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The HIF complex recruits the histone methyltransferase SET1B to activate specific hypoxia-inducible genes

Nature Genetics volume 53, pages 1022–1035 (2021)Cite this article

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Abstract

Hypoxia-inducible transcription factors (HIFs) are fundamental to cellular adaptation to low oxygen levels, but it is unclear how they interact with chromatin and activate their target genes. Here, we use genome-wide mutagenesis to identify genes involved in HIF transcriptional activity, and define a requirement for the histone H3 lysine 4 (H3K4) methyltransferase SET1B. SET1B loss leads to a selective reduction in transcriptional activation of HIF target genes, resulting in impaired cell growth, angiogenesis and tumor establishment in SET1B-deficient xenografts. Mechanistically, we show that SET1B accumulates on chromatin in hypoxia, and is recruited to HIF target genes by the HIF complex. The selective induction of H3K4 trimethylation at HIF target loci is both HIF- and SET1B-dependent and, when impaired, correlates with decreased promoter acetylation and gene expression. Together, these findings show SET1B as a determinant of site-specific histone methylation and provide insight into how HIF target genes are differentially regulated.

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Fig. 1: CRISPR screen identifies genes required to activate a HIF response.
Fig. 2: SET1B depletion impairs the HIF transcriptional response.
Fig. 3: SET1B selectively drives mRNA expression of HIF target genes.
Fig. 4: Functional consequences of SET1B loss in hypoxia.
Fig. 5: SET1B associates with HIF-1α and accumulates on chromatin in hypoxia.
Fig. 6: HIF-1α selectively recruits SET1B to HIF target genes.
Fig. 7: SET1B-dependent H3K4me3 in hypoxia.
Fig. 8: SET1B is recruited by HIF to facilitate activation of the HIF response.

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Data availability

SgRNA read count tables from the CRISPR–Cas9 genetic screen are shown in Supplementary Data 1. RNA-seq (GSE169087) and ChIP–seq (GSE159128, GSE169040 and together under SuperSeries GSE169041) data deposited at Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/). Source data are provided with this paper.

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Acknowledgements

We thank the Nathan laboratory for their helpful discussions. We also thank B. Huntly and E. Meduri for initial help with the RNA-seq analysis. This work was supported by a Wellcome Senior Clinical Research Fellowship to J.A.N. (no. 215477/Z/19/Z) and a Lister Institute Research Fellowship to J.A.N. This work was also supported by the NIHR Cambridge Biomedical Research Centre and the Addenbrooke’s Charitable Trust. P.H.M. is supported by a Wellcome Senior Investigator Award (no. 096956/Z/11/Z). D.R.M. is supported by the National Institute for Health Research (grant no. NIHR-RP-2016-06-004) and the Deanship of Scientific Research, King Abdulaziz University, Ministry of High Education for Saudi Arabia. P.J.R. is supported by the Ludwig Institute for Cancer Research, the Wellcome Trust (grant no. 106241/Z/14/Z) and the Francis Crick Institute, which receives its core funding from Cancer Research UK (grant no. FC001501), the Medical Research Council (grant no. FC001501) and the Wellcome Trust (grant no. FC001501). We thank the Oxford Genomics Centre at the Wellcome Centre for Human Genetics (funded by Wellcome Trust grant no. 203141/Z/16/Z) for the generation and initial processing of sequencing data. Computational facilities included the Oxford Biomedical Research Computing (BMRC) facility, a joint development between the Wellcome Centre for Human Genetics and the Big Data Institute supported by Health Data Research UK and the NIHR Oxford Biomedical Research Centre. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health.

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Authors and Affiliations

  1. Cambridge Institute of Therapeutic Immunology and Infectious Disease (CITIID), Jeffrey Cheah Biomedical Centre, Department of Medicine, University of Cambridge, Cambridge, UK

    Brian M. Ortmann, Esther Arnaiz, Niek Wit, Peter S. J. Bailey, Louise H. Jordon, Rachel Seear & James A. Nathan

  2. Cambridge Institute for Medical Research, The Keith Peters Building, Department of Medicine, University of Cambridge, Cambridge, UK

    Natalie Burrows, Ian T. Lobb, Ana Peñalver, James McCaffrey & Patrick H. Maxwell

  3. NDM Research Building, University of Oxford, Headington, Oxford, UK

    Olivia Lombardi & David R. Mole

  4. Department of Histopathology, Cambridge University NHS Foundation Trust, Cambridge, UK

    James McCaffrey

  5. Ludwig Institute for Cancer Research, University of Oxford, Headington, Oxford, UK

    Peter J. Ratcliffe

  6. The Francis Crick Institute, London, UK

    Peter J. Ratcliffe

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Contributions

B.M.O. and J.A.N. conceptualized the study. B.M.O., N.B., P.S.J.B., E.A., I.T.L., N.W. D.R.M., P.H.M. and J.A.N. were responsible for the methodology. B.M.O., N.B., E.A., N.W., P.S.J.B., B.M.O., I.T.L., A.P., L.H.J., O.L., J.M., R.S., D.R.M. and J.A.N. carried out the investigations. B.M.O. and J.A.N. wrote the original draft of the manuscript. B.M.O., N.B., D.R.M., P.H.M., P.J.R. and J.A.N. reviewed and edited the manuscript. J.A.N. was responsible for funding acquisition. D.R.M., P.J.R., P.H.M. and J.A.N. were responsible for resources. J.A.N. supervised the research.

Corresponding author

Correspondence to James A. Nathan.

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Competing interests

P.J.R. is a scientific cofounder of ReOx Ltd., a company that is developing inhibitors of the HIF hydroxylase enzymes. P.H.M. is a scientific cofounder and equity holder of ReOx and has received speaker honoraria from Fibrogen, both of which aim to develop PHD inhibitors as therapies. The other authors declare no competing interests.

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Extended data

Extended Data Fig. 1 Genome-wide mutagenesis screen identifies genes required to activate a HIF response.

a-g, Screen validation using CRISPR-Cas9 targeted depletion in mixed KO populations. HeLa HRE-ODDGFP reporter cells were transduced with sgRNAs against a, HIF1β or UBE2A; b–d, β2m; e, RNF20 or RNF40; f, HIF1β or PPP4C; g, SET1B. Cells were treated with 21% or 1% O2 for 24 h or DMOG 1 mM for 24 h, and GFP levels measured by flow cytometry. h, i, KO clones of HIF1β and SET1B were generated in HeLa HRE-GFPODD reporter cells by serial dilution and validated by immunoblot (representative of 3 experiments) (i). h, Control or KO clones were incubated at 21% or 1% O2 for 24 h and the GFP levels were measured by flow cytometry (n=3 biologically independent samples). j, Loss of SET1B or HIF1β does not alter basal reporter activity. HIF1β and SET1B mixed KO populations of HeLa HRE-ODDGFP reporter cells were generated using CRISPR-Cas9 targeted depletion, and GFP levels were measured with flow cytometry.

Source data

Extended Data Fig. 2 SET1B depletion decreases HIF-1α activation of CA9.

a, Wildtype HeLa or SET1B clonal KO cells were incubated at 1% O2, and analyzed by immunoblot (representative of 3 biological replicates). b, HIF-1α mRNA expression in different cell types following HIF1β or SET1B loss after 24 h hypoxia. n= 5 (HeLa), 6 (A549), 3 (MCF7), 4 (skin fibroblasts) biological replicates. c-e, Immunoblots for the HIF complex in HeLa (c), MCF7 (d) and skin fibroblast cells (e) depleted of HIF1β or SET1B (n= 3 biological replicates). f, Reconstitution of mixed KO populations of SET1B in A549 cells transfected with control or SET1B siRNA, with and without SET1B overexpression (representative of 3 biological replicates). g, HeLa cells were transfected with a control or SET1B siRNA for 48 h, mRNA extracted and SET1A or SET1B expression measured by qPCR. Control versus SET1B siRNA, P ≤ 0.0001; two-way ANOVA. n=6 biological replicates. h, Reconstitution of SET1B depleted HeLa HRE-GFPODD reporter cells by transfecting control or SET1B siRNA, with or without SET1B overexpression for 48 h. Cells were treated with 1 mM DMOG for 24 h and GFP levels measured by flow cytometry. i, j, SET1B loss decreases HIF activity in response to hypoxia mimetics. HIF1β and SET1B depleted HeLa HRE-GFPODD reporter cells were analyzed by flow cytometry (i) or immunoblotting (j) following 24 h with and without 1 mM DMOG (representative of 3 biological replicates). k, Proteasome inhibition does not increase CA9 levels following SET1B or HIF1β depletion. HeLa cells stably expressing Cas9 were transduced with sgRNAs against either HIF1β or SET1B. Following 7–10 days cells were treated at 21% or 1% O2 for 24 h and where indicated were treated with 20 µM MG132 for 3 h (representative of 3 biological replicates). wt=wildtype. Graphs show mean ± SD. **** P < 0.0001.

Source data

Extended Data Fig. 3 SET1B loss impairs mRNA expression of a subset of HIF target genes.

a-c, Volcano plots of fold change in mRNA expression in wildtype b, HIF1β depleted c, or SET1B depleted d, HeLa cells incubated in 21% or 1% O2 for 12 h. Significantly up (red) or downregulated (blue) genes shown (log2(fold change) of> 0.5 or < −0.5). d-f, Expression of HIF target genes in mixed KO populations of HIF1β or SET1B cells in A549 (d), MCF7 (e) or skin fibroblasts (f), following incubation in 21% O2 or 1% O2for 24 h. d, CA9, control versus HIF1β or SET1B sgRNA P ≤ 0.0001 (n=3 biological replicates); PHD3, control versus HIF1β or SET1B sgRNA P ≤ 0.0001 (n=3 biological replicates); VEGF, control versus HIF1β or SET1B sgRNA P ≤ 0.0001 (n=5 biological replicates); GLUT1, control versus HIF1β, P ≤ 0.0001 (n=3 biological replicates); BAP1 (n=6 biological replicates); two-way ANOVA. e, CA9, control versus HIF1β or SET1B sgRNA P ≤ 0.0001 (n=3 biological replicates); PHD3, control versus HIF1β or SET1B sgRNA P ≤ 0.0001 (n=3 biological replicates); two-way ANOVA. f, CA9, control versus HIF1β or SET1B sgRNA P ≤ 0.0001 (n=3 biological replicates); PHD3, control versus HIF1β or SET1B sgRNA P ≤ 0.0001 (n=3 biological replicates); two-way ANOVA. (g, h) mRNA expression of HIF target genes following reconstitution of SET1B depletion and incubation in 21% or 1% O2 for 24 h. g, HeLa cells: CA9, control versus siSET1B P = 0.0006 (n=3 biological replicates); VEGF, control versus siSET1B P = 0.0005; VEGF, control versus siSET1B+SET1B P = 0.029 (n=3 biological replicates); SET1B, control vs siSET1B+SET1B P = 0.0064; SET1B, control versus siSET1B+SET1B P ≤ 0.0001; BAP1 (n=3 biological replicates); two-way ANOVA. h, A549 cells: CA9, control versus siSET1B P = 0.002 (n=3 biological replicates); SET1B, control vs siSET1B+SET1B P = 0.014; SET1B, control versus siSET1B+SET1B P = 0.0002; BAP1 (n=3 biological replicates); two-way ANOVA. Ct=control. Graphs show mean ± SD, * P < 0.05, ** P < 0.01, *** P < 0.001.

Extended Data Fig. 4 Gene expression changes following SET1B loss are not dependent on HIF-α isoforms.

a–d, Venn diagrams of identified HIF and SET1B dependent genes in the HeLa RNA-seq analysis with previously reported datasets of identified HIF-1 and HIF-2 binding sites63 in MCF7 (a, b) or HepG2 (c, d) cells. e-g, Characterisation of HeLa HRE-HIFODDGFP HIF KO cell lines. e, HeLa wildtype (Wt), HIF-1α KO, HIF-2α or HIF-1/2α KO HeLa clones were generated by sgRNA depletion and dilution cloning. Representative immunoblot of 3 independent experiments confirming HIF-1α or HIF-2α depletion is shown following incubation at 21% or 1% O2 for 24 h (e). f, Combined HIF-1α and HIF-2α loss prevents activation of the GFP reporter (representative null clone). g, HeLa wildtype, HIF-1α KO and HIF-2α KO clones stably expressing Cas9 were transduced with a sgRNA against HIF1β or SET1B. Cells were treated with and without 1 mM DMOG and GFP reporter levels were measured using flow cytometry. (h, i) qPCR of selected HIF target genes following SET1B depletion in 786-0 cells. h, Representative immunoblot of SET1B and HIF1β depletion in 786-0 cells (3 biological replicates). (i) mRNA expression of selected HIF-2α target genes. CA9, control versus HIF1β sgRNA P ≤ 0.0001; CA9, control vs SET1B sgRNA P = 0.0006; PAI, control versus HIF1β P ≤ 0.0001; PAI, control vs SET1B sgRNA P = 0.001; ANGPTL4, control versus HIF1β or SET1B sgRNA P ≤ 0.0001; GLUT1, control vs HIF1β sgRNA P ≤ 0.0001; two-way ANOVA. Ct=control. Graphs show mean ± SD, ** P < 0.01, *** P < 0.001.

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Extended Data Fig. 5 SET1B regulates the expression of a subset of HIF-target genes.

a, Pathway analysis of enriched genes dependent on HIF1β or SET1B in hypoxia. HIF1β and SET1B dependent genes identified from the RNA Seq were run through Metascape analysis to identify the pathways which were enriched. b, Heat map comparing the log2(fold change) between control, HIF1β and SET1B depleted cells focussing on genes involved in angiogenesis and glycolysis. c, qPCR of selected angiogenesis (left) or glycolysis genes (right) in mixed KO populations of HIF1β or SET1B HeLa cells. VEGF, control versus HIF1β or SET1B sgRNA P ≤ 0.0001; PAI, control versus HIF1β or SET1B sgRNA P ≤ 0.0001; ANGPTL4, control versus HIF1β or SET1B sgRNA P ≤ 0.0001; LDHA, control versus HIF1β sgRNA P ≤ 0.0001; GLUT1, control vs HIF1β sgRNA P ≤ 0.0001; two-way ANOVA, n= 3 biological replicates. d, VEGF ELISA in control, HIF1β or SET1B depleted HeLa cells. Cells were grown in 21% or 1% O2 before supernatants were collected. VEGF control versus HIF1β or SET1B sgRNA P ≤ 0.0001; two-way ANOVA, n= 3 biological replicates. Ct=control. Graphs show mean ± SD, *** P < 0.001.

Extended Data Fig. 6 Bioenergetic analyses of glycolysis following SET1B depletion.

a, b, Wildtype, HIF1β depleted or SET1B depleted HeLa cells were generated as described, and incubated with or without DMOG (1 mM), Roxadustat (0.1 mM), or Daprodustat (0.1 mM) for 24 h. Cells were analyzed using a Seahorse XF analyzer by performing a Glycolytic Rate Assay. Oxygen consumption rates (OCR), extracellular acidification rates (ECAR) and the protein efflux rate derived from glycolysis (glycoPER) as a percentage of total were calculated using WAVE version 2.6.1. c, d, Bioenergetic analyses for wildtype, HIF1β depleted or SET1B depleted A549 cells, as described for HeLa cells. In A549 cells DMOG altered OCR in a HIF1β independent manner. n=3 for HeLa, n=2 for A549 for biological replicates. Representative data from one experiment shown with mean ± SD of 6 technical replicates.

Extended Data Fig. 7 Increased apoptosis and impaired angiogenesis following SET1B loss in hypoxia.

a-c) Proliferation assays of control, HIF1β or SET1B depleted A549 (a) or HeLa cells (b, c) in 21% O2 (n=3 biological replicates). d, Time course of SET1B and HIF-1α protein levels in 1% O2 (representative of 3 biological replicates). (e) qPCR analysis of SET1B and CA9 expression following 21% or 1% O2 for 24 h. HeLa SET1B 21% versus 1% O2 P ≤ 0.0001, HeLa CA9 21% versus 1% O2 P = 0.0028, A549 SET1B 21% versus 1% O2 P = 0.0006, HeLa CA9 21% versus 1% O2 P = 0.022; 3 biological replicates, unpaired two-tail t test. f, Proliferation assay of SET1B or SET1A deficient A549 cells in 21% O2. Control versus SET1A depletion at 3 days, P ≤ 0.0001; 3 biological replicates, two-way ANOVA. (g) qPCR analysis for GLUT1, HIF-1α and BAP1 in SET1A or SET1B depleted A549 cells. GLUT1 levels SET1B versus SET1A depletion P = 0.0006, HIF-1α levels SET1B versus SET1A depletion P = 0.0003, BAP1 levels SET1B versus SET1A depletion P = 0.004; 6 biological replicates, two-way ANOVA. h, CFSE assay in HIF1β or SET1B depleted HeLa cells. i, Caspase activity assay in control, HIF1β and SET1B sgRNA depleted cells (21% or 1% O2 for 24 h). j, PARP1 cleavage in control, HIF1β and SET1B depleted cells (21% or 1% for 24 h). Representative of 3 biological replicates. k, HeLa spheroid volume in control, HIF or SET1B depleted HeLa cells. n = 54 (control), 39 (SET1B KO), 51 (HIF1β KO), 28 (HIF-1/2α KO) spheroids. l, m, SET1B or HIF1β deficient HeLa (l) or A549 (m) tumor xenograft growth (n=7 mice each condition). n, Total vessel circumference (μm) in A549 tumor xenografts. Control versus HIF1β or SET1B depletion P ≤ 0.0001; n= 6 (control and HIF1β), 7 SET1B, one-way ANOVA). o, Cell growth in control, HIF1β or SET1B depleted 786-0 cells grown in 21% O2 (n=3 biological replicates). Ct=control. Graphs show mean ± SD, * P < 0.05, ** P < 0.01, *** P < 0.0001.

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Extended Data Fig. 8 Association of SET1B with chromatin and HIF-1α.

a, Endogenous SET1B was immunoprecipitated from HeLa cells incubated at 21% or 1% O2 for 6 h, and immunoblotted for SET1B, HIF-1α or HIF-2α. b, Endogenous HIF-1α was immunoprecipitated from HeLa cells incubated at 21% or 1% O2 for 6 h, and samples immunoblotted for HIF-1α, HIF1β or SET1B. c, Immunoprecipitated SET1B from wildtype and HIF-1α clonal knockout HeLa cells incubated at 21% or 1% O2 for 6 h, and immunoblotted for HIF-1α or SET1B. d, SET1B does not associate with the SUV12 component of PRC2. Immunoprecipitated SET1B from HeLa cells incubated at 21% or 1% O2 for 6 h, and immunoblotted for SET1B, CFP1 and SUV12. *background band. e, Endogenous CFP1 was immunoprecipitated from HeLa cells treated with 21% or 1% O2 for 6 h, and immunoblotted for HIF-1α, HIF1β, SET1B and CFP1. Representative immunoblots from 3 independent biological replicates shown in a-g. f-j, Cell fractionation studies in A549 and 786-0 cells (representative of 3 biological replicates). f, g, Cell fractionation in A549 cells treated at 21% or 1% O2 for 6 h and immublotted for HIF-α or SET1B. Tubulin used as cytoplasmic marker; PARP1 used as a nuclear marker) f, Quantified using ImageJ (n=3 biological replicates) g. h, Cell fractionation for SET1B and SET1A in A549 cells treated with 1% O2 for 6 h. i, j, Cell fractionation in A549 cells treated with Roxadustat 100 μM for 24 hr quantified using ImageJ (n = 3 biological replicates) j, k, Cell fractionation in 786-0 cells treated at 21% or 1% O2 for indicated times (representative of 3 biological replicates). l-n, SET1B overexpression in control or HIF1β null cells does not restore HIF-1α signaling. HIF-1α, SET1B and CA9 levels were measured by immunoblot (l) or qPCR (m, n) (n=3 biological replicates).

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Extended Data Fig. 9 H3K4me3 ChIP-seq analysis in hypoxia, or following HIF or SET1B depletion.

a-c, H3K4me3 increases at HIF target gene promoters in hypoxia. a, H3K4me3 ChIP-PCR in HeLa cells incubated at 21% or 1% O2 for 6 h. CA9, PHD3, or VEGF 21% versus 1% hypoxia P ≤ 0.0001 (4 biological replicates), BAP1 (4 biological replicates); two-way ANOVA (mean ± SD, *** P < 0.0001). b, c, Total H3K4me3 levels in HeLa and A549 cells (1% O2 for indicated times). Representative of 3 biolgical replicates. d, e, H3K4me3 ChIP-seq analysis. d, Heatmaps of H3K4me3 ChIP-seq signal ± 5-kb from TSS. Genes ranked according to expression in the RNA-seq analysis (highest at top). Representative data shown for one replicate in control, HIF1β and SET1B depleted cells incubated at 21% and 1% O2 for 6 h. e, H3K4me3 signal at gene promoters. Plots showing mean H3K4me3 ChIPseq signal (counts per million – cpm) ± 5-kb from TSS of all gene promoters in control, HIF1β and SET1B depleted cells incubated at 21% and 1% O2for 6 h. f, H3K4me3 at the promoters of the top hypoxia-inducible, HIF-bound genes, defined in the RNA-seq and HIF-1α, HIF-2α, and HIF1β ChIP-seq analyses. g, Venn Diagram of high stringency canonical HIF-1 and HIF-2 binding sites (present in both HIF-1α and HIF1β replicates, and/or both HIF-2α and HIF1β replicates). 600 separate binding sites were identified, at 550 gene loci. h, Combined analysis of the 550 HIF-bound gene set and RNA-seq datasets using Gene Set Enrichment Analysis. Comparisons of HIF bound genes in 21% vs 1% O2, control HeLa vs HIF1β KO, and control HeLa vs SET1B KO shown. ES = enrichment score, NES = normalized enrichment score (P value threshold define by 1/number of permutations). i, Metagene plot of H3K4me3 ChIP-seq at the TSS and gene body of HIF1β dependent or independent genes identified in the RNA-seq analyses (Fig. 3d,e).

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Extended Data Fig. 10 HIF-1 and H3K4me3 ChIP-seq examples.

a-c, HIF-1α, HIF1β, and H3K4me3 ChIP-sequencing in wildtype, HIF1β and SET1B mixed population knockout HeLa cells treated with 21% or 1% O2 for 6 h. Analysis of H3K4me3 peaks using the IGV genome browser for normalized reads at specific genomic regions. Selected HIF target angiogenesis genes (a), HIF target glycolysis genes (b), and the non-HIF target BAP1 (c) are shown. Arrows indicate the directionality of the gene of interest, black box highlights region where H3K4me3 varies.

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Supplementary Data 1

MAGeCK analysis of sgRNA counts from TKO CRISPR screen.

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Ortmann, B.M., Burrows, N., Lobb, I.T. et al. The HIF complex recruits the histone methyltransferase SET1B to activate specific hypoxia-inducible genes. Nat Genet 53, 1022–1035 (2021). https://doi.org/10.1038/s41588-021-00887-y

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