Mathematical modeling and sensitivity analysis of the integrated TNFa-mediated apoptotic pathway for identifying key regulators Geoffrey Koh a , Dong-Yup Lee a,b,n a Bioprocessing Technology Institute, Agency for Science, Technology and Research (A n STAR), 20 Biopolis Way, #06-01, Centros, Singapore 138668, Singapore b Department of Chemical and Biomolecular Engineering, National University of Singapore, 4 Engineering Drive 4, Singapore 117576, Singapore article info Article history: Received 27 March 2010 Accepted 28 April 2011 Keywords: Mathematical modeling Sensitivity analysis TNFa Apoptosis Regulatory mechanisms abstract TNFa-mediated apoptosis is one of the complex and tightly regulated cellular processes as it involves the activation of both pro- and anti-apoptotic signaling pathways. Thus, it is important to elucidate the molecular players of this process and their dynamics in order to gain an in-depth understanding of the mechanisms underlying apoptosis. To this end, we proposed an integrated model of TNFa-mediated apoptosis pathway in Type I cells, formulated based on the principles of mass action kinetics. The model includes major apoptotic modules—the extrinsic and intrinsic pathways, the NFkB survival signaling and various regulatory mechanisms. We performed simulations and sensitivity analyses to study the role of NFkB pathway in regulating apoptosis, and identified IAP as one of the more potent regulators of apoptosis. & 2011 Elsevier Ltd. All rights reserved. 1. Introduction Apoptosis, also known as programmed cell death, is a series of well orchestrated biochemical events that lead to cell death. It is tightly regulated through interactions among several molecule species upon activation by both external and internal stimuli [1]. Apoptosis plays a key role in the development of multi-cellular organisms and maintenance of homeostatic balance. It is also an integral component of the immune system, in which cytotoxic T-cells – a type of white blood cell – eliminate viruses by inducing apoptosis of other virus-infected cells [2,3]. Thus, defects in apoptosis will result in uncontrolled cell growth and proliferation, leading to cancer and other autoimmune diseases [4,5]. From a bioengineering point of view, the ability to intervene the onset of apoptosis will allow prolonged cell viability in bioreactors, enhancing the production of useful molecules such as recombi- nant proteins and monoclonal antibodies [6,7]. Hence, elucidating and understanding the mechanisms of apoptosis and its manip- ulation are essential for both therapeutic and bioengineering applications [8,9]. It is now widely accepted that our understanding of biological processes can be further improved by mathematical modeling and simulation [10–12]. This is pertinent especially for apoptosis as it involves several interconnected pathways, each triggered by various combinations of stimuli. In this regard, the mechanistic behaviors of some of these pathways have been simulated and studied by many researchers. Bentele et al. [13] modeled the receptor-mediated extrinsic pathway in apoptosis. They con- ducted simulation studies on their model to identify threshold mechanisms in apoptosis induced by CD95, a protein receptor that recognizes the death ligand Fas. They also explored the impact of some regulatory molecules on those threshold mechan- isms. Fussenegger et al. [14] constructed a kinetic model which comprises both the extrinsic and intrinsic apoptotic pathways. Using the model, they suggested strategies to block the onset of apoptosis, some of which were verified experimentally. Bagci et al. [15] focused on the role of the Bcl-2 protein family in the mitochondrial apoptotic pathway. Their results indicated that cooperative apoptosome formation is the key mechanism for bistable behavior in certain cell types. From these previous works, it is clear that mathematical modeling has been instrumental in providing novel insights into the regulation of apoptosis. Contents lists available at ScienceDirect journal homepage: www.elsevier.com/locate/cbm Computers in Biology and Medicine 0010-4825/$ - see front matter & 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.compbiomed.2011.04.017 Abbreviations: Apaf-1, apoptotic protease activating factor-1; Bak, Bcl-2 homo- logous antagonist/killer; Bax, Bcl-2 associated X protein; Bcl-2, B-cell lymphoma 2; Bcl-XL, B-cell lymphoma-extra large; Bid, BH3 interacting domain death agonist; BIR, baculovirus IAP repeat; C-FLIP, flice inhibitory protein; Caspase, cysteine-dependent asparte-specific protease; DISC, death inducing signaling complex; FADD, Fas-associated death domain protein; IAP, inhibitor of apoptosis; IkBa, NFkB inhibitor alpha; IKK, IkB kinase; LSA, local sensitivity analysis; MPSA, multi-parametric sensitivity analysis; NFkB, nuclear factor kappa-light-chain- enhancer of activated B cells; RING, really interesting new gene; IP1, receptor interacting protein 1; SMAC, second mitochrondria-derived activator of caspase; TNFa, tumor necrosis factor alpha; TNFR1, tumor necrosis factor receptor 1; TRADD, TNFR-associated death domain protein; TRAF2, TNFR-associated factor 2 n Corresponding author at: Bioprocessing Technology Institute, Agency for Science, Technology and Research (A n STAR), 20 Biopolis Way, #06-01, Centros, Singapore 138668, Singapore. E-mail addresses: geoffrey_koh@bti.a-star.edu.sg (G. Koh), cheld@nus.edu.sg (D.-Y. Lee). Computers in Biology and Medicine 41 (2011) 512–528