Coarse and fine woody debris are substantial forest ecosystem carbon stocks; however, there is a lack of understanding how these detrital carbon stocks vary across forested landscapes. Because forest woody detritus production and decay rates may partially depend on climatic conditions, the accumulation of coarse and fine woody debris carbon stocks in forests may be correlated with climate. This study used a nationwide inventory of coarse and fine woody debris in the United States to examine how these carbon stocks vary by climatic regions and variables.Mean coarse and fine woody debris forest carbon stocks vary by Köppen's climatic regions across the United States. The highest carbon stocks were found in regions with cool summers while the lowest carbon stocks were found in arid desert/steppes or temperate humid regions. Coarse and fine woody debris carbon stocks were found to be positively correlated with available moisture and negatively correlated with maximum temperature.2, further research is suggested in the areas of forest detritus decay and production.It was concluded with only medium confidence that coarse and fine woody debris carbon stocks may be at risk of becoming net emitter of carbon under a global climate warming scenario as increases in coarse or fine woody debris production (sinks) may be more than offset by increases in forest woody detritus decay rates (emission). Given the preliminary results of this study and the rather tenuous status of coarse and fine woody debris carbon stocks as either a source or sink of CO Estimation of carbon sequestration using large-scale forest inventory data has become important due to the link between possible climate change and the accumulation of greenhouse gases in the atmosphere ,2. In 192 into photosynthesis and the efflux of CO2 through woody decay processes [2 emitters [Forest terrestrial carbon sinks represent a fine balance between the influx of COrocesses . The decrocesses . Similarrocesses . Some strocesses , whereasemitters ,9. Quantemitters  and highemitters . Emerginemitters  would beemitters . TherefoThe goal of this study is to relate forest coarse and fine woody debris carbon stocks to climatic regions and variables across the United States with specific objectives including: 1) to estimate mean coarse woody debris, fine woody debris, and total woody detritus carbon stocks (coarse + fine woody debris) by Köppen climatic regions, 2) to correlate/model coarse woody debris, fine woody debris, and total woody detritus carbon stocks with individual climatic variables , mean annual maximum temperature (TMAX), mean annual minimum temperature (TMIN), moisture index (MOIST), variability cause (VAR), and potential evapotranspiration (EVAP)), and 3) to interpret the results of this study in the context of possible climate change.Coarse and fine woody debris carbon stocks vary by climatic region with the largest mean stocks found in dry/cool climates such as "warm temperate with dry summer (Cs)" and "snow, fully humid, cool summer (Dfc)" where decay rates may be reduced Table . Forest When correlated with a host of individual climatic variables, coarse and fine woody debris carbon stocks were found to be positively correlated with PRECIP and MOIST. In contrast, coarse and fine woody debris were negatively correlated with TMAX, TMIN, VAR, and EVAP Table . In termLinear regressions between total woody detritus stocks and TMAX and PRECIP indicated tremendous data scatter along with very weak R-square's (< 0.1)   or reduced detritus decay . Forestincrease . Overallincrease ,8.2 source or sink. We further conjecture that under a scenario of global warming, forest woody detritus carbon stocks  will be at risk for becoming net CO2 emitters. Given the uncertainty found with all relationships identified in this study, further analysis of this study's data [The results of this study established an initial link between forest coarse/fine woody debris carbon stocks and climatic regions/variables. Although this study found the relationships between these carbon stocks and climate to be only moderately evident, we propose that carbon sequestration by forest detritus may be increased by increased moisture availability and reduced by warmer temperatures. A delicate balance may exist where slight changes in climate could change a region's forest woody detritus status as a either a net COy's data  may deliThe FIA program, the only congressionally mandated national inventory of U.S. forests, conducts a 3-phase inventory of forest attributes of the country . The FIAIn phase 3, a 1/16 subset of phase 2 plots are measured for coarse and fine woody debris on transects radiating from each FIA subplot center ,31).Fine woody debris are sampled on one transect on each subplot. Fine woody debris pieces with diameters less than 2.54 cm were tallied separately on a 1.83-m slope distance transect. Fine woody debris pieces with transect diameters of 2.55 to 7.59 cm were tallied on a 3.05-m slope-distance transect (for more information on class definitions see ). Fine wBetween 2001 and 2005, a total of 4,531 forest inventory plots were measured for coarse and fine woody debris by the FIA program in 45 of the continental 48 states . Due to extreme disturbance events (e.g. tornadoes) or potential field measurement errors, 1.8 % of plot observations were deemed outliers and removed from analyses (122 plots). Outlier removal protocol was based on 10 times the interquartile range such that a plot having either coarse woody debris carbon estimates > 43.7 tonnes ha^-1 or fine woody debris carbon estimates > 33.3 tonnes ha^-1 was excluded from study analyses. The field data used in this study may be accessed at .The Köppen Climate Classification System, originally developed by Vldamir Köppen in 1900, is one of the most widely used for classifying the world's climatic regions -36. SincSix climatic variables were correlated with coarse and fine woody debris carbon stocks in this study: PRECIP, TMAX, TMIN, MOIST, VAR, and EVAP. Data for the PRECIP, TMAX, and TMIN were obtained from the Parameter-elevation Regressions on Independent Slopes Model (PRISM) dataset . Each oThe MOIST, VAR, and EVAP climatic variables are derived from a revised Thornthwaite global climate classification . MOIST,CWD) (tonnes ha^-1) was calculated using Eq. (1):Coarse and fine woody debris carbon contents were estimated using a combination of line-intersect volume per unit area estimators and conversion factors for biomass and carbon . Line-inn is the number of pieces, ci is the proportion of C in the mass of the ith piece, f is the conversion factor for unit-area values , Gi is the estimated bulk density (g m-3) of the ith piece reduced by a modeled decay reduction factor, L is the total length of the transect corrected for slope (m), Vi is the volume of the ith coarse woody piece (m3), and li is the length of the ith piece in meters [where sity g m- of the in meters  providesn meters  providesFWD) (tonnes ha^-1) was calculated using Eq. (2):Carbon storage in fine woody debris (Cn is fine woody debris size class (medium or large), Gi is the bulk density (g m-3) of the ith class, ai is the nonhorizontal lean angle correction factor for ith class, ci is the proportion of carbon in the ith class, s is the slope correction factor because fine woody debris is measured along a slope-distance transect, k is a constant representing both unit conversion and a constant for fine woody debris piece lengths (1.234), L is the slope length of the transect (m), ti is the number of pieces of fine woody debris in the ith size class, and di is the mean diameter (cm) of pieces within size class i. Because species data are not collected for fine woody debris, values of G, c, and a were based on the forest type assessed during phase 2 measurements [where sity g m- of the iThe mean and standard errors for coarse and fine woody debris carbon stocks were estimated by Köppen climatic region/subregion. Köppen climatic subregions were collapsed into regions if sample sizes were insufficient. The significance of differences in mean coarse and fine woody debris carbon stocks between Köppen's classes was tested using an analysis of variance (ANOVA). Differences in means among climatic regions were deemed significant at the 0.05 level. To assess the relationship between coarse and fine woody debris carbon stocks and climatic variables and to elucidate dead wood trends between Köppen's classes, Pearson's correlations coefficients and associated p-values were determined and displayed in a correlation matrix. Additionally, a linear regression was conducted between the dependent variable of total woody detritus stocks and the independent climatic variables of TMAX and PRECIP.PRECIP: average annual precipitation; TMAX: mean annual maximum temperature; TMIN: mean annual minimum temperature; MOIST: moisture index; VAR: variability cause; EVAP: potential evapotranspiration; FIA: Forest Inventory and AnalysisThe authors declare that they have no competing interests.CWW designed the study, conducted the majority of analyses, and wrote the manuscript, GCL acquired all meteorological data layers and assisted with Geographic Information System analytical operations. Additionally, GCL provided interpretations of study results. All authors read and approved the final manuscript.


Human T cell leukemia virus type 1 (HTLV-1) is the etiologic agent of Adult T cell Leukemia (ATL) and the neurological disorder HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP). Although the majority of HTLV-1–infected individuals remain asymptomatic carriers (AC) during their lifetime, 2–5% will develop either ATL or HAM/TSP, but never both. To better understand the gene expression changes in HTLV-1-associated diseases, we examined the mRNA profiles of CD4+ T cells isolated from 7 ATL, 12 HAM/TSP, 11 AC and 8 non-infected controls. Using genomic approaches followed by bioinformatic analysis, we identified gene expression pattern characteristic of HTLV-1 infected individuals and particular disease states. Of particular interest, the suppressor of cytokine signaling 1—SOCS1—was upregulated in HAM/TSP and AC patients but not in ATL. Moreover, SOCS1 was positively correlated with the expression of HTLV-1 mRNA in HAM/TSP patient samples. In primary PBMCs transfected with a HTLV-1 proviral clone and in HTLV-1-transformed MT-2 cells, HTLV-1 replication correlated with induction of SOCS1 and inhibition of IFN-α/β and IFN-stimulated gene expression. Targeting SOCS1 with siRNA restored type I IFN production and reduced HTLV-1 replication in MT-2 cells. Conversely, exogenous expression of SOCS1 resulted in enhanced HTLV-1 mRNA synthesis. In addition to inhibiting signaling downstream of the IFN receptor, SOCS1 inhibited IFN-β production by targeting IRF3 for ubiquitination and proteasomal degradation. These observations identify a novel SOCS1 driven mechanism of evasion of the type I IFN antiviral response against HTLV-1. Infection with HTLV-1 leads to the development of Adult T cell Leukemia (ATL) or the neurological disorder HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP). Although the majority of HTLV-1–infected individuals remain asymptomatic carriers (AC) during their lifetime, 2–5% will develop either ATL or HAM/TSP. Using gene expression profiling of CD4+ T lymphocytes from HTLV-1 infected patients, we identified Suppressor of cytokine signaling 1 (SOCS1) as being highly expressed in HAM/TSP and AC patients. SOCS1 expression positively correlated with the high HTLV-1 mRNA load that is characteristic of HAM/TSP patients. SOCS1 inhibited cellular antiviral signaling during HTLV-1 infection by degrading IRF3, an essential transcription factor in the interferon pathway. Our study reveals a novel evasion mechanism utilized by HTLV-1 that leads to increased retroviral replication, without triggering the innate immune response. Infection with the Human T cell Leukemia Virus type I (HTLV-I) can result in a number of disorders, including the aggressive T cell malignancy Adult T cell Leukemia (ATL) and the chronic, progressive neurologic disorder termed HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP) in vivo, progresses with the emergence of an IL-2-independent malignant clone that has accumulated multiple secondary genetic changes in growth regulatory and tumor suppressor genes Clinically, acute ATL is characterized by abnormally elevated T cell counts, accompanied by readily observed ‘flower cells’ – multi-lobed, leukemic cells with highly condensed chromatin - hypercalcemia, prominent skin lesions, hepatosplenomegaly and suffer from serious bacterial, viral, fungal and protozoan infections. Most patients present at this final acute stage, often unaware of their HTLV-1 positive status and given a poor prognosis, with a survival estimate of 6–10 months + and CD8+ T cells during early stages of disease, with a predominance of CD8+ T cells later in disease. HTLV-1 viral RNA has been found associated with CD4+ T cells and astrocytes in CNS lesions, suggesting that virus-infected cells migrate through the blood-brain barrier and infect CNS resident cells + (as well as CD4+) T cell response leading to inflammation, myelin loss, and axonal damage HAM/TSP is a systemic immune-mediated inflammatory disease characterized by demyelination of motor neurons in the spinal cord, although other tissues can also be damaged de novo upon IFN stimulation and contributes to the amplification of the IFN response, via expression of multiple IFN-α subtypes It is widely accepted that type I interferon (IFN-α/β) has a negative impact on HIV-1 replication IFN-induced JAK/STAT signaling is negatively regulated at different levels by several cellular factors to control the extent of the antiviral response and limit tissue damage p<0.01)  . Microarp<0.01) . These gp value <0.01, false discovery rate (FDR)  = 0.17%)  was performed on the top 500 genes modulated in HTLV-1-infected versus non-infected samples (= 0.17%) . PCA ide= 0.17%) . Gene clSOCS1 gene expression compared to NI individuals  (p<0.0001)  . Howeverctively) . Using actively) , we demo<0.0001) .SOCS1 gene expression. Initially, the level of SOCS1 mRNA was examined in HTLV-1-carrying T cell lines , control T cell lines  of the HTLV-1 proviral genome; HTLV-1 RNA expression was modest between 24 and 72 h (<10-fold), but the viral mRNA load increased sharply at 96 h (50-fold), concomitent with a dramatic increase in SOCS1 gene expression (∼24-fold).Since high proviral load is a hallmark of HAM/TSP pathology  pX1M-TM  were anaThe initial observation that SOCS1 was induced upon HTLV-1 infection prompted us to examine whether SOCS1 also influenced viral replication. To do so, the effect of SOCS1 expression on HTLV-1 provirus replication was examined in the CEM T cells, co-expressing a SOCS1 expression vector together with the HTLV-1 provirus. The level of HTLV-1 mRNA was consistently higher in SOCS1 expressing cells compared to CEM cells expressing HTLV-1 provirus alone (e.g. 55-fold vs. 10-fold at 24 h) . As a co2) and IFN-stimulated gene expression (IRF7 and CXCL10) was examined in PBMCs expressing the HTLV-1 provirus pX1M-TM  at 24 h post-HTLV-1 transfection, and IRF7 mRNA expression (∼11-fold) was maximal at 36 h. However, mRNA transcripts for all these genes decreased substantially  by 48–72 h. At 96 h, when HTLV-1 and SOCS1 gene expression were maximal, no reactivation of antiviral gene transcription was detected  - a strong inducer of the antiviral response - and kinetics of expression of IFN genes was assessed by Q-PCR . At 24 hprovirus . Inducti to 12 h . Howeverproteins .IFN-β (7.5-fold), ISG56 (2.5-fold), IFN-γ (4-fold) and CXCL10 (∼10-fold) gene expression compared to control siRNA. These results demonstrate that SOCS1 contributes to the inhibition of antiviral responses during HTLV-1 infection.Similarly, knockdown of SOCS1 in MT-2 cells reversed the inhibition of antiviral gene expression imposed by HTLV-1 . Pooled via the proteasomal pathway, as the use of the proteasome inhibitor MG132 prevented HTLV-1 mediated reduction of IRF3 protein level  prevented IRF-3degradation, while HEK293 cells expressing exogenous SOCS1 readily degraded IRF3 . In addiThe complexity of gene expression dysregulation in ATL or HAM/TSP diseases has been highlighted in a number of gene expression profiling et al. demonstrating that SOCS1 mRNA levels were increased in HAM/TSP patients compared to NI SOCS1 gene expression correlated with high levels of HTLV-1 transcription. Increasing HTLV-1 proviral expression blocked expression of type I IFN genes such as IFN-β, IRF7, IFN-α2, as well as the IFN-γ stimulated chemokine gene CXCL10, with maximal inhibition observed when HTLV-1 and SOCS1 gene expression levels were coordinately elevated. Furthermore, depletion of SOCS1 using siRNA decreased HTLV-1 replication and restored the type I IFN response.Among the many genes modulated during HTLV-1 infection, the suppressor of the interferon signaling - SOCS1 - was upregulated in HAM and AC patients but not in ATL. This observation is in agreement with a previous report published by Nishiura IFN-α/β is known to have a negative impact on retrovirus replication. Although few studies have reported its effect on HTLV-1, type I IFN constitutes a potent anti-retroviral mechanism that limits HTLV-1 replication et al. reported that Influenza A virus suppresses the antiviral response by inducing SOCS1 and SOCS3 via TLR3-independent but RIG-I/IFNAR dependent pathways SOCS1 is a cytokine-inducible intracellular negative regulator that inhibits type I and II IFN signaling by triggering the degradation of various components of the JAK-STAT cascade , JAK2 in IFN-γ mediated signaling and NF-κB p65/RelA are all known targets of SOCS1 The interaction between SOCS1 and IRF3 during HTLV-1 infection promotes proteasome-mediated degradation of IRF3 and thus abrogates early IFN antiviral signaling. SOCS1-dependent IRF3 degradation required the elongin B and C binding sites within SOCS1 and K48-linked polyubiquitination of IRF3. Indeed, the SOCS box-mediated function of SOCS1 is chiefly exerted via its ubiquitin ligase activity The present study reveals a novel mechanism of viral evasion of the IFN response in HTLV-1 infected T lymphocytes – the consequence of which can be directly related to the efficiency of HTLV-1 replication in patients suffering from HAM/TSP. Future studies are required to elucidate putative alternate consequences of SOCS1 upregulation in T cells Blood samples from HTLV-1 infected patients and non-infected (NI) donors were obtained from the Centre Hospitalier Universitaire de Fort-de-France in Martinique and Institut Pasteur de Cayenne in French Guyana. Patients suffering from ATL, HAM/TSP or HTLV-1 asymptomatic carriers were recruited according to World Health Organization (WHO) criteria. According to the French Bioethics laws, the collection of samples from HAM/TSP, ATL, AC and NI has been declared to the French Ministry of Research and the study was reviewed and approved by the CPP (Comité de Protection des Personnes) Sud-Ouest/Outre-Mer III, as well as the ARH  from Martinique. Because the protocol is non-interventional , no informed consent was provided by the patient, as stated by the French Public Health code and therefore the study was conducted anonymously. Clinical collection of samples for research purpose are stored at the Centre de Ressources Biologiques de Martinique (CeRBiM). The CeRBiM database has been approved by the CNIL . Leukophoresis from healthy donors were also obtained at the Royal Victoria Hospital, Montreal, Quebec, Canada. Informed consent were written and provided by study participants in accordance with the Declaration of Helsinki. The study was reviewed and approved by the Royal Victoria Hospital, the Jewish General Hospital, and McGill University Research Ethics Committee (REC) board of the SMBD-Jewish General Hospital.et al. In total, we selected for study 12 HAM/TSP, 11 asymptomatics (AC), 7 ATL and 8 not infected individuals (NI). The diagnosis of the 7 ATL cases included in patient cohort number 1 respected the international consensus recently published by Tsukasaki The HTLV-1-carrying T cell lines MT-2, MT-4, C8166, RMP and the HTLV-1-negative T cell lines CEM and Jurkat were used for experiments. MT-2, MT-4 and C8166 cells are derived from umbilical cord blood lymphocytes after cocultivation with leukemic cells from ATL patients 6 cells in serum-free medium supplemented with 10% heat-inactivated fetal bovine serum 2 h postinfection and harvested for whole cell extracts or RNA extraction at indicated times.For proteasome inhibitor treatment, MG132 (Sigma-Aldrich) or Lactacystin (Boston Biochem) were used at 5 and 10 µM, respectively. Sendai virus CANTELL strain (SeV) was obtained from Charles River Laboratory . Cells were infected with SeV at 20 hemagglutinating units (HAU) per 10-tagged SOCS1 full length and the deletion mutant SOCS1-ΔBCBox (amino acids 174–183) were kind gifts from Dr. Ferbeyre Gerardo . Ha-Ub-K48R and Ha-Ub-KO were kind gifts from Dr. Zhijan Chen . Plasmid encoding for Flag-tagged IRF3 full length was decribed previously The HTLV-1 proviral clone pX1M-TM was kind gift from Dr David Derse . Mychttp://www.canvac.ca/) human Immunoarray version 2 manufactured by the Microarray Center  containing 7256 duplicate spots representing 3628 expressed sequence tags (ESTs). Details of the labeling and hybridization procedures can be obtained at http://transnet.uhnres.utoronto.ca.Total RNA was extracted using Trizol Reagent (Invitrogen) or RNeasy kit (Qiagen) according to the manufacturer's instructions. The RNA integrity and purity was assessed with the Agilent 2100 Bioanalyzer (Agilent Technologies). Total RNA was amplified using the MessageAmp II mRNA kit . Sample and universal human RNA probes (Stratagene) for microarray hybridization were prepared by labeling the amplified RNA with Cy5 or Cy3, respectively, by reverse transcription, and hybridizing the labeled cDNA on the CANVAC (http://www.molmine). To establish differentially expressed genes, multi-class analysis was performed by one-way ANOVA on Log2 fold change (Log2Fc) data for ATL, HAM/TSP, AC and NI groups. Genes with a p value ≤0.01 were selected as significant . Visualization was produced by unsupervised clustering of the 1039 genes using Pearson correlation parameters. Pair wise correspondance analysis (PCA) was performed on the first 500 genes by Future Subset Selection (FSS) t-test. Genes were selected based on false discovery rate (FDR) according to the Benjamini/Hochberg (BH) methods. Gene annotations were gathered using manual searches in NCBI as well as the ontology tools DAVID (http://david.abcc.ncifcrf.gov/) and BioRag . Fold change (Fc) for each gene was calculated as 2(Log2X-Log2NI), where Log2 X represents the Log2 (Fc) for either ATL, AC or HAM and Log2 NI represents the Log2 (Fc) for NI. Microarray data have been deposited in the NCBI Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/). The results of the microarray experiment were confirmed by quantitative PCR (Q-PCR) on 47 genes chosen on the basis of a fold change of at least 2-fold, with RNA from 3 patients per group used for validation. A strong correlation between the average fold-change determined by microarray and the average of the qPCR results was observed, with 25/47 genes having a Pearson correlation value of at least 0.6 (Microarrays were scanned using Scanarray Express Scanner (Packard Biosciences) or the Axon 4000B scanner at 10-µm resolution. Array images were inspected visually for poor quality spots and flagged for omission. Quantified raw data was acquired with QuantArray version 3 and saved as quantarray text files. The quantified raw data were managed and pre-processed in GeneTraffic (Iobion Informatic). Following background correction and removal of genes where both channels were less than 100 or represented by less than 90% of the samples and polished data was generated by normalization by Lowess sub-grid. The final data array was analyzed using JExpress Pro software  set at 0.25 kV and 0.95 µF. Cells were plated in six-well plates in complete medium and collected at indicated times for whole cell extracts or RNA extraction.Leukophoresis from healthy donors were obtained at the Royal Victoria Hospital, Montreal, Quebec, Canada. PBMCs were isolated by Ficoll-Hypaque gradient  and activated for 4 days with 2 µg/ml of phytohemagglutinin-P (PHA-P) (Sigma Aldrich) and 50 U of interleukin 2 per ml (IL-2) . 5 µg of pX1M-TM was pulsed into 10×10www.cgiv. 0.2) and listed in Supporting information (T method using the SDS v1.3.1 Relative Quantification (RQ) Software where ddCT  =  dCT(Sample) – dCT (non-infected), dCT (Sample)  =  CT (Sample) - CT (GAPDH) and dCT (non-infected)  =  CT (non-infected) - CT (GAPDH).Validation of selected target genes was performed by relative quantification PCR (RQ-PCR) in 9 samples . A total of 2 µg of amplified RNA from uninfected and HTLV-1-infected samples was converted to cDNA using the High Capacity cDNA Archive Kit  according to the manufacturer's protocol. cDNA was amplified using SyBR Green I PCR master mix  or TaqMan Universal PCR Master Mix . Real-time PCR primers were designed using the primer3 website . The protein concentration was determined by using the Bradford assay . Whole-cell extracts (30 µg) were resolved by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) in a 10%-acrylamide gel and transferred to a nitrocellulose membrane . Membranes were blocked in 5% nonfat dried milk in Tris-buffered saline (TBS) plus 0.1% Tween 20 for 1 h at room temperature. Membranes were then probed overnight with antibodies against Stat 1 phosphorylated (Tyr701)  and non-phosphorylated forms (p91) ; phosphorylated Jak1 (Tyr 1022/1023) ; total Jak 1 (1 µg/ml Santa Cruz); SeV ; SOCS1 , IRF3  in 5% bovine serum albumin and PBS at 4°C. Incubation mixtures were washed in TBS-0.05% Tween 20 five times for a total of 25 min. Following washes, the membrane was incubated with peroxidase-conjugated goat anti-rabbit or anti-mouse antibody  at a dilution of 1∶5,000 for 1 h at room temperature. Following the incubation with the secondary antibody, membranes were washed again  and then visualized with an enhanced chemiluminescence .Cells destined for immunoblotting were washed with PBS and lysed in lysis buffer  were transiently transfected with equal amounts (5 µg) of IRF3 and MYC-tagged SOCS1 expression plasmids by using calcium phosphate precipitation method. Cells were harvested 24 h post-transfection, washed with 1 X phosphate-buffered saline (PBS), and lysed in a 1% Triton X-100 lysis buffer . Immunoprecipitations were performed by incubating WCE (300 µg) with 1 µg of anti-MYC  or 1 µg of antiserum directed against IRF3  coupled to 50 µl of A/G Plus-agarose beads  overnight at 4°C with constant agitation. Immunocomplexes were washed at least 3 times in lysis buffer eluted by boiling beads in 5 volumes SDS-PAGE sample buffer. The proteins were fractioned on 10% SDS-PAGE, transferred to nitrocellulose membrane and analyzed by immunoblot assay using anti-MYC (Sigma-Aldrich) or anti-IRF3  antibodies.HEK293 cells , p<0.01 (**) or p<0.001 (***).Data are presented as the mean ± standard error of the mean (SEM). Statistical significance for comparison of gene expression was assessed by an unpaired Student's A list of accession numbers for genes and proteins mention in this study are listed in Figure S12) and real-time PCR data (log2RQ) for select genes. (C) Pearson correlation data represent the strength and direction of the linear relationship between real-time PCR assays and microarray data represented in (B). Genes with a Pearson correlation value between 0.6 and 0.8 are represented in (C).Confirmation of microarray results by Q-PCR. (A) Total RNA of 9 donors  was reverse transcribed and cDNA was amplified using primers specific for indicated genes by real-time PCR. Values were normalized to GAPDH and relative quantification (RQ) was calculated by the comparative CT method. (B) Raw data of array data (log(0.95 MB TIF)Click here for additional data file.Figure S2CEM and Jurkat CD4+ T cell lines express SOCS1 when treated with IFNα2b. Expression of SOCS1 was measured in HTLV-1-negative T cell lines  with and without 1000U/ml of IFNα2b. cDNA was analyzed by quantitative real time PCR to measured SOCS1 expression. Equivalent mRNA amounts were normalized to GAPDH expression and calculated as fold change with the levels of uninfected Jurkat cells set arbitrarily as 1.(0.44 MB TIF)Click here for additional data file.Figure S3SOCS1 silencing in HTLV-1 infected MT-2 cells restores endogenous IRF3 expression. MT-2 cells were electroporated with control or pool of SOCS1 specific-siRNAs. At 72 h post-transfection, cells lysates were prepared and equal amounts of protein (20 µg) were resolved by SDS-PAGE followed by immunoblotting with anti-SOCS1 or anti-IRF3 antibodies. Immunoblotting against β-actin is shown as a loading control.(0.55 MB TIF)Click here for additional data file.Table S1Cohort #1 of HTLV-1 infected and non-infected donors.(0.07 MB DOC)Click here for additional data file.Table S2Cohort #2 of HAM/TSP and non-infected donors.(0.04 MB DOC)Click here for additional data file.Table S3Supplemental material and methods for Q-PCR.(0.03 MB DOC)Click here for additional data file.Table S4Accession numbers.(0.04 MB XLS)Click here for additional data file.


Thrombospondin-related anonymous protein (TRAP) is essential for sporozoite motility and for liver cell invasion. TRAP is a type 1 membrane protein that possesses multiple adhesive domains in its extracellular region.Plasmodium falciparum TRAP (PfTRAP) and its subdomains were expressed in a mammalian expression system, and eleven different mutants generated to study interaction of PfTRAP with liver cells. Binding studies between HepG2 cell extracts and PfTRAP were performed using co-immunoprecipitation protocols.Five different amino acid residues of PfTRAP that are involved in liver cell binding have been identified. These PfTRAP mutants bound to heparin like the wild type PfTRAP thereby suggesting a non-heparin mediated binding of PfTRAP to liver cells. Three Src family proteins -Lyn, Lck and CrkL which interact with PfTRAP are also identified. Liver cell extracts and immunoprecipitated Src family kinases phosphorylated PfTRAP at multiple sites. An analysis of multiple TRAP sequences revealed Src homology 3 domain (SH3) binding motifs.Binding of PfTRAP to SH3-domain containing proteins like Src-family kinases and their ability to phosphorylate PfTRAP suggests a novel role for PfTRAP in cell signaling during sporozoite invasion and homing inside the liver cells. These data shed new light on TRAP-liver cell interactions. Plasmodium falciparum. Since the search for a malaria vaccine remains elusive, there is a constant and pressing need to identify new drug and vaccine targets. Malaria infection in humans starts when infected female Anopheles mosquitoes take their blood meal and inject sporozoites into the host (human) skin. Although, it remains unclear how sporozoites reach hepatocytes, experimental evidence suggests role of various molecules for successful infection that includes components both from the host and the parasite. Apicomplexans lack a classical locomotory organelles like flagellum or cilium but show an actin based locomotion called gliding motility  ATP in gels were dried and phosphorylation was detected by autoradiography. HepG2 cells extract alone was taken as a negative control and PfTRAP alone with ATP was taken as a nonspecific and autophosphorylation control.PfTRAP ECD, the A-domain and the A+RII domains (2–5 μg) were incubated with HepG2 or HEK 293 whole cell extracts in the presence of ATP at 37°C for 30 min. These PfTRAP fragments were immunoprecipitated using polyclonal anti-PfTRAP antibodies that had been pre-adsorbed on protein A Sepharose beads. Beads were washed in PBS supplemented with 50 mM n-octyl-β-D-glucopyranoside and 500 mM NaCl. The sample was again washed in PBS thrice, boiled and resolved by SDS-PAGE. PfTRAP protein bands were cut and sent for LC-MS/MS analysis. Sample containing  ATP at 37°C for 1 hr. PfTRAP was eluted from the mixture using 1M NaCl, immunoprecipitated using anti-PfTRAP antibodies, resolved on SDS-PAGE and detected by autoradiography after two days of exposure.Antibodies coupled to protein A beads were used to pull down CrkL, Lck, and Lyn from HepG2 membrane extracts. The PfTRAP ECD protein (20 μg) was incubated with above beads in the presence of [γ-PfTRAP ECD and its subdomains were expressed in mammalian expression system and recombinant proteins were purified from media using Ni-ion chelating affinity chromatography and gel filtration chromatography. As shown in Figure To identify amino acid residues involved in interaction of PfTRAP to HepG2 cells, different PfTRAP mutants were constructed Figure  and the P. falciparum TRAP, showed ~47% reduction in binding to HepG2 cells  and incubated it with PfTRAP ECD. The reaction mixture was immunoprecipitated with anti-TRAP antibodies and TRAP band was subjected to mass spectrometric analysis. These results indicated phosphorylation of PfTRAP at multiple sites (data not shown). Autophosphorylation of PfTRAP was ruled out as no specific binding of ATP or autophosphorylation of PfTRAP was observed in the presence of [γ-t Figure . Similart Figure . To iden32ATP alone did not phosphorylate TRAP  in HepG2 cell extracts that are able to phosphorylate PfTRAP, immunoprecipitations of reaction mixtures were carried out with anti-PfTRAP antibodies. The precipitated samples were analysed for presence of Lck, CrkL Lyn, c-Src and Grb2 proteins in an immunoblot assay using kinase specific antibodies. As shown in Figure P Figure . TogethePfTRAP has been previously suggested to bind to HepG2 cells by interacting with sulfated proteoglycans. These studies were carried out with multimeric or soluble aggregates of recombinant PfTRAP ,16,23,24Amino acids involved in binding of PfTRAP proteins to HepG2 cells were evaluated. Five mutants  exhibited 40–70% reduced binding to HepG2 cells. Specifically, the reduced binding of R307 (a part of the RGD triplet) indicates that this conserved sequence plays an important role in binding of PfTRAP to HepG2 cells via yet unidentified receptor(s) on liver cells. Surprisingly, the-T131A mutant that has been earlier shown to be important for hepatocyte invasion and salivary gland infection in mosquitoes ,25 showeIn silico analysis of TRAP from all the Plasmodium species revealed that TRAP molecules contain conserved PxxP motifs and many potential phosphorylation sites  -32 or onThe authors declare that they have no competing interests.PM and AS designed the experiments, RRA conducted them while all four wrote the paper.


Global deciphering of signal transduction pathways represents a new challenge of the post-genomic era. However, for the majority of these signaling pathways the role(s), the function(s) and the interaction(s) of the signaling intermediates remain to be characterized in an integrated fashion. The global molecular study of cell signaling pathways and networks consequently requires sensitive, robust technologies which may allow in addition multi-parallel and highthroughput applications. The Alphascreen™ technology, relying on a bead-based homogenous approach, constitutes a valuable tool to detect and quantify a wide range of signaling events such as enzymatic activities or biomolecular interactions. In this article, we exhaustively review the literature and report the broad spectrum of Alphascreen™-based applications in the study of signal transduction pathways. The ability of intracellular signaling networks to integrate, process and distribute the information through the cell requires that individual signaling partners must interact with multiple effectors identified as inputs or outputs. In addition a significant number of non-proteinaceous entities  also participate in increasing the complexity of the above mentioned molecular signaling networks. Consequently, it becomes of interest to develop specific approaches to monitor, in parallel, a number, as large as possible, of events occurring in a homogenous cell population and which may reflect the activation of specific signaling cascades in precise cellular contexts.via interactions with other molecules – be they other proteins, nucleic acids, lipids, carbohydrates or small molecules – has driven the development of technologies to examine these macromolecular associations. The development of large-scale and versatile assay formats is therefore needed for monitoring enzymatic activities, modifications, interactions or the combination of those parameters for which there are very few direct methods available at present. The amplified luminescence proximity homogenous assay is an example of a technology developed for the biological sciences in the past few years that has followed a progression leading to a genomic scale use. The Alphascreen™ (AS) technology concept also proved to be remarkably malleable, with novel adaptations allowing for the detection of protein–DNA, protein–RNA, or protein–small molecule interactions, as well as protein–protein interactions that are dependent or not on post-translational modifications or which occur in different compartments of the cell. Indeed, in the past few years, a large number of high-throughput assays were developed to decipher cellular signaling pathways or to identify compounds that may modulate protein-protein interactions or enzymatic activities, respectively. Here we review the development of functional AS assays which will be providing an integrated understanding of cell signaling pathways.The observation that, besides intrinsic enzymatic activities, proteins exert virtually all of their functions 2).1).Originally the technology that led to the development of AS, is a luminescent oxygen channeling immunoassay (LOCI). LOCI is a homogeneous bead-based immunoassay method capable of rapid, quantitative determination of a wide range of analytes including high and very low concentrations of large and small molecules, free (unbound) drugs, DNA, and specific IgM. In the mid 1990’s, a group at Syva/Dade Behring developed numerous assays for laboratory diagnostics purposes . In 1999These assays derived from LOCI technology, use latex particle pairs which are formed in the assays through specific binding interactions by sequentially combining the sample and two reagents. One particle contains a photosensitizer whereas the other contains a chemiluminescer. Irradiation causes the photosensitized formation of singlet oxygen species in the photosensitizer-containing bead. The singlet oxygen species transfer to a bound particle and activates the chemiluminescer, thereby initiating a delayed luminescence emission. The singlet oxygen species display a lifetime of approximately 4 µs which allows them to travel 200 nm in aqueous solutions.2). Upon energy transfer between those compounds, activated rubrene emits light at 520-620 nm which is in turn detected by the photodetector in a microplate reader. An excitation wavelength higher than the emission wavelength ensures a low assay fluorescent background by avoiding any auto-fluorescence from biological media or compounds. However, AS may be sensitive to other types of interferences. Antioxidants or other quenchers of reactive oxygen species like metal ions can strongly affect the emitted signal. Moreover, since the AS detection is only based on a fluorescence-intensity measurement, colored compounds absorbing in the 500–600 nm wavelength range artificially decrease the AS signal and therefore may be detected as false positives in HTS. To circumvent these limitations, Acceptors beads were modified to contain Europium. Europium (Eu) has a long fluorescent lifetime, longer than several hundreds of microseconds, whereas traditional organic reagents have several nanoseconds; the emission peaks of Eu complexes are 615 nm and the fluorescent peak profiles are sharp: the half-widths are 10 nm – 20 nm. It is known that the fluorescence is based on the energy transfer from the ligand to the central metal ion. The characteristics of these new beads allowed for the development of a novel assay format commercialized as AlphaLISA™. Using such fluorescent properties this assay leads to the reduction of background interferences of short lifetime from the sample matrix, and enables highly sensitive detection and thus leads to greatly increased specificity and sensitivity of the assay.Based on these principles, the AS technology has been developed in which Donor (photosensitizer) and Acceptor (chemiluminescer) microbeads can be coated with target-specific antibodies, secondary antibodies, proteins, or any molecular entity of interest. A signal is produced when the AS Acceptor and Donor beads are brought into proximity (<200 nm) by a molecular interaction occurring between the binding partners captured on the beads. Laser excitation of the Donor beads at 680 nm causes ambient oxygen to be converted to the singlet state by photosensitizers . These react with chemiluminescent agents  within the Acceptor bead only when the latter is in close proximity . A signal is produced when the AlphaScreen™ Acceptor and Donor beads are brought into proximity by a molecular interaction occurring between the binding partners captured on the beads. Laser excitation at 680 nm causes ambient oxygen to be converted to the singlet state by photosensitizers on the Donor bead. These react with chemiluminescent agents on the Acceptor bead only when the latter is in close proximity, emitting light at 520-620 nm. AlphaScreen™ allows one to quantify various analytes by performing competition assays and interpolating signals with a standard curve.3).3). Briefly, we will describe the AS-based assays monitoring the interaction between receptors and their respective ligands, then those aiming at evaluating the activation of specific signaling pathways by measuring the intracellular concentrations of second messengers, enzymatic activities, or specific sub-cellular localization and finally the assays which aim at measuring the occurrence of specific post-translational modifications whose role could be involved in various aspects of cell signaling.In the following sections, we will extensively review the literature and explore the use of AS as a tool to explore cell signaling pathways. The scheme of our analysis is shown on Fig. (a).i).2+, agonist-induced internalization) were applied to demonstrate that Sphingosine 1-phosphate (S1P) and dihydrosphingosine 1-phosphate (DHS1P) were bona fide activators of the GPR3, GPR6 and GPR12 family benzene) and androstanol [Nuclear receptors are known to function as multimeric structures and generally show a large spectrum of ligands. In this section, we will illustrate how the AS technology was used to monitor the functionality of four different nuclear receptors. The first example is provided by the constitutive androstane receptor  which is an orphan nuclear receptor that is predominantly expressed in the liver , 50. CARrostanol .The functional interaction between the orphan nuclear receptors, small heterodimer partner (SHP) and liver receptor homolog 1 (LRH-1), where SHP binds to LRH-1 and represses its constitutive transcriptional activity, is crucial for regulating genes involved in cholesterol homeostasis. Li and colleagues reported structural and biochemical analyses of the LRH-1-SHP interaction, and the binding of the cofactor motifs to the nuclear receptors was determined using AS . They devia convergence of NR5A (nuclear receptor family) activity and cAMP signaling, to potentially disrupt normal endocrine development and function. Using cellular and biochemical assays several lines of evidence suggest that ATR might not function by directly binding to NR5A receptors and failed neither to alter coactivator peptide recruitment using an AS assay nor to displace the bacterial phosphatidyl glycerol or an exchanged PIP3 ligand present in the SF-1 ligand binding pocket [Finally, the herbicide Atrazine (ATR) binds directly to SF-1 and induces the cAMP phosphodiesterase (PDE) 4D, which is expressed in human fetal tissues and is proposed to mediate inflammatory responses in the myometrium. ATR response seems to be mediated g pocket . ATR alsiii).in vitro, the authors screened hundreds of purified yeast proteins for ubiquitination, and identified previously reported and novel substrates of the yeast E3 ligase RSP5. The relevance of these substrates was confirmed in vivo by showing that a number of them interact genetically with Rsp5, and some were ubiquitinated by RSP5 in vivo.The best example of protein modification, characterization and enzyme substrate interaction was reported previously . In this4).This section aims at reviewing all the AS-based approaches that successfully identified compounds, small molecules, or peptides whose biological activity was to perturb specific signaling pathways. On the one hand, we will review the literature available and on the other hand describe the results available in public repositories.a).μM  to HEK293 cells. The concentrations of ligands tested were 10 pM to 200 nM for chemokines, 1 pM to 20 nM for W-peptide and 0.5 nM to 10 μM for other compounds and a potent agonist of FPRL-1 was identified as being a truncated form of CKbeta8-1 [Several examples of the use of AS in the identification of signaling pathway modulators are available in the literature. The first type of assays which was used to identify such molecules was based on monitoring the activation levels of second messengers downstream of membrane receptors in response to agonists or antagonists. This is illustrated for instance by the Human formyl peptide-receptor-like-1 (FPRL-1) which is a promiscuous G protein-coupled receptor (GPCR), and belongs to a chemo-attractant receptor family protein. The FPRL-1 mediated release of cAMP was measured using AS. To stimulate cAMP production, forskolin was added at 10 Kbeta8-1 . SimilarKbeta8-1  discoverKbeta8-1 .et al. (2007) exploited AS technology to evaluate binding affinity of human NK1, a natural variant of hepatocyte growth factor (HGF), to Met receptor tyrosine kinase [in vivo. Similarly and at a more general level, the use of the AS technology was proposed to study the concept of altered protein-protein interactions in the identification of perturbing agents. Indeed as protein-protein interactions allow the recruitment of cytoplasmic polypeptides to activated receptors, direct their assembly into larger complexes, target them to defined subcellular locations, and determine the specificity with which enzymes interact with their substrates, they consequently represent targets of choice to be perturbed [The second type of assays developed to identify agents perturbing signaling pathways is based on the evaluation of altered protein-protein interactions. This was illustrated for the study of Hepatocyte Growth Factor receptors. Indeed as receptor dimerization is a general paradigm for activation of RTKs, Tolbert e kinase . The reserturbed .b).http://www.ncbi.nlm.nih.gov/) in the PubChem Bioassay database [In addition to the published data mentioned in the previous section, a repository of the AS-based results obtained in the screening of compound libraries is available at NCBI (database  which co5).In the above sections, we have described how AS was use to monitor, dissect and perturb the molecular mechanisms playing a role in the activation of specific signaling pathways.It is clear that each component of a given signaling pathway could be analyzed individually at the genome scale  however the integrated representation of a number of signaling pathways activated in response to specific stimuli would definitely provide a better understanding of the molecular mechanisms set in place in the cell to respond.3) were evaluated using a unique technological approach as AS. This most likely reflects the high versatility of the technology. In addition, although most of the assays described in this review have demonstrated experimental robustness, sensitivity, and efficiency, they were carried out separately and despite of the objectives of providing a complete and integrated view of the signaling pathways activated in response to given stimuli.Moreover, it is interesting that most of the signaling steps described in Fig.  analyses of signal transduction pathways in parallel and in formats compatible with high-throughput screening will emerge.The establishment of such tools will be of course facilitated by the use of a single technology adaptable to the evaluation of an almost infinite number of parameters. In this context, the problematic would necessarily locate beyond the development of the assays, but rather at the level of the interpretation, integration and visualization of the quantitative data.


Recently, a variety of analogues of resveratrol have been synthesised and investigated in in vitro assays. One analogue, 3,4,5,4′-tetramethoxystilbene (DMU 212), showed preferential growth-inhibitory and proapoptotic properties in transformed cells, when compared with their untransformed counterparts. As part of a chemoprevention drug development programme, the pharmacokinetic properties of DMU 212 were compared with those of resveratrol in the plasma, liver, kidney, lung, heart, brain and small intestinal and colonic mucosa of mice. DMU 212 or resveratrol (240 mg kg−1) were administered intragastrically, and drug concentrations were measured by HPLC. Metabolites were characterised by cochromatography with authentic reference compounds and were identified by mass spectrometry. The ratios of area of plasma or tissue concentration vs time curves of resveratrol over DMU 212 (AUCres/AUCDMU212) for the plasma, liver, small intestinal and colonic mucosa were 3.5, 5, 0.1 and 0.15, respectively. Thus, resveratrol afforded significantly higher levels than DMU 212 in the plasma and liver, while DMU 212 exhibited superior availability compared to resveratrol in the small intestine and colon. Resveratrol was metabolised to its sulphate or glucuronate conjugates, while DMU 212 underwent metabolic hydroxylation or single and double O-demethylation. DMU 212 and resveratrol inhibited the growth of human-derived colon cancer cells HCA-7 and HT-29 in vitro with IC50 values of between 6 and 26 μM. In the light of the superior levels achieved in the gastrointestinal tract after the administration of DMU 212, when compared to resveratrol, the results provide a good rationale to evaluate DMU 212 as a colorectal cancer chemopreventive agent.Resveratrol ( Resveratrol inhibits diverse cellular events associated with the three major stages of carcinogenesis: initiation, promotion and progression anthracene-(DMBA) induced mouse mammary organ culture model (a)pyrene-induced transformation of rat tracheal epithelial cells (N-nitrosomethylbenzylamine (NMBA) (Min+ mice (N-methyl-N-nitrosourea-(NMU) treated rats  and its purity established as 99% by HPLC analysis. Authentic resveratrol-3-sulphate was a gift from Dr Tristan Booth , and its identity was corroborated by mass spectrometry. DMU 212  was synthesised by Wittig olefination involving the reaction of 4-methoxybenzyl-tri-phosphonium chloride with 3,4,5-trimethoxybenzaldehyde , 4′-hydroxy-3,4,5-trimethoxystilbene , 4-hydroxy-3,5,4′-trimethoxystilbene  and 3-hydroxy-4,5,4′-trimethoxystilbene   was synthesised according to the method of Resveratrol, DMU 212 and its congeners referred to in this work are exclusively the −1 body weight, equivalent to 1 mmol kg−1 resveratrol or 0.8 mmol kg−1 DMU 212) via the intragastric route . The vehicle was glycerol formal, and the dose volume approximately 10 ml kg−1. In the case of DMU 212, the vehicle also contained 10% DMSO. Mice were killed by terminal gaseous anaesthesia at 10, 30, 60 or 120 min postdosing. Blood was collected by cardiac puncture, and plasma was obtained by centrifugation. The liver, kidney, lung, heart, brain and gut were excised, and scrapings were obtained from small intestine and colon. Tissues were snap-frozen (liquid nitrogen) and stored at −80°C until analysis.Animal experiments were conducted as stipulated by Project Licence 40/2496 granted by the UK Home Office. Experiments were vetted and approved by the Leicester University Animal Welfare Committee and complied with the UKCCCR guidelines for the welfare of animals in experimental neoplasia. Mice aged 8 weeks (20–22 g) received resveratrol or DMU 212 , then at 105 g (1 h) in a Beckman L-8-60 ultracentrifuge . The microsomal pellet was suspended in Tris buffer , recentrifuged at 105 g (1 h) and resuspended in Tris buffer. Liver microsomes from two to four mice were pooled. Microsomes (0.5 mg protein ml−1) were incubated at 37°C with NADPH (1 mM), MgCl2 (1 mM) and resveratrol or DMU 212 (1 mM) for 20 min . The addition of one volume of ice-cold methanol terminated the reaction. The mixture was vortexed (30 s), centrifuged  and the supernatant was collected and analysed by HPLC. For the biosynthesis of resveratrol glucuronide for use as a reference compound, microsomes were incubated with resveratrol (1 mM) as described above, except that NADPH was replaced by uridine-diphosphoglucuronic acid (1 mM).Microsomes were prepared by differential centrifugation of mouse liver homogenate first at 9 × 10M Hepes buffer  using a hand-held glass homogeniser. An aliquot (250 μl) of homogenate, to which an internal standard had been added was vortexed, followed by the addition of acetonitrile (1 ml). After vigorous shaking, mixtures were kept on ice (5–10 min) and centrifuged . The supernatants were dried under a stream of nitrogen and reconstituted in mobile phase (100 μl).Tissues were homogenised (1 : 1 volume to tissue mass ratio) in 50 m18 column . The mobile phase consisted of the three components: aqueous ammonium acetate , propan-2-ol and acetonitrile. The gradient system that determined the composition of the eluent concerning these three components was as follows: for resveratrol 80 : 10 : 10 at the start, 75 : 10 : 15 at 10 min, 70 : 10 : 20 at 15 min, 60 : 10 : 30 at 17 min, 50 : 10 : 40 at 20 min and 20 : 10 : 70 at 25 min; for DMU 212 45 : 10 : 45 at the start for up to 10 min, 20 : 10 : 70 at 15 min and 10 : 10 : 80 at 20 min. The flow rate for both methods was 1 ml min−1.HPLC analysis was performed using a Varian Prostar HPLC system  with a Pro-Star 230 solvent delivery system, a Pro-Star 310 UV–Vis detector, a Pro-Star 363 Fluorescence detector, a 410 Varian autosampler and an Ultracarb Ctrans-stilbene for resveratrol and DMU 212, respectively. Resveratrol and its metabolites was analysed using UV detection (325 nm), and DMU 212 and its metabolites were determined with fluorescence detection . The injection volume of samples reconstituted in the mobile phase was 50 μl. The preliminary characterisation of metabolites was achieved by cochromatography using either synthetic standards or biosynthetically generated resveratrol glucuronide.Internal standards were carbamazepine and 4′-methoxy-4-methyl-R2=0.99 or above. The extraction efficiencies (in percent) for resveratrol and DMU 212 were as follows: from plasma 102±17 and 67±2, respectively, from tissues 86±7 and 78±15, respectively . The recovery of the resveratrol conjugates was approximately 50% that of the DMU 212 metabolites 60%. Therefore, metabolites were not quantitated.Quantification of resveratrol and DMU 212 was performed using standard curves constructed with relevant drug concentrations. The curves were characterised by regression coefficients of vs time curve (AUC) values were calculated using the trapezoidal rule .The area under the plasma or tissue concentration Mass spectrometry was performed using a Quattro Bio-Q tandem quadrupole mass spectrometer upgraded to Quattro MK II specifications  with a pneumatically assisted electrospray interface. Samples were analysed in positive ion mode. The temperature was maintained at 120°C, and the operating voltage of the electrospray capillary was 3.88 kV and the cone voltage was 32 V. HPLC conditions used for the on-line HPLC-mass spectrometric analyses were as described for DMU 212 above.4 per well) in 24-well plates and cultured in DMEM containing Glutamax I  and glucose (4.5 g l−1) and 10% foetal calf serum . Resveratrol or DMU 212 (1–100 μM) dissolved in DMSO was added to cellular incubates 24 h postplating. Cells were counted 72, 96, 120, 144 and 168 h postaddition of agents using a Z2 Coulter Particle Count and Size Analyzer . Control cultures contained the vehicle only. The amount of DMSO added to the incubate did not exceed 0.1%, which on its own failed to affect the cell growth. The IC50 values inserted in vs agent concentration curves at the 168 h time point.Cells were seeded (10−1), and drug levels were measured in the plasma and liver, kidney, lung, brain, small intestinal mucosa and colonic mucosa. These are all tissues in which resveratrol might prevent malignancy, or delay its onset. For comparison, levels in the heart were also studied. The results are shown in Figure 30–120 min values .Mice received intragastric resveratrol or DMU 212 , 3′-hydroxy-DMU 212 (m/z=317) and 3-desmethyl-DMU 212 (m/z=287). In extracts of lung and kidney tissues, these metabolites were also detected, albeit at lower concentrations (result not shown).Extracts of plasma and liver samples from animals that had received DMU 212 exhibited several peaks in addition to that of the parent drug . Extractin vitro in suspensions of liver microsomes fortified with cofactors of cytochrome P450 enzymes. While HPLC analysis of extracts of the incubation mixture with resveratrol did not yield any peak in addition to that of the parent substrate, analysis of incubates with DMU 212 afforded peaks in addition to that of parent DMU 212 . The spectrum of O-demethylated and hydroxylated metabolites found in vivo was accurately reflected by the metabolic profile obtained on incubation of DMU 212 with NADPH-fortified liver microsomes. These findings are consistent with the results of recent in vitro experiments using cytochrome P450 isoenzyme preparations, in which DMU 212 was found to undergo both aromatic hydroxylation and O-demethylation reactions primarily catalysed by isoenzymes of the CYP1 family . In analogy, resveratrol was recently found to undergo metabolic oxidation in vitro to piceatannol , when incubated with a source of CYP1B1  by factors of 32 and 760, respectively. Furthermore, the results of our preliminary assessment of the colon cancer cell growth-inhibitory properties of resveratrol and DMU 212 suggest that the concentrations of either agent required to inhibit growth, with IC50 values between 6 and 26 μM, are comfortably within the range achieved in the colorectal tract of mice that received these agents at the oral doses used in the study described here, 240 mg kg−1.The pharmacokinetic properties of DMU 212 have thus far been unknown. In contrast, resveratrol has been the subject of several pharmacokinetic studies, including those in the rat , the abi−1 per day) decreased adenoma multiplicity in the ApcMin/+ mouse model , the results presented here render the exploration of DMU 212 side by side with resveratrol for chemopreventive efficacy in rodent models of colorectal carcinogenesis propitious.In conclusion, the work described here provides an initial pharmacokinetic groundwork, which can contribute to rational decision making as to the choice of resveratrol analogues that should be selected for comparative testing for cancer chemopreventive potency in preclinical models. DMU 212 showed more favourable pharmacokinetic properties than resveratrol, in that it yielded higher levels of drug in the small intestinal, colonic mucosae and brain. Buttressed by our recent finding that DMU 212 is devoid of any toxicity in rats when administered at single doses of up to 40 mg kg


The epidermal growth factor receptor (EGFR) signaling pathway plays a key role in regulation of cellular growth and development. While highly studied, it is still not fully understood how the signal is orchestrated. One of the reasons for the complexity of this pathway is the extensive network of inter-connected components involved in the signaling. In the aim of identifying critical mechanisms controlling signal transduction we have performed extensive analysis of an executable model of the EGFR pathway using the stochastic pi-calculus as a modeling language.Our analysis, done through simulation of various perturbations, suggests that the EGFR pathway contains regions of functional redundancy in the upstream parts; in the event of low EGF stimulus or partial system failure, this redundancy helps to maintain functional robustness. Downstream parts, like the parts controlling Ras and ERK, have fewer redundancies, and more than 50% inhibition of specific reactions in those parts greatly attenuates signal response. In addition, we suggest an abstract model that captures the main control mechanisms in the pathway. Simulation of this abstract model suggests that without redundancies in the upstream modules, signal transduction through the entire pathway could be attenuated. In terms of specific control mechanisms, we have identified positive feedback loops whose role is to prolong the active state of key components , and negative feedback loops that help promote signal adaptation and stabilization.The insights gained from simulating this executable model facilitate the formulation of specific hypotheses regarding the control mechanisms of the EGFR signaling, and further substantiate the benefit to construct abstract executable models of large complex biological networks. Important cellular processes, such as differentiation and division, rely on signal transduction cascades that occur throughout the cell. The signal transduction cascade, initiated by the binding of epidermal growth factor (EGF) to the epidermal growth factor receptor (EGFR), is essential for normal cell growth and development . ConversThe EGFR signaling cascade is initiated by the binding of EGF to the transmembrane EGFR at its extracellular domain. The binding induces dimerization and autophosphorylation of its intracellular domains. The dimers form docking sites for the recruitment of cytoplasmic enzymes and adapter proteins, starting a complex signaling cascade . The subin silico experimentation, and provide guidance for future experimentation. In addition, this modelling approach may be amenable to detailed analysis of the stochastic behavior of a network using model checking .Previous studies of the EGFR signaling pathway have combined mathematical modeling and quantitative experimentation. These studies revealed insights into the functionalities of the pathway ,17 and fThe ability of the EGFR signaling cascade, as with many other receptor tyrosine kinase signaling systems, to maintain a reproducible output despite input variations can be attributed to the module diversity and redundancy that allows for compensatory functioning in case of component failure . It is tHere we present a modularized model of the EGFR signaling cascade within a single cell in the pi-calculus framework. Our model is adapted from previous mathematical models describing the same pathway ,21. ModuThe original kinetic model of the EGF-induced signaling pathway ,21 was uet. al. [signaling module. Signaling modules are important for modularization of the EGFR signaling pathway as well as more generally for reuse and integration of modules in larger system models. Perturbations to the model were done by knocking-out reactions feeding in and out of the components highlighted in Figure The original model by Schoeberl et. al.  is modulet. al. ,6,20,23.m on the same channel x. (3) an output action !x(n) describes sending a message to another molecule whose receiving an input n on same channel x. The specification do π1.P1 or ... or πN.PN, where πi stands for one of the three previous actions, represents the ability of a molecule to react in N different ways. The parallel composition P|Q represents the existence of molecules at the same time. By defining X(m) = P, we can define a molecule of type X parameterized by m. Each type of molecule will have its definition recorded in a constant environment E. For a more complete introduction to stochastic pi-calculus, we refer the reader to [Similar to the procedure of modeling concurrent computational systems, biological systems can be described in the stochastic pi-calculus language. The behaviour of a molecule, such as a protein or a signaling complex, can be described as a process P, and actions describe possible interactions between molecules. Possible actions π include: (1) a delay action delay@r describes a change in the internal structure of a molecule with a delay whose rate is r. (2) an input action ?x(m) describes receiving a message from another molecule whose sending an output eader to . EssentiOur model was executed using the Stochastic Pi Machine (SPiM) simulator version 1.13. The stochastic pi-calculus code for executing the unperturbed model in SPiM was modified to run simulations on a perturbed EGFR signaling pathway. Each simulation of the EGFR model was carried over 3,600 time units, which is the equivalent of 60 minutes real time, and 100,000 sampling events took place over this time range. Observables generated by SPiM from the state variables were converted into absolute numbers of molecules for each species (each complex of different compounds was considered a unique species). Simulation of each perturbed model was carried over ten replicates and the number of molecules of ERK-PP was averaged over each time unit. The molecular profiles were plotted using the R-statistical platform, and a LOWESS method was applied to smooth the graphs.In these simulations, we identify active signal response as the molecular profile of components in the signaling pathway when 50 ng/ml of EGF is added as a stimulus, and the inactive signal response as the molecular profile when no EGF is stimulating the system.Our model of the EGFR signaling pathway is an updated version of previous models ,21. It iAnalysis of these initial simulations reveals interesting features that hint to the results of later deeper analysis of the model. The activation of the EGF-receptors, in the dimerized and phosphorylated form, clearly depends on the concentration of EGF, responding with greater amplitude and earlier peaks. Although EGF concentration heavily affects membrane receptor activation, there is less concentration sensitivity as we trace down the signaling cascade. In particular, the amplitude and duration of the signal response in ERK-PP is hardly affected, even at low levels of stimulus. As suggested from the sharper and much shorter duration in the signal response of Ras-GTP and Raf-P, it is likely that the degree of activation in upstream components have little effect on the downstream signaling components. Following activation of Raf and Ras, there is considerable signal amplification occurring in the pathways leading to MEK and ERK activation. Even though the amplitude of the signal response does not seem to be significantly affected by the amount of EGF stimulation, the sustainability of the signal response in most components, including ERK-PP, seems to be attributed to the high EGF concentrations.We partition the model into functional modules based on the common biological concept of the importance of substances in the pathway. This partition is highlighted in Figure An important characteristic of the EGFR signaling cascade is its ability to maintain output reproducibility, despite input variation or system perturbation. Design features, like network redundancy, may attribute to this functional robustness. Our first analysis consists of systematic inhibition of each reaction in the model separately. We include in Figure In the middle of the pathway, the Ras modules seem to maintain both fragile and robust network elements. Robustness of the two modules may be attributed to their extensive feedback mechanisms, and fragility may be due to the criticality of Ras-GTP for persistent signal transduction. Inhibition of v31 does not affect ERK from attaining maximal activation, but does affect the sustainability of its activated state Figure . The obsOur next analysis is by simulation of the pathway under inhibition of multiple reactions Figure . Reactioone of the substances in orange or red does not affect activity of the output. In the case that a substance has only orange connections then one is required for activation but not both. The red connections denote inhibition and all others activation. Therefore, this representation of the EGFR signaling pathway provides a summary of the key mechanisms controlling signal transduction between components, and also suggests an intuitive way of understanding how the activation or inactivation of each component can affect the whole system. This representation captures the relations between substances but is not intended to be perceived as purely Boolean. We stress that deactivation of a red/orange input may still affect the amplitude or duration of activity of the signal, however, it remains active.As a result of our simulations under extensive perturbation of the computational model, we can generate dependence relationships between key components in the EGFR signaling pathway. We exhaustively examined all conditions across the EGFR signaling pathway where components achieve active and inactive states. Activity/inactivity values for the molecular activities were compiled for each key component in order to map dependency of activity between these components. The resulting dependencies are summarized in Figure From the connectivity diagram in Figure The connectivity diagram is justified by pi-calculus (SPiM) simulations. We have also created a smaller stochastic pi-calculus model that includes only these key molecular components and their connectivity as presented in Figure This work presents a computational model of the EGFR signaling pathway. The model, written in the stochastic pi-calculus language, represents our current understanding of EGFR signaling dynamics and the contribution of important signaling components to this pathway. Execution of the model allowed us to simulate and observe signal transduction through the pathway under various conditions. Some simulations match the experimental observations and increase our confidence in the model and its consistency with previous models ,27,21. OThe insights gained from simulation and analysis of the kinetic behaviour of the EGFR signaling pathway helps us understand not only the terminal signal response to EGF stimulus, but also the response at various levels of the signaling cascade. The analysis suggests that there is high sensitivity in upstream components to variations in transient EGF stimulus, but this sensitivity does not translate to differential signal response in downstream components. Specifically, sensitivity analysis reveals greater sensitivity in the EGF binding reaction and the Raf dephosphorylation reaction . In addiPartitioning of the EGFR signaling network into modules is not a trivial task, but it leads to a simpler model of the signaling cascade which offers clarity and computational tractability . IdentifBy comparing the results of the simulations in terms of signaling modules, we further verify differences between modules based on network characteristics, like redundancy and robustness to perturbations. Some of these characteristics, such as the dependence of ERK-PP signal response on the activation of EGF receptors in the EGF module, may be an indication of why contact and tyrosine kinase inhibitors continue to be an elective means of preventing EGFR signaling . Our knoin silico experimentations on computational models. More importantly, computational models have been widely used in the fight against numerous detrimental diseases by helping to determine possible targets for drug therapies. Interestingly, through our tests to determine the effectiveness of targeting multiple inhibition sites as a means of combination therapy, we discovered a higher level of system sensitivity to targets in the downstream modules  as opposed to targets in the upstream modules (EGF and Grb2). Specifically, we did not detect any evidence of significant attenuation of EGFR signaling when phosphorylation reactions in the upstream modules are targeted for partial inhibition, contradicting the results of analysis done on other mathematical models [The ability to perturb a biological system without any cost, except for those that are computational, truly attests to the important practicality of conducting l models . Since hl models , it woulAs a means of compiling our observations of the various states that the components in the EGFR signaling pathway achieved under different conditions, and as a way of demonstrating model abstraction with the aid of models in the pi-calculus language, we produced a simplified connectivity diagram Figure . The diaIn order to perform our analysis we have chosen to use the SPiM simulator, which is based on the pi-calculus formalism. There is a wide range of existing tools based on process calculi, such as BetaWorkbench , Bio-PepThrough simulation of the EGFR signaling model under different perturbation conditions, we can discover regions of network robustness and fragility. The molecular profiles of the important signaling components presents evidence for the increasing insensitivity to low EGF stimulus as we move down the signaling pathway. In contrast, greater sensitivity is exhibited by the signaling system when downstream signaling modules are perturbed. There seems to be significant redundancy that is contributing to network robustness in Grb2 and Ras signaling modules. Further study of partial inhibition at the important reactions demonstrates that high signal attenuation is achieved when multiple sites in downstream signaling modules are targeted. By analyzing the behaviour of interface components as the signal passes through the modules, we are able to produce a mapping of signaling modules to simplified operations, and thereby, generating a connectivity diagram for the EGFR signaling pathway. From the diagram, we can see important feedback mechanisms, some of them crucial to the maintenance of activated response in ERK and could explain the irreversible maturation of tumour cells. As is shown, the results from these simulations of the EGFR signaling pathway can be used to help formulate hypotheses, regarding the dynamics of EGFR signaling, to be tested in the 'wet lab'. Furthermore, the experimental results can be used to eliminate spurious assumptions in the model and hence further verify it.DW, NP, and JF conceived and designed the computational simulations. AP and LC participated in crucial discussions. AP provided technical advice with designing the SPiM experiments and running the SPiM simulations. LC implemented an earlier version of the EGFR signaling pathway model, which served as a basis for the current modular version of the model that was implemented by AP. DW edited the model, performed simulations and analyzed the data. DW, NP, LC, and JF wrote the manuscript. AP contributed to the additional files. All authors read and approved the final manuscript.Stochastic pi-calculus model of the biochemical interactions involved in the EGFR signalling pathways. The model is based on the reaction map of Figure http://research.microsoft.com/en-us/um/people/aphillip/egfr09/ and the SPiM simulator is available at http://research.microsoft.com/spim/Click here for fileBehaviour of ERK-PP in response to complete inhibition of key reactions in the EGF module.Click here for fileBehaviour of ERK-PP in response to complete inhibition of key reactions in the Grb2 module.Click here for fileBehaviour of ERK-PP in response to complete inhibition of key reactions in the Ras Shc-independent module.Click here for fileBehaviour of ERK-PP in response to complete inhibition of key reactions in the Ras Shc-dependent module.Click here for fileBehaviour of ERK-PP in response to complete inhibition of key reactions in the Raf module.Click here for fileBehaviour of ERK-PP in response to complete inhibition of key reactions in the MEK module.Click here for fileBehaviour of ERK-PP in response to complete inhibition of key reactions in the ERK module.Click here for fileBoolean table for inferring logical inputs for (EGF-EGFRi)2*.Click here for fileBoolean table for inferring logical inputs for (EGF-EGFR*)2-GAP.Click here for fileBoolean table for inferring logical inputs for (EGF-EGFR*)2-GAP-Shc*.Click here for fileBoolean table for inferring logical inputs for (EGF-EGFR*)2-GAP-Grb2-Sos.Click here for fileBoolean table for inferring logical inputs for (EGF-EGFR*)2-GAP-Shc*-Grb2-Sos.Click here for fileBoolean table for inferring logical inputs for Ras-GTP.Click here for fileBoolean table for inferring logical inputs for Raf*.Click here for fileBoolean table for inferring logical inputs for MEK-PP.Click here for fileMolecular profiles of interface components as a result of perturbations on two different input signals. See highlighted rows in Additional Files Click here for fileMolecular profile of ERK-PP in response to signal from the EGF-EGFR complex as simulated by the abstract pi-calculus model.Click here for fileMolecular profile of ERK-PP in response to signal from the EGF-EGFR complex as simulated by the abstract pi-calculus model, but without abstraction of the Grb module.Click here for file


While the human T-cell leukemia virus type 1 (HTLV-1) is the etiologic agent of adult T-cell leukemia/lymphoma (ATL), to date, its close relative HTLV-2 is not associated with ATL or other types of malignancies. Accumulating evidence shows that HTLV-1 Tax1 and HTLV-2 Tax2 have many shared activities, but the two proteins have a limited number of significantly distinct activities, and these distinctions appear to play key roles in HTLV-1 specific pathogenesis. In this review, we summarize the functions of Tax1 associated with cell survival, cell proliferation, persistent infection as well as pathogenesis. We emphasize special attention to distinctions between Tax1 and Tax2. This transformation event of infected T-cells alone is, however, not sufficient for ATL development, since only a fraction of HTLV-1 infected individuals (approximately 5%) suffer ATL after a long latency period (60 years on average). Thus, both multiple genetic and epigenetic changes [Adult T-cell leukemia/lymphoma (ATL) is an aggressive form of leukemia/lymphoma characterized by the malignant proliferation of CD4 T cells infected with human T-cell leukemia virus type 1 (HTLV-1) ,6. HTLV- changes  in infecin vitro human T-cells in an IL-2-dependent manner as effectively as HTLV-1 [Intriguingly, a closely related delta-retrovirus, human T-cell leukemia virus type 2 (HTLV-2), does not cause any leukemia or lymphoma in infected people in spite of its ability to immortalize s HTLV-1 . Moreoves HTLV-1 -16.gag, pol, and env, HTLV-1 encodes several non-structural genes including p12, p13, p30, Rex, and Tax  of the HTLV-1 genome ,23. In aThe NF-κB family of transcription factors, including RelA, c-Rel, RelB, NF-κB1 (p50 and its precursor p105), NF-κB2 (p52 and its precursor p100), plays a central role in immune functions, such as innate and adaptive responses to pathogens, survival of lymphocytes, and lymphoid tissue development . On the tax1 and tax2 genes defective for NF-κB activation, can not immortalize primary human T cells [NF-κB activity is tightly controlled in normal T cells, and it is transiently activated in certain circumstances such as during immune stimulation. By contrast, NF-κB is constitutively active in HTLV-1-infected T cells -34. This T cells ,36 (howe T cells ). In add T cells ,38,39.Both Tax1 and Tax2 activate the canonical NF-κB pathway through interacting with multiple NF-κB regulators. While the full scheme of canonical NF-κB activation by Tax has not been elucidated yet, the activation of the IKK complex by Tax through binding with its scaffold subunit IKKγ (NEMO) is a central event. The above conclusion was established based on the observation that the loss of NEMO completely abrogates the activation of NF-κB by Tax1 ,41. A MATax1 undergoes several posttranslational modifications, including phosphorylation, acetylation, sumoylation, and ubiquitination -50. AmonIn addition to the canonical NF-κB pathway, Tax1 activates the noncanonical NF-κB pathway . Tax1 siThe transforming activity of Tax1 towards CTLL-2 is much higher than that of Tax2, and such increased activity is partly mediated through Tax1-specific activation of the noncanonical NF-κB pathway -58. For Continued cell cycle progression and resistance to apoptosis are two fundamental functions associated with the transformation of HTLV-1 infected T cells. NF-κB activation by Tax1 is critically involved in both functions. When expressed in G1- arrested primary human T cells, Tax1 induces cell cycle progression from the G1 to S phase through activation of E2F transcription factors . The abiTax1 has been shown to confer resistance to apoptosis through inducing anti-apoptotic proteins such as Bcl-xL, survivin, cFLIP, xIAP, cIAP1, and cIAP2 in a NF-κB dependent manner -75. BothTax1 upregulates the expression of genes encoding cytokines, chemokines, cell surface ligands, and their receptors, in an NF-κB, AP-1, CREB/ATF and/or NFAT dependent manner. They include IL-2 receptor (IL-2R) α-chain, IL-9, IL-13, IL-15/IL-15R, IL-21/IL-21R, IL-8, CCL2, CCL5, CCL22, CCR9, CXCR7, CD40, OX40/OX40L, and 4-1BB/4-1BBL -94. Amonin vivo. However, subsequent studies revealed that most of HTLV-1-infected and leukemic cell lines derived from ATL patients except for HUT102, do not express significant levels of IL-2 [in vitro and the leukemogenesis in vivo are unclear. Unlike HTLV-1, HTLV-2-infected T-cell lines constitutively produce IL-2 in the culture supernatant, and Tax2 without any additional stimulation activates IL-2 gene expression through NFAT in Jurkat cells [in vivo.Transient transfection studies showed that Tax1 induces the expression of IL-2 through the transcription factor NFAT in Jurkat cells treated with either TPA or ionomycin . Togethe of IL-2 ,97. Thusat cells . Moreoveat cells . These rin vivo through regulating T-cell functions such as cell survival, cell motility, adhesion, and tissue distribution. For instance, OX40 and 4-1BB, by inducing a cell to cell interaction, could further augment NF-κB activity, making a positive feedback loop, which would be important for the maintenance of NF-κB activity in HTLV-1-infected cells that express a low level of Tax1 in vivo [It is likely that other factors induced by Tax1 would be beneficial for the survival and proliferation of HTLV-1 infected T-cells  in vivo .in vivo without affecting the IL-2-dependent immortalization of primary T-cells? Interestingly, the deletion of PBM prominently reduces IL-2-independent growth of CTLL-2 cells induced by Tax1 [in vivo is generally too low to support IL-2-induced T-cell proliferation, the reduced requirement of IL-2 induced by Tax1 through PBM may explain the selectively defective function of HTLV-1/ΔPBM in vivo.PDZ (PSD-95/Discs Large/ZO-1) domain containing proteins bind to the PDZ domain binding motif (PBM) which is typically present at the carboxyl-terminus of target proteins . One maj by Tax1 . Taken iin vitro [It is unclear how the Tax1 PBM contributes to inducing IL-2-independent growth of T-cells. The addition of Tax1 PBM to the C-terminus of Tax2 in the context of HTLV-2 significantly increases the proliferation of primary human T-cells infected with the virus in vitro . Thus, Tin vitro -103. ThuSimilar to the pathogenesis differences between HTLV-1 versus HTLV-2, limited subtypes of human papilloma viruses (HPVs) such as HPV16 and 18 are associated with cervical cancers. Interestingly, the E6 oncoproteins from only high risk HPVs, but not low-risk HPVs have a PBM . A similTax1 has been reported to interact with several PDZ domain containing proteins including Dlg1, Scribble, MAGI-3, TIP-1, IL-16 precursor protein, and Erbin ,104-111.dlg mutations in Drosophila cause neoplastic overgrowth of imaginal disc epithelia and embryonic lethality, establishing dlg as a tumor suppressor gene in Drosophila. In mammalian epithelial cells, Dlg1 localizes at adherence junctions (AJ) and is involved in the establishment of AJ as well as tight junctions. Following T cell receptor (TCR) activation in T cells, Dlg1 is transiently translocated to the immune synapses where it functions as a scaffold coordinating the activities of signaling proteins such as Lck, Zap70, Vav, WASP, and p38 kinase [Dlg1 is a mammalian homologue of Drosophila discs-large (dlg) and a member of the membrane-associated guanylate kinase (MAGUK) family proteins . Homozyg8 kinase -116. T c8 kinase .Consistent with its tumor suppressive activity, the overexpression of Dlg1 in NIH-3T3 cells induces cell cycle arrest in G1, and this arrest can be overcome by Tax1 in a PBM dependent manner, indicating that Tax1, through direct binding, interferes with the growth-suppressive activity of Dlg1 . Althougdlg, loss-of-function mutation of scrib in Drosophila results in aberrant proliferation and abnormal cell polarity/architecture of epithelial cells, indicating a role for Scribble as a tumor suppressor. In mammalian epithelial cells, Scribble and Dlg1 also form a scaffolding complex, regulating apical-basal polarity. In T cells, the Scribble complex regulates T cell polarity and morphology during migration and immunological synapse formation [Scribble is a member of the LAP (leucine rich and PDZ domain) family of proteins and functions as a cell polarity protein in cooperation with Dlg1 . Like dlormation .Tax1 binds to Scribble in a PBM dependent manner, although one report suggests there are both PBM-dependent and -independent modes of Tax1-Scribble binding ,108. ScrWhile it is very likely that viral oncoproteins including Tax1 inactivate the tumor suppressive functions of PDZ domain proteins, it remains possible that they might positively utilize such PDZ proteins to transform cells. This idea was raised in order to explain the function of E4-ORF1, since the loss of Dlg1 apparently reduces the transforming activity of E4-ORF1 . By analPI3K and its downstream kinase Akt are activated in T cells by many cytokines including IL-2; this pathway provides cell survival and growth signals . Activatras [In many cancers, the PI3K/Akt pathway is aberrantly activated by several means, including the gain of function mutation in PI3K and Akt, the loss of PTEN, and the constitutive activation of upstream signaling molecules such as the mutation of ras . In bothras ,124. LY2ras . These fras .Several distinct mechanisms for Tax1 to activate PI3K/Akt have been reported. Tax1 frees a catalytic p110α subunit of PI3K complex from an inhibitory subunit p85α through direct binding to p85α . Tax1 alThe mammalian target of rapamycin (mTOR) is one of the crucial downstream targets of Akt which is used to promote cell survival and growth mainly through the stimulation of translational initiation . RapamycParadoxical to the virus' transforming activity, Tax1 expression in or HTLV-1 infection of human cells  has been observed in some settings to induce cell cycle arrest at the G1 phase through the induction of p27/kip1 and p21/waf1 . This isLike HTLV-1 and HTLV-2, HTLV-3 and HTLV-4 encode Tax3 and Tax4, respectively. In their cognate viruses, Tax3 and Tax4 could play major roles in T-cell immortalization and persistent infection  encoded by the virus in an antisense orientation may play a critical role in the malignant proliferation of ATL cells  [Although the e 5' LTR -139. The (APH-2) . Interesin vivo, but HTLV-1 infected cells under conditions of low cytokines can grow much more efficiently than HTLV-2-infected cells. Such growth advantage of HTLV-1 infection would cause more expansion of infected cells in vivo, resulting in increased probability of acquiring genetic alterations, followed by clonal expansion of altered cells, and eventually leading to ATL development. It should be noted that high HTLV-1 proviral load (high numbers of infected cells) is a tightly-linked risk factor for the development of ATL. Such cytokine-independent (or less-dependent) growth properties of HTLV-1 infected T-cells are mediated by Tax1, possibly cooperatively with HBZ. To induce IL-2-independent growth of T-cells, Tax1 has two activities distinct from Tax2: the activation of the noncanonical NF-κB2 pathway and as-yet-uncharacterized signals through PDZ domain-containing proteins. These two activities are already known to play crucial roles in hematopoietic malignancies including leukemia and lymphoma and carcinogenesis induced by high-risk HPVs. This model would also be applicable to the pathogenesis of HAM/TSP, since high proviral loads are also tightly-linked risk factors for HAM/TSP. In HAM/TSP, the increased expansion of HTLV-1 infected T-cells would further raise high immune response to the virus, especially to Tax1, resulting in the development of diseases possibly through already proposed autoimmune mechanism(s). Collectively, we believe that further comparisons of Tax functions from the four human HTLVs will promote greater understanding of viral pathogenesis. In addition, therapies targeted against functions specific to Tax1 could be promising for the treatment of HAM/TSP and certain ATL patients.This review article summarizes our current view pertaining to the molecular mechanism(s) of HTLV-1 mediated T-cell transformation and persistent infection. In our opinion, these mechanism(s) shed light on viral pathogenesis, and offer insights into differences in HTLV-1 Tax1 and HTLV-2 Tax2 function. Based on current information, we propose the following simplified model Figure  which doThe authors declare that they have no competing interests.MH and MF cooperatively wrote and edited this review. Both authors read and approved the final manuscript.