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Base editor scanning charts the DNMT3A activity landscape

Nature Chemical Biology volume 19, pages 176–186 (2023)Cite this article

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Abstract

DNA methylation is critical for regulating gene expression, necessitating its accurate placement by enzymes such as the DNA methyltransferase DNMT3A. Dysregulation of this process is known to cause aberrant development and oncogenesis, yet how DNMT3A is regulated holistically by its three domains remains challenging to study. Here, we integrate base editing with a DNA methylation reporter to perform in situ mutational scanning of DNMT3A in cells. We identify mutations throughout the protein that perturb function, including ones at an interdomain interface that block allosteric activation. Unexpectedly, we also find mutations in the PWWP domain, a histone reader, that modulate enzyme activity despite preserving histone recognition and protein stability. These effects arise from altered PWWP domain DNA affinity, which we show is a noncanonical function required for full activity in cells. Our findings highlight mechanisms of interdomain crosstalk and demonstrate a generalizable strategy to probe sequence–activity relationships of nonessential chromatin regulators.

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Fig. 1: A live-cell reporter enables fluorescence-based readout of endogenous DNMT3A activity.
Fig. 2: Base editor scanning charts mutations across DNMT3A that impact function.
Fig. 3: Functional hotspot analysis highlights an interdomain interface important for allosteric activation.
Fig. 4: PWWP domain mutations have variable impacts on protein stability.
Fig. 5: DNA binding by the PWWP domain modulates DNMT3A activity.
Fig. 6: PWWP domain DNA binding is required for full activity.

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Data availability

RRBS and ChIP–seq data have been deposited to NCBI GEO (GSE199890). Base editor scanning data, genotyping and conservation analysis results, and oligonucleotide sequences are provided as Supplementary Information. Unprocessed gel and immunoblot images, as well as additional data generated by this study, are provided as Source data with this paper. Key plasmids reported in this study have been deposited to Addgene nos. 186966–186970. The following publicly available datasets were used: PDB accession codes 4U7T, 4U7P, 3LLR, 5YX2, 5CIU and 6S01; UniRef and Pfam databases; and the mm10 genome and genomic annotations from UCSC.

Code availability

Custom code used to analyze base editor scanning data, RRBS and ChIP–seq data, genotyping data, reporter bisulfite sequencing data and PWWP evolutionary conservation is available at https://github.com/liaulab/DNMT3A_base_editor_scanning.

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Acknowledgements

We thank members of the Liau Lab for helpful discussions and comments on the manuscript, in particular A. Siegenfeld, A. Waterbury, H. S. Kwok, S. Roseman and P. Gosavi. We thank D. Bolduc for advice regarding biochemistry experiments, Z. Niziolek and J. Nelson for assistance with FACS, A. Meissner for providing TKO ESCs, A. Mattei and E. Jung for advice regarding stem cell culture, S. Berry for computational advice, V. Baidin for advice regarding radiometric assays and T. Haining and K. Richards-Corke for additional assistance. N.Z.L., E.M.G. and K.C.N. were supported by National Science Foundation Graduate Research Fellowships (grant no. DGE1745303). E.M.G. was also supported by a Landry Cancer Biology Fellowship. C.L. was supported by a Herchel Smith Graduate Fellowship. B.B.L. is a Damon Runyon-Rachleff Innovator supported in part by the Damon Runyon Cancer Research Foundation (grant no. DDR 60S-20). This research was additionally supported by award no. 1DP2GM137494 from the National Institute of General Medical Sciences and startup funds from Harvard University.

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Authors and Affiliations

  1. Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA

    Nicholas Z. Lue, Emma M. Garcia, Kevin C. Ngan, Ceejay Lee & Brian B. Liau

  2. Broad Institute of Harvard and MIT, Cambridge, MA, USA

    Nicholas Z. Lue, Emma M. Garcia, Kevin C. Ngan, Ceejay Lee, John G. Doench & Brian B. Liau

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Contributions

N.Z.L. and B.B.L. conceived the study and wrote the manuscript with assistance from E.M.G. N.Z.L., E.M.G. and B.B.L. designed experiments and analyzed data. N.Z.L. performed base editor scanning, cell culture experiments, biochemistry experiments, coding, genomics, genomics analysis and data visualization. E.M.G. performed conservation analysis, cell culture experiments, biochemistry experiments, coding and genomics. K.C.N. assisted in reporter design and validation and contributed code. C.L. assisted in base editor cloning and contributed code. J.G.D. oversaw sgRNA library design and contributed the base editor vector. All authors edited and approved the manuscript. B.B.L. supervised and held overall responsibility for the study.

Corresponding author

Correspondence to Brian B. Liau.

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Competing interests

B.B.L. is on the scientific advisory board of H3 Biomedicine, holds a sponsored research project with H3 Biomedicine, is a scientific consultant for Imago BioSciences and is a shareholder and member of the scientific advisory board of Light Horse Therapeutics. J.G.D. consults for Microsoft Research, Abata Therapeutics, Servier, Maze Therapeutics, BioNTech, Sangamo and Pfizer. J.G.D. consults for and has equity in Tango Therapeutics. J.G.D. serves as a paid scientific advisor to the Laboratory for Genomics Research, funded in part by GlaxoSmithKline. J.G.D. receives funding support from the Functional Genomics Consortium: Abbvie, Bristol Myers Squibb, Janssen, Merck and Vir Biotechnology. J.G.D.’s interests were reviewed and are managed by the Broad Institute in accordance with its conflict of interest policies. The remaining authors declare no competing interests.

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Extended data

Extended Data Fig. 1 Reporter silencing depends on DNMT3A and is concomitant with DNA methylation.

a, Schematic of lentiviral methylation reporter vectors. LTR, lentiviral long terminal repeat; TetO, tetracycline operator; SV40, simian virus 40 poly(A) sequence; rTetR, reverse Tet repressor. b, Representative gating scheme for flow cytometric analysis of reporter silencing assays. Helix NP NIR was used as a viability dye. Citrine fluorescence and mCherry fluorescence were monitored on the FITC and PE-Texas Red channels, respectively. c, Reporter methylation levels after varying duration of dox treatment measured by targeted bisulfite sequencing. In each plot, lines represent the percent cytosine methylation at each position (non-cytosine positions are set to 0). CpG sites are highlighted by dots. A schematic of the reporter is shown below, indicating the location of each sequenced region. This experiment was performed once (n = 1). d, Full timecourse for DNMT3-knockout silencing experiment shown in Fig. 1f (top), with representative histograms of citrine fluorescence from each day (bottom). e, Full timecourse for sgW698 silencing experiment shown in Fig. 1h (top), with representative histograms of citrine fluorescence from each day (bottom). f, Deep sequencing of cells edited with sgW698 after 9 days of dox treatment, either sorted for citrine+ cells (yellow) or unsorted (gray). Plot shows the percentage of aligned reads with C-to-T base edits at each indicated protospacer position, or the percentage of aligned reads with indels. Sequencing was performed once (n = 1). For d and e, data and error bars (where larger than data point) are mean ± s.d. of n = 3 replicates, and results are representative of two independent experiments.

Source data

Extended Data Fig. 2 Analysis and validation of DNMT3A base editor scanning results.

a–d, DNMT3A base editor scanning results: (a) heatmap depicting Spearman correlations between sgRNA scores at different timepoints and for citrine+ or citrine− cells, (b) correlation between day 9 citrine+ sgRNA scores and either day 3 citrine− sgRNA scores (left) or day 6 citrine+ sgRNA scores (right), (c) day 9 citrine+ sgRNA scores for select versus all missense sgRNAs (active site, sgRNAs targeting residues within 5 Å of zebularine or SAH (PDB: 5YX2); near 3A-3L interface, sgRNAs targeting residues called by the InterfaceResidues.py script (https://pymolwiki.org/index.php/InterfaceResidues) as at the DNMT3A–DNMT3L interface (PDB: 5YX2) or those adjacent to these residues in the linear sequence), (d) comparison of day 9 citrine+ sgRNA scores for missense sgRNAs targeting annotated domains versus any non-domain region of DNMT3A. Data are the average of n = 3 replicates. For c and d, dotted lines indicate ±2 s.d. of intergenic control sgRNAs, and boxplot components are as follows: center line, median; box, interquartile range; whiskers, up to 1.5 × interquartile range per the Tukey method. e–g, Structural views of the DNMT3A MTase domain (PDB: 5YX2) highlighting residues targeted by several top enriched missense sgRNAs. Day 9 citrine+ sgRNA scores for the corresponding sgRNAs are printed below (where multiple sgRNAs target the same residue(s), the top sgRNA is shown). h, Full timecourse for the silencing experiment shown in Fig. 2e. Data are mean ± s.d. of n = 3 replicates, and results are representative of two independent experiments. i, Deep sequencing of cells edited with sgE756 after 9 days of dox treatment (left) or with sgG532 after 3 days of dox treatment (right), either unsorted or sorted as indicated. Plots show the percentage of aligned reads with C-to-T base edits at each indicated protospacer position or the percentage of aligned reads with indels. Sequencing was performed once (n = 1).

Source data

Extended Data Fig. 3 Clonal analysis of base editing outcomes.

a, Barplots showing the frequencies of wild-type (blue) and base-edited (other colors as defined in the legend of each plot) alleles in clones derived from sgRNA-treated reporter cells (n = 24 clones for each sgRNA). Single cells were plated using FACS and expanded to derive clonal populations, followed by isolation of genomic DNA using QuickExtract DNA extraction solution (Lucigen). Library preparation, sequencing and analysis were performed as for other genotyping experiments. In plots, each bar represents a clone, and theoretical allele frequencies are indicated by dotted lines (note that K562 is triploid for DNMT3A and therefore three alleles are expected for each clone). All alleles with less than 5% allele frequency were pooled and designated as ‘Other.’ Alleles containing both missense and silent mutations were classified based on the missense mutation. Allele tables for each clone are shown in Supplementary Data 6. b, Summary of results in a showing the fractions of clones for each sgRNA that contain only wild-type or silent alleles (blue), only nonsynonymous edited alleles (red) or a combination of wild-type/silent and nonsynonymous edited alleles (blue/red checkered).

Extended Data Fig. 4 SDS–PAGE of purified proteins.

a, b, Purified (a) full-length DNMT3A2 (80 kDa, residues 224–912 with N-terminal 6×His tag) and (b) PWWP domains (17 kDa, residues 278–427, untagged). Proteins were electrophoresed on Novex 10% acrylamide tricine gels (Thermo Fisher Scientific) and visualized by Coomassie staining. 1 μg protein was loaded in each lane. Protein purifications were generally performed once, although wild-type DNMT3A2 was purified more than once and verified to have comparable activity across purifications. SDS–PAGE was performed twice independently for each purified protein with similar results, except for PWWP R326C, which was analyzed once.

Extended Data Fig. 5 Individual validation of sgRNA hits.

a, Citrine fluorescence of base-edited cells after 9 days of dox treatment for 17 sgRNAs targeting DNMT3A (red or light red). Histograms are representative of n = 3 replicates. Top and bottom plots show data from two independent experimental trials (independent transductions). The citrine fluorescence histogram of nontargeting sgLuc control cells treated with dox in parallel (gray) is overlaid in each plot. Control data shown are identical for samples analyzed in the same experiment. Data shown in Fig. 4d corresponds to trial 2 shown here. b, Next-generation sequencing analysis of base editing efficiency at each C within the target sites of the indicated sgRNAs. Allele tables are provided in Supplementary Data 5. c, Flow cytometric quantification of cells remaining citrine+ after 9 days of dox treatment. Data correspond to those shown in a (trial 2) and are mean ± s.d. of n = 3 replicates. P values were calculated through two-tailed unpaired t tests comparing each sgRNA to sgLuc control. d, Aggregate base editing outcomes for the 17 sgRNAs presented in a (includes PWWP, ADD and MTase hit sgRNAs). The efficiency of base editing is plotted at each protospacer position for all sgRNAs containing a C at that position. Horizontal lines indicate the median at each position. The number of sgRNAs (n) with a C at each position is printed above the plot. Protospacer positions within the editing window (+4 to +8) are highlighted in red. The indel frequencies for all sgRNAs (n = 17) are shown to the right in dark gray. Genotyping was performed once for each sgRNA.

Source data

Extended Data Fig. 6 H3 peptide binding of purified PWWP domains.

Binding of purified PWWP domain variants to biotinylated H3K36me0 or H3K36me2 peptides (H3 residues 21–44). Bound proteins were captured by streptavidin pulldown, resolved by SDS–PAGE, and visualized by silver staining. This experiment was performed in two independent trials, and both are shown. Within each experimental trial, gels were electrophoresed and stained in parallel. A longer silver stain exposure was used for trial 1 than for trial 2. The PWWP truncation used here (residues 278–427, untagged, pI = 5.45 (Expasy ProtParam)) is negatively charged at the assay pH (pH = 7.5), which could promote nonspecific interactions with the positively charged histone peptide. Uncropped gels are provided as Source Data.

Source data

Extended Data Fig. 7 Analysis of base editing outcomes for three sgRNAs targeting the E342 codon of DNMT3A.

a, Schematic of sgRNAs targeting the E342 codon. sgE342.1 (red) and sgE342.2 (light red) correspond to the screening hits presented in Fig. 4 and Extended Data Fig. 5. sgE342.3 (purple) is an additional library sgRNA that did not score as a hit in the screen but also targets the E342 codon. b, Allele frequencies in base-edited reporter cells after 15 days of dox treatment, comparing citrine+ cells to unsorted cells. Genomic DNA was harvested using QuickExtract DNA extraction solution (Lucigen) and libraries were prepared and deep sequenced as for other genotyping experiments. Each row represents an allele (for the purposes of this analysis, alleles were merged if they were identical within the region depicted here). All alleles having at least 1% allele frequency in at least one sample are depicted. Left: nucleotide sequence of each allele, with C-to-T base edits shown in red (these appear as G-to-A because the protospacers are along the opposite strand) and deletions represented by dashes. Middle: amino acid sequence corresponding to the translation of the region shown, with missense and silent mutations colored blue and orange, respectively. Right: allele frequencies in unsorted or citrine+ cells for each sgRNA. Colored dots, citrine+ cells; gray dots, unsorted cells. Colored squares to the right of each plot indicate the log2(fold-change in allele frequency in citrine+ vs. unsorted cells). NA indicates undefined log2(fold-changes) where one or both of the allele frequencies is zero. This experiment was conducted once (n = 1).

Source data

Extended Data Fig. 8 Generation of Dnmt3a2-complemented TKO ESCs.

a, Schematic of PiggyBac (PB) vector used for ectopic Dnmt3a2 expression in TKO ESCs. ITR, inverted terminal repeat; CAG, CAG promoter; IRES2, internal ribosome entry site 2; SV40, simian virus 40 poly(A) sequence. b, Overview of Dnmt3a2 complementation experiment. c, Representative gating strategy for flow cytometric analysis and FACS of TKO ESCs. d, Flow cytometric analysis of mCherry fluorescence in ESCs transposed with the Dnmt3a2 expression vector. Top: histograms of mCherry fluorescence. Parent TKO ESCs are shown in gray (same data for all plots). Bottom: mCherry fluorescence versus forward scatter showing the percentage of cells that are gated as mCherry+. n = 2 biological replicates (separately transposed cells).

Extended Data Fig. 9 Additional analysis of de novo DNA methylation in Dnmt3a2-complemented TKO ESCs.

a, Counts of hypermethylated and hypomethylated differentially methylated regions (DMRs) called for each mutant Dnmt3a2 compared to wild-type Dnmt3a2. b, Overlap of called DMRs with three genomic annotations: CpG islands (gray), genic regions (red) and intergenic regions (blue). Hypermethylated and hypomethylated DMRs for each mutant were considered separately. The plot displays the percentage of DMRs in each group with any overlap with each genomic annotation. c, CpG methylation within 10-kb genomic bins ranked into quartiles based on normalized H3K4me3 ChIP–seq signal (n = 23,379 bins per quartile). Center line, median; box, interquartile range; whiskers, up to 1.5 × interquartile range per the Tukey method; outliers not shown. d, Difference in CpG methylation between top and bottom H3K36me2 quartiles for each sample. 10-kb genomic bins (n = 93,516 total) were grouped into quartiles, and the average methylation in the median bins from the top and bottom quartiles were compared. Biological replicates are shown separately (n = 2). e, CpG methylation within 10-kb genomic bins ranked into quantiles (n = 1,000 quantiles) based on normalized H3K36me2 ChIP–seq signal. The average bin methylation for each quantile is plotted against the H3K36me2 signal. For a–e, only CpGs with 5× coverage across all samples were considered. Methylation values in c and e represent the average of two biological replicates.

Supplementary information

Supplementary Information

Supplementary Fig. 1, Tables 1–7 and legends for Data 1–7.

Reporting Summary

Supplementary Data

Supplementary Data 1–7 (base editor scanning data, allele frequency tables and PWWP residue conservation).

Source data

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Lue, N.Z., Garcia, E.M., Ngan, K.C. et al. Base editor scanning charts the DNMT3A activity landscape. Nat Chem Biol 19, 176–186 (2023). https://doi.org/10.1038/s41589-022-01167-4

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