Project description:Understanding complicated modularization and crosstalk of intracellular signal transduction pathways holds the key to battle against drug resistance in human cancer research. We propose an integrative approach, namely Inferring Modularization of PAthway CrossTalk (IMPACT), to identify aberrant pathway modules and their between-module crosstalk by exploring pathway landscape that is reconstructed from a sampling strategy. The pathway identification method (i.e., IMPACT) was applied to breast cancer data to uncover aberrant pathway modules, which were further investigated with cell line studies to understand drug resistance in breast cancer. The patient datasets we mentioned are published and are available in the GEO database as GSE6532 and GSE17705. The re-processed GSE6532 and GSE17705 patient datasets are linked below as supplementary files. The GSE6532_matrix.txt and GSE17705_matrix.txt are processed by Affy Gene console with plier as normailization. But importantly, we also used 'Combat' method (http://www.bu.edu/jlab/wp-assets/ComBat/Abstract.html) to remove potential institutional batch effect. Four MCF7 derived cell models were included in the study: MCF7-STR, MCF7RR-STR, LCC1 and LCC2 cell lines. MCF7-STR and MCF7RR-STR were grown in phenol red-free IMEM supplemented with 5% charcoal-stripped calf serum and 1nM estradiol for 72 h prior to RNA extraction. LCC1 and LCC2 cells were grown in phenol red-free IMEM supplemented with 5% charcoal-stripped calf serum. The cell line data were used to validate computational results derived from patient datasets.
Project description:Recent experimental findings suggest the involvement of the 26S proteasome, the main protease active in eukaryotic cells, in the process that leads mammalian sperm to become fully fertile, so-called capacitation. Unfortunately, its role in male gametes signaling is still far from being completely understood. For this reason, here, we realized a computational model, based on network theory, with the aim of rebuilding and exploring its signaling cascade. As a result, we found that the 26S proteasome is part of a signal transduction system that recognizes the bicarbonate ion as an input terminal and two intermediate layers of information processing. The first is under the control of the 26S proteasome and protein kinase A (PKA), which are strongly interconnected, while the latter depends on intracellular calcium concentrations. Both are active in modulating sperm function by influencing the protein phosphorylation pattern and then controlling several key events in sperm capacitation, such as membrane and cytoskeleton remodeling. Then, we found different clusters of molecules possibly involved in this pathway and connecting it to the immune system. In conclusion, this work adds a piece to the puzzle of protease and kinase crosstalk involved in the physiology of sperm cells.
Project description:Axon guidance involves multiple second messenger signal transduction pathways. Although each signal transduction pathway has been characterized, only a few studies have examined crosstalk between these cascades. Here, we applied a simultaneous second messenger imaging method to the growth cone and demonstrated correlations between cAMP, cGMP, and Ca(2+). The levels of cAMP and cGMP in non-stimulated freely extending growth cones showed a negative correlation without delay. Although there was no direct correlation between cAMP and Ca(2+), examination of cross correlations using small time windows showed frequent switching behavior from negative to positive and vice versa. Furthermore, spatially asymmetric cAMP and cGMP signals in freely deviating growth cones were visualized directly. These results indicate that we succeed in relating second messenger crosstalk to growth cone deviation and extension, and also indicate the possibility of predicting axon guidance from this second messenger crosstalk.
Project description:Crosstalk is a major challenge to engineering sophisticated synthetic gene networks. A common approach is to insulate signal-transduction pathways by minimizing molecular-level crosstalk between endogenous and synthetic genetic components, but this strategy can be difficult to apply in the context of complex, natural gene networks and unknown interactions. Here, we show that synthetic gene networks can be engineered to compensate for crosstalk by integrating pathway signals, rather than by pathway insulation. We demonstrate this principle using reactive oxygen species (ROS)-responsive gene circuits in Escherichia coli that exhibit concentration-dependent crosstalk with non-cognate ROS. We quantitatively map the degree of crosstalk and design gene circuits that introduce compensatory crosstalk at the gene network level. The resulting gene network exhibits reduced crosstalk in the sensing of the two different ROS. Our results suggest that simple network motifs that compensate for pathway crosstalk can be used by biological networks to accurately interpret environmental signals.
Project description:Signal transduction pathways control most cellular activities in living cells ranging from regulation of gene expression to fine-tuning enzymatic activity and controlling motile behavior in response to extracellular and intracellular signals. Because of their extreme sequence variability and extensive domain shuffling, signal transduction proteins are difficult to identify, and their current annotation in most leading databases is often incomplete or erroneous. To overcome this problem, we have developed the microbial signal transduction (MiST) database (http://genomics.ornl.gov/mist), a comprehensive library of the signal transduction proteins from completely sequenced bacterial and archaeal genomes. By searching for domain profiles that implicate a particular protein as participating in signal transduction, we have systematically identified 69 270 two- and one-component proteins in 365 bacterial and archaeal genomes. We have designed a user-friendly website to access and browse the predicted signal transduction proteins within various organisms. Further capabilities include gene/protein sequence retrieval, visualized domain architectures, interactive chromosomal views for exploring gene neighborhood, advanced querying options and cross-species comparison. Newly available, complete genomes are loaded into the database each month. MiST is the only comprehensive and up-to-date electronic catalog of the signaling machinery in microbial genomes.
Project description:A drug exerts its effects typically through a signal transduction cascade, which is non-linear and involves intertwined networks of multiple signaling pathways. Construction of such a signaling pathway network (SPNetwork) can enable identification of novel drug targets and deep understanding of drug action. However, it is challenging to synopsize critical components of these interwoven pathways into one network. To tackle this issue, we developed a novel computational framework, the Drug-specific Signaling Pathway Network (DSPathNet). The DSPathNet amalgamates the prior drug knowledge and drug-induced gene expression via random walk algorithms. Using the drug metformin, we illustrated this framework and obtained one metformin-specific SPNetwork containing 477 nodes and 1,366 edges. To evaluate this network, we performed the gene set enrichment analysis using the disease genes of type 2 diabetes (T2D) and cancer, one T2D genome-wide association study (GWAS) dataset, three cancer GWAS datasets, and one GWAS dataset of cancer patients with T2D on metformin. The results showed that the metformin network was significantly enriched with disease genes for both T2D and cancer, and that the network also included genes that may be associated with metformin-associated cancer survival. Furthermore, from the metformin SPNetwork and common genes to T2D and cancer, we generated a subnetwork to highlight the molecule crosstalk between T2D and cancer. The follow-up network analyses and literature mining revealed that seven genes (CDKN1A, ESR1, MAX, MYC, PPARGC1A, SP1, and STK11) and one novel MYC-centered pathway with CDKN1A, SP1, and STK11 might play important roles in metformin's antidiabetic and anticancer effects. Some results are supported by previous studies. In summary, our study 1) develops a novel framework to construct drug-specific signal transduction networks; 2) provides insights into the molecular mode of metformin; 3) serves a model for exploring signaling pathways to facilitate understanding of drug action, disease pathogenesis, and identification of drug targets.
Project description:Depending on the threat to a plant, different pattern recognition receptors, such as receptor-like kinases, identify the stress and trigger action by appropriate defense response development. The plant immunity system primary response to these challenges is rapid accumulation of phytohormones, such as ethylene (ET), salicylic acid (SA), and jasmonic acid (JA) and its derivatives. These phytohormones induce further signal transduction and appropriate defenses against biotic threats. Phytohormones play crucial roles not only in the initiation of diverse downstream signaling events in plant defense but also in the activation of effective defenses through an essential process called signaling pathway crosstalk, a mechanism involved in transduction signals between two or more distinct, "linear signal transduction pathways simultaneously activated in the same cell."
Project description:Leptin is a versatile 16 kDa peptide hormone, with a tertiary structure resembling that of members of the long-chain helical cytokine family. It is mainly produced by adipocytes in proportion to fat size stores, and was originally thought to act only as a satiety factor. However, the ubiquitous distribution of OB-R leptin receptors in almost all tissues underlies the pleiotropism of leptin. OB-Rs belong to the class I cytokine receptor family, which is known to act through JAKs (Janus kinases) and STATs (signal transducers and activators of transcription). The OB-R gene is alternatively spliced to produce at least five isoforms. The full-length isoform, OB-Rb, contains intracellular motifs required for activation of the JAK/STAT signal transduction pathway, and is considered to be the functional receptor. Considerable evidence for systemic effects of leptin on body mass control, reproduction, angiogenesis, immunity, wound healing, bone remodelling and cardiovascular function, as well as on specific metabolic pathways, indicates that leptin operates both directly and indirectly to orchestrate complex pathophysiological processes. Consistent with leptin's pleiotropic role, its participation in and crosstalk with some of the main signalling pathways, including those involving insulin receptor substrates, phosphoinositide 3-kinase, protein kinase B, protein kinase C, extracellular-signal-regulated kinase, mitogen-activated protein kinases, phosphodiesterase, phospholipase C and nitric oxide, has been observed. The impact of leptin on several equally relevant signalling pathways extends also to Rho family GTPases in relation to the actin cytoskeleton, production of reactive oxygen species, stimulation of prostaglandins, binding to diacylglycerol kinase and catecholamine secretion, among others.
Project description:BACKGROUND:T-cell mediated immunotherapy brought clinical success for many cancer patients. Nonetheless, downregulation of MHC class I antigen presentation, frequently occurring in solid cancers, limits the efficacy of these therapies. Unraveling the mechanisms underlying this type of immune escape is therefore of great importance. We here investigated the immunological effects of metabolic stress in cancer cells as a result of nutrient deprivation. METHODS:TC1 and B16F10 tumor cell lines were cultured under oxygen- and glucose-deprivation conditions that mimicked the tumor microenvironment of solid tumors. Presentation of peptide antigens by MHC class I molecules was measured by flow cytometry and via activation of tumor-specific CD8 T cell clones. The proficiency of the IFNy-STAT1 pathway was investigated by Western blots on phosphorylated proteins, transfection of constitutive active STAT1 constructs and qPCR of downstream targets. Kinase inhibitors for PI3K were used to examine its role in IFNy receptor signal transduction. RESULTS:Combination of oxygen- and glucose-deprivation resulted in decreased presentation of MHC class I antigens on cancer cells, even in the presence of the stimulatory cytokine IFNy. This unresponsiveness to IFNy was the result of failure to phosphorylate the signal transducer STAT1. Forced expression of constitutive active STAT1 fully rescued the MHC class I presentation. Furthermore, oxygen- and glucose-deprivation increased PI3K activity in tumor cells. Pharmacological inhibition of this pathway not only restored signal transduction through IFNy-STAT1 but also improved MHC class I presentation. Importantly, PI3K inhibitors also rendered tumor cells sensitive for recognition by CD8 T cells in culture conditions of metabolic stress. CONCLUSIONS:These data revealed a strong impact of metabolic stress on the presentation of tumor antigens by MHC class I and suggest that this type of tumor escape takes place at hypoxic areas even during times of active T cell immunity and IFNy release.
Project description:BACKGROUND:Pathway analysis is widely applied in transcriptome analysis. Given certain transcriptomic changes, current pathway analysis tools tend to search for the most impacted pathways, which provides insight into underlying biological mechanisms. Further refining of the enriched pathways and extracting functional modules by "crosstalk" analysis have been proposed. However, the upstream/downstream relationships between the modules, which may provide extra biological insights such as the coordination of different functional modules and the signal transduction flow have been ignored. RESULTS:To quantitatively analyse the upstream/downstream relationships between functional modules, we developed a novel GEne Set Topological Impact Analysis (GESTIA), which could be used to assemble the enriched pathways and functional modules into a super-module with a topological structure. We showed the advantages of this analysis in the exploration of extra biological insight in addition to the individual enriched pathways and functional modules. CONCLUSIONS:GESTIA can be applied to a broad range of pathway/module analysis result. We hope that GESTIA may help researchers to get one additional step closer to understanding the molecular mechanism from the pathway/module analysis results.