DKC1-mediated pseudouridylation of rRNA targets hnRNP A1 to sustain IRES-dependent translation and ATF4-driven metabolic adaptation

Anamika Gupta; Mohit Bansal; Jane Ding; Suman Karki; Madhuparna Pandit; Sunil Sudarshan; Han-Fei Ding

doi:10.1126/sciadv.adv9401

. 2025 Aug 29;11(35):eadv9401. doi: 10.1126/sciadv.adv9401

DKC1-mediated pseudouridylation of rRNA targets hnRNP A1 to sustain IRES-dependent translation and ATF4-driven metabolic adaptation

Anamika Gupta ^1,^2,^†, Mohit Bansal ^1,^2,^*,^†, Jane Ding ^1,², Suman Karki ^2,³, Madhuparna Pandit ^2,³, Sunil Sudarshan ^2,³, Han-Fei Ding ^1,^2,^*

PMCID: PMC12396317 PMID: 40880467

Abstract

The pseudouridine synthase DKC1 regulates internal ribosome entry site (IRES)–dependent translation and is up-regulated in cancers by the MYC family of oncogenes. The functional significance of DKC1 up-regulation and the mechanistic connection between pseudouridylation and IRES-mediated translation remain poorly understood. Here, we report that DKC1 drives an ATF4-mediated transcriptional program that supports amino acid metabolism and stress adaptation. We identify hnRNP A1, an IRES trans-acting factor, as a critical downstream mediator of DKC1 in sustaining ATF4 expression and IRES-dependent translation. Mechanistically, DKC1-mediated pseudouridylation at two specific 28S ribosomal RNA sites is crucial for maintaining hnRNP A1 protein expression. In turn, hnRNP A1 binds and stabilizes ATF4 messenger RNA, preferentially promoting IRES-dependent translation of ATF4 variant 1. Furthermore, cellular stress induces hnRNP A1, which is necessary for stress-induced ATF4 protein expression. Collectively, our findings uncover an MYC-driven DKC1-hnRNP A1 axis that links IRES-dependent translation and ATF4-mediated metabolic adaptation, thereby supporting cancer cell survival under metabolic stress during tumor progression.

DKC1-mediated pseudouridylation drives the metabolic adaptation that allows cancer cells to survive and proliferate.

INTRODUCTION

The dyskerin pseudouridine synthase 1 (DKC1) gene encodes the evolutionarily conserved protein dyskerin (hereafter referred to as DKC1) (1). Mutations in the DKC1 gene cause X-linked dyskeratosis congenita (X-DC), a genetic disorder affecting highly proliferating tissues and characterized by bone marrow failure, immunodeficiency, abnormal skin pigmentation, nail dystrophy, stem cell defects, premature aging, and an elevated cancer risk (1–3). Hypomorphic Dkc1 mutant mice, which express Dkc1 at ~30% of normal levels, recapitulate hallmark features of X-DC, including bone marrow failure and increased cancer susceptibility (4).

DKC1 is a pseudouridine synthase that catalyzes the conversion of uridine to pseudouridine through base rotation (5–8). Unlike other members of the pseudouridine synthase family, DKC1 functions within a complex of ribonucleoproteins and box H/ACA small nucleolar RNAs (snoRNAs). Each snoRNA within this complex acts as a guide, using base complementarity to select the target RNA and the specific uridine for pseudouridylation (7, 9). The primary targets of DKC1-mediated pseudouridylation are ribosomal RNAs (rRNAs) and spliceosomal small nuclear RNAs. Consequently, DKC1 plays a critical role in the biogenesis of ribosomes and spliceosomes (10).

A 2006 study first implicated DKC1 in the regulation of internal ribosome entry site (IRES)–dependent translation. Cells from patients with X-DC and Dkc1 hypomorphic mutant mice exhibited impaired translation of IRES-containing mRNAs, including those encoding p27Kip1, BCL-XL, and XIAP (11). Subsequent studies further showed that reduced DKC1 levels compromise the IRES-dependent translation of p53 mRNA (12, 13). Moreover, reduced DKC1-dependent rRNA pseudouridylation was found to lower ribosome affinity for a viral IRES element (14), suggesting that DKC1-mediated pseudouridylation of rRNA promotes IRES-dependent translation. However, the detailed mechanisms underlying this process remain poorly understood.

We investigated the role of DKC1 in cancer, prompted by genetic evidence linking DKC1 mutations to impaired cellular proliferation (1–3, 15). In addition, DKC1 has been identified as a direct transcriptional target of the MYC oncogene family, including MYC (16) and MYCN (17), which drive the development of various cancers, such as neuroblastoma, by promoting cell proliferation and metabolic reprogramming (18–21). Neuroblastoma, a pediatric cancer of the sympathetic nervous system, accounts for 15% of childhood cancer-related deaths (22, 23). DKC1 is highly expressed in neuroblastoma and is essential for the tumorigenic growth of neuroblastoma cell lines (17). Our investigation revealed that a key function of DKC1 is to sustain the steady-state and stress-induced expression of activating transcription factor 4 (ATF4), a master transcriptional regulator of amino acid metabolism and the integrated stress response (24–27). This function of DKC1 is mediated through pseudouridylation of 28S rRNA, which promotes hnRNP A1 protein synthesis to drive IRES-dependent translation and ATF4 expression. Together, our findings uncover an MYC-activated DKC1 pseudouridylation program that promotes cancer metabolic reprogramming and stress adaptation through hnRNP A1–mediated IRES-dependent translation.

RESULTS

DKC1 sustains ATF4 expression and downstream amino acid metabolism genes

We analyzed RNA sequencing (RNA-seq) datasets from independent neuroblastoma patient cohorts (28, 29), revealing that high DKC1 mRNA levels are significantly associated with advanced neuroblastoma stages and poor patient prognosis (fig. S1, A and B). Consistent with previous findings (17), the knockdown of DKC1 expression by short hairpin RNA (shRNA; shDKC1) in neuroblastoma cell lines inhibited cell proliferation and xenograft growth, prolonging the survival of tumor-bearing mice (fig. S1, C to F). Conversely, DKC1 overexpression in neuroblastoma cell lines significantly accelerated their growth (fig. S1, G and H). These results provide a strong rationale for using neuroblastoma as a model system to explore DKC1-mediated RNA pseudouridylation in cancer and its underlying mechanisms.

To gain molecular insights into the growth-promoting function of DKC1 in neuroblastoma, we performed RNA-seq analysis in MYCN-amplified BE(2)-C cells following shRNA-mediated DKC1 knockdown (table S1). A total of 531 genes (≥−1.50-fold, P < 0.05) was down-regulated following DKC1 knockdown (table S1). Gene ontology (GO) analysis revealed that the down-regulated genes were significantly enriched for GO terms related to amino acid and pyrimidine nucleotide metabolic processes (Fig. 1A and table S2). These down-regulated genes include those encoding ATF4, amino acid synthesis enzymes (e.g., ASNS, PSAT1, and SHMT2), and amino acid transporters (e.g., SLC7A5 and SLC7A11) (Fig. 1B and table S2). Gene set enrichment analysis (GSEA) further revealed that DKC1 knockdown reduced the mRNA expression of genes involved in the cellular response to amino acid starvation (AAR) mediated by the eIF2α kinase EIF2AK4 (GCN2) (Fig. 1C) (24–27). To validate the shDKC1 RNA-seq data, we performed RNA-seq analysis in BE(2)-C cells treated with a DKC1 inhibitor, pyrazofurin (PF) (30), and obtained similar results: DKC1 inhibition (DKC1i) down-regulated ATF4 and genes involved in amino acid synthesis and the GCN2-mediated AAR (fig. S2, A and B, and table S3). We further confirmed the RNA-seq findings by analyzing published proteomics data (31), showing that DKC1 knockdown decreased the expression of proteins involved in amino acid synthesis and transport and one-carbon metabolism, including ASNS, MTHFD2, PHGDH, PSAT1, SHMT2, and SLC7A5 (fig. S2C and table S4).

Fig. 1. — (A) GO analysis of RNA-seq data showing the top biological processes for genes down-regulated (≥−1.5-fold) in neuroblastoma BE(2)-C cells following DKC1 knockdown. (B) Volcano plot showing the down-regulation of genes involved in amino acid metabolism following DKC1 knockdown. (C) GSEA of RNA-seq data showing the down-regulation of genes involved in the EIF2AK4 (GCN2) response to amino acid deficiency following DKC1 knockdown. ES, enrichment score; NES, normalized enrichment score; FDR, false discovery rate. (D and E) Immunoblotting (D) and qRT-PCR (E) showing the down-regulation of genes involved in amino acid metabolism following DKC1 knockdown in neuroblastoma BE(2)-C and LA1-55n cells. (F and G) qRT-PCR (F) and immunoblotting (G) showing DKC1 overexpression up-regulated genes involved in amino acid metabolism in neuroblastoma BE(2)-C and SK-N-AS cells. qRT-PCR data [(E) and (F)] are presented as the means ± SEM (n = 4) and analyzed using two-way ANOVA; **P < 0.01, ***P < 0.001.

We performed quantitative reverse transcription polymerase chain reaction (qRT-PCR) and immunoblot analyses to validate the RNA-seq and proteomics findings. DKC1 knockdown using multiple shDKC1 constructs (Fig. 1, D and E) or inhibition (fig. S2, D to G) led to reduced mRNA and protein expression of the same set of genes. Conversely, DKC1 overexpression resulted in increased mRNA and protein expression of these genes (Fig. 1, F and G).

To determine whether the DKC1 regulation of ATF4 is physiologically relevant, we assessed the impact of DKC1 inhibition on cellular stress responses using models of endoplasmic reticulum (ER) stress and the AAR. We treated BE(2)-C and HeLa cells with tunicamycin (an ER stress inducer) or histidinol (HisOH; an AAR inducer) (32, 33) in the absence or presence of the DKC1 inhibitor pyrazofurin. In control cells, tunicamycin or HisOH treatment induced ATF4, and this induction was substantially reduced in cells treated with pyrazofurin (fig. S2H).

We next asked whether ATF4 functions as a key downstream effector of DKC1 in regulating genes involved in amino acid metabolism. To test this, we generated BE(2)-C_tetoff-ATF4 cells with inducible ATF4 expression upon doxycycline withdrawal. ATF4 overexpression rescued the suppression of amino acid synthesis genes, including ASNS, PHGDH, and PSAT1, caused by DKC1 knockdown or inhibition (fig. S3, A and B). Collectively, these findings demonstrate that DKC1 is critical for sustaining the ATF4-dependent transcriptional program that drives the expression of genes essential for amino acid biosynthesis and transport, thereby explaining its functional importance in neuroblastoma.

DKC1 regulates amino acid metabolism

In light of the gene expression data, we performed targeted metabolomics to assess the impact of DKC1 inhibition on cellular metabolism. Metabolomics profiling of BE(2)-C cells treated with the DKC1 inhibitor pyrazofurin revealed significant changes (P < 0.05) in the levels of 131 metabolites (table S5). Pathway analysis of down-regulated metabolites using MetaboAnalyst (34) showed significant enrichment in amino acid metabolism pathways, including those for alanine, glutamate, methionine, glycine and serine, and aspartate (Fig. 2A).

Fig. 2. — (A) Enriched metabolic pathways identified through metabolite set enrichment analysis of down-regulated metabolites in BE(2)-C cells treated with the DKC1 inhibitor pyrazofurin at 1 μM for 72 hours. (B) Relative levels of amino acids in BE(2)-C cells following DKC1 inhibition. (C) Schematic of the serine-glycine synthesis pathway with indicated enzymes and metabolites. Fold changes (numbers in parentheses) in mRNA expression of relevant enzymes were from qRT-PCR. (D) Relative levels of the serine-glycine pathway metabolites. (E and F) qRT-PCR (E) and immunoblotting (F) showing that DKC1 inhibition abrogated the MYCN up-regulation of genes for amino acid synthesis in neuroblastoma SHEP1 cells. (G) MYCN activation by 4OHT (4-hydroxytamoxifen) promoted cell proliferation (control) but sensitized cells to DKC1 inhibition [pyrazofurin (PF)]. (H) IC₅₀ analysis of pyrazofurin [DKC1 inhibition (DKC1i)] in SHEP-MYCNER cells with or without MYCN activation by 4OHT for 24 hours, followed by treatment with different concentrations of DKC1i for 24 hours. Data in (B) and (D) represent the means ± SEM (n = 6) and were analyzed by unpaired, two-tailed Student’s t test; data in (E), (G), and (H) represent the means ± SEM (n = 4) and were analyzed using a two-way ANOVA. **P < 0.01 and ***P < 0.001.

Analysis of individual amino acids revealed widespread changes, consistent with the gene expression data and highlighting a key role of DKC1 in regulating amino acid metabolism. For instance, levels of essential amino acids such as phenylalanine, threonine, tryptophan, and valine were significantly reduced following DKC1 inhibition (Fig. 2B), potentially due to the down-regulation of SLC7A5 (Fig. 1, B, D, and E), a key transporter responsible for their import (35, 36).

We further analyzed the serine-glycine synthesis pathway, which uses the glycolytic intermediate 3-phosphoglycerate (3PG) to generate serine and glycine (Fig. 2C). DKC1 inhibition led to reduced expression of the pathway enzymes PHGDH, PSAT1, and SHMT2 (fig. S2, D to G), resulting in a significant decrease in glycine levels and an accumulation of upstream intermediates, including serine and 3PG (Fig. 2D). Collectively, these metabolomics and gene expression data underscore a critical role of DKC1 in regulating amino acid metabolism in neuroblastoma cells.

DKC1 is a downstream effector of MYCN in sustaining the expression of ATF4 and amino acid metabolism genes

DKC1 has been identified as a direct transcriptional target of MYCN in neuroblastoma (17). Consistent with this finding, RNA-seq data from the SEQC neuroblastoma patient cohort (28) revealed a strong positive correlation in mRNA expression between DKC1 and MYCN in tumor samples (fig. S4A). We validated the MYCN-dependent up-regulation of DKC1 expression by qRT-PCR and immunoblotting (Fig. 2, E and F, and fig. S4, B and C).

Previously, we demonstrated that MYCN drives amino acid biosynthesis in neuroblastoma by promoting the ATF4-dependent transcriptional up-regulation of metabolic enzymes (37). This function was abrogated by DKC1 inhibition (Fig. 2, E and F) or knockdown (fig. S4, B and C). Moreover, DKC1 inhibition impaired MYCN-driven cell proliferation (Fig. 2G and fig. S4D), and MYCN overexpression sensitized neuroblastoma cells to the DKC1 inhibitor pyrazofurin, reducing its IC₅₀ (median inhibitory concentration) by 12-fold (Fig. 2H). These findings indicate that MYCN overexpression increased the dependency on DKC1-mediated activation of the ATF4 transcriptional program to support neuroblastoma cell survival.

Collectively, our results identify DKC1 as a critical downstream effector of MYCN, driving ATF4 expression and amino acid synthesis to sustain neuroblastoma cell proliferation. These findings reveal the functional significance of MYCN-driven DKC1 up-regulation in neuroblastoma.

DKC1 targets the IRES trans-acting factor hnRNP A1

To further investigate the mechanism of DKC1 action, we aimed to identify downstream effectors that mediate its role in IRES-dependent translation. We performed a Venn diagram analysis to integrate three gene sets: (i) genes down-regulated by DKC1 inhibition (log₂ fold change ≥−1.50, adjusted P < 0.01), (ii) genes whose expression is positively correlated with DKC1 expression in neuroblastoma tumors (R > 0.7, P < 1.14 × 10⁻⁷²) (28), and (iii) genes encoding known IRES trans-acting factors (ITAFs) (38). Our analysis identified a single candidate that met all criteria: hnRNP A1, encoded by the HNRNPA1 gene.

Multiple lines of correlative evidence support hnRNP A1 as a potential effector of DKC1. First, both DKC1 (11, 39, 40) and hnRNP A1 (41, 42) are known regulators of IRES-mediated translation. Second, HNRNPA1 mRNA levels are positively correlated with DKC1 mRNA levels in neuroblastoma tumors (Fig. 3B). Third, DKC1 and hnRNP A1 exhibit similar phenotypes in neuroblastoma: (i) Higher HNRNPA1 mRNA expression is significantly associated with higher MYCN mRNA expression, advanced tumor stages, and poor patient prognosis (fig. S5, A to C); (ii) hnRNP A1 overexpression promotes neuroblastoma cell proliferation (Fig. 3, C and D); and (iii) the knockdown of hnRNP A1 expression using multiple shRNA constructs (Fig. 3E) inhibits neuroblastoma cell growth both in culture (Fig. 3F) and in immunodeficient mice (Fig. 3G), leading to the prolonged survival of xenograft-bearding mice (Fig. 3H). Thus, similar to DKC1, elevated hnRNP A1 expression is essential for sustaining the proliferation and tumorigenicity of neuroblastoma cells.

Fig. 3. — (A) Venn diagram showing hnRNP A1 as the only gene overlapping among three datasets: genes positively correlated with *DKC1* expression in the SEQC neuroblastoma patient cohort, genes down-regulated by DKC1i, and known ITAFs. (B) Positive correlation between DKC1 and *HNRNPA1* mRNA expression in neuroblastoma tumors (SEQC cohort, n = 498). Pearson’s R and P value are indicated. (C) Immunoblotting of hnRNP A1 in neuroblastoma BE(2)-C cells following hnRNP A1 overexpression. (D) hnRNP A1 overexpression promotes proliferation in BE(2)-C and SK-N-AS neuroblastoma cells. (E) Immunoblotting of hnRNP A1 in neuroblastoma BE(2)-C and SK-N-AS cells following hnRNP A1 knockdown. (F) hnRNP A1 knockdown reduces proliferation in BE(2)-C and SK-N-AS cells. (G and H) hnRNP A1 knockdown impairs tumor growth in BE(2)-C xenografts (G) and prolongs the event-free survival of xenograft-bearing mice (H). Cell proliferation data [(D) and (F)] are presented as the means ± SEM (n = 4). Quantitative data [(D), (F), and (G)] were analyzed using a two-way ANOVA. ***P < 0.001.

We obtained direct evidence that hnRNP A1 is a downstream target of DKC1. DKC1 knockdown (Fig. 4, A and B) or inhibition (Fig. 4, C and D) substantially reduced both hnRNP A1 protein and mRNA levels in neuroblastoma cell lines. Similar effects were observed in HeLa cells following DKC1 knockdown (Fig. 4, A and B), indicating that the DKC1-mediated regulation of hnRNP A1 is not cell type specific. These findings suggest that DKC1 is required to maintain steady-state hnRNP A1 expression at both the mRNA and protein levels. DKC1 overexpression increased hnRNP A1 protein levels without significantly affecting its mRNA expression (Fig. 4, E and F), suggesting enhanced translation of existing mRNA. The mechanism by which DKC1 sustains basal HNRNPA1 mRNA expression remains unclear but may involve indirect effects on transcription or RNA stability, as DKC1 is not known to function as a transcription factor.

To investigate the function of DKC1 in regulating HNRNPA1 mRNA translation, we performed l-homopropargylglycine (L-HPG) incorporation assays in control and DKC1-overexpressing BE(2)-C cells (Fig. 4E). L-HPG is a methionine analog containing an alkyne group that becomes incorporated into nascent proteins during active translation, enabling the selective labeling of newly synthesized proteins. These nascent proteins can be detected via click chemistry with TAMRA directly on the blot membrane, followed by incubation with an anti-TAMRA antibody. When combined with immunoprecipitation, this method allows for sensitive and specific quantification of newly synthesized proteins (43, 44). We found that DKC1 overexpression significantly increased levels of newly synthesized hnRNP A1 (Fig. 4, G and H).

To further validate the role of DKC1 in the translational regulation of hnRNP A1 expression, we performed polysome profiling, as actively translated mRNAs are typically associated with multiple ribosomes (polysomes) (45). DKC1 overexpression markedly increased the abundance of HNRNPA1 mRNA in heavy polysome fractions (Fig. 4, I and J) without affecting the distribution of control mRNAs such as β₂-microglobulin (B2M) and RPS25 (fig. S6, A and B). Together, these complementary findings provide strong evidence that DKC1 promotes HNRNPA1 mRNA translation.

hnRNPA 1 is a downstream mediator of DKC1 in sustaining ATF4 expression

As shown above, a key function of DKC1 is to sustain ATF4 expression. To investigate the functional relationship between DKC1 and hnRNP A1 in regulating ATF4 expression, we overexpressed hnRNP A1 in cells with DKC1 knockdown. hnRNP A1 overexpression fully rescued both ATF4 expression (Fig. 5A) and cell growth (Fig. 5B) and conferred resistance to DKC1 inhibition (fig. S6C). These findings indicate that hnRNP A1 acts downstream of DKC1 to sustain ATF4 expression and cell proliferation.

Fig. 5. — (A) hnRNP A1 overexpression in 293FT cells rescues ATF4 protein expression suppressed by DKC1 knockdown. (B) hnRNP A1 overexpression restores cell proliferation suppressed by DKC1 knockdown. Cell growth data are presented as the means ± SEM (n = 4) and analyzed using a two-way ANOVA. (C and D) qRT-PCR (C) and immunoblotting (D) showing decreased mRNA and protein levels of amino acid metabolism–related genes following hnRNP A1 knockdown in the indicated neuroblastoma cell lines. qRT-PCR data are presented as the means ± SEM (n = 4) and analyzed by a two-way ANOVA. (E) Immunoblotting showing that hnRNP A1 knockdown abrogates stress-induced up-regulation of ATF4 and its downstream amino acid metabolism targets in BE(2)-C and SHEP1 cells. HisOH, AAR inducer; Tm, ER stress inducer. (F and G) hnRNP A1 binds ATF4 mRNA: (F) immunoblotting of hnRNP A1 in control (IgG) and anti–hnRNP A1 immunoprecipitates; (G) qRT-PCR analysis of ATF4 and ACTIN mRNAs in the corresponding immunoprecipitates. Data are shown as the means ± SEM (n = 2) and analyzed by a two-way ANOVA. (H) hnRNP A1 knockdown reduces ATF4 mRNA stability in BE(2)-C cells. RNA was collected at the indicated time points following treatment with actinomycin D (5 μg/ml) and analyzed by qRT-PCR. ATF4 mRNA levels were normalized to B2M and presented as a fraction of the initial value at time zero. h, hours. Data are shown as the means ± SEM (n = 3). ***P < 0.001; ns, not significant.

In cells overexpressing hnRNP A1, shDKC1 constructs effectively reduced DKC1 mRNA expression (fig. S6D) but failed to decrease DKC1 protein levels (Fig. 5A), suggesting that hnRNP A1 overexpression stabilizes DKC1 protein levels. Consistent with the idea, both DKC1 and hnRNP A1 are localized to the nucleus (fig. S6E) and can be coimmunoprecipitated with antibodies against either protein (fig. S6F). These observations suggest that DKC1 and hnRNP A1 can form a complex, providing a potential mechanism by which hnRNP A1 stabilizes DKC1 protein levels.

In further support of the model that hnRNP A1 acts downstream of DKC1, the knockdown of hnRNP A1 expression using various shHNRNPA1 constructs fully recapitulated the effect of DKC1 knockdown, including the down-regulation of ATF4 and amino acid metabolism–related genes at both the mRNA and protein levels across multiple neuroblastoma cell lines (Fig. 5, C and D, and fig. S6G). We also examined the effect of hnRNP A1 overexpression. The human HNRNPA1 gene produces two main mRNA variants, V1 (NM_002136.4) and V2 (NM_031157.4), and when overexpressed, both variants increased ATF4 protein expression (fig. S6H).

To determine the physiological relevance of hnRNP A1–mediated regulation of ATF4, we evaluated the impact of hnRNP A1 knockdown on cellular stress responses. Control (shGFP) and hnRNP A1 knockdown cells were treated with tunicamycin to induce ER stress or HisOH to activate the AAR. In control cells, treatment with tunicamycin or HisOH induced ATF4 expression along with key enzymes and transporters involved in amino acid metabolism (Fig. 5E). This induction was markedly attenuated in hnRNP A1 knockdown cells (Fig. 5E). Notably, both ER stress and the AAR also elevated hnRNP A1 protein expression (Fig. 5E), further supporting its critical role in cellular stress responses.

Next, we investigated the mechanisms by which hnRNP A1 sustains ATF4 expression. Given that hnRNP A1 is an RNA binding protein (46, 47), we performed RNA immunoprecipitation using an antibody to hnRNP A1 (Fig. 5F). qRT-PCR analysis showed a significant enrichment of ATF4 mRNA in hnRNP A1–bound RNA compared to control immunoglobulin G (IgG) (Fig. 5G). To further validate this interaction, we examined published RNA interactome data generated through enhanced cross-linking immunoprecipitation analysis of hundreds of human RNA binding proteins (48). These data confirmed the binding of hnRNP A1 to ATF4 mRNA in two independent cancer cell lines, HepG2 and K562 (fig. S7A). Moreover, the knockdown of hnRNP A1 resulted in a twofold reduction in the half-life of ATF4 mRNA (Fig. 5H).

Together, these findings demonstrate that hnRNP A1 acts downstream of DKC1 to promote ATF4 mRNA expression by binding and stabilizing its mRNA, thereby providing a mechanistic explanation for the effects of DKC1 knockdown or overexpression on ATF4 mRNA abundance (Fig. 1, E and F).

hnRNP A1 promotes IRES-dependent ATF4 protein expression

Both DKC1 (11, 39) and hnRNP A1 (41, 42, 49–51) are known to promote the translation of mRNAs containing IRES elements, including those encoding BCL-XL, CCND1, MYC, p27Kip1, and XIAP. While DKC1 knockdown had no effect on the mRNA expression of CCND1, it modestly reduced BCL-XL and XIAP mRNA levels in an shRNA construct–dependent manner (fig. S7A). Whether this reflects changes in transcription or mRNA stability remains to be determined. In contrast, DKC1 knockdown by various shRNA constructs consistently and markedly reduced CCND1, BCL-XL, and XIAP protein levels (Fig. 6A). This reduction was completely reversed by hnRNP A1 overexpression (Fig. 6B), and similar results were observed upon DKC1 inhibition (Fig. 6C). Furthermore, hnRNP A1 overexpression alone was sufficient to increase protein levels of CCND1, BCL-XL, and XIAP in neuroblastoma cell lines (Fig. 6D) and in HeLa cells (fig. S7B). Collectively, these results support a model in which hnRNP A1 functions downstream of DKC1 to promote the IRES-dependent translation of key survival and cell cycle regulators.

Fig. 6. — (A) Immunoblotting showing protein levels of IRES-containing genes following DKC1 knockdown. (B and C) hnRNP A1 overexpression rescues IRES-dependent protein expression suppressed by DKC1 knockdown (B) or inhibition (C). (D) hnRNP A1 overexpression up-regulates both DKC1 and IRES-dependent protein expression. (E) Schematic of ATF4 V1 and V2 mRNAs highlighting the main ORF and IRES site located in the 5′UTR of V1. (F and G) Immunoblotting (F) and quantification (G) of ATF4 variant protein expression 48 hours after cotransfection of 293FT ATF4 KO cells with pCW57.1-ATF4 V1 or pCW57.1-ATF4 V2, along with plasmids expressing hnRNP A1, DKC1, or both. ATF4 levels were normalized to α-tubulin. (H) Schematic representation of the basal bicistronic luciferase reporter construct (pRF) and constructs containing 5′UTRs of EMCV, ATF4 V1, ATF4 V2, or truncated mutants of the ATF4 V1 5′UTR. (I) Luciferase assays in 293FT cells cotransfected with individual reporter constructs and either empty vector (control) or hnRNP A1–expressing plasmids. After 48 hours, cells were harvested and relative luciferase activity was measured to assess IRES-dependent translational regulation. [(G) and (I)] Data are presented as the means ± SEM (n = 3) and analyzed using two-way ANOVA. *P < 0.05, **P < 0.01, ***P < 0.00, and ****P < 0.0001.

The human ATF4 gene generates two main mRNA variants, V1 (NM_001675.4) and V2 (NM_182810.3), which encode the same protein but differ in their 5′ untranslated region (5′UTR). The V2 transcript lacks an internal segment present in the V1 transcript 5′UTR (Fig. 6E). This internal segment in V1 reportedly contains an IRES element that mediates IRES-dependent translation (52). We hypothesized that DKC1 and hnRNP A1 may enhance IRES-dependent ATF4 mRNA translation and protein expression. To test this, 293FT ATF4 knockout (KO) cells were cotransfected with plasmids coding for either ATF4 V1 or V2, alongside DKC1- and/or hnRNP A1–expressing plasmids. Overexpression of DKC1 and hnRNP A1, alone or in combination, increased ATF4 V1 and V2 protein levels (Fig. 6, F and G). The increase was significantly higher for ATF4 V1, particularly under hnRNP A1 overexpression.

To further investigate whether hnRNP A1 promotes the IRES-dependent translation of ATF4 mRNA, we conducted dual luciferase reporter assays using previously characterized constructs (Fig. 6H) (52). The basal bicistronic reporter plasmid pRF contains Renilla luciferase (RLuc) as the first cistron (cap-dependent translation) and firefly luciferase (FLuc) as the second cistron (cap-independent translation). To evaluate IRES activity, candidate IRES elements were inserted between the two cistrons, including the well-characterized encephalomyocarditis virus (EMCV) IRES (positive control), ATF4 V1 5′UTR, ATF4 V2 5′UTR, or various truncated mutants of the V1 5′UTR (Fig. 6H). Each reporter construct was cotransfected into 293FT cells with either a control vector or plasmid expressing hnRNP A1, and IRES activity was quantified as the FLuc/RLuc ratio (Fig. 6I). The EMCV IRES significantly increased FLuc expression compared to the pRF baseline, with a modest, nonsignificant enhancement by hnRNP A1 overexpression. Insertion of the ATF4 V2 5′UTR had a minimal impact on FLuc expression, regardless of hnRNP A1 overexpression. In contrast, the full-length ATF4 V1 5′UTR markedly elevated FLuc expression, which was further and significantly enhanced by hnRNP A1 overexpression. Truncation analyses revealed that the hnRNP A1–responsive element resides within uORF3 (Fig. 6I; ATF4 V1-F3), whereas a region downstream of uORF3 and overlapping with the 5′ end of uORF4 displayed hnRNP A1–independent IRES activity (Fig. 6I; ATF4 V1-F6). These findings are consistent with the previous study that localized the ATF4 IRES element to a region encompassing uORF3 and the 5′ end of uORF4 (52). Collectively, our results support a model in which hnRNP A1 enhances ATF4 protein expression via an IRES-dependent mechanism.

DKC1-mediated 28S rRNA pseudouridylation promotes hnRNP A1 expression to drive IRES-dependent translation and ATF4 expression

A previous study demonstrated that pseudouridylation at two specific sites in 28S rRNA, Ψ4331 and Ψ4966, is significantly reduced in ribosomes from patients with X-DC (53). To assess the impact of DKC1-dependent rRNA pseudouridylation on the regulation of hnRNP A1 and ATF4 expression, we analyzed rRNA samples collected on days 4 and 12 following DKC1 knockdown by Nanopore direct RNA-seq. Consistent with previous findings, our analysis revealed a time-dependent reduction in pseudouridine levels at Ψ4331 and Ψ4966 in 28S rRNA (Fig. 7, A and B). In contrast, the knockdown of another pseudouridine synthase, PUS7, had no effect on pseudouridylation at these sites (fig. S8A), confirming that pseudouridylation at these 28S rRNA positions is specifically DKC1 dependent. Furthermore, our analysis of published data (53–57) demonstrated that pseudouridine modifications at 28S rRNA positions U4331 and U4966 occur at high stoichiometry and are conserved across diverse cell lines (fig. S8B), supporting their potential functional significance.

Using the RNAsnoop tool (58), we identified potential box H/ACA snoRNAs associated with these Ψ sites: SNORA69 and SNORA41 for Ψ4331 and SNORA24 for Ψ4966 (fig. S8C). Analysis of published RNA interactome data revealed that DKC1 interacts with SNORA24 and SNORA41 in HepG2 cells (fig. S8D) (48). In addition, independent DKC1-RNA interactome datasets confirm DKC1 binding to SNORA24 and SNORA69 (59). To investigate the functional significance of these snoRNAs, we used specific antisense oligonucleotides (ASOs) to reduce their expression using an ASO targeting snoRNA U3 (60) as a control (Fig. 7C). We also assessed whether the knockdown of each snoRNA affected the expression of its corresponding host gene: SNORA41 is hosted within EEF1B2, SNORA69 within RPL39, and SNORA24 within SNHG8 (fig. S8E). ASO-mediated depletion of these snoRNAs did not significantly alter the mRNA expression levels of their host genes (fig. S8F).

As expected, for example, ASO-mediated SNORA41 knockdown reduced pseudouridine at Ψ4331 (Fig. 7D), recapitulating the effect of DKC1 depletion. The knockdown of these snoRNAs decreased protein levels of hnRNP A1 and ATF4, along with reduced IRES-dependent expression of MYC, XIAP, CCND1, and BCL-XL (Fig. 7, E and F). In contrast, the knockdown of the control snoRNA U3 had no significant effect (Fig. 7E). Furthermore, overexpression of hnRNP A1 rescued the reduction in ATF4, MYC, and BCL-XL protein levels caused by ASO treatment (Fig. 7G), indicating that the effect of DKC1-mediated pseudouridylation on IRES-dependent translation is mediated through hnRNP A1. Collectively, these findings suggest that DKC1-mediated rRNA pseudouridylation enhances hnRNP A1 protein expression to promote IRES-dependent translation and ATF4 expression.

DISCUSSION

Our study identifies an MYC/MYCN–driven DKC1-hnRNP A1 axis as a critical regulator of IRES-dependent translation and activation of the ATF4-mediated transcriptional program that supports cancer cell survival and proliferation. Mechanistically, DKC1-mediated pseudouridylation of 28S rRNA enhances the translation of HNRNPA1 mRNA, leading to increased hnRNP A1 protein levels. hnRNP A1, in turn, binds and stabilizes ATF4 mRNA, promoting ATF4 protein expression through IRES-mediated translation (Fig. 8). While we previously reported that MYCN transcriptionally up-regulates ATF4 mRNA expression (37), the present findings demonstrate that MYCN also amplifies ATF4 expression through IRES-dependent translation by engaging the DKC1-hnRNP A1 axis. ATF4 orchestrates the cellular stress response to nutrient deprivation (24–27, 61), and its up-regulation confers a survival advantage to cancer cells under persistent metabolic stress, which frequently arises in the context of MYC-driven proliferation (37, 62–65). Thus, the DKC1-hnRNP A1 axis represents a specialized mechanism for sustaining the selective synthesis of stress-adaptive proteins, facilitating tumor growth and progression in metabolically challenging microenvironments.

Fig. 8. — Oncogenic MYC/MYCN activation up-regulates the pseudouridine synthase DKC1, which modifies 28S rRNA to support the expression of the RNA binding protein hnRNP A1. In turn, hnRNP A1 promotes the IRES-dependent translation of ATF4, a key regulator of the integrated stress response. Elevated ATF4 activates a transcriptional program that enhances amino acid metabolism and promotes metabolic adaptation, thereby enabling cancer cell survival under stress.

Our study provides specific mechanistic insights into how DKC1 regulates IRES-dependent translation. We show that DKC1-dependent pseudouridylation at two specific sites in 28S rRNA, Ψ4331 and Ψ4966, mediates its effect on IRES-dependent translation. It has been previously reported that pseudouridylation at these two sites is specifically and significantly reduced in ribosomes isolated from patients with familial dyskeratosis congenita (53). In agreement with the report, we observed a time-dependent reduction in pseudouridine levels at these two sites following DKC1 knockdown. We identified three candidate box H/ACA snoRNAs that may guide DKC1-mediated pseudouridylation at these sites, SNORA41 and SNORA69 for Ψ4331 and SNORA24 for Ψ4966. The ASO-mediated knockdown of these snoRNAs fully recapitulated the effect of DKC1 depletion on hnRNP A1 and ATF4 expression, as well as other proteins regulated through IRES-dependent translation. These findings support the concept of specialized ribosomes, which can selectively translate subsets of mRNAs that contain unique regulatory elements, such as IRESs and upstream open reading frames (uORFs), thereby enabling the context-dependent control of protein synthesis in response to diverse physiological demands (66–68).

In addition, our study identifies hnRNP A1, a well-established ITAF (46, 50), as a key downstream effector of DKC1 in the regulation of IRES-dependent translation. ITAFs promote cap-independent translation by facilitating ribosome recruitment to IRES elements and/or by stabilizing the interaction of translation initiation factors with IRES (50, 69–71). Multiple lines of evidence support hnRNP A1 as a critical mediator of DKC1 function. Functionally, hnRNP A1 knockdown or overexpression phenocopied the effects of DKC1 knockdown or overexpression on the expression of ATF4 and its target genes, as well as on neuroblastoma cell and xenograft growth. Moreover, hnRNP A1 overexpression fully rescued the DKC1 knockdown–induced suppression of IRES-dependent expression of BCL-XL, CCND1, MYC, and XIAP. Mechanistically, DKC1 is required to maintain hnRNP A1 expression. Polysome profiling and L-HPG metabolic labeling revealed that DKC1 promotes the active translation of HNRNPA1 mRNA and the synthesis of nascent hnRNP A1 protein. Intriguingly, we also found evidence suggesting that hnRNP A1 interacts with and stabilizes DKC1 protein, potentially forming a feed-forward loop that reinforces the activity of the DKC1-hnRNP A1 axis.

ATF4 is a master transcriptional regulator of the integrated stress response triggered by diverse stress signals, including amino acid deprivation and ER stress (24–26). Under basal conditions, the translation of ATF4 mRNA is suppressed by inhibitory uORFs that prevent ribosomes from reaching the ATF4 coding region. During stress, eIF2α, a subunit of the translation initiation factor eIF2, is phosphorylated by stress-activated eIF2α kinases such as GCN2 (activated by the AAR) and PERK (activated by ER stress). Phosphorylation of eIF2α reduces active eIF2 levels, impairing the recruitment of the initiator Met-tRNA^Met_i to the 40S ribosomal subunit for translation initiation (26, 72, 73). This global mRNA translation repression paradoxically enhances ATF4 translation by allowing ribosomal scanning past the inhibitory uORFs (24–26). This inhibitory uORF model was originally established on the basis of studies of the ATF4 V2 mRNA, which contains two uORFs (74–76). In contrast, the ATF4 V1 isoform contains four uORFs and harbors an IRES element in its 5′UTR, which is absent from ATF4 V2 (52). This IRES promotes ATF4 V1 translation in response to ER stress and eIF2α phosphorylation and is thought to be regulated by a cellular ITAF (52). Our study identifies hnRNP A1 as the ITAF that activates ATF4 V1 translation during stress. We show that hnRNP A1 binds and stabilizes ATF4 mRNA, preferentially enhancing ATF4 V1 protein expression over ATF4 V2. Bicistronic luciferase reporter assays demonstrate that hnRNP A1 promotes IRES-dependent translation via the ATF4 V1 5′UTR, specifically through uORF3, with no effect on ATF4 V2 5′UTR–driven translation. Furthermore, both the AAR and ER stress induce hnRNP A1 expression, and its knockdown abolishes stress-induced ATF4 up-regulation. These findings provide compelling mechanistic evidence that IRES-dependent translation, facilitated by hnRNP A1, plays a critical role in stress-induced ATF4 protein expression.

Cancer cells frequently encounter hostile microenvironmental conditions, including nutrient deprivation, hypoxia, and ER stress, driven by their rapid proliferation and metabolic demands. To adapt and survive, they rely on the selective translation of stress-responsive and prosurvival proteins (77). Under such stress, canonical cap-dependent translation is suppressed, and IRES-dependent translation becomes a critical alternative mechanism. This allows for the continued synthesis of essential proteins that promote survival and adaptation. Accordingly, many stress-response mRNAs harbor IRES elements within their 5′UTRs (71, 78, 79). Our findings reveal that MYCN activates the DKC1-hnRNP A1 axis, which enhances IRES-mediated translation and promotes the ATF4-dependent up-regulation of amino acid biosynthetic enzymes and transporters. This up-regulation is vital for the growth and survival of MYCN-driven neuroblastoma. Thus, our study uncovers a mechanism by which an oncogene activates IRES-mediated translation to alleviate cellular stress, thereby facilitating tumor growth and progression.

MATERIALS AND METHODS

Cell lines and cell culture

Neuroblastoma cell lines BE(2)-C (CRL-2268) and SK-N-AS (CRL-2137) were obtained from American Type Culture Collection, LA1-55n (06041203) from Sigma-Aldrich, LAN-6 and SMS-KCNR from the Children’s Oncology Group Cell Culture and Xenograft Repository, SHEP1 from V. P. Opipari at the University of Michigan, and SHEP-MYCNER from B. J. Altman at the University of Rochester Medical Center. The 293FT pLHCX hnRNP A1 (NM_002136.4) cell line (80) was a gift from S. B. Kutluay at the Washington University School of Medicine. 293FT (Thermo Fisher Scientific, R70007), 293T Lenti-X (TaKaRa 632180), 293FT ATF4 KO (81), HeLa (American Type Culture Collection, CCL-2), SHEP1, SK-N-AS, and SHEP-MYCNER (82) cells were cultured in Dulbecco’s modified Eagle’s medium (HyClone SH30022), while BE(2)-C and BE(2)-C_tetoff-ATF4 (37) were maintained in Dulbecco’s modified Eagle’s medium/Ham’s F-12 (1:1) (HyClone, SH30023). All other cell lines were cultured in RPMI 1640 (HyClone, SH30027). All media were supplemented with 10% fetal bovine serum (Atlanta Biologicals, S11050). All cell lines were authenticated through short tandem repeat profiling. After authentication, extensive frozen stocks were created to prevent cross-contamination. Cell lines were used within 10 passages postthawing and were regularly screened for Mycoplasma contamination. Phase-contrast microscopy images of cells were captured using the EVOS M5000 Imaging System (Invitrogen). Cell proliferation was assessed using a trypan blue assay.

For stress response experiments, cells were treated for 5 hours with either vehicle (H₂O for HisOH control or dimethyl sulfoxide for tunicamycin control), 5 mM HisOH (Sigma-Aldrich, H6647), or tunicamycin (2 μg/ml; Sigma-Aldrich, T7765) and collected for immunoblot analysis.

Animal experiments

Xenograft studies were conducted using 6-week-old male and female NOD.SCID mice (NOD.Cg-Prkdcscid/J, 001303) from the Jackson Laboratory. BE(2)-C cells expressing shGFP (control), shDKC1-738, shDKC1-326, or shHNRNPA1-586 were suspended in 100 μl of Hanks’ balanced salt solution (Thermo Fisher Scientific, 14170112) and injected subcutaneously into both flanks of each mouse (two sites per mouse) at ~4 × 10⁶ cells per site. The tumor volume was measured every other day with a digital caliper and calculated using the formula V = (L × W²)/2. Mice were euthanized when tumors reached ~1.0 cm in any dimension. All animal procedures were approved by the Institutional Animal Care and Use Committee (IACUC) of the University of Alabama at Birmingham under the Animal Project Number IACUC-22428.

Patient data

Neuroblastoma patient RNA-seq data were collected as described previously (65, 83). Survival and gene expression correlation analyses were conducted using the R2: Genomics Analysis and Visualization Platform (83) (https://hgserver1.amc.nl/cgi-bin/r2/main.cgi?open_page=login). Resulting figures and P values were downloaded for subsequent analysis.

Overexpression, knockdown, and inhibition

The lentiviral construct for overexpressing human DKC1 (pLenti6.3/V5-DEST, HsCD00943802) was obtained from DNASU. Human DKC1 shRNA oligonucleotide sequences shDKC1-738 (TRCN0000039738), shDKC1-326 (TRCN0000010326), and shDKC1-740 (TRCN0000039740) were obtained from the Broad Institute (https://portals.broadinstitute.org/gpp/public/gene/search), synthesized by IDT, amplified by PCR, subcloned into the pLKO.1 puro vector, and validated by sequencing. In addition, shDKC1 sequences (TRCN0000039743 and TRCN0000332892) were cloned into Tet-pLKO-puro (Addgene, 21915) for inducible expression in the presence of doxycycline (0.5 μg/ml).

The lentiviral construct pLHCX-hnRNP A1 for overexpressing human hnRNP A1 variant 1 (NM_002136.4) was provided by S. B. Kutluay (Washington University School of Medicine, St. Louis, MO). The DNA sequence coding for hnRNP A1 variant 2 (NM_031157.4) was obtained from DNASU (HNRNPA1 in pANT7_cGST, HsCD00785011), amplified by PCR, subcloned into pCDH-CMV-MCS-EF1-puro (SBI System Biosciences CD510B-1), and validated through sequencing. Human HNRNPA1 shRNA sequences—shHNRNPA1-566 (TRCN0000147566), shHNRNPA1-582 (TRCN0000006582), shHNRNPA1-585 (TRCN0000006585), shHNRNPA1-586 (TRCN0000006586), and shHNRNPA1-048 (TRCN0000148048)—were obtained from the Broad Institute, synthesized by IDT, amplified by PCR, subcloned into pLKO.1 puro, and verified by sequencing.

Lentiviruses were produced in 293T Lenti-X cells using packaging plasmids pLP1 (Addgene_22614), pLP2, and pLP/VSVG (Thermo Fisher Scientific, K497500). Lentiviral infection of cells was conducted according to standard procedures.

Cotransfection of 293FT ATF4 KO cells was conducted with pCW57.1-ATF4 V1 (NM_001675) or pCW57.1-ATF4 (V2, NM_182810) (81), alongside DKC1- and/or HNRNPA1-expressing plasmids. Cells were cultured in the presence of doxycycline (0.5 μg/ml) and collected 48 hours after transfection for immunoblot analysis.

The DKC1 inhibitor pyrazofurin was purchased from Sigma-Aldrich (cat. no. SML1502), dissolved in water, and stored at −80°C. Cells were treated with pyrazofurin for 3 days before being collected for cell counting, qRT-PCR, and immunoblot analyses.

qRT-PCR

Total RNA was extracted from cells using TRIzol reagent (Thermo Fisher Scientific, 15596026). Reverse transcription was performed with the iScript Advanced cDNA Synthesis Kit (Bio-Rad, 172-5038). qRT-PCR was carried out using a 2X SYBR Green qPCR Master Mix (Bimake, B21203) on an iQ5 real-time PCR system (Bio-Rad) with gene-specific primers (table S6). mRNA levels were normalized to B2M. Primer specificity was confirmed through melting curve analysis after qRT-PCR, ensuring that each primer pair produced a single, distinct amplification peak. To measure mRNA half-life, BE(2)-C shGFP and shHNRNPA1-585 cells were treated with actinomycin D (5 μg/ml; Sigma-Aldrich, A9415) for various times (0, 0.5, 1, 2, and 4 hours), followed by total RNA extraction and qRT-PCR analysis.

Immunoblotting

Cell lysates were prepared using a standard SDS sample buffer, and protein concentrations were measured using the Bio-Rad Protein Assay Kit II (5000002). Proteins (15 to 35 μg) were resolved by SDS–polyacrylamide gel electrophoresis and transferred onto nitrocellulose membranes. The membranes were then blocked for 60 min at room temperature with gentle shaking in 5% nonfat milk prepared in tris-buffered saline containing 0.1% Tween 20. Immunoblotting was performed using the following primary antibodies: rabbit anti-ASNS (1:1000, Proteintech, 14681-1-AP), rabbit anti-ATF4 (D4B8, 1:1000, Cell Signaling, 11815), rabbit anti–BCL-XL (54H6, 1:1000, Cell Signaling, 2764S), mouse anti-CCND1 (DCS-6, 1:200, Santa Cruz, sc-20044), rabbit anti-DKC1 (1:1000, Bethyl Laboratories, A302-591A), mouse anti-DKC1 (1:500, Santa Cruz, sc-373956), rabbit anti–glyceraldehyde-3-phosphate dehydrogenase (GAPDH; FL-335, 1:1000, Santa Cruz, sc-25778, RRID), rabbit anti–hnRNP A1 (1:15,000, Proteintech, 11176-1-AP), mouse anti–hnRNP A1 (4B10, 1:2000, Santa Cruz, sc-32301), rabbit anti-MTHFD2 (1:1500, Proteintech, 12270-1-AP), mouse anti-MYCN (B8.4.B, 1:400, Santa Cruz, sc-53993), mouse anti-p27KIP1 (1:200, Santa Cruz, sc-1641), rabbit anti-PHGDH (1:300, Sigma-Aldrich, HPA021241), rabbit anti-PSAT1 (1:3000, Novus, 21020002), rabbit anti-SHMT2 (1:1000, Millipore Sigma, HPA020549), rabbit anti–SLC7A5/LAT1 (1:1000, Cell Signaling, 5347), rabbit anti–SLC7A11/xCT (D2M7A, 1:1000, Cell Signaling, 12691), rabbit anti–β-actin (1:2000, Thermo Fisher Scientific, MA5-15739, RRID), mouse anti–α-tubulin (B-5-1-2, 1:5000, Sigma-Aldrich, T5168, RRID), mouse anti-TAMRA (1:1000, Invitrogen, MA1-041), and rabbit anti-XIAP (1:1000, Cell Signaling, 2042).

The secondary antibodies included horseradish peroxidase–conjugated goat anti-mouse (Jackson ImmunoResearch, 115-035-146) and goat anti-rabbit IgG (Jackson ImmunoResearch, 111-035-046). Immunoblots were visualized using the Clarity Western ECL Substrate Kit (Bio-Rad, 1705061) and quantified using either the Amersham ImageQuant 800 (Cytiva) or ImageJ software (version 1.53k).

Coimmunoprecipitation

Nuclear extracts were prepared from BE(2)-C cells as previously described (84) and incubated overnight at 4°C with protein A magnetic beads (Bio-Rad, SureBeads 161-4011) coated with 2 μg of rabbit IgG (Santa Cruz, sc-2027), rabbit anti-DKC1 (Bethyl Laboratories, A302-591A), or rabbit anti–hnRNP A1 (Proteintech, 11176-1-AP). The beads were collected using a magnetic separator, washed with extraction buffer, and suspended in standard SDS sample buffer for immunoblot analysis.

RNA immunoprecipitation

RNA immunoprecipitation was performed as described previously (85), with minor modifications. Briefly, BE(2)-C cells were washed with ice-cold phosphate-buffered saline (PBS) and lysed in a lysis buffer (20 mM tris-HCl, pH 7.5, 100 mM KCl, 5 mM MgCl₂, and 0.5% NP-40) for 10 min on ice. The lysate was then centrifuged at 10,000g for 15 min at 4°C. The supernatant was collected and incubated overnight at 4°C with protein A magnetic beads (Bio-Rad, SureBeads 161-4011) coated with 2 μg of mouse IgG (Santa Cruz, sc-2025) or mouse anti-hnRNP (4B10, Santa Cruz, sc-32301). The beads were collected using a magnetic separator, washed with a buffer (50 mM tris-HCl, pH 7.5, 150 mM NaCl, 1 mM MgCl₂, and 0.05% NP-40), and treated with 20 U of ribonuclease-free deoxyribonuclease I for 15 min at 37°C. A portion of the sample was collected for immunoblotting, while the remaining sample was treated with 0.1% SDS and proteinase K (0.5 mg/ml) for 15 min at 55°C to remove proteins. RNA was then extracted using TRIzol and analyzed via qRT-PCR.

Metabolomics

BE(2)-C cells were either untreated or treated with 1 μM pyrazofurin for 3 days. Cells were then collected by scraping and centrifugation, washed once with ice-cold PBS, snap-frozen in liquid nitrogen, and stored at −80°C for metabolomics analysis. Six biological replicates (~5 × 10⁶ cells per sample) were analyzed for each group. Metabolite extraction and untargeted metabolomics profiling were performed at the West Coast Metabolomics Center (University of California, Davis). Pathway analysis of identified metabolites was conducted using MetaboAnalyst (34).

ASO transfection

ASO sequences are listed in table S7. ASO transfection was performed according to a published protocol (86). Briefly, 293FT cells were seeded in a six-well plate at a density optimized to achieve ~70% confluency within 24 to 48 hours. The ASO-polyethylenimine (PEI) complex was prepared by mixing 5 μl of 50 μM ASO with 3.5 μl of PEI (1 mg/ml) in 91.5 μl of sterile 0.9% saline solution. The mixture was thoroughly pipetted to ensure homogenization and then incubated at room temperature for 15 min. Before transfection, the cells were washed once with PBS, 900 μl of fresh medium was added to each well, and the plate was incubated for 15 min. The ASO-PEI complex was then added dropwise to the cells, bringing the final concentration of ASO in the medium to 250 nM. The plate was gently shaken to ensure even distribution of the transfection solution and incubated at 37°C for 5 to 6 hours. After the incubation, the medium was carefully removed, and 2 ml of fresh medium was added to each well. The cells were cultured for 48 to 72 hours to ensure optimal ASO uptake and then were collected for qRT-PCR, immunoblotting, and Nanopore direct RNA-seq.

Poly-A RNA-seq

Total RNA was prepared from BE(2)-C control, BE(2)-C shDKC1-738, and BE(2)-C treated with 1 μM pyrazofurin for 72 hours. Poly-A RNA was extracted from high-quality total RNA (RNA integrity number >9.0), and the poly-A RNA samples from control and pyrazofurin-treated BE(2)-C cells were paired-end sequenced using the Illumina HiSeq 4000 platform by Azenta Life Sciences. Following base calling by Illumina bcl2fastq (version 2.18.0.12), FASTQ files were aligned to the Homo_sapiens.GRCh38.cdna.all reference assembly using the Kallisto tool (https://github.com/pachterlab/kallisto). Transcript counts were normalized using the edgeR package (https://bioconductor.org/packages/release/bioc/html/edgeR.html), and differential expression analysis was performed with the limma-voom package (https://bioconductor.org/packages/release/bioc/html/limma.html).

For Nanopore direct RNA-seq, BE(2)-C control and shDKC1-738 mRNA libraries were prepared as described previously (87). Raw fast5 files were basecalled using Guppy (version 6.4.2), the resulting FASTQ files were aligned to the reference sequence (GRCh38.p13) using minimap2 (88) (https://github.com/lh3/minimap2), and Bambu (89) (https://github.com/GoekeLab/bambu) was used to estimate transcript abundance for differential gene expression analysis. GO analysis and GSEA were performed using the enrichplot R tool (https://bioconductor.org/packages/release/bioc/html/enrichplot.html).

rRNA sequencing

Total RNA was isolated from BE(2)-C control, BE(2)-C shDKC1-738, BE(2)-C shPUS7-33, 293FT ASO control, and 293FT ASO SNORA41 cells. rRNA was enriched from total RNA by depleting poly-A RNA using a Poly(A) mRNA Magnetic Isolation Module (NEB, E7490S). A poly-A tail was then added to rRNA using a Poly(A) Tailing Kit (NEB, M0276). The direct rRNA sequencing library was prepared according to the standard protocol and loaded into a Flongle flow cell for sequencing using MinKnow (version 23). Each flow cell was sequenced for 24 hours. Raw fast5 files were converted to pod5 files for basecalling using Dorado version 8 (https://github.com/nanoporetech/dorado). The resulting FASTQ files were aligned to human noncoding RNA reference sequences, and pseudouridine sites were identified on the basis of significant changes in U-to-C basecalling errors (87).

Polysome profiling

Polysome analysis was performed as described previously (90), with minor modifications. BE(2)-C cells expressing shGFP and shDKC1-326 were treated with cycloheximide (Sigma-Aldrich, cat. no. C4859) at 0.1 mg/ml for 3 min, washed with PBS containing cycloheximide (0.1 mg/ml), and lysed on ice for 15 min using polysome extraction buffer [15 mM tris-Cl, pH 7.4, 15 mM MgCl₂, 0.3 M NaCl, cycloheximide (0.1 mg/ml), heparin (1 mg/ml), and 1% Triton X-100]. The lysates were centrifuged at 13,200g for 10 min, and 0.5 ml of the supernatant was layered onto 10 to 50% sucrose gradients in polysome extraction buffer (without Triton X-100). The gradients were centrifuged at 41,000g for 2 hours in an SW41 Ti rotor (Beckman, cat. no. BR-8101) at 4°C. Fractions were collected using a Gradient Station IP system (BioComp) into open-top polyclear centrifuge tubes (Seton Scientific, cat. no. 7030) and stored at −80°C. Total RNA was extracted from 0.5 ml of each polysome fraction using acid phenol:chloroform (125:24.1, pH 4.5 ± 0.2, Ambion, cat. no. AM9720). The RNA was then precipitated with 70% ethanol and analyzed by qRT-PCR. Data were normalized to GAPDH.

snoRNA-rRNA interaction

The RNAsnoop tool was used for snoRNA-rRNA interaction analysis as previously described (58). H/ACA snoRNA sequences were obtained from the snoDB database (86). To accurately identify snoRNAs associated with DKC1-dependent pseudouridine sites, snoRNA sequences were preprocessed by removing the H box (ANANNA) and ACA box as described previously (58). This preprocessing step yielded a database of 363 unique snoRNA sequences. The 28S rRNA was then used as the input RNA to identify snoRNAs targeting pseudouridine sites at 28S_U4331 and 28S_U4966.

Luciferase reporter assay

293FT cells were cotransfected with pLHCX (control) or pLHCX-hnRNP A1, along with basal (pRF), EMCV, or ATF4 bicistronic luciferase reporter constructs (ATF4-V2, V1, V1-F3, V1-F6, and V1-F7) for 48 hours. Dual luciferase assays were performed using a kit from Promega (Dual-Luciferase Reporter Assay System, cat. no. E2920) (52). Luminescence was measured with an Agilent BioTek Synergy LX Multi-Mode Reader. Relative luciferase activity was calculated by normalizing FLuc signals to RLuc signals for each sample.

L-HPG incorporation assay

This assay was performed as described (43). Briefly, BE(2)-C control and DKC1-overexpressing cells were cultured for 4 hours in methionine-free RPMI 1640 (Thermo Fisher Scientific, A1451701) supplemented with L-HPG (200 μM), a methionine analog, in the presence or absence of cycloheximide (35.5 μM). Total hnRNP A1 protein was immunoprecipitated using a rabbit anti–hnRNP A1 antibody (Proteintech, 11176-1-AP). L-HPG–tagged nascent hnRNP A1 was then captured via click chemistry using a reaction mixture containing 20 mM CuSO₄, 10 μM TAMRA azide, 10 mM aminoguanidine, and 10 mM ascorbate for 1 hour. The resulting TAMRA-labeled proteins were detected using an anti-TAMRA antibody (1:1000, no. MA1-041; Invitrogen), visualized using the Clarity Western ECL Substrate Kit (Bio-Rad, 1705061), and quantified with ImageJ software (version 1.53k). Total immunoprecipitated hnRNP A1 was detected with a mouse anti–hnRNP A1 antibody (4B10, 1:2000, Santa Cruz, sc-32301) and used to normalize the amount of L-HPG–labeled nascent hnRNP A1. Input lysates from L-HPG–free cultures were used as negative controls.

Venn diagram analysis

Venn diagram analysis was conducted using three distinct datasets: (i) Genes positively correlated with DKC1 expression: This dataset was derived from the SEQC neuroblastoma patient dataset (83), applying a correlation threshold of R > 0.7 and a P value threshold of <1.143 × 10⁻⁷². (ii) Genes down-regulated following DKC1 inhibition: This dataset included genes with a fold change of ≥−3.0 and an adjusted P value of <0.01; (iii) Known ITAF factors: This dataset was obtained from the IRESite database (91). The overlap among these three gene sets was visualized using the R package VennDiagram (92).

Statistical analysis

Quantitative data are expressed as the means ± SEM and were analyzed for statistical significance using unpaired, two-tailed Student’s t test or an analysis of variance (ANOVA; one-way or two-way). Dose-response curves for the DKC1 inhibitor were fitted using the “log(inhibitor) versus response (three parameters)” model. Pseudouridine modification data were analyzed by using the chi-square test. For animal studies, the log-rank test was applied to assess mouse survival at the end of the experiment. Unless otherwise specified, all statistical analyses were performed using GraphPad Prism 10.2.3 for Windows. Statistical significance was assigned as *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001.

Data availability

The BioProject accession number for the Illumina RNA-seq and Nanopore RNA-seq data reported in this paper is PRJNA1196392. The patient data analyzed in this study were obtained from R2 Genomics Analysis and Visualization Platform (https://hgserver1.amc.nl/cgi-bin/r2/main.cgi). All other raw data are available upon request from the corresponding authors.

Acknowledgments

We extend our gratitude to S. Kutluay at the University of Washington, St. Louis, for providing the pLHCX-hnRNP A1 plasmid and 293FT pLHCX-hnRNP A1 cells and D.-Y. Jin at the University of Hong Kong Li Ka Shing Faculty of Medicine for providing the ATF4 V1, V2, V1-F3, V1-F6, and V1-F7 bicistronic luciferase vectors. We also thank P. F. Stadler and H. Tafer at the University of Leipzig for assistance with the RNAsnoop tool. In addition, we express appreciation to S. Chen at the Sun Yat-sen University Cancer Center for sharing the DKC1 knockdown proteomics data and to R. Kirkman and S. Karki at the University of Alabama at Birmingham for help with plasmid preparation and for providing the mouse anti-DKC1 antibody, respectively.

Funding: This work was supported by a grant from the NIH to H.-F.D. (grant no. R01 CA190429) and by the US Department of Veterans Affairs (I01BX002930), the NIH (R01 CA200653), and the Department of Defense (HT94252410558) to S.S.

Author contributions: Conceptualization: A.G., M.B., and H.-F.D. Methodology: A.G., M.B., S.K., M.P., and H.-F.D. Investigation: A.G., M.B., J.D., S.K., M.P., S.S., and H.-F.D. Visualization: A.G., M.B., J.D., and H.-F.D. Formal analysis: A.G., M.B., J.D., and H.-F.D. Data curation: A.G., M.B., J.D., and H.-F.D. Software: M.B. Resources: H.-F.D. and S.K. Validation: J.D., A.G., M.B., and H.-F.D. Funding acquisition: H.-F.D. Project administration: A.G., M.B., J.D., and H.-F.D. Supervision: H.-F.D. Writing—original draft: A.G., M.B., and H.-F.D. Writing—review and editing: A.G., M.B., and H.-F.D.

Competing interests: The authors declare that they have no competing interests.

Data and materials availability: All data needed to evaluate the conclusions in the paper are presented in the paper and/or the Supplementary Materials. The BioProject accession number for the Illumina RNA-seq and Nanopore RNA-seq data reported in this paper is PRJNA1196392 (www.ncbi.nlm.nih.gov/bioproject/PRJNA1196392).The detailed information including the publication citations for all datasets can be seen in Materials and Methods.

Supplementary Materials

The PDF file includes:

Figs. S1 to S8

Legends for tables S1 to S7

sciadv.adv9401_sm.pdf^{(1.7MB, pdf)}

Other Supplementary Material for this manuscript includes the following:

Tables S1 to S7

sciadv.adv9401_tables_s1_to_s7.zip^{(3.1MB, zip)}

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Figs. S1 to S8

Legends for tables S1 to S7

sciadv.adv9401_sm.pdf^{(1.7MB, pdf)}

Tables S1 to S7

sciadv.adv9401_tables_s1_to_s7.zip^{(3.1MB, zip)}

Data Availability Statement

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PERMALINK

DKC1-mediated pseudouridylation of rRNA targets hnRNP A1 to sustain IRES-dependent translation and ATF4-driven metabolic adaptation

Anamika Gupta

Mohit Bansal

Jane Ding

Suman Karki

Madhuparna Pandit

Sunil Sudarshan

Han-Fei Ding

Roles

Abstract

INTRODUCTION

RESULTS

DKC1 sustains ATF4 expression and downstream amino acid metabolism genes

Fig. 1. DKC1 sustains the expression of ATF4 and genes involved in amino acid metabolism.

DKC1 regulates amino acid metabolism

Fig. 2. DKC1 is a downstream mediator of MYCN in the regulation of amino acid metabolism.

DKC1 is a downstream effector of MYCN in sustaining the expression of ATF4 and amino acid metabolism genes

DKC1 targets the IRES trans-acting factor hnRNP A1

Fig. 3. DKC1 targets the ITAF hnRNP A1.

Fig. 4. DKC1 promotes HNRNPA1 mRNA translation.

hnRNPA 1 is a downstream mediator of DKC1 in sustaining ATF4 expression

Fig. 5. hnRNPA 1 sustains ATF4 expression and stress responses.

hnRNP A1 promotes IRES-dependent ATF4 protein expression

Fig. 6. hnRNP A1 is a downstream mediator of DKC1 in the regulation of IRES-dependent translation.

DKC1-mediated 28S rRNA pseudouridylation promotes hnRNP A1 expression to drive IRES-dependent translation and ATF4 expression

Fig. 7. DKC1-mediated 28S rRNA pseudouridylation promotes hnRNP A1 expression to drive IRES-dependent translation and ATF4 expression.

DISCUSSION

Fig. 8. Working model of the DKC1-hnRNP A1 axis in promoting ATF4-mediated metabolic adaptation.

MATERIALS AND METHODS

Cell lines and cell culture

Animal experiments

Patient data

Overexpression, knockdown, and inhibition

qRT-PCR

Immunoblotting

Coimmunoprecipitation

RNA immunoprecipitation

Metabolomics

ASO transfection

Poly-A RNA-seq

rRNA sequencing

Polysome profiling

snoRNA-rRNA interaction

Luciferase reporter assay

L-HPG incorporation assay

Venn diagram analysis

Statistical analysis

Data availability

Acknowledgments

Supplementary Materials

The PDF file includes:

Other Supplementary Material for this manuscript includes the following:

REFERENCES AND NOTES

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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