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Shotgun Proteomics Sample Processing Automated by an Open-Source Lab Robot
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Fully Automated Sample Processing and Analysis Workflow for Low-Input Proteome Profiling.

Yiran Liang1, Hayden Acor1, Michaela A McCown2

  • 1Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States.

Analytical Chemistry
|December 22, 2020
PubMed
Summary
This summary is machine-generated.

A new automated platform, autoPOTS, simplifies low-input and single-cell proteomics. This system uses commercial instruments for protein profiling, making advanced techniques accessible to more labs.

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Area of Science:

  • Proteomics
  • Biochemistry
  • Analytical Chemistry

Background:

  • Direct protein expression profiling in single cells and trace samples is advancing.
  • Current low-input sample preparation methods often require specialized, custom-built fluidics and significant expertise, limiting their widespread adoption.

Purpose of the Study:

  • To develop a fully automated platform for low-input and single-cell proteomics using only commercially available instrumentation.
  • To overcome the limitations of specialized, manually operated systems in proteomic laboratories.

Main Methods:

  • Utilized a commercial robotic pipetting platform for one-pot sample preparation.
  • Employed low-volume 384-well plates with controlled evaporation compensation.
  • Modified a commercial autosampler for direct analysis from well plates using nanoLC columns.

Main Results:

  • Successfully analyzed 1-500 HeLa cells with autoPOTS, showing moderate peptide coverage reduction for 150 cells and 24% for single cells.
  • Identified an average of 1095 protein groups from approximately 130 sorted B or T lymphocytes, demonstrating clinical feasibility.

Conclusions:

  • The autoPOTS platform offers a fully automated solution for low-input and single-cell proteomics.
  • Its reliance on commercial instrumentation makes it an accessible and attractive option for diverse proteomic laboratories.
  • This automation facilitates broader implementation of advanced proteomic analyses.