Uncovering a macrophage transcriptional program by integrating evidence from motif scanning and expression dynamics

GeTeSEPdb: A comprehensive database and online tool for the identification and analysis of gene profiles with temporal-specific expression patterns

Gene expression is dynamic and varies at different stages of processes. The identification of gene profiles with temporal-specific expression patterns can provide valuable insights into ongoing biological processes, such as the cell cycle, cell development, circadian rhythms, or responses to external stimuli such as drug treatments or viral infections. However, currently, no database defines, identifies or archives gene profiles with temporal-specific expression patterns. Here, using a high-throughput regression analysis approach, eight linear and nonlinear parametric models were fitted to gene expression profiles from time-series experiments to identify eight types of gene profiles with temporal-specific expression patterns. We curated 2684 time-series transcriptome datasets and identified 2644,370 gene profiles exhibiting temporal-specific expression patterns. The results were stored in the database GeTeSEPdb (gene profiles with temporal-specific expression patterns database, http://www.inbirg.com/GeTeSEPdb/). Moreover, we implemented an online tool to identify gene profiles with temporal-specific expression patterns from user-submitted data. In summary, GeTeSEPdb is a comprehensive web service that can be used to identify and analyse gene profiles with temporal-specific expression patterns. This approach facilitates the exploration of transcriptional changes and temporal patterns of responses. We firmly believe that GeTeSEPdb will become a valuable resource for biologists and bioinformaticians.

A female-biased gene expression signature of dominance in cooperatively breeding meerkats

Dominance is a primary determinant of social dynamics and resource access in social animals. Recent studies show that dominance is also reflected in the gene regulatory profiles of peripheral immune cells. However, the strength and direction of this relationship differs across the species and sex combinations investigated, potentially due to variation in the predictors and energetic consequences of dominance status. Here, we investigated the association between social status and gene expression in the blood of wild meerkats (Suricata suricatta; n = 113 individuals), including in response to lipopolysaccharide, Gardiquimod (an agonist of TLR7, which detects single-stranded RNA in vivo) and glucocorticoid stimulation. Meerkats are cooperatively breeding social carnivores in which breeding females physically outcompete other females to suppress reproduction, resulting in high reproductive skew. They therefore present an opportunity to disentangle the effects of social dominance from those of sex per se. We identify a sex-specific signature of dominance, including 1045 differentially expressed genes in females but none in males. Dominant females exhibit elevated activity in innate immune pathways and a larger fold-change response to LPS challenge. Based on these results and a preliminary comparison to other mammals, we speculate that the gene regulatory signature of social status in the immune system depends on the determinants and energetic costs of social dominance, such that it is most pronounced in hierarchies where physical competition is important and reproductive skew is large. Such a pattern has the potential to mediate life history trade-offs between investment in reproduction versus somatic maintenance.

Comparative transcriptomic analysis of the nodulation-competent zone and inference of transcription regulatory network in silicon applied Glycine max [L.]-Merr. Roots

KEY MESSAGE

The study unveils Si's regulatory influence by regulating DEGs, TFs, and TRs. Further bHLH subfamily and auxin transporter pathway elucidates the mechanisms enhancing root development and nodulation. Soybean is a globally important crop serving as a primary source of vegetable protein for millions of individuals. The roots of these plants harbour essential nitrogen fixing structures called nodules. This study investigates the multifaceted impact of silicon (Si) application on soybean, with a focus on root development, and nodulation employing comprehensive transcriptomic analyses and gene regulatory network. RNA sequence analysis was utilised to examine the change in gene expression and identify the noteworthy differentially expressed genes (DEGs) linked to the enhancement of soybean root nodulation and root development. A set of 316 genes involved in diverse biological and molecular pathways are identified, with emphasis on transcription factors (TFs) and transcriptional regulators (TRs). The study uncovers TF and TR genes, categorized into 68 distinct families, highlighting the intricate regulatory landscape influenced by Si in soybeans. Upregulated most important bHLH subfamily and the involvement of the auxin transporter pathway underscore the molecular mechanisms contributing to enhanced root development and nodulation. The study bridges insights from other research, reinforcing Si's impact on stress-response pathways and phenylpropanoid biosynthesis crucial for nodulation. The study reveals significant alterations in gene expression patterns associated with cellular component functions, root development, and nodulation in response to Si.

Reprogramming of the LXRα Transcriptome Sustains Macrophage Secondary Inflammatory Responses

Macrophages regulate essential aspects of innate immunity against pathogens. In response to microbial components, macrophages activate primary and secondary inflammatory gene programs crucial for host defense. The liver X receptors (LXRα, LXRβ) are ligand-dependent nuclear receptors that direct gene expression important for cholesterol metabolism and inflammation, but little is known about the individual roles of LXRα and LXRβ in antimicrobial responses. Here, the results demonstrate that induction of LXRα transcription by prolonged exposure to lipopolysaccharide (LPS) supports inflammatory gene expression in macrophages. LXRα transcription is induced by NF-κB and type-I interferon downstream of TLR4 activation. Moreover, LPS triggers a reprogramming of the LXRα cistrome that promotes cytokine and chemokine gene expression through direct LXRα binding to DNA consensus sequences within cis-regulatory regions including enhancers. LXRα-deficient macrophages present fewer binding of p65 NF-κB and reduced histone H3K27 acetylation at enhancers of secondary inflammatory response genes. Mice lacking LXRα in the hematopoietic compartment show impaired responses to bacterial endotoxin in peritonitis models, exhibiting reduced neutrophil infiltration and decreased expansion and inflammatory activation of recruited F4/80lo-MHC-IIhi peritoneal macrophages. Together, these results uncover a previously unrecognized function for LXRα-dependent transcriptional cis-activation of secondary inflammatory gene expression in macrophages and the host response to microbial ligands.

SRSF6 balances mitochondrial-driven innate immune outcomes through alternative splicing of BAX

To mount a protective response to infection while preventing hyperinflammation, gene expression in innate immune cells must be tightly regulated. Despite the importance of pre-mRNA splicing in shaping the proteome, its role in balancing immune outcomes remains understudied. Transcriptomic analysis of murine macrophage cell lines identified Serine/Arginine Rich Splicing factor 6 (SRSF6) as a gatekeeper of mitochondrial homeostasis. SRSF6-dependent orchestration of mitochondrial health is directed in large part by alternative splicing of the pro-apoptosis pore-forming protein BAX. Loss of SRSF6 promotes accumulation of BAX-κ, a variant that sensitizes macrophages to undergo cell death and triggers upregulation of interferon stimulated genes through cGAS sensing of cytosolic mitochondrial DNA. Upon pathogen sensing, macrophages regulate SRSF6 expression to control the liberation of immunogenic mtDNA and adjust the threshold for entry into programmed cell death. This work defines BAX alternative splicing by SRSF6 as a critical node not only in mitochondrial homeostasis but also in the macrophage's response to pathogens.

Identification of upstream transcription factor binding sites in orthologous genes using mixed Student’s t-test statistics

Background

Transcription factor (TF) regulates the transcription of DNA to messenger RNA by binding to upstream sequence motifs. Identifying the locations of known motifs in whole genomes is computationally intensive.

Methodology/Principal findings

This study presents a computational tool, named “Grit”, for screening TF-binding sites (TFBS) by coordinating transcription factors to their promoter sequences in orthologous genes. This tool employs a newly developed mixed Student’s t-test statistical method that detects high-scoring binding sites utilizing conservation information among species. The program performs sequence scanning at a rate of 3.2 Mbp/s on a quad-core Amazon server and has been benchmarked by the well-established ChIP-Seq datasets, putting Grit amongst the top-ranked TFBS predictors. It significantly outperforms the well-known transcription factor motif scanning tools, Pscan (4.8%) and FIMO (17.8%), in analyzing well-documented ChIP-Atlas human genome Chip-Seq datasets.

Significance

Grit is a good alternative to current available motif scanning tools.

Locating transcription factor-binding (TF-binding) site in the genome and identification their function is fundamental in understanding various biological processes. Improve the performance of the prediction tools is important because accurate TF-binding site prediction can save cost and time for wet-lab experiments. Also, genome wide TF-binding site prediction can provide new insights for transcriptome regulation in system biology perspective. This study developed a new TF-binding site prediction tool based on mixed Student’s t-test statistical method. The tool is amongst the top-ranked TF-binding site predictors, as such, it can help the researchers in TF-binding site identification and transcriptional regulation mechanism interpretation of genes.

Connections for Matters of the Heart: Network Medicine in Cardiovascular Diseases

Cardiovascular diseases (CVD) are diverse disorders affecting the heart and vasculature in millions of people worldwide. Like other fields, CVD research has benefitted from the deluge of multiomics biomedical data. Current CVD research focuses on disease etiologies and mechanisms, identifying disease biomarkers, developing appropriate therapies and drugs, and stratifying patients into correct disease endotypes. Systems biology offers an alternative to traditional reductionist approaches and provides impetus for a comprehensive outlook toward diseases. As a focus area, network medicine specifically aids the translational aspect of in silico research. This review discusses the approach of network medicine and its application to CVD research.

A comprehensive transcription factor and DNA-binding motif resource for the construction of gene regulatory networks in Botrytis cinerea and Trichoderma atroviride

Botrytis cinerea and Trichoderma atroviride are two relevant fungi in agricultural systems. To gain insights into these organisms' transcriptional gene regulatory networks (GRNs), we generated a manually curated transcription factor (TF) dataset for each of them, followed by a GRN inference utilizing available sequence motifs describing DNA-binding specificity and global gene expression data. As a proof of concept of the usefulness of this resource to pinpoint key transcriptional regulators, we employed publicly available transcriptomics data and a newly generated dual RNA-seq dataset to build context-specific Botrytis and Trichoderma GRNs under two different biological paradigms: exposure to continuous light and Botrytis-Trichoderma confrontation assays. Network analysis of fungal responses to constant light revealed striking differences in the transcriptional landscape of both fungi. On the other hand, we found that the confrontation of both microorganisms elicited a distinct set of differentially expressed genes with changes in T. atroviride exceeding those in B. cinerea. Using our regulatory network data, we were able to determine, in both fungi, central TFs involved in this interaction response, including TFs controlling a large set of extracellular peptidases in the biocontrol agent T. atroviride. In summary, our work provides a comprehensive catalog of transcription factors and regulatory interactions for both organisms. This catalog can now serve as a basis for generating novel hypotheses on transcriptional regulatory circuits in different experimental contexts.

A conserved long noncoding RNA, GAPLINC, modulates the immune response during endotoxic shock

Inflammation has largely been studied in the context of protein-coding genes. Recent studies have uncovered lncRNAs as important regulators of immunity. The functional characterization of these genes remains an active area of research. In this study, we identify GAPLINC as a functionally conserved lncRNA between human and mouse. GAPLINC depletion results in enhanced expression of immune response genes that are direct NF-κB targets. Astoundingly, we observe that Gaplinc knockout mice show resistance to LPS-induced endotoxic shock and find that basal expression of inflammatory genes prevents clot formation to protect against multiorgan failure and death. These findings have implications in the treatment of sepsis, in which new therapies targeting lncRNAs can contribute valuable information in understanding inflammation and improving patient outcome.

Recent studies have identified thousands of long noncoding RNAs (lncRNAs) in mammalian genomes that regulate gene expression in different biological processes. Although lncRNAs have been identified in a variety of immune cells and implicated in immune response, the biological function and mechanism of the majority remain unexplored, especially in sepsis. Here, we identify a role for a lncRNA—gastric adenocarcinoma predictive long intergenic noncoding RNA (GAPLINC)—previously characterized for its role in cancer, now in the context of innate immunity, macrophages, and LPS-induced endotoxic shock. Transcriptome analysis of macrophages from humans and mice reveals that GAPLINC is a conserved lncRNA that is highly expressed following macrophage differentiation. Upon inflammatory activation, GAPLINC is rapidly down-regulated. Macrophages depleted of GAPLINC display enhanced expression of inflammatory genes at baseline, while overexpression of GAPLINC suppresses this response. Consistent with GAPLINC-depleted cells, Gaplinc knockout mice display enhanced basal levels of inflammatory genes and show resistance to LPS-induced endotoxic shock. Mechanistically, survival is linked to increased levels of nuclear NF-κB in Gaplinc knockout mice that drives basal expression of target genes typically only activated following inflammatory stimulation. We show that this activation of immune response genes prior to LPS challenge leads to decreased blood clot formation, which protects Gaplinc knockout mice from multiorgan failure and death. Together, our results identify a previously unknown function for GAPLINC as a negative regulator of inflammation and uncover a key role for this lncRNA in modulating endotoxic shock.

A Comprehensive Map of the Monocyte-Derived Dendritic Cell Transcriptional Network Engaged upon Innate Sensing of HIV

Transcriptional programming of the innate immune response is pivotal for host protection. However, the transcriptional mechanisms that link pathogen sensing with innate activation remain poorly under-stood. During HIV-1 infection, human dendritic cells (DCs) can detect the virus through an innate sensing pathway, leading to antiviral interferon and DC maturation. Here, we develop an iterative experimental and computational approach to map the HIV-1 innate response circuitry in monocyte-derived DCs (MDDCs). By integrating genome-wide chromatin accessibility with expression kinetics, we infer a gene regulatory network that links 542 transcription factors with 21,862 target genes. We observe that an interferon response is required, yet insufficient, to drive MDDC maturation and identify PRDM1 and RARA as essential regulators of the interferon response and MDDC maturation, respectively. Our work provides a resource for interrogation of regulators of HIV replication and innate immunity, highlighting complexity and cooperativity in the regulatory circuit controlling the response to infection.

Pathogen sensing leads to host transcriptional reprogramming to protect against infection. However, it is unclear how transcription factor activity is coordinated across the genome. Johnson et al. integrate chromatin accessibility and gene expression data to infer and validate a gene regulatory network that directs the innate immune response to HIV.

Changes in H3K27ac at Gene Regulatory Regions in Porcine Alveolar Macrophages Following LPS or PolyIC Exposure

Changes in chromatin structure, especially in histone modifications (HMs), linked with chromatin accessibility for transcription machinery, are considered to play significant roles in transcriptional regulation. Alveolar macrophages (AM) are important immune cells for protection against pulmonary pathogens, and must readily respond to bacteria and viruses that enter the airways. Mechanism(s) controlling AM innate response to different pathogen-associated molecular patterns (PAMPs) are not well defined in pigs. By combining RNA sequencing (RNA-seq) with chromatin immunoprecipitation and sequencing (ChIP-seq) for four histone marks (H3K4me3, H3K4me1, H3K27ac and H3K27me3), we established a chromatin state map for AM stimulated with two different PAMPs, lipopolysaccharide (LPS) and Poly(I:C), and investigated the potential effect of identified histone modifications on transcription factor binding motif (TFBM) prediction and RNA abundance changes in these AM. The integrative analysis suggests that the differential gene expression between non-stimulated and stimulated AM is significantly associated with changes in the H3K27ac level at active regulatory regions. Although global changes in chromatin states were minor after stimulation, we detected chromatin state changes for differentially expressed genes involved in the TLR4, TLR3 and RIG-I signaling pathways. We found that regions marked by H3K27ac genome-wide were enriched for TFBMs of TF that are involved in the inflammatory response. We further documented that TF whose expression was induced by these stimuli had TFBMs enriched within H3K27ac-marked regions whose chromatin state changed by these same stimuli. Given that the dramatic transcriptomic changes and minor chromatin state changes occurred in response to both stimuli, we conclude that regulatory elements (i.e. active promoters) that contain transcription factor binding motifs were already active/poised in AM for immediate inflammatory response to PAMPs. In summary, our data provides the first chromatin state map of porcine AM in response to bacterial and viral PAMPs, contributing to the Functional Annotation of Animal Genomes (FAANG) project, and demonstrates the role of HMs, especially H3K27ac, in regulating transcription in AM in response to LPS and Poly(I:C).

Gene Regulatory Strategies that Decode the Duration of NFκB Dynamics Contribute to LPS- versus TNF-Specific Gene Expression

Pathogen-derived lipopolysaccharide (LPS) and cytokine tumor necrosis factor (TNF) activate NFκB with distinct duration dynamics, but how immune response genes decode NFκB duration to produce stimulus-specific expression remains unclear. Here, detailed transcriptomic profiling of combinatorial and temporal control mutants identified 81 genes that depend on stimulus-specific NFκB duration for their stimulus-specificity. Combining quantitative experimentation with mathematical modeling, we found that for some genes a long mRNA half-life allowed effective decoding, but for many genes this was insufficient to account for the data; instead, we found that chromatin mechanisms, such as a slow transition rate between inactive and RelA-bound enhancer states, could also decode NFκB dynamics. Chromatin-mediated decoding is favored by genes acting as immune effectors (e.g., tissue remodelers and T cell recruiters) rather than immune regulators (e.g., signaling proteins and monocyte recruiters). Overall, our results delineate two gene regulatory strategies that decode stimulus-specific NFκB dynamics and determine distinct biological functions.

Systematic Investigation of Multi-TLR Sensing Identifies Regulators of Sustained Gene Activation in Macrophages

A typical pathogen presents a combination of Toll-like receptor (TLR) ligands during infection. Although individual TLR pathways have been well characterized, the nature of this "combinatorial code" in pathogen sensing remains unclear. Here, we conducted a comprehensive transcriptomic analysis of primary macrophages stimulated with all possible pairwise combinations of four different TLR ligands to understand the requirements, kinetics, and outcome of combined pathway engagement. We find that signal integration between TLR pathways leads to non-additive responses for a subset of immune mediators with sustained expression (>6 hr) properties and T cell polarizing function. To identify the underlying regulators, we conducted a focused RNAi screen and identified four genes-Helz2, Phf11d, Sertad3, and Zscan12-which preferentially affect the late phase response of TLR-induced immune effector expression. This study reveals key molecular details of how contemporaneous signaling through multiple TLRs, as would often be the case with pathogen infection, produce biological outcomes distinct from the single ligands typically used to characterize TLR pathways.

Emerging Principles of Gene Expression Programs and Their Regulation

Many mechanisms contribute to regulation of gene expression to ensure coordinated cellular behaviors and fate decisions. Transcriptional responses to external signals can consist of many hundreds of genes that can be parsed into different categories based on kinetics of induction, cell-type and signal specificity, and duration of the response. Here we discuss the structure of transcription programs and suggest a basic framework to categorize gene expression programs based on characteristics related to their control mechanisms. We also discuss possible evolutionary implications of this framework.

FACS-Seq analysis of Pax3-derived cells identifies non-myogenic lineages in the embryonic forelimb

Skeletal muscle in the forelimb develops during embryonic and fetal development and perinatally. While much is known regarding the molecules involved in forelimb myogenesis, little is known about the specific mechanisms and interactions. Migrating skeletal muscle precursor cells express Pax3 as they migrate into the forelimb from the dermomyotome. To compare gene expression profiles of the same cell population over time, we isolated lineage-traced Pax3⁺ cells (Pax3^EGFP) from forelimbs at different embryonic days. We performed whole transcriptome profiling via RNA-Seq of Pax3⁺ cells to construct gene networks involved in different stages of embryonic and fetal development. With this, we identified genes involved in the skeletal, muscular, vascular, nervous and immune systems. Expression of genes related to the immune, skeletal and vascular systems showed prominent increases over time, suggesting a non-skeletal myogenic context of Pax3-derived cells. Using co-expression analysis, we observed an immune-related gene subnetwork active during fetal myogenesis, further implying that Pax3-derived cells are not a strictly myogenic lineage, and are involved in patterning and three-dimensional formation of the forelimb through multiple systems.

Transcriptional landscape of Mycobacterium tuberculosis infection in macrophages

Mycobacterium tuberculosis (Mtb) infection reveals complex and dynamic host-pathogen interactions, leading to host protection or pathogenesis. Using a unique transcriptome technology (CAGE), we investigated the promoter-based transcriptional landscape of IFNγ (M1) or IL-4/IL-13 (M2) stimulated macrophages during Mtb infection in a time-kinetic manner. Mtb infection widely and drastically altered macrophage-specific gene expression, which is far larger than that of M1 or M2 activations. Gene Ontology enrichment analysis for Mtb-induced differentially expressed genes revealed various terms, related to host-protection and inflammation, enriched in up-regulated genes. On the other hand, terms related to dis-regulation of cellular functions were enriched in down-regulated genes. Differential expression analysis revealed known as well as novel transcription factor genes in Mtb infection, many of them significantly down-regulated. IFNγ or IL-4/IL-13 pre-stimulation induce additional differentially expressed genes in Mtb-infected macrophages. Cluster analysis uncovered significant numbers, prolonging their expressional changes. Furthermore, Mtb infection augmented cytokine-mediated M1 and M2 pre-activations. In addition, we identified unique transcriptional features of Mtb-mediated differentially expressed lncRNAs. In summary we provide a comprehensive in depth gene expression/regulation profile in Mtb-infected macrophages, an important step forward for a better understanding of host-pathogen interaction dynamics in Mtb infection.

Identifying novel transcription factors involved in the inflammatory response by using binding site motif scanning in genomic regions defined by histone acetylation

The innate immune response to pathogenic challenge is a complex, multi-staged process involving thousands of genes. While numerous transcription factors that act as master regulators of this response have been identified, the temporal complexity of gene expression changes in response to pathogen-associated molecular pattern receptor stimulation strongly suggest that additional layers of regulation remain to be uncovered. The evolved pathogen response program in mammalian innate immune cells is understood to reflect a compromise between the probability of clearing the infection and the extent of tissue damage and inflammatory sequelae it causes. Because of that, a key challenge to delineating the regulators that control the temporal inflammatory response is that an innate immune regulator that may confer a selective advantage in the wild may be dispensable in the lab setting. In order to better understand the complete transcriptional response of primary macrophages to the bacterial endotoxin lipopolysaccharide (LPS), we designed a method that integrates temporally resolved gene expression and chromatin-accessibility measurements from mouse macrophages. By correlating changes in transcription factor binding site motif enrichment scores, calculated within regions of accessible chromatin, with the average temporal expression profile of a gene cluster, we screened for transcriptional factors that regulate the cluster. We have validated our predictions of LPS-stimulated transcriptional regulators using ChIP-seq data for three transcription factors with experimentally confirmed functions in innate immunity. In addition, we predict a role in the macrophage LPS response for several novel transcription factors that have not previously been implicated in immune responses. This method is applicable to any experimental situation where temporal gene expression and chromatin-accessibility data are available.

CNBP acts as a key transcriptional regulator of sustained expression of interleukin-6

The transcription of inflammatory genes is an essential step in host defense activation. Here, we show that cellular nucleic acid-binding protein (CNBP) acts as a transcription regulator that is required for activating the innate immune response. We identified specific CNBP-binding motifs present in the promoter region of sustained inflammatory cytokines, thus, directly inducing the expression of target genes. In particular, lipopolysaccharide (LPS) induced cnbp expression through an NF-κB-dependent manner and a positive autoregulatory mechanism, which enables prolonged il-6 gene expression. This event depends strictly on LPS-induced CNBP nuclear translocation through phosphorylation-mediated dimerization. Consequently, cnbp-depleted zebrafish are highly susceptible to Shigella flexneri infection in vivo. Collectively, these observations identify CNBP as a key transcriptional regulator required for activating and maintaining the immune response.

Reconstructing the regulatory circuit of cell fate determination in yeast mating response

Massive technological advances enabled high-throughput measurements of proteomic changes in biological processes. However, retrieving biological insights from large-scale protein dynamics data remains a challenging task. Here we used the mating differentiation in yeast Saccharomyces cerevisiae as a model and developed integrated experimental and computational approaches to analyze the proteomic dynamics during the process of cell fate determination. When exposed to a high dose of mating pheromone, the yeast cell undergoes growth arrest and forms a shmoo-like morphology; however, at intermediate doses, chemotropic elongated growth is initialized. To understand the gene regulatory networks that control this differentiation switch, we employed a high-throughput microfluidic imaging system that allows real-time and simultaneous measurements of cell growth and protein expression. Using kinetic modeling of protein dynamics, we classified the stimulus-dependent changes in protein abundance into two sources: global changes due to physiological alterations and gene-specific changes. A quantitative framework was proposed to decouple gene-specific regulatory modes from the growth-dependent global modulation of protein abundance. Based on the temporal patterns of gene-specific regulation, we established the network architectures underlying distinct cell fates using a reverse engineering method and uncovered the dose-dependent rewiring of gene regulatory network during mating differentiation. Furthermore, our results suggested a potential crosstalk between the pheromone response pathway and the target of rapamycin (TOR)-regulated ribosomal biogenesis pathway, which might underlie a cell differentiation switch in yeast mating response. In summary, our modeling approach addresses the distinct impacts of the global and gene-specific regulation on the control of protein dynamics and provides new insights into the mechanisms of cell fate determination. We anticipate that our integrated experimental and modeling strategies could be widely applicable to other biological systems.

A systematic characterization of the proteomic changes during the process of cell differentiation is critical for understanding the underlying molecular mechanisms. However, protein expression can be largely affected by changes in cell physiological state, which hampers the detection of regulatory interactions. Here we proposed an integrated experimental and computational framework to reconstruct regulatory circuits in mating differentiation of budding yeast Saccharomyces cerevisiae, in which distinct cell fates are triggered by alteration in pheromone concentration. A modeling approach was developed to decouple gene-specific regulation from growth-dependent global regulation of protein expression, allowing us to reverse engineering the gene regulatory circuits underlying distinct cell fates. Our work highlights the importance of model-based analysis of proteomic data and delivers new insight into dose-dependent differentiation behavior of budding yeast.

Social status alters immune regulation and response to infection in macaques

Social status is one of the strongest predictors of human disease risk and mortality, and it also influences Darwinian fitness in social mammals more generally. To understand the biological basis of these effects, we combined genomics with a social status manipulation in female rhesus macaques to investigate how status alters immune function. We demonstrate causal but largely plastic social status effects on immune cell proportions, cell type-specific gene expression levels, and the gene expression response to immune challenge. Further, we identify specific transcription factor signaling pathways that explain these differences, including low-status-associated polarization of the Toll-like receptor 4 signaling pathway toward a proinflammatory response. Our findings provide insight into the direct biological effects of social inequality on immune function, thus improving our understanding of social gradients in health.

Solving the influence maximization problem reveals regulatory organization of the yeast cell cycle

The Influence Maximization Problem (IMP) aims to discover the set of nodes with the greatest influence on network dynamics. The problem has previously been applied in epidemiology and social network analysis. Here, we demonstrate the application to cell cycle regulatory network analysis for Saccharomyces cerevisiae. Fundamentally, gene regulation is linked to the flow of information. Therefore, our implementation of the IMP was framed as an information theoretic problem using network diffusion. Utilizing more than 26,000 regulatory edges from YeastMine, gene expression dynamics were encoded as edge weights using time lagged transfer entropy, a method for quantifying information transfer between variables. By picking a set of source nodes, a diffusion process covers a portion of the network. The size of the network cover relates to the influence of the source nodes. The set of nodes that maximizes influence is the solution to the IMP. By solving the IMP over different numbers of source nodes, an influence ranking on genes was produced. The influence ranking was compared to other metrics of network centrality. Although the top genes from each centrality ranking contained well-known cell cycle regulators, there was little agreement and no clear winner. However, it was found that influential genes tend to directly regulate or sit upstream of genes ranked by other centrality measures. The influential nodes act as critical sources of information flow, potentially having a large impact on the state of the network. Biological events that affect influential nodes and thereby affect information flow could have a strong effect on network dynamics, potentially leading to disease. Code and data can be found at: https://github.com/gibbsdavidl/miergolf.

TIGERi: modeling and visualizing the responses to perturbation of a transcription factor network

BACKGROUND

Transcription factor (TF) networks play a key role in controlling the transfer of genetic information from gene to mRNA. Much progress has been made on understanding and reverse-engineering TF network topologies using a range of experimental and theoretical methodologies. Less work has focused on using these models to examine how TF networks respond to changes in the cellular environment.

METHODS

In this paper, we have developed a simple, pragmatic methodology, TIGERi (Transcription-factor-activity Illustrator for Global Explanation of Regulatory interaction), to model the response of an inferred TF network to changes in cellular environment. The methodology was tested using publicly available data comparing gene expression profiles of a mouse p38α (Mapk14) knock-out line to the original wild-type.

RESULTS

Using the model, we have examined changes in the TF network resulting from the presence or absence of p38α. A part of this network was confirmed by experimental work in the original paper. Additional relationships were identified by our analysis, for example between p38α and HNF3, and between p38α and SOX9, and these are strongly supported by published evidence. FXR and MYC were also discovered in our analysis as two novel links of p38α. To provide a computational methodology to the biomedical communities that has more user-friendly interface, we also developed a standalone GUI (graphical user interface) software for TIGERi and it is freely available at https://github.com/namshik/tigeri/ .

CONCLUSIONS

We therefore believe that our computational approach can identify new members of networks and new interactions between members that are supported by published data but have not been integrated into the existing network models. Moreover, ones who want to analyze their own data with TIGERi could use the software without any command line experience. This work could therefore accelerate researches in transcriptional gene regulation in higher eukaryotes.

Iterative Modeling Reveals Evidence of Sequential Transcriptional Control Mechanisms

Combinatorial control of gene expression is presumed to be mediated by molecular interactions between coincident transcription factors (TFs). While information on the genome-wide locations of TFs is available, the genes they regulate and whether they function combinatorially often remain open questions. Here, we developed a mechanistic, rather than statistical, modeling approach to elucidate TF control logic from gene expression data. Applying this approach to hundreds of genes in 85 datasets measuring the transcriptional responses of murine fibroblasts and macrophages to cytokines and pathogens, we found that stimulus-responsive TFs generally function sequentially in logical OR gates or singly. Logical AND gates were found between NF-κB-responsive mRNA synthesis and MAPKp38-responsive control of mRNA half-life, but not between temporally coincident TFs. Our analyses identified the functional target genes of each of the pathogen-responsive TFs and prompt a revision of the conceptual underpinnings of combinatorial control of gene expression to include sequentially acting molecular mechanisms that govern mRNA synthesis and decay.

Identification of crucial genes associated with rat traumatic spinal cord injury

The aim of the present study was to investigate the key genes associated with traumatic spinal cord injuries (TSCI). The dataset GSE52763 was downloaded from the Gene Expression Omnibus, for which lumbar spinal cord samples were obtained from rats at 1 and 3 weeks following contusive spinal cord injury and 1 week subsequent to a sham laminectomy, and used to identify differentially expressed genes (DEGs). Functional enrichment analysis, co‑expression analysis and transcription factor (TF) identification were performed for DEGs common to the 1 and 3 week injury samples. In total, 234 upregulated and 51 downregulated DEGs were common to the 1 and 3 week injury samples. The upregulated DEGs were significantly enriched in Gene Ontology terms concerning immunity (e.g. Itgal and Ccl2) and certain pathways, including natural killer cell mediated cytotoxicity [e.g. Ras‑related C3 botulinum toxin substrate 2 (Rac2) and TYRO protein tyrosine kinase binding protein (Tyrobp)]. The downregulated DEGs were highly enriched in female gonad development [e.g. progesterone receptor (Pgr)], and the steroid biosynthesis pathway. A total of 139 genes had co‑expression associations and the majority of them were upregulated genes. The upregulated co‑expressed genes were predominantly enriched in biological regulation, including TGFB induced factor homeobox 1 (Tgif1) and Rac2. The downregulated co‑expressed genes were enriched in anatomical structure development (e.g. Dnm3). A total of 92 co‑expressed genes composed the protein‑protein interaction network. Additionally, 9 TFs (e.g. Pgr and Tgif1) were identified from the DEGs. It was hypothesized that the genes including Tgif1, Rac2, Tyrobp, and Pgr may be closely associated with TSCI.

Identifying Cell Type-Specific Transcription Factors by Integrating ChIP-seq and eQTL Data-Application to Monocyte Gene Regulation

We describe a novel computational approach to identify transcription factors (TFs) that are candidate regulators in a human cell type of interest. Our approach involves integrating cell type-specific expression quantitative trait locus (eQTL) data and TF data from chromatin immunoprecipitation-to-tag-sequencing (ChIP-seq) experiments in cell lines. To test the method, we used eQTL data from human monocytes in order to screen for TFs. Using a list of known monocyte-regulating TFs, we tested the hypothesis that the binding sites of cell type-specific TF regulators would be concentrated in the vicinity of monocyte eQTLs. For each of 397 ChIP-seq data sets, we obtained an enrichment ratio for the number of ChIP-seq peaks that are located within monocyte eQTLs. We ranked ChIP-seq data sets according to their statistical significances for eQTL overlap, and from this ranking, we observed that monocyte-regulating TFs are more highly ranked than would be expected by chance. We identified 27 TFs that had significant monocyte enrichment scores and mapped them into a protein interaction network. Our analysis uncovered two novel candidate monocyte-regulating TFs, BCLAF1 and SIN3A. Our approach is an efficient method to identify candidate TFs that can be used for any cell/tissue type for which eQTL data are available.

Immune disease-associated variants in gene enhancers point to BET epigenetic mechanisms for therapeutic intervention

Genome-wide association studies have identified thousands of single nucleotide polymorphisms in the human genome that are statistically associated with particular disease traits. In this Perspective, we review emerging data suggesting that most single nucleotide polymorphisms associated with immune-mediated diseases are found in regulatory regions of the DNA - parts of the genome that control expression of the protein encoding genes - rather than causing mutations in proteins. We discuss how the emerging understanding of particular gene regulatory regions, gene enhancers and the epigenetic mechanisms by which they are regulated is opening up new opportunities for the treatment of immune-mediated diseases, focusing particularly on the BET family of epigenetic reader proteins as potential therapeutic targets.

An Empirical Prior Improves Accuracy for Bayesian Estimation of Transcription Factor Binding Site Frequencies within Gene Promoters

A Bayesian method for sampling from the distribution of matches to a precompiled transcription factor binding site (TFBS) sequence pattern (conditioned on an observed nucleotide sequence and the sequence pattern) is described. The method takes a position frequency matrix as input for a set of representative binding sites for a transcription factor and two sets of noncoding, 5′ regulatory sequences for gene sets that are to be compared. An empirical prior on the frequency A (per base pair of gene-vicinal, noncoding DNA) of TFBSs is developed using data from the ENCODE project and incorporated into the method. In addition, a probabilistic model for binding site occurrences conditioned on λ is developed analytically, taking into account the finite-width effects of binding sites. The count of TFBS β (conditioned on the observed sequence) is sampled using Metropolis–Hastings with an information entropy-based move generator. The derivation of the method is presented in a step-by-step fashion, starting from specific conditional independence assumptions. Empirical results show that the newly proposed prior on β improves accuracy for estimating the number of TFBS within a set of promoter sequences.

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

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

A Stringent Systems Approach Uncovers Gene-Specific Mechanisms Regulating Inflammation

Much has been learned about transcriptional cascades and networks from large-scale systems analyses of high-throughput datasets. However, analysis methods that optimize statistical power through simultaneous evaluation of thousands of ChIP-seq peaks or differentially expressed genes possess substantial limitations in their ability to uncover mechanistic principles of transcriptional control. By examining nascent transcript RNA-seq, ChIP-seq, and binding motif datasets from lipid A-stimulated macrophages with increased attention to the quantitative distribution of signals, we identified unexpected relationships between the in vivo binding properties of inducible transcription factors, motif strength, and transcription. Furthermore, rather than emphasizing common features of large clusters of co-regulated genes, our results highlight the extent to which unique mechanisms regulate individual genes with key biological functions. Our findings demonstrate the mechanistic value of stringent interrogation of well-defined sets of genes as a complement to broader systems analyses of transcriptional cascades and networks.

High salt primes a specific activation state of macrophages, M(Na)

High salt is positively associated with the risk of many diseases. However, little is known about the mechanisms. Here we showed that high salt increased proinflammatory molecules, while decreased anti-inflammatory and proendocytic molecules in both human and mouse macrophages. High salt also potentiated lipopolysaccharide-induced macrophage activation and suppressed interleukin 4-induced macrophage activation. High salt induced the proinflammatory aspects by activating p38/cFos and/or Erk1/2/cFos pathways, while inhibited the anti-inflammatory and proendocytic aspects by Erk1/2/signal transducer and activator of transcription 6 pathway. Consistent with the in vitro results, high-salt diet increased proinflammatory gene expression of mouse alveolar macrophages. In mouse models of acute lung injury, high-salt diet aggravated lipopolysaccharide-induced pulmonary macrophage activation and inflammation in lungs. These results identify a novel macrophage activation state, M(Na), and high salt as a potential environmental risk factor for lung inflammation through the induction of M(Na).

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

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

Human Dendritic Cell Response Signatures Distinguish 1918, Pandemic, and Seasonal H1N1 Influenza Viruses

Influenza viruses continue to present global threats to human health. Antigenic drift and shift, genetic reassortment, and cross-species transmission generate new strains with differences in epidemiology and clinical severity. We compared the temporal transcriptional responses of human dendritic cells (DC) to infection with two pandemic (A/Brevig Mission/1/1918, A/California/4/2009) and two seasonal (A/New Caledonia/20/1999, A/Texas/36/1991) H1N1 influenza viruses. Strain-specific response differences included stronger activation of NF-κB following infection with A/New Caledonia/20/1999 and a unique cluster of genes expressed following infection with A/Brevig Mission/1/1918. A common antiviral program showing strain-specific timing was identified in the early DC response and found to correspond with reported transcript changes in blood during symptomatic human influenza virus infection. Comparison of the global responses to the seasonal and pandemic strains showed that a dramatic divergence occurred after 4 h, with only the seasonal strains inducing widespread mRNA loss.

IMPORTANCE

Continuously evolving influenza viruses present a global threat to human health; however, these host responses display strain-dependent differences that are incompletely understood. Thus, we conducted a detailed comparative study assessing the immune responses of human DC to infection with two pandemic and two seasonal H1N1 influenza strains. We identified in the immune response to viral infection both common and strain-specific features. Among the stain-specific elements were a time shift of the interferon-stimulated gene response, selective induction of NF-κB signaling by one of the seasonal strains, and massive RNA degradation as early as 4 h postinfection by the seasonal, but not the pandemic, viruses. These findings illuminate new aspects of the distinct differences in the immune responses to pandemic and seasonal influenza viruses.

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

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

A Conserved Circular Network of Coregulated Lipids Modulates Innate Immune Responses

Lipid composition affects the biophysical properties of membranes that provide a platform for receptor-mediated cellular signaling. To study the regulatory role of membrane lipid composition, we combined genetic perturbations of sphingolipid metabolism with the quantification of diverse steps in Toll-like receptor (TLR) signaling and mass spectrometry-based lipidomics. Membrane lipid composition was broadly affected by these perturbations, revealing a circular network of coregulated sphingolipids and glycerophospholipids. This evolutionarily conserved network architecture simultaneously reflected membrane lipid metabolism, subcellular localization, and adaptation mechanisms. Integration of the diverse TLR-induced inflammatory phenotypes with changes in lipid abundance assigned distinct functional roles to individual lipid species organized across the network. This functional annotation accurately predicted the inflammatory response of cells derived from patients suffering from lipid storage disorders, based solely on their altered membrane lipid composition. The analytical strategy described here empowers the understanding of higher-level organization of membrane lipid function in diverse biological systems.

A temporal gate for viral enhancers to co-opt Toll-like-receptor transcriptional activation pathways upon acute infection

Viral engagement with macrophages activates Toll-Like-Receptors (TLRs) and viruses must contend with the ensuing inflammatory responses to successfully complete their replication cycle. To date, known counter-strategies involve the use of viral-encoded proteins that often employ mimicry mechanisms to block or redirect the host response to benefit the virus. Whether viral regulatory DNA sequences provide an opportunistic strategy by which viral enhancer elements functionally mimic innate immune enhancers is unknown. Here we find that host innate immune genes and the prototypical viral enhancer of cytomegalovirus (CMV) have comparable expression kinetics, and positively respond to common TLR agonists. In macrophages but not fibroblasts we show that activation of NFκB at immediate-early times of infection is independent of virion-associated protein, M45. We find upon virus infection or transfection of viral genomic DNA the TLR-agonist treatment results in significant enhancement of the virus transcription-replication cycle. In macrophage time-course infection experiments we demonstrate that TLR-agonist stimulation of the viral enhancer and replication cycle is strictly delimited by a temporal gate with a determined half-maximal time for enhancer-activation of 6 h; after which TLR-activation blocks the viral transcription-replication cycle. By performing a systematic siRNA screen of 149 innate immune regulatory factors we identify not only anticipated anti-viral and pro-viral contributions but also new factors involved in the CMV transcription-replication cycle. We identify a central convergent NFκB-SP1-RXR-IRF axis downstream of TLR-signalling. Activation of the RXR component potentiated direct and indirect TLR-induced activation of CMV transcription-replication cycle; whereas chromatin binding experiments using wild-type and enhancer-deletion virus revealed IRF3 and 5 as new pro-viral host transcription factor interactions with the CMV enhancer in macrophages. In a series of pharmacologic, siRNA and genetic loss-of-function experiments we determined that signalling mediated by the TLR-adaptor protein MyD88 plays a vital role for governing the inflammatory activation of the CMV enhancer in macrophages. Downstream TLR-regulated transcription factor binding motif disruption for NFκB, AP1 and CREB/ATF in the CMV enhancer demonstrated the requirement of these inflammatory signal-regulated elements in driving viral gene expression and growth in cells as well as in primary infection of neonatal mice. Thus, this study shows that the prototypical CMV enhancer, in a restricted time-gated manner, co-opts through DNA regulatory mimicry elements, innate-immune transcription factors to drive viral expression and replication in the face of on-going pro-inflammatory antiviral responses in vitro and in vivo and; suggests an unexpected role for inflammation in promoting acute infection and has important future implications for regulating latency.

Here we discover how inflammatory signalling may unintentionally promote infection, as a result of viruses evolving DNA sequences, known as enhancers, which act as a bait to prey on the infected cell transcription factors induced by inflammation. The major inflammatory transcription factors activated are part of the TLR-signalling pathway. We find the prototypical viral enhancer of cytomegalovirus can be paradoxically boosted by activation of inflammatory “anti-viral” TLR-signalling independent of viral structural proteins. This leads to an increase in viral gene expression and replication in cell-culture and upon infection of mice. We identify an axis of inflammatory transcription factors, acting downstream of TLR-signalling but upstream of interferon inhibition. Mechanistically, the central TLR-adapter protein MyD88 is shown to play a critical role in promoting viral enhancer activity in the first 6h of infection. The co-option of TLR-signalling exceeds the usage of NFκB, and we identify IRF3 and 5 as newly found viral-enhancer interacting inflammatory transcription factors. Taken together this study reveals how virus enhancers, employ a path of least resistance by directly harnessing within a short temporal window, the activation of anti-viral signalling in macrophages to drive viral gene expression and replication to an extent that has not been recognised before.

An LXR-NCOA5 gene regulatory complex directs inflammatory crosstalk-dependent repression of macrophage cholesterol efflux

LXR-cofactor complexes activate the gene expression program responsible for cholesterol efflux in macrophages. Inflammation antagonizes this program, resulting in foam cell formation and atherosclerosis; however, the molecular mechanisms underlying this antagonism remain to be fully elucidated. We use promoter enrichment-quantitative mass spectrometry (PE-QMS) to characterize the composition of gene regulatory complexes assembled at the promoter of the lipid transporter Abca1 following downregulation of its expression. We identify a subset of proteins that show LXR ligand- and binding-dependent association with the Abca1 promoter and demonstrate they differentially control Abca1 expression. We determine that NCOA5 is linked to inflammatory Toll-like receptor (TLR) signaling and establish that NCOA5 functions as an LXR corepressor to attenuate Abca1 expression. Importantly, TLR3-LXR signal crosstalk promotes recruitment of NCOA5 to the Abca1 promoter together with loss of RNA polymerase II and reduced cholesterol efflux. Together, these data significantly expand our knowledge of regulatory inputs impinging on the Abca1 promoter and indicate a central role for NCOA5 in mediating crosstalk between pro-inflammatory and anti-inflammatory pathways that results in repression of macrophage cholesterol efflux.

System-wide analysis of the transcriptional network of human myelomonocytic leukemia cells predicts attractor structure and phorbol-ester-induced differentiation and dedifferentiation transitions

We present a system-wide transcriptional network structure that controls cell types in the context of expression pattern transitions that correspond to cell type transitions. Co-expression based analyses uncovered a system-wide, ladder-like transcription factor cluster structure composed of nearly 1,600 transcription factors in a human transcriptional network. Computer simulations based on a transcriptional regulatory model deduced from the system-wide, ladder-like transcription factor cluster structure reproduced expression pattern transitions when human THP-1 myelomonocytic leukaemia cells cease proliferation and differentiate under phorbol myristate acetate stimulation. The behaviour of MYC, a reprogramming Yamanaka factor that was suggested to be essential for induced pluripotent stem cells during dedifferentiation, could be interpreted based on the transcriptional regulation predicted by the system-wide, ladder-like transcription factor cluster structure. This study introduces a novel system-wide structure to transcriptional networks that provides new insights into network topology.

Network representations of immune system complexity

The mammalian immune system is a dynamic multiscale system composed of a hierarchically organized set of molecular, cellular, and organismal networks that act in concert to promote effective host defense. These networks range from those involving gene regulatory and protein–protein interactions underlying intracellular signaling pathways and single‐cell responses to increasingly complex networks of in vivo cellular interaction, positioning, and migration that determine the overall immune response of an organism. Immunity is thus not the product of simple signaling events but rather nonlinear behaviors arising from dynamic, feedback‐regulated interactions among many components. One of the major goals of systems immunology is to quantitatively measure these complex multiscale spatial and temporal interactions, permitting development of computational models that can be used to predict responses to perturbation. Recent technological advances permit collection of comprehensive datasets at multiple molecular and cellular levels, while advances in network biology support representation of the relationships of components at each level as physical or functional interaction networks. The latter facilitate effective visualization of patterns and recognition of emergent properties arising from the many interactions of genes, molecules, and cells of the immune system. We illustrate the power of integrating ‘omics’ and network modeling approaches for unbiased reconstruction of signaling and transcriptional networks with a focus on applications involving the innate immune system. We further discuss future possibilities for reconstruction of increasingly complex cellular‐ and organism‐level networks and development of sophisticated computational tools for prediction of emergent immune behavior arising from the concerted action of these networks. WIREs Syst Biol Med 2015, 7:13–38. doi: 10.1002/wsbm.1288

This article is categorized under: 1

Analytical and Computational Methods > Computational Methods

2

Laboratory Methods and Technologies > Macromolecular Interactions, Methods

Transcriptomic Analysis for Different Sex Types of Ricinus communis L. during Development from Apical Buds to Inflorescences by Digital Gene Expression Profiling

The castor plant (Ricinus communis L.) is a versatile industrial oilseed crop with a diversity of sex patterns, its hybrid breeding for improving yield and high purity is still hampered by genetic instability of female and poor knowledge of sex expression mechanisms. To obtain some hints involved in sex expression and provide the basis for further insight into the molecular mechanisms of castor plant sex determination, we performed DGE analysis to investigate differences between the transcriptomes of apices and racemes derived from female (JXBM0705P) and monoecious (JXBM0705M) lines. A total of 18 DGE libraries were constructed from the apices and racemes of a wild monoecious line and its isogenic female derivative at three stages of apex development, in triplicate. Approximately 5.7 million clean tags per library were generated and mapped to the reference castor genome. Transcriptomic analysis showed that identical dynamic changes of gene expression were indicated in monoecious and female apical bud during its development from vegetation to reproduction, with more genes expressed at the raceme formation and infant raceme stages compare to the early leaf bud stage. More than 3000 of differentially expressed genes (DEGs) were detected in Ricinus apices at three developmental stages between two different sex types. A number of DEGs involved in hormone response and biosynthesis, such as auxin response and transport, transcription factors, signal transduction, histone demethylation/methylation, programmed cell death, and pollination, putatively associated with sex expression and reproduction were discovered, and the selected DEGs showed consistent expression between qRT-PCR validation and the DGE patterns. Most of those DEGs were suppressed at the early leaf stage in buds of the mutant, but then activated at the following transition stage (5-7-leaf stage) of buds in the mutant, and ultimately, the number of up-regulated DEGs was equal to that of down-regulation in the small raceme of the mutant. In this study, a large number of DEGs and some suggestions involved in sex expression and reproduction were discovered using DGE analysis, which provides large information and valuable hints for next insights into the molecular mechanism of sex determination. It is useful for other further studies in Ricinus.

Systems-level analysis of innate immunity

Systems-level analysis of biological processes strives to comprehensively and quantitatively evaluate the interactions between the relevant molecular components over time, thereby enabling development of models that can be employed to ultimately predict behavior. Rapid development in measurement technologies (omics), when combined with the accessible nature of the cellular constituents themselves, is allowing the field of innate immunity to take significant strides toward this lofty goal. In this review, we survey exciting results derived from systems biology analyses of the immune system, ranging from gene regulatory networks to influenza pathogenesis and systems vaccinology.

Differential control of Mincle-dependent cord factor recognition and macrophage responses by the transcription factors C/EBPβ and HIF1α

Trehalose-6,6-dimycolate (TDM), the mycobacterial cord factor, and its synthetic analog Trehalose-6,6-dibehenate (TDB) bind to the C-type lectin receptors macrophage-inducible C-type lectin (Mincle) and Mcl to activate macrophages. Genetically, the transcriptional response to TDB/TDM has been defined to require FcRγ-Syk-Card9 signaling. However, TDB/TDM-triggered kinase activation has not been studied well, and it is largely unknown which transcriptional regulators bring about inflammatory gene expression. In this article, we report that TDB/TDM caused only weak Syk-phosphorylation in resting macrophages, consistent with low basal Mincle expression. However, LPS-priming caused MYD88-dependent upregulation of Mincle, resulting in enhanced TDB/TDM-induced kinase activation and more rapid inflammatory gene expression. TLR-induced Mincle expression partially circumvented the requirement for Mcl in the response to TDB/TDM. To dissect transcriptional responses to TDB/TDM, we mined microarray data and identified early growth response (Egr) family transcription factors as direct Mincle target genes, whereas upregulation of Cebpb and Hif1a required new protein synthesis. Macrophages and dendritic cells lacking C/EBPβ showed nearly complete abrogation of TDB/TDM responsiveness, but also failed to upregulate Mincle. Retroviral rescue of Mincle expression in Cebpb-deficient cells restored induction of Egr1, but not of G-CSF. This pattern of C/EBPβ dependence was also observed after stimulation with the Dectin-1 ligand Curdlan. Inducible expression of hypoxia-inducible factor 1α (HIF1α) also required C/EBPβ. In turn, HIF1α was not required for Mincle expression, kinase activation, and Egr1 or Csf3 expression, but critically contributed to NO production. Taken together, we identify C/EBPβ as central hub in Mincle expression and inflammatory gene induction, whereas HIF1α controls Nos2 expression. C/EBPβ also connects TLR signals to cord factor responsiveness through MYD88-dependent upregulation of Mincle.

Identification of the key differential transcriptional responses of human whole blood following TLR2 or TLR4 ligation in-vitro

The use of human whole blood for transcriptomic analysis has potential advantages over the use of isolated immune cells for studying the transcriptional response to pathogens and their products. Whole blood stimulation can be carried out in a laboratory without the expertise or equipment to isolate immune cells from blood, with the added advantage of being able to undertake experiments using very small volumes of blood. Toll like receptors (TLRs) are a family of pattern recognition receptors which recognise highly conserved microbial products. Using the TLR2 ligand (Pam3CSK4) and the TLR4 ligand (LPS), human whole blood was stimulated for 0, 1, 3, 6, 12 or 24 hours at which times mRNA was isolated and a comparative microarray was undertaken. A common NFκB transcriptional programme was identified following both TLR2 and TLR4 ligation which peaked at between 3 to 6 hours including upregulation of many of the NFκB family members. In contrast an interferon transcriptional response was observed following TLR4 but not TLR2 ligation as early as 1 hour post stimulation and peaking at 6 hours. These results recapitulate the findings observed in previously published studies using isolated murine and human myeloid cells indicating that in vitro stimulated human whole blood can be used to interrogate the early transcriptional kinetic response of innate cells to TLR ligands. Our study demonstrates that a transcriptomic analysis of mRNA isolated from human whole blood can delineate both the temporal response and the key transcriptional differences following TLR2 and TLR4 ligation.

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

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

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Macrophages react with specific transcriptional programming upon distinct signals

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

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

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Inflammatory signatures are lost in alveolar macrophages from COPD patients

Transcriptomic meta-analysis of multiple sclerosis and its experimental models

Background

Multiple microarray analyses of multiple sclerosis (MS) and its experimental models have been published in the last years.

Objective

Meta-analyses integrate the information from multiple studies and are suggested to be a powerful approach in detecting highly relevant and commonly affected pathways.

Data sources

ArrayExpress, Gene Expression Omnibus and PubMed databases were screened for microarray gene expression profiling studies of MS and its experimental animal models.

Study eligibility criteria

Studies comparing central nervous system (CNS) samples of diseased versus healthy individuals with n >1 per group and publically available raw data were selected.

Material and Methods

Included conditions for re-analysis of differentially expressed genes (DEGs) were MS, myelin oligodendrocyte glycoprotein-induced experimental autoimmune encephalomyelitis (EAE) in rats, proteolipid protein-induced EAE in mice, Theiler’s murine encephalomyelitis virus-induced demyelinating disease (TMEV-IDD), and a transgenic tumor necrosis factor-overexpressing mouse model (TNFtg). Since solely a single MS raw data set fulfilled the inclusion criteria, a merged list containing the DEGs from two MS-studies was additionally included. Cross-study analysis was performed employing list comparisons of DEGs and alternatively Gene Set Enrichment Analysis (GSEA).

Results

The intersection of DEGs in MS, EAE, TMEV-IDD, and TNFtg contained 12 genes related to macrophage functions. The intersection of EAE, TMEV-IDD and TNFtg comprised 40 DEGs, functionally related to positive regulation of immune response. Over and above, GSEA identified substantially more differentially regulated pathways including coagulation and JAK/STAT-signaling.

Conclusion

A meta-analysis based on a simple comparison of DEGs is over-conservative. In contrast, the more experimental GSEA approach identified both, a priori anticipated as well as promising new candidate pathways.

Rapid temporal dynamics of transcription, protein synthesis, and secretion during macrophage activation

Macrophages provide the first line of host defense with their capacity to react to an array of cytokines and bacterial components requiring tight regulation of protein expression and secretion to invoke a properly tuned innate immune response. To capture the dynamics of this system, we introduce a novel method combining pulsed stable isotope labeling with amino acids in cell culture (SILAC) with pulse labeling using the methionine analog azidohomoalanine that allows the enrichment of newly synthesized proteins via click-chemistry followed by their identification and quantification by mass spectrometry. We show that this permits the analysis of proteome changes on a rapid time scale, as evidenced by the detection of 4852 newly synthesized proteins after only a 20-min SILAC pulse. We have applied this methodology to study proteome response during macrophage activation in a time-course manner. We have combined this with full proteome, transcriptome, and secretome analyses, producing an integrative analysis of the first 3 h of lipopolysaccharide-induced macrophage activation. We observed the rapid induction of multiple processes well known to TLR4 signaling, as well as anti-inflammatory proteins and proteins not previously associated with immune response. By correlating transcriptional, translational, and secretory events, we derived novel mechanistic principles of processes specifically induced by lipopolysaccharides, including ectodomain shedding and proteolytic processing of transmembrane and extracellular proteins and protein secretion independent of transcription. In conclusion, we demonstrate that the combination of pulsed azidohomoalanine and pulsed SILAC permits the detailed characterization of proteomic events on a rapid time scale. We anticipate that this approach will be very useful in probing the immediate effects of cellular stimuli and will provide mechanistic insight into cellular perturbation in multiple biological systems. The data have been deposited in ProteomeXchange with the identifier PXD000600.

De novo characterization of the Anthurium transcriptome and analysis of its digital gene expression under cold stress

Background

Anthurium andraeanum is one of the most popular tropical flowers. In temperate and cold zones, a much greater risk of cold stress occurs in the supply of Anthurium plants. Unlike the freeze-tolerant model plants, Anthurium plants are particularly sensitive to low temperatures. Improvement of chilling tolerance in Anthurium may significantly increase its production and extend its shelf-life. To date, no previous genomic information has been reported in Anthurium plants.

Results

Using Illumina sequencing technology, we generated over two billion base of high-quality sequence in Anthurium, and demonstrated de novo assembly and annotation of genes without prior genome information. These reads were assembled into 44,382 unigenes (mean length = 560 bp). Based on similarity search with known protein in the non-redundant (nr) protein database, 27396 unigenes (62%) were functionally annotated with a cut-off E-value of 10^-5. Further, DGE tags were mapped to the assembled transcriptome for gene expression analysis under cold stress. In total, 4363 differentially expressed genes were identified. Among these genes, 292, 805 and 708 genes were up-regulated after 1-h, 5-h and 24-h cold treatment, respectively. Then we mapped these cold-induced genes to the KEGG database. Specific enrichment was observed in photosynthesis pathway, metabolic pathways and oxidative phosphorylation pathway in 1-h cold-treated plants. After a 5-h cold treatment, the metabolic pathways and oxidative phosphorylation pathway were significantly identified as the top two pathways. After 24-h cold treatment, mRNA surveillance pathway, RNA transport pathway and plant-pathogen interaction pathway were significantly enriched. Together, a total of 39 cold-inducible transcription factors were identified, including subsets of AP2/ERF, Zinc figure, NAC, MYB and bZIP family members.

Conclusion

Our study is the first to provide the transcriptome sequence resource for Anthurium plants, and demonstrate its digital gene expression profiling under cold conditions using the assembled transcriptome data for reference. These data provides a valuable resource for genetic and genomic studies under abiotic conditions for Anthurium plants.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-14-827) contains supplementary material, which is available to authorized users.

Integrated expression profiles of mRNA and miRNA in polarized primary murine microglia

Neuroinflammation contributes to many neurologic disorders including Alzheimer’s disease, multiple sclerosis, and stroke. Microglia is brain resident myeloid cells and have emerged as a key driver of the neuroinflammatory responses. MicroRNAs (miRNAs) provide a novel layer of gene regulation and play a critical role in regulating the inflammatory response of peripheral macrophages. However, little is known about the miRNA in inflammatory activation of microglia. To elucidate the role that miRNAs have on microglial phenotypes under classical (M1) or alternative (M2) activation under lipopolysaccharide (‘M1’-skewing) and interleukin-4 (‘M2a’-skewing) stimulation conditions, we performed microarray expression profiling and bioinformatics analysis of both mRNA and miRNA using primary cultured murine microglia. miR-689, miR-124, and miR-155 were the most strongly associated miRNAs predicted to mediate pro-inflammatory pathways and M1-like activation phenotype. miR-155, the most strongly up-regulated miRNA, regulates the signal transducer and activator of transcription 3 signaling pathway enabling the late phase response to M1-skewing stimulation. Reduced expression in miR-689 and miR-124 are associated with dis-inhibition of many canonical inflammatory pathways. miR-124, miR-711, miR-145 are the strongly associated miRNAs predicted to mediate anti-inflammatory pathways and M2-like activation phenotype. Reductions in miR-711 and miR-124 may regulate inflammatory signaling pathways and peroxisome proliferator-activated receptor-gamma pathway. miR-145 potentially regulate peripheral monocyte/macrophage differentiation and faciliate the M2-skewing phenotype. Overall, through combined miRNA and mRNA expression profiling and bioinformatics analysis we have identified six miRNAs and their putative roles in M1 and M2-skewing of microglial activation through different signaling pathways.