Signaling network of dendritic cells in response to pathogens: a community-input supported knowledgebase

Threonyl-tRNA Synthetase Promotes T Helper Type 1 Cell Responses by Inducing Dendritic Cell Maturation and IL-12 Production via an NF-κB Pathway

Threonyl-tRNA synthetase (TRS) is an aminoacyl-tRNA synthetase that catalyzes the aminoacylation of tRNA by transferring threonine. In addition to an essential role in translation, TRS was extracellularly detected in autoimmune diseases and also exhibited pro-angiogenetic activity. TRS is reported to be secreted into the extracellular space when vascular endothelial cells encounter tumor necrosis factor-α. As T helper (Th) type 1 response and IFN-γ levels are associated with autoimmunity and angiogenesis, in this study, we investigated the effects of TRS on dendritic cell (DC) activation and CD4 T cell polarization. TRS-treated DCs exhibited up-regulated expression of activation-related cell-surface molecules, including CD40, CD80, CD86, and MHC class II. Treatment of DCs with TRS resulted in a significant increase of IL-12 production. TRS triggered nuclear translocation of the NF-κB p65 subunit along with the degradation of IκB proteins and the phosphorylation of MAPKs in DCs. Additionally, MAPK inhibitors markedly recovered the degradation of IκB proteins and the increased IL-12 production in TRS-treated DCs, suggesting the involvement of MAPKs as the upstream regulators of NF-κB in TRS-induced DC maturation and activation. Importantly, TRS-stimulated DCs significantly increased the populations of IFN-γ⁺CD4 T cells, and the levels of IFN-γ when co-cultured with CD4⁺ T cells. The addition of a neutralizing anti-IL-12 mAb to the cell cultures of TRS-treated DCs and CD4⁺ T cells resulted in decreased IFN-γ production, indicating that TRS-stimulated DCs may enhance the Th1 response through DC-derived IL-12. Injection of OT-II mice with OVA-pulsed, TRS-treated DCs also enhanced Ag-specific Th1 responses in vivo. Importantly, injection with TRS-treated DC exhibited increased populations of IFN-γ⁺-CD4⁺ and -CD8⁺ T cells as well as secretion level of IFN-γ, resulting in viral clearance and increased survival periods in mice infected with influenza A virus (IAV), as the Th1 response is associated with the enhanced cellular immunity, including anti-viral activity. Taken together, these results indicate that TRS promotes the maturation and activation of DCs, DC-mediated Th1 responses, and anti-viral effect on IAV infection.

Quantitative Proteomics Analysis Revealed Compromised Chicken Dendritic Cells Function at Early Stage of Very Virulent Infectious Bursal Disease Virus Infection

Chicken dendritic cells (DCs) have been demonstrated to be susceptible to infectious bursal disease virus (IBDV), a causative agent of acute and immunosuppressed disease in young chicks known as infectious bursal disease. Further functional characterization of IBDV-infected DCs of chickens is required to provide a better understanding on the influence of the virus on chicken bone marrow-derived dendritic cells (BM-DCs) following very virulent (vv) IBDV infection. Membrane proteins of BM-DCs were extracted and the proteins were further denatured and reduced before performing labeling with isobaric tags for relative and absolute quantitation. The differential expression protein profiles were identified and quantified using liquid chromatography coupled with tandem mass spectrometry, and later validated using flow cytometry and real-time reverse transcriptase PCR. The analysis has identified 134 differentially regulated proteins from a total of 283 proteins (cutoff values of ≤0.67, ≥1.5, and ProtScore >1.3 at 95% confidence interval), which produced high-yield membrane fractions. The entry of vvIBDV into the plasma membrane of BM-DCs was observed at 3 hr postinfection by the disruption of several important protein molecule functions, namely apoptosis, RNA/DNA/protein synthesis, and transport and cellular organization, without the activation of proteins associated with signaling. At the later stage of infection, vvIBDV induced expression of several proteins, namely CD200 receptor 1-A, integrin alpha-5, HSP-90, cathepsin, lysosomal-associated membrane protein, and Ras-related proteins, which play crucial roles in signaling, apoptosis, stress response, and antigen processing as well as in secretion of danger-associated proteins. These findings collectively indicated that the chicken DCs are expressing various receptors regarded as potential targets for pathogen interaction during viral infection. Therefore, fundamental study of the interaction of DCs and IBDV will provide valuable information in understanding the role of professional antigen-presenting cells in chickens and their molecular interactions during IBDV infection and vaccination.

Differentially Tolerized Mouse Antigen Presenting Cells Share a Common miRNA Signature Including Enhanced mmu-miR-223-3p Expression Which Is Sufficient to Imprint a Protolerogenic State

Dendritic cells (DCs) are pivotal for the induction and maintenance of antigen-specific tolerance and immunity. miRNAs mediate post-transcriptional gene regulation and control in part the differentiation and stimulation-induced immunogenic function of DCs. However, the relevance of miRNAs for the induction and maintenance of a tolerogenic state of DCs has scarcely been highlighted yet. We differentiated mouse bone marrow cells to conventional/myeloid DCs or to tolerogenic antigen presenting cells (APCs) by using a glucocorticoid (dexamethasone) or interleukin-10, and assessed the miRNA expression patterns of unstimulated and LPS-stimulated cell populations by array analysis and QPCR. Differentially tolerized mouse APCs convergingly down-regulated a set of miRNA species at either state of activation as compared with the corresponding control DC population (mmu-miR-9-5p, mmu-miR-9-3p, mmu-miR-155-5p). These miRNAs were also upregulated in control DCs in response to stimulation. In contrast, miRNAs that were convergingly upregulated in both tolerized APC groups at stimulated state (mmu-miR-223-3p, mmu-miR-1224-5p) were downregulated in control DCs in response to stimulation. Overexpression of mmu-miR-223-3p in DCs was sufficient to prevent stimulation-associated acquisition of potent T cell stimulatory capacity. Overexpression of mmu-miR-223-3p in a DC line resulted in attenuated expression of known (Cflar, Rasa1, Ras) mRNA targets of this miRNA species shown to affect pathways that control DC activation. Taken together, we identified sets of miRNAs convergingly regulated in differentially tolerized APCs, which may contribute to imprint stimulation-resistant tolerogenic function as demonstrated for mmu-miR-223-3p. Knowledge of miRNAs with protolerogenic function enables immunotherapeutic approaches aimed to modulate immune responses by regulating miRNA expression.

A web platform for the network analysis of high-throughput data in melanoma and its use to investigate mechanisms of resistance to anti-PD1 immunotherapy

Cellular phenotypes are established and controlled by complex and precisely orchestrated molecular networks. In cancer, mutations and dysregulations of multiple molecular factors perturb the regulation of these networks and lead to malignant transformation. High-throughput technologies are a valuable source of information to establish the complex molecular relationships behind the emergence of malignancy, but full exploitation of this massive amount of data requires bioinformatics tools that rely on network-based analyses. In this report we present the Virtual Melanoma Cell, an online tool developed to facilitate the mining and interpretation of high-throughput data on melanoma by biomedical researches. The platform is based on a comprehensive, manually generated and expert-validated regulatory map composed of signaling pathways important in malignant melanoma. The Virtual Melanoma Cell is a tool designed to accept, visualize and analyze user-generated datasets. It is available at: https://www.vcells.net/melanoma. To illustrate the utilization of the web platform and the regulatory map, we have analyzed a large publicly available dataset accounting for anti-PD1 immunotherapy treatment of malignant melanoma patients.

Increased TREM-2 expression on the subsets of CD11c+ cells in the lungs and lymph nodes during allergic airway inflammation

Dendritic cells (DCs) are professional APCs that traffic to the draining lymph nodes where they present processed antigens to naïve T-cells. The recently discovered triggering receptor expressed on myeloid cells (TREM)-2 has been shown to be expressed on DCs in several disease models, however, its role in asthma is yet to be elucidated. In the present study, we examined the effect of allergen exposure on TREM-2 expression in the airways and on DC subsets in the lung and lymph nodes in murine model of allergic airway inflammation. Sensitization and challenge with ovalbumin reproduced hallmark features of asthma. TREM-2 mRNA expression in the whole lung was significantly higher in the OVA-sensitized and -challenged mice which was associated with increased protein expression in the lungs. Analysis of CD11c⁺MHC-II^hi DCs in the lung and draining lymph nodes revealed that allergen exposure increased TREM-2 expression on all DC subsets with significantly higher expression in the lymph nodes. This was associated with increased mRNA expression of Th2 and Th17 cytokines. Further analyses showed that these TREM-2⁺ cells expressed high levels of CCR-7 and CD86 suggesting a potential role of TREM-2 in mediating maturation and migration of DC subsets in allergic airway inflammation.

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.

Modelling the Structure and Dynamics of Biological Pathways

There is a need for formalised diagrams that both summarise current biological pathway knowledge and support modelling approaches that explain and predict their behaviour. Here, we present a new, freely available modelling framework that includes a biologist-friendly pathway modelling language (mEPN), a simple but sophisticated method to support model parameterisation using available biological information; a stochastic flow algorithm that simulates the dynamics of pathway activity; and a 3-D visualisation engine that aids understanding of the complexities of a system’s dynamics. We present example pathway models that illustrate of the power of approach to depict a diverse range of systems.

This Community Page presents a biologist-friendly method for compiling detailed graphical models of biological pathways from the literature, including their subsequent parameterization for use in dynamic simulations of their activity.

Network Analysis of a Comprehensive Knowledge Repository Reveals a Dual Role for Ceramide in Alzheimer's Disease

Alzheimer’s disease (AD) is the most common cause of senile dementia. Many inflammatory factors such as amyloid-β and pro-inflammatory cytokines are known to contribute to the inflammatory response in the AD brain. Sphingolipids are widely known to have roles in the pathogenesis of inflammatory diseases, where the precise roles for sphingolipids in inflammation-associated pathogenesis of AD are not well understood. Here we performed a network analysis to clarify the importance of sphingolipids and to model relationships among inflammatory factors and sphingolipids in AD. In this study, we have updated sphingolipid signaling and metabolic cascades in a map of AD signaling networks that we named “AlzPathway,” a comprehensive knowledge repository of signaling pathways in AD. Our network analysis of the updated AlzPathway indicates that the pathways related to ceramide are one of the primary pathways and that ceramide is one of the important players in the pathogenesis of AD. The results of our analysis suggest the following two prospects about inflammation in AD: (1) ceramide could play important roles in both inflammatory and anti-inflammatory pathways of AD, and (2) several factors such as Sphingomyelinase and Siglec-11 may be associated with ceramide related inflammation and anti-inflammation pathways in AD. In this study, network analysis of comprehensive knowledge repository reveals a dual role for ceramide in AD. This result provides a clue to clarify sphingolipids related inflammatory and anti-inflammatory pathways in AD.

Dendritic Cells and Leishmania Infection: Adding Layers of Complexity to a Complex Disease

Leishmaniasis is a group of neglected diseases whose clinical manifestations depend on factors from the host and the pathogen. It is an important public health problem worldwide caused by the protozoan parasite from the Leishmania genus. Cutaneous Leishmaniasis (CL) is the most frequent form of this disease transmitted by the bite of an infected sandfly into the host skin. The parasites can be uptook and/or recognized by macrophages, neutrophils, and/or dendritic cells (DCs). Initially, DCs were described to play a protective role in activating the immune response against Leishmania parasites. However, several reports showed a dichotomic role of DCs in modulating the host immune response to susceptibility or resistance in CL. In this review, we discuss (1) the interactions between DCs and parasites from different species of Leishmania and (2) the crosstalk of DCs and other cells during CL infection. The complexity of these interactions profoundly affects the adaptive immune response and, consequently, the disease outcome, especially from Leishmania species of the New World.

Integration of Innate Immune Signaling

The last decades of research in innate immunology have revealed a multitude of sensing receptors that evaluate the presence of microorganisms or cellular damage in tissues. In the context of a complex tissue, many such sensing events occur simultaneously. Thus, the downstream pathways need to be integrated to launch an appropriate cellular response, to tailor the magnitude of the reaction to the inciting event, and to terminate it in a manner that avoids immunopathology. Here, we provide a conceptual overview of the crosstalk between innate immune receptors in the initiation of a concerted immune reaction to microbial and endogenous triggers. We classify the known interactions into categories of communication and provide examples of their importance in pathogenic infection.

NLRs Challenge Impacts Tight Junction Claudins In Sertoli Cells

AIM

The present study aims to investigate the NALP3 system and its effect on claudins in Sertoli cells using a mouse adult Sertoli cell line as a model. We focus on the Sertoli cell biology looking for the possible implications for male reproductive functions.

MATERIALS AND METHODS

Adult Sertoli cells were transfected with NAPL3 siRNA and treated with NOD1 (ie-DAP) and NOD2 (MDP) receptor ligands. Two dimensional gel electrophoresis was performed on lysates of non-challenged and MDP-treated Sertoli cells.

RESULTS

There were positive claudin-5 and claudin-11 expression levels on transcript (RT-qPCR) levels. Specific protein spots in 2D gels were detected after bioinformatics analysis. This study demonstrates direct induction of tight-junction proteins probably favouring junction stability.

CONCLUSIONS

The innate immunity and tight-junction pathway integration probably have a protective role for both blood-testis immune barrier and spermatogenesis compartmentalisation maintained by the very same barrier. This integration also points the way for mechanistic research of the disturbances inflicted during an inflammatory response in the testis niche.

The gastrin and cholecystokinin receptors mediated signaling network: a scaffold for data analysis and new hypotheses on regulatory mechanisms

Background

The gastrointestinal peptide hormones cholecystokinin and gastrin exert their biological functions via cholecystokinin receptors CCK1R and CCK2R respectively. Gastrin, a central regulator of gastric acid secretion, is involved in growth and differentiation of gastric and colonic mucosa, and there is evidence that it is pro-carcinogenic. Cholecystokinin is implicated in digestion, appetite control and body weight regulation, and may play a role in several digestive disorders.

Results

We performed a detailed analysis of the literature reporting experimental evidence on signaling pathways triggered by CCK1R and CCK2R, in order to create a comprehensive map of gastrin and cholecystokinin-mediated intracellular signaling cascades. The resulting signaling map captures 413 reactions involving 530 molecular species, and incorporates the currently available knowledge into one integrated signaling network. The decomposition of the signaling map into sub-networks revealed 18 modules that represent higher-level structures of the signaling map. These modules allow a more compact mapping of intracellular signaling reactions to known cell behavioral outcomes such as proliferation, migration and apoptosis. The integration of large-scale protein-protein interaction data to this literature-based signaling map in combination with topological analyses allowed us to identify 70 proteins able to increase the compactness of the map. These proteins represent experimentally testable hypotheses for gaining new knowledge on gastrin- and cholecystokinin receptor signaling. The CCKR map is freely available both in a downloadable, machine-readable SBML-compatible format and as a web resource through PAYAO (http://sblab.celldesigner.org:18080/Payao11/bin/).

Conclusion

We have demonstrated how a literature-based CCKR signaling map together with its protein interaction extensions can be analyzed to generate new hypotheses on molecular mechanisms involved in gastrin- and cholecystokinin-mediated regulation of cellular processes.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-015-0181-z) contains supplementary material, which is available to authorized users.

Atlas of Cancer Signalling Network: a systems biology resource for integrative analysis of cancer data with Google Maps

Cancerogenesis is driven by mutations leading to aberrant functioning of a complex network of molecular interactions and simultaneously affecting multiple cellular functions. Therefore, the successful application of bioinformatics and systems biology methods for analysis of high-throughput data in cancer research heavily depends on availability of global and detailed reconstructions of signalling networks amenable for computational analysis. We present here the Atlas of Cancer Signalling Network (ACSN), an interactive and comprehensive map of molecular mechanisms implicated in cancer. The resource includes tools for map navigation, visualization and analysis of molecular data in the context of signalling network maps. Constructing and updating ACSN involves careful manual curation of molecular biology literature and participation of experts in the corresponding fields. The cancer-oriented content of ACSN is completely original and covers major mechanisms involved in cancer progression, including DNA repair, cell survival, apoptosis, cell cycle, EMT and cell motility. Cell signalling mechanisms are depicted in detail, together creating a seamless ‘geographic-like' map of molecular interactions frequently deregulated in cancer. The map is browsable using NaviCell web interface using the Google Maps engine and semantic zooming principle. The associated web-blog provides a forum for commenting and curating the ACSN content. ACSN allows uploading heterogeneous omics data from users on top of the maps for visualization and performing functional analyses. We suggest several scenarios for ACSN application in cancer research, particularly for visualizing high-throughput data, starting from small interfering RNA-based screening results or mutation frequencies to innovative ways of exploring transcriptomes and phosphoproteomes. Integration and analysis of these data in the context of ACSN may help interpret their biological significance and formulate mechanistic hypotheses. ACSN may also support patient stratification, prediction of treatment response and resistance to cancer drugs, as well as design of novel treatment strategies.

On the modelling and analysis of the regulatory network of dengue virus pathogenesis and clearance

Dengue virus can ignite both protective and pathogenic responses in human. The pathogenesis is related with modified functioning of our immune system during infection. Pattern recognition receptors like Toll like receptor 3 is vital for the induction of innate immunity in case of Dengue infection. Toll like receptor 3 induces TRIF mediated activation of Type 1 interferons and Fc receptor mediated induction of cytokines. Interferons have been related with clearance of Dengue virus but it has adopted modified regulatory mechanisms to counter this effect. SOCS protein is also induced due to the interferon and cytokine mediated signalling which can subsequently play its part in the regulation of interferon and cytokine production. Our hypothesis in this study relates the pathogenesis of Dengue virus with the SOCS mediated inhibition of our innate immunity. We used the qualitative formalism of René Thomas to model the biological regulatory network of Toll like receptor 3 mediated signalling pathway in an association with pathogenesis of dengue. Logical parameters for the qualitative modelling were inferred using a model checking approach implemented in SMBioNet. A linear hybrid model, parametric linear hybrid automaton, was constructed to incorporate the activation and inhibition time delays in the qualitative model. The qualitative model captured all the possible expression dynamics of the proteins in the form of paths, some of which were observed as abstract cycles (representing homoeostasis) and diverging paths towards stable states. The analysis of the qualitative model highlighted the importance of SOCS protein in elevating propagation of dengue virus through inhibition of type 1 interferons. Detailed qualitative analysis of regulatory network endorses our hypothesis that elevated levels of cytokine subsequently induce SOCS expression which in turn results into the continuous down-regulation of Toll like receptor 3 and interferon. This may result into the Dengue pathogenesis during the stage of immunosuppression. Further analysis with HyTech (HYbrid TECHnology) tool provided us with the real-time constraints (delay constraints) of the proteins involved in the cyclic paths of the regulatory network backing the evidence provided by the qualitative analysis. The HyTech results also suggest that the role of SOCS is vital in homoeostasis.

In silico model-based inference: a contemporary approach for hypothesis testing in network biology

Inductive inference plays a central role in the study of biological systems where one aims to increase their understanding of the system by reasoning backwards from uncertain observations to identify causal relationships among components of the system. These causal relationships are postulated from prior knowledge as a hypothesis or simply a model. Experiments are designed to test the model. Inferential statistics are used to establish a level of confidence in how well our postulated model explains the acquired data. This iterative process, commonly referred to as the scientific method, either improves our confidence in a model or suggests that we revisit our prior knowledge to develop a new model. Advances in technology impact how we use prior knowledge and data to formulate models of biological networks and how we observe cellular behavior. However, the approach for model-based inference has remained largely unchanged since Fisher, Neyman and Pearson developed the ideas in the early 1900s that gave rise to what is now known as classical statistical hypothesis (model) testing. Here, I will summarize conventional methods for model-based inference and suggest a contemporary approach to aid in our quest to discover how cells dynamically interpret and transmit information for therapeutic aims that integrates ideas drawn from high performance computing, Bayesian statistics, and chemical kinetics.

A systems biology approach to the analysis of subset-specific responses to lipopolysaccharide in dendritic cells

Dendritic cells (DCs) are critical for regulating CD4 and CD8 T cell immunity, controlling Th1, Th2, and Th17 commitment, generating inducible Tregs, and mediating tolerance. It is believed that distinct DC subsets have evolved to control these different immune outcomes. However, how DC subsets mount different responses to inflammatory and/or tolerogenic signals in order to accomplish their divergent functions remains unclear. Lipopolysaccharide (LPS) provides an excellent model for investigating responses in closely related splenic DC subsets, as all subsets express the LPS receptor TLR4 and respond to LPS in vitro. However, previous studies of the LPS-induced DC transcriptome have been performed only on mixed DC populations. Moreover, comparisons of the in vivo response of two closely related DC subsets to LPS stimulation have not been reported in the literature to date. We compared the transcriptomes of murine splenic CD8 and CD11b DC subsets after in vivo LPS stimulation, using RNA-Seq and systems biology approaches. We identified subset-specific gene signatures, which included multiple functional immune mediators unique to each subset. To explain the observed subset-specific differences, we used a network analysis approach. While both DC subsets used a conserved set of transcription factors and major signalling pathways, the subsets showed differential regulation of sets of genes that ‘fine-tune’ the network Hubs expressed in common. We propose a model in which signalling through common pathway components is ‘fine-tuned’ by transcriptional control of subset-specific modulators, thus allowing for distinct functional outcomes in closely related DC subsets. We extend this analysis to comparable datasets from the literature and confirm that our model can account for cell subset-specific responses to LPS stimulation in multiple subpopulations in mouse and man.

Differences in innate cytokine responses between European and African children

Although differences in immunological responses between populations have been found in terms of vaccine efficacy, immune responses to infections and prevalence of chronic inflammatory diseases, the mechanisms responsible for these differences are not well understood. Therefore, innate cytokine responses mediated by various classes of pattern-recognition receptors including Toll-like receptors (TLR), C-type lectin receptors (CLRs) and nucleotide-binding oligomerisation domain-like receptors (NLRs) were compared between Dutch (European), semi-urban and rural Gabonese (African) children. Whole blood was stimulated for 24 hours and the pro-inflammatory tumor necrosis factor (TNF) and the anti-inflammatory/regulatory interleukin-10 (IL-10) cytokines in culture supernatant were measured by enzyme-linked immunosorbent assay (ELISA). Gabonese children had a lower pro-inflammatory response to poly(I:C) (TLR3 ligand), but a higher pro-inflammatory response to FSL-1 (TLR2/6 ligand), Pam3 (TLR2/1 ligand) and LPS (TLR4 ligand) compared to Dutch children. Anti-inflammatory responses to Pam3 were also higher in Gabonese children. Non-TLR ligands did not induce substantial cytokine production on their own. Interaction between various TLR and non-TLR receptors was further assessed, but no differences were found between the three populations. In conclusion, using a field applicable assay, significant differences were observed in cytokine responses between European and African children to TLR ligands, but not to non-TLR ligands.

A systems biological approach reveals multiple crosstalk mechanism between gram-positive and negative bacterial infections: an insight into core mechanism and unique molecular signatures

Background

Bacterial infections remain a major threat and a leading cause of death worldwide. Most of the bacterial infections are caused by gram-positive and negative bacteria, which are recognized by Toll-like receptor (TLR) 2 and 4, respectively. Activation of these TLRs initiates multiple pathways that subsequently lead to effective immune response. Although, both the TLRs share common signaling mechanism yet they may exhibit specificity as well, resulting in the release of diverse range of inflammatory mediators which could be used as candidate biomolecules for bacterial infections.

Results

We adopted systems biological approach to identify signaling pathways mediated by TLRs to determine candidate molecules associated with bacterial infections. We used bioinformatics concepts, including literature mining to construct protein-protein interaction network, prioritization of TLRs specific nodes using microarray data and pathway analysis. Our constructed PPI network for TLR 2 (nodes: 4091 and edges: 66068) and TLR 4 (node: 4076 and edges: 67898) showed 3207 common nodes, indicating that both the TLRs might share similar signaling events that are attributed to cell migration, MAPK pathway and several inflammatory cascades. Our results propose the potential collaboration between the shared signaling pathways of both the receptors may enhance the immune response against invading pathogens. Further, to identify candidate molecules, the TLRs specific nodes were prioritized using microarray differential expressed genes. Of the top prioritized TLR 2 molecules, 70% were co-expressed. A similar trend was also observed within TLR 4 nodes. Further, most of these molecules were preferentially found in blood plasma for feasible diagnosis.

Conclusions

The analysis reveals the common and unique mechanism regulated by both the TLRs that provide a broad perspective of signaling events in bacterial infections. Further, the identified candidate biomolecules could potentially aid future research efforts concerning the possibility in differential diagnosis of gram-positive and negative bacterial infections.

A modular cell-type focused inflammatory process network model for non-diseased pulmonary tissue

Exposure to environmental stressors such as cigarette smoke (CS) elicits a variety of biological responses in humans, including the induction of inflammatory responses. These responses are especially pronounced in the lung, where pulmonary cells sit at the interface between the body’s internal and external environments. We combined a literature survey with a computational analysis of multiple transcriptomic data sets to construct a computable causal network model (the Inflammatory Process Network (IPN)) of the main pulmonary inflammatory processes. The IPN model predicted decreased epithelial cell barrier defenses and increased mucus hypersecretion in human bronchial epithelial cells, and an attenuated pro-inflammatory (M1) profile in alveolar macrophages following exposure to CS, consistent with prior results. The IPN provides a comprehensive framework of experimentally supported pathways related to CS-induced pulmonary inflammation. The IPN is freely available to the scientific community as a resource with broad applicability to study the pathogenesis of pulmonary disease.

The structural network of inflammation and cancer: merits and challenges

Inflammation, the first line of defense against pathogens can contribute to all phases of tumorigenesis, including tumor initiation, promotion and metastasis. Within this framework, the Toll-like receptor (TLR) pathway plays a central role in inflammation and cancer. Although extremely useful, the classical representation of this, and other pathways in the cellular network in terms of nodes (proteins) and edges (interactions) is incomplete. Structural pathways can help complete missing parts of such diagrams: they demonstrate in detail how signals coming from different upstream pathways merge and propagate downstream, how parallel pathways compensate each other in drug resistant mutants, how multi-subunit signaling complexes form and in particular why they are needed and how they work, how allosteric events can control these proteins and their pathways, and intricate details of feedback loops and how kick in. They can also explain the mechanisms of some oncogenic SNP mutations. Constructing structural pathways is a challenging task. Here, our goal is to provide an overview of inflammation and cancer from the structural standpoint, focusing on the TLR pathway. We use the powerful PRISM (PRotein Interactions by Structural Matching) tool to reveal important structural information of interactions in and within key orchestrators of the TLR pathway, such as MyD88.

The phagocytic capacity and immunological potency of human dendritic cells is improved by α2,6-sialic acid deficiency

Dendritic cells (DCs) play an essential role in immunity against bacteria by phagocytosis and by eliciting adaptive immune responses. Previously, we demonstrated that human monocyte-derived DCs (MDDCs) express a high content of cell surface α2,6-sialylated glycans. However, the relative role of these sialylated structures in phagocytosis of bacteria has not been reported. Here, we show that treatment with a sialidase significantly improved the capacity of both immature and mature MDDCs to phagocytose Escherichia coli. Desialylated MDDCs had a significantly more mature phenotype, with higher expression of MHC molecules and interleukin (IL)-12, tumour necrosis factor-α, IL-6 and IL-10 cytokines, and nuclear factor-κB activation. T lymphocytes primed by desialylated MDDCs expressed more interferon-γ when compared with priming by sialylated MDDCs. Improved phagocytosis required E. coli sialic acids, indicating a mechanism of host-pathogen interaction dependent on sialic acid moieties. The DCs harvested from mice deficient in the ST6Gal.1 sialyltransferase showed improved phagocytosis capacity, demonstrating that the observed sialidase effect was a result of the removal of α2,6-sialic acid. The phagocytosis of different pathogenic E. coli isolates was also enhanced by sialidase, which suggests that modifications on MDDC sialic acids may be considered in the development of MDDC-based antibacterial therapies. Physiologically, our findings shed new light on mechanisms that modulate the function of both immature and mature MDDCs, in the context of host-bacteria interaction. Hence, with particular relevance to DC-based therapies, the engineering of α2,6-sialic acid cell surface is a novel possibility to fine tune DC phagocytosis and immunological potency.

From a biological hypothesis to the construction of a mathematical model

Mathematical models serve to explain complex biological phenomena and provide predictions that can be tested experimentally. They can provide plausible scenarios of a complex biological behavior when intuition is not sufficient anymore. The process from a biological hypothesis to a mathematical model might be challenging for biologists that are not familiar with mathematical modeling. In this chapter we discuss a possible workflow that describes the steps to be taken starting from a biological hypothesis on a biochemical cellular mechanism to the construction of a mathematical model using the appropriate formalism. An important part of this workflow is formalization of biological knowledge, which can be facilitated by existing tools and standards developed by the systems biology community. This chapter aims at introducing modeling to experts in molecular biology that would like to convert their hypotheses into mathematical models.

AlzPathway: a comprehensive map of signaling pathways of Alzheimer's disease

Background

Alzheimer’s disease (AD) is the most common cause of dementia among the elderly. To clarify pathogenesis of AD, thousands of reports have been accumulating. However, knowledge of signaling pathways in the field of AD has not been compiled as a database before.

Description

Here, we have constructed a publicly available pathway map called “AlzPathway” that comprehensively catalogs signaling pathways in the field of AD. We have collected and manually curated over 100 review articles related to AD, and have built an AD pathway map using CellDesigner. AlzPathway is currently composed of 1347 molecules and 1070 reactions in neuron, brain blood barrier, presynaptic, postsynaptic, astrocyte, and microglial cells and their cellular localizations. AlzPathway is available as both the SBML (Systems Biology Markup Language) map for CellDesigner and the high resolution image map. AlzPathway is also available as a web service (online map) based on Payao system, a community-based, collaborative web service platform for pathway model curation, enabling continuous updates by AD researchers.

Conclusions

AlzPathway is the first comprehensive map of intra, inter and extra cellular AD signaling pathways which can enable mechanistic deciphering of AD pathogenesis. The AlzPathway map is accessible at http://alzpathway.org/.

DC-ATLAS: a systems biology resource to dissect receptor specific signal transduction in dendritic cells

Background

The advent of Systems Biology has been accompanied by the blooming of pathway databases. Currently pathways are defined generically with respect to the organ or cell type where a reaction takes place. The cell type specificity of the reactions is the foundation of immunological research, and capturing this specificity is of paramount importance when using pathway-based analyses to decipher complex immunological datasets. Here, we present DC-ATLAS, a novel and versatile resource for the interpretation of high-throughput data generated perturbing the signaling network of dendritic cells (DCs).

Results

Pathways are annotated using a novel data model, the Biological Connection Markup Language (BCML), a SBGN-compliant data format developed to store the large amount of information collected. The application of DC-ATLAS to pathway-based analysis of the transcriptional program of DCs stimulated with agonists of the toll-like receptor family allows an integrated description of the flow of information from the cellular sensors to the functional outcome, capturing the temporal series of activation events by grouping sets of reactions that occur at different time points in well-defined functional modules.

Conclusions

The initiative significantly improves our understanding of DC biology and regulatory networks. Developing a systems biology approach for immune system holds the promise of translating knowledge on the immune system into more successful immunotherapy strategies.