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Spatially Resolved Proteome Mapping of Laser Capture Microdissected Tissue with Automated Sample Transfer to Nanodroplets*

Overview of attention for article published in Molecular and Cellular Proteomics, June 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 (91st percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

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37 X users
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4 patents

Citations

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107 Dimensions

Readers on

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96 Mendeley
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Title
Spatially Resolved Proteome Mapping of Laser Capture Microdissected Tissue with Automated Sample Transfer to Nanodroplets*
Published in
Molecular and Cellular Proteomics, June 2018
DOI 10.1074/mcp.tir118.000686
Pubmed ID
Authors

Ying Zhu, Maowei Dou, Paul D Piehowski, Yiran Liang, Fangjun Wang, Rosalie K Chu, William B Chrisler, Jordan N Smith, Kaitlynn C Schwarz, Yufeng Shen, Anil K Shukla, Ronald J Moore, Richard D Smith, Wei-Jun Qian, Ryan T Kelly

Abstract

Current mass spectrometry (MS)-based proteomics approaches are ineffective for mapping protein expression in tissue sections with high spatial resolution due to the limited overall sensitivity of conventional workflows. Here we report an integrated and automated method to advance spatially resolved proteomics by seamlessly coupling laser capture microdissection (LCM) with a recently developed nanoliter-scale sample preparation system termed nanoPOTS (Nanodroplet Processing in One pot for Trace Samples). The workflow is enabled by prepopulating nanowells with DMSO, which serves as a sacrificial capture liquid for microdissected tissues. The DMSO droplets efficiently collect laser-pressure catapulted LCM tissues as small as 20 µm in diameter with success rates >87%. We also demonstrate that tissue treatment with DMSO can significantly improve proteome coverage, likely due to its ability to dissolve lipids from tissue and enhance protein extraction efficiency. The LCM-nanoPOTS platform was able to identify 180, 695, and 1827 protein groups on average from 12-µm-thick rat brain cortex tissue sections with diameters of 50, 100, and 200 µm, respectively. We also analyzed 100-µm-diameter sections corresponding to 10-18 cells from three different regions of rat brain and comparatively quantified ~1000 proteins, demonstrating the potential utility for high-resolution spatially resolved mapping of protein expression in tissues.

X Demographics

X Demographics

The data shown below were collected from the profiles of 37 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 96 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 96 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 24 25%
Researcher 17 18%
Student > Master 11 11%
Professor 5 5%
Student > Postgraduate 5 5%
Other 12 13%
Unknown 22 23%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 26 27%
Chemistry 14 15%
Agricultural and Biological Sciences 12 13%
Medicine and Dentistry 5 5%
Neuroscience 4 4%
Other 11 11%
Unknown 24 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 30. 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 20 September 2023.
All research outputs
#1,306,710
of 25,508,813 outputs
Outputs from Molecular and Cellular Proteomics
#115
of 3,226 outputs
Outputs of similar age
#27,525
of 341,554 outputs
Outputs of similar age from Molecular and Cellular Proteomics
#8
of 43 outputs
Altmetric has tracked 25,508,813 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,226 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one has done particularly well, scoring higher than 96% 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 341,554 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 43 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.