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Genome-wide screens uncover KDM2B as a modifier of protein binding to heparan sulfate

Nature Chemical Biology volume 17, pages 684–692 (2021)Cite this article

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An Author Correction to this article was published on 30 March 2022

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Abstract

Heparan sulfate (HS) proteoglycans bind extracellular proteins that participate in cell signaling, attachment and endocytosis. These interactions depend on the arrangement of sulfated sugars in the HS chains generated by well-characterized biosynthetic enzymes; however, the regulation of these enzymes is largely unknown. We conducted genome-wide CRISPR–Cas9 screens with a small-molecule ligand that binds to HS. Screening of A375 melanoma cells uncovered additional genes and pathways impacting HS formation. The top hit was the epigenetic factor KDM2B, a histone demethylase. KDM2B inactivation suppressed multiple HS sulfotransferases and upregulated the sulfatase SULF1. These changes differentially affected the interaction of HS-binding proteins. KDM2B-deficient cells displayed decreased growth rates, which was rescued by SULF1 inactivation. In addition, KDM2B deficiency altered the expression of many extracellular matrix genes. Thus, KDM2B controls proliferation of A375 cells through the regulation of HS structure and serves as a master regulator of the extracellular matrix.

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Fig. 1: Finding novel regulators of HS biosynthesis through genome-wide screens.
Fig. 2: Sequencing data analysis of CRISPR–Cas9 screens selecting for regulators of HS biosynthesis.
Fig. 3: Structural analysis of cell surface HS in KDM2B mutant cells.
Fig. 4: Binding of growth factors and other HS-binding proteins to KDM2B mutant cells.
Fig. 5: Transcriptome and ChIP analysis of KDM2B mutant cells.
Fig. 6: KDM2B inactivation results in a SULF1-dependent decrease in cell growth.

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Data availability

Any data generated or analyzed during this study, associated protocols, materials within the manuscript and public databases (GSE163162, GSE145789) are included in the article and related Supplementary information, or are available from the corresponding author. Source data are provided with this paper.

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Acknowledgements

We thank C. van der Kooi, University of Kentucky, for providing the b1b2 domain of NRP1, and D. Xu, University of Buffalo, for providing the biotinylated S100A12 protein. We also thank the GlycoAnalytics Core Facility at University of California, San Diego for help with analytical experiments. We thank C. Kuo for processing of RNA sequencing data. RNA sequencing and CRISPR amplicon sequencing were conducted at the IGM Genomics Center, University of California, San Diego, La Jolla, CA (MCC grant no. P30CA023100). This work was supported by grant nos. R21 CA199292 (to J.D.E. and N.E.L.), GM33063 (to J.D.E.), GM119850 (to N.E.L.), NSF CHE 200424 (to K.G.) and T32 GM008326 (fellowship support for B.M.T.); and DFG research fellowship no. 420160411 from the German Research Foundation (to S.R.) and no. K12HL141956 (fellowship support for R.J.W.).

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Author notes

  1. These authors contributed equally: Ryan J. Weiss, Philipp N. Spahn

Authors and Affiliations

  1. Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA

    Ryan J. Weiss, Qing Liu, Jing Li, Sandra Rother, Thomas M. Clausen, Marten A. Hoeksema, Christopher K. Glass & Jeffrey D. Esko

  2. Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA

    Philipp N. Spahn & Austin W. T. Chiang

  3. Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, CA, USA

    Kristina M. Hamill, Bryce M. Timm, Kamil Godula & Yitzhak Tor

  4. Department for Immunology and Microbiology, Faculty of Health and Medical Sciences, University of Copenhagen and Department of Infectious Disease, Copenhagen University Hospital, Copenhagen, Denmark

    Thomas M. Clausen

  5. Glycobiology Research and Training Center, University of California, San Diego, La Jolla, CA, USA

    Kamil Godula, Yitzhak Tor, Philip L. S. M. Gordts, Nathan E. Lewis & Jeffrey D. Esko

  6. Department of Medicine, University of California, San Diego, La Jolla, CA, USA

    Christopher K. Glass & Philip L. S. M. Gordts

  7. Department of Pediatrics, The Novo Nordisk Foundation Center for Biosustainability and Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA

    Nathan E. Lewis

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Contributions

R.J.W., P.N.S., P.L.S.M.G., N.E.L. and J.D.E. designed the research. Unless otherwise noted, R.J.W. and P.N.S. performed the experimental work and analyzed the data. A.W.T.C. processed and analyzed the RNA-seq data. Q.L. and J.L. characterized the KDM2B mutant clones and performed immunoblotting and qPCR experiments. K.M.H. synthesized the GNeo-biotin derivative. S.R. performed ELISA experiments. T.M.C. performed soft agar assays. M.A.H. processed and analyzed ChIP–seq experiments. B.M.T. performed immunoblotting experiments. K.G., C.K.G. and Y.T. contributed new reagents. R.J.W., P.N.S., N.E.L. and J.D.E. wrote the paper.

Corresponding authors

Correspondence to Nathan E. Lewis or Jeffrey D. Esko.

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Competing interests

The University of California San Diego and J.D.E. have a financial interest in TEGA Therapeutics, Inc. The terms of this arrangement have been reviewed and approved by the University of California, San Diego in accordance with its conflict-of-interest policies.

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Peer review information Nature Chemical Biology thanks Ulf Lindahl, Linda Troeberg and the other, anonymous, reviewer for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 A genome-wide screen for resistance to diphtheria toxin.

 a, Left: Frequency distribution of gene counts after treatment with either diphtheria toxin (DTX) or PBS (Plasmid = GeCKO plasmid library). Right: Lorenz curves showing the distribution of sequencing reads over the gene library. Numbers represent Gini coefficients. b, Scatterplot of sgRNA counts (log10, normalized) in samples after DTX treatment versus PBS treatment. The sgRNA fraction with significant fold-change is shown in green. sgRNA fraction representing non-targeting controls shown in orange. HBEGF-targeting sgRNAs shown in red, and DPH genes are shown in purple and blue. c, Table of the top 10 ranked genes showing enrichment after DTX treatment. The enrichment level of the six gene-targeting sgRNAs is indicated by color.

Extended Data Fig. 2 KDM2B-deficient cell lines.

a, Sanger sequencing of two A375 KDM2B knockout clones (C5 and C13) and (b) Sanger sequencing of one HeLa knockout clone (C9) after targeting with the indicated sgRNAs. Intron sequence denoted in lower case.

Extended Data Fig. 3 KDM2B affects protein binding.

a, Protein binding in A375 KDM2B knockout clone C13 (t-tests; n = 3). b, Fold change in KDM2B mRNA expression in A375 KDM2BC5 cells, and in A375 KDM2BC5 cells expressing a KDM2B cDNA from a lentiviral construct (hKDM2B) (n = 2). c, FGF1 binding in HeLa KDM2BC9 cells, and in HeLa KDM2BC9 cells expressing KDM2B cDNA (hKDM2B) (t-test on log10 fluorescence data, n = 5). d, Fold change in KDM2B mRNA expression in A375 KDM2BC5 cells expressing a KDM2B cDNA with a point mutation (H242A) in the demethlase domain (n = 2).

Extended Data Fig. 4 Transcriptomic changes in KDM2B-deficient cells.

a, Fold change in SULF1 mRNA expression in A375 KDM2BC5 cells, and in A375 KDM2BC5 cells expressing a siRNA against SULF1 (n = 2). b, top: Western blot of SULF1 protein levels in conditioned media (CM) collected from A375 wild-type and KDM2BC5 cells (CM 10x equals 10-fold concentrated solution) bottom: Total protein (coomassie-stained gel), red frame indicates position of SULF1. c, Gene track for H3K4me3, KDM2B, and H3K36me2 ChIP-Seq at the MNX1 locus, a known target of KDM2B. d, Transcriptome-wide expression data displaying differentially expressed genes in KDM2BC5 cells compared to wild-type. HS biosynthetic genes and extracellular matrix genes are highlighted. e, Gene set enrichment analysis of significantly downregulated (log2 ≤ -0.5, p ≤ 0.05; FDR-corrected) and upregulated (log2 ≥ 0.5, p ≤ 0.05; FDR-corrected) genes in A375 wild-type and KDM2BC5 RNA-Seq datasets (n = 3). f, MMP-9 and TIMP-3 levels in the supernatant from cultured A375 wild-type and KDM2BC5 cells (t-test, n = 3). g, Histograms showing FGF1 binding in A375 wild-type, KDM2BC5 cells, and in KDM2BC5 cells upon treatment with an siRNA targeting SULF1. h, Fold change in HS6ST2 mRNA expression in A375 KDM2BC5 cells, and in A375 KDM2BC5 cells expressing a HS6ST2 cDNA from a lentiviral construct (hHS6ST2) (n = 2). i, Fold change in HS3ST3A1 mRNA expression in A375 KDM2BC5 cells, and in A375 KDM2BC5 cells expressing a HS3ST3A1 cDNA from a lentiviral construct (hHS3ST3A1) (n = 2).

Source data

Extended Data Fig. 5 KDM2B affects cell growth through SULF1.

a, Sanger sequencing of a A375 KDM2B SULF1 double knock-out clone (KDM2BC5 SULF1#1) after targeting with the indicated sgRNA. Both sequence changes result in frameshift mutations. b, Clonogenic assay under normal growth conditions. After 14 days, colony growth was quantified by methylene blue staining and absorption readings at 650 nm (t-test, n = 3). Scale bar = 5 mm.

Supplementary information

Supplementary Information

Synthesis scheme for GNeo-biotin (1). Supplementary figure explaining gating strategy and Tables 1–3.

Reporting Summary

Supplementary Dataset 1

sgRNA enrichment (GNeo-SAP screen). sgRNA enrichment in the GNeo-SAP resistance screen. Counts: normalized read counts in sample treated with GNeo-SAP (average of two replicate experiments). Control mean: normalized read count in sample treated with PBS (average of two replicate experiments). Control stdev: normalized read count standard deviation in PBS-treated sample across two replicate experiments. Fold change: counts divided by control mean. P value: P value of negative binomial test. Significant: statistically significance (true/false), based on FDR = 0.1.

Supplementary Dataset 2

sgRNA enrichment (GNeo-Cy5 screen). sgRNA enrichment in the GNeo-Cy5 binding screen. Counts: normalized read counts in GNeo-Cy5-negative sample (average of two replicate experiments). Control mean: normalized read count in GNeo-Cy5-positive sample (average of two replicate experiments). Control stdev: normalized read count standard deviation in GNeo-Cy5-positive sample across two replicate experiments. Fold change: counts divided by control mean. P value: P value of negative binomial test. Significant: statistically significance (true/false), based on FDR = 0.1.

Supplementary Dataset 3

Gene enrichment scores (GNeo-SAP screen, permissive setting). Ranking of genes based on accumulated sgRNA enrichment (Methods) in the GNeo-SAP resistance screen. SigmaFC: gene-ranking score. P value: estimated P value of obtained gene-ranking score. Significant: statistically significance (true/false), based on FDR = 0.1. #sgRNAs: number of sgRNAs targeting a gene in the library. #signif. sgRNAs: number of gene-targeting sgRNAs reaching statistically significant enrichment.

Supplementary Dataset 4

Gene enrichment scores (GNeo-Cy5 screen, permissive setting). Ranking of genes based on accumulated sgRNA enrichment (Methods) in the GNeo-Cy5 FACS screen. SigmaFC: gene-ranking score. P value: estimated P value of obtained gene-ranking score. Significant: statistically significance (true/false), based on FDR = 0.1. #sgRNAs: number of sgRNAs targeting a gene in the library. #signif. sgRNAs: number of gene-targeting sgRNAs reaching statistically significant enrichment.

Supplementary Dataset 5

Gene candidates shared among both the GNeo-SaAP and GNeo-Cy5 screen (permissive setting). List of genes yielding significant enrichment under both the GNeo-SAP resistance and GNeo-Cy5 FACS screen. SigmaFC (FACS): gene-ranking score in FACS screen. #sgRNAs (FACS): number of gene-targeting sgRNAs reaching statistically significant enrichment in the FACS screen. SigmaFC (Saporin): gene-ranking score in resistance screen. #sgRNAs (Saporin): number of gene-targeting sgRNAs reaching statistically significant enrichment in the resistance screen.

Supplementary Dataset 6

Gene enrichment scores (GNeo-SAP screen, restrictive setting). Ranking of genes based on accumulated sgRNA enrichment (Methods) in the GNeo-SAP resistance screen. SigmaFC: gene-ranking score. P value: estimated P value of obtained gene-ranking score. Significant: statistically significance (true/false) at the 1% level (Sidak correction). #sgRNAs: number of sgRNAs targeting a gene in the library. #signif. sgRNAs: number of gene-targeting sgRNAs reaching statistically significant enrichment.

Supplementary Dataset 7

Gene enrichment scores (GNeo-Cy5 screen, restrictive setting). Ranking of genes based on accumulated sgRNA enrichment (Methods) in the GNeo-Cy5 FACS screen. SigmaFC: gene-ranking score. P value: estimated P value of obtained gene-ranking score. Significant: statistically significance (true/false at the 1% level (Sidak correction). #sgRNAs: number of sgRNAs targeting a gene in the library. #signif. sgRNAs: number of gene-targeting sgRNAs reaching statistically significant enrichment.

Supplementary Dataset 8

Transcriptomic analysis of KDM2B knockout cells. Raw RNA-seq reads from KDM2BC5 cells and Cas9-expressing control cells (three replicates each) and differential expression analysis. BaseMean: mean counts, normalized for sequencing depth. lfcSE: standard error of log2 fold change. Stat: Wald statistic (log2 fold change divided by lfcSE). P value: P value from negative binomial test. Padj: adjusted P value (FDR correction).

Source data

Source Data Fig. 3

Unprocessed immunoblots.

Source Data Extended Data Fig. 4

Unprocessed immunoblots.

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Weiss, R.J., Spahn, P.N., Chiang, A.W.T. et al. Genome-wide screens uncover KDM2B as a modifier of protein binding to heparan sulfate. Nat Chem Biol 17, 684–692 (2021). https://doi.org/10.1038/s41589-021-00776-9

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