Note to users. If you're seeing this message, it means that your browser cannot find this page's style/presentation instructions -- or possibly that you are using a browser that does not support current Web standards. Find out more about why this message is appearing, and what you can do to make your experience of our site the best it can be.

Science 22 April 2005:
Vol. 308. no. 5721, pp. 523 - 529
DOI: 10.1126/science.1105809
Prev | Table of Contents | Next

Research Articles

Causal Protein-Signaling Networks Derived from Multiparameter Single-Cell Data

Karen Sachs,1* Omar Perez,2* Dana Pe'er,3* Douglas A. Lauffenburger,1{dagger} Garry P. Nolan2{dagger}

Machine learning was applied for the automated derivation of causal influences in cellular signaling networks. This derivation relied on the simultaneous measurement of multiple phosphorylated protein and phospholipid components in thousands of individual primary human immune system cells. Perturbing these cells with molecular interventions drove the ordering of connections between pathway components, wherein Bayesian network computational methods automatically elucidated most of the traditionally reported signaling relationships and predicted novel interpathway network causalities, which we verified experimentally. Reconstruction of network models from physiologically relevant primary single cells might be applied to understanding native-state tissue signaling biology, complex drug actions, and dysfunctional signaling in diseased cells.

1 Biological Engineering Division, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA.
2 Stanford University School of Medicine, The Baxter Laboratory of Genetic Pharmacology, Department of Microbiology and Immunology, Stanford, CA 94305, USA.
3 Harvard Medical School, Department of Genetics, Boston, MA 02115, USA.

* These authors contributed equally to this work.

{dagger} To whom correspondence should be addressed. E-mail: lauffen{at}mit.edu (D.A.L.); gnolan{at}stanford.edu (G.P.N.)

Read the Full Text


THIS ARTICLE HAS BEEN CITED BY OTHER ARTICLES:
A boosting approach to structure learning of graphs with and without prior knowledge.
S. Anjum, A. Doucet, and C. C. Holmes (2009)
Bioinformatics 25, 2929-2936
   Abstract »    Full Text »    PDF »
The impact of incomplete knowledge on evaluation: an experimental benchmark for protein function prediction.
C. Huttenhower, M. A. Hibbs, C. L. Myers, A. A. Caudy, D. C. Hess, and O. G. Troyanskaya (2009)
Bioinformatics 25, 2404-2410
   Abstract »    Full Text »    PDF »
Transcriptional Regulatory Circuits: Predicting Numbers from Alphabets.
H. D. Kim, T. Shay, E. K. O'Shea, and A. Regev (2009)
Science 325, 429-432
   Abstract »    Full Text »    PDF »
Using a Microfluidic Device for High-Content Analysis of Cell Signaling.
R. Cheong, C. J. Wang, and A. Levchenko (2009)
Science Signaling 2, pl2
   Abstract »    Full Text »    PDF »
Exploring the human genome with functional maps.
C. Huttenhower, E. M. Haley, M. A. Hibbs, V. Dumeaux, D. R. Barrett, H. A. Coller, and O. G. Troyanskaya (2009)
Genome Res. 19, 1093-1106
   Abstract »    Full Text »    PDF »
Special Feature: Complex Systems: From Chemistry to Systems Biology Special Feature: Modeling the temporal interplay of molecular signaling and gene expression by using dynamic nested effects models.
B. Anchang, M. J. Sadeh, J. Jacob, A. Tresch, M. O. Vlad, P. J. Oefner, and R. Spang (2009)
PNAS 106, 6447-6452
   Abstract »    Full Text »    PDF »
Gene network reconstruction from transcriptional dynamics under kinetic model uncertainty: a case for the second derivative.
D. R. Bickel, Z. Montazeri, P.-C. Hsieh, M. Beatty, S. J. Lawit, and N. J. Bate (2009)
Bioinformatics 25, 772-779
   Abstract »    Full Text »    PDF »
High Content Cell Screening in a Microfluidic Device.
R. Cheong, C. J. Wang, and A. Levchenko (2009)
Mol. Cell. Proteomics 8, 433-442
   Abstract »    Full Text »    PDF »
Insights into the Organization of Biochemical Regulatory Networks Using Graph Theory Analyses.
A. Ma'ayan (2009)
J. Biol. Chem. 284, 5451-5455
   Abstract »    Full Text »    PDF »
STAT-3 and ERK 1/2 phosphorylation are critical for T-cell alloactivation and graft-versus-host disease.
S. X. Lu, O. Alpdogan, J. Lin, R. Balderas, R. Campos-Gonzalez, X. Wang, G.-J. Gao, D. Suh, C. King, M. Chow, et al. (2008)
Blood 112, 5254-5258
   Abstract »    Full Text »    PDF »
Characterizing heterogeneous cellular responses to perturbations.
M. D. Slack, E. D. Martinez, L. F. Wu, and S. J. Altschuler (2008)
PNAS 105, 19306-19311
   Abstract »    Full Text »    PDF »
A molecular signaling model of platelet phosphoinositide and calcium regulation during homeostasis and P2Y1 activation.
J. E. Purvis, M. S. Chatterjee, L. F. Brass, and S. L. Diamond (2008)
Blood 112, 4069-4079
   Abstract »    Full Text »    PDF »
Signatures of combinatorial regulation in intrinsic biological noise.
A. Warmflash and A. R. Dinner (2008)
PNAS 105, 17262-17267
   Abstract »    Full Text »    PDF »
Illuminating signaling network functional biology through quantitative phosphoproteomic mass spectrometry.
N. C. Tedford, F. M. White, and J. A. Radding (2008)
Brief Funct Genomic Proteomic
   Abstract »    Full Text »    PDF »
Network inference using informative priors.
S. Mukherjee and T. P. Speed (2008)
PNAS 105, 14313-14318
   Abstract »    Full Text »    PDF »
Modelling non-stationary gene regulatory processes with a non-homogeneous Bayesian network and the allocation sampler.
M. Grzegorczyk, D. Husmeier, K. D. Edwards, P. Ghazal, and A. J. Millar (2008)
Bioinformatics 24, 2071-2078
   Abstract »    Full Text »    PDF »
Bioengineering and Imaging Research Opportunities Workshop V: Summary of Findings on Imaging and Characterizing Structure and Function in Native and Engineered Tissues.
W. R. Hendee, K. Cleary, R. L. Ehman, G. D. Fullerton, W. S. Grundfest, J. Haller, C. A. Kelley, A. E. Meyer, R. F. Murphy, W. Phillips, et al. (2008)
Radiology 248, 342-347
   Full Text »    PDF »
Systematic Comparison of Gene Expression between Murine Memory and Naive B Cells Demonstrates That Memory B Cells Have Unique Signaling Capabilities.
M. M. Tomayko, S. M. Anderson, C. E. Brayton, S. Sadanand, N. C. Steinel, T. W. Behrens, and M. J. Shlomchik (2008)
J. Immunol. 181, 27-38
   Abstract »    Full Text »    PDF »
Regulating the Regulators: The Future Prospects for Transcription-Factor-Based Agricultural Biotechnology Products.
K. Century, T. L. Reuber, and O. J. Ratcliffe (2008)
Plant Physiology 147, 20-29
   Full Text »    PDF »
Targeting Ras in Myeloid Leukemias.
B. S. Braun and K. Shannon (2008)
Clin. Cancer Res. 14, 2249-2252
   Abstract »    Full Text »    PDF »
Systems biotechnology of mammalian cell factories.
P. M. O'Callaghan and D. C. James (2008)
Brief Funct Genomic Proteomic
   Abstract »    Full Text »    PDF »
Differential impact of mammalian target of rapamycin inhibition on CD4+CD25+Foxp3+ regulatory T cells compared with conventional CD4+ T cells.
R. Zeiser, D. B. Leveson-Gower, E. A. Zambricki, N. Kambham, A. Beilhack, J. Loh, J.-Z. Hou, and R. S. Negrin (2008)
Blood 111, 453-462
   Abstract »    Full Text »    PDF »
Preemptive HMG-CoA reductase inhibition provides graft-versus-host disease protection by Th-2 polarization while sparing graft-versus-leukemia activity.
R. Zeiser, S. Youssef, J. Baker, N. Kambham, L. Steinman, and R. S. Negrin (2007)
Blood 110, 4588-4598
   Abstract »    Full Text »    PDF »
Coevolutionary networks of splicing cis-regulatory elements.
X. Xiao, Z. Wang, M. Jang, and C. B. Burge (2007)
PNAS 104, 18583-18588
   Abstract »    Full Text »    PDF »
A Biochemical Signature for Rapid Recall of Memory CD4 T Cells.
M. R. Chandok, F. I. Okoye, M. P. Ndejembi, and D. L. Farber (2007)
J. Immunol. 179, 3689-3698
   Abstract »    Full Text »    PDF »
Current progress in network research: toward reference networks for key model organisms.
B. S. Srinivasan, N. H. Shah, J. A. Flannick, E. Abeliuk, A. F. Novak, and S. Batzoglou (2007)
Brief Bioinform 8, 318-332
   Abstract »    Full Text »    PDF »
Diagnostic Pathology and Laboratory Medicine in the Age of "Omics": A Paper from the 2006 William Beaumont Hospital Symposium on Molecular Pathology.
W. G. Finn (2007)
J. Mol. Diagn. 9, 431-436
   Abstract »    Full Text »    PDF »
Neurotrophic factors switch between two signaling pathways that trigger axonal growth.
M. Paveliev, M. Lume, A. Velthut, M. Phillips, U. Arumae, and M. Saarma (2007)
J. Cell Sci. 120, 2507-2516
   Abstract »    Full Text »    PDF »
The flow of cytometry into systems biology.
J. P. Nolan and L. Yang (2007)
Brief Funct Genomic Proteomic
   Abstract »    Full Text »    PDF »
Nested effects models for high-dimensional phenotyping screens.
F. Markowetz, D. Kostka, O. G. Troyanskaya, and R. Spang (2007)
Bioinformatics 23, i305-i312
   Abstract »    Full Text »    PDF »
Connecting quantitative regulatory-network models to the genome.
Y. Pan, T. Durfee, J. Bockhorst, and M. Craven (2007)
Bioinformatics 23, i367-i376
   Abstract »    Full Text »    PDF »
Computational modeling of Caenorhabditis elegans vulval induction.
X. Sun and P. Hong (2007)
Bioinformatics 23, i499-i507
   Abstract »    Full Text »    PDF »
K-RasG12D expression induces hyperproliferation and aberrant signaling in primary hematopoietic stem/progenitor cells.
M. E. M. Van Meter, E. Diaz-Flores, J. A. Archard, E. Passegue, J. M. Irish, N. Kotecha, G. P. Nolan, K. Shannon, and B. S. Braun (2007)
Blood 109, 3945-3952
   Abstract »    Full Text »    PDF »
Bayesian methods in bioinformatics and computational systems biology.
D. J. Wilkinson (2007)
Brief Bioinform
   Abstract »    Full Text »    PDF »
Phosphoprotein Pathway Mapping: Akt/Mammalian Target of Rapamycin Activation Is Negatively Associated with Childhood Rhabdomyosarcoma Survival.
E. F. Petricoin III, V. Espina, R. P. Araujo, B. Midura, C. Yeung, X. Wan, G. S. Eichler, D. J. Johann Jr., S. Qualman, M. Tsokos, et al. (2007)
Cancer Res. 67, 3431-3440
   Abstract »    Full Text »    PDF »
Predicting protein-protein interactions based only on sequences information.
J. Shen, J. Zhang, X. Luo, W. Zhu, K. Yu, K. Chen, Y. Li, and H. Jiang (2007)
PNAS 104, 4337-4341
   Abstract »    Full Text »    PDF »
Altered activation of AKT is required for the suppressive function of human CD4+CD25+ T regulatory cells.
N. K. Crellin, R. V. Garcia, and M. K. Levings (2007)
Blood 109, 2014-2022
   Abstract »    Full Text »    PDF »
Thematic review series: Systems Biology Approaches to Metabolic and Cardiovascular Disorders. Multi-organ whole-genome measurements and reverse engineering to uncover gene networks underlying complex traits.
J. Tegner, J. Skogsberg, and J. Bjorkegren (2007)
J. Lipid Res. 48, 267-277
   Abstract »    Full Text »    PDF »
Dynamic modelling and analysis of biochemical networks: mechanism-based models and model-based experiments.
N. A.W. van Riel (2006)
Brief Bioinform 7, 364-374
   Abstract »    Full Text »    PDF »
SEBINI: Software Environment for BIological Network Inference.
R. C. Taylor, A. Shah, C. Treatman, and M. Blevins (2006)
Bioinformatics 22, 2706-2708
   Abstract »    Full Text »    PDF »
Isoelectric focusing technology quantifies protein signaling in 25 cells.
R. A. O'Neill, A. Bhamidipati, X. Bi, D. Deb-Basu, L. Cahill, J. Ferrante, E. Gentalen, M. Glazer, J. Gossett, K. Hacker, et al. (2006)
PNAS 103, 16153-16158
   Abstract »    Full Text »    PDF »
Delayed development and lifespan extension as features of metabolic lifestyle alteration in C. elegans under dietary restriction.
N. J. Szewczyk, I. A. Udranszky, E. Kozak, J. Sunga, S. K. Kim, L. A. Jacobson, and C. A. Conley (2006)
J. Exp. Biol. 209, 4129-4139
   Abstract »    Full Text »    PDF »
Comparative evaluation of reverse engineering gene regulatory networks with relevance networks, graphical gaussian models and bayesian networks.
A. V. Werhli, M. Grzegorczyk, and D. Husmeier (2006)
Bioinformatics 22, 2523-2531
   Abstract »    Full Text »    PDF »
Electrophysiological and gene expression profiling of neuronal cell types in mammalian neocortex.
K. Yano, T. Subkhankulova, F. J. Livesey, and H. P. C. Robinson (2006)
J. Physiol. 575, 361-365
   Abstract »    Full Text »    PDF »
The fluorescent toolbox for assessing protein location and function..
B. N. G. Giepmans, S. R. Adams, M. H. Ellisman, and R. Y. Tsien (2006)
Science 312, 217-224
   Abstract »    Full Text »    PDF »
Gene network inference from incomplete expression data: transcriptional control of hematopoietic commitment.
K. Missal, M. A. Cross, and D. Drasdo (2006)
Bioinformatics 22, 731-738
   Abstract »    Full Text »    PDF »
From components to regulatory motifs in signalling networks.
A. Ma'ayan and R. Iyengar (2006)
Brief Funct Genomic Proteomic 5, 57-61
2005: Signaling Breakthroughs of the Year.
E. M. Adler, N. R. Gough, and L. B. Ray (2006)
Sci. STKE 2006, eg1
   Abstract »    Full Text »    PDF »
Drosophila Genome-wide RNAi Screens: Are They Delivering the Promise?.
B. MATHEY-PREVOT and N. PERRIMON (2006)
Cold Spring Harb Symp Quant Biol 71, 141-148
   Abstract »    PDF »
Deeper Insights into Hematological Oncology Disorders via Single-Cell Phospho-Signaling Analysis.
G. P. Nolan (2006)
Hematology 2006, 123-127
   Abstract »    Full Text »    PDF »
Computational modeling of physiological systems.
D. A. Beard, J. B. Bassingthwaighte, and A. S. Greene (2005)
Physiol Genomics 23, 1-3
   Full Text »    PDF »
Make your own network.
W. A. Wells (2005)
J. Cell Biol. 169, 550
   Full Text »    PDF »
Bayesian Network Analysis of Signaling Networks: A Primer.
D. Pe'er (2005)
Sci. STKE 2005, pl4
   Abstract »    Full Text »    PDF »


To Advertise     Find Products

Science. ISSN 0036-8075 (print), 1095-9203 (online)