The interconnectivity of biological systems, from the scale of interacting molecules up to the chemical communication between organ systems, underlies much of the complexity associated with disease diagnosis and treatment. This complexity is thus driving the need for quantitative experimental and computational approaches that enhance our understanding of system behavior at multiple spatial and temporal scales. In the Department of Pharmacology, we are developing a range of novel approaches for the characterization of these complex systems, as well as their manipulation for the creation of new and/or more effective treatments.
|Systems biology approaches to
decode signaling networks
|Network medicine||Generating kinase activity hypotheses using causal reasoning||Spatio-temporal dynamics
of signaling networks
The cellular protein landscape is dynamically regulated through changes in transcription and by the ubiquitin dependent degradation of specific proteins. In addition to its critical role in regulated protein degradation, the ubiquitin pathway has recently been shown to play a more complex role in regulating signal transduction, through controlling protein interactions and localization. The diversity of ubiquitin signaling outputs, and the perturbation of the ubiquitin proteasome system (UPS) in cancer underscore the importance of understanding key ubiquitin signaling events. However, a key challenge in the ubiquitin field has been to connect UPS enzymes with the substrates that they regulate. Our lab applies emerging genetic and proteomic technologies to systematically explore ubiquitin dependent signal transduction during cell cycle progression and in response to DNA damage. We are implementing and developing technologies that can assess global, proteome wide controlled by ubiquitination. Global Protein Stability Profiling (GPS) is a genetic platform that utilizes fluorescent reporters together with cell sorting to assess changes in protein stability. The GPS system employs a collection of more than 15,000 human open reading frames (ORFs) expressed from a fluorescent reporter construct to simultaneously assess changes in the stability of 15,000 human proteins. As a complement to GPS, we utilize a proteomic approach termed QUAINT (Quantitative Ubiquitylation Interrogation). QUAINT is a mass spectrometry based platform that quantitatively measures changes in protein ubiquitylation for endogenous proteins. Together, these emerging technologies will provide a deep snap shot in the regulated proteome and allow us to better understand global ubiquitin signaling networks regulated during cell growth, in response to stress and in during disease.
As an organizing principle, networks provide a useful representation of biological components and their relationships at multiple scales. In the areas of cancer and infectious disease, our group is actively involved in the development of computational approaches for the creation and analysis of such networks so as to aid directly diagnosis and treatment. For example, with approximately 518 members in humans, protein kinases form the backbone of cellular signaling and play a central role in health and disease. As an integrated network, the kinome is commonly dysregulated in cancer, driving the current interest in the development of kinase inhibitors for use in therapy. Recent work by Gary Johnson’s group has led to the development of Multiplexed Inhibitor Beads coupled with Mass Spectrometry (MIB/MS) that allows one to now assess the activity state of the protein kinome in masse. In collaboration with Gary’s group, we are developing computational approaches to represent and characterize the kinome in breast and other cancers. In addition, we are establishing novel predictive techniques that allow for the prediction of the response of the kinome to treatment with kinase inhibitors. Development of such methods will, for the first time, enable the rational design of combination inhibitor therapies for difficult to treat cancers.
We are applying new methodologies to evaluate kinase adaptations to targeted kinase inhibitors. Previous studies demonstrated that the kinome is highly malleable and remodels quickly to small molecules (1-3). The objectives of the studies in this new NC-TRACs funded pilot grant are two-fold. One is collect kinome data in response to targeted kinase inhibitors such as those targeting MEK or IKK. From the quantitative mass spectrometry data, significant increases or decreases in specific kinases are defined as “state changes”. The second objective is to take this data and apply it to knowledge-based analytical programs to identify unexpected responses or signaling connections. If successful these studies will develop causal reasoning methods to identify novel hypotheses that will be further verified by experimental approaches.
The figure below shows a knowledge-based analysis of a specific MEK inhibitor treatment of triple negative breast cancer (TNBC). Sum 159 cells were treated with 5 uM AZD6244 and the kinome analyzed in Duncan et al. SILAC MS data was used for knowledge-based casual reasoning by Dr. Levy. Shown are predictive kinase increases and decreases from these studies. Yellow=predicted up (none shown); Blue=predicted down; Green=observed up; Red=observed down.
(in collaboration with Dr. Joshua Levy, RTI)
Spatio-temporal dynamics of signaling networks
We are studying the rapid kinetics of GTPase signaling ‘circuits’ and how their transient construction at specific locations controls cell motility. We are focused now on the 'logic' of signaling networks that integrate and relay information from receptors to GTPases, with emphasis on the role of guanine exchange factors. New approaches for network imaging are used to quantify and control specific protein activities, to understand the interactions of adhesion, cytoskeletal and trafficking systems, and to decipher mechanisms of cell polarization, directionality and turning. New microscope techniques are helping us quantify signaling kinetics in individual cells with great accuracy for quantitative modeling and a deeper understanding of network architecture.
In collaboration with John Sondek, Gaudenz Danuser , Keith Burridge and Alan Hall.
(Image: Biosensor fluctuation analysis reveals GEF/GTPase feedback loops. Hunter Elliot, Danuser lab, Harvard)
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Collins KAL, Stuhlmiller TJ, Pham TT, Angus T, Duncan JS, Whittle MC, Graves LM, Johnson GL and Gomez SM. Characterizing the architecture and activation state of the breast cancer kinome. (Submitted)
Duncan JS, Whittle MC, Nkamura K, Abell AN, Midland AA, Zawistowksi JS, Johnson NL, Granger DA, Jordan NV, Darr D, Usary J, Major B, He X, Hoadley K, Sharpless NE, Perou CM, Gomez SM, Jin J, Frye SV, Earp HS, Graves LM and Johnson GL. Dynamic reprogramming of the kinome in response to targeted MEK inhibition in triple negative breast cancer. Cell. 2012 149(2):307-21.
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Midland AA, Whittle MC, Duncan JS, Abell AN, Nakamura K, Zawistowski JS, Carey LA, Earp HS 3rd, Graves LM, Gomez SM and Johnson GL. Defining the expressed breast cancer kinome. Cell Research. 2012 Feb 7. Doi:10.1038/cr.2012.25.
Cooper MJ, Cox NJ, Zimmerman EI, Dewar BJ, Duncan JS, Whittle MC, . . . Graves LM. (2013). Application of multiplexed kinase inhibitor beads to study kinome adaptations in drug-resistant leukemia. PLoS One 8(6):e66755. doi:10.1371/journal.pone.0066755..
Duncan JS, Whittle MC, Nakamura K, Abell AN, Midland AA, Zawistowski JS, . . . Johnson GL. (2012). Dynamic reprogramming of the kinome in response to targeted MEK inhibition in triple-negative breast cancer. Cell 149:307–321. doi:10.1016/j.cell.2012.02.053.
Graves LM, Duncan JS, Whittle MC, and Johnson GL. (2013). The dynamic nature of the kinome. Biochemical Journal 450:1–8. doi:10.1042/BJ20121456.
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