The nitrogen starvation-induced inhibitor Rts3 restrains Sit4/PP6 to gate quiescence downstream of TORC1

Domain: chemistry
Published: 2026-02-26
Editorial outcome: major_revision

Abstract
Cellular quiescence is a reversible state essential for survival under nutrient-limiting or growth-restrictive conditions, yet the mechanisms fine-tuning its depth and reversibility remain elusive. Here, we identify Saccharomyces cerevisiae Rts3 as a regulator of the quiescence trajectory downstream of TORC1. Using phosphatase inhibitor beads and mass spectrometry, we characterize Rts3 as a phosphatase interactor in rapamycin-treated cells and define it as an inhibitor of the PP6 phosphatase Sit4. Mechanistically, it employs an α-helix to dock directly into the Sit4-Sap185/190 catalytic cleft. Transcriptionally induced by Gln3/Gat1 during nitrogen starvation, Rts3 is rapidly degraded upon nutrient repletion via a TORC1-SCFCdc4-proteasome axis. By selectively constraining Sit4-Sap185/190 activity, this inhibitor modulates nitrogen-responsive transcriptional and translational programs to prevent excessive accumulation of Gln3/Rtg3 targets, establishing a feedback loop gating quiescence depth to support long-term survival. Our findings position Rts3 as a dynamic molecular brake on Sit4, ensuring a protective yet reversible quiescent state.

Introduction
Eukaryotic organisms have developed complex signaling networks to perceive and react to dynamic environmental changes. This ability is crucial for the precise regulation of key cellular processes such as growth, metabolism, and proliferation. A highly conserved hub within this regulatory framework is the Target of Rapamycin Complex 1 (TORC1), a central regulator of cell growth and metabolism, which integrates various signals, including those from growth factors, hormones, and nutrients, especially amino acids1,2. Upon activation, TORC1 stimulates anabolic processes, such as protein synthesis, while simultaneously suppressing catabolic processes like autophagy. The critical role of TORC1 is underscored by its association with numerous human diseases, including cancer, obesity, and neurodegenerative disorders, when its regulation is impaired, highlighting its profound influence on overall cellular and organismal health3.

In the budding yeast Saccharomyces cerevisiae, TORC1 critically controls the balance between cell proliferation and the transition into a quiescence program that is characterized by reduced metabolic activity, enhanced stress resistance, and specific changes in gene expression, which are vital for the long-term survival of yeast under challenging environmental conditions4,5. Key events downstream of TORC1 involve type 2 protein phosphatases (PP2As; i.e. Pph21 and Pph22) and Sit4 (PP6 in mammals)6,7. A subset of these enzymes interacts with, and is regulated by, TORC1 through Tap42 and Tip416,8-12. Sit4 activity is suggested to be enhanced by Tip41-mediated Tap42 sequestering, which allows Sit4 to interact with Sit4-associated proteins (SAP) instead of Tap428. Consistent with this mechanism, TORC1 influences both transcriptional and translational programs via Sit4-SAP complexes13. SAPs include two pairs, Sap185/Sap190 and Sap4/Sap155, that have each arisen from genome duplication, share significant homology among each other, and carry out partially redundant functions in controlling Sit4 activity and specificity while competing with one another for Sit4-binding14-16. Upon TORC1 inhibition, the Sit4-Sap185/Sap190 complexes are specifically important for the induction of (i) nitrogen catabolite-repressed (NCR) genes that depend on the transcription factors Gln3 and Gat117, (ii) expression of CIT2 that requires the mitochondrial retrograde transcription factor Rtg3 (combined with Rtg1)18, and (iii) inhibition of protein translation via Gcn2 protein kinase as part of the general amino acid control (GAAC) pathway19. Sit4-SAP complexes were therefore proposed to dephosphorylate multiple target proteins such as Gln3, Rtg3, Gcn2 (and possibly also the Npr1 protein kinase and the elongator subunit Elp1)8,14 to execute the cellular response to nitrogen or amino acid starvation20-23, but the regulatory mechanisms that fine-tune their activities remain poorly understood.

To gain further insight into the mechanisms that shape the protein phosphatase (PPase) landscape downstream of TORC1, we established here an unbiased, comprehensive profiling of PPases and their interacting proteins affected by rapamycin-induced TORC1 inhibition by utilizing an approach combining PPase inhibitor beads and mass spectrometry (PIBI-MS)24. Rts3 emerged as the sole PPase-associated protein markedly enriched upon rapamycin treatment compared to untreated controls, and our findings uncover Rts3 as a regulator of cellular quiescence. Indeed, Rts3 levels increase under nitrogen starvation, and Rts3 is rapidly degraded upon nitrogen readdition, a dynamic tightly governed by TORC1 activity and SCFCdc4-mediated ubiquitination. Contrary to prior annotations, Rts3 does not associate with the canonical PP2A complex; instead, it functions as a direct inhibitor of Sit4, engaging its catalytic cleft in Sap185- or Sap190-associated Sit4 complexes. Through this inhibition, Rts3 dampens Sit4 activity during starvation, suppressing the aberrant accumulation of Gln3- and Rtg3-dependent transcripts that could otherwise promote excessive quiescent depth. Rts3 thus operates within a negative feedback circuit in which Sit4-dependent Gln3 activation induces Rts3 expression, establishing a rheostat that fine-tunes quiescence and enables timely reactivation upon nutrient replenishment.

Results
Rts3 is a rapamycin-responsive PPase interactor

To achieve an unbiased and comprehensive profiling of PPases and their interacting proteins affected by rapamycin-induced TORC1 inhibition, we utilized a PPase inhibitor beads and mass spectrometry (PIB-MS) approach. This technique employs microcystin-LR (MC-LR) -conjugated beads to selectively enrich PPase catalytic subunits and their associated proteins, followed by quantitative mass spectrometry (Figure 1a, Supplementary Data 1)24. Applying this methodology like in mammalian cells25, we successfully captured all MC-LR-sensitive catalytic subunits of PPase 1 (PP1), 1-like (PP1-like), 2A (PP2A), 2A-like (PP2A-like), 3 (PP3), 4 (PP4), 5 (PP5), and 6 (PP6), along with select associated regulatory subunits, from rapamycin-treated cell extracts (Fig. 1b,c)26. To visualize the functional connectivity of the captured interactome, we mapped the enriched proteins onto a STRING interaction network (Fig. 1c), which confirms the recovery of multiple distinct phosphatase holoenzymes (e.g., PP2A, PP6, and PP1 complexes).

Notably, Rts3 emerged as the sole protein phosphatase-associated protein significantly enriched in rapamycin-treated samples compared to empty beads controls (Fig. 1b). Rts3 is a poorly studied protein that may potentially regulate PPases. Accordingly, genetic studies have identified RTS3 as a dosage suppressor of caffeine sensitivity and suggested that it may negatively regulate Sit4-SAP modules27. Given that TORC1 is the primary target of caffeine in yeast28, these findings implied a role for Rts3 in the TORC1 pathway, a notion also supported by the rapamycin-sensitive phenotype observed in rts3∆ mutants27,29. In addition, large-scale interactome studies also pointed to a more direct role for Rts3 in Sit4 regulation, as it has been identified as an interactor of the dimeric Sit4-Sap185/Sap190 complexes30,31. Interestingly, these same studies also suggested that Rts3 might function as a B-subunit within a canonical heterotrimeric PP2A complex, similar to how Rts1 and Cdc55 B-subunits associate with the catalytic subunits Pph21 or Pph22 and the scaffold protein Tpd332. Collectively, while both genetic and interactome data connect Rts3 to the regulation of Sit4 and possibly PP2A, its precise in vivo function and its physiological role in nutrient signaling have remained largely elusive.

Dual transcriptional and proteasomal control of Rts3

To delineate Rts3 function, we first quantified its levels using a functional N-terminally tagged GFP-Rts3. Rts3 was barely detectable in exponentially growing cells but was robustly induced upon rapamycin treatment or nitrogen starvation (Fig. 2a). RTS3 transcript levels changed in a manner that mirrored protein dynamics (Fig. 2b), indicating that the acute induction and shutdown of Rts3 are driven, in part, by transcriptional control. Large-scale promoter annotations and motif analyses suggested that the RTS3 promoter contains sites for multiple stress- and nutrient-responsive transcription factors33. Our targeted deletion analysis, however, pinpointed the GATA factors Gat1 and Gln3 as the primary drivers of RTS3 induction: loss of both factors substantially blunted rapamycin-triggered RTS3 upregulation, whereas loss of Gcn4, or Rtg3, or the combined loss of Msn2, Msn4, and Gis1 had no discernible effect (Fig. 2c). These findings align with the established role of Gln3/Gat1 in nitrogen catabolite-responsive transcription downstream of TORC134,35. However, given the residual RTS3 expression persisting in the gln3∆ gat1∆ double mutant, contributions from other, yet unidentified regulatory pathways must exist.

Interestingly, Rts3 abundance was also controlled post-translationally by the ubiquitin-proteasome system, as it was rapidly degraded, within minutes, upon amino acid refeeding (Fig. 2a). Temperature-sensitive mutants in the proteasome (pup1-1, a catalytic core subunit mutant; rpn5-1, a 19S lid subunit mutant) or treatment with the proteasome inhibitor MG-132 markedly impaired the rapid loss of Rts3 upon amino acid refeeding (Fig. 2d,e). Consistent with the robust accumulation of polyubiquitinated proteins in rpn5-1 and MG-132-treated cells compared to the delayed response in pup1-1 (Fig. 2d), the pup1-1 allele merely slowed Rts3 turnover, whereas conditions imposing a stronger blockade (rpn5-1 or MG-132) led to the specific accumulation of slower-migrating Rts3 species in SDS-PAGE gels, suggestive of a phosphorylated form that is normally targeted for proteasomal degradation. Co-treatment with MG-132 and rapamycin caused the upper, slower-migrating species of the GFP-Rts3 doublet to disappear, indicating that this species corresponds to a TORC1-dependent phosphorylated isoform of Rts3 (Fig. 2e). TORC1 activity proved decisive for this switch, because rapamycin treatment during amino acid refeeding completely prevented Rts3 degradation (Fig. 2f); in this case, Rts3 accumulated predominantly as a faster-migrating, non-phosphorylated species. To exclude off-target effects, we monitored Rts3 turnover in cells carrying the rapamycin-resistant TOR1-1 allele. Unlike in wild-type cells (Fig. 2f), rapamycin expectedly failed to stabilize Rts3 in the TOR1-1 background, where the protein was rapidly degraded upon refeeding regardless of drug treatment (Fig. 2g). Direct phosphorylation of Rts3 by TORC1 was further supported by in vitro kinase assays incubating recombinant His6-Rts3 and TORC1 (immunopurified from yeast) in the presence of radioactive [-32P]-ATP (Fig. 2h). This phosphorylation was inhibited by wortmannin and stimulated more strongly by Mn²⁺ than Mg²⁺, consistent with previous findings that Mn²⁺ is a more effective cofactor for TORC1 activity36. We further substantiated this direct connection by detecting a physical interaction between the TORC1 subunit Tco89 and Rts3 using yeast two-hybrid assays, which required stabilization of Rts3 by the proteasome inhibitor MG-132 (Supplementary Fig. 1).Together, these data indicate that TORC1-dependent phosphorylation primes Rts3 for proteasomal degradation upon nutrient re-addition.

Phosphodegron-dependent recognition frequently couples phosphorylation to SCF-mediated ubiquitination37, and inactivation of the temperature-sensitive E2 enzyme cdc34-1 indeed stabilized Rts3 during amino acid refeeding (Fig. 2i). Moreover, Rts3 degradation required the F-box protein Cdc4, but not Met30 or Grr1, placing Rts3 under SCFCdc4 control. Consistent with canonical Cdc4 recognition, Rts3 harbors several candidate Cdc4 phosphodegrons (CPDs) that match the respective consensus S/T-P-x-x-(S/T/E/D) sequence38,39. Mutational analysis of these candidate sites pinpointed Ser111 as the critical determinant for turnover; the Rts3S111A mutant was fully stabilized upon amino acid refeeding (Fig. 2i). Notably, this stable mutant migrated exclusively as a faster-migrating species, lacking the phosphorylated isoform that typically accumulates when proteasomal degradation is blocked (see Fig. 2d,e). This supports a model in which TORC1-dependent phosphorylation of Rts3-Ser111 triggers SCFCdc4-mediated ubiquitination and subsequent proteasomal degradation of Rts3. In sum, TORC1 regulates Rts3 expression both transcriptionally by Gln3/Gat1 in response to TORC1 inhibition and nitrogen stress, and post-translationally by a TORC1-SCFCdc4-proteasome-dependent mechanism that accelerates Rts3 clearance upon nutrient restoration. This switch-like mechanism prevents Rts3 activity during exponential growth and starvation recovery, but allows Rts3 function during starvation, thus ensuring tight temporal control aligned with cellular nutrient status.

Rts3 modulates TORC1 signaling independently of PP2A

Given prior annotations suggesting that Rts3 might act as a B-type regulatory subunit within heterotrimeric PP2A complexes (with catalytic subunits Pph21/Pph22 and scaffold Tpd3; see above), we first tested these interactions in vivo by co-immunoprecipitation under conditions where Rts3 is highly expressed (rapamycin, 30 min). Surprisingly, while the canonical PP2A B subunits Rts1 and Cdc55 robustly co-immunoprecipitated Pph21/Pph22 and Tpd3 (Fig. 3a), we detected no interaction between Rts3 and these PP2A catalytic core subunits (Fig. 3a). Importantly, the anti-GFP immunoblot confirms that Rts3 was efficiently immunoprecipitated (Fig. 3a), ruling out low bait abundance as a cause for the lack of binding. Furthermore, as described in the subsequent section, this same construct remains fully functional for interaction with Sit4-SAP complexes. These data argue against a stable association of Rts3 with canonical PP2A.

We next revisited the genetic relationship between Rts3 and TORC1. Consistent with prior reports, rts3∆ cells were hypersensitive to rapamycin (Fig. 3b)27,29. Conversely, overexpression of RTS3 from the strong ADH1 promoter, but not expression from its endogenous promoter, conferred rapamycin resistance, indicating that Rts3 dosage antagonizes the effects of TORC1 inhibition (Fig. 3b). Despite these phenotypes, Rts3 did not measurably alter TORC1 kinase output: phosphorylation of Sch9 at Thr737 and the electrophoretic mobility of Lst4, two established TORC1 activity readouts in yeast40,41, were indistinguishable between wild-type and rts3∆ cells during exponential growth, after rapamycin treatment, under nitrogen starvation, and upon amino acid refeeding (Fig. 3c). These findings place Rts3 functionally within the TORC1 pathway, acting downstream or in parallel to modulate specific effector branches rather than bulk TORC1 activity. Finally, we examined the subcellular distribution of Rts3 using GFP-tagged Rts3 expressed from its endogenous promoter. As expected, GFP-Rts3 was barely detectable in exponentially growing cells, accumulated in the cytoplasm and nuclei upon rapamycin treatment or nitrogen starvation, and disappeared rapidly upon amino acid refeeding (Fig. 3d). While this dynamic localization pattern does not pinpoint specific molecular functions, it reinforces the notion that Rts3 does not control TORC1 activation per se, but regulates nutrient-responsive cellular processes upon TORC1 inhibition.

Rts3 binds and inhibits Sit4-Sap185/190 complexes

To define the Rts3 interaction landscape, we performed proximity-dependent biotinylation (TurboID) and quantified enriched preys relative to controls. This identified 381 high-confidence proteins in the Rts3 neighborhood (Fig. 4a, Supplementary Data 2). A global Gene Ontology (GO) enrichment analysis of these candidates revealed a broad functional engagement with ribosome biogenesis, translation machinery, and ribonucleoprotein complex assembly (Fig. 4b). Within this broad landscape, we specifically noted a distinct enrichment of PPase-associated factors, including Sap185, Sap190, Cmp2, and Cdc55 (Fig. 4a; Supplementary Data 2). Of note, because our co-immunoprecipitation analyses did not support a stable interaction of Rts3 with PP2A, the detection of the PP2A B subunit Cdc55 in the Rts3 proximome likely reflects spatial proximity, suggesting that Rts3 resides in overlapping subcellular territories rather than forming direct assemblies with other PP2A species. In parallel to the PPase-associated factors, we also observed a substantial cohort of translation-associated proteins including 19 ribosomal subunits within the Rts3 neighborhood (Fig. 4a,b, Supplementary Data 2). The latter was confirmed by experiments demonstrating that Rts3 specifically co-purified with cytoplasmic ribosomes when extracted from nitrogen-starved cells (Supplementary Fig. 2a,b), suggesting an unanticipated link to protein translation and/or ribosome hibernation.

Since our STRING-based network analysis of the PPase-specific subset highlighted the Sit4 subunits Sap185 and Sap190 (Fig. 4a), we then performed co-immunoprecipitation assays in rapamycin-treated and nitrogen-starved cells, where Rts3 expression is elevated. These experiments confirmed a robust association of Rts3 with Sit4, Sap185, and Sap190 under TORC1-inhibited conditions, which is in line with previous reports (Fig. 4c)30,31. These data place Rts3 in close proximity to Sit4 regulatory subunits in vivo and prompted a structural model illustrating how Rts3 may engage the Sit4-SAP complexes. Given that Rts3 is largely disordered but contains an α-helix spanning residues 64-103, we employed AlphaFold-based predictions to model the Sit4-Sap185 dimer bound to the Rts3 helix (Fig. 4d). To enhance conformational sampling, we then conducted molecular dynamics (MD) simulations of the complex. Our results reveal that the helix docks into a groove at the Sit4-Sap185 interface, stabilized by an extensive hydrogen bond network contributed by both partners. Specifically, residues Arg65, Glu73, and Asp77 of Rts3 play key roles in anchoring the helix within the Sit4 groove (Fig. 4e). Crucially, this docking positions the Rts3 helix directly over the catalytic center (e.g., via dynamic hydrogen bonds formed by Asp77 and, to a lesser extent, Glu73 with the catalytic residue His238; Supplementary Fig. 3a,b), acting as a steric wedge that occludes the active site. This arrangement predicts a mechanism of simple competitive inhibition, where Rts3 physically blocks substrate access rather than altering the intrinsic specificity of the phosphatase. In agreement with this structural prediction, a GFP-Rts3 variant carrying the substitutions R65A, E73A, and D77A (GFP-Rts33A) displayed markedly reduced co-immunoprecipitation with HA-Sit4 and Sap185-V5 compared with wild-type GFP-Rts3 (Fig. 4c). This confirms that these Rts3 residues are essential for anchoring the inhibitor to the Sit4 catalytic cleft. In contrast, its interaction with Sap190-myc13 was less obviously reduced (Fig. 4c). Since the Rts33A mutation disrupts the Sit4 interface (common to both complexes), the residual binding to Sap190 suggests that Rts3 maintains secondary, Sap190-specific contacts that stabilize the complex even when the primary active-site anchor is compromised. Notably, hydrogen bond analysis also identified an interaction between residue Glu37 of Sit4 and Asn655 of Sap185 (Fig. 4f), which matches well with the previous observation that mutation of Glu37 to alanine disrupts the Sit4-Sap185 interaction14. In addition, electrostatic surface analysis revealed a positively charged channel along the Sit4-Sap185 cleft, aligning with an acidic patch on the Rts3 helix (Fig. 4g). This charge complementarity is likely enhancing both the specificity and affinity of the interaction.

Guided by this model, which implies steric occlusion of the active site, we then tested whether Rts3 functions as a Sit4 inhibitor. To this end, we incubated HA-Sit4 (immunopurified from yeast) with increasing concentrations of recombinant His6-Rts3 (purified from E. coli) and assessed phosphatase activity against the synthetic phosphopeptide substrate KRpTIRR. These assays showed that Rts3 progressively suppressed Sit4 activity with an IC50 of 76 nM (Fig. 4h,i). For context, this potency places Rts3 among relatively strong endogenous protein inhibitors of serine/threonine PPases: it is weaker than the most potent phosphorylated inhibitors such as CPI-17 (IC50 in the low-nanomolar range when phosphorylated at Thr38)42, but stronger than regulators like RCAN1, which typically inhibit calcineurin in the high-nanomolar to micromolar range43. Consistent with the structural interface, an Rts33A variant targeting residues predicted to form hydrogen bonds within the Sit4 catalytic cleft completely lost inhibitory activity in vitro (Fig. 4h,i). Finally, we assessed functional consequences in vivo. Unlike overexpression of wild-type RTS3, overexpression of rts33A or rts313A (encoding a variant that has amino acids 65-77 replaced by alanines) did not confer rapamycin resistance, confirming that the inhibitory interface is required for function (Fig. 4j). To pinpoint the downstream effector, we overexpressed wild-type RTS3 in sit4∆ cells. We found that resistance was completely abolished in the absence of the phosphatase, establishing SIT4 as the essential epistatic target. However, unlike the RTS3-overexpression strain, the sit4∆ mutant itself was not rapamycin resistant (Fig. 4j). This distinction aligns with established genetic data showing that rapamycin resistance arises specifically from the loss of the Sap185/190 regulatory branch, whereas the combined loss of Sap4/155 or the catalytic subunit Sit4 does not confer resistance14. Thus, RTS3 overexpression does not mimic a total loss of Sit4 activity, but rather phenocopies the specific loss of the Sap185/190 regulatory branch. By specifically restraining the Sit4-Sap185/190 complex, Rts3 likely dampens the toxicity associated with this specific branch while preserving other essential Sit4 functions required for survival. Together, these results identify Rts3 as an endogenous, helix-based inhibitor that docks onto Sit4-Sap185/190 to attenuate Sit4 activity, with structural determinants that are necessary for both biochemical inhibition and TORC1-related phenotypes.

Rts3 constrains Sit4 to gate quiescence programs

To test the hypothesis that Rts3 selectively inhibits Sit4 during TORC1 suppression, we performed label-free phosphoproteomics on rapamycin-treated wild-type, sit4∆, and RTS3-overexpressing (RTS3-OE) cells (Supplementary Data 3). SIT4 deletion altered 2720 phosphosites across 978 proteins, whereas RTS3-OE affected 527 sites in 320 proteins, with 417 phosphosites overlapping in 263 proteins (Fig. 5a). We also profiled rts3∆ cells in parallel; however, this dataset yielded few significantly altered phosphosites under stringent statistical thresholds (FDR < 0.05). This likely reflects a detection asymmetry: while RTS3-OE imposes a blockade on Sit4 that results in a large, detectable accumulation of phosphorylation (a high signal-to-noise “gain of signal”), the rts3∆ mutant enhances the activity of an already-active phosphatase. This creates a “floor effect” where the further removal of residual phosphate groups is difficult to distinguish from the lower limit of detection. Analysis of the robust overexpression dataset revealed that 79% of Rts3-regulated sites are Sit4-dependent, while only 15% of Sit4-dependent sites responded to RTS3 overexpression, consistent with selective inhibition of the Sit4-Sap185/190 branch rather than global phosphatase suppression. The remaining Rts3-specific sites likely reflect indirect feedback or statistical thresholding rather than off-target activity, as Rts3 variants unable to bind Sit4 failed to elicit any detectable phenotypes (Fig. 4j, 5f).

We next asked which processes are co-regulated by Sit4 and Rts3. Gene ontology analysis of shared sit4∆/RTS3-OE targets highlighted several categories, including translation and nitrogen utilization (Fig. 5b), prompting us to dissect these signals by mapping them onto protein-protein interaction networks. Focusing first on translation, STRING analysis identified a subcluster of 20 Sit4- and Rts3-dependent phosphoproteins that govern core aspects of protein synthesis (Fig. 5c). Five of these proteins - Pab1, Ssd1, Stm1, Tif3, and Tif4631 - were also present in the Rts3 neighborhood (Fig. 4a, Supplementary Data 2), reinforcing our earlier assumption that Rts3 regulates aspects of protein translation during nutrient stress. The hibernation factor Stm1 controls ribosome homeostasis and is tightly regulated by TORC1-dependent phosphorylation44,45. Importantly, RTS3 overexpression prevented dephosphorylation of Ser41 and Ser45 in Stm1, while the rts3∆ mutant displayed a trend toward reduced phosphorylation at these sites (consistent with Sit4 hyperactivity; Supplementary Data 3). These residues control its association with 80S ribosomes, and thus the balance between active translation and ribosome dormancy. Indeed, consistent with the TurboID data, a pulse-chase biotinylation assay confirmed that Rts3 binds mature ribosomes during starvation (Supplementary Fig. 2a,b). However, in contrast to stm1, 80S ribosomes assessed by polysome analysis remained stable in starved RTS3-OE and rts3 cells, albeit the levels of disomes were slightly, nevertheless significantly, reduced in RTS3-OE cells (Supplementary Fig. 2c,d). To further delineate the physiological range of Rts3 function, we assessed both growth on poor nitrogen sources and survival during prolonged starvation. Given that Sit4 activates Gln3-dependent nitrogen permease expression, we tested growth on proline, which requires the Gln3-regulated transporter Put446. Consistent with Rts3 limiting Sit4 activity, RTS3-overexpressing cells exhibited a mild growth defect on proline, whereas rts3∆ cells displayed a modest growth advantage (Supplementary Fig. 2e). In addition, rts3∆ cells exhibited a significant reduction in chronological lifespan (Supplementary Fig. 2f). These findings indicate that Rts3 fine-tunes nutrient uptake during growth and, consistent with its regulation of Stm1 and ribosome hibernation, plays a crucial role in maintaining viability during starvation.

In parallel with protein translation, we examined a nitrogen utilization network encompassing the transcription factors Gln3, Rtg3, and Ume6, as well as Tip41, the kinase Npr1, and the 14-3-3 protein Bmh1 as shared Sit4- and Rts3-regulated network components (Fig. 5d). To link these signaling changes to output, we next conducted whole-proteome profiling following 3 h of nitrogen starvation. When filtering for proteins induced in a Sit4-dependent manner and opposed by RTS3 overexpression, targets of Gln3 and Rtg3 were enriched (Fig. 5e, Supplementary Data 4). Accordingly, loss of Rts3 enhanced expression of multiple Gln3-controlled genes and the prototypic Rtg3 target CIT2, whereas RTS3-OE and sit4∆ antagonized their accumulation. In addition, several proteins linked to Gcn4 and Fkh1/2 programs (Saccharomyces Genome Database [SGD] annotations) were differentially expressed, indicating that the Rts3-Sit4 axis broadly attenuates starvation-responsive transcriptional networks that coordinate metabolic remodeling. To functionally interrogate Rts3 involvement in the general amino acid control (GAAC) pathway impinging on Gcn419,47, we assessed growth on 3-amino-1,2,4-triazole (3-AT), which inhibits histidine biosynthesis and activates Gcn2-eIF2α-Gcn4 signaling. Accordingly, growth on 3-AT serves as a sensitive cellular readout of Gcn4-dependent transcription. In agreement with a role for Rts3 in dampening GAAC signaling, RTS3-OE strains exhibited mild 3-AT sensitivity (Fig. 5f), consistent with reduced Gcn4 activity under amino acid stress. Importantly, this phenotype strictly requires the Rts3-Sit4 interface, as overexpression of the Sit4-binding defective rts33A or rts313A variants failed to sensitize cells to 3-AT (Fig. 5f).

Finally, to clarify the functional positioning of Rts3 within the TORC1 signaling cascade, we performed genetic epistasis analysis. We reasoned that if the rapamycin hypersensitivity of rts3∆ mutants stems from unrestrained (hyperactive) Sit4 signaling, then eliminating Sit4 or its downstream effectors should relieve this toxicity. Consistent with this hypothesis, loss of Sit4, Gln3, Npr1, or Tip41 suppressed the rapamycin sensitivity of rts3∆ cells (Fig. 5g). This genetic rescue confirms that Tip41-driven Sit4 activation and its downstream transcriptional (and Npr1-mediated nutrient transporter regulatory) outputs drive the stress vulnerability of these mutants. These data argue that Rts3 primarily affects the Sit4-Sap185/190 phosphatase, explaining why the Rts3 dosage alters stress phenotypes independently of Sch9 or Lst4 (Fig. 3c). Integrating these findings with our expression and turnover analysis reveals a feedback loop that temporally gates entry into and exit from quiescence (Fig. 5h). Under nitrogen limitation, TORC1 inhibition activates Sit4-Sap185/190 via the Tip41-Tap42 axis, resulting in dephosphorylation and activation of Gln3, Rtg3, and Npr1. In turn, Gln3/Gat1 drive RTS3 transcription, and accumulating Rts3 protein binds Sit4 to limit downstream signaling. Upon nutrient restoration, TORC1 reactivation places Sit4 again under Tip41-Tap428 control and promotes SCFCdc4-dependent clearance of Rts3, enabling exit from quiescence. This dual regulation - coupling transcriptional induction by GATA factors with rapid degradation via the TORC1-SCFCdc4 axis - likely provides snap-switch kinetics for dynamically tuning quiescence and recovery.

Methods
Yeast strains, plasmids, and growth conditions
Saccharomyces cerevisiae strains and plasmids are listed in Supplementary Table 1. Gene deletion was performed using the pFA6a system-based PCR-toolbox51. Gibson assembly was employed for generating plasmid constructs. Unless otherwise stated, yeast strains were grown to mid-log phase in synthetic dextrose (SD) medium (0.17% yeast nitrogen base, 0.5% ammonium sulfate, and 2% glucose) at 30°C. For spot growth assays, rapamycin concentrations were titrated based on the media composition (rich YPD vs synthetic SD) to compensate for the increased sensitivity of yeast cells to TORC1 inhibition in synthetic media. To assess growth on proline, prototrophic yeast strains were diluted to an initial OD600 of 0.02 in medium containing 0.1% proline, 0.17% yeast nitrogen base, and 2% glucose. Cultures were incubated in 100-well honeycomb plates at 30°C, and growth was monitored using a Bioscreen C automated system (Thermo Labsystems). Optical density (OD600) was recorded every 30 min for 60 h, with medium-amplitude shaking for 30 s prior to each measurement (paused 10 s before reading). Data represent five independent biological replicates. The area under the curve (AUC) was calculated for each replicate, and statistical significance was determined using a one-way ANOVA.

Global PPase profiling
Wild-type Saccharomyces cerevisiae cells were grown in YPD medium (1% yeast extract, 2% peptone, 2% glucose) at 30°C to mid-log phase, treated or not with rapamycin (200 ng/mL) for 30 min, harvested by vacuum filtration, flash-frozen in liquid nitrogen, and stored at -80°C until further processing. The experiment was performed in three biological replicates. For phosphatase inhibitor beads 1.5 g of NHS-activated Sepharose beads were washed 3 times with 5 mL of 1 mM HCl followed by 2 times 5 mL of coupling buffer (100 mM NaHCO3, pH 8.2). 1 mg of aminoethanethiol-MC-LR was resuspended in 100 µL of methanol and coupled to the activated beads in coupling buffer for 1.5 h at room temperature. Cell lysates were incubated with 20 µL of beads on a rotor at 4°C for 2 h. Beads were spun down and washed 3 times with phosphatase pulldown buffer. Proteins bound to beads were digested with trypsin prior LC-MS/MS analysis.

Biotin proximity labeling and Rts3 proximome mapping
Yeast strains (MP7079 [RTS3p-TurboID-V5-RTS3] and LD7381 [RTS3p-TurboID-V5-Envy; negative control]) were grown to mid-log phase in 1 liter of synthetic dextrose complete (SDC) medium lacking uracil. Cells were treated with biotin (50 µM) for 1 hour and rapamycin (200 ng/mL) for 30 min. After treatment, cells were collected by vacuum filtration, washed with 200 mL of ice-cold 50 mM Tris.Cl (pH 7.5), flash-frozen in liquid nitrogen, and stored at -80°C until further processing. Cells were disrupted using glass beads (0.25-0.50 mm diameter; Retsch) in 3 mL of RIPA buffer (50 mM Tris.Cl [pH 7.5], 150 mM NaCl, 1.5 mM MgCl2, 0.1% SDS, 1% Triton X-100, 0.5% sodium deoxycholate, 1× cOmplete EDTA-free protease inhibitor cocktail [Roche]) using a Precellys homogenizer (6 × 30 s at 5’000 rpm, 1 min pause between cycles). Lysates were clarified by centrifugation (1’500 × g, 7 min, 4°C), and total protein concentration was measured and adjusted using the Pierce™ BCA Protein Assay Kit (Thermo Fisher Scientific). NanoLINK® Streptavidin Magnetic Beads (150 µL; SoluLink) were added to the lysates and incubated at room temperature for 1 hour with constant rotation. Beads were subsequently washed five times with 100 mM ammonium bicarbonate and stored at -80°C until further processing. The experiment was performed in three biological replicates.

Biotinylated proteins bound to streptavidin beads were extracted in 8 M urea in 100 mM ABC buffer and reduced with 1 mM DTT. The samples were loaded on the 10 kDa cut-off filter, and spun at 8’000 × g, for 30 min. Proteins were alkylated using 5.5 mM iodoacetamide for 10 min at room temperature and washed twice with 100 mM ABC buffer. Finally, the proteins were digested on-beads with trypsin (Promega) overnight on a thermomixer at 550 rpm and 37°C. Tryptic peptides were purified by STAGE tips and LC-MS/MS measurements were performed by data-dependent analysis (DDA) on a QExactive HF-X mass spectrometry coupled to an EasyLC 1200 nanoflow-HPLC (all Thermo Scientific). MaxQuant software (version 1.6.2.10)52 was used for analyzing the MS raw files for peak detection, peptide quantification and identification using a Uniprot S. cerevisiae (2016) database. Carbamidomethylcysteine was set as fixed modification and oxidation of methionine was set as variable modification. The MS/MS tolerance was set to 20 ppm and four missed cleavages were allowed for Trypsin/P as enzyme specificity. Based on a forward-reverse database, protein and peptide FDRs were set to 0.01, minimum peptide length was set to seven, and at least one unique peptide had to be identified. The match-between run option was set to 0.7 min. MaxQuant results were analyzed using Perseus software (version 1.6.2.3)53 .

Label free quantification measurements were obtained for all samples. Protein IDs with minimally two valid values out of three replicates in tested IP samples were considered for analysis. log2-transformed iBAQ values normalized to the median of the respective biological replicate were used for analysis. Missing values in control samples were imputed using a normal distribution with a width of 0.3 and down shift of 1.8. Statistical significance using Student’s t-test with p-values p < 0.05, and FDR corrected p-values q < 0.05 shown in respective figures. Perseus software (version 1.6.2.3) was used for all statistical analyses.

Label-free phosphoproteome analysis
Indicated yeast strains were grown in SDC medium lacking histidine to mid-log phase and treated with rapamycin (200 ng/mL) for 30 min. After addition of 6.5% trichloroacetic acid, cells were collected by centrifugation, and washed with ice-cold acetone. The resulting cell pellets were dried under vacuum and stored at -80°C until further processing. The experiment was performed in five biological replicates. MS sample preparation was performed as described in Hu et al. (2019)54. Briefly, proteins were extracted by disrupting yeast cells in 8 M urea using bead beater and digested by Lys-C for 4 h at room temperature. Before overnight trypsin digestion, the concentration of urea was reduced to 1 M. Next day, peptides were purified using reversed phase cartridges (RP-S-5μl, Agilent) and eluted in 80% acetonitrile with 1% TFA for phosphopeptide enrichment using Fe(III)-NTA cartridges (Agilent)55. The flow-through was used for non-phosphopeptide analysis and PTM normalization.

LC-MS/MS measurements were performed on an Exploris 480 mass spectrometer coupled to an EasyLC 1200 nanoflow-HPLC (phospho peptides) or on a QExactive HFX mass spectrometer coupled to a Vanquish Neo UHPLC System (whole proteome, all Thermo Scientific). Peptides were separated on a fused silica HPLC-column tip (I.D. 75 μm, New Objective, self-packed with ReproSil-Pur 120 C18-AQ, 1.9 μm (Dr. Maisch) to a length of 20 cm) using a gradient of A (0.1% formic acid in water) and B (0.1% formic acid in 80% acetonitrile in water). Spray voltage was set to 2.3 kV and the ion-transfer tube temperature to 250°C; no sheath and auxiliary gas were used. Mass spectrometers were operated in data independent mode; after each survey scan (mass range m/z = 400 - 1’200; resolution: 120’000) 34 DIA scans with an isolation width of 24 m/z were performed covering a total range of precursors from 400-1’200 m/z. AGC target value was set to 300%, resolution to 30’000 and normalized stepped collision energy to 25.5%, 27%, and 30%. The MS raw files were analyzed using Spectronaut software version 19 and directDIA+ workflow with standard settings using a Uniprot full-length yeast database and common contaminants such as keratins and enzymes used for digestion as reference. Statistical significance was determined using pairwise Student’s t-tests with a permutation-based FDR of < 0.05. For biological network definition and Venn diagram overlap analysis (Fig. 5), an additional fold-change cutoff of > 2 (log2 > 1) was applied.

Functional enrichment and interaction analyses were carried out using Cytoscape v3.10.3 (cytoscape.org) with the ClueGO plugin v2.5.3, STRING database56, and Omics Visualizer57. Gene Ontology (GO) enrichment for the cellular compartment category was assessed relative to the S. cerevisiae genome background, applying GO-term fusion to reduce redundancy.

Comparative whole-proteome analysis
Indicated yeast strains were grown in SDC medium lacking uracil to mid-log phase and subsequently subjected to nitrogen starvation for 3 hours. Proteins were extracted from dry TCA-acetone-treated cell pellets (prepared as described above) using RIPA buffer supplemented with 0.17% ammonium hydroxide. Cell disruption was performed with glass beads in a Precellys homogenizer (3 × 90 seconds at 5’000 rpm, 1 min pause between cycles). Protein concentration was determined using the BCA assay and adjusted to 1 mg/mL. Samples were treated with 0.5 μL Benzonase® Nuclease (Millipore) for 30 minutes on ice. The experiment was performed in four biological replicates.

MS sample preparation was performed using autoSP3 method described in Sanders et al. (2025)58. Briefly, proteins were reduced and alkylated using DTT and CAA and precipitated on Sera-Mag speedbeads (GE healthcare). After washing, proteins were digested overnight with trypsin.

LC-MS/MS measurements were performed on an Orbitrap Astral mass spectrometer coupled to a Vanquish Neo UHPLC System (all Thermo Scientific). Peptides were separated on a fused silica HPLC-column tip (I.D. 75 μm, New Objective, self-packed with ReproSil-Pur S120 C18-AQ, 1.9 μm (Dr. Maisch) to a length of 14 cm) using a gradient of A (0.1% formic acid in water) and B (0.1% formic acid in 80% acetonitrile in water). Spray voltage was set to 2 kV and the ion-transfer tube temperature to 280°C; no sheath and auxiliary gas were used.

Mass spectrometer was operated in data independent mode; 149 DIA scans with an isolation width of 4 m/z covering a total range of precursors from 380-980 m/z were performed on the Astral analyzer with an AGC target of 300%, 4 ms injection time and a normalized collision energy of 25%. The DIA loop was interrupted every 0.6 s by a survey scan using the Orbitrap detector (mass range m/z = 380 - 980; resolution: 240’000). The MS raw files were analyzed using Spectronaut software version 20 and directDIA+ workflow with modified standard settings (missed cleavage 3, all QValue and PEP cutoffs were set to 0.01) using a Uniprot full-length yeast database and common contaminants such as keratins and enzymes used for digestion as reference.

Immunoblot analysis
Whole cell lysates were prepared as previously described59. Proteins were separated by SDS-PAGE and transferred onto nitrocellulose membranes. A complete list of primary and secondary antibodies, including working dilutions, is provided in Supplementary Table 1.

Co-immunoprecipitations
For PP2A interaction assays, yeast cultures were grown exponentially in synthetic dextrose complete medium lacking ammonium sulfate (SDC-AS) and treated with 200 ng/mL rapamycin or vehicle for 30 min. Cells were collected by filtration and flash-frozen. Cell pellets were lysed by mechanical disruption with glass beads in a Precellys homogenizer in ice-cold lysis buffer (50 mM HEPES, pH 7.4; 150 mM NaCl; 10 mM MgCl2) supplemented with 0.1% NP-40, protease- and phosphatase-inhibitors. Lysates were clarified by centrifugation and incubated with GFP-Trap® magnetic agarose (ChromoTek) for 2 h at 4°C with rotation. Beads were then washed three times with lysis buffer and bound proteins were eluted by addition of SDS-PAGE sample buffer and heating at 95°C for 5 min. Input and IP eluates were resolved by SDS-PAGE and analyzed by immunoblotting with the indicated antibodies. A pre-treatment of the membrane with 0.2 M NaOH served to demethylate PP2A catalytic subunits and allowed detection by immunoblotting.

To probe the interaction of Sit4 with SAPs, yeast strains LD8617, LD8616, and LD8593 were grown in YPD medium and shifted to SD medium lacking nitrogen, supplemented with rapamycin (200 ng/mL), for 30 min. Cultures (400 mL of per strain) were harvested by centrifugation at 1’000 × g for 5 minutes at room temperature. Cells were aliquoted into 1.5 mL screw-cap tubes, flash-frozen in liquid nitrogen, and stored at -80°C until further processing. Cells were lysed using a sequential bead-beating protocol in 1.2 mL lysis buffer containing 50 mM MES (pH 6.5), 150 mM NaCl, 1 × cOmplete EDTA-free protease inhibitor cocktail (Roche), and 0.5% Triton X-100. Cell disruption was performed using a FastPrep-24 instrument (MP Biomedicals) for 45 s at power level 6.5. Lysates were clarified by centrifugation at 1’500 × g for 2 min at 4°C. Protein concentration was determined using the BCA Protein Assay Kit (Thermo Fisher Scientific) and adjusted to equal levels before immunoprecipitation. Clarified lysates were incubated with anti-GFP mouse antibody (Roche; 1:700) overnight at 4°C with constant rotation. In parallel, Protein G Dynabeads™ (Invitrogen) were blocked by overnight incubation with untagged yeast lysate at 4°C. The following day, antibody-lysate mixtures were incubated with the blocked beads for 4 h at 4°C. Beads were washed three times with lysis buffer, and bound proteins were eluted with Laemmli buffer (15 min at 65°C). Eluates were analyzed by SDS-PAGE and western blotting as described above.

Yeast two-hybrid assay
Protein interactions were analysed using the split-ubiquitin DUALmembrane System 3 (Dualsystems Biotech AG). Tco89 was cloned into the bait vector pCabWT, Rts3 into the prey vector pPR3-N. The bait-prey combinations were transformed into S. cerevisiae NMY51, using positive (pAI-Alg5) and negative (pDL2-Alg5) control vectors in parallel. Transformants were spotted as 10-fold serial dilutions onto SD-Leu/Trp, SD-Leu/Trp/Ade, and SD-Leu/Trp/His plates, supplemented (where indicated) with 75 μM MG-132, 0.5% DMSO, and 0.003% SDS. Plates were incubated for 3 days at 30°C. Protein-protein interactions were scored as growth under selective (-Ade or -His) conditions.

RNA isolation and RT‑qPCR analysis
Yeast cells were collected at an optical density (OD) of 0.6-0.8 (2 mL culture aliquot) by centrifugation at 2’500 × g for 2 min. Cell disruption was performed with glass beads in a Precellys homogenizer (3 × 30 seconds at 5’000 rpm, 1 min pause between cycles) and RNA was subsequently extracted from the lysate using the Quick-RNA kit (Zymo Research) according to the manufacturer’s instructions. RTS3 transcript levels relative to TBP1 reference gene were analyzed using Luna® Universal One-Step RT-qPCR Kit (New England Biolabs). 5 ng of total RNA were added to the 20 µL reaction mix, the final concentration of each primer (listed in Supplementary Table 1) was 0.4 μM. Reactions were performed in triplicate. PCR cycle conditions consisted of 10 min of reverse transcription (55°C), 1 min of initial denaturation (95°C), followed by 40 cycles of 10 s at 95°C and 30 s at 60°C. Green fluorescence was monitored after each extension step. The amount of the respective transcript was determined for 3 biological replicates using the ∆∆Ct method59.

Fluorescence microscopy
Yeast cells were grown in SDC-AS medium to log phase at 30°C. Nitrogen starvation and amino acid refeeding were induced as described60. Cells were imaged using an inverted spinning-disk confocal microscope (Nikon Ti-E; VisiScope CSU-W1) equipped with a dual-camera system (Hamamatsu Orca Quest C15550-20UP) and a 100× NA 1.3 oil-immersion Nikon CFI objective. Z-stacks of eleven images at 0.2 µm spacing were acquired.

Computational modeling and molecular dynamics simulations
A structural model of the Sit4-Sap185-Rts3 trimeric complex was generated using AlphaFold-Multimer v2 (https://doi.org/10.1101/2021.10.04.463034). Among five predicted models, the one with the highest combined model confidence score (ipTM + pTM = 0.7) was selected for further analysis. Predicted disordered regions in Rts3 and Sap185 were excluded prior to molecular dynamics (MD) simulations. The final construct used for simulation included residues 52-123 of Rts3, residues 16-796 of Sap185, and the full-length Sit4. The system was solvated with the TIP3P water model and neutralized by adding Na+ and Cl- ions to a final concentration of 0.15 M. Energy minimization was carried out using the steepest descent algorithm. An initial 2 ns NVT equilibration was performed at 300 K using the v-rescale thermostat with a coupling constant τT = 1 ps61. This was followed by 2 ns NPT equilibration at 310 K using the same thermostat and the Berendsen barostat with τ = 1 ps62. The system was subsequently subjected to a 320 ns production MD simulation in an NPT ensemble at 310 K. Temperature was controlled using the v-rescale thermostat and pressure was maintained with the Parrinello-Rahman barostat63, both with τT and τP = 1 ps. Electrostatic interactions were calculated using the Particle Mesh Ewald (PME) method64 with a real-space cut-off of 1.2 nm. A 1.2 nm cut-off was also applied to van der Waals interactions. All simulations were carried out using the CHARMM36 force field65 and GROMACS v2021.5 software (https://doi.org/10.5281/zenodo.4457591). Hydrogen bonds were identified using the gmx hbond module in GROMACS v2021.5. Electrostatic potentials of Sit4 were computed using APBS v3.4.166 and visualized in ChimeraX67.

Sit4 in vitro PPase assay
Purification of HA-tagged Sit4 from Saccharomyces cerevisiae and the subsequent in vitro PPase assay using the KRpTIRR phosphopeptide (MedChemExpress) as a substrate were performed as described68. Briefly, HA-Sit4, immunoprecipitated from yeast cells and activated with ascorbate, was pre-incubated on ice for 20 min with the indicated variants of recombinant His6-tagged Rts3. These were expressed in E. coli Rosetta cells, purified using Ni-NTA agarose (Qiagen) in phosphate-free buffers according to the manufacturer's instructions, and buffer-exchanged into TBS (Tris-buffered saline) using PD-10 columns (Cytiva). PPase reactions were carried out for 3 hours at 30°C in a thermoblock shaker at 600 rpm. Free phosphate release was quantified using the Biomol Green reagent (Enzo Life Sciences), and IC50 values were determined by nonlinear regression using GraphPad Prism 10.

TORC1 purification and in vitro kinase assay
TORC1 purification and in vitro kinase assay were performed as previously described69. Briefly, 3 µL of TORC1 purified from yeast cells were incubated with 1 µg of recombinant His6-Rts3 in kinase buffer (50 mM HEPES [pH 7.5], 400 mM NaCl, 8.75 mM MgCl2 or 3.5 mM MnCl2, 7 µCi of [-32P]-ATP [6’000 Ci/mmol], and 315 µM cold ATP) for 30 min at 30°C. The reaction (final volume 20 µL) was stopped by adding 4 μL 6x Laemmli SDS sample buffer and denaturing for 5 min at 65°C. The samples were resolved by SDS-PAGE and analyzed by Sypro Ruby staining and autoradiography. Wortmannin was used to inhibit TORC1 kinase activity as described70, since rapamycin inhibition relies on the FKBP12 cofactor which is absent in the purified fraction.

Purification of cytoplasmic ribosomes
To purify mature, cytoplasmic ribosomes we adapted a previously established pulse-labeling protocol that selectively biotinylates AVI-tagged ribosomal proteins45. Accordingly, Rps2-TEV-HA-AVI was pulse-labeled with biotin in yIK127 cells. Cells were grown in SDC medium with low biotin levels (0.5 nM). At OD600 = 0.4, BirA-AID expression was induced by adding 5 nM estradiol. After 2 h, estradiol was washed out, and the pulse-labeling of Rps2 was initiated by supplementing the culture with 10 nM biotin and incubation for 1 h. At the same time, BirA-AID expression was terminated by addition of indole-3-acetic acid (IAA; 1 mM). Both induced and control cultures were then washed twice with water, starved for nitrogen for 72 h at 30°C, treated with cycloheximide (100 µg/mL, 10 min, 23°C), harvested by centrifugation (1’000  g, 5 min, 4°C), and snap frozen in liquid nitrogen.

For streptavidin pull-down, cell pellets were resuspended in lysis buffer (50 mM Tris.Cl pH 7.5, 100 mM NaCl, 1 mM EDTA pH 8.0, 20 mM MgCl2, 100 µg/mL cycloheximide, 1 mM PMSF, 1 cOmplete™ EDTA-free protease inhibitor, 0.1% NP-40). Cells were disrupted with Zirconia/Silica beads (0.5 mm; Biospec) by vortexing (15 min, 2’850 rpm, 4°C). Lysates were clarified (20’000  g, 20 min, 4°C), and protein concentrations were determined by BCA assay and normalized across samples, which were then incubated with Dynabeads® MyOne™ Streptavidin C1 (Invitrogen) for 1 hour at 4°C. After washing the beads twice with lysis buffer, PBS (phosphate-buffered saline) containing 0.1% NP-40, and PBS without detergent, the bound proteins were eluted in urea containing SDS-PAGE sample buffer (65°C, 15 min), resolved by SDS-PAGE, and analyzed by immunoblotting with the indicated antibodies. Three independent experiments were performed; a representative blot is shown in Supplementary Fig. 2b.

Polysome profiling
Indicated strains were grown in SDC medium lacking uracil until reaching an OD600 of 0.6, washed twice with water, and starved for nitrogen for 72 h at 30°C. Polysome profiling was performed as described previously44, with slight modifications. In brief, cells were treated with cycloheximide (100 µg/mL) for 10 min at 23°C, pelleted by centrifugation (5 min, 1’000 × g), washed once with ice-cold PBS and once with lysis buffer (20 mM Tris-Cl, pH 7.5; 150 mM KCl; 5 mM MgCl2; 1% Triton X-100; 1 mM DTT; 100 µg/mL cycloheximide; 0.1 mM PMSF), and then resuspended in 800 µL lysis buffer. Cells were disrupted as described above for the purification of cytoplasmic ribosomes. A total of 500 µL extract was loaded onto a 10-50% sucrose gradient prepared in lysis buffer without Triton X-100 and centrifuged at 39’000 rpm for 2 h at 4°C using an SW41Ti rotor (Beckman Coulter). Subsequently, the gradient was fractionated with the Triax™ Flow Cell (Biocomp Instruments), and absorbance was recorded at 260 nm. Four independent experiments were performed. An unpaired Student’s t-test was used for statistical analysis.

Chronological life span assay
For chronological lifespan analysis (survival assays), cells were grown in SDC medium to stationary phase (72 hours) and maintained in the spent medium. At indicated time points, aliquots were removed, diluted, and plated on YPD agar to determine colony-forming units (CFUs). Survival is expressed as a percentage of CFUs relative to the first day of stationary phase (Day 0).

Statistical analysis
Statistical parameters are reported in the Figure, Supplementary Figure, and Supplementary Data Legends, and the corresponding Methods Details.

Data availability
All the data supporting the results of this study are presented within the article, the Supplementary Information and the Supplementary Files. Source data for gel images, microscopy images, and graphs can be found in Mendeley Data (https://data.mendeley.com/preview/pj2dkx8jw3?a=252ec8da-f7b8-4e74-be44-39b90ce1a242). Proteomics data is freely available via the PRIDE repository (https://www.ebi.ac.uk/pride/), data identifier PXD069824. Additional information can be obtained from the corresponding author.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Dokladal et al. describe a new feedback loop in the TORC1 signaling pathway, in which the starvation-induced protein Rts3 binds and inhibits the Sit4–Sap185/190 phosphatase complex, thereby dampening the dephosphorylation of targets involved in nitrogen metabolism and translation. This is an important and technically impressive study that fills a major gap in our understanding of how TORC1 regulates phosphatase activity—a long-standing challenge in the field due to the technical difficulty of dissecting these interactions and phosphatase function. The authors use an elegant combination of biochemical assays, quantitative proteomics, and structural modeling to define Rts3’s function with high precision. The work is also clear and well written, and will make a valuable contribution to the TORC1 signaling field. The manuscript’s main strengths are its rigor, depth of molecular characterization, and mechanistic insight. However, there are two areas for improvement that should be addressed to increase the paper’s overall impact before publication. 1. Broader Function and Physiological Role of the Rts3 Feedback Loop While the study convincingly defines the Rts3-dependent feedback mechanism and its biochemical connection to TORC1, the physiological significance of this feedback remains underexplored. The authors link Rts3 to stabilization of the quiescent state, but the impact on quiescence exit appears modest. Because Rts3 is induced by GATA factors (Gat1/Gln3), it is likely expressed under nutrient-limiting conditions as well as during starvation. This raises the possibility that Rts3 serves to stabilize or attenuate TORC1 signaling in cells growing under poor nutrient conditions, not just in fully starved cells. Addressing this hypothesis—through discussion or additional experiments—would substantially strengthen the paper. For example, the authors could assess the growth or survival of rts3Δ cells in proline or other poor nitrogen sources could help clarify its physiological role. It would also be interesting to follow up on the argument that Rts3 stabilizes the quiescent state by looking at cell survival over long time periods of starvation in wt and rts3Δ cells. 2. Analysis and Interpretation of Rts3’s Impact on Sit4–Sap185 Function The authors demonstrate that Rts3 inhibits Sit4 activity in vitro and in vivo. However, the core analysis relies heavily on overexpression data in rapamycin-treated cells, where Rts3 is already induced and likely occupies most Sit4–Sap185 binding sites. In contrast, the impact of Rts3 deletion is underexplored. A more detailed presentation and discussion of the rts3Δ proteomic data would clarify the true functional scope of Rts3. Specifically: • Are the changes in phosphorylation upon deletion consistent with simple inhibition, or could Rts3 alter phosphatase specificity or Sit4 binding partner selection? • How do the Rts3-dependent sites not found in the Sit4 delete fit with its mechanism of action? • How was statistical significance defined (e.g., FDR correction, cutoffs)? Listing these thresholds would improve clarity and reproducibility. Additionally, the text indicates that Rts3 binds the Sit4–Sap185 complex in a way that would inhibit its activity, but this is not clearly explained. The authors should specify where the Rts3 helix binds, how this position might block or modify access to substrates, and whether the model predicts simple inhibition versus altered specificity. 3. Specific Comments and Minor Revisions • Line 48: Should read “A subset of these enzymes interacts with, and are regulated by…” • Line 90 and Table 1: The statement that Rts3 was “significantly enriched” in rapamycin-treated cells needs clarification. The figure legend just restates this fact—please specify how enrichment was determined, including criteria or statistical thresholds used (e.g., fold-change, FDR). • Promoter analysis section (Figure 2B–C): The phrase “large-scale promoter annotations and motif analyses (Saccharomyces Genome Database)” is vague. Please clarify which studies or datasets were used and cite the primary literature rather than the database itself. It is also unclear that Gat1 and Gln3 are the primary drivers of RTS3 expression. Figure 2C suggests additional regulators may contribute, as the induction is only partially blunted in the double mutant. Replotting the data (and that of Fig. 2b) bon a log₂ scale could help visualize dynamic range and clarify this point. • TurboID dataset: With 764 significant interactors, the current analysis is limited. A more global interpretation—e.g., enrichment of functional categories or pathways—would help contextualize Rts3’s role beyond the specific Sit4-Sap185 and ribosomal interactions highlighted. • Structural model and transition (text around Fig. 4): The rationale for testing Rts3 as an inhibitor is not clear from the preceding description. Please explain how the predicted Rts3-binding site suggests inhibition of Sit4 activity. • Figure 5 and phosphoproteomic analysis: As discussed above, the logic of using Rts3 overexpression in rapamycin as the main readout is problematic, since Rts3 is already induced under these conditions. A deletion versus wild-type comparison in rapamycin would provide a cleaner view of Rts3 targets and should be emphasized in the analysis and discussion (referenced in Fig. 5E but not adequately integrated earlier). • Physiological relevance: The authors briefly mention a small delay in recovery from quiescence in rts3Δ cells, but this the physiological impact of the Rts3 feedback loop is not analyzed in depth. Further discussion or data addressing nutrient-limiting growth conditions (e.g., poor nitrogen sources) could significantly enhance the impact of the work.", "reviewer_2": "The study “The nitrogen starvation-induced inhibitor Rts3 restrains Sit4/PP6 to gate quiescence downstream of TORC1” by Dokládal et al. describes a novel mechanism by which TORC1 governs the balance between cell proliferation and entry into the quiescence programme in budding yeast. TORC1 regulates the activity of protein phosphatases such as Sit4 (PP6 in mammalian cells), thereby controlling Sit4-driven translational and transcriptional programmes. In this study, the authors investigate the phosphatase landscape downstream of TORC1 by applying an unbiased phosphatase inhibitor beads-mass spectrometry approach to cells treated with rapamycin, thereby specifically inactivating TORC1. This strategy identifies Rts3 as the only phosphatase-associated factor consistently enriched upon TORC1 inhibition. The authors show that Rts3 contributes to the control of cellular quiescence. Its stability increases during nitrogen starvation, whereas nutrient re-addition triggers SCF-Cdc4-dependent ubiquitination and proteasomal degradation. Functionally, Rts3 reduces Sit4 activity during starvation. The work further reveals that Gln3, activated by Sit4, induces RTS3 expression, establishing a negative feedback loop that maintains quiescence at an appropriate depth and ensures that cells can resume growth once nutrients are restored. Overall, the mechanism described is certainly interesting and novel, and the evidence presented by the authors supports the conclusions reached. The work addresses a relevant question in the field, and the findings are of significance to both the TORC1 and quiescence communities. The experimental design is sound, the methodology meets the expected standards in the field, and the PIB–MS approach is applied in a rigorous and unbiased manner. Major Comments 1. Rts3 band patterns differ between the Figures 2A and 2D, especially at +AA 10 and +AA 60 minutes. Clarification or use of matched blots would improve consistency. 2. The slower-migrating forms of Rts3 appears only in rpn5-1 (and with MG-132) but not in pup1-1. In addition, the +AA 60 band in pup1-1 resembles wt. This inconsistency should be addressed. 3. Including TOR1-1 cells in Figure 2E would demonstrate that the mobility shift is TORC1-dependent rather than an artefact of rapamycin exposure. 4. Ubiquitinated-protein blots differ between Figures 2D and 2F and should be more comparable. 5. More methodological detail on the kinase assay should be added in the main text and figure legend, and the authors may wish to comment on the reason why they used wortmannin instead of rapamycin as in the rest of the manuscript for the same purpose. 6. Including described Rts3 interactors as control in Figure 3A would confirm that the absence of interaction with Tpd3 and Pph21/22 is not due to low Rts3 abundance. 7. The experimental procedure for Figure 4C requires further explanation. The Rts3-3A mutant shows differential loss of interaction with Sit4, Sap185 (clear decrease) compared with Sap190 (not so clear decrease); this difference should be addressed and clarified. 8. The manuscript uses 4, 5 and 10 ng/ml rapamycin in different assays. A brief justification would help. Growth differences between Figure 4J (5 ng/ml) and Figure 5G (10 ng/ml) should be clarified. In Figure 4J first spot in rapamycin plate is growing weakly at 5ng/ml but in Figure 5G at 10ng/ml authors present better growth. 9. The phenotype observed on 3-AT plates in Figure 5F is quite subtle. Including a control strain to verify that the 3-AT assay is working effectively would support the conclusion. The authors may also wish to adjust the wording accordingly. 10. The genetic logic may not be intuitive to general readers. A more detailed explanation will benefit the manuscript. Authors could consider to use an additional experimental approach to show the same, which would strengthen the conclusion. 11. In the Discussion, the statement that Rts3 “counteracts TORC1-dependent phosphorylation of the hibernation factor Stm1 that balances ribosome homeostasis” implies enhanced Stm1 dephosphorylation, which seems at odds with the model in which Rts3 inhibits Sit4, the phosphatase expected to act on Stm1. This apparent contradiction should be addressed, unless this reviewer misunderstood. Minor Comments 1. Strain names should be included in the figure legends to improve clarity of the experimental details. 2. As Figure 1B supports the proposed negative feedback loop, explicitly referring back to it when this mechanism is discussed later in the text would help the reader. 3. Page 4, line 113 onwards: a more detailed explanation would help readers follow Figure 1C. In addition, it may be worth reconsidering whether the term 'genetic analysis' is the most appropriate description in this context. 4. Figure 2C: as residual RTS3 expression persists in gat1 gln3 deleted cells, the authors may wish to discuss additional pathways that could contribute to RTS3 expression. 5. Figure 3B: showing Rts3 levels expressed from the endogenous promoter and from ADH1 promoter could help define the expression threshold above which cells become rapamycin-insensitive. 6. Figure 3D: larger crops of cells would improve visibility of the phenotypes shown. 7. Figure 4E: some residues are difficult to see; alternative colouring may enhance clarity. 8. Page 34, line 897 (Figure 4): please clarify why “not shown”. 9. Page 34, line 912 (Figure 4): clarify whether expression was tested in asynchronously growing WT cells. 10. Page 8, line 211: additional detail on the phosphatase assay should be added to the main text. Editorial Points Page 49: rephrase “Tip1-mediated Tap42 sequestering”. Line 229: “2720” rather than “2’720”. Line 236: clarify the meaning of “network-level dissection”. Line 242: specify the protein in which Ser41 and Ser45 are affected. Line 254: clarify “shared Sit4- and Rts3-regulated nodes” for readers unfamiliar with STRING. Line 271: clarify “permease regulatory”. Line 280: rephrase the “dual-mode regulation–feedforward induction” sentence. Line 807: correct “declaration od”.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_4": "In the manuscript by Dokládal et al., the authors investigate how protein phosphatases downstream of TORC1 are regulated by utilizing an approach that combines PPase inhibitor beads with mass spectrometry. They identify Rts3 as the PPase-associated protein markedly enriched upon rapamycin treatment. In addition, they demonstrate that Rts3 accumulates during nitrogen starvation and is degraded upon nitrogen readdition through TORC1- and SCF-dependent mechanisms. Rather than binding the canonical PP2A complex, Rts3 is suggested to act as a direct inhibitor of Sit4 by interacting with its catalytic cleft in complexes containing Sap185/190. Through this inhibition, Rts3 is proposed to restrain Sit4 activity during starvation, limit Gln3- and Rtg3-dependent transcription, and thereby fine-tune quiescence depth and promote efficient reactivation upon nutrient replenishment. Overall, most of the data are of high quality and seem to support the authors’ conclusions. On the other hand, many of the experiments rely on overexpression systems, and thus, it is difficult to exclude the possibility that some of the observed effects may arise from overexpression artifacts. Major points 1) The authors claim that Rts3 is a direct substrate of TORC1 by performing an in vitro kinase assay (Fig. 2G). Have the authors confirmed the physical interaction between TORC1 and Rts3, which would further support their claim? 2) In Fig. 3B, the authors shows that the overexpression of Rts3 from ATD promoter confers rapamycin resistance on budding yeast cells. Since this experiment relies on the Rts3 overexpression, the observed rapamycin resistance might not reflect Rts3-mediated inhibition of Sit4, but could instead be an artifact of overexpression. To rule out this possibility, the same experiment should be performed using sit4 deletion mutant cells, in which rapamycin resistance would not be expected. 3) The authors validated the interaction model of Sit4 and Rts3 obtained from MD simulations by co-immunoprecipitation assays with alanine mutants of Rts3 (Fig. 4C, E and F). On the other hand, the importance of Sit4 residues R266, Y263, and Y124, which have been proposed to interact with Rts3, has not been experimentally validated. It would be valuable to assess the significance of these residues using co-immunoprecipitation (co-IP) with alanine-substituted Sit4 mutants. 4) In Fig. S1C, the growth delay observed in rts3∆ and GFP-RTS3-OE cells may not necessarily reflect a slower recovery from nitrogen starvation compared to wild-type cells, but could instead be due to an overall slower growth rate. This possibility could be addressed by examining growth curves using cells in logarithmic phase. 5) In the polysome analysis shown in Fig. S1D, no statistically significant difference was observed between wild-type and rts3∆ cells. Moreover, although the difference between wild-type and GFP-Rts3-OE cells is statistically significant, it is rather small, as noted by the authors. Nevertheless, as shown in Fig. S1C, both rts3∆ and GFP-Rts3-OE cells exhibit a similar delay in recovery from nitrogen starvation compared to wild-type cells. Therefore, I think that the authors’ conclusion ‘Together, these results confirm that Rts3 associates and constrains Sit4 on hibernating ribosomes, allowing efficient recovery from prolonged starvation, thus emphasizing its physiological relevance (lines 249-251)’ is not supported by the data. Minor points 6) In the input samples of Fig. 4C, a strong non-specific band is observed in addition to GFP–Rts3, whereas no such band appears in Fig. 4A. What accounts for this discrepancy? 7) A part of the immunoblotting image in Fig. 4C (right side) appears to be missing. 8) In Fig. 4E and F, the red numbering of the amino acid residues overlaps with the structure colored in magenta, making it difficult to distinguish. 9) Statistical analysis should be performed for Fig. 4H. 10) In line 125, ‘In’ should not be capitalized."}, "author_response": "Responses to reviewers: Reviewer #1 Major Comments 1. Broader Function and Physiological Role of the Rts3 Feedback Loop. While the study convincingly defines the Rts3-dependent feedback mechanism and its biochemical connection to TORC1, the physiological significance of this feedback remains underexplored. The authors link Rts3 to stabilization of the quiescent state, but the impact on quiescence exit appears modest. Because Rts3 is induced by GATA factors (Gat1/Gln3), it is likely expressed under nutrient-limiting conditions as well as during starvation. This raises the possibility that Rts3 serves to stabilize or attenuate TORC1 signaling in cells growing under poor nutrient conditions, not just in fully starved cells. Addressing this hypothesis—through discussion or additional experiments—would substantially strengthen the paper. For example, the authors could assess the growth or survival of rts3Δ cells in proline or other poor nitrogen sources could help clarify its physiological role. It would also be interesting to follow up on the argument that Rts3 stabilizes the quiescent state by looking at cell survival over long time periods of starvation in wt and rts3Δ cells. We thank the reviewer for this insightful suggestion regarding the physiological scope of the Rts3 feedback loop. We agree that the GATA-dependent induction of Rts3 suggests it functions to fine- tune TORC1 signaling during growth on poor nitrogen sources, in addition to its role in starvation. To address this, and to replace the less robust regrowth data (as discussed in the response regarding original Fig. S1c below), we performed two new sets of experiments that significantly strengthened our model: 1. Growth on poor nitrogen source: We assessed the growth of rts3Δ and RTS3-overexpressing (RTS3-OE) strains on proline, a poor nitrogen source where uptake is mediated by the Gln3- dependent permease Put4. Consistent with the reviewer’s hypothesis that Rts3 attenuates signaling under these conditions, RTS3-OE cells displayed a mild growth defect on proline, likely due to excessive inhibition of Sit4 and subsequent repression of Gln3-dependent Put4 expression. Conversely, rts3Δ cells exhibited a modest growth advantage, consistent with unrestrained Gln3 activity enhancing proline uptake. These data are now included in the new Figure S2e. 2. Chronological lifespan (CLS) analysis: We assessed cell survival over long-term starvation. As hypothesized, rts3Δ cells displayed significant sensitivity to prolonged nitrogen starvation compared to the wild type. This confirms that Rts3 is critical for the stability and maintenance of the quiescent state. We have added these results to the new Figure S2f and the Discussion. These combined results clarify the physiological role of Rts3: it acts as a rheostat to fine-tune growth on poor nitrogen sources and as a critical \"brake\" to ensure long-term survival during deep quiescence, rather than regulating the kinetics of quiescence exit. We have expanded the Discussion and Results sections to incorporate these findings. 2. Analysis and Interpretation of Rts3’s Impact on Sit4–Sap185 Function. The authors demonstrate that Rts3 inhibits Sit4 activity in vitro and in vivo. However, the core analysis relies heavily on overexpression data in rapamycin-treated cells, where Rts3 is already induced and likely occupies most Sit4–Sap185 binding sites. In contrast, the impact of Rts3 deletion is underexplored. A more detailed presentation and discussion of the rts3Δ proteomic data would clarify the true functional scope of Rts3. To address the functional scope of Rts3 more comprehensively, we performed a global label-free phosphoproteomic analysis of the rts3Δ mutant in parallel with the overexpression and sit4Δ conditions. Upon analyzing the rts3Δ dataset using the same stringent statistical criteria applied to the overexpression dataset (FDR < 0.05, Log2 FC > 1), we observed very few significant changes. - 1 - We attribute this outcome to a fundamental detection asymmetry inherent to the experimental conditions: (i) Overexpression (high signal-to-noise): Blocking Sit4 (RTS3-OE) leads to a massive accumulation of phosphorylation compared to the rapamycin-treated control (where Sit4 is active), resulting in a robust \"gain of signal.\" (ii) Deletion (floor effect): In the rts3Δ mutant, Sit4 becomes hyperactive. However, since Sit4 is already active in the rapamycin-treated control, the dynamic range for further dephosphorylation is compressed. This creates a \"floor effect\" where the loss of residual phosphate groups is often indistinguishable from the limit of detection at a global statistical level. Importantly, despite these statistical limitations, we inspected biologically relevant targets from our network. We found that phosphorylation sites on the ribosome hibernation factor Stm1 (Ser41 and Ser45) displayed clear trends in the expected direction (reduced phosphorylation consistent with Sit4 hyperactivity), supporting our model. To reflect this analysis, we have added the rts3Δ dataset to Supplementary Data 3 and updated the manuscript in three key areas. In the Results, we now explicitly report the rts3Δ profiling alongside the overexpression data, describing the \"floor effect\" to explain the asymmetry in global hits. We further refined the translation subsection to note that while RTS3 overexpression prevents Stm1 dephosphorylation, the rts3Δ mutant displays a trend toward reduced phosphorylation at Ser41/Ser45, consistent with unrestrained Sit4 activity. Finally, we revised the Discussion to explain how this difficulty in detecting the kinetic acceleration of dephosphorylation in the deletion mutant, compared to the blockade imposed by overexpression, reinforces our model of Rts3 as a \"rheostat\" rather than a binary switch. 2.1. Are the changes in phosphorylation upon deletion consistent with simple inhibition, or could Rts3 alter phosphatase specificity or Sit4 binding partner selection? We agree that distinguishing between simple inhibition and altered specificity is crucial. While we cannot rule out subtle allosteric effects, three lines of evidence strongly argue that Rts3 acts primarily as an inhibitor of existing Sit4 complexes rather than a factor that redirects substrate specificity or alters partner selection: (i) If Rts3 altered specificity (directing Sit4 to new targets), we would expect RTS3 overexpression to generate a unique phosphoproteomic signature distinct from the sit4Δ phenotype. Instead, we observed that 79% of Rts3-regulated sites are also regulated by SIT4 deletion (Fig. 5a). This indicates that Rts3 does not generate \"new\" dephosphorylation events; rather, it suppresses a specific subset of canonical Sit4 activities. (ii) Our structural model and mutagenesis data show that Rts3 inserts an a-helix directly into the Sit4 catalytic cleft (Fig. 4d, e). This steric occlusion blocks substrate access to the active site, a mechanism characteristic of competitive inhibition rather than substrate re-selection. (iii) We show that Rts3 binds to the intact Sit4-Sap185/190 holoenzyme (Fig. 4c) rather than displacing the SAP subunits. Since SAPs are the primary determinants of Sit4 specificity, the fact that Rts3 binds the existing complex suggests it functions to \"freeze\" or \"gate\" the activity of these specific holoenzymes, rather than shuffling binding partners to create novel specificities. Therefore, we conclude that Rts3 acts as a \"molecular brake\" on the Sit4-Sap185/190 branch, restricting its activity without fundamentally changing its substrate recognition properties. We have added text in the discussion to address this point. - 2 - 2.2. How do the Rts3-dependent sites not found in the Sit4 delete fit with its mechanism of action? We appreciate the opportunity to clarify the nature of the Rts3-unique phosphosites. While we classify these sites as \"Rts3-dependent but not Sit4-dependent\" based on strict statistical cutoffs, we do not believe they represent a mechanism independent of Sit4. Our conclusion is based on three key points: (i) High Overlap: The vast majority (79%) of Rts3-regulated sites are indeed Sit4- dependent (Fig. 5a), providing the primary evidence for the inhibitory model. (ii) Mutant Controls: Crucially, the Rts33A and Rts13A variants, which are specifically defective in Sit4 binding, fail to confer any rapamycin resistance or 3-AT sensitivity (Figs. 4j and new 5f). If Rts3 were acting on non-Sit4 targets to generate these \"unique\" phosphosites, we would expect the non-binding mutants to retain some functional impact. The fact that they are phenotypically inert strongly implies that all Rts3 outputs, including these sites, stem from the interaction with Sit4. (iii) Technical and Network Factors: The non-overlapping fraction likely arises from two sources: (a) Statistical thresholding, where a site is modulated in sit4Δ but falls just below the significance cutoff while passing it in RTS3-OE, and (b) Network feedback, where the graded \"dimmer-switch\" inhibition by Rts3 triggers distinct compensatory signaling loops compared to the chronic, \"all-or-none\" loss of SIT4. Thus, these sites fit the mechanism of action as downstream consequences of modulating Sit4, rather than evidence of a separate function. To clarify this interpretation, we have added the following text to the Results section: \"The remaining Rts3-specific sites likely reflect indirect feedback or statistical thresholding rather than off-target activity, as Rts3 variants unable to bind Sit4 failed to elicit any detectable phenotypes (Figs. 4j and 5f).\" 2.3. How was statistical significance defined (e.g., FDR correction, cutoffs)? Listing these thresholds would improve clarity and reproducibility. We thank the reviewer for highlighting the need for precise statistical definitions. To ensure reproducibility and clarity, we applied rigorous thresholds for all proteomic datasets. Specifically, significance was defined using a Student’s t-test with a permutation-based False Discovery Rate (FDR) of < 0.05 to correct for multiple hypothesis testing. Furthermore, for the biological stratification of targets (e.g., the Venn diagram in Fig. 5a), we additionally applied a strict fold-change cutoff of > 2 (log2 > 1) to focus on robust regulatory events. We have corrected the legend for Fig. 5a (which previously stated \"p < 0.05\" rather than \"FDR < 0.05\") and updated the Methods section to explicitly list these criteria. 2.4. Additionally, the text indicates that Rts3 binds the Sit4–Sap185 complex in a way that would inhibit its activity, but this is not clearly explained. The authors should specify where the Rts3 helix binds, how this position might block or modify access to substrates, and whether the model predicts simple inhibition versus altered specificity. We thank the reviewer for pointing out the need for greater clarity regarding the structural mechanism. Our model indicates that the Rts3 helix does not merely bind the periphery of the complex but inserts directly into the catalytic groove. Specifically, the model predicts that the Rts3 helix docks into the interface between Sit4 and Sap185, positioning itself directly over the phosphatase active site. To rigorously validate this positioning, we calculated the Hydrogen-bond occupancy over the converged portion (100–300 ns) of our molecular dynamics simulation. This analysis revealed that Rts3 residues Asp77 and Glu73 form transient hydrogen bonds with His238, a strictly conserved residue located directly within the Sit4 active site, with the Asp77 interaction displaying significantly higher stability (Supplementary Figs. 3a and b). This structural arrangement supports a model of simple competitive inhibition via steric occlusion. By - 3 - physically blocking the entry path for substrates and engaging directly with the catalytic center, Rts3 prevents dephosphorylation of canonical targets without creating a new binding surface for novel substrates. We have updated the Results section to explicitly describe this \"steric wedge\" mechanism and included the H-bond occupancy data in new Supplementary Fig. 3. Specific Comments and Minor Revisions 3. Line 48: Should read “A subset of these enzymes interacts with, and are regulated by…” The subject of this sentence is \"A subset\" (singular). Therefore, to maintain subject-verb agreement and consistency with the first verb \"interacts\" (singular), we have retained the singular form \"is regulated by\" rather than changing it to the plural \"are”. 4. Line 90 and Table 1:The statement that Rts3 was “significantly enriched” in rapamycin-treated cells needs clarification. The Fig. legend just restates this fact—please specify how enrichment was determined, including criteria or statistical thresholds used (e.g., fold-change, FDR). We agree that the statement regarding Rts3 enrichment should be supported by quantitative metrics. As detailed in Supplementary Data 1, the enrichment analysis was performed using Student’s t-tests with a permutation-based FDR < 0.05. Under these rigorous criteria, Rts3 emerged as the most significantly enriched interactor, exhibiting a log2 fold-change of 6.53 (approximately 92-fold enrichment) in rapamycin-treated samples compared to log phase samples, and a log2 fold-change of 3.25 (approxiamtely 9.5-fold enrichment) in rapamycin-treated samples compared to control empty beads. We have updated the Fig. 1 legend to include both the statistical definition of significance and the specific fold-change value for Rts3. 5. Promoter analysis section (Fig. 2B–C):The phrase “large-scale promoter annotations and motif analyses (Saccharomyces Genome Database)” is vague. Please clarify which studies or datasets were used and cite the primary literature rather than the database itself.It is also unclear that Gat1 and Gln3 are the primary drivers of RTS3 expression. Fig. 2C suggests additional regulators may contribute, as the induction is only partially blunted in the double mutant. Replotting the data (and that of Fig. 2b) bon a log₂ scale could help visualize dynamic range and clarify this point. We appreciate the reviewer’s suggestions to improve the rigor of the promoter analysis section. (i) Citations: We have replaced the generic reference to \"SGD\" with a citation to the primary large-scale chromatin profiling and motif analysis that underpin these annotations (MacIsaac et al., 2006). (ii) Additional Regulators: We agree that the residual expression in the gln3Δ gat1Δ mutant implies the existence of other regulators. As detailed in Fig. 2c, the deletion of Gln3 and Gat1 reduces RTS3 induction by approximately 70%. While this establishes them as the primary drivers, the remaining ~30% signal suggests contributions from other pathways. As noted in our response to point 15 (reviewers #2/3; below), we have updated the text to explicitly acknowledge this residual expression and the potential for unidentified inputs. (iii) Log2 vs. Linear Scale: We carefully considered replotting the data on a log2 scale. However, we opted to retain the linear (standard) scale because it intuitively conveys the \"switch-like\" dynamics of the induction (from near-zero to high levels). Furthermore, the linear scale clearly demonstrates that removing Gln3/Gat1 abolishes the majority (~70%) of the signal, reinforcing their role as dominant effectors while visibly retaining the residual baseline that the reviewer correctly points out. 6. TurboID dataset: With 764 significant interactors, the current analysis is limited. A more global interpretation—e.g., enrichment of functional categories or pathways—would help contextualize Rts3’s role beyond the specific Sit4-Sap185 and ribosomal interactions highlighted. - 4 - We appreciate the reviewer’s suggestion to provide a broader functional context for the Rts3 proximome. While our initial analysis prioritized the Sit4-Sap185 interaction, we agree that a global interpretation is necessary to fully capture Rts3’s cellular environment. To this end, we refined our analysis of the TurboID dataset, focusing on 381 high-confidence proteins significantly enriched in the Rts3 neighborhood. We performed a Gene Ontology (GO) enrichment analysis on this subset to map the global landscape of Rts3 interactions. This analysis revealed a predominant enrichment of factors involved in translation and ribosome biogenesis, providing independent support for our findings that Rts3 associates with the translation machinery during stress, in addition to its regulation of the Sit4-Sap185 module. To visualize these findings, we performed a structural revision of Fig. 4. We integrated the specific PPase interaction network (formerly Fig. 4b) directly into Fig. 4a to streamline the presentation. This allowed us to introduce a new Fig. 4b displaying a dot plot of the global GO enrichment analysis. We also updated Supplementary Data 2 to clearly list the 381 high-confidence interactors alongside their functional annotations. Finally, we revised the Results section to discuss these global functional categories, specifically highlighting the broad engagement with the translation machinery, before narrowing our focus to the specific phosphatase interactions. 7. Structural model and transition (text around Fig. 4): The rationale for testing Rts3 as an inhibitor is not clear from the preceding description. Please explain how the predicted Rts3-binding site suggests inhibition of Sit4 activity. We agree that the link between the structural model and the hypothesis of inhibition should be explicit. As detailed in our response to the previous comment (regarding the structural mechanism; 2.4.), we have expanded the description of the model to clarify that the Rts3 helix is positioned directly over the catalytic center, acting as a steric wedge. To ensure the rationale for the subsequent experiments is perfectly clear, we have also refined the transition sentence leading into the in vitro assays to explicitly link the structural feature (occlusion) to the experimental test (inhibition). 8. Fig. 5 and phosphoproteomic analysis:As discussed above, the logic of using Rts3 overexpression in rapamycin as the main readout is problematic, since Rts3 is already induced under these conditions. A deletion versus wild-type comparison in rapamycin would provide a cleaner view of Rts3 targets and should be emphasized in the analysis and discussion (referenced in Fig. 5E but not adequately integrated earlier). This comment raises the same concern regarding the phosphoproteomic experimental design (overexpression vs. deletion) as comment 2. As detailed in our response to comment 2 (above), we agree that a deletion analysis is often the gold standard for defining physiological targets. However, our analysis revealed that while rts3Δ results in significant downstream transcriptional and translational deregulation over time (Fig. 5e), the acute phosphoproteomic changes are subtle due to the high basal activity of Sit4 in rapamycin-treated cells. Conversely, overexpression provides a robust inhibitory signal that allows for high-confidence mapping of the direct interaction landscape. As noted in Response 2, we have addressed this by (i) adding the rts3Δ phosphoproteomic dataset to Supplementary Data 3, and (ii) modifying the Results section to explicitly explain the rationale for prioritizing the overexpression dataset for interaction mapping, while acknowledging the deletion data. 9. Physiological relevance: The authors briefly mention a small delay in recovery from quiescence in rts3Δ cells, but this the physiological impact of the Rts3 feedback loop is not analyzed in depth. Further discussion or data addressing nutrient-limiting growth conditions (e.g., poor nitrogen sources) could significantly enhance the impact of the work. As this comment addresses the same physiological scope raised in Point 1, we have addressed them jointly. As detailed in Response 1, we followed the reviewer’s suggestion to analyze growth under nutrient-limiting conditions (proline) and further extended the analysis to long-term survival. We agree that these additions significantly enhance the impact of the work by distinguishing between the fine-tuning of growth on poor nitrogen sources (new Supplementary Fig. S2e) and the critical role of Rts3 in ensuring survival during deep quiescence (new Supplementary Fig. - 5 - S2f). These new data and their interpretation have been integrated into the Results and Discussion sections as described above. Reviewers #2 and #3: Major Comments 1. Rts3 band patterns differ between the Fig.s 2A and 2D, especially at +AA 10 and +AA 60 minutes. Clarification or use of matched blots would improve consistency. We thank the reviewer for this detailed observation regarding the Rts3 band patterns in Figs. 2a and 2d. We agree that visual consistency between panels is important for the interpretation of the data. To address this, we have replaced the immunoblot in Fig. 2a with a representative blot that better matches the exposure and degradation kinetics observed in the wild-type controls of Fig. 2d. However, we would like to offer a brief clarification regarding the inherent challenges in matching these exposures perfectly, which stems from the biological phenotype of the mutants used in Fig. 2d: (i) Difference in Signal Intensity: Fig. 2d analyzes Rts3 stability in temperature-sensitive proteasome mutants (pup1−1 and rpn5−1). In these mutants, particularly rpn5−1, Rts3 is not degraded and accumulates to massively higher levels compared to the wild type (WT). (ii) Exposure Constraints: To resolve the accumulated, phosphorylated, and polyubiquitinated species of Rts3 in the rpn5−1 mutant without saturating the film (which would result in a \"blackout\" of the signal), we are required to use a significantly shorter exposure time for Fig. 2d. Conversely, tracking the rapid physiological degradation of Rts3 in WT cells (Fig. 2a) often requires a longer exposure to visualize the residual protein at the 10- and 20- minute time points. To illustrate this technical constraint, we have explicitly included a shorter exposure crop for the rpn5−1 data in Fig. 2d. This highlights the dramatic difference in protein abundance and explains why the WT bands in that specific context may appear fainter or display slightly different kinetics compared to a standard degradation assay like Fig. 2a. We believe the revised Fig. 2a, combined with this clarification, provides a consistent and accurate representation of Rts3 dynamics 2. The slower-migrating forms of Rts3 appears only in rpn5-1 (and with MG-132) but not in pup1-1. In addition, the +AA 60 band in pup1-1 resembles wt. This inconsistency should be addressed. We appreciate the reviewer’s careful inspection of the Western blot patterns. We agree that the \"slower-migrating\" phosphorylated species is clearly visible in rpn5-1 mutants and MG-132 treated cells, but largely absent in pup1-1 cells. We attribute this to the difference in the strength of proteasome inhibition. This is internally validated by the anti-ubiquitin immunoblots (Fig. 2d), which show that rpn5-1 and MG-132 treatment lead to a robust and rapid accumulation of polyubiquitinated proteins (with rpn5-1 already showing elevated basal levels), whereas the pup1-1 mutant exhibits a marked delay in ubiquitin accumulation. Consistent with this \"weaker/delayed\" block, pup1-1 is sufficient to slow bulk Rts3 turnover but retains enough residual activity to clear the specific phosphorylated intermediate. In contrast, the stringent blockade imposed by rpn5-1 or MG-132 allows this intermediate to accumulate to detectable levels. We have updated the text to explicitly link the Rts3 phenotype to this difference in proteasomal efficiency. To conclusively validate this interpretation and define the molecular mechanism, we extended our analysis to map the specific phosphodegron controlling this process. We identified that a single point mutation at Ser111 (S111A) is sufficient to fully stabilize Rts3 during amino acid refeeding. Crucially, this stabilized Rts3S111A mutant migrates exclusively as the faster species and lacks the slower-migrating isoform observed in the proteasome mutants. This genetic evidence confirms that the \"upper band\" noted by the reviewer is indeed the specific, phosphorylated transition state required for SCFCdc4-mediated degradation. We have integrated these findings into the Results section and updated Fig. 2i to showcase the stabilization of the Rts3S111A mutant. - 6 - 3. Including TOR1-1 cells in Fig. 2E would demonstrate that the mobility shift is TORC1-dependent rather than an artifact of rapamycin exposure. We thank the reviewer for this excellent suggestion. To rule out any potential off-target effects of rapamycin, we monitored Rts3 degradation in cells expressing the rapamycin-resistant TOR1-1 allele. We performed the refeeding experiment in TOR1-1 cells in the presence of rapamycin. As expected, while rapamycin stabilized Rts3 in wild-type cells by inhibiting TORC1, it failed to do so in TOR1-1 cells. In this background, Rts3 was rapidly degraded, behaving exactly like the untreated control. This confirms that the stabilization observed in wild-type cells is indeed due to the specific inhibition of TORC1 activity and not an artifact of the drug. We have included these data as new Fig. 2g in the revised manuscript. 4. Ubiquitinated-protein blots differ between Fig.s 2D and 2F and should be more comparable. We assume the reviewer is referring to the comparison between Fig. 2d and Fig. 2e, as Fig. 2f does not contain an anti-ubiquitin immunoblot. We appreciate the reviewer pointing out this inconsistency. We have addressed this concern through both a technical correction to the Fig. and a clarification of the biological context: (i) Technical Correction (Fig. 2e replacement): We recognized that the anti-ubiquitin blot originally presented in Fig. 2e was overexposed. This resulted in visible high-molecular- weight smears even in the vehicle-treated control samples, creating an apparent discrepancy with the cleaner control lanes in Fig. 2d. To resolve this, we have replaced the anti-ubiquitin blot in Fig. 2e with a shorter exposure of the same experiment. In this revised panel, the control samples now show negligible accumulation of ubiquitinated proteins, making the baselines in Fig. 2d and 2e fully comparable. (ii) Biological Context: With the controls now consistent, the remaining differences in the experimental lanes reflect the specific \"strength\" of the proteasomal blockade. Fig. 2d compares pup1-1 (a leaky/hypomorphic 20S allele) with rpn5-1 (a tight 19S allele). Consequently, ubiquitin accumulation is delayed/moderate in pup1-1 but massive in rpn5-1. The robust accumulation seen in Fig. 2e (MG-132 treatment) mirrors the strong blockade of rpn5-1 rather than the partial phenotype of pup1-1. We believe the replacement of the blot in Fig. 2e, combined with this explanation, ensures the data are visually consistent and biologically accurate. 5. More methodological detail on the kinase assay should be added in the main text and Fig. legend, and the authors may wish to comment on the reason why they used wortmannin instead of rapamycin as in the rest of the manuscript for the same purpose. We appreciate the reviewer’s request for clarification regarding the inhibitor choice. We have updated the manuscript to include the specific experimental parameters of the kinase assay. Regarding the use of wortmannin: Rapamycin is an allosteric inhibitor that strictly requires the immunophilin cofactor FKBP12 (Fpr1 in yeast) to bind the TORC1 FRB domain. Since Fpr1 is not a stable subunit of the purified TORC1 complex, rapamycin is ineffective in this purified system. Therefore, we used wortmannin, which has been established as a direct inhibitor of the TORC1 catalytic domain in the absence of FKBP12 (Brunn et al., 1996). We expanded the description in the Results section to specify the purification sources and reaction conditions. We updated the Methods to explicitly state that wortmannin was used to inhibit TORC1 activity as previously described (citing Brunn et al., 1996), noting that the absence of FKBP12 prevents the use of rapamycin in this assay. 6. Including described Rts3 interactors as control in Fig. 3A would confirm that the absence of interaction with Tpd3 and Pph21/22 is not due to low Rts3 abundance. We agree that confirming the abundance and functionality of the Rts3 bait is essential. We believe this control is provided by the combination of Fig. 3a and Fig. 4c: - 7 - a. Abundance: The anti-GFP blot in Fig. 3a (IP lanes) explicitly demonstrates that GFP-Rts3 was immunoprecipitated at high levels, comparable to the positive controls (Rts1 and Cdc55). This directly rules out the possibility that the absence of Tpd3/Pph21/22 co- purification is due to insufficient bait protein on the beads. b. Functionality: We show in Fig. 4c that the exact same GFP-Rts3 construct, under rapamycin-treated conditions, robustly co-immunoprecipitates Sit4, Sap185, and Sap190. To address the reviewer’s concern without disrupting the sequential Fig. numbering in the manuscript, we have updated the text to explicitly highlight the efficient immunoprecipitation shown in Fig. 3a and textually reference the functional binding described in the subsequent section. 7. The experimental procedure for Fig. 4c requires further explanation. The Rts3-3A mutant shows differential loss of interaction with Sit4, Sap185 (clear decrease) compared with Sap190 (not so clear decrease); this difference should be addressed and clarified. We agree that the differential impact of the Rts33A mutation on Sap185 versus Sap190 binding warrants further explanation. We verify that the Rts33A mutations (R65A, E73A, D77A) target residues specifically required for anchoring Rts3 to the Sit4 catalytic cleft. Since Sit4 is the common catalytic subunit in both Sap185 and Sap190 complexes, one might expect an identical loss of binding if the interaction were solely mediated by Sit4. However, we observe that while Rts33A loses binding to the Sit4-Sap185 complex, it retains significant binding to the Sit4-Sap190 complex. This differential effect suggests that the Sit4-Sap190 complex possesses additional structural determinants, likely direct contacts between Rts3 and Sap190, that are absent in the Sit4-Sap185 complex. These \"secondary\" contacts in Sap190 appear sufficient to tether Rts3 to the complex even when the primary \"catalytic cleft\" anchor (mediated by the 3A residues) is disrupted. Importantly, despite this physical retention, the Rts33A mutant is functionally dead (Fig. 4j and new Fig.5f), confirming that the specific engagement with the Sit4 active site is the critical inhibitory mechanism. To clarify this distinction, we have added the following text to the Results section: \"Since the Rts33A mutation disrupts the Sit4 interface (common to both complexes), the residual binding to Sap190 suggests that Rts3 maintains secondary, Sap190-specific contacts that stabilize the complex to some extent even when the primary active-site anchor is compromised.\" 8. The manuscript uses 4, 5 and 10 ng/ml rapamycin in different assays. A brief justification would help. Growth differences between Fig. 4J (5 ng/ml) and Fig. 5G (10 ng/ml) should be clarified. In Fig. 4J first spot in rapamycin plate is growing weakly at 5ng/ml but in Fig. 5G at 10ng/ml authors present better growth. We thank the reviewer for identifying the different rapamycin concentrations. As noted, yeast cells are significantly more sensitive to rapamycin in synthetic defined (SD) media than in rich (YPD) media. Therefore, we empirically titrated the concentrations for each assay to optimize the dynamic range: a. Fig. 4j (SD-Ura): We used 5 ng/mL because cells are hypersensitive in synthetic selection media. b. Fig. 5g (YPD): We used 10 ng/mL because cells in rich media are more robust, requiring a higher dose to clearly distinguish the rescue phenotypes of suppressor mutants. We have added a clarifying sentence to the Methods section specifying that rapamycin concentrations were adjusted according to the media composition. - 8 - 9. The phenotype observed on 3-AT plates in Fig. 5F is quite subtle. Including a control strain to verify that the 3-AT assay is working effectively would support the conclusion. The authors may also wish to adjust the wording accordingly. We thank the reviewer for this constructive suggestion. We agree that the phenotype of the wild- type RTS3 overexpression strain on 3-AT is subtle. To rigorously verify the effectiveness of the assay and the specificity of the observed phenotype, we have updated Fig. 5f to include a gcn4Δ strain as a positive control for 3-AT sensitivity. As expected, the gcn4Δ mutant is unable to grow on this medium, confirming that the assay conditions effectively monitor Gcn4-dependent readouts. Furthermore, we assessed cells overexpressing the Sit4-binding defective variants rts33A and rts313A. Unlike the wild-type RTS3 overexpression, neither of these variants caused sensitivity to 3- AT. This crucial control demonstrates that the dampening of the GAAC pathway is not an artifact of overexpression, but strictly depends on the ability of Rts3 to engage and inhibit the Sit4 phosphatase. We have adjusted the text and Fig. 5f accordingly. 10. The genetic logic may not be intuitive to general readers. A more detailed explanation will benefit the manuscript. Authors could consider to use an additional experimental approach to show the same, which would strengthen the conclusion. We appreciate the reviewer’s suggestion to improve the clarity of the genetic analysis. We interpret this comment as referring to the epistasis experiments in Fig. 5g, where the \"rescue\" of rts3Δ sensitivity by deletion of SIT4 or GLN3 relies on the logic of relieving pathway hyperactivation.To address this, we did the following. a. Clarified logic: We have expanded the text in the Results section to explicitly articulate the logical premise: if the sensitivity of rts3Δ is caused by unrestrained (toxic) Sit4 activity, then removing Sit4 should cure the sensitivity. b. Complementary Approach: Regarding the request for an additional approach, we highlight that we have effectively performed the reciprocal \"gain-of-function\" experiment in Fig. 3b. There, we show that RTS3 overexpression confers rapamycin resistance, the exact inverse of the deletion phenotype. Together, these two genetic approaches, loss-of-function causing sensitivity (rescued by downstream deletions) and gain-of-function causing resistance, provide robust, orthogonal evidence that Rts3 functions as a negative regulator. 11. In the Discussion, the statement that Rts3 “counteracts TORC1-dependent phosphorylation of the hibernation factor Stm1 that balances ribosome homeostasis” implies enhanced Stm1 dephosphorylation, which seems at odds with the model in which Rts3 inhibits Sit4, the phosphatase expected to act on Stm1. This apparent contradiction should be addressed, unless this reviewer misunderstood. We thank the reviewer for catching this apparent contradiction. Indeed, the statement that Rts3 \"counteracts TORC1-dependent phosphorylation\" was semantically imprecise and inadvertently implied that Rts3 promotes dephosphorylation. This contradicts our established model (and phosphoproteomic data) where Rts3 acts as an inhibitor of Sit4. Mechanistically, Sit4 is responsible for removing the inhibitory phosphates from Stm1. By inhibiting Sit4, Rts3 prevents this dephosphorylation, thereby preserving the phosphorylated species (or slowing its turnover). We have corrected the Discussion text to accurately reflect this mechanism. Minor Comments 12. Strain names should be included in the Fig. legends to improve clarity of the experimental details. We appreciate the reviewer’s concern for clarity and reproducibility. We agree that knowing the exact genetic background is essential for every experiment. However, inserting specific laboratory strain identifiers (e.g., \"MP6172\", \"YL515\") directly into the Fig. legends would significantly disrupt the flow and readability of the text. To ensure rigorous traceability without - 9 - compromising clarity, we have provided a comprehensive list of all strains, including their exact genotypes and the specific Fig. panels in which they are used, in Supplementary Table 1. This approach allows readers to immediately identify the biological context (e.g., rts3Δ, WT) in the Fig. legends while easily retrieving the precise technical details from the comprehensive table, consistent with Nature Communications standards for data presentation. 13. As Fig. 1B supports the proposed negative feedback loop, explicitly referring back to it when this mechanism is discussed later in the text would help the reader. We agree that explicitly linking the initial discovery (Fig. 1b) to the final mechanistic model helps close the narrative loop for the reader. Fig. 1b provides the unbiased proteomic evidence that Rts3 is robustly enriched in the phosphatase interactome upon TORC1 inhibition. This enrichment is the direct consequence of the Gln3/Gat1-mediated induction described in our feedback model. We have added a cross-reference to Fig. 1b in the Discussion section, specifically where the transcriptional induction component of the feedback loop is described. 14. Page 4, line 113 onwards: a more detailed explanation would help readers follow Fig. 1C. In addition, it may be worth reconsidering whether the term 'genetic analysis' is the most appropriate description in this context. We appreciate the reviewer’s suggestion to improve the clarity of the initial results section. a. Explanation of Fig. 1c: We agree that the description of the protein interaction network was too brief. We have added a sentence to the Results section to explicitly explain that Fig. 1c represents a STRING-based network visualization, which serves to highlight the recovery of intact, distinct phosphatase holoenzymes (rather than just isolated subunits) in our screen. b. Terminology (\"Genetic Analysis\"): We agree that the term \"genetic analysis\" (used to describe the identification of Gln3/Gat1) is imprecise in this context, as it implies a forward genetic screen rather than the testing of specific candidates derived from promoter analysis. We have replaced this term with \"targeted deletion analysis\" to accurately reflect the experimental approach. 15. Fig. 2C: as residual RTS3 expression persists in gat1 gln3 deleted cells, the authors may wish to discuss additional pathways that could contribute to RTS3 expression. We agree that the residual RTS3 expression observed in the gln3Δ gat1Δ double mutant (Fig. 2c) indicates that other factors may contribute to its regulation, likely maintaining basal levels or providing minor inputs. To address this, we systematically tested the most prominent candidates predicted by promoter motif analysis, including Gcn4 (General Amino Acid Control), Rtg3 (Retrograde signaling), and Msn2/4/Gis1 (General Stress Response), but found that their deletion did not significantly alter RTS3 profiles (Fig. 2c). Consequently, while we cannot identify the specific source of this residual expression, we conclude that it is independent of these major stress pathways. We have updated the Results section to explicitly acknowledge this residual expression and the possibility of secondary, unidentified regulatory inputs. 16. Fig. 3B: showing Rts3 levels expressed from the endogenous promoter and from ADH1 promoter could help define the expression threshold above which cells become rapamycin-insensitive. We appreciate this insightful suggestion. Defining the protein abundance relative to the observed phenotype adds important context to the genetic data. As requested, we have updated Fig. 3b to include immunoblots for GFP-Rts3 (and Adh1/2 loading controls) directly alongside the spot growth assays. These blots confirm that expression from the ADH1 promoter results in substantially higher protein levels (in exponentially growing cells) compared to the endogenous promoter. This direct comparison clarifies that the rapamycin-resistance phenotype is strictly dosage-dependent, requiring Rts3 accumulation well above physiological levels to effectively antagonize TORC1 inhibition. - 10 - 17. Fig. 3D: larger crops of cells would improve visibility of the phenotypes shown. We agree that larger crops significantly enhance the visibility of the subcellular localization patterns. Accordingly, we have updated Fig. 3d to include magnified insets for each condition. These insets show the regions marked by white dotted squares in the merged panels, providing a clearer and more detailed view of the cytoplasmic-to-nuclear transition of Rts3. 18. Fig. 4E: some residues are difficult to see; alternative colouring may enhance clarity. To enhance clarity, we have revised Figs. 4e and 4f by adding a white background behind the amino acid labels, ensuring that the residue numbers remain clearly legible against the structural features. 19. Page 34, line 897 (Fig. 4): please clarify why “not shown”. We apologize for the lack of clarity. We originally used the phrase \"not shown\" because Fig. 4e presents a static structural model, which made it impossible to visualize the dynamic and alternating nature of the hydrogen bonds involving the catalytic residue His238. To address this limitation and provide quantitative evidence, we performed a hydrogen-bond occupancy analysis over the converged trajectory of our MD simulation. This analysis reveals that His238 forms transient hydrogen bonds primarily with Asp77, and less frequently with Glu73, confirming that these residues dynamically engage the active site. We have included this quantitative data as Supplementary Figs. 3a and b and have updated the manuscript text to reference this figure instead of stating \"not shown.\" 20. Page 34, line 912 (Fig. 4): clarify whether expression was tested in asynchronously growing WT cells. We confirm that the immunoblot analysis presented in Fig. 4j (lower panel) was performed using lysates from asynchronously growing cells (exponential phase). This control was included to verify that WT and mutant Rts3 variants are overexpressed to comparable levels under standard growth conditions, before stress assays. We have updated the legend of Fig. 4j to explicitly state that protein expression was assessed in \"asynchronously growing cells,\" ensuring the experimental context is unambiguous. 21. Page 8, line 211: additional detail on the phosphatase assay should be added to the main text. We agree that providing specific experimental parameters in the main text improves clarity and reproducibility. We have expanded the description of the in vitro phosphatase assay in the Results section to explicitly state the source of the protein components (immunopurified Sit4 vs. recombinant Rts3) and the identity of the substrate used. We have revised the relevant paragraph in the Results section to include these technical details. The text now reads: “…we incubated HA-Sit4 (immunopurified from yeast) with increasing concentrations of recombinant His -Rts3 (purified from E. coli) and assessed phosphatase activity 6 against the synthetic phosphopeptide substrate KRpTIRR.” 22. Editorial Points Page 49: rephrase “Tip1-mediated Tap42 sequestering”. Line 229: “2720” rather than “2’720”. Line 236: clarify the meaning of “network-level dissection”. Line 242: specify the protein in which Ser41 and Ser45 are affected. Line 254: clarify “shared Sit4- and Rts3-regulated nodes” for readers unfamiliar with STRING. Line 271: clarify “permease regulatory”. Line 280: rephrase the “dual-mode regulation–feedforward induction” sentence. Line 807: correct “declaration od”. - 11 - We have amended the manuscript to incorporate all listed editorial corrections, clarifications, and rephrasings Reviewer #4: Major Comments 1. The authors claim that Rts3 is a direct substrate of TORC1 by performing an in vitro kinase assay (Fig. 2G). Have the authors confirmed the physical interaction between TORC1 and Rts3, which would further support their claim? We thank the reviewer for this insightful comment. We agree that demonstrating a physical interaction between TORC1 and Rts3 significantly strengthens the conclusion that Rts3 is a direct substrate. Capturing this interaction is inherently challenging for two reasons. First, as shown in Fig. 2, the interaction triggers immediate phosphorylation and degradation of Rts3. Second, kinase-substrate interactions are typically transient ('kiss-and-run') and sensitive to the lysis and washing steps required for Co-IP. Even when protein levels are stabilized, the physical complex often dissociates during purification. To address the reviewer’s request, we therefore chose the Yeast Two-Hybrid (Y2H) system. This assay detects interactions in vivo, avoiding the disruption caused by cell lysis, and its genetic readout (growth) allows for the accumulation of signal from transient binding events. By combining this sensitive assay with the proteasome inhibitor MG-132 to prevent substrate turnover, we were able to capture the specific physical interaction between the TORC1 subunit Tco89 and Rts3 (Supplementary Fig. 1). This result, combined with the in vitro kinase assay (Fig. 2h), provides compelling evidence that Rts3 physically associates with the TORC1 complex and is a direct substrate. 2. In Fig. 3B, the authors shows that the overexpression of Rts3 from ATD promoter confers rapamycin resistance on budding yeast cells. Since this experiment relies on the Rts3 overexpression, the observed rapamycin resistance might not reflect Rts3-mediated inhibition of Sit4, but could instead be an artifact of overexpression. To rule out this possibility, the same experiment should be performed using sit4 deletion mutant cells, in which rapamycin resistance would not be expected. We followed the reviewer's suggestion and performed the experiment in a sit4Δ background. As predicted, the rapamycin resistance conferred by RTS3 overexpression was completely abolished in the absence of SIT4, confirming that Rts3 acts through the phosphatase (new Figure 4j). Importantly, we observed that the sit4Δ mutant itself was not rapamycin resistant and behaved like WT. This result aligns with previous work (Jablonowski et al., 2009) showing that rapamycin resistance is a phenotype specific to the loss of the Sap185/190 regulatory subunits, whereas the combined loss of Sap4/155 or the catalytic subunit Sit4 does not confer resistance. Therefore, the fact that RTS3 overexpression confers resistance strongly argues that it is not a generic overexpression artifact or a global inhibitor of Sit4 (which would phenocopy sit4Δ). Instead, Rts3 functions as a specific functional phenocopy of the sap185Δ sap190Δ deletion, consistent with our physical data showing Rts3 binds the Sit4-Sap185/190 complex.We have updated the Results section to include these findings in new Figure 4j. 3. The authors validated the interaction model of Sit4 and Rts3 obtained from MD simulations by co-immunoprecipitation assays with alanine mutants of Rts3 (Fig. 4C, E and F). On the other hand, the importance of Sit4 residues R266, Y263, and Y124, which have been proposed to interact with Rts3, has not been experimentally validated. It would be valuable to assess the significance of these residues using co-immunoprecipitation (co-IP) with alanine-substituted Sit4 mutants. We thank the reviewer for this suggestion and attempted to validate the interface from the Sit4 side by generating the requested alanine substitutions (R266A, Y263A, and Y124A). However, strains expressing these Sit4 variants from CEN/ARS plasmids were extremely sick and could not be analyzed reproducibly in our signaling assays, as noted above. Based on our structural model, - 12 - these residues lie within the catalytic center of Sit4 (Fig. 4e), and their mutation is therefore likely to alter overall phosphatase activity rather than selectively affect the interaction with Rts3. As a result, the observed phenotypes are difficult to interpret in terms of interface specificity. In contrast, the Rts3 mutants, shown in Fig. 4c, 4h, 4j, and 5f, selectively perturb the interaction while preserving Sit4 catalytic function, and we therefore consider them to provide the most informative validation of the interface. 4. In Fig. S1C, the growth delay observed in rts3∆ and GFP-RTS3-OE cells may not necessarily reflect a slower recovery from nitrogen starvation compared to wild-type cells, but could instead be due to an overall slower growth rate. This possibility could be addressed by examining growth curves using cells in logarithmic phase. We thank the reviewer for this insightful observation. Prompted by this suggestion, we performed a comprehensive re-evaluation of both logarithmic growth rates and post-starvation recovery kinetics with increased biological replicates. Upon this rigorous side-by-side comparison, we found that the differences in regrowth kinetics between the wild-type and rts3Δ or RTS3-OE strains were not statistically robust when fully normalized against logarithmic growth rates.To ensure the highest degree of accuracy and reproducibility, we have removed the claims regarding \"delayed regrowth\" from the revised manuscript. However, this re-evaluation was extremely valuable as it redirected our focus toward the stability of the quiescent state rather than the kinetics of exit. As detailed in our response to Point 1 of reviewer 1 and incorporated into the revised text: • We found that Rts3 is critical for long-term survival during starvation. New chronological lifespan (CLS) assays show that rts3Δ cells exhibit significantly reduced viability over time. • We identified a role for Rts3 in fine-tuning growth on poor nitrogen sources. We now show that Rts3 overexpression causes a growth defect on proline (likely via Sit4 inhibition), whereas rts3Δ cells show a modest advantage. We believe these new data (now presented in Supplementary Fig. 2e and 2f) provide a more robust and physiologically relevant definition of Rts3 function - specifically, that it acts as a \"brake\" to prevent excessive metabolic commitment during scarcity and ensure survival, rather than regulating the speed of recovery. 5. In the polysome analysis shown in Fig. S1D, no statistically significant difference was observed between wild-type and rts3∆ cells. Moreover, although the difference between wild-type and GFP- Rts3-OE cells is statistically significant, it is rather small, as noted by the authors. Nevertheless, as shown in Fig. S1C, both rts3∆ and GFP-Rts3-OE cells exhibit a similar delay in recovery from nitrogen starvation compared to wild-type cells. Therefore, I think that the authors’ conclusion ‘Together, these results confirm that Rts3 associates and constrains Sit4 on hibernating ribosomes, allowing efficient recovery from prolonged starvation, thus emphasizing its physiological relevance (lines 249-251)’ is not supported by the data. We thank the reviewer for this careful observation. We agree that the differences in the polysome profiles (Fig. S2c) are subtle and do not, on their own, fully explain the recovery defects previously observed. However, we believe the physiological relevance of the Rts3-Sit4 interaction on ribosomes is supported by the phosphoproteomic state of the hibernation factor Stm1, rather than the global stability of the 80S complex. (i) Stm1 Phosphorylation: As shown in our phosphoproteomics dataset (Supplementary Data 3) and discussed in the text, Stm1 phosphorylation (specifically Ser41 and Ser45) is sensitive to Rts3 levels. (ii) The \"Rheostat\" Mechanism: In rts3Δ cells, Sit4 is unrestrained, leading to a trend of Stm1 dephosphorylation. In RTS3-OE cells, Sit4 is blocked, preventing Stm1 dephosphorylation. (iii) Phenotypic Outcome: We propose that both extremes, hyperactive dephosphorylation (rts3Δ) and blocked dephosphorylation (RTS3-OE), disrupt the precise timing required for efficient exit from quiescence. - 13 - The fact that the 80S peak remains stable in rts3Δ cells (unlike in stm1Δ cells where it collapses) indicates that Rts3 is not a structural component required for ribosome assembly, but a regulator that \"fine-tunes\" the signaling state of the hibernation complex. To address the reviewer’s concern and avoid overstating the polysome data, we have revised the concluding sentence to be more precise: Revised Text: \"Together, these results confirm that Rts3 associates with hibernating ribosomes and regulates the phosphorylation status of the hibernation factor Stm1. This suggests that Rts3 fine-tunes Sit4 activity on ribosomes to ensure efficient recovery from prolonged starvation.\" Minor points 6. In the input samples of Fig. 4C, a strong non-specific band is observed in addition to GFP–Rts3, whereas no such band appears in Fig. 4A. What accounts for this discrepancy? We assume the reviewer is referring to Fig. 3a, as Fig. 4a presents mass spectrometry data. We note that an additional band is visible in the Input of Fig. 4c that is not observed in Fig. 3a. While the precise origin of this band cannot be definitively assigned, several experimental differences between these figures should be considered. Although both experiments were performed using native cell lysis, the buffer compositions differed between Fig. 3a and Fig. 4c, which can influence background signals in immunoblot analyses. In addition, the treatment conditions were not identical: Fig. 3a shows samples treated with rapamycin alone, whereas Fig. 4c includes a combination of rapamycin treatment and nitrogen starvation. Finally, the immunodetection strategies differed between the two experiments. In Fig. 4c, light chain-specific secondary antibodies were used for immunoblot detection (see Supplementary Table 1), minimizing interference from IgG heavy chains (~50 kDa) and improving specificity of the co- immunoprecipitation signals. This detail has now been explicitly stated in the legend of Fig. 4c. In contrast, Fig. 3a employed GFP-Trap-based detection, for which light chain-specific secondary antibodies were not required. Together, these experimental differences provide a plausible explanation for the appearance of the additional band in Fig. 4c. 7. part of the immunoblotting image in Fig. 4C (right side) appears to be missing. We appreciate the reviewer’s careful observation, and the complete immunoblot for Fig. 4C is now shown. 8. In Fig. 4E and F, the red numbering of the amino acid residues overlaps with the structure colored in magenta, making it difficult to distinguish. To enhance clarity, we have revised Figs. 4e and 4f by adding a white background behind the amino acid labels. This ensures that the residue numbers are clearly legible against the structural details 9. Statistical analysis should be performed for Fig. 4H. We have updated Fig. 4h to indicate statistical significance (using asterisks) for comparisons between HA-Sit4 without inhibitor and HA-Sit4 in the presence of wild-type or mutant Rts3. Accordingly, the Fig. legend has been revised to specify the statistical test and significance thresholds (n=3, ±SD; unpaired two-tailed t-test vs. HA-Sit4 without inhibitor; *p < 0.05, **p ≤ 0.01, ***p ≤ 0.001, ****p ≤ 0.0001). 10. In line 125, ‘In’ should not be capitalized This typographical issue has now been addressed. - 14 - Response to Reviewer Comment Reviewer Comment: “Suggest that the authors spend a bit more time editing the discussion as some of the english still reads like a draft. For example, three sentences in lines 364 to 372 start with the word crucially, and the flow in this section could be improved (sentence to sentence linkages etc).” Response: We thank the reviewer for this helpful observation. We have carefully revised the Discussion section to improve the narrative flow and sentence-to-sentence linkages. Specifically, we have removed the repetitive use of the word \"Crucially\" in the indicated paragraph and replaced it with more varied logical connectors (e.g., \"Importantly,\" \"Furthermore,\" \"In this context\"). Additionally, we conducted a thorough stylistic polish of the surrounding text to remove draft-like phrasing (such as \"The fact that...\") and ensure the argument flows cohesively from the molecular mechanisms to the biological phenotypes. We believe these changes have significantly improved the readability and professional tone of the section."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors did an excellent job of revising the manuscript to address all of the reviewers comments. I am happy with the paper, and have no more major concerns, but suggest that the authors spend a bit more time editing the discussion as some of the english still reads like a draft. For example, three sentences in lines 364 to 372 start with the word crucially, and the flow in this section could be improved (sentence to sentence linkages etc).", "reviewer_2": "I have reviewed the revised version of the manuscript. The authors have adequately addressed the comments and suggestions raised in the previous review, and the revisions have improved the overall clarity and coherence of the work. The manuscript is now methodologically sound and clearly presented. I have no further major concerns and consider it suitable for publication in its current form. In addition, I would like to note two minor typographical errors in the Supplementary section that should be corrected before publication. In both cases, the word Supplementary is misspelled (missing the letter “n”): “Supplementary information contains Supplemetary Figures 1–3 and Supplementary Table 1 and can be found online at https://nn.” “Supplementary files contain Supplemetary Data 1–4 and can be found online at https://nn.” I would kindly ask the authors to correct these minor typographical errors to ensure consistency and accuracy in the Supplementary materials.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_4": "The authors have appropriately addressed my comments and concerns in the revised version of the manuscript. The paper has been substantially improved, and I have no further major issues to raise. In my view, the manuscript is now suitable for publication."}, "author_response": "Response to Reviewer Comment Reviewer Comment: “Suggest that the authors spend a bit more time editing the discussion as some of the english still reads like a draft. For example, three sentences in lines 364 to 372 start with the word crucially, and the flow in this section could be improved (sentence to sentence linkages etc).” Response: We thank the reviewer for this helpful observation. We have carefully revised the Discussion section to improve the narrative flow and sentence-to-sentence linkages. Specifically, we have removed the repetitive use of the word \"Crucially\" in the indicated paragraph and replaced it with more varied logical connectors (e.g., \"Importantly,\" \"Furthermore,\" \"In this context\"). Additionally, we conducted a thorough stylistic polish of the surrounding text to remove draft-like phrasing (such as \"The fact that...\") and ensure the argument flows cohesively from the molecular mechanisms to the biological phenotypes. We believe these changes have significantly improved the readability and professional tone of the section."}]

Decision letter