Timothy Toby (Presenter)
Northwestern University
Bio: Tim obtained his BS in 2012 in Investigative & Medical Sciences from Saint Louis University. During his undergraduate years, Tim worked as a research assistant developing enzymatic biofuel cells in the Minteer Research Group. Upon graduation, Tim worked as a contractor biologist for the Division of Pharmaceutical Analysis of the US FDA in downtown St. Louis. At FDA, Tim began to specialize in the technology that would guide his future interests and career goals: mass spectrometry-based proteomics. Tim is currently an Interdepartmental Biological Sciences (IBiS) doctoral student at Northwestern University in the Kelleher Research Group. Tim’s research in the Kelleher Group focuses on the development of a full-scale proteomic pipeline for the application of top-down proteomics to translational research endeavors.
Authorship: Timothy Toby (1), Luca Fornelli (1), Jeff Anderson (1), Paul Thomas (1), Michael Abecassis (2), Josh Levitsky (2), and Neil Kelleher (1)
(1) Departments of Chemistry and Molecular Biosciences, Northwestern University, Evanston, IL 60208 (2) Comprehensive Transplant Center, Northwestern University Feinberg School of Medicine, Chicago, IL 60611
| Short Abstract Opportunities for top-down proteomics in translational research are beginning to expand as clinicians discern the value of proteoform-resolved measurements. We have developed a comprehensive pipeline applying top-down proteomics to multiple phases of the biomarker discovery workflow for proteoforms, including global discovery modes and high-throughput validation modes. Here, we present an example application of this pipeline in peripheral blood to elucidate proteoform biomarkers of clinical rejection in liver transplantation, a patient phenotype that lacks non-invasive diagnostic measures. Label-free quantitation yielded an initial discovery panel of putative markers of rejection in a cohort of 30 patients. Additionally, a novel method for targeted quantitation, proteoform reaction monitoring, is presented for an early model biomarker. |
Long Abstract
I. INTRODUCTION
Liver transplantation is a life-saving treatment for thousands of patients suffering from chronic and acute liver failure every year. Clinical management of liver allograft recipients is complicated by the threat of acute cellular rejection (AR), a clinically significant immune response to the transplanted organ that occurs weeks to months after transplantation. Summarily, AR is associated with an increased risk of graft failure and subsequent patient mortality, independent of the original cause of liver disease [1]. Similar to other solid organ transplant rejection etiologies, AR in liver is currently diagnosed by biopsy and histology of the transplanted organ tissue, a procedure that is highly invasive for the patient, subject to variation among pathologists, and lacking in predictive potential due to the “for-cause” nature of most collected specimens. Therefore, the discovery of non-invasive predictive and diagnostic biomarkers of AR in liver transplant recipients would be paramount to guiding clinical decision-making to preserve graft function and ensure graft and patient survival. In pursuit of deeper insight on the underlying molecular markers indicative of liver AR, we have applied recent advancements in top-down proteomics to both large-scale and targeted analyses of the peripheral blood mononuclear cell (PBMC) proteomes of a small cohort of patients exhibiting relevant phenotypes of graft dysfunction and rejection.
“Top-down” proteomics (TDP) refers to the large-scale study of proteoforms, which encompass all of the molecular forms of the protein products of a specific gene, including variants resultant from alternative splicing, single nucleotide polymorphisms, and post-translational modification [2]. The ability of TDP to measure proteoforms sets it apart from more common “bottom-up” proteomics methods, which reduce proteomes of interest to peptides before analysis by mass spectrometry, and therefore are not tuned to deeply specific insights on the intact protein molecules that are more directly reflective of cellular and higher-level disease phenotypes. The field of TDP has grown over the past decade, and a number of recent applications in translational research have shown the value of proteoform-resolved measurements in the study of human health and disease [3]. In the following study, we describe the application of our innovative, label-free TDP workflow for the elucidation of immune cell proteoforms that may be associated with, or even predictive of, AR in liver transplant patients. Additionally, we present a novel method to deploy top-down mass spectrometry in a targeted fashion, proteoform reaction monitoring (PfRM), to engender the rapid analysis of ever more minute sample amounts from increasingly large patient numbers. Together, these workflows begin to form the first comprehensive pipeline for TDPs in translational research, from biomarker discovery to large-scale validation, that can be applied to clinical questions beyond the realm of transplantation and across the spectrum of health and disease.
II. METHODS
Peripheral blood was collected from 10 patients of three phenotypes relevant in liver transplantation: healthy transplant recipients with normal biopsies (healthy transplant, HLT), patients exhibiting abnormal laboratory tests but negative biopsies (acute dysfunction no rejection, ADNR), and patients with biopsy-confirmed acute cellular rejection (acute rejection, AR). The PBMCs from each patient were isolated and stored in a clinical biorepository until proteomic analysis. For the global proteomic discovery experiments, label-free top-down quantitation was performed on the patient samples as described previously [4]. Briefly, sample cells were lysed, proteins were prefractionated by gel-elution liquid fraction entrapment electrophoresis (GELFrEE), and then the <30 kDa fraction was separated by nano-flow reverse-phase liquid chromatography (nRPLC) and submitted to online mass analysis on an Orbitrap Elite high-resolution mass spectrometer (Thermo Fisher Scientific). Hierarchical linear modelling was applied to normalized proteoform intensity values for quantitation, and proteoforms were identified and characterized using a Quest instance of ProSight PC.
PfRM experiments were conducted in reduced volumes of unfractionated lysate, utilizing nRPLC online with either a Fusion Lumos or Q-Exactive mass spectrometer (Thermo Fisher Scientific). Quadrupole isolation of precursors and high-resolution mass analysis in the orbitrap were leveraged in a looping single ion monitoring (SIM) method for proteoforms of interest, and fragment-based transitions were developed and quantified offline. PfRM was developed for a model set of biomarkers, the phospho-forms of death-associated protein 1 (DAP1), and deployed in a human cell line model of DAP1 phospho-modulation by rapamycin treatment, followed by a modest cohort of human PBMC samples of the aforementioned liver transplantation phenotypes.
III. RESULTS
After data searching via the ProSight PC informatic pipeline, 1171 proteoforms associated with 245 UniProt accession numbers were identified at a 5% false discovery rate threshold. Of the identified proteoforms, 135 were routinely observed in the majority of data files across all blocks, and formed a pool of intact mass tags (IMT) for introduction to our statistical modeling workflow for label-free quantitation. 73 IMTs passed our thresholds for significance (<5% instantaneous q value, >2-fold change), and were submitted for manual curation and gene ontology analysis as a prerequisite to further investigation as putative molecular markers of liver allograft rejection. An early model set of proteoforms, un-phosphorylated, mono-phosphorylated, and di-phosphorylated DAP1 (DAP1, pDAP1, ppDAP1), was forwarded for PfRM method development and deployment. The PfRM SIM assay developed in cell lines was subjected to decreasing amounts of input lysate and demonstrated linearity over two orders of magnitude, and an isolation window of 3 Thomsons was demonstrated to be sufficient to isolate all precursor proteoforms of interest with high sensitivity. The application of PfRM of DAP1 phospho-forms in the cell line model demonstrated that the assay could detect significant decreases in DAP1 phosphorylation over a time course of rapamycin treatment. Additionally, the assay was successfully deployed in a reduced subset of liver transplantation patients as a proof-of-principle for clinical sample analysis, but did not yield a significant associations between DAP1 phospho-form abundance and liver allograft phenotype.
IV. CONCLUSIONS
Two major elements of a comprehensive TDP pipeline for translational proteomics were developed for application in human PBMCs and deployed in a cohort of liver transplantation patients exhibiting three clinically relevant phenotypes. Discovery mode experiments relying on global proteome analysis and label-free quantitation yielded a set of proteoforms that may represent molecular indicators of the immune-mediated rejection process, supported by immune-related ontological associations and evidence from previous studies. A panel of significant proteoforms will be assembled into a predictive panel to be forwarded for verification and validation in a much larger cohort of patients by PfRM. The development of PfRM was successfully benchmarked in a model of rapamycin inhibition of mTOR-based phosphorylation of DAP1, and deployed in a small cohort of liver transplantation patients. Although DAP1 phospho-forms could not yet be verified as a significant biomarker of allograft rejection, we conclude that PfRM methodology exhibits vastly increased sensitivity over full-scan top-down methods, and allows us to drop patient sample requirements ~100-fold, which facilitates translational proteomics of the future.
References & Acknowledgements:
REFERENCES
1.Levitsky, J., Goldberg, D., Smith, A.R., Mansfield, S.A., Gillespie, B.W., Merion, R.M., Lok, A.S.F., Levy, G., Kulik, L., Abecassis, M., Shaked, A. Acute rejection increases risk of graft failure and death in recent liver transplant recipients. 2016. Clinical Gastroenterology and Hepatology. pii: S1542-3565(16)30561-4. doi: 10.1016/j.cgh.2016.07.035.
2.Smith, L.M., Kelleher, N.L., Consortium for Top Down Proteomics. Proteoform: a single term describing protein complexity. 2013. Nature Methods. 10(3): 186-7. doi: 10.1038/nmeth.2369.
3.Toby, T.K., Fornelli, L., Kelleher, N.L. Progress in top-down proteomics and the analysis of proteoforms. 2016. Annual Reviews of Analytical Chemistry. 9(1): 499-519. doi: 10.1146/annurev-anchem-071015-041550.
4.Savaryn, J.P., Toby, T.K., Catherman, A.D., Fellers, R.T., LeDuc, R.D., Thomas, P.M., Friedewald, J.J., Salomon, D.R., Abecassis, M.M., Kelleher, N.L. Comparative top down proteomics of peripheral blood mononuclear cells from kidney transplant recipients with normal kidney biopsies or acute rejection. 2016. Proteomics. 16(14): 2048-58. doi: 10.1002/pmic.201600008.
ACKNOWLEDGMENTS
Research reported in this presentation was supported by the National Institute Of General Medical Sciences of the National Institutes of Health under Award Number P41GM108569. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health
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