Paul Lacaze

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.

A logic-based diagram of signalling pathways central to macrophage activation

BackgroundThe complex yet flexible cellular response to pathogens is orchestrated by the interaction of multiple signalling and metabolic pathways. The molecular regulation of this response has been studied in great detail but comprehensive and unambiguous diagrams describing these events are generally unavailable. Four key signalling cascades triggered early-on in the innate immune response are the toll-like receptor, interferon, NF-κB and apoptotic pathways, which co-operate to defend cells against a given pathogen. However, these pathways are commonly viewed as separate entities rather than an integrated network of molecular interactions.ResultsHere we describe the construction of a logically represented pathway diagram which attempts to integrate these four pathways central to innate immunity using a modified version of the Edinburgh Pathway Notation. The pathway map is available in a number of electronic formats and editing is supported by yEd graph editor software.ConclusionThe map presents a powerful visual aid for interpreting the available pathway interaction knowledge and underscores the valuable contribution well constructed pathway diagrams make to communicating large amounts of molecular interaction data. Furthermore, we discuss issues with the limitations and scalability of pathways presented in this fashion, explore options for automated layout of large pathway networks and demonstrate how such maps can aid the interpretation of functional studies.

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.

Construction of a large scale integrated map of macrophage pathogen recognition and effector systems

BackgroundIn an effort to better understand the molecular networks that underpin macrophage activation we have been assembling a map of relevant pathways. Manual curation of the published literature was carried out in order to define the components of these pathways and the interactions between them. This information has been assembled into a large integrated directional network and represented graphically using the modified Edinburgh Pathway Notation (mEPN) scheme.ResultsThe diagram includes detailed views of the toll-like receptor (TLR) pathways, other pathogen recognition systems, NF-kappa-B, apoptosis, interferon signalling, MAP-kinase cascades, MHC antigen presentation and proteasome assembly, as well as selected views of the transcriptional networks they regulate. The integrated pathway includes a total of 496 unique proteins, the complexes formed between them and the processes in which they are involved. This produces a network of 2,170 nodes connected by 2,553 edges.ConclusionsThe pathway diagram is a navigable visual aid for displaying a consensus view of the pathway information available for these systems. It is also a valuable resource for computational modelling and aid in the interpretation of functional genomics data. We envisage that this work will be of value to those interested in macrophage biology and also contribute to the ongoing Systems Biology community effort to develop a standard notation scheme for the graphical representation of biological pathways.

ID4 controls mammary stem cells and marks breast cancers with a stem cell-like phenotype

Basal-like breast cancer (BLBC) is a heterogeneous disease with poor prognosis; however, its cellular origins and aetiology are poorly understood. In this study, we show that inhibitor of differentiation 4 (ID4) is a key regulator of mammary stem cell self-renewal and marks a subset of BLBC with a putative mammary basal cell of origin. Using an ID4GFP knock-in reporter mouse and single-cell transcriptomics, we show that ID4 marks a stem cell-enriched subset of the mammary basal cell population. ID4 maintains the mammary stem cell pool by suppressing key factors required for luminal differentiation. Furthermore, ID4 is specifically expressed by a subset of human BLBC that possess a very poor prognosis and a transcriptional signature similar to a mammary stem cell. These studies identify ID4 as a mammary stem cell regulator, deconvolute the heterogeneity of BLBC and link a subset of mammary stem cells to the aetiology of BLBC.

Combined genome-wide expression profiling and targeted RNA interference in primary mouse macrophages reveals perturbation of transcriptional networks associated with interferon signalling

BackgroundInterferons (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.ResultsTransfection 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.ConclusionOur 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.

Reversible Inhibition of Murine Cytomegalovirus Replication by Gamma Interferon (IFN-γ) in Primary Macrophages Involves a Primed Type I IFN-Signaling Subnetwork for Full Establishment of an Immediate-Early Antiviral State

ABSTRACT 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.

Temporal Profiling of the Coding and Noncoding Murine Cytomegalovirus Transcriptomes

ABSTRACT 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.

Whole blood gene expression profiling of neonates with confirmed bacterial sepsis.

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.

Quantitative assessment of human whole blood RNA as a potential biomarker for infectious disease

Infection remains a significant cause of morbidity and mortality especially in newborn infants. Analytical methods for diagnosing infection are severely limited in terms of sensitivity and specificity and require relatively large samples. It is proposed that stringent regulation of the human transcriptome affords a new molecular diagnostic approach based on measuring a highly specific systemic inflammatory response to infection, detectable at the RNA level. This proposition raises a number of as yet poorly characterised technical and biological variation issues that urgently need to be addressed. Here we report a quantitative assessment of methodological approaches for processing and extraction of RNA from small samples of infant whole blood and applying analysis of variation from biochip measurements. On the basis of testing and selection from a battery of assays we show that sufficient high quality RNA for analysis using multiplex array technology can be obtained from small neonatal samples. These findings formed the basis of implementing a set of robust clinical and experimental standard operating procedures for whole blood RNA samples from 58 infants. Modelling and analysis of variation between samples revealed significant sources of variation from the point of sample collection to processing and signal generation. These experiments further permitted power calculations to be run indicating the tractability and requirements of using changes in RNA expression profiles to detect different states between patient groups. Overall the results of our investigation provide an essential first step toward facilitating an alternative way for diagnosing infection from very small neonatal blood samples, providing methods and requirements for future chip-based studies.