Homo sapiens
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ABSTRACT:
SUBMITTER: Cell Collective
PROVIDER: 164949 | Cell Collective |
REPOSITORIES: Cell Collective
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Project description:There is a vast amount of molecular information regarding the differentiation of T lymphocytes, in particular regarding in vitro experimental treatments that modify their differentiation process. This publicly available information was used to infer the regulatory network that controls the differentiation of T lymphocytes into CD4+ and CD8+ cells. Hereby we present a network that consists of 50 nodes and 97 regulatory interactions, representing the main signaling circuits established among molecules and molecular complexes regulating the differentiation of T cells. The network was converted into a continuous dynamical system in the form of a set of coupled ordinary differential equations, and its dynamical behavior was studied. With the aid of numerical methods, nine fixed point attractors were found for the dynamical system. These attractors correspond to the activation patterns observed experimentally for the following cell types: CD4?CD8?, CD4+CD8+, CD4+ naive, Th1, Th2, Th17, Treg, CD8+ naive, and CTL. Furthermore, the model is able to describe the differentiation process from the precursor CD4?CD8? to any of the effector types due to a specific series of extracellular signals.
| 2215 | Cell Collective
Project description:The TOL system encoded by plasmid pWW0 of Pseudomonas putida mt-2 is able to sense a large number of both exogenous and endogenous signals as inputs for the genetic and metabolic circuit that determines the biodegradation of m-xylene. However, whether the enormous combinatorial space of inputs is translated into an equally variable response landscape or is processed into very few outcomes remains unclear. To address this question, we set out to define the number of states that can be obtained by a network of a given set of genes under the control of a specified regulatory circuit that is exposed to all possible combinations of inputs. To this end, the TOL network and its regulatory wiring were formalized as a synchronous logic Boolean circuit that had 10 signals (i.e. pathway substrates, temperature, sugars, amino acids, metabolic regimes and global regulators) as possible inputs. The analysis of the attractors of the circuit using a satisfiability (SAT) algorithm revealed that only eight transcriptional states are reached in response to the 1024 possible combinations of stimuli. The experimental validation resulted in a refinement of the model through the addition of a previously unknown interaction that controls the meta catabolic pathway. The full induction of the two xyl operons occurred with only 1.6% of the input combinations, which suggests that the architecture of the network allows the expression of the xyl genes only under a very narrow range of conditions. These data not only explain much of the unusual layout of the TOL circuit but also strengthen the view of the regulatory circuits of environmental bacteria as digital decision-making devices.
| 3491 | Cell Collective
Project description:Co-infections alter the host immune response but how the systemic and local processes at the site of infection interact is still unclear. The majority of studies on co-infections concentrate on one of the infecting species, an immune function or group of cells and often focus on the initial phase of the infection. Here, we used a combination of experiments and mathematical modelling to investigate the network of immune responses against single and co-infections with the respiratory bacterium Bordetella bronchiseptica and the gastrointestinal helminth Trichostrongylus retortaeformis. Our goal was to identify representative mediators and functions that could capture the essence of the host immune response as a whole, and to assess how their relative contribution dynamically changed over time and between single and co-infected individuals. Network-based discrete dynamic models of single infections were built using current knowledge of bacterial and helminth immunology; the two single infection models were combined into a co-infection model that was then verified by our empirical findings. Simulations showed that a T helper cell mediated antibody and neutrophil response led to phagocytosis and clearance of B. bronchiseptica from the lungs. This was consistent in single and co-infection with no significant delay induced by the helminth. In contrast, T. retortaeformis intensity decreased faster when co-infected with the bacterium. Simulations suggested that the robust recruitment of neutrophils in the co-infection, added to the activation of IgG and eosinophil driven reduction of larvae, which also played an important role in single infection, contributed to this fast clearance. Perturbation analysis of the models, through the knockout of individual nodes (immune cells), identified the cells critical to parasite persistence and clearance both in single and co-infections. Our integrated approach captured the within-host immuno-dynamics of bacteria-helminth infection and identified key components that can be crucial for explaining individual variability between single and co-infections in natural populations.
| 3492 | Cell Collective
Project description:Fig 3B from the following paper\r\nLogical modelling of Drosophila signalling pathways. Mbodj A, Junion G, Brun C, Furlong EE, Thieffry D. Mol Biosyst. 2013 Sep;9(9):2248-58. doi:10.1039/c3mb70187e
| 3510 | Cell Collective
Project description:Caveolin-1 (CAV1) is a vital scaffold protein heterogeneously expressed in both healthy and malignant tissue. We focus on the role of CAV1 when overexpressed in T-cell leukemia. Previously, we have shown that CAV1 is involved in cell-to-cell communication, cellular proliferation, and immune synapse formation; however, the molecular mechanisms have not been elucidated. We hypothesize that the role of CAV1 in immune synapse formation contributes to immune regulation during leukemic progression, thereby warranting studies of the role of CAV1 in CD4(+) T-cells in relation to antigen-presenting cells. To address this need, we developed a computational model of a CD4(+) immune effector T-cell to mimic cellular dynamics and molecular signaling under healthy and immunocompromised conditions (i.e., leukemic conditions). Using the Cell Collective computational modeling software, the CD4(+) T-cell model was constructed and simulated under CAV1 (+/+), CAV1 (+/-), and CAV1 (-/-) conditions to produce a hypothetical immune response. This model allowed us to predict and examine the heterogeneous effects and mechanisms of CAV1 in silico. Experimental results indicate a signature of molecules involved in cellular proliferation, cell survival, and cytoskeletal rearrangement that were highly affected by CAV1 knock out. With this comprehensive model of a CD4(+) T-cell, we then validated in vivo protein expression levels. Based on this study, we modeled a CD4(+) T-cell, manipulated gene expression in immunocompromised versus competent settings, validated these manipulations in an in vivo murine model, and corroborated acute T-cell leukemia gene expression profiles in human beings. Moreover, we can model an immunocompetent versus an immunocompromised microenvironment to better understand how signaling is regulated in patients with leukemia.
| 3521 | Cell Collective