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1.  Mouse NAIP1 detects the type III secretion system needle protein 
Journal of immunology (Baltimore, Md. : 1950)  2013;191(8):10.4049/jimmunol.1301549.
The NAIP/NLRC4 inflammasomes activate caspase-1 in response to bacterial type III secretion systems (T3SS). Inadvertent injection of the T3SS rod protein and flagellin into the cytosol are detected through murine NAIP2 and NAIP5/6, respectively. Here, we identify the agonist for the orphan murine NAIP1 receptor as the T3SS needle protein. NAIP1 is poorly expressed in resting mouse bone marrow-derived macrophages (BMMs), however, priming with poly(I:C) induces it, and confers needle protein sensitivity. Further, overexpression of NAIP1 in immortalized BMMs by retroviral transduction enabled needle detection. In contrast, peritoneal cavity macrophages basally express NAIP1 and respond to needle protein robustly independent of priming. Human macrophages are known to only express one NAIP gene, which detects the needle protein, but not rod or flagellin. Thus, murine NAIP1 is functionally analogous to human NAIP.
PMCID: PMC3819181  PMID: 24043898
Naip1; NLRC4; inflammasomes; T3SS; needle
2.  Caspase-11 protects against bacteria that escape the vacuole 
Science (New York, N.Y.)  2013;339(6122):975-978.
Caspases are either apoptotic or inflammatory. The inflammatory Caspases-1 and -11 trigger pyroptosis, a form of programmed cell death. Whereas both can be detrimental in inflammatory disease, only Caspase-1 has an established protective role during infection. Herein, we report that Caspase-11 is required for innate immunity to cytosolic, but not vacuolar, bacteria. While Salmonella typhimurium and Legionella pneumophila normally reside in the vacuole, specific mutants (sifA and sdhA, respectively) that aberrantly enter the cytosol triggered Caspase-11, enhancing clearance of S. typhimurium sifA in vivo. This response did not require NLRP3, NLRC4, or ASC inflammasome pathways. Burkholderia species that naturally invade the cytosol also triggered Caspase-11, protecting mice from lethal challenge with B. thailandensis and B. pseudomallei. Thus, Caspase-11 is critical for surviving exposure to ubiquitous environmental pathogens.
PMCID: PMC3697099  PMID: 23348507
3.  A systems view of host defense 
Nature biotechnology  2009;27(11):999-1001.
Large-scale perturbations unravel the complex networks of activated dendritic cells.
PMCID: PMC3076594  PMID: 19898453
4.  Genome-wide histone acetylation data improve prediction of mammalian transcription factor binding sites 
Bioinformatics  2010;26(17):2071-2075.
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.
Results: We tested this hypothesis using a multi-evidence approach for predicting binding sites. As a training/test dataset, we used ChIP-Seq-derived TF binding site locations for five TFs in activated murine macrophages. Our model combined TF binding site motif scanning with evidence from sequence-based sources and from HAc ChIP-Seq data, using a weighted sum of thresholded scores. We find that using HAc data significantly improves the performance of motif-based TF binding site prediction. Furthermore, we find that within regions of high HAc, local minima of the HAc ChIP-Seq signal are particularly strongly correlated with TF binding locations. Our model, using motif scanning and HAc local minima, improves the sensitivity for TF binding site prediction by ∼50% over a model based on motif scanning alone, at a false positive rate cutoff of 0.01.
Availability: The data and software source code for model training and validation are freely available online at
Supplementary information: Supplementary data are available at Bioinformatics online.
PMCID: PMC2922897  PMID: 20663846
5.  Role of the transcription factor C/EBPδ in a regulatory circuit that discriminates between transient and persistent Toll-like receptor 4-induced signals 
Nature immunology  2009;10(4):437-443.
The innate immune system is a two-edged sword; it is absolutely required for host defense against infection but, uncontrolled, can trigger a plethora of inflammatory diseases. Here we used systems biology approaches to predict and validate a gene regulatory network involving a dynamic interplay between the transcription factors NF-κB, C/EBPδ, and ATF3 that controls inflammatory responses. We mathematically modeled transcriptional regulation of Il6 and Cebpd genes and experimentally validated the prediction that the combination of an initiator (NF-κB), an amplifier (C/EBPδ) and an attenuator (ATF3) forms a regulatory circuit that discriminates between transient and persistent Toll-like receptor 4-induced signals. Our results suggest a mechanism that enables the innate immune system to detect the duration of infection and to respond appropriately.
PMCID: PMC2780024  PMID: 19270711
6.  Systems biology of innate immunity 
Immunological reviews  2009;227(1):264-282.
Systems biology is the comprehensive and quantitative analysis of the interactions between all of the components of biological systems over time. Systems biology involves an iterative cycle, in which emerging biological problems drive the development of new technologies and computational tools. These technologies and tools then open new frontiers that revolutionize biology. Innate immunity is well suited for systems analysis, because the relevant cells can be isolated in various functional states and their interactions can be reconstituted in a biologically meaningful manner. Application of the tools of systems biology to the innate immune system will enable comprehensive analysis of the complex interactions that maintain the difficult balance between host defense and inflammatory disease. In this review, we discuss innate immunity in the context of the systems biology concepts, emergence, robustness, and modularity, and we describe emerging technologies we are applying in our systems-level analyses. These technologies include genomics, proteomics, computational analysis, forward genetics screens, and analyses that link human genetic polymorphisms to disease resistance.
PMCID: PMC2697920  PMID: 19120490
systems biology; innate immunity; Toll-like receptors; gene regulation; genomics; proteomics
7.  Quantifying gene network connectivity in silico: Scalability and accuracy of a modular approach 
Systems biology  2006;153(4):236-246.
Large, complex datasets that are generated from microarray experiments create a need for systematic analysis techniques to unravel the underlying connectivity of gene regulatory networks. A modular approach, previously proposed by Kholodenko and co-workers, helps to scale down the network complexity into more computationally manageable entities called modules. A functional module includes a gene’s mRNA, promoter and resulting products, thus encompassing a large set of interacting states. The essential elements of this approach are described in detail for a three-gene model network and later extended to a ten-gene model network, demonstrating scalability. The network architecture is identified by analyzing in silico steady-state changes in the activities of only the module outputs -communicating intermediates- that result from specific perturbations applied to the network modules one at a time. These steady-state changes form the system response matrix, which is used to compute the network connectivity or network interaction map. By employing a known biochemical network, we are able to evaluate the accuracy of the modular approach and its sensitivity to key assumptions.
PMCID: PMC2346590  PMID: 16986625
gene networks; reverse engineering; modular approach; connection coefficients
10.  Uncovering a Macrophage Transcriptional Program by Integrating Evidence from Motif Scanning and Expression Dynamics 
PLoS Computational Biology  2008;4(3):e1000021.
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.
Author Summary
Macrophages play a vital role in host defense against infection by recognizing pathogens through pattern recognition receptors, such as the Toll-like receptors (TLRs), and mounting an immune response. Stimulation of TLRs initiates a complex transcriptional program in which induced transcription factor genes dynamically regulate downstream genes. Microarray-based transcriptional profiling has proved useful for mapping such transcriptional programs in simpler model organisms; however, mammalian systems present difficulties such as post-translational regulation of transcription factors, combinatorial gene regulation, and a paucity of available gene-knockout expression data. Additional evidence sources, such as DNA sequence-based identification of transcription factor binding sites, are needed. In this work, we computationally inferred a transcriptional network for TLR-stimulated murine macrophages. Our approach combined sequence scanning with time-course expression data in a probabilistic framework. Expression data were analyzed using the time-lagged correlation. A novel, unbiased method was developed to assess the significance of the time-lagged correlation. The inferred network of associations between transcription factor genes and co-expressed gene clusters was validated with targeted ChIP-on-chip experiments, and yielded insights into the macrophage activation program, including a potential novel regulator. Our general approach could be used to analyze other complex mammalian systems for which time-course expression data are available.
PMCID: PMC2265556  PMID: 18369420
11.  Systems analysis of circadian time-dependent neuronal epidermal growth factor receptor signaling 
Genome Biology  2006;7(6):R48.
A systems level analysis of circadian time-dependent signaling via the epidermal growth factor receptor in the suprachiasmatic nucleus suggests several transcription factors that mediate the transcriptional response to epidermal growth factor receptor signaling.
Identifying the gene regulatory networks governing physiological signal integration remains an important challenge in circadian biology. Epidermal growth factor receptor (EGFR) has been implicated in circadian function and is expressed in the suprachiasmatic nuclei (SCN), the core circadian pacemaker. The transcription networks downstream of EGFR in the SCN are unknown but, by analogy to other SCN inputs, we expect the response to EGFR activation to depend on circadian timing.
We have undertaken a systems-level analysis of EGFR circadian time-dependent signaling in the SCN. We collected gene-expression profiles to study how the SCN response to EGFR activation depends on circadian timing. Mixed-model analysis of variance (ANOVA) was employed to identify genes with circadian time-dependent EGFR regulation. The expression data were integrated with transcription-factor binding predictions through gene group enrichment analyses to generate robust hypotheses about transcription-factors responsible for the circadian phase-dependent EGFR responses.
The analysis results suggest that the transcriptional response to EGFR signaling in the SCN may be partly mediated by established transcription-factors regulated via EGFR transription-factors (AP1, Ets1, C/EBP), transcription-factors involved in circadian clock entrainment (CREB), and by core clock transcription-factors (Rorα). Quantitative real-time PCR measurements of several transcription-factor expression levels support a model in which circadian time-dependent EGFR responses are partly achieved by circadian regulation of upstream signaling components. Our study suggests an important role for EGFR signaling in SCN function and provides an example for gaining physiological insights through systems-level analysis.
PMCID: PMC1779538  PMID: 16784547

Results 1-11 (11)