Kristen Naegle


  • PhD, Massachusetts Institute of Technology
  • MS, Massachusetts Institute of Technology
  • MS, University of Washington
  • BS, University of Washington


Research Interest(s)

Regulation and function of tyrosine phosphorylation in complex networks

Research Description

Tyrosine phosphorylation is a protein modification that can occur during or after translation of a protein.The phosphate addition to a tyrosine residue, regulated by tyrosine kinases and phosphatases, can result in changes in protein function, regulation and localization. It is key to important cell signaling processes, which are the processes that convert extracellular cues, like growth factors and insulin, into biochemical networks that result in a change to the cell. Tyrosine phosphorylation is specifically utilized in the early events of receptor tyrosine kinase (RTK) networks, which are fundamental to many processes in the development and homeostasis of complex organisms. Improvements in measurement technologies have enabled the ability to detect and monitor tyrosine phosphorylation and now we know that tyrosine phosphorylation is extensive — occurring on thousands of tyrosines in the human proteome.

Given the sheer size of the challenge, we use both computational and molecular technologies to predict and test the role of tyrosine phosphorylation on proteins and in cellular networks. Although we incorporate new mathematical and computational methods as needed to tackle the fundamental problems of our research, those techniques always have a foundation in statistical robustness. Hypotheses are tested in molecular and cellular systems, closing the loop between computation and experimentation.

The questions that drive us include:

  • How do we increase the capabilities of research to gain new understanding of tyrosine phosphorylation rapidly, i.e. in a high-throughput manner that matches the rate of discovery of these modifications?
  • How do we develop new capabilities to understand how these networks act in specific contexts? Cell context refers to the differences we see between tissue types and the states of the network components that lead to differential responses of tissues to the same cue. As a philosophy, we approach network dysregulation that occurs in disease as an alteration in cell context.

Selected Publications

  • Cho Y, Sloutsky R, Naegle K, Cavalli V. Injury-Induced HDAC5 Nuclear Export Is Essential for Axon Regeneration. Cell. 2017;161(3): 691. PMID: 28917297
  • Mooradian A, Held J, Naegle K. Using ProteomeScout: A Resource of Post-Translational Modifications, Their Experiments, and the Proteins That They Annotate. Current protocols in bioinformatics. 2017;59 13.32.1-13.32.27. PMID: 28902398
  • Schaberg K, Shirure V, Worley E, George S, Naegle K. Ensemble clustering of phosphoproteomic data identifies differences in protein interactions and cell-cell junction integrity of HER2-overexpressing cells. Integrative biology : quantitative biosciences from nano to macro. 2017;9(6): 539-547. PMID: 28492659
  • Sloutsky R, Naegle K. Proteome-Level Analysis Indicates Global Mechanisms for Post-Translational Regulation of RRM Domains. Journal of molecular biology. 2017;430(1): 41-44. PMID: 29146174
  • Ronan T, Macdonald-Obermann J, Huelsmann L, Bessman N, Naegle K, Pike L. Different Epidermal Growth Factor Receptor (EGFR) Agonists Produce Unique Signatures for the Recruitment of Downstream Signaling Proteins. The Journal of biological chemistry. 2016;291(11): 5528-40. PMID: 26786109 | PMCID: PMC4786695
  • Ronan T, Qi Z, Naegle K. Avoiding common pitfalls when clustering biological data. Science signaling. 2016;9(432): re6. PMID: 27303057
  • Sloutsky R, Naegle K. High-Resolution Identification of Specificity Determining Positions in the LacI Protein Family Using Ensembles of Sub-Sampled Alignments. PloS one. 2016;11(9): e0162579. PMID: 27681038 | PMCID: PMC5040260
  • Holehouse A, Naegle K. Reproducible Analysis of Post-Translational Modifications in Proteomes--Application to Human Mutations. PloS one. 2015;10(12): e0144692. PMID: 26659599 | PMCID: PMC4685989
  • Naegle K, Gough N, Yaffe M. Criteria for biological reproducibility: what does "n" mean? Science signaling. 2015;8(371): fs7. PMID: 25852186
  • Matlock M, Holehouse A, Naegle K. ProteomeScout: a repository and analysis resource for post-translational modifications and proteins. Nucleic acids research. 2014;43 D521-30. PMID: 25414335 | PMCID: PMC4383955
  • Cho Y, Sloutsky R, Naegle K, Cavalli V. Injury-induced HDAC5 nuclear export is essential for axon regeneration. Cell. 2013;155(4): 894-908. PMID: 24209626 | PMCID: PMC3987749
  • Iwai L, Payne L, Luczynski M, Chang F, Xu H, Clinton R, Paul A, Esposito E, Gridley S, Leitinger B, Naegle K, Huang P. Phosphoproteomics of collagen receptor networks reveals SHP-2 phosphorylation downstream of wild-type DDR2 and its lung cancer mutants. The Biochemical journal. 2013;454(3): 501-13. PMID: 23822953 | PMCID: PMC3893797
  • Naegle K, White F, Lauffenburger D, Yaffe M. Robust co-regulation of tyrosine phosphorylation sites on proteins reveals novel protein interactions. Molecular bioSystems. 2012;8(10): 2771-82. PMID: 22851037 | PMCID: PMC3501258
  • Sloutsky R, Jimenez N, Swamidass S, Naegle K. Accounting for noise when clustering biological data. Briefings in bioinformatics. 2012;14(4): 423-36. PMID: 23063929
  • Naegle K, Welsch R, Yaffe M, White F, Lauffenburger D. MCAM: multiple clustering analysis methodology for deriving hypotheses and insights from high-throughput proteomic datasets. PLoS computational biology. 2011;7(7): e1002119. PMID: 21799663 | PMCID: PMC3140961
  • Naegle K, Gymrek M, Joughin B, Wagner J, Welsch R, Yaffe M, Lauffenburger D, White F. PTMScout, a Web resource for analysis of high throughput post-translational proteomics studies. Molecular & cellular proteomics : MCP. 2010;9(11): 2558-70. PMID: 20631208 | PMCID: PMC2984232
  • Joughin B, Naegle K, Huang P, Yaffe M, Lauffenburger D, White F. An integrated comparative phosphoproteomic and bioinformatic approach reveals a novel class of MPM-2 motifs upregulated in EGFRvIII-expressing glioblastoma cells. Molecular bioSystems. 2008;5(1): 59-67. PMID: 19081932 | PMCID: PMC2701618