Controlling the response: predictive modeling of a highly central, pathogen-targeted core response module in macrophage activation

Bidirectional regulation between AP-1 and SUMO genes modulates inflammatory signalling during Salmonella infection

Post-translational modifications (PTMs), such as SUMOylation, are known to modulate fundamental processes of a cell. Infectious agents such as Salmonella Typhimurium (STm) that causes gastroenteritis, utilizes PTM mechanism SUMOylation to highjack host cell. STm suppresses host SUMO-pathway genes Ubc9 and PIAS1 to perturb SUMOylation for an efficient infection. In the present study, the regulation of SUMO-pathway genes during STm infection was investigated. A direct binding of c-Fos, a component of AP-1 (Activator Protein-1), to promoters of both UBC9 and PIAS1 was observed. Experimental perturbation of c-Fos led to changes in expression of both Ubc9 and PIAS1. STm infection of fibroblasts with SUMOylation deficient c-Fos (c-FOS-KOSUMO-def-FOS) resulted in uncontrolled activation of target genes, resulting in massive immune activation. Infection of c-FOS-KOSUMO-def-FOS cells favored STm replication, indicating misdirected immune mechanisms. Finally, chromatin Immuno-precipitation assays confirmed a context dependent differential binding and release of AP-1 to/from target genes due to its Phosphorylation and SUMOylation respectively. Overall, our data point towards existence of a bidirectional cross-talk between c-Fos and the SUMO pathway and highlighting its importance in AP-1 function relevant to STm infection and beyond.

Gene co-expression network analysis in zebrafish reveals chemical class specific modules

BACKGROUND

Zebrafish is a popular animal model used for high-throughput screening of chemical hazards, however, investigations of transcriptomic mechanisms of toxicity are still needed. Here, our goal was to identify genes and biological pathways that Aryl Hydrocarbon Receptor 2 (AHR2) Activators and flame retardant chemicals (FRCs) alter in developing zebrafish. Taking advantage of a compendium of phenotypically-anchored RNA sequencing data collected from 48-h post fertilization (hpf) zebrafish, we inferred a co-expression network that grouped genes based on their transcriptional response.

RESULTS

Genes responding to the FRCs and AHR2 Activators localized to distinct regions of the network, with FRCs inducing a broader response related to neurobehavior. AHR2 Activators centered in one region related to chemical stress responses. We also discovered several highly co-expressed genes in this module, including cyp1a, and we subsequently show that these genes are definitively within the AHR2 signaling pathway. Systematic removal of the two chemical types from the data, and analysis of network changes identified neurogenesis associated with FRCs, and regulation of vascular development associated with both chemical classes. We also identified highly connected genes responding specifically to each class that are potential biomarkers of exposure.

CONCLUSIONS

Overall, we created the first zebrafish chemical-specific gene co-expression network illuminating how chemicals alter the transcriptome relative to each other. In addition to our conclusions regarding FRCs and AHR2 Activators, our network can be leveraged by other studies investigating chemical mechanisms of toxicity.

Activating transcription factor 3 modulates the macrophage immune response to Mycobacterium tuberculosis infection via reciprocal regulation of inflammatory genes and lipid body formation

Infection of macrophages by Mycobacterium tuberculosis elicits an immune response that clears the bacterium. However, the bacterium is able to subvert the innate immune response. Differential expression of transcription factors (TFs) is central to the dynamic balance of this interaction. Among other functions, TFs regulate the production of antibacterial agents such as nitric oxide, pro-inflammatory cytokines and neutral lipids which are stored in lipid bodies (LBs) and favour bacterial survival. Here, we demonstrate that the TF activating transcription factor 3 (ATF3) is upregulated early during infection of macrophages or mice. Depletion of ATF3 enhances mycobacterial survival in macrophages suggesting its host-protective role. ATF3 interacts with chromatin remodelling protein brahma-related gene 1 and both associate with the promoters of interleukin-12p40, interleukin-6 and nitric oxide synthase 2, to activate expression of these genes. Strikingly, ATF3 downregulates LB formation by associating at the promoters of positive regulators of LB formation such as cholesterol 25 hydroxylase and the microRNA-33 locus. ATF3 represses the association of the activating mark, acetyl histone H4 lysine 8 at the promoter of cholesterol 25 hydroxylase. Our study suggests opposing roles of ATF3 in regulation of distinct sets of macrophage genes during infection, converging on a host-protective immune response.

An integrative computational approach for a prioritization of key transcription regulators associated with nanomaterial-induced toxicity

A rapid increase of new nanomaterial products poses new challenges for their risk assessment. Current traditional methods for estimating potential adverse health effect of nanomaterials (NMs) are complex, time consuming and expensive. In order to develop new prediction tests for nanotoxicity evaluation, a systems biology approach and data from high-throughput omics experiments can be used. We present a computational approach that combines reverse engineering techniques, network analysis and pathway enrichment analysis for inferring the transcriptional regulation landscape and its functional interpretation. To illustrate this approach, we used published transcriptomic data derived from mice lung tissue exposed to carbon nanotubes (NM-401 and NRCWE-26). Because fibrosis is the most common adverse effect of these NMs, we included in our analysis the data for bleomycin (BLM) treatment, which is a well-known fibrosis inducer. We inferred gene regulatory networks for each NM and BLM to capture functional hierarchical regulatory structures between genes and their regulators. Despite the different nature of the lung injury caused by nanoparticles and BLM, we identified several conserved core regulators for all agents. We reason that these regulators can be considered as early predictors of toxic responses after NMs exposure. This integrative approach, which refines traditional methods of transcriptomic analysis, can be useful for prioritization of potential core regulators and generation of new hypothesis about mechanisms of nanoparticles toxicity.

Identification of differentially expressed genes and regulatory relationships in Huntington's disease by bioinformatics analysis

Huntington's disease (HD) is an inherited, progressive neurodegenerative disease caused by a CAG expansion in the huntingtin (HTT) gene; various dysfunctions of biological processes in HD have been proposed. However, at present the exact pathogenesis of HD is not fully understood. The present study aimed to explore the pathogenesis of HD using a computational bioinformatics analysis of gene expression. GSE11358 was downloaded from the Gene Expression Omnibus andthe differentially expressed genes (DEGs) in the mutant HTT knock-in cell model STHdhQ111/Q111 were predicted. DEGs between the HD and control samples were screened using the limma package in R. Functional and pathway enrichment analyses were conducted using the database for annotation, visualization and integrated discovery software. A protein-protein interaction (PPI) network was established by the search tool for the retrieval of interacting genes and visualized by Cytoscape. Module analysis of the PPI network was performed utilizing MCODE. A total of 471 DEGs were identified, including ribonuclease A family member 4 (RNASE4). In addition, 41 significantly enriched Kyoto Encyclopedia of Genes and Genomes pathways, as well as several significant Gene Ontology terms (including cytokine-cytokine receptor interaction and cytosolic DNA-sensing) were identified. A total of 18 significant modules were identified from the PPI network. Furthermore, a novel transcriptional regulatory relationship was identified, namely signal transducer and activator of transcription 3 (STAT3), which is regulated by miRNA-124 in HD. In conclusion, deregulation of 18 critical genes may contribute to the occurrence of HD. RNASE4, STAT3, and miRNA-124 may have a regulatory association with the pathological mechanisms in HD.

Phagocytosis and immune response studies of Macrophage-Nanodiamond Interactions in vitro and in vivo

The applications of nanodiamond as drug delivery and bio-imaging can require the relinquishing ND-drug conjugate via blood flow, where interaction with immune cells may occur. In this work, we investigated the ND penetration in macrophage and the immune response using the tissue-resident murine macrophages (RAW 264.7). Confocal fluorescence imaging, immunofluorescence analysis of nuclear translocation of interferon regulatory factor IRF-3 and transcriptional factor NF-κΒ, analysis of pro-inflammatory cytokines production IL-1β, IL-6 IL-10 with a reverse transcription-polymerase chain reaction technique were applied. The TNF-α factor production has been studied both in vitro at ND interaction with the macrophage and in vivo after ND injection in the mice blood system using immunoassay. The macrophage antibacterial function was estimated through E. coli bacterial colony formation. ND didn't stimulate the immune response and functionality of the macrophage was not altered. Using MTT test, ND was found negligibly cytotoxic to macrophages. Thus, ND can serve as a biocompatible platform for bio-medical applications. Left: Graphic representation of Nanodiamond internalization in macrophage. Right: (a) Fluorescence images of lysosomes, (b) nanodiamond and (c) merged image of nanodiamond internalization in macrophage.

Nano-sized zinc oxide and silver, but not titanium dioxide, induce innate and adaptive immunity and antiviral response in differentiated THP-1 cells

Nano-sized metal oxides are currently the most manufactured nanomaterials (NMs), and are increasingly used in consumer products. Recent exposure data reveal a genuine potential for adverse health outcomes for a vast array of NMs, however the underlying mechanisms are not fully understood. To elucidate size-related molecular effects, differentiated THP-1 cells were exposed to nano-sized materials (n-TiO_2, n-ZnO and n-Ag), or their bulk-sized (b-ZnO and b-TiO₂) or ionic (i-Ag) counterparts, and genome-wide gene expression changes were studied at low-toxic concentrations (<15% cytotoxicity). TiO₂ materials were nontoxic in MTT assay, inducing only minor transcriptional changes. ZnO and Ag elicited dose-dependent cytotoxicity, wherein ionic and particulate effects were synergistic with respect to n-ZnO-induced cytotoxicity. In gene expression analyzes, 6 h and 24 h samples formed two separate hierarchical clusters. N-ZnO and n-Ag shared only 3.1% and 24.6% differentially expressed genes (DEGs) when compared to corresponding control. All particles, except TiO₂, activated various metallothioneins. At 6 h, n-Zn, b-Zn and n-Ag induced various immunity related genes associating to pattern recognition (including toll-like receptor), macrophage maturation, inflammatory response (TNF and IL-1beta), chemotaxis (CXCL8) and leucocyte migration (CXCL2-3 and CXCL14). After 24 h exposure, especially n-Ag induced the expression of genes related to virus recognition and type I interferon responses. These results strongly suggest that in addition to ionic effects mediated by metallothioneins, n-Zn and n-Ag induce expression of genes involved in several innate and adaptive immunity associated pathways, which are known to play crucial role in immuno-regulation. This raises the concern of safe use of metal oxide and metal nanoparticle products, and their biological effects.

An Interactive Macrophage Signal Transduction Map Facilitates Comparative Analyses of High-Throughput Data

Macrophages (Mϕs) are key players in the coordination of the lifesaving or detrimental immune response against infections. The mechanistic understanding of the functional modulation of Mϕs by pathogens and pharmaceutical interventions at the signal transduction level is still far from complete. The complexity of pathways and their cross-talk benefits from holistic computational approaches. In the present study, we reconstructed a comprehensive, validated, and annotated map of signal transduction pathways in inflammatory Mϕs based on the current literature. In a second step, we selectively expanded this curated map with database knowledge. We provide both versions to the scientific community via a Web platform that is designed to facilitate exploration and analysis of high-throughput data. The platform comes preloaded with logarithmic fold changes from 44 data sets on Mϕ stimulation. We exploited three of these data sets-human primary Mϕs infected with the common lung pathogens Streptococcus pneumoniae, Legionella pneumophila, or Mycobacterium tuberculosis-in a case study to show how our map can be customized with expression data to pinpoint regulated subnetworks and druggable molecules. From the three infection scenarios, we extracted a regulatory core of 41 factors, including TNF, CCL5, CXCL10, IL-18, and IL-12 p40, and identified 140 drugs targeting 16 of them. Our approach promotes a comprehensive systems biology strategy for the exploitation of high-throughput data in the context of Mϕ signal transduction. In conclusion, we provide a set of tools to help scientists unravel details of Mϕ signaling. The interactive version of our Mϕ signal transduction map is accessible online at https://vcells.net/macrophage.

The effect of inhibition of PP1 and TNFα signaling on pathogenesis of SARS coronavirus

BACKGROUND

The complex interplay between viral replication and host immune response during infection remains poorly understood. While many viruses are known to employ anti-immune strategies to facilitate their replication, highly pathogenic virus infections can also cause an excessive immune response that exacerbates, rather than reduces pathogenicity. To investigate this dichotomy in severe acute respiratory syndrome coronavirus (SARS-CoV), we developed a transcriptional network model of SARS-CoV infection in mice and used the model to prioritize candidate regulatory targets for further investigation.

RESULTS

We validated our predictions in 18 different knockout (KO) mouse strains, showing that network topology provides significant predictive power to identify genes that are important for viral infection. We identified a novel player in the immune response to virus infection, Kepi, an inhibitory subunit of the protein phosphatase 1 (PP1) complex, which protects against SARS-CoV pathogenesis. We also found that receptors for the proinflammatory cytokine tumor necrosis factor alpha (TNFα) promote pathogenesis, presumably through excessive inflammation.

CONCLUSIONS

The current study provides validation of network modeling approaches for identifying important players in virus infection pathogenesis, and a step forward in understanding the host response to an important infectious disease. The results presented here suggest the role of Kepi in the host response to SARS-CoV, as well as inflammatory activity driving pathogenesis through TNFα signaling in SARS-CoV infections. Though we have reported the utility of this approach in bacterial and cell culture studies previously, this is the first comprehensive study to confirm that network topology can be used to predict phenotypes in mice with experimental validation.

Full Spectrum of LPS Activation in Alveolar Macrophages of Healthy Volunteers by Whole Transcriptomic Profiling

Despite recent advances in understanding macrophage activation, little is known regarding how human alveolar macrophages in health calibrate its transcriptional response to canonical TLR4 activation. In this study, we examined the full spectrum of LPS activation and determined whether the transcriptomic profile of human alveolar macrophages is distinguished by a TIR-domain-containing adapter-inducing interferon-β (TRIF)-dominant type I interferon signature. Bronchoalveolar lavage macrophages were obtained from healthy volunteers, stimulated in the presence or absence of ultrapure LPS in vitro, and whole transcriptomic profiling was performed by RNA sequencing (RNA-Seq). LPS induced a robust type I interferon transcriptional response and Ingenuity Pathway Analysis predicted interferon regulatory factor (IRF)7 as the top upstream regulator of 89 known gene targets. Ubiquitin-specific peptidase (USP)-18, a negative regulator of interferon α/β responses, was among the top up-regulated genes in addition to IL10 and USP41, a novel gene with no known biological function but with high sequence homology to USP18. We determined whether IRF-7 and USP-18 can influence downstream macrophage effector cytokine production such as IL-10. We show that IRF-7 siRNA knockdown enhanced LPS-induced IL-10 production in human monocyte-derived macrophages, and USP-18 overexpression attenuated LPS-induced production of IL-10 in RAW264.7 cells. Quantitative PCR confirmed upregulation of USP18, USP41, IL10, and IRF7. An independent cohort confirmed LPS induction of USP41 and IL10 genes. These results suggest that IRF-7 and predicted downstream target USP18, both elements of a type I interferon gene signature identified by RNA-Seq, may serve to fine-tune early cytokine response by calibrating IL-10 production in human alveolar macrophages.

Proteomic Analysis Reveals Distinct Metabolic Differences Between Granulocyte-Macrophage Colony Stimulating Factor (GM-CSF) and Macrophage Colony Stimulating Factor (M-CSF) Grown Macrophages Derived from Murine Bone Marrow Cells

Macrophages are crucial in controlling infectious agents and tissue homeostasis. Macrophages require a wide range of functional capabilities in order to fulfill distinct roles in our body, one being rapid and robust immune responses. To gain insight into macrophage plasticity and the key regulatory protein networks governing their specific functions, we performed quantitative analyses of the proteome and phosphoproteome of murine primary GM-CSF and M-CSF grown bone marrow derived macrophages (GM-BMMs and M-BMMs, respectively) using the latest isobaric tag based tandem mass tag (TMT) labeling and liquid chromatography-tandem mass spectrometry (LC-MS/MS). Strikingly, metabolic processes emerged as a major difference between these macrophages. Specifically, GM-BMMs show significant enrichment of proteins involving glycolysis, the mevalonate pathway, and nitrogen compound biosynthesis. This evidence of enhanced glycolytic capability in GM-BMMs is particularly significant regarding their pro-inflammatory responses, because increased production of cytokines upon LPS stimulation in GM-BMMs depends on their acute glycolytic capacity. In contrast, M-BMMs up-regulate proteins involved in endocytosis, which correlates with a tendency toward homeostatic functions such as scavenging cellular debris. Together, our data describes a proteomic network that underlies the pro-inflammatory actions of GM-BMMs as well as the homeostatic functions of M-BMMs.

Redefining the transcriptional regulatory dynamics of classically and alternatively activated macrophages by deepCAGE transcriptomics

Classically or alternatively activated macrophages (M1 and M2, respectively) play distinct and important roles for microbiocidal activity, regulation of inflammation and tissue homeostasis. Despite this, their transcriptional regulatory dynamics are poorly understood. Using promoter-level expression profiling by non-biased deepCAGE we have studied the transcriptional dynamics of classically and alternatively activated macrophages. Transcription factor (TF) binding motif activity analysis revealed four motifs, NFKB1_REL_RELA, IRF1,2, IRF7 and TBP that are commonly activated but have distinct activity dynamics in M1 and M2 activation. We observe matching changes in the expression profiles of the corresponding TFs and show that only a restricted set of TFs change expression. There is an overall drastic and transient up-regulation in M1 and a weaker and more sustainable up-regulation in M2. Novel TFs, such as Thap6, Maff, (M1) and Hivep1, Nfil3, Prdm1, (M2) among others, were suggested to be involved in the activation processes. Additionally, 52 (M1) and 67 (M2) novel differentially expressed genes and, for the first time, several differentially expressed long non-coding RNA (lncRNA) transcriptome markers were identified. In conclusion, the finding of novel motifs, TFs and protein-coding and lncRNA genes is an important step forward to fully understand the transcriptional machinery of macrophage activation.

Integrated Genomics of Crohn's Disease Risk Variant Identifies a Role for CLEC12A in Antibacterial Autophagy

The polymorphism ATG16L1 T300A, associated with increased risk of Crohn’s disease, impairs pathogen defense mechanisms including selective autophagy, but specific pathway interactions altered by the risk allele remain unknown. Here, we use perturbational profiling of human peripheral blood cells to reveal that CLEC12A is regulated in an ATG16L1-T300A-dependent manner. Antibacterial autophagy is impaired in CLEC12A-deficient cells, and this effect is exacerbated in the presence of the ATG16L1^∗300A risk allele. Clec12a^−/− mice are more susceptible to Salmonella infection, supporting a role for CLEC12A in antibacterial defense pathways in vivo. CLEC12A is recruited to sites of bacterial entry, bacteria-autophagosome complexes, and sites of sterile membrane damage. Integrated genomics identified a functional interaction between CLEC12A and an E3-ubiquitin ligase complex that functions in antibacterial autophagy. These data identify CLEC12A as early adaptor molecule for antibacterial autophagy and highlight perturbational profiling as a method to elucidate defense pathways in complex genetic disease.

•

Integrated genomics reveals risk-allele-specific autophagy pathway interactions

•

CLEC12A is important for antibacterial autophagy in epithelial and immune cells

•

CLEC12A knockdown amplifies antibacterial autophagy defects in ATG16L1^∗300A cells

•

Clec12a^−/− mice are more susceptible to Salmonella infection in vivo

RNA-sequencing reveals transcriptional up-regulation of Trem2 in response to bexarotene treatment

We have recently demonstrated that short term bexarotene treatment of APP/PS1 mice significantly improves their cognitive performance. While there were no changes in plaque load, or insoluble Aβ levels in brain, biochemical analysis strongly suggested improved clearance of soluble Aβ, including Aβ oligomers. To get further insight into molecular mechanisms underlying this therapeutic effect, we explored genome-wide differential gene expression in brain of bexarotene and control treated APP/PS1 mice. We performed high throughput massively parallel sequencing on mRNA libraries generated from cortices of bexarotene or vehicle treated APP/PS1 mice and compared the expression profiles for differential gene expression. Gene Ontology (GO) Biological Process categories with the highest fold enrichment and lowest False Discovery Rate (FDR) are clustered in GO terms immune response, inflammatory response, oxidation-reduction and immunoglobulin mediated immune response. Chromatin immunoprecipitation (ChIP) followed by ChIP-QPCR, and RT-QPCR expression assays were used to validate select genes, including Trem2, Tyrobp, Apoe and Ttr, differentially expressed in response to Retinoid X Receptor (RXR) activation. We found that bexarotene significantly increased the phagocytosis of soluble and insoluble Aβ in BV2 cells. The results of our study demonstrate that in AD model mice expressing human APP, gene networks up-regulated in response to RXR activation by the specific, small molecule, ligand bexarotene may influence diverse regulatory pathways that are considered critical for cognitive performance, inflammatory response and Aβ clearance, and may provide an explanation of the bexarotene therapeutic effect at the molecular level. This study also confirms that unbiased massive parallel sequencing approaches are useful and highly informative for revealing brain molecular and cellular mechanisms underlying responses to activated nuclear hormone receptors in AD animal models.

Key Hub and Bottleneck Genes Differentiate the Macrophage Response to Virulent and Attenuated Mycobacterium bovis

Mycobacterium bovis is an intracellular pathogen that causes tuberculosis in cattle. Following infection, the pathogen resides and persists inside host macrophages by subverting host immune responses via a diverse range of mechanisms. Here, a high-density bovine microarray platform was used to examine the bovine monocyte-derived macrophage transcriptome response to M. bovis infection relative to infection with the attenuated vaccine strain, M. bovis Bacille Calmette-Guérin. Differentially expressed genes were identified (adjusted P-value ≤0.01) and interaction networks generated across an infection time course of 2, 6, and 24 h. The largest number of biological interactions was observed in the 24-h network, which exhibited scale-free network properties. The 24-h network featured a small number of key hub and bottleneck gene nodes, including IKBKE, MYC, NFKB1, and EGR1 that differentiated the macrophage response to virulent and attenuated M. bovis strains, possibly via the modulation of host cell death mechanisms. These hub and bottleneck genes represent possible targets for immuno-modulation of host macrophages by virulent mycobacterial species that enable their survival within a hostile environment.

Transcriptome-based network analysis reveals a spectrum model of human macrophage activation

Macrophage activation is associated with profound transcriptional reprogramming. Although much progress has been made in the understanding of macrophage activation, polarization, and function, the transcriptional programs regulating these processes remain poorly characterized. We stimulated human macrophages with diverse activation signals, acquiring a data set of 299 macrophage transcriptomes. Analysis of this data set revealed a spectrum of macrophage activation states extending the current M1 versus M2-polarization model. Network analyses identified central transcriptional regulators associated with all macrophage activation complemented by regulators related to stimulus-specific programs. Applying these transcriptional programs to human alveolar macrophages from smokers and patients with chronic obstructive pulmonary disease (COPD) revealed an unexpected loss of inflammatory signatures in COPD patients. Finally, by integrating murine data from the ImmGen project we propose a refined, activation-independent core signature for human and murine macrophages. This resource serves as a framework for future research into regulation of macrophage activation in health and disease.

•

Macrophages react with specific transcriptional programming upon distinct signals

•

Activation by TNF, PGE₂, and P3C activates a STAT4-associated transcriptional program

•

NFKB1, JUNB, and CREB1 are central transcription factors of macrophage activation

•

Inflammatory signatures are lost in alveolar macrophages from COPD patients

Characterization of the microRNAome in porcine reproductive and respiratory syndrome virus infected macrophages

Porcine Reproductive and Respiratory Syndrome Virus (PRRSV), a member of the arterivirus family, is the causative agent of Porcine Reproductive and Respiratory Syndrome (PRRS). PRRS is characterized by late term abortions and respiratory disease, particularly in young pigs. Small regulatory RNAs termed microRNA (miRNA) are associated with gene regulation at the post-transcriptional level. MiRNAs are known to play many diverse and complex roles in viral infections. To discover the impact of PRRSV infections on the cellular miRNAome, Illumina deep sequencing was used to construct small RNA expression profiles from in vitro cultured PRRSV-infected porcine alveolar macrophages (PAMs). A total of forty cellular miRNAs were significantly differentially expressed within the first 48 hours post infection (hpi). The expression of six miRNAs, miR-30a-3p, miR-132, miR-27b*, miR-29b, miR-146a and miR-9-2, were altered at more than one time point. Target gene identification suggests that these miRNAs are involved in regulating immune signaling pathways, cytokine, and transcription factor production. The most highly repressed miRNA at 24 hpi was miR-147. A miR-147 mimic was utilized to maintain miR-147 levels in PRRSV-infected PAMs. PRRSV replication was negatively impacted by high levels of miR-147. Whether down-regulation of miR-147 is directly induced by PRRSV or if it is part of the cellular response and PRRSV indirectly benefits remains to be determined. No evidence could be found of PRRSV-encoded miRNAs. Overall, the present study has revealed that a large and diverse group of miRNAs are expressed in swine alveolar macrophages and that the expression of a subset of these miRNAs is altered in PRRSV infected macrophages.

Dysregulation of macrophage activation profiles by engineered nanoparticles

Although the potential human health impacts from exposure to engineered nanoparticles (ENPs) are uncertain, past epidemiological studies have established correlations between exposure to ambient air pollution particulates and the incidence of pneumonia and lung infections. Using amorphous silica and superparamagnetic iron oxide (SPIO) as model high production volume ENPs, we examined how macrophage activation by bacterial lipopolysaccharide (LPS) or the lung pathogen Streptococcus pneumoniae is altered by ENP pretreatment. Neither silica nor SPIO treatment elicited direct cytotoxic or pro-inflammatory effects in bone marrow-derived macrophages. However, pretreatment of macrophages with SPIO caused extensive reprogramming of nearly 500 genes regulated in response to LPS challenge, hallmarked by exaggerated activation of oxidative stress response pathways and suppressed activation of both pro- and anti-inflammatory pathways. Silica pretreatment altered regulation of only 67 genes, but there was strong correlation with gene sets affected by SPIO. Macrophages exposed to SPIO displayed a phenotype suggesting an impaired ability to transition from an M1 to M2-like activation state, characterized by suppressed IL-10 induction, enhanced TNFα production, and diminished phagocytic activity toward S. pneumoniae. Studies in macrophages deficient in scavenger receptor A (SR-A) showed SR-A participates in cell uptake of both the ENPs and S. pneumonia and co-regulates the anti-inflammatory IL-10 pathway. Thus, mechanisms for dysregulation of innate immunity exist by virtue that common receptor recognition pathways are used by some ENPs and pathogenic bacteria, although the extent of transcriptional reprogramming of macrophage function depends on the physicochemical properties of the ENP after internalization. Our results also illustrate that biological effects of ENPs may be indirectly manifested only after challenging normal cell function. Nanotoxicology screening strategies should therefore consider how exposure to these materials alters susceptibility to other environmental exposures.

A network integration approach to predict conserved regulators related to pathogenicity of influenza and SARS-CoV respiratory viruses

Respiratory infections stemming from influenza viruses and the Severe Acute Respiratory Syndrome corona virus (SARS-CoV) represent a serious public health threat as emerging pandemics. Despite efforts to identify the critical interactions of these viruses with host machinery, the key regulatory events that lead to disease pathology remain poorly targeted with therapeutics. Here we implement an integrated network interrogation approach, in which proteome and transcriptome datasets from infection of both viruses in human lung epithelial cells are utilized to predict regulatory genes involved in the host response. We take advantage of a novel “crowd-based” approach to identify and combine ranking metrics that isolate genes/proteins likely related to the pathogenicity of SARS-CoV and influenza virus. Subsequently, a multivariate regression model is used to compare predicted lung epithelial regulatory influences with data derived from other respiratory virus infection models. We predicted a small set of regulatory factors with conserved behavior for consideration as important components of viral pathogenesis that might also serve as therapeutic targets for intervention. Our results demonstrate the utility of integrating diverse ‘omic datasets to predict and prioritize regulatory features conserved across multiple pathogen infection models.

Studying Salmonellae and Yersiniae host-pathogen interactions using integrated 'omics and modeling

Salmonella and Yersinia are two distantly related genera containing species with wide host-range specificity and pathogenic capacity. The metabolic complexity of these organisms facilitates robust lifestyles both outside of and within animal hosts. Using a pathogen-centric systems biology approach, we are combining a multi-omics (transcriptomics, proteomics, metabolomics) strategy to define properties of these pathogens under a variety of conditions including those that mimic the environments encountered during pathogenesis. These high-dimensional omics datasets are being integrated in selected ways to improve genome annotations, discover novel virulence-related factors, and model growth under infectious states. We will review the evolving technological approaches toward understanding complex microbial life through multi-omic measurements and integration, while highlighting some of our most recent successes in this area.

Loss of FMR2 further emphasizes the link between deregulation of immediate early response genes FOS and JUN and intellectual disability

Loss of FMR2 causes Fragile X E (FRAXE) site-associated intellectual disability (ID). FMR2 regulates transcription, promotes alternative splicing with preference for G-quartet structure harbouring exons and is localized to the nuclear speckles. In primary skin fibroblasts from FRAXE patients (n = 8), we found a significant reduction in the number, but a significant increase in the size, of nuclear speckles, when compared with the controls (n = 4). Since nuclear speckles are enriched with factors involved in pre-mRNA processing, we explored the consequence of these defects and the loss of FMR2 on the transcriptome. We performed whole genome expression profiling using total RNA extracted from these cell lines and found 27 genes significantly deregulated by at least 2-fold at P < 0.05 in the patients. Among these genes, FOS was significantly upregulated and was further investigated due to its established role in neuronal cell function. We showed that (i) 30% depletion of Fmr2 in mouse primary cortical neurons led to a 2-fold increase in Fos expression, (ii) overexpression of FMR2 significantly decreased FOS promoter activity in luciferase assays, and (iii) as FOS promoter contains a serum response element, we found that not FOS, but JUN, which encodes for a protein that forms a transcriptional activator complex with FOS, was significantly upregulated in the patients' cell lines upon mitogen stimulation. These results suggest that FMR2 is an upstream regulator of FOS and JUN, and further link deregulation of the immediate early response genes to the pathology of ID- and FRAXE-associated ID in particular.

The landscape of host transcriptional response programs commonly perturbed by bacterial pathogens: towards host-oriented broad-spectrum drug targets

BACKGROUND

The emergence of drug-resistant pathogen strains and new infectious agents pose major challenges to public health. A promising approach to combat these problems is to target the host's genes or proteins, especially to discover targets that are effective against multiple pathogens, i.e., host-oriented broad-spectrum (HOBS) drug targets. An important first step in the discovery of such drug targets is the identification of host responses that are commonly perturbed by multiple pathogens.

RESULTS

In this paper, we present a methodology to identify common host responses elicited by multiple pathogens. First, we identified host responses perturbed by each pathogen using a gene set enrichment analysis of publicly available genome-wide transcriptional datasets. Then, we used biclustering to identify groups of host pathways and biological processes that were perturbed only by a subset of the analyzed pathogens. Finally, we tested the enrichment of each bicluster in human genes that are known drug targets, on the basis of which we elicited putative HOBS targets for specific groups of bacterial pathogens. We identified 84 up-regulated and three down-regulated statistically significant biclusters. Each bicluster contained a group of pathogens that commonly dysregulated a group of biological processes. We validated our approach by checking whether these biclusters correspond to known hallmarks of bacterial infection. Indeed, these biclusters contained biological process such as inflammation, activation of dendritic cells, pro- and anti- apoptotic responses and other innate immune responses. Next, we identified biclusters containing pathogens that infected the same tissue. After a literature-based analysis of the drug targets contained in these biclusters, we suggested new uses of the drugs Anakinra, Etanercept, and Infliximab for gastrointestinal pathogens Yersinia enterocolitica, Helicobacter pylori kx2 strain, and enterohemorrhagic Escherichia coli and the drug Simvastatin for hematopoietic pathogen Ehrlichia chaffeensis.

CONCLUSIONS

Using a combination of automated analysis of host-response gene expression data and manual study of the literature, we have been able to suggest host-oriented treatments for specific bacterial infections. The analyses and suggestions made in this study may be utilized to generate concrete hypothesis on which gene sets to probe further in the quest for HOBS drug targets for bacterial infections. All our results are available at the following supplementary website: http://bioinformatics.cs.vt.edu/ murali/supplements/2013-kidane-plos-one.

Toward a molecular pathogenic pathway for Yersinia pestis YopM

YopM is one of the six "effector Yops" of the human-pathogenic Yersinia, but its mechanism has not been defined. After delivery to J774A.1 monocyte-like cells, YopM can rapidly bind and activate the serine/threonine kinases RSK1 and PRK2. However, in infected mice, effects of Y. pestis YopM have been seen only after 24-48 h post-infection (p.i.). To identify potential direct effects of YopM in-vivo we tested for effects of YopM at 1 h and 16-18 h p.i. in mice infected systemically with 10(6) bacteria. At 16 h p.i., there was a robust host response to both parent and ΔyopM-1 Y. pestis KIM5. Compared to cells from non-infected mice, CD11b(+) cells from spleens of infected mice produced more than 100-fold greater IFNγ. In the corresponding sera there were more than 100-fold greater amounts of IFNγ, G-CSF, and CXCL9, as well as more than 10-fold greater amounts of IL-6, CXCL10, and CXCL1. The only YopM-related differences were slightly lower CXCL10 and IL-6 in sera from mice infected 16 h with parent compared to ΔyopM-1 Y. pestis. Microarray analysis of the CD11b(+) cells did not identify consistent transcriptional differences of ≥4-fold at 18 h p.i. However, at 1 h p.i. mRNA for early growth response transcription factor 1 (Egr1) was decreased when YopM was present. Bone marrow-derived macrophages infected for 1 h also expressed lower Egr1 message when YopM was present. Infected J774A.1 cells showed greater expression of Egr1 at 1 h p.i. when YopM was present, but this pattern reversed at 3 h. At 6 h p.i., Cxcl10 mRNA was lower in parent-strain infected cells. We conclude that decreased Egr1 expression is a very early transcriptional effect of YopM and speculate that a pathway may exist from RSK1 through Egr1. These studies revealed novel early transcriptional effects of YopM but point to a time after 18 h of infection when critical transitional events lead to later major effects on cytokine gene transcription.

Modeling dynamic regulatory processes in stroke

The ability to examine the behavior of biological systems in silico has the potential to greatly accelerate the pace of discovery in diseases, such as stroke, where in vivo analysis is time intensive and costly. In this paper we describe an approach for in silico examination of responses of the blood transcriptome to neuroprotective agents and subsequent stroke through the development of dynamic models of the regulatory processes observed in the experimental gene expression data. First, we identified functional gene clusters from these data. Next, we derived ordinary differential equations (ODEs) from the data relating these functional clusters to each other in terms of their regulatory influence on one another. Dynamic models were developed by coupling these ODEs into a model that simulates the expression of regulated functional clusters. By changing the magnitude of gene expression in the initial input state it was possible to assess the behavior of the networks through time under varying conditions since the dynamic model only requires an initial starting state, and does not require measurement of regulatory influences at each time point in order to make accurate predictions. We discuss the implications of our models on neuroprotection in stroke, explore the limitations of the approach, and report that an optimized dynamic model can provide accurate predictions of overall system behavior under several different neuroprotective paradigms.

Computational modeling aims to use mathematical and algorithmic principles to link components of biological systems to predict system behavior. In the past such models have described a small set of carefully studied molecular interactions (proteins in signal transduction pathways) or larger abstract components (cell types or functional processes in the immune system). In this study we use data from global transcriptional analysis of the processes of neuroprotection in a mouse model of stroke to generate functional modules, groups of genes that coherently act to accomplish functions. We then derive equations relating the expression of these modules to one another, treating these individual equations as a closed system, and demonstrate that the model can be used to simulate the gene expression of the system over time. Our work is novel in describing the use of global transcriptomic data to develop dynamic models of expression in an animal model. We believe that the models developed will aid in understanding the complex dynamics of neuroprotection and provide ways to predict outcomes in terms of neuroprotection or injury. This approach will be broadly applicable to other problems and provides an approach to building dynamic models from the bottom up.

Challenges in Biomarker Discovery: Combining Expert Insights with Statistical Analysis of Complex Omics Data

INTRODUCTION: The advent of high throughput technologies capable of comprehensive analysis of genes, transcripts, proteins and other significant biological molecules has provided an unprecedented opportunity for the identification of molecular markers of disease processes. However, it has simultaneously complicated the problem of extracting meaningful molecular signatures of biological processes from these complex datasets. The process of biomarker discovery and characterization provides opportunities for more sophisticated approaches to integrating purely statistical and expert knowledge-based approaches. AREAS COVERED: In this review we will present examples of current practices for biomarker discovery from complex omic datasets and the challenges that have been encountered in deriving valid and useful signatures of disease. We will then present a high-level review of data-driven (statistical) and knowledge-based methods applied to biomarker discovery, highlighting some current efforts to combine the two distinct approaches. EXPERT OPINION: Effective, reproducible and objective tools for combining data-driven and knowledge-based approaches to identify predictive signatures of disease are key to future success in the biomarker field. We will describe our recommendations for possible approaches to this problem including metrics for the evaluation of biomarkers.

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.

Topological analysis of protein co-abundance networks identifies novel host targets important for HCV infection and pathogenesis

Background

High-throughput methods for obtaining global measurements of transcript and protein levels in biological samples has provided a large amount of data for identification of 'target' genes and proteins of interest. These targets may be mediators of functional processes involved in disease and therefore represent key points of control for viruses and bacterial pathogens. Genes and proteins that are the most highly differentially regulated are generally considered to be the most important. We present topological analysis of co-abundance networks as an alternative to differential regulation for confident identification of target proteins from two related global proteomics studies of hepatitis C virus (HCV) infection.

Results

We analyzed global proteomics data sets from a cell culture study of HCV infection and from a clinical study of liver biopsies from HCV-positive patients. Using lists of proteins known to be interaction partners with pathogen proteins we show that the most differentially regulated proteins in both data sets are indeed enriched in pathogen interactors. We then use these data sets to generate co-abundance networks that link proteins based on similar abundance patterns in time or across patients. Analysis of these co-abundance networks using a variety of network topology measures revealed that both degree and betweenness could be used to identify pathogen interactors with better accuracy than differential regulation alone, though betweenness provides the best discrimination. We found that though overall differential regulation was not correlated between the cell culture and liver biopsy data, network topology was conserved to an extent. Finally, we identified a set of proteins that has high betweenness topology in both networks including a protein that we have recently shown to be essential for HCV replication in cell culture.

Conclusions

The results presented show that the network topology of protein co-abundance networks can be used to identify proteins important for viral replication. These proteins represent targets for further experimental investigation that will provide biological insight and potentially could be exploited for novel therapeutic approaches to combat HCV infection.

Differences in gene expression and cytokine production by crystalline vs. amorphous silica in human lung epithelial cells

Background

Exposure to respirable crystalline silica particles, as opposed to amorphous silica, is associated with lung inflammation, pulmonary fibrosis (silicosis), and potentially with lung cancer. We used Affymetrix/GeneSifter microarray analysis to determine whether gene expression profiles differed in a human bronchial epithelial cell line (BEAS 2B) exposed to cristobalite vs. amorphous silica particles at non-toxic and equal surface areas (75 and 150 × 10⁶μm²/cm²). Bio-Plex analysis was also used to determine profiles of secreted cytokines and chemokines in response to both particles. Finally, primary human bronchial epithelial cells (NHBE) were used to comparatively assess silica particle-induced alterations in gene expression.

Results

Microarray analysis at 24 hours in BEAS 2B revealed 333 and 631 significant alterations in gene expression induced by cristobalite at low (75) and high (150 × 10⁶μm²/cm²) amounts, respectively (p < 0.05/cut off ≥ 2.0-fold change). Exposure to amorphous silica micro-particles at high amounts (150 × 10⁶μm²/cm²) induced 108 significant gene changes. Bio-Plex analysis of 27 human cytokines and chemokines revealed 9 secreted mediators (p < 0.05) induced by crystalline silica, but none were induced by amorphous silica. QRT-PCR revealed that cristobalite selectively up-regulated stress-related genes and cytokines (FOS, ATF3, IL6 and IL8) early and over time (2, 4, 8, and 24 h). Patterns of gene expression in NHBE cells were similar overall to BEAS 2B cells. At 75 × 10⁶μm²/cm², there were 339 significant alterations in gene expression induced by cristobalite and 42 by amorphous silica. Comparison of genes in response to cristobalite (75 × 10⁶μm²/cm²) revealed 60 common, significant gene alterations in NHBE and BEAS 2B cells.

Conclusions

Cristobalite silica, as compared to synthetic amorphous silica particles at equal surface area concentrations, had comparable effects on the viability of human bronchial epithelial cells. However, effects on gene expression, as well as secretion of cytokines and chemokines, drastically differed, as the crystalline silica induced more intense responses. Our studies indicate that toxicological testing of particulates by surveying viability and/or metabolic activity is insufficient to predict their pathogenicity. Moreover, they show that acute responses of the lung epithelium, including up-regulation of genes linked to inflammation, oxidative stress, and proliferation, as well as secretion of inflammatory and proliferative mediators, can be indicative of pathologic potential using either immortalized lines (BEAS 2B) or primary cells (NHBE). Assessment of the degree and magnitude of these responses in vitro are suggested as predictive in determining the pathogenicity of potentially harmful particulates.

Conserved host response to highly pathogenic avian influenza virus infection in human cell culture, mouse and macaque model systems

Background

Understanding host response to influenza virus infection will facilitate development of better diagnoses and therapeutic interventions. Several different experimental models have been used as a proxy for human infection, including cell cultures derived from human cells, mice, and non-human primates. Each of these systems has been studied extensively in isolation, but little effort has been directed toward systematically characterizing the conservation of host response on a global level beyond known immune signaling cascades.

Results

In the present study, we employed a multivariate modeling approach to characterize and compare the transcriptional regulatory networks between these three model systems after infection with a highly pathogenic avian influenza virus of the H5N1 subtype. Using this approach we identified functions and pathways that display similar behavior and/or regulation including the well-studied impact on the interferon response and the inflammasome. Our results also suggest a primary response role for airway epithelial cells in initiating hypercytokinemia, which is thought to contribute to the pathogenesis of H5N1 viruses. We further demonstrate that we can use a transcriptional regulatory model from the human cell culture data to make highly accurate predictions about the behavior of important components of the innate immune system in tissues from whole organisms.

Conclusions

This is the first demonstration of a global regulatory network modeling conserved host response between in vitro and in vivo models.

Lipid metabolism modulation by the P2X7 receptor in the immune system and during the course of infection: new insights into the old view

For decades, scientists have described numerous protein pathways and functions. Much of a protein's function depends on its interactions with different partners, and those partners can change depending on the cell type or system. The P2X7 receptor (P2X7R) is one such multifunctional protein that is related to multiple partners and signaling pathways. The relationship between P2X7R and different enzymes involved in lipid metabolism represents a relatively new field in P2X7R research. This field of research began in epithelial cells and currently includes immune and nervous cells. The P2X7R-lipid metabolism pathway is related to many biological functions of P2X7R, such as cell death and pathogen clearance, and this signaling pathway may be involved in many functions that are dependent on bioactive lipids. In the present review, we will attempt to summarize data related to the P2X7R-lipid metabolism pathway, focusing on signaling pathways and their biological relevance to the immune system and infection.