Ribosome occupancy profiles are conserved between structurally and evolutionarily related yeast domains.

MOTIVATION: Protein synthesis is a non-equilibrium process, meaning that the speed of translation can influence the ability of proteins to fold and function. Assuming that structurally similar proteins fold by similar pathways, the profile of translation speed along an mRNA should be evolutionarily conserved between related proteins to direct correct folding and downstream function. The only evidence to date for such conservation of translation speed between homologous proteins has used codon rarity as a proxy for translation speed. There are, however, many other factors including mRNA structure and the chemistry of the amino acids in the A- and P-sites of the ribosome that influence the speed of amino acid addition. RESULTS: Ribosome profiling experiments provide a signal directly proportional to the underlying translation times at the level of individual codons. We compared ribosome occupancy profiles (extracted from five different large-scale yeast ribosome profiling studies) between related protein domains to more directly test if their translation schedule was conserved. Our analysis reveals that the ribosome occupancy profiles of paralogous domains tend to be significantly more similar to one another than to profiles of non-paralogous domains. This trend does not depend on domain length, structural classes, amino acid composition or sequence similarity. Our results indicate that entire ribosome occupancy profiles and not just rare codon locations are conserved between even distantly related domains in yeast, providing support for the hypothesis that translation schedule is conserved between structurally related domains to retain folding pathways and facilitate efficient folding. AVAILABILITY AND IMPLEMENTATION: Python3 code is available on GitHub at https://github.com/DanNissley/Compare-ribosome-occupancy. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The evolution of contact prediction: evidence that contact selection in statistical contact prediction is changing.

MOTIVATION: Over the last few years, the field of protein structure prediction has been transformed by increasingly accurate contact prediction software. These methods are based on the detection of coevolutionary relationships between residues from multiple sequence alignments (MSAs). However, despite speculation, there is little evidence of a link between contact prediction and the physico-chemical interactions which drive amino-acid coevolution. Furthermore, existing protocols predict only a fraction of all protein contacts and it is not clear why some contacts are favoured over others. Using a dataset of 863 protein domains, we assessed the physico-chemical interactions of contacts predicted by CCMpred, MetaPSICOV and DNCON2, as examples of direct coupling analysis, meta-prediction and deep learning. RESULTS: We considered correctly predicted contacts and compared their properties against the protein contacts that were not predicted. Predicted contacts tend to form more bonds than non-predicted contacts, which suggests these contacts may be more important than contacts that were not predicted. Comparing the contacts predicted by each method, we found that metaPSICOV and DNCON2 favour accuracy, whereas CCMPred detects contacts with more bonds. This suggests that the push for higher accuracy may lead to a loss of physico-chemically important contacts. These results underscore the connection between protein physico-chemistry and the coevolutionary couplings that can be derived from MSAs. This relationship is likely to be relevant to protein structure prediction and functional analysis of protein structure and may be key to understanding their utility for different problems in structural biology. AVAILABILITY AND IMPLEMENTATION: We use publicly available databases. Our code is available for download at https://opig.stats.ox.ac.uk/. SUPPLEMENTARY INFORMATION: Supplementary information is available at Bioinformatics online.

Characterization of the mutagenic spectrum of 4-nitroquinoline 1-oxide (4-NQO) in Aspergillus nidulans by whole genome sequencing.

4-Nitroquinoline 1-oxide (4-NQO) is a highly carcinogenic chemical that induces mutations in bacteria, fungi, and animals through the formation of bulky purine adducts. 4-NQO has been used as a mutagen for genetic screens and in both the study of DNA damage and DNA repair. In the model eukaryote Aspergillus nidulans, 4-NQO-based genetic screens have been used to study diverse processes, including gene regulation, mitosis, metabolism, organelle transport, and septation. Early work during the 1970s using bacterial and yeast mutation tester strains concluded that 4-NQO was a guanine-specific mutagen. However, these strains were limited in their ability to determine full mutagenic potential, as they could not identify mutations at multiple sites, unlinked suppressor mutations, or G:C to C:G transversions. We have now used a whole genome resequencing approach with mutant strains generated from two independent genetic screens to determine the full mutagenic spectrum of 4-NQO in A. nidulans. Analysis of 3994 mutations from 38 mutant strains reveals that 4-NQO induces substitutions in both guanine and adenine residues, although with a 19-fold preference for guanine. We found no association between mutation load and mutagen dose and observed no sequence bias in the residues flanking the mutated purine base. The mutations were distributed randomly throughout most of the genome. Our data provide new evidence that 4-NQO can potentially target all base pairs. Furthermore, we predict that current practices for 4-NQO-induced mutagenesis are sufficient to reach gene saturation for genetic screens with feasible identification of causative mutations via whole genome resequencing.

A microscopy-based screen employing multiplex genome sequencing identifies cargo-specific requirements for dynein velocity.

The timely delivery of membranous organelles and macromolecules to specific locations within the majority of eukaryotic cells depends on microtubule-based transport. Here we describe a screening method to identify mutations that have a critical effect on intracellular transport and its regulation using mutagenesis, multicolor-fluorescence microscopy, and multiplex genome sequencing. This screen exploits the filamentous fungus Aspergillus nidulans, which has many of the advantages of yeast molecular genetics but uses long-range microtubule-based transport in a manner more similar to metazoan cells. Using this method, we identified seven mutants that represent novel alleles of components of the intracellular transport machinery: specifically, kinesin-1, cytoplasmic dynein, and the dynein regulators Lis1 and dynactin. The two dynein mutations identified in our screen map to dynein's AAA+ catalytic core. Single-molecule studies reveal that both mutations reduce dynein's velocity in vitro. In vivo these mutants severely impair the distribution and velocity of endosomes, a known dynein cargo. In contrast, another dynein cargo, the nucleus, is positioned normally in these mutants. These results reveal that different dynein functions have distinct stringencies for motor performance.