hY3 RNA binds and inhibits ribosomes and modulates the starvation-induced integrated stress response

Valentina Pecoraro; EunBin Kong; Puneet Sharma; Yulia Gonskikh; Marek Żywicki; Fabian Nagelreiter; Markus Schosserer; Katrin Freiburghaus; Jean-Marc Nuoffer; Johannes Grillari; Norbert Polacek

doi:10.1093/nar/gkag832

. 2026 Aug 24;54(16):gkag832. doi: 10.1093/nar/gkag832

hY3 RNA binds and inhibits ribosomes and modulates the starvation-induced integrated stress response

Valentina Pecoraro ^1,², EunBin Kong ³, Puneet Sharma ⁴, Yulia Gonskikh ^5,⁶, Marek Żywicki ⁷, Fabian Nagelreiter ⁸, Markus Schosserer ^9,¹⁰, Katrin Freiburghaus ^11,¹², Jean-Marc Nuoffer ¹³, Johannes Grillari ^14,¹⁵, Norbert Polacek ^16,^✉

¹ Department of Chemistry, Biochemistry and Pharmaceutical Sciences, University of Bern, Bern 3012, Switzerland

² Graduate School for Cellular and Biomedical Sciences, University of Bern, Bern 3012, Switzerland

³ Department of Chemistry, Biochemistry and Pharmaceutical Sciences, University of Bern, Bern 3012, Switzerland

⁴ Institute of Biochemistry, ETH Zürich, Zürich 8093, Switzerland

⁵ Department of Chemistry, Biochemistry and Pharmaceutical Sciences, University of Bern, Bern 3012, Switzerland

⁶ Graduate School for Cellular and Biomedical Sciences, University of Bern, Bern 3012, Switzerland

⁷ Department of Computational Biology, Institute of Molecular Biology and Biotechnology, Adam Mickiewicz University, Poznań 61-614, Poland

⁸ Institute of Molecular Biotechnology, BOKU University, 1190 Vienna, Austria

⁹ Institute of Molecular Biotechnology, BOKU University, 1190 Vienna, Austria

¹⁰ Institute of Medical Genetics, Center for Pathobiochemistry and Genetics, Medical University of Vienna, Vienna 1090, Austria

¹¹ University Institute of Clinical Chemistry, Inselspital, Bern University Hospital, University of Bern, Bern 3010, Switzerland

¹² Graduate School for Health Sciences, University of Bern, Bern 3012, Switzerland

¹³ University Institute of Clinical Chemistry, Inselspital, Bern University Hospital, University of Bern, Bern 3010, Switzerland

¹⁴ Institute of Molecular Biotechnology, BOKU University, 1190 Vienna, Austria

¹⁵ Ludwig Boltzmann Institute for Traumatology, The Research Center in Cooperation with AUVA, 1200 Vienna, Austria

¹⁶ Department of Chemistry, Biochemistry and Pharmaceutical Sciences, University of Bern, Bern 3012, Switzerland

^✉

To whom correspondence should be addressed. Email: norbert.polacek@unibe.ch

Roles

Valentina Pecoraro: Conceptualization, Formal analysis, Investigation, Methodology, Visualization, Writing - original draft, Writing - review & editing

EunBin Kong: Investigation, Writing - review & editing

Puneet Sharma: Investigation, Writing - review & editing

Yulia Gonskikh: Investigation, Writing - review & editing

Marek Żywicki: Investigation, Writing - review & editing

Fabian Nagelreiter: Investigation, Writing - review & editing

Markus Schosserer: Resources, Writing - review & editing

Katrin Freiburghaus: Investigation, Writing - review & editing

Jean-Marc Nuoffer: Investigation, Writing - review & editing

Johannes Grillari: Funding acquisition, Resources, Writing - review & editing

Norbert Polacek: Conceptualization, Funding acquisition, Supervision, Writing - review & editing

PMCID: PMC13501136 PMID: 42635123

Abstract

Cells adapt to metabolic stress by orchestrating gene expression to mitigate cellular damage, sustain homeostasis, and promote survival. Within this framework, translational control provides a rapid and efficient layer of regulation. Non-coding RNAs have recently emerged as effective modulators of translation, partly by targeting the ribosome. The contribution of ribosome-associated non-coding RNAs (rancRNAs) to translation regulation, however, remains largely unexplored in human cells. Here, we identified the human Y3 (hY3) RNA as a rancRNA that inhibits protein synthesis and attenuates cellular metabolism. hY3 function was particularly critical under nutrient deprivation, where it promoted adaptive stress responses. In this context, depletion of hY3 disrupted the delicate balance between survival and apoptosis by reducing the expression of pro-survival factors and impairing the activation of the integrated stress response (ISR). Loss of hY3 reduced starvation-dependent phosphorylation of eukaryotic translation initiation factor 2α, thereby attenuating ISR signalling, which results in non-physiologically elevated global translation rates during nutrient deprivation. Together, our findings establish hY3 as a ribosome-bound regulator of translation and stress responses, positioning it as a determinant of cell fate under metabolic stress.

Graphical Abstract

For image description, please refer to the figure legend and surrounding text.

Introduction

Cutting-edge technologies are beginning to spotlight the “dark matter” of genomes, uncovering various types of non-coding RNA (ncRNA) that are essential for orchestrating intricate cellular processes. A subset of these ribo-regulators has been found to target directly the ribosome, the ribozyme at the core of the protein synthesis process [1, 2]. These so-called ribosome-associated non-coding RNAs (rancRNAs) have recently emerged on the scene of regulatory ncRNA research as efficient contributors to translation control [1, 2]. They represent a widely heterogeneous group of regulatory RNA molecules, showing diversity in their chromosomal origin, length, and function. Echoing the David versus Goliath paradigm, rancRNAs, despite consisting sometimes of only a few dozen nucleotides, can effectively take control over the cell’s giant protein machinery. The association of specific rancRNAs with the ribosome has been experimentally confirmed in various organisms spanning all three domains of life, in particular in the context of cellular stress responses [1]. In most cases, rancRNAs inhibit global translation, but also stimulation of protein biosynthesis has been described [3–6]. When confronted with challenging environmental conditions, such as nutrient deprivation, cells can initiate a protective response to mitigate stress and promote cell survival [7]. In these premises, the regulation of translation during stress is of utmost importance, given that protein synthesis is a highly energy-demanding process that consumes the majority of cellular energy resources [8]. Consequently, the reduction in global protein synthesis allows cells to reallocate the saved energy and resources effectively into cellular maintenance and repair, thereby facilitating the adaptation to adverse environments and the restoration of cellular homeostasis.

One of the key adaptive mechanisms that mammalian cells employ to regulate translation under metabolic stress, alongside the mTOR signaling pathway, is the integrated stress response (ISR) [9]. This adaptive response is initiated by eukaryotic translation initiation factor 2α (eIF2α) kinases, including HRI, PKR, general control nonderepressible 2 (GCN2), and PERK. They sense different stress signals and catalyze the phosphorylation of the alpha subunit of eIF2α at serine 51 [9]. The phosphorylation of eIF2α allows for selective protein synthesis that prioritizes stress-responsive proteins while downregulating general messenger RNA (mRNA) translation [10].

During starvation, the GCN2 kinase phosphorylates eIF2α, which leads to a global downregulation of cap-dependent translation while concomitantly promoting the selective translation of specific mRNAs, including the activating transcription factor 4 (ATF4). ATF4 acts as a master transcriptional regulator of metabolic genes that enable cellular adaptation to stress [10]. One prominent ATF4 target involved in amino acid metabolism is asparagine synthetase (ASNS), which plays a crucial role in maintaining amino acid homeostasis under nutrient shortage conditions [11]. Thus, gene expression reprogramming driven by the ISR is essential for cell survival during metabolic stress. Impaired ISR activation can have detrimental consequences, including reduced expression of stress-responsive genes, disrupted amino acid transport, and diminished resistance to oxidative stress. Ultimately, cells that fail to mount an adequate adaptive response are inevitably destined to programmed cell death [12, 13].

In this study, we identified the human Y3 (hY3) RNA as a novel rancRNA. hY3 is part of the abundant and highly conserved class of ncRNAs, known as Y RNAs [14]. The human genome encodes four Y RNA paralogs, hY1, hY3, hY4, and hY5, which range from 84 to 113 nt in length. They are transcribed by the RNA Polymerase III and are found in both the nucleus and the cytoplasm [15]. It has previously been reported that these ncRNAs are implicated in various cellular processes, including the initiation of DNA replication, RNA quality control, ribonucleoprotein (RNP) assembly, and cellular stress responses [16]. Moreover, the cleavage of Y RNAs performed through the caspase-3 dependent pathway, results in the formation of Y RNA-derived fragments (YsRNAs), which are involved in apoptosis, DNA repair, and promotion of inflammation [17, 18].

Y RNAs are characterized by a conserved hairpin-shaped structure, featuring resembling stem regions and subtype-specific central loop sequences [19]. The loop region serves as a binding site for various RNA-binding proteins (RBPs), many of which regulate transcription and translation [20]. In particular, hY3 has been reported to bind translational regulatory proteins such as the neuron-specific HuD and the ubiquitously expressed HuR [21, 22]. Beyond their intracellular functions, Y RNAs can also contribute to intercellular communication via extracellular vesicles [20]. Indeed, Y RNAs are abundantly present in body fluids and have been proposed as potential biomarkers in cancer, cardiovascular diseases, neurodegenerative pathologies, and immune-related diseases [22–24]. However, while their expression and localization have been extensively studied, the distinct molecular functions of individual Y RNAs remain poorly understood.

Here, we explored the role of hY3 in the regulation of translation and metabolism, and its contribution to cellular susceptibility under nutrient deprivation in primary human dermal fibroblasts (HDFs) and in immortalized cancer cells. Our findings revealed that hY3 binds to ribosomes and polysomes and interferes with the proper activation of ISR, thereby playing a decisive role in determining how cells cope with metabolic stress and regulate apoptosis susceptibility.

Materials and methods

Characteristics of human dermal fibroblasts from two donors

Primary HDF cell lines HDF85 and HDF161 were obtained from healthy donors through Evercyte GmbH (Vienna, Austria). HDF85 cells were derived from a 49-year-old female donor, and HDF161 cells from a 65-year-old female donor, both originating from abdominoplasty tissue. Cells were cultured in Dulbecco’s modified Eagle’s medium (DMEM)/Ham’s F-12 1:1 medium (Biochrom, Cat#FG4815, 500 ml) supplemented with 56 ml fetal bovine serum (FBS) (Sigma–Aldrich, Cat#F7524), and 10 ml of 200 mM L-glutamine (Sigma–Aldrich, Cat#G7513). Cultures were maintained at 37°C in a humidified incubator with 7% CO₂. For induction of stress-induced premature senescence (SIPS), population doubling (PD) 13 was used for HDF85 and PD15 for HDF161. All procedures involving primary human cell lines were conducted in accordance with approved ethical protocols.

Human dermal fibroblasts culture

Primary HDFs from two healthy donors (HDF85 and HDF161, Evercyte GmbH Vienna, Austria) were kindly provided by the group of Johannes Grillari, University of Natural Resources and Life Sciences, Vienna, Austria. Cells were routinely cultured in DMEM/Ham’s F-12 1:1 medium (Biochrom, Cat#FG4815, 500 ml) supplemented with 56 ml FBS (Sigma–Aldrich, Cat#F7524) and 10 ml of 200 mM L-glutamine (Sigma–Aldrich, Cat#G7513) at 37°C in a humified incubator with 7% CO₂ and tested for mycoplasma in regular intervals. Cell counting was performed with the automated cell counter Luna-II™ (Logos Biosystems). Proliferating HDFs were passed twice a week in a ratio of 1:2 to 1:3 and detached with trypsin-ethylenediaminetetraacetic acid (EDTA) (0.05% Trypsin-EDTA, phenol red, Gibco™, Thermo Fisher Scientific, Cat#25300062) at 37°C for 5 min. For both quiescent and senescent conditions, HDFs were seeded at a density of 3500 cells/cm² 1 day prior to treatment and allowed to adhere overnight. Quiescence was induced by allowing the cells to reach confluency and undergo contact inhibition, with media changes performed once per week. In parallel, senescence was induced in separate HDF cultures by treating cells with doxorubicin.

Stress-induced premature senescence by doxorubicin

For the induction of premature senescence, HDFs were treated twice with freshly prepared DMEM medium containing 200 nM doxorubicin (Sigma–Aldrich, Cat#D1515-10MG; 5 mM stock solution in H₂O stored at −20°C). One day after seeding, the culture medium was replaced with doxorubicin-containing medium, and cells were incubated at 37°C and 7% CO₂ for 4 days. The treatment was then repeated by replacing the medium with freshly prepared doxorubicin-supplemented DMEM, followed by an additional 3 days of incubation. After the second treatment, the doxorubicin-containing medium was removed, and cells were maintained in regular culture medium for 3 weeks, with media changes once per week, to allow recovery and stabilization of the senescent phenotype. Premature senescence was confirmed by senescence-associated β-galactosidase staining following standard protocols, as well as by morphological assessment under light microscopy [25, 26]. Images were captured using a DFC360 FX monochrome camera (Leica Microsystrems) mounted on a DMI6000B microscope (Leica Microsystems).

For complementary DNA (cDNA) library generation, HDFs under proliferating, quiescent, and senescent conditions were prepared by the group of Johannes Grillari and subsequently sent to our lab for further processing and analysis. For northern blot (NB) experiments, primary HDFs were cultured under the same conditions by our group, following the protocols established by the Grillari lab.

Generation of HDF cDNA libraries

For the generation of cDNA libraries, primary HDFs cultured under proliferating, quiescent, and doxorubicin-induced premature senescence conditions were kindly provided by the group of Johannes Grillari. Two biological replicates from donors HDF85 and HDF161 were processed, each in two technical replicates. Cell pellets were resuspended in resuspension buffer containing 30 mM HEPES/KOH (pH 7.6), 150 mM KOAc, 3.9 mM MgOAc₂, 4 mM dithiothreitol (DTT), protease inhibitor cocktail (cOmplete™ ULTRA Tablets, Mini, EDTA-free, EASYpack, Roche, Cat#05892791001), RNasin® Ribonuclease Inhibitor (Promega, Cat#N2611). One-tenth of each cell suspension was used for total RNA extraction with TRI Reagent® (Zymo Research, Cat#R2050-1-200) following the manufacturer’s instructions.

The remaining cells in suspension were opened by repeated passage through a 25-gauge needle attached to a 1-ml syringe. Cell debris was removed by centrifugation at 20 000 × g at 4°C for 15 min. To enrich rancRNA, cDNA libraries were generated from small RNAs that copurified with the crude ribosomal pellet fraction obtained after centrifugation at 200 000 × g. For ribosome pellet isolation, the cell lysate was layered onto a 0.5 ml pre-cooled 1.1 M sucrose cushion prepared in 30 mM HEPES-KOH (pH 7.6), 150 mM KOAc, 3.9 mM MgOAc₂, 4 mM DTT, and 1 mM PMSF. The ultracentrifugation was performed at 200 000 × g for 1.5 h at 4°C using an fixed-angle rotor S140AT in a Sorvall M120 + mini ultracentrifuge (Thermo Fisher Scientific). RNA was extracted from the resulting ribosome pellet using TRI Reagent® (Zymo Research, Cat#R2050-1-200) according to manufacturer’s protocol.

Both total RNA and RNA derived from ribosome pellet were size-fractionated by denaturing polyacrylamide gel (8% acrylamide M-Bis, 7 M Urea, 1× TBE). RNAs corresponding to the size range between 18 and 300 nt were excised from the gel, eluted overnight in 0.3 M NaOAc (pH 5.5) with 1 mM EDTA, and precipitated in ethanol with 1 μl GlycoBlue™ Coprecipitant (Invitrogen™, Cat#AM9516). RNA was pelleted by centrifugation at 10 000 × g for 2 h at 4°C. To remove cyclic 2′,3′-phosphates at the 3′ end, RNA was treated with T4 polynucleotide kinase (PNK, 10 U/μl, Thermo Fisher Scientific, Cat#EK0032) in a 30 μl reaction containing 1× T4 PNK Reaction Buffer A (Thermo Fisher Scientific, Cat#EK0032), 0.167 mM ATP (Adenosine 5′-triphosphate Sigma–Aldrich, Cat#A8937), 1 μl RiboLock RNase inhibitor (40 U/μl, Thermo Fisher Scientific Cat#EO0382), and 1 μl T4 PNK (10 U/μl Thermo Fisher Scientific, Cat#EK0032), following the protocol described by Honda et al. 2016 [27]. The reaction was incubated in a water bath at 37°C for 40 min and subsequently purified using phenol/chloroform/isoamyl alcohol (ROTI®Aqua-P/C/I, Carl Roth, Cat#X985.2) according to the manufacturer’s protocol. The quantity and quality of the purified total RNA and the RNA derived from the ribosome pellet were assessed using a Thermo Fisher Scientific Qubit 4.0 fluorometer with the Qubit RNA HS Assay Kit (Thermo Fisher Scientific, Cat#Q32855) and an Advanced Analytical Fragment Analyzer System using a Fragment Analyzer RNA Kit (Agilent, Cat#DNF-471), respectively. Total RNA-Seq libraries were generated using a SMARTer Stranded Total RNA-Seq Kit v2 – Pico Input Mammalian Kit (Takara, Cat#634 413) following the SMARTer Stranded Total RNA-Seq Kit v2 - Pico Input Mammalian User Manual (Takara, Cat#022 025). The cDNA libraries were equimolar pooled and sequenced 50 bp paired-end using a shared illumina NovaSeq 6000 SP Reagent Kit v1 (100 cycles, illumina, Cat#20 027 464).

Analysis of HDF rancRNA sequencing data

Raw sequencing reads have been subjected to adapter trimming using cutadapt software v2.8 [28]. Trimmed reads have been aligned to human reference genome GRCh38 and quantified according to Gencode v28 genome annotation using STAR (v2.7.1a) [29]. Differential expression analysis was performed using DESeq2 package [30].

HeLa cell culture and treatments

HeLa cells (ATCC®, CCL-2^TM) were cultured in RPMI 1640 medium (Gibco™, Thermo Fisher Scientific, Cat#31870025) supplemented with 10% FBS (Gibco™, Thermo Fisher Scientific, Cat#A5669801), 2 mM L-glutamine, 100 units/ml penicillin, 100 µg/ml streptomycin (Penicillin-Streptomycin-Glutamine 100×, Gibco™, Thermo Fisher Scientific, Cat#10378016) at 37°C and 5% CO₂. For passaging, cells were washed with phosphate buffered saline (PBS) and detached with trypsin-EDTA (0.05% Trypsin-EDTA, phenol red, Gibco™, Thermo Fisher Scientific, Cat#25300062).

During lipofectamine-mediated transfection, cells were grown in RPMI 1640 medium supplemented with 10% FBS and 2 mM L-glutamine (200 mM, Gibco™, Thermo Fisher Scientific, Cat#25030081), without the addition of antibiotics.

To induce starvation stress, cells were washed twice with PBS and exposed to a low glucose DMEM medium lacking amino acids and serum (DMEM, w: 1.0 g/l Glucose, w/o: L-Glutamine, w/o: Amino acids, w: Sodium pyruvate, w: 3.7 g/l NaHCO₃, PAN-Biotech, Cat#P0401507), with exposure time varying from 20 min to 4 h.

Northern blot analysis

RNA extraction was performed either by TRI Reagent® (Zymo Research, Cat#R2050-1-200) or by PCI (ROTI®Aqua-P/C/I, Carl Roth, Cat#X985.2) according to manufacturer’s instructions. For NB analysis, 10–20 µg RNA were separated on an 8% denaturing polyacrylamide gel (Acrylamide M-Bis solution 30% 29/1, Gerbu, Cat#1108, 7M Urea, 1× TBE buffer) and transferred to a nylon membrane (Hybond^TM-N + Positively charged Nylon Transfer Membrane, Cytiva, Cat#RPN203B) at 400 mA for 45 min using a semidry blotting system (V20-SDB, Scie-Plas). After immobilizing RNA using a UV cross-linker (0.120 J/cm², BLX-254, Vilber Lourmat) membranes were prehybridized for 30 min in hybridization buffer [1 M sodium phosphate buffer, pH 6.2, 7% sodium dodecyl sulfate (SDS)]. DNA oligonucleotides complementary to the RNA of interest were end-labeled with [γ-32P]-ATP (Hartmann Analytic, Cat#SCP-501) and T4 PNK (Thermo Fisher Scientific, Cat#EK0032). Hybridization was carried out overnight at 42°C. Membranes were then washed as previously described [31]. Signals were detected by exposing membranes to phosphor imaging screens, scanned with a Typhoon phosphor imager (GE Typhoon FLA 9000, GE Healthcare), and quantified using ImageQuant TL-11 (Cytiva).

Oligonucleotide probes used for northern blot analysis

hY1: 5′-AAAGAGTAGAACAAGGAGTTCG-3′

hY3: 5′-GGCTAGTCAAGTGAAGCAGTGGGAG-3′

hY4: 5′-TTGTATACCAACTTTA-3′

hY5: 5′-GGGGAGACAATGTTAA-3′

RT-qPCR analysis

RNA from HDF85 ribosome-enriched pellet was extracted using ROTI®Aqua-P/C/I (Carl Roth, Cat#X985.2). Total RNA from HeLa cells under normal conditions and after 20 min of starvation was isolated using the Direct-zol^TM RNA MiniPrep Kit (Zymo Research, Cat#R2050). RNA from ribosome pulldown experiments in HeLa cells was purified using RNA Clean & Concentrator^TM-5 Kit (Zymo Research, Cat#R1015). RNA concentrations were measured using a NanoDrop spectrophotometer.

Reverse transcription of 200–300 ng RNA was performed with SuperScript™ IV Reverse Transcriptase (Invitrogen^TM, Cat#18090050), following manufacturer’s instructions, with Random Hexamer Primer (Thermo Fisher Scientific, Cat#SO142). qPCR was performed using the GoTaq® qPCR Master Mix (Promega, Cat#A6002) on a Rotor-Gene Q system (QIAGEN), with 3–4 technical replicates for each experiment. Gene-specific primers were synthesized by Microsynth.

Primers used for RT-qPCR analysis

hY1 Forward: 5′-GGCTGGTCCGAAGGTAGTGA-3′ [32]

hY1 Reverse: 5′-GCAGTAGTGAGAAGGGGGGA-3′ [32]

hY3 Forward: 5′-GGCTGGTCCGAGTGCAGTGG-3′ [32]

hY3 Reverse: 5′-GAAGCAGTGGGAGTGGAGAA-3′ [32]

hY4 Forward: 5′-GGCTGGTCCGATGGTAGTGG-3′ [32]

hY4 Reverse: 5′-TTAGCAGTGGGGGGTTGTAT-3′ [32]

hY5 Forward: 5′-AGTTGGTCCGAGTGTTGTGG-3′ [32]

hY5 Reverse: 5′-AACAGCAAGCTAGTCAAGCG-3′ [32]

18S rRNA Forward: 5′-GAGAAACGGCTACCACATCCA-3′ [33]

18S rRNA Reverse: 5′-CTCCAATGGATCCTCGTTAA AGG-3′ [33]

GAPDH Forward: 5′-TCAAGGCTGAGAACGGGAAG-3′ [34]

GAPDH Reverse: 5′-CGCCCCACTTGATTTTGGAG-3′ [34]

SCD Forward: 5′-CTCTGCTACACTTGGGAGCC-3′ [35]

SCD Reverse: 5′-GAGCTCCTGCTGTTATGCCC-3′ [35]

CS Forward: 5′-GGACAATTTTCCAACCAATCTGC-3′ [36]

CS Reverse: 5′- AGTCAATGGCTCCGATACTGC-3′ [36]

KRT17 Forward: 5′-GGTGGGTGGTGAGATCAATGT-3′ [37]

KRT17 Reverse: 5′-CGCGGTTCAGTTCCTCTGTC-3′ [37]

Bcl-xL Forward: 5′- CGGTACCGGCGGGCATTCAG-3′ [38]

Bcl-xL Reverse: 5′- CGGCTCTCGGCTGCTGCATT-3′ [38]

CDK6 Forward: 5′-CCAGGCAGGCTTTTCATTCA-3′ [39]

CDK6 Reverse: 5′-AGGTCCTGGAAGTATGGGTG-3′ [39]

ASNS Forward: 5′-TGGCTGCCTTTTATCAGGGG-3′ [40]

ASNS Reverse: 5′-TCTGCCACCTTTCTAGCAGC-3′ [40]

ATF4 Forward: 5′- GGAGATAGGAAGCCAGACTACA -3′ [41]

ATF4 Reverse: 5′- GGCTCATACAGATGCCACTATC-3′ [41]

Polysome profiling

Prior to cell harvest, cells were treated with freshly prepared cycloheximide (CHX) (100 µg/ml, Carl Roth, Cat#8682.3) for 10 min. Cells were then washed with ice-cold PBS and lysed in buffer consisting of 30 mM HEPES/KOH (pH 7.6), 150 mM KOAc, 3.9 mM MgOAc₂, 4 mM DTT, 1% Triton^TM X-100 (Sigma–Aldrich, Cat#T8787), protease inhibitor cocktail (cOmplete™ ULTRA Tablets, Mini, EDTA-free, EASYpack, Roche, Cat#05892791001), RNasin® Ribonuclease Inhibitor (Promega, Cat#N2611), and 100 ng/ml CHX (Carl Roth, Cat#8682.3). To ensure complete cell lysis, the suspension was passed eight times through a 25G needle and centrifuged at 500 × g for 2 min at 4°C (Eppendorf Centrifuge 5804R, rotor F45-30-1). The supernatant was transferred to a new tube and centrifuged at 10 000 × g for 5 min at 4°C. The clarified lysate was collected into a fresh tube. For EDTA treatment, HeLa cell lysate was incubated with 80 mM EDTA (Gerbu, Cat#1034) for 30 min on ice.

Cell lysates containing 10–20 A₂₆₀ units were applied to linear 10%–50% (w/v) sucrose gradients prepared in gradient buffer (30 mM HEPES/KOH, pH 7.6, 150 mM Kac, 5 mM MgAc₂, 4 mM DTT, 1 mM PMSF, 100 µg/ml CHX). For dissociation experiments, lysates were treated with EDTA and layered onto gradients prepared in dissociation buffer (30 mM HEPES/KOH, pH 7.6, 150 mM Kac, 1 mM MgAc₂, 4 mM DTT, 1 mM PMSF). Gradients were centrifuged using a SW-41 swing-out rotor (Beckman) at 39 000 rpm for 2 h 45 min at 4°C. Subsequently, gradients were fractionated with a piston gradient fractionator (Biocomp) and monitored by UV absorbance at 260 nm. Fractions corresponding to free RNA, 40S, 60S, 80S, and polysomes were collected. RNA from each fraction was extracted with ROTI®Aqua-P/C/I (Carl Roth, Cat#X985.2) and precipitated using isopropanol in the presence of 1 μl GlycoBlue™ Coprecipitant (Invitrogen™, Cat#AM9516).

For purification of the 40S and 60S ribosomal subunits, cell lysates were incubated with 50 mM EDTA for 30 min on ice with intermittent vortexing, then applied to linear 10%–40% (w/v) sucrose gradients prepared in dissociation buffer. Gradients were centrifuged for 6 h at 39 000 rpm, 4°C, and fractions containing 40S and 60S subunits were identified by polysome profiling and pooled.

To purify 80S ribosomes, cell lysates were supplemented with 100 µg/ml puromycin (Sigma–Aldrich, Cat#P7255) and incubated at 37°C with shaking at 500 rpm for 15 min. Lysates were layered onto linear 10%–40% (w/v) sucrose gradients prepared in gradient buffer and centrifuged for 2.5 h at 39 000 rpm, 4°C. Fractions containing 80S ribosomes were identified by polysome profiling and pooled.

For ribosome and subunit pelleting, pooled fractions containing 40S, 60S subunits, or 80S ribosomes were diluted in 10% sucrose solution and subjected to overnight centrifugation for 16 h at 39 000 rpm, 4°C. The resulting pellets were resuspended for downstream analysis.

In vitro transcription

DNA templates for hY3, hY3 mutant, Scrambled, and hY1 were generated by PCR. For template assembly, long primers containing the T7 RNA polymerase promoter sequence were first annealed and extended. The resulting products were then amplified PCR using shorter primers.

hY3 Primer Extension Forward 5′-3′:

GGATCCTAATACGACTCACTATAGGCTGGTCCGAGT GCAGTGGTGTTTACAACTAATTGATCACAACCAGTT

hY3 Primer Extension Reverse 5′-3′: AAAAGGCTAGTCAAGTGAAGCAGTGGGAGTGGAGAAGGAACAAAGAAATCTGTAACTGGTTGTGATCAATTAG

hY3 Primer Amplification Forward 5′-3′: GGGATCCTAATACGACTCACTATA

hY3 Primer Amplification Reverse 5′-3′: AAAAGGCTAGTCAAGTGAAGC

hY3 Δ54–70 Primer Extension Forward 5′-3′:

GGATCCTAATACGACTCACTATAGGCTGGTCCGAGT GCAGTGGTGTTTACAACTAATTGATCACAACCAGTT

hY3 Δ54–70 Primer Extension Reverse 5′-3′:

AAAAGGCTAGTCAAGTGAAGCAGTGGGAGTGGCT GTAACTGGTTGTGATCAATTAG

hY3 Δ54–70 Primer Amplification Forward 5′-3′: GGGATCCTAATACGACTCACTATA

hY3 Δ54–70 Primer Amplification Reverse 5′-3′: AAAAGGCTAGTCAAGTGAAGC

Scrambled Primer Extension Forward 5′-3′: GGATCCTAATACGACTCACTATAGACGTTCTATTAACTTGCTCTATCTATTGTCTTAGTTCCATATATCATGT

Scrambled Primer Extension Reverse 5′-3′: GACGGCTCGTAACGAACTTGGCAGGATCGAGTTGCCGAGTATCAGAGCGCAGACATGATATATGGAACTAAGA

Scrambled Primer Amplification Forward 5′-3′: GGGATCCTAATACGACTCACTATA

Scrambled Primer Amplification Reverse 5′-3′: GACGGCTCGTAACGAACTTG

Scrambled 2 Primer Extension Forward 5′-3′: GGATCCTAATACGACTCACTATAGTTCCGTGGTATTAATCGTCCTACTCTCCTGTCGTAACTAAGTGAGTAC

Scrambled 2 Primer Extension Reverse 5′-3′: TAGGAAGGTGGACGAACCTAGCGATATCGATTGATTACAGACAAGGTAGCAGAGTACTCACTTAGTTACGAC

Scrambled 2 Primer Amplification Forward 5′-3′: GGGATCCTAATACGACTCACTATA

Scrambled 2 Primer Amplification Reverse 5′-3′: TAGGAAGGTGGACGAACCTAG

PCR products were purified with the Wizard® SV Gel and PCR Clean-Up System (Promega, Cat#A9281). In vitro transcription reactions were performed under the following standard conditions: 40 mM Tris–HCl (pH 7.5), 40 mM DTT, 2 mM spermidine, 3.75 mM of each NTP, 20 mM MgCl₂, T7 RNA Polymerase (Thermo Fisher Scientific, Cat#EP0111), RNasin® Ribonuclease Inhibitor (Promega, Cat#N2611), and 10 µg DNA template/ml [42]. For crosslinking experiments, 4-Thio-UTP (Jena Bioscience, Cat#NU-1156) was included at an 80% substitution rate. Transcription reactions were incubated in a water bath at 37°C for 6–7 h.

Transcribed RNAs were purified with ROTI®Aqua-P/C/I (Carl Roth, Cat#X985.2) and precipitated in isopropanol using 1 μl GlycoBlue™ Coprecipitant (Invitrogen™, Cat#AM9516). Further purification was performed by size-exclusion chromatography using Sephadex® G-25 (Sigma–Aldrich, Cat#G2580) in 0.3 M NaOAc.

For filter binding and crosslinking assays, transcribed RNA was denatured at 95°C for 2 min, cooled, and dephosphorylated with Quick CIP (New England Biolabs, Cat#M0525) at 37°C for 30 min. RNA was then phenol-chloroform extracted, precipitated in isopropanol with 1 μl GlycoBlue^TM Coprecipitant, and 5′ end-labeled with T4 Polynucleotide Kinase (Thermo Fisher Scientific, Cat#EK0032) and [γ-32P]-ATP (Hartmann Analytic, Cat#SCP-501). Labeled RNA was purified with illustra MicroSpin^TM G-25 Columns (Cytiva, Cat#27-5325-01) according to the manufacturer’s instructions prior to use.

In vitro binding studies

Binding studies of hY3 and hY3 Δ54–70 with ribosomes were performed using a dot blot-filtering device. A scrambled sequence of hY3 served as a negative control for background binding. For each experiment, 3 pmol of purified HeLa ribosomal particles (80S, 60S, or 40S) were incubated with 3 pmol of 5′[32P]-end-labeled in vitro-transcribed RNA in a final volume of 25 μl binding buffer (30 mM HEPES-KOH, pH 7.6, 150 mM KOAc, 3.9 mM MgOAc₂, 4 mM DTT). Following 30 min incubation at 37°C, reactions were diluted with 175 μl ice-cold binding buffer and filtered through pre-equilibrated nitrocellulose membranes (Amersham^TM Protran^TM Premium 0.45 μm NC Nitrocellulose blotting membrane, Cytiva, Cat#10600003) using a vacuum filtration device. Membranes were washed twice with 200 μl ice-cold binding buffer, dried, and exposed to phosphor imaging screens. Radioactive signals were acquired using a Typhoon FLA 9000 phosphor imager (GE Healthcare) and quantified with ImageQuant TL-11 software (Cytiva).

Crosslinking of 4-thio-U-hY3 to HeLa ribosomes

For crosslinking experiments, 4 pmol of 5′[32P]-end-labeled in vitro-transcribed hY3 RNA substituted with 80% 4-thiouridine (4-thioU) were incubated with 4 pmol of purified HeLa ribosomal particles (80S, 60S, or 40S) in a final volume of 18 μl binding buffer (30 mM HEPES-KOH, pH 7.6, 150 mM KOAc, 3.9 mM MgOAc₂, 4 mM DTT). Two scrambled sequences served as negative controls for background binding (Scrambled and Scrambled 2; Scrambled 2 was used exclusively in crosslinking experiments). Following 30 min incubation at 37°C, samples were placed on ice and UV-crosslinked at 365 nm for 15 min. Control samples were incubated on ice without UV exposure. One control reaction was subsequently treated with Protease K for 15 min at 37°C after crosslinking. All samples were supplemented with 6 μl of 4× Laemmli buffer, heated at 95°C for 5 min, and resolved on 7% SDS–polyacrylamide gel electrophoresis (PAGE) gels. Gels were dried onto Whatman® gel blotting paper (Grade GB003, Sigma–Aldrich, Cat#WHA10426892) and exposed to phosphor imaging screens. Radioactive signals were acquired using a Typhoon FLA 9000 phosphor imager (GE Healthcare).

In vitro translation in HeLa cell extracts

In vitro translation systems using crude HeLa cell lysates were prepared according to a previously described protocol [43]. HeLa cells were cultured in 150 cm² plates and harvested at 80%–90% confluency using trypsin-EDTA (0.05% Trypsin-EDTA 1×, Gibco™, Thermo Fisher Scientific, Cat#25 300 062) at 37°C for 5 min. Cell pellets were resuspended in 400 μl lysis buffer [30 mM HEPES/KOH, pH 7.6, 150 mM KOAc, 3.9 mM MgOAc₂, 4 mM DTT, 1% TritonTM X-100 (Sigma–Aldrich, Cat#T8787), protease inhibitor cocktail (cOmplete™ ULTRA Tablets, Mini, EDTA-free, EASYpack, Roche, Cat#05892791001), and RNasin® Ribonuclease Inhibitor (Promega, Cat#N2611)]. To ensure complete cell lysis, cell suspensions were passed 10 times through a 25-gauge needle attached to a 1-ml syringe. After removal of cell debris by centrifugation at 20 000 × g for 15 min at 4°C, lysates were diluted to 10–15 mg/ml with resuspension buffer containing 30 mM HEPES/KOH (pH 7.6), 150 mM KOAc, 3.9 mM MgOAc₂, 4 mM DTT, protease inhibitor cocktail (cOmplete™ ULTRA Tablets, Mini, EDTA-free, EASYpack, Roche, Cat#05892791001), and RNasin® Ribonuclease Inhibitor (Promega, Cat#N2611).

Translation reactions were prepared by combining 6 μl cell lysate with water to a final volume of 9.9 μl. To study hY3 effect on translation, water was replaced with 100 pmol of in vitro-transcribed RNA (hY1, hY3, or Scrambled control). CHX at a final concentration of 7.5 mg/ml was used as a translation inhibition control. After pre-incubation at 37°C for 10 min, 2.1 μl of freshly prepared translation mix was added, consisting of: 1.2 μl 10× translation cocktail [150 mM HEPES/KOH, pH 7.6, 750 mM KOAc, 19.5 mM MgOAc₂, 4 mM GTP, 17.5 mM ATP, 500 μM amino acid mixture minus methionine (Promega, Cat#L996B)], 0.17 μl H₂O, 0.08 μl 3 M creatine phosphate, 0.06 μl 20 mg/ml creatine phosphokinase (prepared in water with 40% glycerol), and 0.625 μl ³⁵S-methionine (10 μCi/μl, Hartmann Analytic, Cat#SCIS-103) for a final reaction volume of 12 μl. Translation reactions were incubated at 37°C for 20 min and stopped with 12 μl 2× Laemmli buffer. After boiling samples for 5 min at 95°C, reactions were resolved on 10% SDS-polyacrylamide gels. Gels were stained with Coomassie solution, destained, vacuum-dried at 70°C for 45 min onto Whatman® gel blotting paper (Grade GB003, Sigma–Aldrich, Cat#WHA10426892), and exposed to phosphor imaging screens. Radioactive signals were acquired using a Typhoon FLA 9000 phosphor imager (GE Healthcare) and quantified with ImageQuant TL-11 software (Cytiva).

Metabolic labeling

For metabolic labeling experiments, HeLa cells were grown in 12-well plates. Following siRNA (small interfering RNA) transfection or hY3 overexpression, cells were incubated with fresh 1 ml RPMI 1640 medium (Gibco™, Thermo Fisher Scientific, Cat#31 870 025) supplemented with 1 μl ³⁵S-methionine (10 μCi/μl, Hartmann Analytic, Cat#SCIS-103) for 1 h at 37°C. Cells were then harvested by scraping in 60 μl lysis buffer containing 30 mM HEPES/KOH (pH 7.6), 150 mM KOAc, 3.9 mM MgOAc₂, 4 mM DTT, 1% Triton^TM X-100 (Sigma–Aldrich, Cat#T8787), protease inhibitor cocktail (cOmplete™ ULTRA Tablets, Mini, EDTA-free, EASYpack, Roche, Cat#05892791001), and RNasin® Ribonuclease Inhibitor (Promega, Cat#N2611), and supplemented with 20 μl 4× Laemmli buffer. After brief sonication on ice, samples were boiled for 5 min at 95°C. A 10 μl aliquot of each reaction was resolved on 10% SDS-polyacrylamide gels. Gels were stained with Coomassie solution, destained, vacuum-dried at 70°C for 45 min onto Whatman® gel blotting paper (Grade GB003, Sigma–Aldrich, Cat#WHA10426892), and exposed to phosphor imaging screens. Radioactive signals were acquired using a Typhoon FLA 9000 phosphor imager (GE Healthcare) and quantified with ImageQuant TL-11 software (Cytiva).

Overexpression of hY3

DNA from HeLa cells was extracted using TRI Reagent® (Zymo Research, Cat#R2050-1-200). After removing the aqueous phase, DNA was precipitated with 100% ethanol and pelleted by centrifugation at 2000 × g for 5 min at 4°C. The pellet was resuspended in 0.1 M sodium citrate in 10% ethanol (pH 8.5), incubated for 30 min, and centrifuged at 2000 × g for 5 min at 4°C. This washing step was repeated twice. The pellet was then resuspended in 75% ethanol, incubated for 20 min, and centrifuged at 2000 × g for 5 min at 4°C. After air-drying the pellet, it was resuspended in 8 mM NaOH and centrifuged at 12 000 × g for 10 min at 4°C to remove insoluble material. The pH was adjusted to 8.0 with HEPES, and DNA concentration was measured using a NanoDrop spectrophotometer.

Primers used for amplification of the hY3 sequence from genomic DNA:

Forward: 5′-ACCGTGGGAGTCTTTGATGG-3′

Reverse: 5′-GGAACAGAAAATGCTTTCCCACC-3′

PCR was performed using Phusion® High-Fidelity DNA Polymerase (New England Biolabs, Cat#M0530) according to the manufacturer’s protocol with an annealing temperature of 57°C, 5× Phusion GC Buffer, and 250 ng genomic DNA template. PCR products were resolved on 1% low-melting-point agarose gels and purified using the Wizard® SV Gel and PCR Clean-Up System (Promega, Cat#A9281).

For standard cloning of PCR products into pGEM®-T Easy vector systems (Promega, Cat#A1360), A-tailing was performed by adding Taq DNA Polymerase (New England Biolabs, Cat#M0267) and incubating at 72°C for 20 min according to the manufacturer’s protocol. Ligations were performed according to the manufacturer’s protocol (pGEM®-T Easy Vector System, Promega, Cat#A1360) using 50 ng vector and 5 ng insert, incubated for 1 h at room temperature. XL1-Blue competent cells were incubated with the ligation mixture for 45 min on ice, followed by heat shock at 42°C for 45 s. Samples were incubated on ice for 2 min, diluted with 300 μl LB medium, and incubated at 37°C with shaking for 1 h. Cells were plated on LB-ampicillin selection plates containing IPTG and X-gal and incubated overnight at 37°C.

Successfully transformed colonies were cultured overnight, and plasmid DNA was isolated using the Wizard® Plus SV Minipreps DNA Purification System (Promega, Cat#A1330) before sequencing at Microsynth using SP6 primer. Subsequently, midiprep was performed using the QIAGEN® Plasmid Plus Midi Kit (Qiagen, Cat#12943) following the manufacturer’s protocol. Plasmid DNA integrity was verified by agarose gel electrophoresis, and concentration was measured using a NanoDrop spectrophotometer.

For the overexpression of the hY3 deletion mutant Δ54–70, site-directed mutagenesis was performed on a pGEM®-T Easy vector containing the hY3 WT sequence using PCR with the following primers:

Forward: 5′-AGTTACAGCCACTCCCACTGCTTCACT-3′

Reverse: 5′-GGAGTGGCTGTAACTGGTTGTGATC AATTAGT-3′

Following PCR amplification, the parental plasmid DNA was digested with DpnI (New England Biolabs, Cat#R0176S). The PCR product was subsequently purified using the Wizard® SV Gel and PCR Clean-Up System (Promega, Cat#A9281).

For transfection experiments, HeLa cells were seeded at 0.8 × 10⁵ cells per well in 12-well plates 12 h prior to transfection. Plasmid DNA (0.5 μg) was transfected using 1.5 μl Lipofectamine^TM 3000 Reagent (InvitrogenTM, Cat#L3000008) in antibiotic-free RPMI 1640 medium (Gibco^TM, Thermo Fisher Scientific, Cat#31870025) according to the manufacturer’s protocol. After 6 h, cells were washed with PBS, and fresh RPMI medium supplemented with antibiotics was added. Cells were used for experiments 24 h post-transfection.

siRNA transfection

HeLa cells were seeded at a density of 0.3 × 10⁵ cells per well in 24-well plates, 0.6 × 10⁵ cells per well in 12-well plates, and 1.5 × 10⁵ cells per well in six-well plates. After 12 h, cells were transfected with siRNA using Lipofectamine™ RNAiMAX Transfection Reagent (Invitrogen^TM, Cat#13778075) in antibiotic-free RPMI 1640 medium (Gibco^TM, Thermo Fisher Scientific, Cat#31870025), following manufacturer’s instructions. The transfection complexes were prepared in Opti-MEM^TM Reduced Serum Medium (Gibco^TM, Cat#31985062). For each well format, the following amounts were used: 2.5 pmol siRNA and 1.5 μl Lipofectamine in 24-well plates, 5 pmol siRNA and 3 μl Lipofectamine in 12-well plates, and 13 pmol siRNA and 7 μl Lipofectamin in six-well plates. Cells were incubated for 48 h post-transfection before being employed for downstream experiments.

hY1 siRNA: 5′-UGUUCUACUCUUUCCCCCCUU-3′ [44]

hY3 siRNA: 5′-CUAAUUGAUCACAACCAGU-3′ [44]

hY3_2 siRNA: 5′-AUUUCUUUGUUCCUUCUCCAC-3′ [44]

hY3_3 siRNA: 5′-UUUACAACUAAUUGAUCACAA-3′ [44]

Non-targeting negative control siRNA: 5′-AGGUAGUGUAAUCGCCUUG-3′ (Microsynth)

rRNA level analysis

2 × 10⁵ HeLa cells transfected with hY1, hY3, or control siRNA were collected in TRI Reagent® (Zymo Research, Cat#R2050-1-200). Two micrograms Spike-in RNA were added to each sample as an internal control. RNA extraction was performed according to the manufacturer’s protocol and precipitated using isopropanol in the presence of 1 μl GlycoBlue™ Coprecipitant (Invitrogen™, Cat#AM9516). Extracted RNA was mixed with RNA Gel Loading Dye 2× (Thermo Fisher Scientific, Cat#R0641) containing ethidium bromide (EtBr). RNA samples were denatured at 70°C for 3 min and loaded onto a 1% denaturing agarose gel. Electrophoresis was performed at 100 V for 1.5 h. EtBr fluorescence of ribosomal RNA (rRNA) bands was normalized to spike-in RNA levels for quantitative analysis.

Cell proliferation and viability assays

HeLa cells were seeded in 24-well plates at 0.3 × 10⁵ cells/well and transfected 12 h later with control, hY1, or hY3 siRNA. An untreated condition served as additional control.

For proliferation assays, cells were harvested and counted at 0 h (time of transfection), 24 h, and 48 h post-transfection. For viability assays, 48 h post-transfection cells were incubated in low-glucose DMEM medium lacking amino acids and serum (DMEM with 1.0 g/l glucose, without L-glutamine, without amino acids, with sodium pyruvate, with 3.7 g/l NaHCO₃; PAN-Biotech, Cat#P0401507). Viability was assessed at 0, 1, 2, 3, and 4 h of starvation. Images were acquired with Nikon Mikroskop Eclipse TS2.

For cell counting, cells were detached with 0.05% trypsin-EDTA (Gibco™, Thermo Fisher Scientific, Cat#25300062) at 37°C for 5 min and counted using a LUNA-II™ Automated Cell Counter (Logos Biosystems).

Seahorse XFe96 metabolic flux analysis

Metabolic flux was analyzed using a Seahorse XFe96 analyzer (Agilent Technologies). Oxygen consumption rate (OCR), an indicator of mitochondrial respiration, and extracellular acidification rate (ECAR), a measure of glycolysis, were recorded simultaneously. HeLa cells transfected with hY3, hY3_2, hY3_3, or control siRNA in DMEM/F-12 (Gibco™, Cat#21331046, supplemented with 10% FBS, Gibco™, Cat#A5669801, and 1× Pen-Strep glutamine, Gibco™, Cat#10378016) were seeded at a density of 20 000 cells/well in a 96-well assay plate 24 h prior to analysis. On the day of the experiment, cells were washed twice with assay medium (DMEM, Merck, Cat#D5030) supplemented with 5.5 mmol/l glucose (Merck, Cat#G7021), 1 mmol/l sodium pyruvate (Merck, Cat#P5240), 5 mmol/l HEPES (Merck, Cat#H0887), 0.2 mmol/l MEM non-essential amino acids (Gibco, Cat#11140035), 0.5 mg/ml penicillin, streptomycin, and glutamine; pH 7.4 (Gibco, Cat#10378016). Following a 1 h incubation at 37°C in a non-humidified, CO₂-free incubator, a mito stress test was performed using Seahorse XFE96 flux paks (Agilent Technologies, Cat#103792-100). OCR and ECAR were measured under basal conditions followed by a sequential injection of oligomycin (1 µmol/l, complex V inhibitor, Merck, Cat#O4876), carbonyl cyanide-p-trifluoromethoxyphenylhydrazone (FCCP) (0.75 µmol/l, uncoupler, Merck, Cat#SML2959), and rotenone (1 µmol/l, complex I inhibitor, Merck, Cat#R8875)/antimycin A (0.5 µmol/l, complex III inhibitor, Merck, Cat#A8674) mix. Optimal concentrations of these metabolic modulators were determined via prior titration. Bioenergetic profiling was conducted on background-corrected OCR and ECAR data as previously described [45]. ORC and ECAR data were normalized to total DNA content (CyQuant, Invitrogen, Cat#C7026). Control cells were analyzed in two biological replicates, and hY3-depleted cells in three biological replicates; all groups included eight technical replicates

MTT assay

HeLa cells were seeded in a 24-well plate at a density of 0.3 × 10⁵ cells/well and transfected with control, hY1, or hY3 siRNA. An untreated condition was included as additional control. Forty-eight hours post-transfection, 250 μl of MTT solution (5 mg/ml in PBS; Invitrogen™, Cat#M6494) were added to each well and incubated at 37°C for 1 h. The MTT solution was then removed, and 300 μl of DMSO (Carl Roth, Cat#7029.1) were added to solubilize the formazan crystals. Absorbance was measured at 570 nm using a Tacan plate reader. To account for differences in cell number, a parallel plate of identically treated cells was used for cell counting with the LUNA-II™ Automated Cell Counter (Logos Biosystems). Relative metabolic activity was calculated by normalizing the MTT absorbance values to the corresponding cell counts for each condition.

Western blot analysis

Cells were harvested in RIPA lysis buffer containing 150 mM NaCl, 50 mM Tris–HCl (pH 8), 0.1% SDS, 0.5% sodium deoxycholate, and 1% NP-40 (IGEPAL® CA-630, Sigma–Aldrich, Cat#56741–50ML-F) supplemented with Protease Inhibitor Cocktail (Roche, Cat#05892791001) and Phosphatase Inhibitor (Thermo Fisher Scientific, Cat#A32957). Lysates were centrifuged at 16 000 × g for 10 min at 4°C to remove debris. Protein concentration was determined by the Pierce^TM BCA Protein Assay Kit (Thermo Fisher Scientific, Cat#23227).

Between 30 and 50 μg of total protein was resolved by SDS–PAGE, then transferred to Amersham™ Protran™ Premium 0.45 μm NC Nitrocellulose membrane (Cytiva, Cat#10600003). Membranes were blocked with 3% milk in TBST and incubated with primary antibodies diluted in blocking solution: GAPDH (1:2000, Rabbit Anti-GAPDH Monoclonal Antibody, Cell Signaling Technology, Cat#2118; RRID:AB_561053), ATF4 (1:1000, ATF-4 (B-3), Santa Cruz Biotechnology, Cat#sc-390063; RRID:AB_2810998), ASNS (1:1000, ASNS (G-10), Cat#sc-365809; RRID:AB_10843357), eIF2α (1:2500, eIF2 alpha Antibody, Cell Signaling Technology, Cat#9722; RRID:AB_2230924), phospho-eIF2α (p-eIF2α) (1:2500, Phospho-eIF2alpha (Ser51) Antibody, Cell Signaling Technology, Cat#9721; RRID:AB_330951), Bcl-xL (1:1000, Bcl-xL (54H6) Rabbit mAb, Cell Signaling Technology, Cat#2764, RRID:AB_2228008), PARP1 (1:1000, PARP-1 (F-2), Santa Cruz Biotechnology, Cat#sc-8007; RRID:AB_628105), and P62 (1:1000, SQSTM1/p62 (D5L7G) Mouse mAb, Cell Signaling Technology, Cat#88 588; RRID:AB_2800125). HRP-conjugated secondary antibodies (1:2000 dilution in 3% Milk/TBST, Anti-mouse IgG, HRP-linked Antibody, Cell Signaling Technology, Cat#7076; RRID:AB_330924, Anti-rabbit IgG, HRP-linked Antibody, Cell Signaling Technology, Cat#7074; RRID:AB_2099233) were used for detection.

Proteins were visualized using SuperSignal™ West Femto Maximum Sensitivity Substrate (Thermo Fisher Scientific, Cat#34095). Representative blots from three or four independent experiments are shown in the figures. Quantification of band intensities was performed using ImageQuant TL-11 software (Cytiva).

RNA isolation and sequencing of translationally active ribosome-associated RNAs

Translationally active ribosome-associated RNAs were isolated using the AHARIBO RNA System (Immagina Biotechnology, Cat#AHA-RM12). Briefly, 150 000 HeLa cells per well were seeded in six-well plates and cultured in RPMI 1640 medium (Gibco™, Cat#31870025). Cells were transfected with 13 pmol siRNA using 7 μl Lipofectamine™ RNAiMAX (Invitrogen^TM, Cat#13778075) prepared in Opti-MEM^TM Reduced Serum Medium (Gibco™, Cat#31985062); transfections were performed in RPMI 1640 medium without antibiotics. After 48 h, media was removed, and cells were washed twice with PBS.

Cells were incubated for 20 min at 37°C in low glucose DMEM medium lacking amino acids and serum (DMEM, w: 1.0 g/l Glucose; w/o L-Glutamine, w/o Amino acids; w/ Sodium pyruvate; w/ 3.7 g/l NaHCO3; PAN-Biotech, Cat#P0401507) supplemented with 10 μl L-azidohomoalanine (AHA). After addition of 2.6 μl sBlock, cells were incubated for an additional 5 min at 37°C. Cells were placed on ice, washed with cold PBS, and lysed with 45 μl cold lysis buffer, followed by vigorous scraping. Lysates were centrifuged at 20 000 × g for 5 min at 4°C. The supernatant was collected, kept on ice for 20 min, and its absorbance measured at 260 nm on a NanoDrop, using lysis buffer for blank subtraction.

Pull-down of active ribosomes was performed by diluting 2 absorbance units (AU) of lysate to 100 μl with freshly prepared Supplemented WB (SWB) Buffer, adding 100 μl of functionalized sBeads, and incubating for 60 min on a slow rotator at 4°C. Beads were washed twice with 700 μl WSS solution and resuspended in 50 μl SWB Buffer. Ribosome-bound RNA was extracted from the bead suspension using the RNA Clean & Concentrator^TM-5 Kit (Zymo Research, Cat#R1015) and eluted in 15 μl nuclease-free water.

For comparative analysis, HeLa cells grown in complete RPMI 1640 medium or starved in low glucose DMEM (as earlier) for 20 min were collected in 1 ml TRI Reagent® (Zymo Research, Cat#R2050-1-200) and RNA was extracted with the Direct-zol^TM RNA MiniPrep Kit (Zymo Research, Cat#R2050), eluted in 50 μl.

All RNA samples underwent rRNA depletion (H/R/M) prior to library preparation. Sequencing libraries were generated using Lexogen’s CORALL^TM RNA-Seq V2 Library Prep Kit with UDIs. Libraries were sequenced as single-end 100 bp reads (SR100).

Reference genomes and annotations (RNA-seq in HeLa cells)

The reference genome and transcriptome for human (GRCh38; annotation version 113) was obtained from ENSEMBL [46].

Bulk RNA sequencing (RNA-seq in HeLa cells)

Decoy (full genome) aware indexing of transcriptome was done using salmon with the parameter “–kmerLen 31″ [47]. Single-end reads from bulk RNA-seq datasets were processed to remove the Illumina universal adapter (AGATCGGAAGAGCACACGTCTGAACTCCAGTCA) using Cutadapt (v4.4) with the parameters “-q 25 -m 25 –cut 12” [28]. The resulting filtered reads were quantified against the index using Salmon with the parameters “–libType A –gcBias –seqBias –useVBOpt –validateMappings.” Subsequent data analysis was performed with custom scripts in R. Data wrangling and visualization were performed using tidyverse package (v2.0.0) [48]. Transcript quantifications were imported using Tximeta [49] and differential expression analysis was conducted using DESeq2 (v1.44) [50].

Differential expression analysis between hY3 siRNA and Control siRNA groups was performed using the python3 gprofiler-official toolkit (v1.0) [51], accessing g:Profiler databases (v2025.01.31). Significantly differentially expressed genes were defined as having absolute log fold change > thresholds mentioned in respective figures and adjusted P-value < .05. Volcano plot analysis was conducted using the python package matplotlib (v3.10).

Reference genomes and annotations (RNA-seq in HeLa cells)

To assess biological pathway enrichment using the differential expression results, we used the gprofiler-official Python package incorporating annotations from Reactome, Gene Ontology (GO) Biological Processes, and GO Cellular Components. We utilized genes with ±0.585 log₂-fold change expression and false discovery rate (FDR) < 0.05 applying Benjamini–Hochberg correction for multiple comparisons and assessed the top 10 (for GO) and five upregulated and downregulated pathways, deeming pathways with a P-value < .05 as significant.

Preranked gene set enrichment analysis (GSEA) was performed using the GSEApy package with GO:CC_Mitochondrion gene set collection (GO:0 005 739), GO:BP cytoplasmic translation gene set collection (GO:0 002 181) and GP:BP ribosome biogenes gene set collection (GO:0 042 254) and starvation states as input, using the calculated log₂-fold change multiplied by -log₁₀(FDR) as the rank statistic. We further selected the top 20 enriched genes and computed their z-score per replicate to compare hY3 and control siRNA conditions.

Quantification and statistical analylsis

Statistical analyses and the sample sizes for each experiment are specified in the respective figure legends. Data were analyzed and visualized using GraphPad Prism 10.

Results

hY3 associates with the ribosome

Our initial investigation into transcriptome dynamics across proliferating, quiescent, and senescent primary HDFs revealed the upregulation of the hY RNA family in non-proliferating cell conditions possessing reduced translation activity (Fig. 1A and B). HDFs from two independent donors exhibited significantly increased hY RNA levels in quiescent and senescent states compared to their proliferating counterparts, a finding that was further validated via northern blot (NB) analysis (Fig. 1C). Driven by our previous findings on rancRNA-mediated translation regulation, we analyzed the rancRNA interactome of ribosomes and polysomes in these HDFs. Considering that both quiescent and senescent cells exhibit metabolic adjustments that affect translational activities, we reasoned that these HDF cells represent a good system for uncovering novel human rancRNAs [52–54]. Deep sequencing analysis of the ribosome-bound RNome revealed a marked enrichment of hY3 and hY4 compared to the other hY RNA family members (Fig. 1D). Reverse transcription quantitative polymerase chain reaction (RT-qPCR) analysis further validated the presence of hY3 in ribosome-enriched subcellular fractions, with a consistently more pronounced signal in quiescent cells, supporting a potential ribosomal interaction of hY3 and its classification as a rancRNA (Fig. 1E). As hY4 was marginally detected in ribosome-enriched fractions, our analyses primarily focused on hY3.

To further dissect the molecular functions of hY3 RNA, we investigated its interaction with ribosomes by performing polysome profiling followed by NB analysis, using the immortalized human cervical cancer cell line HeLa as a tractable model system (Fig. 1F and G). Remarkably, hY3 substantially co-migrated with ribosomal and polysomal fractions in HeLa cells, in contrast to other members of the hY RNA family. Under normal growth conditions, ~10% of the total cellular hY3 was detected in ribosome-associated fractions. Moreover, we noticed that hY3 co-migration with ribosomal and polysomal fractions became more prominent as cell confluency increased and translational activity decreased (Supplementary Fig. S1A), resembling the increased presence observed in ribosome-enriched fractions of quiescent HDFs. This suggested that hY3 association with the ribosome may be regulated in response to a cellular need for attenuating metabolism and translational output.

To test whether co-migration in ribosome-enriched fractions derived from ribosome association, polysome profiling was performed in the presence of the Mg²⁺-chelator EDTA. EDTA dissociates ribosomes into the two ribosomal subunits, 40S and 60S. Upon EDTA treatment, the hY3 signal in the ribosome and polysomal fractions was markedly reduced and shifted to the ribosomal subunit fractions, suggesting that it indeed interacted with ribosomes (Fig. 1H).

To investigate the ribosome association more directly, radiolabeled in vitro-transcribed hY3 was used in an in vitro filter binding assay utilizing purified HeLa 80S ribosomes, or isolated 40S and 60S subunits. As background binding control, a scrambled hY3 sequence was used. The binding data showed that hY3 associates only with the 80S ribosome significantly (Fig. 1I). To delineate the functional region of the hY3 molecule responsible for ribosome association, we focused on the central loop region, where variations in length and sequence are the most discriminating features among the four human Y RNAs (Fig. 1G). To test whether the loop region contributes to ribosome binding, a hY3 variant with a 17-nucleotide AU-rich deletion in the loop region was generated (Fig. 1J), a design which was inspired by a previously characterized mouse Y3 RNA mutant reported to affect translational output [21]. Filter binding assay showed that this deletion mutant (hY3 Δ54–70) displayed clearly reduced binding to the 80S ribosomes compared to the full-length hY3 (hY3 WT), implying that the deleted hY3 loop region is a determinant in ribosome binding.

Furthermore, UV crosslinking experiments were performed using radiolabeled in vitro-transcribed hY3, substituted with 4-thio-uridines. Following incubation with purified ribosomes and UV irradiation at 365 nm, two distinct crosslinked signals were detected by autoradiography. This crosslinking pattern differed from that of the scrambled controls (Supplementary Fig. S1B). The disappearance of the signals upon proteinase K treatment further suggested that hY3 interacts primarily with ribosomal proteins or ribosome-associated proteins rather than rRNA.

Collectively, these findings support the view that hY3 associates with human ribosomes and polysomes, mediated at least in part by its loop sequence, and suggest that hY3 represents an interesting novel rancRNA candidate worth of deeper investigation.

hY3 inhibits translation in vitro and in cellulo

The association of hY3 with ribosomes led us to hypothesize that it may function as a regulatory ncRNA in protein biosynthesis. To investigate whether hY3 affects translation under defined in vitro conditions, we employed a cell-free translation system based on crude HeLa cell lysates [43]. De novo protein synthesis was quantified by the incorporation of radioactive ³⁵S-methionine. Supplementation with in vitro-transcribed hY3 consistently reduced global translation by ~30%. In contrast, neither a scrambled sequence, nor hY1 RNA caused a significant effect, suggesting a sequence-specific inhibitory role of hY3 in translation (Fig. 2A and B).

To corroborate the inhibitory effect of hY3 on translation observed in vitro, we extended our analysis to a cell-based system. We overexpressed hY3 WT in HeLa cells using its endogenous RNA polymerase III type 3 promoter (Fig. 2C). As a control, we overexpressed the ribosome binding-deficient hY3 mutant (hY3 Δ54–70) to investigate the contribution of the loop region to hY3 function. Consistent with the in vitro findings, overexpression of hY3 WT resulted in a significant reduction in protein biosynthesis, as assessed by ³⁵S-methionine incorporation (Fig. 2D). In contrast, overexpression of the hY3 deletion mutant (hY3 Δ54–70) did not significantly alter protein synthesis compared to HeLa cells transfected with the empty vector control. These results suggested that the hY3 ribosome association was important for the translation-regulatory activity. Notably, despite a robust increase in intracellular hY3 levels, translation was not completely suppressed. Given that endogenous hY3 is already abundant in cells, we hypothesized that this partial inhibition may reflect functional saturation which, as a consequence, limits the magnitude of the inhibitory effect upon overexpression.

To test this hypothesis, we asked whether hY3 depletion could relieve the inhibition and enhance translation. HeLa cells were transfected with an siRNA targeting the loop region of hY3. As controls, cells were transfected with either a non-targeting siRNA or a loop-targeting siRNA against hY1 (Fig. 2E and Supplementary Figs S2A and S4A, B). Remarkably, hY3 depletion resulted in a significant increase in global translation activity compared to both control conditions (Fig. 2F). This enhancement was further supported by polysome profiling, which revealed an increased polysome signal in hY3 depleted cells, indicative of raised translational engagement (Fig. 2G and Supplementary Fig. S2B). To determine whether this effect was due to increased ribosome content or enhanced translational efficiency, we assessed rRNA levels (Fig. 2H). hY3 knockdown led to no significant increase in fully maturated ribosomal rRNA, suggesting that changes in ribosome content are unlikely to account for the observed increase in translation.

Taken together, these results demonstrate that hY3 functions as a negative regulator of protein synthesis, both in vitro and in cellulo. Furthermore, the observation that reduction of hY3 alleviated its repressive effect on translation, combined with the high energy demand associated with translation, suggests that lower hY3 levels entail broader metabolic adaptation within cells.

hY3 impinges on the cellular metabolism

To deepen our understanding regarding the effects of hY3 depletion, we analyzed the transcriptome in HeLa cells following siRNA-mediated knockdown of hY3 by RNA-seq (Fig. 3A and Supplementary Fig. S3). Differential expression analysis identified 289 upregulated and 254 downregulated protein-coding genes (adjusted P-value < 0.05, |log₂FC| > 1) in cells with reduced hY3 levels compared to cells transfected with a non-targeting control siRNA. Functional enrichment analysis using Reactome and GO revealed an upregulation of genes associated with various metabolic processes, intracellular structures, mitochondrial function and cholesterol biosynthesis (Fig. 3B and C). These results suggested that the depletion of hY3 triggers a metabolic reprogramming shift that favors enhanced metabolic activity, energy production, and membrane synthesis.

The involvement of hY3 in the altered metabolic activities was further investigated using a Seahorse assay. Mitochondrial respiration and glycolytic activity were measured simultaneously in living HeLa cells transfected with either hY3-targeting siRNA or a non-targeting control siRNA by monitoring the OCR and ECAR, respectively (Fig. 3D and Supplementary Fig. S4C). hY3-depleted cells exhibited a higher energenic phenotype with increased mitochondrial respiration and glycolytic activity compared to control cells. To verify that this effect was indeed depending on altered hY3 levels, and not caused by putative siRNA off-targets effects, the hY3 knockdown and the seahorse assay were also performed using two other siRNA constructs targeting different regions of the hY3 (Supplementary Fig. S4A–C). The elevated mitochondrial respiration and glycolysis rates persisted also under these conditions, strongly indicating reduced hY3 levels as the cause of these effects.

This observation was further supported by a colorimetric MTT assay, which assesses mitochondrial metabolic activity through the conversion of tetrazolium salt into formazan. hY3-depleted cells showed a significant increase in metabolic activity compared with cells transfected with either a non non-targeting control siRNA or an hY1-targeting siRNA (Supplementary Fig. S4D).

To further explore this aspect, GSEA was performed on genes associated with mitochondrial function (Fig. 3E). Although the enrichment did not reach conventional thresholds for statistical significance, the results suggested a biological trend toward increased expression of mitochondrial genes following hY3 depletion.

The observed shift toward increased metabolic activity is consistent with our previous findings showing that hY3-depleted HeLa cells exhibit elevated translation rates compared with control cells (Fig. 2F and G). To further examine this relationship, gene set enrichment analyses were conducted on genes involved in cytoplasmic translation and ribosome biogenesis (Supplementary Fig. S4E). While the enrichment results for these categories did not reach statistical significance, they similarly indicated a biological trend toward enhanced translational activity upon hY3 depletion.

Concomitantly to the altered metabolism, the landscape of differential expression gene analysis revealed that hY3 depletion led to a downregulation of genes linked to extracellular matrix organization, basement membrane structure, anchoring junction, and collagen formation (Fig. 3B and C).

Together, these findings suggest that hY3 depletion promotes cellular metabolic activity at the expense of structural integrity and extracellular environment maintenance.

Depletion of hY3 results in increased translation activity and susceptibility to cell death during starvation

hY3 was more abundantly expressed in senescent and particularly in quiescent cells (Fig. 1B and C), cellular states characterized by metabolic adjustments. The observation that hY3 depletion increased metabolic activity, together with its inhibitory role in translation, led us to hypothesize that hY3 may orchestrate the cellular transition from an energetically demanding to an energy-conserving state. This shift might be facilitated by the coordinated modulation of both metabolism and protein synthesis. Such an adaptive response becomes especially important under unfavorable environmental conditions. Therefore, we reasoned that if hY3 contributes to the adaptation to limited energy resources, its absence might compromise the stress response and consequently impair the cellular ability to cope with stress.

To explore this, we investigated how hY3 influences the cellular response to nutrient starvation, a stress that conventionally requires both translational repression and metabolic downregulation. First, the distribution of hY3 in polysome profiles was examined during starvation. To this end, cells were exposed to low-glucose DMEM medium lacking amino acids and serum. Following 4 h of starvation, increased hY3 NB signals in both ribosomal and polysomal fractions were observed, suggesting enhanced association of hY3 with the ribosome (Fig. 4A). Subsequently, the functional relevance of hY3 during the early phase of nutrient deprivation was examined. For that purpose, hY3-depleted cells were exposed to 1 h of starvation. Remarkably, metabolic labeling revealed a significant increase in global translation in hY3-depleted cells, exceeding 50% (Fig. 4B and Supplementary Fig. S5A). Importantly, depletion of the hY1 paralog did not show this enhanced metabolic labeling phenotype compared with cells transfected with a non-targeting siRNA. This enhanced metabolic labeling activity again was independent on the hY3-targeting siRNA construct used (Supplementary Figs S4A and S5A). This result suggested that hY3 contributes to the prompt suppression of translation in response to nutrient shortage.

Concurrently, we observed that hY3-depleted cells were more vulnerable to prolonged starvation. During a 4-h starvation time course, cell viability was significantly reduced in hY3-depleted cells starting from 2 h onward, whereas control and hY1-depleted cells showed minimally affected survival characteristics (Fig. 4C and D; Supplementary Fig. S5B). Western blot analysis after 2 h of starvation revealed enhanced cleavage of the apoptosis marker PARP1 in hY3-depleted cells, indicating increased apoptosis (Fig. 4E). Notably, the levels of p62, an autophagy marker, decreased similarly in both hY3-depleted and control siRNA transfected cells, suggesting that autophagy, a major pro-survival response pathway to starvation, was not impaired.

These collective findings indicated that hY3’s role in attenuating global translation is considerably accentuated during nutrient deprivation stress. The depletion of hY3 led to sustained translation activity under energy-limiting conditions, culminating in compromised stress adaptation and increased cell death.

Depletion of hY3 disrupts the integrated stress response and alters expression of pro-survival factors during starvation

To understand why protein synthesis remains active during starvation and to uncover the mechanisms underlying the increased susceptibility to cell death, the transcriptome and translatome changes following hY3 depletion were investigated. Given the role of hY3 as a rancRNA, a class of ncRNA known to rapidly modulate translation by directly targeting the ribosome under stress, we focused on dynamic changes during the early phase of nutrient deprivation.

To trace active translation during the first 20 min of starvation, we performed metabolic labeling by supplementing the culture medium with the methionine analog L-AHA (Fig. 5A). AHA-labeled polypeptides were then used as tags for isolating actively translating ribosomes using magnetic beads. Deep sequencing was performed of both the ribosome-captured translated mRNAs (the translatome) and total RNA from HeLa cells transfected with either hY3-targeting siRNA or a control siRNA. To specifically assess the effect of hY3 on translation, we focused on mRNAs that remained stable in expression during starvation but exhibited altered translational output (Fig. 5B). Translation efficiency analysis identified 223 significantly affected mRNAs, with 79 upregulated and 144 downregulated in hY3-depleted cells compared to the control. Notably, downregulation of the anti-apoptotic factor Bcl-xL was observed in the absence of hY3 (Fig. 5B and Supplementary Fig. S6A). Furthermore, hY3 depletion led to a decreased BCL2 expression in the transcriptome RNA-seq analysis (Fig. 5C). This negative regulation of pro-survival factors suggested a tendency toward reduced cell survival signaling, thereby inclining the cellular stress balance toward a pro-apoptotic state.

We next searched for stress-related gene expression patterns in both the transcriptome and translatome RNA-seq analysis under starvation (Fig. 5C and D; Supplementary Figs S6B and S7). Interestingly, the ASNS and the ATF4, both key components of the ISR, were significantly downregulated in hY3-depleted cells compared to controls. This implied that the absence of hY3 resulted in a compromised activation of the ISR (Fig. 5E). The ISR is a central adaptive pathway which is triggered by various stresses, including nutrient deprivation. The activation of this protective response is driven by stress-sensing kinases (PERK, GCN2, PKR, HRI), which phosphorylate eIF2α. This leads to inhibition of global protein synthesis, and concomitant promotion of selective translation of stress-responsive genes such as transcription factor ATF4. Further downstream, ASNS is transcriptionally regulated by ATF4 to support amino acid homeostasis during nutrient stress. Due to the involvement of ATF4 and ASNS in the ISR, additional ISR markers were investigated across both the transcriptome and translatome datasets [56]. And indeed, hY3 depletion resulted in a broad reduction of ISR-related gene expression at both transcriptional and translational levels (Fig. 5F). To validate these findings, we performed western blot analysis of ATF4 and ASNS under normal and starvation conditions (Fig. 5G). Upon 30 min of starvation, both ATF4 and ASNS protein level were significantly lower in hY3-depleted cells compared to controls. While starvation induced expression of ATF4 and ASNS in both hY3-depleted and control cells, the increase was significantly attenuated in hY3-depleted cells, suggesting an impairment in the activation of the ISR upstream of ATF4. To further explore this possibility, we analyzed eIF2α phosphorylation by western blot analysis. Consistent with our hypothesis, hY3-depleted cells showed reduced levels of phosphorylated eIF2α (Fig. 5G and Supplementary Fig. S8A and B), indicating insufficient global translation repression in response to starvation stress, which aligns with the earlier observation of sustained translation (Fig. 4B and Supplementary Fig. S5A). The effect of hY3 on eIF2α phosphorylation was further supported by overexpression experiments. hY3 overexpression resulted in a s significant increase in phosphorylated eIF2α levels (Supplementary Fig. S8C and D). In contrast, overexpression of the ribosome binding-deficient hY3 mutant Δ54–70 did not alter p-eIF2α levels compared with cells transfected with an empty vector, highlighting the importance of hY3 ribosome-association for eIF2α phosphorylation and its role in translation regulation.

Collectively, these results demonstrated that the rancRNA hY3 plays a critical role in orchestrating the cellular stress response during starvation. Reduced hY3 levels impaired ISR activation, which resulted in incomplete translational reprogramming, followed by reduced stress adaptation, and ultimately promoting a shift toward pro-apoptotic signaling.

Discussion

The revelation of a diverse and ever-growing repertoire of ncRNAs governing fundamental cellular processes, including the fine-tuning of gene expression at both transcriptional and translational levels, is profoundly shaping our molecular understanding of cellular regulation [57, 58]. Converging evidence positions the translation machinery as a central regulatory hub modulated by ncRNAs, highlighting an emergent tier of post-transcriptional control [1].

In this study, we demonstrated that the hY3 RNA is associated with ribosomes and inhibits protein synthesis in HDF and HeLa cells (Fig. 1E, F, H, and I). hY3 is an abundant ncRNA, present at an order of magnitude of 10⁵ copies in human cell [59, 60], while ~10% thereof were found to associate to ribosomes (Fig. 1F). The ribosome-bound fraction of hY3 is likely an undeerstimatioin as the ncRNA most certainly dissociates to some extent during the polysome gradient centrifugation procedure. Furthermore, we have previously shown that targeting only a fraction of ribosomes with rancRNAs within polysomes is sufficient to yield global effects on translation [3]. Our data points to the central loop region of hY3 as a pivotal element for this ncRNA-ribosome interaction (Fig. 1J), potentially through RBP cofactors. The precise nature of this association, whether hY3 binds to the ribosome directly or through ribosome-associated proteins, remains to be clarified. Y RNAs are known for their complex interactomes, including RBPs such as Ro60 (TROVE2), La (SBB), HuR (ELAVL1), HuD (ELAVL4), polypyrimidine tract-binding protein 1 (PTBP1), HnRNP K, and IGF2BP1, all of which are involved in translational regulation and observed among ribosome-associated factors [21, 61–68]. This sustains the notion that hY3 functions as a scaffold to recruit regulatory proteins to the ribosome or as a molecular decoy [60]. Remarkably, the fact that the Y RBP Ro60 (TROVE2) has also been observed to associate with ribosomes further corroborates our finding that hY3 binds with the translation machinery [68].

Our studies showed that hY3 functions as a translational repressor in vitro and in a cellular context (Fig. 2A–G and Supplementary Figs S5A and S8). Increased levels of hY3 suppressed protein synthesis, while its depletion enhanced translational activity (Fig. 2D and F; Supplementary Fig. S5A). The mechanism underlying the observed translation inhibition needs yet to be clarified, namely, whether hY3 interferes with protein synthesis as a free RNA or as a part of a RNP complex that is associated with the ribosome. The role of Y3 RNA as an inhibitor of translation has previously been reported in studies conducted in mice [21]. There, mY3 has been shown to sequester HuD, and by doing so inhibit its translation enhancer activity, while the disruption of HuD-binding site within the mY3 loop region reversed this effect. This mechanism could extend to other RBPs that bind the loop region, such as the HuD paralog HuR, which has been reported to predominantly bind mY3 compared to other Y RNA family members [69]. We observed that the same deletion in the loop region of the hY3 RNA led to decreased binding efficiency to 80S ribosomes and a loss of its inhibitory effect on translation activity (Figs 1J and 2C, D; Supplementary Fig. S8C and D), supporting the functional significance of this hY3 region.

Given that protein synthesis is a highly energy-demanding process, we expected that hY3 depletion would induce a broad metabolic adaptation. Congruently, RNA-seq analysis and Seahorse assays confirmed activated metabolism upon hY3 depletion, without affecting viability under basal conditions (Fig. 3 and Supplementary Fig. S4C and D). Concomitantly, hY3 knockdown resulted in downregulation of extracellular matrix (ECM) component genes. In support of this, previous studies have detected Y RNAs on the cell surface of HeLa cell and other mammalian cell lines, implying roles in ECM remodeling and intercellular communication [70]. Furthermore, hY3 has been described to influence the complex remodeling of the extracellular matrix by inducing a specific phenotype of cardiac fibroblasts, a process mediated through the supernatants of hY3-transfected macrophages [71].

Our findings suggest that hY3 depletion enhances cellular metabolic activity, concurrently impending cellular structural integrity and the effective maintenance of the extracellular environment (Figs 2F, 3D, and 4B; Supplementary Figs S4C and S5A). This phenotype is reminiscent of cancer cells, where enhanced energy production and elevated protein biosynthesis are prioritized over structural integrity, leading to increased invasion and metastasis potential. Consistent with these traits, reduced Y RNA levels correlate with poor prognosis and increased malignancy in human tumors [72]. The collective evidence that hY3 is found upregulated in cellular conditions of attenuated metabolism, and that its depletion leads to enhanced metabolic activity, supports the idea that this ncRNA functions as an adaptive switch, which enables the transition from an energy-consuming state to an energy-conserving one. This adaptability is particularly relevant in situations of limited energy availability, such as nutrient starvation. Interestingly, under nutrient deprivation, we observed sustained and elevated translation activity in hY3-depleted cells compared to control cells (Fig. 4B and Supplementary Fig. S5A). After 2 h of starvation, these cells appeared more susceptible to nutrient restriction, and activation of apoptosis pathway predominated, culminating after 4 h of starvation in cell death (Fig. 4C–E).

Y RNAs have previously been shown to undergo specific and rapid caspase-dependent cleavage in response to various apoptosis stimuli in different human cell lines [73]. For hY3 RNA, degradation is initiated by caspase-3-mediated truncation of its loop-binding partner, PTBP1 [74]. Notably, this process is inhibited by Bcl-2 and caspase inhibitors [73]. The cleavage of Y RNAs during apoptosis has been hypothesized to limit the exposure of the bound autoantigens such as Ro60 and La to immune surveillance, as both RNP complexes are found within apoptotic bodies at the surface of apoptotic cells [75, 76]. Reduced Y RNA cleavage during apoptosis has been associated with immune system deregulation and the onset of autoimmune diseases [74]. Interestingly, the translocation of Ro60 on the cell surface during apoptosis has been shown to depend on Y3 [77]. Furthermore, Y RNA–derived small RNAs (YsRNAs) have been reported in the context of both apoptosis and inflammation [17, 18]. Together with our observation, this suggests that full length Y3 RNAs participates in cell survival under moderate stress conditions, however, when cellular stress becomes excessive, it is actively cleaved to elicit apoptosis. In alignment with this, we observed that full-length hY3 is necessary to delay the onset of apoptosis, and its depletion affects the expression of pro-survival factors: BCL2 was downregulated at the transcriptional level, whereas Bcl-xL was downregulated at the translational level (Fig. 5B and C; Supplementary Fig. S6A). Both of these anti-apoptotic factors, on their respective regulatory levels, are controlled by the hY3-binding protein HuR [78, 79]. Together, these findings support the notion that hY3 contributes to cell survival by promoting anti-apoptotic signaling and restricting pro-apoptotic pathways.

Furthermore, our RNA-seq analysis revealed that hY3 depletion resulted in the downregulation of ISR markers, specifically ATF4 and its target ASNS (Fig. 5C, D, F, and G). The decreased levels of ATF4 and ASNS indicate that ISR activation is attenuated under stress conditions. We also investigated upstream phosphorylation of eIF2α and observed reduced phosphorylation upon hY3 depletion (Fig. 5G and Supplementary Fig. S8A and B), which may explain the sustained translation activity observed during starvation conditions. This impairment of ISR activation could lead to oxidative stress accumulation, ultimately resulting in premature cell death. eIF2α phosphorylation during starvation is mediated by the ribosome-bound GCN2 kinase [10]. Notably, the hY3-binding protein HuR has been shown to interact with GCN2 and regulate eIF2α phosphorylation, with HuR depletion leading to increased eIF2α phosphorylation [80]. In line with these previous data, our findings utilizing the ribosome-deficient hY3 variant (Fig. 2C and D; Supplementary Fig. S8C and D), which lacks the HuD/R binding site [21], suggest a functional and likely physical interaction of GCN2, HuR and hY3 on the ribosome. Thus, our data are compatible with the scenario that hY3 RNA may participate in HuR sequestration and ISR activation. The involvement of hY3 in apoptosis and ISR regulation warrants further investigation in cancer cells, which exploit the ISR to survive and regulate apoptosis [12]. Increased Y RNA have been observed in solid tumors, which are often poorly vascularized and face nutrient limitation, suggesting that hY3 could provide an adaptive advantage for cancer cells [44].

In essence, our work established hY3 RNA as a rancRNA to act on translating ribosomes as a kind of cellular “brake” that regulates metabolism and translation. It is important to note that ribosome-association is a prerequsite for affecting these activities, since a ribosome binding-deficient hY3 RNA variant (Fig. 1J) failed to modulate protein biosynthesis, eIF2α phosphorylation, and the ISR (Fig. 2D and Supplementary Fig. S8C and D). This regulatory role is crucial during stress to preserve cellular integrity, positioning hY3 as a regulatory hub at the interface of translation control and stress adaptation. Its absence leads to incomplete ISR activation, resulting in uncontrolled translation under unfavorable conditions and shifting the balance toward increased apoptosis by affecting the expression of survival determinant factors (Fig. 6). While hY3 contributes to global translation repression, it simultaneously regulates the translation of selective mRNAs, likely through its interactions with translation regulatory proteins such as HuR. Binding proteins like HuR have been shown to perform dual functions: regulating eIF2α phosphorylation, maintaining ATF4 mRNA stability, and facilitating selective translation of pro-survival factor such as Bcl-xL [79–81].

This intricate regulatory network between metabolic and survival control underscores the importance of further investigating hY3’s dynamic interactome to obtain a complete picture, which will offer valuable insights for diseases characterized by dysregulated stress responses and apoptotic signaling. To the best of our knowledge hY3 RNA represents the first characterized ncRNA that orchestrates the ISR and targets the ribosome as demonstrated here in non-proliferating HDFs and starved immortalized cancer cells.

Supplementary Material

gkag832_Supplemental_File

gkag832_supplemental_file.pdf^{(2.8MB, pdf)}

Acknowledgements

We thank Max Wolfensberger and Marc Landolfo for their experimental support. The processing of genomics data was performed on the Euler high-performance computing cluster at ETH Zürich. We thank Pamela Nicholson and her team at the next-generation sequencing (NGS) platform of the University of Bern for their valuable contributions. The graphical abstract was created in BioRender. Pecoraro, V. (2026) https://BioRender.com/ikc19uj

Author contributions: Valentina Pecoraro (Conceptualization [equal], Formal analysis [lead], Investigation [lead], Methodology [equal], Visualization [lead], Writing—original draft [lead], Writing—review & editing [equal]), Eunbin Kong (Investigation [supporting], Writing—review & editing [supporting]), Puneet Sharma (Investigation [equal], Writing—review & editing [equal]), Yulia Gonskikh (Investigation [supporting], Writing—review & editing [supporting]), Marek Żywicki (Investigation [equal], Writing—review & editing [supporting]), Fabian Nagelreiter (Investigation [supporting], Writing—review & editing [supporting]), Markus Schosserer (Resources [equal], Writing—review & editing [supporting]), Katrin Freiburghaus (Investigation [supporting], Writing—review & editing [supporting]), Jean-Marc Nuoffer (Investigation [supporting], Writing—review & editing [supporting]), Johannes Grillari (Funding acquisition [supporting], Resources [equal], Writing—review & editing [supporting]), and Norbert Polacek (Conceptualization [lead], Funding acquisition [lead], Supervision [lead], Writing—review & editing [equal]).

Notes

Present address: Department of Biological Sciences and Pathobiology, University of Veterinary Medicine Vienna, Vienna 1210, Austria

Contributor Information

Valentina Pecoraro, Department of Chemistry, Biochemistry and Pharmaceutical Sciences, University of Bern, Bern 3012, Switzerland; Graduate School for Cellular and Biomedical Sciences, University of Bern, Bern 3012, Switzerland.

EunBin Kong, Department of Chemistry, Biochemistry and Pharmaceutical Sciences, University of Bern, Bern 3012, Switzerland.

Puneet Sharma, Institute of Biochemistry, ETH Zürich, Zürich 8093, Switzerland.

Yulia Gonskikh, Department of Chemistry, Biochemistry and Pharmaceutical Sciences, University of Bern, Bern 3012, Switzerland; Graduate School for Cellular and Biomedical Sciences, University of Bern, Bern 3012, Switzerland.

Marek Żywicki, Department of Computational Biology, Institute of Molecular Biology and Biotechnology, Adam Mickiewicz University, Poznań 61-614, Poland.

Fabian Nagelreiter, Institute of Molecular Biotechnology, BOKU University, 1190 Vienna, Austria.

Markus Schosserer, Institute of Molecular Biotechnology, BOKU University, 1190 Vienna, Austria; Institute of Medical Genetics, Center for Pathobiochemistry and Genetics, Medical University of Vienna, Vienna 1090, Austria.

Katrin Freiburghaus, University Institute of Clinical Chemistry, Inselspital, Bern University Hospital, University of Bern, Bern 3010, Switzerland; Graduate School for Health Sciences, University of Bern, Bern 3012, Switzerland.

Jean-Marc Nuoffer, University Institute of Clinical Chemistry, Inselspital, Bern University Hospital, University of Bern, Bern 3010, Switzerland.

Johannes Grillari, Institute of Molecular Biotechnology, BOKU University, 1190 Vienna, Austria; Ludwig Boltzmann Institute for Traumatology, The Research Center in Cooperation with AUVA, 1200 Vienna, Austria.

Norbert Polacek, Department of Chemistry, Biochemistry and Pharmaceutical Sciences, University of Bern, Bern 3012, Switzerland.

Supplementary data

Supplementary data is available at NAR online.

Conflict of interest

None declared.

Funding

This study was supported by the D-A-CH grant 310030E-162559/1 (to N.P.) and, in part, by 310030-188969 and 10.001.322 (to N.P.), all funded by the Swiss National Science Foundation. Additional funding came from the D-A-CH grant I2514 (to J.G.) by the Austrian Science Fund FWF. Funding to pay the Open Access publication charges for this article was provided by the Swiss National Science Foundation (10.001.322).

Data availability

High-throughput sequencing data generated in this study are deposited in the NCBI Gene Expression Omnibus (GEO) database under the accession number GSE309059 and are publicly available as of the publication date. All relevant code used for the analysis of high-throughput sequencing data is available on GitHub (https://github.com/ps-puneetsharma/pecoraro_et_al) and Zenodo (https://doi.org/10.5281/zenodo.21691269).

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Associated Data

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Supplementary Materials

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Data Availability Statement

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PERMALINK

hY3 RNA binds and inhibits ribosomes and modulates the starvation-induced integrated stress response

Valentina Pecoraro

EunBin Kong

Puneet Sharma

Yulia Gonskikh

Marek Żywicki

Fabian Nagelreiter

Markus Schosserer

Katrin Freiburghaus

Jean-Marc Nuoffer

Johannes Grillari

Norbert Polacek

Roles

Abstract

Graphical Abstract

Graphical Abstract.

Introduction

Materials and methods

Characteristics of human dermal fibroblasts from two donors

Human dermal fibroblasts culture

Stress-induced premature senescence by doxorubicin

Generation of HDF cDNA libraries

Analysis of HDF rancRNA sequencing data

HeLa cell culture and treatments

Northern blot analysis

Oligonucleotide probes used for northern blot analysis

RT-qPCR analysis

Primers used for RT-qPCR analysis

Polysome profiling

In vitro transcription

In vitro binding studies

Crosslinking of 4-thio-U-hY3 to HeLa ribosomes

In vitro translation in HeLa cell extracts

Metabolic labeling

Overexpression of hY3

siRNA transfection

rRNA level analysis

Cell proliferation and viability assays

Seahorse XFe96 metabolic flux analysis

MTT assay

Western blot analysis

RNA isolation and sequencing of translationally active ribosome-associated RNAs

Reference genomes and annotations (RNA-seq in HeLa cells)

Bulk RNA sequencing (RNA-seq in HeLa cells)

Reference genomes and annotations (RNA-seq in HeLa cells)

Quantification and statistical analylsis

Results

hY3 associates with the ribosome

Figure 1.

hY3 inhibits translation in vitro and in cellulo

Figure 2.

hY3 impinges on the cellular metabolism

Figure 3.

Depletion of hY3 results in increased translation activity and susceptibility to cell death during starvation

Figure 4.

Depletion of hY3 disrupts the integrated stress response and alters expression of pro-survival factors during starvation

Figure 5.

Discussion

Figure 6.

Supplementary Material

Acknowledgements

Notes

Contributor Information

Supplementary data

Conflict of interest

Funding

Data availability

References

Associated Data

Supplementary Materials

Data Availability Statement

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