Integrated modeling and experimental approach for determining transcription factor profiles from fluorescent reporter data.

backgroundThe development of quantitative models of signal transduction, as well as parameter estimation to improve existing models, depends on the ability to obtain quantitative information about various proteins that are part of the signaling pathway. However, commonly-used measurement techniques such as Western blots and mobility shift assays provide only qualitative or semi-quantitative data which cannot be used for estimating parameters. Thus there is a clear need for techniques that enable quantitative determination of signal transduction intermediates.

resultsThis paper presents an integrated modeling and experimental approach for quantitatively determining transcription factor profiles from green fluorescent protein (GFP) reporter data. The technique consists of three steps: (1) creating data sets for green fluorescent reporter systems upon stimulation, (2) analyzing the fluorescence images to determine fluorescence intensity profiles using principal component analysis (PCA) and K-means clustering, and (3) computing the transcription factor concentration from the fluorescence intensity profiles by inverting a model describing transcription, translation, and activation of green fluorescent proteins. We have used this technique to quantitatively characterize activation of the transcription factor NF-kappaB by the cytokine TNF-alpha. In addition, we have applied the quantitative NF-kappaB profiles obtained from our technique to develop a model for TNF-alpha signal transduction where the parameters were estimated from the obtained data.

conclusionThe technique presented here for computing transcription factor profiles from fluorescence microscopy images of reporter cells generated quantitative data on the magnitude and dynamics of NF-kappaB activation by TNF-alpha. The obtained results are in good agreement with qualitative descriptions of NF-kappaB activation as well as semi-quantitative experimental data from the literature. The profiles computed from the experimental data have been used to re-estimate parameters for a NF-kappaB model and the results of additional experiments are predicted very well by the model with the new parameter values. While the presented approach has been applied to NF-kappaB and TNF-alpha signaling, it can be used to determine the profile of any transcription factor as long as GFP reporter fluorescent profiles are available.