Author response: Adaptation to glucose starvation is associated with molecular reorganization of the circadian clock in Neurospora crassa

Abstract

Article Figures and data Abstract Editor's evaluation Introduction Results Discussion Materials and methods Data availability References Decision letter Author response Article and author information Metrics Abstract The circadian clock governs rhythmic cellular functions by driving the expression of a substantial fraction of the genome and thereby significantly contributes to the adaptation to changing environmental conditions. Using the circadian model organism Neurospora crassa, we show that molecular timekeeping is robust even under severe limitation of carbon sources, however, stoichiometry, phosphorylation and subcellular distribution of the key clock components display drastic alterations. Protein kinase A, protein phosphatase 2 A and glycogen synthase kinase are involved in the molecular reorganization of the clock. RNA-seq analysis reveals that the transcriptomic response of metabolism to starvation is highly dependent on the positive clock component WC-1. Moreover, our molecular and phenotypic data indicate that a functional clock facilitates recovery from starvation. We suggest that the molecular clock is a flexible network that allows the organism to maintain rhythmic physiology and preserve fitness even under long-term nutritional stress. Editor's evaluation This manuscript is of interest to researchers working in the areas of chronobiology, metabolism, or environmental adaptation mechanisms. The authors show that starvation decreases the abundance of the fungal circadian clock component white collar complex (WCC). However, neither phase nor the amplitude of the RNA oscillation of the critical circadian clock gene frq are affected by starvation, indicating a mechanism that recalibrates the central clockwork. Furthermore, Neurospora recovers faster from starvation in the presence of a functioning clock, adding further evidence for the importance of the circadian clock for organismal fitness. https://doi.org/10.7554/eLife.79765.sa0 Decision letter Reviews on Sciety eLife's review process Introduction Circadian clocks are endogenous timekeeping systems allowing organisms to adapt to cyclic changes in the environment. Circadian clocks rely on transcriptional-translational feedback loops (TTFL) in which positive elements of the machinery activate the expression of oscillator proteins which in turn negatively feed back on their own transcription. Circadian clocks are closely linked to metabolism. On the one hand, the clock rhythmically modulates many metabolic pathways (Asher and Schibler, 2011; Huang et al., 2011; Bray and Young, 2011; Duez and Staels, 2009), and on the other hand, nutrients and metabolic cues influence clock function (e.g. Roenneberg and Rehman, 1996; Johnson, 1992; Stokkan et al., 2001). It is therefore not surprising that in human, conditions involving circadian rhythm dysfunction, such as shift work or jetlag, are associated with an increased risk of metabolic disorders including obesity, metabolic syndrome and type 2 diabetes (Baron and Reid, 2014). Although the timing of nutrient availability as an important Zeitgeber determines the phase of the rhythm in many organisms, the circadian oscillator was found to run with constant speed and thus to maintain a constant period in the model organisms Neurospora crassa and Synechococcus elongatus (Sancar et al., 2012; Johnson and Egli, 2014). Accurate synchronization of metabolic processes with recurrent environmental conditions, such as light-darkness or temperature fluctuations, may be particularly critical for efficient adaptation to nutrient deprivation. However, because glucose levels were shown to affect many signal transduction pathways as well as transcription and translation rates in different organisms (Ashe et al., 2000; Corral-Ramos et al., 2021; Jona et al., 2000; Sancar et al., 2012), glucose deficiency may challenge the TTFL-based circadian clock to operate at a constant period. Molecular mechanisms of nutrient compensation have been intensively investigated in Neurospora crassa. In Neurospora the White-Collar-Complex (WCC) composed of the GATA-type transcription factors WC-1 and WC-2, and Frequency (FRQ) represent the core components of the circadian clock. The WCC supports expression of FRQ which then interacts with an RNA helicase (FRH) and the casein kinase 1a (CK1a) (Cheng et al., 2005; Görl et al., 2001). The FRQ-FRH-CK1a complex acting as the negative factor of the clock facilitates phosphorylation and thus inhibition of the WCC. During a circadian day FRQ is progressively phosphorylated, which reduces its inhibitory potential and leads to its degradation (Querfurth et al., 2011). The negative feedback and the gradual maturation of FRQ together result in rhythmic changes of WCC activity and frq levels (Larrondo et al., 2015; Querfurth et al., 2011; Schafmeier et al., 2006). The negative feedback loop is connected to a positive loop, in which FRQ supports the accumulation of both WC-1 and WC-2 (Cheng et al., 2001; Lee et al., 2000). Similarly to other organisms, the Neurospora circadian clock supports rhythmic expression of about 10% of the genome (Hurley et al., 2014; Sancar et al., 2015). The WCC as the major photoreceptor of Neurospora is activated by light and thereby transduces light information to the clock (Froehlich et al., 2002; He et al., 2002). In Neurospora, short-term (0–16 hr) glucose deprivation triggers compensatory mechanisms at the transcriptional and posttranscriptional levels that maintain expression levels of the core clock proteins, thereby keeping period length constant (Adhvaryu et al., 2016; Emerson et al., 2015; Gyöngyösi et al., 2017; Olivares-Yañez et al., 2016). Aim of this study was to characterize how chronic glucose deprivation affects the molecular clock and what role the circadian clock plays in the adaptation to starvation. We analyzed the transcriptome response to long-term glucose starvation in wt and the clock-less mutant Δwc-1 and found that the WCC has a striking impact on nutrient-dependent expression of a large set of genes, including enzymes and regulators of carbohydrate, amino acid, and fatty acid metabolism. We show that molecular timekeeping is robust even under severe limitation of carbon sources. Moreover, our data provide evidence that the TTFL is able to function in a wide range of stoichiometric conditions of its key elements, dependent on glucose availability. Our results show that Neurospora recovers faster from starvation in the presence of a functioning clock, suggesting a significant impact of the circadian clock on organismal fitness. Results Glucose-deprivation results in altered expression of core clock components To assess how long-term glucose starvation might affect the expression of clock components, liquid cultures of wt Neurospora grown at 2% glucose (standard medium) were transferred to a starvation medium with 0.01% glucose for 40 hr. Cultures were kept in constant light (LL). In LL, both the negative and the positive feedback persist, however, the circadian oscillation stops and both RNA and protein levels of the core clock components are at steady state (Crosthwaite et al., 1995; Elvin et al., 2005). Therefore, phase effects that might arise in response to different manipulations under free-running conditions can be excluded. The growth of Neurospora virtually stopped after the medium change and the expression of the major clock components was characteristically changed compared to standard cultures (Figure 1A and B). Both WC-1 and WC-2 expression decreased gradually to about 15% and 20% of the initial levels, respectively (Figure 1—figure supplement 1A). The amount of FRQ remained relatively constant after glucose deprivation, but a mobility shift characteristic for hyperphosphorylation of the protein was observed (Figure 1B). Figure 1 with 2 supplements see all Download asset Open asset Despite changes of the stoichiometry of clock components circadian time-measuring is sustained upon glucose depletion. (A) Neurospora growth is arrested in starvation medium. Following an incubation for 24 hr in standard liquid medium, mycelia were transferred to media containing either 2% or 0.01% glucose. Diameter of the mycelial balls was measured each day. The arrow indicates the time of medium change. (n=3, ± SEM, Repeated measures ANOVA, significant time-treatment interaction; post hoc analysis: Fisher LSD test). (B) Long-term glucose starvation affects expression of clock proteins in wt. Mycelial discs were incubated for 24 hr in standard liquid medium and then transferred to starvation medium (time point 0). Samples were harvested at the indicated time points. Cell extracts were analyzed by western blotting. Solid and dashed arrows indicate hyper- and hypophosphorylated forms of FRQ, respectively. RGB-1 and Ponceau staining (LC: loading control) are shown as loading controls. (n=3) See also A. (C) RNA levels of frq, wc-1 and wc-2 are similar under standard and nutrient limited conditions. Mycelial discs of the wt strain were incubated in standard liquid medium for 24 hr, then transferred to fresh media containing either 0.01% or 2% glucose and incubated for 40 hr in LL. RNA levels were normalized to that in cells grown in standard medium. (n=9–22, ± SEM, two-sample t-test, n.s.). (D) Stability of frq RNA is not affected by starvation. Growth conditions were described in (C). Following 40 hr of incubation in LL, cultures were transferred to DD (time point 0). Samples were harvested at the indicated time points. RNA levels were normalized to those measured at time point 0. (n=6, ± SEM, Repeated measures ANOVA, n.s.). (E) Left panel: FRQ level oscillates under starvation conditions in DD. Following an incubation in standard liquid medium for 24 hr, mycelia were transferred to standard or starvation medium. After 24 hr incubation in LL, cultures were transferred to DD. Samples were harvested at the indicated time points. (n=3, LC: loading control) Right panel: FRQ specific signals were analyzed by densitometry. (n=4–6). (F) WC levels are reduced and FRQ is hyperphosphorylated during glucose starvation. The experiment was performed as described in (E). Cell extracts from both growth conditions were analyzed on the same gel. (n=3, LC: loading control). (G) Expression of frq and ccg-2 is rhythmic during long-term glucose starvation. Experiment was performed as described in (E). RNA levels were determined by qPCR. (n=3–11, ± SEM, Repeated measures ANOVA, n.s.). Figure 1—source data 1 Source data for Figure 1B. (a) Western blots were used to detect expression of FRQ in the indicated samples for Figure 1B. (b) Figure with the area highlighted was used to develop the Figure 1B for FRQ. (c) Western blots were used to detect expression of WC-1 in the indicated samples for Figure 1B. (d) Figure with the area highlighted was used to develop the Figure 1B for WC-1. (e) Western blots were used to detect expression of WC-2 in the indicated samples for Figure 1B. (f) Figure with the area highlighted was used to develop the Figure 1B for WC-2. (g) Western blots were used to detect expression of RGB1 in the indicated samples for Figure 1B. (h) Figure with the area highlighted was used to develop the Figure 1B for RGB1. (i) Ponceau S staining was used to detect loading control of the indicated samples for Figure 1B. (j) Figure with the area highlighted was used for LC of Figure 1B . https://cdn.elifesciences.org/articles/79765/elife-79765-fig1-data1-v1.zip Download elife-79765-fig1-data1-v1.zip Figure 1—source data 2 Source data for Figure 1E. (a) Western blots were used to detect expression of FRQ in the indicated samples grown in 0.01% glucose containing medium for Figure 1E. (b) Figure with the area highlighted was used to develop the Figure 1E for FRQ in 0.01% glucose. (c) Western blots were used to detect expression of FRQ in the indicated samples grown in 2% glucose containing medium for Figure 1E. (d) Figure with the area highlighted was used to develop the Figure 1E for FRQ in 2% glucose. (e) Ponceau S staining was used to detect loading control of the indicated samples for Figure 1E (0.01% glucose). (f) Figure with the area highlighted was used to develop the Figure 1E for LC (0.01% glucose). (g) Ponceau S staining was used to detect loading control of the indicated samples for Figure 1E (2% glucose). (h) Figure with the area highlighted was used to detect loading control of the indicated samples for Figure 1E (2% glucose). https://cdn.elifesciences.org/articles/79765/elife-79765-fig1-data2-v1.zip Download elife-79765-fig1-data2-v1.zip Figure 1—source data 3 Source data for Figure 1F. (a) Western blots were used to detect expression of FRQ in the indicated samples for Figure 1F. (b) Figure with the area highlighted was used to develop the Figure 1F for FRQ. (c) Western blots were used to detect expression of WC-1 in the indicated samples for Figure 1F. (d) Figure with the area highlighted was used to develop the Figure 1F for WC-1. (e) Western blots were used to detect expression of WC-2 in the indicated samples for Figure 1F. (f) Figure with the area highlighted was used to develop the Figure 1F for WC-2. (g) Ponceau S staining was used to detect loading control of the indicated samples for Figure 1F. (h) Figure with the area highlighted was used as LC for Figure 1F. https://cdn.elifesciences.org/articles/79765/elife-79765-fig1-data3-v1.zip Download elife-79765-fig1-data3-v1.zip Figure 1—source data 4 Actin levels are decreased in glucose starvation. Experimental procedures were performed as described in Figure 1C. Ct values of the indicated genes were determined by qPCR. (n=3, ± SEM) In the last row, ratio of the expression levels (wt 0.01%/2%) are shown based on the RNAseq dataset. https://cdn.elifesciences.org/articles/79765/elife-79765-fig1-data4-v1.docx Download elife-79765-fig1-data4-v1.docx Because hyperphosphorylated FRQ exerts a reduced negative feedback on WCC (Schafmeier et al., 2006), we hypothesized that the starvation-induced phosphorylation of FRQ might lead to an increase in WCC activity and consequently to the acceleration of its decay (Kodadek et al., 2006; Punga et al., 2006; Schafmeier et al., 2008). Hence, we followed WC levels in cultures treated with the translation inhibitor cycloheximide to assess WCC stability (Figure 1—figure supplement 1B). Our data suggest that increased turnover of WC-1 may be, at least partially, responsible for the low WCC levels in the starved cells. In LL WCC constantly promotes transcription of frq and wc-1. Although WCC levels were significantly different under standard and glucose-starved conditions, RNA levels of frq, wc-1 and wc-2 were similar (Figure 1C), suggesting a compensatory mechanism that either maintains the active pool of WCC under various nutritional conditions constant or stabilizes the RNA. In the next experiment we examined frq RNA levels after a light-dark transfer (LD), when transcription of frq is repressed, and therefore changes in frq levels reflect RNA degradation. frq RNA levels after LD transition were similar under both culture conditions, suggesting that changes in RNA stability do not contribute to the maintenance of frq levels during starvation (Figure 1D). Although the expression of FRQ and WCC is interdependent (Cheng et al., 2001), their levels did not change proportionally upon starvation in LL, raising the question of whether the circadian oscillator function is intact under starvation conditions. We followed clock protein levels in constant darkness (DD), when the circadian clock displays a free running endogenous rhythm. FRQ protein showed a similar robust oscillation in both standard and starvation media, with no noticeable difference in period or phase (Figure 1E). When protein samples were analyzed on the same gel, increased FRQ phosphorylation was observed under starvation conditions in LL and at all time points in DD (Figure 1F). Similarly to the changes in LL, the expression of WC proteins was greatly reduced in DD upon glucose deprivation. However, neither phase nor amplitude of frq RNA oscillation was affected by starvation (Figure 1G, left panel), indicating that WCC activity was similar under both conditions. Since starvation does not affect frq RNA decay (see above), an unknown mechanism must recalibrate the central clockwork to keep frq transcript levels and oscillation glucose-compensated despite the decline in WCC levels. To examine clock output function, we measured RNA levels of two clock-controlled genes, ccg-2 and fluffy (Bell-Pedersen et al., 1992). Similarly to previous findings, starvation resulted in significant upregulation of ccg-2 expression (Bell-Pedersen et al., 1992; Kaldenhoff and Russo, 1993; Sokolovsky et al., 1992). Interestingly, fluffy levels were also elevated under starvation compared to standard conditions. In addition, a robust oscillation of ccg-2 and fluffy RNA was detected under both conditions, with peaks and troughs at the expected circadian time (Figure 1G, right panel; Figure 1—figure supplement 2). Our results suggest that the circadian clock functions robustly during glucose deprivation despite increased FRQ phosphorylation and decreased WCC levels and drives rhythmic expression of output genes without changes in period length or phase. To examine the activity of the WCC as the photoreceptor of Neurospora, we followed the expression of the light-inducible genes frq, wc-1 and al-2 after dark-light (DL) transfer under both nutrient conditions. The light-induced initial increase of RNA levels was lower in starved than non-starved cultures, whereas the steady state expression levels after light adaptation were similar under both conditions (Figure 2A). The difference in the kinetics of light induction suggests that the light-inducible pool or the photoreceptor function of WCC is reduced upon glucose deprivation. Figure 2 Download asset Open asset Glucose deprivation impacts both light induction of gene expression and subcellular distribution of clock components. (A) Light induction of gene expression is attenuated by glucose starvation. Mycelial discs of the wt strain were incubated in standard liquid medium for 24 hr, then transferred to media containing either 0.01% or 2% glucose. Following a 24 hr incubation in LL, cultures were transferred to DD for 16 hr and then light induced. Samples were harvested at the indicated time points after light on. Relative frq, wc-1 and al-2 RNA levels were normalized to that measured at the first time point. (n=5–11, ± SEM, Repeated measures ANOVA, significant time*treatment interaction, post hoc analysis: Tukey HSD test). (B) Glucose deprivation affects subcellular distribution of clock proteins. Growth conditions were as described in Figure 1C. Nuclear (N) and cytosolic (C) fractions were analyzed by Western blotting. (n=3, s: short exposure, l: long exposure, LC: loading control). Figure 2—source data 1 Source data for Figure 2B. (a) Western blots were used to detect expression of FRQ in the indicated samples for Figure 2B (s: short exposure). (b) Figure with the area highlighted was used to develop the Figure 2B for FRQ (s: short exposure). (c) Western blots were used to detect expression of FRQ in the indicated samples for Figure 2B (l: long exposure). (d) Figure with the area highlighted was used to develop the Figure 2B for FRQ (l: long exposure). (e) Western blots were used to detect expression of WC-1 in the indicated samples for Figure 2B (s: short exposure). (f) Figure with the area highlighted was used to develop the Figure 2B for WC-1 (s: short exposure). (g) Western blots were used to detect expression of WC-1 in the indicated samples for Figure 2B (l: long exposure). (h) Figure with the area highlighted was used to develop the Figure 2B for WC-1 (l: long exposure). (i) Western blots were used to detect expression of WC-2 in the indicated samples for Figure 2B (s: short exposure). (j) Figure with the area highlighted was used to develop the Figure 2B for WC-2 (s: short exposure). (k) Western blots were used to detect expression of WC-2 in the indicated samples for Figure 2B (l: long exposure). (l) Figure with the area highlighted was used to develop the Figure 2B for WC-2 (l: long exposure). (m) Ponceau S staining was used to detect loading control of the indicated samples for Figure 2B. (n) Figure with the area highlighted was used as LC for Figure 2B. https://cdn.elifesciences.org/articles/79765/elife-79765-fig2-data1-v1.zip Download elife-79765-fig2-data1-v1.zip Nucleocytoplasmic distribution of clock proteins is tightly associated with their phosphorylation and activity. Hence, we performed subcellular fractionation on our LL samples (Figure 2B). In accordance with previous data (Cheng et al., 2005; Gyöngyösi et al., 2017; Schafmeier et al., 2006), the majority of FRQ was in the cytosol fraction, and its distribution did not change markedly upon glucose-deprivation. In contrast, WC proteins were virtually absent from the cytosol of starved cells, whereas their nuclear concentrations were similar to those in the control cells. Multiple modulators are involved in the starvation response of the clock components The objective of the following experiments was to explore possible mechanisms that could contribute to the glucose-dependent reorganisation of the TTFL components. Liquid cultures grown in LL were investigated. To address the role of FRQ-mediated feedback in this process, we used the FRQ-less mutant frq9. In frq9 due to a premature stop codon, only a truncated, non-functional and unstable version of FRQ is expressed resulting in the loss of both the negative and positive feed-back of FRQ. One of the advantages of this strain is that activity of the frq promoter can be assessed by measuring frq9 RNA levels in the absence of FRQ protein (Aronson et al., 1994; Liu et al., 2019). Increased amount of frq9 RNA in standard medium compared with frq can be attributed to the absence of the negative feedback from FRQ to WCC (Schafmeier et al., 2005). However, while starvation did not alter frq expression in wt, it decreased the amount of frq9 RNA (Figure 3A), resulting in similar RNA levels (reflecting similar frq promoter activity) in the two strains upon glucose withdrawal. The different behavior of frq promoter activity in frq9 and wt in response to glucose suggests that FRQ-mediated processes contribute to the compensation of frq levels at different glucose availability. Amount of WC-1 did not change significantly in frq9, whereas WC-2 levels were moderately reduced in response to glucose depletion (Figure 3B). However, it is difficult to compare the glucose-dependence of WCC expression in frq9 and wt because, due to the lack of the positive feedback of FRQ on the accumulation of the WCC, WC-1 and WC-2 levels are very low in frq9 (Cheng et al., 2001; Schafmeier et al., 2006). Figure 3 Download asset Open asset FRQ, PKA, GSK and PP2A affect the starvation response of the Neurospora clock. (A) frq9 RNA expression is sensitive to glucose deprivation. Growth conditions were as described in Figure 1C. RNA levels were normalized to that of wt grown in standard medium. (n=6, ± SEM, Factorial ANOVA; significant strain*treatment interaction; post hoc analysis: Tukey HSD test). (B) Effect of starvation on WC levels is reduced in frq9. Growth conditions were as described in Figure 1C. Cell extracts were analyzed by western blotting (left panel). (n=3) Protein signal density was analyzed (right panel). (n=3, ± SEM, LC: loading control for WC-2 (upper panel) and WC-1 (lower panel), Factorial ANOVA; significant strain*treatment interaction; post hoc analysis: Tukey HSD test). (C) Impaired FRQ-CK1a interaction affects the starvation response of the molecular clock. Experiments were performed with the indicated strains as described in Figure 1C. Indicated protein (upper panel) and frq expressions (lower panel) were analyzed. RNA levels were normalized to that of wt grown in standard medium. (n (protein analysis)=12, LC: loading control for FRQ and WC-2 (upper panel) and WC-1 (lower panel), n (RNA analysis)=4–5, ± SEM, Factorial ANOVA; significant strain effect; post hoc analysis: Tukey Unequal N HSD test). (D) The starvation response is altered in the PKA mutant (mcb). Experiments were performed with the indicated strains as described in Figure 1C. Upper panel: analysis of cell extracts by Western blotting (n=12, s: short exposure, l: long exposure; LC: loading control for FRQ (upper panel), WC-1 and WC-2 (lower panel)) Lower panel: frq RNA levels of the indicated strains. RNA levels were normalized to that of wt grown in standard medium. (n=8–9, ± SEM, Factorial ANOVA; significant treatment effect; post hoc analysis: Tukey Unequal N HSD test). (E) Hyperphosphorylation of FRQ upon glucose withdrawal is dependent on GSK. Experiments were performed with the indicated strains as described in Figure 1C. The medium was supplemented with 1.5*10–5M quinic acid (QA) during the first day of incubation. Following the medium change, mycelia were incubated in QA-free medium. Upper panel: cell extracts analyzed by Western blotting. (LC: loading control) Lower panel: frq RNA levels of the indicated strains. RNA levels were normalized to that of wt grown in standard medium. (n=6, ± SEM; Factorial ANOVA, significant strain*treatment interaction, post hoc analysis: Tukey HSD test). (F) PP2A activity is decreased under starvation conditions. Experiments were performed with the indicated strains as described in Figure 1C. PP2A-specific activity of the cell lysates was determined and normalized to that of the wt grown in standard medium. (n=3–4, ± SEM, Factorial ANOVA, Significant strain*treatment interaction, post hoc analysis: Tukey Unequal N HSD test). (G) The starvation response is altered in the strain lacking a functional PP2A regulatory subunit (rgb-1). Experimental procedures were performed with the indicated strains as described in Figure 1C. Cell extracts were analyzed by Western blotting (n=12, LC: loading control for FRQ (upper panel), for WC-1 (middle panel) for WC-2 (lower panel)) (left panel) and RNA levels of frq were determined. RNA levels were normalized to that of wt grown in standard medium. (n=9–10, ± SEM, Factorial ANOVA, significant strain*treatment interaction) (right panel). Figure 3—source data 1 Source data for Figure 3B. (a) Western blots were used to detect expression of WC-1 in the indicated samples for Figure 3B (s: short exposure). (b) Figure with the area highlighted was used to develop the Figure 3B for WC-1 (s: short exposure). (c) Western blots were used to detect expression of WC-1 in the indicated samples for Figure 3B (l: long exposure). (d) Figure with the area highlighted was used to develop the Figure 3B for WC-1 (l: long exposure). (e) Western blots were used to detect expression of WC-2 in the indicated samples for Figure 3B (s: short exposure). (f) Figure with the area highlighted was used to develop the Figure 3B for WC-2 (s: short exposure). (g) Western blots were used to detect expression of WC-2 in the indicated samples for Figure 3B (l: long exposure). (h) Figure with the area highlighted was used to develop the Figure 3B for WC-2 (l: long exposure). (i) Ponceau S staining was used to detect loading control of the indicated samples for Figure 3B. (j) Figure with the area highlighted was used to as LC for WC-1 in Figure 3B. (k) Figure with the area highlighted was used as LC for WC-2 in Figure 3B . https://cdn.elifesciences.org/articles/79765/elife-79765-fig3-data1-v1.zip Download elife-79765-fig3-data1-v1.zip Figure 3—source data 2 Source data for Figure 3C. (a) Western blots were used to detect expression of FRQ in the indicated samples for Figure 3C. (b) Figure with the area highlighted was used to develop the Figure 3C for FRQ. (c) Western blots were used to detect expression of WC-1 in the indicated samples for Figure 3C. (d) Figure with the area highlighted was used to develop the Figure 3C for WC-1. (e) Western blots were used to detect expression of WC-2 in the indicated samples for Figure 3C. (f) Figure with the area highlighted was used to develop the Figure 3C for WC-2. (g) Ponceau S staining was used to detect loading control of WC-1 for Figure 3C. (h) Figure with the area highlighted was used to develop the Figure 3C for LC for WC-1. (i) Ponceau S staining was used to detect loading control of FRQ and WC-2 for Figure 3C. (j) Figure with the area highlighted was used as LC for FRQ and WC-2 for Figure 3C. https://cdn.elifesciences.org/articles/79765/elife-79765-fig3-data2-v1.zip Download elife-79765-fig3-data2-v1.zip Figure 3—source data 3 Source data for Figure 3D. (a) Western blots were used to detect expression of FRQ in the indicated samples for Figure 3D (s: short exposure). (b) Figure with the area highlighted was used to develop the Figure 3D for FRQ (s: short exposure). (c) Western blots were used to detect expression of FRQ in the indicated samples for Figure 3D (l: long exposure). (d) Figure with the area highlighted was used to develop the Figure 3D for FRQ (l: long exposure). (e) Western blots were used to detect expression of WC-1 in the indicated samples for Figure 3D. (f) Figure with the area highlighted was used to develop the Figure 3D for WC-1. (g) Western blots were used to detect expression of WC-2 in the indicated samples for Figure 3D. (h) Figure with the area highlighted was used to develop the Figure 3D for WC-2. (i) Ponceau S staining was used to detect loading control of the indicated samples for Figure 3D. (j) Figure with the area highlighted was used as LC for FRQ in Figure 3D. (k) Figure with the area highlighted was used as LC for WC-