To survive in challenging environments, animals must develop a system to assess food quality and adjust their feeding behavior accordingly. However, the mechanisms that regulate this chronic physiological food evaluation system, which monitors specific nutrients from ingested food and influences food-response behavior, are still not fully understood. Here, we established a low-quality food evaluation assay system and found that heat-killed E. coli (HK-E. coli), a low-sugar food, triggers cellular UPRER and immune response. This encourages animals to avoid low-quality food. The physiological system for evaluating low-quality food depends on the UPRER (IRE-1/XBP-1) - Innate immunity (PMK-1/p38 MAPK) axis, particularly its neuronal function, which subsequently regulates feeding behaviors. Moreover, animals can adapt to a low-quality food environment through sugar supplementation, which inhibits the UPRER -PMK-1 regulated stress response by increasing vitamin C biosynthesis. This study reveals the role of the cellular stress response pathway as physiological food evaluation system for assessing nutritional deficiencies in food, thereby enhancing survival in natural environments.
eLife digest
We quickly learn to steer clear of eating the moldy apple, the foul-smelling piece of chicken or the leftovers that taste a little ‘off’. This survival instinct is shared across most animal species – even those with extremely simple and limited visual or taste systems, like the tiny worm Caenorhabditis elegans. Indeed, assessing the safety and quality of available food items can also rely on cells activating built-in cascades of molecular reactions. However, it remains unclear how these ‘cellular stress response programs’ actually help guide feeding behaviors.
To better understand this process, Liu et al. conducted a series of experiments using C. elegans worms exposed to heat-killed bacteria, which are devoid of many nutrients essential for growth. After initially consuming these bacteria, the worms quickly started to avoid feeding on this type of low-quality food. This suggests that mechanisms occurring after ingestion allowed the worms to adjust their feeding choices.
Further work showed that the consumption of heat-killed bacteria triggered two essential stress response pathways, known as the unfolded protein response and the innate immune response. The activation of these pathways was essential for the animals to be able to change their behavior and avoid the heat-killed bacteria. These biochemical pathways were particularly active in the worms’ nerve cells, highlighting the importance of these cells in sensing and reacting to food. Finally, Liu et al. also found that adding sugars like lactose and sucrose to the low-quality food could prevent the activation of the stress response pathways. This result suggests that specific nutrients play a central role in how these worms decide what to eat.
These findings shed light on the complex systems that ensure organisms consume the nutritious food they need to survive. Understanding these processes in worms can provide insights into the broader biological mechanisms that help animals avoid harmful food.
aversion behaviorUPRERmmune responsefood quality evaluationfood sensingC. elegansResearch organismC. elegansE. colihttp://dx.doi.org/10.13039/501100002855Ministry of Science and Technology of the People's Republic of China2019YFA0802100QiBinhttp://dx.doi.org/10.13039/501100001809National Natural Science Foundation of China32170794QiBinYunnan Provincial Science and Technology Project at Southwest United Graduate School202302AP370005QiBinhttp://dx.doi.org/10.13039/501100008871Yunnan Provincial Science and Technology Department202201AT070196QiBinScience and Technology Talent Cultivation Plan of Yunnan ProvinceK264202230211QiBinhttp://dx.doi.org/10.13039/501100002855Ministry of Science and Technology of the People's Republic of China2019YFA0803100QiBinThe funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.Author impact statementThe cellular stress response pathway helps animals evaluate food quality and regulate feeding behavior to adapt in nutrient-deficient environments.publishing-routeprcIntroduction
Food is essential for the survival, growth, and fitness of all animals. To adapt to fluctuating environments with a wide range of food sources, animals have developed a food evaluation system. This system enables them to identify nutrient-rich food and avoids low-quality or toxic food, thereby maximizing their survival prospects (Filosa et al., 2016; Florsheim et al., 2021; McLachlan et al., 2022). Various sensory neuron evaluation systems in animals has evolved to evaluate food quality through vision (Avery et al., 2021; Melin et al., 2019), olfactory (Bargmann, 2006; Chalasani et al., 2007; Fiala, 2007; Ha et al., 2010; McLachlan et al., 2022; Sengupta et al., 1996; Troemel et al., 1997; Zhang et al., 2021) and gustatory senses (Hukema et al., 2006; Ni et al., 2013; Scott, 2018). Besides these sensory systems that facilitate quick feeding decisions, animals may also initiate cellular stress response programs to detect nutrition/toxin and trigger food response behaviors (Jones and Candido, 1999; Xie et al., 2022). This could be one of physiological food quality evaluation systems that monitor the nutritional status of consumed food. However, the signaling events in cellular stress responses involved in evaluating of specific nutrients and the mechanisms that connect these signaling activities to food behaviors are largely unexplored. More specifically, while cellular stress response through UPRER (Richardson et al., 2010) and PMK-1/p38 MAPK (Kim et al., 2002)-dependent immunity in response to pathogens have been extensively studied, the functions of these cellular stress response in sensing and evaluating specific nutrients from food remain unclear.
Vitamin C is an essential micronutrient that cannot be synthesized by humans due to the loss of a key enzyme in the biosynthetic pathway (Carr and Maggini, 2017). Animals obtain vitamin C from their diet and possibly also from gut microbes (Steinert et al., 2020). Vitamin C is an important physiological antioxidant and a cofactor for a family of biosynthetic and gene regulatory monooxygenase and dioxygenase enzymes. It is also required for the biosynthesis of collagen, L-carnitine, and certain neurotransmitters (Carr and Frei, 1999; Li and Schellhorn, 2007). Vitamin C has been associated with various human diseases including scurvy, immune defect and cardiovascular disease (Carr and Maggini, 2017).
Therefore, in animals, having robust food evaluation systems to detect vitamin C levels could significantly impact their survival in the wild. However, the potential involvement of the cellular stress response pathway in this food evaluation system for sensing and assessing vitamin C remains largely unexplored.
In this study, using the low-quality food evaluation assay system we established (Qi et al., 2017), we elucidated the mechanism by which the cellular stress response pathway operates as a physiological food evaluation system. This pathway assesses the deficiency of D-glucose in food and the subsequent vitamin C content in animals through the unfolded protein response (UPRER) - innate immunity (PMK-1/p38 MAPK) axis. This mechanism promotes animals to leave low-quality food and is critical for their survival in nature environments.
ResultsLow-quality food induces stress response in animals
Our previous studies have shown that Heat-killed E. coli (HK-E. coli), which lacks certain molecules, is considered a low-quality food that is unable to support animal growth (Qi and Han, 2018; Qi et al., 2017). Moreover, through metabolic-seq analysis, we identified significant changes in a large numbers of derivatives (Figure 1—figure supplement 1A, Supplementary file 1a), including lipids and their derivatives (Figure 1—figure supplement 1B, Supplementary file 1b), amino acid and their metabolites (Figure 1—figure supplement 1C, Supplementary file 1c), as well as coenzymes and vitamins (Figure 1—figure supplement 1D, Supplementary file 1d). Interestingly, we observed a significant decrease in carboxylic acids and their derivatives (Figure 1—figure supplement 1E, Supplementary file 1e) in E. coli after being heat-killed (Figure 1—figure supplement 1F, Supplementary file 1f). This suggests that HK-E. coli is nutritionally deficient for C. elegans when compared to normal E. coli food.
Next, we conducted two behavior assays to facilitate the analysis of the food evaluation process in animals by seeding L1 animals in assay plates (Figure 1A and B). In the avoidance assay, wild-type animals avoided the HK-E. coli OP50 (HK-OP50) food (Figure 1A). Interestingly, in the food choice assay, animals initially showed no preference between the two types of food (1–2 hr), but eventually exhibited a preference for high-quality food (Live E. coli) up until the 17 hr mark (Figure 1B, Figure 1—figure supplement 1G). This suggests that worms depart from the HK-E. coli after recognizing it as low-quality food source through ingestion.
The stress response is induced in animals fed low-quality food, HK-<italic>E</italic>. <italic>coli</italic>.
(A) Schematic drawing and quantitative data of the food aversion assay. Circles indicate the food spot for live (yellow) and HK-OP50 (red) bacteria, respectively. The animals were scored 16–17 hr after L1 worms were placed on the food spot. Data are represented as mean ± SD from three independent experiments, 79–129 animals/assay. (B) Schematic method and quantitative data of the food selection assay. Live (yellow), heat-killed (red) E. coli and LB as the buffer for E. coli were placed on indicated position. Synchronized L1 worms were place in the center spot. The selection index was calculated at the indicated time. Data are represented as mean ± SD from eight independent experiments, 123–792 animals/assay. (C) GO enrichment analysis of up-regulated genes in animals fed with HK-E. coli vs live E. coli. (D) Venn diagram showing numbers of UPRER target genes and up-regulated genes in animals fed HK-E. coli, and their overlap. (E) Venn diagram showing numbers of induction genes by four pathogenic bacteria and HK-E. coli induced genes, and their overlap. The gene expression data was extracted from published data of animals’ infection with Pseudomonas aeruginosa (PA) (Nakad et al., 2016), Bacillus thuringiensis (Bthu) (Sinha et al., 2012), Staphylococcus aureus (Saur) (Sinha et al., 2012), and Serratia marcescens (Smar) (Sinha et al., 2012). (F–G) GFP fluorescence images and bar graph showing that Phsp-4::GFP (F) and Pirg-5::GFP (G) were induced in animals fed with HK-E. coli. Blue numbers are the number of worms scored from at least three independent experiments. Data are represented as mean ± SD. For all panels, Scale bar shows on indicated figures, 50 μm. * p<0.05, ** p<0.01, *** p<0.001, **** p<0.0001, ns: no significant difference. Precise p values are provided in Raw Data.
Numerical data of <xref ref-type="fig" rid="fig1">Figure 1A–B and F–G</xref> and <xref ref-type="fig" rid="fig1s1">Figure 1—figure supplement 1G</xref>.
Food selection assay of animals fed HK-<italic>E</italic>. <italic>coli</italic> or <italic>E. coli</italic>.
Relative to Figure 1. (A–E) Metabolomics analysis of different quality food (HK-K12, HK-yfbR and Live-K12). Cluster analysis of all metabolites (A), lipids and their derivatives (B), amino acids and their derivatives (C), coenzymes and vitamins (D), and carbohydrates and their derivatives (E) from Live-K12, HK-K12, and HK-yfbR. Color indicates the relative level of each metabolite. HK-K12: heat-killed E. coli wild-type K12; HK-yfbR: heat-killed E. coli mutant yfbR; K12: live E. coli wild-type K12. z-score for standardizing data, complete for bi-clustering algorithm, and Euclidean for distance method. (F) Principal component analysis to test the repeatability of the metabolic experiment. HK-K12: heat-killed E. coli wild-type K12; HK-yfbR: heat-killed E. coli mutant yfbR; K12: live E. coli wild-type K12. LB: LB buffer for culturing E. coli. (G) The number of worms in each position calculated at the indicated time, indicating that animals initially select both foods (1–2 hr), but eventually favor high-quality food (Live E. coli) until 17 hr. (H) GO enrichment analysis of UPRER dependent IRE-1 branch. For all panels, * p<0.05, ** p<0.01, *** p<0.001, **** p<0.0001, ns: no significant difference. Precise p values are provided in Raw Data.
Stress response of animals fed HK-<italic>E</italic>. <italic>coli</italic> or <italic>E. coli</italic>.
Relative to Figure 1. (A) UPRER reporter (Phsp-4::GFP) and immunity reporter (Pirg-5::GFP) were induced in the neuron and intestine of animals fed with HK-E. coli. Neurons are highlighted with a red arrow. (B) UPRmit reporter (Phsp-6::GFP) was weakly induced in animals fed with HK- E. coli. (C) UPRER reporter (Phsp-4::GFP) expression in animals under normal food (OP50), low-quality food (HK-OP50), and starved (M9: hatching L1 worm in M9, NGM) condition; L1 animals were cultured in OP50, HK-OP50 or starved NGM for 20 hr. (D) Immunity reporter (Pirg-5::GFP) expression in animals under normal food (OP50), low-quality food (HK-OP50), and starved (M9: hatching L1 worm in M9, NGM). L1 animals were cultured in OP50, HK-OP50 or starved NGM for 20 hr. For all panels, Scale bar shows on indicated figures, 50 μm.
In order to investigate the pathways in animals that respond to HK-E. coli, we performed transcriptomics analysis on worms that were cultured with both HK-E. coli and Live E. coli. Gene-expression profiling revealed that stress response genes, including those related to biotic stimulus, immune response and response to stress, are up-regulated in animals fed with HK-E. coli OP50 (HK-OP50; Figure 1C, Supplementary file 2a). Among these up-regulated genes, we identified 11 out of 62 of UPRER target genes (Figure 1D, Figure 1—figure supplement 1H and Supplementary file 2b). Additionally, about 50–80% of up-regulated genes overlap with genes responding pathogenic bacteria (Nakad et al., 2016; Sinha et al., 2012; Figure 1E, Supplementary file 2c). Consistent with the results of the RNA sequencing (RNA-seq) analysis, the UPRER reporter (Phsp-4::GFP) (Calfon et al., 2002) and immunity reporter (Pirg-5::GFP)(Bolz et al., 2010) were strongly induced in intestine (Figure 1F–G) and neurons (Figure 1—figure supplement 2A) by feeding unfavorable food (HK-E. coli OP50), suggesting that UPRER and immune pathways may respond to low-quality food (HK-E. coli OP50). As intestinal fluorescence (Phsp-4::GFP or Pirg-5::GFP) is easy observation and scoring, the further analyses were done in the intestine.
Moreover, UPRMt reporter (Phsp-6::GFP) (Yoneda et al., 2004) was weakly induced under HK-E. coli feeding condition (Figure 1—figure supplement 2B), and starved worm did not induce UPRER and immunity (Figure 1—figure supplement 2C–D).
Together, these findings suggest that low-quality food (HK-E. coli OP50) triggers a stress response pathway in animals, including UPRER and innate immune pathway. This implies that animals may assess the quality of food through UPRER and innate immune pathway.
Animals evaluate food quality through UPR<sup>ER</sup>-immune-dependent physiological food quality evaluation system
To determine whether the UPRER and innate immune pathways play a role in evaluating low-quality food, we first examined whether the activation of the UPRER by HK-E. coli was dependent on the known signaling components of the UPRER branches, including IRE/XBP-1, PERK/ATF-4 and ATF-6 (Hetz et al., 2020; Ron and Walter, 2007). We observed no difference in Phsp-4::GFP induction with atf-4 (Figure 2—figure supplement 1A) or atf-6 (Figure 2—figure supplement 1B) RNAi-mediated knockdown in animals fed with HK-E. coli. However, knockdown of ire-1/xbp-1 or mutation of xbp-1 reduced GFP fluorescence (Figure 2A and B). Among the 11 differentially expressed UPRER target genes in animals fed with HK-E. coli from RNA-seq (Figure 1D), 64% of the genes are IRE-mediated genes (Figure 1—figure supplement 1H, Supplementary file 2d). The mRNA level of IRE-1-mediated splicing of xbp-1 (Calfon et al., 2002) is also induced in animals fed with HK-E. coli OP50 (Figure 2—figure supplement 1C). However, UPRER is not affected in animals feeding live-E. coli by RNAi of ire-1, xpb-1, atf-4, and atf-6 (Figure 2—figure supplement 1D). These data suggest that activation of the UPRER by low-quality food (HK-E. coli) depends on the IRE-1/XBP-1.
(A–B) GFP fluorescence images and bar graph showing that HK-E. coli induced Phsp-4::GFP was decreased in animals with ire-1 or xbp-1 RNAi treatment (A) or xbp-1 mutation (B). Blue numbers are the number of worms scored from at least three independent experiments. Data are represented as mean ± SD. (C) Food aversion assay showing that xbp-1 mutation eliminated the discrimination against HK-E. coli. However, this effect is rescued by expressing xbp-1 in neurons rather than intestine. Data are represented as mean ± SD from five independent experiments, 156–763 animals/assay. (D) GFP fluorescence images and bar graph showing that HK-E. coli induced Pirg-5::GFP was decreased in animals with pmk-1 RNAi treatment. Blue numbers are the number of worms scored from at least three independent experiments. Data are represented as mean ± SD. (E) Western blot images showing the level of p-PMK-1 in L1 animals (Wild-type N2 and xbp-1 mutant) fed with OP50 or HK-OP50 for 4 hr. The level of p-PMK-1 is induced in animals fed HK-OP50. (F) Food aversion assay showing that pmk-1 mutation eliminated the discrimination against HK-E. coli. However, this effect is rescued by expressing pmk-1 in neurons rather than intestine. Data are represented as mean ± SD from five independent experiments, 168–492 animals/assay. (G) Food aversion assay in wild-type, xbp-1, pmk-1 and double mutant. Data are represented as mean ± SD from five independent experiments, 259–490 animals/assay. For all panels, Scale bar shows on indicated figures, 50 μm. * p<0.05, ** p<0.01, *** p<0.001, **** p<0.0001, ns: no significant difference. Precise p values are provided in Raw Data.
Numerical data of <xref ref-type="fig" rid="fig2">Figure 2A–D and F–G</xref>; <xref ref-type="fig" rid="fig2s1">Figure 2—figure supplement 1A–C, F–H</xref>; and <xref ref-type="fig" rid="fig2s2">Figure 2—figure supplement 2A–C</xref>.
The raw western bolts for <xref ref-type="fig" rid="fig2">Figure 2E</xref> (labelled).
The raw western bolts for <xref ref-type="fig" rid="fig2">Figure 2E</xref> (unlabelled, uncropped).
UPR<sup>ER</sup> and innate immunity pathway in animals are critical for evaluating HK-<italic>E</italic>. <italic>coli</italic>.
Relative to Figure 2. (A–B) GFP fluorescence images and bar graph showing that HK-E. coli induced Phsp-4::GFP was not affected in animals with atf-4 (A) or atf-6 (B) RNAi treatment. Blue numbers are the number of worms scored from at least three independent experiments. Data are represented as mean ± SD. (C) qPCR showing that IRE-1-mediated splicing of xbp-1 mRNA is induced in animals fed with HK-E. coli. (D) UPRER reporter (Phsp-4::GFP) expression in animals with candidate RNAi feeding OP50 or HK-OP50. (E) Venn diagram showing the numbers of PMK-1-dependent genes 30 and up-regulated genes in animals fed HK-E. coli, and their overlap. (F) The expression of PMK-1-dependent genes which was extracted from RNA-seq data from animals fed with HK-E. coli. The data from average of three independent experiments. (G–H) GFP fluorescence images and bar graph showing that Psysm-1::GFP (G) and Pirg-1::GFP (H) were induced in animals fed HK-E. coli. Blue numbers are the number of worms scored from at least three independent experiments. Data are represented as mean ± SD. (I) Immunity reporter (Pirg-5::GFP) expression in animals with candidate RNAi feeding OP50 or HK-OP50. For all panels, Scale bar shows on indicated figures, 50 μm. * p<0.05, ** p<0.01, *** p<0.001, **** p<0.0001, ns: no significant difference. Precise p values are provided in Raw Data.
UPR<sup>ER</sup> positively regulates innate immunity pathway in animals.
Relative to Figure 2. (A) GFP fluorescence images and bar graph showing that HK-E. coli induced Pirg-5::GFP was decreased in animals with ire-1 or xbp-1 RNAi treatment. Blue numbers are the number of worms scored from at least three independent experiments. Data are represented as mean ± SD. (B) GFP fluorescence images and bar graph showing that Phsp-4::GFP was not affected in animals with pmk-1 RNAi treatment. Blue numbers are the number of worms scored from at least three independent experiments. Data are represented as mean ± SD. (C) Images and bar graph showing that the avoidance behavior of N2, xbp-1 mutant, and pmk-1 mutant in response to different food source (Saprophytic staphylococci-SS, Pseudomonas aeruginosa-PA14, or OP50). ‘Broder’ indicates regions with thicker SS boundaries; ‘In’ denotes areas inside SS; ‘Out’ refers to areas without SS. The scale is as follows: 2 for animals capable of escaping from PA14 and feeding on PA14 located with edges; 1 for animals capable of escaping from PA14 but not feeding on PA14 located with edges; 0 for animals unable to escape from PA14 and being killed by PA14. Data are represented as mean ± SD from five independent experiments, 359–670 animals/assay. For all panels, Scale bar shows on indicated figures, 50 μm. * p<0.05, ** p<0.01, *** p<0.001, **** p<0.0001, ns: no significant difference. Precise p values are provided in Raw Data.
To further analyze whether XBP-1-dependent UPRER activation is critical for animals to leave low-quality food, we tested food avoidance behavior using xbp-1 mutant. The results show that xbp-1 mutants had a significantly decreased likelihood of leaving of HK-E. coli, which was rescued by expressing xbp-1 in neuron rather than intestine (Figure 2C). This indicates that XBP-1-dependent UPRER activation in neuron is critical for animals to specific evaluate low-quality food (HK-E. coli).
We then investigated which innate immune pathway is involved in evaluating low-quality food. First, we analyzed HK-E. coli-induced genes from RNA-seq. Among these up-regulated genes, 82 out of 409 of PMK-1-dependent genes (Fletcher et al., 2019) were identified (Figure 2—figure supplement 1E, Supplementary file 2c). Second, we confirmed the induction of several well-known PMK-1 target genes in RNA-seq data (Foster et al., 2020; Figure 2—figure supplement 1F) and reporter analysis (Figure 2—figure supplement 1G–H). Moreover, the induction of Pirg-5::GFP was abolished in pmk-1 knockdown animals fed with HK-E. coli (Figure 2D). Third, we found that the phosphorylated PMK-1 (p-PMK-1) level was prominently increased in wild-type N2 animals fed HK-E. coli compared to feeding E. coli OP50 (Figure 2E). Finally, pmk-1 mutants had a decreased likelihood of leaving of HK-E. coli, which was rescued by expressing pmk-1 in neurons rather than intestine (Figure 2F). Moreover, Pirg-5::GFP is not affected in animals feeding live-E. coli by RNAi of pmk-1 (Figure 2—figure supplement 1I).These data suggest that PMK-1 regulated immune pathway evaluates low-quality food, especially the neuronal PMK-1 has a critical function for food quality response.
XBP-1 and PMK-1 are in the same pathway for evaluating food quality
Next, we explored the connection between UPRER (IRE-1/XBP-1) and innate immunity (PMK-1 p38 MAPK) in food quality evaluation. We found that Pirg-5::GFP induction (Figure 2—figure supplements 1I and 2A) and PMK-1 activation (Figure 2E) were decreased in animals with xbp-1 mutation or knockdown when fed with HK-E. coli, suggesting that XBP-1 could regulate PMK-1 under this condition. Additionally, Phsp-4::GFP induction under HK-E. coli was not affected in animals with pmk-1 RNAi (Figure 2—figure supplements 1D and 2B), indicating that XBP-1-dependent UPRER activation is not regulated by PMK-1. Finally, we constructed a double mutant of xbp-1 and pmk-1 and found that the food avoidance phenotype of the double mutant was similar to the pmk-1 mutant (Figure 2G), indicating that PMK-1 is downstream of XBP-1 in responding to low-quality food.
We then asked whether UPRER (IRE-1/XBP-1) - Innate immunity (PMK-1/p38 MAPK) axis is specific to evaluate low-quality food (HK-E. coli). We performed behavior assay in N2, pmk-1 and xbp-1 mutant animals by feeding normal E. coli food, inedible food (Saprophytic staphylococci) (Geng et al., 2022) and pathogenic food (Pseudomonas aeruginosa-PA14; Richardson et al., 2010). We found that N2, pmk-1, and xbp-1 mutant worms did not exhibit avoidance behavior when presented with normal food (OP50). However, both N2 and xbp-1 mutant worms were able to escape from inedible food (N2 was predominantly found on the border areas of the bacterial lawn and xbp-1 mutant worms on border and in), Saprophytic staphylococci, whereas pmk-1 mutant worms did not exhibit this avoidance behavior. Notably, N2 and xbp-1 mutant worms exhibited even more pronounced avoidance behavior when exposed to Pseudomonas aeruginosa, whereas pmk-1 mutant worms were more susceptible to infection by this pathogen (Figure 2—figure supplement 2C). These findings suggest that the UPR-Immunity pathway plays a crucial role in helping animals avoid low-quality food (HK-E. coli) by triggering an avoidance response. In contrast, the Innate immunity pathway, which is mediated by PMK-1/p38 MAPK, appears to play a key role in evaluating unfavorable food sources, such as HK-E. coli, Saprophytic staphylococci, and Pseudomonas aeruginosa, and helping animals avoid these environments.
Sugar deficiency in HK-<italic>E. coli</italic> food induces stress response and avoidance behavior in animals
We then investigated which nutrients/metabolites are sensed by animals through the XBP-1-PMK-1 axis for food quality evaluation. First, we hypothesized that the nutrition status is improved in E. coli mutant (HK-treatment), which could inhibit UPRER and immune response in animals. We established a system for screening the E. coli mutant Keio library (Figure 3—figure supplement 1A), and identified 20 E. coli mutants that did not induce Phsp-4::GFP through the UPRER reporter (Phsp-4::GFP) after three rounds of screening (Supplementary file 3a). From these 20 E. coli mutants, we identified 9 E. coli mutants that did not induce Pirg-5::GFP through the immunity reporter (Pirg-5::GFP) screening (Figure 3—figure supplement 1B–C, Supplementary file 3a). Animals fed HK-yfbR, which catalyzes carbohydrate derivative metabolic process (Weiss, 2007), had a decreased ability to leave food (Figure 3A, Supplementary file 3a), indicating that HK-yfbR may be a higher quality food for animals compared to HK-K12.
HK-<italic>E</italic>. <italic>coli</italic> is low sugar food, which induce stress response and avoidance behavior in animals.
(A) Food aversion assay showing that wild-type animals eliminated the discrimination against HK-E. coli when yfbR is mutated in E. coli. Data are represented as mean ± SD four independent experiments, 251–490 animals/assay. (B) Heat map showing the 13 differential metabolites from HK-K12, HK-yfbR, and K12 in four independent experiments. Color indicates the relative level of each metabolite. (C–D) The bar graph showing that HK-E. coli induced Phsp-4::GFP was decreased in animals with lactose (C) or D-(+)-sucrose (D) supplementation. Blue numbers are the number of worms scored from at least three independent experiments. Data are represented as mean ± SD. (E–F) GFP fluorescence images and bar graph showing that HK-E. coli induced Phsp-4::GFP (E) and Pirg-5::GFP (F) were decreased in animals with D-(+)-glucose (D-Glc) supplementation. Blue numbers are the number of worms scored from at least three independent experiments. Data are represented as mean ± SD. (G) Western blot images showing the level of p-PMK-1 in L1 animals fed HK-E. coli with or without D-(+)-glucose (D-Glc) supplementation for 4 hr. The level of p-PMK-1 is decreased in animals fed HK-OP50 +D Glc. (H) Food aversion assay showing that wild-type animals eliminated the discrimination against HK-E. coli with D-Glc supplementation. Data are represented as mean ± SD six independent experiments, 190–492 animals/assay. For all panels, Scale bar shows on indicated figures, 50 μm. * p<0.05, ** p<0.01, *** p<0.001, **** p<0.0001, ns: no significant difference. Precise p values are provided in Raw Data.
Numerical data of <xref ref-type="fig" rid="fig3">Figure 3A, C–F and H</xref>; <xref ref-type="fig" rid="fig3s1">Figure 3—figure supplement 1B–C</xref>; and <xref ref-type="fig" rid="fig3s2">Figure 3—figure supplement 2C–D, G</xref>.
The raw western bolts for <xref ref-type="fig" rid="fig3">Figure 3G</xref> (labelled).
The raw western bolts for <xref ref-type="fig" rid="fig3">Figure 3G</xref> (unlabelled, uncropped).
<italic>E. coli</italic> Keio mutant screening.
Relative to Figure 3. (A) Flow chart of strategy for E. coli Keio mutant screening. We identified 20 E. coli mutants that did not induce hsp-4::GFP through the UPRER reporter (Pirg-5::GFP) after three rounds of screening (Supplementary file 3a). From these 20 E. coli mutants, we identified 9 E. coli mutants that did not induce Pirg-5::GFP through the immunity reporter (Pirg-5::GFP) screening (Supplementary file 3a). (B–C) The bar graph showing that HK-E. coli induced Phsp-4::GFP (B) and Pirg-5::GFP (C) was decreased in animals fed mutant E. coli (Heat-killed). Blue numbers are the number of worms scored from at least three independent experiments. Data are represented as mean ± SD. For all panels, * p<0.05, ** p<0.01, *** p<0.001, **** p<0.0001, ns: no significant difference. Precise p values are provided in Raw Data.
Low sugar food, HK-<italic>E</italic>. <italic>coli</italic>, induce stress response and avoidance behavior in animals.
Relative to Figure 3. (A) Venn diagram showing the number of differentially metabolites in HK-E. coli-K12, HK-E. coli-yfbR and E. coli. (B) KEGG enrichment analysis of differentially expressed genes in animals fed HK-E. coli vs live E. coli. We noticed that most of glycolysis/gluconeogenesis genes are up-regulated in animals fed HK-E. coli. (C) The bar graph showing that HK-E. coli induced Phsp-4::GFP was not affected in animals with D-(+)-trehalose supplementation. Blue numbers are the number of worms scored from at least three independent experiments. Data are represented as mean ± SD. (D) GFP fluorescence images and bar graph showing that HK-E. coli induced Psysm-1::GFP was decreased in animals with D-(+)-glucose (D-Glc) supplementation. Blue numbers are the number of worms scored from at least three independent experiments. Data are represented as mean ± SD. (E) UPRER reporter (Phsp-4::GFP) expression animals with D-Glc supplementation under OP50, HK-OP50, or NGM condition. (F) immunity reporter (Pirg-5::GFP) expression animals with D-Glc supplementation under OP50, HK-OP50, or NGM condition. (G) Development of animals after 48 h fed with OP50, HK-OP50, HK-OP50 +D Glc, and HK-OP50 +D GlcA. Blue numbers are the number of worms scored from at least three independent experiments. Data are represented as mean ± SD. For all panels, Scale bar shows on indicated figures, 50 μm. * p<0.05, ** p<0.01, *** p<0.001, **** p<0.0001, ns: no significant difference. Precise p values are provided in Raw Data.
Secondly, we performed a metabolomics analysis of different quality food (HK-K12, HK-yfbR and Live-K12). We found that the level of 13 metabolites were similar between HK-yfbR and Live-K12, but significantly changed in HK-K12 (Figure 3B, Figure 3—figure supplement 2A, and Supplementary file 1g). We also found that genes involved in glycolysis/gluconeogenesis were up-regulated in animals fed with HK-E. coli (Figure 3—figure supplement 2B), suggesting that glycolysis/gluconeogenesis metabolism is disordered in animals fed with HK-E. coli, which may result from changes in sugar/carbohydrate intake. The carbohydrates (D-trehalose, lactose, and D-(+)-sucrose) were also decreased in HK-E. coli (Figure 3B), suggesting that carbohydrate deficiency may induce stress response and avoidance behavior in animals feeding HK-E. coli.
Thirdly, to determine which carbohydrate inhibits stress response in animals, we supplemented each metabolite to HK-E. coli and found that only Lactose, and D-(+)-sucrose inhibited HK-E. coli induced UPRER (Figure 3C and D, Figure 3—figure supplement 2C). Moreover, we found from our metabolomic data that the sugar level, including lactose, and D-(+)-sucrose, and D-(+)-glucose, was also decreased in HK-E. coli (Figure 3B, Supplementary file 1h). Since lactose and D-(+)-sucrose are hydrolyzed to produce glucose (Franceus and Desmet, 2020; Xing et al., 2019), we wondered whether glucose also inhibits the stress response in animals. We found that D-(+)-glucose supplementation also inhibited HK-E. coli induced UPRER (Figure 3E), immune response (Figure 3F and G and Figure 3—figure supplement 2D) and avoidance (Figure 3H). Moreover, sugar supplementation did not affect UPRER and immunity in normal food (OP50) or starved condition (NGM) (Figure 3—figure supplement 2E–F). While sugar effectively inhibits the HK-E. coli-induced UPRER and immune response, it does not fully suppress it to the extent observed with live-E. coli (Figure 3C–F). This implies that additional nutrients present in live-E. coli might also contribute to the inhibition of UPRER and immune response.
Previous studies have shown that heat-killed E. coli (HK-E. coli) is a low-quality food source that cannot support the growth of C. elegans larvae (Qi and Han, 2018; Qi et al., 2017), whereas supplementation with vitamin B2 (VB2) can restore animal growth (Qi et al., 2017). Here, we found that sugar deficiency in HK-E. coli induces the UPRER-immune response and avoidance behavior in C. elegans. Given this, we investigated whether sugar supplementation could promote animal growth when fed HK-E. coli. To our surprise, supplementing HK-E. coli with carbohydrates (D-Glc, D-GlcA) did not support animal development (Figure 3—figure supplement 2G), suggesting that carbohydrates are not sufficient for supporting animal growth on this food source. However, we did find that carbohydrates are critical for inhibiting the UPRER-immune response induced by sugar deficiency in HK-E. coli.
Together, these findings suggest that HK-E. coli induces a stress response and avoidance behavior in animals, which can be inhibited by D-(+)-glucose supplementation. This implies that animals may evaluate the sugar deficiency from HK-E. coli through the activation of UPRER and immune responses.
Animals could overcome a low-quality food environment by sugar supplementation through vitamin C biosynthesis
We discovered that D-(+)-glucose supplementation inhibited HK-E. coli induced UPRER (Figure 3E), immune response (Figure 3F and G and Figure 3—figure supplement 2D) and avoidance (Figure 3H). Simultaneously, vitamin C (VC), which is synthesized by glucuronate pathway using D-glucose (Patananan et al., 2015; Yabuta et al., 2020; Figure 4A), was found to contribute to neuroprotective (Moritz et al., 2020; Rice, 2000), immune defense (Maggini et al., 2007; Webb and Villamor, 2007), and inhibits inflammatory and ER stress (Luo et al., 2022; Su et al., 2019). This led us to question whether the vitamin C biosynthesis pathway is involved in evaluating low-quality food by using D-glucose.
Vitamin C biosynthesis pathway is critically involved in evaluating sugar in the food.
(A) Cartoon illustration of a simplified, Vitamin C biosynthesis pathway in C. elegans. The relevant coding genes of enzymes was labeled with red. (B) The level of total L-ascorbic acid (TAA), also known as vitamin C, in animals fed with Live-K12, HK-K12, or HK-yfbR. Data are represented as mean ± SD from six independent experiments. (C) The level of total L-ascorbic acid (TAA) in animals (control or knockdown of Vitamin C biosynthesis genes) fed with HK-E. coli with or without D-glucuronate (D-GlcA) supplementation. Data are represented as mean ± SD from eight independent experiments. (D–E) GFP fluorescence images and bar graph showing that HK-E. coli induced Phsp-4::GFP (D) and Pirg-5::GFP (E) were decreased in animals with D-GlcA or Vitamin C supplementation. Blue numbers are the number of worms scored from at least three independent experiments. Data are represented as mean ± SD. (F–G) Western blot images showing the level of p-PMK-1 in L1 animals fed with HK-E. coli with D-GlcA or Vitamin C supplementation for 4 hr. The level of p-PMK-1 is decreased in animals with D-GlcA (F) or Vitamin C (G) supplementation. (H) Food aversion assay showing that wild-type animals eliminated the discrimination against HK-E. coli with D-GlcA or Vitamin C supplementation. Data are represented as mean ± SD from four independent experiments, 153–292 animals/assay. (I–K) The bar graph showing that suppression of HK-E. coli induced Phsp-4::GFP (I), Pirg-5::GFP (J) and food avoidance (K) by D-GlcA supplementation was abolished in animals with RNAi of VC biosynthesis genes, which was not affect by Vitamin C supplementation. Blue numbers are the number of worms scored from at least three independent experiments and Data are represented as mean ± SD. (I-J) Data are represented as mean ± SD from five independent experiments, 252–537 animals/assay. (K) For all panels, Scale bar shows on indicated figures, 50 μm. * p<0.05, ** p<0.01, *** p<0.001, **** p<0.0001, ns: no significant difference. Precise p values are provided in Raw Data.
Numerical data of <xref ref-type="fig" rid="fig4">Figure 4B–E and H–K</xref> and <xref ref-type="fig" rid="fig4s1">Figure 4—figure supplement 1A–E</xref>.
The raw western bolts for <xref ref-type="fig" rid="fig4">Figure 4F–G</xref> (labelled).
The raw western bolts for <xref ref-type="fig" rid="fig4">Figure 4F–G</xref> (unlabelled, uncropped).
Vitamin C biosynthesis pathway is critical for evaluating low sugar.
Relative to Figure 4. (A) The level of total L-ascorbic acid (TAA) in Live-K12, HK-K12, or HK-yfbR. Data are represented as mean ± SD from six independent experiments. (B) The level of total L-ascorbic acid (TAA) in animals fed HK-E. coli with or without D-Glc supplementation. Data are represented as mean ± SD from eight independent experiments. (C) GFP fluorescence images and bar graph showing that HK-E. coli induced Psysm-1::GFP was decreased in animals with D-GlcA or vitamin C supplementation. Blue numbers are the number of worms scored from at least three independent experiments. Data are represented as mean ± SD. (D) The bar graph showing that suppression of HK-E. coli induced Psysm-1::GFP by D-GlcA supplementation was abolished in animals with RNAi of VC biosynthesis genes, which was not affect by vitamin C supplementation. Blue numbers are the number of worms scored from at least three independent experiments. Data are represented as mean ± SD. (E) Food selection assay showing that the preference of HK-E. coli with D-GlcA supplementation was abolished in animals by RNAi of vitamin C biosynthesis genes. Data are represented as mean ± SD from six independent experiments, 427–775 animals/assay. For all panels, Scale bar shows on indicated figures, 50 μm. * p<0.05, ** p<0.01, *** p<0.001, **** p<0.0001, ns: no significant difference. Precise p values are provided in Raw Data.
Firstly, we observed an increase in the vitamin C level in C. elegans when fed with HK-yfbR (Figure 4B), a high-carbohydrate food compared to HK-E. coli (Figure 3B and Figure 1—figure supplement 1E). However, the VC level in bacteria is the same (Figure 4—figure supplement 1A). The VC level also increased when D-glucose (Figure 4—figure supplement 1B) or D-glucuronate (D-GlcA) was added to HK-E. coli (Figure 4C), which was abolished by knocking down VC biosynthesis genes (Figure 4C and Figure 4—figure supplement 1B). This suggests that addition of sugar supplementation promotes VC synthesis in animals fed with HK-E. coli.
Secondly, we hypothesized that animals could overcome a low-quality food (HK-E. coli) environment by inhibiting the stress response through increasing vitamin C biosynthesis. We found that VC or D-glucuronate (D-GlcA) supplementation inhibits HK-E. coli induced UPRER (Figure 4D), immune response including irg-5/sysm-1 reporter expression (Figure 4E and Figure 4—figure supplement 1C) and p-PMK-1 (Figure 4F and G), as well as food avoidance (Figure 4H).
Finally, we asked whether inhibition of stress response and avoidance by sugar supplementation depends on the vitamin C biosynthesis pathway. We found that suppression of HK-E. coli induced UPRER (Figure 4I), immune response (Figure 4J and Figure 4—figure supplement 1D) and food avoidance (Figure 4K) by D-GlcA/sugar supplementation was abolished in animals with RNAi of VC biosynthesis genes. Food selection behavior assays showed that D-GlcA/sugar supplementation increased the preference for heat-killed bacteria, which was also suppressed by knocking down VC biosynthesis genes (Figure 4—figure supplement 1E). However, VC supplementation still suppressed the UPRER (Figure 4I), immune response (Figure 4J and Figure 4—figure supplement 1D) and food avoidance (Figure 4K), and increased the food preference (Figure 4—figure supplement 1E) in animals with or without RNAi of VC biosynthesis genes. This suggests that VC, as the final metabolite synthesized from D-glucose, is critical for evaluating low-quality food response in animals.
Together, these data indicate that the vitamin C biosynthesis pathway is critical for evaluating whether food is of higher quality and can be eaten by animals. It also suggests that animals could improve their VC levels to adapt to bad food environment.
Animals evaluate sugar and vitamin C through neuronal XBP-1 and PMK-1
As D-GlcA/sugar and VC supplementation suppressed HK-E. coli induced UPRER, immune response and food avoidance behavior, we investigated whether animals evaluate sugar and VC through XBP and PMK-1 dependent pathways. We performed a food selection behavior assay by adding D-Glc, D-GlcA or VC to the NGM, E. coli and HK-E. coli (Figure 5A). The food selection behavior assays revealed that supplementation with D-Glc, D-GlcA, or VC inhibits the animals’ choice of sugar or VC on E. coli-OP50 feeding conditions (Figure 5—figure supplement 1A). This suggests that supplementation with D-Glc, D-GlcA, or VC may alter the metabolites of live bacteria, leading to avoidance by the animals. There was no preference observed on NGM plate (no food condition) supplementation with D-Glc and VC (Figure 5—figure supplement 1B), indicating that the intake of sugar or VC alone does not influence animal preference. However, alone D-GlcA could influence worm physiology which induces preference change (Figure 5—figure supplement 1B). Interestingly, D-Glc and D-GlcA (Figure 5B and C) or VC (Figure 5D) supplementation increased the preference for heat-killed bacteria, which was suppressed in xbp-1 or pmk-1 mutant animals. However, this preference was also rescued in xbp-1 or pmk-1 mutant animals by expressing XBP-1 or PMK-1 in neurons rather than intestine (Figure 5B–D), indicating that neuronal XBP-1 and PMK-1 are critical for physiological food elevation system for monitoring the level of sugar and VC under low-quality food condition.
Animals evaluate sugar and vitamin C through neuronal XBP-1 and PMK-1.
(A) Schematic method of the food selection assay. Food (red) and food with carbohydrate (D-Glc, D-GlcA, or VC) supplementation (green) was placed on indicated position. Synchronized L1 worms were then place in plate. After 16-17h, the selection index was calculated. (B–D) Food selection assay showing that xbp-1 or pmk-1 mutation eliminated the preference of HK-E. coli with D-Glc (B), D-GlcA (C) or Vitamin C (D) supplementation, which was rescued in xbp-1 or pmk-1 mutant animals by expressing XBP-1 or PMK-1 in neurons rather than intestine. Data are represented as mean ± SD from five independent experiments, 68–647 animals/assay (B). Data are represented as mean ± SD from six independent experiments, 83–701 animals/assay (C). Data are represented as mean ± SD from six independent experiments, 67–1035 animals/assay (D). For all panels, Scale bar shows on indicated figures, 50 μm. * p<0.05, ** p<0.01, *** p<0.001, **** p<0.0001, ns: no significant difference. Precise p values are provided in Raw Data.
Numerical data of <xref ref-type="fig" rid="fig5">Figure 5B–D</xref> and <xref ref-type="fig" rid="fig5s1">Figure 5—figure supplement 1A–C</xref>.
Food behavior of animals.
Relative to Figure 5. (A) Food selection assay for OP50 and OP50 +D Glc, D-GlcA, or VC, respectively. Data are represented as mean ± SD from five independent experiments, 241–1182 animals/assay. (B) Food selection assay for buffer (H2O) & buffer (H2O)+D Glc, D-GlcA, or VC, respectively. Data are represented as mean ± SD from five independent experiments, 8–153 animals/assay. (C) Food avoidance assay for N2 and kgb-1 mutant animals fed with HK-E. coli. Data are represented as mean ± SD from six independent experiments, 348–660 animals/assay. (D) Translation ability of animals fed with OP50 or HK-OP50 are presented by western blot of puromycin-labeled peptides. For all panels, * p<0.05, ** p<0.01, *** p<0.001, **** p<0.0001, ns: no significant difference. Precise p values are provided in Raw Data.
The raw western bolts for <xref ref-type="fig" rid="fig5s1">Figure 5—figure supplement 1D</xref> (labelled).
The raw western bolts for <xref ref-type="fig" rid="fig5s1">Figure 5—figure supplement 1D</xref> (unlabelled, uncropped).
Discussion
To better survive, animals must evolve a system to recognize and evaluate the quality of their food. This includes the sensory neuron evaluation system for immediate response and feeding decision (Florsheim et al., 2021), as well as physiological food evaluation system for chronic response to ingested food. In our previous study, we discovered that the TORC1-ELT-2 pathway, acting as master regulators in intestine, evaluates vitamin B2 deficiency in low-quality food (HK-E. coli) and regulates gut digestive activity to impact animal’s food behavior (Qi et al., 2017). To further identified the mechanism by which animals evaluate low-quality food (HK-E. coli), we performed metabolomics and transcriptomics analyses to identify specific nutrition deficiencies in low-quality food and the cellular response pathways that are involved in food evaluation pathway. This study identified a physiological food evaluation mechanism by which animals recognize food quality through UPRER (IRE-1/XBP-1) - Innate immunity (PMK-1/p38 MAPK) regulated cellular stress response program in neurons that dictates food avoidance and selection behaviors (Figure 6).
Schematic model of physiological food evaluation system in evaluating/sensing sugar and vitamin C through UPR<sup>ER</sup> (IRE-1/XBP-1) - Innate immunity (PMK-1/p38 MAPK) axis.
Vitamin C level is low in animals fed low sugar food, HK-E. coli. Sugar and Vitamin C deficiency activate cellular UPRER and immune response, which promote animals to leave low-quality food and seek better food for survival. This cellular stress regulated physiological food evaluation system depends UPRER (IRE-1/XBP-1) - Innate immunity (PMK-1/p38 MAPK) axis in neuron.
One of the cellular stress response pathways, the Unfolded Protein Response (UPRER), is activated by various stresses, including infection and nutrition deficiency, which disrupt the homeostasis of the endoplasmic reticulum (ER) (Hetz et al., 2020). The activation of UPRER, specifically in the nervous system, has been shown to promote changes in feeding and foraging behavior (Özbey et al., 2020). The p38 PMK-1 pathway is also crucial for regulating the expression of secreted innate immune effectors and is essential for survival during infection (Troemel et al., 2006). Therefore, these two pathways play a critical role in ensuring animals' survival in changing environments. However, it is still unclear whether UPRER and innate immunity evaluate food quality under physiological conditions. Our study provides evidence that low-quality food (HK-E. coli) activates both UPRER and p-PMK-1, leading to animals leaving the low-quality food. Previously finding have shown that inhibition of ER function promotes C. elegans avoid to the toxic food, which employs the MLK-1/MEK-1/KGB-1 pathway (Melo and Ruvkun, 2012). Notably, HK-E. coli induced avoidance behavior is independent of the KGB-1 pathway (Figure 5—figure supplement 1C). Additionally, our study reveals that neuronal UPRER and PMK-1 are essential for evaluating low-quality food, suggesting that the nervous system plays a critical role in assessing food quality.
Previous studies have shown that XBP1 deficiency in intestinal epithelial cells leads to IRE1a hyperactivation and increased JNK phosphorylation in the epithelial compartment in vivo (Kaser et al., 2008). The IRE1-XBP1 axis has been identified as a critical protective branch of the Unfolded Protein Response (UPR) induced secondary to an innate immune response in the presence of P. aeruginosa (Kaser and Blumberg, 2010; Richardson et al., 2010). The p38 MAPK has also been shown to directly act on the phosphorylation of IRE-1 to promote the stress response (Guan et al., 2020; Qu et al., 2019). Interestingly, IRE-1 has been found to confer cold resistance independently of XBP-1 by activating JNK-1 MAPK (Melo and Ruvkun, 2012). In contrast, our study reveals a new mechanism where the UPRER (IRE-1/XBP-1) positively regulates Innate Immunity (PMK-1/p38 MAPK) under HK-E. coli food conditions, establishing a novel physiological food evaluation system that activates the cellular stress response program.
A previous study has shown that activating innate immunity (PMK-1 MAPK) leads to a reduction in translation (Weaver et al., 2020). Our own previous research has also demonstrated that PMK-1 activation causes a shutdown of food digestion in animals (Geng et al., 2022), likely to reduce protein translation and cellular metabolism. To investigate this further, we measured the translation level of animals fed with HK-E. coli and found that total translation ability is significantly reduced in these animals (Figure 5—figure supplement 1D). This finding suggests that activating innate immunity (PMK-1 MAPK) may serve as a mechanism to slow down translation progress, thereby alleviating the pressure on the unfolded protein response (UPR) and preventing excessive UPRER activation.
Vitamin C (VC) is an important physiological antioxidant and a cofactor for a family of biosynthetic and gene regulatory monooxygenase and dioxygenase enzymes. It is also required for the biosynthesis of collagen, L-carnitine, and certain neurotransmitters (Carr and Frei, 1999; Li and Schellhorn, 2007). Meanwhile, VC helps animals to protect neuron (Moritz et al., 2020; Rice, 2000), defend excessive immune (Maggini et al., 2007; Webb and Villamor, 2007), and inhibit inflammatory and ER stress Luo et al., 2022; Su et al., 2019 in order to better survive. The synthesis of vitamin C (VC) occurs through the glucuronate pathway, utilizing D-glucose as a precursor (Patananan et al., 2015; Yabuta et al., 2020; Figure 4A). This led us to investigate whether the vitamin C biosynthesis pathway is involved in evaluating low-quality food by using D-glucose. In this study, we found that animals feeding live E. coli, which should produce more VC, exhibit higher glucose levels. However, our results show that animals maintain similar VC levels when fed ideal food (live E. coli) compared to low-quality food (HK-E. coli; Figure 4B), suggesting that animals do not stimulate VC biosynthesis under favorable food conditions. In contrast, when animals are fed low-quality food (HK-OP50), we found that supplementing D-GlcA in HK-E. coli or E. coli-yfbR mutation can improve VC levels and inhibit UPRER-immunity (Figure 4C). These data indicate that glucose boosts the animal’s ability to adapt to unfavorable food environments by increasing VC levels, but not in favorable food conditions.
Unlike the sensory neuron evaluation system, which permits rapid feeding decisions through smell and taste, the cellular stress response as physiological food evaluation system describe here requires a slow and multi-step signal transduction process after the ingestion of food. The disruption of cellular homeostasis by ingested of low-quality or toxic food can activate stress response mechanisms that both increase the cellular ability to withstand and adapt to this disruption of homeostasis and promote behavioral strategies to avoid these conditions and lessen their impact on the organism. These cellular stress response mechanisms include heat shock response, unfolded protein response, oxidative stress response (Özbey et al., 2021). Therefore, this slow physiological food evaluation system is an evolutionary adaptation mechanism for detecting nutrition deficiencies in food that was not detected by quick sensory nervous system.
One limitation of our study is the lack of explanation for why HK-E. coli activates UPRER and immunity. We hypothesized that when heat-killed, HK-E. coli may lack or contain altered levels of certain metabolites that either activate or inhibit UPRER and immunity, respectively. Additionally, we speculated that E. coli mutants killed by heat may lack metabolites that activate UPRER and immunity, or conversely, have increased levels of metabolites that inhibit these pathways. Fortunately, our investigation led to the discovery of the E. coli mutant yfbR, which inhibits UPRER and immunity by increasing carbohydrates that aid in resisting these stress pathways. Moving forward, we intend to further explore the intricate relationship between HK-E. coli and UPRER-immunity. This will be a key focus of our future research efforts.
Collectively, this study uncovers the unexpected function of UPRER (IRE-1/XBP-1) - Innate immunity (PMK-1/p38 MAPK) as a physiological food evaluation system for evaluating and sensing food quality in animals. It also highlights the utility of the HK-E. coli (low-quality food) - C. elegans interaction as a means to dissect the mechanism of food evaluation system in assessing food. Most importantly, it reveals that animals are capable of altering their nutrient (Vitamin C) levels through in vivo synthesis or food intake to adapt to a poor food environment when better food choices are not available.
Materials and methods<italic>C. elegans</italic> strains and maintenance
Nematode stocks were maintained on nematode growth medium (NGM) plates seeded with bacteria (E. coli OP50) at 20 °C.
(1) The following strains/alleles were obtained from the Caenorhabditis Genetics Center (CGC) or as indicated:
YNU108: Ex[Prgef-1::pmk-1::GFP; Podr-1::RFP] (Geng et al., 2022);
xbp-1(tm2482) (Richardson et al., 2011);
KU21：kgb-1(km21);
AU133: agIs17 [Pmyo-2::mCherry +Pirg-1::GFP] IV;
SJ4100: zcIs13 [Phsp-6::GFP +lin-15(+)].
(2) The following strains were constructed by this study:
YNU242: xbp-1(tm2482); pmk-1(km25) double mutant was constructed by crossing: xbp-1(tm2482) with KU25[pmk-1(km25)].
YNU240: ylfEx149 [xbp-1(tm2482); Prgef-1::xbp-1::GFP; Podr-1::RFP] transgene strain was constructed by injecting plasmid Prgef-1::xbp-1::GFP with Podr-1::RFP in xbp-1(tm2482) background
YNU241: ylfEx150 [xbp-1(tm2482); Pges-1::xbp-1::GFP; Podr-1::RFP] transgene strain was constructed by injecting plasmid Pges-1:xbp-1::GFP with Podr-1::RFP in xbp-1(tm2482) background
Bacterial strains
E. coli-OP50, Saprophytic staphylococci, Pseudomonas aeruginosa-PA14, E. coli-K12 (BW25113), and E. coli-K12 mutant were cultured at 37 °C in LB medium. A standard overnight cultured bacteria was then spread onto each Nematode growth media (NGM) plate.
To construct the C. elegans plasmid for expression of xbp-1 in neuron, 3057 bp promoter of rgef-1 and genomic DNA of xbp-1 was inserted into the PPD95.77 vector. DNA plasmid mixture containing Prgef-1::xbp-1::GFP (25 ng/µl) and Podr-1::RFP (25 ng/µl) was injected into the gonads of adult xbp-1(tm2482).
To construct the C. elegans plasmid for expression of xbp-1 in intestine, 2549 bp promoter of ges-1 and genomic DNA of xbp-1 was inserted into the PPD95.77 vector. DNA plasmid mixture containing Pges-1::xbp-1::GFP (25 ng/µl) and Podr-1::RFP (25 ng/µl) was injected into the gonads of adult xbp-1(tm2482).
Preparation and feeding of worm food
We followed an established protocol (Qi and Han, 2018; Qi et al., 2017) to prepare heat-killed (HK) E. coli. Briefly, a standard OD600=0.5–0.6 of E. coli OP50 and E. coli K12 grown in LB broth was concentrated to 1/20 vol and was then heat-killed at 80 °C for 180 min. About 150 µl of the heat-killed bacteria was spread onto each 35 mm NGM plate.
Preparation of HK-<italic>E. coli</italic> + carbohydrate or vitamin C food
100 µl of water, 100 µl of L-ascorbic acid (dissolved in water at a concentration of 100 mg/ml, Sangon Biotech, 100143–0100) or 100 µl of D-glucuronic acid (dissolved in water at a concentration of 100 mg/ml, Adamas, 1102520) was mixed with 500 µl of HK-E. coli, then 150 µl of the mixture was spread onto 35 mm NGM plates.
12.5 µl of water or 12.5 µl of D-(+)-glucose (dissolved in water at a concentration of 100 mg/ml, Sangon Biotech, A501991-0500) was mixed with 500 µl of HK-E. coli, then 150 µl of the mixture was spread onto 35 mm NGM plates.
For C. elegans to have enough space to evaluate food, we add 18 µl of the sample onto a 35 mm NGM plate. This creates a round lawn with a radius of 5 mm, which occupies about 8% of the total plate area.ab=πr12πγ22=5mm217.5mm2=8％
a: the area of bacterial lawn
b: the space of worm life (area of culture dish)
18 µl of heat-killed OP50, live OP50, and LB broth (as the buffer for bacteria) was added into 35 mm NGM plate in an equilateral triangle pattern. Then, synchronized L1 worms were seeded in the center of NGM plate for 16–17 hr at 20 °C (as indicated in Figure 1B).
18 µl of heat-killed OP50 and heat-killed OP50 with D-GlcA or vitamin C was added into 35 mm NGM plate in an equilateral triangle pattern, then synchronized L1 worms were seeded on equilateral triangle of NGM plate for 16–17 hr at 20 °C (as indicated in Figure 5A).
Here is Selection rate formula:selectionrate=wormamountonelawnareawormamountlawn1area+wormamountlawn2area+wormamountlawn3area⋅⋅⋅⋅
<italic>C. elegans</italic> aversion assays
18 µl food was spread out the center of NGM plate, then synchronized L1 by bleach solution (NaOH: 1 M, NaClO:4–6%) worms were seeded on center of food for 16–17 hr at 20 °C.Aversionindex=wormamountofoutoflawnwormamountof(out+in)lawn
Three to 10 replicates for each condition were performed for each assay, and the experiments were duplicated on different days.
Analysis of the fluorescence intensity in worms
The synchronized L1 worms carrying either UPRER reporter (Phsp-4::GFP) or innate immunity reporter (Pirg-5::GFP; Psysm-1p::GFP; Pirg-1p::GFP) were seeded on NGM with indicated food and incubated for 24 hr at 20 °C. For fluorescence imaging, worms were anesthetized with 25 mM levamisole and photographed using either an Olympus BX53 microscope or Olympus MVX10 dissecting microscope equipped with a DP80 camera.
The fluorescence intensity in entire intestinal region was quantified using ImageJ software and normalized to the body area.
<italic>E. coli</italic> Keio collection screen
The whole Keio E. coli single mutant collection (Baba et al., 2006) was screened. Mutant bacteria strains, as well as the wild-type control strain BW25113, were cultured in LB medium with 50 µg/ml kanamycin at 37 °C until an OD600 of 0.5–0.6 was reached. The bacteria were then heat-killed following our established protocol (Qi et al., 2017), and 150 µl of the heat-killed mutant E. coli was spread onto 35 mm NGM plates. Synchronized L1 worms carrying UPRER reporter (Phsp-4::GFP) were seeded and cultured for 24 hr at 20 °C. The fluorescence was then examined by using an Olympus MVX10 dissecting microscope, progressive screening three times. Next, a 4th screen was performed using immune reporter (Pirg-5::GFP) animals fed with HK-E. coli mutants that reduced the Phsp-4::GFP fluorescence. Finally, an aversion behavior assay was performed using HK-E. coli mutants that both reduced Phsp-4::GFP and Pirg-5::GFP. HK-E. coli mutants that reduced UPRER, immune and avoidance behavior were identified through this screening.
RNAi treatment
RNAi plasmid is delivered in a E. coli strain, HT115, from either the MRC RNAi library (Kamath et al., 2003) or the ORF-RNAi Library (Rual et al., 2004). RNAi plates were prepared by adding IPTG to NGM agar to a final concentration of 1 mM. Overnight E. coli cultures (LB broth containing 100 µg/ml ampicillin and 100 uM IPTG) of specific RNAi strains and the control HT115 strain were seeded onto RNAi feeding plates and cultured at room temperature until dry. Synchronized L1 worms were treated RNAi by feeding (Ahringer, Reverse genetics, WormBook 2006) for the first generation and allowed to grow to maturity. The worms were then bleached and hatched in M9 buffer for 18 hr. The synchronized L1 worms were then seeded on the indicated feeding plate.
Western blot
To measure the level of p-PMK-1, worms (feeding different food for 4 hr) were analyzed by standard western blot methods and probed with anti-p38 (dilution = 1:5000; Cell Signaling, 9212 S), anti-p-p38 (dilution = 1:5000; Cell Signaling, 4511 S) and anti-α-tubulin (dilution = 1:10,000; Sigma T5168) as a loading control.
To measure the level of protein translation, worms (feeding different food for 24 hr) were analyzed by standard western blot methods and probed with anti-Puromycin (dilution = 1:10,000; Sigma-Aldrich, MABE343) and anti-α-tubulin (dilution = 1:10,000; Sigma T5168) as a loading control.
Total content of ascorbic acid (TAA) assay
The total content of ascorbic acid was measured using the kits (Beijing Biotech-Pack-analytical Scientific Co., Ltd., Beijing, China, BKWB132 http://biotech-pack-analytical.foodmate.net/) according to the manufacturer’s protocol. Briefly, L1 worms were seeded on the different feeding assay plate and cultured for 4 hr. The worms were then lysed in ice-cold conditions using lysis buffer. Equal amounts of protein were used for the normalization. Here is formula for getting TAA concentrationTAA(ug/mgprot)=((ΔA−a)÷b)÷(Cpr×V1)×D
V1 - the volume of supernatant of for experiment
Cpr – the concentration of supernatant protein
D – Dilution ratio of supernatant
a – the intercept of standard curve
b – the slope of standard curve
the standard curve y=0.0611 x+0.0003 for Figure 4C; y=0.0258 x+0.0066 for Figure 4B, Figure 4—figure supplement 1A and Figure 4—figure supplement 1B.
Preparation of samples for RNA sequencing
RNA-seq was done with three biological replicates that were independently generated, collected, and processed. Adult wild type (N2) worms were bleached and then the eggs were incubated in M9 for 18 hr to obtain synchronized L1 worms. L1 worms were cultured in the NGM plate with HK-E. coli or E. coli for 4 hr at 20 °C. L1 worms were then collected for sequencing.
RNA sequencing and data processing
For the RNA sequencing assay, cDNA libraries were constructed, and single-end libraries were sequenced using the Illumina platform (Novogene, Beijing, China). HISAT2 (Mortazavi et al., 2008) was used to map the clean reads to the reference gene sequence (Species: Caenorhabditis_elegans; Source: NCBI; Reference Genome Version: GCF_000002985.6_WBcel235), and then ‘featureCounts’ tool in subread software (Liao et al., 2014) was used to calculate the gene expression level of each sample. Read counts were inputted into DESeq2 Love et al., 2014 to calculate differential gene expression and statistical significance. Differentially expressed genes (DEGs) were screened using following criteria: |log2(FoldChange)|>1 & padj ≤ 0.05.
Preparation of samples for metabolome sequencing
Metabolome-seq of bacterial was done with four biological replicates that were independently generated, collected, and processed. Total of three group E. coli sample including: E. coli K12 (Con), HK-E. coli K12 (HK), and HK-E. coli yfbR mutant (HY). All bacteria were overnight cultured to the same OD (OD600=1). E. coli K12 and E. coli yfbR mutant are heat-killed (80, 180 min), E. coli K12, HK-E. coli K12 and HK-E. coli yfbR mutant were then spread out NGM plate for 72 hr at room temperature. Finally, sample was collected into 1.5 ml tube by using sterile cell scraping.
Metabolome sequencing and data processing
Metabolome were sequenced using the Ultra Performance Liquid Chromatography (UPLC) (ExionLC AD, https://sciex.com.cn/) and Quadrupole-Time of Flight (TripleTOF 6600, AB SCIEX) for Non-targeted; Ultra Performance Liquid Chromatography (UPLC) (ExionLC AD, https://sciex.com.cn/) and Tandem mass spectrometry (MS/MS) (QTRAP, https://sciex.com/) for Broad targeting (Metware, Wuhan, China). Multiple reaction monitoring (MRM) was used to calculate the expression level of each metabolite. Differential metabolites were screened through Fold change ≥2 or Fold change ≤0.5 and VIP ≥1 (Variable Importance in Projection of OPLS-DA model).
Microscopy
Analysis of fluorescence was performed with an Olympus BX53 microscope, CLSM (Zeiss LSM900), or Olympus MVX10 dissecting with a DP80 camera.
Quantification and statistical analysisQuantification
ImageJ software was used for quantifying fluorescence intensity of UPRER and Innate immunity reporter. ImageJ software was used for counting the number of worms about selection and aversion behavior.
Statistical analysis
All statistical analyses were performed in Graphpad prism 8.0. Two-tailed unpaired t test was used for statistical analysis of two groups of samples, one-way or two-way ANOVA was used for statistical analysis of more than two groups of samples. Data are presented as Mean ± SD, and p<0.05 was considered a significant difference, ‘*’ represents p<0.05, ‘**’ represents p<0.01, ‘***’ is represents <0.001, ‘****’ represents p<0.0001, ‘ns’ represents no significant difference. For all figures, ‘n’ represents the number of worms scored from at least three independent experiments.
Additional informationCompeting interests
No competing interests declared
Author contributions
Conceptualization, Resources, Data curation, Software, Formal analysis, Validation, Investigation, Methodology, Writing - original draft, Writing - review and editing
Screening data for <italic>E. coli</italic> mutant keio library.
Metabolism-seq data of HK-K12, HK-yfbR and K12.
RNA-seq data of animals fed with HK-<italic>E. coli</italic> OP50 and <italic>E. coli</italic> OP50.
Data availability
Sequencing data have been deposited in CNCB under accession codes PRJCA028417. All data generated or analysed during this study are included in the manuscript and supporting files; source data files have been provided for all Figures.
The following dataset was generated:
LiuPLiuXQiB2024RNA-seq fron C. elegans fed with E. coli OP50 or HK-E. coli OP50Genome Sequence ArchivePRJCA028417
Acknowledgements
We thank the Caenorhabditis Genetics Center (CGC) (funded by NIH P40OD010440) for strains; Dr. Zhao Shan for suggestions. This work was supported by the Ministry of Science and Technology of the People’s Republic of China (2019YFA0802100, 2019YFA0803100), the National Natural Science Foundation of China (32170794), Yunnan Provincial Science and Technology Project at Southwest United Graduate School (202302AP370005), Yunnan Applied Basic Research Projects (202201AT070196), Science and Technological Talent Cultivation Plan of Yunnan Province (K264202230211).
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This valuable work uses unbiased approaches to discover critical molecules in C. elegans and its bacterial food for nutrition sensing and food choice, providing a framework for other studies. The data convincingly support their model that C. elegans uses UPRER and immune response pathways to evaluate sugar contents in the bacteria to change their behaviors.
In this work, the authors aim to better understand how C. elegans detects and responds to heat-killed (HK) E. coli, a low-quality food. They find that HK food activates two canonical stress pathways, ER-UPR and innate immunity, in the nervous system to promote food aversion. Through the creative use of E. coli genetics and metabolomics, the authors provide evidence that the altered carbohydrate content of HK food is the trigger for the activation of these stress responses and that supplementation of HK food with sugars (or their biosynthetic product, vitamin C), reduces stress pathway induction and food avoidance. This work makes a valuable addition to the literature on metabolite detection as a mechanism for evaluation of nutritional value; it also provides some new insight into physiologically relevant roles of well-known stress pathways in modulating behavior.
Strengths:
-The work addresses an important question by focusing on understanding how the nervous system evaluates food quality and couples this to behavioral change.
-The work takes full advantage of the tools available in this powerful system and builds on extensive previous studies on feeding behavior and stress responses in C. elegans.
-Creative use of E. coli genetics and metabolite profiling enabled identification of carbohydrate metabolism as a candidate source of food-quality signals.
-For the most part, the studies are rigorous and logically designed, providing good support for the authors' model.
Weaknesses:
-The authors' claim that they can detect induction of hsp-4 and irg-5 expression in neurons (Fig 1-S2A) requires further support. The two tail cells shown are quite a bit larger than would by typically expected for neurons. The rescue they observe by neuronal expression is largely convincing, so it's quite possible that these pathways do indeed function in neurons, but that their level of induction in the nervous system is below reporter detection limits (or is 'swamped out' by much higher levels of expression in the intestine).
-The authors conclude that "the induction of Pirg-5::GFP was abolished in pmk-1 knockdown animals fed with HK-E. coli" (Fig 2D). Because a negative control for induction (e.g., animals fed with control E. coli) is not shown, this conclusion must be regarded as tentative.
-The effect sizes in the food-preference assay shown in Figure 5 are extremely small and do not provide strong support for the strong conclusions about the role of stress response pathways in food preference behavior.
Animals can evaluate food quality in many ways. In contrast to the rapid sensory evaluation with smell and taste, the mechanism of slow nutrient sensation and its impact on food choice is unexplored. The authors utilize C. elegans larvae and their bacterial food as an elegant model to tackle this question and reveal the detailed molecular mechanism to avoid nutrient-poor foods.
Strength:
The strength of this study is that they identified the molecular identities of the critical players in bacterial food and C. elegans using unbiased approaches, namely metabolome analysis, E. coli mutant screening, and RNA sequencing. Furthermore, they strengthened their findings by thorough experiments combining multiple methods such as genetics, fluorescent reporter analysis, and Western blot.
Weakness:
The major caveat of this study is the reporter genes; specifically, transcriptional reporters used to monitor the UPRER and immune responses in the intestine of C. elegans. However, their tissue-specific rescue experiments suggest that the genes in the UPRER and immune response function in the neurons. Thus, we should carefully interpret the results of the reporter genes. Another point to be aware of is that although they show that lack of carbohydrates elicits the response to "low-quality" food, carbohydrate supplementation with heat-killed E. coli was insufficient to support animal growth.
Overall, this work provides convincing data to support their model. In the C. elegans field, the behaviors of larvae are not well studied compared to adults. This work will pose an interesting question about the difference between larvae and adults in nutrition sensing in C. elegans and provide a framework and candidate molecules to be studied in other organisms.
The following is the authors’ response to the original reviews.
Public Reviews:
Reviewer #1 (Public Review):
Summary:
This manuscript by Liu et al explores the role of the UPR and immune regulators in the evaluation of nutritional quality in C. elegans. They identify neuronal UPR activation and the MAPK PMK-1 as key responders to low food quality. In particular, the data suggest that these pathways are activated by low levels of vitamin C synthesis that result from the low sugar levels present in heat-killed E. coli.
Strengths:
The results are intriguing and expand our understanding both of physiological food evaluation systems, and of the known roles of stress response pathways in organismal physiology. The authors use a range of techniques, encompassing imaging, metabolomic analysis, gene expression analysis, and behavioural assays, to support their claims.
Thank you for your thorough review and acknowledgment of the strengths of our study.
Weaknesses:
There is limited mechanistic analysis in the study. In particular, how does low vitamin C trigger UPR activation? This is an intriguing finding that, if followed up, could potentially reveal a novel mechanism of UPR activation. In addition, how is the activation of the PMK-1 pathway driven by/coordinated with UPR activation? The data in some figures is not as convincing as it could be: the magnitude of the effect size is small in the supplementation experiments, and the statistical tests used are not always appropriate to enable multiple comparisons.
(1) There is limited mechanistic analysis in the study. In particular, how does low vitamin C trigger UPR activation? This is an intriguing finding that, if followed up, could potentially reveal a novel mechanism of UPR activation.
Thank you for highlighting the need for further mechanistic analysis in our study. We appreciate the opportunity to clarify the process by which low vitamin C triggers UPR activation.
Our investigation revealed that the vitamin C content in heat-killed E. coli (HK-E. coli) is comparable to that of live E. coli or HK-yfbR mutant E. coli (Figure 4-figure supplement 1A), indicating that the induction of unfolded protein response (UPR) in C. elegans by HK-E. coli is not solely attributed to low vitamin C levels but rather involves other unidentified factors.
Through metabolomic analysis, we observed significant decreases in sugar levels, including lactose, D-(+)-sucrose, and D-(+)-glucose, in HK-E. coli (Figure 3B, Table S1). Notably, supplementing D-(+)-glucose effectively inhibited UPRER, immune response, and avoidance behavior induced by HK-E. coli (Figure 3E-H). These findings suggest that the deficiency in sugars in HK-E. coli triggers a stress response and avoidance behavior in animals, which can be alleviated by D-(+)-glucose supplementation.
Furthermore, when comparing heat-killed E. coli mutant yfbR (HK-yfbR) to HK-E. coli, we observed significantly higher sugar levels, including lactose and D-(+)-sucrose, in HK-yfbR (Figure 3B). This was accompanied by reduced UPRER in animals feeding on HK-yfbR (Figure 3-figure supplement 1B), indicating that higher sugar levels may inhibit the induction of UPRER by low-quality food.
Considering that the synthesis of vitamin C (VC) occurs through the glucuronate pathway, utilizing D-glucose as a precursor 1, 2 (Figure 4A), we investigated whether the vitamin C biosynthesis pathway is involved in evaluating low-quality food using D-glucose. Contrary to our initial hypothesis, animals fed live E. coli did not exhibit higher glucose levels compared to those fed low-quality food (HK_-E. coli_). Our results indicate that animals maintain similar VC levels when fed ideal food (live E. coli) compared to low-quality food (HK-E. coli) (Figure 4B), suggesting that animals do not stimulate VC biosynthesis under favorable food conditions. However, supplementation of D-GlcA or E. coli-yfbR mutation in HK-E. coli significantly improved VC levels when animals were fed low-quality food (HK-OP50) (Figure 4B, 4C). Moreover, VC or D-glucuronate (D-GlcA) supplementation inhibited HK-E. coli-induced UPRER (Figure 4D), indicating that glucose boosts the animal's ability to adapt to unfavorable food environments by increasing VC levels, thereby inhibiting UPRER, but not under favorable food conditions.
These findings shed light on the complex interplay between vitamin C, sugar levels, and UPR activation, providing valuable insights into the mechanisms underlying food evaluation and stress response pathways in organisms.
Overall, we are grateful for the reviewer's constructive feedback, which motivates us to continue our efforts to understanding how the UPR response contributes to the complexities of food evaluation and behavioral responses in organisms.
(2) In addition, how is the activation of the PMK-1 pathway driven by/coordinated with UPR activation?
Thank you for your insightful inquiry. In our discussion section, we have addressed this question by integrating new data and discussion to provide insights into the coordination between PMK-1 pathway activation and UPR activation.
Previous studies have demonstrated that activating innate immunity, specifically the PMK-1 MAPK pathway, results in a reduction in translation3, as well as a shutdown of food digestion in animals4, likely aimed at reducing protein translation and cellular metabolism. To further investigate this relationship, we measured the translation level of animals fed with heat-killed E. coli (HK-E. coli) and found a significant reduction in total translation ability in these animals (Figure 5-figure supplement 1D). This observation suggests that activating innate immunity through the PMK-1 MAPK pathway may serve as a mechanism to slow down translation progress, thereby alleviating the pressure on the unfolded protein response (UPR) and preventing excessive UPRER activation.
By integrating these findings, we propose a model wherein activation of the PMK-1 pathway coordinates with UPR activation to regulate translation and cellular metabolism in response to low-quality food. This coordinated response likely serves to maintain cellular homeostasis and prevent detrimental effects associated with excessive UPRER activation.
These insights contribute to our understanding of the intricate interplay between innate immunity, cellular stress responses, and metabolic regulation in organisms facing nutritional challenges.
(3) The data in some figures is not as convincing as it could be: the magnitude of the effect size is small in the supplementation experiments, and the statistical tests used are not always appropriate to enable multiple comparisons.
We appreciate the reviewers' concerns regarding the data presentation and statistical analyses in some of our figures. In response to this feedback, we have made revisions to improve the robustness and clarity of our statistical methods.
All statistical analyses were conducted using GraphPad Prism 8.0 software. Specifically, a two-tailed unpaired t-test was employed for the statistical analysis of two groups of samples, while one-way or two-way ANOVA was utilized for the statistical analysis of more than two groups of samples. These adjustments ensure appropriate statistical comparisons and enhance the reliability of our findings.
Reviewer #2 (Public Review):
Summary:
In this work, the authors aim to better understand how C. elegans detects and responds to heat-killed (HK) E. coli, a low-quality food. They find that HK food activates two canonical stress pathways, ER-UPR, and innate immunity, in the nervous system to promote food aversion. Through the creative use of E. coli genetics and metabolomics, the authors provide evidence that the altered carbohydrate content of HK food is the trigger for the activation of these stress responses and that supplementation of HK food with sugars (or their biosynthetic product, vitamin C), reduces stress pathway induction and food avoidance. This work makes a valuable addition to the literature on metabolite detection as a mechanism for the evaluation of nutritional value; it also provides some new insight into the physiologically relevant roles of well-known stress pathways in modulating behavior.
Strengths:
-The work addresses an important question by focusing on understanding how the nervous system evaluates food quality and couples this with behavioral change. -The work takes full advantage of the tools available in this powerful system and builds on extensive previous studies on feeding behavior and stress responses in C. elegans.
-Creative use of E. coli genetics and metabolite profiling enabled the identification of carbohydrate metabolism as a candidate source of food-quality signals.
-For the most part, the studies are rigorous and logically designed, providing good support for the authors' model.
We deeply appreciate the reviewer's insightful assessment of our study's strengths.
Weaknesses:
-It is not clear how the mechanism identified here is connected to previously described, related processes. In particular, it is not clear whether this mechanism has a role in the detection of other low-quality foods. Further, the specificity of the ability of sugar/vitamin C to suppress stress pathway induction is unclear (i.e., does sugar/vitamin C have any effect on the activation of these pathways through other means?). Additionally, the relationship of this pathway to the vitamin B2-sensing mechanism previously described by the senior author is unclear. These issues do not weaken confidence in the authors' conclusions, but they do reduce the potential significance of the work.
(1) In particular, it is not clear whether this mechanism has a role in the detection of other low-quality foods.
Thank you for your valuable feedback. In response to your inquiry, we investigated whether the UPRER (IRE-1/XBP-1) - Innate immunity (PMK-1/p38 MAPK) axis is specific to evaluating low-quality food (HK-E. coli) or if it plays a broader role in food detection.
We conducted behavioral assays using N2, pmk-1, and xbp-1 mutant animals fed with normal E. coli food, inedible food (Saprophytic staphylococci)4, and pathogenic food (Pseudomonas aeruginosa-PA14)5. We found that N2, pmk-1, and xbp-1 mutant worms did not exhibit avoidance behavior when presented with normal food (OP50). However, both N2 and xbp-1 mutant worms were able to escape from inedible food (N2 was predominantly found on the border areas of the bacterial lawn and xbp-1 mutant worms on border and in), Saprophytic staphylococci, whereas pmk-1 mutant worms did not exhibit this avoidance behavior. Notably, N2 and xbp-1 mutant worms exhibited even more pronounced avoidance behavior when exposed to Pseudomonas aeruginosa, whereas pmk-1 mutant worms were more susceptible to infection by this pathogen (Figure 2-figure supplement 2C). These findings suggest that the UPR-Immunity pathway plays a crucial role in helping animals avoid low-quality food (HK-E. coli) by triggering an avoidance response. In contrast, the Innate immunity pathway, mediated by PMK-1/p38 MAPK, appears to play a key role in evaluating unfavorable food sources, such as HK-E. coli, Saprophytic staphylococci, and Pseudomonas aeruginosa, and helping animals avoid these environments.
(2) Further, the specificity of the ability of sugar/vitamin C to suppress stress pathway induction is unclear (i.e., does sugar/vitamin C have any effect on the activation of these pathways through other means?).
Thank you for your inquiry regarding the specificity of the ability of sugar/vitamin C to suppress stress pathway induction. We aimed to address this question by investigating whether high levels of VC inhibit other stress-induced UPRER pathways.
Previous studies have shown that both Tunicamycin6 and pathogenic bacteria, such as Pseudomonas aeruginosa-PA145, induce UPRER in C. elegans. In response to your query, we conducted experiments to examine whether VC supplementation inhibits UPRER induced by these stressors. Our findings indicate that VC supplementation does not inhibit UPRER induced by either Tunicamycin or PA14 (Author response image 1).
These results suggest that while sugar/vitamin C may suppress stress pathway induction in the context of low-quality food, its effects may not extend to other stressors that induce UPRER through different mechanisms. This insight helps clarify the specificity of sugar/vitamin C's role in modulating stress pathway activation, contributing to a better understanding of the broader regulatory networks involved in stress response in C. elegans.
VC supplementation does not inhibit Tunicamycin or PA14-induced UPRER.
(3) Additionally, the relationship of this pathway to the vitamin B2-sensing mechanism previously described by the senior author is unclear.
In response to your comment, we would like to clarify the relationship of our pathway to the previously described vitamin B2-sensing mechanism we found. Previous studies have demonstrated that heat-killed E. coli (HK-E. coli) serves as a low-quality food source incapable of supporting the growth of C. elegans larvae, whereas supplementation with vitamin B2 (VB2) can restore animal growth7
This study investigates the role of sugar deficiency in HK-E. coli, which induces the UPRER-immune response and avoidance behavior in C. elegans. Surprisingly, our findings indicate that supplementing HK-E. coli with carbohydrates such as D-Glc and D-GlcA does not promote animal development (Figure 3-figure supplement 2G), suggesting that carbohydrates are not essential for supporting animal growth on this food source. However, we did observe that carbohydrates play a critical role in inhibiting the UPRER-immune response induced by sugar deficiency in HK-E. coli.
-The authors claim that the induction of the innate immune pathway reporter irg-5::GFP is "abolished" in pmk-1(RNAi) animals, but Figure S2K seems to show a clear GFP signal when these animals are fed HK-OP50. Similarly, the claim that feeding WT animals HK-OP50 enriches phospho-PMK-1 levels (Fig 2E) is unconvincing - only one western blot is shown, with no quantification, and there is a smear in the critical first lane.
(1) The authors claim that the induction of the innate immune pathway reporter irg-5::GFP is "abolished" in pmk-1(RNAi) animals, but Figure S2K seems to show a clear GFP signal when these animals are fed HK-OP50.
We sincerely appreciate the reviewer's attention. To address this concern, we have replaced the images with higher resolution, larger ones in Figure 2-figure supplement 1-I. These updated images provide a clearer representation of the data, ensuring that all details are readily visible and enabling a more accurate interpretation of the results.
(2) Similarly, the claim that feeding WT animals HK-OP50 enriches phospho-PMK-1 levels (Fig 2E) is unconvincing - only one western blot is shown, with no quantification, and there is a smear in the critical first lane.
Thank you, following reviewer’s suggestion, we also repeated some of the western. We now replace the Figure 2E and quantified relative intensity of pPMK-1/tublin. We also provide the uncropped western blots images as source data (“raw-data WB” file).
-The rationales for some of the paper's hypotheses could be improved. For example, the rationale for screening the E. coli mutant library is that some mutants, when heat-killed, may be missing a metabolite that induces the ER-UPR. A more straightforward hypothesis might be that some mutant E. coli strains aberrantly induce the ER-UPR when *not* heat-killed, because they are missing a metabolite that prevents stress pathway induction. This is not in itself a major concern, but it would be useful for the authors to provide a rationale for their hypothesis.
Thank you for the insightful suggestion. We acknowledge the importance of providing a clear rationale for our hypotheses in the paper. In response to this feedback, we have enhanced the discussion section to better elucidate the rationale behind our hypotheses.
One limitation of our study is the lack of explanation for why HK-E. coli activates UPRER and immunity. We hypothesized that when heat-killed, HK-E. coli may lack or contain altered levels of certain metabolites that either activate or inhibit UPRER and immunity, respectively. Additionally, we speculated that E. coli mutants killed by heat may lack metabolites that activate UPRER and immunity, or conversely, have increased levels of metabolites that inhibit these pathways.
Fortunately, our investigation led to the discovery of the E. coli mutant yfbR, which inhibits UPRER and immunity by increasing carbohydrates that aid in resisting these stress pathways. Moving forward, we intend to further explore the intricate relationship between HK-E. coli and UPRER-immunity. This will be a key focus of our future research efforts.
-The authors do not provide any explanation for some unexpected results from the E. coli screen. Earlier in the paper, the authors found that innate immune signaling is downstream of ER-UPR activation. However, of the 20 E. coli mutants that, when heat-killed, "did not induce... the UPR-ER reporter," 9 of them still activate the innate immune response. This seems at odds with the authors' simple model since it suggests that low-quality food can induce innate immune signaling independently of the ER-UPR. Further, only one of the 9 has an effect on behavior, even though failure to activate the innate immune pathway might be expected to lead to a behavioral defect in all of these.
Thank you for your understanding, and we apologize for any confusion caused by our earlier statement. To provide clarification, our study revealed that out of the 20 E. coli mutants examined, none activated the UPRER. Among these mutants, 9 did not induce immunity, and interestingly, one out of these 9 mutants demonstrated the ability to inhibit avoidance behavior.
This diversity in phenotypic outcomes can be attributed to the varied metabolites present in different E. coli mutants. To thoroughly evaluate the effects of these mutants, we conducted a comprehensive three-step screening process, utilizing UPRER marker, immunity marker, and avoidance behavior assays.
Through this rigorous approach, we identified the E. coli mutant, yfbR, which exhibited the desired inhibitory effects on UPRER, immunity, and avoidance behavior.
Subsequently, we conducted a metabolomics analysis of various food qualities (HK-K12, HK-yfbR, and Live-K12). Our findings revealed higher sugar levels in
HK-yfbR and Live-K12 compared to HK-K12 (Figure 3B, Figure 3-figure supplement 2A, and Table S1), indicating that sugar deficiency might trigger the UPRER, immunity responses, and subsequent avoidance behavior.
-In a number of places, the writing style can make the authors' arguments difficult to follow.
Thanks for the reviewer’s efforts. We changed all of these errors and polish the language of this paper.
-Some of the effect sizes observed by the authors are exceedingly small (e.g, the suppression of hsp-4::gfp induction by sugar supplementation in Figs 3C-E), raising some concern about the biological significance of the effect.
Thank you for your feedback. In response to your concern, we have included additional clarification in the manuscript.
We have added the following statement: “While sugar effectively inhibits the HK-E. coli-induced UPRER and immune response, it does not fully suppress it to the extent observed with live-E. coli (Figure 3C-F). This implies that additional nutrients present in live-E. coli might also contribute to the inhibition of UPRER and immune response.”
This addition helps to address the observation that some effect sizes appear small, providing context and suggesting potential factors that may influence the outcomes.
-In some cases, there is a discrepancy between the fluorescence images and their quantitation (e.g., Figure 3E, where the effect of glucose on GFP fluorescence seems much stronger in the image than in the graph).
Thank you for your valuable suggestion. In response, we have revised our image selection process to ensure impartiality. We now randomly select images to ensure they accurately represent the quantified data without bias. More details regarding this update can be found in Author response image 2.
More original picture corresponding to Figure 3E.
Reviewer #3 (Public Review):
Summary:
Animals can evaluate food quality in many ways. In contrast to the rapid sensory evaluation with smell and taste, the mechanism of slow nutrient sensation and its impact on food choice is unexplored. The authors utilize C. elegans larvae and their bacterial food as an elegant model to tackle this question and reveal the detailed molecular mechanism to avoid nutrient-poor foods.
Strengths:
The strength of this study is that they identified the molecular identities of the critical players in bacterial food and C. elegans using unbiased approaches, namely metabolome analysis, E. coli mutant screening, and RNA sequencing. Furthermore, they strengthen their findings by thorough experiments combining multiple methods such as genetics, fluorescent reporter analysis, and Western blot.
Thank you for highlighting the strengths of our study.
Weaknesses:
The major caveat of this study is the reporter genes. The transcriptional reporters were used to monitor the UPRER and immune responses in the intestine of C. elegans.
However, their tissue-specific rescue experiments suggest that the genes in the UPRER and immune response function in the neurons. Thus, we should carefully interpret the results of the reporter genes.
Thank you for your insightful comment. We appreciate the opportunity to address your concerns regarding the interpretation of our reporter gene data.
Upon reevaluation, we observed strong induction of the UPRER reporter
(Phsp-4::GFP)8 and immunity reporter (Pirg-5::GFP)9 both in the intestine (Figure 1F-G) and in neurons (Figure 1-figure supplement 2A) in response to feeding unfavorable food (HK-E. coli). This suggests that both the UPRER and immune pathways may indeed respond to low-quality food (HK-E. coli) in multiple tissues of C. elegans. While we acknowledge that our tissue-specific rescue experiments suggest a role for these pathways in neurons, the intestinal fluorescence of Phsp-4::GFP or Pirg-5::GFP is easily observable and scorable. Therefore, we chose to focus our further analyses on the intestine for practical reasons.
Overall, this work provides convincing data to support their model. In the C. elegans field, the behaviors of larvae are not well studied compared to adults. This work will pose an interesting question about the difference between larvae and adults in nutrition sensing in C. elegans and provide a framework and candidate molecules to be studied in other organisms.
Recommendations for the authors:
Reviewer #1 (Recommendations For The Authors):
Major suggestions:
(1) My major overall comment is that the paper would be substantially strengthened by more mechanistic analysis. In particular, how does low vitamin C trigger UPR activation? This is an intriguing finding and it would be important to see it more fully explored.
Our study revealed that the vitamin C content in HK_-E. coli_ is comparable to that of live E. coli or HK-yfbR (Figure 4-figure supplement 1A), suggesting that the induction of unfolded protein response (UPR) in C. elegans by HK-E. coli is not attributed to low vitamin C levels, but rather to unknown factors.
Metabolomic analysis showed that the sugar levels, including lactose, D-(+)-sucrose, and D-(+)-glucose, were significantly decreased in HK-E. coli (Figure 3B, Table S1).
Furthermore, we found that supplementing D-(+)-glucose effectively inhibited UPRER (Figure 3E), immune response (Figure 3F, 3G, and Figure 3-figure supplement 2D), and avoidance behavior (Figure 3H) induced by HK-E. coli. Our findings suggest that the deficiency in sugars in HK-E. coli triggers a stress response and avoidance behavior in animals, which can be alleviated by D-(+)-glucose supplementation.
Notably, when E. coli was heat-killed, we observed that the sugar levels, including lactose and D-(+)-sucrose, were significantly higher in the heat-killed E. coli mutant yfbR (HK-yfbR) compared to HK-E. coli (Figure 3B). Moreover, we found that UPRER was reduced in animals feeding HK-yfbR (Figure 3-figure supplement 1B), indicating that higher sugar levels may inhibit the induction of UPRER by low-quality food.
The synthesis of vitamin C (VC) occurs through the glucuronate pathway, utilizing D-glucose as a precursor 1, 2 (Figure 4A). This led us to investigate whether the vitamin C biosynthesis pathway is involved in evaluating low-quality food by using D-glucose. In this study, we found that animals feeding live E. coli, which should produce more VC, exhibit higher glucose levels. However, our results show that animals maintain similar VC levels when fed ideal food (live E. coli) compared to low-quality food (HK-E. coli) (Figure 4B), suggesting that animals do not stimulate VC biosynthesis under favorable food conditions. In contrast, when animals are fed low-quality food (HK-OP50), we found that supplementing D-GlcA (Figure 4C) or E. coli-yfbR mutation (Figure 4B) in HK-E. coli can improve VC levels. Moreover, we found that VC or D-glucuronate (D-GlcA) supplementation inhibited HK-E. coli induced UPRER (Figure 4D). These data indicate that glucose boosts the animal's ability to adapt to unfavorable food environments by increasing VC levels, thereby inhibiting UPRER, but not in favorable food conditions.
In addition,we asked whether high level of VC inhibits other stress induced UPRER. Previous study shown that Tunicamycin6 and pathogenic bacteria-Pseudomonas aeruginosa-PA145 induce UPRER in C. elegans. We found that VC supplementation does not inhibit Tunicamycin or PA14-induced URPER (Author response image 1).
In addition, how is the activation of the PMK-1 pathway driven by/coordinated with UPR activation?
If the authors do not want to pursue these directions experimentally in this study, the discussion would be strengthened by considering these questions and identifying candidate regulatory mechanisms for further exploration.
In this study, we found that heat-killed E. coli (HK-E. coli), a low-sugar food, triggers cellular unfolded protein response (UPRER) and immune response. We also demonstrated that (1) the activation of UPRER by low-quality food depends on the IRE-1/XBP-1, (2) activation of immune response (PMK-1) is downstream of XBP-1 in responding to low-quality food.
how is the activation of the PMK-1 pathway driven by/coordinated with UPR activation?
In our discussion part, we added new data and discussion to answer reviewer’s question.
A previous study has shown that activating innate immunity (PMK-1 MAPK) leads to a reduction in translation 3. Our own previous research has also demonstrated that PMK-1 activation causes a shutdown of food digestion in animals4, likely to reduce protein translation and cellular metabolism. To investigate this further, we measured the translation level of animals fed with HK-E. coli and found that total translation ability is significantly reduced in these animals (Figure 5-figure supplement 1D). This finding suggests that activating innate immunity (PMK-1 MAPK) may serve as a mechanism to slow down translation progress, thereby alleviating the pressure on the unfolded protein response (UPR) and preventing excessive UPRER activation.
(2) Figure 2C: The data shows that xbp-1 mutants are significantly more likely to leave heat-killed E. coli. However, no other conditions are examined. Is this avoidance defect specific to heat-killed E. coli, or is it a more general effect of xbp-1 mutants - that is, are other conditions that evoke avoidance also affected by mutation of xbp-1? Is feeding behavior on regular E. coli altered in this background? The finding would be more relevant if the authors could clarify or provide more context for their claims here.
We then asked whether UPRER (IRE-1/XBP-1) - Innate immunity (PMK-1/p38 MAPK) axis is specific to evaluate low-quality food (HK-E. coli). We examined the avoidance behavior phenotype of wild-type and mutant L1 animals by placing them on various food conditions, including normal E. coli food, inedible food (Saprophytic staphylococci) and pathogenic food (Pseudomonas aeruginosa-PA14), for a 24-hour period. We found that N2, pmk-1, and xbp-1 mutant worms did not exhibit avoidance behavior when presented with normal food (OP50). However, both N2 and xbp-1 mutant worms were able to escape from inedible food, Saprophytic staphylococci, whereas pmk-1 mutant worms did not show this avoidance. Notably, xbp-1 mutant worms exhibited even more pronounced avoidance behavior when exposed to Pseudomonas aeruginosa, whereas pmk-1 mutant worms were more susceptible to infection by this pathogen (Figure 2-figure supplement 2C). These findings suggest that the UPR-Immunity pathway plays a crucial role in helping animals avoid low-quality food by triggering an avoidance response. In contrast, the Innate immunity pathway, which is mediated by PMK-1/p38 MAPK, appears to play a key role in evaluating unfavorable food sources, such as HK-E. coli, Saprophytic staphylococci, and Pseudomonas aeruginosa, and helping animals avoid these environments.
(3) Figure 3C-F: The magnitude of the changes between conditions shown in these panels is small. To what extent does this supplementation represent a full rescue? The findings would be strengthened if figures/images for the control condition (non-HK E. coli) were shown for comparison to allow the reader to assess the extent to which UPR/PMK-1 activation is rescued.
In response to a reviewer's suggestion, we included live-E. coli as a control in our study. Notably, our data revealed that the addition of lactose, D-(+)-sucrose, and D-(+)-glucose partially inhibited the HK-E. coli-induced unfolded protein response (UPRER) and immune response, suggesting that other nutrients present in live-E. coli may also play a role in inhibiting UPRER.
We added this in manuscript: “While sugar effectively inhibits the HK-E. coli-induced UPRER and immune response, it does not fully suppress it to the extent observed with live-E. coli (Figure 3C-F). This implies that additional nutrients present in live-E. coli might also contribute to the inhibition of UPRER and immune response.”
(4) Figure 5B-D: The magnitude of changes shown between conditions here again appear to be very small, even those labelled as statistically significant. It is important to ensure that the correct statistical tests have been used to assess the significance of these differences (see below).
All statistical analyses were performed in Graphpad prism 8.0. Two-tailed unpaired t test was used for statistical analysis of two groups of samples，one-way or two-way ANOVA was used for statistical analysis of more than two groups of samples.
(5) Methods: In the "Statistical analysis" section, the authors state that "All statistical analyses were performed using Student's t-test". However, this is not the appropriate test to use in experiments where multiple comparisons are made, which is true in several instances across the paper. In these cases, a more appropriate statistical test should be used.
All statistical analyses were performed in Graphpad prism 8.0. Two-tailed unpaired t test was used for statistical analysis of two groups of samples，one-way or two-way ANOVA was used for statistical analysis of more than two groups of samples.
Minor suggestions:
(1) Figure S2: RNAi is usually delivered in a different E. coli strain, HT115. Is this the case with the RNAi knockdowns in Figure S2, and given that diet can influence UPR activation, is it possible that this different diet could change the phenotypes observed?
This should be clarified by the authors.
In this study, all RNAi experiments involved bleaching adult animals under RNAi strain culture conditions to obtain L1 animals. Subsequently, L1 animals were transferred to HK-E. coli OP50 for phenotype analysis. In response to a reviewer's suggestion, we observed that L1 animals obtained from mothers fed E. coli strains OP50, HT115, or K12 exhibited similar UPR induction under HK-E. coli OP50 feeding conditions (Author response image 3). These findings suggest that variations in diet did not alter the UPR phenotypes.
L1 animals obtained from mothers fed <italic>E. coli</italic> strains OP50, HT115, or K12 exhibited similar UPR induction under HK-<italic>E. coli</italic> OP50 feeding conditions.
Reviewer #2 (Recommendations For The Authors):
Line 182: "irg-5::GFP" should be "hsp-4::gfp".
Thanks for the reviewer’s efforts. We have changed this error.
Reviewer #3 (Recommendations For The Authors):
Major comments:
(1) The reporter genes of UPRER and immune response were analyzed in the intestine throughout the study. On the other hand, their rescue experiments suggest that these pathways function in the neurons. They should provide the fluorescence data in the neurons at least for Figures 1F and 1G to confirm that the intestinal response matches the neuronal response and mention that further analyses were done in the intestine for easy scoring.
Consistent with the results of the RNA sequencing (RNA-seq) analysis, the UPRER reporter (Phsp-4::GFP)8 and immunity reporter (Pirg-5::GFP)9 were strongly induced in intestinal (Figure 1F-G) and neurons (Figure 1-figure supplement 2A) by feeding unfavorable food (HK-E. coli), suggesting that UPRER and immune pathways may respond to low-quality food (HK-E. coli). As intestinal fluorescence (Phsp-4::GFP or Pirg-5::GFP) is easy observation and scoring, the further analyses were done in the intestine.
(2) I have concerns about the interpretation of the p-PMK-1 data. Although the authors described that "p-PMK-1 is prominently increased" in the text (Line 150), it is unclear on the data (Figure 2E). Similarly, the authors' statement "p-PMK-1 is decreased in animals with D-GlcA (F).." was not fully supported by the data in Figure 4F. The experiment should be repeated and quantified. Moreover, pPMK-1 showed single bands in Figure 2E, but double bands in Figure 3G, 4F, and 4G. The authors should explain why that is the case and which band we should look at for Figures 3G, 4F, and 4G.
As reviewer’s suggestion, we also repeated some of the western. We found that after longer expose, there are two bands for pPMK-1 (Figure 2E, new data; and “raw-data WB” file). The VHP-1 phosphatase is known to inhibit PMK-13. In our previous study, we found that worms treated with vhp-1(RNAi), which hyperactivates p-PMK-1 (lower band) 4. In contrast, the two bands are disappeared in pmk-1 mutant (Author response image 4). Thus, the lower band indicates the pPMK-1. We now replace the Figure 2E and quantified relative intensity of pPMK-1/tublin. We also provide the uncropped western blots images as source data (“raw-data WB” file).
In our previous study, we found that worms treated with vhp-1(RNAi), which hyperactivates p-PMK-1 (lower band) 4.
In contrast, the two bands are disappeared in pmk-1 mutant. These pictures are extracted from our previous study4.
(3) Heat-killed E. coli (HK-E. coli) is low-quality because the lack of sugar cannot support the growth of C. elegans larvae (Qi and Han, Cell, 2018). Thus, animals do not show the UPRER-immune response and avoidance when HK-E. coli is supplemented with sugars such as glucose (Line 225-227). If these sugars are the key, C. elegans larvae should be able to grow better with HK-E. coli supplemented with glucose. Authors should address this possibility.
Previous studies have shown that heat-killed E. coli (HK-E. coli) is a low-quality food source that cannot support the growth of C. elegans larvae7. Here, we found that sugar deficiency in HK-E. coli induces the UPRER-immune response and avoidance behavior in C. elegans. Given this, we investigated whether sugar supplementation could promote animal growth when fed HK-E. coli. To our surprise, supplementing HK-E. coli with carbohydrates (D-Glc, D-GlcA) did not support animal development (Figure 3-figure supplement 2G), suggesting that carbohydrates are not essential for supporting animal growth on this food source. However, we did find that carbohydrates are critical for inhibiting the UPRER-immune response induced by sugar deficiency in HK-E. coli.
(4) Line 884: Instead of the Student's t-test, the ANOVA should be used for multiple comparisons.
All statistical analyses were performed in Graphpad prism 8.0. Two-tailed unpaired t test was used for statistical analysis of two groups of samples，one-way or two-way ANOVA was used for statistical analysis of more than two groups of samples.
(5) Although the results are interesting and convincing, the manuscript needs some careful editing and proofreading. As far as I could catch, there are more than 100 errors and typos, as I summarized in minor comments. I recommend the authors proofread thoroughly to make this work easier to read.
Thanks for the reviewer’s efforts. We changed all of these errors and polish the language of this paper.
Minor comments:
(1) Line 30: nature -> natural
(2) Line 86: elegnas -> elegans
(3) Line 93: the17h -> the 17h
(4) Line 97: response -> respond
(5) Line106: responded -> respond
(6) Lien 107-109: Add references for the three reporters
(7) Line 114: immune -> immune pathway
(8) Line 118: immune depended -> immune-dependent
(9) Line 128, 594, 596: deferentially -> differentially
(10) Line 131: Explain what IRE-1-mediated splicing of xbp-1 with references
(11) Line 170: XPB-1 -> XBP-1
(12) Line 179: URP -> UPR
(13) Line 181: hsp-4::GFP -> Phsp-4::GFP
(14) Line 183: Italicize E. coli; mutant -> mutants
(15) Line 184: irg-5::GFP -> Pirg-5::GFP (2 places)
(31) Line 459: Make it clear what is the relationship between vitamin C and TAA
(32) Line 527: Do not italicize mutant
(33) Line 538: Phsp-6:GFP -> Phsp-6::GFP (to match other descriptions)
(34) Line 540: Phsp-4:GFP -> Phsp-4::GFP (to match other descriptions)
(35) Line 540: Italicize hsp-4
(36) Line 543: Pirg-5:GFP -> Pirg-5::GFP (to match other descriptions) and italicize irg-5
(37) Line 550, 881: Innate -> innate
(38) Line 557, 560, 564, 838: Do not italicize HK
(39) Line 561: Remove the extra space before "three"
(40) Line 575, 577: Reporter -> reporter
(41) Line 575, 607: Italicize Phsp-4::GFP
(42) Line 577: immunity -> Immunity; Italicize Pirg-5::GFP
(43) Line 585, 653: keio -> Keio
(44) Line 586: hsp-4::GFP -> Phsp-4::GFP
(45) Line 586, 589 (2 places): irg-5::GFP -> Pirg-5::GFP
(46) Line 597: Remove "all"
(47) Line 600: Trehalose -> trehalose
(48) Line 609: Italicize Pirg-5::GFP
(49) Line 615: critically -> critical
(50) Line 636: Remove "+"
(51) Line 656 (2 places), 682: Do not italicize OP50
(52) Line 664: Lead -> lead
(53) Line 681: Describe the composition of NGM or show the reference. Since this paper examines nutrition, the composition of the medium is crucial.
(54) Line 686-706: Italicize all allele names. Be consistent with how to write the promoter to avoid confusion (e.g., ttx-3p -> Pttx-3). Be consistent with how to describe the transgene (e.g., Phsp-4::GFP(zcIs4) -> zcIs4[Phsp-4::GFP])
(55) Line 710: Describe the composition of LB or show the reference. Since this paper examines nutrition, the composition of the medium is crucial.
(56) Line 709, 856 (2 places), 858: Do not italicize K12 to make it consistent
(57) Line 719: Podr-1p:RFP -> Podr-1::RFP
(58) Line 722, 724: Italicize ges-1 and xbp-1
(59) Line 723: Pges-1:xbp-1::GFP -> Pges-1::xbp-1::GFP
(60) Line 735: Glucuronic -> glucuronic
(61) Line 748: I believe it is 5 mm instead of 0.5 mm
(62) Line 750: The equation should be (5 mm)2/(17.5 mm)2
(63) Line 759: Remove the period after "pattern".
(64) Line 766: Describe how they were synchronized
(71) Line 804: I do not understand what "until adulthood" means in this context;
Remove a space before "by". (I recommend searching double space and correcting it.)
(72) Line 853: Metabolome -> metabolome
(73) Line 893-1082: Species and gene names should be italicized in Reference
(74) Figures 1F, 1G, S2F, S2G: The panels' order should match the bar graphs' order. The apparent difference in the representative data does not match the marginal difference in the bar graph in Fig. 1G. The authors should double-check the results.
(82) Figure S3H and S3I: Describe which ones are Glu + conditions
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