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Cell-surface SLC nucleoside transporters and purine levels modulate BRD4-dependent chromatin states

Abstract

Metabolism negotiates cell-endogenous requirements of energy, nutrients and building blocks with the immediate environment to enable various processes, including growth and differentiation. While there is an increasing number of examples of crosstalk between metabolism and chromatin, few involve uptake of exogenous metabolites. Solute carriers (SLCs) represent the largest group of transporters in the human genome and are responsible for the transport of a wide variety of substrates, including nutrients and metabolites. We aimed to investigate the possible involvement of SLC-mediated solutes uptake and cellular metabolism in regulating cellular epigenetic states. Here, we perform a CRISPR–Cas9 transporter-focused genetic screen and a metabolic compound library screen for the regulation of BRD4-dependent chromatin states in human myeloid leukaemia cells. Intersection of the two orthogonal approaches reveal that loss of transporters involved with purine transport or inhibition of de novo purine synthesis lead to dysfunction of BRD4-dependent transcriptional regulation. Through mechanistic characterization of the metabolic circuitry, we elucidate the convergence of SLC-mediated purine uptake and de novo purine synthesis on BRD4-chromatin occupancy. Moreover, adenine-related metabolite supplementation effectively restores BRD4 functionality on purine impairment. Our study highlights the specific role of purine/adenine metabolism in modulating BRD4-dependent epigenetic states.

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Fig. 1: A SLC-focused CRISPR–Cas9 genetic screen identifies a functional link between SLC nucleoside transporters and BRD4.
Fig. 2: Metabolic perturbation on de novo purine synthesis leads to BRD4 inhibition.
Fig. 3: Impairing purine metabolism by blocking nucleoside uptake or de novo purine synthesis results in BRD4 inhibition.
Fig. 4: SLC-mediated purine uptake and de novo purine synthesis converge on BRD4 regulation.
Fig. 5: Adenine-containing nucleotide supplementation rescues BRD4 functionality on purine metabolism impairment.

Data availability

ChIP–seq and RNA-seq data have been deposited to NCBI GEO (GSE167374, GSE168099 and GSE168101). Source data are provided with this paper.

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Acknowledgements

We thank all members of the Superti-Furga and Kubicek laboratories for discussions, feedback and reagents, the Platform Austria for Chemical Biology (PLACEBO) for metabolic compound library plating, the Proteomics and Metabolomics Facility for metabolomics analyses and the BSF for next-generation sequencing. In particular, we thank A. Casiraghi for providing valuable feedback. CeMM and the Superti-Furga and Kubicek laboratories are supported by the Austrian Academy of Sciences. We acknowledge receipt of third-party funds from the Austrian Science Fund (grant nos. FWF SFB F4711 to F.K., J.W.B. and G.S-F. and I2192-B22 ERASE to V.S.), the European Research Council (grant no. ERC AdG 695214 GameofGates to K-C.L., E.G., A.B., U.G. and G.S-F.), the European Commission (Marie Skodowska-Curie Action Fellowship grant no. 661491 to E.G.) and an EMBO long-term Fellowship (grant no. ALTF 733-2016 to T.P.). S.G. is supported by the Peter and Traudl Engelhorn Foundation. Research in the Kubicek laboratory is supported by the Austrian Science Fund (grant no. FWF F4701) and the European Research Council under the European Union’s Horizon 2020 research and innovation programme (grant no. ERC-CoG-772437).

Author information

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Authors

Contributions

G.S.-F. conceived the study. K-C.L., E.G., S.K., S. Sdelci and G.S.-F. designed the study. K.-C.L. performed experiments and analysed the data. B.G., D.R. and K.K. performed and analysed the metabolomics experiments. T.P., A.B., J.W.B., J.-M.G.L. and S. Schick generated reagents and provided scientific insight. S. Schick helped on the ChIP experiment. S.G. analysed the ChIP–seq data. U.G. analysed the SLC CRISPR–Cas9 screen data. F.K. established the image-based metabolic compound library screen pipeline and analysed the data. V.S. analysed the transcriptomics data. K.-C.L., E.G., S. Sdelci and G.S-F. wrote the paper.

Corresponding author

Correspondence to Giulio Superti-Furga.

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Competing interests

G.S.-F., S.K. and A.B. are founders and own shares of Solgate GmbH, an SLC-focused company. S. Sdelci and S.K. have filed patent application WO 2018/087401 A2 on synergistic combinations with BRD4 inhibitors. The other authors declare no competing interests.

Additional information

Peer review information Nature Metabolism thanks Santosha Vardhana and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: George Caputa.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Characterization and validation of BRD4 reporter REDS clones.

a, RFP expression in REDS1, REDS15 and REDS17 clones with DMSO or 1 μM (+)-JQ1 treatment for 72 h. b, Representation of RFP insertion gene locus in REDS15 and REDS17 clones. Single RFP was inserted in chromosome 12, 410 bp (REDS15) or 673 bp (REDS17) upstream of STX2.

Extended Data Fig. 2 Generation of SLC nucleoside transporters knockout.

To generate the SLC knockout cells, we co-infected REDS cells with lentivirus-based Cas9-sgRNA expression cassettes (pLentiCRISPRv3-PuromycinR), pLentiGuide-BlasticidinR and pLentiGuide-NeomycinR carrying sgRen or sgSLC. The control and knockout cells were selected with 0.5 μg/ml puromycin, 20 μg/ml blasticidin and 250 μg/ml neomycin for 7 days.

Extended Data Fig. 3 Purine supplementation attenuates BRD4 inhibition phenotype in exogenous nucleosides limited condition.

a, Relative RFP intensity in REDS1 and REDS15 clones cultured in medium supplemented with 10% dialyzed serum (dFBS) over time. The log2 fold change of the RFP intensity was normalized with cells cultured in medium supplemented with 10% FBS. Mean ± s.d., n = 3 biologically independent samples. The p-value was calculated by unpaired t-tests. b, Relative RFP intensity in REDS15 cells after growing in medium supplemented with 10% dFBS for 10 days and further exogenously added with purine (adenosine and guanosine) or pyrimidine nucleosides (cytidine and thymidine) for 72 h. Mean ± s.d., n = 3 biologically independent samples.

Extended Data Fig. 4 Identification of the metabolic pathway involving in BRD4 regulation.

a, Summary of the targeted pathways of metabolic compound library. b, Representative images of REDS15 cells with DMSO, 1 μM (+)-JQ1, 10 μM CPI-0610 or 10 μM 6-MP treatment for 72 h. Scale bar, 100 μm. c, RFP expression in REDS1 cells with indicated concentrations of 6-MP-related compounds treatment for 72 h. d, RFP expression in REDS1 and REDS15 cells with indicated concentrations of pelitrexol and lometrexol treatment for 72 h. e, RFP expression in REDS1 and REDS15 cells with indicated concentrations of pyrimidine metabolism inhibitors treatment for 72 h. f, Scheme of purine metabolism, enzymes participating in the cascade and the pathway intermediates.

Extended Data Fig. 5 Investigation of BRD4 and its related histone acetylation markers expression in REDS15 cells upon purine metabolism impairment.

a, Western blot analysis of BRD4 expression in chromatin-bound, nucleoplasm and cytoplasmic fractions after 10 μM pelitrexol or lometrexol treatment for 72 h. Lamin B1, GAPDH and histone H3 were markers for nuclear-chromatin, cytoplasm and chromatin-bound protein fractions. b,c, Western blot analysis of BRD4, H3K27ac and pan-H3ac expression in cells with 10 μM 6-MP treatment or bearing triple SLC knockout (SLC TKO, 12 days after sgRNA transduction) (b), and in cells with 10 μM pelitrexol or lometrexol treatment for 72 h (c). ns, non-specific band. Source data

Extended Data Fig. 6 BRD4 ChIP-seq in REDS15 cells upon purine metabolism impairment.

a, Principal component analysis on BRD4 ChIP-seq raw counts in cells with indicated treatments. Upper panel, with 3 replicates of individual treatment. Lower panel, with replicate number 3 in 6-MP treated group (6-MP_BRD4_IP_rep3) excluded. b, Heatmaps representing BRD4 binding enrichment for all ChIP-seq consensus peak regions (N = 24,140) in individual replicates. c, Aggregate coverage plots showing mean enrichment for the different ChIP-seq consensus peak regions in cells with 10 μM 6-MP or 1 μM (+)-JQ1 treatment or bearing triple SLC knockout (SLC TKO), with ±10 kb centred on the regions. d, Genome browser visualization of BRD4 binding at its representative target genes MYC and BCL-2 in cells with indicated treatments.

Extended Data Fig. 7 Transcriptome analysis in cells with purine metabolism impairment.

a,b, Heat map of relative transcriptional change (a) and Pearson correlation coefficient of gene expression (b) in REDS1 and REDS15 clones with triple SLC knockout (SLC TKO, 12 days after sgRNA transduction), 10 μM 6-MP or 1 μM (+)-JQ1 treatment for 72 h. The log2 fold change of gene expression was calculated relatively to sgRen or DMSO treated cells. c,d, GSEA of the downregulated genes from the merged RNA-seq results of REDS1 and REDS15 clones (c). The GSEA plots show downregulation of MYC and E2F target gene sets (d). e, RT–qPCR analysis of MYC expression by using two different MYC primer sets in REDS1, REDS15 and K562 cells. Mean ± s.d., n = 3 biologically independent samples. f, Heat map of relative transcriptional change of purine metabolism genes in REDS1 and REDS15 clones with 10 μM 6-MP or 1 μM (+)-JQ1 treatment for 72 h or with triple SLC knockout (SLC TKO, 12 days after sgRNA transduction).

Extended Data Fig. 8 Loss of BRD4 inhibition phenotype in REDS15 cells after SLC sgRNA transduction for 23 days.

a, RFP expression in cells with SLC knockout 23 days after sgRNA transduction. b, TIDE analysis of SLC sgRNA editing efficiency. c, Metabolite composition in cells with triple SLC knockout (SLC TKO) 23 days after sgRNA transduction. The log2 fold change of metabolites level was calculated relatively to sgRen cells. AA, amino acids; NT, nucleotides; NB, nucleobases; NS, nucleosides. d, Western blot analysis of BRD4 expression in chromatin-bound, nucleoplasm and cytoplasmic fractions. Lamin B1, GAPDH and histone H3 were markers for nuclear-chromatin, cytoplasm and chromatin-bound protein fractions. ns, non-specific band. e, The viability of triple SLC knockout (SLC TKO) day 12 and day 23 cells after lometrexol treatment for 72 h. Cell numbers were measured by CASY Cell Counter and Analyzer and normalized with the control sgRen day 12 or day 23 cells. Mean ± s.d., n = 3 biologically independent samples. f, Relative RFP intensity in sgRen or triple SLC knockout (SLC TKO) day 12 or 23 cells with lometrexol treatment for 72 h. The log2 fold change of the RFP intensity was normalized with sgRen cells with DMSO treatment. g, Heat map of the relative transcriptional change of genes in SLC28, SLC29 and SLC35 families in REDS15 triple SLC knockout day 12 and day 23 cells normalized with the respective controls sgRen day 12 and day 23 cells. h, Stable isotope labeled +1 adenine or +3 glycine tracing into nucleotides in sgRen or triple SLC knockout (SLC TKO) day 12 and day 23 cells. Mean ± s.d., n = 3 biologically independent samples. The p-value was calculated by unpaired t-tests. Source data

Extended Data Fig. 9 Inhibition of nucleoside transport or de novo purine synthesis synergistically impairs leukemia cells growth with CPI-0610.

a,b, Dose-response matrix displaying the cell viability measured using CellTiter Glo (a) and CASY Cell Counter and Analyzer (b) of Jurkat E6.1, Raji and K562 cells treated with indicated concentrations of CPI-0610 or 6-MP, or in combination for 72 h.

Extended Data Fig. 10 Investigating the rescuing effect of nucleotide metabolites on BRD4 functionality.

a-c, Relative RFP expression in REDS1 and REDS15 cells co-treated with 100 μM nucleotide metabolites and 10 μM SLC29A4 inhibitor TC-T 6000 for 72 h (a), 10 nM dBET6 for 24 h (b) and 1 μM (+)-JQ1 for 72 h (c). The log2 fold change was normalized with DMSO treated cells. d, Western blot analysis of BRD4, c-MYC and BRD4-related histone acetylation markers expression in REDS15 cells co-treated with 100 μM nucleotide metabolites and 10 μM 6-MP or 1 μM (+)-JQ1 for 72 h. ns, non-specific band. Source data

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Source Data Fig. 1

Scans of western blot image_Fig. 1f.

Source Data Fig. 3

Scans of western blot image_Fig. 3b.

Source Data Extended Data Fig. 5

Scans of western blot image_Fig. 5a–c.

Source Data Extended Data Fig. 8

Scans of western blot image_Fig. 8b.

Source Data Extended Data Fig. 10

Scans of western blot image_Fig. 10d.

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Li, KC., Girardi, E., Kartnig, F. et al. Cell-surface SLC nucleoside transporters and purine levels modulate BRD4-dependent chromatin states. Nat Metab 3, 651–664 (2021). https://doi.org/10.1038/s42255-021-00386-8

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