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The translation of genetic information according to the sequence of the mRNA template occurs with high accuracy and fidelity. Critical events in each single step of translation are selection of transfer RNA (tRNA), codon reading and tRNA-regeneration for a new cycle. We developed a model that accurately describes the dynamics of single elongation steps, thus providing a systematic insight into the sensitivity of the mRNA translation rate to dynamic environmental conditions. Alterations in the concentration of the aminoacylated tRNA can transiently stall the ribosomes during translation which results, as suggested by the model, in two outcomes: either stress-induced change in the tRNA availability triggers the premature termination of the translation and ribosomal dissociation, or extensive demand for one tRNA species results in a competition between frameshift to an aberrant open-reading frame and ribosomal drop-off. Using the bacterial Escherichia coli system, we experimentally draw parallels between these two possible mechanisms.
A simple measure for the efficiency of protein synthesis by ribosomes is provided by the steady state amount of protein per messenger RNA (mRNA), the so-called translational ratio, which is proportional to the translation rate. Taking the degradation of mRNA into account, we show theoretically that both the translation rate and the translational ratio decrease with increasing mRNA length, in agreement with available experimental data for the prokaryote Escherichia coli. We also show that, compared to prokaryotes, mRNA degradation in eukaryotes leads to a less rapid decrease of the translational ratio. This finding is consistent with the fact that, compared to prokaryotes, eukaryotes tend to have longer proteins.
The most crucial step in data processing from high-throughput sequencing applications is the accurate and sensitive alignment of the sequencing reads to reference genomes or transcriptomes. The accurate detection of insertions and deletions (indels) and errors introduced by the sequencing platform or by misreading of modified nucleotides is essential for the quantitative processing of the RNA-based sequencing (RNA-Seq) datasets and for the identification of genetic variations and modification patterns. We developed a new, fast and accurate algorithm for nucleic acid sequence analysis, FANSe, with adjustable mismatch allowance settings and ability to handle indels to accurately and quantitatively map millions of reads to small or large reference genomes. It is a seed-based algorithm which uses the whole read information for mapping and high sensitivity and low ambiguity are achieved by using short and non-overlapping reads. Furthermore, FANSe uses hotspot score to prioritize the processing of highly possible matches and implements modified Smith-Watermann refinement with reduced scoring matrix to accelerate the calculation without compromising its sensitivity. The FANSe algorithm stably processes datasets from various sequencing platforms, masked or unmasked and small or large genomes. It shows a remarkable coverage of low-abundance mRNAs which is important for quantitative processing of RNA-Seq datasets.
Environmental stress is detrimental to cell viability and requires an adequate reprogramming of cellular activities to maximize cell survival. We present a global analysis of the response of Escherichia coli to acute heat and osmotic stress. We combine deep sequencing of total mRNA and ribosome-protected fragments to provide a genome-wide map of the stress response at transcriptional and translational levels. For each type of stress, we observe a unique subset of genes that shape the stress-specific response. Upon temperature upshift, mRNAs with reduced folding stability up-and downstream of the start codon, and thus with more accessible initiation regions, are translationally favoured. Conversely, osmotic upshift causes a global reduction of highly translated transcripts with high copy numbers, allowing reallocation of translation resources to not degraded and newly synthesized mRNAs.