A virulent strain of deformed wing virus (DWV) of honeybees (Apis mellifera) prevails after Varroa destructor-mediated, or in vitro, transmission.

The globally distributed ectoparasite Varroa destructor is a vector for viral pathogens of the Western honeybee (Apis mellifera), in particular the Iflavirus Deformed Wing Virus (DWV). In the absence of Varroa low levels DWV occur, generally causing asymptomatic infections. Conversely, Varroa-infested colonies show markedly elevated virus levels, increased overwintering colony losses, with impairment of pupal development and symptomatic workers. To determine whether changes in the virus population were due Varroa amplifying and introducing virulent virus strains and/or suppressing the host immune responses, we exposed Varroa-naïve larvae to oral and Varroa-transmitted DWV. We monitored virus levels and diversity in developing pupae and associated Varroa, the resulting RNAi response and transcriptome changes in the host. Exposed pupae were stratified by Varroa association (presence/absence) and virus levels (low/high) into three groups. Varroa-free pupae all exhibited low levels of a highly diverse DWV population, with those exposed per os (group NV) exhibiting changes in the population composition. Varroa-associated pupae exhibited either low levels of a diverse DWV population (group VL) or high levels of a near-clonal virulent variant of DWV (group VH). These groups and unexposed controls (C) could be also discriminated by principal component analysis of the transcriptome changes observed, which included several genes involved in development and the immune response. All Varroa tested contained a diverse replicating DWV population implying the virulent variant present in group VH, and predominating in RNA-seq analysis of temporally and geographically separate Varroa-infested colonies, was selected upon transmission from Varroa, a conclusion supported by direct injection of pupae in vitro with mixed virus populations. Identification of a virulent variant of DWV, the role of Varroa in its transmission and the resulting host transcriptome changes furthers our understanding of this important viral pathogen of honeybees.

MosaicSolver: a tool for determining recombinants of viral genomes from pileup data.

Viral recombination is a key evolutionary mechanism, aiding escape from host immunity, contributing to changes in tropism and possibly assisting transmission across species barriers. The ability to determine whether recombination has occurred and to locate associated specific recombination junctions is thus of major importance in understanding emerging diseases and pathogenesis. This paper describes a method for determining recombinant mosaics (and their proportions) originating from two parent genomes, using high-throughput sequence data. The method involves setting the problem geometrically and the use of appropriately constrained quadratic programming. Recombinants of the honeybee deformed wing virus and the Varroa destructor virus-1 are inferred to illustrate the method from both siRNAs and reads sampling the viral genome population (cDNA library); our results are confirmed experimentally. Matlab software (MosaicSolver) is available.

Exploring the potential of template-based modelling.

MOTIVATION: Template-based modelling can approximate the unknown structure of a target protein using an homologous template structure. The core of the resulting prediction then comprises the structural regions conserved between template and target. Target prediction could be improved by rigidly repositioning such single template, structurally conserved fragment regions. The purpose of this article is to quantify the extent to which such improvements are possible and to relate this extent to properties of the target, the template and their alignment. RESULTS: The improvement in accuracy achievable when rigid fragments from a single template are optimally positioned was calculated using structure pairs from the HOMSTRAD database, as well as CASP7 and CASP8 target/best template pairs. Over the union of the structurally conserved regions, improvements of 0.7 A in root mean squared deviation (RMSD) and 6% in GDT_HA were commonly observed. A generalized linear model revealed that the extent to which a template can be improved can be predicted using four variables. Templates with the greatest scope for improvement tend to have relatively more fragments, shorter fragments, higher percentage of helical secondary structure and lower sequence identity. Optimal positioning of the template fragments offers the potential for improving loop modelling. These results demonstrate that substantial improvement could be made on many templates if the conserved fragments were to be optimally positioned. They also provide a basis for identifying templates for which modification of fragment positions may yield such improvements.

Directionality in protein fold prediction.

BACKGROUND: Ever 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. RESULTS: A 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. CONCLUSIONS: There 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.

A restriction enzyme reduced representation sequencing approach for low-cost, high-throughput metagenome profiling.

Microbial community profiles have been associated with a variety of traits, including methane emissions in livestock. These profiles can be difficult and expensive to obtain for thousands of samples (e.g. for accurate association of microbial profiles with traits), therefore the objective of this work was to develop a low-cost, high-throughput approach to capture the diversity of the rumen microbiome. Restriction enzyme reduced representation sequencing (RE-RRS) using ApeKI or PstI, and two bioinformatic pipelines (reference-based and reference-free) were compared to bacterial 16S rRNA gene sequencing using repeated samples collected two weeks apart from 118 sheep that were phenotypically extreme (60 high and 58 low) for methane emitted per kg dry matter intake (n = 236). DNA was extracted from freeze-dried rumen samples using a phenol chloroform and bead-beating protocol prior to RE-RRS. The resulting sequences were used to investigate the repeatability of the rumen microbial community profiles, the effect of laboratory and analytical method, and the relationship with methane production. The results suggested that the best method was PstI RE-RRS analyzed with the reference-free approach, which accounted for 53.3±5.9% of reads, and had repeatabilities of 0.49±0.07 and 0.50±0.07 for the first two principal components (PC1 and PC2), phenotypic correlations with methane yield of 0.43±0.06 and 0.46±0.06 for PC1 and PC2, and explained 41±8% of the variation in methane yield. These results were significantly better than for bacterial 16S rRNA gene sequencing of the same samples (p<0.05) except for the correlation between PC2 and methane yield. A Sensitivity study suggested approximately 2000 samples could be sequenced in a single lane on an Illumina HiSeq 2500, meaning the current work using 118 samples/lane and future proposed 384 samples/lane are well within that threshold. With minor adaptations, our approach could be used to obtain microbial profiles from other metagenomic samples.

A multi-stage approach to clustering and imputation of gene expression profiles.

MOTIVATION: Microarray experiments have revolutionized the study of gene expression with their ability to generate large amounts of data. This article describes an alternative to existing approaches to clustering of gene expression profiles; the key idea is to cluster in stages using a hierarchy of distance measures. This method is motivated by the way in which the human mind sorts and so groups many items. The distance measures arise from the orthogonal breakup of Euclidean distance, giving us a set of independent measures of different attributes of the gene expression profile. Interpretation of these distances is closely related to the statistical design of the microarray experiment. This clustering method not only accommodates missing data but also leads to an associated imputation method. RESULTS: The performance of the clustering and imputation methods was tested on a simulated dataset, a yeast cell cycle dataset and a central nervous system development dataset. Based on the Rand and adjusted Rand indices, the clustering method is more consistent with the biological classification of the data than commonly used clustering methods. The imputation method, at varying levels of missingness, outperforms most imputation methods, based on root mean squared error (RMSE). AVAILABILITY: Code in R is available on request from the authors.

Cotranslational protein folding--fact or fiction?

MOTIVATION: Experimentalists have amassed extensive evidence over the past four decades that proteins appear to fold during production by the ribosome. Protein structure prediction methods, however, do not incorporate this property of folding. A thorough study to find the fingerprint of such sequential folding is the first step towards using it in folding algorithms, so assisting structure prediction. RESULTS: We explore computationally the existence of evidence for cotranslational folding, based on large sets of experimentally determined structures in the PDB. Our perspective is that cotranslational folding is the norm, but that the effect is masked in most classes. We show that it is most evident in alpha/beta proteins, confirming recent findings. We also find mild evidence that older proteins may fold cotranslationally. A tool is provided for determining, within a protein, where cotranslation is most evident.

Modelling sequential protein folding under kinetic control.

MOTIVATION: This study presents a novel investigation of the effect of kinetic control on cotranslational protein folding. We demonstrate the effect using simple HP lattice models and show that the cotranslational folding of proteins under kinetic control has a significant impact on the final conformation. Differences arise if nature is not capable of pushing a partially folded protein back over a large energy barrier. For this reason we argue that such constraints should be incorporated into structure prediction techniques. We introduce a finite surmountable energy barrier which allows partially formed chains to partly unfold, and permits us to enumerate exhaustively all energy pathways. RESULTS: We compare the ground states obtained sequentially with the global ground states of designing sequences (those with a unique global ground state). We find that the sequential ground states become less numerous and more compact as the surmountable energy barrier increases. We also introduce a probabilistic model to describe the distribution of final folds and allow partial settling to the Boltzmann distribution of states at each stage. As a result, conformations with the highest probability of final occurrence are not necessarily the ones of lowest energy. AVAILABILITY: Software available on request.

The Iflaviruses Sacbrood virus and Deformed wing virus evoke different transcriptional responses in the honeybee which may facilitate their horizontal or vertical transmission.

Sacbrood virus (SBV) and Deformed wing virus (DWV) are evolutionarily related positive-strand RNA viruses, members of the Iflavirus group. They both infect the honeybee Apis mellifera but have strikingly different levels of virulence when transmitted orally. Honeybee larvae orally infected with SBV usually accumulate high levels of the virus, which halts larval development and causes insect death. In contrast, oral DWV infection at the larval stage usually causes asymptomatic infection with low levels of the virus, although high doses of ingested DWV could lead to DWV replicating to high levels. We investigated effects of DWV and SBV infection on the transcriptome of honeybee larvae and pupae using global RNA-Seq and real-time PCR analysis. This showed that high levels of SBV replication resulted in down-regulation of the genes involved in cuticle and muscle development, together with changes in expression of putative immune-related genes. In particular, honeybee larvae with high levels of SBV replication, with and without high levels of DWV replication, showed concerted up-regulated expression of antimicrobial peptides (AMPs), and down-regulated expression of the prophenoloxidase activating enzyme (PPAE) together with up-regulation of the expression of a putative serpin, which could lead to the suppression of the melanisation pathway. The effects of high SBV levels on expression of these immune genes were unlikely to be a consequence of SBV-induced developmental changes, because similar effects were observed in honeybee pupae infected by injection. In the orally infected larvae with high levels of DWV replication alone we observed no changes of AMPs or of gene expression in the melanisation pathway. In the injected pupae, high levels of DWV alone did not alter expression of the tested melanisation pathway genes, but resulted in up-regulation of the AMPs, which could be attributed to the effect of DWV on the regulation of AMP expression in response to wounding. We propose that the difference in expression of the honeybee immune genes induced by SBV and DWV may be an evolutionary adaptation to the different predominant transmission routes used by these viruses.

Error correction and diversity analysis of population mixtures determined by NGS.

The impetus for this work was the need to analyse nucleotide diversity in a viral mix taken from honeybees. The paper has two findings. First, a method for correction of next generation sequencing error in the distribution of nucleotides at a site is developed. Second, a package of methods for assessment of nucleotide diversity is assembled. The error correction method is statistically based and works at the level of the nucleotide distribution rather than the level of individual nucleotides. The method relies on an error model and a sample of known viral genotypes that is used for model calibration. A compendium of existing and new diversity analysis tools is also presented, allowing hypotheses about diversity and mean diversity to be tested and associated confidence intervals to be calculated. The methods are illustrated using honeybee viral samples. Software in both Excel and Matlab and a guide are available at http://www2.warwick.ac.uk/fac/sci/systemsbiology/research/software/, the Warwick University Systems Biology Centre software download site.

Cotranslational protein folding and terminus hydrophobicity.

Peptides fold on a time scale that is much smaller than the time required for synthesis, whence all proteins potentially fold cotranslationally to some degree (followed by additional folding events after release from the ribosome). In this paper, in three different ways, we find that cotranslational folding success is associated with higher hydrophobicity at the N-terminus than at the C-terminus. First, we fold simple HP models on a square lattice and observe that HP sequences that fold better cotranslationally than from a fully extended state exhibit a positive difference (N-C) in terminus hydrophobicity. Second, we examine real proteins using a previously established measure of potential cotranslationality known as ALR (Average Logarithmic Ratio of the extent of previous contacts) and again find a correlation with the difference in terminus hydrophobicity. Finally, we use the cotranslational protein structure prediction program SAINT and again find that such an approach to folding is more successful for proteins with higher N-terminus than C-terminus hydrophobicity. All results indicate that cotranslational folding is promoted in part by a hydrophobic start and a less hydrophobic finish to the sequence.

Exon size distribution and the origin of introns.

Since it was first recognised that eukaryotic genes are fragmented into coding segments (exons) separated by non-coding segments (introns), the reason for this phenomenon has been debated. There are two dominant theories: that the piecewise arrangement of genes allows functional protein domains, represented by exons, to recombine by shuffling to form novel proteins with combinations of functions; or that introns represent parasitic DNA that can infest the eukaryotic genome because it does not interfere grossly with the fitness of its host. Differing distributions of exon lengths are predicted by these two theories. In this paper we examine distributions of exon lengths for six different organisms and find that they offer empirical evidence that both theories may in part be correct.

Comparing SILAC and two-dimensional gel electrophoresis image analysis for profiling urokinase plasminogen activator signaling in ovarian cancer cells.

Two-dimensional gel electrophoresis (2-DE) image analysis is conventionally used for comparative proteomics. However, there are a number of technical difficulties associated with 2-DE protein separation that limit the depth of proteome coverage, and the image analysis steps are typically labor-intensive and low-throughput. Recently, mass spectrometry-based quantitation strategies have been described as alternative differential proteome analysis techniques. In this study, we investigated changes in protein expression using an ovarian cancer cell line, OVMZ6, 24 h post-stimulation with the relatively weak agonist, urokinase-type plasminogen activator (uPA). Quantitative protein profiles were obtained by MALDI-TOF/TOF from stable isotope-labeled cells in culture (SILAC), and these results were compared to the quantitative ratios obtained using 2-DE gel image analysis. MALDI-TOF/TOF mass spectrometry showed that differential quantitation using SILAC was highly reproducible (approximately 8% coefficient of variation (CV)), and this variance was considerably lower than that achieved using automated 2-DE image analysis strategies (CV approximately 25%). Both techniques revealed subtle alterations in cellular protein expression following uPA stimulation. However, due to the lower variances associated with the SILAC technique, smaller changes in expression of uPA-inducible proteins could be found with greater certainty.