Dr. Gregg Morin received his PhD in Biochemistry from the University of Colorado, Boulder in 1988. Following a postdoctoral fellowship in the Department of Molecular Biophysics and Biochemistry at Yale University and an assistant professorship at the University of California, Davis, Dr. Morin was the Director of the Department of Molecular Biology and Biochemistry at Geron Corporation. In 2004, he joined Canada’s Michael Smith Genome Sciences Centre where he is currently the Head of Proteomics. He is also an Adjunct Professor in the Department of Molecular Biology and Biochemistry at Simon Fraser University and an Associate Professor in the Department of Medical Genetics at the University of British Columbia. Finally, he was the founding Scientific Director of the BC Proteomics Network, which provides proteomic support services and education to BC scientists.

Dr Morin’s achievements include pioneering the use of mass spectrometry for analyzing protein-protein interactions involved in disease, mapping the interactions within the TNFα inflammatory pathway. He was the first to observe human telomerase activity and developed assays to detect and measure it. Based on these discoveries, Geron Corporation was formed. There, his group demonstrated that hTERT expression is sufficient to immortalize human cells in a landmark Science publication in 1998. Dr. Morin is listed as an inventor on 64 patents related to these telomerase discoveries and applications.

As Head of the Proteomics Platform at Canada's Michael Smith Genome Sciences Centre, Dr. Morin’s role is to advance mass spectrometry-based oncology research with other investigators at BC Cancer and other institutions. This includes developing proteomic methods for quantitative global proteome profiling of clinical and research samples, basic and aberrant protein function research, and the comprehensive analysis of post-translational modifications (e.g., phospho, ubiquitin, methyl, acetyl). His expertise is in advanced proteomics methods, biochemistry, and RNA processing.

Dr. Gregg Morin has coauthored >70 publications (including reviews) that have been cited >19,000 times, and has 64 issued patents worldwide (37 in USA) related to his telomerase research.

  • Senior Scientist, BC Cancer
  • Associate Professor, Department of Medical Genetics, University of British Columbia 
  • Adjunct Professor, Department of Molecular Biology and Biochemistry, Simon Fraser University
  • PhD, Biochemistry, University of Colorado, Boulder, US 
  • MSc, Chemistry, University of California, San Diego, US 
  • BA, Chemistry, Carleton College Northfield, Minnesota, US 


Selected Publications

Telomerase catalytic subunit homologs from fission yeast and human.

Science (New York, N.Y.), 1997
Nakamura, T M, Morin, G B, Chapman, K B, Weinrich, S L, Andrews, W H, Lingner, J, Harley, C B, Cech, T R
Catalytic protein subunits of telomerase from the ciliate Euplotes aediculatus and the yeast Saccharomyces cerevisiae contain reverse transcriptase motifs. Here the homologous genes from the fission yeast Schizosaccharomyces pombe and human are identified. Disruption of the S. pombe gene resulted in telomere shortening and senescence, and expression of mRNA from the human gene correlated with telomerase activity in cell lines. Sequence comparisons placed the telomerase proteins in the reverse transcriptase family but revealed hallmarks that distinguish them from retroviral and retrotransposon relatives. Thus, the proposed telomerase catalytic subunits are phylogenetically conserved and represent a deep branch in the evolution of reverse transcriptases.

Large-scale mapping of human protein-protein interactions by mass spectrometry.

Molecular systems biology, 2007
Ewing, Rob M, Chu, Peter, Elisma, Fred, Li, Hongyan, Taylor, Paul, Climie, Shane, McBroom-Cerajewski, Linda, Robinson, Mark D, O'Connor, Liam, Li, Michael, Taylor, Rod, Dharsee, Moyez, Ho, Yuen, Heilbut, Adrian, Moore, Lynda, Zhang, Shudong, Ornatsky, Olga, Bukhman, Yury V, Ethier, Martin, Sheng, Yinglun, Vasilescu, Julian, Abu-Farha, Mohamed, Lambert, Jean-Philippe, Duewel, Henry S, Stewart, Ian I, Kuehl, Bonnie, Hogue, Kelly, Colwill, Karen, Gladwish, Katharine, Muskat, Brenda, Kinach, Robert, Adams, Sally-Lin, Moran, Michael F, Morin, Gregg B, Topaloglou, Thodoros, Figeys, Daniel
Mapping protein-protein interactions is an invaluable tool for understanding protein function. Here, we report the first large-scale study of protein-protein interactions in human cells using a mass spectrometry-based approach. The study maps protein interactions for 338 bait proteins that were selected based on known or suspected disease and functional associations. Large-scale immunoprecipitation of Flag-tagged versions of these proteins followed by LC-ESI-MS/MS analysis resulted in the identification of 24,540 potential protein interactions. False positives and redundant hits were filtered out using empirical criteria and a calculated interaction confidence score, producing a data set of 6463 interactions between 2235 distinct proteins. This data set was further cross-validated using previously published and predicted human protein interactions. In-depth mining of the data set shows that it represents a valuable source of novel protein-protein interactions with relevance to human diseases. In addition, via our preliminary analysis, we report many novel protein interactions and pathway associations.

Using Public Data for Comparative Proteome Analysis in Precision Medicine Programs.

Proteomics. Clinical applications, 2018
Hughes, Christopher S, Morin, Gregg B
Maximizing the clinical utility of information obtained in longitudinal precision medicine programs would benefit from robust comparative analyses to known information to assess biological features of patient material toward identifying the underlying features driving their disease phenotype. Herein, the potential for utilizing publically deposited mass-spectrometry-based proteomics data to perform inter-study comparisons of cell-line or tumor-tissue materials is investigated.

Class I HDAC inhibitors enhance YB-1 acetylation and oxidative stress to block sarcoma metastasis.

EMBO reports, 2019
El-Naggar, Amal M, Somasekharan, Syam Prakash, Wang, Yemin, Cheng, Hongwei, Negri, Gian Luca, Pan, Melvin, Wang, Xue Qi, Delaidelli, Alberto, Rafn, Bo, Cran, Jordan, Zhang, Fan, Zhang, Haifeng, Colborne, Shane, Gleave, Martin, Mandinova, Anna, Kedersha, Nancy, Hughes, Christopher S, Surdez, Didier, Delattre, Olivier, Wang, Yuzhuo, Huntsman, David G, Morin, Gregg B, Sorensen, Poul H
Outcomes for metastatic Ewing sarcoma and osteosarcoma are dismal and have not changed for decades. Oxidative stress attenuates melanoma metastasis, and melanoma cells must reduce oxidative stress to metastasize. We explored this in sarcomas by screening for oxidative stress sensitizers, which identified the class I HDAC inhibitor MS-275 as enhancing vulnerability to reactive oxygen species (ROS) in sarcoma cells. Mechanistically, MS-275 inhibits YB-1 deacetylation, decreasing its binding to 5'-UTRs of NFE2L2 encoding the antioxidant factor NRF2, thereby reducing NFE2L2 translation and synthesis of NRF2 to increase cellular ROS. By global acetylomics, MS-275 promotes rapid acetylation of the YB-1 RNA-binding protein at lysine-81, blocking binding and translational activation of NFE2L2, as well as known YB-1 mRNA targets, HIF1A, and the stress granule nucleator, G3BP1. MS-275 dramatically reduces sarcoma metastasis in vivo, but an MS-275-resistant YB-1K81-to-alanine mutant restores metastatic capacity and NRF2, HIF1α, and G3BP1 synthesis in MS-275-treated mice. These studies describe a novel function for MS-275 through enhanced YB-1 acetylation, thus inhibiting YB-1 translational control of key cytoprotective factors and its pro-metastatic activity.

A Standardized and Reproducible Proteomics Protocol for Bottom-Up Quantitative Analysis of Protein Samples Using SP3 and Mass Spectrometry.

Methods in molecular biology (Clifton, N.J.), 2019
Hughes, Christopher S, Sorensen, Poul H, Morin, Gregg B
The broad utility of mass spectrometry (MS) for investigating the proteomes of a diverse array of sample types has significantly expanded the use of this technology in biological studies. This widespread use has resulted in a substantial collection of protocols and acquisition approaches designed to obtain the highest-quality data for each experiment. As a result, distilling this information to develop a standard operating protocol for essential workflows, such as bottom-up quantitative shotgun whole proteome analysis, can be complex for users new to MS technology. Further complicating this matter, in-depth description of the methodological choices is seldom given in the literature. In this work, we describe a workflow for quantitative whole proteome analysis that is suitable for biomarker discovery, giving detailed consideration to important stages, including (1) cell lysis and protein cleanup using SP3 paramagnetic beads, (2) quantitative labeling, (3) offline peptide fractionation, (4) MS analysis, and (5) data analysis and interpretation. Special attention is paid to providing comprehensive details for all stages of this proteomics workflow to enhance transferability to external labs. The standardized protocol described here will provide a simplified resource to the proteomics community toward efficient adaptation of MS technology in proteomics studies.

Single-pot, solid-phase-enhanced sample preparation for proteomics experiments.

Nature protocols, 2019
Hughes, Christopher S, Moggridge, Sophie, Müller, Torsten, Sorensen, Poul H, Morin, Gregg B, Krijgsveld, Jeroen
A critical step in proteomics analysis is the optimal extraction and processing of protein material to ensure the highest sensitivity in downstream detection. Achieving this requires a sample-handling technology that exhibits unbiased protein manipulation, flexibility in reagent use, and virtually lossless processing. Addressing these needs, the single-pot, solid-phase-enhanced sample-preparation (SP3) technology is a paramagnetic bead-based approach for rapid, robust, and efficient processing of protein samples for proteomic analysis. SP3 uses a hydrophilic interaction mechanism for exchange or removal of components that are commonly used to facilitate cell or tissue lysis, protein solubilization, and enzymatic digestion (e.g., detergents, chaotropes, salts, buffers, acids, and solvents) before downstream proteomic analysis. The SP3 protocol consists of nonselective protein binding and rinsing steps that are enabled through the use of ethanol-driven solvation capture on the surface of hydrophilic beads, and elution of purified material in aqueous conditions. In contrast to alternative approaches, SP3 combines compatibility with a substantial collection of solution additives with virtually lossless and unbiased recovery of proteins independent of input quantity, all in a simplified single-tube protocol. The SP3 protocol is simple and efficient, and can be easily completed by a standard user in ~30 min, including reagent preparation. As a result of these properties, SP3 has successfully been used to facilitate examination of a broad range of sample types spanning simple and complex protein mixtures in large and very small amounts, across numerous organisms. This work describes the steps and extensive considerations involved in performing SP3 in bottom-up proteomics, using a simplified protein cleanup scenario for illustration.

RawTools: Rapid and Dynamic Interrogation of Orbitrap Data Files for Mass Spectrometer System Management.

Journal of proteome research, 2019
Kovalchik, Kevin A, Colborne, Shane, Spencer, Sandra Elizabeth, Sorensen, Poul H, Chen, David D Y, Morin, Gregg B, Hughes, Christopher S
Optimizing the quality of proteomics data collected from a mass spectrometer (MS) requires careful selection of acquisition parameters and proper assessment of instrument performance. Software tools capable of extracting a broad set of information from raw files, including meta, scan, quantification, and identification data, are needed to provide guidance for MS system management. In this work, direct extraction and utilization of these data is demonstrated using RawTools, a standalone tool for extracting meta and scan data directly from raw MS files generated on Thermo Orbitrap instruments. RawTools generates summarized and detailed plain text outputs after parsing individual raw files, including scan rates and durations, duty cycle characteristics, precursor and reporter ion quantification, and chromatography performance. RawTools also contains a diagnostic module that includes an optional "preview" database search for facilitating informed decision-making related to optimization of MS performance based on a variety of metrics. RawTools has been developed in C# and utilizes the Thermo RawFileReader library and thus can process raw MS files with high speed and high efficiency on all major operating systems (Windows, MacOS, Linux). To demonstrate the utility of RawTools, the extraction of meta and scan data from both individual and large collections of raw MS files was carried out to identify problematic characteristics of instrument performance. Taken together, the combined rich feature-set of RawTools with the capability for interrogation of MS and experiment performance makes this software a valuable tool for proteomics researchers.

Parsing and Quantification of Raw Orbitrap Mass Spectrometer Data Using RawQuant.

Journal of proteome research, 2018
Kovalchik, Kevin A, Moggridge, Sophie, Chen, David D Y, Morin, Gregg B, Hughes, Christopher S
Effective analysis of protein samples by mass spectrometry (MS) requires careful selection and optimization of a range of experimental parameters. As the output from the primary detection device, the "raw" MS data file can be used to gauge the success of a given sample analysis. However, the closed-source nature of the standard raw MS file can complicate effective parsing of the data contained within. To ease and increase the range of analyses possible, the RawQuant tool was developed to enable parsing of raw MS files derived from Thermo Orbitrap instruments to yield meta and scan data in an openly readable text format. RawQuant can be commanded to export user-friendly files containing MS{{sup}}1{{/sup}}, MS{{sup}}2{{/sup}}, and MS{{sup}}3{{/sup}} metadata as well as matrices of quantification values based on isobaric tagging approaches. In this study, the utility of RawQuant is demonstrated in several scenarios: (1) reanalysis of shotgun proteomics data for the identification of the human proteome, (2) reanalysis of experiments utilizing isobaric tagging for whole-proteome quantification, and (3) analysis of a novel bacterial proteome and synthetic peptide mixture for assessing quantification accuracy when using isobaric tags. Together, these analyses successfully demonstrate RawQuant for the efficient parsing and quantification of data from raw Thermo Orbitrap MS files acquired in a range of common proteomics experiments. In addition, the individual analyses using RawQuant highlights parametric considerations in the different experimental sets and suggests targetable areas to improve depth of coverage in identification-focused studies and quantification accuracy when using isobaric tags.

PP2A inhibition sensitizes cancer stem cells to ABL tyrosine kinase inhibitors in BCR-ABL+ human leukemia.

Science translational medicine, 2018
Lai, Damian, Chen, Min, Su, Jiechuang, Liu, Xiaohu, Rothe, Katharina, Hu, Kaiji, Forrest, Donna L, Eaves, Connie J, Morin, Gregg B, Jiang, Xiaoyan
Overcoming drug resistance and targeting leukemic stem cells (LSCs) remain major challenges in curing BCR-ABL{{sup}}+{{/sup}} human leukemia. Using an advanced drug/proliferation screen, we have uncovered a prosurvival role for protein phosphatase 2A (PP2A) in tyrosine kinase inhibitor (TKI)-insensitive leukemic cells, regulated by an Abelson helper integration site-1-mediated PP2A-β-catenin-BCR-ABL-JAK2 protein complex. Genetic and pharmacological inhibition of PP2A impairs survival of TKI nonresponder cells and sensitizes them to TKIs in vitro, inducing a dramatic loss of several key proteins, including β-catenin. We also demonstrate that the clinically validated PP2A inhibitors LB100 and LB102, in combination with TKIs, selectively eliminate treatment-naïve TKI-insensitive stem and progenitor cells, while sparing healthy counterparts. In addition, PP2A inhibitors and TKIs act synergistically to inhibit the growth of TKI-insensitive cells, as assessed by combination index analysis. The combination eliminates infiltrated BCR-ABL{{sup}}+{{/sup}} blast cells and drug-insensitive LSCs and confers a survival advantage in preclinical xenotransplant models. Thus, dual PP2A and BCR-ABL inhibition may be a valuable therapeutic strategy to synergistically target drug-insensitive LSCs that maintain minimal residual disease in patients.
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