ER Proteotoxic Stress Drives Mitochondrial Dysfunction in Heat-Stressed Intestinal Epithelial Cells

Abstract

Global climate change has increased the frequency and intensity of heat waves, posing a significant threat to livestock production. During heat exposure, the disruption of intestinal barrier integrity is a pivotal event in the pathogenesis of heat stress-induced intestinal injury. Endoplasmic reticulum (ER) stress and mitochondrial dysfunction are key consequences of heat stress at the cellular level. However, direct causal evidence linking ER stress to mitochondrial dysfunction in heat-stressed enterocytes remains limited. To investigate this, we used an integrated transcriptomic, metabolomic, and functional validation strategy to assess mitochondrial bioenergetics and cellular ultrastructure in porcine intestinal epithelial (IPEC-J2) cells under acute heat stress. Transcriptomic analysis revealed extensive reprogramming, highlighting the significant enrichment of pathways related to protein processing in the endoplasmic reticulum, apoptosis, and MAPK signaling. Untargeted metabolomics identified significant perturbations in amino acid and energy metabolism, as well as altered bile acid profiles. Functional assessments confirmed that heat stress severely impaired mitochondrial bioenergetics, as evidenced by reduced maximal respiration and ATP production, and induced ultrastructural damage to mitochondria. The pharmacological inhibition of ER stress by 4-phenylbutyric acid (4-PBA) significantly attenuated the mitochondrial bioenergetic impairment and ultrastructural damage, whereas ER stress induction recapitulated these defects. We demonstrate that heat stress induces profound transcriptional and metabolic remodeling characterized by ER stress activation, which critically mediates subsequent mitochondrial bioenergetic dysfunction and ultrastructural damage. Our findings suggest that targeting ER stress may represent a promising therapeutic strategy to ameliorate enterocyte mitochondrial dysfunction and mitigate heat stress-induced intestinal injury in livestock.

1. Introduction

The increasing frequency and intensity of heat waves due to global climate change poses a significant threat to livestock health and production [1,2,3]. In swine, heat stress suppresses growth and triggers systemic disturbances such as inflammatory responses and metabolic dysregulation [4,5]. The breakdown of intestinal homeostasis is a pivotal event in heat stress pathology. As the primary interface with the luminal environment, intestinal epithelial cells are highly susceptible to heat stress, and their dysfunction or death constitutes the cellular basis for subsequent barrier impairment [6,7]. Heat stress impairs epithelial integrity, primarily through the disruption of tight junctions and the induction of inflammatory responses [8,9]. Therefore, controlled in vitro models are indispensable to explore the underlying mechanisms. The porcine intestinal epithelial cell line IPEC-J2, which retains key characteristics of differentiated enterocytes such as tight junction formation and polarization, provides a well-established and relevant model for this purpose [10,11].

At the cellular level, heat stress induces rapid transcriptional and metabolic reprogramming and activates organelle-specific stress pathways [12,13]. Within this stress response, the ER and mitochondria emerge as critically affected organelles and key determinants of cellular fate. The ER, as the primary site for protein folding and lipid biosynthesis, is highly sensitive to homeostatic perturbations [14,15]. Heat stress disrupts ER proteostasis, leading to the accumulation of misfolded proteins and subsequent activation of the unfolded protein response (UPR) [16,17,18]. Concurrently, mitochondria, the primary sites of cellular energy production, frequently undergo functional decline under heat stress, characterized by diminished oxidative phosphorylation capacity and elevated generation of reactive oxygen species (ROS) [19,20]. While the individual activation of ER stress and mitochondrial dysfunction in heat-stressed cells are recognized, the nature of their interaction remains poorly understood. The bidirectional crosstalk between the ER and mitochondria, mediated by calcium flux and membrane contacts [21,22,23], constitutes a critical signaling axis that determines cellular fate. However, direct experimental evidence that causally links ER stress to downstream mitochondrial dysfunction in heat-stressed enterocytes is still limited, representing a significant gap in our understanding of the pathogenesis of heat stress-induced intestinal injury.

Previous studies have largely employed single-omics approaches or isolated pathway analyses to investigate either ER stress or mitochondrial dysfunction independently [18,19]. Consequently, a systems-level understanding of how heat stress concurrently remodels the transcriptional landscape, metabolomic profile, and functional outputs of intestinal epithelial cells remains lacking. This fragmented view leaves a critical gap in our knowledge regarding the integrated molecular response and, crucially, prevents the establishment of precise causal relationships between key stress pathways. The central unresolved question is whether ER stress acts as a critical mediator of the subsequent mitochondrial dysfunction observed in heat-stressed enterocytes [24,25].

To address this critical gap, we applied an integrated multi-omics and functional phenotyping strategy to comprehensively decipher the response of IPEC-J2 cells to acute heat stress. We hypothesized that heat stress induces extensive transcriptional and metabolic reprogramming orchestrated by ER stress activation, and that ER stress plays a critical mediating role in the concomitant mitochondrial bioenergetic and structural dysfunction. To test this hypothesis and elucidate the causal relationship between ER stress and mitochondrial damage, we aimed to: (1) map the transcriptional and metabolic remodeling induced by acute heat stress using integrated RNA-sequencing and untargeted metabolomics; (2) functionally characterize the resulting mitochondrial bioenergetic impairment and ultrastructural damage; and (3) directly test the causal role of ER stress in mediating mitochondrial dysfunction through the specific pharmacological modulation of the ER stress pathway.

2. Materials and Methods

2.1. Cell Culture and Establishment of an In Vitro Heat Stress Model

The porcine intestinal epithelial cell line IPEC-J2 used in this study was obtained from the State Key Laboratory for Animal Disease Control and Prevention (College of Veterinary Medicine, Chinese Academy of Agricultural Sciences, Lanzhou, China). This cell line has been characterized and used in previous studies [26]. Cells were cultured in high-glucose Dulbecco’s Modified Eagle Medium (DMEM; Gibco, Waltham, MA, USA) supplemented with 10% fetal bovine serum (Gibco), 100 U/mL penicillin, and 100 μg/mL streptomycin (Gibco), and maintained at 37 °C in a humidified atmosphere with 5% CO₂. To establish a reproducible heat stress model, cells were grown to approximately 80% confluence and then subjected to heat stress using a separate, calibrated incubator set to 42 °C with 5% CO₂. Both the 37 °C (control) and 42 °C incubators were maintained in a humidified atmosphere. To determine the optimal exposure duration for inducing significant but sublethal stress, a preliminary time-course experiment was conducted. Cells were exposed to 42 °C for 6, 12, and 24 h, and cell viability was assessed using a Cell Counting Kit-8 (CCK-8) assay (as described in Section 2.2). A 12-h exposure at 42 °C resulted in a significant reduction in cell viability (~30% decrease), establishing an acute heat injury model with ~70% cell viability, which is suitable for exploring the early mechanistic events of heat stress without massive cell death. This duration was therefore selected for all subsequent experiments to investigate the initiating events of cellular dysfunction. This model is intended to represent acute, severe heat stress in vitro. Immediately before transferring the cells to the 42 °C incubator, the culture medium was replaced with fresh medium pre-warmed to 42 °C to avoid thermal shock. Control cells were handled identically but remained in the 37 °C incubator for the same duration. After the 12-h treatment, cells were immediately processed for downstream analyses.

2.2. Assessment of Intracellular ROS and Cell Viability

Cell viability was assessed with a Cell Counting Kit-8 (Beyotime Biotechnology, Shanghai, China) assay. After treatment, cells were incubated with 10% CCK-8 reagent for 2 h at 37 °C, and the absorbance at 450 nm was measured using a microplate reader. Viability was calculated as a percentage of the control (set as 100%). For each independent experiment, six technical replicates were performed. Three independent experiments were conducted. Intracellular ROS were detected using the fluorescent probe 2′,7′-Dichlorodihydrofluorescein diacetate (DCFH-DA; Beyotime Biotechnology, Shanghai, China). Following treatment, cells were loaded with 10 µM DCFH-DA in serum-free medium for 20 min at 37 °C in the dark and then washed. For quantitative analysis by flow cytometry, stained cells were trypsinized, resuspended in PBS, and analyzed on a flow cytometer (BD Biosciences, San Diego, CA, USA). Fluorescence of the oxidized DCF product was measured with excitation at 488 nm and emission collected through a 530/30 nm filter; at least 10,000 events were recorded per sample. Data were processed using FlowJo software (version 7.6.2, BD Biosciences, San Diego, CA, USA), and the median fluorescence intensity was used to indicate ROS levels. All experiments were repeated three times.

2.3. RNA Sequencing and Transcriptomic Analysis

Total RNA was extracted using TRIzol reagent (Invitrogen, Carlsbad, CA, USA). RNA quality was assessed using a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA) and an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Sequencing libraries were prepared with the VAHTS Universal V10 RNA-seq Library Prep Kit (Vazyme, Nanjing, China) and sequenced on an Illumina NovaSeq 6000 platform (150 bp paired-end) by OE Biotech (Shanghai, China). The raw sequencing data have been deposited in the NCBI SRA database under accession number PRJNA1412493. Raw FASTQ reads were processed with fastp for quality control. Clean reads were aligned to the Sus scrofa reference genome (Ensembl Sscrofa11.1) using HISAT2 (version 2.0.5), and gene-level read counts were obtained with HTSeq-count. Differential expression analysis was conducted using DESeq2 in R on the raw integer count data, with genes satisfying |log₂ fold change| ≥ 0.5 and adjusted p-value (FDR) < 0.05 considered differentially expressed genes (DEGs). For visualization purposes only, gene expression levels were estimated using the tximport pipeline in R and expressed as Transcripts Per Million (TPM) for downstream analysis. Principal component analysis (PCA) was performed based on variance-stabilized counts. Functional enrichment analysis of DEGs for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways was carried out via hypergeometric testing. Additionally, Gene Set Enrichment Analysis (GSEA) was performed. All results were visualized using ggplot2. To validate the RNA-seq results, five randomly selected DEGs were analyzed by RT-qPCR (primer sequences in Supplementary Table S1). cDNA was synthesized from 1 μg total RNA using the PrimeScript RT reagent Kit with gDNA Eraser (TaKaRa, Kyoto, Japan). RT-qPCR was performed in triplicate on a QuantStudio 5 system (Applied Biosystems, Foster City, CA, USA) with SYBR Green Premix Pro Taq HS qPCR Kit (TaKaRa, Kyoto, Japan) under the following conditions: 95 °C for 30 s, then 40 cycles of 95 °C for 5 s and 60 °C for 30 s. GAPDH served as the endogenous control, and relative expression was calculated via the 2^−ΔΔCt method. Validation results are presented in Figure S1.

2.4. Western Blot Analysis

Cells were lysed in RIPA buffer containing protease and phosphatase inhibitor cocktails (both from Beyotime Biotechnology, Shanghai, China). Protein concentrations were determined using a BCA protein assay kit (Beyotime Biotechnology, Shanghai, China). Equal amounts of protein (30 μg per lane) were separated by SDS-PAGE and transferred onto PVDF membranes (Millipore, Billerica, MA, USA). After blocking with 5% non-fat milk, the membranes were incubated overnight at 4 °C with the following primary antibodies: HSP90B1 (1:1000, Servicebio, GB111280), GRP78 (1:1000, Servicebio, GB15098), ATF4 (1:1000, Servicebio, GB11157), phospho-eIF2α (Ser51) (1:1000, CST, #3398), eIF2α (1:1000, Servicebio, GB150025), CHOP (1:1000, Servicebio, GB115691), Cleaved Caspase-3 (1:1000, Servicebio, GB11532), and β-Actin (1:5000, Servicebio, GB15003). After washing, the membranes were incubated with an HRP-conjugated goat anti-rabbit IgG secondary antibody (1:20,000, Servicebio, GB23303) at room temperature for 1 h. Protein bands were visualized using an enhanced chemiluminescence (ECL) detection system (Tanon, Shanghai, China). Band intensities were quantified with ImageJ software (version 1.8.0, National Institutes of Health, New York, NY, USA), normalized to β-actin, and expressed relative to the control group.

2.5. Untargeted Metabolomic Profiling

Untargeted metabolomic profiling was performed using a Waters ACQUITY UPLC I-Class plus system coupled to a Thermo Q Exactive™ Plus (Thermo Fisher Scientific, Waltham, MA, USA) mass spectrometer. Metabolites were extracted from samples with ice-cold methanol–water (4:1, v/v, containing internal standards) and homogenized by ice-bath sonication. After incubation at −40 °C overnight and centrifugation, the supernatant was dried under nitrogen. The residue was reconstituted in methanol–water (1:4, v/v), vortexed, sonicated, and incubated again at −40 °C. Following a final centrifugation, the supernatant was subjected to LC-MS analysis. A pooled quality control (QC) sample was prepared from equal aliquots of all extracts. Chromatographic separation was carried out on an ACQUITY UPLC HSS T3 column (100 mm × 2.1 mm, 1.8 μm) at 45 °C with mobile phases of 0.1% formic acid in water (A) and acetonitrile (B), flowing at 0.35 mL/min. Mass spectrometry employed a heated electrospray ionization (HESI) source in both positive and negative ion modes. Data were acquired in data-dependent acquisition (DDA) mode, collecting high-resolution full-scan MS data followed by MS/MS scans of the ten most intense ions.

2.6. Measurement of Oxidative Stress Markers, Lactate, and ATP

To evaluate the effects of heat stress, IPEC-J2 cells from the control (37 °C) and heat-stress (42 °C for 12 h) groups were collected. The levels of malondialdehyde (MDA), superoxide dismutase (SOD) activity, lactate, and adenosine triphosphate (ATP) were measured using commercial kits (Servicebio, Wuhan, China) following the manufacturer’s protocols, with all samples assayed in triplicate and normalized to protein concentration, determined via a BCA kit (Beyotime Biotechnology, Shanghai, China). For MDA, harvested cells were lysed in PBS by ultrasonication on ice, centrifuged (10,000× g, 4 °C, 15 min), and the supernatant was incubated with an MDA working solution (assay buffer, probe working solution, and antioxidant reagent at a 200:200:4 µL ratio per sample) at 95 °C for 40 min. After cooling and centrifugation, the absorbance of the supernatant was measured at 532 nm. Total SOD activity was assessed in cell lysates prepared similarly. Briefly, samples were mixed with enzyme and detection working solutions in a 96-well plate, incubated at 37 °C for 20 min, and absorbance was read at 450 nm; one unit (U) was defined as the inhibition rate of 50%. For intracellular lactate, cells were homogenized in pre-cooled PBS, centrifuged, and the supernatant was incubated sequentially with detection buffer (37 °C, 5 min) and enzyme solution (37 °C, 5 min), with absorbance measured at 546 nm. For ATP, cells were lysed in the provided buffer, homogenized, boiled for 2 min, and centrifuged. The supernatant was added to a white plate containing ATP detection working solution, and luminescence was measured after a 15 s shake. Concentrations for MDA, lactate, and ATP were calculated from standard curves.

2.7. Analysis of Mitochondrial Function

Mitochondrial respiration was assessed using a Seahorse XF96 Analyzer (Agilent Technologies, CA, USA) with the XF Cell Mito Stress Test Kit. Cells were seeded at 1 × 10⁴ cells per well in a 96-well plate, incubated for 1 h to attach, and cultured for 16–20 h. The sensor cartridge was hydrated overnight at 37 °C (non-CO₂) and loaded with pre-warmed XF calibrant 45–60 min before the assay. The assay medium (XF base medium with 10 mM glucose, 1 mM pyruvate, 2 mM glutamine, pH 7.4) was used to wash cells twice, followed by incubation for 60 min at 37 °C (non-CO₂). Inhibitors were injected sequentially: 1.5 μM oligomycin, 0.5 μM FCCP (optimized by titration), and 0.5 μM rotenone/antimycin A. OCR was measured over three cycles per phase. Three independent experiments were performed (n = 3), with 5–6 technical replicates per condition averaged for each biological replicate. Background correction was applied using cell-free wells. Post-assay, cells were lysed, and protein concentration was determined by BCA assay to normalize OCR values.

2.8. Transmission Electron Microscopy (TEM)

Cells grown to approximately 80% confluence were trypsinized, collected by centrifugation (3000 rpm, 5 min), and fixed in 2.5% glutaraldehyde in 0.1 M phosphate buffer (PB, pH 7.4) for 2 h at 4 °C in the dark. After washing with PB, the pellet was pre-embedded in 1% agarose. Post-fixation was performed with 1% osmium tetroxide in PB for 2 h at 4 °C in the dark, followed by further PB washes. Subsequent processing included dehydration through a graded ethanol series, infiltration and embedding in resin, and ultrathin sectioning for TEM observation.

2.9. Statistical Analysis

Data are presented as mean ± standard deviation (SD) from at least three independent biological replicate experiments. For each independent biological replicate, technical replicates (parallel wells/detections for the same sample) were set according to the requirements of different assays: the CCK-8 assay included 6 technical replicates per biological replicate, and all other assays (including ROS detection, RT-qPCR, Western blot, metabolite detection, and Seahorse assay) included 3 technical replicates per biological replicate. The mean value of technical replicates for each independent experiment was used as the final value of that biological replicate for subsequent statistical analysis.

Normality was assessed with the Shapiro–Wilk test, and the homogeneity of variances was assessed with the Brown–Forsythe test. For two-group comparisons of normally distributed data, a two-tailed Student’s t-test was used. For multiple groups, one-way ANOVA with Tukey’s post hoc test was applied if assumptions were met; otherwise, non-parametric tests (Mann–Whitney U for two groups, or Kruskal–Wallis with Dunn’s test for multiple groups) were employed. Tests used for each dataset are specified in the figure legends. p < 0.05 was considered statistically significant. All statistical analyses were performed using Prism version 10.2.3 (GraphPad Software, La Jolla, CA, USA).

2.10. Pharmacological Modulation of ER Stress

To modulate ER stress pharmacologically, we employed 4-phenylbutyric acid (4-PBA; sodium salt, Sigma-Aldrich, St. Louis, MO, USA) as an ER stress inhibitor and tunicamycin (Sigma-Aldrich, St. Louis, MO, USA) as an ER stress inducer. 4-PBA was prepared as a 1 mM stock solution in dimethyl sulfoxide (DMSO) and diluted in fresh culture medium to a final working concentration of 1 μmol/L immediately before use. Tunicamycin was dissolved in DMSO at a concentration of 1 mg/mL as a stock solution and diluted to a final working concentration of 1 µg/mL in culture medium. The concentrations were selected based on previous studies demonstrating their efficacy in modulating ER stress in porcine or other mammalian intestinal epithelial cell models [27,28]. The final concentration of DMSO did not exceed 0.1% (v/v) in all treatment and vehicle control groups. For experiments involving ER stress inhibition, cells were pretreated with 4-PBA (1 μmol/L) for 6 h and then co-treated with 4-PBA throughout the subsequent 12-h heat-stress exposure. To directly assess the consequences of ER stress induction, a separate group of cells was treated with tunicamycin (1 µg/mL) alone for 12 h at 37 °C, which corresponds to the duration of the heat stress exposure in the experimental groups. As a control for this treatment, cells were incubated with vehicle (DMSO) at a final concentration of 0.1% (v/v) under identical conditions (37 °C for 12 h) in parallel. The vehicle control (DMSO) for the 4-PBA treatment experiments was also handled according to this protocol.

2.11. Experimental Controls and Quality Assurance

To ensure robustness, stringent controls were implemented. IPEC-J2 cells were used within passages 5–15. All assays included parallel 37 °C negative controls, and pharmacological interventions included vehicle controls (DMSO ≤ 0.1% v/v). Assay-specific controls were: CCK-8 blank wells for background subtraction; unstained cells for ROS autofluorescence baseline; tunicamycin-treated lysates as positive Western blot controls, with β-Actin as loading control; RNA integrity (RIN ≥ 8.0) for sequencing, plus no-template and no-RT controls for RT-qPCR; pooled QC samples every 10 runs and blank solvents for metabolomics; no-cell wells for Seahorse background correction, with FCCP pre-titrated. Raw data were inspected for outliers; normality-guided statistical tests and FDR correction for high-throughput data were applied.

3. Results

3.1. Heat Stress Induces Time-Dependent Intracellular ROS Accumulation and Impairs Cell Viability

Heat stress triggered a time-dependent increase in intracellular ROS in IPEC-J2 cells, as visualized using the DCFH-DA probe (Figure 1A). This ROS accumulation was quantified by flow cytometry, which showed a progressive rightward shift in fluorescence peaks at 6, 12, and 24 h post-exposure compared to the control (Figure 1B). Concomitantly, cell viability exhibited a time-dependent decline (Figure 1C). Notably, viability decreased to 69.1 ± 6.1% of control levels after 12 h (p < 0.001; Figure 1C). This reduction indicates a severe stress state where cells are functionally compromised yet the majority remain metabolically active, allowing for the assessment of upstream mechanistic drivers preceding massive cell population collapse. Consequently, this time point was selected for all subsequent experiments.

3.2. Transcriptomic Profiling Reveals Extensive Reprogramming of Stress-Response Pathways

Heat stress profoundly altered the transcriptomic landscape of IPEC-J2 cells. PCA revealed clear separation between the control and heat-stressed groups, with samples within each group clustering tightly, indicating high reproducibility of the biological triplicates (Figure 2A). Differential expression analysis identified 2511 significantly upregulated and 2775 significantly downregulated genes (|log₂FC| ≥ 0.5, adjusted p < 0.05), including canonical ER stress markers such as HSP90B1 (GRP94), EIF2AK3 (PERK), DDIT3 (CHOP), and HSPA5 (GRP78) (Figure 2B). The top 10 upregulated and downregulated genes are listed in

Table 1. Top 10 upregulated and downregulated differentially expressed genes in IPEC-J2 cells under heat stress.

Genes	Regulation	log2 Fold Change	p-Value	Description
LOC100737483	Up	8.82	2.84 × 10−12	Keratin, type II cytoskeletal 6A
HTR6	Up	6.60	3.51 × 10−6	5-hydroxytryptamine receptor 6
FITM1	Up	6.57	2.59 × 10−6	Fat storage inducing transmembrane protein 1
OSM	Up	6.43	6.08 × 10−9	Oncostatin-M
SLC16A4	Up	6.38	1.84 × 10−18	Monocarboxylate transporter 5
HSPA6	Up	6.19	1.12 × 10−43	Heat shock protein 70
SIGLEC11	Up	6.04	3.40 × 10−5	Sialic acid-binding Ig-like lectin 11
C2H11orf96	Up	5.87	1.98 × 10−7	Uncharacterized protein C11orf96
RDH16	Up	5.82	0.00013	Retinol dehydrogenase 16 (all-trans)
MATN3	Up	5.72	2.71 × 10−5	Matrilin-3
CCDC78	Down	−6.39	2.55 × 10−6	Coiled-coil domain-containing protein 78
HOXC4	Down	−5.89	5.24 × 10−5	Homeobox protein Hox-C4
PRDM11	Down	−5.70	9.32 × 10−5	PR domain-containing protein 11
SLC16A6	Down	−5.67	2.21 × 10−42	Monocarboxylate transporter 7
C15H2orf72	Down	−5.31	3.22 × 10−6	Uncharacterized protein C2orf72
C7H6orf222	Down	−5.26	6.26 × 10−6	Protein BNIP5
LOC100157987	Down	−5.05	0.0019	Zinc finger and SCAN domain-containing protein 21
TNFSF13B	Down	−4.96	0.00045	TNF superfamily member 13b
CFAP73	Down	−4.93	1.15 × 10−14	Cilia- and flagella-associated protein 73
TTC36	Down	−4.90	0.00069	Transmembrane protein 25

. Gene Set Enrichment Analysis (GSEA) indicated that the ‘Protein processing in endoplasmic reticulum’ pathway was significantly activated (normalized enrichment score, NES = 1.87, false discovery rate, FDR < 0.001) under heat stress (Figure 2C). KEGG pathway analysis revealed significant enrichment (adjusted p < 0.05) in multiple pathways, including ‘Apoptosis’, the ‘MAPK signaling pathway’, ‘p53 signaling pathway’, as well as pathways related to metabolism (specifically beta-alanine metabolism), cell cycle regulation, and other signaling cascades (e.g., TNF, PI3K-Akt, and JAK-STAT) (Figure 2D). The top 20 enriched KEGG pathways are presented in

Table 2. Top 20 enriched KEGG pathways among differentially expressed genes in IPEC-J2 cells under heat stress.

KEGG Pathway/Term	p-Value	KEGG Classification Level 1	KEGG Classification Level 2
HIF-1 signaling pathway	0.00012	Environmental Information Processing	Signal transduction
Beta-Alanine metabolism	0.00013	Metabolism	Metabolism of other amino acids
Cell cycle	0.00015	Cellular Processes	Cell growth and death
Arginine and proline metabolism	0.00030	Metabolism	Amino acid metabolism
p53 signaling pathway	0.00035	Cellular Processes	Cell growth and death
Apoptosis	0.00039	Cellular Processes	Cell growth and death
TNF signaling pathway	0.00041	Environmental Information Processing	Signal transduction
MAPK signaling pathway	0.00048	Environmental Information Processing	Signal transduction
Prolactin signaling pathway	0.00059	Organismal Systems	Endocrine system
Ras signaling pathway	0.00072	Environmental Information Processing	Signal transduction
Pyrimidine metabolism	0.00073	Metabolism	Nucleotide metabolism
Amino sugar and nucleotide sugar metabolism	0.00082	Metabolism	Carbohydrate metabolism
DNA replication	0.001	Genetic Information Processing	Replication and repair
Signaling pathways regulating pluripotency of stem cells	0.001	Cellular Processes	Cellular community—eukaryotes
VEGF signaling pathway	0.0011	Environmental Information Processing	Signal transduction
Peroxisome	0.0011	Cellular Processes	Transport and catabolism
PI3K-Akt signaling pathway	0.0012	Environmental Information Processing	Signal transduction
Carbohydrate digestion and absorption	0.0014	Organismal Systems	Digestive system
JAK-STAT signaling pathway	0.0014	Environmental Information Processing	Signal transduction
Histidine metabolism	0.0017	Metabolism	Amino acid metabolism

. GO enrichment analysis highlighted terms associated with the cytosol, cilium assembly, ATP binding, and metal ion binding (Figure 2E), with the top 20 GO terms summarized in

Table 3. Top 20 enriched GO terms among differentially expressed genes in IPEC-J2 cells under heat stress.

Category	GO ID	GO Term	p-Value	Adjusted p-Value	Gene Count
cellular_component	GO:0005829	cytosol	3.74 × 10−13	1.89 × 10−9	636
	GO:0005930	axoneme	1.20 × 10−10	3.02 × 10−7	39
	GO:0005929	cilium	4.56 × 10−10	7.67 × 10−7	59
	GO:0005634	nucleus	4.16 × 10−9	4.23 × 10−6	741
	GO:0005814	centriole	4.19 × 10−9	4.23 × 10−6	47
	GO:0005654	nucleoplasm	7.82 × 10−9	6.58 × 10−6	455
	GO:0005737	cytoplasm	7.01 × 10−8	3.93 × 10−5	696
	GO:0031514	motile cilium	1.52 × 10−7	7.69 × 10−5	33
	GO:0005813	centrosome	5.02 × 10−7	0.000211335	98
	GO:0005778	peroxisomal membrane	4.80 × 10−5	0.012109976	18
biological_process	GO:0003341	cilium movement	2.35 × 10−8	1.70 × 10−5	22
	GO:0060271	cilium assembly	4.00 × 10−7	0.000183633	55
	GO:0035082	axoneme assembly	2.94 × 10−6	0.001139764	14
	GO:0090660	cerebrospinal fluid circulation	1.92 × 10−5	0.006939312	8
	GO:0007368	determination of left/right symmetry	2.66 × 10−5	0.008938355	18
	GO:1901620	regulation of smoothened signaling pathway involved in dorsal/ventral neural tube patterning	3.15 × 10−5	0.009927528	5
	GO:0060287	epithelial cilium movement involved in determination of left/right asymmetry	4.21 × 10−5	0.011172279	7
molecular_function	GO:0005524	ATP binding	4.90 × 10−8	3.09 × 10−5	254
	GO:0001784	phosphotyrosine residue binding	3.49 × 10−5	0.010060771	16
	GO:0046872	metal ion binding	3.59 × 10−5	0.010060771	349

. A heatmap of selected DEGs within the enriched PI3K-Akt signaling pathway is shown in Figure 2F. To validate the transcriptomic data, we performed RT-qPCR on five randomly selected DEGs. The expression trends obtained by RT-qPCR were consistent with the RNA-seq data, confirming the reliability of the sequencing results (Supplementary Figure S1).

3.3. Heat Stress Activates the ER Stress Response at the Protein Level

Western blot analysis confirmed the activation of the ER stress response. Compared to the control group, heat stress significantly upregulated the expression of key ER stress markers, including HSP90B1, GRP78, ATF4, CHOP, and the apoptotic marker cleaved Caspase-3, as shown by the representative blots (Figure 3A). Densitometric quantification further confirmed these observations (Figure 3B). Furthermore, the phosphorylation ratio of eIF2α (p-eIF2α/eIF2α) was significantly elevated, confirming the activation of the PERK branch of the UPR (Figure 3B).

3.4. Untargeted Metabolomics Reveals Heat Stress-Induced Metabolic Reprogramming

Untargeted metabolomic analysis identified distinct metabolic reprogramming in IPEC-J2 cells in response to heat stress. The orthogonal partial least squares discriminant analysis (OPLS-DA) score plot showed clear separation between heat-stressed (42 °C) and control (37 °C) cells, suggesting distinct metabolic states (Figure 4A). Volcano plot analysis revealed significantly increased levels of N-glycolylneuraminic acid (NeuGc), taurocholic acid, and glycocholic acid, along with decreased levels of 5-N-glycolyl-9-O-sulpho-neuraminic acid and phosphorylcholine (p < 0.05; Figure 4B). The top 10 significantly upregulated and downregulated metabolites are listed in

Table 4. Top 10 significantly upregulated and downregulated metabolites in IPEC-J2 cells under heat stress.

Metabolites	Regulation	log2 Fold Change	p-Value
Prostaglandin E2	Up	7.37	0.00000114
4-Amino-5-hydroxymethyl-2-methylpyrimidine	Up	4.65	0.01
N1-Acetylspermidine	Up	2.45	0.05
Lanthionine ketimine	Up	1.86	0.04
22-Oxodocosanoate	Up	1.86	0.02
3-Hydroxy-N6,N6,N6-trimethyl-L-lysine	Up	1.69	0.01
S-Pyruvylglutathione	Up	1.62	0.00077
1-(2-methoxy-13-methyl-tetradecanyl)-sn-glycero-3-phosphoserine	Up	1.45	0.03
1-Acetoxy-2-hydroxy-16-heptadecen-4-one	Up	1.30	0.00204
N-Acetyl-beta-alanine	Up	1.29	1.62 × 10−7
Arachidyl carnitine	Down	−6.73	0.0023
L-Cysteinylglycine disulfide	Down	−5.39	3.2 × 10−5
Asparaginyl-Methionine	Down	−5.25	0.0037
7-Hydroxy-6-methyl-8-ribityl lumazine	Down	−4.84	0.030
(9E)-9-Nitrooctadec-9-enoylcarnitine	Down	−4.68	0.0025
Oleoside	Down	−4.58	0.0074
Gly-Glu-Asp	Down	−4.56	1.33 × 10−7
Beta-Citryl-L-glutamic acid	Down	−4.47	0.025
Unidentified PC species	Down	−4.36	0.042
Glutaminylmethionine	Down	−4.30	6.36 × 10−6

. KEGG pathway enrichment analysis of the differentially abundant metabolites identified significant involvement of pathways related to amino acid metabolism (e.g., alanine, aspartate and glutamate metabolism; arginine biosynthesis), energy metabolism (oxidative phosphorylation), and protein digestion and absorption (Figure 4C). A comprehensive list of the top 20 enriched KEGG pathways is provided in

Table 5. Top 20 enriched KEGG pathways of differentially abundant metabolites in response to heat stress.

KEGG Pathway/Term	KEGG Classification Level 1	KEGG Classification Level 2	p-Value
Alanine, aspartate and glutamate metabolism	Metabolism	Amino acid metabolism	0.000126
Oxidative phosphorylation	Metabolism	Energy metabolism	0.00037
Protein digestion and absorption	Organismal Systems	Digestive system	0.00055
Arginine biosynthesis	Metabolism	Amino acid metabolism	0.00072
Glutathione metabolism	Metabolism	Metabolism of other amino acids	0.0013
Cholesterol metabolism	Organismal Systems	Nervous system	0.0025
Cysteine and methionine metabolism	Metabolism	Amino acid metabolism	0.0035
Aminoacyl-tRNA biosynthesis	Genetic Information Processing	Translation	0.0038
Lysine degradation	Metabolism	Amino acid metabolism	0.0056
Glycerophospholipid metabolism	Metabolism	Lipid metabolism	0.0056
Bile secretion	Organismal Systems	Digestive system	0.0067
Histidine metabolism	Metabolism	Amino acid metabolism	0.012
Glycine, serine and threonine metabolism	Metabolism	Amino acid metabolism	0.013
Phenylalanine metabolism	Metabolism	Amino acid metabolism	0.014
Arginine and proline metabolism	Metabolism	Amino acid metabolism	0.017
Neuroactive ligand-receptor interaction	Environmental Information Processing	Signaling molecules and interaction	0.019
Longevity regulating pathway	Organismal Systems	Aging	0.021
cAMP signaling pathway	Environmental Information Processing	Signal transduction	0.036
Sulfur metabolism	Metabolism	Energy metabolism	0.039
Phospholipase D signaling pathway	Environmental Information Processing	Signal transduction	0.04

. Among the top 50 altered metabolites, several are implicated in broader cellular stress responses or metabolic adaptations. These included increased levels of 3-Hydroxy-N⁶, N⁶, N⁶-trimethyl-L-lysine and decreased levels of phosphate, hypoxanthine, and L-cysteinylglycine disulfide (Figure 4D). Figure 4E–H further illustrate the biochemical consequences of heat stress in IPEC-J2 cells. Intracellular MDA levels, an indicator of lipid peroxidation, were elevated under heat stress (Figure 4E). Conversely, SOD activity, a key antioxidant enzyme, was significantly reduced in heat-stressed cells compared with controls (Figure 4F). ATP levels were also markedly decreased upon heat exposure (Figure 4G), suggesting an impairment of cellular energy metabolism. In parallel, lactic acid accumulation was notably higher in the heat-stress group (Figure 4H), indicating a shift toward glycolytic metabolism. Together, these data demonstrate that heat stress induces oxidative stress, compromises antioxidant capacity, disrupts energy homeostasis, and leads to lactate accumulation in IPEC-J2 cells.

3.5. Integrated Transcriptomic and Metabolomic Analysis Reveals Coordinated Alterations in Amino Acid and Glutathione Metabolism

To identify coordinated changes under heat stress, we integrated transcriptomic and metabolomic data for two pathways central to redox balance: arginine and proline metabolism, and glutathione metabolism (

Table 6. Integrated analysis of metabolite and gene expression changes in key pathways under heat stress.

	Metabolite	KEGG ID	Metabolite Change (log2FoldChange)	Metabolite p-Value	Related Gene	Gene Change (log2 Fold Change)	Gene p-Value	Biological Interpretation
arginine and proline metabolism	L-Glutamic acid	C00025	−0.80	0.00018	ALDH4A1, PYCR3	ALDH4A1 (−1.22) PYCR3 (−1.35)	ALDH4A1 (5.69 × 10−29) PYCR3 (1.67 × 10−25)	ALDH4A1: enzyme that converts proline to glutamate, downregulation reduces glutamate production; PYCR3: proline synthesis enzyme (consumes glutamate-derived precursors), downregulation reduces glutamate consumption
	L-Proline	C00148	−0.52	0.0047	PYCR3, ALDH4A1	PYCR3 (−1.35) ALDH4A1 (−1.22)	PYCR3 (1.67 × 10−25) ALDH4A1 (5.69 × 10−29)	PYCR3: proline synthesis enzyme, downregulation reduces synthesis; ALDH4A1: proline degradation enzyme, downregulation reduces degradation
	Spermidine	C00315	−1.64	0.0044	SAT2	SAT2 (−1.22)	SAT2 (4.25 × 10−23)	SAT2: downregulation suggests reduced consumption, but the significant reduction in spermidine levels is primarily driven by the robust upregulation of SAT1: (glutathione metabolism)
glutathione metabolism	L-Glutamic acid	C00025	−0.80	0.00019	ALDH4A1	ALDH4A1 (−1.22)	ALDH4A1 (5.69 × 10−29)	ALDH4A1: enzyme that converts proline to glutamate, downregulation reduces glutamate production;
	Oxidized glutathione	C00127	−1.23	0.014	-	-	-	No significantly differentially expressed genes were identified in this study
	Spermidine	C00315	−1.64	0.0044	SAT1, SAT2	SAT1 (2.21) SAT2 (−1.22)	SAT1 (4.95 × 10−69) SAT2 (4.25 × 10−23)	SAT1: spermidine acetyltransferase, upregulation promotes consumption; SAT2: spermidine acetyltransferase, downregulation reduces consumption

). In arginine and proline metabolism, both L-glutamic acid and L-proline decreased. This coincided with coordinated downregulation of their metabolic enzymes: ALDH4A1 (proline→glutamate) and PYCR3 (proline synthesis). The net proline decline, despite reduced degradation, suggests pathway flux is redirected toward other stress responses. Spermidine also fell sharply; although the expression of SAT2, which consumes spermidine, was downregulated, the robust upregulation of SAT1, another spermidine acetyltransferase, likely drives the net depletion of spermidine. In glutathione metabolism, L-glutamic acid depletion and downregulation of ALDH4A1 (a glutamate source) and GSS (glutathione synthetase) point to impaired glutathione synthesis. This aligns with reduced oxidized glutathione (GSSG), though GSSG-related genes were unchanged, suggesting post-transcriptional regulation. Crucially, strong SAT1 upregulation and spermidine depletion further indicate disrupted polyamine and redox homeostasis.

Beyond metabolic pathways, transcriptomic data specifically highlighted potential alterations at the ER-mitochondrial interface. We identified a cluster of differentially expressed genes encoding proteins known to localize to mitochondria-associated membranes (MAMs) or regulate ER-mitochondria signaling (

Table 7. Differentially expressed genes encoding proteins associated with MAMs and ER-mitochondria crosstalk in heat-stressed IPEC-J2 cells.

Gene Symbol	log2 Fold Change	p-Value	Regulation	Molecular Function & Localization
BCL2L10	4.91	0.0073	Up	Anti-apoptotic protein; localizes to mitochondria-associated ER membrane (GO:0044233).
PNPLA8	2.14	1.56 × 10−89	Up	Calcium-independent phospholipase; localizes to both ER and mitochondrial membranes.
RAB38	3.94	0.024	Up	GTPase activity; localizes to mitochondria-associated ER membrane (GO:0044233).
SLC8A2	3.58	0.00041	Up	Sodium/calcium exchanger; involved in calcium ion transmembrane transport.
ERO1A	1.83	8.59 × 10−52	Up	Oxidoreductase enriched at MAMs; regulates oxidative protein folding.

). Notably, genes such as BCL2L10 (log2Fold Change = 4.91) and RAB38 (log2Fold Change = 3.94), which are associated with MAM function, were significantly upregulated. Of particular interest was the upregulation of ERO1A (Endoplasmic Reticulum Oxidoreductase 1 Alpha; log2Fold Change = 1.83), an oxidoreductase enriched at MAMs that regulates ER-mitochondrial calcium flux. The coordinated induction of these genes, along with PNPLA8 and the calcium transporter SLC8A2, indicates a potential disruption in the interface-associated proteome. While direct physical assessment of MAM dynamics was not performed in this study, these data provide a plausible molecular link, suggesting that heat-induced ER stress may propagate signals to mitochondria through perturbations in the interface-associated proteome, setting the stage for the functional and structural mitochondrial deficits validated in subsequent experiments.

3.6. Heat Stress Impairs Mitochondrial Bioenergetics via an ER Stress-Dependent Mechanism

Seahorse XF analysis showed that heat stress significantly compromised mitochondrial function in IPEC-J2 cells (Figure 5A). Maximal respiration was significantly reduced in the Heat Stress group compared to the Control and Heat Stress+4-PBA groups (Figure 5B). This impairment was partially but significantly rescued by co-treatment with the ER stress inhibitor 4-PBA (Heat Stress+4-PBA), while pretreatment with the ER stress inducer tunicamycin recapitulated the suppressive effect of heat stress on mitochondrial function. Similarly, ATP production (Figure 5C) was markedly decreased under heat stress, and 4-PBA treatment significantly restored ATP levels. Treatment with tunicamycin alone also resulted in similarly low ATP levels, while the vehicle control (DMSO) did not alleviate the heat stress-induced deficit. Analysis of spare respiratory capacity (Figure 5D) revealed a pronounced reduction in heat-stressed cells, which was again attenuated by 4-PBA. Notably, treatment with tunicamycin alone also significantly lowered spare respiratory capacity to a level comparable to that of the heat stress group, further supporting the role of ER stress in this process. Finally, basal respiration (Figure 5E) was significantly suppressed by heat stress, and this suppression was attenuated by 4-PBA but not by DMSO. Treatment with tunicamycin alone also significantly reduced basal respiration. Taken together, these data demonstrate that heat stress impairs mitochondrial respiratory function and energy production, and that these deficits can be mitigated by inhibiting ER stress, indicating that heat stress disrupts mitochondrial bioenergetics via an ER stress-dependent mechanism.

3.7. Ultrastructural and Pharmacological Validation of ER Stress-Mediated Mitochondrial Damage

TEM was used to assess mitochondrial ultrastructure (Figure 6A–C). Control cells exhibited well-preserved cellular ultrastructure, with mitochondria displaying intact cristae and normal morphology (Figure 6A). In contrast, heat stress induced severe mitochondrial damage, characterized by marked swelling, membrane rupture, and cristae fragmentation and disorganization (Figure 6B). Co-administration of 4-PBA with heat stress significantly attenuated this mitochondrial damage, resulting in mitochondria with only moderate swelling and partially preserved, albeit disorganized, cristae (Figure 6C). To assess the molecular correlates of this protection, we performed Western blot analysis on protein lysates collected from parallel experimental batches treated under identical conditions as those used for the mitochondrial functional assays shown in Figure 5. The results confirmed that the heat stress-induced upregulation of key ER stress markers (GRP78, HSP90B1, CHOP) and the increased phosphorylation ratio of eIF2α (p-eIF2α/eIF2α) were effectively mitigated by co-treatment with 4-PBA (Figure 6D). These findings demonstrate that the protective effects of 4-PBA on mitochondrial function are associated with a significant reduction in ER stress under our experimental conditions.

Collectively, these findings demonstrate that acute heat stress instigates ER proteotoxic stress and concurrent metabolic reprogramming, which drive mitochondrial bioenergetic dysfunction and oxidative damage, ultimately promoting apoptotic cell death in intestinal epithelial cells (Figure 7).

4. Discussion

4.1. The ER Stress-Mitochondria Axis in Heat-Stressed Enterocytes

This study demonstrates that acute heat stress triggers a hierarchical stress response in intestinal epithelial cells wherein ER stress acts as a critical intermediary, driving subsequent mitochondrial bioenergetic failure and ultrastructural damage. By employing an integrated multi-omics approach, we demonstrate that heat stress triggers extensive transcriptional and metabolic reprogramming in enterocytes, which converges on the robust activation of the ER stress response and culminates in significant mitochondrial bioenergetic dysfunction and ultrastructural damage. Crucially, pharmacological inhibition of ER stress significantly ameliorated mitochondrial dysfunction and attenuated morphological injury [29,30,31,32]. These findings establish ER stress as a central mediator in heat-stressed enterocytes, linking the initial transcriptional and metabolic disturbances to the downstream dysfunction of mitochondria [7,33,34,35].

Consistent with previous reports on heat stress in other cell types [36,37], our transcriptomic profiling revealed a broad reprogramming of the IPEC-J2 cell transcriptome under heat stress [36,37,38,39]. The pivotal role of the ER stress response in heat-stressed enterocytes is underscored by the robust activation of the unfolded protein response (UPR), as evidenced by both transcriptomic and protein-level analyses. This activation likely represents a critical attempt to restore proteostasis but, under sustained stress, may transition toward pro-apoptotic signaling, as suggested by the concomitant enrichment of apoptosis-related pathways. This aligns with previous reports demonstrating UPR activation under thermal stress in other cell types [16,17,40], but our multi-omics approach functionally links this activation to downstream metabolic and organellar dysfunctions in enterocytes [41,42,43]. The concurrent enrichment of apoptosis, MAPK, and p53 signaling pathways, together with the upregulation of CHOP and cleaved Caspase-3, suggests that the UPR shifted from an adaptive to a terminal, pro-apoptotic state under our experimental conditions [44,45,46].

Untargeted metabolomics provided a complementary perspective, revealing distinct heat-induced metabolic remodeling. The significant alterations in bile acid profiles and amino acid metabolism pathways reflect a profound disruption of core metabolic homeostasis, potentially driven by the metabolic demands and signaling cascades associated with the activated UPR [47,48,49]. These metabolic alterations likely reflect both an adaptive rewiring to meet altered energy demands and downstream consequences of sustained ER stress on anabolic and catabolic pathways.

At the functional level, our data establish a direct causal link between ER stress and mitochondrial impairment. Seahorse XF analysis demonstrated that heat stress severely compromised mitochondrial bioenergetics, significantly reducing maximal and basal respiration, ATP production, and spare respiratory capacity [50,51,52]. Importantly, our focus on the acute phase of heat stress (12 h exposure, ~70% viability) ensures that the observed mitochondrial bioenergetic defects represent primary pathological events rather than secondary consequences of advanced cell death. A key finding is the significant mitigation of these bioenergetic deficits by co-treatment with 4-PBA, a chemical chaperone that alleviates ER stress [53,54,55]. Conversely, induction of ER stress with tunicamycin mimicked the deleterious effects of heat stress. Together, these pharmacological interventions indicate that ER stress is a critical mediator of the observed mitochondrial dysfunction. Transmission electron microscopy solidified this conclusion morphologically, showing that heat stress induced characteristic mitochondrial damage—swelling, cristae disorganization, and membrane rupture—and that 4-PBA co-treatment markedly attenuated these ultrastructural abnormalities [56,57].

Our transcriptomic data suggest a potential molecular basis for this observed ER-mitochondrial crosstalk. We detected the robust upregulation of ERO1A, a key oxidoreductase enriched at MAMs. Overexpression of ERO1A has been previously shown to potentiate Ca²⁺ release from the ER into mitochondria, triggering mitochondrial ROS generation and apoptosis [58,59,60]. This is consistent with our observation of mitochondrial swelling, elevated ROS, and bioenergetic collapse. Concurrently, the upregulation of the MAM-resident protein BCL2L10 further supports the implication of this contact site during heat stress. Although direct measurement of MAM structural dynamics or calcium flux was beyond the scope of this study, these transcriptional findings, combined with the functional rescue by 4-PBA, strongly propose a model where heat stress-induced ER stress propagates damage to mitochondria, potentially via an ERO1A-dependent perturbation of the organelle interface.

Based on our findings, we propose a mechanistic model whereby heat stress disrupts ER proteostasis, leading to UPR activation. The sustained ER stress likely perturbs inter-organellar communication. Based on established paradigms of ER-mitochondria crosstalk, this may occur through mechanisms such as altered calcium flux or the propagation of ROS signals [21,22,23], although these specific pathways were not directly tested in the current study. Nonetheless, our interventional data strongly support a causal role for ER stress. The partial, albeit significant, restoration of mitochondrial function by 4-PBA suggests that ER stress is a key, but not the exclusive, mediator. Other heat-induced insults, such as direct protein denaturation within mitochondria or oxidative stress independent of ER signaling, may also contribute concurrently to the overall mitochondrial dysfunction.

While our findings establish a strong causal relationship between ER stress and mitochondrial dysfunction, we acknowledge a limitation inherent in our experimental approach. The primary evidence for this causal link relies on pharmacological modulation of ER stress using 4-PBA and tunicamycin. Although we have demonstrated that 4-PBA effectively reduces UPR markers under the identical conditions used for our mitochondrial functional readouts (Figure 6D), we cannot completely rule out potential off-target effects of these compounds. To further strengthen and refine this mechanistic model, future investigations should employ orthogonal approaches. Specifically, genetic silencing of key UPR components, such as PERK, ATF4, or CHOP using siRNA or CRISPR/Cas9 technology, would provide more precise evidence for the role of specific branches of the UPR in mediating mitochondrial damage. Additionally, the use of more selective pharmacological inhibitors, such as PERK inhibitors (e.g., GSK2606414), would complement the current findings. Such studies would definitively establish the precise molecular transducers of the ER stress–mitochondrial signaling axis and could identify more specific therapeutic targets for mitigating heat stress-induced intestinal injury.

4.2. Translational Perspectives, Broader Implications, and Limitations

From a translational perspective, our findings suggest the potential therapeutic value of targeting ER stress to enhance enterocyte resilience. Our metabolomic data point to specific perturbed pathways, such as bile acid and amino acid metabolism, which merit future investigation to determine if their modulation can synergize with ER stress-targeting approaches to enhance cytoprotection. These could be used alongside pharmacological agents that bolster ER proteostasis [61,62].

Beyond the cellular and translational implications, the broader applicability of our findings to diverse mammalian species warrants consideration. While the core mechanism of ER stress-mediated mitochondrial dysfunction is likely conserved across homeotherms, the physiological thresholds and adaptive capacities may vary significantly. For instance, mammals native to equatorial regions have evolved under persistent thermal pressure and may possess genetic or physiological adaptations—such as more efficient heat shock protein expression or distinct metabolic baselines—that confer greater enterocyte resilience compared to temperate-climate species [63,64]. Conversely, in temperate regions, livestock and wildlife are increasingly exposed to extreme heat surges due to climate change. Our data suggest that such acute thermal challenges could overwhelm their less-adapted cellular proteostasis mechanisms, potentially leading to the intestinal epithelial damage and barrier dysfunction observed in our model. Therefore, while the fundamental pathway is likely universal, the susceptibility and the “threshold” for heat-induced ER stress may be modulated by evolutionary history and acclimatization state [65,66,67].

Our findings also offer a mechanistic perspective on the health challenges observed in human populations migrating from temperate to tropical or subtropical climates. The acute heat stress model employed here may mirror the initial physiological insult experienced by unacclimatized individuals during extreme heat events. We posit that the surge in heat-related gastrointestinal and systemic inflammatory disorders in such migrating populations could be partially attributed to the ER stress–mitochondrial dysfunction axis identified in our study [68,69,70]. The failure of intestinal epithelial cells to maintain barrier integrity under sudden thermal load would facilitate endotoxin translocation, potentially exacerbating systemic inflammation and heat stroke pathology. This raises the intriguing possibility that interventions aimed at bolstering ER proteostasis, perhaps through nutritional supplementation or gradual acclimatization protocols, could mitigate the incidence of these disorders during the critical early phase of heat exposure.

Several limitations of this study should be acknowledged. First, we used an acute, constant heat stress model in an immortalized cell line. In agricultural settings, livestock often experience chronic or cyclical heat stress, which may elicit different adaptive or pathological responses [71,72,73]. Our findings thus require validation in in vivo models, such as piglet models of environmental heat stress or relevant rodent models, that more closely mimic these real-world conditions. Second, although we established a strong pharmacological link between ER stress and mitochondrial dysfunction, the precise molecular transducers (e.g., the relative contributions of PERK, IRE1α, or ATF6 branches, or specific calcium channels) warrant further investigation using genetic tools [22,74]. Finally, while IPEC-J2 cells are a useful model, it is important to validate the physiological relevance of this ER stress-mitochondria axis in primary porcine enterocytes and in vivo models [75,76,77]. Future in vivo studies should assess whether ameliorating ER stress can preserve intestinal barrier integrity, mitigate systemic inflammation, and improve growth performance during heat challenge.

While our study utilized the standard cell culture temperature of 37 °C as a control, which is common practice for in vitro studies, we acknowledge that this is lower than the porcine physiological body temperature of approximately 38–38.5 °C. This difference may subtly influence the baseline cellular state and could affect the perceived magnitude of the heat stress response at 42 °C. Future investigations comparing IPEC-J2 cell physiology and stress responses at both 37 °C and 38.5 °C would be valuable to determine the most physiologically relevant control condition and to more accurately quantify the cellular response to hyperthermia.

This multi-omics investigation elucidates that acute heat stress induces profound cellular remodeling in intestinal epithelial cells, with ER stress activation serving as a central hub that critically mediates subsequent mitochondrial dysfunction and damage. Thus, this study provides a mechanistic framework linking heat-induced ER stress to mitochondrial failure in enterocytes, highlighting the modulation of ER proteostasis as a potential strategy to enhance enterocyte resilience under heat stress.

5. Conclusions

This integrated multi-omics study demonstrates that acute heat stress triggers a coordinated cellular response in intestinal epithelial cells, characterized by transcriptional and metabolic reprogramming alongside robust ER stress activation. Our data support a model in which ER stress activation serves as a central mechanistic node, critically driving subsequent mitochondrial bioenergetic and ultrastructural damage. The significant attenuation of mitochondrial dysfunction upon ER stress inhibition underscores its central mediating role in heat-stressed enterocytes. These findings provide a mechanistic framework for heat-induced intestinal injury. They highlight the targeting of ER proteostasis as a promising strategy for developing interventions to enhance enterocyte resilience and overall thermotolerance in livestock.