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Highly multiplexed and quantitative cell-surface protein profiling using genetically barcoded antibodies

Overview of attention for article published in Proceedings of the National Academy of Sciences of the United States of America, February 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (88th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (53rd percentile)

Mentioned by

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22 X users
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2 patents
reddit
1 Redditor

Citations

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46 Dimensions

Readers on

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176 Mendeley
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2 CiteULike
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Title
Highly multiplexed and quantitative cell-surface protein profiling using genetically barcoded antibodies
Published in
Proceedings of the National Academy of Sciences of the United States of America, February 2018
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

X Demographics

The data shown below were collected from the profiles of 22 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 176 Mendeley readers of this research output. Click here to see the associated Mendeley record.

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%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 20. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 11 May 2023.
All research outputs
#1,783,110
of 24,622,191 outputs
Outputs from Proceedings of the National Academy of Sciences of the United States of America
#22,816
of 101,438 outputs
Outputs of similar age
#38,636
of 335,144 outputs
Outputs of similar age from Proceedings of the National Academy of Sciences of the United States of America
#487
of 1,045 outputs
Altmetric has tracked 24,622,191 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 101,438 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 38.8. This one has done well, scoring higher than 77% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 335,144 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% of its contemporaries.
We're also able to compare this research output to 1,045 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.