News 11th International Conference on Artificial Immune Systems (ICARIS 2012) in Taormina!

Toll-like Receptor & BlenX

In collaboration with:
Department of Mathematics and Computer Science, University of Catania, Catania, CT, 95125, Italy.
The Microsoft Research, Centre for Computational and Systems Biology, Trento, TN, 38123, Italy.

Aims of this research are: (i) use the CoSBi-Lab software to study a region of the Oda & Kitano map for the TLR; (ii) exploit spatial structures embedding BlenX boxes in them; and (iii) correlate different topologies with different immuno-responses. Recognition of pathogen-associated molecular signatures is critically important in proper activation of the immune system. The toll-like receptor (TLR) signaling network is responsible for innate immune response. In mammalians, there are 11 TLRs that recognize a variety of ligands from pathogens to trigger immunological responses. In this paper, we present a comprehensive map of TLRs and interleukin 1 receptor signaling networks based on papers published so far. The map illustrates the possible existence of a main network subsystem that has a bow-tie structure in which myeloid differentiation primary response gene 88 (MyD88) is a nonredundant core element, two collateral subsystems with small GTPase and phosphatidylinositol signaling, and MyD88-independent pathway. There is extensive crosstalk between the main bow-tie network and subsystems, as well as feedback and feedforward controls. One obvious feature of this network is the fragility against removal of the nonredundant core element, which is MyD88, and involvement of collateral subsystems for generating different reactions and gene expressions for different stimuli.

Papers:

This work is in-progress and there is a non-disclosure agreements signed among Microsoft and I.

Part of my previous work on such topic is published in the following Cellular Automata for the Immune System modeling:

1. [2011, inproceedings]
   G. Stracquadanio, R. Umeton, J. Costanza, V. Annibali, R. Mechelli, M. Pavone, L. Zammataro, and G. Nicosia, "Large Scale Agent-Based Modeling of the Humoral and Cellular Immune Response," in Proceedings of the 10th International Conference on Artificial Immune Systems, Cambridge, United Kingdom, July 18-21, 2011, pp. 15-29.
   @INPROCEEDINGS{ umeton2011icaris, title = {Large Scale {Agent-Based} Modeling of the Humoral and Cellular Immune Response},
  volume = {6825},
  isbn = {978-3-642-22370-9},
  url = {http://www.springerlink.com/content/4u442m1g41610474/},
  booktitle = {Proceedings of the 10th International Conference on Artificial Immune Systems, Cambridge, United Kingdom, July 18-21},
  publisher = {Springer Berlin Heidelberg},
  AUTHOR = {Stracquadanio, Giovanni and Umeton, Renato and Costanza, Jole and Annibali, Viviana and Mechelli, Rosella and Pavone, Mario and Zammataro, Luca and Nicosia, Giuseppe},
  editor = {Li\`o, Pietro and Nicosia, Giuseppe and Stibor, Thomas},
  year = {2011},
  pages = {15--29},
  abstract = {The Immune System is, together with Central Nervous System, one of the most important and complex unit of our organism. Despite great advances in recent years that shed light on its understanding and in the unraveling of key mechanisms behind its functions, there are still many areas of the Immune System that remain object of active research. The development of in-silico models, bridged with proper biological considerations, have recently improved the understanding of important complex systems [1,2]. In this paper, after introducing major role players and principal functions of the mammalian Immune System, we present two computational approaches to its modeling; i.e., two in-silico Immune Systems. (i) A large-scale model, with a complexity of representation of 106 − 108 cells (e.g., APC, T, B and Plasma cells) and molecules (e.g., immunocomplexes), is here presented, and its evolution in time is shown to be mimicking an important region of a real immune response. (ii) Additionally, a viral infection model, stochastic and light-weight, is here presented as well: its seamless design from biological considerations, its modularity and its fast simulation times are strength points when compared to (i). Finally we report, with the intent of moving towards the virtual lymph note, a cost-benefits comparison among Immune System models presented in this paper. }
}

Source-code:

Proprietary, no-redistribution. Compiled prototypes of the BlenX system are available here.