Topological analysis of protein co-abundance networks identifies novel host targets important for HCV infection and pathogenesis

<p>Abstract</p> <p>Background</p> <p>High-throughput methods for obtaining global measurements of transcript and protein levels in biological samples has provided a large amount of data for identification of 'target' genes and proteins of interest. These targets may be mediators of functional processes involved in disease and therefore represent key points of control for viruses and bacterial pathogens. Genes and proteins that are the most highly differentially regulated are generally considered to be the most important. We present topological analysis of co-abundance networks as an alternative to differential regulation for confident identification of target proteins from two related global proteomics studies of hepatitis C virus (HCV) infection.</p> <p>Results</p> <p>We analyzed global proteomics data sets from a cell culture study of HCV infection and from a clinical study of liver biopsies from HCV-positive patients. Using lists of proteins known to be interaction partners with pathogen proteins we show that the most differentially regulated proteins in both data sets are indeed enriched in pathogen interactors. We then use these data sets to generate co-abundance networks that link proteins based on similar abundance patterns in time or across patients. Analysis of these co-abundance networks using a variety of network topology measures revealed that both degree and betweenness could be used to identify pathogen interactors with better accuracy than differential regulation alone, though betweenness provides the best discrimination. We found that though overall differential regulation was not correlated between the cell culture and liver biopsy data, network topology was conserved to an extent. Finally, we identified a set of proteins that has high betweenness topology in both networks including a protein that we have recently shown to be essential for HCV replication in cell culture.</p> <p>Conclusions</p> <p>The results presented show that the network topology of protein co-abundance networks can be used to identify proteins important for viral replication. These proteins represent targets for further experimental investigation that will provide biological insight and potentially could be exploited for novel therapeutic approaches to combat HCV infection.</p

A Systems Biology Approach to Infectious Disease Research: Innovating the Pathogen-Host Research Paradigm

The twentieth century was marked by extraordinary advances in our understanding of microbes and infectious disease, but pandemics remain, food and waterborne illnesses are frequent, multidrug-resistant microbes are on the rise, and the needed drugs and vaccines have not been developed. The scientific approaches of the past—including the intense focus on individual genes and proteins typical of molecular biology—have not been sufficient to address these challenges. The first decade of the twenty-first century has seen remarkable innovations in technology and computational methods. These new tools provide nearly comprehensive views of complex biological systems and can provide a correspondingly deeper understanding of pathogen-host interactions. To take full advantage of these innovations, the National Institute of Allergy and Infectious Diseases recently initiated the Systems Biology Program for Infectious Disease Research. As participants of the Systems Biology Program, we think that the time is at hand to redefine the pathogen-host research paradigm

Conserved host response to highly pathogenic avian influenza virus infection in human cell culture, mouse and macaque model systems

<p>Abstract</p> <p>Background</p> <p>Understanding host response to influenza virus infection will facilitate development of better diagnoses and therapeutic interventions. Several different experimental models have been used as a proxy for human infection, including cell cultures derived from human cells, mice, and non-human primates. Each of these systems has been studied extensively in isolation, but little effort has been directed toward systematically characterizing the conservation of host response on a global level beyond known immune signaling cascades.</p> <p>Results</p> <p>In the present study, we employed a multivariate modeling approach to characterize and compare the transcriptional regulatory networks between these three model systems after infection with a highly pathogenic avian influenza virus of the H5N1 subtype. Using this approach we identified functions and pathways that display similar behavior and/or regulation including the well-studied impact on the interferon response and the inflammasome. Our results also suggest a primary response role for airway epithelial cells in initiating hypercytokinemia, which is thought to contribute to the pathogenesis of H5N1 viruses. We further demonstrate that we can use a transcriptional regulatory model from the human cell culture data to make highly accurate predictions about the behavior of important components of the innate immune system in tissues from whole organisms.</p> <p>Conclusions</p> <p>This is the first demonstration of a global regulatory network modeling conserved host response between <it>in vitro </it>and <it>in vivo </it>models.</p

Folyóirat vagy gyűjteményes kötet? (Csokonai Diétai Magyar Múzsája)

BACKGROUND: The complex interplay between viral replication and host immune response during infection remains poorly understood. While many viruses are known to employ anti-immune strategies to facilitate their replication, highly pathogenic virus infections can also cause an excessive immune response that exacerbates, rather than reduces pathogenicity. To investigate this dichotomy in severe acute respiratory syndrome coronavirus (SARS-CoV), we developed a transcriptional network model of SARS-CoV infection in mice and used the model to prioritize candidate regulatory targets for further investigation. RESULTS: We validated our predictions in 18 different knockout (KO) mouse strains, showing that network topology provides significant predictive power to identify genes that are important for viral infection. We identified a novel player in the immune response to virus infection, Kepi, an inhibitory subunit of the protein phosphatase 1 (PP1) complex, which protects against SARS-CoV pathogenesis. We also found that receptors for the proinflammatory cytokine tumor necrosis factor alpha (TNFα) promote pathogenesis, presumably through excessive inflammation. CONCLUSIONS: The current study provides validation of network modeling approaches for identifying important players in virus infection pathogenesis, and a step forward in understanding the host response to an important infectious disease. The results presented here suggest the role of Kepi in the host response to SARS-CoV, as well as inflammatory activity driving pathogenesis through TNFα signaling in SARS-CoV infections. Though we have reported the utility of this approach in bacterial and cell culture studies previously, this is the first comprehensive study to confirm that network topology can be used to predict phenotypes in mice with experimental validation

Proteome Profiling Outperforms Transcriptome Profiling for Coexpression Based Gene Function Prediction

Coexpression of mRNAs under multiple conditions is commonly used to infer cofunctionality of their gene products despite well-known limitations of this “guilt-by-association” (GBA) approach. Recent advancements in mass spectrometry-based proteomic technologies have enabled global expression profiling at the protein level; however, whether proteome profiling data can outperform transcriptome profiling data for coexpression based gene function prediction has not been systematically investigated. Here, we address this question by constructing and analyzing mRNA and protein coexpression networks for three cancer types with matched mRNA and protein profiling data from The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC). Our analyses revealed a marked difference in wiring between the mRNA and protein coexpression networks. Whereas protein coexpression was driven primarily by functional similarity between coexpressed genes, mRNA coexpression was driven by both cofunction and chromosomal colocalization of the genes. Functionally coherent mRNA modules were more likely to have their edges preserved in corresponding protein networks than functionally incoherent mRNA modules. Proteomic data strengthened the link between gene expression and function for at least 75% of Gene Ontology (GO) biological processes and 90% of KEGG pathways. A web application Gene2Net (http://cptac.gene2net.org) developed based on the three protein coexpression networks revealed novel gene-function relationships, such as linking ERBB2 (HER2) to lipid biosynthetic process in breast cancer, identifying PLG as a new gene involved in complement activation, and identifying AEBP1 as a new epithelial-mesenchymal transition (EMT) marker. Our results demonstrate that proteome profiling outperforms transcriptome profiling for coexpression based gene function prediction. Proteomics should be integrated if not preferred in gene function and human disease studies

A Network Integration Approach to Predict Conserved Regulators Related to Pathogenicity of Influenza and SARS-CoV Respiratory Viruses

Respiratory infections stemming from influenza viruses and the Severe Acute Respiratory Syndrome corona virus (SARS-CoV) represent a serious public health threat as emerging pandemics. Despite efforts to identify the critical interactions of these viruses with host machinery, the key regulatory events that lead to disease pathology remain poorly targeted with therapeutics. Here we implement an integrated network interrogation approach, in which proteome and transcriptome datasets from infection of both viruses in human lung epithelial cells are utilized to predict regulatory genes involved in the host response. We take advantage of a novel "crowd-based" approach to identify and combine ranking metrics that isolate genes/proteins likely related to the pathogenicity of SARS-CoV and influenza virus. Subsequently, a multivariate regression model is used to compare predicted lung epithelial regulatory influences with data derived from other respiratory virus infection models. We predicted a small set of regulatory factors with conserved behavior for consideration as important components of viral pathogenesis that might also serve as therapeutic targets for intervention. Our results demonstrate the utility of integrating diverse 'omic datasets to predict and prioritize regulatory features conserved across multiple pathogen infection models

Efficiency and safety of varying the frequency of whole blood donation (INTERVAL): a randomised trial of 45 000 donors

Background: Limits on the frequency of whole blood donation exist primarily to safeguard donor health. However, there is substantial variation across blood services in the maximum frequency of donations allowed. We compared standard practice in the UK with shorter inter-donation intervals used in other countries. Methods: In this parallel group, pragmatic, randomised trial, we recruited whole blood donors aged 18 years or older from 25 centres across England, UK. By use of a computer-based algorithm, men were randomly assigned (1:1:1) to 12-week (standard) versus 10-week versus 8-week inter-donation intervals, and women were randomly assigned (1:1:1) to 16-week (standard) versus 14-week versus 12-week intervals. Participants were not masked to their allocated intervention group. The primary outcome was the number of donations over 2 years. Secondary outcomes related to safety were quality of life, symptoms potentially related to donation, physical activity, cognitive function, haemoglobin and ferritin concentrations, and deferrals because of low haemoglobin. This trial is registered with ISRCTN, number ISRCTN24760606, and is ongoing but no longer recruiting participants. Findings: 45 263 whole blood donors (22 466 men, 22 797 women) were recruited between June 11, 2012, and June 15, 2014. Data were analysed for 45 042 (99·5%) participants. Men were randomly assigned to the 12-week (n=7452) versus 10-week (n=7449) versus 8-week (n=7456) groups; and women to the 16-week (n=7550) versus 14-week (n=7567) versus 12-week (n=7568) groups. In men, compared with the 12-week group, the mean amount of blood collected per donor over 2 years increased by 1·69 units (95% CI 1·59–1·80; approximately 795 mL) in the 8-week group and by 0·79 units (0·69–0·88; approximately 370 mL) in the 10-week group (p&lt;0·0001 for both). In women, compared with the 16-week group, it increased by 0·84 units (95% CI 0·76–0·91; approximately 395 mL) in the 12-week group and by 0·46 units (0·39–0·53; approximately 215 mL) in the 14-week group (p&lt;0·0001 for both). No significant differences were observed in quality of life, physical activity, or cognitive function across randomised groups. However, more frequent donation resulted in more donation-related symptoms (eg, tiredness, breathlessness, feeling faint, dizziness, and restless legs, especially among men [for all listed symptoms]), lower mean haemoglobin and ferritin concentrations, and more deferrals for low haemoglobin (p&lt;0·0001 for each) than those observed in the standard frequency groups. Interpretation: Over 2 years, more frequent donation than is standard practice in the UK collected substantially more blood without having a major effect on donors' quality of life, physical activity, or cognitive function, but resulted in more donation-related symptoms, deferrals, and iron deficiency. Funding: NHS Blood and Transplant, National Institute for Health Research, UK Medical Research Council, and British Heart Foundation

Macaques vaccinated with live-attenuated SIV control replication of heterologous virus

An effective AIDS vaccine will need to protect against globally diverse isolates of HIV. To address this issue in macaques, we administered a live-attenuated simian immunodeficiency virus (SIV) vaccine and challenged with a highly pathogenic heterologous isolate. Vaccinees reduced viral replication by ∼2 logs between weeks 2–32 (P ≤ 0.049) postchallenge. Remarkably, vaccinees expressing MHC-I (MHC class I) alleles previously associated with viral control completely suppressed acute phase replication of the challenge virus, implicating CD8+ T cells in this control. Furthermore, transient depletion of peripheral CD8+ lymphocytes in four vaccinees during the chronic phase resulted in an increase in virus replication. In two of these animals, the recrudescent virus population contained only the vaccine strain and not the challenge virus. Alarmingly, however, we found evidence of recombinant viruses emerging in some of the vaccinated animals. This finding argues strongly against an attenuated virus vaccine as a solution to the AIDS epidemic. On a more positive note, our results suggest that MHC-I–restricted CD8+ T cells contribute to the protection induced by the live-attenuated SIV vaccine and demonstrate that vaccine-induced CD8+ T cell responses can control replication of heterologous challenge viruses

Efficacy of brief behavioral counselling by allied health professionals to promote physical activity in people with peripheral arterial disease (BIPP): study protocol for a multi-center randomized controlled trial

Background: Physical activity is recommended for people with peripheral arterial disease (PAD), and can improve walking capacity and quality of life; and reduce pain, requirement for surgery and cardiovascular events. This trial will assess the efficacy of a brief behavioral counselling intervention delivered by allied health professionals to improve physical activity in people with PAD. Methods: This is a multi-center randomised controlled trial in four cities across Australia. Participants (N = 200) will be recruited from specialist vascular clinics, general practitioners and research databases and randomised to either the control or intervention group. Both groups will receive usual medical care, a written PAD management information sheet including advice to walk, and four individualised contacts from a protocol-trained allied health professional over 3 months (weeks 1, 2, 6, 12). The control group will receive four 15-min telephone calls with general discussion about PAD symptoms and health and wellbeing. The intervention group will receive behavioral counselling via two 1-h face-to-face sessions and two 15-min telephone calls. The counselling is based on the 5A framework and will promote interval walking for 3 × 40 min/week. Assessments will be conducted at baseline, and 4, 12 and 24 months by staff blinded to participant allocation.Objectively assessed outcomes include physical activity (primary), sedentary behavior, lower limb body function, walking capacity, cardiorespiratory fitness, event-based claudication index, vascular interventions, clinical events, cardiovascular function, circulating markers, and anthropometric measures. Self-reported outcomes include physical activity and sedentary behavior, walking ability, pain severity, and health-related quality of life. Data will be analysed using an intention-to-treat approach. An economic evaluation will assess whether embedding the intervention into routine care would likely be value for money. A cost-effectiveness analysis will estimate change in cost per change in activity indicators due to the intervention, and a cost-utility analysis will assess change in cost per quality-adjusted life year. A full uncertainty analysis will be undertaken, including a value of information analysis, to evaluate the economic case for further research. Discussion: This trial will evaluate the efficacy and cost-effectiveness of a brief behavioral counselling intervention for a common cardiovascular disease with significant burden. Trial registration: ACTRN 12614000592640 Australian New Zealand Clinical Trials Registry. Registration Date 4 June 2014

Hypergraph models of biological networks to identify genes critical to pathogenic viral response

Background: Representing biological networks as graphs is a powerful approach to reveal underlying patterns, signatures, and critical components from high-throughput biomolecular data. However, graphs do not natively capture the multi-way relationships present among genes and proteins in biological systems. Hypergraphs are generalizations of graphs that naturally model multi-way relationships and have shown promise in modeling systems such as protein complexes and metabolic reactions. In this paper we seek to understand how hypergraphs can more faithfully identify, and potentially predict, important genes based on complex relationships inferred from genomic expression data sets. Results: We compiled a novel data set of transcriptional host response to pathogenic viral infections and formulated relationships between genes as a hypergraph where hyperedges represent significantly perturbed genes, and vertices represent individual biological samples with specific experimental conditions. We find that hypergraph betweenness centrality is a superior method for identification of genes important to viral response when compared with graph centrality. Conclusions: Our results demonstrate the utility of using hypergraphs to represent complex biological systems and highlight central important responses in common to a variety of highly pathogenic viruses