Proteomics

Proteomics is the large-scale study of proteins, including their structures, abundance, functions, interactions, modifications, and changes under different biological conditions. The complete set of proteins produced by a cell, tissue, organism, or biological system is commonly called its proteome.

Proteomics is closely related to genomics, bioinformatics, molecular biology, biochemistry, analytical chemistry, and systems biology. While genomics studies genetic information, proteomics focuses on the proteins that are actually present and functioning within a biological system.

Proteins can vary substantially between cell types and can change in response to development, disease, environmental conditions, nutrition, drugs, or other influences. A single gene can also contribute to multiple protein forms through processes such as alternative splicing and post-translational modification. Proteomics therefore provides information that cannot always be predicted from DNA sequence alone.

This topic page is for organizing the development of proteomics related content on this wiki. Please, feel free to improve upon what you see; your contributions will be greatly appreciated.

Major areas of proteomics

The proteomics workflow

A proteomics experiment can involve several stages. The exact workflow depends on the research question.

A simplified workflow may include:

Select a biological sample.
Extract proteins from the sample.
Separate or purify proteins.
Prepare proteins or peptides for analysis.
Analyze the sample using instruments such as a mass spectrometer.
Identify proteins using computational methods.
Quantify proteins when appropriate.
Analyze and interpret the resulting data.
Compare findings with other experiments or biological information.

Careful sample preparation is important because proteins differ in abundance, size, charge, stability, solubility, and chemical properties.

Protein separation and purification

Proteins often need to be separated or purified before analysis.

Methods can include:

Chromatography
Gel electrophoresis
Affinity purification
Ion-exchange chromatography
Size-exclusion chromatography
Liquid chromatography

Affinity methods can take advantage of specific molecular interactions. For example, proteins engineered with a histidine tag can be purified using materials that bind the histidine-containing region.

This connects directly with the existing learning project Chromatography adsorbent and purification of histidine tagged proteins.

Protein purification can itself be an educational project because learners can investigate experimental design, buffers, binding conditions, contamination, protein concentration, and methods used to determine whether purification was successful.

Mass spectrometry

Mass spectrometry is one of the most important technologies used in modern proteomics.

Proteins are commonly broken into smaller fragments called peptides. These peptides can then be separated and analyzed according to properties related to their mass and electrical charge.

The resulting measurements can be compared with protein sequence databases to help identify which proteins were present in the original sample.

Mass spectrometry can also be used to investigate:

Relative protein abundance.
Protein modifications.
Protein complexes.
Differences between biological samples.
Changes over time.

Modern proteomics experiments can generate large amounts of data, making computational analysis an important part of the field.

Quantitative proteomics

Quantitative proteomics attempts to determine how much of particular proteins are present or how protein abundance differs between samples.

For example, researchers might compare:

Healthy and diseased tissue.
Treated and untreated cells.
Different stages of development.
Different environmental conditions.
Different organisms or strains.

Quantitative information can help identify biological pathways that become more or less active under particular conditions.

Researchers must still consider experimental variability, measurement limitations, sample preparation, and statistical analysis when interpreting the results.

Protein modifications

Proteins can be chemically modified after they are produced.

These post-translational modifications can affect protein activity, location, stability, interactions, or signaling.

Examples include:

Phosphorylation
Glycosylation
Acetylation
Methylation

Ubiquitination
Lipid modification
Proteolytic cleavage
Disulfide bond formation

Studying these modifications can be important because two proteins with the same underlying amino acid sequence may behave differently depending on their modifications.

Proteomics and bioinformatics

Bioinformatics is important for interpreting proteomics data.

Software can be used to:

Match measured peptides with protein sequences.
Search protein databases.
Compare samples.
Analyze protein abundance.
Identify biological pathways.
Study protein interactions.
Visualize experimental results.
Integrate proteomics with genomic or transcriptomic data.

Proteomics therefore provides a useful example of how laboratory biology and computer science increasingly overlap.

Students interested in proteomics can benefit from learning basic statistics, databases, scripting, data visualization, and reproducible research methods.

Applications of proteomics

Proteomics has applications in many areas of biological and biomedical research.

Possible applications include:

Studying disease mechanisms.
Searching for potential biomarkers.
Understanding cellular signaling.
Investigating drug responses.
Studying microorganisms.
Characterizing protein complexes.
Comparing tissues or cell types.
Studying aging and development.
Investigating agriculture and plant biology.
Understanding interactions between genes, proteins, and the environment.

Proteomic results generally need to be interpreted along with other biological information rather than treated as isolated measurements.

Learning projects and resources

Learning materials and learning projects can be used by multiple departments. Please cooperate with other departments that use the same learning resource.

Remember, this wiki has adopted the "learning by doing" model for education. Lessons should center on learning activities for participants on this wiki.

Also, select a descriptive name for each learning project. Learning projects can be listed in order by Meta:Naming conventions.

About proteomics
Chromatography adsorbent and purification of histidine tagged proteins
Search
Compare genomics, transcriptomics, and proteomics.
Research how mass spectrometry can be used to identify proteins.
Examine a publicly available proteomics dataset and identify what types of measurements it contains.
Design a hypothetical experiment comparing protein abundance between two biological conditions.
Research several forms of chromatography used for protein purification.
Create a diagram showing the steps in a basic proteomics workflow.
Study how protein databases are used during proteomic analysis.

Discussion questions, essay ideas, and learning related AI prompt ideas

What information can proteomics provide that genomics cannot?
Why does the proteome change more rapidly than the genome?
What are the major challenges involved in measuring very low-abundance proteins?
How does chromatography contribute to proteomics?
Why is mass spectrometry particularly useful for protein analysis?
What are the advantages and limitations of quantitative proteomics?
How can bioinformatics improve interpretation of proteomic data?
What role do post-translational modifications play in protein function?
Ask an AI system to explain a basic proteomics workflow, then verify each major step using biological references.
Ask an AI system to compare mass spectrometry with gel-based approaches to protein analysis.
Design a learning project that combines protein purification, mass spectrometry, and bioinformatics.
How could proteomics contribute to research involving disease, aging, agriculture, or biotechnology?