of transgenic crop plants expressing CryM genes, and to remove or alter sequences that might adversely affect their activity in plants.

RESULTS

To assess the insecticidal efficacy of the Cry1BM/Cry1CM genes, constructs were introduced into the model Brassica Arabidopsis thaliana in which Cry1BM/Cry1CM expression was directed from either single (S4/S7) or double (S4S4/S7S7) subterranean clover stunt virus (SCSV) promoters. The resulting transgenic plants displayed a high-level of Cry1BM/Cry1CM expression. Protein accumulation for Cry1CM ranged from 5.18 to 176.88 µg Cry1CM/g dry weight of leaves. Contrary to previous work on stunt promoters, we found no correlation between the use of either single or double stunt promoters and the expression levels of Cry1BM/Cry1CM genes, with a similar range of Cry1CM transcript abundance and protein content observed from both constructs. First instar Diamondback moth (Plutella xylostella) larvae fed on transgenic Arabidopsis leaves expressing the Cry1BM/Cry1CM genes showed 100% mortality, with a mean leaf damage score on a scale of zero to five of 0.125 for transgenic leaves and 4.2 for wild-type leaves.

CONCLUSIONS

Our work indicates that the modified Cry1 genes are suitable for the development of insect resistant GM crops. Except for the PAT gene in the USA, our assessment of the intellectual property landscape of components presents within the constructs described here suggest that they can be used without the need for further licensing. This has the capacity to significantly reduce the cost of developing and using these Cry1M genes in GM crop plants in the future.

Optimal design of synthetic circular RNAs

Circular RNAs are an unusual class of single-stranded RNAs whose ends are covalently linked via back-splicing. Due to their versatility, the need to express circular RNAs in vivo and in vitro has increased. Efforts have been made to efficiently and precisely synthesize circular RNAs. However, a review on the optimization of the processes of circular RNA design, synthesis, and delivery is lacking. Our review highlights the multifaceted aspects considered when producing optimal circular RNAs and summarizes the available options for each step of exogenous circular RNA design and synthesis, including circularization strategies. Additionally, this review describes several potential applications of circular RNAs.

Comparative genomics analysis and transposon mutagenesis provides new insights into high menaquinone-7 biosynthetic potential of Bacillus subtilis natto

This research combined Whole-Genome sequencing, intraspecific comparative genomics and transposon mutagenesis to investigate the menaquinone-7 (MK-7) synthesis potential in Bacillus subtilis natto. First, Whole-Genome sequencing showed that Bacillus subtilis natto BN-P15-11-1 contains one single circular chromosome in size of 3,982,436 bp with a GC content of 43.85 %, harboring 4,053 predicted coding genes. Next, the comparative genomics analysis among strain BN-P15-11-1 with model Bacillus subtilis 168 and four typical Bacillus subtilis natto strains proves that the closer evolutionary relationship Bacillus subtilis natto BN-P15-11-1 and Bacillus subtilis 168 both exhibit strong biosynthetic potential. To further dig for MK-7 biosynthesis latent capacity of BN-P15-11-1, we constructed a mutant library using transposons and a high throughput screening method using microplates. We obtained a YqgQ deficient high MK-7 yield strain F4 with a yield 3.02 times that of the parent strain. Experiments also showed that the high yield mutants had defects in different transcription and translation regulatory factor genes, indicating that regulatory factor defects may affect the biosynthesis and accumulation of MK-7 by altering the overall metabolic level. The findings of this study will provide more novel insights on the precise identification and rational utilization of the Bacillus subtilis subspecies for biosynthesis latent capacity.

Molecular Evolution of Protein Sequences and Codon Usage in Monkeypox Viruses

The monkeypox virus (mpox virus, MPXV) epidemic in 2022 has posed a significant public health risk. Yet, the evolutionary principles of MPXV remain largely unknown. Here, we examined the evolutionary patterns of protein sequences and codon usage in MPXV. We first demonstrated the signal of positive selection in OPG027, specifically in the Clade I lineage of MPXV. Subsequently, we discovered accelerated protein sequence evolution over time in the variants responsible for the 2022 outbreak. Furthermore, we showed strong epistasis between amino acid substitutions located in different genes. The codon adaptation index (CAI) analysis revealed that MPXV genes tended to use more non-preferred codons compared to human genes, and the CAI decreased over time and diverged between clades, with Clade I > IIa and IIb-A > IIb-B. While the decrease in fatality rate among the three groups aligned with the CAI pattern, it remains unclear whether this correlation was coincidental or if the deoptimization of codon usage in MPXV led to a reduction in fatality rates. This study sheds new light on the mechanisms that govern the evolution of MPXV in human populations.

Utilizing 5' UTR Engineering Enables Fine-Tuning of Multiple Genes within Operons to Balance Metabolic Flux in Bacillus subtilis

The application of synthetic biology tools to modulate gene expression to increase yield has been thoroughly demonstrated as an effective and convenient approach in industrial production. In this study, we employed a high-throughput screening strategy to identify a 5' UTR sequence from the genome of B. subtilis 168. This sequence resulted in a 5.8-fold increase in the expression level of EGFP. By utilizing the 5' UTR sequence to overexpress individual genes within the rib operon, it was determined that the genes ribD and ribAB serve as rate-limiting enzymes in the riboflavin synthesis pathway. Constructing a 5' UTR library to regulate EGFP expression resulted in a variation range in gene expression levels exceeding 100-fold. Employing the same 5' UTR library to regulate the expression of EGFP and mCherry within the operon led to a change in the expression ratio of these two genes by over 10,000-fold. So, employing a 5' UTR library to modulate the expression of the rib operon gene and construct a synthetic rib operon resulted in a 2.09-fold increase in riboflavin production. These results indicate that the 5' UTR sequence identified and characterized in this study can serve as a versatile synthetic biology toolkit for achieving complex metabolic network reconstruction. This toolkit can facilitate the fine-tuning of gene expression to produce target products.

Large-scale duplication events underpin population-level flexibility in tRNA gene copy number in Pseudomonas fluorescens SBW25

The complement of tRNA genes within a genome is typically considered to be a (relatively) stable characteristic of an organism. Here, we demonstrate that bacterial tRNA gene set composition can be more flexible than previously appreciated, particularly regarding tRNA gene copy number. We report the high-rate occurrence of spontaneous, large-scale, tandem duplication events in laboratory populations of the bacterium Pseudomonas fluorescens SBW25. The identified duplications are up to ∼1 Mb in size (∼15% of the wildtype genome) and are predicted to change the copy number of up to 917 genes, including several tRNA genes. The observed duplications are inherently unstable: they occur, and are subsequently lost, at extremely high rates. We propose that this unusually plastic type of mutation provides a mechanism by which tRNA gene set diversity can be rapidly generated, while simultaneously preserving the underlying tRNA gene set in the absence of continued selection. That is, if a tRNA set variant provides no fitness advantage, then high-rate segregation of the duplication ensures the maintenance of the original tRNA gene set. However, if a tRNA gene set variant is beneficial, the underlying duplication fragment(s) may persist for longer and provide raw material for further, more stable, evolutionary change.

Translation efficiency driven by CNOT3 subunit of the CCR4-NOT complex promotes leukemogenesis

Protein synthesis is frequently deregulated during tumorigenesis. However, the precise contexts of selective translational control and the regulators of such mechanisms in cancer is poorly understood. Here, we uncovered CNOT3, a subunit of the CCR4-NOT complex, as an essential modulator of translation in myeloid leukemia. Elevated CNOT3 expression correlates with unfavorable outcomes in patients with acute myeloid leukemia (AML). CNOT3 depletion induces differentiation and apoptosis and delayed leukemogenesis. Transcriptomic and proteomic profiling uncovers c-MYC as a critical downstream target which is translationally regulated by CNOT3. Global analysis of mRNA features demonstrates that CNOT3 selectively influences expression of target genes in a codon usage dependent manner. Furthermore, CNOT3 associates with the protein network largely consisting of ribosomal proteins and translation elongation factors in leukemia cells. Overall, our work elicits the direct requirement for translation efficiency in tumorigenesis and propose targeting the post-transcriptional circuitry via CNOT3 as a therapeutic vulnerability in AML.

Resource allocation in mammalian systems

Cells execute biological functions to support phenotypes such as growth, migration, and secretion. Complementarily, each function of a cell has resource costs that constrain phenotype. Resource allocation by a cell allows it to manage these costs and optimize their phenotypes. In fact, the management of resource constraints (e.g., nutrient availability, bioenergetic capacity, and macromolecular machinery production) shape activity and ultimately impact phenotype. In mammalian systems, quantification of resource allocation provides important insights into higher-order multicellular functions; it shapes intercellular interactions and relays environmental cues for tissues to coordinate individual cells to overcome resource constraints and achieve population-level behavior. Furthermore, these constraints, objectives, and phenotypes are context-dependent, with cells adapting their behavior according to their microenvironment, resulting in distinct steady-states. This review will highlight the biological insights gained from probing resource allocation in mammalian cells and tissues.

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.

Neuronal Stem Cells from Late-Onset Alzheimer Patients Show Altered Regulation of Sirtuin 1 Depending on Apolipoprotein E Indicating Disturbed Stem Cell Plasticity

Late-onset Alzheimer's disease (AD) is a complex multifactorial disease. The greatest known risk factor for late-onset AD is the E4 allele of the apolipoprotein E (APOE), while increasing age is the greatest known non-genetic risk factor. The cell type-specific functions of neural stem cells (NSCs), in particular their stem cell plasticity, remain poorly explored in the context of AD pathology. Here, we describe a new model that employs late-onset AD patient-derived induced pluripotent stem cells (iPSCs) to generate NSCs and to examine the role played by APOE4 in the expression of aging markers such as sirtuin 1 (SIRT1) in comparison to healthy subjects carrying APOE3. The effect of aging was investigated by using iPSC-derived NSCs from old age subjects as healthy matched controls. Transcript and protein analysis revealed that genes were expressed differently in NSCs from late-onset AD patients, e.g., exhibiting reduced autophagy-related protein 7 (ATG7), phosphatase and tensin homolog (PTEN), and fibroblast growth factor 2 (FGF2). Since SIRT1 expression differed between APOE3 and APOE4 NSCs, the suppression of APOE function in NSCs also repressed the expression of SIRT1. However, the forced expression of APOE3 by plasmids did not recover differently expressed genes. The altered aging markers indicate decreased plasticity of NSCs. Our study provides a suitable in vitro model to investigate changes in human NSCs associated with aging, APOE4, and late-onset AD.

Engineering Saccharomyces cerevisiae for efficient production of recombinant proteins

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

Making sense of mRNA translational "noise"

The importance of translation fidelity has been apparent since the discovery of genetic code. It is commonly believed that translation deviating from the main coding region is to be avoided at all times inside cells. However, ribosome profiling and mass spectrometry have revealed pervasive noncanonical translation. Both the scope and origin of translational "noise" are just beginning to be appreciated. Although largely overlooked, those translational "noises" are associated with a wide range of cellular functions, such as producing unannotated protein products. Furthermore, the dynamic nature of translational "noise" is responsive to stress conditions, highlighting the beneficial effect of translational "noise" in stress adaptation. Mechanistic investigation of translational "noise" will provide better insight into the mechanisms of translational regulation. Ultimately, they are not "noise" at all but represent a signature of cellular activities under pathophysiological conditions. Deciphering translational "noise" holds the therapeutic and diagnostic potential in a wide spectrum of human diseases.

Vo N, Nguyen BT, Huynh ST, Nguyen HD. Analyzing the correlation between protein expression and sequence-related features of mRNA and protein in Escherichia coli K-12 MG1655 model

It was necessary to have a tool that could predict the amount of protein and optimize the gene sequences to produce recombinant proteins efficiently. The Transim model published by Tuller et al. in 2018 can calculate the translation rate in E. coli using features on the mRNA sequence, achieving a Spearman correlation with the amount of protein per mRNA of 0.36 when tested on the dataset of operons' first genes in E. coli K-12 MG1655 genome. However, this Spearman correlation was not high, and the model did not fully consider the features of mRNA and protein sequences. Therefore, to enhance the prediction capability, our study firstly tried expanding the testing dataset, adding genes inside the operon, and using the microarray of the mRNA expression data set, thereby helping to improve the correlation of translation rate with the amount of protein with more than 0.42. Next, the applicability of 6 traditional machine learning models to calculate a "new translation rate" was examined using initiation rate and elongation rate as inputs. The result showed that the SVR algorithm had the most correlated new translation rates, with Spearman correlation improving to R = 0.6699 with protein level output and to R = 0.6536 with protein level per mRNA. Finally, the study investigated the degree of improvement when combining more features with the new translation rates. The results showed that the model's predictive ability to produce a protein per mRNA reached R = 0.6660 when using six features, while the correlation of this model's final translation rate to protein level was up to R = 0.6729. This demonstrated the model's capability to predict protein expression of a gene, rather than being limited to predicting expression by an mRNA and showed the model's potential for development into gene expression predicting tools.

A Comprehensive Exploration of Bioluminescence Systems, Mechanisms, and Advanced Assays for Versatile Applications

Bioluminescence has been a fascinating natural phenomenon of light emission from living creatures. It happens when the enzyme luciferase facilitates the oxidation of luciferin, resulting in the creation of an excited-state species that emits light. Although there are many bioluminescent systems, few have been identified. D-luciferin-dependent systems, coelenterazine-dependent systems, Cypridina luciferin-based systems, tetrapyrrole-based luciferins, bacterial bioluminescent systems, and fungal bioluminescent systems are natural bioluminescent systems. Since different bioluminescence systems, such as various combinations of luciferin-luciferase pair reactions, have different light emission wavelengths, they benefit industrial applications such as drug discovery, protein-protein interactions, in vivo imaging in small animals, and controlling neurons. Due to the expression of luciferase and easy permeation of luciferin into most cells and tissues, bioluminescence assays are applied nowadays with modern technologies in most cell and tissue types. It is a versatile technique in a variety of biomedical research. Furthermore, there are some investigated blue-sky research projects, such as bioluminescent plants and lamps. This review article is mainly based on the theory of diverse bioluminescence systems and their past, present, and future applications.

Short-Term Effect of Rose Bengal Photodynamic Therapy (RB-PDT) on Collagen I, Collagen V, NF-κB, LOX, TGF-β and IL-6 Expression of Human Corneal Fibroblasts, In Vitro

PURPOSE

To investigate collagen I, collagen V, nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), lysyl oxidase (LOX), transforming growth factor β1 (TGF-β1) and interleukin-6 (IL-6) expression in healthy and keratoconus human corneal fibroblasts (HCFs and KC-HCFs), 24 h after Rose Bengal photodynamic therapy (RB-PDT).

METHODS

HCFs were isolated from healthy human corneal donors (n = 5) and KC-HCFs from elective penetrating keratoplasties (n = 5). Both cell cultures underwent RB-PDT (0.001% RB concentration, 0.17 J/cm2 fluence) and 24 h later collagen I, collagen V, NF-κB, LOX, TGF-β1 and IL-6 mRNA and protein expression have been determined using qPCR and Western blot, IL-6 concentration in the cell culture supernatant by ELISA.

RESULTS

TGF-β1 mRNA expression was significantly lower (p = 0.02) and IL-6 mRNA expression was significantly higher in RB-PDT treated HCFs (p = 0.01), than in HCF controls. COL1A1, COL5A1 and TGF-β1 mRNA expression was significantly lower (p = 0.04; p = 0.02 and p = 0.003) and IL-6 mRNA expression was significantly higher (p = 0.02) in treated KC-HCFs, than in KC-HCF controls. TGF-β1 protein expression in treated HCFs was significantly higher than in HCF controls (p = 0.04). IL-6 protein concentration in the HCF and KC-HCF culture supernatant after RB-PDT was significantly higher than in controls (p = 0.02; p = 0.01). No other analyzed mRNA and protein expression differed significantly between the RB-PDT treated and untreated groups.

CONCLUSIONS

Our study demonstrates that RB-PDT reduces collagen I, collagen V and TGF-β1 mRNA expression, while increasing IL-6 mRNA and protein expression in KC-HCFs. In HCFs, RB-PDT increases TGF-β1 and IL-6 protein level after 24 h.

Production and secretion of recombinant spider silk in Bacillus megaterium

BACKGROUND

Silk proteins have emerged as versatile biomaterials with unique chemical and physical properties, making them appealing for various applications. Among them, spider silk, known for its exceptional mechanical strength, has attracted considerable attention. Recombinant production of spider silk represents the most promising route towards its scaled production; however, challenges persist within the upstream optimization of host organisms, including toxicity and low yields. The high cost of downstream cell lysis and protein purification is an additional barrier preventing the widespread production and use of spider silk proteins. Gram-positive bacteria represent an attractive, but underexplored, microbial chassis that may enable a reduction in the cost and difficulty of recombinant silk production through attributes that include, superior secretory capabilities, frequent GRAS status, and previously established use in industry.

RESULTS

In this study, we explore the potential of gram-positive hosts by engineering the first production and secretion of recombinant spider silk in the Bacillus genus. Using an industrially relevant B. megaterium host, it was found that the Sec secretion pathway enables secretory production of silk, however, the choice of signal sequence plays a vital role in successful secretion. Attempts at increasing secreted titers revealed that multiple translation initiation sites in tandem do not significantly impact silk production levels, contrary to previous findings for other gram-positive hosts and recombinant proteins. Notwithstanding, targeted amino acid supplementation in minimal media was found to increase production by 135% relative to both rich media and unaltered minimal media, yielding secretory titers of approximately 100 mg/L in flask cultures.

CONCLUSION

It is hypothesized that the supplementation strategy addressed metabolic bottlenecks, specifically depletion of ATP and NADPH within the central metabolism, that were previously observed for an E. coli host producing the same recombinant silk construct. Furthermore, this study supports the hypothesis that secretion mitigates the toxicity of the produced silk protein on the host organism and enhances host performance in glucose-based minimal media. While promising, future research is warranted to understand metabolic changes more precisely in the Bacillus host system in response to silk production, optimize signal sequences and promoter strengths, investigate the mechanisms behind the effect of tandem translation initiation sites, and evaluate the performance of this system within a bioreactor.

Antibody production relies on the tRNA inosine wobble modification to meet biased codon demand

Antibodies are produced at high rates to provide immunoprotection, which puts pressure on the B cell translational machinery. Here, we identified a pattern of codon usage conserved across antibody genes. One feature thereof is the hyperutilization of codons that lack genome-encoded Watson-Crick transfer RNAs (tRNAs), instead relying on the posttranscriptional tRNA modification inosine (I34), which expands the decoding capacity of specific tRNAs through wobbling. Antibody-secreting cells had increased I34 levels and were more reliant on I34 for protein production than naïve B cells. Furthermore, antibody I34-dependent codon usage may influence B cell passage through regulatory checkpoints. Our work elucidates the interface between the tRNA pool and protein production in the immune system and has implications for the design and selection of antibodies for vaccines and therapeutics.

Novel Plastid Genome Characteristics in Fugacium kawagutii and the Trend of Accelerated Evolution of Plastid Proteins in Dinoflagellates

Typical (peridinin-containing) dinoflagellates possess plastid genomes composed of small plasmids named "minicircles". Despite the ecological importance of dinoflagellate photosynthesis in corals and marine ecosystems, the structural characteristics, replication dynamics, and evolutionary forcing of dinoflagellate plastid genomes remain poorly understood. Here, we sequenced the plastid genome of the symbiodiniacean species Fugacium kawagutii and conducted comparative analyses. We identified psbT-coding minicircles, features previously not found in Symbiodiniaceae. The copy number of F. kawagutii minicircles showed a strong diel dynamics, changing between 3.89 and 34.3 copies/cell and peaking in mid-light period. We found that F. kawagutii minicircles are the shortest among all dinoflagellates examined to date. Besides, the core regions of the minicircles are highly conserved within genus in Symbiodiniaceae. Furthermore, the codon usage bias of the plastid genomes in Heterocapsaceae, Amphidiniaceae, and Prorocentraceae species are greatly influenced by selection pressure, and in Pyrocystaceae, Symbiodiniaceae, Peridiniaceae, and Ceratiaceae species are influenced by both natural selection pressure and mutation pressure, indicating a family-level distinction in codon usage evolution in dinoflagellates. Phylogenetic analysis using 12 plastid-encoded proteins and five nucleus-encoded plastid proteins revealed accelerated evolution trend of both plastid- and nucleus-encoded plastid proteins in peridinin- and fucoxanthin-dinoflagellate plastids compared to plastid proteins of nondinoflagellate algae. These findings shed new light on the structure and evolution of plastid genomes in dinoflagellates, which will facilitate further studies on the evolutionary forcing and function of the diverse dinoflagellate plastids. The accelerated evolution documented here suggests plastid-encoded sequences are potentially useful for resolving closely related dinoflagellates.

Systematic analysis of the codon usage patterns of African swine fever virus genome coding sequences reveals its host adaptation phenotype

African swine fever (ASF) is a severe haemorrhagic disease caused by the African swine fever virus (ASFV), transmitted by ticks, resulting in high mortality among domestic pigs and wild boars. The global spread of ASFV poses significant economic threats to the swine industry. This study employs diverse analytical methods to explore ASFV's evolution and host adaptation, focusing on codon usage patterns and associated factors. Utilizing phylogenetic analysis methods including neighbour-joining and maximum-likelihood, 64 ASFV strains were categorized into four clades. Codon usage bias (CUB) is modest in ASFV coding sequences. This research identifies multiple factors - such as nucleotide composition, mutational pressures, natural selection and geographical diversity - contributing to the formation of CUB in ASFV. Analysis of relative synonymous codon usage reveals CUB variations within clades and among ASFVs and their hosts. Both Codon Adaptation Index and Similarity Index analyses confirm that ASFV strains are highly adapted to soft ticks (Ornithodoros moubata) but less so to domestic pigs, which could be a result of the long-term co-evolution of ASFV with ticks. This study sheds light on the factors influencing ASFV's codon usage and fitness dynamics, enriching our understanding of its evolution, adaptation and host interactions.

Decoding stoichiometric protein synthesis in E. coli through translation rate parameters

E. coli is one of the most widely used organisms for understanding the principles of cellular and molecular genetics. However, we are yet to understand the origin of several experimental observations related to the regulation of gene expression in E. coli. One of the prominent examples in this context is the proportional synthesis in multiprotein complexes where all of their obligate subunits are produced in proportion to their stoichiometry. In this work, by combining the next-generation sequencing data with the stochastic simulations of protein synthesis, we explain the origin of proportional protein synthesis in multicomponent complexes. We find that the estimated initiation rates for the translation of all subunits in those complexes are proportional to their stoichiometry. This constraint on protein synthesis kinetics enforces proportional protein synthesis without requiring any feedback mechanism. We also find that the translation initiation rates in E. coli are influenced by the coding sequence length and the enrichment of A and C nucleotides near the start codon. Thus, this study rationalizes the role of conserved and nonrandom features of genes in regulating the translation kinetics and unravels a key principle of the regulation of protein synthesis.

A small stretch of poor codon usage at the beginning of dengue virus open reading frame may act as a translational checkpoint

OBJECTIVE

Rare codons were previously shown to be enriched at the beginning of the dengue virus (DENV) open reading frame. However, the role of rare codons in regulating translation efficiency and replication of DENV remains unclear. The present study aims to clarify the significance of rare codon usage at the beginning of DENV transcripts using the codon adaptation index (CAI).

METHODOLOGY

CAIs of the whole starting regions of DENV transcripts as well as 18-codon sliding windows of the regions were analyzed.

RESULTS

One of the intriguing findings is that those rare codons do not typically result in uniformly low CAI in the starting region with rare codons. However, it shows a notable local drop in CAI around the 50th codon in all dengue serotypes. This suggests that there may be a translational checkpoint at this site and that the rare codon usage upstream to this checkpoint may not be related to translational control.

Molecular bases for strong phenotypic effects of single synonymous codon substitutions in the E. coli ccdB toxin gene

BACKGROUND

Single synonymous codon mutations typically have only minor or no effects on gene function. Here, we estimate the effects on cell growth of ~ 200 single synonymous codon mutations in an operonic context by mutating almost all positions of ccdB, the 101-residue long cytotoxin of the ccdAB Toxin-Antitoxin (TA) operon to most degenerate codons. Phenotypes were assayed by transforming the mutant library into CcdB sensitive and resistant E. coli strains, isolating plasmid pools, and subjecting them to deep sequencing. Since autoregulation is a hallmark of TA operons, phenotypes obtained for ccdB synonymous mutants after transformation in a RelE toxin reporter strain followed by deep sequencing provided information on the amount of CcdAB complex formed.

RESULTS

Synonymous mutations in the N-terminal region involved in translation initiation showed the strongest non-neutral phenotypic effects. We observe an interplay of numerous factors, namely, location of the codon, codon usage, t-RNA abundance, formation of anti-Shine Dalgarno sequences, predicted transcript secondary structure, and evolutionary conservation in determining phenotypic effects of ccdB synonymous mutations. Incorporation of an N-terminal, hyperactive synonymous mutation, in the background of the single synonymous codon mutant library sufficiently increased translation initiation, such that mutational effects on either folding or termination of translation became more apparent. Introduction of putative pause sites not only affects the translational rate, but might also alter the folding kinetics of the protein in vivo.

CONCLUSION

In summary, the study provides novel insights into diverse mechanisms by which synonymous mutations modulate gene function. This information is useful in optimizing heterologous gene expression in E. coli and understanding the molecular bases for alteration in gene expression that arise due to synonymous mutations.

Effect of mRNA/tRNA mutations on translation speed: Implications for human diseases

Recent discoveries establish tRNAs as central regulators of mRNA translation dynamics, and therefore cotranslational folding and function of the encoded protein. The tRNA pool, whose composition and abundance change in a cell- and tissue-dependent manner, is the main factor which determines mRNA translation velocity. In this review, we discuss a group of pathogenic mutations, in the coding sequences of either protein-coding genes or in tRNA genes, that alter mRNA translation dynamics. We also summarize advances in tRNA biology that have uncovered how variations in tRNA levels on account of genetic mutations affect protein folding and function, and thereby contribute to phenotypic diversity in clinical manifestations.

Orb2 enables rare-codon-enriched mRNA expression during Drosophila neuron differentiation

Regulation of codon optimality is an increasingly appreciated layer of cell- and tissue-specific protein expression control. Here, we use codon-modified reporters to show that differentiation of Drosophila neural stem cells into neurons enables protein expression from rare-codon-enriched genes. From a candidate screen, we identify the cytoplasmic polyadenylation element binding (CPEB) protein Orb2 as a positive regulator of rare-codon-dependent expression in neurons. Using RNA sequencing, we reveal that Orb2-upregulated mRNAs in the brain with abundant Orb2 binding sites have a rare-codon bias. From these Orb2-regulated mRNAs, we demonstrate that rare-codon enrichment is important for expression control and social behavior function of the metabotropic glutamate receptor (mGluR). Our findings reveal a molecular mechanism by which neural stem cell differentiation shifts genetic code regulation to enable critical mRNA and protein expression.

Homeostatic regulation of ribosomal proteins by ubiquitin-independent cotranslational degradation

Ribosomes are the workplace for protein biosynthesis. Protein production required for normal cell function is tightly linked to ribosome abundance. It is well known that ribosomal genes are actively transcribed and ribosomal messenger RNAs (mRNAs) are rapidly translated, and yet ribosomal proteins have relatively long half-lives. These observations raise questions as to how homeostasis of ribosomal proteins is controlled. Here, we show that ribosomal proteins, while posttranslationally stable, are subject to high-level cotranslational protein degradation (CTPD) except for those synthesized as ubiquitin (Ub) fusion precursors. The N-terminal Ub moiety protects fused ribosomal proteins from CTPD. We further demonstrate that cotranslational folding efficiency and expression level are two critical factors determining CTPD of ribosomal proteins. Different from canonical posttranslational degradation, we found that CTPD of all the ribosomal proteins tested in this study does not require prior ubiquitylation. This work provides insights into the regulation of ribosomal protein homeostasis and furthers our understanding of the mechanism and biological significance of CTPD.

Generative and predictive neural networks for the design of functional RNA molecules

RNA is a remarkably versatile molecule that has been engineered for applications in therapeutics, diagnostics, and in vivo information-processing systems. However, the complex relationship between the sequence and structural properties of an RNA molecule and its ability to perform specific functions often necessitates extensive experimental screening of candidate sequences. Here we present a generalized neural network architecture that utilizes the sequence and structure of RNA molecules (SANDSTORM) to inform functional predictions. We demonstrate that this approach achieves state-of-the-art performance across several distinct RNA prediction tasks, while learning interpretable abstractions of RNA secondary structure. We paired these predictive models with generative adversarial RNA design networks (GARDN), allowing the generative modelling of novel mRNA 5' untranslated regions and toehold switch riboregulators exhibiting a predetermined fitness. This approach enabled the design of novel toehold switches with a 43-fold increase in experimentally characterized dynamic range compared to those designed using classic thermodynamic algorithms. SANDSTORM and GARDN thus represent powerful new predictive and generative tools for the development of diagnostic and therapeutic RNA molecules with improved function.

In silico evolutionary and structural analysis of cAMP response proteins (CARPs) from Leishmania major

With unidentified chemical triggers and novel-effectors, cAMP signaling is broadly noncanonical in kinetoplastida parasites. Though novel protein kinase A regulatory subunits (PKAR) have been identified earlier, cAMP Response Proteins (CARPs) have been identified as a unique and definite cAMP effector of trypanosomatids. CARP1-CARP4 emerged as critical regulatory components of cAMP signaling pathway in Trypanosoma with evidences that CARP3 can directly interact with a flagellar adenylate cyclase (AC). CARP-mediated regulations, identified so far, reflects the mechanistic diversity of cAMP signaling. Albeit the function of the orthologous is not yet delineated, in kinetoplastids like Leishmania, presence of CARP1, 2 and 4 orthologues suggests existence of conserved effector mechanisms. Targeting CARP orthologues in Leishmania, a comprehensive evolutionary analysis of CARPs have been aimed in this study which revealed phylogenetic relationship, codon adaptation and structural heterogeneity among the orthologues, warranting functional analysis in future to explore their involvement in infectivity.

Association of SNPs in the PAI1 Gene with Disease Recurrence and Clinical Outcome in Bladder Cancer

PURPOSE

Bladder cancer (BCa) is one of the most common cancer types worldwide and is characterized by a high rate of recurrence. In previous studies, we and others have described the functional influence of plasminogen activator inhibitor-1 (PAI1) in bladder cancer development. While polymorphisms in PAI1 have been associated with increased risk and worsened prognosis in some cancers, the mutational status of PAI1 in human bladder tumors has not been well defined.

METHODS

In this study, we evaluated the mutational status of PAI1 in a series of independent cohorts, comprised of a total of 660 subjects.

RESULTS

Sequencing analyses identified two clinically relevant 3' untranslated region (UTR) single nucleotide polymorphisms (SNPs) in PAI1 (rs7242; rs1050813). Somatic SNP rs7242 was present in human BCa cohorts (overall incidence of 72%; 62% in Caucasians and 72% in Asians). In contrast, the overall incidence of germline SNP rs1050813 was 18% (39% in Caucasians and 6% in Asians). Furthermore, Caucasian patients with at least one of the described SNPs had worse recurrence-free survival and overall survival (p = 0.03 and p = 0.03, respectively). In vitro functional studies demonstrated that SNP rs7242 increased the anti-apoptotic effect of PAI1, and SNP rs1050813 was related to a loss of contact inhibition associated with cellular proliferation when compared to wild type.

CONCLUSION

Further investigation of the prevalence and potential downstream influence of these SNPs in bladder cancer is warranted.

The layered costs and benefits of translational redundancy

The rate and accuracy of translation hinges upon multiple components - including transfer RNA (tRNA) pools, tRNA modifying enzymes, and rRNA molecules - many of which are redundant in terms of gene copy number or function. It has been hypothesized that the redundancy evolves under selection, driven by its impacts on growth rate. However, we lack empirical measurements of the fitness costs and benefits of redundancy, and we have poor a understanding of how this redundancy is organized across components. We manipulated redundancy in multiple translation components of Escherichia coli by deleting 28 tRNA genes, 3 tRNA modifying systems, and 4 rRNA operons in various combinations. We find that redundancy in tRNA pools is beneficial when nutrients are plentiful and costly under nutrient limitation. This nutrient-dependent cost of redundant tRNA genes stems from upper limits to translation capacity and growth rate, and therefore varies as a function of the maximum growth rate attainable in a given nutrient niche. The loss of redundancy in rRNA genes and tRNA modifying enzymes had similar nutrient-dependent fitness consequences. Importantly, these effects are also contingent upon interactions across translation components, indicating a layered hierarchy from copy number of tRNA and rRNA genes to their expression and downstream processing. Overall, our results indicate both positive and negative selection on redundancy in translation components, depending on a species' evolutionary history with feasts and famines.

A dynamical stochastic model of yeast translation across the cell cycle

Translation is a central step in gene expression, however its quantitative and time-resolved regulation is poorly understood. We developed a discrete, stochastic model for protein translation in S. cerevisiae in a whole-transcriptome, single-cell context. A "base case" scenario representing an average cell highlights translation initiation rates as the main co-translational regulatory parameters. Codon usage bias emerges as a secondary regulatory mechanism through ribosome stalling. Demand for anticodons with low abundancy is shown to cause above-average ribosome dwelling times. Codon usage bias correlates strongly both with protein synthesis rates and elongation rates. Applying the model to a time-resolved transcriptome estimated by combining data from FISH and RNA-Seq experiments, it could be shown that increased total transcript abundance during the cell cycle decreases translation efficiency at single transcript level. Translation efficiency grouped by gene function shows highest values for ribosomal and glycolytic genes. Ribosomal proteins peak in S phase while glycolytic proteins rank highest in later cell cycle phases.

Engineered multiple translation initiation sites: a novel tool to enhance protein production in Bacillus licheniformis and other industrially relevant bacteria

Gram-positive bacteria are a nascent platform for synthetic biology and metabolic engineering that can provide new opportunities for the production of biomolecules. However, the lack of standardized methods and genetic parts is a major obstacle towards attaining the acceptance and widespread use of Gram-positive bacterial chassis for industrial bioproduction. In this study, we have engineered a novel mRNA leader sequence containing more than one ribosomal binding site (RBS) which could initiate translation from multiple sites, vastly enhancing the translation efficiency of the Gram-positive industrial strain Bacillus licheniformis. This is the first report elucidating the impact of more than one RBS to initiate translation and enhance protein output in B. licheniformis. We also explored the application of more than one RBS for both intracellular and extracellular protein production in B. licheniformis to demonstrate its efficiency, consistency and potential for biotechnological applications. Moreover, we applied these concepts for use in other industrially relevant Gram-positive bacteria, such as Bacillus subtilis and Corynebacterium glutamicum. In all, a highly efficient and robust broad-host expression element has been designed to strengthen and fine-tune the protein outputs for the use of bioproduction in microbial cell factories.