Introduction

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 ^1–3. Various sensory neuron evaluation systems in animals has evolved to evaluate food quality through vision ^4,5, olfactory ^3,6–12 and gustatory senses ^13–15. 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 ^16,17. 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 UPR^{ER 18} and PMK-1/p38 MAPK ¹⁹ 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 ²⁰. Animals obtain Vitamin C from their diet and possibly also from gut microbes ²¹. 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 ^22,23. Vitamin C has been associated with various human diseases including scurvy, immune defect and cardiovascular disease ²⁰. Therefore, food evaluation systems in animals for sensing Vitamin C could be critical for their fitness in nature. However, the role of the cellular stress response pathway as food evaluation system for sensing and evaluating Vitamin C remains unexplored.

In this study, using the low-quality food evaluation assay system we established ²⁴, we uncovered the mechanism of cellular stress responses pathway as physiological food evaluation system in evaluating D-Glucose deficiency in food and downstream Vitamin C content in animals through the UPR^ER (IRE-1/XBP-1) - 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.

Results

Low-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 ^24,25. Morevoer, through metabolic-seq analysis, we identified significant changes in a large numbers of metabolites (Figure S1A, Table S1), including lipids (Figure S1B, Table S1), amino acid and their metabolites (Figure S1C, Table S1), as well as coenzymes and vitamins (Figure S1D, Table S1). Interestingly, we observed a significant decrease in carboxylic acids and their derivatives (Figure S1E, Table S1) in E. coli after being heat-killed (Figure S1F, Table S1). This suggests that HK-E. coli is nutritionally deficient for C. elegnas 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 1B). In the avoidance assay, wild-type animals avoided the HK-E. coli food (Figure 1A). Interestingly, in the food choice assay, animals initially showed no preference between the two types of food (1-2h), but eventually exhibited a preference for high-quality food (Live E. coli) up until the17h mark (Figure 1B, Figure S1H). This suggests that worms depart from the HK-E. coli after recognizing it as low-quality food source through ingestion.

Figure 1.

In order to investigate the pathways in animals that response 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 (Figure 1C, Table S2). Among these up-regulated genes, we identified 11 out of 62 of UPR^ER target genes (Figure 1D, Figure S1G and Table S2). Additionally, about 50%-80% of up-regulated genes overlap with genes responding pathogenic bacteria ^26,27 (Figure 1E, Table S2), suggesting that UPR^ER and immune pathways may responded to low-quality food. Consistent with the results of the RNA sequencing (RNA-seq) analysis, the UPR^ER reporter (Phsp-4::GFP) and immunity reporter (Pirg-5::GFP) were strongly induced under HK-E. coli feeding condition (Figure 1F and 1G). Moreover, UPR^Mt reporter (Phsp-6::GFP) was weakly induced under HK-E. coli feeding condition (Figure S1I), and starved worm did not induce UPR^ER and immunity (Figure S1J and S1K).

Together, these findings suggest that low-quality food (HK-E. coli) triggers a stress response pathway in animals, including UPR^ER and innate immune. This implies that animals may assess the quality of food through UPR^ER and innate immune pathway.

Animals evaluate food quality through UPR^ER-immune depended physiological food quality evaluation system

To determine whether the UPR^ER and innate immune pathways play a role in evaluating low-quality food, we first examined whether the activation of the UPR^ER by HK-E. coli was dependent on the known signaling components of the UPR^ER branches, including IRE/XBP-1, PERK/ATF-4 and ATF-6 ^28,29. We observed no difference in Phsp-4::GFP induction with atf-4 (Figure S2A and S2J) or atf-6 (Figure S2B and S2J) 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, 2B and S2J). Among the 11 deferentially expressed UPR^ER target genes in animals fed with HK-E. coli from RNA-seq (Figure 1D), 64% of the genes are IRE-mediated genes (Figure S1G, Table S2). The mRNA level of IRE-1-mediated splicing of xbp-1 is also induced in animals fed with HK-E. coli (Figure S2C). These data suggest that activation of the UPR^ER by low-quality food depends on the IRE-1/XBP-1.

Figure 2.

To further analyze whether XBP-1-dependent UPR^ER 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 indicats that XBP-1-dependent UPR^ER activation in neuron is critical for animals to evaluate low-quality food.

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 ³⁰ were identified (Figure S2D, Table S2). Second, we confirmed the induction of several well-known PMK-1 target genes in RNA-seq data³¹ (Figure S2E) and reporter analysis (Figure S2F and S2G). Moreover, the induction of Pirg-5::GFP was abolished in pmk-1 knockdown animals fed with HK-E. coli (Figure 2D and S2K). 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). 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 UPR^ER (IRE-1/XBP-1) and innate immunity (PMK-1 p38 MAPK) in food quality evaluation. We found that Pirg-5::GFP induction (Figure S2H and S2K) 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 S2I), indicating that XBP-1-dependent UPR^ER 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 XPB-1 in responding to low-quality food.

Sugar deficiency in HK-E. coli 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 URP^ER and immune response in animals (Figure S3A). We established a system for screening the E. coli mutant keio library (Figure S3A), and identified 20 E. coli mutants that did not induce hsp-4::GFP through the UPR^ER reporter (irg-5::GFP) after three rounds of screening (Table S3). From these 20 E. coli mutant, we identified 9 E. coli mutants that did not induce irg-5::GFP through the immunity reporter (irg-5::GFP) screening (Figure S3B, S3C, Table S3). Animals fed HK-yfbR, which catalyzes carbohydrate derivative metabolic process³², had a decreased ability to leave food (Figure 3A, Table S3), indicating that HK-yfbR may be a higher quality food for animals compared to HK-K12.

Figure 3.

Secondly, we preformed 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 S3D, and Table S1). We also found that genes involved in glycolysis/gluconeogenesis were up-regulated in animals fed with HK-E. coli (Figure S3E), 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.

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 UPR^ER (Figure 3C and 3D, Figure S3F). 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, Table S1). Since Lactose and D-(+)-sucrose are hydrolyzed to produce glucose^33,34, we wondered whether glucose also inhibits the stress response in animals. We found that D-(+)-Glucose supplementation also inhibited HK-E. coli induced UPR^ER (Figure 3E), immune response (Figure 3F, 3G and Figure S3G) and avoidance (Figure 3H). Moreover, sugar supplementation did not affect UPR^ER and immunity in normal food (OP50) or starved condition (NGM) (Figure S3H and S3I).

Together, these findings suggest that sugar/carbohydrates deficiency in 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 sugars deficiency through the activation of UPR^ER 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 UPR^ER (Figure 3E), immune response (Figure 3F, 3G and Figure S3G) and avoidance (Figure 3H). Simultaneously, vitamin C (VC), which is synthesized by glucuronate pathway using D-Glucose ^35,36 (Figure 4A), was found contribute to neuroprotective^37,38, immune defense^39,40, and inhibits inflammatory and ER stress^41,42. This led us to question whether the Vitamin C biosynthesis pathway is involved in evaluating low-quality food by using D-Glucose.

Figure 4.

Firstly, we observed an increase in the vitamin C level in animals when fed with HK-yfbR (Figure 4B), a high carbohydrate food compared to HK-E. coli (Figure 3B and Figure S1E). However, the VC level in bacteria is same (Figure S4A). The VC level also increased when D-Glucose (Figure S4B) 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 S4B). This suggests that additional 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 inhibited HK-E. coli induced UPR^ER (Figure 4D), immune response including irg-5/sysm-1 reporter expression (Figure 4E and Figure S4C) and p-PMK-1 (Figure 4F and 4G), 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 UPR^ER (Figure 4I), immune response (Figure 4J and Figure S4D) 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 S4E). However, VC supplementation still suppressed the UPR^ER (Figure 4I), immune response (Figure 4J and Figure S4D) and food avoidance (Figure 4K), and increased the food preference (Figure S4E) 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 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 UPR^ER, 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 conditons (Figure S4F). 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 (no food condition) supplementation with D-Glc and VC (Figure S4G), 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 S4G). Interestingly, D-Glc and D-GlcA (Figure 5B and 5C) 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.

Figure 5.

Figure 6.

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 ², 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 ²⁴. 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 detect sugar (in food) and vitamin C (in animals) deficiency through UPR^ER (IRE-1/XBP-1) - Innate immunity (PMK-1/p38 MAPK) regulated cellular stress response program in neurons that dictates food avoidance and selection behaviors.

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 ⁴³. 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 neuronal system.

One of cellular stress response, UPR^ER, is activated by stresses such as infection and nutrition deficiency that affect homeostasis in the endoplasmic reticulum (ER) ²⁸. The activation of the UPR^ER by expression of xbp-1s in the nervous system has recently been shown to promote changes in feeding and foraging behavior ⁴⁴. The p38 PMK-1 pathway regulates the expression of secreted innate immune effectors and is required for survival during infection ⁴⁵. Moreover, UPR^ER and innate immunity increased by disrupting in vivo state would induce worm aversion from food lawn^46–49. Thus, these two cellular stress response pathways are critical for animals’ survival in changing environment. However, whether UPR^ER (IRE-1/XBP-1) - Innate immunity (PMK-1/p38 MAPK) evaluates food quality under physiological conditions is largely unexplored. Our study presents evidence that low-quality food (HK-E. coli) activate UPR^ER and PMK-1, and promotes animals to leave food. It is independent of avoidance behavior of hyperactivation of kgb-1/MAPK pathway⁴⁹ (Figure S4H). Mover, our study also shows that neuronal UPR^ER and PMK-1 are critical for evaluating low-quality food. Therefore, our study established a novel physiological food evaluation system by activating the cellular stress response program with UPR^ER (IRE-1/XBP-1) - Innate immunity (PMK-1/p38 MAPK).

Collectively, this study uncovers the unexpected function of UPR^ER (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.

Author Contributions

P. L designed, performed experiments, analyzed data. X. L constructed all transgenic animals. B.Q. designed research, supervised this study, and wrote the paper with inputs from P. L.

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 (2019YFA0803100,2019YFA0802100), the National Natural Science Foundation of China (32170794), Yunnan Applied Basic Research Projects (202001AV070011, 202001AW070006, 202201AT070196), the Yunnan University Startup Program.

Declaration of interests

The authors declare no competing interests.

Supplemental Figure legends

Figure S1.

Figure S2.

Figure S3.

Figure S4.

Supplemental Tables

Table S1. Metabolices analysis. Relative to Figure S1A, S1B, S1C, S1D, S1E, S1F, 3B, and S3D.

Table S2. RNA-seq analysis. Relative to Figure 1C, 1D, 1E, S1G, and S2D.

Table S3. Screening data for E. coli mutant keio library. Relative to Figures S3A, S3B, and S3C.

Table S4. Metabolomics-seq data of HK-K12, HK-yfbR and K12.

Table S5. RNA-seq data of animals fed with HK-E. coli OP50 and E. coli OP50.

Raw-data. Raw data for experiments.

Star Methods

Resource Availability

Lead contact

Further information and requests for reagents may be directed to the Lead contact Bin Qi (qb@yun.edu.cn).

Materials availability

All reagents and strains generated by this study are available through request to the lead contact with a completed Material Transfer Agreement.

Data and code availability

Metabolomics-seq data are accessible in Table S4 RNA-seq data are accessible in Table S5.

This paper does not report original code.

Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

Experimental model and subject details

C. elegans 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:

N2 Bristol (wild type control strain);

AU78: agIs219 [T24B8.5p::GFP::unc-54 3’ UTR + ttx-3p::GFP::unc-54 3’ UTR];

SJ4005: Phsp-4::GFP(zcIs4);

AY101: acIs101 [F35E12.5p::GFP + rol-6(su1006)]IG274: frIs7 [nlp-29p::GFP + col-12p::DsRed] IV;

SJ17: xbp-1 (zc12); KU25: pmk-1(km25);

AY102: pmk-1(km25) IV; acEx102 [vha-6p::pmk-1::GFP + rol-6(su1006)];

YNU108: Ex[Prgef-1::pmk-1::GFP; Podr-1::RFP]⁵⁰;

xbp-1(tm2482) ⁵¹;

KU21: kgb-1(km21);

AU133: agIs17 [myo-2p::mCherry + irg-1p::GFP] IV;

SJ4100: zcIs13 [hsp-6p::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, 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.

Method Details

Generation of transgenes

• 1) To construct the C. elegans plasmid for expression of xbp-1 in neuron, 3057bp 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 (25ng/ul) and Podr-1p:RFP (25ng/ul) was injected into the gonads of adult xbp-1(tm2482).

• 2) 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 (25ng/ul) and Podr-1p:RFP (25ng/ul) was injected into the gonads of adult xbp-1(tm2482).

Preparation and feeding of worm food

We followed an established protocol ^24,25 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 150ul of the heat-killed bacteria was spread onto each 35mm NGM plate.

Preparation of HK-E. coli + carbohydrate or Vitamin C food

1. 100ul of water, 100ul of L-ascorbic acid (dissolved in water at a concentration of 100mg/ml, Sangon Biotech, 100143-0100) or 100 ul of D-Glucuronic acid (dissolved in water at a concentration of 100mg/ml,Adamas, 1102520) was mixed with 500 ul of HK-E. coli, then 150ul of the mixture was spread onto 35mm NGM plates.

2. 12.5ul of water or 12.5ul of D-(+)-Glucose (dissolved in water at a concentration of 100mg/ml, Sangon Biotech, A501991-0500) was mixed with 500 ul of HK-E. coli, then 150ul of the mixture was spread onto 35mm NGM plates.

Behavioral assay

C. elegans selection assays

For C.elegans to have enough space to evaluate food, we add 18ul of the sample onto a 35mm NGM plate. This creates a round lawn with a radius of 0.5mm, which occupies about 8% of the total plate area.

a: the area of bacterial lawn

b: the space of worm life (area of culture dish)

1. 18ul of heat-killed OP50, live OP50, and LB broth (as the buffer for bacteria) was added into 35mm NGM plate in an equilateral triangle pattern. Then, synchronized L1 worms were seeded in the center of NGM plate for 16-17h at 20°C (as indicated in Figure1B).

2. 18ul of heat-killed OP50 and heat-killed OP50 with D-GlcA or Vitamin C was added into 35mm NGM plate in an equilateral triangle pattern., then synchronized L1 worms were seeded on equilateral triangle of NGM plate for 16-17h at 20°C (as indicated in Figure 5A).

Here is Selection rate formula:

C. elegans aversion assays

18ul food was spread out the center of NGM plate, then synchronized L1 worms were seeded on center of food for 16-17h at 20°C.

Three to ten 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 UPR^ER 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 24h 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.

E. coli 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 50µg/ml kanamycin at 37°Cuntil an OD600 of 0.5-0.6 was reached. The bacteria were then heat-killed following our established protocol ²⁴, and 150 ul of the heat-killed the mutant E. coli was spread onto 3.5 cm NGM plates. Synchronized L1 worms carrying UPR^ER reporter (Phsp-4::GPF) were seeded and cultured for 24h at 20 °C. The fluorescence was then examined by using an Olympus MVX10 dissecting microscope, progressive screening three times. next, an 4^th screen was performed using immune reporter (Pirg-5::GPF) animals fed with HK-E. coli mutants that reduced the Phsp-4::GPF fluorescence. Finally, an aversion behavior assay was performed using HK-E. coli mutants that both reduced Phsp-4::GPF and Pirg-5::GPF. HK-E. coli mutants that reduced UPR^ER, immune and avoidance behavior were identified through this screening.

RNAi treatment

Bacterial clones from either the MRC RNAi library ⁵² or the ORF-RNAi Library⁵³ were used. 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 ug/ml ampicillin and 100uM IPTG) of specific RNAi strains and the control HT115 strain were seeded onto RNAi feeding plates and cultured at room temperature until adulthood. 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 18hr. 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 4h) were analyzed by standard western blot methods and probed with anti-p38 (dilution = 1:5,000; Cell Signaling, 9212S), anti-p-p38 (dilution = 1:5,000; Cell Signaling, 4511S) 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 hours. 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 concentration

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 = 0.0611x + 0.0003 for Figure 4C; y = 0.0258x + 0.0066 for Figure 4B, S4A and S4B.

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 hours to obtain synchronized L1 worms. L1 worms were cultured in the NGM plate with HK-E. coli or E. coli for 4hrs 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 ⁵⁴ 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 ⁵⁵ was used to calculate the gene expression level of each sample. Read counts were inputted into DESeq2 ⁵⁶to 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, 180min), E. coli K12, HK-E. coli K12 and HK-E. coli yfbR mutant were then spread out NGM plate for 72hs at room temperature. Finally, sample was collected into 1.5ml 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 or Olympus MVX10 dissecting with a DP80 camera.

Quantification and statistical analysis

Quantification

ImageJ software was used for quantifying fluorescence intensity of UPR^ER 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 preformed using Student’s t-test in Graphpad prism 8.0. Two-tailed unpaired t test was used for statistical analysis of 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.