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Related Concept Videos

Proteomics01:33

Proteomics

8.6K
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...
8.6K

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Related Experiment Video

Updated: Oct 29, 2025

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
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Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification

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[Advances in high-throughput proteomic analysis].

Qiong Wu1, Xintong Sui1, Ruijun Tian1

  • 1Department of Chemistry, School of Science, Southern University of Science and Technology, Shenzhen 518055, China.

Se Pu = Chinese Journal of Chromatography
|July 6, 2021
PubMed
Summary
This summary is machine-generated.

High-throughput proteomic analysis uses automated sample preparation, micro-flow liquid chromatography-mass spectrometry, and advanced data analysis to accelerate large-scale protein characterization for biomedical research.

Keywords:
chromatographyhigh-throughputmass spectrometry (MS)proteomicssample preparation

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Area of Science:

  • Biochemistry
  • Analytical Chemistry
  • Bioinformatics

Background:

  • Proteomic analysis characterizes proteins, aiding disease mechanism elucidation and biomarker discovery.
  • Mass spectrometry (MS)-based technologies enable comprehensive proteome profiling.
  • Increasing demand for large cohort studies necessitates high-throughput proteomic analysis.

Purpose of the Study:

  • To review state-of-the-art developments in high-throughput proteomic analysis.
  • To highlight advancements in sample preparation, detection, instrumentation, and data analysis.
  • To discuss the challenges and future prospects of high-throughput proteomics.

Main Methods:

  • Automated sample preparation using liquid-handling workstations.
  • Micro-flow liquid chromatography coupled with tandem mass spectrometry (micro-flow LC-MS/MS).
  • High-sensitivity, fast-scanning MS instrumentation, including ion mobility-based MS.
  • Artificial intelligence, deep neural network, and machine learning for data analysis.

Main Results:

  • Automation significantly reduces manual operation variations and sample loss in preparation.
  • Micro-flow LC-MS/MS offers improved robustness and efficiency over nano-flow LC-MS/MS.
  • Advanced MS instrumentation enables rapid, in-depth proteome profiling of numerous samples.
  • AI and machine learning accelerate high-throughput proteomic data analysis.

Conclusions:

  • High-throughput proteomic technologies are crucial for large cohort biomedical research.
  • Advancements in automation, detection, instrumentation, and data analysis are driving the field.
  • These technologies are poised to transform large-scale proteomic analysis in the near future.