An Optimized and High-Throughput Method for Histone Propionylation and Data-Independent Acquisition Analysis for the Identification and Quantification of Histone Post-translational Modifications

Abstract

Histones are DNA binding proteins that allow for packaging of the DNA into the nucleus. They are abundantly present across the genome and thus serve as a major site of epigenetic regulation through the use of post-translational modifications (PTMs). Aberrations in histone expression and modifications have been implicated in a variety of human diseases and thus are a major focus of disease etiology studies. A well-established method for studying histones and PTMs is through the chemical derivatization of isolated histones followed by liquid chromatography and mass spectrometry analysis. Using such an approach has allowed for a swath of discoveries to be found, leading to novel therapeutics such as histone deacetylase (HDAC) inhibitors that have already been applied in the clinic. However, with the rapid improvement in instrumentation and data analysis pipelines, it remains important to temporally re-evaluate the established protocols to improve throughput and ensure data quality. Here, we optimized the histone derivatization procedure to increase sample throughput without compromising peptide quantification. An implemented spike-in standard peptide further serves as a quality control to evaluate the propionylation and digestion efficiencies as well as reproducibility in chromatographic retention and separation. Last, the application of various data-independent acquisition (DIA) strategies was explored to ensure low variation between runs. The output of this study is a newly optimized derivatization protocol and mass spectrometry method that maintains high identification and quantification of histone PTMs while increasing sample throughput.

Figure 1.

Schematic representation of the histone propionylation and sample analysis pipeline.

Figure 2.

Evaluation of the effect of histone protocol variables on histone peptide quantification. A) Total number of peptides identified in each variable. B) Number of peptides with a CV less than 20% or 5% as calculated using observed peak areas or peptide ratios. C) Top 25 most differentially observed peptides across all variables, shown as the average peak area across four replicates. D) Correlation matrix of all variables and all replicates.

Figure 3.

Evaluation of quantitative differences between the old histone propionylation procedure and the new propionylation procedure. A) Total number peptides identified and quantified, and the number of quantified peptides with CV under 20% and 5% at peptide ratio and peak area. B) Heatmap of all peptide ratios of the old and new histone propionylation procedure. C) Heatmap of the top 25 differentially quantified peptide ratios of the old and new histone propionylation procedure. D) Correlation matrix of all replicates of the old and new histone propionylation procedure.

Figure 4.

Analysis of spike-in histone standard peptide subjected to the histone propionylation workflow. A) Calculated rations of each histone standard peptide product in the old and new propionylation procedure. B) Variation of peak area of complete derivatization and digestion products across replicates. C) Retention time reproducibility of complete derivatization and digestion products across replicates.

Figure 5.

Effect of DIA sequential-window and overlapping-window isolation schemes on histone PTM quantitation. A) Number of peptides identified in each isolation scheme and the CV’s of peptide ratios. B) Venn diagram of peptides identified and quantified in the N25 and N34 isolation scheme.