The yeast Hsp70 chaperone Ssb interacts with ribosomes and nascent polypeptides to assist protein folding. To reveal its working principle, we determined the nascent chain-binding pattern of Ssb at near-residue resolution by in vivo selective ribosome profiling. Ssb associates broadly with cytosolic, nuclear, and hitherto unknown substrate classes of mitochondrial and endoplasmic reticulum (ER) nascent proteins, supporting its general chaperone function. Ssb engages most substrates by multiple binding-release cycles to a degenerate sequence enriched in positively charged and aromatic amino acids. Timely association with this motif upon emergence at the ribosomal tunnel exit requires ribosome-associated complex (RAC) but not nascent polypeptide-associated complex (NAC). Ribosome footprint densities along orfs reveal faster translation at times of Ssb binding, mainly imposed by biases in mRNA secondary structure, codon usage, and Ssb action. Ssb thus employs substrate-tailored dynamic nascent chain associations to coordinate co-translational protein folding, facilitate accelerated translation, and support membrane targeting of organellar proteins.

Analysis methods based on simulations and optimization have been previously developed to estimate relative translation rates from next-generation sequencing data. Translation involves molecules and chemical reactions, hence bioinformatics methods consistent with the laws of chemistry and physics are more likely to produce accurate results. Here, we derive simple equations based on chemical kinetic principles to measure the translation-initiation rate, transcriptome-wide elongation rate, and individual codon translation rates from ribosome profiling experiments. Our methods reproduce the known rates from ribosome profiles generated from detailed simulations of translation. By applying our methods to data from S . cerevisiae and mouse embryonic stem cells, we find that the extracted rates reproduce expected correlations with various molecular properties, and we also find that mouse embryonic stem cells have a global translation speed of 5.2 AA/s, in agreement with previous reports that used other approaches. Our analysis further reveals that a codon can exhibit up to 26-fold variability in its translation rate depending upon its context within a transcript. This broad distribution means that the average translation rate of a codon is not representative of the rate at which most instances of that codon are translated, and it suggests that translational regulation might be used by cells to a greater degree than previously thought.

The ejection of nascent proteins out of the ribosome exit tunnel, after their covalent bond to transfer-RNA has been broken, has not been experimentally studied due to challenges in sample preparation. Here, we investigate this process using a combination of multiscale modeling, ribosome profiling, and gene ontology analyses. Simulating the ejection of a representative set of 122 E. coli proteins we find a greater than 1000-fold variation in ejection times. Nascent proteins enriched in negatively charged residues near their C-terminus eject the fastest, while nascent chains enriched in positively charged residues tend to eject much more slowly. More work is required to pull slowly ejecting proteins out of the exit tunnel than quickly ejecting proteins, according to all-atom simulations. An energetic decomposition reveals, for slowly ejecting proteins, that this is due to the strong attractive electrostatic interactions between the nascent chain and the negatively charged ribosomal-RNA lining the exit tunnel, and for quickly ejecting proteins, it is due to their repulsive electrostatic interactions with the exit tunnel. Ribosome profiling data from E. coli reveals that the presence of slowly ejecting sequences correlates with ribosomes spending more time at stop codons, indicating that the ejection process might delay ribosome recycling. Proteins that have the highest positive charge density at their C-terminus are overwhelmingly ribosomal proteins, suggesting the possibility that this sequence feature may aid in the cotranslational assembly of ribosomes by delaying the release of nascent ribosomal proteins into the cytosol. Thus, nascent chain ejection times from the ribosome can vary greatly between proteins due to differential electrostatic interactions, can influence ribosome recycling, and could be particularly relevant to the synthesis and cotranslational behavior of some proteins.

The rates at which domains fold and codons are translated are important factors in determining whether a nascent protein will co-translationally fold and function or misfold and malfunction. Here we develop a chemical kinetic model that calculates a protein domain's co-translational folding curve during synthesis using only the domain's bulk folding and unfolding rates and codon translation rates. We show that this model accurately predicts the course of co-translational folding measured in vivo for four different protein molecules. We then make predictions for a number of different proteins in yeast and find that synonymous codon substitutions, which change translation-elongation rates, can switch some protein domains from folding post-translationally to folding co-translationally—a result consistent with previous experimental studies. Our approach explains essential features of co-translational folding curves and predicts how varying the translation rate at different codon positions along a transcript's coding sequence affects this self-assembly process.

Analysis methods based on simulations and optimization have been previously developed to estimate relative translation rates from next-generation sequencing data. Translation involves molecules and chemical reactions; hence, bioinformatics methods consistent with the laws of chemistry and physics are more likely to produce accurate results. Here, we derive simple equations based on chemical kinetic principles to measure the translation-initiation rate, transcriptome-wide elongation rate, and individual codon translation rates from ribosome profiling experiments. Our methods reproduce the known rates from ribosome profiles generated from detailed simulations of translation. Applying our methods to data from S. cerevisiae and mouse embryonic stem cells we find that the extracted rates reproduce expected correlations with various molecular properties. A codon can exhibit up to 26-fold variability in its translation rate depending upon its context within a transcript. This broad distribution means that the average translation rate of a codon is not representative of the rate at which most instances of that codon are translated. We also find that mouse embryonic stem cells have a global translation speed of 5.2 AA/s, is similar to what has been previous reported using another analysis method. This large variability in translation rates suggests that translational regulation might be used by cells to a greater degree than previously thought. ‡ These authors contributed equally to this work.Introduction. Translation-associated rates influence in vivo protein abundance, structure and function. It is therefore crucial to be able to accurately measure these rates. The synthesis of a protein consists of three sequential phasesinitiation, elongation, and termination [1][2][3]. During the initiation phase ribosome subunits form a stable translation-initiation complex at the start codon of the mRNA transcript [4,5]. The ribosome then stochastically moves forward along the transcript one codon at a time during the elongation phase, adding one residue to the nascent chain at each step. The elongation phase is terminated when the ribosome's A-site reaches the stop codon, resulting in release of the fully synthesized protein. The initiation and elongation phases of translation contribute to protein levels inside a cell; indeed, alteration of their rates can cause protein abundance to vary by up to five orders of magnitude [6][7][8], and alter protein structure and function [9]. Termination does not influence the cellular concentration of proteins as it is not a rate limiting step [10]. Therefore, knowledge of translation initiation and codon translation rates are important to understand the regulation of gene expression.Significant efforts have been made to extract these rates from data generated from ribosome profiling experiments [11][12][13][14], a technique that measures the relative ribosome density across transcripts [15]. In a number of methods, the actual rates are not measured but instead a ratio of rates, or other releva...

Identifying the A- and P-site locations on ribosome-protected mRNA fragments from Ribo-Seq experiments is a fundamental step in the quantitative analysis of transcriptome-wide translation properties at the codon level. Many analyses of Ribo-Seq data have utilized heuristic approaches applied to a narrow range of fragment sizes to identify the A-site. In this study, we use Integer Programming to identify the A-site by maximizing an objective function that reflects the fact that the ribosome’s A-site on ribosome-protected fragments must reside between the second and stop codons of an mRNA. This identifies the A-site location as a function of the fragment’s size and its 5′ end reading frame in Ribo-Seq data generated from S. cerevisiae and mouse embryonic stem cells. The correctness of the identified A-site locations is demonstrated by showing that this method, as compared to others, yields the largest ribosome density at established stalling sites. By providing greater accuracy and utilization of a wider range of fragment sizes, our approach increases the signal-to-noise ratio of underlying biological signals associated with translation elongation at the codon length scale.

Ribosome profiling experiments have found greater than 100-fold variation in ribosome density along mRNA transcripts, indicating that individual codon elongation rates can vary to a similar degree. This wide range of elongation times, coupled with differences in codon usage between transcripts, suggests that the average codon translation-rate per gene can vary widely. Yet, ribosome run-off experiments have found that the average codon translation rate for different groups of transcripts in mouse stem cells is constant at 5.6 AA/s. How these seemingly contradictory results can be reconciled is the focus of this study. Here, we combine knowledge of the molecular factors shown to influence translation speed with genomic information from Escherichia coli, Saccharomyces cerevisiae and Homo sapiens to simulate the synthesis of cytosolic proteins in these organisms. The model recapitulates a near constant average translation rate, which we demonstrate arises because the molecular determinants of translation speed are distributed nearly randomly amongst most of the transcripts. Consequently, codon translation rates are also randomly distributed and fast-translating segments of a transcript are likely to be offset by equally probable slow-translating segments, resulting in similar average elongation rates for most transcripts. We also show that the codon usage bias does not significantly affect the near random distribution of codon translation rates because only about 10% of the total transcripts in an organism have high codon usage bias while the rest have little to no bias. Analysis of Ribo-Seq data and an in vivo fluorescent assay supports these conclusions.

Collagen gene family, comprising 30% of the total protein mass in mammals, is the major part of extracellular matrix. To understand the complexity of collagen gene family, detailed sequence, phylogenetic and synteny analyses of 44 collagen genes were performed. According to sequence analysis results, Fibril-associated collagen with interrupted triple helices (FACITs) were identified as the most recently evolved vertebrate-specific collagens while Fibril-forming collagens and Collagen VI, VII, XXVI, and XXVIII were the most ancient collagens, originating at the time of choanoflagellates. Network-forming collagens were entirely conserved from arthopods to homo sapiens, except one gene loss event. Of note, bird specific gene dispensability of COL1A1, COL3A1, COL5A3 and COL11A2 genes was observed in Fibril-forming collagens. According to phylogenetic analysis, gene duplications in collagen family occurred at variable time points during invertebrate to vertebrate evolution. However, majority of gene duplications in FACITs and network-forming collagens occurred at fish time point, suggesting large scale duplications at the root of vertebrate lineage. Lastly, synteny analysis identified 12 conserved blocks containing 27 collagen genes in vertebrate species. Interestingly, dysregulation of seven conserved blocks including block1 (COL11A1), block3 (COL3A1, COL5A2), block5 (COL6A5, COL6A6), block7 (COL1A2), block9 (COL4A1, COL4A2), block11 (COL6A1, COL6A2, COL18A1) and block12 (COL4A5, COL4A6) were also reported in different diseases including cancer. The current study revealed many critical insights into sequence, structural and functional diversity of collagen gene family. In future, by using this information we may be able to establish the clinical and pathological relevance of these conserved collagen blocks in different diseases.