Expression profiling of autism candidate genes during human brain development implicates central immune signaling pathways

The Autism Spectrum Disorders (ASD) represent a clinically heterogeneous set of conditions with strong hereditary components. Despite substantial efforts to uncover the genetic basis of ASD, the genomic etiology appears complex and a clear understanding of the molecular mechanisms underlying Autism remains elusive. We hypothesized that focusing gene interaction networks on ASD-implicated genes that are highly expressed in the developing brain may reveal core mechanisms that are otherwise obscured by the genomic heterogeneity of the disorder. Here we report an in silico study of the gene expression profile from ASD-implicated genes in the unaffected developing human brain. By implementing a biologically relevant approach, we identified a subset of highly expressed ASD-candidate genes from which interactome networks were derived. Strikingly, immune signaling through NFκB, Tnf, and Jnk was central to ASD networks at multiple levels of our analysis, and cell-type specific expression suggested glia--in addition to neurons--deserve consideration. This work provides integrated genomic evidence that ASD-implicated genes may converge on central cytokine signaling pathways.     

Network inference through synergistic subnetwork evolution

Study of signaling networks is important for a better understanding of cell behaviors e.g., growth, differentiation, metabolism, proptosis, and gaining deeper insights into the molecular mechanisms of complex diseases. While there have been many successes in developing computational approaches for identifying potential genes and proteins involved in cell signaling, new methods are needed for identifying network structures that depict underlying signal cascading mechanisms. In this paper, we propose a new computational approach for inferring signaling network structures from overlapping gene sets related to the networks. In the proposed approach, a signaling network is represented as a directed graph and is viewed as a union of many active paths representing linear and overlapping chains of signal cascading activities in the network. Gene sets represent the sets of genes participating in active paths without prior knowledge of the order in which genes occur within each path. From a compendium of unordered gene sets, the proposed algorithm reconstructs the underlying network structure through evolution of synergistic active paths. In our context, the extent of edge overlapping among active paths is used to define the synergy present in a network. We evaluated the performance of the proposed algorithm in terms of its convergence and recovering true active paths by utilizing four gene set compendiums derived from the KEGG database. Evaluation of results demonstrate the ability of the algorithm in reconstructing the underlying networks with high accuracy and precision.     

Specific inhibition of MyD88-independent signaling pathways of TLR3 and TLR4 by resveratrol: molecular targets are TBK1 and RIP1 in TRIF complex

TLRs can activate two distinct branches of downstream signaling pathways. MyD88 and Toll/IL-1R domain-containing adaptor inducing IFN-beta (TRIF) pathways lead to the expression of proinflammatory cytokines and type I IFN genes, respectively. Numerous reports have demonstrated that resveratrol, a phytoalexin with anti-inflammatory effects, inhibits NF-kappaB activation and other downstream signaling pathways leading to the suppression of target gene expression. However, the direct targets of resveratrol have not been identified. In this study, we attempted to identify the molecular target for resveratrol in TLR-mediated signaling pathways. Resveratrol suppressed NF-kappaB activation and cyclooxygenase-2 expression in RAW264.7 cells following TLR3 and TLR4 stimulation, but not TLR2 or TLR9. Further, resveratrol inhibited NF-kappaB activation induced by TRIF, but not by MyD88. The activation of IFN regulatory factor 3 and the expression of IFN-beta induced by LPS, poly(I:C), or TRIF were also suppressed by resveratrol. The suppressive effect of resveratrol on LPS-induced NF-kappaB activation was abolished in TRIF-deficient mouse embryonic fibroblasts, whereas LPS-induced degradation of IkappaBalpha and expression of cyclooxygenase-2 and inducible NO synthase were still inhibited in MyD88-deficient macrophages. Furthermore, resveratrol inhibited the kinase activity of TANK-binding kinase 1 and the NF-kappaB activation induced by RIP1 in RAW264.7 cells. Together, these results demonstrate that resveratrol specifically inhibits TRIF signaling in the TLR3 and TLR4 pathway by targeting TANK-binding kinase 1 and RIP1 in TRIF complex. The results raise the possibility that certain dietary phytochemicals can modulate TLR-derived signaling and inflammatory target gene expression and can alter susceptibility to microbial infection and chronic inflammatory diseases.     

Towards integrative annotation of the cell-type specific gene functional and signaling map in vascular endothelial cells

Vascular endothelial cells (VECs), which form the inner surface of blood vessels, play essential roles in many physiological and pathological processes. VECs are exposed to various micro-environmental stimuli delivered by the circulatory systems. Systematically deciphering the gene functions and signaling circuits in VECs responsive to the complex micro-environmental stimuli is one of the fundamental tasks in vascular biology. Currently, several databases aim at genome-widely annotating the gene functions and signaling circuits, but most of them take limited consideration on the cell-type specific information. And also, current annotations only provide the core genes involved in different signaling circuits, lacking the annotations on the peripheral signaling molecules or the signaling cross-talks. To quickly construct the genome-wide gene functional and signaling map in VECs, we developed a N[combining low line]etwork-based a[combining low line]n[combining low line]n[combining low line]o[combining low line]tating system (Nanno) by integrating cell-type specific gene expression profiles, genome-wide protein-protein interaction (PPI) networks, Gene Ontology (GO) annotations and microRNA (miRNA) target gene information. Using this system, we successfully re-annotated the genes involved in several essential cellular functions and also identified the signaling circuits under different stimuli in VECs in a cell-type specific manner. Many important genes, which are not included in GO annotations, can be recovered by Nanno. And several canonical signaling pathways and miRNAs are predicted to involve in the inflammatory and angiogenic signaling in VECs. The annotations suggest that there may exist cross-talks in cell cycle regulation between the two conditions.     

Lipoteichoic Acid Induces Unique Inflammatory Responses when Compared to Other Toll-Like Receptor 2 Ligands

Toll-like receptors (TLRs) recognize evolutionarily-conserved molecular patterns originating from invading microbes. In this study, we were interested in determining if microbial ligands, which use distinct TLR2-containing receptor complexes, represent unique signals to the cell and can thereby stimulate unique cellular responses. Using the TLR2 ligands, R-FSL1, S-FSL1, Pam2CSK4, Pam3CSK4, and lipoteichoic acid (LTA), we demonstrate that these ligands activate NF-κB and MAP Kinase pathways with ligand-specific differential kinetics in murine macrophages. Most strikingly, LTA stimulation of these pathways was substantially delayed when compared with the other TLR2 ligands. These kinetics differences were associated with a delay in the LTA-induced expression of a subset of genes as compared with another TLR2 ligand, R-FSL1. However, this did not translate to overall differences in gene expression patterns four hours following stimulation with different TLR2 ligands. We extended this study to evaluate the in vivo responses to distinct TLR2 ligands using a murine model of acute inflammation, which employs intravital microscopy to monitor leukocyte recruitment into the cremaster muscle. We found that, although R-FSL1, S-FSL1, Pam2CSK4, and Pam3CSK4 were all able to stimulate robust leukocyte recruitment in vivo, LTA remained functionally inert in this in vivo model. Therefore distinct TLR2 ligands elicit unique cellular responses, as evidenced by differences in the kinetic profiles of signaling and gene expression responses in vitro, as well as the physiologically relevant differences in the in vivo responses to these ligands.     

The Evolution and Origin of Animal Toll-Like Receptor Signaling Pathway Revealed by Network-Level Molecular Evolutionary Analyses

Genes carry out their biological functions through pathways in complex networks consisting of many interacting molecules. Studies on the effect of network architecture on the evolution of individual proteins will provide valuable information for understanding the origin and evolution as well as functional conservation of signaling pathways. However, the relationship between the network architecture and the individual protein sequence evolution is yet little known. In current study, we carried out network-level molecular evolution analysis on TLR (Toll-like receptor ) signaling pathway, which plays an important role in innate immunity in insects and mammals, and we found that: 1) The selection constraint of genes was negatively correlated with its position along TLR signaling pathway; 2) all genes in TLR signaling pathway were highly conserved and underwent strong purifying selection; 3) the distribution of selective pressure along the pathway was driven by differential nonsynonymous substitution levels; 4) The TLR signaling pathway might present in a common ancestor of sponges and eumetazoa, and evolve via the TLR, IKK, IκB and NF-κB genes underwent duplication events as well as adaptor molecular enlargement, and gene structure and conservation motif of NF-κB genes shifted in their evolutionary history. Our results will improve our understanding on the evolutionary history of animal TLR signaling pathway as well as the relationship between the network architecture and the sequences evolution of individual protein.     

Pathogen-specific TLR2 protein activation programs macrophages to induce Wnt-beta-catenin signaling

Innate immunity recognizes and resists various pathogens; however, the mechanisms regulating pathogen versus nonpathogen discrimination are still imprecisely understood. Here, we demonstrate that pathogen-specific activation of TLR2 upon infection with Mycobacterium bovis BCG, in comparison with other pathogenic microbes, including Salmonella typhimurium and Staphylococcus aureus, programs macrophages for robust up-regulation of signaling cohorts of Wnt-β-catenin signaling. Signaling perturbations or genetic approaches suggest that infection-mediated stimulation of Wnt-β-catenin is vital for activation of Notch1 signaling. Interestingly, inducible NOS (iNOS) activity is pivotal for TLR2-mediated activation of Wnt-β-catenin signaling as iNOS(-/-) mice demonstrated compromised ability to trigger activation of Wnt-β-catenin signaling as well as Notch1-mediated cellular responses. Intriguingly, TLR2-driven integration of iNOS/NO, Wnt-β-catenin, and Notch1 signaling contributes to its capacity to regulate the battery of genes associated with T(Reg) cell lineage commitment. These findings reveal a role for differential stimulation of TLR2 in deciding the strength of Wnt-β-catenin signaling, which together with signals from Notch1 contributes toward the modulation of a defined set of effector functions in macrophages and thus establishes a conceptual framework for the development of novel therapeutics.     

Elimination of thermodynamically infeasible loops in steady-state metabolic models

The constraint-based reconstruction and analysis (COBRA) framework has been widely used to study steady-state flux solutions in genome-scale metabolic networks. One shortcoming of current COBRA methods is the possible violation of the loop law in the computed steady-state flux solutions. The loop law is analogous to Kirchhoff's second law for electric circuits, and states that at steady state there can be no net flux around a closed network cycle. Although the consequences of the loop law have been known for years, it has been computationally difficult to work with. Therefore, the resulting loop-law constraints have been overlooked. Here, we present a general mixed integer programming approach called loopless COBRA (ll-COBRA), which can be used to eliminate all steady-state flux solutions that are incompatible with the loop law. We apply this approach to improve flux predictions on three common COBRA methods: flux balance analysis, flux variability analysis, and Monte Carlo sampling of the flux space. Moreover, we demonstrate that the imposition of loop-law constraints with ll-COBRA improves the consistency of simulation results with experimental data. This method provides an additional constraint for many COBRA methods, enabling the acquisition of more realistic simulation results.     

Signaling flux redistribution at toll-like receptor pathway junctions

Various receptors on cell surface recognize specific extracellular molecules and trigger signal transduction altering gene expression in the nucleus. Gain or loss-of-function mutations of one molecule have shown to affect alternative signaling pathways with a poorly understood mechanism. In Toll-like receptor (TLR) 4 signaling, which branches into MyD88- and TRAM-dependent pathways upon lipopolysaccharide (LPS) stimulation, we investigated the gain or loss-of-function mutations of MyD88. We predict, using a computational model built on the perturbation-response approach and the law of mass conservation, that removal and addition of MyD88 in TLR4 activation, enhances and impairs, respectively, the alternative TRAM-dependent pathway through signaling flux redistribution (SFR) at pathway branches. To verify SFR, we treated MyD88-deficient macrophages with LPS and observed enhancement of TRAM-dependent pathway based on increased IRF3 phosphorylation and induction of Cxcl10 and Ifit2. Furthermore, increasing the amount of MyD88 in cultured cells showed decreased TRAM binding to TLR4. Investigating another TLR4 pathway junction, from TRIF to TRAF6, RIP1 and TBK1, the removal of MyD88-dependent TRAF6 increased expression of TRAM-dependent Cxcl10 and Ifit2. Thus, we demonstrate that SFR is a novel mechanism for enhanced activation of alternative pathways when molecules at pathway junctions are removed. Our data suggest that SFR may enlighten hitherto unexplainable intracellular signaling alterations in genetic diseases where gain or loss-of-function mutations are observed.     

Dangerous liaisons between interleukin-6 cytokine and toll-like receptor families: A potent combination in inflammation and cancer

The potent pro-inflammatory actions of members of the interleukin (IL)-6 cytokine and toll-like receptor (TLR) families have been implicated in numerous inflammatory disorders, as well as inflammation-associated cancers. It is fast becoming apparent that a hallmark of many such inflammatory-related diseases is the overlapping deregulated expression of members of each family, and the consequent augmented activation of shared signaling pathways. Here, we review the molecular basis by which the IL-6 cytokine and TLR family signaling networks are regulated, and integrate recent advances exploring the intimate cross-regulation of these two families which may provide the foundation for the future development of therapeutics to target chronic inflammation-associated diseases, including cancer.     

BCL10 mediates lipopolysaccharide/toll-like receptor-4 signaling through interaction with Pellino2

Toll-like receptor (TLR) pathways signal through microbial components stimulation to induce innate immune responses. Herein, we demonstrate that BCL10, a critical molecule that signals between the T cell receptor and IkappaB kinase complexes, is involved in the innate immune system and is required for appropriate TLR4 pathway and nuclear factor-kappaB (NF-kappaB) activation. In response to lipopolysaccharide (LPS) stimulation, BCL10 was recruited to TLR4 signaling complexes and associated with Pellino2, an essential component down-stream of BCL10 in the TLR4 pathway. In a BCL10-deficient macrophage cell line, LPS-induced NF-kappaB activation was consistently defective, whereas activator protein-1 and Elk-1 signaling was intact. In addition, we found that BCL10 was targeted by SOCS3 for negative regulation in LPS signaling. The recruitment of BCL10 to TLR4 signaling complexes was attenuated by induced expression of SOCS3 in a feedback loop. Furthermore, ectopic SOCS3 expression blocked the interaction between BCL10 and Pellino2 together with BCL10-generated NF-kappaB activation and inducible nitric-oxide synthase expression. Together, these data define an important role of BCL10 in the innate immune system.     

Variance of gene expression identifies altered network constraints in neurological disease

Gene expression analysis has become a ubiquitous tool for studying a wide range of human diseases. In a typical analysis we compare distinct phenotypic groups and attempt to identify genes that are, on average, significantly different between them. Here we describe an innovative approach to the analysis of gene expression data, one that identifies differences in expression variance between groups as an informative metric of the group phenotype. We find that genes with different expression variance profiles are not randomly distributed across cell signaling networks. Genes with low-expression variance, or higher constraint, are significantly more connected to other network members and tend to function as core members of signal transduction pathways. Genes with higher expression variance have fewer network connections and also tend to sit on the periphery of the cell. Using neural stem cells derived from patients suffering from Schizophrenia (SZ), Parkinson's disease (PD), and a healthy control group, we find marked differences in expression variance in cell signaling pathways that shed new light on potential mechanisms associated with these diverse neurological disorders. In particular, we find that expression variance of core networks in the SZ patient group was considerably constrained, while in contrast the PD patient group demonstrated much greater variance than expected. One hypothesis is that diminished variance in SZ patients corresponds to an increased degree of constraint in these pathways and a corresponding reduction in robustness of the stem cell networks. These results underscore the role that variation plays in biological systems and suggest that analysis of expression variance is far more important in disease than previously recognized. Furthermore, modeling patterns of variability in gene expression could fundamentally alter the way in which we think about how cellular networks are affected by disease processes.     

TLR2 signaling is critical for Mycoplasma pneumoniae-induced airway mucin expression

Excessive airway mucin production contributes to airway obstruction in lung diseases such as asthma and chronic obstructive pulmonary disease. Respiratory infections, such as atypical bacterium Mycoplasma pneumoniae (Mp), have been proposed to worsen asthma and chronic obstructive pulmonary disease in part through increasing mucin. However, the molecular mechanisms involved in infection-induced airway mucin overexpression remain to be determined. TLRs have been recently shown to be a critical component in host innate immune response to infections. TLR2 signaling has been proposed to be involved in inflammatory cell activation by mycoplasma-derived lipoproteins. In this study, we show that TLR2 signaling is critical in Mp-induced airway mucin expression in mice and human lung epithelial cells. Respiratory Mp infection in BALB/c mice activated TLR2 signaling and increased airway mucin. A TLR2-neutralizing Ab significantly reduced mucin expression in Mp-infected BALB/c mice. Furthermore, Mp-induced airway mucin was abolished in TLR2 gene-deficient C57BL/6 mice. Additionally, Mp was shown to increase human lung A549 epithelial cell mucin expression, which was inhibited by the overexpression of a human TLR2 dominant-negative mutant. These results clearly demonstrate that respiratory Mp infection increases airway mucin expression, which is dependent on the activation of TLR2 signaling.     

Gene expression in the social behavior network of the wire‐tailed manakin (Pipra filicauda) brain

The vertebrate basal forebrain and midbrain contain a set of interconnected nuclei that control social behavior. Conserved anatomical structures and functions of these nuclei have now been documented among fish, amphibians, reptiles, birds and mammals, and these brain regions have come to be known as the vertebrate social behavior network (SBN). While it is known that nuclei (nodes) of the SBN are rich in steroid and neuropeptide activity linked to behavior, simultaneous variation in the expression of neuroendocrine genes among several SBN nuclei has not yet been described in detail. In this study, we use RNA‐seq to profile gene expression across seven brain regions representing five nodes of the vertebrate SBN in a passerine bird, the wire‐tailed manakin Pipra filicauda. Using weighted gene co‐expression network analysis, we reconstructed sets of coregulated genes, showing striking patterns of variation in neuroendocrine gene expression across the SBN. We describe regional variation in gene networks comprising a broad set of hormone receptors, neuropeptides, steroidogenic enzymes, catecholamines and other neuroendocrine signaling molecules. Our findings show heterogeneous patterns of brain gene expression across nodes of the avian SBN and provide a foundation for future analyses of how the regulation of gene networks may mediate social behavior. These results highlight the importance of region‐specific sampling in studies of the mechanisms of behavior.