Chapter Six - Investigating Histone Acetylation Stoichiometry and Turnover Rate
Introduction
Histones are subject to a myriad of covalent posttranslational modifications (PTMs), especially on the lysine-rich N-terminal tails. The PTMs of histones, together with the differential deposition of histone variants, affect chromatin structure and play an essential role in regulating transcription. Particularly, acetylation of lysine residues on histones neutralizes the positive charge, resulting in a more open and accessible chromatin conformation. Additionally, lysine acetylation can serve as a recognition “mark” for the recruitment of acetyl-lysine-binding domains, thus recruiting large multisubunit complexes that regulate transcription and other DNA-templated processes. Dysregulation of histone PTMs is associated with many human diseases, such as cancer and diabetes (Berdasco and Esteller, 2010, Leroy et al., 2013, Mellor et al., 2015, Miao et al., 2014).
Mass spectrometry (MS)-based methods have provided powerful tools to analyze histone PTM states and to identify novel histone modifications (Arnaudo and Garcia, 2013, Dai et al., 2014, Tan et al., 2011). Bottom-up approaches for quantifying histone modifications utilize chemical labeling of the unmodified lysine on histones, allowing trypsin-digested histone peptides to be resolved by reverse-phase chromatography and analysis by MS. With this approach, it has been possible to quantify different histone PTM states, and the fraction of a lysine that is modified with a particular mark, i.e., stoichiometry. Measuring the stoichiometry of a given modification is essential to interpret the biological significance of that modification. Recently we reported a method for quantifying site-specific acetylation stoichiometry (Baeza et al., 2014).
Histone PTMs are dynamically regulated by many enzyme complexes that “read,” “write,” or “erase” histone marks. The addition of histone PTMs requires small metabolites as substrates. For the case of acetylation, the acetyl donor is acetyl-CoA, a central metabolite produced by multiple metabolic pathways including glucose metabolism, fatty acid β-oxidation, and amino acid degradation. The acetyl group is directly transferred onto lysine residues by various histone acetyltransferases (HATs). Deacetylation occurs through both NAD+-dependent sirtuins and NAD+-independent histone deacetylases (HDACs). The direct transfer of the acetyl moiety from acetyl-CoA to lysine residues allows for the quantification of histone acetylation turnover rate by isotopic labeling with a metabolic precursor of acetyl-CoA and following the kinetic incorporation of the labeled acetyl group onto histone. Quantifying the turnover rate of histone PTMs provides a dynamic view of epigenetic regulation and is critical to understanding the mechanisms by which histone PTMs are controlled under different biological conditions. For example, analyzing the dynamic change of histone PTMs on newly replicated DNA compared to parental histones during mitotic cell division revealed the different modes that histone marks propagate (Alabert et al., 2015), quantifying H3K9 methylation turnover in the presence or absence of H3K14 acetylation revealed the influence of neighboring PTM on the modification of a specific site (Zee et al., 2010), and measuring acetylation turnover rate with HDAC inhibitors demonstrated the contribution of these HDACs in controlling histone acetylation (Evertts et al., 2013, Zheng et al., 2013).
A challenge in quantifying histone PTM turnover with metabolic labeling is that many precursors, which generate metabolites used as substrates for histone modifications, also result in the labeling of amino acids that can subsequently be incorporated into newly synthesized histone proteins and generate multiple isotopic permutations of the same protein. In the case of acetylation, glucose is the precursor that contributes to the majority of acetyl-CoA production in most mammalian cell lines, while uniformly labeled 13C-glucose ([U-13C] glucose) also labels alanine, aspartate, asparagine, serine, and glutamate within a relatively short-time period. The labeling of amino acids in addition to acetylation complicates the MS analysis and can make it difficult to quantify the overall histone acetylation rate that includes newly synthesized histone.
In addition to investigating site-specific acetylation stoichiometry and turnover rate under various conditions, other important questions have been raised in recent reports concerning histone PTMs as a whole, and its connection with metabolism: How much of the acetyl group is in the covalently bonded form on histones compared to free acetyl-CoA? Does this covalently modified form serve as a reserve pool for acetyl metabolism or a substrate for acetate production (McBrian et al., 2013)? And does the acetylation turnover on histones pose a significant demand for acetyl-CoA supply, or does the flux through protein PTMs impact cellular metabolism by consuming or producing key metabolites (Martinez-Pastor, Cosentino, & Mostoslavsky, 2013)? To answer these questions, as well as to understand the influence of different metabolic states on protein PTMs in general, a method to quantify overall histone PTM stoichiometry and turnover rate is needed.
In this chapter, we describe methods to quantify both overall, as well as site-specific, histone acetylation turnover with metabolic labeling. This method specifically traces the labeling kinetics of acetylation, regardless of the labeling of amino acids on histone peptides. We also describe methods to quantify overall and site-specific stoichiometry of histone acetylation. The stoichiometry together with the turnover rate provides a comprehensive characterization of histone acetylation under the investigated condition.
Section snippets
General Experimental Design
The histone acetylation rate is analyzed by feeding cells an isotopic-labeled precursor of acetyl-CoA and following the dynamic incorporation of the labeled acetyl group onto histones. The observed labeling of histone acetylation is dependent upon the actual rate of histone acetylation as well as the labeling kinetics of acetyl-CoA from its isotopic precursors, which is usually not negligible compared to histone-labeling rate. Thus, to accurately quantify the histone acetylation rate, it is
Analyzing Metabolite Labeling
To analyze the labeling time course of acetyl-CoA and free amino acids from metabolite extraction, many HPLC–MS methods are available (Lu et al., 2008, Lu et al., 2010). Our current setup is a Thermo Q-Exactive Orbitrap mass spectrometer coupled to a UPLC (Dionex 3000). Metabolites are separated with an 1.7 μm particle 2.1 × 100 mm ACQUITY UPLC® BEH C18 column, with a gradient of solvent A (95% H2O, 5% methanol, 10 mM tributanolamine, 9 mM acetate, pH 8.2) and solvent B (100% methanol) at 0.2 mL/min
Analyzing Small-Molecule Data
LC–MS data from metabolite analysis and completed histone digest are analyzed using metabolomics analysis and visualization engine (Melamud, Vastag, & Rabinowitz, 2010). For histone digests, signals in the procedure blank indicate the level of amino acids that result from enzyme self-digestion. This signal should be a very small fraction compared to the corresponding signal in histone samples. The procedure blank signals are deducted in the data analysis. For all labeling data, we adjust for
Discussion and Perspective
We have discussed methods to quantify the overall and site-specific dynamics and stoichiometry of histone acetylation. These approaches give a comprehensive characterization of histone acetylation under a given condition. And because the abundance and kinetics of acetyl-CoA are measured at the same time, these methods allow a researcher to relate histone acetylation to acetyl-CoA metabolism. This approach provides a useful tool to investigate the impact of different factors on histone
Acknowledgments
We would like to thank Kimberly Krautkramer and Dr. James Dowell for helpful discussions and generous help with the PIC labeling. We would also like to thank the UW-Madison Biotechnology Center Mass Spectrometry/Proteomics Facility for use of the Mascot server. This work was supported, in whole or in part, by National Institutes of Health (NIH) Grant GM065386-14 (J.M.D.), GM059785-15 (J.M.D.), NIH National Research Service Award T32 GM007215 (J.B.), and National Science Foundation (NSF) GRFP
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