cocktail of antibodies including polyclonal sheep anti-human type I IFNa neutralizing antibodies (PBL Biomedical Laboratories) (4000 U/mL), polyclonal sheep anti-human type I IFNb neutral- izing antibodies (PBL Biomedical Laboratories) (4000 U/ml) and monoclonal mouse anti-human type 1 IFN-a/b receptor chain 2 neutralizing antibodies (Antigenix) (10 mg/ml). Sorting of single MDDCs Single MDDCs were directly sorted into 384-well PCR plates as previously described [14]. Briefly, MDDCs were screened and sorted by visual light scatter or labeled fluorescence (MoFlo high speed cell sorter) directly into 384-well bar-coded PCR plates (Roche LC480), which contained 5 mL cell lysis buffer [4 mM magnesium acetate (Sigma), 0.05% NP40 (Sigma), 0.8 U/mL Protector RNAse Inhibitor (Roche Applied Sciences)] in each well. Sorted MDDCs were immediately placed on dry ice and stored at –70uC to prevent RNA degradation. Real time RT-PCR of total RNAs Cultured human MDDCs (16106cells) were divided into two samples (56105cells each). Cells in one sample were infected by NDV at an MOI of 0.5 and cells in another sample were uninfected and used as an experimental control. Total RNAs were isolated from both samples using an RNeasy mini kit (Qiagen) after 10-hour infection. 100 ng of RNA sample was used as template for real time RT-PCR to determine the expression levels of IFNB1 and DDX58. The details of the PCR reactions are presented in Supplementary Text S1 (Detailed PCR Protocols). The data were normalized to the housekeeping gene ACTB. Single cell hemi-nested PCR Single MDDCs were sorted directly into 384-well bar-coded PCR plates as previous described [14]. Specifically, a 5 mL aliquot of a 2x AccuRT master mix solution prepared as described above was added to each well. In control wells with no cells, 1 mL of genomic DNA of varying dilutions (103–40 copies/mL) was added along with the 5 mL aliquot of 2x master mix. Hemi-nested PCR was performed as described in Supplementary Text S1 (Detailed PCR Protocols) for the multiplex hemi-nested PCR of IFNB1 and DDX58. PCR results were analyzed with the Roche Lightcycler 480 where the PCR cross point (Cp) value for each amplification curve was determined by a secondary derivative calculation. Cp values were converted to copy numbers using the absolute quantification method based on Cp values for the genomic DNA standards. An illustration of the experimental procedure is shown in Supplementary Figure S4 with validation data in Supplemen- tary Figures S5,S6. A few PCR dropouts (for both IFNB1 and DDX58) were observed and excluded from analysis. Agent based model of RIG-I mediated DC response to viral infection Single-cell stochastic behavior is important in many biological processes, leading to phenotypic variability among genetically identical organisms and determining cellular fate following viral infection in bacteria and eukaryotic cells [21,22,23,24,25,26, 27,28,29]. In order to test the hypothesis of early responder cells we developed an agent based model (ABM) that simulates the IFNB1-DDX58 positive feedback loop. The simulation emulates a portion of a medium containing both infected and uninfected MDDCs. The inter-cellular model we use is two dimensional (2d), and the medium is represented by a square lattice, where each lattice square has the size of a single cell (Supplementary Figure S7). Each cell is simulated as an independent agent, where the IFNB1-DDX58 Feedback Loop Cell-to-Cell Variability agents interface through the extracellular medium. The graphical display engine generates an animation by depicting the state of the simulated area at each simulation step. Where possible, parameters used in the simulation were based on experimental results. The experimental basis for parameter values related to extracellular signaling was summarized previously [30]. We assume that these same values are applicable to our 2d lattice model. The measured diffusion rate is of the order of D~3:10{11 m2 , and the diameter of a cell is 30 mm. The diffusion sec coefficient and the lattice unit size determine the time step in the simulation, leading to a time step of 9 seconds (as explained below). We chose the total lattice size according to the diffusion distance after 11 hours, which is the latest measurement time. Since the average displacement of a molecule performing a random walk or diffusing increases like the square root of time this leads to a lattice size of 40 by 40 units. According to [30], 6.5% of the medium’s volume is occupied by the cells, which translates to an average distance between neighboring cells of about 2.5 times their diameter. We used this average distance between nearest neighbors in the 2d simulation, which leads to a population of a little over 200 cells in the whole lattice, distributed randomly. Intra-cellular simulation In order to reflect the variations in response that result from a small number of reactants within individual cells, the dynamics of each cell was simulated using a stochastic simulation based on Gillespie’s algorithm. The simulation follows the number of transcripts of IFNB1 and of DDX58, the number of RIG-I proteins, and the number of bound receptors on every cell. The initial RIG- I level in each cell was chosen from a log-normal distribution so that a small number of cells had a large amount of RIG-I, while the majority had a small amount [31]. The parameters for IFNB1 induction were chosen so that only cells with sufficient RIG-I could be induced. RIG-I concentration in infected cells determines IFNB1 induction in a Michaelis-Menten like form. Bound cell surface receptors activate DDX58 transcription according to a Michaelis-Menten like function. Stochastic Processes, Rates, and Rate Constants The modified Gillespie algorithm to stochastically simulate each cell follows the time dependence of IFNB1 transcripts, DDX58 transcripts, and RIG-I proteins. These molecular species are denoted as IFN, DDX, and RIG, respectively. The simulation follows six reactions, as summarized in Figure 8: DDX58 message transcription, IFNB1 message transcription, RIG-I translation, DDX58 message degradation, IFNB1 message degradation, and RIG-I degradation. The rate constants for IFN and DDX transcription are denoted by KIFN and KDDX , respectively. The translation rate constant for RIG is given by KRIG. The degradation rate constants for IFN, DDX, and RIG are given by dIFN ,dDDX , and dRIG, respectively. The transcription rate DDX58 depends on the number of bound interferon receptors, denoted by B, in a Michaelis-Menten form using a Hill coefficient of HDDX ~1:5 and a half-induction level given by 1=b (meaning that when B~b, DDX58 reaches half it maximal induction). According to experiments, DDX58 is constitutively expressed in the cells. The ratio between the maximal induction of DDX58 and the constitutive induction is given by C~1=50. IFNB1 induction depends on Rig-I concen- tration in a Michaelis-Menten form with a Hill coefficient HIFN ~3, and a half-induction concentration give by 1=c. All the degradation processes follow an exponential decay. The processes and the rates at which they occur are summarized PLoS ONE | www.plosone.org 9 February 2011 | Volume 6 | Issue 2 | e16614