Synonymous codon substitutions modulate transcription and translation of a divergent upstream gene by modulating antisense RNA production.

Synonymous codons were originally viewed as interchangeable, with no phenotypic consequences. However, substantial evidence has now demonstrated that synonymous substitutions can perturb a variety of gene expression and protein homeostasis mechanisms, including translational efficiency, translational fidelity, and cotranslational folding of the encoded protein. To date, most studies of synonymous codon-derived perturbations have focused on effects within a single gene. Here, we show that synonymous codon substitutions made far within the coding sequence of Escherichia coli plasmid-encoded chloramphenicol acetyltransferase (cat) can significantly increase expression of the divergent upstream tetracycline resistance gene, tetR. In four out of nine synonymously recoded cat sequences tested, expression of the upstream tetR gene was significantly elevated due to transcription of a long antisense RNA (asRNA) originating from a transcription start site within cat. Surprisingly, transcription of this asRNA readily bypassed the native tet transcriptional repression mechanism. Even more surprisingly, accumulation of the TetR protein correlated with the level of asRNA, rather than total tetR RNA. These effects of synonymous codon substitutions on transcription and translation of a neighboring gene suggest that synonymous codon usage in bacteria may be under selection to both preserve the amino acid sequence of the encoded gene and avoid DNA sequence elements that can significantly perturb expression of neighboring genes. Avoiding such sequences may be especially important in plasmids and prokaryotic genomes, where genes and regulatory elements are often densely packed. Similar considerations may apply to the design of genetic circuits for synthetic biology applications.

Network analysis of synonymous codon usage.

MOTIVATION: Most amino acids are encoded by multiple synonymous codons, some of which are used more rarely than others. Analyses of positions of such rare codons in protein sequences revealed that rare codons can impact co-translational protein folding and that positions of some rare codons are evolutionarily conserved. Analyses of their positions in protein 3-dimensional structures, which are richer in biochemical information than sequences alone, might further explain the role of rare codons in protein folding. RESULTS: We model protein structures as networks and use network centrality to measure the structural position of an amino acid. We first validate that amino acids buried within the structural core are network-central, and those on the surface are not. Then, we study potential differences between network centralities and thus structural positions of amino acids encoded by conserved rare, non-conserved rare and commonly used codons. We find that in 84% of proteins, the three codon categories occupy significantly different structural positions. We examine protein groups showing different codon centrality trends, i.e. different relationships between structural positions of the three codon categories. We see several cases of all proteins from our data with some structural or functional property being in the same group. Also, we see a case of all proteins in some group having the same property. Our work shows that codon usage is linked to the final protein structure and thus possibly to co-translational protein folding. AVAILABILITY AND IMPLEMENTATION: https://nd.edu/∼cone/CodonUsage/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

CHARMING: Harmonizing synonymous codon usage to replicate a desired codon usage pattern.

There is a growing appreciation that synonymous codon usage, although historically regarded as phenotypically silent, can instead alter a wide range of mechanisms related to functional protein production, a term we use here to describe the net effect of transcription (mRNA synthesis), mRNA half-life, translation (protein synthesis) and the probability of a protein folding correctly to its active, functional structure. In particular, recent discoveries have highlighted the important role that sub-optimal codons can play in modifying co-translational protein folding. These results have drawn increased attention to the patterns of synonymous codon usage within coding sequences, particularly in light of the discovery that these patterns can be conserved across evolution for homologous proteins. Because synonymous codon usage differs between organisms, for heterologous gene expression it can be desirable to make synonymous codon substitutions to match the codon usage pattern from the original organism in the heterologous expression host. Here we present CHARMING (for Codon HARMonizING), a robust and versatile algorithm to design mRNA sequences for heterologous gene expression and other related codon harmonization tasks. CHARMING can be run as a downloadable Python script or via a web portal at http://www.codons.org.

Analysis of computational codon usage models and their association with translationally slow codons.

Improved computational modeling of protein translation rates, including better prediction of where translational slowdowns along an mRNA sequence may occur, is critical for understanding co-translational folding. Because codons within a synonymous codon group are translated at different rates, many computational translation models rely on analyzing synonymous codons. Some models rely on genome-wide codon usage bias (CUB), believing that globally rare and common codons are the most informative of slow and fast translation, respectively. Others use the CUB observed only in highly expressed genes, which should be under selective pressure to be translated efficiently (and whose CUB may therefore be more indicative of translation rates). No prior work has analyzed these models for their ability to predict translational slowdowns. Here, we evaluate five models for their association with slowly translated positions as denoted by two independent ribosome footprint (RFP) count experiments from S. cerevisiae, because RFP data is often considered as a "ground truth" for translation rates across mRNA sequences. We show that all five considered models strongly associate with the RFP data and therefore have potential for estimating translational slowdowns. However, we also show that there is a weak correlation between RFP counts for the same genes originating from independent experiments, even when their experimental conditions are similar. This raises concerns about the efficacy of using current RFP experimental data for estimating translation rates and highlights a potential advantage of using computational models to understand translation rates instead.

A New Look at Codon Usage and Protein Expression.

%MinMax, a model of intra-gene translational elongation rate, relies on codon usage frequencies. Historically, %MinMax has used tables that measure codon usage bias for all genes in an organism, such as those found at HIVE-CUT. In this paper, we provide evidence that codon usage bias based on all genes is insufficient to accurately measure absolute translation rate. We show that alternative "High-ϕ" codon usage tables, generated by another model (ROC-SEMPPR), are a promising alternative. By creating a hybrid model, future codon usage analyses and their applications (e.g., codon harmonization) are likely to more accurately measure the "tempo" of translation elongation. We also suggest a High-ϕ alternative to the Codon Adaptation Index (CAI), a classic metric of codon usage bias based on highly expressed genes. Significantly, our new alternative is equally well correlated with empirical data as traditional CAI without using experimentally determined expression counts as input.

%MinMax: A versatile tool for calculating and comparing synonymous codon usage and its impact on protein folding.

Most amino acids can be encoded by more than one synonymous codon, but these are rarely used with equal frequency. In many coding sequences the usage patterns of rare versus common synonymous codons is nonrandom and under selection. Moreover, synonymous substitutions that alter these patterns can have a substantial impact on the folding efficiency of the encoded protein. This has ignited broad interest in exploring synonymous codon usage patterns. For many protein chemists, biophysicists and structural biologists, the primary motivation for codon analysis is identifying and preserving usage patterns most likely to impact high-yield production of functional proteins. Here we describe the core functions and new features of %MinMax, a codon usage calculator freely available as a web-based portal and downloadable script (http://www.codons.org). %MinMax evaluates the relative usage frequencies of the synonymous codons used to encode a protein sequence of interest and compares these results to a rigorous null model. Crucially, for analyzing codon usage in common host organisms %MinMax requires only the coding sequence as input; with a user-input codon frequency table, %MinMax can be used to evaluate synonymous codon usage patterns for any coding sequence from any fully sequenced genome. %MinMax makes no assumptions regarding the impact of transfer ribonucleic acid concentrations or other molecular-level interactions on translation rates, yet its output is sufficient to predict the effects of synonymous codon substitutions on cotranslational folding mechanisms. A simple calculation included within %MinMax can be used to harmonize codon usage frequencies for heterologous gene expression.

Automated 3-D echocardiography analysis compared with manual delineations and SPECT MUGA.

A major barrier for using 3-D echocardiography for quantitative analysis of heart function in routine clinical practice is the absence of accurate and robust segmentation and tracking methods necessary to make the analysis automatic. In this paper, we present an automated three-dimensional (3-D) echocardiographic acquisition and image-processing methodology for assessment of left ventricular (LV) function. We combine global image information provided by a novel multiscale fuzzy-clustering segmentation algorithm, with local boundaries obtained with phase-based acoustic feature detection. We then use the segmentation results to fit and track the LV endocardial surface using a 3-D continuous transformation. To our knowledge, this is the first report of a completely automated method. The protocol is evaluated in a small clinical case study (nine patients). We compare ejection fractions (EFs) computed with the new approach to those obtained using the standard clinical technique, single-photon emission computed tomography multigated acquisition. Errors on six datasets were found to be within six percentage points. A further two, with poor image quality, improved upon EFs from manually delineated contours, and the last failed due to artifacts in the data. Volume-time curves were derived and the results compared to those from manual segmentation. Improvement over an earlier published version of the method is noted.

High-frequency percussive ventilation for intercontinental aeromedical evacuation.

High-frequency percussive ventilation (HFPV) has been used for the management of patients with smoke inhalation injury for more than 20 years and is considered a standard of care at many burn centers. Because the ventilator is powered by air and oxygen rather than electricity, prehospital use has been limited by large-volume medical gas requirements. Since 2003, Operations Iraqi Freedom and Enduring Freedom have created a need for long-range aeromedical transfer of service members with severe burn and inhalation injuries. Unique to these conflicts is the availability of US Air Force C-17 cargo aircraft as the primary long-distance airframe. Because C-17 aircraft have a built-in medical oxygen supply, transcontinental patient transport using HFPV has become feasible. In this study, the authors report their initial experiences with the aeromedical transportation of 33 burn patients over a combined distance of 174,145 air miles using HFPV. HFPV is safe and efficacious for transcontinental flight when used by an experienced medical transport team.

An emergency medical bag set for long-range aeromedical transportation.

The global war on terror has created the need for urgent long-range aeromedical transport of severely wounded service members over distances of several thousand miles from Afghanistan or Iraq to the United States. This need is met by specialized medical transport teams such as US Air Force Critical Care Air Transport Teams (CCATT) or by the US Army Burn Flight Team (BFT). Both teams travel with multiple bags or cases of emergency equipment, which are comprehensive but cumbersome. To avoid the need to search multiple bags for equipment or drugs when an in-flight emergency occurs, many CCATT and BFT physicians also carry a personal bag of emergency supplies for rapid access. Over the last year, we have evolved and standardized an emergency equipment bag designed to provide the supplies necessary for initial management of emergencies that occur during flight and ground transport. This or a similar emergency kit would be useful for inter or intrahospital transport of critically ill or injured civilian patients, or for physicians who respond to civil emergencies, such as members of Disaster Medical Assistance Teams.