Measurement

Measurement and the study of cell decision processes

Michael B. Yaffe

New experimental approaches combined with fresh thinking are redefining how measurements of complex biological systems can add to scientific knowledge and impact human health. Quality measurements are the starting point for a signaling-network model, the core of any systems biology project, and the end goal for a new biological sensor. Molecular and cellular measurements thus pervade the Cell Decision Processes (CDP) Center, starting from the initial methods-development phase and progressing through real biological applications. The CDP Center distinguishes itself by equally valuing the contributions of new measurement technologies, well-established biological techniques, and proof-of-principle devices.

Measurement approaches in the Center can be broken down into two interrelated goals: quantitation and discovery. The challenge of quantitation lies mostly in modifying and validating existing techniques so that the resulting measurements faithfully reflect the biological sample. One clear example of the interplay among quantitative measurements developed within the Center is the stress and checkpoint kinase, mitogen-activated protein kinase-activated protein kinase 2 (MK2). Recently, we made important modifications to an oriented peptide library approach (1) that enabled us to define an optimal peptide substrate for MK2 (2). Using this substrate motif, we correctly identified new oxidase- and cell cycle-related MK2 substrates. In addition, however, the optimal MK2tide peptide served as a critical reagent for the development of a high-throughput MK2 kinase activity assay (3) that could accurately quantify MK2 signaling in cell lysates. The MK2tide sequence also provided the peptide-sensing motif for a new MK2-S1 peptide, which can be used in a fluorescence-based kinase assay to detect MK2 signaling in real time (4).

Modifications and extensions of other biochemical techniques (5) were occurring in parallel with the MK2 kinase assay development at MIT. These methods recently combined to capture 10,000 signaling and apoptotic-response measurements of the intracellular network activated by TNF, EGF, and insulin (6). Subsequent experiments and analysis of the dataset revealed that late MK2 signaling was a critical prosurvival signal for TNF-induced apoptosis (7). Thus, by designing the MK2tide peptide, applying this reagent to assay development, and fusing these assays with other biochemical techniques, we were able to develop a hypothesis linking MK2 to cell-fate control.

The molecular mechanism for the MK2-apoptosis link has not been determined. To develop this hypothesis further, our measurements must now shift toward a discovery focus. In the CDP Center, discovery-based measurements rely more on the development of new reagents or assay platforms to identify novel genes, substrates, and therapeutic targets. How might MK2 kinase activity provide a prosurvival signal to TNF-treated cells? One reasonable explanation is that MK2 phosphorylates a pro- or antiapoptotic protein that has not yet been recognized as an MK2 substrate. To explore this possibility, we could again take advantage of the optimal MK2 substrate sequence. New MK2 substrates could be suggested by inputting the MK2 selectivity matrix into Scansite (8) and searching for high-scoring potential substrates. To constrain the search, it would be valuable to know coassociated proteins that are expressed at the late time points when MK2 is prosurvival. This could be revealed by 2-D electrophoresis of MK2 immunoprecipitates (see (9) for details). Likewise, to explore the possibility that a new MK2 substrate might be upregulated just in time (10) for late MK2 phosphorylation, we have validated dual-fluorescence labeling techniques that could distinguish early-vs.-late changes in protein levels. Finally, in collaboration with the White lab, we are pursuing phosphoproteomic (11) measurement strategies to survey cruder cellular mixtures by using mass spectrometry.

Where does the late MK2 signal come from? To screen for upstream MK2 regulators, it would be possible to knockdown genes within the kinome as part of a collaboration with the RNAi consortium (TRC) and the Sabatini lab. However, to address this exhaustively would require a simple but effective readout of MK2 activation in cells. One useful reagent for this purpose would be an anti-phospho-MK2tide antibody, like those that are commercially available (http://www.cellsignal.com) for other kinase motifs. MK2 activation could then be analyzed in single cells by microscopy or flow cytometry (see (12) for examples of enzyme-activity reporters used in the Center). The production of anti-phospho-MK2tide would also make possible the development of other cell-based assays, such as in-cell Westerns. Using the Li-Cor infrared imaging system, we are actively developing quantitative in-cell Westerns for ErbB signaling pathways. Taken together, this illustrates how a combination of discovery-based assays can be used to reveal molecular mechanisms controlling cell decisions.

As with any multi-investigator project, a major consideration for heterogeneous measurements is the subsequent data-fusion phase. Large-scale signaling experiments at the Center have been intentionally designed to tackle the difficult challenge of combining measurements from different assay platforms (13). We expect that these challenges will only increase as more measurements move from the proof-of-principle stage toward real biological questions, so data fusion will remain an important area of focus in the future. On the bioinformatics side, our current datasets (6) are still manageable with spreadsheets and simple file formats. However, related projects are pursuing more sophisticated approaches for handling the unstructured nature of biological data (14). The transition from experimental measurements to databases is greatly facilitated by the mix of biologists, engineers, and informaticians joined within the Center

Cell decisions are mediated by complex combinations of signals that cannot possibly be measured by a single experimental method. Rather than chase new technologies exclusively, we argue that much can be achieved by applying older methods with a mindset toward quantitation and throughput. For this reason, we use scaled-up versions of classic techniques, like Western blotting (6), in the same breath that we pursue advances in mass spectrometry or label-free detection. Our multifaceted approach for characterizing intracellular networks promises to capture the richness of signaling, which should ultimately aid computational modeling efforts and lead to new biological discoveries.

References

  1. Songyang, Z., Carraway, K. L., 3rd, Eck, M. J., Harrison, S. C., Feldman, R. A., Mohammadi, M., Schlessinger, J., Hubbard, S. R., Smith, D. P., Eng, C., and et al. (1995) Catalytic specificity of protein-tyrosine kinases is critical for selective signalling. Nature 373, 536-539
  2. Manke, I. A., Nguyen, A., Lim, D., Stewart, M. Q., Elia, A. E., and Yaffe, M. B. (2005) MAPKAP kinase-2 is a cell cycle checkpoint kinase that regulates the G2/M transition and S phase progression in response to UV irradiation. Mol Cell 17, 37-48
  3. Janes, K. A., Albeck, J. G., Peng, L. X., Sorger, P. K., Lauffenburger, D. A., and Yaffe, M. B. (2003) A high-throughput quantitative multiplex kinase assay for monitoring information flow in signaling networks: application to sepsis-apoptosis. Mol Cell Proteomics 2, 463-473
  4. Shults, M. D., Janes, K. A., Lauffenburger, D. A., and Imperiali, B. (2005) A multiplexed homogeneous fluorescence-based assay for protein kinase activity in cell lysates. Nat Methods 2, 277-284
  5. Nielsen, U. B., Cardone, M. H., Sinskey, A. J., MacBeath, G., and Sorger, P. K. (2003) Profiling receptor tyrosine kinase activation by using Ab microarrays. Proc Natl Acad Sci U S A 100, 9330-9335
  6. Janes, K. A., Gaudet, S., Albeck, J. G., Nielsen, U. B., Lauffenburger, D. A., and Sorger, P. K. (2005) Autocrine crosstalk in the response of human cells to apoptotic and mitogenic stimuli. In preparation
  7. Janes, K. A., Albeck, J. G., Gaudet, S., Sorger, P. K., Lauffenburger, D. A., and Yaffe, M. B. (2005) A predictive systems model of signaling identifies a molecular basis set for cytokine-induced apoptosis. In preparation
  8. Obenauer, J. C., Cantley, L. C., and Yaffe, M. B. (2003) Scansite 2.0: Proteome-wide prediction of cell signaling interactions using short sequence motifs. Nucleic Acids Res 31, 3635-3641
  9. Brown, G. E., Stewart, M. Q., Bissonnette, S. A., Elia, A. E., Wilker, E., and Yaffe, M. B. (2004) Distinct ligand-dependent roles for p38 MAPK in priming and activation of the neutrophil NADPH oxidase. J Biol Chem 279, 27059-27068
  10. Zaslaver, A., Mayo, A. E., Rosenberg, R., Bashkin, P., Sberro, H., Tsalyuk, M., Surette, M. G., and Alon, U. (2004) Just-in-time transcription program in metabolic pathways. Nat Genet 36, 486-491
  11. Zhang, Y., Wolf-Yadlin, A., Papin, D., Rush, J., Lauffenburger, D. A., and White, F. M. (2005) Time-resolved mass spectrometry of tyrosine phosphorylation sites in the EGF receptor signaling network reveals dynamic modules. Mol Cell Proteomics, in revision
  12. Albeck, J. G., Burke, J. M., Lauffenburger, D. A., and Sorger, P. K. (2005), in preparation
  13. Gaudet, S., Janes, K. A., Albeck, J. G., Pace, E. A., Lauffenburger, D. A., and Sorger, P. K. (2005) A compendium of signals and responses triggered by prodeath and prosurvival cytokines. in preparation
  14. Swedlow, J. R., Goldberg, I., Brauner, E., and Sorger, P. K. (2003) Informatics and quantitative analysis in biological imaging. Science 300, 100-102

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This page last modified on June 10th, 2009