Immune Signaling Network Research Articles

Utilizing whole genome sequences to study population genomics of gene networks: a case study of the Arabidopsis thaliana immune-signaling network

Utilizing whole genome sequences to study population genomics of gene networks: a case study of the Arabidopsis thaliana immune-signaling network

Utilizing whole genome sequences to study population genomics of gene networks: a case study of the Arabidopsis thalianaimmune-signaling network

Arabidopsis thaliana is a member of the mustard (Brassicaceae) family that is widely used as a model organism in plant biology. The 1001 Genomes Project [1] has been sequencing the genomes of Arabidopsis strains (accessions) and has made these sequences available. We selected the genomes of 30 Arabidopsis accessions with diverse geographical and environmental origins for our analysis. Using the TAIR8 annotation of the Arabidopsis reference genome, for the accession Col-0, we generated a dataset of approximately 27,000 protein-coding genes for all of the 30 genomes. With such population genomic data, it is feasible to ask whether a group of genes is under a different type of selection from the rest of the genome. The plant immune-signaling network is robust to network perturbations. We hypothesized that genes that constitute a robust network tend to be under neutral selection because deleterious mutations in such genes do not strongly affect the immune phenotype owing to the robustness of the network. We identified the component genes of the plant immune-signaling network in a relatively unbiased manner by mining AraNet [2], which is a functional gene network built without using phenotype information. We compared population genetic summary statistics for the network component genes and those for all of the genes in the genome. For example, Tajima’s D is such a summary statistic, and positive, negative and zero values of Tajima’s D suggest diversifying, purifying and neutral selection, respectively, when the effective population size does not change. The Tajima’s D value distribution for all of the genes in the genome has a single clear peak with a negative value, suggesting that purifying selection is the genomic norm. Our preliminary results showed that the plant immune-signaling network genes are significantly enriched with genes whose Tajima’s D values are near zero compared with all of the genes in the genome. This finding suggests that there is a lower level of purifying selection among the network component genes than other genes.

Cellular and Intracellular Network Characterization of Cytokine JAK/STAT Signaling In Whole Blood Across Multiple Healthy Individuals: Defining “Normal”

AbstractAbstract 4768 Introduction:As aberrant JAK/STAT signaling in hematopoietic cells is associated with certain hematologic and immune diseases, understanding the regulation of JAK/STAT signaling is critical. Signaling pathway- and cell type-specific responses to various cytokines in immune system signaling networks can elicit a wide range of biological outcomes due to the combinatorial use of a limited set of kinases and STAT proteins. Although advances have been made in uncovering the intracellular mechanisms relating to cytokine signaling, the biological outcome may vary depending on composition and activation state of the cellular network. Single Cell Network Profiling (SCNP) by flow cytometry allows the interrogation of intracellular signaling networks within a heterogeneous cellular network, such as in unfractionated whole blood. We applied SCNP to investigate cytokine induced JAK/STAT signaling in whole blood across healthy human donors (n=11) to 1) measure the relative contribution of distinct cytokines to induce signaling across multiple cell subsets; 2) measure the kinetics of signaling activation across cytokines and cell subsets; 3) measure the variation among donors in their overall signaling characteristics. Our aim was to better characterize “normal” cytokine responses across healthy individuals as a basis to eventually describe abnormal states. Methods:Whole blood from 11 healthy donors (20-65 yrs, 7 males, 4 females, 8 Caucasians, 2 Hispanics, 1 East Asian) was stimulated at 37°C in 96-well plates with a low, medium, and high dose of GM-CSF, IFN-α, IL-27 and IL-6, each added separately. For each dose, a stimulation time course was run with 6 time points between 3 and 45 minutes. Each well had a final concentration of 90% whole blood. SCNP assay was performed using a fluorophore-labeled antibody cocktail to simultaneously measure signaling in six distinct cell populations, including: neutrophils, CD20+ B cells, CD3+CD4+T cells, CD3+CD4- T cells (CD8 enriched), CD3-CD20- lymphocytes (NK cell enriched), and CD14+ monocytes. The median fluorescent intensity of phospho (p)-STAT1(Y701), p-STAT3(Y705), and p-STAT5(Y694) were measured in each defined cell population for each experimental condition. Results:This SCNP assay was relatively high-throughput and provided high-content data, that equates to 19,000 gel lanes if attempted by Western analysis (11 donors × 4 cytokines × 4 concentrations × 6 time points × 6 cell subsets × 3 p-readouts). In general, each cytokine demonstrated unique dose-dependent signaling characteristics (e.g. activation/termination kinetics, magnitude of response) for each cell type analyzed, and in some cases, the kinetics differed between p-STAT readouts within the same cell subset for the same cytokine. For instance, IL-6 induced signaling was only observed in CD4+ T cells and monocytes with peak p-STAT3 levels at 3 minutes followed by p-STAT1 and p-STAT5 at 10–15 minutes. In addition, signal resolution fell to baseline levels at 45 minutes in monocytes, while the CD4+ T cells showed sustained elevated signaling, suggesting a cell-type specific regulation. In contrast to IL-6, IFN-α stimulation activated all 3 STAT proteins, peaking at 10 minutes with similar kinetics in all cell subsets. However, termination of IFN-α signaling was faster and almost complete at 45 minutes in monocytes, while in the all other subsets the signal was sustained. This efficient signal termination in monocytes was also observed with GM-CSF→p-STAT5, while neutrophils maintained persistent p-STAT5 levels. IL-27 induced p-STAT1 and p-STAT3 in T cell subsets, B cells, and monocytes with peak activation at 30 minutes. In general, signaling characteristics were remarkably uniform across the healthy donors. IL-6→p-STAT3 was particularly consistent across time points and ligand concentrations, while p-STAT1 and p-STAT5 showed more variation. Conclusions:Approaching cell signaling from the perspective of the cellular network under physiological conditions (whole blood) allows for a more comprehensive and clinically relevant view of the signaling state of complex tissues. As many small molecule compounds targeting JAK/STAT pathways enter the clinic, this study provides an important reference point for comparison of healthy signaling networks with networks altered either by pathological disease state or therapy. Disclosures:Covey:Nodality Inc.: Employment, Equity Ownership. Gulrajani:Nodality Inc.: Employment, Equity Ownership. Marimpietri:Nodality Inc.: Employment, Equity Ownership. Chiang:Nodality Inc.: Employment, Equity Ownership. Panganiban-Lustan:Nodality Inc.: Employment, Equity Ownership. Cordeiro:Nodality Inc.: Employment, Equity Ownership. Longo:Nodality Inc.: Employment, Equity Ownership. Rosen:Nodality Inc.: Employment, Equity Ownership. Cesano:Nodality Inc.: Employment, Equity Ownership.

Plant Immunity: It’s the Hormones Talking, But What Do They Say?

Plants live in complex environments in which they intimately interact with a broad range of other organisms. Besides the plethora of deleterious interactions with pathogens and insect herbivores, relationships with beneficial microorganisms are frequent in nature as well, improving plant growth or helping the plant to overcome stress. The evolutionary arms race between plants and their enemies provided plants with a highly sophisticated defense system that, like the animal innate immune system, recognizes nonself molecules or signals from injured cells, and responds by activating an effective immune response against the invader encountered. Recent advances in plant immunity research underpin the pivotal role of cross-communicating hormones in the regulation of the plant’s defense signaling network (Spoel and Dong, 2008; Pieterse et al., 2009). Their powerful regulatory potential allows the plant to quickly adapt to its hostile environment and to utilize its resources in a cost-efficient manner. Plant enemies on the other hand, can hijack the plant’s defense signaling network for their own benefit by affecting hormone homeostasis to antagonize the host immune response (Grant and Jones, 2009). Similarly, beneficial microbes actively interfere with hormone-regulated immune responses to avoid being recognized as an alien organism (Van Wees et al., 2008). In nature, plants simultaneously or sequentially interact with multiple beneficial and antagonistic organisms with very different lifestyles. However, knowledge on how the hormone-regulated plant immune signaling network functions during multispecies interactions is still in its infancy. Bioinformatic and systems biology approaches will prove essential to crack this tough nut.

Network Modeling Reveals Prevalent Negative Regulatory Relationships between Signaling Sectors in Arabidopsis Immune Signaling

Biological signaling processes may be mediated by complex networks in which network components and network sectors interact with each other in complex ways. Studies of complex networks benefit from approaches in which the roles of individual components are considered in the context of the network. The plant immune signaling network, which controls inducible responses to pathogen attack, is such a complex network. We studied the Arabidopsis immune signaling network upon challenge with a strain of the bacterial pathogen Pseudomonas syringae expressing the effector protein AvrRpt2 (Pto DC3000 AvrRpt2). This bacterial strain feeds multiple inputs into the signaling network, allowing many parts of the network to be activated at once. mRNA profiles for 571 immune response genes of 22 Arabidopsis immunity mutants and wild type were collected 6 hours after inoculation with Pto DC3000 AvrRpt2. The mRNA profiles were analyzed as detailed descriptions of changes in the network state resulting from the genetic perturbations. Regulatory relationships among the genes corresponding to the mutations were inferred by recursively applying a non-linear dimensionality reduction procedure to the mRNA profile data. The resulting static network model accurately predicted 23 of 25 regulatory relationships reported in the literature, suggesting that predictions of novel regulatory relationships are also accurate. The network model revealed two striking features: (i) the components of the network are highly interconnected; and (ii) negative regulatory relationships are common between signaling sectors. Complex regulatory relationships, including a novel negative regulatory relationship between the early microbe-associated molecular pattern-triggered signaling sectors and the salicylic acid sector, were further validated. We propose that prevalent negative regulatory relationships among the signaling sectors make the plant immune signaling network a “sector-switching” network, which effectively balances two apparently conflicting demands, robustness against pathogenic perturbations and moderation of negative impacts of immune responses on plant fitness.

Targeting of immune signalling networks by bacterial pathogens

Host defence against microbial pathogens requires appropriate coordination of multiple signalling pathways. These pathways are triggered by innate immune recognition of conserved microbial molecules, and initiate an inflammatory cascade that involves recruitment of leukocytes to the site of infection, activation of antimicrobial effector mechanisms and induction of an adaptive immune response that promotes clearance of infection and long-term immune memory. Microbial pathogens possess specialized proteins termed virulence factors, which interfere with host defence at several levels. Many virulence factors from diverse pathogens have been identified in recent years and their functions linked to disruption of essential processes of immune defence, from signalling to phagocytosis. Although the diversity of pathogens and virulence factors is immense, common themes have emerged with regard to how microbial pathogens interfere with immune responses. Here we discuss recent advances in our understanding of how virulence factors target innate and adaptive immune responses, focusing on bacterial pathogens. We also propose that pathogens responsible for causing acute infection tend to target central components (hubs) of cellular signalling pathways, causing global disruption of the host response. By contrast, pathogens that cause chronic or persistent infections tend to target more peripheral signalling network components (nodes) to promote pathogen persistence.

The Tangled Web of Signaling in Innate Immunity

Similarities in innate immune signaling exist between mammals and the nematode Caenorhabditis elegans. Now, Ziegler et al. (2009) and Ren et al. (2009) demonstrate that a protein kinase C delta homolog in C. elegans is involved in innate immunity, providing evidence that the conservation of immune signaling networks extends further than previously thought.

Death receptor signal transducers: nodes of coordination in immune signaling networks

Death receptors (DRs) are members of the tumor necrosis factor receptor superfamily that possess a cytoplasmic death domain (DD). DRs regulate important operational and homeostatic aspects of the immune system. They transmit signals through apical protein complexes, which are nucleated by the DD adaptors FADD and TRADD, to control cellular outcomes that range from apoptosis to gene activation. FADD and TRADD also nucleate several distal signaling complexes, which mediate cross-talk between distinct DR signaling pathways. Moreover, together with other DR signal transducers, FADD and TRADD participate in functional complexes assembled by certain non-DR immune cell receptors, such as pattern-recognition receptors. Thus, DR signal transducers may provide important nodes of coordination in immune signaling networks.

Choreographing the Fly's Danse Macabre

In several species, immune signaling networks are emerging as critical modulators of disease resistance, energy metabolism, and aging. In this issue of Cell Metabolism, Ren et al. (2007) lay the groundwork for dissecting the mechanisms of this coordination by characterizing the interplay between microbial pathogens and aging in the fly.

Listeria monocytogenes as a probe of immune function

For almost half a century, the mouse model of Listeria monocytogenes infection has been used to analyse both innate and adaptive components of immunity and to discover key immune genes. Vast accumulated knowledge about the disease in mice provides a unique framework for identifying and characterising immune molecules using a variety of experimental approaches. To illustrate the range of questions that can be addressed using modern genetics and genomics tools, the authors provide an overview of the analysis of components of immune signalling networks using the mouse model of L. monocytogenes infection.