Highly multiplexed and quantitative cell-surface protein profiling using genetically barcoded antibodies.
Samuel B PollockAmy HuYun MouAlexander J MartinkoOlivier JulienMichael HornsbyLynda PloderJarrett J AdamsHuimin GengMarkus MüschenSachdev S SidhuJason MoffatJames A WellsPublished in: Proceedings of the National Academy of Sciences of the United States of America (2018)
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.
Keyphrases
- single cell
- rna seq
- cell surface
- high throughput
- acute lymphoblastic leukemia
- deep learning
- machine learning
- binding protein
- pseudomonas aeruginosa
- high resolution
- poor prognosis
- acute myeloid leukemia
- gene expression
- mass spectrometry
- tyrosine kinase
- mesenchymal stem cells
- genome wide
- dna methylation
- label free
- bone marrow
- quantum dots