A first truly systems level mechanistic model unravelling the gene regulation of Th2 differentiation [IRF4]

Recent and ongoing revolutions in measurement technologies imply completely new possibilities for genome research: today, time-resolved, quantitative, and systems-level data are available. Nevertheless, without a corresponding revolution in methods for data analysis, these new data tend to drown researchers and doctors, rather than provide clear and useful insights. Such new methods are developed within the field of systems biology. Systems biology has two main approaches: mechanistically detailed and well-determined simulation models for small subsystems, and more approximative statistical models for the entire genome. However, there are few, if any, methods that combine the strengths of these two approaches. Herein, we present LASSIM, a new simulation-based approach, which can be applied to systems of the size of the entire genome. The superior performance of LASSIM is demonstrated in three examples: i) an example with simulated data shows that unlike traditional large-scale methods, LASSIM correctly identifies the true behavior between measured data-points, ii) LASSIM outperforms the winner of a previous DREAM challenge, the most competitive benchmarking approach available, iii) based on new data from TH2 differentiation, LASSIM identifies a first mechanistic model for the entire genome. The key predictions of this model are typically enriched for DNA bindings, which suggests that most predicted interactions are direct. Moreover, in silico knockdowns were experimentally validated. In summary, LASSIM opens the door to a new type of model-based data analysis: to models that combine the strengths of reliable mechanistic models with truly systems-level data. Human naive CD4+ T cells were isolated from fresh buffy coats with Miltenyis Naïve CD4+ T Cell Isolation Kit II according to the manufacturers instructions. 1x106 cells were either transfected in a cuvette with 600nM human on target plus SMART pool against IRF4 (Dharmacon, USA), non-targeting siRNA (Dharmacon) or with transfection buffer using the Amaxa transfection program U-014. Six hours after the nucleofection cells were washed, activated and polarized towards Th2 for 12 hours. The cells were activated with platebound anti-CD3 (500 ng/ml), 500 ng/ml soluble anti-CD28, 5 ug/ml anti-IL-12, 10 ng/ml IL-4 and 17 ng/ml IL-2 (R&D Systems). For microarray experiments the cells were harvested at 12 hours of polarization and lysed in 600 ll Qiazol. For the gene expression microarray analysis 200 ng total RNA was Cy3-labeled using the Agilent Quick Amp Labeling Kit, one color. The labeled cRNA was purified with the RNeasy Mini Kit from Qiagen. After checking the labeling efficiency using the NanoDrop ND-1000 UVVIS Spectrophotometer, 1.65 ug Cy3 labeled RNA from each sample was hybridized to Agilent Sure-Print G3 Human GE 4 x 44 K slides (Agilent Gene Expression Hybridization Kit). The microarray slides were incubated for 17 h at 65 C in a rotating hybridization oven. After washing according to the manufacturers protocol the slides were analyzed using the Agilent Microarray scanner (2505C) with default settings for all parameters. Microarray expression data were obtained by use of Agilent feature extraction software (version 10.7.3.1).