RIPK1 is a crucial regulator of cell death and survival. Ripk1 deficiency promotes mouse survival in the prenatal period while inhibits survival in the early postnatal period without a clear mechanism. Metabolism regulation and autophagy are critical to neonatal survival from severe starvation at birth. However, the mechanism by which RIPK1 regulates starvation resistance and survival remains unclear. Here, we address this question by discovering the metabolic regulatory role of RIPK1. First, metabolomics analysis reveals that Ripk1 deficiency specifically increases aspartate levels in both mouse neonates and mammalian cells under starvation conditions. Increased aspartate in Ripk1−/− cells enhances the TCA flux and ATP production. The energy imbalance causes defective autophagy induction by inhibiting the AMPK/ULK1 pathway. Transcriptional analyses demonstrate that Ripk1−/− deficiency downregulates gene expression in aspartate catabolism by inactivating SP1. To summarize, this study reveals that RIPK1 serves as a metabolic regulator responsible for starvation resistance.
Receptor-interacting protein kinase-1 (RIPK1) is a master regulator of cell survival and death1,2,3,4 and mediates FADD/caspase-8-dependent apoptosis and RIPK3-dependent necrosis5,6. In mice, genetic ablation of cell death-related genes mostly leads to prenatal death or embryonic defects (e.g., Fadd−/− mice)7. However, Ripk1−/− mice appear almost normally in the prenatal period while exhibit postnatal lethality with extensive cell death within 1–3 days after birth8,9,10,11,12. Although Ripk1 knockout rescues the prenatal death of Fadd−/− mice, Ripk1−/− Fadd−/− mice still die in a short time after birth9. This demonstrates that RIPK1 specifically promotes survival in the neonatal period. At birth, the transplacental nutrient supply is suddenly interrupted, and neonates face severe nutritional deficiency. Neonates adapt to this severe starvation circumstance by activating autophagy to maintain the supply of amino acids and metabolic homeostasis13. Similar to Ripk1−/− mice, genetic ablation of autophagy machines, such as Atg5 in mice, also causes postnatal lethality with a significantly decreased amino acid pool13. This suggests that RIPK1 may serve as a regulator that is responsible for starvation resistance at birth and supports neonatal survival.
Metabolic alteration plays a pivotal role in the response to starvation, which enables cell survival and maintains organismal function14,15,16. Given that metabolic balance is critical to starvation resistance, how cells sense starvation and reprogram metabolism is still elusive. RIPK1 has been reported as a sensor of various stresses17,18. Emerging evidence has delineated the regulatory role of RIPK1 in metabolism. For example, the loss of RIPK1 in lung cancer cells impairs mitochondrial oxidative phosphorylation and accelerates glycolysis19. Thus, we hypothesized that RIPK1 may also play a vital role in starvation resistance by regulating cellular metabolism.
In this study, we first discovere that RIPK1 is required for cell survival under starvation conditions but not under normal conditions. Then, we employe metabolomics to profile the metabolic changes responding to Ripk1 deficiency and discovere the dysregulation of aspartate metabolism in Ripk1-deficient conditions. Amino acids play an important role in regulating various cellular processes, including autophagy20. For example, the concentrations of amino acids in neonatal Atg5−/− mice are significantly lower than those in wild-type (WT) mice13. In particular, aspartate has been reported as an essential metabolite for cell growth21,22. Then, through combined metabolomics, RNA-sequencing (RNA-seq), and mechanistic studies, we reveal that Ripk1 deficiency modulates aspartate catabolism and disrupts metabolic homeostasis, which inactivates starvation-induced autophagy. The results demonstrate that RIPK1 is a nutrient stress sensor and metabolic regulator that is critical to maintaining metabolic homeostasis under starvation conditions.
RIPK1 is essential for survival under starvation conditions by activating autophagy
Ripk1 deficiency had little effect on cell survival under normal or glucose starvation conditions but significantly inhibited cell survival under the deprivation of total nutrients (Earle’s balanced salt solution, EBSS; Fig. 1a, b and Supplementary Fig. 1a). Under starvation, cells activate catabolism (e.g., autophagy) and suppress anabolism (e.g., protein synthesis). We further inhibited protein synthesis using cycloheximide (CHX). However, under CHX treatment and EBSS starvation conditions, Ripk1 deficiency still inhibited cell survival significantly (Fig. 1a, b). The results suggest that RIPK1 may regulate catabolism instead of anabolism. In accordance, Ripk1−/− mouse neonates died in a short time without milk feeding after delivery (Fig. 1c), and the survival time was slightly prolonged with milk feeding (Fig. 1d), suggesting that Ripk1−/− neonates may die due to defects in starvation resistance. We further measured the autophagy levels in tissues obtained from starved WT, Ripk1−/− and Ripk1+/− mouse neonates. Transmission electron microscopy (TEM) imaging showed the abundant formation of autophagic vacuoles, including autophagosomes (AP) and autolysosomes (AL), in the heart tissues from starved WT neonates. But these vacuoles were largely absent in Ripk1−/− neonates (Fig. 1e, f). Immunofluorescent staining of LC3 dots in the heart tissues further demonstrated that the formation of autophagosomes was significantly upregulated at 6 h after delivery in WT neonates (Fig. 1g, h). In contrast, significantly fewer LC3 puncta were observed in starved Ripk1−/− neonates. Similar results were observed in the mouse brain tissues (Supplementary Fig. 1b–e). Western blot (WB) results further validated that autophagy was induced by postnatal starvation in WT and Ripk1+/− neonates, as indicated by the upregulation of LC3-II protein levels and degradation of SQSTM1/p62 (p62) protein levels, but inhibited in Ripk1−/− neonates (Fig. 1i).
To investigate the regulatory role of RIPK1 in autophagy, mouse embryonic fibroblast (MEF) cells with Ripk1 knockout were used. WT and Ripk1−/− MEFs were incubated in EBSS to mimic nutritional deficiency conditions. Interestingly, Ripk1 deficiency promoted autophagy under normal conditions (culture medium) but inhibited autophagy under starvation conditions (EBSS, Fig. 1j). This result is similar to the phenomenon that Ripk1 deficiency promotes survival in the prenatal period (sufficient nutrient supply) but inhibits survival in the neonatal period (interrupted nutrient supply)7,8,9,10,11,12. Autophagy is important for survival in neonatal starvation, further suggesting that RIPK1 plays a role in starvation resistance. We found that autophagy was induced in WT cells in a time-dependent manner but not in Ripk1−/− cells, as indicated by the upregulation of LC3-II protein levels and downregulation of p62 protein levels (Fig. 1k). The downregulated levels of autophagy were successfully rescued by overexpressing Ripk1 in Ripk1−/− cells (i.e., Ripk1−/− + Ripk1 cells, Fig. 1k). Furthermore, we used a stable green fluorescent protein (GFP)-LC3-transfected H4 cell line (i.e., H4-GFP-LC3)23 and transiently transfected the cells with siRNAs targeting Ripk1. As shown in Fig. 1l, m, GFP-LC3 puncta were not observed under starvation conditions in the Ripk1 knockdown groups, suggesting that autophagosome formation was inhibited by Ripk1 deficiency. Taken together, these results demonstrated that RIPK1 is essential for starvation resistance under starvation conditions.
Aspartate is a RIPK1-dependent metabolite under starvation
We first profiled the metabolic changes responding to Ripk1 deficiency in both MEFs and Jurkat cells under normal conditions using liquid chromatography–mass spectrometry (LC–MS)-based targeted metabolomics24. A total of ~200 essential metabolites were measured, and 68 metabolites were significantly changed in Ripk1−/− MEFs (Student’s t-test, p < 0.05; and fold change >1.2; Fig. 2a). Metabolic pathway enrichment analysis further revealed that the alanine, aspartate, and glutamate metabolism pathway was one of the enriched pathways (Fig. 2b, c). Similar results were also obtained using RIPK1−/− Jurkat cells (Supplementary Fig. 2a–c). Then, under starvation conditions, we confirmed that aspartate levels were consistently upregulated in Ripk1−/− cells and rescued by overexpressing Ripk1 in Ripk1−/− cells (i.e., Ripk1−/− + Ripk1 cells, Fig. 2d, e). Similar results were also validated in the early neonatal Ripk1−/− mouse tissues (Fig. 2f, g and Supplementary Fig. 2d, e). By checking all RIPK1-dependent metabolites from the mouse brain tissue, liver tissues, MEFs, and Jurkat cells under starvation conditions (Fig. 2d–g), we found that aspartate was the specific metabolite that consistently responded to RIPK1 expression in all four biological sample groups under starvation conditions. These results indicate that RIPK1 deficiency causes increased aspartate levels in cells and mouse tissues, which are rescued by RIPK1 complementation.
Increased aspartate induced by RIPK1 deficiency inhibits starvation-induced autophagy
We further studied the effects of intracellular aspartate levels on starvation-induced autophagy. Under starvation, increased aspartate levels by adding aspartate to WT MEFs led to decreased LC3-II and increased p62 levels in a dose-dependent manner (Fig. 3a, b). Consistently, in starved H4-GFP-LC3 cells, aspartate treatment significantly decreased the formation of autophagosomes (Fig. 3c, d). In contrast, we also reduced the intracellular aspartate levels in Ripk1−/− MEFs by knocking down glutamic-oxaloacetic transaminase 2 (GOT2), which is a key enzyme involved in intracellular synthesis of aspartate (Fig. 3e). As expected, the knockdown of Got2 dramatically restored autophagy levels in Ripk1−/− MEFs under starvation conditions. LC3-II protein levels were increased while p62 protein levels were decreased in response to Got2 knockdown (Fig. 3f). Among the shRNAs targeting GOT2, #1 shRNA induced the most significant decrease of GOT2 level (Fig. 3f). Accordingly, we consistently observed the most significant decrease of aspartate level and increase of autophagy in Ripk1−/− cells with #1 shRNA (Fig. 3e), suggesting that aspartate inhibiting autophagy induction under starvation is proportional to the concentrations of aspartate. The results were further validated through a GFP-LC3 assay in RIPK1−/− HEK293T cells (Fig. 3g, h and Supplementary Fig. 3a). Similar results were obtained with the treatment of a GOT2 inhibitor, aminooxy acetic acid (AOA)25. The inhibition of GOT2 decreased the intracellular aspartate levels in Ripk1−/− MEFs (Fig. 3i) and activated autophagy, as shown by the increased levels of LC3-II, reduced levels of p62 (Fig. 3j), and increased numbers of GFP-LC3 puncta in H4-GFP-LC3 cells with RIPK1 knockdown (Fig. 3k–m). Although AOA had a massive effect on aspartate (Fig. 3i), it generated a very similar effect on autophagy induction, which may be due to the side effect of AOA treatment. AOA was reported as an inhibitor of GOT2 as well as an inhibitor of cystathionine-beta-synthase (CBS)26. In addition, we used relatively high concentrations of AOA for treatment, which may have toxic effects on cells. Taken together, these results suggest that the increased aspartate levels in Ripk1−/− cells underlie the mechanism of defective starvation-induced autophagy. In addition, we measured mRNA expression in WT and Ripk1−/− MEFs using RNA-seq. Among the 3,160 significantly changed genes in Ripk1−/− MEFs (p < 0.05; Student’s t-test), pathway enrichment showed that autophagy-related genes were not enriched (Supplementary Fig. 3b). Individual gene expression analysis also showed that the autophagy-related genes had no significant changes in the Ripk1−/− cells (Supplementary Fig. 3c). These results demonstrated that RIPK1 regulated starvation-induced autophagy by modulating metabolism rather than autophagy-related genes.
Increased aspartate inhibits the AMPK pathway in RIPK1-deficient cells under starvation
Previous reports have revealed the regulatory role of AMPK in autophagy in response to nutrient starvation27,28. AMPK senses changes in intracellular AMP/ATP ratio to maintain energy homeostasis29. Our data first showed that AMP/ATP ratios were decreased in both newborn Ripk1−/− mice and cultured cells (Fig. 4a, b and Supplementary Fig. 4a, b). Consistently, we found that the activation of AMPK through AMPK phosphorylation (AMPKα Thr172) and phosphorylation of its downstream substrate acetyl-CoA carboxylase (ACC Ser79) was blocked by Ripk1 deficiency in both neonatal mouse brains and EBSS-cultured MEFs (Fig. 4c, d and Supplementary Fig. 4c–e). These observations were consistent with the low autophagy levels in starved Ripk1−/− mice and Ripk1−/− MEFs (Fig. 1). Previous reports have demonstrated that AMPK regulates autophagy activation through the direct phosphorylation of ULK1 (mammalian homolog of yeast Atg1)27,30. Here, we confirmed that phosphorylation of ULK1 (Ser317) was inhibited in starved Ripk1−/− mice and Ripk1−/− MEFs (Supplementary Fig. 4d, e). In contrast, when Ripk1−/− cells were treated with aminoimidazole carboxamide ribonucleotide (AICAR), a direct activator of AMPK, both autophagy and p-AMPK/p-ULK1 levels were upregulated under starvation (Fig. 4e). Thus, the defective autophagy induction in Ripk1−/− mice and cells was ascribed to the defective activation of the AMPK signaling pathway.
We further demonstrated that the increased aspartate levels reduced the AMP/ATP ratios in both starved WT Jurkat cells and MEFs (Fig. 4f). Consistently, the starvation-induced elevation of p-AMPK, p-ACC, and p-ULK1 levels in WT cells was reduced upon aspartate treatment (Fig. 4g). The defective activation of AMPK in starved WT MEFs inhibited by aspartate treatment was further restored by the direct activation of AMPK using AICAR (Fig. 4h). In comparison, the reduction in intracellular aspartate levels in Ripk1−/− cells through Got2 knockdown significantly increased the AMP/ATP ratios (Fig. 4i). As a result, p-AMPK and p-ULK1 levels were increased in response to GOT2 knockdown (Fig. 4j). Similar results were observed when GOT2 activities were inhibited by AOA treatment (Fig. 4k, l). Altogether, increased intracellular aspartate regulated autophagy by inhibiting the AMPK pathway.
RIPK1 deficiency increases ATP production by enhancing TCA flux
We demonstrated that the increased aspartate levels in Ripk1−/− cells decreased the AMP/ATP ratios and inhibited AMPK-mediated autophagy. Thus, energy metabolism in Ripk1−/− cells should be significantly altered. We performed cell energy metabolism analyses of WT and Ripk1−/− MEFs using Seahorse. Specifically, measurements of oxygen consumption rates (OCRs) demonstrated that ATP production was upregulated in starved Ripk1−/− MEFs (Fig. 5a). Similar results were obtained in starved WT MEFs treated with aspartate (375 μM, Fig. 5b). The elevation of ATP levels in Ripk1−/− cells and aspartate-treated WT cells was further confirmed by LC–MS analysis (Fig. 5c, d). Although aspartate treatment has been reported to increase ATP production by promoting glycolysis in tumor cells31, our data showed that ECAR values had no significant changes in Ripk1−/− MEFs and aspartate-treated WT MEFs (Fig. 5e, f and Supplementary Fig. 5a, b). The increased production of ATP may be ascribed to the enhanced activity of TCA cycle. Indeed, LC–MS analyses demonstrated that metabolites in TCA cycle, such as citrate and cis-aconitate, were elevated in Ripk1−/− MEFs and Jurkat cells under starvation (Fig. 5g and Supplementary Fig. 5c). Similarly, aspartate treatment also increased TCA metabolites in MEFs and Jurkat cells (Fig. 5h and Supplementary Fig. 5d). Consistently, glycolysis metabolites showed no changes in response to RIPK1 deficiency and aspartate treatment (Supplementary Fig. 5e, f). We further employed stable-isotope tracing technology with [U-13C]-aspartate to validate the enhanced TCA activity in response to Ripk1 deficiency. The results in starved WT and Ripk1−/− cells clearly demonstrated that aspartate-derived metabolites in TCA cycle, such as citrate, cis-aconitate, α-ketoglutarate, and malate, were significantly increased in Ripk1−/− cells (Fig. 5i, j). Similarly, with the treatment of [U-13C]-glutamine, the fully labeled TCA metabolites and aspartate were also significantly higher in Ripk1−/− MEFs (Supplementary Fig. 5g, h). These results suggest that the increased aspartate level in Ripk1−/− cells contributes to the increased ATP production by enhancing the activity of TCA cycle, which eventually causes energy metabolic disorder under starvation.
RIPK1 deficiency suppresses aspartate catabolism by inactivating SP1
To understand how Ripk1 deficiency affects aspartate metabolism, we checked the Ripk1-dependent genes associated with aspartate metabolism. RNA-seq data showed that the expressions of the aspartate/glutamate transporter Slc1a1 (Solute carrier family 1 member 1) and Slc1a3 were decreased in Ripk1−/− MEFs (Fig. 6a and Supplementary Fig. 6a). The results suggestd that the increased intracellular aspartate in Ripk1−/− cells is not from extracellular transportation. This was further confirmed by the measurements of intracellular aspartate levels in aspartate-treated WT and Ripk1−/− cells (Supplementary Fig. 6b). We also found that genes encoding aspartate catabolic enzymes, including Got1 (glutamate oxaloacetate transaminase 1), Asns (asparagine synthetase), Ass1 (argininosuccinate synthetase 1), Adss (adenylosuccinate synthetase), and Cad (aspartate transcarbamylase), were downregulated in Ripk1−/− MEFs (Fig. 6a and Supplementary Fig. 6c–e). The results were confirmed by real-time PCR analyses in MEFs (Fig. 6b). Meanwhile, in the [U-13C]-aspartate-based isotope tracing experiment, we found that the degradation metabolites of aspartate, such as adenylosuccinate and orotate, were significantly decreased in Ripk1−/− cells under starvation conditions (Fig. 6c). Therefore, RIPK1 may increase intracellular aspartate levels by inhibiting aspartate catabolism. Transcription factor prediction analysis showed that genes encoding aspartate catabolic enzymes share a GC-rich motif in the [−2 kb, 2 kb] region, which can be recognized by the transcription factor SP1 (Fig. 6d and Supplementary Table 1 and 2). SP1 has been reported to activate the promoter activity of Got132, Cad32,33, Asns34, and Ass135. Real-time PCR analysis validated that Sp1 knockdown decreased the expressions of Got1, Ass1, Asns, Adss, and Cad under starvation (Fig. 6e). These results suggest that RIPK1 regulates SP1 to further influence the expressions of aspartate catabolism genes. Although the mRNA and protein expression levels of SP1 were not affected by RIPK1 deficiency (Supplementary Fig. 6f, g), the luciferase activities of SP1 were significantly downregulated in Ripk1−/− cells under starvation (Fig. 6f). Consistently, luciferase data showed that the promoter activities of GOT1, ASS1, ASNS, ADSS, and CAD were also decreased in RIPK1−/− HEK293T cells and reversed by SP1 overexpression under starvation (Fig. 6g).
To validate that the increased aspartate levels in Ripk1−/− cells because of the SP1 inactivation, intracellular aspartate levels responding to Sp1 knockdown were determined. LC–MS data showed that aspartate levels were increased in MEFs transfected with siRNAs targeting Sp1 (Fig. 6h) and accompanied by decreased AMP/ATP ratios (Fig. 6i). In addition, immunoblot and GFP-LC3 assays showed that Sp1 knockdown also inhibited autophagy levels and AMPK signaling (Fig. 6j and Supplementary Fig. 6h, i), similar to Ripk1 deficiency. Furthermore, overexpression of SP1 abrogated Ripk1 deficiency-induced autophagy retardation (Fig. 6k). These results suggest that RIPK1 regulates autophagy by modulating aspartate catabolism, which is achieved by negatively regulating transcription factor SP1.
RIPK1 deficiency inactivates SP1 by inhibiting SP1 nuclear translocation
Since RIPK1 does not affect the expression of SP1 but rather its activity, we then explored how SP1 inactivation was achieved upon Ripk1 deficiency. The transcriptional activity of SP1 could be affected by many factors, such as binding affinity to promoters, nuclear translocation, protein stability, and interaction with other protein factors36. SP1 nuclear translocation was increased under starvation conditions (Fig. 7a). In WT MEFs, we found that the SP1 expression was largely increased in the nucleus, while nuclear SP1 was significantly decreased in Ripk1−/− MEFs (Fig. 7b, c). SP1 nuclear translocation can be regulated by its phosphorylation36,37. Accordingly, we also found that phosphorylated SP1 (T739) was significantly decreased in Ripk1−/− MEFs (Fig. 7d). To evaluate whether RIPK1 kinase activity is required for SP1 nuclear translocation, necrostain-1 (Nec-1), a RIPK1 kinase activity inhibitor, was used38. Nuclear separation data showed that Nec-1 did not affect SP1 nuclear translocation under starvation and normal conditions (Fig. 7e and Supplementary Fig. 7b). Our IHC data confirmed that Nec-1 had little effect on SP1 nuclear translocation under starvation conditions (Supplementary Fig. 7a). We also found that Nec-1 treatment had no effect on SP1 phosphorylation and autophagy activation under various conditions (Fig. 7f). Transfection of the RIPK1 kinase-dead mutant (K45M) rescued SP1 nuclear localization in Ripk1−/− MEFs, suggesting the kinase-independent regulation of RIPK1 (Fig. 7g). Together, the results suggest that RIPK1 regulates SP1 nuclear expression and phosphorylation in a kinase-independent manner. Although our data indicated that RIPK1 and SP1 colocalized in the cytosol and nucleus (Supplementary Fig. 7c, d), and RIPK1 interacted with SP1 (Supplementary Fig. 7e), the mechanism by which RIPK1 regulates SP1 translocation and activity requires more experimental evidences.
Reduced aspartate levels rescue the survival of Ripk1 −/− cells from starvation
To determine whether aspartate accumulation is a byproduct of the mechanism by which RIPK1 deficiency fails to protect cells from starvation, we then tested the survival of Ripk1−/− cells responding to the reduced intracellular aspartate. Our results showed that AOA treatment decreased aspartate, increased AMP/ATP levels, and activated autophagy in Ripk1−/− cells (Figs. 3 and 4). We further demonstrated that upon AOA treatment, Ripk1−/− MEFs showed higher cell viability than untreated cells under starvation conditions (Fig. 8a, b). SP1 overexpression, which upregulated the expression of aspartate catabolism genes and decreased aspartate in Ripk1−/− cells (Fig. 8c), rescued the viability of RIPK1−/− HEK293T cells under starvation conditions (Fig. 8d, e). Taken together, the results demonstrated that aspartate catabolism represents the underlying mechanism by which RIPK1 regulates starvation resistance (Fig. 8f).
Metabolism homeostasis is important for survival under starvation conditions39,40. Mice deficient in autophagy-related genes (ATGs), such as Atg3, Atg5, Atg7, Atg12, and Ulk1/2, are born with normal morphology but die within 1 day after birth due to defective metabolism-autophagy crosstalk in response to nutrient stress41. Ripk1-deficient mouse neonates show a similar phenomenon8,9,10, suggesting that RIPK1 is important in starvation resistance. In this work, we demonstrated that RIPK1 has an undefined function in regulating starvation resistance by modulating aspartate catabolism. This new regulatory role of RIPK1 is essential for energy homeostasis and autophagy in response to starvation. We found that the increased intracellular aspartate in Ripk1−/− cells enhanced the activity of the TCA cycle and increased the production of ATP in cells. Then, the disrupted energy metabolic balance caused defective autophagy induction, which contributed to the neonatal lethality of Ripk1−/− mice. These findings demonstrated that RIPK1 served as a metabolism regulator that is responsible for starvation resistance.
Starvation occurs not only in the neonatal period but also in ischemia/respiration, the tumor microenvironment, and other situations. Here, we also found that RIPK1 acts as a sensor of starvation and translates the starvation signal to transcription factor SP1 to modulate the transcription of aspartate catabolism genes. SP1 is a shared regulator of aspartate catabolism genes. Transcriptional analyses showed that RIPK1 deficiency inhibited the activity of the transcription factor SP1, resulting in downregulated gene expressions in aspartate catabolism. Both SP1 overexpression and reduction of aspartate levels reversed the inhibitory effects of RIPK1 deficiency on starvation-induced autophagy. It is worth noting that, unlike the inhibition effect of Ripk1 deficiency on starvation-induced autophagy, Ripk1 deficiency promoted basal autophagy in normal conditions (Fig. 1j)42. We think that, although aspartate levels were increased in Ripk1−/− cells under both normal and starvation conditions, aspartate may have minimal effects on cell survival and autophagy under normal condition since amino acids are sufficient. However, under starvation condition, the increased aspartate levels inhibited the activation of autophagy and starvation resistance. Thus, RIPK1 seems to regulate autophagy by different mechanisms in normal growth condition and starvation condition.
Aspartate is an important intermediate metabolite required for anabolism and maintenance of redox homeostasis. Aspartate also serves as a building block of pyrimidine synthesis that is critical for cell proliferation21,22. Our results showed that aspartate was the specific metabolite that consistently responded to RIPK1 expression in both MEF/Jurkat cell lines and mouse tissues under starvation conditions (Fig. 2). Although we showed that aspartate metabolism is critical in RIPK1-regulated autophagy, by no means do we conclude that aspartate metabolism is the sole target of RIPK1. Other metabolites are consistently regulated by RIPK1 under different conditions (Fig. 2). It is likely that other downstream metabolic signaling pathways may also contribute to the biological functions of RIPK1.
RIPK1 is a multifunctional protein that regulates both cell death and survival. It has been reported that RIPK1 can regulate cell necrosis through energy metabolism43. Furthermore, Najafov et al. reported that RIPK1 regulates energy-sensing through the AMPK-mTOR pathway44. Here, we report that the RIPK1-aspartate catabolism-TCA cycle metabolic axis represents the underlying metabolic mechanism by which RIPK1 regulates the AMPK pathway and autophagy. Mechanistically, we found that RIPK1 regulates aspartate metabolism by inhibiting SP1 nuclear expression, probably by altered phosphorylation (T739) of SP1, in a kinase-independent manner. It has been well reported that some of RIPK1’s functions, such as promotion of cell death, require its kinase activity45, whereas others, such as the activation of MAPK and NF-κB46 to mediate pro-survival signals, are kinase activity-independent. Here, our results suggest that the kinase activity of RIPK1 is dispensable for starvation resistance and autophagy. Although our data indicated that RIPK1 interacted with SP1 in cells, the mechanism by which RIPK1 regulates SP1 activity and phosphorylation in a kinase-independent manner requires more experimental evidences. Together, our results confirmed that RIPK1 serves as an important regulator to maintain energy homeostasis under nutrient stress and supports survival. Our study will facilitate future work to explore the functions of RIPK1 related to cellular metabolism. This also offers new possibilities for therapeutic applications by targeting RIPK1 to treat nutrient stress-related diseases47.
Cell line names and sources are described in Supplementary Table 3; recombinant DNA plasmids and their gene numbers are described in Supplementary Table 4; chemical names and catalog numbers are described in Supplementary Table 5; antibody names and catalog numbers are described in Supplementary Table 6.
Mice (C57BL/6) were group-housed in a barrier facility at room temperatures of 20–26 °C with 40–70% humidity and 12 h light/12 h dark cycles. All mice received a regular chow diet ad libitum. All animal care and experiments were conducted in accordance with the Institutional Animal Care and Use Committees of Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences.
Mice were perfused first with PBS and then 4% paraformaldehyde (PFA) and 1% glutaraldehyde for 4 h at 25 °C, and then postfixed in 1% OsO4 followed by 2% uranyl acetate. After ethanol and propylene oxide dehydration, tissues were embedded in polybed 812 resin (Polysciences, 025950-1). Then ultrathin tissue sections (~70 nm) of brain and heart tissues were cut and post-stained with 2% uranyl acetate followed by 0.3% lead citrate. Tissue sections were analyzed on a TECNAI 10 transmission electron microscope (FEI) at an acceleration voltage of 80 kV. Autophagosomes typically have a double membrane. This structure is distinctly visible by TEM as two parallel membrane layers (bilayers) separated by a relatively narrower or wider electron-translucent cleft. Autolysosomes typically have only one limiting membrane. Frequently, they contain electron-dense cytoplasmic material and/or organelles at various stages of degradation. Autolysosomes are typically smaller than autophagosomes, and their structures are typically stained dark in TEM samples.
Serial coronal brain or heart tissue sections (12 μm) were used for immunohistochemical staining with the following modifications. Briefly, coronal sections were blocked in Tris Buffered Saline (TBS) combined with 1% Triton X-100 and 10% donkey serum for 2 h. All primary antibodies were used and incubated for 2 days at 4 °C. Secondary antibodies were used and incubated for 4 h at room temperature. Fluorescently stained sections were counterstained with DAPI (200 ng/ml; Sigma-Aldrich) for 2–5 min, and then coverslipped with Gel/Mount (Biomeda).
Cell imaging and statistical analysis
Cells were fixed with 4% PFA (Sigma-Aldrich) and stained with 3 μg/mL DAPI (Beyotime). Image data quantification was measured using an ArrayScan HCS 4.0 reader with a 203 objective (Cellomics ArrayScan VTI) for DAPI-labeled nuclei and GFP-tagged intracellular proteins.
Cell samples were extracted using a MeOH:ACN:H2O (2:2:1, v/v) solvent mixture. A volume of 1 mL of cold solvent was added to each cell pellet, vortexed for 30 s, and incubated in liquid nitrogen for 1 min. The samples were then allowed to thaw at room temperature and sonicated for 10 min. This freeze-thaw cycle was repeated three times in total. To precipitate proteins, samples were incubated for 1 h at −20 °C, followed by 15 min of centrifugation at 17,000xg and 4 °C. The resulting supernatant was taken and evaporated to dryness in a vacuum concentrator. The dry extracts were then reconstituted in 100 µL of ACN:H2O (1:1, v/v), sonicated for 10 min, and centrifuged for 15 min at 17,000xg and 4 °C to remove insoluble debris. The supernatant was then transferred to HPLC vials and kept at −80 °C until LC–MS analysis.
The metabolomics analyses of MEFs and Jurkat cells (WT vs. Ripk1−/−) under normal condition followed our previous publication24. Briefly, an HPLC system (1260 series, Agilent Technologies, USA) coupled to a triple quadrupole mass spectrometer (Agilent 6460, Agilent Technologies, USA) was used for LC–MS analyses. Phenomenex Luna aminopropyl column [particle size, 3 μm; 100 mm (length) × 2.1 mm (i.d.)] was used for separation. The metabolomics analyses of MEFs and Jurkat cells (WT, Ripk1−/−, and Ripk1−/− + Ripk1) under starvation and mouse brain and liver tissues followed an updated method in the publication48. Briefly, a UHPLC system (1290 series, Agilent Technologies, USA) coupled to a triple quadrupole mass spectrometer (Agilent 6495, Agilent Technologies, USA) was used for LC–MS analyses. A BEH Amide column [particle size,1.7 μm; 100 mm (length) × 2.1 mm (i.d.)] was used for separation. A total of 200 metabolites were simultaneously monitored, and the positive/negative polarity switching was used. All metabolite identifications and quantification were further manually confirmed using MRM transitions and retention times from chemical standards. The detailed instrument parameters were used the same as our previous reprot48. In Brief, Agilent MassHunter Workstation Data Acquisition (Version B.07.00), Agilent MassHunter Workstation Qualitative Analysis (Version B.07.00) were used in data collection.
Isotope tracing analysis
The MEFs were plated in 6-cm dishes at 2,000,000 cells/dish, and cultured in DMEM medium containing dFBS (10%) and penicillin/streptomycin (1%). The MEFs were first grown to 75–80% confluence in log-phase in the cell culture plates. Then, the culture medium solution was changed to a fresh medium solution with 375 μM [U-13C]-aspartate or 4 mM [U-13C]-glutamine. The labeling experiments were performed for 7 h for [U-13C]-aspartate and 12 h for [U-13C]-glutamine. Fast extraction of intracellular metabolites was performed as follows. In brief, the culture medium was quickly removed, and the cells were washed with the cold PBS twice. The cell dishes were placed on dry ice and the metabolite extraction solution (MeOH:ACN:H2O = 2/2/1, v/v/v, 1 mL) was added to the dishes to quench the metabolism. The extraction solution was precooled at −80 °C for 1 h prior to the extraction. The plates were then incubated at −80 °C for at least 40 min. The cell contents were scraped and transferred to a 1.5-mL Eppendorf tube. The samples were vortexed for 1 min and centrifuged for 10 min at 17,000 x g and 4 °C to precipitate the insoluble materials. The supernatant was taken to a new 1.5-mL Eppendorf tube and evaporated to dryness at 4 °C using a vacuum concentrator. The dried extracts were then reconstituted in 100 µL of ACN:H2O (1:1, v/v), sonicated for 10 min, and centrifuged for 15 min at 17,000 x g and 4 °C to remove insoluble debris. The supernatant was then transferred to HPLC vials and kept at −80 °C until LC–MS analysis. The LC–MS analysis was performed using a UHPLC system (1290 series; Agilent Technologies, USA) coupled to a quadrupole time-of-flight mass spectrometer (TripleTOF 6600, SCIEX, Canada).
Measurements of AMP/ATP
Intracellular AMP and ATP levels were measured using AMP-Glo™ Assay (Promega) and CellTiterGlo™ ATP assay (Promega) according to the manufacturer’s instruction.
Measurement of cellular OCR and ECAR
Cellular OCR and ECAR values were measured using the Seahorse XFe96 Extracellular Flux Analyzer (Agilent Technologies, USA) following the manufacturer-supplied protocols. Briefly, MEFs were seeded in an XFe96-well microplate with 1.5 × 104 cells per well and incubated for 20 h in normal growth conditions then starved in EBSS for 4 h prior to XF assay. Oligomycin (14 mM; ATP synthase inhibitor), carbonyl cyanide-4-(trifluoromethoxy) phenylhydrazone (FCCP, 10 mM; cellular uncoupler), rotenone/antimycin A (4 mM each; complex 1/complex 3 inhibitor) were sequentially added to determine basal-, ATP-dependent-, maximal-, and mitochondria-independent oxygen consumptions, respectively. ECAR was measured in XF medium in basal conditions. Glucose (10 mM), oligomycin (5 μM), and 2-deoxyglucose (2-DG, 100 mM; glycolysis inhibitor) were sequentially added to measure glycolysis, glycolysis capacity, and glycolysis reverse, respectively. The Seahorse measurements were all performed with the following assay conditions: 3 min of mixing; 3 min of waiting; and 3 min of measurements. The reported OCR and ECAR values were normalized to the cell numbers. The results were analyzed and exported from software Seahorse Wave (Version220.127.116.11).
RNA was isolated from WT and Ripk1−/− MEFs. Residual DNA contamination was removed using a TURBO DNA-free kit according to the manufacturer’s instruction (Thermo Fisher Scientific, USA). One microgram of total RNA was used for the preparation of the sequencing library. PolyA-tailed RNAs were selected by NEBNext Poly (A) mRNA Magnetic Isolation Module (NEB), followed by the library preparation using NEBNext Ultra RNA Library Prep Kit for Illumina according to the manufacturer’s instruction. The libraries were checked by Bioanalyzer 2100 (Agilent Technologies, USA), then pooled together in equimolar amounts to a final concentration of 2 nM. Pooled denature libraries were sequenced on an Illumina MiSeq System.
RNA was isolated using Trizol Reagent (Thermo Fisher Scientific, USA) in accordance with the manufacturer’s instructions. RNA was resuspended in DEPC-treated RNase-free water (Thermo Fisher Scientific, USA). Reverse transcription was catalyzed using a SuperScript III First-strand synthesis system (Thermo Fisher Scientific, USA). Real-time PCR analysis was performed using the QuantStudio 6 Flex real-time PCR system with SYBR selected master mix (Thermo Fisher Scientific, USA).
Luciferase activity assay
The reporter plasmids were transiently transfected into cells using the Lipofectamine method (Thermo Fisher Scientific, USA) according to the manufacturer’s protocol. Transfection efficiency was determined using the Renilla luciferase gene-containing pRL-CMV plasmid (Promega Corp.). HEK293T cells were transiently transfected with the reporter plasmid. After 24 h of the treatment, the transfected cells were washed twice with phosphate-buffered saline and lysed in passive lysis buffer (Promega Corp.) with gentle shaking at room temperature for 20 min. The cell lysate was centrifuged at 17,000xg for 2 min to pellet the cell debris. The supernatants were transferred to a fresh tube, and the dual-luciferase activity in the cell extracts was determined according to the manufacturer’s protocol (Promega Corp.) The firefly luciferase activity was measured using a luminometer which was programmed to perform a 2 s pre-measurement delay, followed by a 10 s measurement period for each reporter assay. After measuring the firefly luciferase activity (Stop & Glo®, Promega Corp.), Renilla luciferase-measuring buffer was added, and the Renilla luciferase activity was measured. Each transfection was performed in duplication, and all measurements were repeated at least four times.
Statistics and reproducibility
All quantifications of fluorescence were represented as mean ± SEM from three replicates. Quantifications of immunoblots and immunostaining were performed using ImageJ and CellProfiler. All statistical analyses were performed using GraphPad Prism (v 6.0 and v 8.0) and Microsoft Excel 2010. All western blots from cell samples and mice tissues were repeated at least three times with similar results, with uncropped blots shown in the Source data. Differences were considered to be significant if p value <0.05.
Further information on research design is available in the Nature Research Reporting Summary linked to this article.
The raw data files of the transcriptomics and metabolomics data generated in this study have been deposited and are available in the National Omics Data Encyclopedia under accession code OEP002409. The metabolite identification and quantification results generated in this study are provided in Supplementary Data 1–6. The identification and quantification of genes from RNA-sequencing generated in this study are provided in Supplementary Data 7. siRNA sequences are described in Supplementary Data 8. Primer sequences used in this study are described in Supplementary Data 9. Source data are provided with this paper.
Christofferson, D. E., Li, Y. & Yuan, J. Control of life-or-death decisions by RIP1 kinase. Annu. Rev. Physiol. 76, 129–150 (2014).
Festjens, N., Vanden Berghe, T., Cornelis, S. & Vandenabeele, P. RIP1, a kinase on the crossroads of a cell’s decision to live or die. Cell Death Differ. 14, 400–410 (2007).
Declercq, W., Vanden Berghe, T. & Vandenabeele, P. RIP kinases at the crossroads of cell death and survival. Cell 138, 229–232 (2009).
Weinlich, R. & Green, D. R. The two faces of receptor interacting protein kinase-1. Mol. Cell 56, 469–480 (2014).
Micheau, O. & Tschopp, J. Induction of TNF receptor I-mediated apoptosis via two sequential signaling complexes. Cell 114, 181–190 (2003).
Sun, L. et al. Mixed lineage kinase domain-like protein mediates necrosis signaling downstream of RIP3 kinase. Cell 148, 213–227 (2012).
Silke, J., Rickard, J. A. & Gerlic, M. The diverse role of RIP kinases in necroptosis and inflammation. Nat. Immunol. 16, 689–697 (2015).
Dillon, C. P. et al. RIPK1 blocks early postnatal lethality mediated by caspase-8 and RIPK3. Cell 157, 1189–1202 (2014).
Zhang, H. et al. Functional complementation between FADD and RIP1 in embryos and lymphocytes. Nature 471, 373–376 (2011).
Kelliher, M. A. et al. The death domain kinase RIP mediates the TNF-induced NF-kappaB signal. Immunity 8, 297–303 (1998).
Rickard, J. A. et al. RIPK1 regulates RIPK3-MLKL-driven systemic inflammation and emergency hematopoiesis. Cell 157, 1175–1188 (2014).
Takahashi, N. et al. RIPK1 ensures intestinal homeostasis by protecting the epithelium against apoptosis. Nature 513, 95–99 (2014).
Kuma, A. et al. The role of autophagy during the early neonatal starvation period. Nature 432, 1032–1036 (2004).
Galluzzi, L., Pietrocola, F., Levine, B. & Kroemer, G. Metabolic control of autophagy. Cell 159, 1263–1276 (2014).
Rabinowitz, J. D. & White, E. Autophagy and metabolism. Science 330, 1344–1348 (2010).
Kaur, J. & Debnath, J. Autophagy at the crossroads of catabolism and anabolism. Nat. Rev. Mol. Cell Biol. 16, 461–472 (2015).
Wang, X. et al. RNA viruses promote activation of the NLRP3 inflammasome through a RIP1-RIP3-DRP1 signaling pathway. Nat. Immunol. 15, 1126–1133 (2014).
Biton, S. & Ashkenazi, A. NEMO and RIP1 control cell fate in response to extensive DNA damage via TNF-alpha feedforward signaling. Cell 145, 92–103 (2011).
Chen, W. et al. RIP1 maintains DNA integrity and cell proliferation by regulating PGC-1alpha-mediated mitochondrial oxidative phosphorylation and glycolysis. Cell Death Differ. 21, 1061–1070 (2014).
Zoncu, R. et al. mTORC1 senses lysosomal amino acids through an inside-out mechanism that requires the vacuolar H(+)-ATPase. Science 334, 678–683 (2011).
Birsoy, K. et al. An essential role of the mitochondrial electron transport chain in cell proliferation is to enable aspartate synthesis. Cell 162, 540–551 (2015).
Sullivan, L. B. et al. Supporting aspartate biosynthesis is an essential function of respiration in proliferating cells. Cell 162, 552–563 (2015).
Zhang, L. H. et al. Small molecule regulators of autophagy identified by an image-based high-throughput screen. Proc. Natl Acad. Sci. USA 104, 19023–19028 (2007).
Cai, Y. & Zhu, Z. J. An integrated targeted metabolomic platform for high-throughput metabolite profiling and automated data processing. Metabolomics 11, 1575–1586 (2015).
Xu, T. et al. Metabolic control of TH17 and induced Treg cell balance by an epigenetic mechanism. Nature 548, 228–233 (2017).
Zuhra, K., Augsburger, F., Majtan, T. & Szabo, C. Cystathionine-β-synthase: molecular regulation and pharmacological inhibition. Biomolecules 10, 697 (2020).
Kim, J., Kundu, M., Viollet, B. & Guan, K. L. AMPK and mTOR regulate autophagy through direct phosphorylation of Ulk1. Nat. Cell Biol. 13, 132–141 (2011).
Mihaylova, M. M. & Shaw, R. J. The AMPK signalling pathway coordinates cell growth, autophagy and metabolism. Nat. Cell Biol. 13, 1016–1023 (2011).
Hardie, D. G. AMP-activated/SNF1 protein kinases: conserved guardians of cellular energy. Nat. Rev. Mol. Cell Biol. 8, 774–785 (2007).
Egan, D. F. et al. Phosphorylation of ULK1 (hATG1) by AMP-activated protein kinase connects energy sensing to mitophagy. Science 331, 456–461 (2011).
Madiraju, A. K. et al. Argininosuccinate synthetase regulates hepatic AMPK linking protein catabolism and ureagenesis to hepatic lipid metabolism. Proc. Natl Acad. Sci. USA 113, E3423–3430 (2016).
Kollmar, R., Sukow, K. A., Sponagle, S. K. & Farnham, P. J. Start site selection at the TATA-less carbamoyl-phosphate synthase (glutamine-hydrolyzing)/aspartate carbamoyltransferase/dihydroorotase promoter. J. Biol. Chem. 269, 2252–2257 (1994).
Kollmar, R., Lindstrom, M. J. & Farnham, P. J. Heat sensitivity and Sp1 activation of complex formation at the Syrian hamster carbamoyl-phosphate synthase (glutamine-hydrolyzing)/aspartate carbamoyltransferase/dihydroorotase promoter in vitro. J. Biol. Chem. 267, 385–391 (1992).
Leung-Pineda, V. & Kilberg, M. S. Role of Sp1 and Sp3 in the nutrient-regulated expression of the human asparagine synthetase gene. J. Biol. Chem. 277, 16585–16591 (2002).
Brasse-Lagnel, C. et al. Glutamine and interleukin-1beta interact at the level of Sp1 and nuclear factor-kappaB to regulate argininosuccinate synthetase gene expression. FEBS J. 274, 5250–5262 (2007).
Chu, S. Transcriptional regulation by post-transcriptional modification–role of phosphorylation in Sp1 transcriptional activity. Gene 508, 1–8 (2012).
Jackson, S. P., MacDonald, J. J., Lees-Miller, S. & Tjian, R. GC box binding induces phosphorylation of Sp1 by a DNA-dependent protein kinase. Cell 63, 155–165 (1990).
Degterev, A. et al. Chemical inhibitor of nonapoptotic cell death with therapeutic potential for ischemic brain injury. Nat. Chem. Biol. 1, 112–119 (2005).
Yu, J. S. & Cui, W. Proliferation, survival and metabolism: the role of PI3K/AKT/mTOR signalling in pluripotency and cell fate determination. Development 143, 3050–3060 (2016).
Kolwicz, S. C. Jr., Purohit, S. & Tian, R. Cardiac metabolism and its interactions with contraction, growth, and survival of cardiomyocytes. Circulation Res. 113, 603–616 (2013).
Kuma, A., Komatsu, M. & Mizushima, N. Autophagy-monitoring and autophagy-deficient mice. Autophagy 13, 1619–1628 (2017).
Yonekawa, T. et al. RIP1 negatively regulates basal autophagic flux through TFEB to control sensitivity to apoptosis. EMBO Rep. 16, 700–708 (2015).
Zhang, D. W. et al. RIP3, an energy metabolism regulator that switches TNF-induced cell death from apoptosis to necrosis. Science 325, 332–336 (2009).
Najafov, A. et al. RIPK1 promotes energy sensing by the mTORC1 pathway. Mol. Cell 81, 370–385 e377 (2021).
Delanghe, T., Dondelinger, Y. & Bertrand, M. J. M. RIPK1 kinase-dependent death: a symphony of phosphorylation events. Trends Cell Biol. 30, 189–200 (2020).
Declercq, W., Vanden Berghe, T. & Vandenabeele, P. RIP kinases at the crossroads of cell death and survival. Cell 138, 229–232 (2009).
Degterev, A., Ofengeim, D. & Yuan, J. Targeting RIPK1 for the treatment of human diseases. Proc. Natl Acad. Sci. USA 116, 9714–9722 (2019).
Cai, Y. & Zhu, Z. J. A high-throughput targeted metabolomics workflow for the detection of 200 polar metabolites in central carbon metabolism. Methods Mol. Biol. 1859, 263–274 (2019).
We thank Prof. Jiahuai Han (Xiamen University, China) for kindly providing the RIPK1−/− HEK293T cells, and Prof. Michelle Kelliher (UMass medical school) for kindly providing the Ripk1−/− mice. This work was financially supported by grants from the National Natural Science Foundation of China (31801167, 31971356, and 92057114), and Shanghai Municipal Science and Technology Major Project (2019SHZDZX02). X.M. is also supported by Shanghai Municipal Science and Technology Commission (17YF1424200). Z.-J.Z. is supported by the Excellent Young Scholar Fund from the National Natural Science Foundation of China (22022411).
The authors declare no competing interests.
Peer review information Nature Communications thanks Zachary Schafer and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Mei, X., Guo, Y., Xie, Z. et al. RIPK1 regulates starvation resistance by modulating aspartate catabolism. Nat Commun 12, 6144 (2021). https://doi.org/10.1038/s41467-021-26423-4