[Show abstract][Hide abstract] ABSTRACT: Viral engagement with macrophages activates Toll-Like-Receptors (TLRs) and viruses must contend with the ensuing inflammatory responses to successfully complete their replication cycle. To date, known counter-strategies involve the use of viral-encoded proteins that often employ mimicry mechanisms to block or redirect the host response to benefit the virus. Whether viral regulatory DNA sequences provide an opportunistic strategy by which viral enhancer elements functionally mimic innate immune enhancers is unknown. Here we find that host innate immune genes and the prototypical viral enhancer of cytomegalovirus (CMV) have comparable expression kinetics, and positively respond to common TLR agonists. In macrophages but not fibroblasts we show that activation of NFκB at immediate-early times of infection is independent of virion-associated protein, M45. We find upon virus infection or transfection of viral genomic DNA the TLR-agonist treatment results in significant enhancement of the virus transcription-replication cycle. In macrophage time-course infection experiments we demonstrate that TLR-agonist stimulation of the viral enhancer and replication cycle is strictly delimited by a temporal gate with a determined half-maximal time for enhancer-activation of 6 h; after which TLR-activation blocks the viral transcription-replication cycle. By performing a systematic siRNA screen of 149 innate immune regulatory factors we identify not only anticipated anti-viral and pro-viral contributions but also new factors involved in the CMV transcription-replication cycle. We identify a central convergent NFκB-SP1-RXR-IRF axis downstream of TLR-signalling. Activation of the RXR component potentiated direct and indirect TLR-induced activation of CMV transcription-replication cycle; whereas chromatin binding experiments using wild-type and enhancer-deletion virus revealed IRF3 and 5 as new pro-viral host transcription factor interactions with the CMV enhancer in macrophages. In a series of pharmacologic, siRNA and genetic loss-of-function experiments we determined that signalling mediated by the TLR-adaptor protein MyD88 plays a vital role for governing the inflammatory activation of the CMV enhancer in macrophages. Downstream TLR-regulated transcription factor binding motif disruption for NFκB, AP1 and CREB/ATF in the CMV enhancer demonstrated the requirement of these inflammatory signal-regulated elements in driving viral gene expression and growth in cells as well as in primary infection of neonatal mice. Thus, this study shows that the prototypical CMV enhancer, in a restricted time-gated manner, co-opts through DNA regulatory mimicry elements, innate-immune transcription factors to drive viral expression and replication in the face of on-going pro-inflammatory antiviral responses in vitro and in vivo and; suggests an unexpected role for inflammation in promoting acute infection and has important future implications for regulating latency.
[Show abstract][Hide abstract] ABSTRACT: Homeostasis underpins at a systems level the regulatory control of immunity and metabolism. While physiologically these systems are often viewed as independent, there is increasing evidence showing a tight coupling between immune and metabolic functions. Critically upon infection, the homeostatic regulation for both immune and metabolic pathways is altered yet these changes are often investigated in isolation. Here, we summarise our current understanding of these processes in the context of a clinically relevant pathogen, cytomegalovirus. We synthesise from the literature an integrative view of a coupled immune-metabolic infection process, centred on sugar and lipid metabolism. We put forward the notion that understanding immune control of key metabolic enzymatic steps in infection will promote the future development of novel therapeutic modalities based on metabolic modifiers that either enhance protection or inhibit infection.
Medical Microbiology and Immunology 03/2015; 204(3). DOI:10.1007/s00430-015-0402-5 · 3.04 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Interferons (IFNs) play a central role in immunity and emerging evidence suggests that IFN-signalling coordinately regulates sterol biosynthesis in macrophages, via Sterol Regulatory Element-Binding Protein (SREBP) dependent and independent pathways. However, the precise mechanisms and kinetic steps by which IFN controls sterol biosynthesis are as yet not fully understood. Here, we elucidate the molecular circuitry governing how IFN controls the first regulated step in the mevalonate-sterol pathway, 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR), through the synthesis of 25-Hydroxycholesterol (25-HC) from cholesterol by the IFN-inducible Cholesterol-25-Hydroxylase (CH25H). We show for the first 30-min of IFN stimulation of macrophages the rate of de novo synthesis of the Ch25h transcript is markedly increased but by 120-min becomes transcriptionally curtailed, coincident with induction of the Activating Transcription Factor 3 (ATF3) repressor. We demonstrate ATF3 induction by Toll-like receptors is strictly dependent on IFN-signalling. While the SREBP-pathway dependent rates of de novo transcription of Hmgcr are relatively unchanged in the first 90-min of IFN treatment, we find HMGCR enzyme levels undergo a rapid proteasomal-mediated degradation, defining a previously unappreciated SREBP-independent mechanism for IFN-action. These events precede a sustained marked reduction in Hmgcr RNA levels involving SREBP-dependent mechanisms. We demonstrate that HMGCR proteasomal-degradation by IFN strictly requires the synthesis of endogenous 25-HC and functionally couples HMGCR to CH25H to coordinately suppress sterol biosynthesis. In conclusion, we quantitatively delineate proteomic and transcriptional levels of IFN-mediated control of HMGCR, the primary enzymatic step of the mevalonate-sterol biosynthesis pathway, providing a foundational framework for mathematically modelling the therapeutic outcome of immune-metabolic pathways.
[Show abstract][Hide abstract] ABSTRACT: Neonatal infection remains a primary cause of infant morbidity and mortality worldwide and yet our understanding of how human neonates respond to infection remains incomplete. Changes in host gene expression in response to infection may occur in any part of the body, with the continuous interaction between blood and tissues allowing blood cells to act as biosensors for the changes. In this study we have used whole blood transcriptome profiling to systematically identify signatures and the pathway biology underlying the pathogenesis of neonatal infection. Blood samples were collected from neonates at the first clinical signs of suspected sepsis alongside age matched healthy control subjects. Here we report a detailed description of the study design, including clinical data collected, experimental methods used and data analysis workflows and which correspond with data in Gene Expression Omnibus (GEO) data sets (GSE25504). Our data set has allowed identification of a patient invariant 52-gene classifier that predicts bacterial infection with high accuracy and lays the foundation for advancing diagnostic, prognostic and therapeutic strategies for neonatal sepsis.
Genomics Data 03/2015; 3:41-48. DOI:10.1016/j.gdata.2014.11.003
[Show abstract][Hide abstract] ABSTRACT: CD200 receptor (CD200R) negatively regulates peripheral and mucosal innate immune responses. Viruses, including herpesviruses, have acquired functional CD200 orthologs, implying that viral exploitation of this pathway is evolutionary advantageous. However, the role that CD200R signaling plays during herpesvirus infection in vivo requires clarification. Utilizing the murine cytomegalovirus (MCMV) model, we demonstrate that CD200R facilitates virus persistence within mucosal tissue. Specifically, MCMV infection of CD200R-deficient mice (CD200R-/-) elicited heightened mucosal virus-specific CD4 T cell responses that restricted virus persistence in the salivary glands. CD200R did not directly inhibit lymphocyte effector function. Instead, CD200R-/- mice exhibited enhanced APC accumulation that in the mucosa was a consequence of elevated cellular proliferation. Although MCMV does not encode an obvious CD200 homolog, productive replication in macrophages induced expression of cellular CD200. CD200 from hematopoietic and non-hematopoietic cells contributed independently to suppression of antiviral control in vivo. These results highlight the CD200-CD200R pathway as an important regulator of antiviral immunity during cytomegalovirus infection that is exploited by MCMV to establish chronicity within mucosal tissue.
[Show abstract][Hide abstract] ABSTRACT: The recent exponential growth of genomic databases has resulted in the common task of sequence alignment becoming one of the major bottlenecks in the field of computational biology. It is typical for these large datasets and complex computations to require cost prohibitive High Performance Computing (HPC) to function. As such, parallelised solutions have been proposed but many exhibit scalability limitations and are incapable of effectively processing “Big Data” – the name attributed to datasets that are extremely large, complex and require rapid processing. The Hadoop framework, comprised of distributed storage and a parallelised programming framework known as MapReduce, is specifically designed to work with such datasets but it is not trivial to efficiently redesign and implement bioinformatics algorithms according to this paradigm. The parallelisation strategy of “divide and conquer” for alignment algorithms can be applied to both data sets and input query sequences. However, scalability is still an issue due to memory constraints or large databases, with very large database segmentation leading to additional performance decline. Herein, we present Hadoop Blast (HBlast), a parallelised BLAST algorithm that proposes a flexible method to partition both databases and input query sequences using “virtual partitioning”. HBlast presents improved scalability over existing solutions and well balanced computational work load while keeping database segmentation and recompilation to a minimum. Enhanced BLAST search performance on cheap memory constrained hardware has significant implications for in field clinical diagnostic testing; enabling faster and more accurate identification of pathogenic DNA in human blood or tissue samples.
[Show abstract][Hide abstract] ABSTRACT: Herein, we report the draft genome sequence of Staphylococcus warneri ED-NGS-1001, cultivated from a blood sample taken from a preterm neonate blood sepsis patient at the Royal Infirmary, Edinburgh,
Scotland, United Kingdom.
[Show abstract][Hide abstract] ABSTRACT: Herein, we report the draft genome sequence of Staphylococcus aureus ED-NGS-1006, cultivated from a blood sample taken from a neonatal sepsis patient at the Royal Infirmary in Edinburgh, Scotland,
[Show abstract][Hide abstract] ABSTRACT: Herein, we report the draft genome sequence of Enterococcus faecalis ED-NGS-1009, cultivated from a blood sample taken from a neonatal sepsis patient at the Royal Infirmary in Edinburgh, Scotland,
[Show abstract][Hide abstract] ABSTRACT: Herein, we report the draft genome sequence of Pantoea sp. ED-NGS-1003, cultivated from a blood sample taken from a neonatal sepsis patient at the Royal Infirmary, Edinburgh, Scotland,
[Show abstract][Hide abstract] ABSTRACT: Herein, we report the draft genome sequence for isolate ED-NGS-1015 of Serratia marcescens, cultivated from a blood sample obtained from a neonatal sepsis patient at the Royal Infirmary in Edinburgh, Scotland, United
[Show abstract][Hide abstract] ABSTRACT: Herein, we report the draft genome sequence of Streptococcus agalactiae ED-NGS-1000, cultivated from a blood sample taken from a preterm neonate blood sepsis patient at the Royal Infirmary, Edinburgh,
Scotland, United Kingdom.
[Show abstract][Hide abstract] ABSTRACT: Understanding how human neonates respond to infection remains incomplete. Here, a system-level investigation of neonatal systemic responses to infection shows a surprisingly strong but unbalanced homeostatic immune response; developing an elevated set-point of myeloid regulatory signalling and sugar-lipid metabolism with concomitant inhibition of lymphoid responses. Innate immune-negative feedback opposes innate immune activation while suppression of T-cell co-stimulation is coincident with selective upregulation of CD85 co-inhibitory pathways. By deriving modules of co-expressed RNAs, we identify a limited set of networks associated with bacterial infection that exhibit high levels of inter-patient variability. Whereas, by integrating immune and metabolic pathways, we infer a patient-invariant 52-gene-classifier that predicts bacterial infection with high accuracy using a new independent patient population. This is further shown to have predictive value in identifying infection in suspected cases with blood culture-negative tests. Our results lay the foundation for future translation of host pathways in advancing diagnostic, prognostic and therapeutic strategies for neonatal sepsis.
[Show abstract][Hide abstract] ABSTRACT: Vaccinia virus (VACV) is a large, cytoplasmic, double-stranded DNA virus that requires complex interactions with host proteins in order to replicate. To explore these interactions a functional high throughput small interfering RNA (siRNA) screen targeting 6719 druggable cellular genes was undertaken to identify host factors (HF) influencing the replication and spread of an eGFP-tagged VACV. The experimental design incorporated a low multiplicity of infection, thereby enhancing detection of cellular proteins involved in cell-to-cell spread of VACV. The screen revealed 153 pro- and 149 anti-viral HFs that strongly influenced VACV replication. These HFs were investigated further by comparisons with transcriptional profiling data sets and HFs identified in RNAi screens of other viruses. In addition, functional and pathway analysis of the entire screen was carried out to highlight cellular mechanisms involved in VACV replication. This revealed, as anticipated, that many pro-viral HFs are involved in translation of mRNA and, unexpectedly, suggested that a range of proteins involved in cellular transcriptional processes and several DNA repair pathways possess anti-viral activity. Multiple components of the AMPK complex were found to act as pro-viral HFs, while several septins, a group of highly conserved GTP binding proteins with a role in sequestering intracellular bacteria, were identified as strong anti-viral VACV HFs. This screen has identified novel and previously unexplored roles for cellular factors in poxvirus replication. This advancement in our understanding of the VACV life cycle provides a reliable knowledge base for the improvement of poxvirus-based vaccine vectors and development of anti-viral theraputics.
PLoS ONE 06/2014; 9(6):e98431. DOI:10.1371/journal.pone.0098431 · 3.23 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Sex differences in susceptibility to infections, and their clinical course and outcome, have been well described in the literature. Thus adult females generally mount more pronounced pro-inflammatory innate and adaptive immune responses to viral and bacterial infections than males, and generally males have poorer outcomes in bacterial septic shock. Despite this, few studies consider the effect of sex when analysing responses to vaccines. Females have been shown to mount stronger humoral responses to vaccines compared to males and have higher rates of adverse reactions.
International Journal of Infectious Diseases; 04/2014
[Show abstract][Hide abstract] ABSTRACT: The statistical language R is favoured by many biostatisticians for processing microarray data. In recent times, the quantity of data that can be obtained in experiments has risen significantly, making previously fast analyses time consuming or even not possible at all with the existing software infrastructure. High performance computing (HPC) systems offer a solution to these problems but at the expense of increased complexity for the end user. The Simple Parallel R Interface is a library for R that aims to reduce the complexity of using HPC systems by providing biostatisticians with drop-in parallelised replacements of existing R functions. In this paper we describe parallel implementations of two popular techniques: exploratory clustering analyses using the random forest classifier and feature selection through identification of differentially expressed genes using the rank product method.
Concurrency and Computation Practice and Experience 03/2014; 26(4). DOI:10.1002/cpe.2928 · 1.00 Impact Factor