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Sulfur Assimilation

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Sulfur is an essential element in biological systems, contributing to synthesizing key biomolecules, including amino acids such as cysteine and methionine, and cofactors such as coenzyme A and biotin. Microorganisms primarily assimilate sulfur as sulfate (SO₄²⁻) from the environment, which must undergo a series of biochemical transformations before it can be incorporated into cellular components. As sulfate is highly oxidized, it must undergo assimilatory sulfate reduction to...

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Author Spotlight: Advancing Structural and Biochemical Studies of Proteins Through Thermal Shift Assays

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Published on: August 9, 2024

Selenocysteine: Wherefore Art Thou?

David Fenyö¹, Ronald C Beavis²

¹Center for Health Informatics and Bioinformatics, New York University Medical School , 227 East 30 Street, New York, New York 10016, United States.

Journal of Proteome Research

|December 19, 2015

Summary

Selenocysteine, an amino acid in many research proteins, was missed in mass spectrometry data. A simple search parameter change now allows its confident identification in existing proteomics datasets.

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Area of Science:

Biochemistry
Proteomics
Molecular Biology

Background:

Selenocysteine is a unique amino acid incorporated into proteins during translation.
Proteomics studies often overlook selenocysteine due to limitations in mass spectrometry data analysis.
Many model organisms contain abundant selenoprotein genes crucial for biomedical research.

Discussion:

Tandem mass spectrometry (MS/MS) analysis failed to identify peptides containing selenocysteine.
The chemical properties of selenocysteine were responsible for its exclusion during standard data processing.
Understanding the basis of exclusion enabled a straightforward solution.

Key Insights:

A simple adjustment to search parameters in proteomics data analysis is sufficient for selenocysteine identification.
No modifications to experimental procedures or sample preparation are necessary.
This finding significantly enhances the utility of existing proteomics data.

Outlook:

Improved selenocysteine detection will advance research in selenoprotein function and biology.
This method can be applied to re-analyze vast amounts of previously generated proteomics data.
Facilitates a deeper understanding of biological processes involving selenocysteine.