Heat Stress Triggers Bone Performance Degeneration via Impairing Intestinal Barrier Function and Altering Gut Microbiota in Chickens

Heat Stress Triggers Bone Performance Degeneration via Impairing Intestinal Barrier Function and Altering Gut Microbiota in Chickens | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Heat Stress Triggers Bone Performance Degeneration via Impairing Intestinal Barrier Function and Altering Gut Microbiota in Chickens Hang Gao, Jingsha Gu, Yi Wang, Yu Zou, Zhouyuan Wang, Rendong Fang, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9395311/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Heat stress (HS) is a pervasive environmental hazard in intensive poultry production that severely impairs skeletal health and causes substantial economic losses. While emerging evidence links gut microbiota dysbiosis to bone metabolism, its causal role in mediating HS-induced bone loss remains poorly defined. Here, we established a chicken model of HS and employed fecal microbiota transplantation (FMT) to investigate the mechanistic link between gut microbiota and skeletal deterioration. Our results demonstrated that HS reduced growth performance, disrupted gut microbial community structure, and impaired bone microarchitecture and biomechanical strength. Critically, FMT from HS-exposed donors recapitulated the key features of HS-induced bone loss in recipient chickens, characterized by impaired trabecular bone microarchitecture, reduced biomechanical strength, and enhanced bone resorption-related gene expression. Mechanistically, the HS-microbiota induces functional dysbiosis, characterized by a relative increase in the abundance of the genus Turicibacter , while compromising intestinal barrier integrity, triggering an inflammatory response, and inhibiting intestinal mineral absorption. Collectively, these factors contribute to reduced bone performance. These findings establish the gut microbiota as a key mediator of HS-induced bone loss, providing a novel mechanistic framework for understanding host–microbiota–environment interactions in the context of environmental hazards, which has broader implications for animal health and environmental toxicology. Heat stress Gut microbiota Bone health Poultry Animal welfare Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. Introduction In recent years, the cumulative emissions of greenhouse gases have accelerated global warming[ 1 ]. Future projections indicate that warming will persist, with heat extremes becoming not only more common but also longer-lasting and more severe. Record-breaking heatwaves continue to shatter historical extremes, posing severe challenges to human and animal health. Increasing evidence suggests that prolonged exposure to high temperatures can lead to heat stress (HS) and heighten the risk of morbidity and mortality[ 2 ]. Commercial chickens, serving as a vital protein source for humans, are highly susceptible to HS due to their high metabolic rate, substantial heat production, and lack of sweat glands coupled with feather coverage[ 3 ]. Chickens are homeothermic animals whose thermoneutral zone spans only 18–30°C. Once ambient temperature climbs above this narrow ceiling, birds enter heat-stress conditions that rapidly trigger physiological and behavioral disruptions, resulting in feed intake and performance fall[ 4 ], and mortality rises[ 5 ]. At present, due to its widespread occurrence and prolonged duration, HS has become one of the most typical harmful environmental stressors in the scenarios of global warming and intensive poultry farming. Skeletal integrity underpins growth rate, standing ability, and productive output in modern chickens, while tibial dyschondroplasia[ 6 ], osteoporosis[ 7 ], and fractures[ 8 ] inflict multibillion dollar losses through mortality, culling, and carcass downgrading. These losses underscore that bone formation is not a simple by-product of growth; rather, it is a complex, finely tuned process governed by an intricate interplay of genetics, nutrition, and environmental factors. Reports indicate that HS amplifies skeletal deterioration, simultaneously diminishing tibial break strength[ 9 ], ash content, and bone volume per tissue volume in chickens[ 10 ]. Decreased bone performance in chickens represents one of the major HS-induced physiological impairments, which not only severely impairs flock locomotor ability, elevates fracture risk and compromises animal welfare[ 11 ], but also results in reduced slaughter grades of commercial broilers[ 12 ] and shortened laying cycles of laying hens[ 13 ]. However, the mechanisms by which HS causes leg problems and skeletal diseases remain incompletely understood to date. The vertebrate skeleton is no longer viewed as an isolated organ system. The gut microbiota is increasingly recognized as a pivotal regulator of host skeletal development through the gut-bone axis. Germ-free or antibiotic-treated mice exhibit low systemic IGF-1 and impaired bone formation[ 14 ], whereas supplementation with probiotics such as Lactobacillus Rhamnosus GG restores trabecular bone mass by expanding regulatory T cells and suppressing osteoclastogenic cytokines[ 15 ]. Similarly, fecal microbiota transplantation (FMT) alleviates lipopolysaccharide-induced osteoporosis by modulating the gut microbiota and long non-coding RNA[ 16 ]. These findings indicate that the gut microbiota may act as a pivotal regulatory factor in bone metabolic signaling transduction within mammals. In the chickens, our previous research has demonstrated that cecal microbiota transplantation from adult laying hens significantly enhances calcium uptake and retention efficiency in chicks by transcriptionally upregulating key calcium ion transporters[ 17 ]. As the primary site for absorbing bone-associated critical nutrients (e.g., calcium and vitamins), the intestinal tract maintains a microbiota homeostasis that modulates the integrity and physiological functions of the intestinal mucosa, thereby potentially influencing the absorption efficiency of those nutrients[ 7 ]. In addition, gut microbiota dysbiosis induces skeletal damage associated with tibial dyschondroplasia in commercial broilers by disrupting glucose homeostasis[ 18 ]. However, systematic investigations into the association between gut microbiota and HS-induced bone loss in chickens remain relatively scarce at present. As a critical intermediary in damage induced by adverse environmental stressors, the gut microbiota may play a key mediating role in the process of HS-induced bone loss in chickens. Therefore, the present study aimed to investigate the effects of HS on gut microbiota structure and bone metabolism in chickens. Subsequently, FMT were performed to verify the causal relationship that HS induces bone loss in chickens by disrupting gut microbiota structure, as well as to elucidate the underlying crucial mechanisms. This study will provide novel insights into the mechanisms underlying physiological impairment induced by adverse environmental stressors, and facilitate the development of targeted prevention and control strategies. Meanwhile, it will lay a solid theoretical foundation for ensuring production efficiency and supporting the green and sustainable development of the poultry industry. 2. Materials and methods 2.1. Animal and study design 2.1.1. HS treatment Forty 1-day-old male Cobb 500 broiler chicks with uniform body weight were randomly allocated to two treatment groups, each consisting of four replicates with five birds per replicate. The brooding temperature was maintained at 34°C on day 1 and then gradually reduced by 0.5°C daily until a constant temperature of 22°C was achieved. On day 21, the birds were subjected to two environmental regimens: a normal control group (NC) housed continuously at 22 ± 1°C with a relative humidity (RH) of 55 ± 5%, and a heat stress group (HS) exposed to 35 ± 1°C and 55 ± 5% RH for 8 h daily (10:00–18:00) over 14 consecutive days[ 10 ]. 2.1.2. FMT Based on previous studies[ 17 ], partial modifications were made in the present experiment. It is worth noting that, due to the presence of white urate deposits in chicken feces, fresh feces were not directly collected from donor birds; instead, cecal contents were utilized. The detailed protocol is briefly described as follows: briefly, cecal feces from donor chickens were mixed with phosphate-buffered saline (PBS, pH = 7.4) at a ratio of 1:6 (w/v) in a sterile centrifuge tube. After vigorous vortexing, the mixture was centrifuged at 800 × g for 10 min. The resulting supernatant was harvested and filtered through a 200-µm sterile sieve (Retsch, Haan, Germany) to eliminate large particulate matter and ensure homogeneous inoculum. A total of 60 1-day-old male Cobb 500 broiler chicks with uniform body weight were randomly assigned to three treatment groups, each comprising four replicates of five birds: (1) Recipient chicks received PBS, FMT-PBS group, (2) fecal microbiota from normal control donors, FMT-NC, and (3) fecal microbiota from heat-stressed donors, FMT-HS group. Oral gavage with 1 mL of the prepared inoculum was administered once daily from day 1 to day 10, with booster doses given on days 17, 24, and 31[ 17 ]. All birds were provided with ad libitum access to feed and water throughout the entire experimental period. The lighting schedule and feeding management strictly followed the guidelines specified in the Cobb Broiler Management Guide. Body weight (BW) and cage-level feed intake were recorded throughout the trial. Body weight gain (BWG) and feed conversion ratio (FCR) were calculated on a per-cage basis. On day 35, two birds from each of the four replicate cages per group were randomly selected, weighed, and anesthetized with sodium pentobarbital at a dosage of 30 mg/kg body weight. Blood, tibia and ileum tissues, and cecal contents were aseptically collected for subsequent analysis. 2.2. Blood smear and serum biochemical analysis Blood samples were collected from the brachial vein of each bird into 1.5 mL EDTA-coated tubes, which were immediately inverted gently to prevent coagulation and then stored at 4°C for no more than 2 h prior to analysis. For blood smear examination, duplicate smears were prepared, stained with Wright-Giemsa stain, and examined under a light microscope at 100× magnification (oil immersion). A total of 100 leukocytes were counted and classified per smear, and the percentages of lymphocytes, heterophils, eosinophils, basophils, and monocytes were calculated accordingly. Concentrations of serum calcium (Ca), phosphorus (P), and alkaline phosphatase (ALP) were measured using an automatic biochemical analyzer (Mindray BS-240 Vet, Shenzhen, China). 2.3. ELISA analysis Serum lipopolysaccharide (LPS) (Cat# EHJ-50229, Xiamen Huijia Biotechnology Co., Ltd.), diamine oxidase (DAO) (Cat# EHJ-98358C, Xiamen Huijia Biotechnology Co., Ltd.) and D-lactate (DLA) (Cat# EHJ-96759C, Xiamen Huijia Biotechnology Co., Ltd.) were detected by ELISA kit per instructions with minor modifications. In short, 10 µL of serum and standards were added to black 96-well plates. Working reagent was added to sample wells, and blank reagent to blank wells. Reaction was terminated with stop solution, and absorbance was measured at a specific wavelength. LPS, DAO, and DLA concentrations were calculated via standard curve. 2.4. Micro-CT analysis Soft tissues (skin and musculature) were meticulously dissected from the right tibiae, after which the cleaned bones were blotted dry with sterile gauze to remove surface lipids. Subsequently, the right tibiae were scanned using a NEMO NMC-200 micro-CT system (PingSheng Medical Technology Co., Ltd., Suzhou, China). Data acquisition was conducted with Cruiser software (Version 2.3, PingSheng Medical Technology), while image reconstruction was performed via Recon software (Version 3.1) using the Feldkamp–Davis–Kress (FDK) algorithm. Three-dimensional (3D) visualization and volume-of-interest (VOI) segmentation were accomplished with Avatar software (Version 1.7). The scanning parameters were set as follows: X-ray tube voltage = 80 kV, tube current = 0.04 mA, pixel size = 70 µm, and rotation step = 0.5°. The following bone microstructural parameters were quantified: bone mineral density (BMD), bone surface area to tissue volume ratio (BS/TV), trabecular separation (Tb.Sp), trabecular number (Tb.N), trabecular mean thickness (Tb.Th) and cortical bone thickness (Ct.Th). 2.5. Bone mechanical properties analysis Following micro-CT scanning, all right tibiae were subjected to bone biomechanical analysis. Biomechanical testing was performed via the three-point bending method using a universal material testing machine (LR10K Plus, Lloyd Instruments Ltd., Hampshire, UK) equipped with a 5 N load cell. Each tibia was positioned with its anterior aspect facing upward, and loaded at the midpoint between the two bottom supports, which corresponded to the longitudinal midpoint of the bone. Loading was applied at a constant crosshead speed of 15 mm/min until bone fracture occurred. Force-displacement data were recorded and subsequently used to calculate whole-bone stiffness, fracture load, and Young’s modulus using NEXYGEN Plus software (Lloyd Instruments Ltd.). 2.6. Bone ash and mineral composition analysis The tibiae were ground into fine powder and passed through a 40-mesh sieve. The ground bone powder was dried at 110°C to a constant weight. Aliquots of 0.1 g were first carbonized at 200°C, followed by ashing at 550°C for 3 h. The ash mass was recorded to calculate the bone ash content. Each ash sample was then digested in hot concentrated nitric acid (HNO₃), diluted to a final volume of 50 mL with deionized water, and the concentrations of Ca, P, and magnesium (Mg) were quantified using inductively coupled plasma optical emission spectrometry (ICP-OES; iCAP 7000, Thermo Fisher Scientific, Waltham, MA, USA). 2.7. HE staining For each harvested ileal specimen, a 1 cm segment was subjected to gradient ethanol dehydration, followed by xylene clearing and immersion in liquid paraffin. The processed samples were embedded via an embedding apparatus and sectioned into 3 µm-thick slices using a sliding microtome (Leica RM2235, Leica Microsystems, Wetzlar, Germany), prior to hematoxylin-eosin (HE) staining. Histological sections were observed under a light microscope with a 4× objective lens; randomly selected non-overlapping fields (3 fields on average per section) were examined, and a minimum of 15 villus-crypt complexes were evaluated per section. Image-Pro Plus 6.0 software was employed to quantify villus height (VH) and crypt depth (CD) in each small intestinal segment, and the villus height-to-crypt depth ratio (VH/CD) was subsequently computed. 2.8. Immunohistochemistry Paraffin-embedded ileum sections were dewaxed and hydrated by immersion in xylene and gradient ethanol solutions. After antigen retrieval, the sections were then incubated with mouse polyclonal anti-CaBP-D28K antibody (Cat# GB113362) at 4°C overnight. On the following day, the sections were washed three times with PBS, and subsequent staining steps were conducted as per the kit instructions. DAB chromogenic substrate (DAB-031, Maxin Biotechnologies) was used for color development, followed by hematoxylin staining for nuclear counterstaining and mounting with neutral resin. All sections were semi-quantitatively analyzed using Image-Pro Plus software, with the positive staining area determined by the ratio of integrated optical density to the region of interest in three images per sample. 2.9. Real-time quantitative PCR analysis (RT-qPCR) TRIzol reagent (Tsingke Biotech Co., Ltd., #TSP401, Nanjing, China) served to isolate total RNA from the left tibia and ileum tissue. Reverse transcription of the RNA into cDNA was accomplished with TransScript Uni All-in-One First-Strand cDNA Synthesis SuperMix from TransGen Biotech Co., Ltd. (#AU341–02-V2, Nanjing). Subsequent qPCR reactions, performed on a QuantStudio™ 6 Flex Real-Time PCR system (Applied Biosystems, Wilmington, MA, USA), employed diluted cDNA and PerfectStart Green qPCR SuperMix (TransGen Biotech Co., Ltd., #AQ601–02, Nanjing). Primers, whose sequences appear in Table S1 , were designed in Oligo 7.0 and synthesized by Sangon Biotech (Shanghai, China). Relative mRNA levels were quantified via the 2 −ΔΔCT method, with Peptidyl-prolyl cis-trans isomerase A (PPIA) acting as the endogenous control. 2.10. 16S rRNA sequencing Microbial DNA was isolated from cecal content samples using the FastDNA® Spin Kit for Soil (MP Biomedicals, Santa Ana, CA, USA) in strict accordance with the manufacturer’s recommended protocol. The V3-V4 hypervariable region of the 16S rRNA gene was amplified using the specific primers 338F (5’-ACTCCTACGGGAGGCAGCAG-3’) and 806R (5’-GGACTACHVGGGTWTCTAAT-3’). The PCR reaction system was prepared with a total volume of 20 µL, consisting of 4 µL of 5× FastPfu Buffer, 2 µL of 2.5 mM dNTPs, 0.8 µl of each 5 µM primer (338F and 806R), 0.4 µl of TransStart FastPfu DNA Polymerase (TransGen Biotech, Beijing, China), 0.2 µL of BSA, and 10 ng of genomic DNA template. The size of the PCR amplicons was verified by 2% agarose gel electrophoresis. Amplicons were then purified using the AxyPrep DNA Gel Extraction Kit (Axygen, Union City, CA, USA) and quantified with a QuantiFluor ST Fluorometer (Promega, Madison, WI, USA) following the manufacturers’ instructions. Purified amplicons were pooled in equimolar amounts and subjected to paired-end sequencing (2 × 300 bp) on the Illumina MiSeq platform (Illumina, San Diego, CA, USA) at Shanghai Majorbio Bio-pharm Technology Co., Ltd. (Shanghai, China), in compliance with the manufacturer’s standard procedures. The raw 16S rRNA gene sequence reads were deposited in the NCBI Sequence Read Archive (SRA) under the accession number PRJNA1106229 and PRJNA1421088. 2.11. Statistical analysis Except for the microbiome data, data were analyzed and plotted using SPSS (Version 21.0, IBM, USA) and GraphPad Prism (Version 8.0.2, San Diego, California, USA) statistical analysis software, respectively. The mean ± SD of the data was displayed. For multigroup comparisons: one-way ANOVA was applied when the assumption of homogeneity of variance was met, followed by Tukey’s post-hoc test for pairwise comparisons. The Student’s t-test was used to analyze the differences between two groups. In all cases, P < 0.05 was considered statistically significant. Regarding microbiota profiling, the raw sequencing data is first subjected to quality control, filtering, and assembly processing to obtain high-quality clean sequences. Subsequently, the DADA2 algorithm was used for denoising to generate high-resolution amplicon sequence variation (ASV). Alpha and beta diversity indices were analyzed systematically. Taxonomic annotation was performed by aligning sequences against the SILVA 138 SSU rRNA database and NCBI 16S RefSeq database (with a confidence threshold set at ≥ 0.7), so as to construct species abundance profiles. The Mann-Whitney U test was employed to compare the two sample groups. Linear discriminant analysis effect size (LEfSe) was applied to identify microbial taxa with significant differences in abundance. Additionally, Spearman’s rank correlation analysis was used to evaluate the association between bone parameter and the differential microbiota ( P < 0.05). 3. Results 3.1. Heat stress impairs growth performance and bone characteristics in chickens To evaluate the effects of HS on growth performance and bone parameters in chickens, a 14-day HS model was established (Fig. 1 A). Feed intake and body weight were recorded during the experimental period, and blood and bone samples were collected at 35 days of age for subsequent analyses. The heterophil-to-lymphocyte ratio (H/L) is a reliable indicator for evaluating HS in poultry. In the current experiment, it was found that the H/L ratio was significantly increased in heat-stressed chickens (Fig. 1 B), indicating the successful establishment of the HS model. Subsequently, Average daily feed intake (ADFI), average daily gain (ADG), and FCR were calculated. The results demonstrated that HS significantly decreased ADFI and ADG, but had no significant effect on FCR (Fig. 1 C, D and E). Serum bone metabolism markers serve as direct indicators of bone turnover. However, due to the lack of poultry-specific commercial kits, only serum Ca, P, and ALP levels were determined in the present study. The results showed that HS did not alter serum Ca and P concentrations, but significantly increased ALP activity (Fig. 1 F, G, and H). Furthermore, the mRNA expression levels of genes associated with osteogenesis and osteoclastogenesis were analyzed by RT‑qPCR. The results revealed that HS only significantly downregulated the relative mRNA expression of RUNX2, with no significant effects on other bone turnover‑related genes (Fig. 1 I and 1 J). Micro‑CT is widely applied to evaluate bone microarchitecture. The results indicated that HS impaired the trabecular microarchitecture of the chicken tibia, as evidenced by significantly decreased bone mineral density, trabecular separation (Tb.Sp), and cortical thickness (Ct.Th), together with a decreasing trend in trabecular thickness (Tb.Th) (Fig. 2 A– 2 G). The ash percentage and mineral composition of the tibia were further determined. Similarly, HS significantly reduced tibial ash content, accompanied by a decrease in Ca concentration, whereas no significant changes were observed in P and Mg levels (Fig. 2 H– 2 K). Alterations in bone microarchitecture may lead to changes in bone mechanical properties. The results demonstrated that both the breaking load and Young’s modulus of the tibia were significantly decreased in heat‑stressed chickens (Fig. 2 L and 2 N). In conclusion, HS impaired growth performance and compromised bone parameters in chickens. 3.2. Heat stress induced gut microbiota dysbiosis in chickens To explore the effects of HS on the composition and functional correlations of the chicken gut microbiota, 16S rRNA gene sequencing was conducted on samples from the NC and HS groups. A Venn diagram revealed that 126 amplicon sequence variants (ASVs) were shared between the two groups, with 19 ASVs unique to the NC group and 15 ASVs unique to the HS group (Fig. 3 A). A bar plot of genus-level community composition displayed distinct structural differences between the NC and HS groups (Fig. 3 B). Principal Coordinates Analysis (PCoA) at the ASV level further demonstrated a clear separation between the NC and HS clusters (R = 0.2500, P = 0.016), indicating that HS significantly altered the overall gut microbial community structure (Fig. 3 C). Analysis of α-diversity indices revealed that HS significantly decreased the Ace and Chao indices compared with the NC group (Fig. 3 D and 3 E), suggesting a marked reduction in gut microbial α-diversity under HS conditions. Linear discriminant analysis effect size (LEfSe) identified differentially abundant taxa between the two groups (Fig. 3 H). Follow-up analyses confirmed that Gordonibacter , Peptococcus , Lactobacillus , and Tyzzerella were significantly enriched in the NC group, while Turicibacter was significantly more abundant in the HS group at the genus level (Fig. 3 I– 3 M). A correlation heatmap further revealed significant associations between these differential genera and bone quality parameters. Specifically, Lactobacillus and Gordonibacter were positively correlated with bone ash, whereas Turicibacter exhibited a significant negative correlation with bone ash. In addition, Gordonibacter was also positively correlated with BMD (Fig. 3 N). Taken together, these findings indicate that HS causes a significant modification in the composition and function of the gut microbiota in chickens. 3.3. FMT-HS induced bone loss in chickens To investigate the causal role of gut microbiota in HS-induced bone loss, we performed FMT in chicks with a regimen of daily gavage from 1 to 10 days of age and weekly gavage from 11 to 35 days of age. The groups included FMT-PBS, FMT-NC, and FMT-HS (Fig. 4 A). Growth performance revealed no significant differences in ADFI or ADG among the three groups (Fig. 4 B and 4 C). However, the FCR was significantly elevated in the FMT-HS group compared with the FMT-PBS and FMT-NC groups (Fig. 4 D), indicating that HS-derived microbiota impaired feed utilization efficiency. Serum levels of Ca, P and ALP showed no significant changes across groups (Fig. 4 E, 4 F and 4 G). Additionally, the expression of osteoblast-related gene OPG was significantly downregulated in the FMT-HS group while expression of other osteogenic genes including RUNX2, SP7, ALPL, COL1A1 and BMP2 remained unaltered (Fig. 4 H). For osteoclast-related genes, the expression of MMP9 was significantly upregulated in the FMT-HS group relative to the FMT-PBS and FMT-NC groups whereas no significant differences were detected in the expression of NFATc1, ACP5, RANK or RANKL (Fig. 4 I). Quantitative micro-CT analysis showed that BMD, BS/TV, Tb.Th, and Ct.Th were comparable between these three groups (Fig. 5 B, 5 C, 5 E, and 5 G). Tb.N was significantly reduced in the FMT-HS group compared with FMT-NC groups (Fig. 5 D). Tb.Sp tended to be higher in the FMT-HS group, though this difference did not reach statistical significance ( P = 0.083) (Fig. 5 F). Bone ash and tibial calcium content remained unchanged across all three groups (Fig. 5 H and 5 I). Biomechanical testing further confirmed compromised bone strength in FMT-HS chickens. Fracture load, bone stiffness, and Young’s modulus were significantly lower in the FMT-HS group compared with FMT-PBS and FMT-NC groups (Fig. 5 J– 5 L). These results demonstrate that transplantation of gut microbiota from heat-stressed donors impairs trabecular bone microarchitecture and reduces bone biomechanical strength in recipient chickens, recapitulating the key features of HS-induced bone loss. 3.4. FMT-HS disrupted intestinal morphology barrier function and mineral absorption in chickens To further explore the mechanisms by which gut microbiota mediates HS-induced skeletal dysfunction, we analyzed intestinal morphology, barrier function, inflammatory status and mineral absorption-related gene expression in FMT chickens. Histological analysis revealed that FMT-HS significantly impaired intestinal structure compared with FMT-PBS and FMT-NC groups. Villus height and villus height to crypt depth ratio (VH/CD) were markedly reduced in the FMT-HS group while crypt depth remained unchanged across groups (Fig. 6 A and 6 B). Consistent with morphological deterioration, the positive stained area of CaBP-D28K, a key mediator of intestinal calcium absorption, was significantly decreased in the FMT-HS group (Fig. 6 A and 6 C). Circulating markers of intestinal barrier integrity were also altered. Serum LPS concentration showed no significant differences among groups. Serum DAO and DLA concentration were comparable between FMT-PBS and FMT-NC groups but significantly reduced in the FMT-HS group (Fig. 6 D). In line with these barrier changes mRNA expression of tight junction proteins was differentially affected. Expression of ZO-1 was significantly downregulated in the FMT-HS group while expression of JAM, OCLN and Claudin-1 showed no significant differences among groups (Fig. 6 E). Pro-inflammatory cytokine expression was enhanced in the FMT-HS group. Relative mRNA levels of IL-1β, IL-6 and TNFα were all significantly upregulated in the FMT-HS group compared with FMT-PBS and FMT-NC groups (Fig. 6 F). Furthermore, the expression of genes involved in intestinal mineral absorption was suppressed by HS-derived microbiota. The mRNA expression of CaBP-D28K, NCX1, and PMCA1b were significantly lower in the FMT-HS group than in FMT-PBS and FMT-NC groups (Fig. 6 G). 3.5. FMT-HS induced microbial dysbiosis in chickens We next evaluated the impact of FMT-HS on the composition and structure of the gut microbiota in chickens compared with FMT-NC group. A Venn diagram revealed 191 shared ASVs between the FMT-NC and FMT-HS groups. The FMT-NC group harbored 20 unique ASVs while the FMT-HS group contained 30 unique ASVs (Fig. 7 A). Genus-level taxonomic profiling showed distinct patterns in the relative abundance of microbial taxa between the two groups (Fig. 7 B). PCoA at the ASV level displayed a trend toward separation between FMT-NC and FMT-HS communities though this difference did not reach statistical significance (R = 0.2259, P = 0.069) (Fig. 7 C). Analysis of microbial dysbiosis and health indices revealed functional shifts in the microbiota. The Microbial Dysbiosis Index (MDI) was significantly elevated in the FMT-HS group relative to the FMT-NC group while the Gut Microbiota Health Index (GMHI) was significantly reduced (Fig. 7 D and 7 E). No significant differences were detected in α-diversity indices including Simpson, Chao, Shannon, and Ace indices between FMT-NC and FMT-HS groups (Fig. 5 F– 5 I). LEfSe identified taxa with differential enrichment between groups (Fig. 7 J). Among these Turicibacter a genus previously linked to bone loss was significantly more abundant in the FMT-HS group than in the FMT-NC group (Fig. 7 K). These findings indicate that FMT-HS drives functional dysbiosis and enriches specific bone-related taxa without overtly altering overall microbial α-diversity. 4. Discussion Growing evidence indicates that gut microbiota regulates bone remodeling through the gut-bone axis[ 19 ]; however, whether HS-induced deterioration of bone performance in chickens is associated with intestinal microbiota remains unclear. The present study delineates a critical mechanistic pathway linking HS, a prevalent environmental hazard in intensive poultry production, to skeletal deterioration, with the gut microbiota functioning as a pivotal intermediary. These findings advance understanding of how environmental stressors disrupt host-microbiota homeostasis to compromise distant organ systems, offering novel insights for mitigating HS impacts in agricultural environments. A fundamental finding of the current study is that FMT-HS recapitulates the bone loss observed in directly HS-challenged chickens, confirming the gut microbiota as a critical functional mediator translating HS exposure into deleterious skeletal outcomes. However, there were no significant changes in either α-diversity or β-diversity indices between FMT-HS and FMT-NC groups, indicating that the overall species richness and structural stability of the microbial community were not markedly affected[ 20 ]. In contrast, FMT-HS induced pronounced functional gut dysbiosis, as evidenced by increased MDI and decreased GMHI. This functional dysbiosis preceded the collapse of the overall ecological structure, suggesting potential alterations in the metabolic activity, gene expression, or strain-level characteristics of key functional bacteria, which in turn mediated host phenotypic changes[ 21 ]. Notably, genus Turicibacter , which was previously associated with HS-related bone loss in our initial model, was significantly enriched in FMT-HS recipients. The genus Turicibacter is a key component of the animal gut microbiota and is well known for its close association with bile acid metabolism and host lipid homeostasis[ 22 , 23 ]. Although direct evidence supporting a regulatory role of Turicibacter in bone metabolism is lacking, from the perspective of the liver‑bone axis, altered lipid metabolism may indirectly affect bone remodeling[ 24 , 25 ]. In addition, multiple studies have demonstrated that various bioactive compounds, including Spirulina platensis components[ 26 ], grape seed extract[ 27 ], and xanthohumol[ 28 ], modulate bone metabolism by altering the relative abundance of Turicibacter . Thus, these findings suggest Turicibacter as a potential biomarker for HS-induced bone loss, although its mechanistic role remains to be elucidated. Heat stress-induced gut dysbiosis directly impairs intestinal barrier integrity. The intestinal barrier serves as a critical defense interface between the host and the luminal environment and is essential for preventing the translocation of microbial metabolites and pathogens, which may represent a key step in amplifying the detrimental effects of environmental stressors. The present study demonstrated that FMT-HS markedly disrupted intestinal morphology, as evidenced by decreased villus height and VH/CD ratio. These structural alterations suggest intestinal atrophy, leading to reduced absorptive capacity and compromised epithelial integrity, thereby exacerbating the deleterious effects of heat stress-associated microbiota[ 29 , 30 ]. Meanwhile, FMT-HS impaired intestinal barrier function, reflected by altered serum markers of intestinal permeability, including reduced DAO activity and elevated DLA levels, accompanied by downregulated mRNA expression of the tight junction protein ZO-1. Although barrier leakage is known to induce systemic proinflammatory responses that drive bone resorption[ 31 , 32 ], no significant alterations in serum LPS levels were observed in this FMT study, but only increased intestinal local inflammation, which is inconsistent with previous reports[ 33 , 34 ]. This discrepancy may be attributed to the rapid phagocytosis and inactivation of LPS leaked from the intestine by hepatic Kupffer cells following entry into the portal vein[ 35 ], resulting in no significant increase in peripheral blood LPS levels. Instead, local intestinal inflammation induced the release of proinflammatory cytokines such as TNF‑α and IL‑1β via the activation of immune cells and the release of damage‑associated molecular patterns[ 36 ]. These cytokines promoted osteoclast differentiation and activation[ 37 ]. Consistent with this, the present study revealed that FMT‑HS downregulated the expression of OPG, a decoy receptor for RANKL. The reduction in OPG shifted the RANKL/OPG ratio toward osteoclastogenesis and accelerated bone resorption. Conversely, FMT‑HS significantly upregulated the expression of MMP9, a protease secreted by osteoclasts that plays a critical role in bone matrix degradation; its upregulation further enhanced bone resorption. Similar phenomena have frequently been observed in patients with inflammatory bowel disease[ 38 ]. Notably, FMT-HS-induced gut dysbiosis also impaired intestinal mineral absorption. Bone formation strictly depends on the bioavailability of calcium and phosphorus, and the intestine represents the primary site for mineral absorption. The present study demonstrated that FMT-HS significantly downregulated the expression of key genes involved in intestinal mineral transport, including CaBP-D28K, NCX1, and PMCA1b. Nevertheless, this downregulation did not induce significant alterations in bone ash content or BMD. The organism may maintain the relative stability of bone mineral content and BMD via compensatory regulation of systemic calcium‑phosphorus homeostasis[ 39 ]. Notably, FMT-HS reduced trabecular bone number and impaired bone biomechanical properties. Bone biomechanical characteristics are highly dependent on trabecular number, connectivity, and spatial architecture, and exhibit extreme sensitivity to microstructural damage of trabecular bone[ 40 ]. The phenomenon whereby FMT-HS induces impaired bone biomechanics without changes in bone mass may be attributed not only to alterations in bone microstructure, but also to variations in the crystallite size, uniformity, and arrangement of bone minerals[ 41 ], as well as the structure and integrity of bone collagen[ 42 ]. Accordingly, functional alterations in intestinal barrier integrity, inflammatory status, and mineral absorption directly translated into impaired bone quality in FMT-HS chickens. These findings highlight the complexity of host–microbiota–environment interactions, in which heat stress disrupt microbiota function, thereby impairing multiple physiological pathways and ultimately compromising skeletal health. HS constitutes a major environmental hazard in intensive poultry production, resulting in considerable economic losses and impaired animal welfare. The present study demonstrates that the gut microbiota represents a promising intervention target for alleviating heat stress-induced bone loss, with the potential to improve stress resilience in poultry. Targeted strategies, including suppressing the excessive proliferation of Turicibacter and employing probiotics, prebiotics, or synbiotics to restore microbial homeostasis, can enhance intestinal barrier function, alleviate inflammatory responses, and improve mineral absorption, thereby attenuating heat stress-induced skeletal damage. Future studies should focus on delineating the specific microbial metabolites (e.g., short-chain fatty acids[ 43 ], bile acids[ 44 ], polyamines[ 45 ]) and signaling pathways that mediate the regulation of the gut–bone axis under HS. 5. Conclusion In conclusion, this study provides definitive causal evidence that gut microbiota dysbiosis acts as a critical mediator of HS-induced bone loss in chickens. We demonstrated that HS reshapes the gut microbiota to induce functional dysbiosis, which in turn impairs intestinal barrier integrity, triggers inflammation response, and suppresses intestinal mineral absorption. These perturbations collectively disrupt bone metabolism, impairing trabecular bone microarchitecture, and reducing biomechanical strength. These findings advance our understanding of the gut-bone axis in the context of environmental stress, offering novel insights for mitigating the adverse impacts of HS in agricultural systems. Declarations The current experiment adhered to animal welfare guidelines and experimental protocols established by the Research Ethics Committee of Southwest University. Approval was granted by the Laboratory Animal Management Committee of Southwest University (Protocol No. IACUC-20231023-04). Funding This work was financially supported by the National Natural Science Foundation of China (grant number 32402955), the Fundamental Research Funds for the Central Universities (grant number SWU-KQ24004), and the Yunnan Province Science and Technology Talents and Platform Program (Grant 202405AF140106). Acknowledgments We would like to thank our colleagues at the Joint International Research Laboratory of Animal Health and Animal Food Safety. Competing interest statement The authors declare no competing interests. Author contributions H.G. and S.J. conceived and designed the study. J.G., Y.W., Y.Z., and Z.W. executed the experiment and analyzed tissue samples. J.G. performed the data analysis and generated the figures. H.G., S.J., and R.F. drafted, revised, and reviewed the manuscript. 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Zhang J, Cai C, Zhang Y, Luo C, Huo S, Wang K, et al. The functional roles and mechanisms of polyamines in age-related bone diseases. Cell Mol Life Sci. 2025;83(1):38. Additional Declarations No competing interests reported. Supplementary Files SupplementalMaterial.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 11 May, 2026 Reviewers invited by journal 28 Apr, 2026 Editor assigned by journal 28 Apr, 2026 Submission checks completed at journal 14 Apr, 2026 First submitted to journal 12 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9395311","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":631518045,"identity":"d734ffdc-9efe-470b-ab56-94683c868fb6","order_by":0,"name":"Hang Gao","email":"","orcid":"","institution":"Southwest University","correspondingAuthor":false,"prefix":"","firstName":"Hang","middleName":"","lastName":"Gao","suffix":""},{"id":631518046,"identity":"092bcbf1-1194-4326-978e-8159a0823a3b","order_by":1,"name":"Jingsha Gu","email":"","orcid":"","institution":"Southwest University","correspondingAuthor":false,"prefix":"","firstName":"Jingsha","middleName":"","lastName":"Gu","suffix":""},{"id":631518047,"identity":"cba4bdf3-d489-4d8d-9d2a-41ece18e92a1","order_by":2,"name":"Yi Wang","email":"","orcid":"","institution":"Southwest University","correspondingAuthor":false,"prefix":"","firstName":"Yi","middleName":"","lastName":"Wang","suffix":""},{"id":631518048,"identity":"ba2391b5-99c8-4e0a-8fbf-915f71927c53","order_by":3,"name":"Yu Zou","email":"","orcid":"","institution":"Southwest University","correspondingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Zou","suffix":""},{"id":631518049,"identity":"f2766537-042f-4b58-9e37-368df7481960","order_by":4,"name":"Zhouyuan Wang","email":"","orcid":"","institution":"Kunming Hemeihua Feed Limited Company","correspondingAuthor":false,"prefix":"","firstName":"Zhouyuan","middleName":"","lastName":"Wang","suffix":""},{"id":631518050,"identity":"498e7d58-9698-4a2e-a920-ca44df1dd957","order_by":5,"name":"Rendong Fang","email":"","orcid":"","institution":"Southwest University","correspondingAuthor":false,"prefix":"","firstName":"Rendong","middleName":"","lastName":"Fang","suffix":""},{"id":631518051,"identity":"315b1762-e4fe-4867-881c-3c954177877b","order_by":6,"name":"sha jiang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABA0lEQVRIie3QPWrDMBiA4U8Y5EXQVcIEX8HB4GZo6VVkDJmaqZApg4pBnYJX5xbuklkgcK5QiJcunjp4KMGDoLXbDlmieOygd5BA6EE/AC7XPwzlP5MCHOpD3/0uRtPIDcWclVPIXwpYSaKATCHei9e+f5omjI4iiu+MToWf7ylsGsvF8G08k+28ahTPVnIgpF5TqFvbW5KACY0qxZVeiWMq6GNCkdAW4p8CavRDpdLnfGEGEn5cIyRhHdbprsw8D/B4CrlK1gGSOitIjdFWfsWSLJ8WvL5M5sVhz3qj76VfnKA3y1nh69e3bmMhYvhocr6Cx4FfBADheLnessHlcrlc8A1qqVtnF34m9wAAAABJRU5ErkJggg==","orcid":"","institution":"Southwest University","correspondingAuthor":true,"prefix":"","firstName":"sha","middleName":"","lastName":"jiang","suffix":""}],"badges":[],"createdAt":"2026-04-12 15:23:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9395311/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9395311/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108806186,"identity":"e3fac457-682e-49aa-b5d6-9639e14174dd","added_by":"auto","created_at":"2026-05-08 15:27:56","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":124646,"visible":true,"origin":"","legend":"\u003cp\u003eHeat stress impaired growth performance and bone metabolism in chickens. (A) Schematic of the experimental design. Male broilers were subjected to either a thermoneutral control condition (NC: 22 ± 1°C) or chronic heat stress (HS: 35 ± 1°C) from 21 to 35 days of age. (B) Heterophil/lymphocyte (H/L) ratio. (C–E) Growth performance parameters: (C) average daily feed intake (ADFI), (D) average daily gain (ADG), and (E) feed conversion ratio (FCR) of NC and HS chickens. (F–H) Serum bone metabolic markers: (F) Ca, (G) P concentrations, and (H) ALP activity in NC and HS chickens. (I–J) Relative mRNA expression of genes involved in (I) osteoblastogenesis (RUNX2, SP7, ALPL, COL1A1) and (J) osteoclastogenesis (NFATc1, ACP5, MMP9, CTSK, TRAF6) in NC and HS chickens, analyzed by RT-qPCR. Data are presented as mean ± SD, n = 8. *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05 indicates a significant difference between the NC and HS groups as determined by Student’s t-test.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9395311/v1/dd451264aaec1fdfeb3dcb53.png"},{"id":108724469,"identity":"1718b989-d68d-47ec-984a-c60c2de32c3e","added_by":"auto","created_at":"2026-05-07 16:44:29","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":100758,"visible":true,"origin":"","legend":"\u003cp\u003eHeat stress damaged the bone microstructure and mechanical properties in chickens. (A) Representative micro-CT images of tibial cross-sections and longitudinal views from thermoneutral control (NC) and HS broilers. (B) Bone mineral density (BMD). (C) Bone surface over bone volume (BS/TV). (D) Trabecular number (Tb.N). (E) Trabecular thickness (Tb.Th). (F) Trabecular separation (Tb.Sp). (G) Cortical thickness (Ct.Th). (H) Bone ash content. (I) Tibial Ca content. (J) Tibial P content. (K) Tibial Mg content. (L) Fracture load. (M) Bone stiffness. (N) Young’s modulus. Data are presented as mean ± SD, n = 8. *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05 indicates a significant difference between the NC and HS groups as determined by Student’s t-test. A \u003cem\u003eP\u003c/em\u003e-value of 0.072 is noted for Tb.Th, indicating a trend toward a reduction in the HS group.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9395311/v1/1b8665efc398aab5c46b1d5f.png"},{"id":108724467,"identity":"6e7e887b-45f9-4cc7-8447-1c8aca090e7a","added_by":"auto","created_at":"2026-05-07 16:44:29","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":176803,"visible":true,"origin":"","legend":"\u003cp\u003eHeat stress induced gut microbiota dysbiosis in chickens. (A) Venn diagram displaying shared and unique ASVs between NC and HS groups. (B) Bar plot illustrating the relative abundance of gut microbial genera in NC and HS chickens. (C) PCoA based on ASV-level data, showing distinct separation of microbial communities between NC and HS groups (R=0.2500, \u003cem\u003eP\u003c/em\u003e=0.016). (D–G) Boxplots of α-diversity indices: (D) Ace index, (E) Chao index, (F) Shannon index, and (G) Simpson index, comparing NC and HS chickens. (H) Linear discriminant analysis effect size (LEfSe) bar plot identifying differentially abundant taxa between NC (blue) and HS (red) groups (LDA score \u0026gt; 3.5). (I–M) Proportional abundance of differentially abundant genera: (I) \u003cem\u003eGordonibacter\u003c/em\u003e, (J) \u003cem\u003eTyzzerella\u003c/em\u003e, (K) \u003cem\u003ePeptococcus\u003c/em\u003e, (L) \u003cem\u003eLactobacillus\u003c/em\u003e, and (M) \u003cem\u003eTuricibacter\u003c/em\u003e in NC and HS groups. (N) Heatmap showing Spearman correlations between differential genera and bone parameters, including ALP, BMD, bone ash weight, and fracture load. Data are expressed as boxplot, n = 6. *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01 compared with the NC group (Mann-Whitney U test).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9395311/v1/94aab8f06f5a0f011b88e3dc.png"},{"id":108805893,"identity":"268915b9-8730-470e-aa3e-e6b7473264bd","added_by":"auto","created_at":"2026-05-08 15:27:07","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":137887,"visible":true,"origin":"","legend":"\u003cp\u003eFMT-HS induced growth performance and bone metabolism alterations. (A) Schematic of the FMT experimental protocol. (B–D) Growth performance parameters. (B) Average daily feed intake. (C) Average daily gain. (D) Feed conversion ratio in FMT-PBS, FMT-NC and FMT-HS chickens. (E–G) Serum bone metabolic markers. (E) Ca concentration. (F) P concentration. (G) ALP activity in the three groups. (H–I) Relative mRNA expression of genes involved in bone metabolism. (H) Osteoblastogenesis-related genes (OPG, RUNX2, SP7, ALPL, COL1A1, BMP2). (I) Osteoclastogenesis-related genes (NFATc1, ACP5, MMP9, RANK, RANKL) analyzed by RT-qPCR. Data are presented as mean ± SD, n = 8. Bars with different lowercase letters indicate significant differences (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05) between groups as determined by one-way ANOVA followed by Tukey’s post-hoc test.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-9395311/v1/191745774a4f335bbf37b324.png"},{"id":108807648,"identity":"f96ff3c2-cb3e-406d-a7c8-31f6e9df8210","added_by":"auto","created_at":"2026-05-08 15:31:02","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":115958,"visible":true,"origin":"","legend":"\u003cp\u003eFMT-HS impaired the bone microstructure and mechanical properties in chickens.\u003c/p\u003e\n\u003cp\u003e(A) Representative micro-CT images of trabecular and cortical bone in tibiae from FMT-PBS, FMT-NC, and FMT-HS chickens. (B) BMD. (C) BS/TV. (D) Tb.N. (E) Tb.Th. (F) Tb.Sp. (G) Cortical thickness (Ct.Th). (H) Bone ash. (I) Tibial calcium content. (J) Fracture load. (K) Bone stiffness. (L) Young’s modulus. Bars with different lowercase letters indicate significant differences (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05) between groups as determined by one-way ANOVA followed by Tukey’s post-hoc test. A \u003cem\u003eP\u003c/em\u003e-value of 0.083 is noted for Tb.Sp, indicating a trend toward a reduction between the FMT-NC and FMT-HS group.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-9395311/v1/8faa717972615fe68d27a0e6.png"},{"id":108806999,"identity":"321ed6cf-82fc-4cde-9e53-dd10f5136d38","added_by":"auto","created_at":"2026-05-08 15:29:53","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":216548,"visible":true,"origin":"","legend":"\u003cp\u003eFMT-HS disrupted intestinal morphology barrier function and mineral absorption in chickens. (A) Representative images of H\u0026amp;E staining for intestinal morphology and immunohistochemical staining for CaBP-D28K in FMT-PBS FMT-NC and FMT-HS chickens. Scale bar 500 μm. (B) Quantification of intestinal morphological parameters including villus height crypt depth and villus height to crypt depth ratio (VH/CD). (C) Quantitative analysis of CaBP-D28K positive stained area in the intestine. (D) Serum concentrations of LPS, DAO, and DLA. (E) Relative mRNA expression of intestinal tight junction genes (JAM, ZO-1, OCLN, and Claudin-1). (F) Relative mRNA expression of pro-inflammatory cytokine genes (IL-1β, IL-6, and TNF-α). (G) Relative mRNA expression of intestinal mineral absorption-related genes (CaBP-D28K, NCX1, PMCA1b, Npt2b, and VDR). Data are presented as mean ± SD, n = 8. Bars with different lowercase letters indicate significant differences (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05) between groups as determined by one-way ANOVA followed by Tukey’s post-hoc test.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-9395311/v1/ee4d8a1d6085be9bcbb06fca.png"},{"id":108806878,"identity":"22695ee3-e8da-495f-a01c-7fea51dcddec","added_by":"auto","created_at":"2026-05-08 15:29:36","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":149722,"visible":true,"origin":"","legend":"\u003cp\u003eFMT-HS induced microbial dysbiosis in chickens. (A) Venn diagram displaying shared and unique ASVs between FMT-NC and FMT-HS groups. (B) Bar plot illustrating the relative abundance of gut microbial taxa at the genus level in FMT-NC and FMT-HS chickens. (C) PCoA based on ASV-level data showing clustering of microbial communities in FMT-NC and FMT-HS groups (R=0.2259, \u003cem\u003eP\u003c/em\u003e=0.069). (D) Microbial Dysbiosis Index (MDI) comparison between FMT-NC and FMT-HS groups. (E) Gut Microbiota Health Index (GMHI) comparison between FMT-NC and FMT-HS groups. (F–I) Boxplots of α-diversity indices including Simpson index Chao index Shannon index and Ace index in FMT-NC and FMT-HS chickens. (J) LEfSe bar plot identifying differentially abundant taxa between FMT-NC (blue) and FMT-HS (red) groups with an LDA score threshold of 3. (K) Relative abundance of \u003cem\u003eTuricibacter\u003c/em\u003e in FMT-NC and FMT-HS groups. The asterisk indicates a significant difference at \u003cem\u003eP\u003c/em\u003e\u0026lt; 0.05 between groups determined by the Mann-Whitney U test.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-9395311/v1/cfc6f05f93c0d747d0861054.png"},{"id":108810344,"identity":"112cdfa3-1b02-4c3d-a335-7cc59975fe1d","added_by":"auto","created_at":"2026-05-08 15:58:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1143361,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9395311/v1/627b000c-faaa-4616-a7a7-38f4074f1edd.pdf"},{"id":108724466,"identity":"29490322-d819-47b7-aed9-5d4782a45f12","added_by":"auto","created_at":"2026-05-07 16:44:29","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":22474,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-9395311/v1/a72feec7338bdad481cbf405.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Heat Stress Triggers Bone Performance Degeneration via Impairing Intestinal Barrier Function and Altering Gut Microbiota in Chickens","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eIn recent years, the cumulative emissions of greenhouse gases have accelerated global warming[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Future projections indicate that warming will persist, with heat extremes becoming not only more common but also longer-lasting and more severe. Record-breaking heatwaves continue to shatter historical extremes, posing severe challenges to human and animal health. Increasing evidence suggests that prolonged exposure to high temperatures can lead to heat stress (HS) and heighten the risk of morbidity and mortality[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Commercial chickens, serving as a vital protein source for humans, are highly susceptible to HS due to their high metabolic rate, substantial heat production, and lack of sweat glands coupled with feather coverage[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Chickens are homeothermic animals whose thermoneutral zone spans only 18\u0026ndash;30\u0026deg;C. Once ambient temperature climbs above this narrow ceiling, birds enter heat-stress conditions that rapidly trigger physiological and behavioral disruptions, resulting in feed intake and performance fall[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], and mortality rises[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. At present, due to its widespread occurrence and prolonged duration, HS has become one of the most typical harmful environmental stressors in the scenarios of global warming and intensive poultry farming.\u003c/p\u003e \u003cp\u003eSkeletal integrity underpins growth rate, standing ability, and productive output in modern chickens, while tibial dyschondroplasia[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], osteoporosis[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], and fractures[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] inflict multibillion dollar losses through mortality, culling, and carcass downgrading. These losses underscore that bone formation is not a simple by-product of growth; rather, it is a complex, finely tuned process governed by an intricate interplay of genetics, nutrition, and environmental factors. Reports indicate that HS amplifies skeletal deterioration, simultaneously diminishing tibial break strength[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], ash content, and bone volume per tissue volume in chickens[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Decreased bone performance in chickens represents one of the major HS-induced physiological impairments, which not only severely impairs flock locomotor ability, elevates fracture risk and compromises animal welfare[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], but also results in reduced slaughter grades of commercial broilers[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] and shortened laying cycles of laying hens[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. However, the mechanisms by which HS causes leg problems and skeletal diseases remain incompletely understood to date.\u003c/p\u003e \u003cp\u003eThe vertebrate skeleton is no longer viewed as an isolated organ system. The gut microbiota is increasingly recognized as a pivotal regulator of host skeletal development through the gut-bone axis. Germ-free or antibiotic-treated mice exhibit low systemic IGF-1 and impaired bone formation[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], whereas supplementation with probiotics such as \u003cem\u003eLactobacillus Rhamnosus GG\u003c/em\u003e restores trabecular bone mass by expanding regulatory T cells and suppressing osteoclastogenic cytokines[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Similarly, fecal microbiota transplantation (FMT) alleviates lipopolysaccharide-induced osteoporosis by modulating the gut microbiota and long non-coding RNA[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. These findings indicate that the gut microbiota may act as a pivotal regulatory factor in bone metabolic signaling transduction within mammals. In the chickens, our previous research has demonstrated that cecal microbiota transplantation from adult laying hens significantly enhances calcium uptake and retention efficiency in chicks by transcriptionally upregulating key calcium ion transporters[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. As the primary site for absorbing bone-associated critical nutrients (e.g., calcium and vitamins), the intestinal tract maintains a microbiota homeostasis that modulates the integrity and physiological functions of the intestinal mucosa, thereby potentially influencing the absorption efficiency of those nutrients[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In addition, gut microbiota dysbiosis induces skeletal damage associated with tibial dyschondroplasia in commercial broilers by disrupting glucose homeostasis[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, systematic investigations into the association between gut microbiota and HS-induced bone loss in chickens remain relatively scarce at present. As a critical intermediary in damage induced by adverse environmental stressors, the gut microbiota may play a key mediating role in the process of HS-induced bone loss in chickens. Therefore, the present study aimed to investigate the effects of HS on gut microbiota structure and bone metabolism in chickens. Subsequently, FMT were performed to verify the causal relationship that HS induces bone loss in chickens by disrupting gut microbiota structure, as well as to elucidate the underlying crucial mechanisms. This study will provide novel insights into the mechanisms underlying physiological impairment induced by adverse environmental stressors, and facilitate the development of targeted prevention and control strategies. Meanwhile, it will lay a solid theoretical foundation for ensuring production efficiency and supporting the green and sustainable development of the poultry industry.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Animal and study design\u003c/h2\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003e2.1.1. HS treatment\u003c/h2\u003e \u003cp\u003eForty 1-day-old male Cobb 500 broiler chicks with uniform body weight were randomly allocated to two treatment groups, each consisting of four replicates with five birds per replicate. The brooding temperature was maintained at 34\u0026deg;C on day 1 and then gradually reduced by 0.5\u0026deg;C daily until a constant temperature of 22\u0026deg;C was achieved. On day 21, the birds were subjected to two environmental regimens: a normal control group (NC) housed continuously at 22\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u0026deg;C with a relative humidity (RH) of 55\u0026thinsp;\u0026plusmn;\u0026thinsp;5%, and a heat stress group (HS) exposed to 35\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u0026deg;C and 55\u0026thinsp;\u0026plusmn;\u0026thinsp;5% RH for 8 h daily (10:00\u0026ndash;18:00) over 14 consecutive days[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.1.2. FMT\u003c/h2\u003e \u003cp\u003eBased on previous studies[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], partial modifications were made in the present experiment. It is worth noting that, due to the presence of white urate deposits in chicken feces, fresh feces were not directly collected from donor birds; instead, cecal contents were utilized. The detailed protocol is briefly described as follows: briefly, cecal feces from donor chickens were mixed with phosphate-buffered saline (PBS, pH\u0026thinsp;=\u0026thinsp;7.4) at a ratio of 1:6 (w/v) in a sterile centrifuge tube. After vigorous vortexing, the mixture was centrifuged at 800 \u0026times; g for 10 min. The resulting supernatant was harvested and filtered through a 200-\u0026micro;m sterile sieve (Retsch, Haan, Germany) to eliminate large particulate matter and ensure homogeneous inoculum. A total of 60 1-day-old male Cobb 500 broiler chicks with uniform body weight were randomly assigned to three treatment groups, each comprising four replicates of five birds: (1) Recipient chicks received PBS, FMT-PBS group, (2) fecal microbiota from normal control donors, FMT-NC, and (3) fecal microbiota from heat-stressed donors, FMT-HS group. Oral gavage with 1 mL of the prepared inoculum was administered once daily from day 1 to day 10, with booster doses given on days 17, 24, and 31[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAll birds were provided with ad libitum access to feed and water throughout the entire experimental period. The lighting schedule and feeding management strictly followed the guidelines specified in the Cobb Broiler Management Guide. Body weight (BW) and cage-level feed intake were recorded throughout the trial. Body weight gain (BWG) and feed conversion ratio (FCR) were calculated on a per-cage basis. On day 35, two birds from each of the four replicate cages per group were randomly selected, weighed, and anesthetized with sodium pentobarbital at a dosage of 30 mg/kg body weight. Blood, tibia and ileum tissues, and cecal contents were aseptically collected for subsequent analysis.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Blood smear and serum biochemical analysis\u003c/h2\u003e \u003cp\u003eBlood samples were collected from the brachial vein of each bird into 1.5 mL EDTA-coated tubes, which were immediately inverted gently to prevent coagulation and then stored at 4\u0026deg;C for no more than 2 h prior to analysis. For blood smear examination, duplicate smears were prepared, stained with Wright-Giemsa stain, and examined under a light microscope at 100\u0026times; magnification (oil immersion). A total of 100 leukocytes were counted and classified per smear, and the percentages of lymphocytes, heterophils, eosinophils, basophils, and monocytes were calculated accordingly. Concentrations of serum calcium (Ca), phosphorus (P), and alkaline phosphatase (ALP) were measured using an automatic biochemical analyzer (Mindray BS-240 Vet, Shenzhen, China).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.3. ELISA analysis\u003c/h2\u003e \u003cp\u003eSerum lipopolysaccharide (LPS) (Cat# EHJ-50229, Xiamen Huijia Biotechnology Co., Ltd.), diamine oxidase (DAO) (Cat# EHJ-98358C, Xiamen Huijia Biotechnology Co., Ltd.) and D-lactate (DLA) (Cat# EHJ-96759C, Xiamen Huijia Biotechnology Co., Ltd.) were detected by ELISA kit per instructions with minor modifications. In short, 10 \u0026micro;L of serum and standards were added to black 96-well plates. Working reagent was added to sample wells, and blank reagent to blank wells. Reaction was terminated with stop solution, and absorbance was measured at a specific wavelength. LPS, DAO, and DLA concentrations were calculated via standard curve.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Micro-CT analysis\u003c/h2\u003e \u003cp\u003eSoft tissues (skin and musculature) were meticulously dissected from the right tibiae, after which the cleaned bones were blotted dry with sterile gauze to remove surface lipids. Subsequently, the right tibiae were scanned using a NEMO NMC-200 micro-CT system (PingSheng Medical Technology Co., Ltd., Suzhou, China). Data acquisition was conducted with Cruiser software (Version 2.3, PingSheng Medical Technology), while image reconstruction was performed via Recon software (Version 3.1) using the Feldkamp\u0026ndash;Davis\u0026ndash;Kress (FDK) algorithm. Three-dimensional (3D) visualization and volume-of-interest (VOI) segmentation were accomplished with Avatar software (Version 1.7). The scanning parameters were set as follows: X-ray tube voltage\u0026thinsp;=\u0026thinsp;80 kV, tube current\u0026thinsp;=\u0026thinsp;0.04 mA, pixel size\u0026thinsp;=\u0026thinsp;70 \u0026micro;m, and rotation step\u0026thinsp;=\u0026thinsp;0.5\u0026deg;. The following bone microstructural parameters were quantified: bone mineral density (BMD), bone surface area to tissue volume ratio (BS/TV), trabecular separation (Tb.Sp), trabecular number (Tb.N), trabecular mean thickness (Tb.Th) and cortical bone thickness (Ct.Th).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Bone mechanical properties analysis\u003c/h2\u003e \u003cp\u003eFollowing micro-CT scanning, all right tibiae were subjected to bone biomechanical analysis. Biomechanical testing was performed via the three-point bending method using a universal material testing machine (LR10K Plus, Lloyd Instruments Ltd., Hampshire, UK) equipped with a 5 N load cell. Each tibia was positioned with its anterior aspect facing upward, and loaded at the midpoint between the two bottom supports, which corresponded to the longitudinal midpoint of the bone. Loading was applied at a constant crosshead speed of 15 mm/min until bone fracture occurred. Force-displacement data were recorded and subsequently used to calculate whole-bone stiffness, fracture load, and Young\u0026rsquo;s modulus using NEXYGEN Plus software (Lloyd Instruments Ltd.).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Bone ash and mineral composition analysis\u003c/h2\u003e \u003cp\u003eThe tibiae were ground into fine powder and passed through a 40-mesh sieve. The ground bone powder was dried at 110\u0026deg;C to a constant weight. Aliquots of 0.1 g were first carbonized at 200\u0026deg;C, followed by ashing at 550\u0026deg;C for 3 h. The ash mass was recorded to calculate the bone ash content. Each ash sample was then digested in hot concentrated nitric acid (HNO₃), diluted to a final volume of 50 mL with deionized water, and the concentrations of Ca, P, and magnesium (Mg) were quantified using inductively coupled plasma optical emission spectrometry (ICP-OES; iCAP 7000, Thermo Fisher Scientific, Waltham, MA, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.7. HE staining\u003c/h2\u003e \u003cp\u003e For each harvested ileal specimen, a 1 cm segment was subjected to gradient ethanol dehydration, followed by xylene clearing and immersion in liquid paraffin. The processed samples were embedded via an embedding apparatus and sectioned into 3 \u0026micro;m-thick slices using a sliding microtome (Leica RM2235, Leica Microsystems, Wetzlar, Germany), prior to hematoxylin-eosin (HE) staining. Histological sections were observed under a light microscope with a 4\u0026times; objective lens; randomly selected non-overlapping fields (3 fields on average per section) were examined, and a minimum of 15 villus-crypt complexes were evaluated per section. Image-Pro Plus 6.0 software was employed to quantify villus height (VH) and crypt depth (CD) in each small intestinal segment, and the villus height-to-crypt depth ratio (VH/CD) was subsequently computed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.8. Immunohistochemistry\u003c/h2\u003e \u003cp\u003eParaffin-embedded ileum sections were dewaxed and hydrated by immersion in xylene and gradient ethanol solutions. After antigen retrieval, the sections were then incubated with mouse polyclonal anti-CaBP-D28K antibody (Cat# GB113362) at 4\u0026deg;C overnight. On the following day, the sections were washed three times with PBS, and subsequent staining steps were conducted as per the kit instructions. DAB chromogenic substrate (DAB-031, Maxin Biotechnologies) was used for color development, followed by hematoxylin staining for nuclear counterstaining and mounting with neutral resin. All sections were semi-quantitatively analyzed using Image-Pro Plus software, with the positive staining area determined by the ratio of integrated optical density to the region of interest in three images per sample.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e2.9. Real-time quantitative PCR analysis (RT-qPCR)\u003c/h2\u003e \u003cp\u003eTRIzol reagent (Tsingke Biotech Co., Ltd., #TSP401, Nanjing, China) served to isolate total RNA from the left tibia and ileum tissue. Reverse transcription of the RNA into cDNA was accomplished with TransScript Uni All-in-One First-Strand cDNA Synthesis SuperMix from TransGen Biotech Co., Ltd. (#AU341\u0026ndash;02-V2, Nanjing). Subsequent qPCR reactions, performed on a QuantStudio\u0026trade; 6 Flex Real-Time PCR system (Applied Biosystems, Wilmington, MA, USA), employed diluted cDNA and PerfectStart Green qPCR SuperMix (TransGen Biotech Co., Ltd., #AQ601\u0026ndash;02, Nanjing). Primers, whose sequences appear in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e, were designed in Oligo 7.0 and synthesized by Sangon Biotech (Shanghai, China). Relative mRNA levels were quantified via the 2\u003csup\u003e\u0026minus;ΔΔCT\u003c/sup\u003e method, with Peptidyl-prolyl cis-trans isomerase A (PPIA) acting as the endogenous control.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e2.10. 16S rRNA sequencing\u003c/h2\u003e \u003cp\u003eMicrobial DNA was isolated from cecal content samples using the FastDNA\u0026reg; Spin Kit for Soil (MP Biomedicals, Santa Ana, CA, USA) in strict accordance with the manufacturer\u0026rsquo;s recommended protocol. The V3-V4 hypervariable region of the 16S rRNA gene was amplified using the specific primers 338F (5\u0026rsquo;-ACTCCTACGGGAGGCAGCAG-3\u0026rsquo;) and 806R (5\u0026rsquo;-GGACTACHVGGGTWTCTAAT-3\u0026rsquo;). The PCR reaction system was prepared with a total volume of 20 \u0026micro;L, consisting of 4 \u0026micro;L of 5\u0026times; FastPfu Buffer, 2 \u0026micro;L of 2.5 mM dNTPs, 0.8 \u0026micro;l of each 5 \u0026micro;M primer (338F and 806R), 0.4 \u0026micro;l of TransStart FastPfu DNA Polymerase (TransGen Biotech, Beijing, China), 0.2 \u0026micro;L of BSA, and 10 ng of genomic DNA template. The size of the PCR amplicons was verified by 2% agarose gel electrophoresis. Amplicons were then purified using the AxyPrep DNA Gel Extraction Kit (Axygen, Union City, CA, USA) and quantified with a QuantiFluor ST Fluorometer (Promega, Madison, WI, USA) following the manufacturers\u0026rsquo; instructions. Purified amplicons were pooled in equimolar amounts and subjected to paired-end sequencing (2 \u0026times; 300 bp) on the Illumina MiSeq platform (Illumina, San Diego, CA, USA) at Shanghai Majorbio Bio-pharm Technology Co., Ltd. (Shanghai, China), in compliance with the manufacturer\u0026rsquo;s standard procedures. The raw 16S rRNA gene sequence reads were deposited in the NCBI Sequence Read Archive (SRA) under the accession number PRJNA1106229 and PRJNA1421088.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e2.11. Statistical analysis\u003c/h2\u003e \u003cp\u003eExcept for the microbiome data, data were analyzed and plotted using SPSS (Version 21.0, IBM, USA) and GraphPad Prism (Version 8.0.2, San Diego, California, USA) statistical analysis software, respectively. The mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD of the data was displayed. For multigroup comparisons: one-way ANOVA was applied when the assumption of homogeneity of variance was met, followed by Tukey\u0026rsquo;s post-hoc test for pairwise comparisons. The Student\u0026rsquo;s t-test was used to analyze the differences between two groups. In all cases, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003cp\u003eRegarding microbiota profiling, the raw sequencing data is first subjected to quality control, filtering, and assembly processing to obtain high-quality clean sequences. Subsequently, the DADA2 algorithm was used for denoising to generate high-resolution amplicon sequence variation (ASV). Alpha and beta diversity indices were analyzed systematically. Taxonomic annotation was performed by aligning sequences against the SILVA 138 SSU rRNA database and NCBI 16S RefSeq database (with a confidence threshold set at \u0026ge;\u0026thinsp;0.7), so as to construct species abundance profiles. The Mann-Whitney U test was employed to compare the two sample groups. Linear discriminant analysis effect size (LEfSe) was applied to identify microbial taxa with significant differences in abundance. Additionally, Spearman\u0026rsquo;s rank correlation analysis was used to evaluate the association between bone parameter and the differential microbiota (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Heat stress impairs growth performance and bone characteristics in chickens\u003c/h2\u003e \u003cp\u003eTo evaluate the effects of HS on growth performance and bone parameters in chickens, a 14-day HS model was established (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Feed intake and body weight were recorded during the experimental period, and blood and bone samples were collected at 35 days of age for subsequent analyses. The heterophil-to-lymphocyte ratio (H/L) is a reliable indicator for evaluating HS in poultry. In the current experiment, it was found that the H/L ratio was significantly increased in heat-stressed chickens (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB), indicating the successful establishment of the HS model. Subsequently, Average daily feed intake (ADFI), average daily gain (ADG), and FCR were calculated. The results demonstrated that HS significantly decreased ADFI and ADG, but had no significant effect on FCR (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC, D and E). Serum bone metabolism markers serve as direct indicators of bone turnover. However, due to the lack of poultry-specific commercial kits, only serum Ca, P, and ALP levels were determined in the present study. The results showed that HS did not alter serum Ca and P concentrations, but significantly increased ALP activity (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF, G, and H). Furthermore, the mRNA expression levels of genes associated with osteogenesis and osteoclastogenesis were analyzed by RT‑qPCR. The results revealed that HS only significantly downregulated the relative mRNA expression of RUNX2, with no significant effects on other bone turnover‑related genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eI and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eJ).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMicro‑CT is widely applied to evaluate bone microarchitecture. The results indicated that HS impaired the trabecular microarchitecture of the chicken tibia, as evidenced by significantly decreased bone mineral density, trabecular separation (Tb.Sp), and cortical thickness (Ct.Th), together with a decreasing trend in trabecular thickness (Tb.Th) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA\u0026ndash;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eG). The ash percentage and mineral composition of the tibia were further determined. Similarly, HS significantly reduced tibial ash content, accompanied by a decrease in Ca concentration, whereas no significant changes were observed in P and Mg levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eH\u0026ndash;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eK). Alterations in bone microarchitecture may lead to changes in bone mechanical properties. The results demonstrated that both the breaking load and Young\u0026rsquo;s modulus of the tibia were significantly decreased in heat‑stressed chickens (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eL and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eN). In conclusion, HS impaired growth performance and compromised bone parameters in chickens.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Heat stress induced gut microbiota dysbiosis in chickens\u003c/h2\u003e \u003cp\u003eTo explore the effects of HS on the composition and functional correlations of the chicken gut microbiota, 16S rRNA gene sequencing was conducted on samples from the NC and HS groups. A Venn diagram revealed that 126 amplicon sequence variants (ASVs) were shared between the two groups, with 19 ASVs unique to the NC group and 15 ASVs unique to the HS group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). A bar plot of genus-level community composition displayed distinct structural differences between the NC and HS groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Principal Coordinates Analysis (PCoA) at the ASV level further demonstrated a clear separation between the NC and HS clusters (R\u0026thinsp;=\u0026thinsp;0.2500, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.016), indicating that HS significantly altered the overall gut microbial community structure (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). Analysis of α-diversity indices revealed that HS significantly decreased the Ace and Chao indices compared with the NC group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE), suggesting a marked reduction in gut microbial α-diversity under HS conditions. Linear discriminant analysis effect size (LEfSe) identified differentially abundant taxa between the two groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eH). Follow-up analyses confirmed that \u003cem\u003eGordonibacter\u003c/em\u003e, \u003cem\u003ePeptococcus\u003c/em\u003e, \u003cem\u003eLactobacillus\u003c/em\u003e, and \u003cem\u003eTyzzerella\u003c/em\u003e were significantly enriched in the NC group, while \u003cem\u003eTuricibacter\u003c/em\u003e was significantly more abundant in the HS group at the genus level (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eI\u0026ndash;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eM). A correlation heatmap further revealed significant associations between these differential genera and bone quality parameters. Specifically, \u003cem\u003eLactobacillus and Gordonibacter\u003c/em\u003e were positively correlated with bone ash, whereas \u003cem\u003eTuricibacter\u003c/em\u003e exhibited a significant negative correlation with bone ash. In addition, \u003cem\u003eGordonibacter\u003c/em\u003e was also positively correlated with BMD (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eN). Taken together, these findings indicate that HS causes a significant modification in the composition and function of the gut microbiota in chickens.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.3. FMT-HS induced bone loss in chickens\u003c/h2\u003e \u003cp\u003eTo investigate the causal role of gut microbiota in HS-induced bone loss, we performed FMT in chicks with a regimen of daily gavage from 1 to 10 days of age and weekly gavage from 11 to 35 days of age. The groups included FMT-PBS, FMT-NC, and FMT-HS (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Growth performance revealed no significant differences in ADFI or ADG among the three groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). However, the FCR was significantly elevated in the FMT-HS group compared with the FMT-PBS and FMT-NC groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD), indicating that HS-derived microbiota impaired feed utilization efficiency. Serum levels of Ca, P and ALP showed no significant changes across groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE, \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eG). Additionally, the expression of osteoblast-related gene OPG was significantly downregulated in the FMT-HS group while expression of other osteogenic genes including RUNX2, SP7, ALPL, COL1A1 and BMP2 remained unaltered (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eH). For osteoclast-related genes, the expression of MMP9 was significantly upregulated in the FMT-HS group relative to the FMT-PBS and FMT-NC groups whereas no significant differences were detected in the expression of NFATc1, ACP5, RANK or RANKL (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eI).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eQuantitative micro-CT analysis showed that BMD, BS/TV, Tb.Th, and Ct.Th were comparable between these three groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB, \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC, \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE, and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eG). Tb.N was significantly reduced in the FMT-HS group compared with FMT-NC groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). Tb.Sp tended to be higher in the FMT-HS group, though this difference did not reach statistical significance (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.083) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF). Bone ash and tibial calcium content remained unchanged across all three groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eH and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eI). Biomechanical testing further confirmed compromised bone strength in FMT-HS chickens. Fracture load, bone stiffness, and Young\u0026rsquo;s modulus were significantly lower in the FMT-HS group compared with FMT-PBS and FMT-NC groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eJ\u0026ndash;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eL). These results demonstrate that transplantation of gut microbiota from heat-stressed donors impairs trabecular bone microarchitecture and reduces bone biomechanical strength in recipient chickens, recapitulating the key features of HS-induced bone loss.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e3.4. FMT-HS disrupted intestinal morphology barrier function and mineral absorption in chickens\u003c/h2\u003e \u003cp\u003eTo further explore the mechanisms by which gut microbiota mediates HS-induced skeletal dysfunction, we analyzed intestinal morphology, barrier function, inflammatory status and mineral absorption-related gene expression in FMT chickens. Histological analysis revealed that FMT-HS significantly impaired intestinal structure compared with FMT-PBS and FMT-NC groups. Villus height and villus height to crypt depth ratio (VH/CD) were markedly reduced in the FMT-HS group while crypt depth remained unchanged across groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). Consistent with morphological deterioration, the positive stained area of CaBP-D28K, a key mediator of intestinal calcium absorption, was significantly decreased in the FMT-HS group (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC). Circulating markers of intestinal barrier integrity were also altered. Serum LPS concentration showed no significant differences among groups. Serum DAO and DLA concentration were comparable between FMT-PBS and FMT-NC groups but significantly reduced in the FMT-HS group (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD). In line with these barrier changes mRNA expression of tight junction proteins was differentially affected. Expression of ZO-1 was significantly downregulated in the FMT-HS group while expression of JAM, OCLN and Claudin-1 showed no significant differences among groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE). Pro-inflammatory cytokine expression was enhanced in the FMT-HS group. Relative mRNA levels of IL-1β, IL-6 and TNFα were all significantly upregulated in the FMT-HS group compared with FMT-PBS and FMT-NC groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF). Furthermore, the expression of genes involved in intestinal mineral absorption was suppressed by HS-derived microbiota. The mRNA expression of CaBP-D28K, NCX1, and PMCA1b were significantly lower in the FMT-HS group than in FMT-PBS and FMT-NC groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eG).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e3.5. FMT-HS induced microbial dysbiosis in chickens\u003c/h2\u003e \u003cp\u003eWe next evaluated the impact of FMT-HS on the composition and structure of the gut microbiota in chickens compared with FMT-NC group. A Venn diagram revealed 191 shared ASVs between the FMT-NC and FMT-HS groups. The FMT-NC group harbored 20 unique ASVs while the FMT-HS group contained 30 unique ASVs (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). Genus-level taxonomic profiling showed distinct patterns in the relative abundance of microbial taxa between the two groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB). PCoA at the ASV level displayed a trend toward separation between FMT-NC and FMT-HS communities though this difference did not reach statistical significance (R\u0026thinsp;=\u0026thinsp;0.2259, P\u0026thinsp;=\u0026thinsp;0.069) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC). Analysis of microbial dysbiosis and health indices revealed functional shifts in the microbiota. The Microbial Dysbiosis Index (MDI) was significantly elevated in the FMT-HS group relative to the FMT-NC group while the Gut Microbiota Health Index (GMHI) was significantly reduced (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eD and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eE). No significant differences were detected in α-diversity indices including Simpson, Chao, Shannon, and Ace indices between FMT-NC and FMT-HS groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF\u0026ndash;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eI). LEfSe identified taxa with differential enrichment between groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eJ). Among these \u003cem\u003eTuricibacter\u003c/em\u003e a genus previously linked to bone loss was significantly more abundant in the FMT-HS group than in the FMT-NC group (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eK). These findings indicate that FMT-HS drives functional dysbiosis and enriches specific bone-related taxa without overtly altering overall microbial α-diversity.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eGrowing evidence indicates that gut microbiota regulates bone remodeling through the gut-bone axis[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]; however, whether HS-induced deterioration of bone performance in chickens is associated with intestinal microbiota remains unclear. The present study delineates a critical mechanistic pathway linking HS, a prevalent environmental hazard in intensive poultry production, to skeletal deterioration, with the gut microbiota functioning as a pivotal intermediary. These findings advance understanding of how environmental stressors disrupt host-microbiota homeostasis to compromise distant organ systems, offering novel insights for mitigating HS impacts in agricultural environments.\u003c/p\u003e \u003cp\u003eA fundamental finding of the current study is that FMT-HS recapitulates the bone loss observed in directly HS-challenged chickens, confirming the gut microbiota as a critical functional mediator translating HS exposure into deleterious skeletal outcomes. However, there were no significant changes in either α-diversity or β-diversity indices between FMT-HS and FMT-NC groups, indicating that the overall species richness and structural stability of the microbial community were not markedly affected[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In contrast, FMT-HS induced pronounced functional gut dysbiosis, as evidenced by increased MDI and decreased GMHI. This functional dysbiosis preceded the collapse of the overall ecological structure, suggesting potential alterations in the metabolic activity, gene expression, or strain-level characteristics of key functional bacteria, which in turn mediated host phenotypic changes[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Notably, genus \u003cem\u003eTuricibacter\u003c/em\u003e, which was previously associated with HS-related bone loss in our initial model, was significantly enriched in FMT-HS recipients. The genus \u003cem\u003eTuricibacter\u003c/em\u003e is a key component of the animal gut microbiota and is well known for its close association with bile acid metabolism and host lipid homeostasis[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Although direct evidence supporting a regulatory role of \u003cem\u003eTuricibacter\u003c/em\u003e in bone metabolism is lacking, from the perspective of the liver‑bone axis, altered lipid metabolism may indirectly affect bone remodeling[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. In addition, multiple studies have demonstrated that various bioactive compounds, including Spirulina platensis components[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], grape seed extract[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], and xanthohumol[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], modulate bone metabolism by altering the relative abundance of \u003cem\u003eTuricibacter\u003c/em\u003e. Thus, these findings suggest \u003cem\u003eTuricibacter\u003c/em\u003e as a potential biomarker for HS-induced bone loss, although its mechanistic role remains to be elucidated.\u003c/p\u003e \u003cp\u003eHeat stress-induced gut dysbiosis directly impairs intestinal barrier integrity. The intestinal barrier serves as a critical defense interface between the host and the luminal environment and is essential for preventing the translocation of microbial metabolites and pathogens, which may represent a key step in amplifying the detrimental effects of environmental stressors. The present study demonstrated that FMT-HS markedly disrupted intestinal morphology, as evidenced by decreased villus height and VH/CD ratio. These structural alterations suggest intestinal atrophy, leading to reduced absorptive capacity and compromised epithelial integrity, thereby exacerbating the deleterious effects of heat stress-associated microbiota[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Meanwhile, FMT-HS impaired intestinal barrier function, reflected by altered serum markers of intestinal permeability, including reduced DAO activity and elevated DLA levels, accompanied by downregulated mRNA expression of the tight junction protein ZO-1. Although barrier leakage is known to induce systemic proinflammatory responses that drive bone resorption[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], no significant alterations in serum LPS levels were observed in this FMT study, but only increased intestinal local inflammation, which is inconsistent with previous reports[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. This discrepancy may be attributed to the rapid phagocytosis and inactivation of LPS leaked from the intestine by hepatic Kupffer cells following entry into the portal vein[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], resulting in no significant increase in peripheral blood LPS levels. Instead, local intestinal inflammation induced the release of proinflammatory cytokines such as TNF‑α and IL‑1β via the activation of immune cells and the release of damage‑associated molecular patterns[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. These cytokines promoted osteoclast differentiation and activation[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Consistent with this, the present study revealed that FMT‑HS downregulated the expression of OPG, a decoy receptor for RANKL. The reduction in OPG shifted the RANKL/OPG ratio toward osteoclastogenesis and accelerated bone resorption. Conversely, FMT‑HS significantly upregulated the expression of MMP9, a protease secreted by osteoclasts that plays a critical role in bone matrix degradation; its upregulation further enhanced bone resorption. Similar phenomena have frequently been observed in patients with inflammatory bowel disease[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNotably, FMT-HS-induced gut dysbiosis also impaired intestinal mineral absorption. Bone formation strictly depends on the bioavailability of calcium and phosphorus, and the intestine represents the primary site for mineral absorption. The present study demonstrated that FMT-HS significantly downregulated the expression of key genes involved in intestinal mineral transport, including CaBP-D28K, NCX1, and PMCA1b. Nevertheless, this downregulation did not induce significant alterations in bone ash content or BMD. The organism may maintain the relative stability of bone mineral content and BMD via compensatory regulation of systemic calcium‑phosphorus homeostasis[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Notably, FMT-HS reduced trabecular bone number and impaired bone biomechanical properties. Bone biomechanical characteristics are highly dependent on trabecular number, connectivity, and spatial architecture, and exhibit extreme sensitivity to microstructural damage of trabecular bone[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. The phenomenon whereby FMT-HS induces impaired bone biomechanics without changes in bone mass may be attributed not only to alterations in bone microstructure, but also to variations in the crystallite size, uniformity, and arrangement of bone minerals[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], as well as the structure and integrity of bone collagen[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Accordingly, functional alterations in intestinal barrier integrity, inflammatory status, and mineral absorption directly translated into impaired bone quality in FMT-HS chickens. These findings highlight the complexity of host\u0026ndash;microbiota\u0026ndash;environment interactions, in which heat stress disrupt microbiota function, thereby impairing multiple physiological pathways and ultimately compromising skeletal health.\u003c/p\u003e \u003cp\u003eHS constitutes a major environmental hazard in intensive poultry production, resulting in considerable economic losses and impaired animal welfare. The present study demonstrates that the gut microbiota represents a promising intervention target for alleviating heat stress-induced bone loss, with the potential to improve stress resilience in poultry. Targeted strategies, including suppressing the excessive proliferation of \u003cem\u003eTuricibacter\u003c/em\u003e and employing probiotics, prebiotics, or synbiotics to restore microbial homeostasis, can enhance intestinal barrier function, alleviate inflammatory responses, and improve mineral absorption, thereby attenuating heat stress-induced skeletal damage. Future studies should focus on delineating the specific microbial metabolites (e.g., short-chain fatty acids[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], bile acids[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], polyamines[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]) and signaling pathways that mediate the regulation of the gut\u0026ndash;bone axis under HS.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn conclusion, this study provides definitive causal evidence that gut microbiota dysbiosis acts as a critical mediator of HS-induced bone loss in chickens. We demonstrated that HS reshapes the gut microbiota to induce functional dysbiosis, which in turn impairs intestinal barrier integrity, triggers inflammation response, and suppresses intestinal mineral absorption. These perturbations collectively disrupt bone metabolism, impairing trabecular bone microarchitecture, and reducing biomechanical strength. These findings advance our understanding of the gut-bone axis in the context of environmental stress, offering novel insights for mitigating the adverse impacts of HS in agricultural systems.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eThe current experiment adhered to animal welfare guidelines and experimental protocols established by the Research Ethics Committee of Southwest University. Approval was granted by the Laboratory Animal Management Committee of Southwest University (Protocol No. IACUC-20231023-04).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was financially supported by the National Natural Science Foundation of China (grant number 32402955), the Fundamental Research Funds for the Central Universities (grant number SWU-KQ24004), and the Yunnan Province Science and Technology Talents and Platform Program (Grant 202405AF140106).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank our colleagues at the Joint International Research Laboratory of Animal Health and Animal Food Safety.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eH.G. and S.J. conceived and designed the study. J.G., Y.W., Y.Z., and Z.W. executed the experiment and analyzed tissue samples. J.G. performed the data analysis and generated the figures. H.G., S.J., and R.F. drafted, revised, and reviewed the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eBhatti UA, Bhatti MA, Tang H, Syam MS, Awwad EM, Sharaf M, et al. Global production patterns: Understanding the relationship between greenhouse gas emissions, agriculture greening and climate variability. Environ Res. 2024;245:118049.\u003c/li\u003e\n \u003cli\u003eCramer MN, Gagnon D, Laitano O, Crandall CG. Human temperature regulation under heat stress in health, disease, and injury. Physiol Rev. 2022;102(4):1907-89.\u003c/li\u003e\n \u003cli\u003eGoel A. Heat stress management in poultry. J Anim Physiol Anim Nutr (Berl). 2021;105(6):1136-45.\u003c/li\u003e\n \u003cli\u003eAkanuma S, Nishiguchi H, Ali MFZ, Nagao Y, Miura C, Takizawa T, et al. 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Cell Mol Life Sci. 2025;83(1):38.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"animal-microbiome","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"amic","sideBox":"Learn more about [Animal Microbiome](http://animalmicrobiome.biomedcentral.com)","snPcode":"42523","submissionUrl":"https://submission.nature.com/new-submission/42523/3","title":"Animal Microbiome","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Heat stress, Gut microbiota, Bone health, Poultry, Animal welfare","lastPublishedDoi":"10.21203/rs.3.rs-9395311/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9395311/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHeat stress (HS) is a pervasive environmental hazard in intensive poultry production that severely impairs skeletal health and causes substantial economic losses. While emerging evidence links gut microbiota dysbiosis to bone metabolism, its causal role in mediating HS-induced bone loss remains poorly defined. Here, we established a chicken model of HS and employed fecal microbiota transplantation (FMT) to investigate the mechanistic link between gut microbiota and skeletal deterioration. Our results demonstrated that HS reduced growth performance, disrupted gut microbial community structure, and impaired bone microarchitecture and biomechanical strength. Critically, FMT from HS-exposed donors recapitulated the key features of HS-induced bone loss in recipient chickens, characterized by impaired trabecular bone microarchitecture, reduced biomechanical strength, and enhanced bone resorption-related gene expression. Mechanistically, the HS-microbiota induces functional dysbiosis, characterized by a relative increase in the abundance of the genus \u003cem\u003eTuricibacter\u003c/em\u003e, while compromising intestinal barrier integrity, triggering an inflammatory response, and inhibiting intestinal mineral absorption. Collectively, these factors contribute to reduced bone performance. These findings establish the gut microbiota as a key mediator of HS-induced bone loss, providing a novel mechanistic framework for understanding host\u0026ndash;microbiota\u0026ndash;environment interactions in the context of environmental hazards, which has broader implications for animal health and environmental toxicology.\u003c/p\u003e","manuscriptTitle":"Heat Stress Triggers Bone Performance Degeneration via Impairing Intestinal Barrier Function and Altering Gut Microbiota in Chickens","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-07 16:44:24","doi":"10.21203/rs.3.rs-9395311/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"257221843818818284091868122556773974796","date":"2026-05-11T13:32:09+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-28T17:39:23+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-28T15:53:57+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-14T15:06:05+00:00","index":"","fulltext":""},{"type":"submitted","content":"Animal Microbiome","date":"2026-04-12T15:15:26+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"animal-microbiome","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"amic","sideBox":"Learn more about [Animal Microbiome](http://animalmicrobiome.biomedcentral.com)","snPcode":"42523","submissionUrl":"https://submission.nature.com/new-submission/42523/3","title":"Animal Microbiome","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bb2b4a28-458e-49d6-8a6a-d54c06d339e9","owner":[],"postedDate":"May 7th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"257221843818818284091868122556773974796","date":"2026-05-11T13:32:09+00:00","index":13,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-07T16:44:25+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-07 16:44:24","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9395311","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9395311","identity":"rs-9395311","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}