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Robertson, D. L.

Publications and source records attributed to Robertson, D. L..

At least 37 records · Page 2Linked to original sources

Selection analysis identifies unusual clustered mutational changes in Omicron lineage BA.1 that likely impact Spike function

Among the 30 non-synonymous nucleotide substitutions in the Omicron S-gene are 13 that have only rarely been seen in other SARS-CoV-2 sequences. These mutations cluster within three functionally important regions of the S-gene at sites that will likely impact (i) interactions between subunits of the Spike trimer and the predisposition of subunits to shift from down to up configurations, (ii) interactions of Spike with ACE2 receptors, and (iii) the priming of Spike for membrane fusion. We show here that, based on both the rarity of these 13 mutations in intrapatient sequencing reads and patterns of selection at the codon sites where the mutations occur in SARS-CoV-2 and related sarbecoviruses, prior to the emergence of Omicron the mutations would have been predicted to decrease the fitness of any genomes within which they occurred. We further propose that the mutations in each of the three clusters therefore cooperatively interact to both mitigate their individual fitness costs, and adaptively alter the function of Spike. Given the evident epidemic growth advantages of Omicron over all previously known SARS-CoV-2 lineages, it is crucial to determine both how such complex and highly adaptive mutation constellations were assembled within the Omicron S-gene, and why, despite unprecedented global genomic surveillance efforts, the early stages of this assembly process went completely undetected.

evolutionary biology↗

The Interferon Resistance of Transmitted HIV-1 is a Consequence of Enhanced Replicative Fitness

HIV-1 transmission via sexual exposure is a relatively inefficient process. When successful transmission does occur, newly infected individuals are colonized by either a single or a very small number of establishing virion(s). These transmitted founder (TF) viruses are more interferon (IFN) resistant than chronic control (CC) viruses present 6 months after transmission. To identify the specific molecular defences that make CC viruses more susceptible to the IFN-induced antiviral state than TF viruses, we established a pair of fluorescent GFP-IRES-Nef TF and CC viruses and used arrayed interferon-stimulated gene (ISG) expression screening. The relatively uniform ISG resistance of transmitted HIV-1 directed us to investigate the underlying mechanism. Our subsequent in silico simulations, modelling, and in vitro characterisation of a model TF/CC pair (closely matched in replicative fitness), revealed that small differences in replicative growth rates can explain the broad IFN resistance displayed by transmitted HIV-1. We propose that the apparent IFN resistance of transmitted HIV-1 is a consequence of enhanced replicative fitness, as opposed to specific resistance to individual IFN-induced defences.

microbiology↗

Conserved recombination patterns across coronavirus subgenera

Recombination contributes to the genetic diversity found in coronaviruses and is known to be a prominent mechanism whereby they evolve. It is apparent, both from controlled experiments and in genome sequences sampled from nature, that patterns of recombination in coronaviruses are non-random and that this is likely attributable to a combination of sequence features that favour the occurrence of recombination breakpoints at specific genomic sites, and selection disfavouring the survival of recombinants within which favourable intra-genome interactions have been disrupted. Here we leverage available whole-genome sequence data for six coronavirus subgenera to identify specific patterns of recombination that are conserved between multiple subgenera and then identify the likely factors that underlie these conserved patterns. Specifically, we confirm the non-randomness of recombination breakpoints across all six tested coronavirus subgenera, locate conserved recombination hot- and cold-spots, and determine that the locations of transcriptional regulatory sequences are likely major determinants of conserved recombination breakpoint hot-spot locations. We find that while the locations of recombination breakpoints are not uniformly associated with degrees of nucleotide sequence conservation, they display significant tendencies in multiple coronavirus subgenera to occur in low guanine-cytosine content genome regions, in non-coding regions, at the edges of genes, and at sites within the Spike gene that are predicted to be minimally disruptive of Spike protein folding. While it is apparent that sequence features such as transcriptional regulatory sequences are likely major determinants of where the template-switching events that yield recombination breakpoints most commonly occur, it is evident that selection against misfolded recombinant proteins also strongly impacts observable recombination breakpoint distributions in coronavirus genomes sampled from nature.

bioinformatics↗

Defining the Characteristics of Type I Interferon Stimulated Genes: Insight from Expression Data and Machine Learning

A virus-infected cell triggers a signalling cascade resulting in the secretion of interferons (IFNs), which in turn induce the up-regulation of IFN-stimulated genes (ISGs) that play an important role in the inhibition of the viral infection and the return to cellular homeostasis. Here, we conduct detailed analyses on 7443 features relating to evolutionary conservation, nucleotide composition, gene expression, amino acid composition, and network properties to elucidate factors associated with the stimulation of genes in response to type I IFNs. Our results show that ISGs are less evolutionary conserved than genes that are not significantly stimulated in IFN experiments (non-ISGs). ISGs show significant depletion of GC-content in the coding region of their canonical transcripts, which leads to under-representation in the nucleotide compositions. Differences between ISGs and non-ISGs are also reflected in the properties of their coded amino acid sequence compositions. Network analyses show that ISG products tend to be involved in key paths but are away from hubs or bottlenecks of the human protein-protein interaction (PPI) network. Our analyses also show that interferon-repressed human genes (IRGs), which are down-regulated in the presence of IFNs, can have similar properties to ISGs, thus leading to false positives in ISG predictions. Based on these analyses, we design a machine learning framework integrating the usage of support vector machine (SVM) and feature selection algorithms. The ISG prediction achieves an area under the receiver operating characteristic curve (AUC) of 0.7455 and demonstrates the similarity between ISGs triggered by type I and III IFNs. Our machine learning model predicts a number of genes as potential ISGs that so far have shown no significant differential expression when stimulated with IFN in the cell types and tissue types compiled in the available IFN-related databases. A webserver implementing our method is accessible at http://isgpre.cvr.gla.ac.uk/. Author summaryInterferons (IFNs) are signalling proteins secreted from host cells. IFN-triggered signalling activates the host immune system in response to intra-cellular infection. It results in the stimulation of many genes that have anti-pathogen roles in host defenses. Interferon-stimulated genes (ISGs) have unique properties that make them different from those not significantly up-regulated in response to IFNs (non-ISGs). We find the down-regulated interferon-repressed genes (IRGs) have some shared properties with ISGs. This increases the difficulty of distinguishing ISGs from non-ISGs. The use of machine learning is a sensible strategy to provide high throughput classifications of putative ISGs, for investigation with in vivo or in vitro experiments. Machine learning can also be applied to human genes for which there are insufficient expression levels before and after IFN treatment in various experiments. Additionally, the interferon type has some impact on ISG predictability. We expect that our study will provide new insight into better understanding the inherent characteristics of human genes that are related to response in the presence of IFNs.

immunology↗

Unique protein features of SARS-CoV-2 relative to other Sarbecoviruses

Defining the unique properties of SARS-CoV-2 protein sequences, has potential to explain the range of Coronavirus Disease 2019 (COVID-19) severity. To achieve this we compared proteins encoded by all Sarbecoviruses using profile Hidden Markov Model similarities to identify protein features unique to SARS-CoV-2. Consistent with previous reports, a small set of bat and pangolin-derived Sarbecoviruses show the greatest similarity to SARS-CoV-2 but unlikely to be the direct source of SARS-CoV-2. Three proteins (nsp3, spike and orf9) showed differing regions between the bat Sarbecoviruses and SARS-CoV-2 and indicate virus protein features that might have evolved to support human infection and/or transmission. Spike analysis identified all regions of the protein that have tolerated change and revealed that the current SARS-CoV-2 variants of concern (VOCs) have sampled only a fraction (~31%) of the possible spike domain changes which have occurred historically in Sarbecovirus evolution. This result emphasises the evolvability of these coronaviruses and potential for further change in virus replication and transmission properties over the coming years.

evolutionary biology↗

Quantifying and cataloguing unknown sequences within human microbiomes

Advances in genome sequencing technologies and lower costs have enabled the exploration of a multitude of known and novel environments and microbiomes. This has led to an exponential growth in the raw sequence data that is deposited in online repositories. Metagenomic and metatranscriptomic data sets are typically analysed with regards to a specific biological question. However, it is widely acknowledged that these data sets are comprised of a proportion of sequences that bear no similarity to any currently known biological sequence, and this so-called dark matter is often excluded from downstream analyses. In this study, a systematic framework was developed to assemble, identify, and measure the proportion of unknown sequences present in distinct human microbiomes. This framework was applied to forty distinct studies, comprising 963 samples, and covering ten different human microbiomes including fecal, oral, lung, skin and circulatory system microbiomes. The framework was used to determine the proportion of taxonomically unknown sequences present within samples, and to compare such sequences both within and across assembled metagenomes. We found that whilst the human microbiome is one of the most extensively studied, on average 2% of assembled sequences have not yet been taxonomically defined. However, this proportion varied extensively among different microbiomes and was as high as 25% for skin and oral microbiomes that have more interactions with the environment. The publicly available data sets used have not previously been systematically mined to quantify and compare such dark matter. Typically, these unknown sequences are found in several microbiomes and potentially belong to unidentified novel microbes that we interact with on a daily basis. A cross-study comparison led to the identification of similar unknown sequences in different samples and/or microbiomes. A rate of taxonomic characterisation of 1.64% of unknown sequences being characterised per month was calculated from these taxonomically unknown sequences discovered in this study. Additionally, the approach led to the discovery of several potentially novel viral genomes that bear no similarity to sequences in the public databases. Both our computational framework and the novel unknown sequences produced are publicly available for future cross-referencing.

bioinformatics↗

Exploring the natural origins of SARS-CoV-2

The lack of an identifiable intermediate host species for the proximal animal ancestor of SARS-CoV-2, and the large geographical distance between Wuhan and where the closest evolutionary related coronaviruses circulating in horseshoe bats (Sarbecoviruses) have been identified, is fuelling speculation on the natural origins of SARS-CoV-2. We have comprehensively analysed phylogenetic relations between SARS-CoV-2, and the related bat and pangolin Sarbecoviruses sampled so far. Determining the likely recombination events reveals a highly reticulate evolutionary history within this group of coronaviruses. Clustering of the inferred recombination events is non-random with evidence that Spike, the main target for humoral immunity, is beside a recombination hotspot likely driving antigenic shift in the ancestry of bat Sarbecoviruses. Coupled with the geographic ranges of their hosts and the sampling locations, across southern China, and into Southeast Asia, we confirm horseshoe bats, Rhinolophus, are the likely SARS-CoV-2 progenitor reservoir species. By tracing the recombinant sequence patterns, we conclude that there has been relatively recent geographic movement and co-circulation of these viruses ancestors, extending across their bat host ranges in China and Southeast Asia over the last 100 years or so. We confirm that a direct proximal ancestor to SARS-CoV-2 is yet to be sampled, since the closest relative shared a common ancestor with SARS-CoV-2 approximately 40 years ago. Our analysis highlights the need for more wildlife sampling to (i) pinpoint the exact origins of SARS-CoV-2s animal progenitor, and (ii) survey the extent of the diversity in the related Sarbecoviruses phylogeny that present high risk for future spillover. HighlightsO_LIThe origin of SARS-CoV-2 can be traced to horseshoe bats, genus Rhinolophus, with ranges in both China and Southeast Asia. C_LIO_LIThe closest known relatives of SARS-CoV-2 exhibit frequent transmission among their Rhinolophus host species. C_LIO_LISarbecoviruses have undergone extensive recombination throughout their evolutionary history. C_LIO_LIAccounting for the mosaic patterns of these recombinants is important when inferring relatedness to SARS-CoV-2. C_LIO_LIBreakpoint patterns are consistent with recombination hotspots in the coronavirus genome, particularly upstream of the pike open reading frame with a coldspot in S1. C_LI

evolutionary biology↗

Meta-analysis of virus-induced host gene expression reveals unique signatures of immune dysregulation induced by SARS-CoV-2

The clinical outcome of COVID-19 has an extreme age, genetic and comorbidity bias that is thought to be driven by an impaired immune response to SARS-CoV-2, the causative agent of the disease. The unprecedented impact of COVID-19 on global health has resulted in multiple studies generating extensive gene expression datasets in a relatively short period of time. In order to better understand the immune dysregulation induced by SARS-CoV-2, we carried out a meta-analysis of these transcriptomics data available in the published literature. Datasets included both those available from SARS-CoV-2 infected cell lines in vitro and those from patient samples. We focused our analysis on the identification of viral perturbed host functions as captured by co-expressed gene module analysis. Transcriptomics data from lung biopsies and nasopharyngeal samples, as opposed to those available from other clinical samples and infected cell lines, provided key signatures on the role of the hosts immune response on COVID-19 pathogenesis. For example, severity of infection and patients age are linked to the absence of stimulation of the RIG-I-like receptor signaling pathway, a known critical immediate line of defense against RNA viral infections that triggers type-I interferon responses. In addition, co-expression analysis of age-stratified transcriptional data provided evidence that signatures of key immune response pathways are perturbed in older COVID-19 patients. In particular, dysregulation of antigen-presenting components, down-regulation of cell cycle mechanisms and signatures of hyper-enriched monocytes were strongly correlated with the age of older individuals infected with SARS-CoV-2. Collectively, our meta-analysis highlights the ability of transcriptomics and gene-module analysis of aggregated datasets to aid our improved understanding of the host-specific disease mechanisms underpinning COVID-19.

bioinformatics↗

Recurrent emergence and transmission of a SARS-CoV-2 Spike deletion ΔH69/V70

SARS-CoV-2 amino acid replacements in the receptor binding domain (RBD) occur relatively frequently and some have a consequence for immune recognition. Here we report recurrent emergence and significant onward transmission of a six-nucleotide out of frame deletion in the S gene, which results in loss of two amino acids: H69 and V70. We report that in human infections {Delta}H69/V70 often co-occurs with the receptor binding motif amino acid replacements N501Y, N439K and Y453F, and in the latter two cases has followed the RBD mutation. One of the {Delta}H69/V70+ N501Y lineages, now known as B.1.1.7, has undergone rapid expansion and includes eight S gene mutations: RBD (N501Y and A570D), S1 ({Delta}H69/V70 and {Delta}144) and S2 (P681H, T716I, S982A and D1118H). In vitro, we show that {Delta}H69/V70 does not reduce serum neutralisation across multiple convalescent sera. However, {Delta}H69/V70 increases infectivity and is associated with increased incorporation of cleaved spike into virions. {Delta}H69/V70 is able to compensate for small infectivity defects induced by RBD mutations N501Y, N439K and Y453F. In addition, replacement of H69 and V70 residues in the B.1.1.7 spike reduces its infectivity and spike mediated cell-cell fusion. Based on our data {Delta}H69/V70 likely acts as a permissive mutation that allows acquisition of otherwise deleterious immune escape mutations. Enhanced surveillance for the {Delta}H69/V70 deletion with and without RBD mutations should be considered as a global priority not only as a marker for the B.1.1.7 variant, but potentially also for other emerging variants of concern. Vaccines designed to target the deleted spike protein could mitigate against its emergence as increased selective forces from immunity and vaccines increase globally. HighlightsO_LI{Delta}H69/V70 is present in at least 28 SARS-CoV-2 lineages C_LIO_LI{Delta}H69/V70 does not confer escape from convalescent sera C_LIO_LI{Delta}H69/V70 increases spike infectivity and compensates for RBD mutations C_LIO_LI{Delta}H69/V70 is associated with greater spike cleavage C_LIO_LIB.1.1.7 requires {Delta}H69/V70 for optimal spike cleavage and infectivity C_LI

microbiology↗

Respiratory disease in cats associated with human-to-cat transmission of SARS-CoV-2 in the UK

Two cats from different COVID-19-infected households in the UK were found to be infected with SARS-CoV-2 from humans, demonstrated by immunofluorescence, in situ hybridisation, reverse transcriptase quantitative PCR and viral genome sequencing. Lung tissue collected post-mortem from cat 1 displayed pathological and histological findings consistent with viral pneumonia and tested positive for SARS-CoV-2 antigens and RNA. SARS-CoV-2 RNA was detected in an oropharyngeal swab collected from cat 2 that presented with rhinitis and conjunctivitis. High throughput sequencing of the virus from cat 2 revealed that the feline viral genome contained five single nucleotide polymorphisms (SNPs) compared to the nearest UK human SARS-CoV-2 sequence. An analysis of cat 2s viral genome together with nine other feline-derived SARS-CoV-2 sequences from around the world revealed no shared catspecific mutations. These findings indicate that human-to-cat transmission of SARS-CoV-2 occurred during the COVID-19 pandemic in the UK, with the infected cats developing mild or severe respiratory disease. Given the versatility of the new coronavirus, it will be important to monitor for human-to-cat, cat-to-cat and cat-to-human transmission.

microbiology↗

Bacteriophage deficiency characterizes respiratory virome dysbiosis in childhood asthma

Asthma development and persistence is tightly linked to respiratory viruses. Viral presence is usually interrogated with targeted approaches during periods of disease activity and/or infections, thus neglecting viral occurrence during steady states. We investigate the virome in the upper respiratory system of healthy and asthmatic preschool children during asymptomatic/non-infection periods using metagenomics. Children with asthma have a characteristically dysbiotic virome that correlates to disease severity and control. The major component of dysbiosis is bacteriophage deficiency, while eukaryotic viral presence is increased. At the metacommunity level, differential virus species co-occurrence patterns suggest a decrease of the microbiota community resilience in asthma. Viral dysbiosis is therefore a key characteristic of asthma pathophysiology.

microbiology↗

Evidence of significant natural selection in the evolution of SARS-CoV-2 in bats, not humans

RNA viruses are proficient at switching host species, and evolving adaptations to exploit the new hosts cells efficiently. Surprisingly, SARS-CoV-2 has apparently required no significant adaptation to humans since the start of the COVID-19 pandemic, with no observed selective sweeps since genome sampling began. Here we assess the types of natural selection taking place in Sarbecoviruses in horseshoe bats versus SARS-CoV-2 evolution in humans. While there is moderate evidence of diversifying positive selection in SARS-CoV-2 in humans, it is limited to the early phase of the pandemic, and purifying selection is much weaker in SARS-CoV-2 than in related bat Sarbecoviruses. In contrast, our analysis detects significant positive episodic diversifying selection acting on the bat virus lineage SARS-CoV-2 emerged from, accompanied by an adaptive depletion in CpG composition presumed to be linked to the action of antiviral mechanisms in ancestral hosts. The closest bat virus to SARS-CoV-2, RmYN02 (sharing an ancestor [~]1976), is a recombinant with a structure that includes differential CpG content in Spike; clear evidence of coinfection and evolution in bats without involvement of other species. Collectively our results demonstrate the progenitor of SARS-CoV-2 was capable of near immediate human-human transmission as a consequence of its adaptive evolutionary history in bats, not humans.

evolutionary biology↗

Evolutionary origins of the SARS-CoV-2 sarbecovirus lineage responsible for the COVID-19 pandemic

There are outstanding evolutionary questions on the recent emergence of coronavirus SARS-CoV-2/hCoV-19 in Hubei province that caused the COVID-19 pandemic, including (1) the relationship of the new virus to the SARS-related coronaviruses, (2) the role of bats as a reservoir species, (3) the potential role of other mammals in the emergence event, and (4) the role of recombination in viral emergence. Here, we address these questions and find that the sarbecoviruses - the viral subgenus responsible for the emergence of SARS-CoV and SARS-CoV-2 - exhibit frequent recombination, but the SARS-CoV-2 lineage itself is not a recombinant of any viruses detected to date. In order to employ phylogenetic methods to date the divergence events between SARS-CoV-2 and the bat sarbecovirus reservoir, recombinant regions of a 68-genome sarbecovirus alignment were removed with three independent methods. Bayesian evolutionary rate and divergence date estimates were consistent for all three recombination-free alignments and robust to two different prior specifications based on HCoV-OC43 and MERS-CoV evolutionary rates. Divergence dates between SARS-CoV-2 and the bat sarbecovirus reservoir were estimated as 1948 (95% HPD: 1879-1999), 1969 (95% HPD: 1930-2000), and 1982 (95% HPD: 1948-2009). Despite intensified characterization of sarbecoviruses since SARS, the lineage giving rise to SARS-CoV-2 has been circulating unnoticed for decades in bats and been transmitted to other hosts such as pangolins. The occurrence of a third significant coronavirus emergence in 17 years together with the high prevalence and virus diversity in bats implies that these viruses are likely to cross species boundaries again. In BriefThe Betacoronavirus SARS-CoV-2 is a member of the sarbecovirus subgenus which shows frequent recombination in its evolutionary history. We characterize the extent of this genetic exchange and identify non-recombining regions of the sarbecovirus genome using three independent methods to remove the effects of recombination. Using these non-recombining genome regions and prior information on coronavirus evolutionary rates, we obtain estimates from three approaches that the most likely divergence date of SARS-CoV-2 from its most closely related available bat sequences ranges from 1948 to 1982. Key PointsO_LIRaTG13 is the closest available bat virus to SARS-CoV-2; a sub-lineage of these bat viruses is able to infect humans. Two sister lineages of the RaTG13/SARS-CoV-2 lineage infect Malayan pangolins. C_LIO_LIThe sarbecoviruses show a pattern of deep recombination events, indicating that there are high levels of co-infection in horseshoe bats and that the viral pool can generate novel allele combinations and substantial genetic diversity; the sarbecoviruses are efficient explorers of phenotype space. C_LIO_LIThe SARS-CoV-2 lineage is not a recent recombinant, at least not involving any of the bat or pangolin viruses sampled to date. C_LIO_LINon-recombinant regions of the sarbecoviruses can be identified, allowing for phylogenetic inference and dating to be performed. We constructed three such regions using different methods. C_LIO_LIWe estimate that RaTG13 and SARS-CoV-2 diverged 40 to 70 years ago. There is a diverse unsampled reservoir of generalist viruses established in horseshoe bats. C_LIO_LIWhile an intermediate host responsible for the zoonotic event cannot be ruled out, the relevant evolution for spillover to humans very likely occurred in horseshoe bats. C_LI

evolutionary biology↗

Increased resolution of African Swine Fever Virus genome patterns based on profile HMM protein domains

African Swine Fever Virus (ASFV) was originally described in Africa almost 100 years ago and is now spreading uncontrolled across Europe and Asia and threatening to destroy the domestic pork industry. Neither effective antiviral drugs nor a protective vaccine are currently available. Efforts to understand the basis for viral pathogenicity and the development of attenuated potential vaccine strains are complicated by the large and complex ASFV genome. We report here a novel method of documenting viral diversity based on profile Hidden Markov Model domains on a genome scale. The method can be used to infer genomic relationships independent of genome alignments and also reveal ASFV genome sequence differences that alter the presence of functional protein domains in the virus. We show that the method can quickly identify differences and shared patterns between virulent and attenuated ASFV strains and will be a useful tool for developing much-needed vaccines and antiviral agents to help control this virus. The tool is rapid to run and easy to implement, readily available as a simple Docker image.

genomics↗

Human genetic disease is greatly influenced by the underlying fragility of evolutionarily ancient genes

The ability to predict disease association in human genes is enhanced by an evolutionary understanding. Importantly genes linked with heritable disease, particularly dominant disorders, tend to have undergone duplication in our early vertebrate ancestors, with a strong asymmetric relationship between disease-association within duplicate/paralog pairs. Using a novel phylogenetic approach, alongside a whole-genome comparative analysis, we show that contrary to the accepted compensatory model of disease evolution, the majority of disease-associations reside with the more evolutionary constrained gene, inferred to most closely resemble the progenitor. This indicates that the strong association between paralogs, specifically ohnologs, and dominant disorders is often a consequence of a mechanism through which pre-existing dosage sensitive/haploinsufficient genes are successfully duplicated and retained. Heritable disease is thus as much a consequence of the fragility of evolutionarily more ancient genes as compensatory mechanisms. From these findings, we demonstrate the utility of a new model with which to predict disease associated genes in the human genome.

genetics↗

Using set theory to reduce redundancy in pathway sets

1.1.01 BackgroundThe consolidation of pathway databases, such as KEGG[1], Reactome[2]and ConsensusPathDB[3], has generated widespread biological interest, however the issue of pathway redundancy impedes the use of these consolidated datasets. Attempts to reduce this redundancy have focused on visualizing pathway overlap or merging pathways, but the resulting pathways may be of heterogeneous sizes and cover multiple biological functions. Efforts have also been made to deal with redundancy in pathway data by consolidating enriched pathways into a number of clusters or concepts. We present an alternative approach, which generates pathway subsets capable of covering all of genes presented within either pathway databases or enrichment results, generating substantial reductions in redundancy.\n\n1.02 ResultsWe propose a method that uses set cover to reduce pathway redundancy, without merging pathways. The proposed approach considers three objectives: removal of pathway redundancy, controlling pathway size and coverage of the gene set. By applying set cover to the ConsensusPathDB dataset we were able to produce a reduced set of pathways, representing 100% of the genes in the original data set with 74% less redundancy, or 95% of the genes with 88% less redundancy. We also developed an algorithm to simplify enrichment data and applied it to a set of enriched osteoarthritis pathways, revealing that within the top ten pathways, five were redundant subsets of more enriched pathways. Applying set cover to the enrichment results removed these redundant pathways allowing more informative pathways to take their place.\n\n1.03 ConclusionOur method provides an alternative approach for handling pathway redundancy, while ensuring that the pathways are of homogeneous size and gene coverage is maximised. Pathways are not altered from their original form, allowing biological knowledge regarding the data set to be directly applicable. We demonstrate the ability of the algorithms to prioritise redundancy reduction, pathway size control or gene set coverage. The application of set cover to pathway enrichment results produces an optimised summary of the pathways that best represent the differentially regulated gene set.

bioinformatics↗

Network controllability: viruses are driver agents in dynamic molecular systems

In recent years control theory has been applied to biological systems with the aim of identifying the minimum set of molecular interactions that can drive the network to a required state. However in an intra-cellular network it is unclear what control means. To address this limitation we use viral infection, specifically HIV-1 and HCV, as a paradigm to model control of an infected cell. Using a large human signalling network comprised of over 6000 human proteins and more than 34000 directed interactions, we compared two dynamic states: normal/uninfected and infected. Our network controllability analysis demonstrates how a virus efficiently brings the dynamic host system into its control by mostly targeting existing critical control nodes, requiring fewer nodes than in the uninfected network. The driver nodes used by the virus are distributed throughout the pathways in specific locations enabling effective control of the cell via the high control centrality of the viral and targeted host nodes. Furthermore, this viral infection of the human system permits discrimination between available network-control models, and demonstrates the minimum-dominating set (MDS) method better accounts for how biological information and signals are transferred than the maximum matching (MM) method as it identified most of the HIV-1 proteins as critical driver nodes and goes beyond identifying receptors as the only critical driver nodes. This is because MDS, unlike MM, accounts for the inherent non-linearity of signalling pathways. Our results demonstrate control-theory gives a more complete and dynamic understanding of the viral hijack mechanism when compared with previous analyses limited to static single-state networks.

systems biology↗

Protein Structural Disorder Of The Envelope V3 Loop Contributes To The Switch In Human Immunodeficiency Virus Type 1 Cell Tropism

Human immunodeficiency virus type 1 (HIV-1) envelope gp120 is partly an intrinsically disordered (unstructured/disordered) protein as it contains regions that do not fold into well-defined protein structures. These disordered regions play important roles in HIVs life cycle, particularly, V3 loop-dependent cell entry, which determines how the virus uses two coreceptors on immune cells, the chemokine receptors CCR5 (R5), CXCR4 (X4) or both (R5X4 virus). Most infecting HIV-1 variants utilise CCR5, while a switch to CXCR4-use occurs in the majority of infections. Why does this rewiring event occur in HIV-1 infected patients? As changes in the charge of the V3 loop are associated with this receptor switch and it has been suggested that charged residues promote structure disorder, we hypothesise that the intrinsic disorder of the V3 loop plays a role in determining cell tropism. To test this we use three independent data sets of gp120 to analyse V3 loop disorder. We find that the V3 loop of X4 virus has significantly higher intrinsic disorder tendency than R5 and R5X4 virus, while R5X4 virus has the lowest. These results indicate that structural disorder plays an important role in determining HIV-1 cell tropism and CXCR4 binding. We speculate that changes in N-linked glycosylation associated with tropism change (from R5 to X4) are required to stabilise the V3 loop with increased disorder tendency during HIV-1 evolution. We discuss the potential evolutionary mechanisms leading to the fixation of disorder promoting mutations and the adaptive potential of protein structural disorder in viral host adaptation.\n\nIMPORTANCEHIV-1 cell entry relies on the V3 loop of its heavily glycosylated envelope protein gp120 to bind to a host coreceptor CCR5 or CXCR4. Unraveling the mechanism whereby HIV-1 switches host coreceptor is critical to understanding HIV-1 pathogenesis and development of novel intervention strategies. However, a mechanistic understanding of the switch is limited as no gp120-CCR5/CXCR4 complex is available, due to the intrinsically disordered nature of the V3 loop responsible for coreceotor swtich. We hypothesise that shifts of V3 disorder may contribute to HIV-1 coreceptor switch and cell tropism. In this study we compared the disorder tendency of the V3 loop before and after the coreceptor switch. We find that the coreceptor switch is associated with a significant increase of V3 loop disorder from CCR5 to CXCR4 using. This result provides a mechanistic explanation of coreceptor switch that increasingly disordered V3 loop results in use of a different host coreceptor.

bioinformatics↗