Title |
Highly multiplexed and quantitative cell-surface protein profiling using genetically barcoded antibodies
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Published in |
Proceedings of the National Academy of Sciences of the United States of America, February 2018
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DOI | 10.1073/pnas.1721899115 |
Pubmed ID | |
Authors |
Samuel B. Pollock, Amy Hu, Yun Mou, Alexander J. Martinko, Olivier Julien, Michael Hornsby, Lynda Ploder, Jarrett J. Adams, Huimin Geng, Markus Müschen, Sachdev S. Sidhu, Jason Moffat, James A. Wells |
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. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 11 | 50% |
France | 2 | 9% |
Canada | 1 | 5% |
Italy | 1 | 5% |
Israel | 1 | 5% |
Unknown | 6 | 27% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 14 | 64% |
Scientists | 7 | 32% |
Practitioners (doctors, other healthcare professionals) | 1 | 5% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 176 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 43 | 24% |
Researcher | 28 | 16% |
Student > Master | 16 | 9% |
Student > Bachelor | 13 | 7% |
Student > Doctoral Student | 12 | 7% |
Other | 26 | 15% |
Unknown | 38 | 22% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 44 | 25% |
Agricultural and Biological Sciences | 31 | 18% |
Engineering | 12 | 7% |
Chemistry | 10 | 6% |
Medicine and Dentistry | 7 | 4% |
Other | 31 | 18% |
Unknown | 41 | 23% |