1. Highly multiplexed and quantitative cell-surface protein profiling using genetically barcoded antibodies.
- Author
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Pollock SB, Hu A, Mou Y, Martinko AJ, Julien O, Hornsby M, Ploder L, Adams JJ, Geng H, Müschen M, Sidhu SS, Moffat J, and Wells JA
- Subjects
- Antibodies genetics, Bacteriophages genetics, Bacteriophages metabolism, Burkitt Lymphoma metabolism, Cell Line, Tumor, Humans, Leukemia metabolism, Membrane Proteins chemistry, Membrane Proteins metabolism, Antibodies analysis, Burkitt Lymphoma genetics, High-Throughput Nucleotide Sequencing methods, Leukemia genetics, Membrane Proteins genetics, Proteomics methods
- Abstract
Human cells express thousands of different surface proteins that can be used for cell classification, or to distinguish healthy and disease conditions. A method capable of profiling a substantial fraction of the surface proteome simultaneously and inexpensively would enable more accurate and complete classification of cell states. We present a highly multiplexed and quantitative surface proteomic method using genetically barcoded antibodies called phage-antibody next-generation sequencing (PhaNGS). Using 144 preselected antibodies displayed on filamentous phage (Fab-phage) against 44 receptor targets, we assess changes in B cell surface proteins after the development of drug resistance in a patient with acute lymphoblastic leukemia (ALL) and in adaptation to oncogene expression in a Myc-inducible Burkitt lymphoma model. We further show PhaNGS can be applied at the single-cell level. Our results reveal that a common set of proteins including FLT3, NCR3LG1, and ROR1 dominate the response to similar oncogenic perturbations in B cells. Linking high-affinity, selective, genetically encoded binders to NGS enables direct and highly multiplexed protein detection, comparable to RNA-sequencing for mRNA. PhaNGS has the potential to profile a substantial fraction of the surface proteome simultaneously and inexpensively to enable more accurate and complete classification of cell states., Competing Interests: The authors declare no conflict of interest., (Copyright © 2018 the Author(s). Published by PNAS.)
- Published
- 2018
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