Uncovering a Macrophage Transcriptional Program by Integrating Evidence from Motif Scanning and Expression Dynamics

Macrophages are versatile immune cells that can detect a variety of pathogen-associated molecular patterns through their Toll-like receptors (TLRs). In response to microbial challenge, the TLR-stimulated macrophage undergoes an activation program controlled by a dynamically inducible transcriptional regulatory network. Mapping a complex mammalian transcriptional network poses significant challenges and requires the integration of multiple experimental data types. In this work, we inferred a transcriptional network underlying TLR-stimulated murine macrophage activation. Microarray-based expression profiling and transcription factor binding site motif scanning were used to infer a network of associations between transcription factor genes and clusters of co-expressed target genes. The time-lagged correlation was used to analyze temporal expression data in order to identify potential causal influences in the network. A novel statistical test was developed to assess the significance of the time-lagged correlation. Several associations in the resulting inferred network were validated using targeted ChIP-on-chip experiments. The network incorporates known regulators and gives insight into the transcriptional control of macrophage activation. Our analysis identified a novel regulator (TGIF1) that may have a role in macrophage activation

Genome-wide histone acetylation data improve prediction of mammalian transcription factor binding sites

Motivation: Histone acetylation (HAc) is associated with open chromatin, and HAc has been shown to facilitate transcription factor (TF) binding in mammalian cells. In the innate immune system context, epigenetic studies strongly implicate HAc in the transcriptional response of activated macrophages. We hypothesized that using data from large-scale sequencing of a HAc chromatin immunoprecipitation assay (ChIP-Seq) would improve the performance of computational prediction of binding locations of TFs mediating the response to a signaling event, namely, macrophage activation

The phosphoproteome of toll-like receptor-activated macrophages

First global and quantitative analysis of phosphorylation cascades induced by toll-like receptor (TLR) stimulation in macrophages identifies nearly 7000 phosphorylation sites and shows extensive and dynamic up-regulation and down-regulation after lipopolysaccharide (LPS).In addition to the canonical TLR-associated pathways, mining of the phosphorylation data suggests an involvement of ATM/ATR kinases in signalling and shows that the cytoskeleton is a hotspot of TLR-induced phosphorylation.Intersecting transcription factor phosphorylation with bioinformatic promoter analysis of genes induced by LPS identified several candidate transcriptional regulators that were previously not implicated in TLR-induced transcriptional control

Controlling the Response: Predictive Modeling of a Highly Central, Pathogen-Targeted Core Response Module in Macrophage Activation

We have investigated macrophage activation using computational analyses of a compendium of transcriptomic data covering responses to agonists of the TLR pathway, Salmonella infection, and manufactured amorphous silica nanoparticle exposure. We inferred regulatory relationship networks using this compendium and discovered that genes with high betweenness centrality, so-called bottlenecks, code for proteins targeted by pathogens. Furthermore, combining a novel set of bioinformatics tools, topological analysis with analysis of differentially expressed genes under the different stimuli, we identified a conserved core response module that is differentially expressed in response to all studied conditions. This module occupies a highly central position in the inferred network and is also enriched in genes preferentially targeted by pathogens. The module includes cytokines, interferon induced genes such as Ifit1 and 2, effectors of inflammation, Cox1 and Oas1 and Oasl2, and transcription factors including AP1, Egr1 and 2 and Mafb. Predictive modeling using a reverse-engineering approach reveals dynamic differences between the responses to each stimulus and predicts the regulatory influences directing this module. We speculate that this module may be an early checkpoint for progression to apoptosis and/or inflammation during macrophage activation

Dissecting interferon-induced transcriptional programs in human peripheral blood cells

Interferons are key modulators of the immune system, and are central to the control of many diseases. The response of immune cells to stimuli in complex populations is the product of direct and indirect effects, and of homotypic and heterotypic cell interactions. Dissecting the global transcriptional profiles of immune cell populations may provide insights into this regulatory interplay. The host transcriptional response may also be useful in discriminating between disease states, and in understanding pathophysiology. The transcriptional programs of cell populations in health therefore provide a paradigm for deconvoluting disease-associated gene expression profiles.We used human cDNA microarrays to (1) compare the gene expression programs in human peripheral blood mononuclear cells (PBMCs) elicited by 6 major mediators of the immune response: interferons alpha, beta, omega and gamma, IL12 and TNFalpha; and (2) characterize the transcriptional responses of purified immune cell populations (CD4+ and CD8+ T cells, B cells, NK cells and monocytes) to IFNgamma stimulation. We defined a highly stereotyped response to type I interferons, while responses to IFNgamma and IL12 were largely restricted to a subset of type I interferon-inducible genes. TNFalpha stimulation resulted in a distinct pattern of gene expression. Cell type-specific transcriptional programs were identified, highlighting the pronounced response of monocytes to IFNgamma, and emergent properties associated with IFN-mediated activation of mixed cell populations. This information provides a detailed view of cellular activation by immune mediators, and contributes an interpretive framework for the definition of host immune responses in a variety of disease settings

Identification and Validation of Ifit1 as an Important Innate Immune Bottleneck

The innate immune system plays important roles in a number of disparate processes. Foremost, innate immunity is a first responder to invasion by pathogens and triggers early defensive responses and recruits the adaptive immune system. The innate immune system also responds to endogenous damage signals that arise from tissue injury. Recently it has been found that innate immunity plays an important role in neuroprotection against ischemic stroke through the activation of the primary innate immune receptors, Toll-like receptors (TLRs). Using several large-scale transcriptomic data sets from mouse and mouse macrophage studies we identified targets predicted to be important in controlling innate immune processes initiated by TLR activation. Targets were identified as genes with high betweenness centrality, so-called bottlenecks, in networks inferred from statistical associations between gene expression patterns. A small set of putative bottlenecks were identified in each of the data sets investigated including interferon-stimulated genes (Ifit1, Ifi47, Tgtp and Oasl2) as well as genes uncharacterized in immune responses (Axud1 and Ppp1r15a). We further validated one of these targets, Ifit1, in mouse macrophages by showing that silencing it suppresses induction of predicted downstream genes by lipopolysaccharide (LPS)-mediated TLR4 activation through an unknown direct or indirect mechanism. Our study demonstrates the utility of network analysis for identification of interesting targets related to innate immune function, and highlights that Ifit1 can exert a positive regulatory effect on downstream genes

Reconstruction of regulatory networks through temporal enrichment profiling and its application to H1N1 influenza viral infection

BACKGROUND: H1N1 influenza viruses were responsible for the 1918 pandemic that caused millions of deaths worldwide and the 2009 pandemic that caused approximately twenty thousand deaths. The cellular response to such virus infections involves extensive genetic reprogramming resulting in an antiviral state that is critical to infection control. Identifying the underlying transcriptional network driving these changes, and how this program is altered by virally-encoded immune antagonists, is a fundamental challenge in systems immunology. RESULTS: Genome-wide gene expression patterns were measured in human monocyte-derived dendritic cells (DCs) infected in vitro with seasonal H1N1 influenza A/New Caledonia/20/1999. To provide a mechanistic explanation for the timing of gene expression changes over the first 12 hours post-infection, we developed a statistically rigorous enrichment approach integrating genome-wide expression kinetics and time-dependent promoter analysis. Our approach, TIme-Dependent Activity Linker (TIDAL), generates a regulatory network that connects transcription factors associated with each temporal phase of the response into a coherent linked cascade. TIDAL infers 12 transcription factors and 32 regulatory connections that drive the antiviral response to influenza. To demonstrate the generality of this approach, TIDAL was also used to generate a network for the DC response to measles infection. The software implementation of TIDAL is freely available at http://tsb.mssm.edu/primeportal/?q=tidal_prog. CONCLUSIONS: We apply TIDAL to reconstruct the transcriptional programs activated in monocyte-derived human dendritic cells in response to influenza and measles infections. The application of this time-centric network reconstruction method in each case produces a single transcriptional cascade that recapitulates the known biology of the response with high precision and recall, in addition to identifying potentially novel antiviral factors. The ability to reconstruct antiviral networks with TIDAL enables comparative analysis of antiviral responses, such as the differences between pandemic and seasonal influenza infections

Using cell fate attractors to uncover transcriptional regulation of HL60 neutrophil differentiation

<p>Abstract</p> <p>Background</p> <p>The process of cellular differentiation is governed by complex dynamical biomolecular networks consisting of a multitude of genes and their products acting in concert to determine a particular cell fate. Thus, a systems level view is necessary for understanding how a cell coordinates this process and for developing effective therapeutic strategies to treat diseases, such as cancer, in which differentiation plays a significant role. Theoretical considerations and recent experimental evidence support the view that cell fates are high dimensional attractor states of the underlying molecular networks. The temporal behavior of the network states progressing toward different cell fate attractors has the potential to elucidate the underlying molecular mechanisms governing differentiation.</p> <p>Results</p> <p>Using the HL60 multipotent promyelocytic leukemia cell line, we performed experiments that ultimately led to two different cell fate attractors by two treatments of varying dosage and duration of the differentiation agent all-trans-retinoic acid (ATRA). The dosage and duration combinations of the two treatments were chosen by means of flow cytometric measurements of CD11b, a well-known early differentiation marker, such that they generated two intermediate populations that were poised at the apparently same stage of differentiation. However, the population of one treatment proceeded toward the terminally differentiated neutrophil attractor while that of the other treatment reverted back toward the undifferentiated promyelocytic attractor. We monitored the gene expression changes in the two populations after their respective treatments over a period of five days and identified a set of genes that diverged in their expression, a subset of which promotes neutrophil differentiation while the other represses cell cycle progression. By employing promoter based transcription factor binding site analysis, we found enrichment in the set of divergent genes, of transcription factors functionally linked to tumor progression, cell cycle, and development.</p> <p>Conclusion</p> <p>Since many of the transcription factors identified by this approach are also known to be implicated in hematopoietic differentiation and leukemia, this study points to the utility of incorporating a dynamical systems level view into a computational analysis framework for elucidating transcriptional mechanisms regulating differentiation.</p

Reconstruction of lipid metabolism regulatory network in Mycobacterium tuberculosis

Lipid metabolism plays a prominent role in the survival of Mycobacterium tuberculosis (MTB) in both the macrophage and mammalian hosts. A central question in the reconstruction of lipid metabolism in MTB is the key regulatory programs responsible for changes in this metabolism under different conditions. One of the most studied conditions is hypoxia (oxygen deprivation) as adaptations to hypoxia are thought to play an important role in MTB pathogenesis and latency. To identify temporal trends during a hypoxic time course and associate them with possible regulators, expression data was clustered into paths using DREM algorithm and available ChIP-Seq data for over 80 transcription factors (TFs). The degree to which expression patterns might reflect the direct action of transcription factors was assessed by evaluating the consistency between the path, the expression of each TF binding genes in the path, and the predicted regulatory role of the TF from the regulatory network. DosR was correctly identified as an activator of the path corresponding almost entirely to its regulon. Rv0081 was found to be a candidate high level regulator broadly predictive of the overall expression of sets of genes during hypoxia and re-aeration. An essential part of the continued survival of MTB in the host is due to its adaptation to the phagosomal compartment of the macrophage where the bacterium faces hypoxic as well as other stresses. Using the same approach and several time course expression data sets available for MTB in macrophage cultures, macrophage temporal expression models were built and compared to the hypoxia model. Similar trends were found in the expression of genes involved in respiration, cholesterol catabolism and methylcitrate cycle. In contrast, a group of genes responsible for the synthesis of complex cell wall lipids (PAT/DAT and SL-1) were up-regulated in the macrophage models and downregulated in the hypoxic model. PhoP was predicted as a potential main regulator of these genes as a result of pH change which takes place in the macrophage environment but not during hypoxia