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Updated: Jan 4, 2026

Quantification of Bacterial Histidine Kinase Autophosphorylation Using a Nitrocellulose Binding Assay

Quantification of Bacterial Histidine Kinase Autophosphorylation Using a Nitrocellulose Binding Assay

Published on: January 11, 2017

Proteome Bioinformatics Methods for Studying Histidine Phosphorylation.

Andrew R Jones¹, Oscar Martin Camacho²

¹Department of Functional and Comparative Genomics, Institute of Integrative Biology, University of Liverpool, Liverpool, UK. andrew.jones@liverpool.ac.uk.

Methods in Molecular Biology (Clifton, N.J.)

|November 11, 2019

Summary

This summary is machine-generated.

This chapter details bioinformatics techniques for analyzing histidine phosphorylation (pHis) using LC-MS/MS. It covers data processing, modification site localization, and functional enrichment analysis for modified proteins.

Keywords:

Bioinformatics Database searching Phosphohistidine Phosphoproteomics Proteomics Site localization

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Area of Science:

Biochemistry
Proteomics
Bioinformatics

Background:

Histidine phosphorylation (pHis) is a crucial post-translational modification involved in cellular signaling.
Understanding pHis dynamics requires robust analytical and computational methods.
LC-MS/MS is a powerful technique for identifying and quantifying protein modifications.

Purpose of the Study:

To provide a comprehensive overview of bioinformatics methods for studying histidine phosphorylation (pHis) using LC-MS/MS.
To guide researchers in data processing, modification site localization, and functional interpretation of pHis data.
To enhance the understanding of pHis-related cellular processes.

Main Methods:

Data conversion and preprocessing from mass spectrometry (MS) instruments.
Database searching of MS data for peptide identification and modification site localization.
Statistical scoring for confidence assessment of modification site localization.
Pathway enrichment analysis for functional annotation of pHis-containing proteins.

Main Results:

Established protocols for handling raw LC-MS/MS data specific to pHis studies.
Methods for confident identification and localization of histidine phosphorylation sites.
Framework for inferring functional roles of pHis-modified proteins through pathway analysis.

Conclusions:

Bioinformatics approaches are essential for accurate interpretation of histidine phosphorylation data.
A combination of experimental and computational methods is key to advancing pHis research.
This chapter equips researchers with the necessary tools for effective pHis analysis.