NF-κB is a key transcription factor that regulates innate immune response. Its activity is tightly controlled by numerous feedback loops, including two negative loops mediated by NF-κB inducible inhibitors, IκBα and A20, which assure oscillatory responses, and by positive feedback loops arising due to the paracrine and autocrine regulation via TNFα, IL-1 and other cytokines. We study the NF-κB system of interlinked negative and positive feedback loops, combining bifurcation analysis of the deterministic approximation with stochastic numerical modeling. Positive feedback assures the existence of limit cycle oscillations in unstimulated wild-type cells and introduces bistability in A20-deficient cells. We demonstrated that cells of significant autocrine potential, i.e., cells characterized by high secretion of TNFα and its receptor TNFR1, may exhibit sustained cytoplasmic–nuclear NF-κB oscillations which start spontaneously due to stochastic fluctuations. In A20-deficient cells even a small TNFα expression rate qualitatively influences system kinetics, leading to long-lasting NF-κB activation in response to a short-pulsed TNFα stimulation. As a consequence, cells with impaired A20 expression or increased TNFα secretion rate are expected to have elevated NF-κB activity even in the absence of stimulation. This may lead to chronic inflammation and promote cancer due to the persistent activation of antiapoptotic genes induced by NF-κB. There is growing evidence that A20 mutations correlate with several types of lymphomas and elevated TNFα secretion is characteristic of many cancers. Interestingly, A20 loss or dysfunction also leaves the organism vulnerable to septic shock and massive apoptosis triggered by the uncontrolled TNFα secretion, which at high levels overcomes the antiapoptotic action of NF-κB. It is thus tempting to speculate that some cancers of deregulated NF-κB signaling may be prone to the pathogen-induced apoptosis. Innate immunity forms the first line of defense against pathogens. In the first phase, cells detect pathogens with their membrane and cytoplasmic receptors. This leads to the activation of transcription factors from the NF-κB, IRF and AP-1 families. These factors jointly regulate the activity of several hundred genes responsible for inflammation, antiviral protection, proliferation and apoptosis. In particular, they induce the production of pro-inflammatory cytokines like IL-1, TNFα, as well as IFN-α and IFN-ß. Secretion of these cytokines leads to the second phase of the cellular innate immune response in cells that have not yet encountered the pathogen. The cytokine-activated cells may themselves produce and secrete the same cytokines leading to the spread of paracrine signaling NF-κB regulates numerous genes important for pathogen- or cytokine-induced inflammation, immune response, cell proliferation and survival  and TRIF-dependent pathways (late phase), reviewed in Finally, we should mention that there exist other cytokines, in particular IL-1, which are NF-κB-responsive The modeling studies of NF-κB system started in 2002, by the study of oscillations of NF-κB–IκBα feedback loop (damped by the presence of IκBϵ and IκBß isoforms) by Hoffmann, Levchenko and colleagues Nuclear NF-κB activity is controlled by two interlinked negative feedback loops, one mediated by IκB proteins: IκBα and IκB, the other mediated by A20 . The inht  =  1 hour regardless of the TNFα dose, and shows a low plateau which extends to beyond 10 hours.TNFα is one of NF-κB-responsive genes, and its expression level is cell type-dependent. 3T3 cells, which we studied experimentally in this work, exhibit a relatively low TNFα expression, reaching 20 mRNA molecules (on average) per cell at the highest TNFα stimulation dose, Interestingly, we found that a small fraction (about 3%) of 3T3 cells secrete TNFα without any stimulation as shown by ELISpot assay, We analyze the evolution of the NF-κB system in the absence of any stimulation as well as its responses to the imposed concentrations of TNFα, considering both tonic and pulsed stimulation. In the whole analysis we account for intracellular and extracellular TNFα degradation, with degradation half-time 1 h (degradation rate of s), consistent with our earlier estimations atlab and BioNetGen . Trajectories obtained in stochastic simulations are interpreted as single cell trajectories. These trajectories, as we will see, may switch between the attractors of the deterministic approximation or may exhibit the excitatory behavior. Stochastic simulations will be used to determine the fraction of responding cells as a function of the TNFα dose. Averages over a large number of stochastic trajectories will be used to fit the model to the population data. As demonstrated before, in non-linear systems, the average over a large number of stochastic trajectories may qualitatively differ from the trajectory obtained in the deterministic approximation, and thus the deterministic approximation of the process may not satisfactorily reproduce population data In the stochastic approach, chemical reactions are simulated using the direct Stochastic Simulation Algorithm The analysis performed in our previous study Intrinsic noise in the system results mainly from the discrete regulation of TNFR1 receptors activity and activation of A20, IκBα, and TNFα genes, see The presence of the negative feedback loop together with the delay introduced by the mRNA transcription, protein translation and cytoplasmic to nuclear transport induces oscillatory responses to tonic TNFα stimulation. One can thus expect that cells which produce and secrete TNFα can exhibit tonic oscillations even without any external stimulation, being constantly activated by TNFα they secrete. In the bifurcation analysis , Fig. S2In A20 cells the negative feedback is disturbed. Since A20 promotes transformation from active IKK (IKK) to inactive IKK (IKK), lack of A20 results in the prolonged IKK activity. This in turn prevents the accumulation of IκBα protein and results in the persistent nuclear NF-κB occupancy. As a result, in response to the tonic TNFα stimulation, A20-deficient cells do not exhibit limit cycle oscillation, but reach the active steady state, characterized by a high IKK activity, a high level of nuclear NF-κB and correspondingly high level of IκBα transcript, but low level of IκBα protein, which is constantly degraded due to the high IKK activity. One can thus expect that A20 cells which synthesize and secrete TNFα may remain in the active state, without external stimulation. In fact, the bifurcation analysis  demonstrThe bifurcation analysis of the deterministic model demonstrated that due to the positive feedback regulation, even in the absence of any external stimulation, WT cells exhibit limit cycle oscillations while A20-deficient cells exhibit persistent activation, provided that TNFα mRNA synthesis rate is sufficiently large. The A20 cells were found to be much more sensitive, i.e., they can remain active for 10 times lower TNFα synthesis rate than needed for WT cells activation. In addition, we found that both A20 and WT cells exhibit bistability: in WT cells it is manifested by the coexistence of the stable limit cycle and the stable steady state. One can thus expect that real (noisy) cells will exhibit transitions between the basins of attraction of recurrent solutions found in the deterministic analysis.In In As already said, A20-deficient cells are more sensitive to TNFα, and they are activated at a much smaller TNFα transcription coefficient . This property is even more evident when the stochastic system is analyzed. For the transitions to the active state are very infrequent , but forTurner et al. The single cell trajectories obtained in numerical simulations  are in pThe low dose (≤30 pg/ml) responses have a purely stochastic nature. They are not observed in the deterministic simulations (thick red line), and are invisible at the population level due to the asynchrony of individual cells. The average activation time and its variance increases with decreasing TNFα dose, which suggests that the first activation has a stochastic character. As predicted and demonstrated recently, massive NF-κB translocation may follow binding of single TNFα molecules to TNFR1 receptors As found by Turner et al., the fraction of activated cells in first 300 minutes decreases with TNFα dose, but even for zero doses the activated cell fraction is about 20% In their seminal work, Lee et al. observed that A20 MEFs (in contrast to WT cells) do not exhibit oscillations to the tonic TNFα stimulation In We investigated theoretically and computationally the effect of autocrine TNFα signaling on NF-κB regulation. NF-κB activity is regulated by two interlinked negative feedback loops. The first loop involves NF-κB responsive inhibitors: IκBα and IκB, which directly bind to NF-κB and sequester it in the cytoplasm. The second loop is mediated by another NF-κB strongly responsive protein, A20, which attenuates the IKK activity. Without A20 expression, IKK retains its activity, which leads to the rapid degradation of the newly synthesized IκBα and destroys the NF-κB–IκBα feedback loop. The autocrine positive feedback loop arises in cell lines that are characterized by a sufficiently high TNFR1 expression and TNFα secretion. As demonstrated in this study, the positive feedback qualitatively changes the system dynamics. It may lead to long-lasting NF-κB oscillations in WT cells and persistent NF-κB activity in A20-deficient cells, which were found to be very prone to activation. The approach proposed in this study combined deterministic and stochastic modeling.Bifurcation analysis was performed for WT and A20-deficient cells. In both cases, TNFα mRNA synthesis rate was chosen as a bifurcation parameter . Analysis of WT cells shown in stochastic resonance, which in the broad definition refers to the case when noise has a positive role in the signal-processing context By analyzing the stochastic model we demonstrated that noise, arising mostly at the level of gene regulation, enables switching between the stable steady state and limit cycle in WT cells, and between inactive and active steady state in A20-deficient cells . InteresIntroduction of positive feedback enabled us to reproduce the noise-triggered oscillations observed by Turner et al. in unstimulated cells, as well as earlier experiments by Werner et al. showing prolonged NF-κB activation in response to the pulsed TNFα stimulation in A20-deficient MEFs There is a bulk of evidence that the loss or dysfunction of A20 as well as the other inhibitory DUBase, named Cyld, promote inflammatory diseases and cancer Click here for additional data file.Material S1atlab code of the model for performing deterministic simulations. (ZIP-archived directory containing Matlab scripts and a ReadMe file).M(ZIP)Click here for additional data file.Material S2ioNetGen code of the model for performing both deterministic and stochastic simulations. (ZIP-archived directory containing a BNGL model file and a ReadMe file).B(ZIP)Click here for additional data file.Material S3atlab/Matcont code for performing bifurcation analysis. .M(ZIP)Click here for additional data file.


Activation of the NF-κB transcription factor and its associated gene expression in microglia is a key component in the response to brain injury. Its activation is dynamic and is part of a network of biochemical species with multiple feedback regulatory mechanisms. Mathematical modeling, which has been instrumental for understanding the NF-κB response in other cell types, offers a valuable tool to investigate the regulation of NF-κB activation in microglia at a systems level.We quantify the dynamic response of NF-κB activation and activation of the upstream kinase IKK using ELISA measurements of a microglial cell line following treatment with the pro-inflammatory cytokine TNFα. A new mathematical model is developed based on these data sets using a modular procedure that exploits the feedback structure of the network. We show that the new model requires previously unmodeled dynamics involved in the stimulus-induced degradation of the inhibitor IκBα in order to properly describe microglial NF-κB activation in a statistically consistent manner. This suggests a more prominent role for the ubiquitin-proteasome system in regulating the activation of NF-κB to inflammatory stimuli. We also find that the introduction of nonlinearities in the kinetics of IKK activation and inactivation is essential for proper characterization of transient IKK activity and corresponds to known biological mechanisms. Numerical analyses of the model highlight key regulators of the microglial NF-κB response, as well as those governing IKK activation. Results illustrate the dynamic regulatory mechanisms and the robust yet fragile nature of the negative feedback regulated network.We have developed a new mathematical model that incorporates previously unmodeled dynamics to characterize the dynamic response of the NF-κB signaling network in microglia. This model is the first of its kind for microglia and provides a tool for the quantitative, systems level study the dynamic cellular response to inflammatory stimuli. The nuclear factor-κB (NF-κB) transcription factor is ubiquitously expressed in mamallian cells and regulates the expression of many target genes. In the nervous system NF-κB is known to play a key role in the immune and injury responses and in governing normal brain function . During Members of the NF-κB family of transcription factors are found in their inactive state as dimers bound to their IkB inhibitor proteins. Upon stimulation by a diverse set of stimuli, NF-κB is freed from its inhibitor to coordinate gene expression in a highly specific and tightly regulated manner. The IκBα inhibitor and p65(RelA):p50 NF-κB heterodimer are the most extensively studied members of their respective families, and their response to extracellular stimuli illustrates the canonical pathway of NF-κB activation Figure .In the canonical pathway, binding of extracellular TNFα trimers to TNFR1 receptors at the cell membrane initiates NF-κB activation. The ligand-receptor complex interacts with several adapter proteins, including TNF receptor-associated factor 2 (TRAF2) and receptor-interacting protein-1 (RIP1), which are essential for recruitment and activation of the IκB kinase complex (IKK) . The IKKde novo IκBα and A20 proteins. Newly synthesized IκBα sequesters NF-κB from the nucleus to inhibit further transcriptional activity, forming a strong negative feedback regulatory mechanism. The synthesis of A20 proteins creates a second negative feedback loop by regulating the ubiquitination of adapter proteins responsible for activating the IKK complex, thus inhibiting further NF-κB activation [NF-κB is released following proteasomal degradation of IκBα  and trantivation . Many chGiven the dynamic nature of NF-κB signaling and its regulation involving multiple feedback loops, it is necessary to consider the network as a whole when studying this system. The seminal work by Hoffmann and colleagues , in whicHere we develop a mathematical model to describe NF-κB signaling in microglia. Beginning with a recently published model structure shown to be capable of predicting NF-κB signaling in other cell types , we atteTo characterize the dynamics of canonical NF-κB activation in microglia, cells from the microglial cell line BV2 were cultured and treated with 10 ng/ml TNFα. Whole cell extracts were collected in triplicate over a time course following stimulation in five identical experiments conducted on different days. ELISA measurements of NF-κB p65 DNA binding activity show that NF-κB activation in BV2 microglia is strongly induced by TNFα Figure . Five miTo better characterize the inflammatory response in microglia we additionally examined the activation of the upstream IκB kinase (IKK) experimentally. The time course of IKK activity was measured for the first 30 min following 10 ng/ml TNFα treatment in three identical experiments. IKK is rapidly activated, reaching peak levels near 5 min. By 10 min IKK activity sharply drops to below half-maximal levels and gradually declines to near basal levels over the next 20 min Figure . This trNext we sought to quantitatively describe microglial NF-κB activation using a mathematical model. While a number of mathematical models for NF-κB have been published in recent years (reviewed in ), our prWe first attempted to identify parameters for the existing model structure to fit the experimental NF-κB and IKK activation profiles of microglia. An optimization-based parameter estimation algorithm was run using many randomly selected parameter values from the parameter space as initial guesses. However, no parameter sets were found that matched microglial IKK and NF-κB activity. In particular, the model was unable to qualitatively reproduce the rapid induction and attenuation of IKK activity observed in microglia for any of the parameter sets tested, and NF-κB activation was predicted to occur more rapidly than the 5 min delay observed in Figure Sensitivity analyses were performed on the model to quantify the relative contributions of each of the system parameters to the concentration of free NF-κB during the first 10 min given the large mismatches between the model and data in this interval. Only seven of the original 26 system parameters have appreciable effects on NF-κB activity during this time based on their time-averaged sensitivity scores . The results showed that with the original model structure, 100% of the estimated parameter sets had P-values < 10-7 . Numerical investigation showed this more oscillatory behavior predicted by the integrated model was due to small changes in the later activation profile of IKK predicted by the upstream model, which had been assumed to remain at a constant, low level when developing the isolated downstream signaling module. After increasing the rate of IκBα nuclear import and re-estimating the A20 feedback and IKK recycling rates, the newly developed model was able to provide good agreement with the data, with fitting errors of only 0.34 for NF-κB (P = 0.013) and 0.43 for IKK (P = 0.291)  Figure  and 4D.Given that the model was developed using a limited set of data from IKK and NF-κB activation, we next sought to test its ability to predict the dynamics of other model species for which no information was used during parameter estimation. The model was first simulated to obtain the levels of total cellular IκBα protein following TNFα stimulus Figure . The modTo test this prediction experimentally, BV2 cells were again treated with 10 ng/ml TNFα, and levels of total cellular IκBα were measured at several time points after treatment using ELISA. The results of the experiments were normalized with respect to the initial quantities and compared with the simulation predictions Figure . The expThe model was next analyzed using sensitivity analysis to gain deeper insight into how the different components of the system interact to regulate the dynamic NF-κB response in microglia. Sensitivity analyses of the NF-κB regulatory network have been performed previously -33, and The normalized sensitivity coefficients for NF-κB activation were solved and plotted as heat maps to illustrate the dynamic relationship between the signaling components and the system response Figure .ki1 and ke1) for which the sensitivity scores remain high throughout the entire response, NF-κB activity exhibits highly dynamic sensitivity with respect to most other parameters. In other words, there is a strong temporal component to the regulation of NF-κB activity, where variations in different parameters can exhibit great influence over certain phases of activity but have only marginal effects on activation during other time intervals , but also moderately or highly sensitive to others (dark red and blue) Figure , consistkp) also is among the most significant parameters in the attenuation of NF-κB activity. While NF-κB activity is at its lowest levels between 60-90 min, the stability of the remaining IκBα transcripts and the induced phosphorylation, ubiquitination and degradation of IκBα exert more influence on free NF-κB levels. The second peak of NF-κB activity is regulated greatly by the nuclear import rate of free IκBα, as evidenced by the high sensitivity of ki3a only during this time period. Feedback from IκBα again has highly significant contributions to the dynamics of the second peak, with induced synthesis of IκBα and its affinity to unbound IκBα having very high sensitivities.However, the system shows extreme sensitivity to rates controlling the inner and outer feedback loops. The system is very senstive to the rates for induced IκBα synthesis and its association with NF-κB during a time period coinciding with the decline of the first peak, with synthesis and binding rates negatively affecting NF-κB activation. The rate of conversion of inactivated IKK back to native IKK (kp) to regulate this response, made clear by the opposite signs of sensitivity values throughout the response.The NF-κB response is also highly sensitive to the outer A20 feedback loop in a time-dependent manner. The rates for IKK inactivation by A20 significantly affect the termination of initial NF-κB activity as well as the second phase of activity. This effect is actuated through inhibition of the activation of IKK that has recently been converted from the inactive form and made available for activation; feedback from A20 inhibition of IKK activation has a less substantial role on the dynamics in the model. The outer feedback parameters governing A20 act in opposition to the IKK recycling rate (ka) and inactivation rate parameters controlling the magnitude (ki) and the dissociation constant (kmmi). Twenty minutes after the initial stimulus when IKK is mostly in its inactivated form, the response becomes highly sensitive to the IKK recycling rate and to A20 synthesis, degradation, and negative feedback rates which constitute the outer feedback loop. The late phase IKK response is also relatively sensitive to the rates governing IκBα induced synthesis and transcript stability, and to a lesser extent to its induced degradation of IκBα protein, which indicates that the dynamics of IKK are still highly coupled to the inner feedback loop of IκBα despite the absence of direct crosstalk reactions.Although many features of the NF-κB response have been studied previously using sensitivity analysis, little attention has been paid to the dynamic sensitivities of IKK. We therefore assessed parameter sensitivities of IKK activation in the same way as just described for NF-κB Figure . IKK actki1 and ke1), a result which is unexpected given the sensitivity analysis results in which these rates were among the most sensitive. Large changes in these parameters alter the level of damping in the second phase of the response, but the initial peak remains nearly identical  molecules to phosphorylated substrate to form a polyubiquitin chain able to be recognized by the proteasome in a process lasting only seconds after the first Ub molecule has been added [Ubiquitination of IκBα is typically thought to occur almost instantaneously following its phosphorylation by IKK . Consisten added . Howeveren added  also demen added . A smallen added . Others en added , allowinBesides potentially less efficient recognition of IκBα by βTrCP, another possibility is that the normally rapid polyubiquitination of IκBα occurs less efficiently in microglia due to smaller quantities of Nedd8-ylated Cul-1 in the SCF complex. Conjugation of only a small fraction of Cul-1 with Nedd8 greatly increases the efficiency of ubiquitination of IκBα without affecting the association between βTrCP and phosphorylated IκBα  due to fThe new model structure indicates a more prominent role of the ubiquitin-proteasome system in regulating NF-κB activation dynamics, which merits consideration of what are its functional implications on how microglia respond to inflammatory stimuli. Analyses of the model show that the ubiquitin-related parameters have large effects on the initial activation of NF-κB and a relatively smaller role in regulating later dynamics Figure . ParametSubstantial modifications to the upstream signaling pathway are required to fit the new model to the microglial IKK activation data. The TNFα-induced IKK activation and inactivation reaction kinetics are changed from first order linear mass-action rates to nonlinear Hill equations in the new model. We note that the new model differs from  in that In contrast to the parameters governing initial transient IKK activity, our model analyses indicate that the signaling components which regulate later phase IKK activation also exert significant control over NF-κB activation  supplemented with 8% Fetal Bovine Serum , Penicillin , and Streptomycin . Cells were passaged every four days and were used between passages 10-20.5 cells per well in six well plates 36 hrs prior to treatment with 10 ng/ml recombinant mouse TNFα . Cells were then harvested for protein at the indicated time points with Phosphosafe Extraction buffer  supplemented with 0.01 volume Protease Inhibitor cocktail  and 5 mM DTT before use. Protein concentration was measured using the Coomassie Plus assay . 25 μg total protein from each sample was transferred to a pre-chilled Eppendorf tube and brought to 25 μl with complete lysis buffer. These aliquots were stored at -80°C until use for activated NF-κB p65 measurement. Active NF-κB was measured using the Trans AM NFκB p65 Transcription Factor Assay Kit  according to the manufacturer's instructions. 20 μg total protein was used for each sample. Three cultures were assayed for each group. Standards were prepared from recombinant p65 .BV2 cells were seeded at 4 × 102 mix from the kit. Beads were then centrifuged at 13,000 rpm for 5 min at 4°C, and 60 μl of supernatant was transferred to a well of the glutathione coated 96-well plate provided with the K-LISA kit. Two-fold serial dilutions of the recombinant IKKβ provided with the kit were run as standards according to the kit instructions, but omitting IKK inhibitor. In addition the post-immunoprecipitation supernatant was concentrated 20 × and run to demonstrate that all IKK activity was depleted from the supernatant. In all cases this sample showed no IKK activity. The plate was incubated 30 min at 30°C to allow the GST-IκBα to bind, and subsequent processing was done according to the vendor's instructions. Final concentrations measured were normalized to the total amount of protein used in a given experiment.IKK activity was measured by immunoprecipitation of IKK trimers, followed by a kinase assay/ELISA using a modification of the K-LISA IKKβ Inhibitor Screening Kit . A total of 400 μg protein from each sample was incubated at 4°C 5 hrs with 5 μg goat anti-IKKγ antibody M18  with shaking, followed by overnight incubation with shaking with 50 μl 2 × diluted Protein G-Sepharose  previously washed in complete lysis buffer. Beads were then centrifuged for 5 min at 13,000 rpm 4°C, the post-immunoprecipitation supernatant removed, and beads were washed in the 1 × kinase assay buffer from the K-LISA kit. Beads were then incubated with shaking in an incubator for 1 h at 30°C in 75 μl 1 × kinase assay buffer containing 150 ng GST-IκBα and 1 × ATP/MgCl5 cells/ml on day one and treated with 10 ng/ml TNFα on day three. Cell lysates were prepared and ELISA analysis performed following the manufacturer's instructions. Total protein concentrations were measured using the BCA method; 275 μg total protein was used to measure total IκBα at each time point. The experiments were repeated 3 times.Total IκBα measurements from TNFα treated BV2 cells were performed using the PathScan Total IκBα Sandwich ELISA kit from Cell Signaling (#7360). BV2 cells from passage 14-18 were seeded at 4 × 10Data from each experiment for NF-κB and IKK was normalized relative to the maximum mean level of activity during that particular experiment to account for variations in optical absorbance readings between experiments. The normalized data were then averaged to produce the ensemble average data set used for data fitting.interp1 function in Matlab. Similarly, nuclear NF-κB was interpolated in an identical procedure from a simulated curve for development of the upstream module. Further details about the mathematical modeling and tables listing all model species, reactions and parameters can be found in Additional file The model, based on the ordinary differential equation two-feedback model in , was dev5), and so it is assumed that the sample average from this large collection of cells is normally distributed with mean equal to the population average, but that the standard deviation can vary with time. Individual samples are assumed to be independent across experiment replicates and identically distributed with regard to their respective time points. This is justified since all samples are collected from independent cell populations.The agreement between model simulations and experimental data was assessed using an approach based on Fisher's combined probability test , which iθ, to the sample mean from i nexperimental samples collected at time it. The null hypothesis that the two are consistent is rejected at a significance level α if the p-value corresponding to the ith t-statistic is ip< α.Under these assumptions, a two-sided one sample t-test can be used to compare the population mean from the model simulations corresponding to a specific set of parameters, i nexperimental samples come from cell populations whose time evolution of the population average is given by the kinetic model. The test statistic for Fisher's method is computed by combining each independent test as follows:Fisher's method combines the information from the individual test results to test the shared null hypothesis that all the i pare the p-values from the t-tests at n time points. Under the null hypothesis, χ2F follows a chi-square distribution with 2n degrees of freedom. The shared null hypothesis is rejected at a significance level αF confidence if pF< α, thus giving a statistical basis upon which a candidate parameter set can be rejected or retained.where log denotes the natural logarithm, and Parameter values were estimated by minimizing the a cost function based on the goodness of fit between model and data. Two objective functions were used: one which computed the normalized sum of squares error (SSE),θ, i,θ), y(tand observed data points obs(ti)y, where i indexes the n time points at which data was collected. A second objective function used the chi-square test statistic computed from Fisher's method (χ2F), an adaptation of the moment-matching algorithm proposed in [fmincon constrained minimization algorithm from the Matlab Optimization Toolbox (MathWorks). Lower and upper bounds for the parameter values were taken from the available literature, as specified in Additional file between the model simulations at parameter set posed in . The simThe normalized first order sensitivity coefficients of the system,i yis a system output and θj is the jth rate parameter, were solved using the CVODES forward sensitivity solver from the SUNDIALS 2.4.0 software suite . Sensitivity scores were also assigned based on the time-averaged integral of the normalized sensitivity magnitudes,where The authors declare that they have no competing interests.MK, RGG and PWS contributed to the design of experiments, PWS developed the mathematical model and performed the simulations, JFE and XS perfomed the experiments with BV2 cells, PWS, RGG and MK contributed to writing the manuscript. All authors read and approved the final manuscript.Supplementary text and figures. The pdf contains supplementary text describing development of the mathematical model; Tables S1-S3 which list the model species, reactions, and rate parameters; and Figures S1-S8 that provide more detailed simulation results.Click here for fileSBML model of microglial NF-κB activation. This .xml file is an SBML translation of the mathematical model originally developed in Matlab (MathWorks). Simulations correspond to the response of microglia cells following treatment with 10 ng/ml TNFα.Click here for file


A large body of functional and epidemiological evidence have previously illustrated the impact of specific MHC class I subtypes on clinical outcome during HIV-1 infection, and these observations have recently been re-iterated in genome wide association studies (GWAS). Yet because of the complexities surrounding GWAS-based approaches and the lack of knowledge relating to the identity of rarer single nucleotide polymorphism (SNP) variants, it has proved difficult to discover independent causal variants associated with favourable immune control. This is especially true of the candidate variants within the HLA region where many of the recently proposed disease influencing SNPs appear to reflect linkage with ‘protective’ MHC class I alleles. Yet causal MHC-linked SNPs may exist but remain overlooked owing to the complexities associated with their identification. Here we focus on the ancestral TNFα promoter −237A variant (rs361525), shown historically to be in complete linkage disequilibrium with the ‘protective’ HLA-B*5701 allele. Many of the ancestral SNPs within the extended TNFα promoter have been associated with both autoimmune conditions and disease outcomes, however, the direct role of these variants on TNFα expression remains controversial. Yet, because of the important role played by TNFα in HIV-1 infection, and given the proximity of the −237 SNP to the core promoter, its location within a putative repressor region previously characterized in mice, and its disruption of a methylation-susceptible CpG dinucleotide motif, we chose to carefully evaluate its impact on TNFα production. Using a variety of approaches we now demonstrate that carriage of the A SNP is associated with lower TNFα production, via a mechanism not readily explained by promoter methylation nor the binding of transcription factors or repressors. We propose that the −237A variant could represent a minor causal SNP that additionally contributes to the HLA-B*5701-mediated ‘protective’ effect during HIV-1 infection. As demonstrated by both epidemiological findings and in functional studies the MHC locus represents a crucial host factor that strongly impacts the clinical course of HIV-1 infection Bf, C4A, C4B, and TNFα/β related-polymorphisms), and is also linked to HLA-B*5701 in the absence of HLA haplotype-defining genes Given the strong association of HLA-B*5701 with sustained viral control and prolonged AIDS-free survival, the impact of SNPs in strong linkage with this allele warrants further investigation. Of note are TNFα promoter SNPs, which are in linkage disequilibrium (LD) with a number of ancient HLA haplotypes, and have been implicated both positively and negatively with disease outcomes in the setting of various viral/bacterial infections and autoimmune conditions. Of particular interest is the TNFα promoter −237G to A SNP (rs361525) which is in complete LD with the ‘protective’ MHC class I HLA-B*5701 subtype. This SNP maps to the ancestral 57.1 haplotype  and co-activators; together, these form a multi-component nucleosome (the TNFα enhanceosome) of which the exact composition is dictated by the nature of the inducing stimulus in vivoTNFα is an important pleiotropic pro-inflammatory cytokine, which plays a fundamental role in both innate and adaptive immunity. Yet excessive TNFα is associated with various autoimmune, inflammatory and infectious pathologies, hence its production is tightly regulated Firstly, we questioned if the single G to A polymorphism at position −237 directly affected the activity of the TNFα promoter, and using a luciferase reporter system we evaluated the impact of both promoter polymorphisms on luciferase gene expression. This approach was chosen to remove any potential interference from post-transcriptional control mechanisms targeting the TNFα mRNA 3′ UTR region We then asked if the functional differences between the A and G −237 SNP variant promoters were evident under physiological settings. To do this we evaluated TNFα production in cell lines that carried these polymorphisms. Newly generated and low-passage immortalised BCLs from −237A/G heterozygous, and −237AA/GG homozygous donors were stimulated with PMA for 4 hours prior to mRNA isolation and quantitative PCR evaluation. TNFα mRNA expression levels were measured relative to GAPDH expression, which was quantified using inventoried Taqman primers and probes. A trend was observed which illustrated, in line with the luciferase promoter assays, that TNFα mRNA fold increase was less in individuals who carried the −237A SNP following stimulation, with a reduction in median TNFα transcript levels from −237GG to −237AA on a homozygous background. The differences between these two groups were significant. However, median TNFα fold induction was highest in −237AG heterozygous donors .Production of soluble TNFα was measured in follow-up analyses using a subset of the BCL lines tested for TNFα mRNA expression. Assay supernatants were harvested following 4 hours stimulation with PMA and soluble TNFα was measured by ELISA. As observed for TNFα mRNA expression, increased soluble TNFα (sTNFα) production was observed on a homozygous −237GG background, however, under these experimental conditions, was higher relative to both GA and AA donors .Collectively, our BCL-derived data suggested that promoters encoding the −237A variant generally demonstrated weaker activity relative to their common G variant counterparts. As all our assays were performed with a single concentration of PMA and for a fixed period of incubation we carried out a small-scale experiment to determine if these disparities were apparent under different experimental conditions. Our results illustrated that for BCLs, the intrinsic differences between these promoters were also evident when these variables were taken into account .in vivo. Using isolated PBMCs from healthy individuals who carried either the −237A (GA heterozygous) and −237G SNPs (GG homozygous) as a source of monocytes, we evaluated soluble TNFα production upon LPS stimulation. When soluble TNFα levels were evaluated per fixed number of PBMC input (1 million cells), there were no statistical differences between carriage of either SNP and absolute levels of TNFα production. However, when the datasets were corrected for the total number of CD14 positive cells per assay, and when sTNFα levels were adjusted and normalised relative to a fixed number of CD14 positive, CD3 negative cells then carriage of the −237A SNP on a heterozygous background was associated with lower TNFα production relative to −237G homozygosity, both in terms of TNFα production  and in relation to fold induction   .The −237 SNP is located in close proximity to the 200 bp core promoter, within a region corresponding to a putative Y box repressor site identified in mice. We questioned if the functional disparities between promoters containing the A and G variants could be explained by differences in the binding of Tfs, co-activators or repressor proteins in this region. Complementary oligos up to 30 base pairs in length and encoding either the A or G −237 polymorphisms were annealed and tested for binding to nuclear extracts purified from Jurkat cells by radioactive EMSA (data not shown). Despite various attempts using different annealing conditions, buffers, nuclear extracts, binding conditions, and experimental approaches, we did not detect binding of nuclear proteins to oligos contain either the G or A SNP variants.We then utilised various Tf Binding prediction software programs to gauge whether Tf or repressors were predicted to bind the region encompassing the −237 SNP. Of the factors predicted, a proportion were not affected by the nature of the encoded −237 SNP variant, whereas others demonstrated exclusivity depending on the presence of either the G or A polymorphism .in vivo; this is in close proximity to neighbouring CpG dinucleotide motifs near the 5′region of the core promoter. We argued that because the −237A variant alters the spacing and frequency of CpG dinucleotide motifs in this region it could impact the extent or pattern of local CpG methylation, and in turn TNFα production. Firstly, we evaluated the influence of CpG methylation on the activity of the individual TNFα promoters using both the −237G and −237A luciferase reporter plasmids. The plasmids were methylated prior to transfection, and transfected cells were subjected to a DNA methyltransferase inhibitor, 5-Azacytidine to prevent subsequent plasmid methylation upon incubation. Using this strategy we observed that methylation of both the −237A and G containing promoters severely disrupts luciferase activity, reinforcing the role played by DNA methylation in the activity of the proximal TNFα promoter . We extended screening to include mutations that encompass the TNFα promoter −1030 SNP (rs1799964), as this T to C variant is frequently inherited as a complotype with the −237A SNP and generates a methylation-susceptible CpG dinucleotide motif. Although the extent of methylation was greater in this region of the promoter, a correlation between TNFα production and the degree of methylation was not observed .Analysis of bisulfite-converted DNA through PCR amplification and TOPO cloning is limited in terms of in-depth sequence coverage, and data biases can also occur during the amplification and cloning of bisulfite-converted PCR products HLA-B*5701 is associated with slower disease progression and although a large percentage of B*5701 positive individuals progress slowly to AIDS, a number of patients who carry this allele progress at normal rates. This is assumed to reflect differences in the interplay between CD8 and NK cell-mediated immune control, and the evolution of viral escape variants The major impact of HLA, mostly notably MHC class I subtypes, on clinical outcome in HIV-1 infection has recently been re-iterated in large GWAS studies. Yet because of the complexities surrounding these approaches, specifically factors relating to cohort selection and linkage disequilibrium (LD), it has proved difficult to identify independent causal variants associated with favourable immune control Sympahalangus genera of small apes, the −237A/−1030C complotype evolved independently in humans, and based on population frequencies is likely to have originated in Africa prior to migration into Asia and Europe in vivo.The −237 SNP represents one of ten common TNFα promoter SNPs linked to ancient human HLA haplotypes that denote evolutionary markers of ancestry traceable to primate lineages in vivo. When we explored the methylation status surrounding the −237 SNP in BCLs we did not observe overt differences between the methylation profiles in terms of the extent, pattern and frequency of promoters carrying either the A or G SNP, and CpG methylation was low for all promoters in this region. Although we did detect inter-individual differences in the methylation status of the distal promoters in the region encompassing the −1030 SNP, a clear relationship between the degree or pattern of DNA methylation and promoter activity, and the presence of either SNP in this region was not apparent.As the −1030 SNP introduces a CpG dinucleotide motif and the −237A SNP disrupts an existing site this complotype could presumably impact the promoter epigenetically via processes relating to DNA methylation. DNA methylation is known to play an important role in the function of the human TNFα promoter, a finding re-capitulated in our plasmid-based 5-Azacytidine experiments in vivoIn summary, we observed that the carriage of the −237A SNP in the human TNFα promoter is associated with a modest reduction in TNFα production, a finding that appears independent of the cell-types and stimuli tested. Although the number of subjects in this study was low, the variety of different approaches illustrated a common result. In the setting of HIV-1 infection, the A variant SNP could represent an independent contributory SNP affecting the course of disease progression, although its impact is presumably minor relative to that conferred by the B*5701 allele, particularly as the A SNP is also inherited with MHC class I types not associated with favourable immune control. Nonetheless, a modest impact on TNFα production may be significant, as positive feedback loops leading to enhanced TNFα production might amplify the impact of this SNP HIV-1 infected subjects were enrolled from both the King’s College long term non-progressor (LTNP) Cohort and the John Warin Ward in Oxford for the evaluation of TNFα promoter haplotypes and SNP analyses. Ethical approval was obtained from the relevant Ethical Committees  at King’s College, London ((LREC 99-075) and the NHS Research Ethical Committee ) and all patients gave written consent to donate blood. As healthy control subjects were independently and anonymously recruited for typing and cellular studies and because all staff working on this project were fully-blinded to their identity, ethical consent was not required. Nonetheless, all donors were fully informed and gave verbal consent to donate a one-off sample of blood for the purpose of this investigation. HLA class I typing was performed by the amplification refractory mutation systems PCR (ARMS-PCR) using sequence specific primers.Peripheral blood mononuclear cells (PBMCs) were isolated from heparinised venous blood by Ficoll-Hypaque  density gradient centrifugation, and were subsequently washed in RMPI 1640  supplemented with 10% foetal calf serum, 2 mM Glutamine 100 IU of penicillin/L, 100 mg of streptomycin/L (referred to herein as R10) . PBMCs were cryopreserved in 10%DMSO/foetal calf serum for subsequent analyses.2/95% air incubator. EBV-immortalised BCLs were generated in-house according to previously published methods The Jurkat E6.1 cell line (purchased from ECCAC) and EBV-immortalised B cell lines (BCLs) were maintained in R10 at 37°C in a 5% COGenomic DNA was extracted from cryopreserved PBMCs using the Qiagen Gentra Puregene DNA extraction kit . Approximately 1.35 kb of the TNFα promoter was amplified by PCR using primers; Fw2 (5′-GCA GGG AGG GGA CTA TTT ATG AAG G-3′) and Rv1 (5′-GGG ATT TGG AAA GTT GGG GAC AC-3′). The resulting PCR products were cloned into pCR-4 TOPO TA cloning vectors (Invitrogen) and sequenced. Results obtained from sequence analyses were also verified by Restriction Fragment Length Polymorphism (RFLP) analysis using previously published methodologies 5′-AAG ACC CCC CTC GGA ATC AGA GCA GGG AGG ATG-3′ and 5′-CAT CCT CCC TGC TCT GAT TCC GAG GGG GGT CTT-3′) were used to PCR amplify the TNFα Translucent Gene Promoter Reporter Vector. Template DNA was subsequently digested using the DNA methylated specific endonuclease DpnI, leaving the mutated variant vector, which was transformed into Escherichia coli strain XL10 Gold and recovered using the EndoFree Plasmid Maxi Kit . The presence of the −237A mutation was verified by sequencing.The TNFα Translucent Gene Promoter Reporter Vector, which naturally encodes the -237 G variant, was obtained from Panomics. The −237A mutation was introduced into this vector using QuikChange® II XL Site Directed Mutagenesis Kit  according to the manufacturer’s instructions. In brief, two mutagenesis oligonucleotides  in conjunction with a freeze-thaw cycle. 100µl of Luciferase Assay Substrate Buffer was then added , and Luciferase activity was measured immediately on a Fusion 3.5 Universal Microplate Analyzer .Transfection of Jurkat cells with the TNFα Translucent Gene Promoter Reporter Vectors carrying both the −237G and A variants was carried out using Lipofectamine LTX and PLUS Reagent . The day before transfection, cells were split to a density of 5×10−ΔΔCT method.Newly established and low passage BCLs from healthy −237AG heterozygous and −237GG/AA homozygous donors were stimulated with PMA (50 ng/ml) for 4 hours prior to RNA extraction (kit) and cDNA synthesis (kit). TNFα primers and probes, sourced from Applied Biosystems , were used to amplify cDNA. Results were normalised relative to GAPDH expression, using inventoried human GAPDH endogenous control primers and FAM/MGB probes (Applied Biosystems). The final datasets were normalised for relative expression, using the 2Following PMA stimulation of BCL targets for 4 hours, assay supernatants were harvested and TNFα was quantified using the Human TNFα ELISA Ready-Set-Go kit (eBioscience).Transfections and Luciferase Assay section outlined above.Luciferase reporter plasmids carrying the −237A and G SNP were methylated prior to transfection using CpG Methyltransferase (M.SSS I). Methylation was confirmed by digestion with the CpG methylation-sensitive enzyme, BstUI, and agarose gel electrophoresis. A fraction of transfected Jurkat cells were incubated with 500 nM of the DNA methyltransferase inhibitor 5-Azacytidine to prevent subsequent plasmid methylation upon transfection. Transfection and luciferase assay protocols were performed according to those described in the BCLs encoding the GG, AA and GA SNPs at −237 were either pre-treated with 500 nM 5-Azacytidine or left untreated for 2 days. Cells were subsequently harvested, plated at 1mg/ml and stimulated with 50 ng/ml of PMA for 4 hours, following which assay supernatants were harvested. sTNFα was assayed using a commercially available Human TNFα ELISA Ready-Set-Go kit (eBioscience).AAA CAT TCT CCT ACC CAT TAC TAT AAT CAC ATC TC -3′. PCR products were subcloned into the pCR4 TOPO TA cloning vector  and sequenced.Genomic DNA was extracted from the different cell types using PureGene DNA purification kit  and 500 ng of genomic DNA was bisulfite converted using Methylcode™ Bisulfite Conversion Kit  according to manufacturer’s instructions. PCR-generated fragments were amplified using the following primers: −237 amplification: 5′-TTT GTA TTT TGT TTG GAA GTT AGA AGG AAA TAG ATT A-3′ and 5′-AAA ACT TCC TTA ATA AAA AAA CCC ATA AAC TCA TC-3′; −1030 amplification; 5′-AGA GTT GTG GGG AGA ATA AAA GGA TAA GG-3′ and 5′-5′-ACGT-3′ overhangs on annealed oligonucleotides containing the −237G and A SNPs were radioactively labeled with 32P, and incubated with 2 µg nuclear extract (previously prepared from Jurkat cell) for 10 minutes in a reaction containing standard Hepes buffer, pH 7.8. Reactions were resolved on a 4.5% polyacrylamide gel (200 V for 150 minutes at 4°C). Vacuum dried gels were exposed to hyperfilm (Amersham).Table S1Transcription factor binding prediction analyses for the −237A and −237G promoter variants. TNFα promoter sequences encoding the −237A and −237G SNP variants were evaluated using PROMO and MatInspector Software. Factors predicted to bind exclusively to DNA coding either the A or G variants are reported.(DOC)Click here for additional data file.


SKIV2L or in TTC37, 2 genes encoding subunits of the putative human SKI complex. The estimated prevalence is 1/1,000,000 births and the transmission is autosomal recessive. The classical form is characterized by 5 clinical signs: intractable diarrhea of infancy beginning in the first month of life, usually leading to failure to thrive and requiring parenteral nutrition; facial dysmorphism characterised by prominent forehead and cheeks, broad nasal root and hypertelorism; hair abnormalities described as woolly and easily removable; immune disorders resulting from defective antibody production; intrauterine growth restriction. The aetiology is a defect in TTC37, a TPR containing protein, or in the RNA helicase SKIV2L, both constituting the putative human ski complex. The ski complex is a heterotetrameric cofactor of the cytoplasmic RNA exosome which ensures aberrants mRNAs decay. The diagnosis SD/THE is initially based on clinical findings and confirmed by direct sequencing of TTC37 and SKIV2L. Differential diagnosis with the other causes of intractable diarrhea is easily performed by pathologic investigations. During their clinical course, most of the children require parenteral nutrition and often immunoglobulin supplementation. With time, some of them can be weaned off parenteral nutrition and immunoglobulin supplementation. The prognosis depends on the management and is largely related to the occurrence of parenteral nutrition complications or infections. Even with optimal management, most of the children seem to experience failure to thrive and final short stature. Mild mental retardation is observed in half of the cases.Syndromic diarrhea/Tricho-hepato-enteric syndrome (SD/THE) is a rare and severe bowel disorder caused by mutation in TTC37, une protéine à motif TPR et SKIV2L, une hélicase à ARN, toutes 2 étant des constituants du complexe SKI humain. Le complexe SKI est un co-facteur de l’exosome cytoplasmique qui assure la dégradation des ARN aberrants ou exogènes. Le diagnostic est d’abord clinique puis confirmé par le séquençage des gènes TTC37 et SKIV2L. Le diagnostic différentiel avec les autres formes de diarrhées intraitables est fait grâce aux analyses anatomopathologiques qui montrent dans les autres formes, des lésions spécifiques. La prise en charge clinique repose sur la nutrition parentérale et la supplémentation en immunoglobuline si nécessaire. Un certain nombre d’enfants peuvent être sevrés de la nutrition parentérale et des supplémentations en immunoglobulines. En cas d’atteinte hépatique, celle-ci peut être sévère et conduire au décès. Même avec une prise en charge optimale, les enfants présentent une petite taille et, dans la moitié des cas, un retard mental modéré.Les diarrhées syndromiques ou syndrome tricho-hepato-enterique (SD/THE) sont un syndrome rare et sévère dont l’incidence est estimée à 1 cas pour 1 million de naissances et la transmission autosomique récessive. La forme typique associe 5 signes cliniques: une diarrhée grave rebelle nécessitant dans la majorité des cas une nutrition parentérale du fait de la malnutrition, une dysmorphie avec un front large et bombé, une racine du nez large et un hypertélorisme, des anomalies des cheveux qui sont fragiles, cassants, incoiffables et qualifiés de « laineux », un retard de croissance intra utérine et des anomalies de l’immunité à type de déficit en immunoglobuline ou d’absence de réponse aux antigènes vaccinaux. Des anomalies de deux protéines peuvent être à l’origine du syndrome SD/THE: Disease name/synonyms – Syndromic diarrhea – Phenotypic diarrhea – Tricho-hepato-enteric syndrome – Intractable diarrhea of infancy with facial dysmorphism – Trichorrhexis nodosa and cirrhosis – Neonatal hemochromatosis phenotype with intractable diarrhea and hair abnormalities – Intractable infant diarrhea associated with phenotypic abnormalities and immune deficiency- Syndromatic diarrhea. [ORPHA84064 MIM 222470 and MIM614602]. Possibly chronic diarrhea and skin hyperpigmentation. TTC37 (HGNC:23639) or in SKIV2L (HGNC:10898), 2 genes encoding co-factors of the putative human SKI complex . During the last 20 years, 13 cases have been diagnosed in children born in France  which, according to the annual number of births in France, indicates a prevalence of at least 1/1,000,000. It should be noted that 21 cases out of 44 are from consanguineous families. The prevalence may be underestimated due to the fact that only patients with important gastrointestinal manifestations are referred to specialists. SD/THE seems to be present in all populations. To date, patients have been described in Indian, European and Mediterranean populations .SD/THE is a rare disease. Between 1982 and 2012, 44 cases have been published ]. During]. Three are constant: intractable diarrhea, facial dysmorphism and hair abnormality. Two are very frequent (more than 90%): IUGR and immunodeficiency; 2 are frequent: skin abnormalities and liver disease and 2 are rare: congenital cardiac defects and platelet anomaly.From the review of the literature, 9 clinical signs are associated with SD/THE -15]. ThrThe following description is based on the 44 reported cases -15 and dIntractable diarrhea (48/48): All the children presented intractable diarrhea of infancy defined as a chronic diarrhea persistent despite an enteral rest. This disease was at first diagnosed among children hospitalised for feeding problems. The onset of diarrhea was variable, from the first day to 32 weeks of life. Most children had parenteral nutrition during the follow up. The pathology analysis of intestinal tract showed normal (7/44) or mild to severe villous atrophy with no specific alterations, especially no sign specific of tufting enteropathy or microvillus inclusion disease. Colitis (16/22) or gastritis has also been found.Hair abnormalities are one of the most consistent signs as all children presented abnormal hair (48/48). Hair was described most often as woolly, easily removable, unmanageable, brittle and scanty. When searched, trichorrhexis nodosa were frequently found (35/39).Facial dysmorphism (47/47): Children presented wide forehead, broad nasal root, hypertelorism, and coarse features Figure . The facImmune defect (39/44): this sign was the most difficult to appreciate as investigations were different from one case to another. Signs reported most frequently were a low immunoglobin level (24 patients), a defect in antibody production after vaccination (14), monoclonal hyper IgA (3), a low lymphocytes count (2). Some children needed an immunoglobulin supplementation (temporarily or for a long period), some were prone to frequent infections.IUGR/SGA (31/46): Most children had a small birth weight for gestational age: out of 41 with recorded weight, 30 children were below the 10th percentile and 27 below the third percentile : More than half of the children had a liver disease. Cirrhosis (18) and siderosis were the main signs. Rarely, patients presented an isolated hepatomegaly. One patient was described as having a hepatoblastoma .Skin abnormalities (18/36): Half of the children with skin description presented abnormalities .Cardiac abnormalities (8/31): Several children presented cardiac abnormalities: aortic insufficiency (2 patients), peripheral pulmonary stenosis (one patient), tetralogy of Fallot (one patient), atrial septal defect or ventricular septal defect (4 patients), persistent arterial duct (1 patient).Platelet: first described by Hartley et al., platelet morphology has not been investigated in all patients. Increased size of the platelet was found in 5 out of 21 patients and was temporary in some cases. Phenotypic abnormalities observed in transmission electron microscopy were not performed in studies other than that of Hartley et al.Other signs  were described in only a few patients. The association with THE syndrome might be coincidental.Finally a slight mental retardation is noted in more than half of the patients but this is not well documented.TTC37 or SKIV2L) or the mutation's type. In the case of children bearing the same mutation, the phenotype severity can vary from one individual to another.Signs described in THE syndrome are summarised in Table SKIV2L in 40% of the cases or TTC37 in 60% of the cases [SKIV2L and TTC37 form along with WDR61, the human ortholog of Ski8p, the putative human SKI complex. The functional part of the complex is SKIV2L which is an RNA helicase, TTC37 and WDR61 (containing respectively TPR and WDR repeats) being involved in protein-protein interactions. In 2005, Zhu et al. showed that these 3 human proteins co-localized with the human PAF but their association within a functional complex remains to be formally demonstrated [SD/THE is an autosomal recessive disease caused by mutation in he cases ; it is tnstrated . The prenstrated . The skiTTC37 or in SKIV2L. For TTC37, among 25 mutations found, 6 are missense, 5 are stop mutations, 5 are frame shift mutations due to deletion or insertion within the coding region and 9 are mutations in splice sites . Trp936* is one of the rare recurrent mutations and has been found in 4 families among 25, all originating from India or Pakistan. For SKIV2L, among 9 mutations explored in 7 individuals from 7 families, 5 are deletions or insertion leading to frame shift, 3 are stop mutations and 1 a missense. There is no recurrent mutation. Table Most mutations are private mutations and are distributed in all exons without hot spot either in TTC37 and SKIV2L.The association of intractable diarrhea of infancy, i.e. chronic diarrhea persisting despite enteral rest, with woolly hair and dysmorphism is highly suggestive of SD/THE. The analysis of an intestinal biopsy is indicated to rule out other forms of intractable diarrhea caused by enterocyte abnormalities. The diagnosis is confirmed by the sequencing of SD/THE are mostly diagnosed by Hepato-gastro-intestinal pediatricians because the intractable diarrhea or the liver disease are the foremost signs. The main differential diagnoses are other causes of chronic diarrhea. Most of the non-genetic causes  can be ruled out by explorations and clinical observation as they are resolved with adequate treatment. Among intractable diarrhea of infancy, only the syndromic tufting entheropathy also presents hair abnormalities , but it SD/THE is an autosomal recessive disorder. Considering the severity of the disease, an antenatal diagnosis could be offered to the parents of an affected child once the molecular defect is characterized.The management concerns the three life-threatening signs: intractable diarrhea leading to failure to thrive, immune abnormalities and liver disease. Intractable diarrhea often needs a parenteral nutrition to achieve nutrition and growth, during a variable period of time ranging from a few months to several years. In some cases, the association of enteral with parenteral nutrition can be indicated. For reasons of immune disorders, immunoglobulin supplementation is sometimes necessary and the antibody production after vaccination should be monitored. Finally, some children can present a severe liver disease independent of parenteral nutrition ,6,12 whiEven if the prognosis seems to have improved with years, there is still a high mortality rate . The main complications are liver disease and infections. Some patients are weaned off parenteral nutrition  but otheSKIV2L or TTC37 and dysfunction of the Ski complex remains to be formally demonstrated. Further investigations will allow us to understand how the alteration of a basic function such as RNA decay leads to these specific signs. There are probably several ways and environmental interactions which have to be investigated and a part of the pathology could be caused by misregulation of non coding RNAs. The possibility of the existence of milder forms, especially regarding gastrointestinal signs, has to be considered. In 2008, Al Qoer et al. described a cohort of children with mild diarrhea, hair and skin abnormalities who may possibly present an authentic SD/THE [The discovery of the molecular basis of SD/THE opens the perspective to better understand the disease and indicates that it must be considered as a mRNAs quality control disease even though the link between mutations in TTC37 or SKIV2L, but it supports other functions in meiosis and in the PAF complex making its involvement improbable [WDR61, the third component of the SKI complex, would have been a candidate gene for SD/THE in patients with no mutation in probable .SD/THE is the first mendelian disease linked to a cytoplasmic exosome anomaly. With at least 2 genes involved, it is a genetically heterogeneous disease which should be evocated in cases of intractable diarrhea with hair abnormalities and confirmed by molecular diagnosis. Although improvements have been made recently regarding molecular basis and diagnosis, the prognosis remains severe.The author declares no competing interests.AF and CB take responsibility for the review and have been involved in drafting the manuscript and revising it critically; AF, CMV and OG conducted clinical investigations, collected clinical data and revised the manuscript. All authors have given final approval of the version to be published.Written informed consent was obtained from the patient’s parent for publication of this report and any accompanying images.


In a mouse model of viral induced atopic disease, expression of FcεRI on dendritic cells is critical. While adult human conventional (cDC) and plasmacytoid (pDC) dendritic cells have been shown to express FcεRI, it is not known if this receptor is expressed in childhood and how its expression is governed by IgE.− ILT7− CD1c+; pDC: CD19− ILT7+ CD1c−). Total and specific serum IgE levels to food and inhalant allergens were determined by ImmunoCAP, and the relationship between FcεRI expression on dendritic cells and sensitization, free IgE, cell bound IgE, and age was determined.Following informed consent of subjects , peripheral blood was stained for surface expression of CD19, ILT7, CD1c, IgE, FcεRI and analyzed by flow cytometry (cDC: CD19Independent of sensitization status, FcεRI expression was noted on cDC and pDC as early as 12 months of age. Serum IgE level correlated with expression of FcεRI on cDC, but not pDC. Based on the concentration of IgE, a complex relationship was found between surface bound IgE and expression of FcεRI on cDC. pDC exhibited a linear relationship of FcεRI expression and bound IgE that was consistent through all IgE concentrations.In children, FcεRI expression on cDC and pDC is modulated differently by serum and cell bound IgE. IgE governance of FcεRI expression on cDC depends upon a complex relationship. Further studies are needed to determine the functional roles of FcεRI on cDC and pDC. Severe viral respiratory infections early in life are associated with increased risk of asthma and atopic disease One hallmark of our model is that murine cDC and pDC do not express FcεRI except during severe viral infections, when cognate interactions with a specific neutrophil subset drives FcεRI expression Our study documents expression patterns of FcεRI on peripheral blood cDC and pDC in young children. While the receptors are present early in life, we found a marked differential effect of low and high IgE on cDC FcεRI expression. This finding implies that cDC expressed FcεRI has disparate effects on cDC function depending on serum level of IgE. Further, our data suggest that IgE control of FcεRI may be different in children compared to adults.A cross sectional time analysis was employed. Our primary goal was to determine the age at which human cDC and pDC expressed FcεRI. Our secondary goal was to determine if sensitization to any food or inhalant allergen was associated with FcεRI and IgE expression.This study was approved by the Children's Hospital of Wisconsin IRB. Parental written consent and subject verbal assent was obtained before enrollment of subjects into this study.Once consent and assent was obtained, an abbreviated atopic history was collected and venipuncture performed. Eligible patients were children aged 1–15 years. Exclusion criteria were: atopic dermatitis, persistent controlled asthma, uncontrolled asthma, immunodeficiency, or any co-morbid disease; use of any corticosteroids within the last month; current therapy with any prescribed medication; use of any investigational agent in the last 30 days; women of childbearing age not on contraception or women breastfeeding.D. farinae, D. pteronyssinus, cockroach, cat dander, dog dander, mouse epithelium, rat epithelium, guinea pig epithelium, mouse serum protein, rat serum protein, mouse urine protein, rat urine protein, June grass, Alternaria tenuis, Cladosporium herbarum, Aspergillis fumigatus, common ragweed, oak, birch, L. destructor) were determined by ImmunoCAP (Quest Dignostics/IBT Laboratories). Sensitization was defined as elevated serum specific IgE (>0.35 kU/L) to one or more allergens tested.Total IgE and specific IgE levels to foods  and aeroallergens  was performed with 5×105 to 1×106 total cellular events collected on each stained specimen. cDC  were identified as CD19−/ILT7−/CD1c+ and pDC identified as CD19−/ILT7+/CD1c−. This type of phenotyping strategy has been used before, as ILT7 is a specific marker for pDC and CD19−CD1c+ cells have been shown to be essentially all cDC Immunophenotyping for evaluation of pDC and cDC was performed within 6 hours of specimen collection. 100 µl of heparinized whole blood was stained with antibodies to human CD19 , ILT7 , and CD1c , as well as either antibodies against FcεRIα  or IgE  for 15 min. at room temperature. Erythrocytes were lysed with 2 ml FACSLyse (BD Biosciences) and stained cells were washed with PBS/0.1% NaNhttp://salford-systems.com/). Regression trees are a non-parametric approach where the data are split recursively into two groups based on an optimizing function, until the specified limits for subgroups are reached. A least absolute deviance from the median was used as the optimizing function, with a limit of 10 in any group to be split and 5 minimally needed for any group. Linear regression was used to fit the data with linear or a polynomial trend with normality of the error term checked with a normal probability plot. cDC IgE was fit to serum IgE using a non-linear regression for a sigmoidal type curve of the form 1/(1+M/serum IgE)m, where M is the (fitted) median value of cDC IgE and m is the slope of the curve at that value. We fit linear regression using SAS 9.2 and non-linear regression using JMP 9.0. Given the relatively small sample, we did not use a bootstrap approach or a holdout sample to validate the model results. Therefore, these results will need to be validated on another sample.Data were expressed as frequency and percent for categorical variables and median and interquartile range for continuous variables. Since the data were skewed, continuous variables were compared using a Mann-Whitney test while doing 2 group comparisons, and continuous variables were examined using scatter plots and Pearson correlations. To investigate the inter-related effects of variables on the outcomes of interest, a regression tree analysis was done using Salford Systems' CART software , with about 25% of the variation of IgE explained by the linear relationship with age. However, much of this relationship occurred in the non-sensitized group (r = 0.56) compared to the sensitized group (r = 0.29). This is not surprising, since serum IgE levels can fluctuate, such as with viral infections, and our data were obtained at only a single time point per subject Comparing the relative frequencies of conventional (cDC) and plasmacytoid dendritic cells (pDC) amongst all of our subjects, we found 1.26 (0.66–2.55) (median (IQR)) fold more cDC than pDC. This ratio was not significantly different between sensitized and non-sensitized subjects, nor did it correlate with age (data not shown). While this ratio of cDC to pDC is lower than what has been reported in older children, it is similar to what has been reported in adult studies using a dendritic cell phenotyping strategy similar to ours We initially hypothesized that similar to the rodent system, peripheral blood cDC would not express FcεRI early in life. However, as shown in In human mast cells and basophils, IgE modulates FcεRI expression Sensitization status did not differentiate level of expression of FcεRI on cDC . HoweverSince bound IgE modulates expression of FcεRI on human mast cells and basophils, we examined the level of IgE on peripheral blood cDC and correlated this with FcεRI expression. As shown in By overlaying serum IgE levels, we found only subjects with a serum IgE above 34–42 kU/L had a cDC fold IgE expression of 12 or greater . These dUnlike peripheral blood cDC, pDC expression of FcεRI was minimal (median (IQR) = 15.82 (12.74–21.05) versus 2.47 (1.47–3.25) on cDC and pDC, respectively). In fact, 6 of the 27 subjects appeared to have no expression of FcεRI on their pDC . As shown in Unlike with cDC , serum IOther studies have attempted to describe relationships between serum IgE, cell-bound IgE, and FcεRI expression on dendritic cells Interestingly, we found no association between sensitization status and FcεRI expression. We cannot equate sensitization with atopy because we did not challenge our subjects with the respective allergens. Further, it is quite possible that those subjects we identified as non-sensitized were indeed making specific IgE—just against antigens that were not included in our panels. For these reasons our data may be different from two studies in adults where atopic subjects were noted to have significantly higher FcεRI expression on cDC and pDC The most intriguing finding of our study is the major difference in the role of IgE in receptor expression. Whereas a direct relationship between FcεRI expression and IgE on both cDC and pDC have been reported by others, we found that only pDC FcεRI expression correlated in a linear fashion with bound IgE Unlike pDC, expression of FcεRI on cDC correlated directly with serum IgE levels. However, the relationship between bound IgE and FcεRI was more complex. When cell bound IgE was below 12 fold MFI there was little effect of bound IgE on FcεRI expression. Once bound IgE levels crossed the threshold, a direct relationship developed. At low levels of serum IgE (<34–42 kU/L) there is rapid accumulation of bound IgE with little effect on FcεRI expression. At these low levels of IgE, a difference in correlation of bound IgE and FcεRI exists between sensitized and non-sensitized subjects. Both responses are parabolic, however, non-sensitized subjects tend to have an initial increase in FcεRI expression with increasing bound IgE (below 12 fold MFI). Sensitized subjects had the exact opposite effect. Once serum IgE levels reached 34–42 kU/L, corresponding to bound IgE levels of 12 fold MFI, both sensitized and non-sensitized subjects exhibited a direct correlation between IgE and FcεRI.We have found a threshold effect of bound IgE on cDC FcεRI. The functional implications for this threshold effect are unclear; it is inviting to speculate that FcεRI has disparate functions at low versus high IgE levels. Perhaps at lower levels FcεRI acts as a rheostat, similar to what is seen in rodents, where the receptor functions as a mechanism for cellular recruitment and less for antigen-uptake Our study had several limitations. First and foremost, we utilized statistical modeling to evaluate our data, and, as a result, it is important that these findings be validated in a second cohort. Further, our sample size was relatively small and likely limited our ability to detect subtle differences. We did not enroll infants younger than 12 months of age, and we were unable to determine if viral infection relates to induction of FcεRI. Finally, defining sensitization status by selected ImmunoCAP may not be ideal—especially from a clinical perspective. However, given that our results were mostly independent of sensitization status, we believe this is not a major defect. Indeed, most of the limitations of our study would only lessen our ability to define statistically significant differences. Since we were able to document clear relationships between IgE (serum and cell bound) and cDC and pDC expression of FcεRI despite these limitations, their presence only strengthen the importance of our findings.In summary, our results demonstrate the presence of FcεRI on peripheral blood cDC and pDC in children as young as 1 year old, which is in contrast to what is seen in the rodent system. Our data also provide evidence of differential regulation of FcεRI on cDC and pDC in children. With cDC a complex inter-relationship between serum IgE, cell bound IgE, and expression of FcεRI exists that appears to hinge on an IgE level of 34–42 kU/L. The functional significance of this relationship is unclear, and we do not yet understand the mechanisms responsible for this relationship. Future studies need to be undertaken to examine expression of FcεRI on cDC and how IgE modulates this receptor and cDC function.


Humans can recognize spoken words with unmatched speed and accuracy. Hearing the initial portion of a word such as “formu…” is sufficient for the brain to identify “formula” from the thousands of other words that partially match . Two alt ► Lexical competition and segment prediction accounts of spoken word recognition ► Overnight consolidation of pseudowords modifies segment prediction ► Predictive coding simulates MEG data in superior temporal gyrus ► Prediction error supports word recognition without competition at the lexical level All current accounts of spoken word recognition propose that identification occurs once speech segments that uniquely identify a single item are heard  that closely overlap with one existing word (“formula” and “mushroom”) A. Once aPre- and post-DP magnetoencephalographic (MEG) responses to consolidated (day 1) novel words (“formubo”), source words (“formula”), and baseline nonwords (“formuty”) were therefore recorded during a pause-detection task  and compBehavioral evidence of overnight consolidation of newly learned words was assessed during a subsequent delayed repetition task A 13]. O. O13]. OWe first computed the main effect of day 1 versus day 2 training on pre-DP neural responses, averaging responses over all three item types  because these are lexically indistinguishable using pre-DP speech segments  A. It wasThe novelty-by-day interaction was significant in both the GFP  A and theIn summary, the complete pattern of significant effects in (160) = 4.7) and right  = 4.3) STG survived correction for multiple comparisons within this restricted volume  and activity in state units  derived from acoustic analysis in lower levels  and furFinally, our inability to detect neural effects predicted by a lexical entropy account does not entirely rule out traditional accounts based on lexical competition . Our point is that we did find evidence consistent with a predictive coding account and that such an account appears able to achieve the same functions without requiring lexical competition. Nonetheless, further evidence and simulations will be required to establish whether or not previously proposed neural correlates of lexical competition , and spThe computational measures explored here were computed by combining the phonological transcriptions and word frequency measures in the CELEX database , for theLexical activation during each segment of a spoken word is expressed as the conditional probability of hearing a word “i” given a speech signal that matches a set “{j}” containing “n” words:This conditional probability is computed for each segment in a speech sequence using the phonological transcriptions and word frequencies in CELEX divided by the summed frequency of the set of matching words. Novel words trained on day 1 were assigned a frequency of occurrence equal to the frequency of the source words in the experimental item set; this is the amount of learning assumed for novel words). This equation is identical to that explicitly specified in Bayesian models of word recognition such as Shortlist-B (see Equation 5 in ), althouGiven the set of words in CELEX that match the current speech sequence, and the frequency of occurrence of these words, we can compute the conditional probability of each of the possible segments that could follow the current segment. This is computed using the equation below for the set of n words {j} that are compatible with the current speech sequence and that share the same next segment /i/.n|k@ptI) = 0.899 or /v/ P(v|k@ptI) = 0.101 given their relative frequencies above. To turn these predictions into an error measure, we can then compute the summed absolute error between the conditional probabilities for predicted segments and the observed probability of the speech segment. Given an ideal observer, hence error-free segment recognizers, these observed probabilities are one or zero for segments that are heard or absent, respectively.Therefore, hearing /k@ptI/ (see example above) leads to a prediction that the next segment is either /n/, P are (0.899 0.101) given the relative frequency of these words. If the final segment of the word “captain” is heard, then the observed probabilities are (1 0), and hence segment prediction error is 0.202.