Transfection of primary immune cells is difficult to achieve at high efficiency and without cell activation and maturation. Dendritic cells (DCs) represent a key link between the innate and adaptive immune systems. Delineating the signaling pathways involved in the activation of human primary DCs and reverse engineering cellular inflammatory pathways have been challenging tasks. We optimized and validated an effective high-throughput transfection protocol, allowing us to transiently express DNA in naïve primary DCs, as well as investigate the effect of gene silencing by RNA interference. Using a high-throughput nucleofection system, monocyte-derived DCs were nucleoporated with a plasmid expressing green fluorescent protein (GFP), and transfection efficiency was determined by flow cytometry, based on GFP expression. To evaluate the effect of nucleoporation on DC maturation, the expression of cell surface markers CD86 and MHCII in GFP-positive cells was analyzed by flow cytometry. We established optimal assay conditions with a cell viability reaching 70%, a transfection efficiency of over 50%, and unchanged CD86 and MHCII expression. We examined the impact of small interfering RNA (siRNA)-mediated knockdown of RIG-I, a key viral recognition receptor, on the induction of the interferon (IFN) response in DCs infected with Newcastle disease virus. RIG-I protein was undetectable by Western blot in siRNA-treated cells. RIG-I knockdown caused a 75% reduction in the induction of IFN-β mRNA compared with the negative control siRNA. This protocol should be a valuable tool for probing the immune response pathways activated in human DCs.
Dendritic cells; Nucleofection; High-throughput; Green fluorescent protein; siRNA; Interferon signaling
Hallucinogenic drugs, such as lysergic acid diethylamide (LSD), mescaline and psilocybin, alter perception and cognitive processes. All hallucinogenic drugs have in common a high affinity for the serotonin 5-HT2A receptor. Metabotropic glutamate 2/3 (mGlu2/3) receptor ligands show efficacy in modulating the cellular and behavioral responses induced by hallucinogenic drugs. Here, we explored the effect of chronic treatment with the mGlu2/3 receptor antagonist 2S-2-amino-2-(1S,2S-2-carboxycyclopropan-1-yl)-3-(xanth-9-yl)-propionic acid (LY341495) on the hallucinogenic-like effects induced by LSD (0.24 mg/kg). Mice were chronically (21 days) treated with LY341495 (1.5 mg/kg), or vehicle, and experiments were carried out one day after the last injection. Chronic treatment with LY341495 down-regulated [3H]ketanserin binding in somatosensory cortex of wild-type, but not mGlu2 knockout (KO), mice. Head-twitch behavior, and expression of c-fos, egr-1 and egr-2, which are responses induced by hallucinogenic 5-HT2A agonists, were found to be significantly decreased by chronic treatment with LY341495. These findings suggest that repeated blockade of the mGlu2 receptor by LY341495 results in reduced 5-HT2A receptor-dependent hallucinogenic effects of LSD.
Hallucinogenic drugs; Serotonin 5-HT2A receptor; Metabotropic glutamate 2 (mGlu2) receptor; Lysergic acid diethylamide (LSD); LY341495; G protein-coupled receptor (GPCR); schizophrenia; psychosis
Identifying the early gene program induced by GnRH would help understand how GnRH-activated signaling pathways modulate gonadotrope secretory response. We previously analyzed GnRH-induced early genes in LβT2 cells, however these lack GnRH self-potentiation, a physiological attribute of gonadotropes. To minimize cellular heterogeneity, rat primary pituitary cultures were enriched for gonadotropes by 40–60% using a sedimentation gradient. Given the limited number of gonadotropes, RNA was amplified prior to microarray analysis. Thirty-three genes were up-regulated 40 minutes after GnRH stimulation. Real-time PCR confirmed regulation of several transcripts including fosB, c-fos, egr-2 and rap1b, a small GTPase and member of the Ras family. GnRH stimulated rap1b gene expression in gonadotropes, measured by a sensitive single cell assay. Immunocytochemistry revealed increased Rap1 protein in GnRH-stimulated gonadotropes. These data establish rap1b as a novel gene rapidly induced by GnRH and a candidate to modulate gonadotropin secretion in rat gonadotropes.
GnRH; Rap1b; rat primary pituitary cultures; gonadotrope enrichment; early gene; single-cell gene expression
In schizophrenia patients, optimal treatment with antipsychotics requires weeks to months of sustained drug therapy. However, single administration of antipsychotic drugs can reverse schizophrenia-like behavioral alterations in rodent models of psychosis. This raises questions about the physiological relevance of such antipsychotic-like activity.
This study evaluates the effects of chronic treatment with clozapine on the cellular and behavioral responses induced by the hallucinogenic serotonin 5-HT2A receptor agonist lysergic acid diethylamide (LSD) as a mouse model of psychosis.
Mice were treated chronically (21 days) with 25 mg/kg/day clozapine. Experiments were conducted 1, 7, 14, and 21 days after the last clozapine administration. [3H]Ketanserin binding and 5-HT2A mRNA expression were determined in mouse somatosensory cortex. Head-twitch behavior, expression of c-fos, which is induced by all 5-HT2A agonists, and expression of egr-1 and egr-2, which are LSD-like specific, were assayed.
Head-twitch response was decreased and [3H]ketanserin binding was downregulated in 1, 7, and 14 days after chronic clozapine. 5-HT2A mRNA was reduced 1 day after chronic clozapine. Induction of c-fos, but not egr-1 and egr-2, was rescued 7 days after chronic clozapine. These effects were not observed after short treatment (2 days) with clozapine or chronic haloperidol (1 mg/kg/day).
Our findings provide a murine model of chronic atypical antipsychotic drug action and suggest downregulation of the 5-HT2A receptor as a potential mechanism involved in these persistent therapeutic-like effects.
Schizophrenia; Hallucinogenic drugs; LSD; Mouse models; GPCR
The physiological function of the immune system and the response to therapeutic immunomodulators may be sensitive to combinatorial cytokine micro-environments that shape the responses of specific immune cells. Previous work shows that paracrine cytokines released by virus-infected human dendritic cells (DC) can dictate the maturation state of naïve DCs. To understand the effects of paracrine signaling, we systematically studied the effects of combinations cytokines in this complex mixture in generating an anti-viral state. After naïve DCs were exposed to either IFNβ or to paracrine signaling released by DCs infected by Newcastle disease virus (NDV), microarray analysis revealed a large number of genes that were differently regulated by the DC-secreted paracrine signaling. In order to identify the cytokine mechanisms involved, we identified 20 cytokines secreted by NDV infected DCs for which the corresponding receptor gene is expressed in naïve DCs. By exposing cells to all combinations of 19 cytokines (leave-one-out studies), we identified five cytokines (IFNβ, TNFα, IL-1β, TNFSF15, and IL28) as candidates for regulating DC maturation markers. Subsequent experiments identified IFNβ, TNFα, and IL1β as the major contributors to this anti-viral state. This finding was supported by infection studies in vitro, by T-cell activation studies and by in vivo infection studies in mouse. Combination of cytokines can cause response states in DCs that differ from those achieved by the individual cytokines alone. These results suggest that the cytokine microenvironment may act via a combinatorial code to direct the response state of specific immune cells. Further elucidation of this code may provide insight into responses to infection and neoplasia as well as guide the development of combinatorial cytokine immunomodulation for infectious, autoimmune, and immunosurveillance-related diseases.
TNFa; IL1b; IFNb; anti-viral signaling; DC maturation; combinatorial effect
Cell-to-cell variability in mRNA and proteins has been observed in many biological systems, including the human innate immune response to viral infection. Most of these studies have focused on variability that arises from (a) intrinsic stochastic fluctuations in gene expression and (b) extrinsic sources (e.g. fluctuations in transcription factors). The main focus of our study is the effect of extracellular signaling on enhancing intrinsic stochastic fluctuations. As a new source of noise, the communication between cells with fluctuating numbers of components has received little attention. We use agent-based modeling to study this contribution to noise in a system of human dendritic cells responding to viral infection.
Our results, validated by single-cell experiments, show that in the transient state cell-to-cell variability in an interferon-stimulated gene (DDX58) arises from the interplay between the spatial randomness of the cellular sources of the interferon and the temporal stochasticity of its own production. The numerical simulations give insight into the time scales on which autocrine and paracrine signaling act in a heterogeneous population of dendritic cells upon viral infection. We study the effect of different factors that influence the magnitude of the cell-to-cell-variability of the induced gene, including the cell density, multiplicity of infection, and the time scale over which the cellular sources begin producing the cytokine.
We propose a mechanism of noise propagation through extracellular communication and establish conditions under which the mechanism is operative. The cellular stochasticity of gene induction, which we investigate, is not limited to the specific interferon-induced gene we have studied; a broad distribution of copy numbers across cells is to be expected for other interferon-stimulated genes. This can lead to functional consequences for the system-level response to a viral challenge.
Cytokine signaling; Dendritic cells; Multi-scale modeling; Noise propagation; Spatial heterogeneity
Motivation: For flow cytometry data, there are two common approaches to the unsupervised clustering problem: one is based on the finite mixture model and the other on spatial exploration of the histograms. The former is computationally slow and has difficulty to identify clusters of irregular shapes. The latter approach cannot be applied directly to high-dimensional data as the computational time and memory become unmanageable and the estimated histogram is unreliable. An algorithm without these two problems would be very useful.
Results: In this article, we combine ideas from the finite mixture model and histogram spatial exploration. This new algorithm, which we call flowPeaks, can be applied directly to high-dimensional data and identify irregular shape clusters. The algorithm first uses K-means algorithm with a large K to partition the cell population into many small clusters. These partitioned data allow the generation of a smoothed density function using the finite mixture model. All local peaks are exhaustively searched by exploring the density function and the cells are clustered by the associated local peak. The algorithm flowPeaks is automatic, fast and reliable and robust to cluster shape and outliers. This algorithm has been applied to flow cytometry data and it has been compared with state of the art algorithms, including Misty Mountain, FLOCK, flowMeans, flowMerge and FLAME.
Availability: The R package flowPeaks is available at https://github.com/yongchao/flowPeaks.
Supplementary data are available at Bioinformatics online
We show that influenza A H1N1 virus infection leads to very low infectivity in mouse dendritic cells (DCs) in vitro compared with that in human DCs. This holds when H3 or H5 replaces H1 in recombinant viruses. Viruslike particles confirm the difference between mouse and human, suggesting that reduced virus entry contributes to lower mouse DC infectivity. Low infectivity of mouse DCs should be considered when they are used to study responses of DCs that are actually infected.
The histone demethylase LSD1, a component of the CoREST (corepressor for element 1-silencing transcription factor) corepressor complex, plays an important role in the downregulation of gene expression during development. However, the activities of LSD1 in mediating short-time-scale gene expression changes have not been well understood. To reveal the mechanisms underlying these two distinct functions of LSD1, we performed genome-wide mapping and cellular localization studies of LSD1 and its dimethylated histone 3 lysine 4 (substrate H3K4me2) in mouse embryonic stem cells (ES cells). Our results showed an extensive overlap between the LSD1 and H3K4me2 genomic regions and a correlation between the genomic levels of LSD1/H3K4me2 and gene expression, including many highly expressed ES cell genes. LSD1 is recruited to the chromatin of cells in the G1/S/G2 phases and is displaced from the chromatin of M-phase cells, suggesting that LSD1 or H3K4me2 alternatively occupies LSD1 genomic regions during cell cycle progression. LSD1 knockdown by RNA interference or its displacement from the chromatin by antineoplastic agents caused an increase in the levels of a subset of LSD1 target genes. Taken together, these results suggest that cell cycle-dependent association and dissociation of LSD1 with chromatin mediates short-time-scale gene expression changes during embryonic stem cell cycle progression.
The serotonin 5-HT2A receptor (5-HT2AR) and dopamine D2 receptor (D2R) are high-affinity G protein-coupled receptor targets for two different classes of antipsychotic drugs used to treat schizophrenia. Interestingly, the antipsychotic effects are not based on the regulation of same signaling mediators since activation of the 5-HT2AR and of the D2R regulate Gq/11 protein and Gi/o protein, respectively. Here we use radioligand binding and second messenger production assays to provide evidence for a functional crosstalk between 5-HT2AR and D2R in brain and in HEK293 cells. D2R activation increases the hallucinogenic agonist affinity for 5-HT2AR and decreases the 5-HT2AR induced inositol phosphate production. In vivo, 5-HT2AR expression is necessary for the full effects of D2R antagonist on MK-801-induced locomotor activity. Co-immunoprecipitation studies show that the two receptors can physically interact in HEK293 cells and raise the possibility that a receptor heterocomplex mediates the crosstalk observed. The existence of this 5-HT2AR-D2R heteromer and crosstalk may have implications for diseases involving alterations of serotonin and dopamine systems and for the development of new classes of therapeutic drugs.
Serotonin 5-HT2A receptor; Dopamine D2 receptor; Crosstalk; Schizophrenia; Hallucinogen; Antipsychotic
Conventional compensation of flow cytometry (FMC) data of an N-stained sample requires additional data sets, of N single-stained control samples, to estimate the spillover coefficients. Single-stained controls however are the least rigorous controls because any of the multi-stained controls are closer to the N-stained sample. In this paper a new, optimization based, compensation method has been developed that is able to use not only single- but also multi-stained controls to improve estimates of the spillover coefficients. The method is demonstrated on a data set from 5-stained dentritic cells (DCs) with 5 single-stained and 8 multi-stained controls. This approach is practical and leads to significant improvements in FCM compensation.
Compensation in flow cytometry; optimization; spillover coefficients; dendritic cells
Hallucinogenic drugs, including mescaline, psilocybin and lysergic acid diethylamide (LSD), act at serotonin 5-HT2A receptors (5-HT2ARs). Metabotropic glutamate receptor 2/3 (mGluR2/3) ligands show efficacy in modulating the responses induced by activation of 5-HT2ARs. The formation of a 5-HT2AR-mGluR2 complex suggests a functional interaction that affects the hallucinogen-regulated cellular signaling pathways. Here, we tested the cellular and behavioral effects of hallucinogenic 5-HT2AR agonists in mGluR2 knockout (mGluR2-KO) mice. Mice were intraperitoneally injected with the hallucinogens DOI (2 mg/kg) and LSD (0.24 mg/kg), or vehicle. Head-twitch behavioral response, expression of c-fos, which is induced by all 5-HT2AR agonists, and expression of egr-2, which is hallucinogen-specific, were determined in wild type and mGluR2-KO mice. [3H]Ketanserin binding displacement curves by DOI were performed in mouse frontal cortex membrane preparations. Head twitch behavior was abolished in mGluR2-KO mice. The high-affinity binding site of DOI was undetected in mGluR2-KO mice. The hallucinogen DOI induced c-fos in both wild type and mGluR2-KO mice. However, the induction of egr-2 by DOI was eliminated in mGlu2-KO mice. These findings suggest that the 5-HT2AR-mGluR2 complex is necessary for the neuropsychological responses induced by hallucinogens.
Hallucinogenic drugs; LSD; Serotonin 5-HT2A receptor; Metabotropic glutamate mGlu2 receptor; G protein-coupled receptor (GPCR); Schizophrenia and psychosis
Nipah virus is an emerging pathogen that causes severe disease in humans. It expresses several antagonist proteins that subvert the immune response and that may contribute to its pathogenicity. Studies of its biology are difficult due to its high pathogenicity and requirement for biosafety level 4 containment. We integrated experimental and computational methods to elucidate the effects of Nipah virus immune antagonists. Individual Nipah virus immune antagonists (phosphoprotein and V and W proteins) were expressed from recombinant Newcastle disease viruses, and the responses of infected human monocyte-derived dendritic cells were determined. We developed an ordinary differential equation model of the infectious process that that produced results with a high degree of correlation with these experimental results. In order to simulate the effects of wild-type virus, the model was extended to incorporate published experimental data on the time trajectories of immune-antagonist production. These data showed that the RNA-editing mechanism utilized by the wild-type Nipah virus to produce immune antagonists leads to a delay in the production of the most effective immune antagonists, V and W. Model simulations indicated that this delay caused a disconnection between attenuation of the antiviral response and suppression of inflammation. While the antiviral cytokines were efficiently suppressed at early time points, some early inflammatory cytokine production occurred, which would be expected to increase vascular permeability and promote virus spread and pathogenesis. These results suggest that Nipah virus has evolved a unique immune-antagonist strategy that benefits from controlled expression of multiple antagonist proteins with various potencies.
Because G protein-coupled receptors (GPCRs) are numerous, widely expressed and involved in major physiological responses, they represent a relevant therapeutic target for drug discovery, particularly regarding pharmacological treatments of neurological disorders. Among the biological phenomena regulating receptor function, GPCR heteromerization is an important emerging area of interest and investigation. There is increasing evidence showing that heteromerization contributes to the pharmacological heterogeneity of GPCRs by modulating receptor ontogeny, activation and recycling. Although in many cases the physiological relevance of receptor heteromerization has not been fully established, the unique pharmacological and functional properties of heteromers are likely to lead to new strategies in clinical medicine. This review describes the main GPCR heteromers and their implications for major neurological disorders such as Parkinson’s disease, schizophrenia and addiction. A better understanding of molecular mechanisms underlying drug interactions related to the targeting of receptor heteromers could provide more specific and efficient therapeutic agents for the treatment of brain diseases.
Heteromerization; heteromer; GPCR; neurological disorder; drug discovery
The dendritic cell (DC) is a master regulator of immune responses. Pathogenic viruses subvert normal immune function in DCs through the expression of immune antagonists. Understanding how these antagonists interact with the host immune system requires knowledge of the underlying genetic regulatory network that operates during an uninhibited antiviral response. In order to isolate and identify this network, we studied DCs infected with Newcastle Disease Virus (NDV), which is able to stimulate innate immunity and DC maturation through activation of RIG-I signaling, but lacks the ability to evade the human interferon response. To analyze this experimental model, we developed a new approach integrating genome-wide expression kinetics and time-dependent promoter analysis. We found that the genetic program underlying the antiviral cell-state transition during the first 18-hours post-infection could be explained by a single convergent regulatory network. Gene expression changes were driven by a step-wise multi-factor cascading control mechanism, where the specific transcription factors controlling expression changed over time. Within this network, most individual genes are regulated by multiple factors, indicating robustness against virus-encoded immune evasion genes. In addition to effectively recapitulating current biological knowledge, we predicted, and validated experimentally, antiviral roles for several novel transcription factors. More generally, our results show how a genetic program can be temporally controlled through a single regulatory network to achieve the large-scale genetic reprogramming characteristic of cell state transitions.
Schizophrenia is one of the most common mental illnesses, with hereditary and environmental factors important for its etiology. All antipsychotics have in common a high affinity for monoaminergic receptors. Whereas hallucinations and delusions usually respond to typical (haloperidol-like) and atypical (clozapine-like) monoaminergic antipsychotics, their efficacy in improving negative symptoms and cognitive deficits remains inadequate. In addition, devastating side effects are a common characteristic of monoaminergic antipsychotics. Recent biochemical, preclinical and clinical findings support group II metabotropic glutamate receptors (mGluR2 and mGluR3) as a new approach to treat schizophrenia. This paper reviews the status of general knowledge of mGluR2 and mGluR3 in the psychopharmacology, genetics and neuropathology of schizophrenia
Schizophrenia; Antipsychotics; G protein-coupled receptors (GPCR); Serotonin receptors; 5-HT2A; Metabotropic glutamate receptors; mGluR2; mGluR3
There are many important clustering questions in computational biology for which no satisfactory method exists. Automated clustering algorithms, when applied to large, multidimensional datasets, such as flow cytometry data, prove unsatisfactory in terms of speed, problems with local minima or cluster shape bias. Model-based approaches are restricted by the assumptions of the fitting functions. Furthermore, model based clustering requires serial clustering for all cluster numbers within a user defined interval. The final cluster number is then selected by various criteria. These supervised serial clustering methods are time consuming and frequently different criteria result in different optimal cluster numbers. Various unsupervised heuristic approaches that have been developed such as affinity propagation are too expensive to be applied to datasets on the order of 106 points that are often generated by high throughput experiments.
To circumvent these limitations, we developed a new, unsupervised density contour clustering algorithm, called Misty Mountain, that is based on percolation theory and that efficiently analyzes large data sets. The approach can be envisioned as a progressive top-down removal of clouds covering a data histogram relief map to identify clusters by the appearance of statistically distinct peaks and ridges. This is a parallel clustering method that finds every cluster after analyzing only once the cross sections of the histogram. The overall run time for the composite steps of the algorithm increases linearly by the number of data points. The clustering of 106 data points in 2D data space takes place within about 15 seconds on a standard laptop PC. Comparison of the performance of this algorithm with other state of the art automated flow cytometry gating methods indicate that Misty Mountain provides substantial improvements in both run time and in the accuracy of cluster assignment.
Misty Mountain is fast, unbiased for cluster shape, identifies stable clusters and is robust to noise. It provides a useful, general solution for multidimensional clustering problems. We demonstrate its suitability for automated gating of flow cytometry data.
Dendritic cells are antigen-presenting cells that play an essential role in linking the innate and adaptive immune systems. Much research has focused on the signaling pathways triggered upon infection of dendritic cells by various pathogens. The high level of activity in the field makes it desirable to have a pathway-based resource to access the information in the literature. Current pathway diagrams lack either comprehensiveness, or an open-access editorial interface. Hence, there is a need for a dependable, expertly curated knowledgebase that integrates this information into a map of signaling networks.
We have built a detailed diagram of the dendritic cell signaling network, with the goal of providing researchers with a valuable resource and a facile method for community input. Network construction has relied on comprehensive review of the literature and regular updates. The diagram includes detailed depictions of pathways activated downstream of different pathogen recognition receptors such as Toll-like receptors, retinoic acid-inducible gene-I-like receptors, C-type lectin receptors and nucleotide-binding oligomerization domain-like receptors. Initially assembled using CellDesigner software, it provides an annotated graphical representation of interactions stored in Systems Biology Mark-up Language. The network, which comprises 249 nodes and 213 edges, has been web-published through the Biological Pathway Publisher software suite. Nodes are annotated with PubMed references and gene-related information, and linked to a public wiki, providing a discussion forum for updates and corrections. To gain more insight into regulatory patterns of dendritic cell signaling, we analyzed the network using graph-theory methods: bifan, feedforward and multi-input convergence motifs were enriched. This emphasis on activating control mechanisms is consonant with a network that subserves persistent and coordinated responses to pathogen detection.
This map represents a navigable aid for presenting a consensus view of the current knowledge on dendritic cell signaling that can be continuously improved through contributions of research community experts. Because the map is available in a machine readable format, it can be edited and may assist researchers in data analysis. Furthermore, the availability of a comprehensive knowledgebase might help further research in this area such as vaccine development. The dendritic cell signaling knowledgebase is accessible at http://tsb.mssm.edu/pathwayPublisher/DC_pathway/DC_pathway_index.html.
Improving the ability to reverse engineer biochemical networks is a major goal of systems biology. Lesions in signaling networks lead to alterations in gene expression, which in principle should allow network reconstruction. However, the information about the activity levels of signaling proteins conveyed in overall gene expression is limited by the complexity of gene expression dynamics and of regulatory network topology. Two observations provide the basis for overcoming this limitation: a. genes induced without de-novo protein synthesis (early genes) show a linear accumulation of product in the first hour after the change in the cell's state; b. The signaling components in the network largely function in the linear range of their stimulus-response curves. Therefore, unlike most genes or most time points, expression profiles of early genes at an early time point provide direct biochemical assays that represent the activity levels of upstream signaling components. Such expression data provide the basis for an efficient algorithm (Plato's Cave algorithm; PLACA) to reverse engineer functional signaling networks. Unlike conventional reverse engineering algorithms that use steady state values, PLACA uses stimulated early gene expression measurements associated with systematic perturbations of signaling components, without measuring the signaling components themselves. Besides the reverse engineered network, PLACA also identifies the genes detecting the functional interaction, thereby facilitating validation of the predicted functional network. Using simulated datasets, the algorithm is shown to be robust to experimental noise. Using experimental data obtained from gonadotropes, PLACA reverse engineered the interaction network of six perturbed signaling components. The network recapitulated many known interactions and identified novel functional interactions that were validated by further experiment. PLACA uses the results of experiments that are feasible for any signaling network to predict the functional topology of the network and to identify novel relationships.
Elucidating the biochemical interactions in living cells is essential to understanding their behavior under various external conditions. Some of these interactions occur between signaling components with many active states, and their activity levels may be difficult to measure directly. However, most methods to reverse engineer interaction networks rely on measuring gene activity at steady state under various cellular stimuli. Such gene measurements therefore ignore the intermediate effects of signaling components, and cannot reliably convey the interactions between the signaling components themselves. We propose using the changes in activity of early genes shortly after the stimulus to infer the functional interactions between the unmeasured signaling components. The change in expression in such genes at these times is directly and linearly affected by the signaling components, since there is insufficient time for other genes to be transcribed and interfere with the early genes' expression. We present an algorithm that uses such measurements to reverse engineer the functional interaction network between signaling components, and also provides a means for testing these predictions. The algorithm therefore uses feasible experiments to reconstruct functional networks. We applied the algorithm to experimental measurements and uncovered known interactions, as well as novel interactions that were then confirmed experimentally.
Gonadotropin-releasing hormone (GnRH) regulates biosythesis in the pituitary gonadotrope via a complex signaling and gene network. Small non-coding microRNAs (miRNA) can play important roles in gene expression. We investigated the microtranscriptome in the mouse LβT2 gonadotrope cell line using microarray, single molecule coincidence detection assays, hairpin real time PCR and LNA (locked nucleic acid) primer-extension PCR. Expression of nearly 200 miRNAs were detected by array and a panel of 101 hairpin real-time PCR assays. Within this broad family of expressed miRNAs, GnRH induced upregulation of two miRNA products of the same primary transcript, miR-132 and miR-212, a result confirmed by single molecule, hairpin and LNA assays. Induction peaked 6 hours after GnRH exposure and showed no significant frequency sensitivity. Bioinformatics analysis was used to predict potential targets of each of these GnRH-regulated miRNAs. These findings suggest the importance of the microtranscriptome in gene control in the gonadotrope and implicate miR-132 and miR-212 in the regulation of GnRH-stimulated biosynthetic response.
mouse; cell line; gonadotrope; microRNA; reproduction; pituitary
The psychosis associated with schizophrenia is characterized by alterations in sensory processing and perception1,2. Some antipsychotic drugs were identified by their high affinity for serotonin 5-HT2A receptors (2AR)3,4. Drugs that interact with metabotropic glutamate receptors (mGluR) also show potential for the treatment of schizophrenia5-7. The effects of hallucinogenic drugs, such as psilocybin and lysergic acid diethylamide (LSD), require the 2AR8-10 and resemble some of the core symptoms of schizophrenia10-12. Here we show that the mGluR2 interacts via specific transmembrane helix domains with the 2AR, a member of an unrelated G protein-coupled receptor (GPCR) family, to form functional complexes in brain cortex. The 2AR/mGluR2 complex triggers unique cellular responses when targeted by hallucinogenic drugs, and activation of mGluR2 abolishes hallucinogen specific signalling and behavioural responses. In postmortem human brain from untreated schizophrenic subjects, the 2AR is up-regulated and the mGluR2 is down-regulated, a pattern that could predispose to psychosis. These regulatory changes suggest that the 2AR/mGluR2 complex may be involved in the altered cortical processes of schizophrenia, and represents a promising new target for the treatment of psychosis.
A problem of cell-to-cell communication by diffusible ligands is analyzed for the case when cells are distributed in three dimensions and diffusible ligands are secreted by cells and reversibly bind to cell surface receptors. Following its binding to a receptor, the ligand can either dissociate and be released back in the medium or be absorbed by the cell in a process that is called internalization. Using an effective medium approximation, we derive analytical expressions that characterize the time and length scales associated with the ligand trajectories leading to internalization. We discuss the applicability of our approximation and illustrate the application of our results to a specific cellular system.
Benjamini and Hochberg (1995) proposed the false discovery rate (FDR) as an alternative to the familywise error rate (FWER) in multiple testing problems. Since then, researchers have been increasingly interested in developing methodologies for controlling the FDR under different model assumptions. In a later paper, Benjamini and Yekutieli (2001) developed a conservative step-up procedure controlling the FDR without relying on the assumption that the test statistics are independent.
In this paper, we develop a new step-down procedure aiming to control the FDR. It incorporates dependence information as in the FWER controlling step-down procedure given by Westfall and Young (1993). This new procedure has three versions: lFDR, eFDR and hFDR. Using simulations of independent and dependent data, we observe that the lFDR is too optimistic for controlling the FDR; the hFDR is very conservative; and the eFDR a) seems to control the FDR for the hypotheses of interest, and b) suggests the number of false null hypotheses. The most conservative procedure, hFDR, is proved to control the FDR for finite samples under the subset pivotality condition and under the assumption that joint distribution of statistics from true nulls is independent of the joint distribution of statistics from false nulls.
Adjusted p-value; false discovery rate; familywise error rate; microarray; multiple testing; resampling
Influenza virus produces a protein, NS1, that inhibits infected cells from releasing type I interferon (IFN) and blocks maturation of conventional dendritic cells (DCs). As a result, influenza virus is a poor activator of both mouse and human DCs in vitro. However, in vivo a strong immune response to virus infection is generated in both species, suggesting that other factors may contribute to the maturation of DCs in vivo. It is likely that the environment in which a DC encounters a virus would contain multiple pro-inflammatory molecules, including type I IFN. Type I IFN is a critical component of the viral immune response that initiates an antiviral state in cells, primarily by triggering a broad transcriptional program that interferes with the ability of virus to establish infection in the cell. In this study, we have examined the activation profiles of both conventional and plasmacytoid dendritic cells (cDCs and pDCs) in response to an influenza virus infection in the context of a type I IFN-containing environment. We found that both cDCs and pDCs demonstrate a greater activation response to influenza virus when pre-exposed to IFN-β (IFN priming); although, the priming kinetics are different in these two cell types. This strongly suggests that type I IFN functions not only to reduce viral replication in these immune cells, but also to promote greater DC activation during influenza virus infections.
Influenza infection leads to a serious respiratory infection of the lung epithelium. Lying directly below the epithelial cells are immune system sentinels known as dendritic cells. These cells interact with the virus and carry parts of the virus to draining lymph nodes to activate killer T cells. In order to effectively carry out this function, DCs must perceive the presence of a virus using receptors specially adapted for this function. However, when DCs are mixed with influenza virus in the laboratory, no activation occurs because the virus produces a protein called NS1 that blocks the receptors. Yet, patients infected with influenza virus develop a strong adaptive response that leads to recovery from infection. This observation suggests that additional factors must be present that contribute to the activation of the DCs. The most likely contributor is type I interferon, a ubiquitous protein released from many cells upon exposure to virus. In this study, we mixed influenza virus with DCs in the presence of type I interferon and found that this greatly enhanced their activation. Treatment with interferon allowed the DC to bypass the block in activation mediated by the influenza NS1 protein. Our data suggest that the production of type I interferon within an infected patient may endow the DCs with the ability to fully respond to influenza virus.