Will Old

William Old

Research Assistant Professor

Office: JSCBB C1B90A
Office Phone: 303 735 4019
Lab: JSCBB C1B90
Lab Phone: 303 492 5519
Group Website: Coming Soon
Email: This email address is being protected from spambots. You need JavaScript enabled to view it.


Ph.D.: University of Colorado, Boulder 2000

Postdoc: University of Colorado Health Sciences Center


Our research is focused on development and application of analytical methods and computational approaches for comprehensive profiling of the proteome, defined as the complete set of proteins expressed in cells. In contrast to the relatively static human genome, with an estimated 20,000 genes, the proteome is dynamic and exponentially more complex due to alternative splicing and post-translational modifications. Furthermore, the dynamic range in protein abundance within human cells spans at least six orders of magnitude; in plasma, this range is even larger at 1011. This poses a significant challenge for technologies aimed at systematically detecting proteins in complex biological samples. A major goal of our research is to create efficient strategies to identify and quantify the proteome and associated post-translational modifications in complex human samples, on a time-scale amenable to biological experimentation.

 Mass spectrometry (MS)-based proteomics has emerged as a key technology for basic research and clinical biomarker identification. High-resolution instruments enable the identification of thousands of proteins in a single sample using “bottom up” proteomics, where protein mixtures are proteolyzed into constituent peptides and dissociated in the gas phase using tandem mass spectrometry (MS/MS). MS/MS spectra are then matched to peptide sequences, which report proteins present in the sample. In spite of many recent advances, proteomics shows important limitations in sensitivity and throughput, where only a fraction of the proteome can be identified from complex samples, and proteins of very low abundance are not observed.

 To address these challenges, we are actively developing mass spectrometry based methods, sample fractionation strategies, and ultra-sensitive quantitative assays for targeted analysis of low abundance proteins. A large component of our research program is also focused on computational problems, where we have developed a sophisticated spectral matching algorithm, Spec2spec, which incorporates gas-phase peptide fragmentation models to improve our ability to identify peptides from the millions of MS/MS spectra typically generated in large-scale proteomics experiments.


Reversible protein phosphorylation is essential to virtually all cellular processes, being a central mechanism by which cells communicate, transmit information from membrane receptors to the nucleus, and respond to environmental cues. In many cancers, key signaling pathways become dysregulated, frequently by mutations in protein kinases, resulting in phosphorylation of downstream substrates, constitutive pathway activation and unregulated growth. By measuring the phosphorylation state of many proteins simultaneously, we can detect the activation status of these signaling pathways responsible for initiating cancerous growth. However, current approaches for large-scale analysis of protein phosphorylation provide only a limited snapshot of the true complexity of the “phosphoproteome”. We are developing highly sensitive mass spectrometry based methods and fractionation strategies for comprehensive profiling of phosphorylation sites in complex mixtures, allowing us to quantify these events on many thousands of proteins in a single biological sample. In collaboration with researchers here at CU Boulder, we are applying these methods to uncovering the molecular drivers of human cancers.


1.         Yen, C.Y., Houel, S., Ahn, N.G., and Old, W.M. (2011) Spectrum-to-spectrum searching using a proteome-wide spectral library. Mol Cell Proteomics 10, M111 007666.

2.         Meyer-Arendt, K., Old, W.M., Houel, S., Renganathan, K., Eichelberger, B., Resing, K.A., and Ahn, N.G. (2011) IsoformResolver: A Peptide-Centric Algorithm for Protein Inference. J Proteome Res 10, 3060-3075.

4.         Houel, S., Abernathy, R., Renganathan, K., Meyer-Arendt, K., Ahn, N.G., and Old, W.M. (2010) Quantifying the impact of chimera MS/MS spectra on peptide identification in large-scale proteomics studies. J Proteome Res 9, 4152-4160.

5. Old, W.M., Shabb, J.B., Houel, S., Wang, H., Couts, K.L., Yen, C.-y., Litman, E.S., Croy, C.H., Meyer-Arendt, K., Miranda, J.G., Brown, R.A., Witze, E.S., Schweppe, R.E., Resing, K.A., and Ahn, N.G. (2009) Functional Proteomics Identifies Targets of Phosphorylation by B-Raf Signaling in Melanoma. Molecular Cell 34, 115-131.

6.         Yen, C.Y., Meyer-Arendt, K., Eichelberger, B., Sun, S., Houel, S., Old, W.M., Knight, R., Ahn, N.G., Hunter, L.E., and Resing, K.A. (2009) A simulated MS/MS library for spectrum-to-spectrum searching in large-scale identification of proteins. Mol Cell Proteomics 8, 857-869.

7.         Xu, Q., Zhu, S., Wang, W., Zhang, X., Old, W., Ahn, N., and Liu, X. (2009) Regulation of Kinetochore Recruitment of Two Essential Mitotic Spindle Checkpoint Proteins by Mps1 Phosphorylation. Mol. Biol. Cell 20, 10-20.

8.         Wang, W., Yang, Y., Gao, Y., Xu, Q., Wang, F., Zhu, S., Old, W., Resing, K., Ahn, N., Lei, M., and Liu, X. (2009) Structural and mechanistic insights into Mps1 kinase activation. J Cell Mol Med 13, 1679-1694.

9.         Holinger, E.P., Old, W.M., Giddings, T.H., Jr., Wong, C., Yates, J.R., 3rd, and Winey, M. (2009) Budding yeast centrosome duplication requires stabilization of Spc29 via Mps1-mediated phosphorylation. J Biol Chem 284, 12949-12955.

10.       Xu, Q., Zhu, S., Wang, W., Zhang, X., Old, W., Ahn, N., and Liu, X. (2008) Regulation of Kinetochore Recruitment of Two Essential Mitotic Spindle Checkpoint Proteins by Mps1 Phosphorylation. Mol. Biol. Cell, E08-03-0324.

11.       Witze, E.S., Old, W.M., Resing, K.A., and Ahn, N.G. (2007) Mapping protein post-translational modifications with mass spectrometry. Nat Methods 4, 798-806.

12.       Sun, S., Meyer-Arendt, K., Eichelberger, B., Brown, R., Yen, C.Y., Old, W.M., Pierce, K., Cios, K.J., Ahn, N.G., and Resing, K.A.(2007) Improved validation of peptide MS/MS assignments using spectral intensity prediction. Mol Cell Proteomics 6, 1-17.

13.       Mattison, C. P., Old, W.M., Steiner, E., Huneycutt, B. J., Resing, K. A., Ahn, N. G., and Winey, M. (2007) Mps1 activation loop autophosphorylation enhances kinase activity. J Biol Chem 282, 30553-30561.

14.       Ahn, N.G., Shabb, J.B., Old, W.M., and Resing, K.A. (2007) Achieving in-depth proteomics profiling by mass spectrometry. ACS Chem Biol 2, 39-52.

15.       Ruth, M.C., Old, W.M., Emrick, M.A., Meyer-Arendt, K., Aveline-Wolf, L.D., Pierce, K.G., Mendoza, A.M., Sevinsky, J.R., Hamady, M., Knight, R.D., Resing, K.A., and Ahn, N.G. (2006) Analysis of membrane proteins from human chronic myelogenous leukemia cells: comparison of extraction methods for multidimensional LC-MS/MS. J Proteome Res 5, 709-719.

16.       Old, W.M., Meyer-Arendt, K., Aveline-Wolf, L., Pierce, K.G., Mendoza, A., Sevinsky, J. R., Resing, K.A., and Ahn, N.G. (2005) Comparison of Label-free Methods for Quantifying Human Proteins by Shotgun Proteomics. Mol Cell Proteomics 4, 1487-1502.

17.       Russell, S.A., Old, W., Resing, K.A., and Hunter, L. (2004) Proteomic informatics. Int Rev Neurobiol 61, 127-157.

18.       Resing, K.A., Meyer-Arendt, K., Mendoza, A.M., Aveline-Wolf, L.D., Jonscher, K.R., Pierce, K.G., Old, W.M., Cheung, H.T., Russell, S., Wattawa, J.L., Goehle, G.R., Knight, R.D., and Ahn, N.G. (2004) Improving reproducibility and sensitivity in identifying human proteins by shotgun proteomics. Analytical Chemistry 76, 3556-3568.