Jonathan J. Ellis

Molecular basis for specificity of nuclear import and prediction of nuclear localization

Although proteins are translated on cytoplasmic ribosomes, many of these proteins play essential roles in the nucleus, mediating key cellular processes including but not limited to DNA replication and repair as well as transcription and RNA processing. Thus, understanding how these critical nuclear proteins are accurately targeted to the nucleus is of paramount importance in biology. Interaction and structural studies in the recent years have jointly revealed some general rules on the specificity determinants of the recognition of nuclear targeting signals by their specific receptors, at least for two nuclear import pathways: (i) the classical pathway, which involves the classical nuclear localization sequences (cNLSs) and the receptors importin-α/karyopherin-α and importin-β/karyopherin-β1; and (ii) the karyopherin-β2 pathway, which employs the proline-tyrosine (PY)-NLSs and the receptor transportin-1/karyopherin-β2. The understanding of specificity rules allows the prediction of protein nuclear localization. We review the current understanding of the molecular determinants of the specificity of nuclear import, focusing on the importin-α•cargo recognition, as well as the currently available databases and predictive tools relevant to nuclear localization. This article is part of a Special Issue entitled: Regulation of Signaling and Cellular Fate through Modulation of Nuclear Protein Import.

Protein–RNA interactions: Structural analysis and functional classes

A data set of 89 protein–RNA complexes has been extracted from the Protein Data Bank, and the nucleic acid recognition sites characterized through direct contacts, accessible surface area, and secondary structure motifs. The differences between RNA recognition sites that bind to RNAs in functional classes has also been analyzed. Analysis of the complete data set revealed that van der Waals interactions are more numerous than hydrogen bonds and the contacts made to the nucleic acid backbone occur more frequently than specific contacts to nucleotide bases. Of the base‐specific contacts that were observed, contacts to guanine and adenine occurred most frequently. The most favored amino acid–nucleotide pairings observed were lysine–phosphate, tyrosine–uracil, arginine–phosphate, phenylalanine–adenine and tryptophan–guanine. The amino acid propensities showed that positively charged and polar residues were favored as expected, but also so were tryptophan and glycine. The propensities calculated for the functional classes showed trends similar to those observed for the complete data set. However, the analysis of hydrogen bond and van der Waal contacts showed that in general proteins complexed with messenger RNA, transfer RNA and viral RNA have more base specific contacts and less backbone contacts than expected, while proteins complexed with ribosomal RNA have less base‐specific contacts than the expected. Hence, whilst the types of amino acids involved in the interfaces are similar, the distribution of specific contacts is dependent upon the functional class of the RNA bound. Proteins 2007.

Calypso: a user-friendly web-server for mining and visualizing microbiome–environment interactions

Abstract Calypso is an easy‐to‐use online software suite that allows non‐expert users to mine, interpret and compare taxonomic information from metagenomic or 16S rDNA datasets. Calypso has a focus on multivariate statistical approaches that can identify complex environment‐microbiome associations. The software enables quantitative visualizations, statistical testing, multivariate analysis, supervised learning, factor analysis, multivariable regression, network analysis and diversity estimates. Comprehensive help pages, tutorials and videos are provided via a wiki page. Availability and Implementation: The web‐interface is accessible via http://cgenome.net/calypso/. The software is programmed in Java, PERL and R and the source code is available from Zenodo (https://zenodo.org/record/50931). The software is freely available for non‐commercial users. Contact: l.krause@uq.edu.au Supplementary information: Supplementary data are available at Bioinformatics online.

Predicting protein kinase specificity: Predikin update and performance in the DREAM4 challenge.

Predikin is a system for making predictions about protein kinase specificity. It was declared the “best performer” in the protein kinase section of the Peptide Recognition Domain specificity prediction category of the recent DREAM4 challenge (an independent test using unpublished data). In this article we discuss some recent improvements to the Predikin web server — including a more streamlined approach to substrate-to-kinase predictions and whole-proteome predictions — and give an analysis of Predikins performance in the DREAM4 challenge. We also evaluate these improvements using a data set of yeast kinases that have been experimentally characterised, and we discuss the usefulness of Frobenius distance in assessing the predictive power of position weight matrices.

Evaluating conformational changes in protein structures binding RNA

Many protein–RNA recognition events are known to exhibit conformational changes from qualitative observations of individual complexes. However, a quantitative estimation of conformational changes is required if protein–RNA docking and template‐based methods for RNA binding site prediction are to be developed. This study presents the first quantitive evaluation of conformational changes that occur when proteins bind RNA. The analysis of twelve RNA‐binding proteins in the bound and unbound states using error‐scaled difference distance matrices is presented. The binding site residues are mapped to each structure, and the conformational changes that affect these residues are evaluated. Of the twelve proteins four exhibit greater movements in nonbinding site residues, and a further four show the greatest movements in binding site residues. The remaining four proteins display no significant conformational change. When interface residues are found to be in conformationally variable regions of the protein they are typically seen to move less than 2 Å between the bound and unbound conformations. The current data indicate that conformational changes in the binding site residues of RNA binding proteins may not be as significant as previously suggested, but a larger data set is required before wider conclusions may be drawn. The implications of the observed conformational changes for protein function prediction are discussed. Proteins 2008.

PREDIVAC: CD4+T-cell epitope prediction for vaccine design that covers 95% of HLA class II DR protein diversity

BackgroundCD4+ T-cell epitopes play a crucial role in eliciting vigorous protective immune responses during peptide (epitope)-based vaccination. The prediction of these epitopes focuses on the peptide binding process by MHC class II proteins. The ability to account for MHC class II polymorphism is critical for epitope-based vaccine design tools, as different allelic variants can have different peptide repertoires. In addition, the specificity of CD4+ T-cells is often directed to a very limited set of immunodominant peptides in pathogen proteins. The ability to predict what epitopes are most likely to dominate an immune response remains a challenge.ResultsWe developed the computational tool Predivac to predict CD4+ T-cell epitopes. Predivac can make predictions for 95% of all MHC class II protein variants (allotypes), a substantial advance over other available methods. Predivac bases its prediction on the concept of specificity-determining residues. The performance of the method was assessed both for high-affinity HLA class II peptide binding and CD4+ T-cell epitope prediction. In terms of epitope prediction, Predivac outperformed three available pan-specific approaches (delivering the highest specificity). A central finding was the high accuracy delivered by the method in the identification of immunodominant and promiscuous CD4+ T-cell epitopes, which play an essential role in epitope-based vaccine design.ConclusionsThe comprehensive HLA class II allele coverage along with the high specificity in identifying immunodominant CD4+ T-cell epitopes makes Predivac a valuable tool to aid epitope-based vaccine design in the context of a genetically heterogeneous human population.The tool is available at: http://predivac.biosci.uq.edu.au/.

Dynamics of re-constitution of the human nuclear proteome after cell division is regulated by NLS-adjacent phosphorylation.

Phosphorylation by the cyclin-dependent kinase 1 (Cdk1) adjacent to nuclear localization signals (NLSs) is an important mechanism of regulation of nucleocytoplasmic transport. However, no systematic survey has yet been performed in human cells to analyze this regulatory process, and the corresponding cell-cycle dynamics have not yet been investigated. Here, we focused on the human proteome and found that numerous proteins, previously not identified in this context, are associated with Cdk1-dependent phosphorylation sites adjacent to their NLSs. Interestingly, these proteins are involved in key regulatory events of DNA repair, epigenetics, or RNA editing and splicing. This finding indicates that cell-cycle dependent events of genome editing and gene expression profiling may be controlled by nucleocytoplasmic trafficking. For in-depth investigations, we selected a number of these proteins and analyzed how point mutations, expected to modify the phosphorylation ability of the NLS segments, perturb nucleocytoplasmic localization. In each case, we found that mutations mimicking hyper-phosphorylation abolish nuclear import processes. To understand the mechanism underlying these phenomena, we performed a video microscopy-based kinetic analysis to obtain information on cell-cycle dynamics on a model protein, dUTPase. We show that the NLS-adjacent phosphorylation by Cdk1 of human dUTPase, an enzyme essential for genomic integrity, results in dynamic cell cycle-dependent distribution of the protein. Non-phosphorylatable mutants have drastically altered protein re-import characteristics into the nucleus during the G1 phase. Our results suggest a dynamic Cdk1-driven mechanism of regulation of the nuclear proteome composition during the cell cycle.

Directionality in protein fold prediction.

BackgroundEver since the ground-breaking work of Anfinsen et al. in which a denatured protein was found to refold to its native state, it has been frequently stated by the protein fold prediction community that all the information required for protein folding lies in the amino acid sequence. Recent in vitro experiments and in silico computational studies, however, have shown that cotranslation may affect the folding pathway of some proteins, especially those of ancient folds. In this paper aspects of cotranslational folding have been incorporated into a protein structure prediction algorithm by adapting the Rosetta program to fold proteins as the nascent chain elongates. This makes it possible to conduct a pairwise comparison of folding accuracy, by comparing folds created sequentially from each end of the protein.ResultsA single main result emerged: in 94% of proteins analyzed, following the sense of translation, from N-terminus to C-terminus, produced better predictions than following the reverse sense of translation, from the C-terminus to N-terminus. Two secondary results emerged. First, this superiority of N-terminus to C-terminus folding was more marked for proteins showing stronger evidence of cotranslation and second, an algorithm following the sense of translation produced predictions comparable to, and occasionally better than, Rosetta.ConclusionsThere is a directionality effect in protein fold prediction. At present, prediction methods appear to be too noisy to take advantage of this effect; as techniques refine, it may be possible to draw benefit from a sequential approach to protein fold prediction.

The T-cell receptor repertoire influences the tumor microenvironment and is associated with survival in aggressive B-cell lymphoma

Purpose: To investigate the relationship between the intra-tumoral T-cell receptor (TCR) repertoire and the tumor microenvironment (TME) in de novo diffuse large B-cell lymphoma (DLBCL) and the impact of TCR on survival. Experimental Design: We performed high-throughput unbiased TCRβ sequencing on a population-based cohort of 92 patients with DLBCL treated with conventional (i.e., non-checkpoint blockade) frontline “R-CHOP” therapy. Key immune checkpoint genes within the TME were digitally quantified by nanoString. The primary endpoints were 4-year overall survival (OS) and progression-free survival (PFS). Results: The TCR repertoire within DLBCL nodes was abnormally narrow relative to non-diseased nodal tissues (P < 0.0001). In DLBCL, a highly dominant single T-cell clone was associated with inferior 4-year OS rate of 60.0% [95% confidence interval (CI), 31.7%–79.6%], compared with 79.8% in patients with a low dominant clone (95% CI, 66.7%–88.5%; P = 0.005). A highly dominant clone also predicted inferior 4-year PFS rate of 46.6% (95% CI, 22.5%–76.6%) versus 72.6% (95% CI, 58.8%–82.4%, P = 0.008) for a low dominant clone. In keeping, clonal expansions were most pronounced in the EBV+ DLBCL subtype that is known to express immunogenic viral antigens and is associated with particularly poor outcome. Increased T-cell diversity was associated with significantly elevated PD-1, PD-L1, and PD-L2 immune checkpoint molecules. Conclusions: Put together, these findings suggest that the TCR repertoire is a key determinant of the TME. Highly dominant T-cell clonal expansions within the TME are associated with poor outcome in DLBCL treated with conventional frontline therapy. Clin Cancer Res; 23(7); 1820–8. ©2016 AACR.

Rare, potentially pathogenic variants in ZNF469 are not enriched in keratoconus in a large Australian cohort of European descent

Purpose The Zinc Finger Protein 469 (ZNF469) gene has been proposed as a candidate gene for keratoconus due to the association of an upstream polymorphism (rs9938149) with the disease in two independent studies, and the role of the gene in the autosomal recessive disease Brittle Cornea Syndrome. Coding variants in ZNF469 have been assessed for association with keratoconus in several small studies, with conflicting results. We assessed rare, potentially pathogenic variants in ZNF469 for enrichment in keratoconus patients in a cohort larger than all previous studies combined. Methods ZNF469 was sequenced in 385 Australian keratoconus patients of European descent, 346 population controls, and 230 ethnically matched screened controls by either whole exome sequencing or targeted gene sequencing. The frequency of rare and very rare potentially pathogenic variants was compared between cases and controls using χ2 or Fishers exact tests and further explored using a gene based test (Sequence Kernel Association Test [SKAT]), weighting on the rarity of variants. Results A total of 49 rare, including 33 very rare, potentially pathogenic variants were identified across all groups. No enrichment of rare or very rare potentially pathogenic variants in ZNF469 was observed in our cases compared to the control groups following analysis using χ2 or Fishers exact tests. This finding was further supported by the SKAT results, which found no significant difference in the frequency of variants predicted to be damaging between cases and either control group (P = 0.06). Conclusions Rare variants in ZNF469 do not contribute to keratoconus susceptibility and do not account for the association at rs9938149.