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Related Concept Videos

Proteomics01:33

Proteomics

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A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
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Organic Solvent-Based Protein Precipitation for Robust Proteome Purification Ahead of Mass Spectrometry
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Modular automated bottom-up proteomic sample preparation for high-throughput applications.

Yan Chen1,2,3, Nurgul Kaplan Lease1,2,3, Jennifer W Gin1,2,3

  • 1Joint BioEnergy Institute, Lawrence Berkeley National Laboratory, Emeryville, CA, United States of America.

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|February 25, 2022
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Summary

This study presents an automated protocol for preparing bacterial and fungal samples for proteomic analysis. The method enhances throughput and data quality for high-volume studies.

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Area of Science:

  • Microbiology
  • Biochemistry
  • Proteomics

Background:

  • Manual proteomic sample preparation is time-consuming and can compromise data quality, especially for large-scale studies.
  • Automated liquid handling systems offer a solution to improve throughput and reproducibility in sample preparation.

Purpose of the Study:

  • To develop and validate a modular, automated protocol for bottom-up proteomic sample preparation of Gram-negative bacteria and fungal cells.
  • To enable rapid, low-variance preparation of hundreds of samples using automated liquid handlers.

Main Methods:

  • A three-part modular protocol was optimized for cell lysis, protein quantification, and normalization/tryptic digestion.
  • The protocol was implemented on Beckman-Coulter Biomek automated liquid handlers.
  • Validation involved analyzing 47 samples from Pseudomonas putida and Rhodosporidium toruloides.

Main Results:

  • The automated workflow prepared 50 micrograms of protein from 96 samples for tryptic digestion in under an hour.
  • Achieved protein relative quantity variance (CV%) below 15% for 94 peptide samples.
  • Eliminated the need for desalting column cleanup in the sample preparation process.

Conclusions:

  • The developed modular workflow provides robust and reproducible proteomic samples for high-throughput applications.
  • This automated method significantly improves sample preparation efficiency for bacterial and fungal proteomics.
  • The protocol is flexible and adaptable for future advancements in proteomic analysis.