Epstein–Barr virus-positive post-transplant lymphoproliferative disease (PTLD) is a potentially lethal complication of iatrogenic immunosupression after transplantation. Predicting the development of PTLD allowing early and effective intervention is therefore of importance. Polymorphisms within cytokine genes are implicated in susceptibility to, and progression of, disease however the published data are often conflicting. We undertook investigation of polymorphic alleles within cytokine genes in PTLD and non-PTLD transplant cohorts to determine risk factors for disease.α, interleukin- 1, -6, -10 and lymphotoxin-α genes. The TNF-α levels were measured by standard enzyme-linked immuno-absorbant assay.SSP-PCR was used to analyse single nucleotide polymorphism within tumour necrosis factor (TNF)-α promoter (−1031C (P=0.005)); −863A (P=0.0001) and TNF receptor I promoter regions (−201T (P=0.02)); −1135C (P=0.03) with the development of PTLD. We also show an association with TNF-α promoter haplotypes with haplotype-3 significantly increased (P=0.0001) and haplotype-1 decreased (P=0.02) in PTLD patients compared to transplant controls. Furthermore, we show a significant increase (P=0.02) in the level of TNF-α in PTLD patient plasma (range 0–97.97 pg ml−1) compared to transplant controls (0–8.147 pg ml−1), with the highest levels found in individuals carrying the variant alleles.We show an association between variant alleles within the TNF-α loci and the level of plasma cytokine could be used as a predictive risk factor for the development of PTLD.We suggest that genetic variation within TNF- It occuCytokine networks interact in a dynamic way to regulate the immune response, thus it is not surprising that variations in cytokine levels have been correlated with susceptibility to disease and disease progression . A fundaγ) genotype has been implicated in EBV reactivation after stem cell transplantation and with the development of PTLD after renal and liver transplantation , IL-1-α, IL-6, IL-10, TNF receptor(R)I, TNFRII, IL-1R and IL-10R genes : 1 × NH4 buffer; 1.5 mM MgCl2; 200 μM dNTPs and 0.35 U Taq polymerase. Cycling parameters were staged as follows: 96°C for 1 min; 4 cycles of 96°C for 20 s, 75°C for 45 s, 72°C for 25 s; 20 cycles of 96°C for 25 s, 65°C for 50 s, 72°C for 30 s; 3 cycles of 96°C for 30 s, 55°C for 60 s, 72°C for 90 s; 5°C for 10 min. The resultant PCR product was visualised on a 2% agarose-ethidium bromide gel under UV illumination.DNA was extracted using the Easy-DNA kit  and amplified in 47 separate PCR reactions using primers amplifying polymorphic regions within tumour necrosis factor(TNF)-0R genes . Each prα was measured in plasma samples from PTLD patients, non-PTLD transplant control patients and healthy EBV sero-positive controls by quantitative ELISA  following the manufacturer's instructions. Briefly, wells were coated overnight with the monoclonal antibody TNF-α-I, washed and blocked before the addition of quantified TNF standards and patient plasma (undiluted). Plasma was allowed to absorb for 2 h and was then washed. Bound TNF-α was detected using the biotinylated monoclonal antibody to TNF-α-II and streptavidin-alkaline phosphatase. The optical density at 405 nm was measured after 30 min incubation with the development substrate p-nitrophenyl-phosphate .The level of human TNF-χ2 test (this was not adjusted for multiple testing). The Mann–Whitney U test and the one-way ANOVA test were used to test for differences in the medians of quantitative variables. Tests were two-tailed and a P-value <0.05 was considered significant. All statistical analysis was performed using GraphPad PRISM software .Each polymorphism was tested for Hardy–Weinberg disequilibrium by comparing the observed allele frequency with the expected frequency if equilibrium applied. Classical association analysis was conducted to compare allele frequencies between the groups of subjects  and tested using the Fisher's exact or α, LT-α, IL-1-α, IL-6, IL-10, TNFRI, TNFRII, IL-1R and IL-10R (detailed in n=45) or without (n=65) EBV-positive PTLD . Similar analyses were also performed on a healthy adult EBV sero-positive control cohort (n=183). Both the transplant and healthy control cohorts were compared with published frequencies (HapMap Caucasian European (CEU) and CEU Geno frequencies; Pubmed SNP database www.Ncbi.nlm.nih.gov) to assess any variation from the normal expected frequencies: no major variation from expected frequencies was noted. All polymorphic alleles were found to be in Hardy–Weinberg equilibrium except for the single nucleotide polymorphism at position 230 (A/G base change) in the TNFRI promoter region within the transplant control group and therefore individual analysis of this allele was not performed.Known polymorphic alleles/regions from the TNF-vs 19%; P=0.005; vs 23%; P=0.01; vs 3% transplant control subjects; TC: 38% vs 32%; TT: 44% vs 65%, P=0.01; CC: 3%, TC: 40%, TT: 57%; P=0.001 for healthy control subjects, A total of five polymorphic alleles within the TNF promoter region (nucleotide positions relative to transcription start site −1031(T/C), −863(C/A), −857(C/T), −307(G/A) and −237(G/A)) were investigated. For the TNF promoter polymorphism at position −1031(T/C), we observed a significant increase in the frequency of the rarer TNF −1031C allele in the PTLD subject group compared with the non-PTLD transplant control group  we observed a significant increase in the TNF-863A allele frequency in the PTLD transplant group compared with the transplant control group ) whereas haplotype-3 (CACGG) was over represented , +1668(T/G), +1690(C/T) and exon-6, position +676(T/G)) and TNFRI promoter regions (nucleotide positions −201(G/T), −230(A/G), −845(A/G), −839(G/A), −1135(T/C)) were investigated. Analysis of the TNFRI promoter at position −201 showed a significant decrease in the frequency of the −201T allele within the PTLD group compared with the transplant control group  and an increase in the frequency of genotype −1135CC (47% vs 31%) within the PTLD group compared with the transplant control group, however, this did not reach significance  and a decrease in the frequency of haplotype-3 . However, both haplotypes-1 and -3 were significantly different when the PTLD cohort was compared with the healthy control cohort  and non-PTLD transplant controls (n=25) as well as in a cohort of healthy EBV sero-positve controls (n=25). Similar plasma TNF-α levels were observed for the healthy EBV sero-positve and non-PTLD transplant control groups . In contrast, there was a significant increase in the level of TNF-α in plasma obtained from PTLD patients , we assessed those with (C positive) and without (C negative) the risk allele. A median value of 4.053pg ml−1 (range 0–66.69) was observed for C-negative individuals compared with a median of 2.547 pg ml−1 (range 0–97.97) for C-positive individuals, however this was not a significant difference , TNF promoter haploytpes -1 and -3, or TNF receptor loci −201(G/T) and −1135(T/C) (Polymorphisms within the TNF-fference . Similarα levels . No sign135(T/C) Table 5.α, IL-1-α, IL-6 and IL-10 loci and their corresponding receptor loci for evidence of an association with the development of EBV-associated PTLD. The rarer alleles of the TNF promoter polymorphisms at nucleotide positions −1031 and −863 were found to be significantly increased in EBV-positive PTLD cases compared with non-PTLD transplant and healthy controls. Likewise, genotypes containing the non-ancestral allele were also significantly increased in the EBV-positive PTLD cases compared with transplant and healthy control groups. Furthermore, these polymorphic differences within the TNF promoter region resulted in a significant increase of TNF haplotype-3 (CACGG) and a decrease in TNF haplotype-1 (TCCGG) in EBV-positive PTLD subjects compared with transplant and healthy controls suggesting an important role for these haplotypes in determining susceptibility to EBV-positive lymphoma after transplantation. Interestingly, the frequency of the TNFRI promoter −1135C allele was also significantly increased and the −201T allele decreased in EBV-positive PTLD compared with transplant and healthy controls. A corresponding increase in the frequency of the homozygous −1135CC and a decrease in the −201TT genotypes were also observed for the EBV-positive PTLD group confirming the importance of the TNF family of cytokines and their receptors in the development of EBV-positive PTLD.In this study, we have assessed polymorphisms within the TNF, LT-κB and the apoptotic pathway through capsase 8  in the general population .α levels are significantly higher in EBV-positive PTLD patients. However, there remains a group of EBV-positive PTLD patients who do not carry these alleles, genotypes or haplotypes, perhaps indicating that these polymorphisms are not independently functional and that other, as yet, unidentified variants are in linkage disequlibrium with these loci. These data require confirmation in a second, larger sized cohort to be certain of an association  and further analysis of soluble TNF levels may offer some information on the functional activity of these polymorphic alleles. Nevertheless, the genotypic evidence for the involvement of TNF in EBV-positive PTLD presented here provides further information for identifying those most at risk.In summary, we have shown an association between variant alleles of the TNF promoter and the subsequent TNF promoter haplotype with the development of EBV-positive PTLD . We have also shown that TNF-


The pathogenesis of brain inflammation and damage by human immunodeficiency virus (HIV) infection is unclear. Because blood–brain barrier damage and impaired cerebral perfusion are common features of HIV-1 infection, we evaluated the role of tumour necrosis factor-α (TNF-α) and interleukin-1β (IL-1β) in mediating disruption of the blood–brain barrier. Levels of TNF-α were more elevated in cerebrospinal fluid (CSF) than in serum of HIV-1 infected patients and were mainly detected in those patients who had neurologic involvement. Intrathecal TNF-α levels correlated with signs of blood–brain barrier damage, manifested by high CSF to serum albumin quotient, and with the degree of barrier impairment. In contrast, intrathecal IL-1β levels did not correlate with blood-brain barrier damage in HIV-1 infected patients. TNF-α seems to be related to active neural inflammation and to blood–brain barrier damage. The proinflammatory effects of TNF-α in the nervous system are dissociated from those of IL-1β.


Sir,IJP, April 2009[We have read the article, “Is cytochrome modulation the new frontier for decreasing the risk of cataract?” published in pril 2009 with greNADPH is used as a cofactor for aldose reductase and it is also used to transfer electrons in the cytochrome P450 system which then participates in the metabolism of drug/endogenous metabolites. Thus, anThe aldose reductase pathway is absent in liver. It thereIt has been hypothesized that by simple alteration in the medication (CYP inhibitors instead of CYP inducers) one can reduce the risk of cataract. If we assume that cytochrome modulations alter the activity of aldose reductase through NADPH, then this would mean that enzyme induction will decrease the amount of NADPH which is available to be used as a cofactor by aldose reductase (because more NADPH is now being used in cytochrome pathway due to its induction) and thus decrease the rate of this enzymatic reaction. In other words, it appears that enzyme inducers will decrease the amount of sorbitol formed and vice-versa.If we assume that drugs directly modulate the activity of aldose reductase, then one has to keep in mind that as stated earlier, aldose reductase is absent in liver, where most of diltiazem (about 60%) undergoes first pass metabolism. Direct iThe authors have used pioglitazone as an enzyme inducer but doubts have already been raised on its potential to induce CYP3A4.6Authors have used galactose-rich diet to induce cataract although it has been argued that galactose fed rats are not a good model of diabetes and the subsequent induction of cataract. It has a


The pathophysiology of diabetic retinopathy involves leukocyte adhesion to retinal vasculature, early blood-retinal barrier breakdown, capillary nonperfusion, and endothelial cell death. We investigated the involvement of tumor necrosis factor α (TNF-α) in diabetes-related histopathological changes in two relevant rodent models.In short-term studies, Long-Evans rats with streptozotocin–induced diabetes were treated with or without the TNF-α inhibitor, etanercept. For long-term studies, tumor necrosis factor receptor I (TNF-RI)-deficient mice and TNF-RII-deficient mice, as well as C57/Bl6 wild-type mice, were fed 30% galactose for up to 20 months. The retinal histopathological alterations of hypergalactosemia were analyzed in trypsin digest preparations. Endothelial cell injury and apoptosis in rat retinas were evaluated by propidium iodide, TUNEL, CytoDeath staining, and DNA fragmentation ELISA. Caspase 3 and 8 activity was evaluated by immunoblotting and quantitative enzymatic activity assay.Etanercept suppressed caspase activation, retinal cell injury, and apoptosis in short-term diabetic rats. Pericyte and endothelial cell loss were also reduced in long-term hypergalactosemic mice. Long-term studies demonstrated that pericyte loss and endothelial cell loss were reduced in comparison to wild-type diabetic controls.Our study identifies an important role for TNF-α in the pathogenesis of signature diabetic retinopathy pathologies and demonstrates that etanercept can inhibit retinal cell death and long-term complication of diabetes. Taken together, our results suggest that etanercept could prove beneficial in preventing both early and late vascular diabetic complications. Leukocyte adhesion to the diabetic retinal vasculature results in early blood-retinal barrier breakdown, capillary nonperfusion, endothelial cell injury, and cell death. We have previously shown that intercellular adhesion molecule-1 (ICAM-1) and the leukocyte integrin CD18 are required for these processes . We alsoTNF-α is the prototypical member of a family of cytokines that also include Fas ligand (FasL), CD40 ligand (CD40L) and TNF-related apoptosis inducing ligand (TRAIL), and induce apoptosis, differentiation, cell activation, and inflammation . TNF-α iTNF-α is a potent inducer of endothelial cell apoptosis ,16. Yet,−/−, B6.129-Tnfrsf1atm1Mak/J), and Rp75  were used . Age-matched C57BL/6J mice served as controls. Rp55−/− and Rp75−/− mice possess normal retinas and are markedly hypomorphic rather than null alleles for tumor necrosis factor receptor I (TNF-RI)-deficient mice and TNF-RII. Animal care guidelines comparable to those published by the Institute for Laboratory Animal Research  were followed and were approved by the Animal Care and Use Committee of the Regierungspräsidium, Köln, Germany.Male Long-Evans rats purchased from Jackson Labs  weighing approximately 200 g at an age of 6 weeks were used. The animals were fed standard laboratory chow and allowed free access to water in an air-conditioned room with a 12h:12h light-dark cycle. Unless otherwise stated, the animals were anesthetized with 40 mg/kg ketamine  and 4 mg/kg xylazine  before all experiments. For long-term experiments, mice deficient for TNF-α receptor protein 55  in 10 mM sodium citrate buffer, pH 4.5 or citrate buffer alone. Then 24 h later, animals with blood glucose levels higher than 250 mg/dl were considered diabetic. In vivo experiments were performed two weeks following STZ injection, and blood glucose was measured again before the onset of the experiments. In previous studies, we had demonstrated that STZ nonconverters do not differ in term of gene expression, amount of blood-retinal barrier breakdown, or leukostasis from nondiabetic controls . Thus, i−/− and Rp75−/− mice and respective controls a diet of Teklad 7004  enriched with 30% D-galactose as previously described [Experimental galactosemia was produced by feeding Rp55escribed . This reescribed .Soluble p75 TNF-α receptor/Fc fusion protein  was reconstituted with sterile water according to the manufacturer’s instructions. Starting one day after the STZ treatment, confirmed diabetic rats were randomized to receiving either etanercept or solvent alone. The drug was administered subcutaneously. The dose was 0.3 mg/kg at three times per week according to the recommendation of the manufacturer for treatment of rheumatoid arthritis in humans and according to our previous studies in the rat model ,20-22. F2PO4, pH 7.4) was injected intravenously via the tail vein at a concentration of 5 µmol/kg (0.668 ml/200 mg bodyweight). After fixation by intracardiac perfusion with 1% paraformaldehyde in PBS labeling with concanavalin A-lectin was performed as described before [Dead and injured endothelial cells were labeled in vivo using propidium iodide . Following the induction of deep anesthesia with 50 mg/kg intraperitoneal sodium pentobarbital, 1 mg/ml PI in PBS . This ELISA detects apoptotic fragmentation in BrdU-labeled DNA. Within 24 h after the last injection of either etanercept or the solvent, the assay was performed as described . BrieflyWhole eyes from normal and diabetic rats treated with either etanercept or vehicle were fixed in 4% paraformaldehyde overnight at 4 °C and embedded in paraffin using standard histological procedures. Terminal Transferase dUTP nick end labeling (TUNEL) staining was performed in tissue sections as previously described ,23,24 usCytokeratin 18 is cleaved by caspases in early apoptotic events. The M30 CytoDeath antibody (Boehringer Mannheim) is a monoclonal mouse IgG2b antibody that binds to a caspase cleaved formalin resistant epitope of the cytokeratin 18 (CK18) cytoskeletal proteins. Immunoreactivity of the M30 antibodies is confined to the cytoplasm of apoptotic cells. It allows the determination of caspase-related enzymatic activity early in the course of apoptosis.2O2, and then incubated for 1 h in incubation buffer (PBS containing 1% BSA and 0.1% Tween-20). The M30 CytoDeath antibody was applied for 1 h at room temperature in a 1:50 dilution in incubation buffer. The sections were subsequently washed in PBS containing 0.1% Tween-20 and incubated with an anti-fluorescein-POD (horse-radishperoxidase) antibody (Roche Diagnostics) according to the manufacturer’s instructions. The peroxidase reaction was developed with DAB , and the slides were counterstained with hematoxylin.M30 Cytodeath immunoreactivity was evaluated as described ,25. In bThe levels of protein expression of caspase 3 and caspase 8 were evaluated by western blotting, performed as described previously ,26. BrieThe activity of caspase 3 and caspase 8 was measured by a colorimetric analysis of the enzymatic conversion of a specific substrate as described . The actTrypsin digestion of the retina was performed according to the method of Cogan et al.  with som±standard deviation (SD). The data were compared by ANOVA with post hoc comparisons tested by using Fisher’s protected least significant difference procedure. The data of the quantitative PCR were analyzed by Whitney-Mann-U-test. Differences were considered statistically significant when p values were less than 0.05.All results are expressed as the meanTo investigate the role of TNF-α in mediating retinal endothelial cell death in early diabetic retinopathy, we assessed the effect of etanercept on retinal endothelial injury using a PI labeling assay as previously described . AccordiTo quantify the apoptotic cell death in the retina, we used a modified ELISA for fragmented DNA . Two weeTo localize the apoptotic cell death within the retina, we stained formalin-fixed, paraffin-embedded retinal sections by using TUNEL assay  and M30 To quantify the amount of apoptotic cell death in the retinal vessels, we determined the ratio of TUNEL-positive endothelial cells or M30-positve cells to the total number of endothelial cells in cross-sections of 12 distinct eyes from each of six animals per group. After two weeks of diabetes, the ratio of TUNEL-positive cells increased 6.2 fold when compared to nondiabetic control animals . Treating diabetic animals with etanercept reduced the TUNEL-positive staining by one-third . Treatment of diabetic animals with etanercept reduced the conversion rate to 65.94 ± 14.35 .To achieve an extended observation period, we investigated galactose-fed mice, which demonstrate similar histopathological changes as diabetic animals . With gaHypergalactosemia reduced the number of endothelial cells in all of the three mouse strains . Endothe−/− and Rp75−/− mice the number of endothelial cells was significantly higher than in galactosemic wild-type mice as counted after 15–16 months  and 18–20 months  of hypergalactosemia. After 20 months of galactosemia, endothelial cell counts in Rp55−/− mice and Rp75−/− mice did not differ significantly from age-matched normal litter mates (90.6±6.3 versus 107±12.3 and 95.8+6.8 versus 96.6±7.2 (p>0.05).However, TNF-α receptor deficiency protected against endothelial cell loss. In both galactosemic Rp55−/−, Rp75−/−, and wild-type mice during the time course of hypergalactosemia  and 20 months .The number of pericytes decreased in all Rp55ctosemia . Maximal−/− 2.25±0.5, and Rp75−/− 2.5±0.57. In all strains, the number of acellular capillaries increased with the duration of galactose feeding. The number of acellular capillaries showed an approximately ninefold increase after 20 months of hypergalactosemia (Furthermore, the formation of acellular capillaries per retina was quantified as described previously ,6,19,28.ctosemia  and a deIn the current study, we investigated the role of the inflammatory cytokine TNF-α in the apoptotic cell death of retinal endothelial cells during early and late stages of diabetic retinopathy using a rat model of streptozotocin-induced diabetes and a mouse model of long-term galactosemia.Our data emphasize the role of TNF-α in signature pathologies in both early and late diabetic retinopathy. We have previously demonstrated that TNF-α increases early during the course of diabetic retinopathy . TNF-α iEndothelial and pericyte cell loss is one of the earliest and key manifestations of diabetic retinopathy. It leads to blood-retinal barrier breakdown, formation of acellular capillaries, microaneurysms, and retinal ischemia that hallmark the transition to proliferative diabetic retinopathy. As we  and otheCaspases, a family of cysteine proteases, are both involved in activation of cytokines as well as in the initiation and execution of apoptosis . InitiatAccording to our data, all the aforedescribed pathologies, including cellular loss, TUNEL reactivity, and caspase activation are significantly reduced in the anti-TNF-α-treated retinas. This leads us to the conclusion that TNF-α is a major player in retinal cell death in diabetic retinopathy. TNF-α is known to be a potent inducer of apoptosis in endothelial cells ,16. TNF However, there might be also an indirect involvement for TNF-α in diabetic apoptotic cell death. In experimental diabetes, adhesion of leukocytes to the retinal vasculature is one of the earliest events and results in enhanced blood-retinal barrier breakdown, endothelial injury, and cell death as well as capillary nonperfusion ,2. As weIn this study, apoptosis was significantly reduced in endothelial cells as well as in the inner nuclear layer in the retinas of diabetic rats upon the administration of the TNF-α inhibitor and the concomitant reduction of leukocyte adhesion. This leads to the conclusion that leukocytes that adhere to the vasculature might be responsible for the observed endothelial apoptosis, whereas leukocytes extravasating to the retinal tissue are responsible for the apoptotic death observed in other cell layers. This is in accordance with our previous data in diabetes, where inhibition of leukocyte-mediated death by neutralizing FasL reduced apoptotic death not only in the endothelial cell layer but also in the ganglion and inner cell layer .To establish a role for TNF-α in the pathogenesis of signature lesions in diabetic retinopathy and to address the question whether the demonstrated effects are only due to its transient overexpression in early diabetes, we used a long-term mouse model of diabetic retinopathy. The course of diabetes in rodents includes the formation of signature lesions similar to those in humans, such as acellular capillary formation, microaneurysms breakdown of the blood-retinal barrier, and macular edema. These similarities allow extrapolating valuable conclusions from the rodent models of long-term diabetes relevant to human diabetes. We have examined the vascular pathology in a mouse model of galactose-induced diabetes that allows for the analysis of the histopathological alterations up to two years after the induction of diabetes. We  and otheIn conclusion, our data indicate that the proinflammatory cytokine TNF-α plays a major role in endothelial and retinal cell injury and apoptosis during diabetes. TNF-α is involved in endothelial apoptosis directly via death receptor-mediated apoptosis and indirectly via an increased leukostasis. Together with our previous data demonstrating the role of TNF-α on diabetic vascular leakage , we can


In this study it is reported that: (1) the levels of bloodplatelet-activating factor and serum tumour necrosis factorsignificantly increased after coronary ligation and reperfusion,compared with sham-ligated controls, in an anaesthetized rat model;(2) compared with vehicle controls, pretreatment with the PAFantagonist BN 50739  produced significantdecreases in infarct size  and the level of serum TNF ; and (3) a significan positive correlation was found between thelevel of blood PAF or serum TNF and infarct size. The presentresults indicate that PAF and TNF may be important mediatorsinvolved in myocardial ischaemia and reperfusion injury, and thatPAF antagonists may exert a protective effect on ischaemic orreperfused myocardium by inhibiting the interaction of PAF and TNF.


Next, we established a Hela cell line, where scapinin expression was induced by tetracycline. In these cells, expression of scapinin stimulated cell spreading and motility. Scapinin was colocalized with actin at the edge of spreading cells. To explore the roles of the RPEL-repeat and PP1-binding domains, we expressed wild-type and mutant scapinins as fusion proteins with green fluorescence protein (GFP) in Cos7 cells. Expression of GFP-scapinin (wild type) also stimulated cell spreading, but mutation in the RPEL-repeat domain abolished both the actin binding and the cell spreading activity. PP1-binding deficient mutants strongly induced cell retraction. Long and branched cytoplasmic processes were developed during the cell retraction. These results suggest that scapinin enhances cell spreading and motility through direct interaction with actin and that PP1 plays a regulatory role in scapinin-induced morphological changes.Scapinin, also named phactr3, is an actin and protein phosphatase 1 (PP1) binding protein, which is expressed in the adult brain and some tumor cells. At present, the role(s) of scapinin in the brain and tumors are poorly understood. We show that the RPEL-repeat domain of scapinin, which is responsible for its direct interaction with actin, inhibits actin polymerization  The actin cytoskeleton is a vital component of a wide variety of cellular and developmental processes such as cell adhesion, cell migration, cell-cell interaction, and signal transduction Scapinin was initially identified as a PP1-binding protein that is tightly associated with nuclear non-chromatin structures (the nuclear matrix or nucleoskeleton) in HL-60 cells, a leukemia cell line Scapinin is a member of phactr/scapinin family, in which the PP1-binding domain and the RPEL-repeat domain are highly conserved. This family includes four members, phactr1, phactr2, scapinin/phactr3, and phactr4 The RPEL-repeat domain is composed of tandem repeats of three RPEL motifs (pfam PF02755) and was initially identified as an actin binding domain in megakaryocytic acute leukemia protein (MAL) in vitro. From these results, we propose a role for scapinin as a regulator of actin cytoskeleton structures.To explore the function(s) of scapinin, we expressed scapinin in cells and monitored their morphological changes. Scapinin expression stimulated cell spreading and motility. Furthermore, mutation experiments showed that both the RPEL-repeat domain and the PP1-binding domain play crucial roles in these morphological changes. Scapinin was colocalized with actin at the edge of spreading cells. The RPEL-repeat domain of scapinin directly interacts with actin and inhibits actin polymerization Scapinin monoclonal antibody was developed as described 5′-AATCTCTATGGCCTGTGGAA-3′, a reverse primer 5′-TCTCTATGGCCTGTGGAATCT-3′, a forward primer 5′-CTGGATGAGATGGACCAAACG-3′, a template poly A+ RNA of HL-60 cells, and a high fidelity RNA PCR kit . The 1.55 kb RT-PCR product was integrated into SmaI site in pKF18k  and sequenced. The BamHI/EcoRI fragment from pKF18k/scapinin was inserted into BglII/EcoRI sites of pEGFP-c2 (Clontech) or into BamHI/EcoRI sites of pcDNA3 (Invitorgen). Deletion and point mutants of pEGFP-c2/scapinin were generated by PCR based mutagenesis as described The full-length scapinin cDNA was obtained by RT-PCR using a RT primer Cos7 and Hela cells were cultured in Dulbecco's modified minimal essential medium (DMEM) containing 10% fetal bovine serum, 100 units/ml penicillin, and 100 µg/ml streptomycin. One day before transfection, cells were seeded on Lab-Tek 8-chambered coverglass or slideglass . 0.1 µg of pEGFP-c2-scapinin and 0.3 µl of the transfection reagent Fugene 6  were mixed and added to cell cultures (0.25 ml medium) according to the manufacturer's instructions. Transfected cells were cultured in DMEM containing 0.5% fetal bovine serum after transfection. Fluorescent cells were observed in the viable state by using a fluorescent microscope, Axiovert S100 (Carl Zeiss Corporation). In starvation/serum stimulation experiments, the concentration of serum was reduced to 0.5% at 3 hours after transfection, and 10% serum was added to the medium for serum stimulation.BamHI and EcoRI sites and established in a Hela cell line. We did not use myc- or 6xhistidine-tags in this study, thus any scapinin expressed was untagged. All procedures in establishing cell lines were followed according to the manufacturer's instructions.To establish Hela cell lines, in which scapinin expression is inducible, we used a tetracycline-regulated mammalian expression system, the T-Rex system (Invitrogen Life Technology). In this system, scapinin expression is depressed in the absence of tetracycline and is induced by the addition of tetracycline to the culture medium. We transfected pcDNA6/TR coding repressor proteins for the tetracycline operator to Hela cells and established a cell line that constitutively produced repressors. We then, transfected pcDNA4/TO/myc-His where the full-length scapinin cDNA was inserted between the 4 cells/ well in 96-well plates and cultured with or without 0.1 µg/ml tetracycline. At each time point, the number of viable cells was assessed by the MTT assay according to the manufacturer's instructions (Promega), and the absorbance was measured at a wavelength of 570 nm with a 96-well plate reader.Cell proliferation was measured by an MTT assay. Hela cells established as above were plated at 1×10To measure cell motility, we used a wound healing assay. Hela cells were cultured on 6-well plates  until confluent. The confluent monolayer cultures were treated with or without 0.1 µg/ml tetracycline for 4 hours and were then wounded with a straight scratch using a yellow pipette tip. After washing them three times with serum-free DMEM, the wounded monolayer cultures were further incubated with or without 0.1 µg/ml tetracycline in DMEM containing 1% fetal bovine serum. To reduce cell growth, the serum concentration was reduced to 1%.Scapinin-inducible Hela cells were grown on Lab-Tek 8-chambered coverglass  and cultured in the presence or absence of 0.1 µg/ml tetracycline to induce scapinin expression. The cells were fixed with 3.7% formaldehyde in phosphate buffered saline for 15 minutes at room temperature, permealized with 0.2% Triton X-100 in PBS for 2 minutes, and incubated with blocking solution  for 15 minutes. The cells were then incubated with 0.2 µg/ml anti-scapinin monoclonal antibody for 1 hour. Anti-scapinin monoclonal antibody was developed as described Scapinin-inducible Hela cells and GFP-scapinin-expressing Cos7 cells were grown on Lab-Tek 8-chambered coverglass and fixed with 3.7% formaldehyde as described above. In the Hela cells, the scapinin was stained with scapinin monoclonal antibody (the first antibody). Alexa Fluor 488-conjugated goat anti-mouse antibody (Molecular Probes) was used as the secondary antibody. Actin was stained with rhodamine-phalloidin. The localization of scapinin, GFP-scapinin, and actin was observed under a laser scanning microscope LSM 5 EXCITER (Carl Zeiss MicroImaging Inc.).2) from weights, the ruled 50×50 µ m area  of a hemocytometer was used as a standard.Scapinin-inducible Hela cells grown on Lab-Tek 8-chambered slideglass were cultured in the presence or absence of tetracycline as described above. The cells were monitored and randomly photographed. After printing the photographs, the cells were cut out with a scalpel, and their weights were determined with a quartz crystal microbalance . Cos7 cells that expressed GFP or GFP-scapinin were randomly photographed under a fluorescent microscope. Fluorescent Cos7 cells were cut out of the printed photographs and weighed with a quartz crystal microbalance as above. To calculate the cell area  as described previously EcoRI (forward primer) or SalI (reverse primer) recognition sequence were added. The cDNA fragment was inserted into EcoRI/SalI sites in pGEX-4T-1 (Amersham Biosciences). GST fusion proteins were produced in E. coli BL21 (DE3) pLys and purified with glutathione-sepharose (Amersham Biosciences). Each GST fusion protein was conjugated to CNBr-activated sepharose at a protein concentration of 5 mg/ml bed volume. HL-60 cells (2×108) were lysed in 0.5% Triton X-100/cytoskeleton buffer  including protease inhibitor cocktail and sonicated. The cell lysate were separated by centrifugation at 10,000 g for 20 minutes and incubated with GST fusion protein-conjugated sepharose beads for 2 hours. After incubation, the beads were washed twice with 0.5% Triton X-100/cytoskeleton buffer and once with RIPA buffer . RIPA buffer was used to reduce non-specific binding of actin to sepharose beads. Finally, proteins were extracted from the beads with SDS sample buffer and were subjected to SDS acrylamide gel electrophoresis.The cDNA fragment of Scapinin coding RPEL repeat(s) was amplified by PCR using a specific primer set, to which 5) grown on 100 mm dishes, and after 24 hours the cells were suspended in 0.5% Triton X-100/cytoskeleton buffer including protease inhibitor cocktail with the aid of sonication. After centrifugation at 10,000 g for 15 mins, the supernatants were incubated with anti-GFP antibody for 3 hours. Immunocomplexes were collected with protein G-agarose beads that had been washed twice with 0.5% Triton X-100/cytoskeleton buffer. For the actin binding assay, after washing with 0.5% Triton X-100/cytoskeleton buffer, protein G-agarose beads were washed once with RIPA buffer to reduce the non-specific binding of actin to agarose beads. Immunocomplexes were subjected to Western blotting with anti-scapinin monoclonal antibody, anti-actin monoclonal antibody, or anti-PP1 polyclonal antibodies.GFP-scapinin plasmids were transfected into Cos7 cells  actins that were unable to polymerize even without GST-RPEL and unable to bind to GST-RPEL and depolymerize, respectively. At and Fup are known values, and Fb is a function of X.The apparent affinity of RPEL-GST for actin was determined by exploiting its ability to inhibit actin polymerization. The dissociation constants (Kd) and number of RPEL binding sites of actin (n) were calculated by nonlinear regression in Igor Pro software  using the following equation:We applied the yeast two-hybrid method to determine scapinin-binding proteins. We have previously determined PP1 as a binding partner with this approach. After further analysis using the C-terminal region (300–518 aa) as a bite, we obtained eight independent clones that coded for β-actin cDNA (data not shown). Three RPEL motifs are perfect fits for the consensus sequence, RPxxxEL, of the RPEL motif . Deletioin vitro pull-down assay with HL-60 cell lysates . To reduce the non-specific binding of actin to agarose beads, GST-RPEL conjugated agarose beads (pull-down samples) were washed twice with 0.5% Triton X-100/cytoskeleton buffer and once with RIPA buffer . Without a stringent wash with RIPA buffer, substantial amounts of actin were nonspecifically co-precipitated with the agarose beads. Scapinin-RPEL constructs of 350–468 aa and 350–422 aa bound with actin in vitro, but a single RPEL motif construct (350–385 aa) showed no actin-binding activity  or two proline residues (PP34/78AA) of the PREL-repeat domain E. Coli, and the purified samples included substantial amounts of cleaved polypeptides , respectively. Cell spreading of parental Hela cells was not enhanced by tetracycline treatment . MAL translocates from the cytoplasm to the nucleus upon serum stimulation (15% FBS) after starvation (0.5% FBS) 2 and 1576±221 µm2  respectively. In Cos7 cells, GFP-scapinin was predominantly distributed throughout cells. Notably, GFP-scapinin was frequently distributed in membrane ruffle-like structures  also induced cell spreading in Cos7 cells . Cell arructures . Confocaructures . This reTwo approaches using a transient expression system  and a teA mutant without the PP1-binding domain (Δ469–518) induced cell rounding or shrinkage instead of cell spreading. Notably, cell rounding and shrinkage were accompanied by development of long and branched cytoplasmic processes. Allen et al. Time course of morphological changes induced by a PP1-binding deficient mutant of F515A showed that, at early times (6 hours) after transfection, some cells expressing F515A mutant showed spread morphologies like wild-type scapinin expressing cells, but they promptly shrank to show rounded morphologies with long and branched cytoplasmic processes . We obtaFurther deletion of the C-terminal region including the three RPEL motifs (Δ359–518) completely abolished the morphology-changing activities . Δ359–51in vitro. Then, we introduced mutations into the second motif of the RPEL repeat, the RP>AA mutant, in which both arginine (407) and proline (408) residues have been replaced with alanine . Favot et al. This study suggests that scapinin can enhance cell spreading and motility through interactions with actin cytoskeletons. EST clone analysis demonstrated the presence of scapinin gene transcripts in some tumors cells such as lung and kidney carcinomas. Cell migration is a critical step in tumor invasion and metastasis, and regulation of this process will lead to therapies for treating cancer PP1 is a major eukaryotic serine/threonine protein phosphatase that regulates diverse cellular processes such as muscle contraction, glycogen metabolism, neuronal signaling, and actin cytoskeleton organization humpty dumpty mouse mutant phenotype with failure to close the neural tube and optic fissure is caused by a missense mutation in phacrt4 (a member of the phactr/scapinin family), and interestingly, the missense mutation specifically disrupts binding to PP1 It was reported that the humpty embryos display elevated proliferation and abnormally phosphorylated, inactive PP1, resulting in RB hyperphosphorylation and derepression of E2F targets. We initially identified scapinin as a component of the nuclear nonchromatin structures (nuclear matrix or nucleoskeleton) in HL-60 cells and found that scapinin is down-regulated during differentiation induced by all-trans retinoic acid treatment (an anti-tumor drug). Recently numerous studies have established the presence of actin in the nucleus and have shown that actin is involved diversely in nuclear activities including gene transcription, chromatin remodeling, and nucleocytoplasmic trafficking The scapinin/phactr3 gene has four leader exons, implying that regulation of its gene expression may be complicated scapinin/phactr3 gene may make it difficult. Further genetic studies are necessary to determine the roles of scapinin in cell proliferation and morphogenesis of normal neuronal tissues.The


In humans, four genes encode PMCA proteins termed PMCA1-PMCA4. PMCA4 is the major PMCA isoform expressed in human corneal epithelium (hCE); however, little is known about its role. The present study documented expression of PMCA4 in rabbit CE (rbCE) and followed the distribution of PMCA4 during CE wound healing in a rabbit (rb) model.Plasma Membrane Calcium-ATPases (PMCAs) are integral membrane proteins essential to the control of intracellular CaPMCA4 was used to transfect telomerase-immortalized human corneal epithelial (hTCEpi) cells. Cell cultures were wounded 48 h after transfection, and the wound area was measured at 0 h and at 3 h intervals post-wounding.Reverse transcriptase PCR using PMCA4 isoform gene-specific primers that flanked alternative splice site A was used to examine the presence of PMCA4 mRNA in rbCE. Protein expression was assessed by immunoblotting using panPMCA- and PMCA4-specific antibodies. Immunocytochemistry was employed to examine PMCA immunolocalization in frozen, formaldehyde-fixed sections of control and wounded rb corneas. In wound healing studies, circular, 6-mm diameter corneal wounds were produced in the central CE using the n-heptanol technique. The distribution of PMCA4 in CE was examined by immunohistochemical staining of frozen sections using PMCA4 isoform-specific antibody at 6-, 24-, 36-, and 48 h post-injury. siRNAPMCA4 transfected hTCEpi cells failed to seal the wound area, whereas wounds in control cultures transfected with a scrambled construct were completed healed.Direct sequencing of PCR DNAs documented the presence of PMCA4 transcripts in rbCE and showed that the splice variant at site A was PMCA4x. Immunoblot analysis for PMCA4 detected an intense band at approximately 160 kDa and a faint band at approximately 142 kDa. Immunohistochemistry with the panPMCA antibody demonstrated strong immunoreactivity (IR) in all layers of uninjured rbCE. Immunohistochemistry with a PMCA4-specific antibody demonstrated a similar pattern of intense IR along the plasma membrane of cells in all layers of CE, except for the notable absence of PMCA4 IR along the basal cell membranes adjacent to the stroma. The pattern of PMCA4 IR changed following wound healing. During the lag phase of corneal epithelial wound healing, PMCA4 IR was seen mostly on apical plasma membranes of basal cells near the wound margin, with little staining of basal plasma membranes. During the migration phase (24 h), PMCA4 IR was found mostly on basal cell membranes adjacent to the stroma. At 6 h and 24 h following wounding, PMCA4 IR of the cytoplasm was increased compared to control eyes. After closure of the denuded area and stratification, PMCA4 IR was again primarily found along the apical and lateral plasma membranes of basal cells and was again absent from basal cell membranes adjacent to the stroma; PMCA4 IR of the cytoplasm was also similar to that observed in control eyes. siRNAPMCA4 is strongly expressed in rabbit CE and its immunolocalization exhibits marked changes in distribution during the wound healing process. Knockdown of PMCA4 expression in hTCEpi cells decreases wound healing. Present findings suggest that PMCA4 redistribution could function as one factor in mediating calcium-regulated events necessary for cell migration in regenerating CE. The corneal epithelium (CE) after artificial wounding provides a valuable model to study the migration of stratified epithelial cells in vivo. The CE is a nonkeratinized stratified squamous epithelium that covers the anterior surface of the cornea -4. It coCE exhibits a highly developed ability to repair itself following wounding; thus, providing a mechanism to quickly re-establish integrity of its critical barrier functions . The pro2+ concentrations regulate integrin-mediated adhesion during cell migration i i ,25.2+ concentration is plasma membrane Ca2+-ATPase (PMCA). PMCAs are present in the surface membranes of cells and extrude Ca2+ against very large concentration gradients i i ,36,37,392+ as messenger or trigger, including synthesis of proteins and glycoproteins [2+]i may occur during the wound healing process, and that changes in [Ca2+]i could function in the regulatory programs that direct changes in cell motility, morphology and adhesion.It has been shown that during the migration phase of mouse CE wound healing, PMCAs redistribute from plasma membrane caveolae to membranous structures in the cytoplasm. PMCAs then returned to the plasma membrane when the defect was healed ,42. Thisproteins , glycogeproteins , and actproteins ,45,46. RPrior studies in our laboratory have determined the expression of PMCA splice variants and their distribution in native human corneal epithelium ,48. ThesCritically, there was lack of PMCA4 immunoreactivity along the portion of the plasma membranes of basal cells adjacent to the underlying stroma. Because basal cells in CE are the only cells in CE capable of mitosis and CE wound repair, and the localization of PMCA4 differs in basal cells compared to the other cell types  that comprise CE, we hypothesized that PMCA4 would be a good “candidate PMCA” to study. Thus, in the present work, we investigated the localization of PMCA4 during CE wound healing in a rabbit (rb) model. We report here that during CE wound healing, PMCA4 redistributes in the plasma membrane of CE cells at the wound margin and returns to its normal distribution soon after the wound is closed. We hypothesize that PMCA4 redistribution is a factor in mediating calcium-regulated events necessary for cell migration in regenerating CE.Experiments were conducted according to the guidelines of Indiana University School of Medicine and in compliance with federal regulations governing the use and protection of animal subjects in research. A total of 14 male, New Zealand albino rabbits, approximately 4–5 pounds each, were purchased from Kuiper Rabbit Ranch  for use in this study.2HPO4, 0.016 M KH2PO4, 0.9% NaCl). Sample preparation, electrophoresis, and immunoblotting were done as previously described i and to selectively respond to signals regulating [Ca2+]i and junctional levels of Ca2+ during CE wound healing. To fully understand calcium handling by the corneal epithelium during the wound healing process, the transporters catalyzing calcium efflux must be characterized. The present work has begun this process by examining PMCA4 expression and distribution in rabbit corneal epithelial wound healing, and the knockdown of PMCA4 expression in corneal epithelial wound healing in vitro. The stage is now set for additional studies to further characterize the functional role(s) of each PMCA isoform in wound healing of stratified epithelium. These functional experiments might include the selective knockdown of additional PMCA isoform expression in corneal epithelial cells during adhesion and migration studies, and may also investigate possible interactions of PMCAs with fodrin, actin and E-cadherins.This study shows that PMCA4 is strongly expressed in rabbit corneal epithelium and that the pattern of PMCA4 IR markedly changes during the process of corneal epithelial wound healing. The functional significance of the change in PMCA4 localization is not resolved by this study, however, the results here suggest a role for PMCA4 in migration during CE wound healing. Most certainly Ca


SP thymocytes exhibited a poor ability to produce TNF when compared to splenic T cells despite expressing similar TCR levels and possessing comparable activation kinetics (upregulation of CD25 and CD69). Provision of optimal antigen presenting cells from the spleen did not fully enable SP thymocytes to produce TNF, suggesting an intrinsic defect in their ability to produce TNF efficiently. Using a thymocyte adoptive transfer model, we demonstrate that the ability of T cells to produce TNF increases progressively with time in the periphery as a function of their maturation state. RTEs that were identified in NG-BAC transgenic mice by the expression of GFP showed a significantly enhanced ability to express TNF relative to SP thymocytes but not to the extent of fully MN T cells. Together, these findings suggest that TNF expression by naïve T cells is regulated via a gradual licensing process that requires functional maturation in peripheral lymphoid organs.The peripheral naïve T cell pool is comprised of a heterogeneous population of cells at various stages of development, which is a process that begins in the thymus and is completed after a post-thymic maturation phase in the periphery. One hallmark of naïve T cells in secondary lymphoid organs is their unique ability to produce TNF rapidly after activation and prior to acquiring other effector functions. To determine how maturation influences the licensing of naïve T cells to produce TNF, we compared cytokine profiles of CD4 Contact with secondary lymphoid cells (spleen and lymph node) during TCR activation partially enables SP thymocytes to produce TNF in vitro by providing optimal antigen-presentation. However, the frequency of TNF producing cells is still significantly lower than in the periphery. RTEs in the spleen on the other hand, display an intermediate TNF response, which is higher than their SP thymic precursors but lower relative to the fully MN T cells. The differences in the TNF profile exhibited by these 3 populations of lymphocytes mirrors their distinctive maturation status. Moreover, as developing T cells mature in the periphery, they show a progressive increase in their capability to produce TNF upon TCR activation. Together, these findings suggest that naïve T cells become gradually licensed to efficiently produce TNF in a maturation-dependent manner that requires their localization to secondary lymphoid organs.Given the important role of TNF in regulating immune responses, here we determined the developmental stage when naïve T cells become competent to produce TNF by comparing the capability of SP naïve T cells to produce TNF before and after emigration from the thymus. These studies reveal that CD4+ and CD8+ T lymphocytes (CD44lo) from secondary lymphoid organs rapidly produce TNF after TCR engagement before gaining other effector functions + and CD4+ TCR-transgenic mice  were stimulated with specific peptides and αCD28 costimulation for 4 hrs in vitro. + CD8− and CD4− CD8+ SP thymocytes produced TNF when compared to naïve (CD44lo) splenic T cells during TCR stimulation. This inability to produce TNF was not overcome by increasing the concentrations of the peptide (data not shown). To determine if the reduced TNF response by SP thymocytes was due to a lower TCR expression on SP thymocytes relative to naïve splenic T cells + thymocytes and naïve (CD44lo) splenic T cells were stained with mAbs to TCR Vα2 and TCR Vβ8.1. + thymocytes and splenic T cells were similar. Next, to determine if the reduced ability of SP thymocytes to produce TNF was due to a generalized defect in their activation, we examined the expression of activation markers CD25, CD69, CD44 and CD62L on the P14-CD8+ SP thymocytes and splenic T cells. As shown in Naïve CD4+ SP P14-CD8+ thymocytes were stimulated in the presence of either WT CD45.2+ H-2Db-positive B6 splenocytes or CD45.2+ H-2Db-deficient B6 splenocytes (incapable of presenting GP33 to P14 cells). In comparison to the high frequencies of TNF-producing splenocytes depicted in + thymocytes that produced TNF, when stimulated in the presence of WT B6 splenocytes . We then determined whether SP P14-CD8+ thymocytes produced TNF as a consequence of changes occurring in antigen presenting cells during the co-culture, by using irradiated splenocytes. We found that SP P14-CD8+ thymocytes stimulated with irradiated (3000cGy) WT B6 splenocytes showed a similar increase in the proportion of TNF producing cells comparable to SP P14-CD8+ thymocytes stimulated with live WT B6 splenocytes (b-deficient splenocytes (live or irradiated) did not produce TNF. Together, these results indicate that although optimal TCR-MHC interactions provided by spleen cells enable a small subset of SP thymocytes to produce TNF, the frequency of cells and the level of TNF produced on a per cell basis was reduced compared to peripheral naïve CD8+ splenic T cells, suggesting an intrinsic defect in SP thymocytes to produce TNF efficiently upon TCR activation.Recent studies have shown that thymic DCs and splenic DCs have unique properties and that the microenvironment contributes to their distinct functions enocytes . Both puenocytes , indicat−CD8+ and their respective naïve splenic (CD44lo) counterparts purified from (transgenic) P14 mice at resting state. SP P14-CD8+ thymocytes were sorted to 98% purity and (CD44lo) P14-CD8+ splenic T cells were sorted to 90.3% purity −CD8+) and their naïve splenic counterparts were similar and the differences were not significant (+ thymocytes and naïve (CD44lo) splenic T cells that were stimulated as indicated. We found that the levels of TNF mRNA were dramatically higher in (CD44lo) P14-CD8+ splenic T cells during GP33 and GP33+αCD28 stimulation relative to SP thymocytes. The levels of TNF transcripts increased in the thymic subsets upon stimulation but not to the extent detected in the splenic subset  for 2 days. The spleens of recipient mice were recovered 4 hours later and directly stained for intracellular TNF by the donor T cells. Both P14-CD8+ and SMARTA-CD4+ donor T cells produced TNF in mice that were infected with WT LCMV Armstrong  during LCMV infection  followed by subgroup 2 (CD24hi-intQa2lo), subgroup 3 (CD24lo Qa2lo) and finally subgroup 4 (CD24lo Qa2hi) which was the most mature + thymocytes that produced TNF displayed a more mature phenotypic profile with the majority of the TNF producers falling in subgroups 2 and 3 compared to the TNF non-producers that fell mostly in subgroups 1 and 2. The maturation differences between the TNF-producing SP thymocytes and the non-producers were also seen in the MFI changes in CD24, CD45RB and Qa2  that approached a level similar to that of splenic T cells by day 14 after transfer. While the recovery of donor cells diminished over time, as shown in lo) donor CD45.1+ SP P14-CD8+ thymocytes producing TNF from day 2 to day 14 after transfer (+ P14-CD8+ thymocytes was significant (p<0.05) and was consistent with the increasing maturation phenotype observed at these time points  from secondary lymphoid organs rapidly produce TNF after TCR engagement before gaining other effector functions + CD8− and CD4− CD8+ SP thymocytes produced TNF when compared to naïve (CD44lo) splenic T cells during TCR stimulation  hi), RTEs (GFPhi+lo) in the spleen, and MN T cells (GFPneg) in the spleen  thymocytes in vitro − CD8− double negative thymocytes that coexpressed both TNFR1 and TNFR2 at low doses but stimulated proliferation at higher doses + and SP CD8+ T cell subsets due to absence of apoptosis in DN thymocytes Several studies have shown that TNF is expressed in the thymus and have demonstrated that this TNF has a physiological role within the thymus. In situ hybridization studies revealed the localization of TNF mRNA to the cortical regions of the thymus during ontogeny, and studies by Giroir et.al showed that there was constitutive expression of TNF in thymic lymphocytes Trypanosoma Cruzi show severe thymocyte depletion of CD4+ CD8+ DP thymocytes due to an exacerbated inflammatory reaction mediated by TNF Alternatively, there is also evidence showing the dangerous effects of deregulated production of TNF in the thymus. For instance, mice that over-express human TNF within the thymus exhibit thymic atrophy, which is primarily associated with premature apoptosis of double negative (DN2) developing thymocytes and diminished numbers of cortical thymic epithelial cells (cTECs) + T cells with the transcriptional inhibitor actinomycin-D completely abrogated the production of TNF, suggesting that transcription is vital for TNF protein synthesis by naïve CD8+ T cells + SP thymocytes upon TCR stimulation, but this is insufficient for the optimal production of protein. The splenic T cells, on the other hand, show a dramatic upregulation in TNF message and protein upon activation. Work done in Jurkat T cells and macrophages has revealed that the AU rich regions of the 3′UTR of TNF mRNA is vital for TNF regulation A previous report revealed that TNF production by T cells does not require de novo mRNA expression from the TNF locus, as primary CD4 T cells contain a premature TNF transcript which, following TCR engagement, is spliced to form a mature TNF message, resulting in the synthesis of TNF protein in the absence of new transcription Stimulation in the presence of splenocytes partially enabled SP thymocytes to produce TNF efficiently as there was only a partial increase in the proportion of cells producing the cytokine. This effect may be either due to better antigen presentation of exogenous peptides by splenocytes to SP thymocytes. For example, secondary lymphoid cells (spleen and lymph nodes) might offer additional accessory signals leading to enhanced clustering of adhesion molecules during immunological synapse formation and to the partial production of TNF + SP P14-CD8+ thymocytes with time in the periphery may be due to preferential survival of SP thymocytes that are capable of TNF production. Nevertheless, the hierarchical pattern observed in the MFI of the TNF signal of transferred thymocytes and polyclonal RTEs clearly indicates that the progressive gain in the TNF producing capability of naïve T cells occurs as they mature in the periphery.Contact with secondary lymphoid organs is vital for the completion of post-thymic maturation of developing SP thymocytes In mice, developing thymocytes emigrate and populate the periphery at the rate of 1–2% of thymocytes per day throughout the life In conclusion, our findings indicate that the licensing of naïve T cells for rapid TNF production is determined by their developmental state. It is an intrinsic property of the developing T cells that is acquired gradually, where functional maturation in secondary lymphoid organs drives developing naïve T cells to eventually attain full competence to produce TNF efficiently during TCR stimulation.Guide for the Care and Use of Laboratory Animals .All the experiments with animals were done in compliance with the institutional guidelines as approved by the University of Massachusetts Institutional Animal Care and Use Committee (IACUC). Animals were maintained in accordance with the + C57BL/6J (B6) mice were purchased from The Jackson Laboratory  and used at 6–12 weeks of age. CD45.1+ P14 CD8+ TCR-transgenic mice, with T cells that recognize the Db-restricted, LCMV epitope GP33-41 + SMARTA CD4+ TCR-transgenic mice, with T cells that recognize the IAb-restricted, LCMV epitope GP61-80 + OT-1 CD8 TCR-transgenic mice, with T cells that recognize the Kb-restricted, ovalbumin epitope OVA257-264 + OT-2 CD4 TCR-transgenic mice, with T cells that recognize the IAb-restricted, ovalbumin epitope OVA323-339 + and CD45.2+ background and were used at 6–12 weeks of age btm1 N12 (H-2Db KO) mice were purchased from Taconic Farms and used at 6 weeks of age. All animals were housed and maintained within the Department of Animal Medicine at UMMS.Male and female CD45.2b-restricted CTL 4 PFU of each virus strain i.p. Stocks of LCMV, strain Armstrong, and a LCMV variant GP1V virus that possesses an amino acid mutation at position 38 (F to L) in the GP33-41 epitope of LCMV Armstrong were used. This mutation results in the escape of the virus from recognition by LCMV specific D6 cells) were stimulated with either 1 µM of the indicated peptide with monoclonal antibodies specific for CD3e  and CD28  or with PMA (0.5 µg/ml) and ionomycin (0.5µg/ml) in the presence of GolgiPlug™ (0.1 µg/ml) for 4 hours at 37°C in 5% CO2. In some experiments, thymocytes were co-cultured at 1∶1 ratios with either splenocytes from the indicated mouse strains or with the indicated cell populations derived from the spleens of congenic B6 mice and stimulated simultaneously. After the incubation, cells were stained with monoclonal antibodies specific for congenic markers (CD45.1: A20) and (CD45.2: 104), CD4 (RM4-5), CD8 (53-6.7), CD25 (PC61), CD44 (IM7), CD62L (MEL-14), CD69 (H1.2F3), CD24 (M1/69), Qa2 (1-1-2), TCR Vα2 mAb (B20.1) and Vβ8.1 mAb (MR5-2) purchased from BD Pharmingen and CD45RB (C363.16A) from eBioscience. Following the surface stain, cells were fixed and permeabilized using BD Cytofix/Cytoperm™ solution and then stained for intracellular TNF (MP6-XT22 from BD Pharmingen) and CD4 as described previously hi+lo and GFPneg cells in the thymus and the spleen. Samples were analyzed using a Becton Dickinson LSRII Flow Cytometer (BD Biosciences) and FlowJo software .Single cell suspensions of thymocytes and splenocytes were prepared in RPMI 1640 supplemented with 10% FBS, 100U/ml penicillin, 100µg/ml streptomycin sulfate and 2mM L-glutamine and stimulated as indicated. For intracellular cytokine assays, lymphocytes (2×10− CD8+ SP thymocytes and naïve (CD44low) splenic T cells using the MoFlo™ XDP cell sorter (Beckton Coulter). The purity of SP CD8 thymocytes was 98% and the purity of CD8+CD44low splenic T cells was 90.3%. For cell enrichment, subsets of P14-CD8+ T cells were obtained by negative magnetic selection in 1× PBS with 2% FBS, 2mM EDTA. For this, thymocytes were depleted of CD4+ cells and splenocytes were depleted of CD4+ and CD19+ cells by initially staining the cells with biotinylated anti-CD4  and anti-CD19  followed by selection with Streptavidin (SA) microbeads . The purification of CD8+ cells after negative selection was 60% from both tissues. To isolate cell subsets from the CD45.2+ splenocytes for the co-culture experiments described above, B cells were positively selected using anti-CD19 microbeads and T cells were positively selected by Thy1.2 microbeads (Miltenyi Biotech). The cells remaining in the flow-through were used as a source of splenic APCs (20% CD11c+).Single cell suspensions of thymocytes and splenocytes from P14 TCR transgenic mice were purified by staining with anti-CD4, anti-CD8 and anti-CD44 antibodies in 1× PBS with 2% FBS, 2mM EDTA and sorted for CD45′-CAT CTT CTC AAA ATT CGA GTG ACA A-3′, RV 5′- TGG GAG TAG ACA AGG TAC AAC CC-3′ primers  5′-CGA GGC CCA GAG CAA GAG AG-3′, RV 5′- CGG TTGGCC TTA GGGTTC AG-3′ and  were used. The following program was used for the real time PCR reaction, Cycle 1: (1×) step 1: 95°C for 10:00; Cycle 2: (40×) step 1: 95°C for 00:15; step 2: 60°C for 1:00; Cycle 3: (1×) step 1: 95°C for 1:00; Cycle 4: (80×) Step 1: 55°C for 00:10. For absolute quantification of the data, standard curves were generated using serial dilution of pCR® 4 –TOPO M13 plasmids containing cDNA clones of TNF and β actin.T cell subsets purified either by sorting or enrichment were used as indicated. Total RNA was isolated using a RNA isolation kit . An additional step was incorporated to remove genomic DNA using a RNAse-free DNAse kit (Qiagen). The concentration of recovered RNA was determined using the NanoDrop® ND-1000 spectrophotometer . RNA (25 or 50 ng as indicated) was reverse-transcribed into cDNA using Superscript™ III first strand synthesis system  using oligo(dT) primers. Amplification of the cDNA was then performed by Real time PCR with the SYBR® green mastermix  using MyiQ™ BioRad icycler. The following TNF primers: FW + P14 and CD45.1+ SMARTA mice 10×106 each (mixed at a 1∶1 ratio) were treated in vitro with 0.5 µg/ml GolgiPlug (BD biosciences) for 20 min at 37°C. Following the incubation, the cells were adoptively transferred into CD45.2+ B6 hosts that were infected 2 days previously with 5×104 PFU of LCMV Armstrong or GP1V CTL escape variant. Additionally each mouse received 250 µg of bfA (Sigma) i.v. Four hours after transfer, host spleens were harvested and donor T cells were stained directly for TNF using the intracellular cytokine staining protocol as described above. Additionally, 20×106 P14 thymocytes and splenocytes were transferred separately into uninfected CD45.2+ B6 hosts in the absence of bfA. Host spleens were harvested 1, 2, 7 and 14 days after transfer and stimulated in vitro with 1 µM GP33 peptide and αCD28 (2.5µg/ml) in the presence of GolgiPlug™ (0.1 µg/ml) for 4 hours at 37°C in 5% CO2 followed by standard intracellular cytokine staining protocol for TNF by donor T cells as described above. Dead cells were excluded using Live Dead Aqua Dead cell stain  for this experiment.This assay was modified from a previously published protocol Sample analyses were done using Graph Pad Prism (Graph Pad Software). A one-way ANOVA with a Tukey post-test was used to compare multiple samples, with a P value of <0.05 considered significant.


Mycobacterium tuberculosis (Mtb) infection is complex. Experimental evidence has revealed that tumor necrosis factor (TNF) plays a major role in host defense against Mtb in both active and latent phases of infection. TNF-neutralizing drugs used to treat inflammatory disorders have been reported to increase the risk of tuberculosis (TB), in accordance with animal studies. The present study takes a computational approach toward characterizing the role of TNF in protection against the tubercle bacillus in both active and latent infection. We extend our previous mathematical models to investigate the roles and production of soluble (sTNF) and transmembrane TNF (tmTNF). We analyze effects of anti-TNF therapy in virtual clinical trials (VCTs) by simulating two of the most commonly used therapies, anti-TNF antibody and TNF receptor fusion, predicting mechanisms that explain observed differences in TB reactivation rates. The major findings from this study are that bioavailability of TNF following anti-TNF therapy is the primary factor for causing reactivation of latent infection and that sTNF—even at very low levels—is essential for control of infection. Using a mathematical model, it is possible to distinguish mechanisms of action of the anti-TNF treatments and gain insights into the role of TNF in TB control and pathology. Our study suggests that a TNF-modulating agent could be developed that could balance the requirement for reduction of inflammation with the necessity to maintain resistance to infection and microbial diseases. Alternatively, the dose and timing of anti-TNF therapy could be modified. Anti-TNF therapy will likely lead to numerous incidents of primary TB if used in areas where exposure is likely.The immune response to  Tuberculosis (TB) is the leading cause of death due to infectious disease in the world today. It is estimated that 2 billion people are currently infected, and although most people have latent infection, reactivation occurs due to factors such as HIV-1 and aging. Antibiotic treatments exist; however, there is still no cure and the current vaccine has proven to be unreliable. Experimental science has uncovered a plethora of immune factors that help the host control infection and maintain latency. One such factor, tumor necrosis factor alpha (TNF), is a protein that facilitates cell–cell communication during an inflammatory immune response. Animal models have shown that TNF is necessary for control of TB infection. Different types of anti-TNF drugs were developed for patients with non-TB related inflammatory diseases such as rheumatoid arthritis and Crohn's disease. Some of these patients who had latent TB suffered reactivation, especially with one drug type. Because these studies cannot be performed in the mouse, and nonhuman primates are expensive, we developed a computational model to perform virtual clinical trials (VCTs) that predicted why reactivation occurs and why it happens differentially between the two classes of drugs tested. We make recommendations on how this issue can be combated. Mycobacterium tuberculosis (Mtb) infection is a result of a successful immune response that requires priming and activation of antigen-specific CD4+ and CD8+ T lymphocytes, recruitment of cells to the infection site , and production of cytokines, some of whose role is to activate macrophages. This leads to inhibition or killing of some but not all bacilli. Immunological structures (granulomas) form in the lung in response to persistent antigen and cytokine and chemokine signals. In 95% of infected hosts, M. tuberculosis (Mtb) persists without causing symptoms or disease. Latent infection can subsequently reactivate to cause active TB. Experimental evidence has revealed that tumor necrosis factor (TNF) plays a major role in host defense against Mtb in both the active and chronic phases of infection  . Both foSeveral biologic inhibitors (antibodies and receptor fusion molecules) have been developed that interfere with TNF activity and are used to control inflammation in diseases such as rheumatoid arthritis ,22 and CThe present study takes a theoretical approach toward characterizing the role of TNF in protection against the tubercle bacillus in both active and latent infection. We extend our previous models –31 to inWe describe results in these different areas of TNF study: mathematical modeling of typical infection progressions in humans, mechanisms driving infection outcomes, and anti-TNF therapies. Deletion and depletion experiments are discussed in Negative control simulations have been performed on the model . The mod3 of granulomatous tissue), and all intracellular bacteria . IL-12, IL-10  and Th1 cells (α32) throughout the infection  is only significant in the first 250 days post-infection, suggesting that it is important for establishing latency but not maintaining it  with bacterial load throughout the course of infection. On the other hand, macrophage activation plays a more important role in maintaining latency: the correlation between macrophage activation rate (3k) and bacterial load is significant only after latency is achieved (<1 year). TmTNF effects on macrophage (3f) and lymphocyte activation (d) are not significant in either achieving or maintaining latency.The model predicts that enhanced recruitment of lymphocytes  is a desirable strategy toward establishing latency, as suggested by the strong and very significant negative correlation of TNF-dependent recruitment parameters  that is cleaved into sTNF in vivo. We introduce a parameter σ to indicate the fraction of TNF cleaved. The remaining (1 − σ )αF represents tmTNF (where sTNF + tmTNF = ασ F + (1 − σ )αF = αF. Considering the relative transient expression of tmTNF in vitro [σ is approximately 95%  so that the majority of tmTNF is cleaved and released in its bioactive soluble form. We test variations on levels of σ (percent sTNF) and report results in two settings in σ) and look at the effects on bacteria load, and then we deplete different levels of σ after latency has been attained.Little or no data are available to indicate the fraction of TNF . We obtain a similar dynamic during a depletion experiment where at day 500 (after latency is attained) we deplete varying levels of sTNF from the system  of anti-TNF treatments . We define each drug as having a specific ability to neutralize TNF at the granuloma site; these data are not currently known . We define reactivation threshold (RT) as a level (percent of TNF in latency) of bioavailable TNF below which results in reactivation . Considering the transient expression of tmTNF in vitro [σ varies between 50% and 100%. A series of VCT were simulated assuming different TNF bioavailability ranges induced by the two different treatments and a natural biological variation of in vitro , we assuIf TNF bioavailability at the granuloma site is <20% of baseline latency level (at the initiation of therapy at 500 days), both treatments induce 100% reactivation. In the range 20%–30%, anti-TNF antibody always causes reactivation, while TNFR2Fc reactivates 83/100 virtual patients. At higher bioavailability ranges (30%–50%), the differential risk of reactivation goes down to 34 or 4 per 100 virtual patients for anti-TNF antibody versus TNFR2Fc, respectively. No reactivation occurs for both treatments if more than 50% of TNF is bioavailable. The prediction that anti-TNF antibody treatment has a stronger impact on reactivation risk than TNFR2Fc in the bioavailability range of 20%–50% suggests that other factors may be playing a role in reactivation in addition to bioavailability. To explore this, we simulated another clinical trial.σ) may also be an important variable. First, we will assume that both molecules equally affect TNF bioavailability so we can explore independently the effects of sTNF versus tmTNF levels. σ to investigate the role of tmTNF in TB reactivation during anti-TNF therapy. If we assume that σ is not very variable in the population and approximately equal to 95% , and we vary TNF bioavailability in the same range for both treatments (between 20% and 50%), our model predictions show that the differential reactivation risk is 34 per 100 anti-TNF antibody-treated virtual patients versus 28 per 100 TNFR2Fc-treated virtual patients . So, a lower σ (more tmTNF and less sTNF) has a negative impact on maintaining latency during anti-TNF antibody treatment.In addition to bioavailability, the percentage of total TNF cleaved .Our sensitivity analysis  demonstrtmTNF-MI). Thus, anti-TNF treatment reduces the number of MAs and T8 cells and increases bacterial levels, increasing risk of reactivation. Although anti-TNF antibody also reduces the number of MIs, this is not sufficient to maintain latency. This may explain why a higher percentage of tmTNF has a negative impact on infection containment during anti-TNF antibody treatment: with more tmTNF, more MAs and T8 cells are lost from the granuloma.The cell loss rate of MI negatively correlated with total bacterial load (μσ (between 50% and 100%), setting different protocols for treatment duration. There is a significant difference in average RTs between a 12-month regimen and 18- or 24-month regimen for both treatments. We tested whether bacterial load at treatment initiation affects reactivation risk. If the total bacterial load is <500 CFU, no reactivation is observed for both treatments. If total bacterial load is 2–3 fold higher than latency level (∼ 3–4e3 CFU), the system always reactivates for both treatments (unpublished data).Duration of treatment also affects risk of reactivation for both therapies. If treatment starts before infection with Mtb occurs, we assume that drug penetration is not relevant because the granuloma has not yet formed. We assume instead that a certain concentration of anti-TNF molecules are present in the lung where granulomas would begin to form in response to infection. Average serum concentrations of anti-TNF molecules are published  but no dThe major findings from this study are that bioavailability of TNF following anti-TNF therapy is the primary factor for causing reactivation of latent infection, that anti-TNF therapy will likely lead to numerous incidents of primary TB if used in areas where exposure is likely, and that sTNF—even at very low levels—is essential for control of infection.σ of total TNF cleaved is decreased, i.e., allowing more tmTNF in the system.Our model predictions see  recapituWe use the model to analyze the effects of anti-TNF therapy by simulating anti-TNF antibody and TNFR2Fc. The reported measure unit for a steady state or average concentration of anti-TNF drugs in serum is on the order of μg/ml. Data on soluble TNFRs concentration in serum are on the order of ng/ml . We use The VCT simulations suggest that TNF bioavailability is the main factor leading to reactivation by anti-TNF treatments in latently infected patients. Reactivation always occurs if both drugs penetrate the granuloma equally well (TNF bioavailability less than 20%). High bacterial load at treatment initiation increases the likelihood of reactivation. This suggests that a complete regimen of antibiotic treatment for Mtb infection prior to anti-TNF treatment could reduce the risk of reactivation. If TNF bioavailability is equally affected by the two treatments, differential cell level losses induced by anti-TNF antibody therapy accounts for higher reactivation rates: activated CD8+ T cells and MA loss are not compensated by the apparently beneficial effect of MI loss. We speculate that the intracellular bacteria released after MI death induced by antibody binding to tmTNF  can only facilitate bacterial clearance by the host and does not enhance dissemination. Further, our results show that the longer patients are exposed to anti-TNF drugs through longer duration treatment protocols, the risk of reactivation increases. If infection with Mtb occurs after treatment is initiated, chances of developing active infection are very high if we assume reasonable levels of drug penetration into lungs (TNF bioavailability <50%). This is particularly important if anti-TNF treatments are implemented in regions of the world where infection risk is elevated. Bacteria grow uncontrolled when both sTNF and tmTNF are depleted (anti-TNF antibody therapy).These data suggest that tmTNF plays a key role in controlling active infection, where tmTNF preserves a subset of the beneficial mechanisms of TNF while lacking detrimental effects. Our predictions and recent experimental data  support control of the infection [Current studies in both murine and NHP animal models by our group are now following up on these predictions. Our recent data from a mouse model showed that treatment with anti-TNF Ab in the chronic phase rapidly resulted in fulminant TB, while treatment with an etanercept-like molecule (receptor fusion) allowed mice to maintain nfection . In contnfection . Our stunfection  support To better understand underlying dynamics of TNF production and function, we build on our mathematical model of Mtb in humans using 16 nonlinear ordinary differential equations. The updated model tracks three macrophage populations  and multiple T cell  populations . The modThe nonlinear ODE model is based on  and simuThe equations describing dynamics for the macrophage subpopulations are given by:M) and a natural death term (-μRMMR). In the course of infection, additional resting macrophages are recruited in a TNF-dependent fashion at a rate Sr4B, and this process is downregulated by IL-10. We also account for TNF-independent recruitment mechanisms (for both macrophages and lymphocytes) with a term that indirectly represent chemokines secreted primarily by MAs and MIs (α(MA + w MI), 0 < w < 1): the magnitude of recruitment (α) varies from macrophages to lymphocytes. Resting macrophages at the site of infection can become chronically infected at a maximum rate k2  and activated at rate k3 . Note that due to differences in measurement units, TNF is scaled by a factor β. IFN-γ induction is downregulated by IL-4.Rate of change of resting macrophages  includesI. This mechanism has a maximal rate k17, and is described by a Hill process. Immune responses also contribute to MI killing by several mechanisms. Both CD8+ and CD4+ T cells can use the Fas-FasL apoptotic pathway to induce apoptosis in these cells at a maximum rate k14a. The half-saturation constant c4 describes the effector-target ratio (Tt:MI) at which this process is half maximal. TNF can also induce apoptosis by binding to the TNFR1 receptor. This process is downregulated by IL-10 and occurs at a rate k14b. Finally, CTL killing by CD8+ and CD4+ T cells happens at a rate of k52. Specifically, CD4+ T cells have a limited contribution and this is accounted for by scaling the CD4+ T cell numbers (0 < w1 <1). CD8+ T cell numbers are scaled by a Michaelis-Menten term accounting for the indirect dependence on CD4+ T cells for their killing capability. MAs are generated from the term in AMMA). MAs can be deactivated by IL-10 at a rate k4.MIs  can be c1A, Sr1B for Th0 and T80 cells; α3A, Sr3B for Th1 and Th2 cells; α3Ac, Sr3Bc for CD8+ T cells, respectively). We assume that CD4+ T cells can arrive at the site of infection either as Th0 (majority), or a small fraction may arrive already differentiated intoTh1 or Th2 cells . Th1 cells can be killed due to IFN-γ induced apoptosis in the presence of MAs at a rate μTγ. Both Th1 and Th2 cells die naturally at rates μT1 and μT2, respectively. As is the case for CD4+ T cells, we assume that CD8+ T cells can arrive at the site of infection as T80 (majority)  , or a smajority)  or TC (Eajority)  type. T8Tcγ, and die at a rate μTc. Since the T8s  and CD8+ T cells (rate α33) in response to antigen, and TNF has a given half-life.TNF  is produ5A and α5B, respectively. Production by Th0 and T80 cells is further enhanced by IL-12, and inhibited by IL-10. Other sources of IFN-γ, such as NK cells, are also believed to play a role in TB infection. Since these are not accounted for in the model, we include an extra source term (sg) dependent on extent of infection and IL-12 level.Th0, Th1, and CD8+ T cells produce IFN-γ  in respo23. MAs also produce IL-12, and this process is downregulated by IL-10. Dendritic cells are the primary source of IL-12 upon Mtb infection and are accounted for by an infection-dependent source term, s12. Finally, there is a natural half-life for IL-12.Resting macrophages produce IL-12  in respo6. Other sources such as Th1 cells, Th2 cells, and CD8+ T cells produce IL-10 at rates α16, α17, and α18, respectively. IL-4 is produced by Th0, and Th2 cells produce  adds to the extracellular subpopulation. To account for loss of intracellular bacteria due to various killing mechanisms, we assume each killed MI to hold an “average” number of bacteria, given by NAVG (<=N). The corresponding gain in extracellular bacteria depends on the mechanism of killing: while Fas-FasL–induced apoptosis (k14a) releases all intracellular bacteria, TNF-induced apoptosis (k14b) eliminates approximately 50% of the bacteria within the macrophage, and this is shown by the Nafrac multiplier in the BE (extracellular bacteria) equation (52) kills virtually all the intracellular bacteria, and does not add on to the BE (extracellular bacteria) population. Lastly, we assume that natural death of MIs also releases all intracellular bacteria, and this is modeled as a constant turnover of the bacteria (μIBI) from intracellular to extracellular. Extracellular bacteria grow at a maximum rate α20. They are taken up and killed by activated and resting macrophages at rates k15 and k18, respectively.Intracellular bacteria  grow at bacteria  become iequation . CTL actsTNF is produced predominantly by cells of the macrophage lineage upon infection or exposure to bacteria or bacterial products . Other cα) represents the dynamics of total sTNF and tmTNF in the system. Using the model, we investigate how different percentages of total TNF cleaved  affect infection progression. We updated the model equations to address tmTNF effects on cell activation and apoptosis, based on Our previously published models of Mtb infection simulated cell recruitment as a function of MAs and MIs, the main producers of chemokine and sTNF. In our most recent model , TNF wasd.The strength of tmTNF effect on T cell activation through TNFR1 and TNFR2 is represented in the model by the coefficient We also add new terms representing apoptosis or cell loss induced by anti-TNF antibody binding to tmTNF on macrophages ,20 and TThese terms are present in the mathematical model only during anti-TNF antibody treatment simulations. The fraction of intracellular bacteria released in the extracellular domain due to tmTNF-induced apoptosis of MIs is likely very small . A new t3) as follows (bold term):Under pathological conditions (chronic inflammatory states), the presence of anti-TNF antibodies (and not TNF receptor fusion molecules) and subsequent binding to tmTNF can induce activation of the complement cascade (due to high concentration of Abs)  and apopα in the model, but we indirectly account for LTα-dependent recruitment of macrophages and lymphocytes during anti-TNF therapy (namely TNF receptor fusion protein), since TNF receptor fusion protein binds LTα while anti-TNF antibody does not  Service Pack 3 (The Mathworks) platform and its numerical methods together with a computer code using a different solver written by our group.As discussed previously ,29,31, wBefore simulations can be performed, parameters must be estimated from literature sources or by mathematical means. Values for most model parameters are estimated from published experimental data or data generated from our group. Data from human studies and Mtb experiments are favored over mice and other mycobacterial species, respectively. Where no appropriate data is available for a given parameter, we conduct uncertainty analysis to obtain a range within orders of magnitude. A detailed description of techniques used to evaluate model parameters, as well as a listing of parameters already estimated can be found in work previously published by our group . All parParameter values represent mechanisms in the host–pathogen system, and these were estimated from many different experimental sources. There is great variation that likely exists among them. In previous work , we explThere is an intrinsic biological and experimental variability in rates measured from in vivo or in vitro studies. Further, some interactions in the Mtb–host system are not currently measurable, particularly at the level of the lung granuloma. This complicates accurate estimation of model parameters .n is significantly large). The stochastic approach allows for a global sensitivity study as compared with a deterministic analysis that gives local results based on the sensitivity equations. One major drawback of the deterministic approach is that the results are based on baseline values (often unknown) for the parameters involved in the sensitivity equations. The LHS approach does not suffer from this limitation.We quantify the importance of each TNF-related mechanism involved directly and indirectly in the infection dynamics using both uncertainty and sensitivity analyses as described previously . The stap-value that indicates significance. A negative PRC coefficient indicates that a decrease in the value of that parameter results in an increase of the bacterial load. A positive PRC coefficient indicates that a decrease in the value of that parameter results in a decrease of the bacterial load. PRC coefficients also evaluate temporal changes in the significance of these parameters as they relate to bacterial load at different times during the infection. Statistical significance of these correlations is assessed by a generalized t-test . For example, the rate of TNF production by Th1 cells (α32) is always very significant and negative  are between −1 and 1 and have a standard tive see : if we lσ prior to infection  by varying the parameter nfection A or aftenfection B. Settindel (see  for deta-/-). This occurs with low-level cellularity, i.e., macrophage numbers are almost an order of magnitude lower (mainly infected and activated) than when disease occurs in the wild-type scenario  that capture the overall neutralizing power of either receptor fusion or antibody in granulomatous tissue.The US Federal Drug Administration monitors the safety of TNF inhibitors through its Adverse Event Reporting System (AERS), a surveillance system to which drug manufacturers are required to submit reports of adverse events and to which health care professionals and consumers voluntarily send adverse event reports. Wallis et al.  publishe3 [Infliximab is a human–mouse chimeric monoclonal TNF antibody that binds potently and essentially irreversibly to monomeric and trimeric TNF, both soluble and membrane-bound, but does not bind to soluble LTα3 . Further3 . Binding3, with a 4-fold lower affinity for tmTNF with respect to infliximab [Another anti-TNF drug, etanercept, is a TNF receptor p75-IgG fusion protein rather than an antibody. It binds selectively to human trimeric sTNF and LTαfliximab . As a refliximab , althoug3 are engaged for very short time intervals, allowing for a redistribution of TNF throughout the system. However, if receptor fusion concentration is relatively high, those released molecules will quickly be reassociated with the receptor fusion and are therefore not free in the system. In contrast, under situations where TNF is released from the receptor fusion molecule and there are high numbers of cell associated TNF receptors present (such as in a granuloma) and possibly a lower level of receptor fusion (due to poor penetration), TNF might bind to the cell-associated TNFR1 or TNFR2 instead of back onto the receptor fusion. This contributes even more to lowering levels of bioavailable TNF in granulomas during receptor fusion treatment.Receptor fusion has a fast dissociation rate: it sheds 50% of sTNF and 90% of tmTNF in only 10 minutes, but can bind TNF again immediately . Thus itbioav): we assume that LTα-neutralization is of the same magnitude as sTNF neutralization.We indirectly test LTα-neutralization in the model by lowering all the TNF-independent recruitment parameters using the bioavailability coefficient . Finally, we investigate both the role of different bacterial loads during latency at treatment initiation and the duration of therapy as additional factors affecting risk of reactivation. To test whether bacterial levels play a role in reactivation rates, we vary two parameters that yield latency scenarios with higher bacterial levels before initiation of treatment . The duration of both anti-TNF antibody and receptor fusion treatments varies between 12 and 24 months. We classify a virtual patient as undergoing TB reactivation when the bacterial load grows larger than 105 (latency level) during or after the end of the treatment. See Several factors and mechanisms hypothesized to be involved in TB reactivation by anti-TNF drugs can be tested. These include the differential power of the drugs to neutralize TNF bioavailability , differereactivation threshold (RT) as a threshold where reduction of bioavailable TNF below this threshold level leads to reactivation. This value is expressed as a percentage of the TNF concentrations defined from the latency value.We define a t-test .Each VCT comprises 100 simulations, where TNF bioavailability is varied in a specified interval. Each run is classified based on the bacterial load level, and reactivation is defined when bacterial loads grows uncontrolled. We define the reactivation subset of the 100 runs as the collection of all the reactivation cases with their bioavailabilities . We obtain our RT as the average TNF bioavailability calculated on the reactivation subset. We statistically compare RTs between different trials by a standard Contradictory data exist regarding levels of sTNF and sTNF receptors in lung epithelial lining fluid obtained by bronchoalveolar lavage ,59 in ac3 of granulomatous tissue and we describe cytokine concentrations in pg/mL of granuloma homogenate.Average steady-state concentrations of anti-TNF antibodies  and TNF t-test  with Matlab. See the Uncertainty and Sensitivity Analyses section for more details.We perform PRC  and Figure S1(152 KB PDF)Click here for additional data file.Figure S2(130 KB PDF)Click here for additional data file.Figure S3x-axis represents the 16 variables of the ODE system (1–16). The y-axis represents the 16 variables of the ODE system (1)-(16). The y-axis represents The (54 KB PDF)Click here for additional data file.Table S1(27 KB DOC)Click here for additional data file.Table S2(20 KB DOC)Click here for additional data file.Table S3(21 KB DOC)Click here for additional data file.Table S4(22 KB DOC)Click here for additional data file.Table S5(21 KB DOC)Click here for additional data file.Table S6New Parameter Estimates in addition to those estimated previously ,31 show.(101 KB DOC)Click here for additional data file.Text S1(40 KB PDF)Click here for additional data file.Text S2(40 KB PDF)Click here for additional data file.