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Pairwise agonist scanning predicts cellular signaling responses to combinatorial stimuli

Nature Biotechnology volume 28, pages 727–732 (2010)Cite this article

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Abstract

Prediction of cellular response to multiple stimuli is central to evaluating patient-specific clinical status and to basic understanding of cell biology. Cross-talk between signaling pathways cannot be predicted by studying them in isolation and the combinatorial complexity of multiple agonists acting together prohibits an exhaustive exploration of the complete experimental space. Here we describe pairwise agonist scanning (PAS), a strategy that trains a neural network model based on measurements of cellular responses to individual and all pairwise combinations of input signals. We apply PAS to predict calcium signaling responses of human platelets in EDTA-treated plasma to six different agonists (ADP, convulxin, U46619, SFLLRN, AYPGKF and PGE2) at three concentrations (0.1, 1 and 10 × EC50). The model predicted responses to sequentially added agonists, to ternary combinations of agonists and to 45 different combinations of four to six agonists (R = 0.88). Furthermore, we use PAS to distinguish between the phenotypic responses of platelets from ten donors. Training neural networks with pairs of stimuli across the dose-response regime represents an efficient approach for predicting complex signal integration in a patient-specific disease milieu.

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Figure 1: Experimental and computational methods to study platelet signaling.
Figure 2: PAS.
Figure 3: Neural network model reveals the global platelet response to all agonist combinations.
Figure 4: Donor-specific synergy maps.

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Acknowledgements

The authors thank H. Li for suggesting the permutation test to evaluate the significance of donor clustering. This work was supported by the US National Institutes of Health R01-HL-56621 (S.L.D.), R33-HL-87317 (S.L.D. and L.F.B.) and T32-HG000046 (J.E.P.).

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Authors and Affiliations

  1. Department of Chemical and Biomolecular Engineering, Institute for Medicine and Engineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA

    Manash S Chatterjee & Scott L Diamond

  2. Institute for Medicine and Engineering, Genomics and Computational Biology, University of Pennsylvania, Philadelphia, Pennsylvania, USA

    Jeremy E Purvis & Scott L Diamond

  3. Department of Medicine, Institute for Medicine and Engineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA

    Lawrence F Brass

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  1. Manash S Chatterjee
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  2. Jeremy E Purvis
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  4. Scott L Diamond
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Contributions

M.S.C. designed and performed all experiments. J.E.P. constructed neural network models of platelet activation. M.S.C. wrote the paper with contributions from all authors. L.F.B. advised on experimental conditions, and S.L.D. conceived the study.

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Correspondence to Scott L Diamond.

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The authors declare no competing financial interests.

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Supplementary Tables 1–3, Supplementary Figs. 1–15 and Supplementary Discussion (PDF 3839 kb)

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Chatterjee, M., Purvis, J., Brass, L. et al. Pairwise agonist scanning predicts cellular signaling responses to combinatorial stimuli. Nat Biotechnol 28, 727–732 (2010). https://doi.org/10.1038/nbt.1642

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