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Clusters of codons pairing to low-abundance tRNAs synchronize the translation with co-translational folding of single domains in multidomain proteins. Although proven with some examples, the impact of the ribosomal speed on the folding and solubility on a global, cell-wide level remains elusive. Here we show that upregulation of three low-abundance tRNAs in Escherichia coil increased the aggregation propensity of several cellular proteins as a result of an accelerated elongation rate. Intriguingly, alterations in the concentration of the natural tRNA pool compromised the solubility of various chaperones consequently rendering the solubility of some chaperone-dependent proteins.
Preferential accumulation of mutant proteins in the nucleus has been suggested to be the molecular culprit that confers cellular toxicity in the neurodegenerative disorders caused by polyglutamine (polyQ) expansion. Here, we use dynamic imaging approaches, orthogonal cross-seeding, and composition analysis to examine the dynamics and structure of nuclear and cytoplasmic inclusions of atrophin-1, implicated in dentatorubropallidoluysian atrophy, a polyQ-based disease with complex clinical features. Our results reveal a large heterogeneity in the dynamics of the nuclear inclusions compared with the compact and immobile cytoplasmic aggregates. At least two types of inclusions of expanded atrophin-1 with different mobility of the molecular species and ability to exchange with the surrounding monomer pool coexist in the nucleus. Intriguingly, the enrichment of nuclear inclusions with slow dynamics parallels changes in the aggregate core architecture that are dominated by the polyQ stretch. We propose that the observed complexity in the dynamics of the nuclear inclusions provides a molecular explanation for the enhanced cellular toxicity of the nuclear aggregates in polyQ-based neurodegeneration.
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.