Immune signal transduction in leishmaniasis from natural to artificial systems: role of feedback loop insertion

Abstract

Background: Modulated immune signal (CD14-TLR and TNF) in leishmaniasis can be linked to EGFR pathway involved in wound healing, through crosstalk points. This signaling network can be further linked to a synthetic gene circuit acting as a positive feedback loop to elicit a synchronized intercellular communication among the immune cells which may contribute to a better understanding of signaling dynamics in leishmaniasis.

Methods: Network reconstruction with positive feedback loop, simulation (ODE 15s solver) and sensitivity analysis of CD14-TLR, TNF and EGFR was done in SimBiology (MATLAB 7.11.1). Cytoscape and adjacency matrix were used to calculate network topology. PCA was extracted by using sensitivity coefficient in MATLAB. Model reduction was done using time, flux and sensitivity score.

Results: Network has five crosstalk points: NIK, IκB-NFκB and MKK (4/7, 3/6, 1/2) which show high flux and sensitivity. PI3K in EGFR pathway shows high flux and sensitivity. PCA score was high for cytoplasmic ERK1/2, PI3K, Atk, STAT1/3 and nuclear JNK. Of the 125 parameters, 20% are crucial as deduced by model reduction.

Conclusions: EGFR can be linked to CD14-TLR and TNF through the MAPK crosstalk points. These pathways may be controlled through Ras and Raf that lie upstream of signaling components ERK ½ (c) and JNK (n) that have a high PCA score via a synthetic gene circuit for activating cell-cell communication to elicit an inflammatory response. Also a disease resolving effect may be achieved through PI3K in the EGFR pathway.

General significance: The reconstructed signaling network can be linked to a gene circuit with a positive feedback loop, for cell-cell communication resulting in synchronized response in the immune cell population, for disease resolving effect in leishmaniasis.

Keywords: AMPs; APCs; Atk; CD 14; Cross-talk; DAG; EGFR; ERK; FBA; IFN; IL; IL1 receptor associated kinases; INOH; IRAK; Integrating Network Objects with Hierarchies; JNK; Jun NH2-terminal kinase; KEGG; Kyoto Encyclopedia of Genes and Genomes; LCF; LPG; Leishmania; MAPK; MKK; Mathematical modeling; NFκB; NFκB-inducing kinase; NIK; NO; ODE; PCA; PI3K; PKC; PMN; PP2A; PSA; ROS; Ras; SBML; SOCS; STAT; Signaling; Systems Biology Markup Language; Systems biology; T helper cells 1/2; TAB; TAK; TAK1 binding protein; TGFβ activated kinase; TLR; TNF; TNF receptor associated factor; TRAF; Th1/2; agammaglobulinemia tyrosine kinase; antigen presenting cells; antimicrobial (poly) peptides; cluster determinant 14; directed acyclic graph; epidermal growth factor receptor; extracellular regulated MAP kinase; flux balance analysis; interferon; interleukins; leucocyte chemotactic factor; lipo phosphoglycan; mitogen activated protein kinases; mitogen kinase kinases; nitric oxide; nuclear factor kappa B; ordinary differential equation; parasite surface antigen; phosphatidylinositol 4-phosphate 3-kinase; poly morphonuclear neutrophil; principal component analysis; protein kinase C; protein phosphatase 2A; rat sarcoma; reactive oxygen species; signal transducer and activator of transcription; suppressor of cytokine synthesis; toll like receptor; tumor necrotic factor.