Systems and Synthetic Biology

, Volume 7, Issue 4, pp 185–195

Signaling networks in Leishmania macrophages deciphered through integrated systems biology: a mathematical modeling approach

Research Article

Abstract

Network of signaling proteins and functional interaction between the infected cell and the leishmanial parasite, though are not well understood, may be deciphered computationally by reconstructing the immune signaling network. As we all know signaling pathways are well-known abstractions that explain the mechanisms whereby cells respond to signals, collections of pathways form networks, and interactions between pathways in a network, known as cross-talk, enables further complex signaling behaviours. In silico perturbations can help identify sensitive crosstalk points in the network which can be pharmacologically tested. In this study, we have developed a model for immune signaling cascade in leishmaniasis and based upon the interaction analysis obtained through simulation, we have developed a model network, between four signaling pathways i.e., CD14, epidermal growth factor (EGF), tumor necrotic factor (TNF) and PI3 K mediated signaling. Principal component analysis of the signaling network showed that EGF and TNF pathways can be potent pharmacological targets to curb leishmaniasis. The approach is illustrated with a proposed workable model of epidermal growth factor receptor (EGFR) that modulates the immune response. EGFR signaling represents a critical junction between inflammation related signal and potent cell regulation machinery that modulates the expression of cytokines.

Keywords

Leishmania Mathematical modeling Principal component analysis Systems biology Signaling dynamics 

Abbreviations

AP-1

Activator protein 1

cAMP

Cyclic adenosine monophosphate

CD

Cluster determinant

COPASI

Complex pathway simulator

DC

Dendritic cell

EGF

Epidermal growth factor

EGFR

Epidermal growth factor receptor

Erk1/2

Extracellular signal-regulated kinases

GAP

GTPase-activating protein

GTP

Guanosine triphosphate

IFNγ

Interferon

IKK

IkB kinase

IL

Interleukin

INOH

Integrating network objects hierarchies

IRAK1/4

IL1 receptor associated kinase

JAK2

Janus kinase

KEGG

Kyoto encyclopedia of genes and genomes

KTIM

Kinase tyrosyl-based inhibitory motif

LMR

Leishmania major response

LPG

Lipophosphoglycan

LPS

Lipopolysaccharide

MAPK

Mitogen-activated protein kinase

MyD88

Myeloid differentiating factor

NF-κB

Nuclear factor κB

NK

Natural killer cells

NO

Nitric oxide

ODE

Ordinary differential equation

PAK

P21-activated kinase

PCA

Principal component analysis

PfEMP1

Erythrocyte membrane protein 1

PI3 K

Phosphatidylinositol 3-kinase

PKA/C

Protein kinase A/C

PRRs

Pattern-recognition receptors

SBML

System biology markup language

SHP1

Protein-tyrosine phosphatase

STAT-1

Signal transducer and activator of transcription

TAB 1/2

TAK1 activating binding protein

TAK 1

TGF-β activated kinase 1

TLR

Toll-like receptors

TNFα

Tumor necrotic factor alpha

TRAF

Tumor necrotic factor (TNF) receptor activating factor

Supplementary material

11693_2013_9111_MOESM1_ESM.pptx (8.5 mb)
Supplementary material 1 (PPTX 8739 kb)
11693_2013_9111_MOESM2_ESM.docx (34 kb)
Supplementary material 2 (DOCX 34 kb)

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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.National Centre for Cell SciencePuneIndia

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