•IFN-γ leads to the proteasomal degradation of HMGCR.•IFN-γ and 25-HC can transcriptionally and post-translationally alter levels of HMGCR.•The reduction of HMGCR through the action of IFN-γ requires the de novo synthesis of 25-HC by CH25H.
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.
HMGCR, 3-hydroxy-3-methylglutaryl-CoA reductase; 25-HC, 25-hydroxycholesterol; IFN, interferon; SREBP, sterol regulatory element-binding protein; SCAP, SREBP cleavage activating protein; ER, endoplasmic reticulum; ERAD, ER-associated protein degradation; FBS, fetal bovine serum; LPDS, lipoprotein depleted serum; MEV, mevalonate; LS, lanosterol; CHO, cholesterol; CH25H, cholesterol 25-hydroxylase; TLR, Toll-like receptor; BMDMs, bone marrow derived macrophages; DCs, dendritic cells; SBGN, systems biology graphical notation; PRRs, Pattern recognition receptors; IFNAR1, IFN-α/β receptor; CH25H; Cholesterol biosynthesis; 25-Hydroxycholesterol; Macrophages; Immunity; Infection
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.
Here we discover how inflammatory signalling may unintentionally promote infection, as a result of viruses evolving DNA sequences, known as enhancers, which act as a bait to prey on the infected cell transcription factors induced by inflammation. The major inflammatory transcription factors activated are part of the TLR-signalling pathway. We find the prototypical viral enhancer of cytomegalovirus can be paradoxically boosted by activation of inflammatory “anti-viral” TLR-signalling independent of viral structural proteins. This leads to an increase in viral gene expression and replication in cell-culture and upon infection of mice. We identify an axis of inflammatory transcription factors, acting downstream of TLR-signalling but upstream of interferon inhibition. Mechanistically, the central TLR-adapter protein MyD88 is shown to play a critical role in promoting viral enhancer activity in the first 6h of infection. The co-option of TLR-signalling exceeds the usage of NFκB, and we identify IRF3 and 5 as newly found viral-enhancer interacting inflammatory transcription factors. Taken together this study reveals how virus enhancers, employ a path of least resistance by directly harnessing within a short temporal window, the activation of anti-viral signalling in macrophages to drive viral gene expression and replication to an extent that has not been recognised before.
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.
Infection remains a leading cause of morbidity and mortality in neonates worldwide. Here the authors report disproportionate immune stimulatory, co-inhibitory and metabolic pathway responses that specifically mark bacterial infection and can be used to predict sepsis in neonatal patients at the first clinical signs of infection.
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.
HPC; Genomics; Parallel programming
Uterine NK cells (uNK) play a role in the regulation of placentation but their functions in non-pregnant endometrium are not understood. We have previously reported suppression of endometrial bleeding and alteration of spiral artery morphology in women exposed to asoprisnil, a progesterone receptor modulator. We now compare global endometrial gene expression in asoprisnil-treated versus control women, and we demonstrate a statistically significant reduction of genes in the IL-15 pathway, known to play a key role in uNK development and function. Suppression of IL-15 by asoprisnil was also observed at mRNA level (p<0.05), and immunostaining for NK cell marker CD56 revealed a striking reduction of uNK in asoprisnil-treated endometrium (p<0.001). IL-15 levels in normal endometrium are progesterone-responsive. Progesterone receptor (PR) positive stromal cells transcribe both IL-15 and IL-15RA. Thus, the response of stromal cells to progesterone will be to increase IL-15 trans-presentation to uNK, supporting their expansion and differentiation. In asoprisnil-treated endometrium, there is a marked down-regulation of stromal PR expression and virtual absence of uNK. These novel findings indicate that the IL-15 pathway provides a missing link in the complex interplay between endometrial stromal cells, uNK and spiral arteries affecting physiological and pathological endometrial bleeding.
Endometrium; spiral arteries; NK cells; IL-15
MicroRNAs (miRNAs) are a class of short non-coding RNA that play important roles in disease processes in animals and are present in a highly stable cell-free form in body fluids. Here, we examine the capacity of host and parasite miRNAs to serve as tissue or serum biomarkers of Schistosoma mansoni infection.
We used Exiqon miRNA microarrays to profile miRNA expression in the livers of mice infected with S. mansoni at 7 weeks post-infection. Thirty-three mouse miRNAs were differentially expressed in infected compared to naïve mice (>2 fold change, p<0.05) including miR-199a-3p, miR-199a-5p, miR-214 and miR-21, which have previously been associated with liver fibrosis in other settings. Five of the mouse miRNAs were also significantly elevated in serum by twelve weeks post-infection. Sequencing of small RNAs from serum confirmed the presence of these miRNAs and further revealed eleven parasite-derived miRNAs that were detectable by eight weeks post infection. Analysis of host and parasite miRNA abundance by qRT-PCR was extended to serum of patients from low and high infection sites in Zimbabwe and Uganda. The host-derived miRNAs failed to distinguish uninfected from infected individuals. However, analysis of three of the parasite-derived miRNAs (miR-277, miR-3479-3p and bantam) could detect infected individuals from low and high infection intensity sites with specificity/sensitivity values of 89%/80% and 80%/90%, respectively.
This work identifies parasite-derived miRNAs as novel markers of S. mansoni infection in both mice and humans, with the potential to be used with existing techniques to improve S. mansoni diagnosis. In contrast, although host miRNAs are differentially expressed in the liver during infection their abundance levels in serum are variable in human patients and may be useful in cases of extreme pathology but likely hold limited value for detecting prevalence of infection.
Schistosomiasis is a chronic disease caused by blood flukes that affects over 200 million people worldwide, of which 90% live in Sub-Saharan Africa. In the field setting schistosomiasis caused by S. mansoni is diagnosed by detection of parasite eggs in stool samples using microscopic techniques. Here we investigate the potential of microRNAs (miRNAs), a class of short noncoding RNAs, to act as biomarkers of S. mansoni infection. We have identified a specific subset of murine miRNAs whose expression is significantly altered in the liver between 6–12 weeks post infection. However their abundance in serum is not significantly different between naïve and S. mansoni-infected mice until twelve weeks post infection and they do not display consistent differential abundance in the serum of infected versus uninfected humans. In contrast, three parasite-derived miRNAs (miR-277, bantam and miR-3479-3p) were detected in the serum of infected mice and human patients and the combined detection of these miRNAs could distinguish S. mansoni infected from uninfected individuals from low and high infection intensity areas with 89%/80% or 80%/90% specificity/sensitivity, respectively. These results demonstrate that miRNAs of parasite origin are a new class of serum biomarker for detecting S. mansoni and likely other helminth infections.
Recent studies suggest that the sterol metabolic network participates in the interferon (IFN) antiviral response. However, the molecular mechanisms linking IFN with the sterol network and the identity of sterol mediators remain unknown. Here we report a cellular antiviral role for macrophage production of 25-hydroxycholesterol (cholest-5-en-3β,25-diol, 25HC) as a component of the sterol metabolic network linked to the IFN response via Stat1. By utilizing quantitative metabolome profiling of all naturally occurring oxysterols upon infection or IFN-stimulation, we reveal 25HC as the only macrophage-synthesized and -secreted oxysterol. We show that 25HC can act at multiple levels as a potent paracrine inhibitor of viral infection for a broad range of viruses. We also demonstrate, using transcriptional regulatory-network analyses, genetic interventions and chromatin immunoprecipitation experiments that Stat1 directly coupled Ch25h regulation to IFN in macrophages. Our studies describe a physiological role for 25HC as a sterol-lipid effector of an innate immune pathway.
► Macrophage PRR sensing of virus or IFN activation induce 25HC synthesis and secretion ► Stat1 rapidly binds and activates the promoter of cholesterol-25-hydroxylase (Ch25h) ► 25HC exerts multilevel antiviral function for a range of different viruses ► 25HC is an intrinsic paracrine and autocrine effector of the IFN antiviral response
Activated macrophages play a central role in controlling inflammatory responses to infection and are tightly regulated to rapidly mount responses to infectious challenge. Type I interferon (alpha/beta interferon [IFN-α/β]) and type II interferon (IFN-γ) play a crucial role in activating macrophages and subsequently restricting viral infections. Both types of IFNs signal through related but distinct signaling pathways, inducing a vast number of interferon-stimulated genes that are overlapping but distinguishable. The exact mechanism by which IFNs, particularly IFN-γ, inhibit DNA viruses such as cytomegalovirus (CMV) is still not fully understood. Here, we investigate the antiviral state developed in macrophages upon reversible inhibition of murine CMV by IFN-γ. On the basis of molecular profiling of the reversible inhibition, we identify a significant contribution of a restricted type I IFN subnetwork linked with IFN-γ activation. Genetic knockout of the type I-signaling pathway, in the context of IFN-γ stimulation, revealed an essential requirement for a primed type I-signaling process in developing a full refractory state in macrophages. A minimal transient induction of IFN-β upon macrophage activation with IFN-γ is also detectable. In dose and kinetic viral replication inhibition experiments with IFN-γ, the establishment of an antiviral effect is demonstrated to occur within the first hours of infection. We show that the inhibitory mechanisms at these very early times involve a blockade of the viral major immediate-early promoter activity. Altogether our results show that a primed type I IFN subnetwork contributes to an immediate-early antiviral state induced by type II IFN activation of macrophages, with a potential further amplification loop contributed by transient induction of IFN-β.
The global transcriptional program of murine cytomegalovirus (MCMV), involving coding, noncoding, and antisense transcription, remains unknown. Here we report an oligonucleotide custom microarray platform capable of measuring both coding and noncoding transcription on a genome-wide scale. By profiling MCMV wild-type and immediate-early mutant strains in fibroblasts, we found rapid activation of the transcriptome by 6.5 h postinfection, with absolute dependency on ie3, but not ie1 or ie2, for genomic programming of viral gene expression. Evidence is also presented to show, for the first time, genome-wide noncoding and bidirectional transcription at late stages of MCMV infection.
Upon infection, our immune cells produce a small protein called interferon, which in turn signals a protective response through a series of biochemical reactions that involves lowering the cells' ability to make cholesterol by targeting a gene essential for controlling the pathway for cholesterol metabolism.
Little is known about the protective role of inflammatory processes in modulating lipid metabolism in infection. Here we report an intimate link between the innate immune response to infection and regulation of the sterol metabolic network characterized by down-regulation of sterol biosynthesis by an interferon regulatory loop mechanism. In time-series experiments profiling genome-wide lipid-associated gene expression of macrophages, we show a selective and coordinated negative regulation of the complete sterol pathway upon viral infection or cytokine treatment with IFNγ or β but not TNF, IL1β, or IL6. Quantitative analysis at the protein level of selected sterol metabolic enzymes upon infection shows a similar level of suppression. Experimental testing of sterol metabolite levels using lipidomic-based measurements shows a reduction in metabolic output. On the basis of pharmacologic and RNAi inhibition of the sterol pathway we show augmented protection against viral infection, and in combination with metabolite rescue experiments, we identify the requirement of the mevalonate-isoprenoid branch of the sterol metabolic network in the protective response upon statin or IFNβ treatment. Conditioned media experiments from infected cells support an involvement of secreted type 1 interferon(s) to be sufficient for reducing the sterol pathway upon infection. Moreover, we show that infection of primary macrophages containing a genetic knockout of the major type I interferon, IFNβ, leads to only a partial suppression of the sterol pathway, while genetic knockout of the receptor for all type I interferon family members, ifnar1, or associated signaling component, tyk2, completely abolishes the reduction of the sterol biosynthetic activity upon infection. Levels of the proteolytically cleaved nuclear forms of SREBP2, a key transcriptional regulator of sterol biosynthesis, are reduced upon infection and IFNβ treatment at both the protein and de novo transcription level. The reduction in srebf2 gene transcription upon infection and IFN treatment is also found to be strictly dependent on ifnar1. Altogether these results show that type 1 IFN signaling is both necessary and sufficient for reducing the sterol metabolic network activity upon infection, thereby linking the regulation of the sterol pathway with interferon anti-viral defense responses. These findings bring a new link between sterol metabolism and interferon antiviral response and support the idea of using host metabolic modifiers of innate immunity as a potential antiviral strategy.
Currently, little is known about the crosstalk between the body's immune and metabolic systems that occurs after viral infection. This work uncovers a previously unappreciated physiological role for the cholesterol-metabolic pathway in protecting against infection that involves a molecular link with the protein interferon, which is made by immune cells and known to “interfere” with viral replication. We used a clinically relevant model based on mouse cytomegalovirus (CMV) infection of bone-marrow-derived cells. Upon infection these cells produce high levels of interferon as part of the innate-immune response, which we show in turn signals through the interferon receptor resulting in lowering enzyme levels on the cholesterol pathway. We observed this effect with a range of other viruses, and in each case it leads to a notable drop in the metabolites involved in the cholesterol pathway. We found that the control mechanism involves regulation by interferon of an essential transcription factor, named SREBP-2, which coordinates the gene activity of the cholesterol pathway. This mechanism may explain clinical observations of reduced cholesterol levels in patients receiving interferon treatment. Our initial investigation into how lowered cholesterol might protect against viral infection reveals that the protection is not due to a requirement of the virus for cholesterol itself but instead involves a particular side-branch of the pathway that chemically links lipids to proteins. Drugs such as statins and small interfering RNAs that block this part of the pathway are also shown to protect against CMV infection of cells in culture and in mice. This provides the first example of targeting a host metabolic pathway in order to protect against an acute infection.
RNA interference (RNAi) has become a powerful technique for reverse genetics and drug discovery and, in both of these areas, large-scale high-throughput RNAi screens are commonly performed. The statistical techniques used to analyze these screens are frequently borrowed directly from small-molecule screening; however small-molecule and RNAi data characteristics differ in meaningful ways. We examine the similarities and differences between RNAi and small-molecule screens, highlighting particular characteristics of RNAi screen data that must be addressed during analysis. Additionally, we provide guidance on selection of analysis techniques in the context of a sample workflow.
Interferons (IFNs) are potent antiviral cytokines capable of reprogramming the macrophage phenotype through the induction of interferon-stimulated genes (ISGs). Here we have used targeted RNA interference to suppress the expression of a number of key genes associated with IFN signalling in murine macrophages prior to stimulation with interferon-gamma. Genome-wide changes in transcript abundance caused by siRNA activity were measured using exon-level microarrays in the presence or absence of IFNγ.
Transfection of murine bone-marrow derived macrophages (BMDMs) with a non-targeting (control) siRNA and 11 sequence-specific siRNAs was performed using a cationic lipid transfection reagent (Lipofectamine2000) prior to stimulation with IFNγ. Total RNA was harvested from cells and gene expression measured on Affymetrix GeneChip Mouse Exon 1.0 ST Arrays. Network-based analysis of these data revealed six siRNAs to cause a marked shift in the macrophage transcriptome in the presence or absence IFNγ. These six siRNAs targeted the Ifnb1, Irf3, Irf5, Stat1, Stat2 and Nfkb2 transcripts. The perturbation of the transcriptome by the six siRNAs was highly similar in each case and affected the expression of over 600 downstream transcripts. Regulated transcripts were clustered based on co-expression into five major groups corresponding to transcriptional networks associated with the type I and II IFN response, cell cycle regulation, and NF-KB signalling. In addition we have observed a significant non-specific immune stimulation of cells transfected with siRNA using Lipofectamine2000, suggesting use of this reagent in BMDMs, even at low concentrations, is enough to induce a type I IFN response.
Our results provide evidence that the type I IFN response in murine BMDMs is dependent on Ifnb1, Irf3, Irf5, Stat1, Stat2 and Nfkb2, and that siRNAs targeted to these genes results in perturbation of key transcriptional networks associated with type I and type II IFN signalling and a suppression of macrophage M1 polarization.
Microarray analysis allows the simultaneous measurement of thousands to millions of genes or sequences across tens to thousands of different samples. The analysis of the resulting data tests the limits of existing bioinformatics computing infrastructure. A solution to this issue is to use High Performance Computing (HPC) systems, which contain many processors and more memory than desktop computer systems. Many biostatisticians use R to process the data gleaned from microarray analysis and there is even a dedicated group of packages, Bioconductor, for this purpose. However, to exploit HPC systems, R must be able to utilise the multiple processors available on these systems. There are existing modules that enable R to use multiple processors, but these are either difficult to use for the HPC novice or cannot be used to solve certain classes of problems. A method of exploiting HPC systems, using R, but without recourse to mastering parallel programming paradigms is therefore necessary to analyse genomic data to its fullest.
We have designed and built a prototype framework that allows the addition of parallelised functions to R to enable the easy exploitation of HPC systems. The Simple Parallel R INTerface (SPRINT) is a wrapper around such parallelised functions. Their use requires very little modification to existing sequential R scripts and no expertise in parallel computing. As an example we created a function that carries out the computation of a pairwise calculated correlation matrix. This performs well with SPRINT. When executed using SPRINT on an HPC resource of eight processors this computation reduces by more than three times the time R takes to complete it on one processor.
SPRINT allows the biostatistician to concentrate on the research problems rather than the computation, while still allowing exploitation of HPC systems. It is easy to use and with further development will become more useful as more functions are added to the framework.
Emiliania huxleyi virus strain 86 is the largest algal virus sequenced to date and is unique among the Phycodnaviridae since its genome is predicted to contain six RNA polymerase subunit genes. We have used a virus microarray to profile the temporal transcription strategy of this unusual virus during infection. There are two distinct transcription phases to the infection process. The primary phase is dominated by a group of coding sequences (CDSs) expressed by 1 h postinfection that are localized to a subregion of the genome. The CDS of the primary group have no database homologues, and each is associated with a unique promoter element. The remainder of the CDSs are expressed in a secondary phase between 2 and 4 hours postinfection. Compartmentalized transcription of the two distinctive phases is discussed. We hypothesize that immediately after infection the nucleic acid of the virus targets the host nucleus, where primary-phase genes are transcribed by host RNA polymerase which recognizes the viral promoter. Secondary-phase transcription may then be conducted in the cytoplasm.
Macrophages play an integral role in the host immune system, bridging innate and adaptive immunity. As such, they are finely attuned to extracellular and intracellular stimuli and respond by rapidly initiating multiple signalling cascades with diverse effector functions. The macrophage cell is therefore an experimentally and clinically amenable biological system for the mapping of biological pathways. The goal of the macrophage expression atlas is to systematically investigate the pathway biology and interaction network of macrophages challenged with a variety of insults, in particular via infection and activation with key inflammatory mediators. As an important first step towards this we present a single searchable database resource containing high-throughput macrophage gene expression studies.
The GPX Macrophage Expression Atlas (GPX-MEA) is an online resource for gene expression based studies of a range of macrophage cell types following treatment with pathogens and immune modulators. GPX-MEA follows the MIAME standard and includes an objective quality score with each experiment. It places special emphasis on rigorously capturing the experimental design and enables the searching of expression data from different microarray experiments. Studies may be queried on the basis of experimental parameters, sample information and quality assessment score. The ability to compare the expression values of individual genes across multiple experiments is provided. In addition, the database offers access to experimental annotation and analysis files and includes experiments and raw data previously unavailable to the research community.
GPX-MEA is the first example of a quality scored gene expression database focussed on a macrophage cellular system that allows efficient identification of transcriptional patterns. The resource will provide novel insights into the phenotypic response of macrophages to a variety of benign, inflammatory, and pathogen insults. GPX-MEA is available through the GPX website at .
High-throughput, parallel gene expression analysis by means of microarray technology has become a widely used technique in recent years. There are currently two main dye-labelling strategies for microarray studies based on custom-spotted cDNA or oligonucleotides arrays: (I) Dye-labelling of a single target sample with a particular dye, followed by subsequent hybridisation to a single microarray slide, (II) Dye-labelling of two different target samples with two different dyes, followed by subsequent co-hybridisation to a single microarray slide. The two dyes most frequently used for either method are Cy3 and Cy5. We propose and evaluate a novel experiment set-up utilising three differently labelled targets co-hybridised to one microarray slide. In addition to Cy3 and Cy5, this incorporates Alexa 594 as a third dye-label. We evaluate this approach in line with current data processing and analysis techniques for microarrays, and run separate analyses on Alexa 594 used in single-target, dual-target and the intended triple-target experiment set-ups (a total of 18 microarray slides). We follow this by pointing out practical applications and suitable analysis methods, and conclude that triple-target microarray experiments can add value to microarray research by reducing material costs for arrays and related processes, and by increasing the number of options for pragmatic experiment design.
The addition of Alexa 594 as a dye-label for an additional – third – target sample works within the framework of more commonplace Cy5/Cy3 labelled target sample combinations. Standard normalisation methods are still applicable, and the resulting data can be expected to allow identification of expression differences in a biological experiment, given sufficient levels of biological replication (as is necessary for most microarray experiments).
The use of three dye-labelled target samples can be a valuable addition to the standard repertoire of microarray experiment designs. The method enables direct comparison between two experimental populations as well as measuring these two populations in relation to a third reference sample, allowing comparisons within the slide and across slides. These benefits are only offset by the added level of consideration required in the experimental design and data processing of a triple-target study design. Common methods for data processing and analysis are still applicable, but there is scope for the development of custom models for triple-target data. In summary, we do not consider the triple-target approach to be a new standard, but a valuable addition to the existing microarray study toolkit.
The statistical language R and its Bioconductor package are favoured by many biostatisticians for processing microarray data. The amount of data produced by some analyses has reached the limits of many common bioinformatics computing infrastructures. High Performance Computing systems offer a solution to this issue. The Simple Parallel R Interface (SPRINT) is a package that provides biostatisticians with easy access to High Performance Computing systems and allows the addition of parallelized functions to R. Previous work has established that the SPRINT implementation of an R permutation testing function has close to optimal scaling on up to 512 processors on a supercomputer. Access to supercomputers, however, is not always possible, and so the work presented here compares the performance of the SPRINT implementation on a supercomputer with benchmarks on a range of platforms including cloud resources and a common desktop machine with multiprocessing capabilities. Copyright © 2011 John Wiley & Sons, Ltd.
HPC; MPI; Permutation; Microarray; R; SPRINT