Tumor necrosis factor superfamily ligands and receptors are responsible for development, immunity, and homeostasis of metazoan organisms. Thus, it is not surprising that signals emanating from these receptors are tightly regulated. Binding of TNF-related weak inducer of apoptosis (TWEAK) to its cognate receptor, FN14, triggers the assembly of receptor-associated signaling complex, which allows the activation of canonical and non-canonical nuclear factor kappa B (NF-κB) as well as mitogen-activated protein kinase signaling pathways. Ubiquitin ligases cellular inhibitor of apoptosis 1 and 2 (c-IAP1 and 2) and adaptor proteins TNFR-associated factors 2 and 3 (TRAF2 and TRAF3) are crucial for the regulation of TWEAK signaling as they facilitate the recruitment of distal signaling components including IKK and linear ubiquitin chain assembly complex complexes. At the same time c-IAP1/2, together with TRAF2 and TRAF3, promote constitutive ubiquitination and proteasomal degradation of NF-κB inducing kinase (NIK) – a kinase with critical role in the activation of non-canonical NF-κB signaling. While c-IAP1/2 mediated ubiquitination allows the activation of TWEAK-stimulated canonical NF-κB signaling, these E3 ligases are negative regulators of non-canonical signaling. TWEAK stimulation prompts the recruitment of c-IAP1/2 as well as TRAF2 and TRAF3 to the FN14 signaling complex leading to c-IAP1/2 autoubiquitination and degradation, which stabilizes NIK and allows subsequent phosphorylation of IKKα and partial proteasomal processing of p100 to activate gene expression. Recent studies have revealed that the spatio-temporal pattern of TWEAK-stimulated ubiquitination is a carefully orchestrated process involving several substrates that are modified by different ubiquitin linkages. Understanding the significance of ubiquitination for TWEAK signaling is important for the overall understanding of TWEAK biology and for the design of therapeutics that can be used in the treatment of human pathologies that are driven by TWEAK/FN14 expression and activity. The regulated posttranslational modification and degradation of cellular proteins by the ubiquitin-proteasome system impacts a wide range of crucial processes in normal and diseased cells . Tumor nHundreds of E3 ligases that ensure substrate specificity and tens of E2 enzymes that dictate the type of the ubiquitin chain assembly present the ubiquitination processes with a remarkable combinatorial potential . NumerouTumor necrosis factor superfamily ligands are homotrimeric type 2 transmembrane proteins that are either membrane-embedded or cleaved to generate soluble proteins . These lTNF-related weak inducer of apoptosis  is a TNF family cytokine that binds FN14 receptor  to promote proliferation but also apoptosis in a wide variety of epithelial and endothelial cells , 20. AssFollowing this first wave of signaling, non-canonical NF-κB signaling gets activated few hours after the formation of TWEAK-FN14 complex . The reaSimilar mechanism for the activation of non-canonical NF-κB signaling is employed by vast majority of TNF family ligands and receptors  . The onlThus, ubiquitination is instrumental for the proper regulation of the non-canonical NF-κB pathway and TWEAK/FN14 and most of the related TRAF3-binding TNFR family members depend on ubiquitination for effective activation of signaling .Several ubiquitin ligases have been implicated in TWEAK signaling but probably the most important ones are c-IAP1 and 2 as the elimination or reduction of c-IAP levels severely diminishes canonical NF-κB and MAPK signaling . CellulaLinear ubiquitin chain assembly complex is an E3 ligase complex that consists of HOIP/RNF31, Heme-oxidized IRP2 ubiquitin ligase-1 (HOIL-1L), and/or SHANK-associated RH domain-interacting protein (Sharpin) , 30. It Non-canonical NF-κB signaling is also critically regulated by ubiquitination and proteasomal degradation. Cytoplasmic complexes consisting of ubiquitin ligases c-IAP1 and 2 and adaptor proteins TRAF2 and TRAF3 promote constitutive ubiquitination and proteasomal degradation of kinase NIK –33. BefoInterestingly, the activation of the non-canonical NF-κB also relies on the c-IAP ubiquitin ligase activity. Stimulation of cells with TWEAK, as well as with the related TNF family ligands that trigger recruitment of TRAF2 and TRAF3 – LIGHT, CD30L, or CD40L leads to the aggregation of c-IAP proteins within the receptor-associated membrane fraction . There, Processing of p100 to p52 is one of the final steps in the activation of non-canonical NF-κB signaling, and it is also regulated by ubiquitination. IKKα mediated phosphorylation of p100 recruits SCF-βTrCP E3 ligase complex, which promotes p100 ubiquitination and partial proteasomal degradation to yield a p52 form –61. In aGiven the importance of ubiquitination for TWEAK mediated signaling it is no surprise that deubiquitination also plays a functional role for TWEAK biology. DUBs are enzymes that remove ubiquitin moieties from substrate proteins and allow reversal or inhibition, but in some cases also activation of signaling that is regulated by ubiquitination , 10. RecAn additional DUB candidate for the regulation of TWEAK-stimulated non-canonical NF-κB signaling is OTUD7B or Cezanne . OTUD7B The controlled posttranslational modification of signaling adaptors and effectors has a great potential to regulate signaling outcomes , 9, 30. The author is an employee of Genentech, Inc.


Osteogenic differentiation from mesenchymal progenitor cells (MPCs) are initiated and regulated by a cascade of signaling events. Either Wnt/β-catenin or estrogen signaling pathway has been shown to play an important role in regulating skeletal development and maintaining adult tissue homeostasis. Here, we investigate the potential crosstalk and synergy of these two signaling pathways in regulating osteogenic differentiation of MPCs. We find that the activation of estrogen receptor (ER) signaling by estradiol (E2) or exogenously expressed ERα in MPCs synergistically enhances Wnt3A-induced early and late osteogenic markers, as well as matrix mineralization. The E2 or ERα-mediated synergy can be effectively blocked by ERα antagonist tamoxifen. E2 stimulation can enhance endochondral ossification of Wnt3A-transduced mouse fetal limb explants. Furthermore, exogenously expressed ERα significantly enhances the maturity and mineralization of Wnt3A-induced subcutaneous and intramuscular ectopic bone formation. Mechanistically, we demonstrate that E2 does not exert any detectable effect on β-catenin/Tcf reporter activity. However, ERα expression is up-regulated within the first 48h in AdWnt3A-transduced MPCs, whereas ERβ expression is significantly inhibited within 24h. Moreover, the key enzyme for the biosynthesis of estrogens aromatase is modulated by Wnt3A in a biphasic manner, up-regulated at 24h but reduced after 48h. Our results demonstrate that, while ER signaling acts synergistically with Wnt3A in promoting osteogenic differentiation, Wnt3A may crosstalk with ER signaling by up-regulating ERα expression and down-regulating ERβ expression in MPCs. Thus, the signaling crosstalk and synergy between these two pathways should be further explored as a potential therapeutic approach to combating bone and skeletal disorders, such as fracture healing and osteoporosis. MPCs are multipotent progenitors and can be isolated from numerous tissues, but mostly from bone marrow stromal cells. MPCs can undergo self-renewal and differentiate into multiple lineages, including osteogenic, chondrogenic, and adipogenic lineages -3. Osteo in vivo -8. We ha in vivo -19. Wnt signaling plays a critical role in embryonic development, postnatal development, and adult tissue homeostasis ,21. The Estrogen is essential in both genders, not only for the pubertal growth spurt and skeletal maturation, but also for the accrual and maintenance of bone mass throughout adult life -30. The Here, we investigate the possible crosstalk and synergy between ER signaling and canonical Wnt signaling in regulating osteogenic differentiation of MPCs. Using our previously characterized mesenchymal progenitor cells iMEFs which are treated with either estradiol (E2) or adenovirus-mediated exogenous expression of ERα, we find that the activation of ER signaling synergistically enhances Wnt3A-induced both early and late osteogenic markers, as well as matrix mineralization. The E2 or ERα-mediated synergy can be effectively blocked by ERα antagonist tamoxifen. E2 stimulation on Wnt3A-transduced mouse fetal limb explants leads to an expansion of hypertrophic chondrocyte and ossification zones and an increase in mean bone density. Ectopic bone formation via subcutaneous and intramuscular injections of Wnt3A and/or ERα-transduced MPCs reveals that ERα significantly enhances the maturity and mineralization of Wnt3A-induced ectopic bone masses. Mechanistically, we demonstrate that E2 does not exert any detectable effect on Wnt/β-catenin reporter activity. However, ERα expression is up-regulated within the first 48h in AdWnt3A-transduced MPCs, whereas ERβ expression is significantly inhibited within 24h. Furthermore, the aromatase  exhibits a biphasic expression pattern, up-regulated at 24h but reduced after 48h, upon Wnt3A stimulation. Thus, our results demonstrate that while ER signaling acts synergistically with Wnt3A in promoting osteogenic differentiation, Wnt3A may crosstalk with ER signaling by up-regulating ERα expression and down-regulating ERβ expression in MPCs. It is conceivable that the signaling crosstalk and synergy between these two pathways should be further explored as a potential therapeutic approach to combating bone and skeletal disorders, such as fracture healing and osteoporosis.HEK293 cells were obtained from ATCC . Mouse mesenchymal progenitor cells iMEFs were established in our lab and previously characterized . Both ceThe recombinant adenoviruses were constructed by using AdEasy technology as described ,6,39-41.ALP activity was assessed using a modified Great Escape SEAP Chemiluminescence Assay  and/or histochemical staining assay , as described ,40,43,44Alizarin Red S staining was carried out as described previously ,42,43,45IHC staining was carried out as previously described ,46-49. T2 cell culture flasks and transfected with 2μg per flask of Tcf/β-catenin responsive luciferase reporter pTop-Luc using Lipofectamine (Invitrogen) as described [-4mol/L to 10-8mol/L estradiol. After 24h, cells were lysed, and collected for luciferase assays using Promega’s Luciferase Assay Kit . Each assay condition was performed in triplicate. Luciferase activity was normalized by total cellular protein concentrations among the samples. Relative Top-Luc reporter activity was expressed as mean ± SD.Exponentially growing cells were seeded in 25cmescribed ,11,50-53Total RNA was isolated with the TRIzol Reagents (Invitrogen) by following manufacturer’s instructions. The cDNA synthesis was carried out by reverse-transcription reaction with hexamer and M-MuLV Reverse Transcriptase . The cDNA products were further diluted 5 to10 fold and used as PCR templates. The sqPCR was carried out as described ,44,54,55-6mol/L) 24h after dissection. At least five limb explants were included in each assay group. On day 7, calcein (100mM) was added to the medium. On day 10, the cultured tissues were harvested. Soft tissues were removed. The samples were subjected to fluorescence microscopy, micro-CT imaging, and histologic evaluation. All animal experiments reported in this study were carried out in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. The protocol was approved by the Institutional Animal Care and Use Committee (IACUC) of The University of Chicago (protocol Number #71108). All surgery was performed under anesthesia, and all efforts were made to minimize suffering. The isolation and culture of mouse fetal limb explants was carried out as previously described ,14,36. BCultured mouse fetal limb specimens were imaged using the µCT component of a GE Triumph  trimodality preclinical imaging system as described ,36,44,566/injection) into the flanks, or for intramuscular injection into the quadriceps of athymic nude mice . At 6 weeks after implantation, animals were euthanized. The implant sites were retrieved for histologic evaluation.The use and care of animals was approved by the Institutional Animal Care and Use Committee. The subcutaneous and intramuscular ectopic bone formation assays were carried out as previously described ,36,44,56Retrieved and cultured tissues were fixed in 10% formalin, decalcified, and paraffin-embedded. Serial sections of the embedded specimens were stained with hematoxylin and eosin (H & E) as described ,40,43,56Quantitative data were expressed as mean ± SD. Statistical significances between treatment groups vs. control groups were determined by one-way analysis of variance and the two-tailed Student’s t test. A p-value of < 0.05 was defined as statistically significance.To determine if estrogen receptor signaling pathway exerts any effect on Wnt3A-induced osteogenic differentiation, we tested the effect of estradiol (E2) on Wnt3A-stimulated MPC line iMEFs. Exogenous expression of Wnt3A was mediated by a recombinant adenoviral vector, which was shown to transduce iMEFs with high efficiency 1A. As p-8M (p<0.05). Accordingly, when iMEFs were stimulated with E2 (10-7M), transduction with increasing titers of AdWnt3A led to a dose-dependent increase of ALP activity at day 5 and day 7 (except the highest titer) (at least p<0.05) (p<0.05) and 10μM (p<0.01) (p<0.05) and 5μM (p<0.01)  2B. We o p<0.05) 2C, alth(p<0.01) 2D. Simi(p<0.01) 2E. Take-7M E2, the expression of late osteogenic markers osteocalcin . Using fluorescence labeling dye calcein, we were able to trace the new bone formation . At the endpoint of assays the limb cultures were fixed and subjected to micro-CT scanning. We found that both Wnt3A and Wnt3A+E2 groups exhibited significantly higher mean bone density than that of the GFP+DMSO control   4B. Therctively) 4B. It ictively) 4C. Wnt3ctively) 4C. Thesin vivo. The iMEFs were first transduced with AdWnt3A and AdERα, or AdGFP , a key enzyme for the biosynthesis of estrogens, exhibits a biphasic expression pattern, up-regulated at 24h but reduced after 48h, upon Wnt3A stimulation. Thus, our results demonstrate that estrogen signaling acts synergistically with Wnt3A in promoting osteogenic differentiation and suggest that Wnt3A may crosstalk with estrogen signaling by up-regulating ERα expression and down-regulating ERβ expression in MPCs.Our findings indicate that Wnt3A can regulate the expression of ERα and ERβ in an opposite fashion, which may be consistent with numerous reports about the antagonist relationship between the two receptors -30. The It was reported that ERα may directly interact with β-catenin in human colon and breast cancer cells . HoweverIn summary, we investigate the possible crosstalk and synergy between ER signaling and canonical Wnt signaling in regulating osteogenic differentiation of MPCs. Our results demonstrate that the activation of ER signaling via estradiol and exogenously expressed ERα in MPCs synergistically enhances Wnt3A-induced both early and late osteogenic markers, as well as matrix mineralization. The E2 or ERα-mediated synergy can be effectively blocked by tamoxifen. E2 stimulation enhances endochondral ossification of Wnt3A-transduced mouse fetal limb explants. Exogenously expressed ERα in MPCs significantly enhances the maturity and mineralization of Wnt3A-induced ectopic bone masses. Mechanistically, we show that Wnt3A up-regulates the expression of ERα and aromatase but down-regulates ERβ expression in MPCs. It is conceivable that the signaling crosstalk and synergy between the ER signaling and Wnt/β-catenin pathways may be further explored as potential novel approach to combating bone and skeletal disorders, such as osteoporosis.Table S1Oligonucleotides for cloning and RT-PCR.(XLS)Click here for additional data file.


The relative importance of routes of transmission of Human T cell Lymphotropic Virus type 1 (HTLV-1) in Guinea-Bissau is largely unknown; vertical transmission is thought to be important, but there are very few existing data. We aimed to examine factors associated with transmission in mothers and children in Guinea-Bissau, where HTLV-1 is endemic .A cross-sectional survey was performed among mothers and their children (aged <15 years) in a rural community in Guinea-Bissau. A questionnaire to identify risk factors for infection and a blood sample were obtained. HTLV-1 proviral load in peripheral blood was determined and PCR was performed to compare Long Terminal Repeat (LTR) sequences in mother-child pairs.Fourteen out of 55 children (25%) of 31 HTLV-1 infected mothers were infected versus none of 70 children of 30 uninfected mothers. The only factor significantly associated with HTLV-1 infection in the child was the proviral load of the mother; the risk of infection increased significantly with the log10 proviral load in the mother's peripheral blood , adjusted for weaning age and maternal income. HTLV-1 sequences of the LTR region obtained from mother-child pairs were identical within pairs but differed between the pairs.Vertical transmission plays an important role in HTLV-1 transmission in this community in Guinea-Bissau. The risk of transmission increases with the mother’s proviral load in the peripheral blood. Identical sequences in mother-child pairs give additional support to the maternal source of the children's infection.


The term “retrograde signaling” refers to the concept that signals originating from chloroplasts or mitochondria can modulate nuclear gene expression (NGE). The evolutionary establishment of the complex mechanisms underlying retrograde signaling is likely to have required a long time period , Hypothesis and Theory, Mini Review, Review, and Perspective articles assembled for this Research Topic reflects not only the progress made in characterizing the four “classical” signal sources, but also highlights alternative interpretations of how information transfer from chloroplasts and mitochondria might be mediated and how the activities of these two organelles might be coordinated with that of the nucleus. Taken together, the contributions suggest a framework for future research in the retrograde signaling field.The collection of Original Research , the superoxide anion radical (O2−), the hydroxyl radical (OH·), and hydrogen peroxide (H2O2), more especially when exposed to stresses  in plastids (GO plants) can be exploited to study the effects of plastid-generated H2O2  and the triose phosphate/phosphate translocator , shows impaired acclimation to HL, resulting in impairments of the diurnal pattern of photoassimilate export from the chloroplast , which is involved in the chloroplast antioxidant defence system  causes the formation of white and green sectors. The report by Foudree et al.  mutants gun1-gun4 that show uncoupling of NGE from the physiological state of chloroplasts and assessed (2) the impact of post-translationally down-regulated ALA synthesis in gabaculine-treated seedlings and the gun4-1 mutant by global transcriptome analysis. Another model postulates that a specific heme pool generated by flux through ferrochelatase I serves as a signal source  is important for both chloroplast and mitochondrial retrograde signaling pathways is presented by León et al. . Van AkeProteins that are found both in the energy-producing organelles and the nucleus are excellent candidates for communicating information between these compartments. WHIRLY1 is such a protein, since it can be translocated from chloroplasts to the nucleus (Isemer et al., Duchêne and Giegé  review tMany research efforts have focused on dissecting retrograde signaling pathways using biochemical and genetic approaches. In addition, metabolomics and systems biology have great potential to promote hypothesis generation and help dissect signaling networks in an unbiased fashion. Here, Caldana et al.  outline The concept of retrograde signaling posits that signaling factors are generated in the organelles, are exported from the organelles, traverse the cytosol, and act in the nucleus. This notion is critically discussed by Leister , highlig


Human T-cell leukemia virus type 1 (HTLV-1) and type 2 both target T lymphocytes, yet induce radically different phenotypic outcomes. HTLV-1 is a causative agent of Adult T-cell leukemia (ATL), whereas HTLV-2, highly similar to HTLV-1, causes no known overt disease. HTLV gene products are engaged in a dynamic struggle of activating and antagonistic interactions with host cells. Investigations focused on one or a few genes have identified several human factors interacting with HTLV viral proteins. Most of the available interaction data concern the highly investigated HTLV-1 Tax protein. Identifying shared and distinct host-pathogen protein interaction profiles for these two viruses would enlighten how they exploit distinctive or common strategies to subvert cellular pathways toward disease progression.We employ a scalable methodology for the systematic mapping and comparison of pathogen-host protein interactions that includes stringent yeast two-hybrid screening and systematic retest, as well as two independent validations through an additional protein interaction detection method and a functional transactivation assay. The final data set contained 166 interactions between 10 viral proteins and 122 human proteins. Among the 166 interactions identified, 87 and 79 involved HTLV-1 and HTLV-2 -encoded proteins, respectively. Targets for HTLV-1 and HTLV-2 proteins implicate a diverse set of cellular processes including the ubiquitin-proteasome system, the apoptosis, different cancer pathways and the Notch signaling pathway.This study constitutes a first pass, with homogeneous data, at comparative analysis of host targets for HTLV-1 and -2 retroviruses, complements currently existing data for formulation of systems biology models of retroviral induced diseases and presents new insights on biological pathways involved in retroviral infection. Deltaretrovirus genus of the Retroviridae family [Human T-cell lymphotropic viruses HTLV-1 and -2 are members of e family , a neuroe family ,5. The ee family . ModulatHTLV genomes encode structural proteins that form the viral core particle (Gag and Env), and enzymatic retroviral proteins . HTLV contain a cluster of alternatively spliced open reading frames (ORFs) that encode regulatory proteins .VirusMINT [VirHostNet [Investigations focused on one or a few genes have identified numerous human factors interacting with HTLV viral proteins, with the results collected in several databases: irusMINT  and VirHrHostNet . Most ofrHostNet ,10. HencOur high-throughput yeast two-hybrid (HT-Y2H) technology employs well-defined collections of cloned open reading frames to provide systematic interrogation of potential PPIs -14. HT-YTo identify retroviral PPIs with the human proteome we adapted our well-established HT-Y2H system ,14. UsinHTLV structural and regulatory proteins have significant sequence or functional similarity . These homologous viral proteins might share one or more interacting partners amongst the human proteins, interactions that were not identified in initial screens because (i) highly overlapping or similar viral ORFs may be misidentified with BLAST, and (ii) interactions can be missed in a single screen ,13,18. WIn addition to applying stringent internal controls and retests, to eliminate artifacts of the assay , we verik = 13.75) compared to the whole network (k = 3.79), are more centrally located as measured by higher betweenness centrality (BC), 12443 for viral targets vs 2208 for random proteins, and have lower characteristic path length (CPL), 3.09 for viral targets vs. 4.38 for random proteins.Human proteins interacting with viral proteins apparently have significantly different topological properties compared to random proteins in the human PPI network ,21. ViraDegree, Characteristic path length (CPL) and betweenness centrality (Betweenness) for the 131 human proteins identified in our screen , the whole human PPI network (Whole Network), and for human proteins interacting with 19 random human proteins (Random Sources). P-values assess the difference between viral targets and the whole networkin vivo. To functionally validate our PPI dataset, we reasoned that some human proteins interacting with viral transactivators are likely to influence Tax transcriptional activities and thus contribute to viral replication and expression of cellular genes.As previously demonstrated and again confirmed here, our Y2H methodology delivers high quality, reproducible biophysical interactions -14, but Many HTLV-human interactions in our data set 106/166) involved the retroviral transactivator proteins HTLV-1 Tax (57/166) or HTLV-2 Tax2 (49/166). To examine the functional consequences of these associations, HEK293T cells were cotransfected with expression vectors for Tax-1 and Tax-interacting proteins, together with a firefly luciferase reporter driven by the HTLV-1 LTR promoter. As determined by normalized luciferase reporter assays, we identified 31 proteins (37% of the 83 Tax-interacting proteins) that regulated HTLV-1 LTR promoter activation by Tax , transcription factors  and proteins involved in the endosomal-lysosomal system (AP4M1 and GCC1)  contain only few PPI related to HTLV viruses. We thus manually curated the literature and found that most of host factors, which have been demonstrated to interact with HTLV proteins, concern the highly investigated HTLV-1 Tax (122/147)  , i.e. thFor each enriched KEGG pathway is given the pathway identifier in the KEGG database (Pathway ID), the number of observed proteins belonging to the considered pathway (Observed), the number of proteins in the pathway expected at random (Random), the ratio between the number of observed proteins and the expected number (Odds Ratio), the false discovery rate (FDR), and the corrected FDR (FDR-Corr)In an apoptotic pathway sub-network, KEGG analysis highlighted the tumor necrosis factor (TNF) receptor and the AKT/PI3K signaling pathways as potential targets for HTLV proteins. In this network HTLV Tax and Rex proteins are closely linked to the Akt/PI3K and mitochondrial apoptotic pathways. We identified interactions between HTLV Tax proteins and nitric oxide synthase 3 (NOS3), hepatocyte growth factor-regulated tyrosine kinase substrate (HGS), Ewing sarcoma breakpoint region 1 (EWSR1) and glucose transporter-4 (SLC2A4) proteins. KEGG analysis indicated that phosphatidylinositol-3-kinase (PI3K), BCL2-antagonist of cell death (Bad), and DNA fragmentation factor alpha (DFFA) proteins are second-degree targets of HTLV Tax proteins Figure . We alsoWe also identified TNF receptor-associated factor type 2 (TRAF-2) as a central protein mediating interactions between HTLV proteins, TNF receptor (TNFR) signaling, and the Akt/PI3K survival pathway Figure . We founCell cycle is a tightly regulated cellular process targeted by transforming viruses to modulate cell division and proliferation. HTLV-1 Tax has been shown to bind cell cycle key regulators including cyclins-D1, D2 and D3, cyclin-dependent kinases (CDK) 4 and 6; and CDK inhibitor p16INK4a, to influence T lymphocyte G1-S progression -47. HTLVWe identified cellular E2 ubiquitin-conjugating enzymes UBE2I and UBE2N or UBC13; and E3 SUMO-protein ligases PIAS (protein inhibitor of activated STAT) 1, 2 and 4. Both types of enzymes have been previously shown to play a role in Tax-mediated NF-kB activation ,51. KEGGMost eukaryotic cellular proteins are selectively degraded by the ubiquitin-proteasome system . Numeroup < 2.1E-5), Gag (p < 0.04) and Tax1 (p < 0.003) expression in MT4 cells Several global analyses of virus-host protein-protein interaction networks have led to interesting hypotheses about network topological properties and about shared target human proteins and pathways ,21. SuchHere, we identified by a systematic stringent high-throughput methodology, cellular interacting partners for HTLV-1 Tax, Rex, Env and HBZ; and for HTLV-2 Tax, Rex, Env, Pol, Gag, and APH-2 Figure  and 10. In conclusion, our experimental identification of 166 PPIs involving 10 HTLV-1 and -2 retroviral proteins with 122 human proteins extends and complements existing data on human-viral protein interactions ,71,72.We also identify and discuss common and distinct host cellular proteins targeted by HTLV-1 and -2 in relations with several cellular pathways, and we present innovative targets for further investigation of HTLV-induced network perturbations and illustrate the usefulness of this dataset by further investigation of Rex-DLC2, TRAF2-Gag and the involvement of the Notch pathway.http://pbildb1.univ-lyon1.fr/virhostnet. Interactions resulting from this study are provided in MIMIX specifications http://mibbi.org/index.php/Projects/MIMIx in Additional file All protein-protein interaction data were submitted to VirHostNet Invitrogen) using as PCR templates the following DNA clones obtained through the AIDS Research and Reference Reagent Program, Division of AIDS, NIAID, NIH: MT-2, ATK, pH6 B 3.5 and pH6 B 5.0. DNA clones MT-2 [HTLV-1 and HTLV-2 ORFeomes were cloned by Gateway recombination methodology  were transferred by LR cloning into pDB-dest and pAD-dest-CYH  to generMATa and MATα strains of yeast, respectively: MaV103 and Y8800 for all AD-ORFs and MaV203 and Y8930 for all DB-ORFs. Transformed yeast cells were spotted on solid synthetic complete (Sc) media lacking tryptophan (Sc-T) to select for AD-rvORF clones, or lacking leucine (Sc-L) to select for DB-rvORF clones. Growing colonies were cultured in liquid Sc-L or Sc-T media and stored in glycerol for subsequent use. To eliminate autoactivator baits that activate reporter genes in the absence of AD plasmids, all DB-ORFs in Mav203 strain or Y8930 were individually tested for auto-activation by growth on solid SC-L-H medium containing 20 mM (Mav103 strain) or 2 mM (Y8930 strain) 3-amino-triazole (3-AT). Aliquots of AD-rvORF transformed yeast were pooled to generate the AD-rvORF library.AD-rvORF and DB-rvORF yeast expressing vectors were transformed into two different MATα yeast strains of the human ORFeome version 3.1 [MATa yeast strains containing individual retroviral AD-rvORFs. The screen was also done in the reciprocal orientation, mating individual retroviral DB-rvORF yeast clones with the 12,212 human AD-ORFs pooled into 65 mini-libraries [de novo autoactivators were eliminated using the counter-selectable marker CYH2 [Yeast two-hybrid screening was as described . Yeast msion 3.1  was mateibraries . Diploidker CYH2 . PositivMATα (Mav203 or Y8930) and MATa (Mav103 or Y8800) yeast cells containing individual DB and AD fused to interacting human and retroviral ORF, respectively. Resulting diploid cells were tested for activation of multiple reporter genes [Each human protein found to interact with viral proteins was individually retested against all homologous proteins in the HTLV viruses. To this end, we mated er genes .The mammalian protein-protein interaction trap (MAPPIT)  fuses a t-test to assess the difference of the means between samples with and without the human interactor. For a trial to be considered positive, the relative luciferase activities have to be > = 2 or < = 0.5, and the p-value of the t-test < 0.05.The plasmid pHTLV1LTR-Luc, containing a luciferase reporter gene under the control of the HTLV-1 LTR promoter, a renilla luciferase control vector, and plasmids expressing HTLV-1 Tax and each human ORF found to interact with these viral proteins, were co-transfected into HEK293T cells by the calcium phosphate method. The LTR luciferase construct was obtained by subcloning HTLV-1 LTR promoter (a gift from F. Bex ) into pGt-test on triplicate experiments.HTLV-1 LTR promoter fused to firefly luciferase was transduced into Jurkat cells using the pREP10 vector (Invitrogen). Selection with hygromycin B (100 μg/ml) was employed to obtain stable transfectants (Jurkat-LTR-Luc cells). Lentiviral particles expressing a control shRNA and validated shRNA targeting various sequences of the SPG21 and FANCG mRNAs  were preU-test to compare the degree, CPL and betweenness distributions of the 131 viral targets to the whole network.We computed the mean degree, characteristic path length (CPL) and betweenness centrality in an unbiased human-human PPI network  for the Definitions of pathways came from the KEGG database (September 2008). We used Fisher's Exact Test to determine pathway enrichment of direct targets of viral proteins. To evaluate the significance of indirect targets enrichment, we ran 100,000 simulations where we randomized the identity of the direct targets. The interactors of these targets were identified in the unbiased PPI network ; interacTo avoid study bias inherent to literature curation, we used the CCSB-HI1 network  to compuTo construct sub-networks Figures  and 10 fHEK293T cells were cultured in a humidified atmosphere with 5% CO2 at 37°C in DMEM supplement with 10% of fetal bovine serum and antibiotics. HEK293T cells were transfected using the calcium phosphate method . In someHeLa cells were transfected with expression vectors for Rex1-GFP and Flag tagged DLC2 using Lipofectamine 2000 according to the manufacturer instructions (Invitrogen). Twenty four hours post-transfection, cells were fixed in 4% formaldehyde (20 minutes at room temperature), permeabilized with 0.5% triton X-100, and incubated with anti Flag M2 antibody (Sigma) followed by Alexa546 -coupled anti-mouse secondary antibody (Invitrogen). After nuclear staining with DRAQ5 (Invitrogen), and fixing with mounting medium , cells were analyzed using a Zeiss fluorescence confocal microscope (Carl Zeiss Microscopy).t-test.HTLV-1 transformed cell line (MT4) from Dr. Douglas Richman  was obtaHTLV-1: Human T-lymphotropic virus type-1; HTLV-2: Human T-lymphotropic virus type-2; HIV-1: Human immunodeficiency virus type 1; PPI: Protein-protein interaction; Y2H: Yeast two-hybrid; HT-Y2H: High-throughput yeast two-hybrid; MAPPIT: Mammalian protein-protein interaction trap; CPL: Characteristic path length; TNF: Tumor necrosis factor; FDR: False discovery rate.The authors declare that they have no competing interests.NS and J-CT designed and performed experiments, analyzed data and wrote the paper; J-FR and IL supervised some Y2H and MAPPIT experiments, respectively; TH and NK performed sequence analysis; THK, AD and J-FW performed some Y2H experiments; J-SG performed infection studies, MB performed confocal microscopy analysis, DV performed mass spectrometry analysis, SD, SL, MM, contributed to transactivation experiments and manuscript editing; VN curated PPI data. MEC, FD CVL and AB edited the manuscript; RK, MV, DEH and JT supervised the project. All authors read and approved the final manuscript.Table S1. List of viral ORFs. Table S2. experimental results. Table S3. Host factors regulating HTLV-1 LTR promoter activation by Tax. Table S4. Human proteins interacting with Tax viral proteins. Table S5. List of HTLV-1 and -2 host factors extracted from public database (Virhosnet) or literature search. Table S6. Viral targets degrees HTLV_human_PPIs_MIMiX.txt PPIs experimental results - MIMiX standard.Click here for filePPIs experimental results in MIMiX standard specifications.Click here for file


Human T-cell Leukemia Virus type-1 (HTLV-1) is highly immunogenic and has low variability so tight regulation of its expression is essential for virus maintenance in vivo. HTLV-1 replication is positively regulated by Tax and Rex, and negatively by the p30 and HBZ proteins. Here, we demonstrate that HTLV-1 encodes another negative regulator of virus expression, the p13 protein. Expressed separately, p13 localizes to the mitochondria, but in the presence of Tax, p13 is stabilized, and re-routed to the nuclear speckles. The p13 protein directly binds Tax, decreases Tax binding to the CBP/p300 transcriptional co-activator and, by reducing Tax transcriptional activity, suppresses viral expression. These findings suggest that HTLV-1 has evolved a complex mechanism to control its own replication through regulation of positive and negative viral proteins. Further, these results emphasize the importance of studying the function of the HTLV-1 viral proteins, not only in isolation, but also in the context of full viral replication.


Homo sapiens. We have implemented the method on this pathway system and observed the behavior of host signaling molecules upon pathogen attack. The entire study has been divided into six different cases, based on the perturbed/unperturbed conditions. In other words, we have investigated unperturbed and pathogen perturbed human TCR signaling pathway, with different combinations of optimization of concentrations of regulatory and signaling molecules. One of these cases has aimed at finding out whether minimization of the toxin production in a pathogen leads to the change in the concentration levels of the proteins coded by TCR signaling pathway genes in the infected host. Based on the computed results, we have hypothesized that the balance between TCR signaling inhibitory and stimulatory molecules can keep TCR signaling system into resting/stimulating state, depending upon the perturbation. The proposed integrated host-pathogen interaction pathway model has accurately reflected the experimental evidences, which we have used for validation purpose. The significance of this kind of investigation lies in revealing the susceptible interaction points that can take back the Staphylococcal Enterotoxin (SE)-challenged system within the range of normal behavior.Response of an immune system to a pathogen attack depends on the balance between the host immune defense and the virulence of the pathogen. Investigation of molecular interactions between the proteins of a host and a pathogen helps in identifying the pathogenic proteins. It is necessary to understand the dynamics of a normally behaved host system to evaluate the capacity of its immune system upon pathogen attack. In this study, we have compared the behavior of an unperturbed and pathogen perturbed host system. Moreover, we have developed a formalism under Flux Balance Analysis (FBA) for the optimization of conflicting objective functions. We have constructed an integrated pathway system, which includes Staphylococcal Superantigen (SAg) expression regulatory pathway and TCR signaling pathway of  Encounter with a specific antigen leads to the activation, proliferation and differentiation of T cells into mature/memory T cells in vivo, which is followed by a partial deletion of responder T cells. Responder T cells that survived the SAg response were found to be incapable of generating a secondary proliferative response to a SAg challenge Thymus derived lymphocytes/T cells play a central role in cellular immunity Difference between conventional antigen and superantigen: SAgs are bacterial and viral proteins that are potent activators of T cells. Conventional antigens are first processed within antigen presenting cells (APCs), bind with the peptide binding groove of MHC, and are presented to T cells with an antigen specific T cell receptor (TCR). In contrast, SAgs skip these processes. SAg proteins are usually of bacterial or viral origin, which are not internalized by APCs. They do not undergo intracellular processing, and are not presented on the surface of APCs Staphylococcus aureus can cause severe toxic shock through the release of pyrogenic exotoxins, known as SAgs, which trigger massive T cell activation and a ‘cytokine storm’ Superantigenicity of Staphylococcal Enterotoxins (SEs)- reason behind the choice of SAg for designing the study: SEs exert their effect on the host organism as follows: (1) as enterotoxins, they induce emesis and diarrhoea in humans and non-human primates e.g., interleukin 2 (IL-2) and tumor necrosis factor Pathogen perturbation on host system: In order to evaluate how SAg affects the TCR signaling pathway, it is first necessary to understand the dynamics of a normally functioning pathway. It can be used as a baseline against which a pathogen perturbed system can be compared. Such comparisons can expose the most susceptible proteins that are altered by a pathogen as well as the most critical reactions responsible for better functioning of a host’s biochemical network. In general, the outcome of host-pathogen interactions (in terms of a naive infected host) is dependent on the balance between the host immune defense and the virulence of a pathogen.in silico studies on host-pathogen interactions. FBA has been coupled with experimental studies to predict how viral infection would alter bacterial metabolism Bordetellae, viz., B. bronchiseptica and B. pertussisBordetellae can be separated into three distinct phases based on the most active immune processes. Co-culture experiments were performed for clinical strains of the opportunistic human pathogen Pseudomonas aeruginosa with Dictyostelium amoebae, to investigate the interactions of two organisms, such as, bacteria’s pathogenic action against amoeba There exists a few in silico gene deletions. The current state of the art for linear optimization in FBA is limited to the optimization of single objective function. We have considered modified methodology of FBA viz., minimization of toxin expression in a pathogen (S. aureus) and maximization of the concentrations of a stimulatory molecule present in TCR signaling pathway of an infected host (H. sapiens) for a case. Our aim is to compare the pathogen perturbed host system with that of unperturbed one.FBA has been used to analyze genome-scale reconstructions of several organisms; it has also been used to analyze the effect of perturbations, such as H. sapiens as given in literature and different biochemical pathway databases, then integrated it with SAg expression regulatory pathway of S. aureus. We have studied and compared the behavior of TCR signaling pathway in six different cases: (1) We have first implemented the methodology over an unperturbed TCR signaling pathway of H. sapiens and observed the concentrations of regulators  that maintain the required status/concentrations of the particular signaling molecules, (2) Secondly, we have studied the pathogen perturbed TCR signaling pathway , where objective function was to maximize the concentrations of stimulatory molecules  form. (3) In the third case, we have maximized both SAg expression in S. aureus as well as the concentrations of stimulatory molecules  to study the behavior of perturbed TCR signaling pathway molecules. (4) We have studied the behavior of the same integrated pathway on the optimization of two conflicting objective functions under FBA, where minimization of SAg expression and maximization of the concentrations of stimulatory molecules (TCR:CD3 complex and ZAP70) have been done. (5) In case (5), we have reversed the conflicting objective functions for optimization as given in case (4). (6) In the last case, the change in the concentrations of some of the signaling molecules, viz., ZAP70, LCK, FYN is explored, under pathogen perturbed and unperturbed conditions. We have compared the computed c-values and found that they were lower for most of the signaling molecules present in an unperturbed TCR signaling pathway in comparison to the perturbed one, except for the signaling molecules, e.g., SHP1 and CBL, which keep the TCR signaling pathway in a resting state. Moreover, for the last case (6), we have observed the higher concentration levels for the regulators that maintain status/concentrations of CBL and SHP1 and lower for immune response molecules, upon minimization of the concentrations of molecules, ZAP70, LCK and FYN in an unperturbed TCR signaling pathway. The results were in contrast to this for the case, where maximization of the concentrations of ZAP70, LCK and FYN in a perturbed TCR signaling pathway, has been done. We have compared the simulation results with existing experimental evidences and depicted the similarities between the two for validation purpose. We have also generated a hypothesis based on the in silico results. This kind of study can reveal potential targets for drugs also.First of all, we have designed TCR signaling pathway of i.e., SAg expression regulatory pathway in S. aureus, TCR signaling pathway in H. sapiens and molecular interactions among them. We have been able to construct an integrated pathway model for host-pathogen interaction based on the information available in literature as described below.Here we describe the pathways which are integrated for the study, Staphylococci are Gram positive cocci of 0.5∼1.5 e.g. hemolysins) and cell wall proteins  in S. aureus. The sar locus, contained within a 1.2-kb1 fragment, is composed of three overlapping transcripts designated sarP1 , sarP3  and sarP2 . SarA protein level is an important determinant of agr activation A second regulatory locus with pleiotropic effects on the production of virulence genes is sarA  viz., SarZ and MgrA sar was subsequently changed to sarA based on identification of 11 homologs T cell receptor (TCR) activation promotes a number of signaling cascades that ultimately determine cell fate through regulating cytokine production, cell survival, proliferation, and differentiation. An early event in TCR activation is phosphorylation of immunoreceptor tyrosine-base activation motifs (ITAMs) on the cytosolic side of the TCR/CD3 complex by lymphocyte protein-tyrosine kinase (Lck). The CD45 receptor tyrosine phosphatase modulates the phosphorylation and activation of Lck and other Src family tyrosine kinases. z-chain associated protein kinase (ZAP70) is recruited to the TCR/CD3 complex where it is activated and phosphorylation of downstream adaptor or scaffold proteins. Phosphorylation of SLP-76 by ZAP70 promotes recruitment of Vav (a guanine nucleotide exchange factor), the adaptor proteins NCK and GADS, and an inducible T cell kinase (ITK) DAG activates PKC-The binding of SAgs to TCR and/or to MHC class II molecules triggers intracellular biochemical signals for cell activation, differentiation, proliferation and the release of inflammatory cytokines 4 or 106 T cells, whereas SAgs are capable of interacting with as many as 5 to 20% of resting T cells. It is important to mention that this number can vary depending on the number of Vi.e., only self MHC class II molecules), whereas the response of T cells to SAg is MHC unrestricted and can occur in the presence of either self or foreign MHC class II molecules.The interaction of SAgs with MHC class II molecules is important for their ability to stimulate T cells, because accessory cells that do not express class II fail to provide costimulation for the superantigenic response H. sapiens in perturbed/unperturbed conditions, with six possible combinations of objective functions for optimization. We have also shown these combinations through a diagram, as given in Here, we provide the behavior of the signaling molecules present in TCR pathway of H. sapiens. We have manually constructed TCR signaling pathway (http://www.genome.jp/kegg/pathway/hsa/hsa04660.html), PANTHER (http://www.pantherdb.org/pathway/pathwayDiagram.jsp?catAccession=P00053), and as given in the websites of companies, CellSignaling Technology  and SABiosciences  among others.First of all, we have implemented the aforesaid method on pathogen unperturbed TCR signaling pathway of  pathway  from thei.e., The starting signaling molecule is TCRS. aureus and TCR signaling pathway of H. sapiens and is conceptually depicted by viz., LCK, FYN and ZAP70 We have constructed the pathogen perturbed integrated pathway comprising aforesaid SAg expression regulatory pathway of We have chosen this combination of objective function to demonstrate the effect of maximum perturbation on the host’s immune system, when it functions at its best. In this case, we have maximized the objective function in the form of maximizing expression of SAg and the concentration of stimulatory molecules of TCR signaling pathway present in the abovementioned integrated pathway. For this purpose, the objective function is i.e., minimization of toxin expression in a pathogen and maximization of the status/concentrations of TCR:CD3 complex and ZAP70 in a TCR signaling pathway of the infected host. Thus the objective function can be expressed as Next, on the same integrated pathway, we have opted to optimize two conflicting objectives simultaneously, c-values) of regulators quantitatively, through which these TCR signaling pathway proteins form. In this case, we have found the lower ) expression/concentrations of regulators that maintain the concentrations of the defense molecules  present in TCR signaling pathway of H. sapiens. It is due to toxin minimization in S. aureus in comparison to pathogen perturbed TCR signaling pathway in which SAg expression was kept unperturbed  of Here, we have aimed at finding out whether minimization of the toxin production in a pathogen leads to the change in the concentrations of the proteins coded by TCR signaling pathway genes in the infected host. The optimization of two conflicting objective functions is shown in erturbed . Howeverc-values for different combinations of conflicting objective function optimization have been given in Here we would like to observe the behavior of the host immune system at the time of maximum perturbation, when the host immune system is at its weakest status. For this purpose, we have chosen the same integrated pathway as above, with 99 molecules and 161 interactions. The objective function is c-values obtained for 6 different cases are justified. The biological significance of this variation in c-values lies in the choice of objective functions during optimization in 6 different cases. As we have mentioned earlier, we have found higher concentrations of regulators that maintain the concentrations of TCR signaling inhibitory molecules (SHP1 and CBL) in resting state of the T cells ). However, in the same case, the concentrations of regulators that maintain the concentrations of TCR signaling stimulatory molecules  would be lower. The reason behind this variation is that TCR signaling pathway does not need to be stimulated as there is no pathogen perturbation upon host. Likewise, we have considered six cases and almost all the TCR signaling molecules for analysis in these cases. From column 7 (Remarks) of c-values obtained for most of the cases are justified in biological context.Column 7 (Remarks) of viz., LCK and FYN, which initiates TCR signals. The regulation of LCK is critical for maintaining the resting state of the T cell and for signal transduction that includes tyrosine phosphoprotein induction as shown in LCK deficient studies The understanding of the control and regulation of TCR signaling is a key point to explore an adaptive immune system. It is mentioned earlier that activation of SYK family kinase (ZAP70) is an essential step in TCR signaling, which later phosphorylates the protein adaptor molecule, Linker for Activation of T cells (LAT). There exist two more protein tyrosine phosphate (PTKs), Taking these evidences of ZAP70, LCK and FYN into considerations, we have chosen the perturbation of their signals to check the effect on the signaling for inhibitory molecules (SHP1 and CBL) as well as on immune response cytokines. SHP1, a tyrosine phosphatase, regulates the level of active tyrosine kinases in peripheral T cells viz., ZAP70, LCK and FYN, which are responsible for stimulating the TCR signaling pathway upon infection. These signaling molecules are otherwise kept as inhibited by signaling molecules, CBL and SHP1. We have performed it upon two different conditions, viz., without and with pathogen perturbation, along with different objective functions. 1) We have opted for minimization of the expression/concentrations of the aforesaid signaling molecules, in an unperturbed TCR signaling pathway and 2) maximization of the same in a perturbed one. For these objective functions, we have observed the changes in concentrations of regulators for the reactions through which CBL and SHP1 form, and for immune response molecules, like, IL-2,-4,-5,-10, IFN-c-values for CBL and SHP1 in an unperturbed (resting) TCR signaling pathway, for which we have minimized the concentrations of ZAP70, LCK and FYN. In contrast to this, for perturbed (stimulated) TCR signaling pathway, where we have maximized the concentrations of the abovementioned signaling molecules, we have found lower c-values for CBL and SHP1 (due to pathogen infection). Moreover, we have also observed c-values for above mentioned immune response molecules in both the aforesaid cases. c-values for most of the immune response molecules were lower in an unperturbed TCR signaling pathway, where concentrations were minimized for ZAP70, LCK and FYN as an objective function, while it was higher in the other case as mentioned in We have perturbed the concentrations of the signaling molecules, c-values obtained for chosen signaling molecules upon resting and perturbed conditions, along with the choice of different objective functions. The hypothesis is as follows. The expression/concentrations of regulators that maintain the status/concentrations of the inhibitory molecules will be decreased upon pathogen attack on the host system. In contrast, the expression/concentrations of regulators that maintain the status/concentrations of the stimulatory molecules will be increased at this condition. These activities altogether leads to the stimulation of host immune system at the time of pathogen attack. Moreover, we would also like to mention that the concentrations of regulators that maintain the concentrations of the inhibitory molecules would be higher in resting TCR signaling system (with no pathogen perturbation). This is due to the fact that TCR signaling system does not require to be stimulated if there is no perturbation upon host. However, it would be lower upon pathogen attack on host as now the TCR signaling system requires to be activated/stimulated in order to fight against the pathogen.Thus we can hypothesize a relation between resting and stimulatory states, and for the behavior of the responsible signaling and immune response molecules in TCR signaling pathway. This hypothesis is based on different c-values under unperturbed, pathogen perturbed and perturbation with conflicting objectives (case 4) in the following text. The abstract of this Section has been given in H. sapiens for a particular perturbation condition.In this Section, we provide the biological validation of the results obtained from abovementioned methodology implemented on six different cases. Here, we compare our results with existing experimental evidences on TCR signaling pathway following the stimulation with Staphylococcal enterotoxins. We have mostly compared the As mentioned earlier, we have studied and compared the behavior of TCR signaling pathway for six different cases:H. sapiens and observed c-values of the signaling molecules.First of all, we have implemented the method over an unperturbed (resting state) TCR signaling pathway of S. aureus and TCR signaling pathway of H. sapiens has been integrated.Pathogen perturbed (stimulated) TCR signaling pathway has been investigated for which SAg expression regulatory pathway of S. aureus as well as the concentrations of the stimulatory molecules  to study the behavior of perturbed TCR signaling pathway molecules.We have maximized both SAg expression in c-values. Here, minimization of SAg expression and maximization of the concentrations of stimulatory molecules (TCR:CD3 complex and ZAP70) have been done.We have studied the behavior of the same integrated pathway over the optimization of two conflicting objective functions for which, we have applied a conflicting objective function optimization under FBA and compared the We have explored the behavior of the same integrated pathway, upon optimization of two conflicting objective functions, however, here the conflicting objectives are just opposite of the case (4).c-values for CBL, SHP1 and interleukins, while perturbing the concentrations of the some of the signaling molecules, viz., ZAP70, LCK and FYN, under pathogen perturbed and unperturbed conditions.We have also compared the c-values in [0–1] for inhibitor molecules, like, for CBL and SHP1, in the absence of any pathogen attack. In the presence of a pathogen (pathogen perturbed system), we have assumed higher c-values for the stimulatory molecules, like, ZAP70, LCK among others, which later produce cytokines and interleukins. The fourth case is of optimization of conflicting objective functions, where we have assumed comparatively lower c-values of stimulatory molecules due to toxin minimization in S. aureus. On the basis of above assumptions, we have compared c-values and validated the results through existing experimental observations for TCR signaling pathway stimulated by Staphylococcal enterotoxins (direct evidences) or otherwise (indirect evidences). The comparison of c-values for some of the signaling molecules based on abovementioned three cases are given in We have assumed higher e.g., E3 ubiquitin ligases c-CBL, b-CBL, SHP1 among others c-value for NFAT in an unperturbed TCR signaling pathway, whereas, it is increased (0.51727) due to the effect of SAg on TCR signaling. In the third case, it has become 0.30107 on SAg expression minimization.There are some negative regulators for TCR signaling pathway that inhibit TCR-mediated downstream signaling, c-value for signaling molecule CBL in an unperturbed system that further inhibit LCK, FYN and ZAP70. We have got c-value of 0.99269 for CBL in pathogen unperturbed system, whereas it has become 0.5974 and 0.21257 for pathogen perturbed system and for the system, where conflicting objectives have been optimized. It is the same case with SHP1, which inhibits ZAP70 and TCRc-values. The c-value for the regulators of SHP1 is higher (0.67791) in a pathogen unperturbed pathway, where as it has become 0.3227 at the time of pathogen attack and 0.34291 during conflicting objective function optimization  for PKC-c-values has become 0.85534 and 0.15222 in a pathogen perturbed system and in the system, where it is optimized for two conflicting objectives, respectively. PKC-i.e., c-value of 0.39187 for PLC-The intracellular signals underlying programmed cell death suggests that DAG activated PKC may serve as a negative regulator. Lin et al. c-value of c-value for IP3 in an unperturbed TCR signaling pathway. In contrast, it has become 0.77416 and 0.92249 in a pathogen perturbed system and in the system, where it is optimized for two conflicting objective functions, respectively.SEB mobilizes intracellular free calcium (Ca) in HLA-DR positive but not in HLA-DR negative keratinocytes c-value for both DAG and PKC-c-value for DAG in an unperturbed TCR signaling pathway. On the other hand, it has become 1 in a pathogen perturbed system and in the system, where it is optimized for two conflicting objective functions, respectively. For PKC-A study has shown to block TNF-c-values. We have found lower (0.026283) c-value for LCK in an unperturbed TCR signaling pathway. In contrast, it has become 0.91611 and 0.39188 in a pathogen perturbed system and in the system, where it is optimized for two conflicting objective functions, respectively. In the same way, we got lower (0.40972) c-value for FYN in an unperturbed TCR signaling pathway. In contrast, it has become 0.86331 and 0.76781 in a pathogen perturbed system and in the system, where it is optimized for two conflicting objective functions, respectively.It is well known that the activation of the src-family kinases LCK and FYN is central to the initiation of TCR signaling pathways c-value for RasGRP1 in an unperturbed TCR signaling pathway. In contrast, it has become 0.58313 and 0.51328 in a pathogen perturbed system and in the system, where it is optimized for two conflicting objective functions, respectively. Moreover, we have got lower (0.11708) c-value for MEK1/2 in an unperturbed TCR signaling pathway, respectively. In contrast, it has become 0.12904 and 0.33124 in a pathogen perturbed system and in the system, where it is optimized for two conflicting objective functions respectively. We have found lower (0.42317) c-value for Raf in an unperturbed TCR signaling pathway. In contrast, it has become 0.49728 and 0.44493 in a pathogen perturbed system and in the system, where it is optimized for two conflicting objective functions, respectively.Li et al. c-value for SLP-76 in an unperturbed TCR signaling pathway. In contrast, it has became 0.60307 and 0.5495 in pathogen perturbed system and in the system, where it is optimized for two conflicting objective functions, respectively. In the same manner, we have found lower (0.25764) c-value for LAT in an unperturbed TCR signaling pathway. In contrast, it has become 0.57508 and 0.15188 in pathogen perturbed system and in the system, where it is optimized for two conflicting objective functions, respectively. In LAT-deficient J.Cam2 Shim et al. c-value for Dlgh1 (or Dlg1) in an unperturbed TCR signaling pathway. In contrast, it has become 0 and 0.46094 in pathogen perturbed system and in the system, where it is optimized for two conflicting objective functions, respectively.Dlg1 is expressed in all T cell developmental stages and forms a stable complex with LCK c-value for Rho/Cdc42 in an unperturbed TCR signaling pathway. In contrast, it has become 0 and 0.31557 in a pathogen perturbed system and in the system, where it is optimized for two conflicting objective functions, respectively.The cytoskeleton of eukaryotic cells has a pivotal role in host-pathogen interactions as it is essential for epithelial and endothelial barrier functions. It limits the invasion and dissemination of pathogens in tissues c-value for IL-2, which has become higher (0.84865) at the time of infection, and has again been lower (0.83404) when we optimized the integrated pathway system for two conflicting objective functions. The case is similar to IL-10, IFN-c-values can be compared as given in c-value for IFN-SAgs have been demonstrated to act as potent inducers of several proinflammatory cytokines in the APCs such as interleukin-1 (IL-1) and tumor necrosis factor-It should be mentioned here that repeated injections of enterotoxin in mice resulted in high levels of IL-10, but there was also a dramatic decrease in all the other cytokines , MALT1 (mucosa-associated lymphoid tissue lymphoma translocation protein 1), and IKK complex into an immunological synapse c-value of 0 for NF-CARMA1 recruits signaling components, c-values for AKT1 was lower (0.032244) in an unperturbed TCR signaling pathway, whereas, it was higher (0.95152) in perturbed one and again lower (0.093664) in an integrated pathway which was optimized for two conflicting objective functions. The case is similar with IKK complex, where c-value is lower (0.70419) in an unperturbed TCR signaling pathway, which later has increased (0.90608) in a perturbed TCR signaling pathway. It has again decreased (0.71188) in an integrated pathway which was optimized for two conflicting objective functions.Similarly, Wang et al. c-value for CARMA complex in an unperturbed TCR signaling pathway. In contrast, it has become 0.81185 and 0.23229 in pathogen perturbed system and in the system, where it is optimized for two conflicting objective functions, respectively.MALT1 is recruited to the lipid rafts of the immunological synapse following activation of TCR and CD28 coreceptor (CD3/CD28 costimulation). This recruitment is dependent on CARMA1 c-values obtained from our results, we can say that we have got almost similar results in the form of lower c-values of NCK and PAK in an unperturbed TCR signaling pathway, which then has increased upon stimulation. We have found lower (0.654) c-value for NCK in an unperturbed TCR signaling pathway. In contrast, it has become 0.57508 and 0.042724 in pathogen perturbed system and in the system, where it is optimized for two conflicting objective functions, respectively. For PAK, the c-values are, 0.017261 for an unperturbed TCR signaling pathway. In contrast, it has become 0.20377 and 0.096005 in pathogen perturbed system and in the system, where it is optimized for two conflicting objective functions, respectively.NCK plays a pivotal role in TCR-induced reorganization of the actin cytoskeleton and the formation of the immunological synapse in T lymphocytes. It binds with phosphorylated SLP76 and recruits WASP, where, SLP76 functions as a scaffold bringing NCK and WASP into proximity with VAV1 and Cdc42-GTP in silico analysis, we have found lower (0.5286) c-value for SOS in unperturbed TCR signaling pathway. In contrast, it became 0.50821 in both pathogen perturbed system and in the system, where it is optimized for two conflicting objective functions, respectively. Considering the case of VAV, we have found lower (0.24826) c-value for VAV in an unperturbed TCR signaling pathway. In contrast, it has become 0.7427 and 0.53051 in a pathogen perturbed system and in the system, where it is optimized for two conflicting objective functions, respectively.In activated T cells, SOS promotes the conversion of Ras to the GTP-bound active state H. sapiens for aforesaid six different cases. In this way, we can study how an immune signaling pathway behaves at the time of infection/pathogen attack. Significance of this kind of study is that it exposes the proteins which get altered upon infection. The expression of many virulence determinants in S. aureus is controlled by regulatory loci, like, agr and sar. S. aureus toxins are the staphylococcal enterotoxin, SAgs that can stimulate whole T cell subpopulations by cross-linking TCRs with MHC-II molecules. Both human and mouse T cells can be activated by enterotoxins and produce cytokines.We have constructed an integrated pathogen perturbed immune signaling pathway model. Here we have implemented a simple gradient descent based optimization developed under FBA, which enables us to compare and studied the behavior of TCR signaling pathway of in vivo. Responder T cells that survived the SAg challenge were found to be incapable of generating a secondary proliferative response (known as anergy) against SAg due to CD8-positive regulatory suppressive T cells. These regulatory cells inhibit cell division of preactivated T cells but not the SAg response of naive T cells in vivoin vivo SEB-induced anergic state of T cells H. sapiens under pathogen perturbed and unperturbed conditions, assuming naive T cells.Superantigen (SAg) stimulates naive T cells Systems level modeling and simulations have been proved invaluable in obtaining a quantitative and dynamic perspective of various aspects of cellular functions. Among them, constraint-based analyses, such as flux balance analysis (FBA), are quite popular for simulating cellular systems, specifically metabolism. Unlike mechanistic simulations (that depend on scarcely available accurate kinetic data), FBA is based on the principle of conservation of mass in a network, which utilizes the stoichiometric matrix and a biologically relevant objective function to identify optimal reaction flux distributions.S. aureus. However, it is possible that some other host’s systems may also be affected due to the pathogen attack. In the case of pathogen S. aureus, we have only considered expression regulatory pathway for SAg, although, S. aureus expresses many other forms of enterotoxins, exotoxins as well as virulence proteins. Therefore, steady state and closed boundary assumptions are required here.Stoichiometric representation of a biochemical pathway can be in the form of a matrix, e.g., transcription factors/enzymes/other regulators, like, addition of phosphate molecule in phosphorylation reactions, called phosphoregulation), catalyzing various reactions in the biochemical network, may not be expressed at the desired level. This is the reason behind incorporating concentration factor For the expression i.e., We are able to know, using viz., minimization of the expression level of SAg in S. aureus and maximization of the expression/concentration levels of TCR:CD3 complex and ZAP70 in host. Minimization of the expression level of SAg in S. aureus simply refers to in silico manipulation of the concentration of the regulators , The modified value of


HTLV-1 increases susceptibility to infections. Few studies have addressed the co-infection between HPV/HTLV-1 and the immune response involved in this interaction.To determine prevalence of cervical HPV infection and to evaluate HTLV-proviral load and CD4 T lymphocyte proportion in co-infected patients.A cross-sectional study was carried out in Salvador-Brazil, between September 2005 to December 2008, involving 50 HTLV-1-infected women from the HTLV Reference Center and 40 uninfected patients from gynecological clinic, both at the Bahiana School of Medicine. HPV infection was assessed by hybrid capture. HTLV-1 proviral load was quantified by real time PCR and CD4+ T-lymphocyte count using flow cytometry.6 PBMC) and uninfected patients  nor in the proportion of CD4+ T-lymphocytes .Mean age of HTLV-1-infected women (38±10 yrs) was similar to that of the control group (36±13 yrs). The prevalence of HPV infection was 44% in the HTLV-1-infected group and 22.5% in uninfected women (p=0.03). HTLV-1-infected women had lower mean age at onset of sexual life  and greater number of lifetime partners compared to the control group . In the group of HTLV-1-infected patients, there was neither difference in HTLV-1 proviral load between HPV-infected women (16,000 copies/10The prevalence of HPV infection is higher in HTLV-1-infected women. No association was found between HPV infection, CD4+ T lymphocyte proportion or HTLV-1-proviral load in HTLV-1-infectred patients. Further studies should be performed to evaluate the progression of this co-infection.


Enterococcus hirae is composed of a soluble functional domain V1 (A3B3DF) and an integral membrane domain Vo (ac), where V1 and Vo domains are connected by a central stalk, composed of D-, F-, and d-subunits; and two peripheral stalks (E- and G-subunits). We identified 120 interacting residues of A3B3 heterohexamer with D-subunit in DF heterodimer in the crystal structures of A3B3 and A3B3DF. In our previous study, we reported 10 mutants of E. hirae V1-ATPase, which showed lower binding affinities of DF with A3B3 complex leading to higher initial specific ATPase activities compared to the wild-type. In this study, we identified a mutation of A-subunit (LV476-7AA) at its C-terminal domain resulting in the A3B3 complex with higher binding affinities for wild-type or mutant DF heterodimers and lower initial ATPase activities compared to the wild-type A3B3 complex, consistent with our previous proposal of reciprocal relationship between the ATPase activity and the protein-protein binding affinity of DF axis to the A3B3 catalytic domain of E. hirae V-ATPase. These observations suggest that the binding of DF axis at the contact region of A3B3 rotary ring is relevant to its rotation activity.Vacuolar ATPase (V-ATPase) of  This acs Forgac .Thermus thermophilus and Enterococcus hirae. T. thermophilus V-ATPase physiologically functions as an ATP synthase  and 2 peripheral stalks (composed of E- and G-subunits of V1)  of A- at Figure .Figure 1476-7AA)  Figure B neighboe Figure F of A-su3B3 and A3B3DF  of V1-ATPase 3B(L389A)3 heterohexamer. A(LV476-7AA) monomer showed a very low efficiency of complex formation with either wild-type B or B(L389A) monomer in the presence of 2 mM ATP, distinct from wild-type  showed efficient reconstitution of A(LV476-7AA)3B3 and A(LV476-7AA)3B(L389A)3 heterohexamers in the presence of 200 μM AMP-PNP  instead of 2 mM ATP . Both mutant heterohexamers were purified by gel-filtration chromatography 3B3 and A(LV476-7AA)3B(L389A)3 heterohexamers showed lower stability than the wild-type A3B3; in native PAGE, a band at position of A(LV476-7AA)1B1 or A(LV476-7AA)1B(L389A)1 complex was observed after a few days storage at -80˚C and A(LV476-7AA)3B(L389A)3 heterohexamer dissociated into monomers after a few weeks storage at 4°C ).From the crystal structures of A476-7AA)3B3 and A(LV476-7AA)3B(L389A)3 heterohexamers formed V1 domains (A(LV476-7AA)3B3DF and A(LV476-7AA)3B(L389A)3DF complex, respectively) of V-ATPase with DF heterodimer 3B3 and A(LV476-7AA)3B(L389A)3 heterohexamers were incubated with DF heterodimer in the absence of nucleotides, both heterohexamers formed catalytic domains, A(LV476-7AA)3B3DF and A(LV476-7AA)3B(L389A)3DF, respectively 3B3D(RR165-6AA)F and A(LV476-7AA)3B3D(L170N)F, showing the similar reconstitution efficiencies in native-PAGE like as the wild-type (data not shown), which indicates similar structural integrity of the purified mutant V1-ATPases.A3B3DF and A(LV476-7AA)3B(L389A)3DF complexes 3B3DF and A(LV476-7AA)3B(L389A)3DF complexes were not so much different  from that of wild-type (Km = 0.4 mM) 3B3D(RR165-6AA)F and A(LV476-7AA)3B3D(L170N)F complexes showed almost similar initial specific activities 3B3 heterohexamer showed higher binding affinity 3B3 heterohexamer showed very low binding affinity for D(RR165-6AA)F  and B(L389A) were capable to form heterohexamers, A(LV476-7AA)3B3 and A(LV476-7AA)3B(L389A)3, like as the wild-type  with wild-type/mutant DF heterodimers as the similar extent of the wild-type. These mutant V1-ATPases were functionally active and showed different initial specific activities depending on the nature of the amino acid substituted. Hydrophilic/polar arginine  are in close contact with R165, L170  is closely located near LV476-7 residues of A-subunit  mutation showed similar to lower initial specific activities with higher binding affinities than those of the wild-type ), we found almost similar ATPase activity as the wild-type and small difference of binding affinity correlating with initial specific activities  mutant with wild-type A3B3 complex 3B3, it showed very low binding affinity with high ATPase activity (compared to A(LV476-7AA)3B3DF, Table 3B3DF; this low ATPase activity may be because of the dissociation of some DF heterodimer during ATPase assay owing to the low affinity, consistent with the expectation that RR165-6 of D-subunit is closely located to LV476-7 of A-subunit in “tight” form (ACR-BCR pair) of our crystal structures  and D(L170N)F mutants gave compensating effect showing nearly similar specific activities and binding affinities to those of each single mutant, suggesting the substantial interaction between A(LV476-7) and D(L170)  Table .A and B genes with optimal codon usage for an Escherichia coli expression system were cloned into the plasmid vector pET23d  in modified-Davis Mingioli-Casamino Acid (m-DM-CA) medium  proteins obtained was 20 mg. We also tried to obtain a deletion mutant ΔRLV475-7 of A-subunit at the C-terminal domain and also a double mutant VL388-9AA of B-subunit locating at the conserved region of D-subunit, but VL388-9AA could not be expressed and ΔRLV475-7 was not purified due to its instability.Synthesized DNA fragments corresponding to the E. coli cell-free protein expression system was used, as described elsewhere . The protein mixture was then incubated on ice for 1 h in the presence of 200 μM AMP-PNP and afterward concentrated to 100 μL by ultrafiltration using Amicon Ultra-4 30 K filters . Then, 4 mL of buffer A with AMP-PNP was added to dilute the protein solution, and the solution was concentrated again to 100 μL. This dilution/concentration process was repeated thrice without adding AMP-PNP. The A3B3 heterohexamer was finally purified using a Superose 6 pg column (500 × 16 mm ID) . Complex formation was confirmed by using basic native-PAGE as previously described , purified wild-type/mutant A3B3 heterohexamers and synthesized DF heterodimer were incubated on ice for 1 hour mixing at a 1:5 molar ratio . The reaction was initiated by adding 4 μg proteins. The rate of ATP hydrolysis was monitored at 25°C in terms of the rate of oxidation of NADH, as determined by the decrease in absorbance at 340 nm. Specific activities were calculated as units/mg proteins, with 1 unit of ATPase activity being defined as hydrolysis of 1 μmol ATP/min. Initial ATPase activity was calculated by measuring the specific activity during the first minute (starting from the 16th second) after adding the proteins. The measurement was repeated three times and averaged and the standard deviation was calculated. Km and Vmax were calculated by fitting the averaged values as straight lines in Lineweaver-Burk plots.Initial ATPase activities of the reconstituted A3B3 complex was measured by SPR analysis on a Biacore T100 instrument  as described previously  sorbitol monolaurate), passing through the Biacore flow cell at a rate of 10 μL/min. A flow cell containing no protein served as a negative control. Different concentrations of DF complex were prepared as analyte in the running buffer. The obtained sensorgrams were evaluated using Biacore T100 evaluation software. The equilibrium constant for dissociation, KD, were obtained using the Langmuir binding model (1:1 binding model).The binding affinity of DF complex to the reconstituted AProtein concentration was determined by DC Protein Assay Kit (Bio-Rad Laboratories) using bovine serum albumin as the standard. To check the purified proteins, SDS-PAGE was performed according to Laemmli Laemmli , and sta


HTLV-I and –II (HTLV-I/II) infection is prevalent at low levels in the United States, but recent reports on HTLV-I/II prevalence among blood donors are lacking.Computerized data on all first-time blood donors in a large network of United States blood centers was examined during the period 2000-2009. HTLV-I/II antibody was measured by enzyme immunoassay (EIA), with supplemental testing of all reactive samples using an EIA from an alternate manufacturer. Prevalence rates were calculated, and odds ratios (OR) and 95% confidence intervals (CI) for associations with demographic characteristics were assessed using multivariate logistic regression.Among 1,904,155 first-time blood donors, HTLV-I/II prevalence decreased from 10 per 10,000 in 2000 to 5 per 10,000 in 2009 (p trend < 0.0001). Prevalence increased with age through middle age and then decreased in older age. HTLV-I/II infection was associated with female sex , age 50-59 , Black  and Hispanic  race/ethnicity, and inversely with university education . There was minimal geographic variation, although donors from the southwestern US had slightly higher prevalence.HTLV-I/II prevalence is decreasing slowly among US blood donors, consistent with a birth cohort effect whereby donors born in the 1950s and 60s had higher prevalence rates compared to younger donors. HTLV-I/II associations with female sex, non-white race and lower educational achievement are consistent with previous studies. With 3.2 million first-time donors annually nationwide, US blood banks detect several hundred HTLV-I/II infections per year.


VLA-4 conformation is rapidly up-regulated by inside-out signaling through Gαi-coupled GPCRs and down-regulated by Gαs-coupled GPCRs. However, other signaling pathways, which include nitric oxide-dependent signaling, have been implicated in the regulation of cell adhesion. The goal of the current report was to study the effect of nitric oxide/cGMP signaling pathway on VLA-4 conformational regulation.Integrin activation in response to inside-out signaling serves as the basis for rapid leukocyte arrest on endothelium, migration, and mobilization of immune cells. Integrin-dependent adhesion is controlled by the conformational state of the molecule, which is regulated by seven-transmembrane Guanine nucleotide binding Protein-Coupled Receptors (GPCRs). αi-coupled receptors: wild type CXCR4, CXCR2 (IL-8RB), and a non-desensitizing mutant of formyl peptide receptor (FPR ΔST). Upon signaling, we detected rapid changes in the ligand dissociation rate. The dissociation rate after inside-out integrin de-activation was similar to the rate for resting cells. In a VLA-4/VCAM-1-specific myeloid cell adhesion system, inhibition of the VLA-4 affinity change by nitric oxide had a statistically significant effect on real-time cell aggregation.Using fluorescent ligand binding to evaluate the integrin activation state on live cells in real-time, we show that several small molecules, which specifically modulate nitric oxide/cGMP signaling pathway, as well as a cell permeable cGMP analog, can rapidly down-modulate binding of a VLA-4 specific ligand on cells pre-activated through three Gαi-coupled GPCR signaling, generated by a non-desensitizing receptor mutant. This suggests a fundamental role of this pathway in de-activation of integrin-dependent cell adhesion.We conclude that nitric oxide/cGMP signaling pathway can rapidly down-modulate the affinity state of the VLA-4 binding pocket, especially under the condition of sustained Gα Integrins are ubiquitous cell adhesion molecules that play an essential role in the regulation of leukocyte traffic, stem cell mobilization and homing, immune responses, development, hemostasis, and cancer -3. On th4β1-integrin, CD49d/CD29) is expressed on a majority of peripheral blood leukocytes, hematopoietic progenitors and stem cells, as well as hematopoietic cancer cells pyridine, activator of soluble guanylate cyclase); DEA-NONOate: -diazenolate, nitric oxide donor); cGMP: ; dbcGMP: (NAC designed the study, carried out ligand binding experiments, and wrote the manuscript. YS carried out ligand binding and aggregation experiments. LAS participated in study coordination. All authors read and approved the final manuscript.


Macrophages regulate many developmental and pathological processes in both embryonic and adult tissues, and recent studies have shown a significant role in angiogenesis. Similarly, Wnt signaling is fundamental to tissue morphogenesis and also has a role in vascular development. In this review, we summarize recent advances in the field of macrophage-regulated angiogenesis, with a focus on the role of macrophage-derived Wnt ligands. We review data that provide both direct and indirect evidence for macrophage-derived Wnt regulation of physiologic and pathologic angiogenesis. Finally, we propose that Wnt signaling plays a central role in differentiation of tumor associated and wound infiltrating macrophages to a proangiogenic phenotype. Angiogenesis is the growth of new blood vessels from the existing vasculature. This process plays critical roles in both development and pathological conditions such as tumor growth and diabetic retinopathy . During Members of the Wnt protein family have been shown to regulate diverse biological processes including cell proliferation, apoptosis, polarity, differentiation and the maintenance of pluripotency in stem cells . Wnt pro2+influx as well as activation of the small GTPases, RhoA, Cdc42 and Rac [http://www.stanford.edu/~rnusse/wntwindow.html.In humans, Wnt signaling is mediated by a family of 19 secreted Wnt glycoproteins and 10 transmembrane Frizzled (Fzd) receptors . Althoug and Rac ,12. A de and Rac ,8,10,11 Evidence for Wnt signals regulating angiogenesis is provided firstly by reports of ECs expressing a number of Wnt receptors including Fzd1, Fzd2, Fzd4, Fzd5, Fzd6, Fzd7, Fzd9, Fzd10, Lrp5, Lrp6 and the Wnt signaling modulator,Ryk -16. It iThe story is much the same in vivo, with several reports of active Wnt signaling in EC undergoing angiogenesis -33. More−/− mice display significant reductions in arteriole density in the heart and kidney as well as impaired angiogenesis in a mouse model of hind limb ischemia [Disturbing Wnt receptor expression in vivo can also lead to vascular defects, with the most well-studied receptors being Fzd4 and Fzd5. Fzd4 loss-of-function mutations have been linked to familial exudative vitreoretinopathy (FEVR), a disease characterized by abnormal retinal vasculature . Furtherischemia . The eviischemia . A more ischemia .Clearly there is a plethora of evidence implicating Wnt signaling in modulating angiogenesis. For a more extensive overview of the literature, the reader is referred to several recent reviews -44.−/− and Csf-1op/op mice, resulted in a decreased number of vessel intersections in the hindbrain, providing the first evidence that macrophages actively participate in vessel anastomosis [There is substantial evidence that macrophages play a significant role in both physiological and pathological angiogenesis ,45,46. Istomosis . Interesstomosis . Also ofstomosis . Howeverstomosis -51. Outtstomosis  and studop/op mice and this correlated with decreased vascular density [Macrophages, given their ability to migrate within virtually all tissues of the body, are also an ideal cell to regulate angiogenesis during tissue injury and repair. Using, a transgenic mouse model of ischemic cardiomyopathy, Moldovan et al. showed that macrophages carved out tunnels in the ECM, thereby providing avenues for subsequent capillary infiltration . Macroph density . Thus, aA rapidly developing field is the study of tumor-associated macrophages (TAMs) and their role in promoting tumor progression. It comes as no surprise that TAMs mediate some of their effects on tumor growth by regulating angiogenesis ,46,55,56Based on the studies outlined above, it is evident that both macrophages and secreted Wnt proteins regulate angiogenesis. It may, therefore, be reasonable to hypothesize that Wnt ligands mediate some of the effects that macrophages have on angiogenesis, and indeed, macrophages do express Wnt ligands. Interferon-γ (IFN-γ) and lipopolysaccharide (LPS), two potent inducers of inflammation, lead to significant upregulation of Wnt5a transcript and protein levels in macrophages . FurtherAside from inflammatory angiogenesis, research in cancer biology also points to a role for macrophage-derived Wnts in regulating tumor angiogenesis. Smith et al. looked at Wnt expression in 14 matched cases of normal, adenomatous and malignant colorectal tissues and reported upregulation of Wnt gene expression in TAMs, in particular, Wnt2 and Wnt5a, during the progression from normal through adenoma to carcinoma in colorectal tissue . Of noteDirect evidence for the involvement of macrophage-derived Wnts in regulating hyaloid vascular remodeling and developmental angiogenesis in the retina comes from studies by Lang and colleagues. The hyaloid vessel system is laid down during development of the eye and requires remodeling after birth to allow for unobstructed vision . Macroph+/− and Wnt11+/− heterozygotes. The mechanism was shown to involve an autocrine-signaling axis where macrophage-derived Wnt5a and Wnt11 induce secretion of the soluble VEGF inhibitor Flt1 [Non-canonical Wnts secreted by macrophages also regulate vessel branching in the mouse retina. Shortly after birth, vessels from the superficial vascular plexus on the surface of the retina sprout vertically, down through the ganglion. Upon reaching the outer edge of the inner nuclear layer, EC turn and branch to form the deep vascular plexus . Stefatetor Flt1 ,89 that,tor Flt1 .It is clear that Wnt signaling is important for angiogenic regulation by macrophages and we anticipate that future research in this field will reveal an even more crucial role for these proteins in this process.series of events with different morphological changes required at different stages. Therefore, the same protein may inhibit or induce angiogenesis depending on the stage of angiogenesis at which it is present. We also reason that these differences are due to differential Wnt receptor expression on the various cells responding to the signal as well as different signaling proteins that are present in the microenvironment. Coordinated crosstalk of Wnt signaling pathways with other pathways in EC such as Notch/Dll4, VEGF, Ang1/2 and focal adhesion kinase (FAK) [We have laid out evidence indicating that macrophages regulate angiogenesis, in part, through secreting and responding to Wnt signaling glycoproteins. This is true in both developmental and pathological angiogenesis. It is interesting and perhaps not unexpected that in some cases Wnts seem to be pro-angiogenic, as is the case for Wnt5a-induced EC proliferation and migration ,20, and se (FAK)  ultimateBased on the studies that we have presented in this review, we hypothesize that Wnt5a is a crucial mediator of macrophage phenotype. It is known that Wnt5a induces Tie-2 expression in EC  and it wAdditionally, studies of TAMs show that “invasive” TAMs in breast cancer are enriched for Wnt signaling pathway components  and coloThe authors declare no competing interests.ACN and CCWH wrote the paper. Both authors read and approved the final manuscript.


Integrin signaling regulates cell migration and plays a pivotal role in developmental processes and cancer metastasis. Integrin signaling has been studied extensively and much data is available on pathway components and interactions. Yet the data is fragmented and an integrated model is missing. We use a rule-based modeling approach to integrate available data and test biological hypotheses regarding the role of talin, Dok1 and PIPKI in integrin activation. The detailed biochemical characterization of integrin signaling provides us with measured values for most of the kinetics parameters. However, measurements are not fully accurate and the cellular concentrations of signaling proteins are largely unknown and expected to vary substantially across different cellular conditions. By sampling model behaviors over the physiologically realistic parameter range we find that the model exhibits only two different qualitative behaviors and these depend mainly on the relative protein concentrations, which offers a powerful point of control to the cell. Our study highlights the necessity to characterize model behavior not for a single parameter optimum, but to identify parameter sets that characterize different signaling modes. Cell migration is a carefully regulated process that is essential for embryonic development and life Talin binds to the integrin beta-tail and stabilizes the active, open integrin conformation Such questions are difficult to address by verbal reasoning alone. Mathematical modeling can help to integrate available isolated experimental information into a single model and permits the efficient analysis and comparison of model alternatives. Given the many states and complexes that need to be considered the dynamics of integrin activation can be best captured by a rule-based modeling approach Integrin activity is regulated by the interaction with the extra-cellular matrix  and intra-cellular cytoskeletal adaptors . We use a rule-based modeling approach, in order to capture the complexity of integrin signaling. This approach allows us to model integrin signaling compactly by a set of 30 biochemical reactions rules, which are summarized graphically in The basic dynamics of our model are as follows. Binding of ligand and/or talin stabilizes the open/active conformation of integrin . In case of outside-in signaling integrin signaling is initiated by binding of ligand  and internal signals . As discussed above both modes of signaling are observed only with group 1 parameters  and we wWe have developed a rule-based model to explore the roles of talin, PIPKI, and Dok1 in integrin activation and signaling. In spite of much detailed biochemical data a significant level of uncertainty remains because measurements are not fully accurate and the concentrations of signaling proteins are largely unknown and expected to vary substantially across different cellular conditions. It is generally infeasible to sample the entire physiological parameter space. We therefore addressed this challenge in modeling signaling pathways by restricting the sampled parameter space according to the quality of the available measurements. The width of the ranges was based on general rules as to the accuracy of different experimental methods as well as prior knowledge on physiologically reasonable ranges. This restriction enabled us to systematically analyze model dynamics with only Within the wide range of model dynamics, we observed two different qualitative behaviours: one group of parameter sets supported integrin activation both by outside-in or inside-out signaling, and was characterized by high levels of talin-integrin complex formation, a strong dependence of PIPKI recruitment on talin, low levels of integrin phosphorylation and high levels of PIPKI activation. The other group of parameter sets did not support inside-out signaling, and was characterized by high levels of Dok1-integrin complex formation, no dependency of PIPKI recruitment on the presence of talin and higher levels of integrin phosphorylation.Importantly, the most decisive parameters were the relative cellular protein concentrations. Accordingly, the total concentrations of network components can serve as powerful control points to achieve distinct network dynamics. Thus for low talin concentrations we predict impaired inside-out signaling, yet much Dok1-integrin complexes form in response to outside-in signaling which will direct downstream signaling via recruitment of a range of proteins, including Ras-GAP, the adaptor protein Nck, the non-receptor tyrosine kinase Csk, and the phosphatase SHP2 Previous experimental observations led to the suggestion of an integrin phosphorylation switch. Biochemical measurements revealed that phosphorylation of integrins and PIPKI would lower the talin-integrin affinity and enhance PIPKI-talin binding The simulation further revealed that the opening of the integrin conformation not necessarily leads to integrin phosphorylation. Because binding shields the integrin phosphorylation motif, strong recruitment of either Dok1 or talin to integrin tails will counteract integrin phosphorylation. Therefore integrin phosphorylation is indirectly regulated by recruitment of talin and Dok1. We observe that conditions which enable high levels of Dok1 signaling also allow for a sensitive, sustained phosphorylation response while talin-dependent signaling allows only for transient levels of high phosphorylation. Since talin is the more stable signaling platform, its stable interaction with integrin tails does not allow for high levels of integrin phosphorylation but a sustained level of open integrins. Our modeling therefore suggest, that integrin activation and integrin phosphorylation serve as independent nodes in integrin signal propagation. Finally our simulation suggests that outside-in and inside-out signaling differ in the kinetics of the activation process. Thus while outside-in signaling is biphasic with a rapid talin-independent and a slow talin-dependent activation phase, there is only the late talin-dependent activation phase in inside-out signaling.It has long been recognized that model behaviours should be analysed not for a single measured parameter set alone, but over a wider parameter range. Ensemble modeling strategies combined with various clustering algorithms have been used to reveal parameter sets that yield similar qualitative results Overall, our study illustrates how detailed biochemical measurements together with a thorough computational analysis can be used to reveal qualitative behaviors of biological signaling networks. Without biological data the space of possible parameter combinations is too large to be explored. Yet without the computational model it is impossible to integrate biological knowledge to grasp the dynamic range of biological networks and to estimate the possible impact of parameter variations under different cellular conditions.We use a rule-based approach to explore the roles of talin, Dok1, and PIPKI in integrin signaling dynamics We collected parameter values for all biochemical reactions from the literature and parameterized the model according to We use the following eight criteria to characterize model behavior.DOK∶INT formation in response to stimulus:TAL∶INT formation in response to stimulus:PIPKI-dependent TAL recruitment:TAL-dependent PIPKI recruitment:PIPKI phosphorylation in response to stimulus:INT phosphorylation in response to stimulus:Integrin activation by outside-in signaling:Integrin activation by inside-out signaling:Here, Based on the first two criteria, we selected the 2000 parameter sets (2%) which achieved the highest levels of TAL∶INT (group 1) and DOK∶INT (group 2). In order to identify the relevant parameters which characterize both groups, we further compared the distribution of group 1 and group 2 parameters set with their corresponding uniform sampling distributions and among each other. We computed the empirical cumulative distribution function Click here for additional data file.Text S1A computational analysis of the dynamic roles of talin, Dok1, and PIPKI for integrin activation - Supplementary Text.(PDF)Click here for additional data file.