Gene regulatory networks in the immune system

Differentiation-dependent antiviral capacities of amphibian (Xenopus laevis) macrophages

Infections by ranaviruses such as Frog virus 3 (Fv3), are significantly contributing to worldwide amphibian population declines. Notably, amphibian macrophages (Mφs) are important to both the Fv3 infection strategies and the immune defense against this pathogen. However, the mechanisms underlying amphibian Mφ Fv3 susceptibility and resistance remain unknown. Mφ differentiation is mediated by signaling through the colony-stimulating factor-1 receptor (CSF-1R) which is now known to be bound not only by CSF-1, but also by the unrelated interleukin-34 (IL-34) cytokine. Pertinently, amphibian (Xenopus laevis) Mφs differentiated by CSF-1 and IL-34 are highly susceptible and resistant to Fv3, respectively. Accordingly, in the present work, we elucidate the facets of this Mφ Fv3 susceptibility and resistance. Because cellular resistance to viral replication is marked by expression of antiviral restriction factors, it was intuitive to find that IL-34-Mφs possess significantly greater mRNA levels of select restriction factor genes than CSF-1-Mφs. Xenopodinae amphibians have highly expanded repertoires of antiviral interferon (IFN) cytokine gene families, and our results indicated that in comparison with the X. laevis CSF-1-Mφs, the IL-34-Mφs express substantially greater transcripts of representative IFN genes, belonging to distinct gene family clades, as well as their cognate receptor genes. Finally, we demonstrate that IL-34-Mφ-conditioned supernatants confer IFN-mediated anti-Fv3 protection to the virally susceptible X. laevis kidney (A6) cell line. Together, this work underlines the differentiation pathways leading to Fv3-susceptible and -resistant amphibian Mφ populations and defines the molecular mechanisms responsible for these differences.

Langerhans Cells-Programmed by the Epidermis

Langerhans cells (LCs) reside in the epidermis as a dense network of immune system sentinels. These cells determine the appropriate adaptive immune response (inflammation or tolerance) by interpreting the microenvironmental context in which they encounter foreign substances. In a normal physiological, "non-dangerous" situation, LCs coordinate a continuous state of immune tolerance, preventing unnecessary and harmful immune activation. Conversely, when they sense a danger signal, for example during infection or when the physical integrity of skin has been compromised as a result of a trauma, they instruct T lymphocytes of the adaptive immune system to mount efficient effector responses. Recent advances investigating the molecular mechanisms underpinning the cross talk between LCs and the epidermal microenvironment reveal its importance for programming LC biology. This review summarizes the novel findings describing LC origin and function through the analysis of the transcriptomic programs and gene regulatory networks (GRNs). Review and meta-analysis of publicly available datasets clearly delineates LCs as distinct from both conventional dendritic cells (DCs) and macrophages, suggesting a primary role for the epidermal microenvironment in programming LC biology. This concept is further supported by the analysis of the effect of epidermal pro-inflammatory signals, regulating key GRNs in human and murine LCs. Applying whole transcriptome analyses and in silico analysis has advanced our understanding of how LCs receive, integrate, and process signals from the steady-state and diseased epidermis. Interestingly, in homeostasis and under immunological stress, the molecular network in LCs remains relatively stable, reflecting a key evolutionary need related to tissue localization. Importantly, to fulfill their key role in orchestrating antiviral adaptive immune responses, LC share specific transcriptomic modules with other DC types able to cross-present antigens to cytotoxic CD8⁺ T cells, pointing to a possible evolutionary convergence mechanism. With the development of more advanced technologies allowing delineation of the molecular networks at the level of chromatin organization, histone modifications, protein translation, and phosphorylation, future "omics" investigations will bring in-depth understanding of the complex molecular mechanisms underpinning human LC biology.

Petri Net computational modelling of Langerhans cell Interferon Regulatory Factor Network predicts their role in T cell activation

Langerhans cells (LCs) are able to orchestrate adaptive immune responses in the skin by interpreting the microenvironmental context in which they encounter foreign substances, but the regulatory basis for this has not been established. Utilising systems immunology approaches combining in silico modelling of a reconstructed gene regulatory network (GRN) with in vitro validation of the predictions, we sought to determine the mechanisms of regulation of immune responses in human primary LCs. The key role of Interferon regulatory factors (IRFs) as controllers of the human Langerhans cell response to epidermal cytokines was revealed by whole transcriptome analysis. Applying Boolean logic we assembled a Petri net-based model of the IRF-GRN which provides molecular pathway predictions for the induction of different transcriptional programmes in LCs. In silico simulations performed after model parameterisation with transcription factor expression values predicted that human LC activation of antigen-specific CD8 T cells would be differentially regulated by epidermal cytokine induction of specific IRF-controlled pathways. This was confirmed by in vitro measurement of IFN-γ production by activated T cells. As a proof of concept, this approach shows that stochastic modelling of a specific immune networks renders transcriptome data valuable for the prediction of functional outcomes of immune responses.

Interaction of CCR4-NOT with EBF1 regulates gene-specific transcription and mRNA stability in B lymphopoiesis

Yang et al. used SILAC-based mass spectrometry of proteins associated with endogenous EBF1 in pro-B cells and identified most components of the multifunctional CCR4–NOT complex, which regulates transcription and mRNA degradation. The interaction of the CCR4–NOT complex with EBF1 diversifies the function of EBF1 in a context-dependent manner and may coordinate transcriptional and post-transcriptional gene regulation.

Transcription factor EBF1 (early B-cell factor 1) regulates early B-cell differentiation by poising or activating lineage-specific genes and repressing genes associated with alternative cell fates. To identify proteins that regulate the diverse functions of EBF1, we used SILAC (stable isotope labeling by amino acids in cell culture)-based mass spectrometry of proteins associated with endogenous EBF1 in pro-B cells. This analysis identified most components of the multifunctional CCR4–NOT complex, which regulates transcription and mRNA degradation. CNOT3 interacts with EBF1, and we identified histidine 240 in EBF1 as a critical residue for this interaction. Complementation of Ebf1^−/− progenitors with EBF1H240A revealed a partial block of pro-B-cell differentiation and altered expression of specific EBF1 target genes that show either reduced transcription or increased mRNA stability. Most deregulated EBF1 target genes show normal occupancy by EBF1H240A, but we also detected genes with altered occupancy, suggesting that the CCR4–NOT complex affects multiple activities of EBF1. Mice with conditional Cnot3 inactivation recapitulate the block of early B-cell differentiation, which we found to be associated with an impaired autoregulation of Ebf1 and reduced expression of pre-B-cell receptor components. Thus, the interaction of the CCR4–NOT complex with EBF1 diversifies the function of EBF1 in a context-dependent manner and may coordinate transcriptional and post-transcriptional gene regulation.

Defining antigen-specific plasmablast and memory B cell subsets in human blood after viral infection or vaccination

Antigen-specific B cells bifurcate into antibody secreting cells (ASC) and memory B cells after infection or vaccination. ASCs or plasmablasts have been extensively studied in humans but less is known about B cells that get activated but do not differentiate into early plasmablasts. Here, we define the phenotype and transcriptional program of an antigen-specific B cell subset, referred to as activated B cells (ABC), that is distinct from ASCs and is committed to the memory B cell lineage. ABCs were detected in humans after infection with Ebola virus or influenza virus and also after vaccination. By simultaneously analyzing antigen-specific ASCs and ABCs in human blood after influenza vaccination we interrogated the clonal overlap and extent of somatic hypermutation (SHM) in the ASC (effector) and ABC (memory) lineages. Longitudinal tracking of vaccination-induced HA-specific clones revealed minimal increase in SHM over time suggesting that repeated annual immunization may have limitations in enhancing the quality of influenza-specific antibody.

Modular genetic regulatory networks increase organization during pattern formation

Studies have shown that genetic regulatory networks (GRNs) consist of modules that are densely connected subnetworks that function quasi-autonomously. Modules may be recognized motifs that comprise of two or three genes with particular regulatory functions and connectivity or be purely structural and identified through connection density. It is unclear what evolutionary and developmental advantages modular structure and in particular motifs provide that have led to this enrichment. This study seeks to understand how modules within developmental GRNs influence the complexity of multicellular patterns that emerge from the dynamics of the regulatory networks. We apply an algorithmic complexity to measure the organization of the patterns. A computational study was performed by creating Boolean intracellular networks within a simulated epithelial field of embryonic cells, where each cell contains the same network and communicates with adjacent cells using contact-mediated signaling. Intracellular networks with random connectivity were compared to those with modular connectivity and with motifs. Results show that modularity effects network dynamics and pattern organization significantly. In particular: (1) modular connectivity alone increases complexity in network dynamics and patterns; (2) bistable switch motifs simplify both the pattern and network dynamics; (3) all other motifs with feedback loops increase multicellular pattern complexity while simplifying the network dynamics; (4) negative feedback loops affect the dynamics complexity more significantly than positive feedback loops.

The analysis of novel distal Cebpa enhancers and silencers using a transcriptional model reveals the complex regulatory logic of hematopoietic lineage specification

C/EBPα plays an instructive role in the macrophage-neutrophil cell-fate decision and its expression is necessary for neutrophil development. How Cebpa itself is regulated in the myeloid lineage is not known. We decoded the cis-regulatory logic of Cebpa, and two other myeloid transcription factors, Egr1 and Egr2, using a combined experimental-computational approach. With a reporter design capable of detecting both distal enhancers and silencers, we analyzed 46 putative cis-regulatory modules (CRMs) in cells representing myeloid progenitors, and derived early macrophages or neutrophils. In addition to novel enhancers, this analysis revealed a surprisingly large number of silencers. We determined the regulatory roles of 15 potential transcriptional regulators by testing 32,768 alternative sequence-based transcriptional models against CRM activity data. This comprehensive analysis allowed us to infer the cis-regulatory logic for most of the CRMs. Silencer-mediated repression of Cebpa was found to be effected mainly by TFs expressed in non-myeloid lineages, highlighting a previously unappreciated contribution of long-distance silencing to hematopoietic lineage resolution. The repression of Cebpa by multiple factors expressed in alternative lineages suggests that hematopoietic genes are organized into densely interconnected repressive networks instead of hierarchies of mutually repressive pairs of pivotal TFs. More generally, our results demonstrate that de novo cis-regulatory dissection is feasible on a large scale with the aid of transcriptional modeling. Current address: Department of Biology, University of North Dakota, 10 Cornell Street, Stop 9019, Grand Forks, ND 58202-9019, USA.

Regulatory network control of blood stem cells

Hematopoietic stem cells (HSCs) are characterized by their ability to execute a wide range of cell fate choices, including self-renewal, quiescence, and differentiation into the many different mature blood lineages. Cell fate decision making in HSCs, as indeed in other cell types, is driven by the interplay of external stimuli and intracellular regulatory programs. Given the pivotal nature of HSC decision making for both normal and aberrant hematopoiesis, substantial research efforts have been invested over the last few decades into deciphering some of the underlying mechanisms. Central to the intracellular decision making processes are transcription factor proteins and their interactions within gene regulatory networks. More than 50 transcription factors have been shown to affect the functionality of HSCs. However, much remains to be learned about the way in which individual factors are connected within wider regulatory networks, and how the topology of HSC regulatory networks might affect HSC function. Nevertheless, important progress has been made in recent years, and new emerging technologies suggest that the pace of progress is likely to accelerate. This review will introduce key concepts, provide an integrated view of selected recent studies, and conclude with an outlook on possible future directions for this field.

A review on computational systems biology of pathogen-host interactions

Pathogens manipulate the cellular mechanisms of host organisms via pathogen-host interactions (PHIs) in order to take advantage of the capabilities of host cells, leading to infections. The crucial role of these interspecies molecular interactions in initiating and sustaining infections necessitates a thorough understanding of the corresponding mechanisms. Unlike the traditional approach of considering the host or pathogen separately, a systems-level approach, considering the PHI system as a whole is indispensable to elucidate the mechanisms of infection. Following the technological advances in the post-genomic era, PHI data have been produced in large-scale within the last decade. Systems biology-based methods for the inference and analysis of PHI regulatory, metabolic, and protein-protein networks to shed light on infection mechanisms are gaining increasing demand thanks to the availability of omics data. The knowledge derived from the PHIs may largely contribute to the identification of new and more efficient therapeutics to prevent or cure infections. There are recent efforts for the detailed documentation of these experimentally verified PHI data through Web-based databases. Despite these advances in data archiving, there are still large amounts of PHI data in the biomedical literature yet to be discovered, and novel text mining methods are in development to unearth such hidden data. Here, we review a collection of recent studies on computational systems biology of PHIs with a special focus on the methods for the inference and analysis of PHI networks, covering also the Web-based databases and text-mining efforts to unravel the data hidden in the literature.