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. 2019 Mar 1;5(4):663–670. doi: 10.1021/acscentsci.9b00044

A Chemical Genetic Method for Monitoring Genome-Wide Dynamics of O-GlcNAc Turnover on Chromatin-Associated Proteins

Ta-Wei Liu 1, Mike Myschyshyn 1, Donald A Sinclair 1, David J Vocadlo 1,*
PMCID: PMC6487452  PMID: 31041386

Abstract

graphic file with name oc-2019-000448_0004.jpg

Advances in DNA sequencing are enabling new experimental modalities for studying chromatin. One emerging area is to use high-throughput DNA sequencing to monitor dynamic changes occurring to chromatin. O-Linked N-acetylglucosamine (O-GlcNAc) is a reversible protein modification found on many chromatin-associated proteins. The mechanisms by which O-GlcNAc regulates gene transcription are of high interest. Here we use DNA precipitation methods to enable monitoring time-dependent turnover of O-GlcNAc modified proteins associated with chromatin. Using an antibody-free chemical reporter strategy to map O-GlcNAc to the genome, we performed time course metabolic feeding experiments with wild-type Drosophila larvae alongside larvae lacking O-GlcNAc hydrolase (OGA), which are accordingly unable to remove O-GlcNAc. Analysis of resulting next-generation DNA sequencing data revealed that O-GlcNAc on chromatin-associated proteins at most genomic loci is processed with a half-life in hours. Notably, loss of OGA only increases this half-life by ∼3-fold. Interestingly, a small set of genomic loci are particularly sensitive to loss of OGA. In addition to these observations and new strategies to permit monitoring turnover of O-GlcNAc on chromatin, we also detail methods for coded blinding of samples alongside new normalization strategies to enable time-resolved, genome-wide analyses using chemical genetic methods. We envision these general methods will be applicable to diverse protein and nucleic acid modifications.

Short abstract

Timed feeding of metabolic precursors, followed by click chemistry and next-generation sequencing, enables monitoring time-resolved changes in post-translational modifications in a genome-wide manner.

Introduction

Hundreds of proteins within the nucleus and cytoplasm of multicellular eukaryotes are modified with N-acetylglucosamine (GlcNAc) β-O-linked to serine and threonine residues (O-GlcNAc).1−3 Many proteins modified with O-GlcNAc are known, but the roles of this modification remain largely undefined. O-GlcNAc is installed by O-GlcNAc transferase (OGT) onto target proteins using uridine diphosphate GlcNAc (UDP-GlcNAc) as a donor sugar. The glycoside hydrolase O-GlcNAcase (OGA) is responsible for removing O-GlcNAc. Both OGT and OGA are found in all tissues and are essential for development in mammals, but only OGT is essential in Drosophila.1−3 Notably, O-GlcNAc levels are regulated by the action of OGT and OGA enabling this modification to cycle on and off proteins. The reversible nature of O-GlcNAc is hypothesized to contribute to nutrient-sensitive regulation by O-GlcNAc modified proteins.3−6

The Drosophila melanogaster gene known as super sex combs (sxc) encodes the fly homologue of mammalian OGT.7,8sxc was identified as a polycomb group (PcG) protein through its role in silencing the set of developmentally important HOX genes.9 A wide range of nuclear proteins within Drosophila have been found to be O-GlcNAc modified, including several other PcG proteins.7,10,11 Motivated by interest in the mechanisms by which modification of nuclear proteins by O-GlcNAc regulates gene expression in fly and in mammals,12 we developed a chemical method to enable genome-wide mapping of O-GlcNAcylated proteins.10 This method circumvents the use of antibodies and lectins that are typically used in chromatin immunoprecipitation followed by sequencing experiments (ChIP-seq). In this chemical method (Figure 1a), proteins from live Drosophila are metabolically labeled with N-azidoacetylgalactosamine (Ac4GalNAz),13 a precursor that is assimilated by cellular metabolic pathways to form uridine diphosphate N-azidoacetylglucosamine (UDP-GlcNAz), which is installed onto proteins by OGT. Downstream bioorthogonal chemistry enables enrichment of O-GlcNAz-modified proteins, including those bound to genomic DNA fragments that can be sequenced by next-generation methods. This chemoselective chromatin precipitation followed by sequencing strategy, which we call O-GlcNAc-seq, revealed a diverse set of genomic loci bearing O-GlcNAc.10

Figure 1.

Figure 1

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Validation of TC Ac4GalNAz strategy. (a) Visual representation of TC Ac4GalNAz feeding workflow. WT and OGA-null Drosophila embryos were incubated on 150 μM Ac4GalNAz media or DMSO control for 36 h. During this time, UDP-GalNAz is converted to UDP-GlcNAz by Drosophila UDP-galactose 4′ epimerase (GalE), and OGT installs GlcNAz onto target proteins using UDP-GlcNAz as the donor sugar. 36 h later, the resulting larvae were collected from the Ac4GalNAz media and transferred to Ac4GalNAz free media (DMSO). The larvae were grown on Ac4GalNAz free media for 0, 4, 8, 12, 16, 20, 24, and 36 h post transfer and snap frozen. These larvae samples were used for biochemical studies and TC O-GlcNAc-seq Bioinformatics analysis of the sequencing data was then performed. (b) Timeline of Ac4GalNAz metabolic labeling performed in WT and OGA-null Drosophila larvae. Synchronized parents were given a 2 h window to lay eggs on Ac4GalNAz-containing media and non-Ac4GalNAz media for the no feed control. After 36 h of growth, larvae were collected (0 h and no feed control) or transferred onto non-Ac4GalNAz media. (c) Immunoblots of WT and OGA-null TC Ac4GalNAz Drosophila larvae. Time, in hours, after transfer of Ac4GalNAz fed larvae to non-Ac4GalNAz containing media shown above each lane for WT and OGA-null Drosophila larvae. Proteins were extracted and conjugated by click chemistry to biotin and blotted using streptavidin (Strvn, top panel). (d) O-GlcNAc (CTD110.6) blot of TC Ac4GalNAz fed larvae. The lower panels for each blot shows actin loading control (the band is between 55 and 40 kDa).

Continuing reductions in the costs of sequencing are permitting new data-intensive experimental modalities that are allowing quantitative analysis of the genome. One emerging area is to understand the time-dependent changes that occur to the genome using a series of ChIP-seq experiments performed at different times. By quantifying the number of sequencing reads at each locus of interest at each time point, insights into time-dependent changes in chromatin-associated proteins binding to the genome can be uncovered.14 Using new chemistries in combination with sequencing to study chromatin has permitted time course (TC) studies to monitor proteins, DNA modifications, and DNA lesions.15−17 Although chemoselective labeling strategies for many protein modifications are rapidly advancing, few such methods have been shown to enable mapping protein modifications to chromatin.10 Further, despite the crucial roles played by protein modifications in regulating gene expression,12,18 no methods have been developed to enable monitoring time-resolved turnover of protein modifications on chromatin-associated proteins.

Here, we describe a combined chemical genetic method to examine time-resolved changes to post-translational modifications of chromatin-associated proteins. We demonstrate the use of O-GlcNAc-seq in a TC study in live Drosophila to investigate the turnover of O-GlcNAc on chromatin-associated proteins. We also describe a series of quantitative controls for this chemoselective O-GlcNAc-seq method as well as methods for blinding of samples by using internal codes. Given the essential roles played by nutrient-regulated O-GlcNAc in controlling gene expression,3,4,12 coupled with the beneficial effects of modulating OGA activity in various disease models,19,20 methods to understand its dynamic nature on the genome should prove useful. Here, using wild-type (WT) and OGA knockout (OGA-null) flies in combination with TC O-GlcNAc-seq, we determine relative rates of turnover of O-GlcNAc on the genome and show that different genomic loci vary in their behavior.

Results and Discussion

We designed our experiments to monitor the loss of O-GlcNAz through both OGA-mediated cleavage of O-GlcNAc as well as protein turnover in the larval stage of Drosophila. We first cultivated two groups of synchronized Drosophila whose egg-laying times were within 2 h. The experimental group was cultured on Ac4GalNAz containing media and the control group on Ac4GlcNAz free media (control media). After 36 h, larvae from both groups were harvested, yielding the no feed control and the 0 h time point larvae. Additionally, larvae from the experimental group were transferred to control media and allowed to grow for 4, 8, 12, 16, 20, 24, or 36 h and then harvested (Figure 1a,b). Because the loss of the O-GlcNAc modification from chromatin-associated proteins can be driven by the action of OGA as well as dissociation of proteins and their downstream degradation, we prepared both WT and OGA-null21 larvae using this Ac4GalNAz feeding timeline (Figure 1b). In this way, we could compare the groups to distinguish between the rates of degradation of modified chromatin-associated proteins and the rates of OGA-catalyzed cleavage of O-GlcNAc (O-GlcNAc turnover) on chromatin-associated proteins.

As a first step to validate this approach, we used streptavidin immunoblots of biotin-conjugated O-GlcNAz modified proteins from larval lysates (Figure 1c and Figure S1a, replicates) to monitor the time-dependent changes to overall labeling of proteins following our Ac4GalNAz feeding timeline. As expected, we observed a time-dependent decrease in the levels of O-GlcNAz modified proteins, relative to actin, that is slower in OGA-null flies as compared to WT flies. We attribute this observation to a loss of OGA enzyme (Figure S1b,c), which blocks the ability of these flies to remove O-GlcNAz from labeled proteins. We reasoned that the observed decrease in OGA-null flies stems from the degradation of these proteins and dilution effects from cell division, whereas in WT flies the decrease stems from a combination of OGA activity, protein degradation, and dilution effects. Notably, the marked decline in signal over time arises only from a reduction of the levels of O-GlcNAz modification since levels of endogenous O-GlcNAc remain constant as assessed using a pan-specific anti-O-GlcNAc antibody (Figure 1d). As expected, O-GlcNAc levels are higher in OGA-null flies (Figure 1d). Accordingly, these immunoblots confirmed that OGA can hydrolyze O-GlcNAz and supported pursuing TC O-GlcNAc-seq experiments to examine the turnover of O-GlcNAcylated proteins associated with the genome.

To evaluate the kinetics of O-GlcNAc turnover on DNA bound proteins using O-GlcNAc-seq, we reasoned that it would be important to accurately quantify the DNA recovered from immunoprecipitation of O-GlcNAz modified proteins. Indeed, one underappreciated aspect in the design of ChIP-seq experiments is that the quantitation of sequencing reads from one sample to the next requires replicates to obtain statistically significant data and, importantly, an internal control to normalize the number of reads and account for complex sample handling steps. Traditional ChIP-seq normalization strategies, including scaling to total sequencing reads and quantile normalization, are biased when it comes to accurately quantifying sequencing reads.22 We therefore opted to use an exogenous spiked-in reference genome as a normalization approach.23,24 To this end, we prepared azidohomoalanine (AHA)-labeled yeast cells (Figure S2) and added AHA-tagged yeast chromatin to each TC Drosophila chromatin sample. All azide-modified proteins were then precipitated. Since the same amount of AHA labeled yeast chromatin was added to each sample, we were able to scale the Drosophila sequencing reads to the sequencing reads for the yeast spiked-in control (Figure 2a, Figure S3, Table S1). It is noteworthy that this chemoselective AHA spike-in strategy is likely more accurate than previously reported techniques that use two organism-specific antibodies because here there is only one precipitation step for proteins bound to each of the two genomes, and so the control accounts for variations in all sample handling steps.

Figure 2.

Figure 2

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TC O-GlcNAc-seq normalization, blinding procedure, and peak calling strategy. (a) DNA reads aligned to Saccharomyces cerevisiae (sacCer3) and D. melanogaster (dm3) shown in log scale within each time point (collection times in hours indicated on x-axis; NF = DMSO control) before and after normalization to DNA reads aligned to the yeast genome. Data shown here are for the first replicate from WT Drosophila. (b) Verification of spiked-in gBlock fragment mixes (G1, G2, and G3) within each time point for the first replicate from WT Drosophila. The intensity of the color indicates the percent aligned reads of the total gBlock fragments. The results match very closely to the expected ratios, indicating successful blinding. (c) Heatmap of peak centers and 1000 bp upstream and downstream of 1883 loci that overlap between WT (top panels) and OGA-null (bottom panels) Drosophila at 0 h (left panels) and 36 h (right panels).

In parallel, we also developed a strategy to efficiently blind the ChIP-seq protocol using minimal amounts of different mixtures of synthetic double-stranded DNA probes. A separate probe mixture was added to each TC O-GlcNAc-seq sample, and the sequencing results from each sample showed a highly similar identity to the probe mixtures added to each sample, indicating proper coding of blinded samples (Figure 2b, Figure S4, Table S2). After sequencing two independent replicates from each time point in the TC O-GlcNAc-seq experiment in both WT and OGA-null, we normalized the number of sequenced Drosophila reads using the spiked-in yeast controls by alignment to the yeast genome.25,26 Genomic regions bearing O-GlcNAz modified proteins were determined by quantifying peaks, which represent a large number of overlapping sequencing reads observed at specific genomic loci, from the experimental samples at 0 h as compared to the vehicle fed Drosophila. Using this strategy, we identified a total of 1883 peaks present in both WT and OGA-null TC O-GlcNAc-seq Drosophila samples. We also observed a time-dependent decrease in peak height, the rate of which was greater in WT as compared to OGA-null flies (Figure 2c), which is consistent with our immunoblot experiments (Figure 1). Before analyzing the effects of OGA knockout on the density of sequencing reads at loci over time, we aimed to validate the strategy we used to identify peaks. We compared the genes encompassing the 1883 O-GlcNAz peaks in larvae we identified here with those identified in both Drosophila pupae and S2 cells. We found that over 50% of the genes overlapped with genes found to contain O-GlcNAcylated proteins in pupae and S2 cells (Figure S5a). Furthermore, there were a large number of genes encompassing polycomb repressive elements (PREs), which are loci that are bound by known O-GlcNAc modified PcG proteins such as Ph and Pho.7,10,11 Accordingly, these correlations support the peak identification strategy we used here.

Using FlyBase,27 we retrieved genes categorized into different levels of transcription within the larvae and pupae stages of Drosophila.28 We then intersected the genes found at genomic loci enriched in O-GlcNAc at each stage with the different groups of genes from FlyBase. Comparing the observed intersection of O-GlcNAc bound genes at each transcript category to all genes in the genome, we calculated the Chi-squared observed over expected probabilities (Figure S5b). These probabilities indicate which gene transcript categories are significantly enriched or depleted in O-GlcNAc bound proteins at the genomic loci encoding these genes. We observed that O-GlcNAzylated proteins are lower at genes that are deficiently expressed and enriched at those that are moderately highly expressed in both larvae and pupae. One might expect that PRE genes targeted by O-GlcNAcylated PcG proteins would be silenced, and thus have low expression levels, resulting in an enrichment rather than a depletion of low expressed genes. These data, however, suggest that O-GlcNAcylated proteins have roles predominantly in gene activation, which is consistent with biochemical studies that have discovered O-GlcNAc on transcriptional activators29,30 and RNA polymerase II.31 Satisfied with the accuracy of our peak calling strategy, we set out to analyze the TC data sets in detail. Visual inspection of peaks over time revealed that OGA-null Drosophila retained signal from the O-GlcNAz modification (Figure 3a and Figure S6) longer than WT Drosophila. We used three different analytical tools to investigate the differences in O-GlcNAc turnover in WT and OGA-null flies at a genome-wide level. First, we modeled TC data at each peak to sigmoidal curves using time-dependent ChIP-seq analyzer (TDCA).14 This strategy revealed a genome-wide heatmap of sequencing reads across time that showed OGA-null flies retain signal from O-GlcNAz modified proteins to a greater extent as compared to WT flies (Figure 3b), which supports the average sigmoidal curve from OGA-null TC data changing from being concave to convex along the time points, indicative of O-GlcNAz modification half-life (Figure 3c). The average O-GlcNAz modification half-life, calculated by the modeled inflection points, was found to be 4.6 ± 0.9 h for WT and 14.4 ± 1.6 h for OGA-null Drosophila.

Figure 3.

Figure 3

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OGA-null Drosophila retains O-GlcNAz genome-wide longer compared to WT Drosophila. (a) Tracks WT and OGA-null Drosophila Ac4GalNAz TC experiment. The gene bithoraxoid (bxd) (chr3R:12,589,000-12,591,000) is shown in the left box and charlatan (chn) (chr2R:11,015,000-11,017,000) is to the right. Time points are labeled to the left in hours, and NF indicates the no feed control. (b) Normalized heatmap of sequencing coverage at each of the 1883 loci that overlap between WT and OGA-null Drosophila using TDCA. (c) Sigmoidal curve fit of WT (circles) and OGA-null (triangles) Drosophila using TDCA. Error bars show standard deviation (SD) from biological replicates (n = 2, independent-samples t test, *p < 0.05, **p < 0.01, ***p < 0.001). (d) Peak intersection across time quantified using the Jaccard coefficient. The heatmap is divided into diagonal sections with WT and OGA-null TC experiments on opposite sides of the diagonal. (e) OGA ChIP-seq analysis in Drosophila. Gene overlap between OGA ChIP-seq (black circles) and O-GlcNAc-seq in Drosophila cells (S2 cells; red circle), larvae (blue circle), and pupae (green circle).

We also performed a Jaccard analysis32 of the samples. In this strategy, peaks from each time point, individually quantified using the vehicle control samples, were intersected with each other, where the intersection between data sets was reduced to a single value called the Jaccard coefficient. A high Jaccard coefficient indicates a more significant intersection. We observed a high degree of intersection within early time points which deteriorated at late time points for both WT and OGA-null TC O-GlcNAc-seq experiments (Figure 3d). OGA-null samples had a less drastic decrease in Jaccard coefficients over time as compared to WT samples. Finally, we used Diffbind33 to measure the differences in sequencing coverage across time points in WT and OGA-null O-GlcNAc-seq data sets.34 The results of the Diffbind analysis are consistent with the Jaccard analysis (Figure S7). We observed a higher similarity between adjacent time points as compared to those that were farther apart. Also, as expected, OGA-null data retained a more significant overall similarity between early and late time points as compared to WT data. Overall, each of these analysis strategies supports the quality of the TC data sets and indicates that OGA acts on O-GlcNAc modified proteins while they are associated with the genome.

In addition to comparing global changes in O-GlcNAc modified proteins bound to the genome for WT and OGA-null Drosophila, we also investigated whether the loss of OGA impacted specific loci to a greater extent than others. To do this, we calculated the standard scores of the O-GlcNAc modification half-life values obtained using TDCA. We reasoned that loci with significantly (p < 0.05) high standard scores are the most resistant to removal of O-GlcNAz by OGA. Only the WT TC experiment was used to calculate these scores given that the depletion of reads over time in the OGA-null TC experiment should only be indicative of the protein half-lives rather than O-GlcNAc modification half-life. Surprisingly, only about 3% (56/1883) of the TC O-GlcNAc-seq peaks exhibited an observable OGA resistant behavior (Figure S8 and Table S3). There is longer retention of O-GlcNAz at these OGA resistant loci, and, as expected, these loci still show a faster half-life compared to the OGA-null TC data set. We observed a significant depletion of these OGA resistant loci at gene bodies and exons compared to all the O-GlcNAc-seq peaks, which was not observed for the non-OGA resistant loci (Figure S9). This suggests that O-GlcNAc modified proteins bound to these OGA resistant loci may have specific molecular and/or biological functions. We report the overlap of nonredundant FlyBase Drosophila genes at these OGA resistant loci as well as the remaining 1827 loci (Table S4). Next, using traditional ChIP-seq, we found that the distribution of OGA across the genome overlaps significantly with the distribution of O-GlcNAc modified proteins. We found more than 30% of genes to which O-GlcNAcylated proteins are bound overlapped with genes bound by OGA in Drosophila cells (S2 cells; 39%), larvae (43%), and pupae (35%) (Figure 3e and Figure S10). The high correlation of OGA and O-GlcNAz occupancy supports the accuracy of the O-GlcNAc-seq method and suggests that OGA acts directly on proteins bound to the genome. Further, the presence of OGA at many loci, including those defined here as resistant to OGA, suggests that OGA may also have noncatalytic functions at some loci.35

Notably, recent studies detected and identified a GlcNAc modification on cysteine of a small set of proteins, suggesting the possible occurrence of S-GlcNAcylation and artificial S-GlcNAzylation in mammalian cells.36,37 Because S-GlcNAc is not cleaved by OGA,38 the fact that the Ac4GalNAz labeling in Drosophila is sensitive to OGA (Figure S11) and the low background labeling in OGT-null Drosophila10 supports that this particular chemical reporter mainly labels O-GlcNAc, which is consistent with other reports using Ac4GalNAz.39 One additional factor to consider is that protein degradation rates may vary between WT and OGA-null Drosophila, which may lead to variations in the estimated rate of turnover of O-GlcNAc on proteins as defined here. Given, however, that OGA-null Drosophila show no obvious defects at the developmental stages described here, we expect any such possible differences would be subtle. Nevertheless, it will be interesting in future studies to examine protein degradation in OGA-null Drosophila at various developmental stages.

Safety

No unexpected or unusually high safety hazards were encountered.

Conclusion

In summary, this chemoselective metabolic feeding strategy, exemplified here by our TC O-GlcNAc-seq study, enables monitoring turnover of modifications on proteins associated with the genome. We further illustrate effective methods for blinding and normalization of sequencing reads from large numbers of sequencing samples. More specifically, these data indicate that OGA has broad activity on a wide range of chromatin-associated proteins as manifest by the relatively small (∼3%) number of OGA resistant loci. These data support OGA playing critical roles in regulating the function of chromatin-bound proteins11,30 and open the door to analysis of the roles of O-GlcNAc at OGA-resistant loci.

We envision that this approach could be used to examine the effects of varying nutrient availability or for studies in various different genetic knockout models. Such research should provide insight into nutrient-regulated gene expression, the involvement of O-GlcNAc in various diseases, as well as defining the mechanisms by which OGA and OGT inhibitors might confer therapeutic benefit. More broadly, the decreasing costs of sequencing coupled with the many metabolic feeding strategies that have been developed to monitor a wide range of protein or nucleotide modifications15,40−44 suggest that this general chemical genetic TC metabolic labeling strategy, and the associated methods we disclose here for normalization and analysis, will be of growing interest as a ChIP-seq methodology, as researchers from diverse fields can apply the methods highlighted here for their specific modifications of interest to further efforts to understand dynamic genome modifications and their roles in regulating cell physiology.

Acknowledgments

Financial support from the Mizutani Foundation for Glycoscience (D.V.&T.-W.L., MIZUTANI - 180165), Tokyo, Japan, the Natural Sciences and Engineering Research (D.V., NSERC, RGPIN/-2015-05426), and the Canadian Institutes of Health Research (D.V., CIHR, PJT - 148732) is gratefully acknowledged. D.V. acknowledges the Canada Research Chairs program for a Tier I Canada Research Chair in Chemical Glycobiology.

Supporting Information Available

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acscentsci.9b00044.

  • Supporting experimental methods (PDF)

  • Supporting tables (XLSX1, XLSX)

Author Contributions

† T.W.L. and M.M. contributed equally.

The authors declare no competing financial interest.

Supplementary Material

oc9b00044_si_001.pdf (1.4MB, pdf)
oc9b00044_si_002.xlsx (102.9KB, xlsx)
oc9b00044_si_003.xlsx (32.7KB, xlsx)

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oc9b00044_si_001.pdf (1.4MB, pdf)
oc9b00044_si_002.xlsx (102.9KB, xlsx)
oc9b00044_si_003.xlsx (32.7KB, xlsx)

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