Robert Moritz, PhD


Robert Moritz

Dr. Robert Moritz, a native of Australia, joined the ISB faculty in mid 2008 as Associate Professor and Director of Proteomics. Dr. Moritz began his work in 1983 in the Joint Protein Structure laboratory of Prof. Richard J. Simpson (JPSL-Ludwig Institute for Cancer Research, and The Walter and Eliza Hall Institute of Medical Research, Melbourne, Australia). During his 25 years at JPSL, Dr. Moritz designed and implemented a number of technologies currently used in many proteomics laboratories across the globe. Examples include technologies such as the development of micro-chromatography for proteomics from the late 1980’s to its current day implementation, a micro-fractionation technique widely used by many laboratories worldwide. His collaborative research into cytokine biochemistry, protein-receptor chemistry and cellular biochemistry culminated in the novel identification of a number of proteins (e.g., IL-6, IL-9 A33 ligand, DIABLO, as well as several others), their interacting partners, and 3-dimensional structures of their cell surface receptors important in human health concerns such as cancer and inflammation. During his time at JPSL, Dr. Moritz progressed through the ranks whilst obtaining his Bachelor’s degree in Biochemistry with first-class Honors, and his Ph.D., from the University of Melbourne.

Dr. Moritz has brought wide-ranging skills and expertise to ISB, much of it drawn from his Australian experience. There, in 2005, he conceptualized a shared proteomics high-performance computing system, organized a consortia of proteomic scientists from all states in Australia, and proposed a computational system specifically for proteomics data analysis for all Australian researchers to access. For this work, in 2006, he was awarded an enabling grant from the Australian National Health and Medical Research Council worth AUS$2M. With that award, he established a bioinformatics center in Australia that enabled proteomic researchers anywhere in the country to analyze mass spectrometry data. It was the first effort on a national scale to bring proteomic data analysis and algorithms to any researcher in the whole country without the need for them to build their own bioinformatics group. In late 2006, the Australian Proteomics Computational Facility (APCF, was inaugurated, and Dr. Moritz remains as Director of the APCF. The dedicated proteomics data analysis facility is equipped with a 1000 CPU high-performance computing cluster, and full-time software engineers for the continued development of proteomics algorithms and data validation. This facility serves all researchers in Australia and others regardless of their global geographical location. He is continuing that work at ISB by expanding the ISB proteomics centre into a national facility with online tools for data analysis.

PhD, University of Melbourne, Australia

Proteomics, protein chemistry, technology development

Omenn, G. S., D. J. States, M. Adamski, T. W. Blackwell, R. Menon, H. Hermjakob, R. Apweiler, et al. 2005. “Overview of the HUPO Plasma Proteome Project: Results from the Pilot Phase with 35 Collaborating Laboratories and Multiple Analytical Groups, Generating a Core Dataset of 3020 Proteins and a Publicly-Available Database.” Proteomics 5 (13): 3226–45. Cite
Mathivanan, S., M. Ahmed, N. G. Ahn, H. Alexandre, R. Amanchy, P. C. Andrews, J. S. Bader, et al. 2008. “Human Proteinpedia Enables Sharing of Human Protein Data.” Nat Biotechnol 26 (2): 164–67. Cite
Saleem, R. A., R. S. Rogers, A. V. Ratushny, D. J. Dilworth, P. Shannon, D. Shteynberg, Y. Wan, et al. 2010. “Integrated Phosphoproteomics Analysis of a Signaling Network Governing Nutrient Response and Peroxisome Induction.” Mol Cell Proteomics 9 (9): 2076–88. Cite
Chung, T. W., C. L. Moss, M. Zimnicka, R. S. Johnson, R. L. Moritz, and F. Turecek. 2011. “Electron-Capture and -Transfer Dissociation of Peptides Tagged with Tunable Fixed-Charge Groups: Structures and Dissociation Energetics.” J Am Soc Mass Spectrom 22 (1): 13–30. Cite
Ramos, H., P. Shannon, M. Y. Brusniak, U. Kusebauch, R. L. Moritz, and R. Aebersold. 2011. “The Protein Information and Property Explorer 2: Gaggle-like Exploration of Biological Proteomic Data within One Webpage.” Proteomics 11 (1): 154–58. Cite
Brusniak, M. Y., S. T. Kwok, M. Christiansen, D. Campbell, L. Reiter, P. Picotti, U. Kusebauch, et al. 2011. “ATAQS: A Computational Software Tool for High Throughput Transition Optimization and Validation for Selected Reaction Monitoring Mass Spectrometry.” BMC Bioinformatics 12 (1): 78. Cite
Friedman, D. B., T. M. Andacht, M. K. Bunger, A. S. Chien, D. H. Hawke, J. Krijgsveld, W. S. Lane, et al. 2011. “The ABRF Proteomics Research Group Studies: Educational Exercises for Qualitative and Quantitative Proteomic Analyses.” Proteomics 11 (8): 1371–81. Cite
Mathias, R. A., Y. S. Chen, R. J. Goode, E. A. Kapp, S. Mathivanan, R. L. Moritz, H. J. Zhu, and R. J. Simpson. 2011. “Tandem Application of Cationic Colloidal Silica and Triton X-114 for Plasma Membrane Protein Isolation and Purification: Towards Developing an MDCK Protein Database.” Proteomics 11 (7): 1238–53. Cite
Farrah, T., E. W. Deutsch, G. S. Omenn, D. S. Campbell, Z. Sun, J. A. Bletz, P. Mallick, et al. 2011. “A High-Confidence Human Plasma Proteome Reference Set with Estimated Concentrations in PeptideAtlas.” Molecular & Cellular Proteomics : MCP, June. Cite
Shteynberg, D., E. W. Deutsch, H. Lam, J. K. Eng, Z. Sun, N. Tasman, L. Mendoza, R. L. Moritz, R. Aebersold, and A. I. Nesvizhskii. 2011. “IProphet: Multi-Level Integrative Analysis of Shotgun Proteomic Data Improves Peptide and Protein Identification Rates and Error Estimates.” Molecular & Cellular Proteomics : MCP, August. Cite
Helsens, K., M. Y. Brusniak, E. Deutsch, R. L. Moritz, and L. Martens. 2011. “JTraML: An Open Source Java API for TraML, the PSI Standard for Sharing SRM Transitions.” Journal of Proteome Research, October. Cite
Yoon, S. H., D. J. Reiss, J. C. Bare, D. Tenenbaum, M. Pan, J. Slagel, R. L. Moritz, et al. 2011. “Parallel Evolution of Transcriptome Architecture during Genome Reorganization.” Genome Research 21 (11): 1892–1904. Cite
Swearingen, K. E., M. R. Hoopmann, R. S. Johnson, R. A. Saleem, J. D. Aitchison, and R. L. Moritz. 2011. “Nanospray FAIMS Fractionation Provides Significant Increases in Proteome Coverage of Unfractionated Complex Protein Digests.” Molecular & Cellular Proteomics : MCP, December. Cite
Kinsinger, C. R., J. Apffel, M. Baker, X. Bian, C. H. Borchers, R. Bradshaw, M. Y. Brusniak, et al. 2012. “Recommendations for Mass Spectrometry Data Quality Metrics for Open Access Data (Corollary to the Amsterdam Principles).” Journal of Proteome Research 11 (2): 1412–19. Cite
Farrah, T., E. W. Deutsch, R. Kreisberg, Z. Sun, D. S. Campbell, L. Mendoza, U. Kusebauch, et al. 2012. “PASSEL: The PeptideAtlas SRM Experiment Library.” Proteomics, February. Cite
Hoopmann, M. R., M. J. MacCoss, and R. L. Moritz. 2012. “Identification of Peptide Features in Precursor Spectra Using Hardklor and Kronik.” In Current Protocols in Bioinformatics / Editoral Board, Andreas D. Baxevanis ... [et Al.], 2012/03/06 ed., Chapter 13:Unit13 18. Cite
Bislev, S. L., U. Kusebauch, M. C. Codrea, R. J. Beynon, V. M. Harman, C. M. Rontved, R. Aebersold, R. L. Moritz, and E. Bendixen. 2012. “Quantotypic Properties of QconCAT Peptides Targeting Bovine Host Response to Streptococcus Uberis.” Journal of Proteome Research 11 (3): 1832–43. Cite
Deutsch, E. W., M. Chambers, S. Neumann, F. Levander, P. A. Binz, J. Shofstahl, D. S. Campbell, et al. 2012. “TraML–A Standard Format for Exchange of Selected Reaction Monitoring Transition Lists.” Molecular & Cellular Proteomics : MCP 11 (4): R111 015040. Cite
Brusniak, M. Y., C. S. Chu, U. Kusebauch, M. J. Sartain, J. D. Watts, and R. L. Moritz. 2012. “An Assessment of Current Bioinformatic Solutions for Analyzing LC-MS Data Acquired by Selected Reaction Monitoring Technology.” Proteomics 12 (8): 1176–84. Cite
Qin, S., Y. Zhou, A. S. Lok, A. Tsodikov, X. Yan, L. Gray, M. Yuan, et al. 2012. “SRM Targeted Proteomics in Search for Biomarkers of HCV-Induced Progression of Fibrosis to Cirrhosis in HALT-C Patients.” Proteomics 12 (8): 1244–52. Cite
Gold, E. S., S. A. Ramsey, M. J. Sartain, J. Selinummi, I. Podolsky, D. J. Rodriguez, R. L. Moritz, and A. Aderem. 2012. “ATF3 Protects against Atherosclerosis by Suppressing 25-Hydroxycholesterol-Induced Lipid Body Formation.” The Journal of Experimental Medicine 209 (4): 807–17. Cite
Vidal, M., D. W. Chan, M. Gerstein, M. Mann, G. S. Omenn, D. Tagle, S. Sechi, et al. 2012. “The Human Proteome - a Scientific Opportunity for Transforming Diagnostics, Therapeutics, and Healthcare.” Clinical Proteomics 9 (1): 6. Cite
Huttenhain, R., M. Soste, N. Selevsek, H. Rost, A. Sethi, C. Carapito, T. Farrah, et al. 2012. “Reproducible Quantification of Cancer-Associated Proteins in Body Fluids Using Targeted Proteomics.” Science Translational Medicine 4 (142): 142ra94. Cite
Hood, L. E., G. S. Omenn, R. L. Moritz, R. Aebersold, R. Yamamoto K, M. Amos, J. Hunter-Cevera, and L. Locascio. 2012. “New and Improved Proteomics Technologies for Understanding Complex Biological Systems: Addressing a Grand Challenge in the Life Sciences.” Proteomics, July. Cite
Bislev, S. L., E. W. Deutsch, Z. Sun, T. Farrah, R. Aebersold, R. L. Moritz, E. Bendixen, and M. C. Codrea. 2012. “A Bovine PeptideAtlas of Milk and Mammary Gland Proteomes.” Proteomics, July. Cite
Swearingen, K. E., and R. L. Moritz. 2012. “High-Field Asymmetric Waveform Ion Mobility Spectrometry for Mass Spectrometry-Based Proteomics.” Expert Review of Proteomics 9 (5): 505–17. Cite
Chambers, M. C., B. Maclean, R. Burke, D. Amodei, D. L. Ruderman, S. Neumann, L. Gatto, et al. 2012. “A Cross-Platform Toolkit for Mass Spectrometry and Proteomics.” Nature Biotechnology 30 (10): 918–20. Cite
Farrah, T., E. W. Deutsch, M. R. Hoopmann, J. L. Hallows, Z. Sun, C. Y. Huang, and R. L. Moritz. 2012. “The State of the Human Proteome in 2012 as Viewed through PeptideAtlas.” Journal of Proteome Research, December. Cite
Lewis, S., A. Csordas, S. Killcoyne, H. Hermjakob, M. R. Hoopmann, R. L. Moritz, E. W. Deutsch, and J. Boyle. 2012. “Hydra: A Scalable Proteomic Search Engine Which Utilizes the Hadoop Distributed Computing Framework.” BMC Bioinformatics 13 (1): 324. Cite
Lindner, S. E., K. E. Swearingen, A. Harupa, A. M. Vaughan, P. Sinnis, R. L. Moritz, and S. H. Kappe. 2013. “Total and Putative Surface Proteomics of Malaria Parasite Salivary Gland Sporozoites.” Molecular & Cellular Proteomics : MCP, January. Cite
Picotti, P., M. Clement-Ziza, H. Lam, D. S. Campbell, A. Schmidt, E. W. Deutsch, H. Rost, et al. 2013. “A Complete Mass-Spectrometric Map of the Yeast Proteome Applied to Quantitative Trait Analysis.” Nature, January. Cite
Hoopmann, M. R., and R. L. Moritz. 2013. “Current Algorithmic Solutions for Peptide-Based Proteomics Data Generation and Identification.” Curr Opin Biotechnol 24 (1): 31–38. Cite
Huttenhain, R., S. Surinova, R. Ossola, Z. Sun, D. Campbell, F. Cerciello, R. Schiess, et al. 2013. “N-Glycoprotein SRMAtlas: A Resource of Mass-Spectrometric Assays for N-Glycosites Enabling Consistent and Multiplexed Protein Quantification for Clinical Applications.” Molecular & Cellular Proteomics : MCP, February. Cite
Sun, B., A. G. Utleg, Z. Hu, S. Qin, A. Keller, C. Lorang, L. Gray, et al. 2013. “Glycocapture-Assisted Global Quantitative Proteomics (GagQP) Reveals Multiorgan Responses in Serum Toxicoproteome.” Journal of Proteome Research, March. Cite
Tauro, B. J., R. A. Mathias, D. W. Greening, S. K. Gopal, H. Ji, E. A. Kapp, B. M. Coleman, et al. 2013. “Oncogenic H-Ras Reprograms Madin-Darby Canine Kidney (MDCK) Cell-Derived Exosomal Proteins Following Epithelial-Mesenchymal Transition.” Mol Cell Proteomics, May. Cite
Shteynberg, D., A. I. Nesvizhskii, R. L. Moritz, and E. W. Deutsch. 2013. “Combining Results of Multiple Search Engines in Proteomics.” Mol Cell Proteomics 12 (9): 2383–93. Cite
Mercier, Sarah K., Heather Donaghy, Rachel A. Botting, Stuart G. Turville, Andrew N. Harman, Najla Nasr, Hong Ji, et al. 2013. “The Microvesicle Component of HIV-1 Inocula Modulates Dendritic Cell Infection and Maturation and Enhances Adhesion to and Activation of T Lymphocytes.” PLoS Pathogens 9 (10): e1003700. Cite
Yoon, S. H., S. Turkarslan, D. J. Reiss, M. Pan, J. A. Burn, K. C. Costa, T. J. Lie, et al. 2013. “A Systems Level Predictive Model for Global Gene Regulation of Methanogenesis in a Hydrogenotrophic Methanogen.” Genome Res 23 (11): 1839–51. Cite
Moruz, L., M. R. Hoopmann, M. Rosenlund, V. Granholm, R. L. Moritz, and L. Kall. 2013. “Mass Fingerprinting of Complex Mixtures: Protein Inference from High-Resolution Peptide Masses and Predicted Retention Times.” J Proteome Res 12 (12): 5730–41. Cite
Kusebauch, U., E. W. Deutsch, D. S. Campbell, Z. Sun, T. Farrah, and R. L. Moritz. 2014. “Using PeptideAtlas, SRMAtlas, and PASSEL: Comprehensive Resources for Discovery and Targeted Proteomics.” Current Protocols in Bioinformatics / Editoral Board, Andreas D. Baxevanis ... [et Al.] 46: 13 25 1-13 25 28. Cite
Bundgaard, Louise, Stine Jacobsen, Mette Aamand Sørensen, Zhi Sun, Eric W. Deutsch, R. L. Moritz, and Emøke Bendixen. 2014. “The Equine PeptideAtlas–a Resource for Developing Proteomics-Based Veterinary Research.” Proteomics. Cite
Muller, Emilie E. L., Nicolás Pinel, Cédric C. Laczny, Michael R. Hoopmann, Shaman Narayanasamy, Laura A. Lebrun, Hugo Roume, et al. 2014. “Community-Integrated Omics Links Dominance of a Microbial Generalist to Fine-Tuned Resource Usage.” Nature Communications 5: 5603. Cite
Surmann, Kristin, Stephan Michalik, Petra Hildebrandt, Philipp Gierok, Maren Depke, Lars Brinkmann, Jörg Bernhardt, et al. 2014. “Comparative Proteome Analysis Reveals Conserved and Specific Adaptation Patterns of Staphylococcus Aureus after Internalization by Different Types of Human Non-Professional Phagocytic Host Cells.” Front Microbiol 5: 392. Cite
Farrah, Terry, Eric W. Deutsch, Gilbert S. Omenn, Zhi Sun, Julian D. Watts, Tadashi Yamamoto, David Shteynberg, Micheleen M. Harris, and Robert L. Moritz. 2014. “State of the Human Proteome in 2013 as Viewed through PeptideAtlas: Comparing the Kidney, Urine, and Plasma Proteomes for the Biology- and Disease-Driven Human Proteome Project.” Journal of Proteome Research 13 (1): 60–75. Cite
Vialas, V., Z. Sun, Y. Penha C. V. Loureiro, M. Carrascal, J. Abian, L. Monteoliva, E. W. Deutsch, R. Aebersold, R. L. Moritz, and C. Gil. 2014. “A Candida Albicans PeptideAtlas.” Journal of Proteomics 97 (January): 62–68. Cite
Lindner, Scott E., Mark J. Sartain, Kiera Hayes, Anke Harupa, R. L. Moritz, Stefan H. I. Kappe, and Ashley M. Vaughan. 2014. “Enzymes Involved in Plastid-Targeted Phosphatidic Acid Synthesis Are Essential for Plasmodium Yoelii Liver-Stage Development.” Mol Microbiol 91 (February): 679–93. Cite
Carpp, L. N., R. S. Rogers, R. L. Moritz, and J. D. Aitchison. 2014. “Quantitative Proteomic Analysis of Host-Virus Interactions Reveals a Role for GBF1 in Dengue Infection.” Molecular & Cellular Proteomics : MCP, May. Cite
Kusebauch, U., C. Ortega, A. Ollodart, R. S. Rogers, D. R. Sherman, R. L. Moritz, and C. Grundner. 2014. “Mycobacterium Tuberculosis Supports Protein Tyrosine Phosphorylation.” Proceedings of the National Academy of Sciences of the United States of America, June. Cite
Tien, Jerry F., Neil T. Umbreit, Alex Zelter, Michael Riffle, Michael R. Hoopmann, Richard S. Johnson, Bryan R. Fonslow, et al. 2014. “Kinetochore Biorientation in Saccharomyces Cerevisiae Requires a Tightly Folded Conformation of the Ndc80 Complex.” Genetics, September. Cite
Rosenberger, George, Ching Chiek Koh, Tiannan Guo, Hannes L. Röst, Petri Kouvonen, Ben C. Collins, Moritz Heusel, et al. 2014. “A Repository of Assays to Quantify 10,000 Human Proteins by SWATH-MS.” Scientific Data 1 (September): 140031. Cite