Identification of conserved slow codons that are important for protein expression and function.

ABSTRASTDue to the redundancy of the genetic code most amino acids are encoded by several 'synonymous' codons. These codons are used unevenly, and each organism demonstrates its own unique codon usage bias, where the 'preferred' codons are associated with tRNAs that are found in high concentrations. Therefore, for decades, the prevailing view had been that preferred and non-preferred codons are linked to high or slow translation rates, respectively.However, this simplified view is contrasted by the frequent failures of codon-optimization efforts and by evidence of non-preferred (i.e. 'slow') codons having specific roles important for efficient production of functional proteins. One such specific role of slower codons is the regulation of co-translational protein folding, a complex biophysical process that is very challenging to model or to measure.Here, we combined a genome-wide approach with experiments to investigate the role of slow codons in protein production and co-translational folding. We analysed homologous gene groups from divergent bacteria and identified positions of inter-species conservation of bias towards slow codons. We then generated mutants where the conserved slow codons are substituted with 'fast' ones, and experimentally studied the effects of these codon substitutions. Using cellular and biochemical approaches we find that at certain locations, slow-to-fast codon substitutions reduce protein expression, increase protein aggregation, and impair protein function.This report provides an approach for identifying functionally relevant regions with slower codons and demonstrates that such codons are important for protein expression and function.

Evolutionary selection against short nucleotide sequences in viruses and their related hosts.

Viruses are under constant evolutionary pressure to effectively interact with the host intracellular factors, while evading its immune system. Understanding how viruses co-evolve with their hosts is a fundamental topic in molecular evolution and may also aid in developing novel viral based applications such as vaccines, oncologic therapies, and anti-bacterial treatments. Here, based on a novel statistical framework and a large-scale genomic analysis of 2,625 viruses from all classes infecting 439 host organisms from all kingdoms of life, we identify short nucleotide sequences that are under-represented in the coding regions of viruses and their hosts. These sequences cannot be explained by the coding regions' amino acid content, codon, and dinucleotide frequencies. We specifically show that short homooligonucleotide and palindromic sequences tend to be under-represented in many viruses probably due to their effect on gene expression regulation and the interaction with the host immune system. In addition, we show that more sequences tend to be under-represented in dsDNA viruses than in other viral groups. Finally, we demonstrate, based on in vitro and in vivo experiments, how under-represented sequences can be used to attenuated Zika virus strains.

Generation and comparative genomics of synthetic dengue viruses.

BACKGROUND: Synthetic virology is an important multidisciplinary scientific field, with emerging applications in biotechnology and medicine, aiming at developing methods to generate and engineer synthetic viruses. In particular, many of the RNA viruses, including among others the Dengue and Zika, are widespread pathogens of significant importance to human health. The ability to design and synthesize such viruses may contribute to exploring novel approaches for developing vaccines and virus based therapies. RESULTS: Here we develop a full multidisciplinary pipeline for generation and analysis of synthetic RNA viruses and specifically apply it to Dengue virus serotype 2 (DENV-2). The major steps of the pipeline include comparative genomics of endogenous and synthetic viral strains. Specifically, we show that although the synthetic DENV-2 viruses were found to have lower nucleotide variability, their phenotype, as reflected in the study of the AG129 mouse model morbidity, RNA levels, and neutralization antibodies, is similar or even more pathogenic in comparison to the wildtype master strain. Additionally, the highly variable positions, identified in the analyzed DENV-2 population, were found to overlap with less conserved homologous positions in Zika virus and other Dengue serotypes. These results may suggest that synthetic DENV-2 could enhance virulence if the correct sequence is selected. CONCLUSIONS: The approach reported in this study can be used to generate and analyze synthetic RNA viruses both on genotypic and on phenotypic level. It could be applied for understanding the functionality and the fitness effects of any set of mutations in viral RNA and for editing RNA viruses for various target applications.

Universal evolutionary selection for high dimensional silent patterns of information hidden in the redundancy of viral genetic code.

Motivation: Understanding how viruses co-evolve with their hosts and adapt various genomic level strategies in order to ensure their fitness may have essential implications in unveiling the secrets of viral evolution, and in developing new vaccines and therapeutic approaches. Here, based on a novel genomic analysis of 2625 different viruses and 439 corresponding host organisms, we provide evidence of universal evolutionary selection for high dimensional 'silent' patterns of information hidden in the redundancy of viral genetic code. Results: Our model suggests that long substrings of nucleotides in the coding regions of viruses from all classes, often also repeat in the corresponding viral hosts from all domains of life. Selection for these substrings cannot be explained only by such phenomena as codon usage bias, horizontal gene transfer and the encoded proteins. Genes encoding structural proteins responsible for building the core of the viral particles were found to include more host-repeating substrings, and these substrings tend to appear in the middle parts of the viral coding regions. In addition, in human viruses these substrings tend to be enriched with motives related to transcription factors and RNA binding proteins. The host-repeating substrings are possibly related to the evolutionary pressure on the viruses to effectively interact with host's intracellular factors and to efficiently escape from the host's immune system. Supplementary information: Supplementary data are available at Bioinformatics online.

A code for transcription elongation speed.

The two major steps of gene expression are transcription and translation. While hundreds of studies regarding the effect of sequence features on the translation elongation process have been published, very few connect sequence features to the transcription elongation rate. We suggest, for the first time, that short transcript sub-sequences have a typical effect on RNA polymerase (RNAP) speed: we show that nucleotide 5-mers tend to have typical RNAP speed (or transcription rate), which is consistent along different parts of genes and among different groups of genes with high correlation. We also demonstrate that relative RNAP speed correlates with mRNA levels of endogenous and heterologous genes. Furthermore, we show that the estimated transcription and translation elongation rates correlate in endogenous genes. Finally, we demonstrate that our results are consistent for different high resolution experimental measurements of RNAP densities. These results suggest for the first time that transcription elongation is partly encoded in the transcript, affected by the codon-usage, and optimized by evolution with a significant effect on gene expression and organismal fitness.

Unsupervised detection of regulatory gene expression information in different genomic regions enables gene expression ranking.

BACKGROUND: The regulation of all gene expression steps (e.g., Transcription, RNA processing, Translation, and mRNA Degradation) is known to be primarily encoded in different parts of genes and in genomic regions in proximity to genes (e.g., promoters, untranslated regions, coding regions, introns, etc.). However, the entire gene expression codes and the genomic regions where they are encoded are still unknown. RESULTS: Here, we employ an unsupervised approach to estimate the concentration of gene expression codes in different non-coding parts of genes and transcripts, such as introns and untranslated regions, focusing on three model organisms (Escherichia coli, Saccharomyces cerevisiae, and Schizosaccharomyces pombe). Our analyses support the conjecture that regions adjacent to the beginning and end of ORFs and the beginning and end of introns tend to include higher concentration of gene expression information relatively to regions further away. In addition, we report the exact regions with elevated concentration of gene expression codes. Furthermore, we demonstrate that the concentration of these codes in different genetic regions is correlated with the expression levels of the corresponding genes, and with splicing efficiency measurements and meiotic stage gene expression measurements in S. cerevisiae. CONCLUSION: We suggest that these discoveries improve our understanding of gene expression regulation and evolution; they can also be used for developing improved models of genome/gene evolution and for engineering gene expression in various biotechnological and synthetic biology applications.

Selection for reduced translation costs at the intronic 5' end in fungi.

It is generally believed that introns are not translated; therefore, the potential intronic features that may be related to the translation step (occurring after splicing) have yet to be thoroughly studied. Here, focusing on four fungi, we performed for the first time a comprehensive study aimed at characterizing how translation efficiency is encoded in introns and affects their evolution. By analysing their intronome we provide evidence of selection for STOP codons close to the intronic 5' end, and show that the beginning of introns are selected for significantly high translation, presumably to reduce translation and metabolic costs in cases of non-spliced introns. Ribosomal profiling data analysis in Saccharomyces cerevisiae supports the conjecture that in this organism intron retention frequently occurs, introns are partially translated, and their translation efficiency affects organismal fitness. We show that the reported results are more significant in highly translated and highly spliced genes, but are not associated only with genes with a specific function. We also discuss the potential relation of the reported signals to efficient nonsense-mediated decay due to splicing errors. These new discoveries are supported by population-genetics considerations. In addition, they are contributory steps towards a broader understanding of intron evolution and the effect of silent mutations on gene expression and organismal fitness.

Nucleotide sequence composition adjacent to intronic splice sites improves splicing efficiency via its effect on pre-mRNA local folding in fungi.

RNA splicing is the central process of intron removal in eukaryotes known to regulate various cellular functions such as growth, development, and response to external signals. The canonical sequences indicating the splicing sites needed for intronic boundary recognition are well known. However, the roles and evolution of the local folding of intronic and exonic sequence features adjacent to splice sites has yet to be thoroughly studied. Here, focusing on four fungi (Saccharomyces cerevisiae, Schizosaccharomyces pombe, Aspergillus nidulans, and Candida albicans), we performed for the first time a comprehensive high-resolution study aimed at characterizing the encoding of intronic splicing efficiency in pre-mRNA transcripts and its effect on intron evolution. Our analysis supports the conjecture that pre-mRNA local folding strength at intronic boundaries is under selective pressure, as it significantly affects splicing efficiency. Specifically, we show that in the immediate region of 12-30 nucleotides (nt) surrounding the intronic donor site there is a preference for weak pre-mRNA folding; similarly, in the region of 15-33 nt surrounding the acceptor and branch sites there is a preference for weak pre-mRNA folding. We also show that in most cases there is a preference for strong pre-mRNA folding further away from intronic splice sites. In addition, we demonstrate that these signals are not associated with gene-specific functions, and they correlate with splicing efficiency measurements (r = 0.77, P = 2.98 × 10(-21)) and with expression levels of the corresponding genes (P = 1.24 × 10(-19)). We suggest that pre-mRNA folding strength in the above-mentioned regions has a direct effect on splicing efficiency by improving the recognition of intronic boundaries. These new discoveries are contributory steps toward a broader understanding of splicing regulation and intronic/transcript evolution.

Detection of abnormal cardiac activity using principal component analysis--a theoretical study.

Electrogram-guided ablation has been recently developed for allowing better detection and localization of abnormal atrial activity that may be the source of arrhythmogeneity. Nevertheless, no clear indication for the benefit of using electrograms guided ablation over empirical ablation was established thus far, and there is a clear need of improving the localization of cardiac arrhythmogenic targets for ablation. In this paper, we propose a new approach for detection and localization of irregular cardiac activity during ablation procedures that is based on dimension reduction algorithms and principal component analysis (PCA). Using an 8×8 electrode array, our method produces manifolds that allow easy visualization and detection of possible arrhythmogenic ablation targets characterized by irregular conduction. We employ mathematical modeling and computer simulations to demonstrate the feasibility of the new approach for two well established arrhythmogenic sources for irregular conduction--spiral waves and patchy fibrosis. Our results show that the PCA method can differentiate between focal ectopic activity and spiral wave activity, as these two types of activity produce substantially different manifold shapes. Moreover, the technique allows the detection of spiral wave cores and their general meandering and drifting pattern. Fibrotic patches larger than 2 mm(2) could also be visualized using the PCA method, both for quiescent atrial tissue and for tissue exhibiting spiral wave activity. We envision that this method, contingent to further numerical and experimental validation studies in more complex, realistic geometrical configurations and with clinical data, can improve existing atrial ablation mapping capabilities, thus increasing success rates and optimizing arrhythmia management.

Accurate, model-based tuning of synthetic gene expression using introns in S. cerevisiae.

Introns are key regulators of eukaryotic gene expression and present a potentially powerful tool for the design of synthetic eukaryotic gene expression systems. However, intronic control over gene expression is governed by a multitude of complex, incompletely understood, regulatory mechanisms. Despite this lack of detailed mechanistic understanding, here we show how a relatively simple model enables accurate and predictable tuning of synthetic gene expression system in yeast using several predictive intron features such as transcript folding and sequence motifs. Using only natural Saccharomyces cerevisiae introns as regulators, we demonstrate fine and accurate control over gene expression spanning a 100 fold expression range. These results broaden the engineering toolbox of synthetic gene expression systems and provide a framework in which precise and robust tuning of gene expression is accomplished.

Reconstruction of retrospective cardiac activity--numerical study in a single cell and in a linear strand.

Although computational modeling of the prospective electrical activity in the cardiac tissue is well established and robust, the retrospective extrapolation of this activity has not been explored to date. Here, we establish an algorithm for the backward-in-time extrapolation of electrical activity from measurements taken in the present. Using minimal human cardiac kinetic models and a modified Newton-Raphson algorithm, we demonstrate the feasibility of past activity reconstruction in a single cell and in a linear strand. In a single cell, reconstruction of state variables' shape, the action potential morphology, and the time of stimulation was successful for up to 1300 ms poststimulation and for data with signal-to-noise ratio levels higher than 40 dB. For linear strands, the action potential morphology was reconstructed for 500 ms poststimulation, and the reconstructed conduction velocity remained unaffected for signal-to-noise ratio levels higher than 50 dB. Moreover, tissue restitution properties due to various pacing rates were successfully reconstructed by the backward-in-time algorithm. These preliminary results demonstrate that past cardiac activity may be reconstructed from measurements in the present. We envision that this methodology could be implemented in future clinical applications, for example to trace the location and timing of ectopic foci during ablation procedures.