Skeletal muscle wasting is a debilitating and often irreversible process that occurs in myopathy, neuromuscular disorders and chronic diseases, and is also a hallmark of aging¹. When the age-dependent decrease in muscle mass and function reaches a critical threshold, the condition is known as sarcopenia². With an increasing average lifespan in the human population, sarcopenia has become the main cause of frailty and falls in the elderly, posing an important socio-economic challenge^3,4,5. Therefore, uncovering mechanisms to mitigate aging-associated skeletal muscle wasting is important for human healthcare.

Muscle mass is determined by the balance of protein synthesis and degradation. A key regulator of protein synthesis in response to nutrient availability and many other stimuli is the mammalian target of rapamycin (mTOR) serine/threonine kinase^6,7. Signaling via mTOR appears to be impaired in elderly human individuals, leading to an impaired anabolic response and amino acid resistance^8,9. Overcoming anabolic resistance by boosting mTOR activity was expected to attenuate sarcopenia, but the sustained mTORC1 activation via deletion of the repressive tuberous sclerosis 1 (TSC1) gene was shown to result in reduced muscle mass and strength¹⁰.

The inhibition of the mTOR kinase by rapamycin (RM) and calorie restriction (CR) are the most broadly tested interventions that promote both life and health span in model organisms from yeast to mammals^11,12. The long-term RM treatment has been recently found to attenuate sarcopenia^13,14, while CR, defined as 60–70% of ad libitum diet without malnutrition¹⁵, was shown to improve the muscle mass-to-body weight ratio and the locomotor activity of rodents^16,17. Early-onset CR counteracts the loss of muscle fibers in rats¹⁸ and decreases aging-associated abnormalities in the neuromuscular junctions (NMJ) of mice¹⁹. Short-term CR also increased the availability and activity of stem cells in the skeletal muscle of old mice, improving their repair capacity²⁰, though another study found that the proliferation of such cells in vitro was reduced²¹. CR and RM were reported to reduce protein synthesis in various organs^22,23,24, including the muscle^25,26. However, how these treatments remodel mRNA translation to maintain muscle function, especially when applied for long periods of time²⁷, is not well understood.

The method of choice for studying the dynamics of protein synthesis with nucleotide resolution is ribosome footprinting, also known as ribo-seq^28,29. The method has been used to identify novel sites of translation initiation in differentiating muscle cells³⁰ as well as targets of translational control in response to endurance exercise³¹. In the context of aging, ribosome footprinting has revealed the impaired translation of mTOR-responsive transcripts, as well as an apparent change in the density of ribosomes along mRNAs, away from start codons and toward stop codons³². Furthermore, the translation elongation rate has been reported to decrease with age³³. As CR and RM generally affect protein synthesis and improve muscle function during aging, we asked whether their partially overlapping mechanisms also involve translational control. We carried out ribosome footprinting on the Quadriceps femoris muscle of adult, old, CR and RM-treated mice. We identified numerous non-canonical ORFs as targets of translational control, and found that RM primarily remodels the translation of uORFs, while CR the stop codon readthrough and translation of downstream ORFs.

Ribosome footprinting enables the comprehensive quantification of protein synthesis in the muscle

We have implemented the ribo-seq method for Quadriceps femoris (QUAD) samples from mice fed an AIM93M diet, ad libitum, from 15 to 30 months of age, as well as mice receiving the anti-aging treatments RM or 35% CR (Fig. 1a). The functionality of various muscles from these mice was characterized in a previous study¹⁷, the mass of QUAD relative to body mass being improved by both RM and CR. To quantify the translation efficiency (TE = ratio of normalized ribo-seq and mRNA-seq reads on the coding region) on a per transcript basis, we sequenced both mRNAs and ribosome footprints (referred to as ribosome-protected fragments, RPFs) from these samples. We obtained six replicates of ribo-seq and three replicates of mRNA-seq for each condition, namely 10-month-old adult mice (10M_WT), 30-month-old geriatric mice aged under standard conditions (30M_WT), as well as under RM (30M_RM) or CR (30M_CR) treatment. The sequenced RPFs conformed to expectations³⁴, both in terms of length (28–30 nucleotides; Fig. 1b) and 3-nucleotide periodicity of the P-sites inferred from reads (Fig. 1c, Supplementary Fig. 1). On average, the vast majority of reads from a sample mapped to coding regions, 9% mapped to 5′UTRs and 4% to 3′UTRs (Fig. 1d). Altogether, these quality metrics indicate samples consist of reliable ribosome footprints. We further verified sample quality by correlating protein levels, determined by mass spectrometry (intensity-based absolute quantification, iBAQ), with the density of RPFs on the respective mRNAs. RPF density correlated relatively well with protein levels (Pearson and Spearman correlation coefficients ~0.6, Supplementary Fig. 2), more so than did the mRNA levels (Supplementary Fig. 2). That ribo-seq provides protein output data that is well correlated with but more comprehensive than mass spectrometry (~10,000 translated mRNAs vs. ~4000 quantified proteins, depending on the sample) emphasizes the utility of the method in exploring a tissue’s translational landscape.

Anti-aging treatments distinctly remodel the translation efficiency in geriatric muscle

Next, we quantified the translational output of each mRNA in each sample by the sample size-normalized number of RPFs associated with mRNA coding regions (Supplementary Data 1). Principal component analysis (PCA) showed that 10M_WT and 30M_RM muscles form distinct clusters, while muscles from untreated (30M_WT) or CR-treated (30M_CR) aged mice were intermixed. RM-treated samples separated from the others along the first PC, while adult muscle samples separated from aged samples, treated or not, along the second PC (Fig. 2a). For subsequent analyses, we calculated average gene expression measures (at RNA, RPF and TE levels) and compared them between 30M_WT and 10M_WT muscles (i.e., AGE effect), 30M_RM and 30M_WT (i.e., RM effect), and 30M_CR and 30M_WT (i.e., CR effect). 771 genes underwent significant changes³⁵ in translational output during aging, while the RM and CR treatments significantly altered the translational output of 1020 and 405 genes, respectively (Supplementary Data 2). The overlap of genes changing in all conditions was small but significant (28 genes, p-value = 2.54e-34, SuperExact test³⁶) (Fig. 2b). Only ~15% (151 of 1020) of the genes responding to RM also had a significant aging-associated change, while for CR the proportion was higher, ~25% (102 of 405, Fig. 2b). To determine how the treatment-induced changes relate to the aging-associated changes, we calculated correlation between log₂ fold-changes in gene expression across pairs of conditions: CR vs AGE and RM vs AGE. Furthermore, we checked both the mRNA level and TE, and in both cases, we observed that aging-associated changes were negatively correlated with those occurring upon anti-aging treatments (Fig. 2c, d, Supplementary Fig. 3). This indicates that the treatments partially restore both the steady-state level and the TE of mRNAs. RM had a more pronounced effect than calorie restriction, in line with our previous observations of mRNA-level changes in multiple muscles¹⁷. To identify biological processes that are most impacted in these conditions, we carried out Gene Set Enrichment Analysis (GSEA), taking the KEGG pathways as gene sets. At the mRNA level, genes involved in metabolism and basic cellular processes were upregulated, while genes involved in development, intercellular communication and neuronal signal transmission were downregulated during aging (Fig. 2e). Metabolism-related changes were counteracted by RM but further exacerbated by the CR treatment, while both RM and CR mitigated the aging-associated changes in developmental and cell communication-related genes. For many KEGG categories, the changes in ribosome footprints mirrored the changes in mRNA, indicating that the regulation was largely at the level of transcription (Fig. 2e, marked as “transcriptional”). However, within signaling pathways, the TE appears to counter-balance transcriptional changes leading to minimally altered ribosome footprints (Fig. 2e, marked as “translational”). For a small cluster of KEGG categories the changes at mRNA and translation level were complex. For example, ribosome constituents and genes involved in oxidative phosphorylation exhibited a significant aging-associated reduction in TE, partially restored by RM and CR. Moreover, nucleus and mitochondria-encoded genes from the oxidative phosphorylation pathway exhibited divergent patterns of TE change upon treatment (Fig. 2f); CR almost restored the aging-induced reduction in the TE of mitochondria-encoded genes (median log₂ fold-change of 0.4 in CR relative to −0.62 in aging), while RM exacerbated this reduction (median log₂ fold-change: −0.79). In contrast, nuclear genes did not show a significant change in TE during aging (median log₂ fold-change = −0.11), but were upregulated by CR and especially by RM (median log₂ fold-change: 0.21 and 0.4, respectively). Thus, both aging and anti-aging interventions modulate the synthesis of specific categories of proteins in the Quadriceps muscle of mice, primarily at the mRNA level, and for some pathways at the level of mRNA translation. As previously observed in other muscles¹³, the extent of regulation of different genes in a given pathway varies substantially between treatments (Supplementary Data 2, Supplementary Fig. 4).

Rapamycin remodels aging-associated changes in translation initiation

A key site of translational control, especially under stress, is the upstream open reading frames (uORFs)^37,38. To determine whether uORFs play a role in TE changes in aging muscle, we examined the RPFs mapping to the 5′UTRs of annotated protein-coding genes. We found that many genes (803-2264, depending on the condition and sequencing depth, Fig. 3a, Supplementary Data 3) yielded 5′UTR-derived RPFs in all samples from a given condition, with 459 genes being covered in all 4 conditions. To control for differences in the overall gene expression levels between samples when evaluating the significance of 5′UTR-derived reads, we computed the ratio of 5′UTR- to CDS-derived RPFs for each gene in each sample. PCA of these ratios revealed that 30M_RM samples tend to separate from the others along the first principal component (Fig. 3b). The mean 5′UTR-to-CDS ratio per gene was 0.15 lower in 30M_WT than 10M_WT samples, indicating reduced ribosome density on 5′UTRs in aged muscles or, alternatively, increased density on the coding regions. CR (+0.29) and especially RM (+0.33) increased this mean ratio (Fig. 3c). The per-gene-level illustration of 5′UTR-to-CDS ratio changes revealed several distinct clusters (Fig. 3d). Cluster 1 contains genes from the proteolysis/ubiquitination, development/morphogenesis and axonal-related GO term/pathways, for which the 5′UTR-to-CDS ratio is significantly decreased upon muscle aging and restored by both RM and CR treatments (Supplementary Fig. 5). Cluster 2 contains genes related to oxidative phosphorylation, the electron transport chain, mitochondrion organization and muscle movement/cell development (Supplementary Fig. 5), whose reduction in 5′UTR-to-CDS read ratio upon aging is primarily counteracted by CR. The analogous cluster 3 contains genes whose age-related decrease in the 5′UTR-to-CDS ratio is primarily counteracted by RM. These genes are important for muscle structure and contractility (Fig. 3e). Figure 3f shows a few examples of altered 5′UTR-to-CDS ratios in different conditions³⁹. Specifically, the carnitine O’-acetyltransferase (Crat) shows a reduced 5′UTR coverage relative to the CDS in the aged muscle, and both CR and RM treatments restore the coverage pattern of the younger muscle. In contrast, for the ribosomal protein S25 and the translation initiation factor Eif1Ax, RM induces a more pronounced reduction of the RPF density on the CDS. This likely reflects the well-known translation initiation block induced by RM⁴⁰, underscoring the accuracy of ribo-seq in revealing how the translational landscape of cells is remodeled in various conditions. Two additional small clusters contain genes with increased 5′UTR-to-CDS ratios during aging that are mitigated by RM or CR. Specifically, RM reduces the ratio for some components of the mitochondria (e.g., the ribosomal protein Mrps21, the enzymes Aldoa, Ckmt2 and Ndufb11), while CR reduces the ratio for genes related to thermogenesis and oxoacid metabolic processes (e.g., Atf4, Scd1, Jph2 and Hnrnpa2b1). The RM-induced translational block was also apparent from the negative correlation (Pearson’s correlation coefficient of r = −0.63, p-value = 1.94e-12) between changes in the 5′UTR-to-CDS read ratio and in the change in CDS-derived RPFs (Fig. 3g, for WT and CR in Supplementary Fig. 6), further accompanied by the downregulation of many translation initiation factors (Fig. 3h). Thus, the long-term RM treatment appears to reduce translation, increase the relative accumulation of RPFs on 5′UTRs, and partially revert aging-induced changes in ribosome interactions with 5′UTRs.

Calorie restriction remodels stop codon readthrough and translation downstream of CDS

We carried out a similar analysis of RPFs derived from the 3′UTRs. Fewer genes (140–275) yielded 3′UTR- compared to 5′UTR-derived RPFs in all samples of a given condition (Fig. 4a), with 72 genes being covered in all conditions. PCA of the 3′UTR-to-CDS ratio revealed the separation of 10M_WT and 30M_CR samples from all other groups along the first principal component (Fig. 4b). On individual genes, the ratio generally decreased with age in WT mice and was restored by treatments, especially CR (Fig. 4c, d). For example, the calcium-binding parvalbumin and the Hspb7 member of the heat shock family both yielded 3′UTR-derived RPFs in the 10M_WT and the 30M_CR samples, while in the 30M_WT and 30M_RM samples such RPFs were almost undetectable (Fig. 4e). Overall, genes that showed this pattern of variation in 3′UTR coverage are involved in energy metabolism and muscle contraction (Fig. 4f). The apparent loss of 3′UTR-derived RPFs in the 30M_WT and 30M_RM groups is also reflected in the meta-gene plot of normalized read coverage in the vicinity of both start and stop codons. This shows a relative enrichment of reads at the stop codon in the 30M_WT compared to 10M_WT samples and a more pronounced decrease in the 3′UTR-derived reads, partially resorted by CR (Fig. 4g). Importantly, this observation cannot be attributed to reduced sequencing depth in these samples, as read numbers were comparable across libraries (Supplementary Data 3). In contrast to 5′UTR-derived reads, we did not observe significant correlations between the 3′UTR-to-CDS ratio and protein output of the coding region (Supplementary Fig. 7). Altogether, these data indicate that non-canonical reading frames located downstream of the canonical coding region are translated in the muscle, reads derived from these regions decreasing in abundance during aging and being partially restored by CR.

Mass spectrometry confirms the expression of non-canonical peptides

To assess whether the RPF redistribution patterns induced by CR and RM are reflected in the proteome, we carried out mass spectrometry analysis of the Quadriceps muscle from all cohorts of mice included in our analysis. We prepared samples from total lysates, from polysome as well as size-separated small peptide fractions (Fig. 5a). We further re-analyzed mass spectrometry (MS) datasets available in the PRIDE database⁴¹ (see “Methods”). As the protein identification by MS relies on protein databases, we augmented the reference Uniprot database⁴² with peptides predicted from 5′ and 3′UTR regions where RPFs were detected, corresponding to upstream/downstream open reading frames (uORFs/dORFs), and stop codon readthrough. We selected the candidates stringently, requiring evidence of frame bias of the RPFs for peptide prediction (see “Methods”). By searching the spectra obtained in multiple MS experiments against this augmented database, we reproducibly identified peptides derived from 98 uORFs, 55 dORFs and 23 stop codon readthrough regions. These were detected in more than one dataset at a false discovery rate cutoff of 0.01 using the Fragpipe analysis software⁴³. Figure 5b–d shows the proteins and specific peptides with the highest total spectral count across all datasets (>10 spectra for u/dORFs and 5 spectra for readthrough peptides). From the distributions of RPF densities (Fig. 5e–g), we can infer that u/dORFs are expressed at similar levels as the main ORF, while the stop codon readthrough regions display a ~ten-fold lower expression than the main ORFs. Importantly, products of stop codon readthrough translation that we predicted from 3′UTR-derived RPFs are not encoded by any annotated protein-coding isoform of the corresponding genes, arguing against these RPFs originating in canonical coding regions of splice variants. The density of RPFs on the main coding regions of mRNAs yielding readthrough peptides was similar to that on mRNAs not yielding such products (Supplementary Fig. 8). Altogether, these analyses confirm the presence of readthrough peptides inferred from ribo-seq data, further identifying the reading frame of stop codon readthrough translation.

We also intersected the set of non-canonical peptides we inferred from our data with a recently published metamORF database of curated small open reading frames⁴⁴. Strikingly, despite the similarly high RPF density in u/dORFs relative to the main CDS, 39% of the uORFs identified in our study are also present in metamORF, but only 1% of the dORFs. The reason for this discrepancy is currently unclear. Our data thus provide multiple lines of evidence for non-canonical translation products, the majority of which have not been reported before. In addition, our data shows how these translation products are altered by aging and anti-aging interventions.

CR restores translation of lncRNA-derived peptides

While long non-coding RNAs (lncRNAs) do not generally undergo translation^45,46,47, a few have been found to encode small peptides (less than 100 amino acids) in various tissues, including muscle (reviewed in ref. ⁴⁷). To validate our data and provide further evidence for the translation of small peptides with functional relevance for the muscle, we asked whether any of the known myokines is represented in our data. Indeed, as shown in Fig. 6a, we found evidence of translation for a number of myokines. Their translation output, given in terms of RPF density along the ORF, varies quite widely within individual cohorts of mice. Despite the variability, Fndc5 and Sparc have significantly reduced expression in aged muscle (Fig. 6a), the first restored by the anti-aging treatments, especially CR, the second one insensitive to the treatments. We also checked for lncRNA-derived peptides previously found relevant for muscle function, such as SPAR, which regulates the amino acid release from lysosomes and hinders the mTORC1-dependent muscle regeneration⁴⁸, myoregulin⁴⁹ and DWORF⁵⁰, which regulate calcium release from the sarcoplasmic reticulum. While our ribo-seq data confirms the synthesis of these peptides (Fig. 6b), they do not appear to be sensitive to aging or anti-aging treatments. We note that since their initial discovery, the annotation of the corresponding RNAs has been updated, and they are found among the protein-coding genes in databases such as Uniprot and Ensembl.

To determine whether our data provides evidence of translation for additional lncRNAs, we mapped the ribo-seq reads that did not match annotated mRNAs to lncRNAs from the noncode database (version 6)⁵¹. Surprisingly, we found that we can thus account for 10% of these reads, and, with the same selection criteria as before, i.e., the presence of start/stop codons and evidence of frame bias, we identified 252 potential peptide-encoding lncRNAs. MS datasets provide evidence for 32 of these peptides, derived from 28 lncRNAs, 5 of them being supported by data from at least 2 datasets (Supplementary Data 4). One such peptide derives from PARTICLE (promoter of MAT2A-Antisense RadiaTion Induced Circulating LncRNA), a lncRNA involved in histone and DNA methylation⁵². The 8 amino acid-long peptide derived from this lncRNA was not reported before, though it is represented in 2 independent datasets that we have analyzed (Supplementary Data 4). Another 8 amino acid-long peptide derives from the Gm45923 (MUNC) lncRNA, previously described as an enhancer RNA for the Myod1 gene (^DDReRNA). The lncRNA was implicated in muscle cell differentiation and skeletal myogenesis^53,54, but the peptide was not reported before. We further used the ribo-seq data to estimate the change in expression of lncRNA-associated ORFs between conditions (Fig. 6b, c). Interestingly, among lncRNA-encoded ORFs with a significant expression difference in at least one condition, there is a strikingly consistent pattern, whereby most of these ORFs have reduced expression upon aging, a change which is counteracted by the treatments, primarily CR (Fig. 6c). This analysis re-emphasizes the increased sensitivity of ribo-seq compared to mass spectrometry and suggests that our set of 252 lncRNAs contains additional bioactive molecules.

Regenerative processes are activated in aging muscle and by anti-aging treatments

It has been previously described that regenerative processes are activated, but ultimately inadequate, in old skeletal muscle due to age-related deterioration in skeletal muscle stem cells and their niche⁵⁵. Intriguingly, one of the translational readthrough targets, Pvalb, was found to play a key role in the response of the muscle to denervation, by regulating the uptake of Ca²⁺ in mitochondria and the expression of the pro-hypertrophy gene PGC-1α4⁵⁶. We therefore asked whether our interventions also altered age-related markers of muscle regeneration. Nascent muscle fibers transiently express an embryonic form of myosin heavy chain (eMHC) before transitioning to express their mature myosin heavy chain isoform (e.g., Myh4 in fast IIB fibers). This allows newly regenerated fibers to be identified via immunostaining.

In cross sections of QUAD muscles from 30M_WT mice, the proportion of fibers expressing eMHC was significantly higher than in 10M_WT mice, where eMHC+ fibers were virtually absent (Fig. 7a, b). While the proportion of eMHC+ fibers tended to be reduced by the CR treatment, the RM treatment approximately doubled the eMHC+ fiber prevalence compared to 30M_WT mice. In all cases, eMHC+ fibers were markedly smaller than surrounding fibers expressing mature myosin heavy chain isoforms (Fig. 7a) and comprised just a tiny fraction of total fiber number. While eMHC+ fibers represent acute signs of regeneration, an indication of the cumulative occurrence of muscle fiber regeneration events can be gleaned by the appearance of centrally nucleated muscle fibers. Centralized myonuclei are a well-established hallmark of muscle fiber regeneration in adult muscle and were recently shown to occur as a result of myocyte fusion within the shrunken residual basement membranes of damaged myofibers during the repair process⁵⁷. Importantly, central nucleation in regenerated muscle fibers appears to be permanent, remaining more than 6 months after injury in mice^57,58. The proportion of centrally nucleated fibers quantified in vastus medialis was markedly higher in 30M_WT (12.0%) than 10M_WT (3.4%) mice but not significantly affected by CR or RM treatments (Fig. 7c, d). Together, these results indicate that at very high age, the acute regeneration of fast fibers is suppressed by CR and accentuated by the RM treatment. Differences in regenerating fiber prevalence could stem from differences in the extent of tissue damage or the magnitude and duration of regenerative responses⁵⁹. While we have previously demonstrated that CR and RM attenuate skeletal muscle aging^13,17, mTORC1 activity is also important for efficient muscle regeneration⁴⁸, and CR has been shown to have both beneficial²⁰ and inhibitory effects²¹ on regenerative responses to muscle injury. As such, further work is needed to elucidate the interplay between the age-related activation of muscle regenerative processes and the multi-modal influences of CR and RM, particularly at the level of protein synthesis in various cell types.

Perturbed proteostasis is a well-known hallmark of aging⁶⁰. Consistently, we recently found that the increased activity of mTORC1, a master regulator of ribosome biogenesis and protein synthesis, can itself be considered a hallmark of aging in skeletal muscle¹³. Anti-aging treatments such as rapamycin and calorie restriction partly restore muscle functionality and global protein synthesis rates^25,26, but their impact on the translational landscape of the muscle was unknown. Our study fills this gap, identifying and quantifying the output of canonical and especially non-canonical translation units in the skeletal muscle of mice aged under standard laboratory conditions, or under long-term treatment with CR or RM. At the functional level, these treatments have been found to have muscle-specific and partially additive effects, with the Triceps brachii responding more to RM and Soleus to CR^13,17. The Quadriceps femoris muscle is strongly affected by age, and both interventions alleviate age-dependent reductions in relative mass¹⁷, prompting the question of whether they do so by targeting similar translational targets. The large size of QUAD allows the collection of the necessary datasets to investigate translational control. We also note that while our study focused on the QUAD, the data expands the growing atlas of mRNA-level gene expression in muscles of untreated or CR/RM-treated aged mice. As was the case with other muscles¹⁷, RM and CR have both shared and specific mRNA targets in the QUAD (Fig. 2e).

The protein output measured by RPF density along ORFs varied substantially across conditions, and most of this variation came from changes in mRNA-level expression rather than TE (Fig. 2e). Significant TE changes were localized to specific pathways such as oxidative phosphorylation, where we further observed divergent responses of nucleus and mitochondria-encoded genes: TE of mitochondrial-encoded genes decreased at high age and was reverted by CR only, while RM upregulated the TE of nuclear genes from this pathway (Fig. 2f). The downregulation of mitochondrial genes could be due to age-related mitochondrial dysfunction⁶¹, which has also been observed in the human muscle, where the translation of mitochondrial proteins is reduced⁶². Conversely, CR was reported to improve mitochondrial efficiency in humans⁶³.

Our data revealed unexpected patterns of translation outside canonical protein-coding regions, in 5′ and 3′ UTRs, which could not be attributed to sequencing depth artifacts (Supplementary Fig. 9). To control for changes in mRNA abundance when assessing 5′/3′UTR-derived RPF variation between conditions, we analyzed the 5′UTR-to-CDS read ratio. This ratio decreased with age, a change that was mitigated by the treatments, especially RM (Fig. 3c). The increased 5′UTR-to-CDS ratio in the RM condition was at least partly due to a translation initiation block, indicated by the reduced expression of multiple subunits of translation initiation factors 1 and 2 (Fig. 3h). We also observed an upregulation of the Eif3f subunit, which was reported as inhibitory for translation in proliferating cells⁶⁴, though another study reported an activation effect in the muscle⁶⁵. The translation block was reflected in RPF accumulation on the 5′UTR relative to the main ORF (Fig. 3f) as well as the reduced translation output of the latter, which could be a consequence of the translation inhibitory effect of uORFs (Fig. 3g). Indeed, we identified 7704 uORFs with ribosome footprints in our ribo-seq data, 98 of which are supported by mass spectrometry evidence from multiple datasets. The protein output predicted from the RPFs along these uORFs was comparable to that of the main ORFs and, in RM/CR conditions, even higher. Furthermore, of the 7704 ribo-seq-supported uORFs, a high proportion, 39%, are also present in the metamORF⁴⁴ database of small ORFs. The uORF with the most extensive mass spectrometric evidence comes from the gene Downregulator of Transcription 1 (Dr1), which is translationally regulated by Proline-rich coiled-coiled 2 proteins that promote leaky scanning⁶⁶. The significance of this regulation or of the small peptide generated from this uORF in the context of aging remains to be evaluated.

Perhaps the most unexpected observation was the pattern of variation of RPFs captured downstream of stop codons. Recent studies have started to report peptides generated by either stop codon readthrough⁶⁷ or (re)initiation on dORFs⁶⁸. Here we provide ribo-seq and mass spectrometric evidence for the existence of such peptides and further establish that translation downstream of stop codons is reduced in aging skeletal muscle and restored by CR, indicating they may play functional roles. 55 dORFs and 23 readthrough peptides are supported by multiple mass spectrometry datasets. The capture of readthrough peptides is especially remarkable since their expression levels inferred from RPFs are at least 10-fold lower than expression levels of the corresponding main ORFs (Fig. 5f). This is not the case for dORFs, which are expressed at comparable levels to the main ORF. Although dORFs have been reported to enhance translation⁶⁹—in contrast to uORFs which are generally inhibitory⁷⁰—we did not observe a positive correlation between dORF and main ORF expression here (Supplementary Fig. 7). The dORFs with mass spectrometric evidence come from genes involved in metabolism, development and signaling. However, they did not exhibit significant levels of evolutionary conservation measured by the PhyloP score⁷¹ (not shown).

An age-dependent redistribution of RPFs away from start codons and toward stop codons was reported previously³². While our meta-gene analysis supports the accumulation of ribosomes upstream of the stop codon in 30 M compared to 10 M samples (Fig. 4g), we found the most significant change in coverage to occur not in the CDS, but rather downstream, in the 3′UTR, where the density of reads decreases upon aging, a change mitigated by CR. What could be the significance of these reads? Translation readthrough has been described for some genes, requiring an extended sequence context and generating protein isoforms with specific patterns of localization within cells^72,73,74. A number of metabolic enzymes such as lactate and pyruvate dehydrogenase, as well as triosephosphate isomerase, acquire peroxisomal-targeting sequences via readthrough^72,74,75, while expression of mitochondrial carrier homolog 2 (MTCH2) protein is autoregulated via stop codon readthrough with important consequences for mitochondrial membrane potential⁷⁶. The water channel aquaporin 4 (Aqp4) also has a translational readthrough isoform, specifically localized at astrocyte endfeet⁷⁷, where it regulates the waste clearance at the brain-blood barrier⁷⁸. While we did not observe an enrichment of the readthrough-permissive UGA stop codon⁷⁹ in genes with evidence of readthrough relative to those without (Supplementary Fig. 10), the readthrough isoforms reflect the functional themes that have been observed before. For example, the candidates with the strongest proteomics evidence include the triosephosphate isomerase⁷⁴, peroxisome and mitochondria-related proteins (Pex10, Etfa), and other proteins that localize to membrane-delimited compartments. Interestingly, while the MS-validated dataset did not include Aqp4, it included a homolog, Aqp5. Aside from the prior data studies supporting the functional relevance of stop codon readthrough isoforms, our study provides multiple lines of evidence for their existence. Generally, it is unlikely that 3′UTR-derived RPFs result from faulty translation, as their frequency would be expected to increase rather than decrease with age, as we observe here. Furthermore, they do not seem to be artifacts of systematic library size differences, whereby 3′UTR-derived reads would be detected in libraries sequenced more deeply. Instead, our results are more in line with reports of senescence, which affects an increasing number of cells as organisms age⁸⁰, inhibiting both basal translation readthrough and aminoglycoside-induced readthrough⁸¹. Another potential origin of apparent readthrough peptides could be alternative splice forms, in which the respective genomic regions are part of coding exons. This was also not the case in our data, because an exhaustive search of respective peptides in all annotated transcripts did not yield any match. Thus, our data indicate that 3′UTRs encode as yet unannotated peptides sufficiently stable to be detected, both by ribosome footprinting and mass spectrometry. Moreover, evidence for these peptides can also be found in other datasets within the PRIDE database⁴¹. Interestingly C-terminal extensions resulting from stop codon readthrough tend to destabilize proteins or localize them to membranes⁸². In our study, structural muscle proteins showed evidence of translation readthrough in animals of younger age. This suggests that these isoforms may interact with membranes to modulate muscle functionality, an interaction that is perturbed in sarcopenic muscles and partially restored by CR. Interestingly, while regenerative processes are activated in all of the aged muscles, newly regenerated eMHC+ fibers are less frequent in the 30M_CR compared to 30M_WT and 30M_RM muscles, while the muscle undergoes a fast-to-slow fiber-type switch¹⁷. Our study provides new leads toward deciphering the dynamics of structural muscle proteins in relation to age-dependent regenerative processes.

A number of studies have uncovered short peptides (less than 100 amino acids, sometimes referred to as micropeptides) derived from transcripts initially thought to be non-coding, and many of these are muscle-specific^47,83. For example, phospholamban and sarcolipin regulate the contraction of cardiac and skeletal muscle by interacting with the sarcoplasmic reticulum Ca²⁺ ATPase^84,85. Other microproteins regulate the mitochondrial function, e.g., mitoregulin, also involved in β-oxidation^86,87, and the unfolded protein response, e.g., the PIGBOS peptide⁸⁸. Our ribo-seq data provided evidence for many of the known micropeptides, but only some, specifically myokines, were detected by mass spectrometry. This could have a variety of reasons, from the lower sensitivity of the MS technology, to challenges in detecting membrane-associated proteins. The non-canonical translation products that we identified in ribo-seq data may pose similar challenges for mass spectrometry-based detection, which could explain why we only found peptide evidence for 28 of the 252 translated lncRNA. Nevertheless, this large set of candidates that we stringently selected could represent entry points for studying so-far-unsuspected regulatory mechanisms in the complex muscle tissue.

To conclude, our study reveals the translation dynamics during aging and anti-aging interventions in skeletal muscle, demonstrating intervention-dependent redistribution of ribosome footprints on 5′ and 3′ untranslated regions. We expand the gene expression atlas of aging mouse muscles with data for Quadriceps femoris, a muscle whose relative mass is improved by both RM and CR. While RM primarily blocks translation initiation, thereby reducing protein synthesis, CR improves the functionality of mitochondria. A large proportion of the uORFs we identified here are also represented in another database of small ORFs, indicating that they undergo robust translation. Of these, 98 uORFs are supported by mass spectrometric evidence from multiple datasets, further indicating that they generate small peptides with functions that remain to be characterized. In metabolic enzymes and muscle structural proteins, we identified translational readthrough events that are detectable in younger muscles and are promoted by CR, suggesting they could be part of the mechanism by which CR imparts its beneficial effects on muscle function. Our data thus provides a large resource for non-canonical translation units whose changes during aging are restored by anti-aging interventions. Characterizing their functions will advance our understanding of translational control to improve healthy aging.

Animal care

All procedures were performed in accordance with Swiss regulations for animal experimentation and approved by the veterinary commission of the Canton Basel-Stadt. Male, C57BL/6JRj mice from a previous aging study^13,17 were purchased from the aging colony at Janvier Labs (Le Genest-Saint-Isle, France). For all studies, mice were kept in single cages under a fixed 12 h light-dark cycle (6 a.m. to 6 p.m.) at 22 °C (range 20–24 °C) and 55% (range 45–65%) relative humidity and were acclimatized to individual housing (due to the calorie restriction group) and the control diet for 3–4 weeks before the start of the experiment. In the week immediately prior to starting the experiment, body mass, food intake, grip strength, and body composition (via EchoMRI) were measured and used for balanced group selection. Ten-month-old mice were used as an adult control (10M_WT), while 15-month-old mice received either a control AIN-93M diet (TestDiet) containing Eudragit (vehicle) ad libitum (30M_WT), a calorie-restricted diet (30M_CR; 65% of standard diet without restricting vitamins and minerals) or a diet containing 42 mg/kg chow active encapsulated (Eudragit) RM (30M_RM) from the age of 15–30 months. Based on measured food intake, mice received an RM dose of 4.2 mg/kg body mass/day. Prior to tissue collection, food was removed from the cages in the early morning. Mice were deeply anesthetized with a sub-lethal dose of pentobarbital (80–150 mg/kg) and subsequently sacrificed by cervical dislocation. Death was assured by removing the heart. Quadriceps muscles were rapidly dissected and snap-frozen.

Ribosome profiling (ribo-seq)

The method for ribosome-protected fragment sequencing was adapted from ref. ⁸⁹ and ref. ⁹⁰. The detailed protocol was as follows.

Lysate preparation

Snap-frozen quadriceps muscles from various mice cohorts were lysed in cryogenic conditions in 2.5 ml lysis buffer (20 mM Tris-HCl, pH 7.5 (Sigma, T294), 100 mM NaCl (Sigma, 71386), 10 mM MgCl₂ (Sigma, 63069), 2 mM DTT (Sigma, 646563), 1% Triton X-100 (Sigma, T8787), and 100 μg/ml cycloheximide (Sigma, G7698), 500 U/ml RNase inhibitor RNasin Plus (Promega, N2615), Protease inhibitor, DNase) using a freezer mill (Spex) with machine setting “Pre-cool: 2 min, Run time: 2 min, Cool time: 2 min, Cycles: 3, Rate: 15 CPS”. Lysate in powdered form was collected and thawed at 4 °C for 1 h with continuous rotation, then triturated through 18G and 26G-needle several times and centrifuged at 20,000 × g for 10 min at 4 °C. The supernatant was collected and the optical density (OD) of the lysate at A260 was measured with a NanoDrop2000. For ribo-seq, 800 µl lysate was subjected to RNase I digestion (2.5U per OD; Invitrogen, AM2294) at 22 °C for 20 min with continuous rotation at 800 rpm in thermoblock (Eppendorf). The RNase I was inactivated by adding 10 µl of RNase inhibitor SuperaseIN (Invitrogen, AM2696).

Sample loading on sucrose gradient

A linear 10–50% sucrose gradient was prepared using a Gradient Master instrument (Biocomp) according to the manufacturer’s instructions. In brief, 10 and 50% sucrose (Sigma, 84100) solutions were prepared in gradient buffer (50 mM Tris-HCl, 50 mM NH₄Cl (Sigma, 09718), 12 mM MgCl₂ 0.5 mM DTT, 100 µg/ml CHX and 10 µl SuperaseIN). A 14 × 89 mm tube (Beckman Coulter, 331372) (used in rotor SW-41/TH-641) (Beckmann Coulter) with a long cap that can hold 800 µl of sample was used to prepare the gradient. First, the 10% solution was laid in the tube, then the 50% solution was under-laid with the help of a long syringe. The gradient was prepared by using a pre-program for 10% to 50% sucrose gradient in Gradient master 108 instrument. The gradient was cooled down at 4 °C for a minimum of 1 h. Undigested (for polysome profile) and digested samples (for ribo-seq) were loaded onto pre-cooled 10–50% sucrose gradient and centrifuged in ultracentrifuge at 35,000 rpm for 3 h at 4 °C in a TMT41.14 swing-out rotor (KONTRON instruments, Augsburg, Germany). Finally, all gradients were monitored and gradient was collected in 400 µl fractions in Eppendorf tubes containing 40 µl of 1% SDS with the help of a gradient fractionator (BR-188, Brandel, Gaithersburg, MD, US) with the setting of pump speed of 0.75 ml per min and a collection time of 32 s per tube. The UV absorbance was recorded concomitantly at a sensitivity setting of 1.0 at 254 nm, and the absorbance spectrum was plotted with the PeakChart software (Brandel).

Isolation of ribosome-protected RNA and sequencing library preparation

The fractions containing 80S monosomes were processed for sequencing library preparation. In brief, RNA was isolated from the monosome fraction with the hot phenol method. RNA fragments of 28–32 nucleotides were obtained by running samples on 15% polyacrylamide denaturing TBE-Urea gel and visualized by SYBR Gold dye (Life Technologies). The size-selected RNA was dephosphorylated by T4 polynucleotide kinase (PNK, New England Biolabs, B0201S) treatment for 1 h at 37 °C. PNK was heat-inactivated, and RNA was purified using the phenol chloroform method and overnight precipitation of RNA in ethanol. An RNA amount equivalent to 12 ng was used to prepare the sequencing library using SMARTer® smRNA-Seq Kit for Illumina® (Takara 635031) according to the kit manual till cDNA synthesis. After cDNA synthesis, rRNA was depleted by using the protocol and probes defined in ref. ²⁹, and a final PCR was done according to Smarter kit with multiplexing barcodes. The PCR product was purified on 8% native polyacrylamide TBE gel and sequenced on a NextSeq 500 instrument at the genomic facility Basel.

Analysis of ribosome profiling (ribo-seq) data

Reads from fastq files were trimmed with fastx_clipper from FASTX-Toolkit version 0.0.14 with parameters ‘-a (3′adapter) AAAAAAAAAA, -l (minimum-length) 20, -c (discards non-clipped sequences) and -n (discards sequences with unknown (N) nucleotides)’. The trimmed reads were further trimmed with fastq_quality_trimmer from the same toolkit with -t (minimum quality) 20, -Q (quality type) 33. Then the trimmed reads were filtered with fastq_quality_filter from the same toolkit for read quality with the following parameters: ‘-q (minimum quality) 20, -p (minimum percent of bases that must have [-q] quality) 90’, -l (minimum-length) 20. These reads were first aligned to ribosomal RNA (rRNA) sequences obtained from Mus musculus ribosomal DNA (rDNA), complete repeat unit (https://www.ncbi.nlm.nih.gov/nuccore/bk000964) using Segemehl⁹¹ version 0.2.0. The reads that did not map to rDNA were then aligned to the longest coding transcripts for each gene identified from Mus musculus GRCm38–mm10 genome assembly, Ensembl 99 annotation using Segemehl. The uniquely mapped reads from this alignment were used for downstream analysis.

Analysis of RNA sequencing (RNA-seq) data

Single-end reads from raw fastq files were processed using ZARP⁹² workflow with the default parameters, Mus musculus GRCm38–mm10 genome assembly, Ensembl 99 annotation, 3′ adapter ‘GATCGGAAGAGCACAC’, ‘SR’ for library type (strand-specific reads coming from the reverse strand). The kallisto⁹³ (version 0.46.2) output of ZARP workflow was used for downstream analysis.

Analysis of differential expression, translation and translation efficiency

Differential expression (RNA-seq) and differential translation (ribo-seq) analyses were performed using the Deseq2 R package³⁵ version 1.34.0 with default parameters. The deltaTE⁹⁴ procedure was applied for differential translation efficiency analysis using the reads mapped to coding sequence (CDS) regions obtained from GRCm38–mm10 genome assembly, Ensembl 99 annotation both for RNA-seq and ribo-seq libraries. Rsubread⁹⁵ R package version 2.8.2 was employed to obtain the RNA-seq reads aligned to CDS regions. An in-house algorithm was used to obtain the ribo-seq reads mapped to CDS regions based on their estimated P-sites.

Gene Ontology (GO) analysis

The ClusterProfiler⁹⁶ R package version 3.18.1 was used for all the GO term analyses reported in this study. ComplexHeatmap^96,97 version 2.6.2 and circlize⁹⁸ version 0.4.15 R packages were used to construct the heatmaps. InteractiVenn⁹⁹ was used for Venn diagrams.

Identification of small open reading frames (sORFs) and readthrough peptides (RTs)

To identify non-canonical translation products (sORFs and RTs), we employed an in-house developed tool that first identifies all alternative start and stop codons on all possible frames of untranslated regions (UTRs) of all transcripts. It then checks the RPF coverage (P-site) within those regions and uses the non-parametric Wilcoxon rank-sum test to assess the differences in apparent use of possible frames and generates peptide sequences based on the dominant frame (p-value < 0.05, for comparisons between dominant and alternative frames). If the number of actively used P-site positions along a candidate sORF is smaller than 5, the tool accepts this candidate sORF as a possible non-canonical translation product if the number of RPFs assigned to the dominant frame is at least 2 times higher than the other 2 alternative frames. Finally, the tool appends all the putative non-canonical peptides to the standard protein database for the organism of interest for further use in the analysis of LC-MS-based proteomics data.

LC-MS-based proteomics analysis

Samples were lysed in 100 μl of lysis buffer (8 M Urea/0.1 M ABC, 5 mM TCEP buffer) using strong sonication (Pixul, 20 min, active motif). Samples were incubated for 60 min at 37 °C, followed by the addition of iodoacetamide at a final concentration of 10 mM and incubation at RT in the dark for 30 min. Subsequently, protein concentration of each sample was determined by tryptophan fluorescence. For peptidomics analysis, sample aliquots containing 100 μg of total protein were TCA precipitated according to a protocol originally from Luis Sanchez (https://www.its.caltech.edu/~bjorker/TCA_ppt_protocol.pdf) as follows. One volume of TCA was added to every 4 volumes of sample, mixed by vortexing, incubated for 10 min at 4 °C, followed by collection of precipitate by centrifugation for 5 min at 23,000 × g. The supernatants containing the peptides were collected and stored for peptide clean-up. The protein pellets were discarded. For proteomics analysis, sample aliquots containing 50 μg of proteins were diluted 1:4 (v:v) with 0.1 M ammonium bicarbonate buffer to a final urea concentration of 1.6 M. Then, sequencing-grade modified trypsin (1/50, w/w; Promega, Madison, Wisconsin) was added, and proteins were digested for 12 h at 37 °C shaking at 300 rpm. Digests and TCA supernatant peptide samples were acidified (pH < 3) using TFA and desalted using iST cartridges (PreOmics, Martinsried, Germany) according to the manufacturer’s instructions. Peptides were dried under vacuum and stored at −20 °C.

For polysome samples, aliquots of 0.4 μg of total peptides were subjected to LC-MS analysis using a dual-pressure LTQ-Orbitrap Elite mass spectrometer connected to an electrospray ion source (both Thermo Fisher Scientific) and a custom-made column heater set to 60 °C. Peptide separation was carried out using an EASY nLC-1000 system (Thermo Fisher Scientific) equipped with an RP-HPLC column (75 μm × 30 cm) packed in-house with C18 resin (ReproSil-Pur C18–AQ, 1.9 μm resin; Dr. Maisch GmbH, Germany) using a linear gradient from 95% solvent A (0.1% formic acid in water) and 5% solvent B (80% acetonitrile, 0.1% formic acid, in water) to 35% solvent B over 50 min to 50% solvent B over 10 min to 95% solvent B over 2 min and 95% solvent B over 18 min at a flow rate of 0.2 μl/min. The data acquisition mode was set to obtain one high-resolution MS scan in the FT part of the mass spectrometer at a resolution of 120,000 full width at half maximum (at 400 m/z, MS1) followed by MS/MS (MS2) scans in the linear ion trap of the 20 most intense MS signals. The charged state screening modus was enabled to exclude unassigned and singly charged ions, and the dynamic exclusion duration was set to 30 s. The collision energy was set to 35%, and one microscan was acquired for each spectrum.

For peptide samples, 1 μg of peptides were subjected to LC-MS/MS analysis using a Q Exactive Plus Mass Spectrometer fitted with an EASY-nLC 1000 (both Thermo Fisher Scientific) and a custom-made column heater set to 60 °C. Peptides were resolved using an RP-HPLC column (75 μm × 30 cm) packed in-house with C18 resin (ReproSil-Pur C18–AQ, 1.9 μm resin; Dr. Maisch GmbH) at a flow rate of 0.2 μl min⁻¹. A linear gradient ranging from 5% buffer B to 45% buffer B over 60 min was used for peptide separation. Buffer A was 0.1% formic acid in water and buffer B was 80% acetonitrile, 0.1% formic acid in water. The mass spectrometer was operated in DDA mode with a total cycle time of approximately 1 s. Each MS1 scan was followed by high-collision-dissociation (HCD) of the 20 most abundant precursor ions with dynamic exclusion set to 5 s. For MS1, 3e6 ions were accumulated in the Orbitrap over a maximum time of 25 ms and scanned at a resolution of 70,000 FWHM (at 200 m/z). MS2 scans were acquired at a target setting of 1e5 ions, maximum accumulation time of 110 ms and a resolution of 17,500 FWHM (at 200 m/z). Singly charged ions, ions with charge state ≥6 and ions with unassigned charge state were excluded from triggering MS2 events. The normalized collision energy was set to 27%, the mass isolation window was set to 1.4 m/z, and one microscan was acquired for each spectrum.

For total proteomics samples, 0.2 μg of peptides was subjected to LC-MS/MS analysis using an Orbitrap Exploris 480 Mass Spectrometer fitted with a Vanquish Neo (both Thermo Fisher Scientific) and a custom-made column heater set to 60 °C. Peptides were resolved using an RP-HPLC column (75 μm × 30 cm) packed in-house with C18 resin (ReproSil-Pur C18–AQ, 1.9 μm resin; Dr. Maisch GmbH) at a flow rate of 0.2 μl min⁻¹. Separation of peptides was achieved using the following gradient: 4% Buffer B to 10% Buffer B in 5 min, 10% Buffer B to 35% Buffer B in 45 min, 35% Buffer B to 50% Buffer in 10 min. Buffer A was 0.1% formic acid in water and buffer B was 80% acetonitrile, 0.1% formic acid in water. The mass spectrometer was operated in DIA acquisition mode with a total cycle time not exceeding approximately 3 s. For MS1, the following parameters were set: Resolution: 120,000 FWHM (at 200 m/z), Scan Range: 350–1400 m/z, Injection time: 25 ms, Normalized AGC Target: 300%. MS2 (SWATH) scans were acquired using the following parameters: Isolation Window: 11 m/z, HCD Collision Energy (normalized): 28%, Normalized AGC target: 1000%, Resolution: 15,000 FWHM (at 200 m/z), Precursor Mass Range: 400–900 m/z, Max. Fill Time: 22 ms, DataType: Centroid. In total, 100 DIA (MS2) mass windows per MS cycle followed by one MS1 scan.

The acquired raw files were converted to mzML format using ThermoRawFileParser¹⁰⁰ and searched using FragPipe v.20.0¹⁰¹ with default parameters. For non-canonical peptide identification, the protein FDR filter was not applied.

Immunostaining

Sections were thawed before being fixed in 4% PFA for 10 min and washed in PBS or washed in PBS alone (fiber type stain) before being blocked and permeabilized in PBS containing 10% goat serum and 0.4% triton X-100 for 30 min. Sections were incubated for 2 h at RT (room temperature) in a primary antibody solution containing 10% goat serum, washed 4 × 10 min in PBS and then incubated in a secondary antibody solution for 1 h at RT. After incubation in secondary antibodies, sections were washed 4 × 10 min in PBS and mounted with ProLong™ Gold antifade (Invitrogen). Primary antibodies used were F1.652-B (embryonic MHC; 1:100), BF-F3 (IIB, 1:50), which were developed by Prof. Stefano Schiaffino and obtained from the Developmental Studies Hybridoma Bank developed under the auspices of the National Institute of Child Health and Human Development and maintained by the University of Iowa Department of Biology, and laminin β1γ1 (1:200; #L9393, Sigma). Secondary antibodies used were IgG1 GaM Alexa 568 (1:100; #21124, Invitrogen), IgM GaM Alexa 488 (1:100; #21042, Invitrogen), and DaRb Alexa647 (1:200; #711-605-152, Jackson). Muscle sections were imaged at the Biozentrum Imaging Core Facility with an Axio Scan.Z1 Slide Scanner (Zeiss) equipped with appropriate band-pass filters. An in-house-customized, Fiji-based version of Myosoft^102,103 was used to outline fibers and count centralized nuclei.