Thorsten Forster

Statistical methods for analysis of high-throughput RNA interference screens

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.

High-resolution gene expression profiling for simultaneous kinetic parameter analysis of RNA synthesis and decay

RNA levels in a cell are determined by the relative rates of RNA synthesis and decay. State-of-the-art transcriptional analyses only employ total cellular RNA. Therefore, changes in RNA levels cannot be attributed to RNA synthesis or decay, and temporal resolution is poor. Recently, it was reported that newly transcribed RNA can be biosynthetically labeled for 1-2 h using thiolated nucleosides, purified from total cellular RNA and subjected to microarray analysis. However, in order to study signaling events at molecular level, analysis of changes occurring within minutes is required. We developed an improved approach to separate total cellular RNA into newly transcribed and preexisting RNA following 10-15 min of metabolic labeling. Employing new computational tools for array normalization and half-life determination we simultaneously study short-term RNA synthesis and decay as well as their impact on cellular transcript levels. As an example we studied the response of fibroblasts to type I and II interferons (IFN). Analysis of RNA transcribed within 15-30 min at different times during the first three hours of interferon-receptor activation resulted in a >10-fold increase in microarray sensitivity and provided a comprehensive profile of the kinetics of IFN-mediated changes in gene expression. We identify a previously undisclosed highly connected network of short-lived transcripts selectively down-regulated by IFNgamma in between 30 and 60 min after IFN treatment showing strong associations with cell cycle and apoptosis, indicating novel mechanisms by which IFNgamma affects these pathways.

The Transcription Factor STAT-1 Couples Macrophage Synthesis of 25-Hydroxycholesterol to the Interferon Antiviral Response

Summary 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.

Combined agonist-antagonist genome-wide functional screening identifies broadly active antiviral microRNAs

Although the functional parameters of microRNAs (miRNAs) have been explored in some depth, the roles of these molecules in viral infections remain elusive. Here we report a general method for global analysis of miRNA function that compares the significance of both overexpressing and inhibiting each mouse miRNA on the growth properties of different viruses. Our comparative analysis of representatives of all three herpesvirus subfamilies identified host miRNAs with broad anti- and proviral properties which extend to a single-stranded RNA virus. Specifically, we demonstrate the broad antiviral capacity of miR-199a-3p and illustrate that this individual host-encoded miRNA regulates multiple pathways required and/or activated by viruses, including PI3K/AKT and ERK/MAPK signaling, oxidative stress signaling, and prostaglandin synthesis. Global miRNA expression analysis further demonstrated that the miR-199a/miR-214 cluster is down-regulated in both murine and human cytomegalovirus infection and manifests similar antiviral properties in mouse and human cells. Overall, we report a general strategy for examining the contributions of individual host miRNAs in viral infection and provide evidence that these molecules confer broad inhibitory potential against multiple viruses.

Parasite-Derived MicroRNAs in Host Serum As Novel Biomarkers of Helminth Infection

Background 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. Methods/Principal Findings 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. Conclusions 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.

Prostaglandin E2 constrains systemic inflammation through an innate lymphoid cell–IL-22 axis

A prostaglandin barrier to inflammation Blood-borne bacterial infections and severe trauma can send the immune system into overdrive, causing it to pump out inflammatory mediators, sometimes at lethal doses. Duffin et al. now report on a role for prostaglandins in keeping systemic inflammation in check. Systemic inflammation correlates with decreased production of the prostaglandin E2 (PGE2). Blocking PGE2 signaling in mice led to severe inflammation associated with the translocation of gut bacteria. PGE2 acts on innate lymphoid cells, which produce interleukin-22, a secreted protein that helps promote intestinal integrity. Science, this issue p. 1333 Prostaglandin E2 prevents systemic inflammation by maintaining gut barrier integrity. Systemic inflammation, which results from the massive release of proinflammatory molecules into the circulatory system, is a major risk factor for severe illness, but the precise mechanisms underlying its control are not fully understood. We observed that prostaglandin E2 (PGE2), through its receptor EP4, is down-regulated in human systemic inflammatory disease. Mice with reduced PGE2 synthesis develop systemic inflammation, associated with translocation of gut bacteria, which can be prevented by treatment with EP4 agonists. Mechanistically, we demonstrate that PGE2-EP4 signaling acts directly on type 3 innate lymphoid cells (ILCs), promoting their homeostasis and driving them to produce interleukin-22 (IL-22). Disruption of the ILC–IL-22 axis impairs PGE2-mediated inhibition of systemic inflammation. Hence, the ILC–IL-22 axis is essential in protecting against gut barrier dysfunction, enabling PGE2-EP4 signaling to impede systemic inflammation.

Identification of a human neonatal immune-metabolic network associated with bacterial infection

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.

Innate immune response gene expression profiles of N9 microglia are pathogen-type specific

Glial cells, particularly microglia, are thought to play a pivotal role in initiating and guiding innate immune responses to CNS infections and in perpetuating inflammation and pathology in CNS diseases such as multiple sclerosis and Alzheimers disease. We describe here the development and use of a new microarray designed to specifically profile transcript expression of innate immunity genes. Microarray analysis validated by quantitative PCR demonstrated an extensive range of pattern recognition receptor gene expression in resting N9 microglia, including Toll-like receptors, scavenger receptors and lectins. Stimulation with LPS or infection with virus modulated pattern recognition receptor, cytokine, chemokine and other innate immune transcripts in a distinct and stimulus-specific manner. This study demonstrates that a single glial cell phenotype has an innate capability to detect infection, determine its form and generate specific responses.

Locus-specific gene expression pattern suggests a unique propagation strategy for a giant algal virus

ABSTRACT 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.

SPRINT: A new parallel framework for R

BackgroundMicroarray 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.ResultsWe 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.ConclusionSPRINT 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.