Campylobacter jejuni strains with different pathogenic potential shapes host-pathogen interactions and gut microbiota dynamics

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Although typically a commensal of the avian gut, it can induce pro-inflammatory responses, damage intestinal integrity and affect broilers’ performance. To understand the host response to Campylobacter infection, ROSS 308 male broiler chickens were experimentally infected at 21 days of age with three C. jejuni strains of different pathogenic potential (potentially benign, potentially harmful and invasive). An unchallenged group served as control. Results After infection, feed conversion rate was significantly impaired by 3% in groups infected with the harmful and invasive strains. At 2-, 7- and 14-days post-infection (dpi), 10 birds per group were euthanized for Campylobacter isolation, evaluation of immune response, intestinal morphometry, microbiota composition and determination of short chain fatty acids. C. jejuni was recovered from all caeca samples from all infected groups and timepoints except for one infected bird at 2 dpi. At 7 dpi significant increase was observed in interferon gamma gene expression in chickens infected with the harmful and invasive strains, while bile secretory immunoglobulin A levels were elevated in all challenged groups. At this timepoint, chickens infected with harmful and invasive strains showed a reduced villus height:crypt depth ratio. Microbiota analysis revealed reduced α-diversity in infected birds, especially at 2 dpi. β-diversity showed distinct microbial clustering between control and infected groups at early timepoints, confirming infection-driven dysbiosis. Several differentially abundant genera were identified at early timepoints including enrichment of Faecalibacterium in controls, higher abundance of an unclassified Rikenellaceae genus in benign and invasive infected groups, and increased Clostridiales taxa at later timepoints in harmful and invasive infected groups. At early timepoints, infected chickens showed reduced butyrate and formate levels, along with increased lactate and succinate accumulation, particularly in chickens infected with the invasive strain. These metabolic changes reflect functional shifts in microbial activity associated with dysbiosis. Conclusions These results underscore the strain-specific pathogenic potential of C. jejuni in broilers, ranging from gut commensals to disruptors of intestinal integrity, highlighting the need for in-depth studies of Campylobacter biology for targeted control strategies, to improve animal health and control its spread to humans. Campylobacter immune response intestinal health gut microbiota SCFA Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Introduction Campylobacter jejuni is the leading, extensively prevalent, and widespread cause of human gastroenteritis worldwide, with broiler chicken identified as the most relevant reservoir for transmission to humans through contaminated chicken meat (EFSA & ECDC, 2024). The incidence of campylobacteriosis has escalated both in developed and in low- and middle-income countries (Havelaar et al., 2015 ) and has been the most frequently reported zoonosis in humans across the EU since the beginning of EU surveillance in 2007 (EFSA & ECDC, 2024). For years, C. jejuni has been considered an asymptomatic commensal in chickens, with no negative impact on their health. Recently, several researcher groups have explored whether Campylobacter functions as a commensal organism or a pathogen in chicken. (Wigley, 2015 ). The host-pathogen interaction between C. jejuni and the avian host involves a complex response that can differ according to the strain characteristics and the host genetics (Chaloner et al., 2014 ). Some strains have shown a highly invasive and virulent phenotype, with capacity for hepatic dissemination which represents both a productive and sanitary risk (Humphrey et al., 2015 ). In contrast to humans, chickens are known to carry high C. jejuni loads in their intestines (up to 10 9 CFU/g of cecal content) (Beery et al., 1988). It has long been recognized that C. jejuni rapidly colonizes the intestinal tract of broiler chickens following exposure. Shanker et al., ( 1988 ) showed that 88% of experimentally infected chicks exhibited cecal colonization within 3 days post-infection, regardless of the age of exposure. Similarly, Connerton et al., ( 2018 ) reported complete cecal colonization of 20-day-old broilers infected with C. jejuni after 2 days of infection, with average counts reaching approximately 10 6 CFU/g and persisting throughout the study period. Fast dissemination has also been reported in experimental infections where broiler chickens challenged with different C. jejuni strains were put in contact with uninfected birds (Chaloner et al., 2014 ), simulating natural conditions. Several studies have investigated the immune response of broiler chickens to C. jejuni colonization (Mortada et al., 2021 ), mostly without considering the varying pathogenic potential among different strains (Hermans et al., 2011 b). Understanding these host-pathogen interactions is crucial for improving animal health and mitigating the risk of transmission to humans. C. jejuni infection can activate the expression of pro-inflammatory interleukin (IL)-1β, IL-6, IL-17A and interferon gamma (IFN)-γ, and anti-inflammatory (IL-10) cytokines, and transforming growth factor (TGF-β). All of them have been documented as important cytokines against pathogen infection and colonization (Mortada et al., 2021 ; Reid et al., 2016 ) and regulation of intestinal inflammatory dynamics which can influence bacterial colonization (Taha-Abdelaziz et al., 2020 ). In parallel, the production of secretory immunoglobulin A (sIgA) represents a fundamental adaptative line of defense in the intestinal mucosa, whose role against C. jejuni is not yet fully elucidated. Moreover, its efficacy may depend on multiple factors such as post-infection time and the immune maturation of the host (Lacharme-Lora et al., 2017 ). C. jejuni infection may also be associated (strain-dependent), with structural modifications of the intestinal epithelium, such as reduced villus height (VH) and increased crypt depth (CD), which can compromise the absorptive capacity and physical barrier of the intestine (Awad et al., 2015). These changes can also occur in parallel with one of the most prominent effects of infection, the intestinal dysbiosis. The establishment of a normal and healthy microbiota constitutes an important component of gut health, and has implications for proper development and maturation of the immune system and for the correct poultry nutrition (Oakley et al., 2014 ). Several studies have explored how C. jejuni infection perturbs the chicken gut microbiota, revealing potential consequences for host health (Oakley & Kogut, 2016 ; Hankel et al., 2019 ; Valečková et al., 2023 ). Intestinal dysbiosis is characterized by the loss of beneficial microorganisms, reducing microbial diversity and displacing beneficial bacteria, which in turn can lead to an alteration in the production of certain short-chain fatty acids (SCFA). Particularly acetate and butyrate, that are critical for immune homeostasis, epithelial health and maintaining the intestinal barrier integrity (Al Hakeem et al., 2024 ; Connerton et al., 2018 ). Despite the progress in understanding the biology of Campylobacter , important key knowledge gaps still remain, such as the host response to infection with strains of C. jejuni with different pathogenic potential (non-invasive vs. invasive strains). In this context, the present study aimed to comprehensively evaluate and analyze the immune and intestinal response of broiler chickens infected with C. jejuni strains with different pathogenic potential. Thus, C. jejuni excretion, expression of cytokines in cecal tonsils, quantification of secretory IgA in bile, and changes in the intestinal morphology, in microbiota composition and SCFA production were analyzed. This multidimensional approach will allow a better understanding of the mechanisms underlying the C. jejuni -host interaction, aiming to provide key information for control strategies in poultry production, relevant both to bird health and welfare, and to food safety. Materials and methods Bacterial strains and culture conditions Three different C. jejuni strains were used in the challenge study. Two cecal strains: one strain potentially benign, recovered from a flock with low feed conversion rate (FCR) and one strain potentially harmful, recovered from a flock with high FCR. The third strain was an invasive one isolated from internal tissue liver. The strains were selected from our own strain collection for which we have performance and health data from the flocks where cecal isolates have been recovered. Hence, cecal C. jejuni isolates from flocks in the top and bottom 25% in terms of performance (FCR) were initially selected as potentially harmful and benign strains. Selection criteria were also based on the invasiveness potential and the presence or absence of genetic features potentially associated with host interaction, and colonization. Bacteria were grown on Columbia blood agar (BioMerieux, Marcy l’Etoile, France) for 48 h at 37°C under microaerobic conditions from stocks maintained in brain heart infusion broth (BHI, Merck KGaA, Darmstadt, Germany) with 20% glycerol at -75°C. Experimental design All work was conducted in accordance with proper veterinary practices, in accordance with European (Directive 2010/63/EU) and Spanish (Real Decreto 53/2013) regulation. The study was conducted with prior approval of the Animal Experimentation Committee of the Institution and the Catalan Government (Protocol number 11213). One-day-old Ross 308 chicks were obtained from a commercial hatchery. All animals were checked twice daily to ensure their health and welfare. Chicks were randomly distributed in 4 experimental groups: a control uninfected group and three challenged groups, each infected with one of the above-mentioned C. jejuni strains (benign, harmful, invasive). For simplicity, throughout the manuscript, the groups will be referred to as Group C (Control group), Group B (challenged with the benign strain), Group H (challenged with the harmful strain), and Group I (challenged with the invasive strain). Each group with 100 birds each was allocated in independent rooms and maintained in floor pens. Birds were distributed in 5 pens per group, with 20 birds per pen. Chicks were reared under farm conditions, at a temperature of 30°C, which was gradually reduced to 20°C when the birds were 3 weeks of age. Strict biosecurity measures were taken to avoid cross-contamination among rooms. Prior to the experimental infection, regular monitoring of the farm was conducted to ensure that all housing units remained free of Campylobacter contamination. Weekly sampling was performed using boot socks, which were collected from all rooms and corridors of the facility; these samples were analyzed by PCR to confirm the absence of Campylobacter spp. At 3 weeks of age, all birds were confirmed as Campylobacter free prior to the experimental infection by collecting cloacal swabs from each individual which were streaked onto modified Charcoal Cefoperozone Deoxycholate agar plates (mCCDA, CM739 with selective supplement, SR0155E; Oxoid, Basingstoke, UK). Animals were challenged at 21 days of age with the corresponding strain and from this date onwards, the boot socks monitoring was maintained exclusively for the control group (unchallenged birds) to verify continued absence of Campylobacter throughout the study. Challenge was performed by oral gavage with 1 ml of an inoculum containing 10 5 CFU/ml in saline solution for each strain. Control group was administered only with saline solution. Sample collection Performance parameters were assessed weekly (on days 7, 14, 21, 28 and 35): body weight (BW), daily gain (DG), daily feed intake (DFI) and FCR. On days 2, 7, and 14 post infection (dpi) two animals per pen were randomly euthanized. Samples of cecal content, liver, ileum tissue, cecal tonsils, and bile were collected. Cecal content and liver samples for Campylobacter determination were stored refrigerated and processed within 24h of collection. An aliquot of cecal content for SCFA analysis was placed in tubes placed in dry ice and stored frozen until analysis. Another aliquot of cecal content for intestinal microbiota analysis was placed in tubes containing 3 ml of ethanol (96%) (1:3 cecal content:ethanol) and stored refrigerated until further processing. Cecal tonsils samples for RNA extraction were preserved frozen (-75ºC) in RNA later until analysis of cytokine expression. Bile samples for sIgA determination were also kept frozen (-75ºC) until analysis. Samples of ileum for histological analysis were preserved in buffered formaline. C. jejuni determination Assessment of C. jejuni in the intestine was performed by bacterial isolation from the cecal content by conventional culture methods using mCCDA agar (Urdaneta et al., 2015 ). C. jejuni isolation from the internal liver tissue was attempted from a 2 g portion of internal tissue aseptically collected (surface sanitized by searing with a flame-sterilized spatula); 1 g was homogenized and mixed with 5 ml of Buffered Peptone Water (BPW) for direct plating onto mCCDA. The remaining 1 g was subjected to pre-enrichment in 3 ml of Bolton broth (Oxoid CM0983 supplemented with SR0183E and laked horse blood SR0048C), and subsequently, 100 µl of the enriched sample was streaked onto mCCDA. Presumptive colonies from mCCDA plates from caeca and liver samples were subcultured onto blood agar plates for 48h at 37ºC in microaerophilic conditions. Isolates were preserved in BHI (Merck KGaA, Darmstadt, Germany) with 20% glycerol at -75ºC for further analyses. Immune response characterization Expression of pro- (e.g. interleukin-1β, IL-6, IFN-γ and IL-17A) and anti-inflammatory cytokines (e.g. IL-10) in cecal tonsils was performed by real-time quantitative reverse transcription-PCR (qRT-PCR). Total RNA was extracted from 20 mg of tissue using RNeasy Mini Kit (QIAGEN, Hilden, Germany) according to the manufacturer’s instructions. The pollutant DNA was digested with RNase-free DNase Set (QIAGEN) and RNA was eluted with 50 µl of water RNase free and preserved at -75ºC. The quantity and quality of RNA was determined with Biodrop spectrophotometer (Thermofisher). Expression of mRNA was measured by qPCR, using the EXPRESS One-Step SYBR GreenER kit (QIAGEN, CA, USA) according to the manufacturer’s protocol. Previously described primers for IFNγ (Carvajal et al., 2008 ), IL-1β, IL-6, IL-10 (Fasina et al., 2008 ; Smith et al., 2005 ) and IL-17A (Reid et al., 2016 ) were used. Beta actin (ACTB) was used as the housekeeping gene, for which the following primers were used: ACTB_FW (5’-CCAGACATCAGGGTGTGATGG-3’) and ACTB_RV (5’-CTCCATATCATCCCAGTTGGTGA-3’). Amplification and detection of specific products were performed using 7500 Fast Real-Time PCR system and 7500 software version 2.3 (Applied Biosystems, CA, USA) with the following conditions: cDNA synthesis at 50°C for 5 min, followed by initial denaturation at 95°C for 20 s, and 40 cycles of denaturation at 95°C for 3 s and annealing/extension at 60°C for 30 s. Expression of each target gene was determined using the cycle threshold (CT) value relative to that for the ACTB reference gene (ΔCT). Results are expressed as fold changes in corrected target gene expression (ΔCT) in infected animals relative to the control animals (2 −ΔΔCT ). The concentration of sIgA from bile samples was determined by ELISA (Bethyl Laboratories Inc., Montgomery, TX, USA) following the manufacturer instructions. Intestinal morphometry Intestinal ileum tissue samples were fixed in 10% buffered formalin and then dehydrated and embedded in paraffin. The samples were sectioned with a microtome and stained with Periodic acid Schiff (PAS). The villus height (VH) and crypt depth (CD) were measured using a light microscope with a linear ocular micrometer (Olympus 209-35040) and the VH:CD ratio was calculated. SCFA production Cecal content samples from 2, 7 and 14 dpi were analyzed for acetate, formate, propionate, butyrate, isobutyrate, valerate, isovalerate, lactate and succinate using gas chromatography with flame ionization detection (GC-FID). The analytical procedure was performed following an internal procedure based on the classical method described by Jouany ( 1982 ). Final SCFA concentrations were expressed as µmol/g cecal content. Statistical analysis Performance data were analyzed using a one-way analysis of variance (ANOVA) to evaluate the effect of the experimental challenge on BW, ADG, ADFI, and FCR. Least Squares Means (LSMeans) and their standard error (SEM) were calculated for each group. Statistical significance was considered at p ≤ 0.05. The analysis was performed using R software (version 3.6.3). To assess differences in intestinal morphometric parameters and immunological parameters (cytokines and sIgA) among the four experimental groups, a one-way analysis of variance (ANOVA) was conducted. When significant effects were detected (p ≤ 0.05), pairwise group comparisons were carried out using Tukey’s Honestly Significant Difference (HSD) post-hoc test; statistical significance for this test was also set at p ≤ 0.05. The analysis was performed using R software (version 3.6.3). Significant differences in the SCFA concentrations among groups were analyzed using one-way ANOVA to strain effects for each SCFA at each time point using SAS 9.4 software. Moreover, Spearman correlation analysis was performed to assess the association between SCFA concentrations and the relative abundance (log-transformed) of bacterial genera previously identified as differentially abundant. Correlations coefficients (ρ) and p-values were calculated using the cor.test() function in R (version 3.6.3) with the Spearman method, which does not assume normality. Benjamini–Hochberg correction was applied to control the false discovery rate (FDR), with significance defined as p ≤ 0.05 and trends as 0.05 < p ≤ 0.10. Results were visualized as a heatmap (pheatmap package, (Kolde, 2025 )), displaying ρ values and coloured gradients to indicate the strength and direction of associations. Microbiota analysis Total DNA was extracted from caecum contents using the QIAamp DNA Stool Mini Kit (Qiagen, West Sussex, UK). Metagenomics analysis was used to determine the impact of infection with the different C. jejuni strains on the gut microbiome and to compare the microbiome of Campylobacter -positive and -negative birds. The microbial communities were characterized through amplification and high-throughput sequencing of the V3–V4 variable regions of the 16S rRNA gene (Caporaso et al., 2010 ). This variable region has proven to produce a more detailed composition than others for microbial diversity and community composition analysis of cecal microbiota (Pandit et al., 2018 ). Sequencing was performed with Illumina MiSeq pair-end 2X250 bp sequencing following the manufacturer’s instructions (MS-102-2003 MiSeq® Reagent Kit v2, 500 cycle). Sequencing services were outsourced to Microomics Systems S.L. (Barcelona, Spain). The analysis of the 16S rRNA gene amplicons was performed using Quantitative Insights into Microbial Ecology (QIIME) 2 software package vs 2022.11 (Bolyen et al., 2019 ). Alpha diversity was estimated using different metrics: Shannon index (Shannon & Weaver, 1949 ), Chao index (Chao, 1984 ) and Simpson Index (Simpson, 1949 ). Richness was evaluated using Observed Features. Different beta diversity metrics were used to assess the diversity across the samples, both quantitatively using Bray Curtis dissimilarity index (Bray & Curtis, 1957 ) and qualitatively with Jaccard similarity coefficient (Jaccard, 1908 ). These distance matrices were used to perform Principal Coordinate Analysis (PCoA) using core-metrics plugin and a PERMANOVA was conducted to estimate the significance of group clustering. To extract the percentage of variations explained by each metadata column (effect size), the Adonis function from Vegan package (Oksanen et al., 2020 ) was performed on every distance matrix. Confidence ellipses (95%) were generated using a multivariate t-distribution (stat_ellipse(type = "t", level = 0.95)) in R (v3.6.3.) to visualize group-level clustering and dispersion. Taxonomic assignment of amplicon sequence variants (ASV) was performed using a scikit-learn naïve Bayes classifier implemented in QIIME2, previously trained on the V3-V4 region from 16S rRNA gene and the Greengenes database (13.8 version) clustered at 99% identity (McDonald et al., 2012 ). Differential abundance analysis at both amplicon sequence variant level and collapsed at different taxonomic levels was performed using the Analysis of composition of microbiomes with bias correction (ANCOM-BC) (Lin & Peddada, 2020 ), performed at each timepoint among all the groups. For data visualization, Rstudio (Version 3.6.3; R Core Team, 2020 ), ggplot2 (Wickham, 2009 ) and tidyverse (Wickham et al., 2019 ) packages were used. Results Genetic differences among C. jejuni strains used for experimental infection The three C. jejuni strains used in this study were selected to represent a different pathogenic potential and belong to different MLST ST and CC: benign (ST883, CC21), harmful (ST572, CC206) and invasive (ST48, CC48). Previous whole-genome sequencing analysis (data not shown) revealed that all three strains harbored nearly all analyzed virulence-associated genes, with minor differences. Hence, few virulence genes where differentially distributed among the strains: the harmful and invasive strains carried the neuA1 and the hddC virulence-associated genes. Also, accessory genes analysis revealed that the three strains clustered separately, with each cluster displaying a distinct accessory gene profile. The benign strain exhibited a broader repertoire of metabolic and surface structure genes, while harmful strain encoded functions associated with motility and nutrient acquisition, and the invasive strain carried genes linked to oxidative stress, DNA repair and immune evasion. Campylobacter isolation C. jejuni was recovered from cecal samples from all but one infected bird at 2 dpi and from all sampled birds at 7 and 14 dpi. It was also recovered from internal tissue liver in up to 3 birds per infected group at different time points. All unchallenged birds were negative at all time points for both kind of samples. Performance parameters Before infection, non-significant differences in BW, DG, DFI and FCR were detected among groups (FCR within ± 0.5% of group C = 1.314) (Table 1 ). Statistically significant differences among groups at 35 days of life were observed for the FCR, with no differences for the other variables (Table 2 ). FCR was significantly impaired by 3% in groups H and I (1.642 and 1.643, respectively) compared to group C (1.599), with no significant differences between group C (1.599) and group B (1.606). Table 1 Performance variables before infection (1 to 21 days of life). Values are means. Control Benign Harmful Invasive SEM P-value BW d21 877 885 911 892 16.8 0.543 ADG 39.9 40.3 41.5 40.6 0.80 0.543 ADFI 52.4 52.7 54.8 53.0 0.95 0.297 FCR 1.314 1.309 1.321 1.307 0.0089 0.680 a BW: Average body weight (g; initial BW 39.8g), ADG: Average daily gain (g), ADFI: average daily feed intake (g), FCR: feed conversion ratio (kg feed/kg weight gain) Table 2 Performance variables post infection (22 to 35 days of life). Values are means. Control Benign Harmful Invasive SEM P-value BW d22 a 877 885 911 892 16.8 0.543 BW d35 2168 2183 2231 2214 44.9 0.760 ADG 91.7 92.7 94.3 94.5 2.25 0.813 ADFI 146.5 149.0 154.9 155.2 4.04 0.393 FCR 1.599 b 1.606 b 1.642 c 1.643 c 0.0118 0.037 a BW: Average body weight (g), ADG: Average daily gain (g), ADFI: average daily feed intake (g), FCR: feed conversion ratio (kg feed/kg weight gain) b,c Different letters mean significant differences among groups. Cytokine gene expression Significant differences in IFNγ gene expression were observed at 7 dpi in chickens infected with invasive (~ 12-fold higher) and harmful (~ 8-fold higher) strains compared to group C (Fig. 1 ). In contrast, the same groups showed numerically down regulation or marginal IL6 gene expression on that same day. sIgA quantification sIgA levels in bile were studied at 2, 7, and 14 dpi (Fig. 2 ). Across all experimental groups there was a time-dependent increase in the total sIgA levels. No statistically significant differences were found at 2dpi. Post-hoc analysis with Tukey’s test revealed that group B had higher titters at 7 dpi compared to group C (p = 0.004) and group I (p = 0.016). Moreover, at 14 dpi, group C had higher titters compared to group B (p = 0.004). Changes in intestinal morphology The intestinal integrity of the ileum samples at 7 and 14 dpi was evaluated (Table 3 ). At 7 dpi, the VH, CD and VH:CD ratio were significantly different among experimental groups (p < 0.05). Post-hoc analysis with Tukey’s test revealed significant higher VH:CD ratios in the group C compared to both the groups H (p = 0.0475) and I (p = 0.0117) (Fig. 3 ). No significant differences at 14 dpi among experimental groups were observed (p = 0.668). Table 3 Mean values of intestinal morphometric parameters, villus height (VH), crypt depth (CD) and VH:CD ratio, at 7 and 14 dpi. 7 dpi Control Benign Harmful Invasive SEM P-value VH (µm) 523 b 620 a 548 b 594 ab 23.7 0.0377 CD (µm) 108 b 140 a 136 ab 156 a 7.54 0.0021 VH:CD 4.848 a 4.526 ab 4.073 b 3.910 b 0.2 0.0089 14 dpi Control Benign Harmful Invasive SEM P-value VH (µm) 523 557 583 580 16.8 0.203 CD (µm) 117 128 134 143 6.08 0.087 VH:CD 4.537 4.369 4.460 4.144 0.28 0.668 a,b Different letters mean statistically significant differences among groups. Microbiota α-diversity and β-diversity The microbiota composition of the caecum was analyzed at 2-, 7- and 14-dpi. The α-diversity was longitudinally evaluated in each group through Shannon’s and Simpson’s indexes. Results for Shannon’s index are shown in Fig. 4 . Overall, all infected groups exhibited a different and disturbed microbiota composition compared to group C (p = 0.04), with the strongest alterations observed at early time points (Fig. 4 ). At 2 dpi, the lowest and the most unbalanced diversity was found in group B, being dominated by few genera and significantly different when compared with C (p = 0.016) and H (p = 0.047) groups. Also, the microbial diversity in group H was lower than in group C (p = 0.047). At 7 and 14 dpi there were no significant differences among groups (p = 0.37 and p = 0.65, respectively), but a generalized decreased tendency of α-diversity at 7 dpi was observed in all groups, with group H showing the lowest median (Fig. 4 ). β-diversity analyses using quantitative (Bray-Curtis) and qualitative (Jaccard) metrics revealed temporal and group-specific differences in microbial community composition (Fig. 5 ). At 2 dpi, both analyses demonstrated that infected groups clustered apart from the control when considered altogether (Adonis R 2 = 0.31, p = 0.001). This indicates that the 31% of the differences in community structure could be explained by the infection status. Pairwise comparisons showed that group B displayed the most distinct microbiota composition compared to the control, particularly in qualitative terms (Jaccard), while group I also differed significantly ( p = 0.026). In contrast, group H did not differ significantly from the control ( p = 0.108), suggesting a milder community shift. At 7 dpi, significant differences among groups persisted (Adonis R² = 0.24, p = 0.009), although the overall clustering pattern indicated a partial convergence between infected and control birds, suggesting a progressive recovery of microbial community structure. Even at 14 dpi, both analyses revealed significant differences between the microbiota composition of the infected groups and group C (p < 0.05), as illustrated in the PCoA plot (Fig. 5 ), indicating that microbial reorganization and strain-dependent dysbiosis persisted throughout the study period. However, the separation among infected groups became less distinct. Differential abundance analysis ANCOM-BC was used to identify significant taxonomic shifts at both genus and ASV levels across groups and time points (Fig. 6 ). We focused on reporting those taxa with known relevance to gut health, fermentative function, or Campylobacter -associated dysbiosis. Longitudinally, the microbial changes were different among groups. Group C maintained a relatively stable microbial composition throughout the study, with few taxa showing significant changes. In contrast, infected groups (B, H and I) exhibited more pronounced and dynamic alterations, particularly at 7 dpi. Focusing on the effect of the infection, we observed that Campylobacter showed a marked and consistent pattern across infected groups, while it remained undetectable in group C throughout all study. At 2 dpi, the relative abundance of this genus was significantly higher in groups B and H, being also detected in group I, though at lower abundance. At 7 dpi, Campylobacter persisted in all infected groups, maintaining its highest relative abundance in group B. By 14 dpi, reduced Campylobacter levels were observed, compared to earlier time points in all infected groups (Fig. 6 ). We analyzed the differentially abundant genera among the different groups at each time point. Overall, infected groups showed reduced relative abundances of genera within Firmicutes such as Ruminococcus , Faecalibacterium, Oscillospira and Coprobacillus , compared to group C. At 2 dpi, an unclassified genus from Rikenellaceae family was undetectable in group C, nearly absent in group H, while being highly enriched in groups B and I. At 7 dpi, group-specific differences emerged: Enterococcus was more abundant in groups C and H, with lower abundance in group I but absent in B; Bifidobacterium was more abundant in groups I and C; whereas Bacteroides showed a high relative abundance in groups B and H. At 14 dpi, several unclassified Clostridiales , such as an unclassified genus from Mogibacteriaceae family, together with Subdoligranulum genus showed higher abundances in groups H and I. Additionally, Butyricicoccus showed higher relative abundances in the I group; Bilophila appeared exclusively in group H and Coprobacillus showed a higher abundance in group H. We also performed the differential abundance analysis at ASV level. At 2 dpi, two specific ASVs classified as Lactobacillus were detected as differentially abundant, with the highest relative abundance observed in group B and in very low abundance in group C. At 7 dpi, a specific ASV classified as Oscillospira was detected in group B and C, with highest relative abundance in group C. Additionally, multiple ASVs classified as Bacteroides fragilis were differentially abundant across groups, with the most pronounced observed in group B, followed by C and H, being absent in group I. At 14 dpi, different ASVs, including Bacteroides, Ruminococcus, Faecalibacterium, Blautia and Bacteroides fragilis were identified. Faecalibacterium prausnitzii was more abundant in group B, followed by H and C, while completely absent in group I. In contrast, Butyricicoccus pullicaecorum and Ruminococcus were predominantly detected in group I, with minimal representation in the others. Notably, Bacteroides fragilis remained absent in group I, but was consistently present in all other groups, most prominently in B. ASVs assigned to Blautia and Anaerofustis also appeared uniquely or more abundantly in group I, further supporting a strain-specific microbial signature that persists through late-stages of infection. SCFA in cecal contents The concentrations of SCFA in cecal contents at days 2, 7 and 14 dpi were quantified in the four experimental groups. The mean results obtained (µmol/g) for each metabolite are presented in Table 4 and in Fig. 7 only those SCFA which showed statistically significant differences between groups are presented. The cecal concentration of SCFAs varied over time post-infection, and the pattern differed for each fatty acid. At 2 dpi, formate levels were markedly higher in group C (911 µmol/g) compared to the infected groups (30.8–143.5 µmol/g; p < 0.001). Isobutyrate was significantly higher in group C (p = 0.017). Acetate showed numerically higher concentrations at group C and B compared to group H and I. Lactate and succinate accumulated in infected groups, particularly in the group H and I (lactate: 8–9 µmol/g; succinate: 18.5–32.6 µmol/g), while remaining low in C. At 7 dpi, formate increased in infected groups (245–270 µmol/g) and dropped in group C (14.6 µmol/g). Acetate was lower in group I compared to group H. Propionate showed a numerically increase in infected groups. Butyrate remained similar across all groups except for group I, which showed the lowest level. Lactate and succinate decreased across H and I groups. At 14 dpi, SCFA levels largely stabilized. Group C retained higher acetate (60.5 µmol/g). Propionate increased in all groups compared to previous dpi. Succinate remained elevated only in group I (10.6 µmol/g; p = 0.025), opposite to the other groups. Correlation between SCFA concentrations and microbiota composition Spearman correlation analysis revealed no statistically significant associations after adjustment for multiple comparisons (q > 0.10 for all correlations) at any timepoint. However, several moderate correlations with unadjusted p-values below 0.05 were observed and may reflect biologically relevant patterns between cecal SCFA concentrations and the relative abundance (log-transformed) of specific bacterial genera in the different infected groups (Fig. 8 ). In group C, Butyricicoccus was positively correlated with butyrate (ρ 0.65). Sphingomonas exhibited a positive association with lactate (ρ 0.65). On the contrary, a strong negative correlation was identified between Lactobacillus presence and lactate (ρ -0.73) showing that higher lactate accumulation was associated with lower abundance of Lactobacillus genus. For propionate, Pelomonas showed a moderate positive correlation (ρ 0.69), while Blautia was negatively correlated (ρ -0.67). In group B, several taxa exhibited significant correlations with SCFAs. Some positive correlations were observed between Rikenellaceae and butyrate (ρ 0.65), Dorea and succinate (ρ 0.61), Mogibacteriaceae with propionate (ρ 0.53) and Faecalibacterium and valerate (ρ 0.74). In contrast, negative correlations were also observed, particularly between Campylobacter and isovalerate (ρ -0.56) and between Faecalibacterium and succinate (ρ -0.57). In group H notably, positive correlations were observed between Clostridium and multiple SCFAs (e.g., propionate (ρ 0.72) and valerate (ρ 0.68)), as well as Bifidobacterium with lactate (ρ 0.65) and Sphingomonas with valerate (ρ 0.75). Negative associations were noted for Campylobacter , particularly with acetate (ρ -0.67) and propionate (ρ -0.59). Finally, in group I, positive correlations were observed between Bifidobacterium and formate (ρ 0.54), as well as Bacteroides and isobutyrate (ρ 0.65). Valerate was positively correlated with Subdoligranulum (ρ 0.57). In contrast, negative correlations were identified for an unclassified Lachnospiraceae genus and Bacteroides with acetate (ρ -0.52, -0.53). Campylobacter also showed a negative correlation with isovalerate (ρ -0.43). Additionally, Bacteroides also correlated negatively with butyrate (ρ -0.62), lactate (ρ -0.64) and succinate (ρ -0.74). Table 4 Concentrations (µmol/g) of SCFA in cecal contents at days 2, 7 and 14 post infection (dpi) in each experimental group. Benign: infected group with the benign strain; Harmful: infected group with the harmful strain; Invasive: infected group with the liver strain. Means obtained for each experimental group and metabolite are shown. Different letters mean significant differences among groups for each SCFA and day. 2 dpi 7 dpi 14 dpi Control Benign Harmful Invasive Control Benign Harmful Invasive Control Benign Harmful Invasive Acetate 56.2 58.7 44.3 37.9 51 ab 47.2 b 58.5 a 41.9 b 60.5 46.7 55.6 43.8 Butyrate 11.9 13.3 10.2 11 14.2 14 14.3 8.7 11.6 12.5 13.1 9.2 Formate 911 a 143.5 b 33.4 b 30.8 b 14.6 245.2 270.1 261.1 23.3 38.4 18.3 19.7 Isobutyrate 1.3 a 0.4 b 0.5 b 0.3 b 0.35 b 0.27 b 0.44 ab 0.63 a 0.8 0.4 0.5 0.9 Isovalerate 0.54 a 0.21 b 0.59 a 0.19 b 0.15 b 0.21 b 0.31 a 0.15 b 0.14 0.23 0.36 0.23 Lactate 0.1 0.4 8.9 8.2 1.4 1.7 0.7 0.3 0.2 0.6 0.7 0.7 Propionate 2.1 3.2 2.9 3.3 1.8 4.2 5 5.2 6 6.7 6.3 5.8 Succinate 11.5 b 8.7 b 18.5 ab 32.6 a 7 3.7 4.1 8.8 2.1 b 2.6 b 2.6 b 10.6 a Valerate 0.6 0.3 0.2 0.3 0.4 0.4 0.3 0.5 0.7 0.6 0.7 0.6 Discussion The present study provides a multidimensional view of the effects of C. jejuni infection in broilers, evaluating the impact of three C. jejuni strains with different pathogenic potential on performance, immune response, intestinal morphometry, cecal microbiota composition, and SCFA production. The three strains were selected from a subset of strains from our strain collection, after an initial grouping of these strains as benign, harmful or invasive. The benign strain was isolated from a flock with low FCR and overall good performance, suggesting commensal behavior. In contrast, the potentially harmful strain was recovered from a high-FCR flock showing poor productivity, supporting a possible adverse or negative implication for bird health. The invasive strain was isolated from the internal liver tissue, indicative of its capacity for translocation outside the gut. Genomic data of the subset of strains from each group (data not shown) were used for the final selection of the three strains used in the experimental infection, based on the presence or absence of virulence-associated genes and accessory genes. The harmful strain was the only one carrying the maf4 gene, which is thought to enhance persistence and immune evasion in poultry contexts (Van Alphen et al., 2008 ). Both the harmful and invasive strains carried the neuA1 gene, involved in sialylation of surface structures, which may facilitate immune evasion and have been associated with post-infectious sequelae like Guillain-Barré syndrome (A. Karlyshev et al., 2005 ). They also shared the hddC gene, crucial for heptose biosynthesis within the capsular polysaccharide (A. V. Karlyshev et al., 2005 ). Accessory genome analysis further reinforced the functional divergence among the strains. The benign strain stood out for functions suggestive of metabolic adaptability and stable colonization, the harmful strain for elements linked to competitiveness and host impact, and the invasive isolate for genes potentially enhancing stress tolerance and extraintestinal survival. According to the data published in the PubMLST database, all three C. jejuni strains belong to ST and CC which have been predominantly isolated from human samples (ranging from 47% to 84% of records), followed by chicken-related sources (from 6% to 24% of records). C. jejuni established rapidly and persistently in the caeca in experimentally challenged birds and was recovered from all but one infected bird by 2 dpi and from all sampled birds at 7 and 14 dpi; occasional translocation to the liver occurred in up to three birds per group. These findings mirror earlier work demonstrating that oral challenge reliably induces consistent cecal carriage by 2 or 3 weeks of age (Awad et al., 2016 ; Connerton et al., 2018 ), with sporadic extraintestinal spread under certain strain and host conditions. Broilers infected with the harmful and invasive strains exhibited a FCR impairment at 14 dpi, whereas the benign strain had no measurable effect. This lower feed efficiency aligns with previous studies reporting that subclinical C. jejuni infection can produce moderate performance deficits via compromised nutrient absorption secondary to mucosal damage (Awad et al., 2016 ; Naseri et al., 2012). Previous studies showed the chicken immune system being inefficiently activated, allowing high-level, asymptomatic colonization, which contributed to the persistence of Campylobacter colonization (Hermans et al., 2011 ; Meade et al., 2009 ). Our finding of a 8–12‐fold surge in cecal IFN-γ expression at 7 dpi in birds infected with invasive and harmful strains indicates a strong T helper type 1 (Th1) response that likely contributes to an inflammatory response, epithelial disruption and to the mild FCR impairment similar to what was found in other studies (Chagneau et al., 2023 ; Mortada et al., 2021 ). Furthermore, marginal or downregulated IL-6 in those same groups at 7 dpi parallels Mortada et al., ( 2021 ) observation that the expression of chicken IL-6 cytokine may be significantly downregulated. However, it contrasts with Al-Banna et al., ( 2018 ) that proposed IL-6 as a key driver of early inflammatory signaling in human campylobacteriosis. The pronounced Th1-type bias, marked by this elevated IFN-γ and reduced IL-6 in the groups infected with the harmful and invasive strains likely contributes to epithelial barrier disruption (Mortada et al., 2021 ), whereas a more balanced Th1/Th2 profile may allow C. jejuni cecal persistence without pathology as also suggested by Wigley ( 2015 ). The bile sIgA kinetics we observed, generally rising with age is similar to what Lacharme-Lora et al., ( 2017 ) reported, other than peaking unusually in group B at 7 dpi. Moreover, the sIgA can be also variably induced by different colonization patterns as reported by Gloanec et al., ( 2023 ). Chagneau et al. ( 2023 ) further showed that systemic (IgY) and local (IgA) humoral responses coincide with the possibility of hepatic dissemination and Th1/Th2 shifts. At the structural level, C. jejuni infection has been associated with intestinal morphological alterations, including decreased VH, and increased CD, reducing the absorptive area, compromising epithelial barrier integrity and the nutrient uptake (Awad et al., 2015). In our study, infection with the invasive and harmful strains induced a drop in VH:CD ratio in the ileum at 7 dpi. This transitory intestinal structure impairment at 7 dpi, followed by partial recovery at 14 dpi, parallels Awad et al., (2015) early-challenge model, in which mucosal injury peaks within the first week post‐infection but subsequently resolves. Previous studies emphasize that VH:CD measurements remain the gold-standard biomarker for poultry intestinal health, with lower ratios consistently associated with dysbiosis and epithelial dysfunction (Ducatelle et al., 2018 ). Longitudinal analysis of cecal microbiota diversity following C. jejuni challenge reveals a rapid, strain-dependent dysbiosis that parallels and extends findings in the literature (Oakley & Kogut, 2016 ; Valečková et al., 2023 ). The early and pronounced decline in α-diversity observed across all infected groups suggests that C. jejuni infection disrupts microbial homeostasis during a critical window of intestinal maturation. This drop in species’ richness and evenness reflects both a direct microbial displacement by Campylobacter and an indirect effect through host immune activation. Given the known role of microbial diversity in maintaining colonization resistance, these patterns support the notion that C. jejuni promotes dysbiosis that may facilitate its own persistence. These findings align with those of Valečková et al. ( 2023 ) reporting that C. jejuni colonization in broilers precipitates an early collapse in α-diversity with partial recovery by the end of the period (slaughter age). The sharp reduction in α-diversity observed in all infected groups at 2 dpi, when compared to group C, strongly supports a direct impact of C. jejuni infection rather than a natural fluctuation over time. While Qi et al., ( 2019 ) and Richards et al., ( 2019 ) showed a consistent trajectory of increasing α-diversity in developing broilers; the early loss of richness and evenness in infected birds clearly deviates from this pattern, reinforcing the infection-driven nature of dysbiosis. Both quantitative (Bray–Curtis) and qualitative (Jaccard) β-diversity metrics demonstrated that C. jejuni challenge induces an immediate and strain-specific restructuring of the broiler cecal microbiota composition. Already at 2 dpi, all infected groups diverged from the control group, indicating that even at early stages of colonization by C. jejuni , disruption of the composition of the microbiota occurs. Importantly, this effect was not limited to the strains with higher pathogenic potential, as group B also exhibited distinct community profiles. The alterations in cecal microbiota observed at early stages persisted over time. Bray–Curtis analysis showed that groups I and B remained more distinct from the control by the end of the study. The persistent divergence of group I suggests a longer lasting or more profound disruption, which could be linked to reduced SCFA production and slower recovery of key beneficial taxa. These different trajectories illustrate that C. jejuni infection does not simply lower microbial diversity but actively reorganizes microbial networks in ways that may affect host health and pathogen persistence. Similarly, Pang et al. ( 2023 ), showed that C. jejuni positive flocks develop stable, farm-specific β-diversity profiles clearly distinct from Campylobacter -negative flocks, and Di Marcantonio et al. ( 2022 ) found enduring, flock-specific community shifts linked to pathogen carriage. Our experimental infections also demonstrate that each C. jejuni strain imprints a strain-specific β-diversity signature in broiler caeca, which remains differentiated from group C across time points, although the magnitude and direction of these differences evolve throughout the infection course. ANCOM-BC analyses at both genus and ASV level revealed a dynamic, strain-dependent remodeling of the cecal microbiota composition, extending previous observations in poultry infection and gut-microbiome diversity.The concurrent bloom of Rikenellaceae and Campylobacter in groups B and I at 2 dpi suggests a potential synergistic interaction, where pathogen-induced mucosal or metabolic changes facilitate Rikenellaceae expansion. Given the fermentative capacity of Rikenellaceae and their early increase post-challenge, these taxa could act either as opportunistic colonizers of a disrupted niche or as functional enablers of Campylobacter persistence. Members of Rikenellaceae , belonging to Bacteroidetes , are core inhabitants of the chicken caecum, implicated in polysaccharide fermentation and propionate production (Rychlik, 2020 ). Similarly, another experimental C. jejuni challenge in broilers triggered an early bloom of Bacteroidetes, especially Bacteroides , at 3 dpi, suggesting these lineages exploit ecological niches vacated by pathogen‐driven community shifts (Valečková et al., 2023 ). Concurrently, at 2 dpi, classical fermenters within Firmicutes, including Ruminococcus , Faecalibacterium and Oscillospira (Rychlik, 2020 ; Yang et al., 2021 ), were reduced in all infected groups compared to the group C. These genera are key butyrate producers and barrier-protective taxa in healthy broilers; their loss aligns with reports that shows how C. jejuni dysbiosis suppresses SCFA-producing consortia, increasing inflammation and impairing nutrient uptake (Awad et al., 2016 ; Fan et al., 2023 ). Notably, group I, which showed the lowest cecal butyrate concentration, also exhibited the most pronounced reduction in VH:CD ratio at 7 dpi. While these measurements were taken from distinct intestinal segments, the observation supports a functional link between microbiota, SCFA reduction and epithelial atrophy, consistent with the role of butyrate as a major energy source for enterocytes and a driver of intestinal health. At 2 dpi all experimental groups showed higher levels of Bifidobacterium , known for its role in gut barrier integrity and mucosal health (Bindari & Gerber, 2022 ) and by 7 dpi, was notably reduced in all groups and nearly absent in group B. This mirrors previous studies which showed that Bifidobacteriales act as early cecal colonizers in broilers (Mancabelli et al., 2016 ). At 7 dpi, in group B, Bacteroides heavily increased, probably taking advantage of empty niches left by reduced Firmicutes, whereas in other groups these niches remained occupied. Similar opportunistic blooms of Bacteroides following C. jejuni challenge have been reported before by Hankel et al., ( 2019 ) and Valečková et al., ( 2023 ). At 14 dpi, changes became more strain specific. The results reflect biologically relevant patterns linked to infection dynamics and suggest that the cecal microbiota shows small but specific differences between infecting strains. The genera Faecalibacterium , Ruminococcus and Blautia all rebounded in I and H groups, suggesting that certain Clostridiales lineages more readily re-establish post-challenge, consistent with Rychlik, ( 2020 ) which noted that cecal Clostridiales possess diverse carbohydrate-fermenting capabilities essential for community recovery. ASV-level ANCOM-BC uncovered strain-specific shifts masked at the genus level. These findings echo Lin & Peddada, ( 2020 ) recommendations that high-resolution ASV analysis reveal small details in community shifts otherwise overlooked. Our cecal SCFA data reveal a dynamic, again, strain-specific fermentative response to C. jejuni challenge that closely mirrors shifts in community composition and aligns with findings from other studies in broiler chickens (Al Hakeem et al., 2024 ; Awad et al., 2016 ; Fan et al., 2023 ). Although most correlations between bacterial genera and SCFA concentrations were group-specific, some consistent patterns emerged. Generally, SCFA-producing Firmicutes such as Faecalibacterium , Ruminococcaceae , and Butyricicoccus exhibited positive correlations with key metabolites like butyrate and propionate in several groups, reinforcing their functional relevance in gut recovery and highlighting their potential as microbial biomarkers of resilience. Specifically, at 2 dpi, infected birds exhibited a dramatic decline in butyrate and formate alongside succinate accumulation, consistent with Awad et al., ( 2016 ). Early blooms of Bacteroides and lactate-producers suggest opportunistic expansion in niches vacated by fermenters (Valečková et al., 2023 ). At 7 dpi, formate levels were markedly higher in all infected groups, potentially via blooms of Rikenellaceae and succinate‐to‐formate converters, indicating metabolic adaptation or restructuration of the microbiota. Butyrate remained relatively stable across groups except in group I, where it declined significantly, consistent with delayed recovery of butyrate-producing Faecalibacterium , Ruminococcus and Blautia . Meanwhile, succinate began to normalize in groups B and H, suggesting a possible functional recovery, but stayed elevated in group I, underscoring strain‐specific persistence of dysbiosis. At 14 dpi, a general trend towards stabilization of the fermentation profile was observed in most groups. Acetate and propionate reached values similar to group C in groups B and H, indicating a possible reactivation of healthy fermentation and reflecting re‐establishment of acetate‐producers ( Ruminococcus , Oscillospira ) as described by Rychlik, ( 2020 ). Butyrate also remained high in these groups, consistent with renewed growth of Faecalibacterium which could produce butyrate by acetyl-CoA acetyl-transferase (Polansky et al., 2016 ). However, group I maintained the lowest butyrate and the highest succinate levels, suggesting persistent functional imbalance of the microbial ecosystem. The low lactate concentration in all infected groups indicates a partial recovery of microbial balance. Although none of the correlations between microbiota composition and SCFAs production were not significant after false discovery rate correction, several pointed to biologically relevant interactions deserving further investigations in larger sample sets. Together, these results reflect an early and marked alteration of cecal fermentative activity after infection, followed by differential recovery patterns among groups, with the group I showing the most limited recovery and a more dysbiotic metabolic profile. These strain-specific effects highlight both the heterogeneity in C. jejuni pathogenic potential and the central role of gut microbiota in shaping infection outcomes. Our data suggest that beneficial taxa such as Faecalibacterium , Ruminococcus and Butyricicoccus are linked to resilient, fermentatively balanced states, whereas Bacteroides bloom, loss of Firmicutes fermenters, and succinate accumulation in group I point to a microbiome vulnerable to disruption. Importantly, the identification of specific microbial lineages linked to SCFA recovery and mucosal homeostasis provides a basis for targeted probiotic interventions. Enriching taxa that support butyrate and acetate production, could mitigate the dysbiosis caused by C. jejuni colonization, improve poultry performance and welfare, and may help reduce intestinal loads of this zoonotic pathogen, thereby improving food safety. In conclusion, this study underscores the broad, strain-dependent impact of C. jejuni infection in broilers, ranging from harmless or near-commensal colonization with minimal microbiota disruption to marked dysbiosis characterized by epithelial injury, proinflammatory responses, altered fermentation patterns, leading to performance impairment. Our results reinforce the microbiota as both a target and tool in combatting Campylobacter infection and support future research into precision microbiota-based strategies to improve broiler resilience and reduce zoonotic risk in poultry production systems. Declarations The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Author Contribution A.M-P conducted farm and laboratory experiments, analyzed and interpreted the data and wrote the draft manuscript. F.C-F assisted with microbiota data analysis and interpretation. P.O-G assisted with microbiota data analysis. A.D assisted with immune response characterization. T.A conducted wet lab experiments. B.V assisted with analysis of SCFA production and with performance parameters data analysis and interpretation. M.N and M.C-C conceptualized and designed the study, assisted in farm and lab experiments, analyzed and interpreted the data, revised and checked the manuscript. All authors read and approved the final manuscript. Acknowledgement This study was supported by the Spanish Ministry of Science and Innovation (grant No. RTI2018-095081-B-I00) and the Spanish Ministry of Science, Innovation and Universities (grant No, PID2021-128079OB-I00). A. M. P. was supported by a pre-doctoral fellowship FPI 2019 from the Spanish Ministry of Science, Innovation and Universities (PRE2019-087435). Technical support of Ana Pérez de Rozas, Núria Aloy and Judith González is greatly appreciated; Diego Pérez and Alcarràs IRTA farm staff support are also appreciated. CERCA from the Generalitat de Catalunya is acknowledged. Data Availability All data supporting the findings of this study are available within the paper and its Supplementary Files. References Al Hakeem, W. G., Cason, E. E., Adams, D. A., Villanueva, K. Y. A., Shanmugasundaram, R., Lourenco, J., & Selvaraj, R. K. (2024). The effect of Campylobacter jejuni challenge on the ileal microbiota and short-chain fatty acids at 28 and 35 days of age. 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New York: Springer-Verlag; 2009. Wigley, P. (2015). Blurred Lines: Pathogens, Commensals, and the Healthy Gut. Frontiers in Veterinary Science , 2 . https://doi.org/10.3389/fvets.2015.00040 Yang, J., Li, Y., Wen, Z., Liu, W., Meng, L., & Huang, H. (2021). Oscillospira—A candidate for the next-generation probiotics. Gut Microbes , 13 (1), 1987783. https://doi.org/10.1080/19490976.2021.1987783 Additional Declarations No competing interests reported. Supplementary Files SupplementaryFilesMicrobiomeBMCAliciaManzanaresPedrosa.xlsx Cite Share Download PDF Status: Posted Version 1 posted 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. 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17:36:41","extension":"png","order_by":23,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":152176,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-8346657/v1/8175778c0e70141f07543b94.png"},{"id":100615824,"identity":"49d67c16-9b21-4cfe-b0d0-1280e7d8ed5d","added_by":"auto","created_at":"2026-01-19 17:37:05","extension":"png","order_by":24,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":71791,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-8346657/v1/290cf3b10adffb7c0cd1180b.png"},{"id":100615790,"identity":"1e77b5b1-aa0e-4e85-bd78-4cdc995dd637","added_by":"auto","created_at":"2026-01-19 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17:35:43","extension":"html","order_by":27,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":243797,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8346657/v1/2fba83c253aaca0839001a71.html"},{"id":100615612,"identity":"4f43fbf3-8b3d-4590-819e-82c7d7682e60","added_by":"auto","created_at":"2026-01-19 17:35:09","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":26195,"visible":true,"origin":"","legend":"\u003cp\u003eCytokine expression from cecal tonsils samples for each group of broilers at 2-, 7- and 14-days post infection (dpi).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8346657/v1/e4d9436ac66910ad6d9cbe2a.png"},{"id":100615792,"identity":"dc8b0bf1-36ab-4301-8e73-c2ed854fdb7d","added_by":"auto","created_at":"2026-01-19 17:36:54","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":15558,"visible":true,"origin":"","legend":"\u003cp\u003esIgA concentrations in bile from the different experimental groups. Results expressed as a means of all samples in each experimental group and day post infection. Different letters mean statistically significant differences between groups (P \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8346657/v1/f12200f6006e96313263e34f.png"},{"id":100615855,"identity":"b360725f-2412-419b-af8b-683ddf8976b5","added_by":"auto","created_at":"2026-01-19 17:37:34","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":16508,"visible":true,"origin":"","legend":"\u003cp\u003eVillus height:crypt depth (VH:CD) ratios from the different experimental groups on days 7 and 14 post infection. Values are means. Different letters mean statistically significant differences between groups (P \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8346657/v1/050ad89e3e35602efe0d399a.png"},{"id":100615657,"identity":"c569bd1d-916d-4a50-a808-37267e752832","added_by":"auto","created_at":"2026-01-19 17:35:41","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":32525,"visible":true,"origin":"","legend":"\u003cp\u003eDynamics of the cecal microbiota α-diversity throughout the study. Boxplots showing the distribution of Shannon diversity indexes for caecal microbiota across three time points post-infection (2, 7, and 14 dpi) in the four experimental groups. Each box represents the interquartile range, indicating the median, and whiskers extending to the lowest and highest values. Outliers are plotted as individual points in grey.Different letters mean statistically significant differences between groups.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8346657/v1/2ab2f14950c80f148e905c5d.png"},{"id":100615661,"identity":"429f86c1-80e7-48ba-ada6-ad2eae917680","added_by":"auto","created_at":"2026-01-19 17:35:44","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":134541,"visible":true,"origin":"","legend":"\u003cp\u003eβ-diversity of cecal microbiota across experimental groups and time points. Principal Coordinates Analysis (PCoA) plots displaying β-diversity patterns of cecal microbial communities at 2-, 7-, and 14-days post-infection (dpi) across the four experimental groups: Control uninfected (C), Benign (B), Harmful (H), and Invasive (I) strains. In PCoA based on Bray–Curtis dissimilarity distances (A) or Jaccard distance (B) are shown. Each point represents one individual sample. Confidence ellipses (95%) were generated using a multivariate t-distribution (stat_ellipse(type = \"t\", level = 0.95)) in R (v3.6.3.) to visualize group-level clustering and dispersion.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8346657/v1/47812a1f842b4988daf054c1.png"},{"id":100615845,"identity":"397c87a4-113c-4511-a7a3-9741de7cab24","added_by":"auto","created_at":"2026-01-19 17:37:21","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":61284,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 6\u003c/strong\u003e. (A) Heatmap representing the log-transformed relative abundances of genera identified as differentially abundant in caecal microbiota across treatment groups and days post infection. Each row corresponds to a genera and each column to an experimental group (C: Control uninfected, B: Benign strain, H: Harmful strain, and I: Invasive strain). The additional annotation panel on the right indicates (in orange squares) at which time point each genus was identified as differentially abundant among groups. The relative abundance of the differentially abundant taxa are shown in Supplementary Files.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-8346657/v1/2d8004de17e8fdfa59bbee4c.png"},{"id":100615857,"identity":"bcca18d7-d108-492d-b01a-bbc5efd528b7","added_by":"auto","created_at":"2026-01-19 17:37:35","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":52502,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 6\u003c/strong\u003e. (B) Heatmap representing the log-transformed relative abundances of ASVs identified as differentially abundant in caecal microbiota across treatment groups and days post infection. Each row corresponds to the genera corresponding to each ASV identified and experimental groups are in columns (C: Control uninfected, B: Benign strain, H: Harmful strain, and I: Invasive strain). The additional annotation panel on the right indicates (in orange squares) at which time point each ASV was identified as differentially abundant among groups. The relative abundance of the differentially abundant taxa are shown in Supplementary Files.\u003c/p\u003e","description":"","filename":"6b.png","url":"https://assets-eu.researchsquare.com/files/rs-8346657/v1/7a8ce34ac1ca37de91a32ac5.png"},{"id":100615741,"identity":"b34d6f0c-f952-4cda-9f46-e86a3e03e7c2","added_by":"auto","created_at":"2026-01-19 17:36:18","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":58942,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 7\u003c/strong\u003e. SCFA concentrations (µmol/g) at 2-, 7- and 14-days post-infection. Values are means for each experimental group. C: Control uninfected, B: Benign strain, H: Harmful strain, I: Invasive strain. Different letters mean statistically significant differences between groups (P \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-8346657/v1/ff25c10a057e2cfdb939cf2b.png"},{"id":100615737,"identity":"198fe416-d6d7-4bd2-aa0d-9e730f92ea06","added_by":"auto","created_at":"2026-01-19 17:36:15","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":197261,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 8\u003c/strong\u003e. Heatmap showing the Spearman correlation between SCFA concentrations and microbiota composition for all four experimental groups and time points. The heatmaps displays Spearman correlation coefficients (ρ). Each panel corresponds to a different experimental group: (A) Control uninfected; (B) Benign strain; (C) Harmful strain; (D) Invasive strain. Positive correlations are shown in red and negative correlations in blue, with intensity indicating strength. Hierarchical clustering was applied to both genera and SCFAs to visualize co-variation patterns.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-8346657/v1/7db1dde905a593dd3b92ae56.png"},{"id":102330784,"identity":"a367cde0-3ca3-446a-b508-2ec6cbd866f6","added_by":"auto","created_at":"2026-02-10 15:13:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1518216,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8346657/v1/7ef24d8c-349c-4be2-93e2-6279480bb2dc.pdf"},{"id":100615846,"identity":"52a31771-f1cc-441a-9e1b-375571eac384","added_by":"auto","created_at":"2026-01-19 17:37:22","extension":"xlsx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":21958,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFilesMicrobiomeBMCAliciaManzanaresPedrosa.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8346657/v1/ce6f71ed0403dd1c2cf1690f.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Campylobacter jejuni strains with different pathogenic potential shapes host-pathogen interactions and gut microbiota dynamics","fulltext":[{"header":"Introduction","content":"\u003cp\u003e \u003cem\u003eCampylobacter jejuni\u003c/em\u003e is the leading, extensively prevalent, and widespread cause of human gastroenteritis worldwide, with broiler chicken identified as the most relevant reservoir for transmission to humans through contaminated chicken meat (EFSA \u0026amp; ECDC, 2024). The incidence of campylobacteriosis has escalated both in developed and in low- and middle-income countries (Havelaar et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) and has been the most frequently reported zoonosis in humans across the EU since the beginning of EU surveillance in 2007 (EFSA \u0026amp; ECDC, 2024).\u003c/p\u003e \u003cp\u003eFor years, \u003cem\u003eC. jejuni\u003c/em\u003e has been considered an asymptomatic commensal in chickens, with no negative impact on their health. Recently, several researcher groups have explored whether Campylobacter functions as a commensal organism or a pathogen in chicken. (Wigley, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The host-pathogen interaction between \u003cem\u003eC. jejuni\u003c/em\u003e and the avian host involves a complex response that can differ according to the strain characteristics and the host genetics (Chaloner et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Some strains have shown a highly invasive and virulent phenotype, with capacity for hepatic dissemination which represents both a productive and sanitary risk (Humphrey et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn contrast to humans, chickens are known to carry high \u003cem\u003eC. jejuni\u003c/em\u003e loads in their intestines (up to 10\u003csup\u003e9\u003c/sup\u003e CFU/g of cecal content) (Beery et al., 1988). It has long been recognized that \u003cem\u003eC. jejuni\u003c/em\u003e rapidly colonizes the intestinal tract of broiler chickens following exposure. Shanker et al., (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e1988\u003c/span\u003e) showed that 88% of experimentally infected chicks exhibited cecal colonization within 3 days post-infection, regardless of the age of exposure. Similarly, Connerton et al., (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) reported complete cecal colonization of 20-day-old broilers infected with \u003cem\u003eC. jejuni\u003c/em\u003e after 2 days of infection, with average counts reaching approximately 10\u003csup\u003e6\u003c/sup\u003e CFU/g and persisting throughout the study period. Fast dissemination has also been reported in experimental infections where broiler chickens challenged with different \u003cem\u003eC. jejuni\u003c/em\u003e strains were put in contact with uninfected birds (Chaloner et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), simulating natural conditions.\u003c/p\u003e \u003cp\u003eSeveral studies have investigated the immune response of broiler chickens to \u003cem\u003eC. jejuni\u003c/em\u003e colonization (Mortada et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), mostly without considering the varying pathogenic potential among different strains (Hermans et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2011\u003c/span\u003eb). Understanding these host-pathogen interactions is crucial for improving animal health and mitigating the risk of transmission to humans. \u003cem\u003eC. jejuni\u003c/em\u003e infection can activate the expression of pro-inflammatory interleukin (IL)-1β, IL-6, IL-17A and interferon gamma (IFN)-γ, and anti-inflammatory (IL-10) cytokines, and transforming growth factor (TGF-β). All of them have been documented as important cytokines against pathogen infection and colonization (Mortada et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Reid et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) and regulation of intestinal inflammatory dynamics which can influence bacterial colonization (Taha-Abdelaziz et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In parallel, the production of secretory immunoglobulin A (sIgA) represents a fundamental adaptative line of defense in the intestinal mucosa, whose role against \u003cem\u003eC. jejuni\u003c/em\u003e is not yet fully elucidated. Moreover, its efficacy may depend on multiple factors such as post-infection time and the immune maturation of the host (Lacharme-Lora et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003eC. jejuni\u003c/em\u003e infection may also be associated (strain-dependent), with structural modifications of the intestinal epithelium, such as reduced villus height (VH) and increased crypt depth (CD), which can compromise the absorptive capacity and physical barrier of the intestine (Awad et al., 2015). These changes can also occur in parallel with one of the most prominent effects of infection, the intestinal dysbiosis. The establishment of a normal and healthy microbiota constitutes an important component of gut health, and has implications for proper development and maturation of the immune system and for the correct poultry nutrition (Oakley et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Several studies have explored how \u003cem\u003eC. jejuni\u003c/em\u003e infection perturbs the chicken gut microbiota, revealing potential consequences for host health (Oakley \u0026amp; Kogut, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Hankel et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Valečkov\u0026aacute; et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Intestinal dysbiosis is characterized by the loss of beneficial microorganisms, reducing microbial diversity and displacing beneficial bacteria, which in turn can lead to an alteration in the production of certain short-chain fatty acids (SCFA). Particularly acetate and butyrate, that are critical for immune homeostasis, epithelial health and maintaining the intestinal barrier integrity (Al Hakeem et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Connerton et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite the progress in understanding the biology of \u003cem\u003eCampylobacter\u003c/em\u003e, important key knowledge gaps still remain, such as the host response to infection with strains of \u003cem\u003eC. jejuni\u003c/em\u003e with different pathogenic potential (non-invasive vs. invasive strains). In this context, the present study aimed to comprehensively evaluate and analyze the immune and intestinal response of broiler chickens infected with \u003cem\u003eC. jejuni\u003c/em\u003e strains with different pathogenic potential. Thus, \u003cem\u003eC. jejuni\u003c/em\u003e excretion, expression of cytokines in cecal tonsils, quantification of secretory IgA in bile, and changes in the intestinal morphology, in microbiota composition and SCFA production were analyzed. This multidimensional approach will allow a better understanding of the mechanisms underlying the \u003cem\u003eC. jejuni\u003c/em\u003e-host interaction, aiming to provide key information for control strategies in poultry production, relevant both to bird health and welfare, and to food safety.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003eBacterial strains and culture conditions\u003c/p\u003e \u003cp\u003eThree different \u003cem\u003eC. jejuni\u003c/em\u003e strains were used in the challenge study. Two cecal strains: one strain potentially benign, recovered from a flock with low feed conversion rate (FCR) and one strain potentially harmful, recovered from a flock with high FCR. The third strain was an invasive one isolated from internal tissue liver. The strains were selected from our own strain collection for which we have performance and health data from the flocks where cecal isolates have been recovered. Hence, cecal \u003cem\u003eC. jejuni\u003c/em\u003e isolates from flocks in the top and bottom 25% in terms of performance (FCR) were initially selected as potentially harmful and benign strains. Selection criteria were also based on the invasiveness potential and the presence or absence of genetic features potentially associated with host interaction, and colonization. Bacteria were grown on Columbia blood agar (BioMerieux, Marcy l\u0026rsquo;Etoile, France) for 48 h at 37\u0026deg;C under microaerobic conditions from stocks maintained in brain heart infusion broth (BHI, Merck KGaA, Darmstadt, Germany) with 20% glycerol at -75\u0026deg;C.\u003c/p\u003e \u003cp\u003eExperimental design\u003c/p\u003e \u003cp\u003e All work was conducted in accordance with proper veterinary practices, in accordance with European (Directive 2010/63/EU) and Spanish (Real Decreto 53/2013) regulation. The study was conducted with prior approval of the Animal Experimentation Committee of the Institution and the Catalan Government (Protocol number 11213).\u003c/p\u003e \u003cp\u003eOne-day-old Ross 308 chicks were obtained from a commercial hatchery. All animals were checked twice daily to ensure their health and welfare. Chicks were randomly distributed in 4 experimental groups: a control uninfected group and three challenged groups, each infected with one of the above-mentioned \u003cem\u003eC. jejuni\u003c/em\u003e strains (benign, harmful, invasive). For simplicity, throughout the manuscript, the groups will be referred to as Group C (Control group), Group B (challenged with the benign strain), Group H (challenged with the harmful strain), and Group I (challenged with the invasive strain). Each group with 100 birds each was allocated in independent rooms and maintained in floor pens. Birds were distributed in 5 pens per group, with 20 birds per pen. Chicks were reared under farm conditions, at a temperature of 30\u0026deg;C, which was gradually reduced to 20\u0026deg;C when the birds were 3 weeks of age. Strict biosecurity measures were taken to avoid cross-contamination among rooms.\u003c/p\u003e \u003cp\u003ePrior to the experimental infection, regular monitoring of the farm was conducted to ensure that all housing units remained free of \u003cem\u003eCampylobacter\u003c/em\u003e contamination. Weekly sampling was performed using boot socks, which were collected from all rooms and corridors of the facility; these samples were analyzed by PCR to confirm the absence of \u003cem\u003eCampylobacter\u003c/em\u003e spp. At 3 weeks of age, all birds were confirmed as \u003cem\u003eCampylobacter\u003c/em\u003e free prior to the experimental infection by collecting cloacal swabs from each individual which were streaked onto modified Charcoal Cefoperozone Deoxycholate agar plates (mCCDA, CM739 with selective supplement, SR0155E; Oxoid, Basingstoke, UK). Animals were challenged at 21 days of age with the corresponding strain and from this date onwards, the boot socks monitoring was maintained exclusively for the control group (unchallenged birds) to verify continued absence of \u003cem\u003eCampylobacter\u003c/em\u003e throughout the study.\u003c/p\u003e \u003cp\u003eChallenge was performed by oral gavage with 1 ml of an inoculum containing 10\u003csup\u003e5\u003c/sup\u003e CFU/ml in saline solution for each strain. Control group was administered only with saline solution.\u003c/p\u003e \u003cp\u003eSample collection\u003c/p\u003e \u003cp\u003ePerformance parameters were assessed weekly (on days 7, 14, 21, 28 and 35): body weight (BW), daily gain (DG), daily feed intake (DFI) and FCR. On days 2, 7, and 14 post infection (dpi) two animals per pen were randomly euthanized. Samples of cecal content, liver, ileum tissue, cecal tonsils, and bile were collected.\u003c/p\u003e \u003cp\u003eCecal content and liver samples for \u003cem\u003eCampylobacter\u003c/em\u003e determination were stored refrigerated and processed within 24h of collection. An aliquot of cecal content for SCFA analysis was placed in tubes placed in dry ice and stored frozen until analysis. Another aliquot of cecal content for intestinal microbiota analysis was placed in tubes containing 3 ml of ethanol (96%) (1:3 cecal content:ethanol) and stored refrigerated until further processing. Cecal tonsils samples for RNA extraction were preserved frozen (-75\u0026ordm;C) in RNA later until analysis of cytokine expression. Bile samples for sIgA determination were also kept frozen (-75\u0026ordm;C) until analysis. Samples of ileum for histological analysis were preserved in buffered formaline.\u003c/p\u003e \u003cp\u003e \u003cem\u003eC. jejuni\u003c/em\u003e determination\u003c/p\u003e \u003cp\u003eAssessment of \u003cem\u003eC. jejuni\u003c/em\u003e in the intestine was performed by bacterial isolation from the cecal content by conventional culture methods using mCCDA agar (Urdaneta et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003eC. jejuni\u003c/em\u003e isolation from the internal liver tissue was attempted from a 2 g portion of internal tissue aseptically collected (surface sanitized by searing with a flame-sterilized spatula); 1 g was homogenized and mixed with 5 ml of Buffered Peptone Water (BPW) for direct plating onto mCCDA. The remaining 1 g was subjected to pre-enrichment in 3 ml of Bolton broth (Oxoid CM0983 supplemented with SR0183E and laked horse blood SR0048C), and subsequently, 100 \u0026micro;l of the enriched sample was streaked onto mCCDA.\u003c/p\u003e \u003cp\u003ePresumptive colonies from mCCDA plates from caeca and liver samples were subcultured onto blood agar plates for 48h at 37\u0026ordm;C in microaerophilic conditions. Isolates were preserved in BHI (Merck KGaA, Darmstadt, Germany) with 20% glycerol at -75\u0026ordm;C for further analyses.\u003c/p\u003e \u003cp\u003eImmune response characterization\u003c/p\u003e \u003cp\u003eExpression of pro- (e.g. interleukin-1β, IL-6, IFN-γ and IL-17A) and anti-inflammatory cytokines (e.g. IL-10) in cecal tonsils was performed by real-time quantitative reverse transcription-PCR (qRT-PCR). Total RNA was extracted from 20 mg of tissue using RNeasy Mini Kit (QIAGEN, Hilden, Germany) according to the manufacturer\u0026rsquo;s instructions. The pollutant DNA was digested with RNase-free DNase Set (QIAGEN) and RNA was eluted with 50 \u0026micro;l of water RNase free and preserved at -75\u0026ordm;C. The quantity and quality of RNA was determined with Biodrop spectrophotometer (Thermofisher).\u003c/p\u003e \u003cp\u003eExpression of mRNA was measured by qPCR, using the EXPRESS One-Step SYBR GreenER kit (QIAGEN, CA, USA) according to the manufacturer\u0026rsquo;s protocol. Previously described primers for IFNγ (Carvajal et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), IL-1β, IL-6, IL-10 (Fasina et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Smith et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) and IL-17A (Reid et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) were used. Beta actin (ACTB) was used as the housekeeping gene, for which the following primers were used: ACTB_FW (5\u0026rsquo;-CCAGACATCAGGGTGTGATGG-3\u0026rsquo;) and ACTB_RV (5\u0026rsquo;-CTCCATATCATCCCAGTTGGTGA-3\u0026rsquo;).\u003c/p\u003e \u003cp\u003eAmplification and detection of specific products were performed using 7500 Fast Real-Time PCR system and 7500 software version 2.3 (Applied Biosystems, CA, USA) with the following conditions: cDNA synthesis at 50\u0026deg;C for 5 min, followed by initial denaturation at 95\u0026deg;C for 20 s, and 40 cycles of denaturation at 95\u0026deg;C for 3 s and annealing/extension at 60\u0026deg;C for 30 s.\u003c/p\u003e \u003cp\u003eExpression of each target gene was determined using the cycle threshold (CT) value relative to that for the ACTB reference gene (ΔCT). Results are expressed as fold changes in corrected target gene expression (ΔCT) in infected animals relative to the control animals (2 \u003csup\u003e\u0026minus;ΔΔCT\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003eThe concentration of sIgA from bile samples was determined by ELISA (Bethyl Laboratories Inc., Montgomery, TX, USA) following the manufacturer instructions.\u003c/p\u003e \u003cp\u003eIntestinal morphometry\u003c/p\u003e \u003cp\u003eIntestinal ileum tissue samples were fixed in 10% buffered formalin and then dehydrated and embedded in paraffin. The samples were sectioned with a microtome and stained with Periodic acid Schiff (PAS). The villus height (VH) and crypt depth (CD) were measured using a light microscope with a linear ocular micrometer (Olympus 209-35040) and the VH:CD ratio was calculated.\u003c/p\u003e \u003cp\u003eSCFA production\u003c/p\u003e \u003cp\u003eCecal content samples from 2, 7 and 14 dpi were analyzed for acetate, formate, propionate, butyrate, isobutyrate, valerate, isovalerate, lactate and succinate using gas chromatography with flame ionization detection (GC-FID). The analytical procedure was performed following an internal procedure based on the classical method described by Jouany (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e1982\u003c/span\u003e). Final SCFA concentrations were expressed as \u0026micro;mol/g cecal content.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003ePerformance data were analyzed using a one-way analysis of variance (ANOVA) to evaluate the effect of the experimental challenge on BW, ADG, ADFI, and FCR. Least Squares Means (LSMeans) and their standard error (SEM) were calculated for each group. Statistical significance was considered at p\u0026thinsp;\u0026le;\u0026thinsp;0.05. The analysis was performed using R software (version 3.6.3).\u003c/p\u003e \u003cp\u003eTo assess differences in intestinal morphometric parameters and immunological parameters (cytokines and sIgA) among the four experimental groups, a one-way analysis of variance (ANOVA) was conducted. When significant effects were detected (p\u0026thinsp;\u0026le;\u0026thinsp;0.05), pairwise group comparisons were carried out using Tukey\u0026rsquo;s Honestly Significant Difference (HSD) post-hoc test; statistical significance for this test was also set at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.05. The analysis was performed using R software (version 3.6.3).\u003c/p\u003e \u003cp\u003eSignificant differences in the SCFA concentrations among groups were analyzed using one-way ANOVA to strain effects for each SCFA at each time point using SAS 9.4 software. Moreover, Spearman correlation analysis was performed to assess the association between SCFA concentrations and the relative abundance (log-transformed) of bacterial genera previously identified as differentially abundant. Correlations coefficients (ρ) and p-values were calculated using the cor.test() function in R (version 3.6.3) with the Spearman method, which does not assume normality. Benjamini\u0026ndash;Hochberg correction was applied to control the false discovery rate (FDR), with significance defined as p\u0026thinsp;\u0026le;\u0026thinsp;0.05 and trends as 0.05\u0026thinsp;\u0026lt;\u0026thinsp;p\u0026thinsp;\u0026le;\u0026thinsp;0.10. Results were visualized as a heatmap (pheatmap package, (Kolde, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2025\u003c/span\u003e)), displaying ρ values and coloured gradients to indicate the strength and direction of associations.\u003c/p\u003e \u003cp\u003eMicrobiota analysis\u003c/p\u003e \u003cp\u003eTotal DNA was extracted from caecum contents using the QIAamp DNA Stool Mini Kit (Qiagen, West Sussex, UK). Metagenomics analysis was used to determine the impact of infection with the different \u003cem\u003eC. jejuni\u003c/em\u003e strains on the gut microbiome and to compare the microbiome of \u003cem\u003eCampylobacter\u003c/em\u003e-positive and -negative birds. The microbial communities were characterized through amplification and high-throughput sequencing of the V3\u0026ndash;V4 variable regions of the 16S rRNA gene (Caporaso et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). This variable region has proven to produce a more detailed composition than others for microbial diversity and community composition analysis of cecal microbiota (Pandit et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Sequencing was performed with Illumina MiSeq pair-end 2X250 bp sequencing following the manufacturer\u0026rsquo;s instructions (MS-102-2003 MiSeq\u0026reg; Reagent Kit v2, 500 cycle). Sequencing services were outsourced to Microomics Systems S.L. (Barcelona, Spain). The analysis of the 16S rRNA gene amplicons was performed using Quantitative Insights into Microbial Ecology (QIIME) 2 software package vs 2022.11 (Bolyen et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlpha diversity was estimated using different metrics: Shannon index (Shannon \u0026amp; Weaver, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e1949\u003c/span\u003e), Chao index (Chao, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1984\u003c/span\u003e) and Simpson Index (Simpson, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e1949\u003c/span\u003e). Richness was evaluated using Observed Features. Different beta diversity metrics were used to assess the diversity across the samples, both quantitatively using Bray Curtis dissimilarity index (Bray \u0026amp; Curtis, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1957\u003c/span\u003e) and qualitatively with Jaccard similarity coefficient (Jaccard, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1908\u003c/span\u003e). These distance matrices were used to perform Principal Coordinate Analysis (PCoA) using \u003cem\u003ecore-metrics\u003c/em\u003e plugin and a PERMANOVA was conducted to estimate the significance of group clustering. To extract the percentage of variations explained by each metadata column (effect size), the Adonis function from \u003cem\u003eVegan\u003c/em\u003e package (Oksanen et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) was performed on every distance matrix. Confidence ellipses (95%) were generated using a multivariate t-distribution (stat_ellipse(type = \"t\", level\u0026thinsp;=\u0026thinsp;0.95)) in R (v3.6.3.) to visualize group-level clustering and dispersion. Taxonomic assignment of amplicon sequence variants (ASV) was performed using a scikit-learn na\u0026iuml;ve Bayes classifier implemented in QIIME2, previously trained on the V3-V4 region from 16S rRNA gene and the Greengenes database (13.8 version) clustered at 99% identity (McDonald et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Differential abundance analysis at both amplicon sequence variant level and collapsed at different taxonomic levels was performed using the Analysis of composition of microbiomes with bias correction (ANCOM-BC) (Lin \u0026amp; Peddada, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), performed at each timepoint among all the groups. For data visualization, Rstudio (Version 3.6.3; R Core Team, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), ggplot2 (Wickham, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) and tidyverse (Wickham et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) packages were used.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eGenetic differences among \u003cem\u003eC. jejuni\u003c/em\u003e strains used for experimental infection\u003c/p\u003e \u003cp\u003eThe three \u003cem\u003eC. jejuni\u003c/em\u003e strains used in this study were selected to represent a different pathogenic potential and belong to different MLST ST and CC: benign (ST883, CC21), harmful (ST572, CC206) and invasive (ST48, CC48). Previous whole-genome sequencing analysis (data not shown) revealed that all three strains harbored nearly all analyzed virulence-associated genes, with minor differences. Hence, few virulence genes where differentially distributed among the strains: the harmful and invasive strains carried the \u003cem\u003eneuA1\u003c/em\u003e and the \u003cem\u003ehddC\u003c/em\u003e virulence-associated genes. Also, accessory genes analysis revealed that the three strains clustered separately, with each cluster displaying a distinct accessory gene profile. The benign strain exhibited a broader repertoire of metabolic and surface structure genes, while harmful strain encoded functions associated with motility and nutrient acquisition, and the invasive strain carried genes linked to oxidative stress, DNA repair and immune evasion.\u003c/p\u003e \u003cp\u003e \u003cem\u003eCampylobacter\u003c/em\u003e isolation\u003c/p\u003e \u003cp\u003e \u003cem\u003eC. jejuni\u003c/em\u003e was recovered from cecal samples from all but one infected bird at 2 dpi and from all sampled birds at 7 and 14 dpi. It was also recovered from internal tissue liver in up to 3 birds per infected group at different time points. All unchallenged birds were negative at all time points for both kind of samples.\u003c/p\u003e \u003cp\u003ePerformance parameters\u003c/p\u003e \u003cp\u003eBefore infection, non-significant differences in BW, DG, DFI and FCR were detected among groups (FCR within \u0026plusmn;\u0026thinsp;0.5% of group C\u0026thinsp;=\u0026thinsp;1.314) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Statistically significant differences among groups at 35 days of life were observed for the FCR, with no differences for the other variables (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). FCR was significantly impaired by 3% in groups H and I (1.642 and 1.643, respectively) compared to group C (1.599), with no significant differences between group C (1.599) and group B (1.606).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePerformance variables before infection (1 to 21 days of life). Values are means.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBenign\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHarmful\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eInvasive\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSEM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBW\u003csub\u003ed21\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e877\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e885\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e911\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e892\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.543\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eADG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.543\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eADFI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.297\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFCR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.314\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.309\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.680\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003ea\u003c/sup\u003eBW: Average body weight (g; initial BW 39.8g), ADG: Average daily gain (g), ADFI: average daily feed intake (g), FCR: feed conversion ratio (kg feed/kg weight gain)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePerformance variables post infection (22 to 35 days of life). Values are means.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBenign\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHarmful\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eInvasive\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSEM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBW\u003csub\u003ed22\u003c/sub\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e877\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e885\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e911\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e892\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.543\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBW\u003csub\u003ed35\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e44.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.760\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eADG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e94.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e94.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.813\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eADFI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e146.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e149.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e154.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e155.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.393\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFCR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.599\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.606\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.642\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.643\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003ea\u003c/sup\u003eBW: Average body weight (g), ADG: Average daily gain (g), ADFI: average daily feed intake (g), FCR: feed conversion ratio (kg feed/kg weight gain)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003csup\u003eb,c\u003c/sup\u003e Different letters mean significant differences among groups.\u003c/p\u003e \u003cp\u003eCytokine gene expression\u003c/p\u003e \u003cp\u003eSignificant differences in IFNγ gene expression were observed at 7 dpi in chickens infected with invasive (~\u0026thinsp;12-fold higher) and harmful (~\u0026thinsp;8-fold higher) strains compared to group C (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In contrast, the same groups showed numerically down regulation or marginal IL6 gene expression on that same day.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003esIgA quantification\u003c/p\u003e \u003cp\u003esIgA levels in bile were studied at 2, 7, and 14 dpi (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Across all experimental groups there was a time-dependent increase in the total sIgA levels. No statistically significant differences were found at 2dpi. Post-hoc analysis with Tukey\u0026rsquo;s test revealed that group B had higher titters at 7 dpi compared to group C (p\u0026thinsp;=\u0026thinsp;0.004) and group I (p\u0026thinsp;=\u0026thinsp;0.016). Moreover, at 14 dpi, group C had higher titters compared to group B (p\u0026thinsp;=\u0026thinsp;0.004).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eChanges in intestinal morphology\u003c/p\u003e \u003cp\u003eThe intestinal integrity of the ileum samples at 7 and 14 dpi was evaluated (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). At 7 dpi, the VH, CD and VH:CD ratio were significantly different among experimental groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Post-hoc analysis with Tukey\u0026rsquo;s test revealed significant higher VH:CD ratios in the group C compared to both the groups H (p\u0026thinsp;=\u0026thinsp;0.0475) and I (p\u0026thinsp;=\u0026thinsp;0.0117) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). No significant differences at 14 dpi among experimental groups were observed (p\u0026thinsp;=\u0026thinsp;0.668).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean values of intestinal morphometric parameters, villus height (VH), crypt depth (CD) and VH:CD ratio, at 7 and 14 dpi.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003e7 dpi\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBenign\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHarmful\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eInvasive\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSEM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVH (\u0026micro;m)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e523\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e620\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e548\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e594\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0377\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD (\u0026micro;m)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e108\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e140\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e136\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e156\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0021\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVH:CD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.848\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.526\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.073\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.910\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0089\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003e14 dpi\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBenign\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHarmful\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eInvasive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSEM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVH (\u0026micro;m)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e523\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e557\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e583\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e580\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.203\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD (\u0026micro;m)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.087\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVH:CD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.537\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.369\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.460\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.668\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003csup\u003ea,b\u003c/sup\u003e Different letters mean statistically significant differences among groups.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMicrobiota α-diversity and β-diversity\u003c/p\u003e \u003cp\u003eThe microbiota composition of the caecum was analyzed at 2-, 7- and 14-dpi.\u003c/p\u003e \u003cp\u003eThe α-diversity was longitudinally evaluated in each group through Shannon\u0026rsquo;s and Simpson\u0026rsquo;s indexes. Results for Shannon\u0026rsquo;s index are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Overall, all infected groups exhibited a different and disturbed microbiota composition compared to group C (p\u0026thinsp;=\u0026thinsp;0.04), with the strongest alterations observed at early time points (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e At 2 dpi, the lowest and the most unbalanced diversity was found in group B, being dominated by few genera and significantly different when compared with C (p\u0026thinsp;=\u0026thinsp;0.016) and H (p\u0026thinsp;=\u0026thinsp;0.047) groups. Also, the microbial diversity in group H was lower than in group C (p\u0026thinsp;=\u0026thinsp;0.047). At 7 and 14 dpi there were no significant differences among groups (p\u0026thinsp;=\u0026thinsp;0.37 and p\u0026thinsp;=\u0026thinsp;0.65, respectively), but a generalized decreased tendency of α-diversity at 7 dpi was observed in all groups, with group H showing the lowest median (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eβ-diversity analyses using quantitative (Bray-Curtis) and qualitative (Jaccard) metrics revealed temporal and group-specific differences in microbial community composition (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). At 2 dpi, both analyses demonstrated that infected groups clustered apart from the control when considered altogether (Adonis R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.31, p\u0026thinsp;=\u0026thinsp;0.001). This indicates that the 31% of the differences in community structure could be explained by the infection status. Pairwise comparisons showed that group B displayed the most distinct microbiota composition compared to the control, particularly in qualitative terms (Jaccard), while group I also differed significantly (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.026). In contrast, group H did not differ significantly from the control (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.108), suggesting a milder community shift. At 7 dpi, significant differences among groups persisted (Adonis R\u0026sup2; = 0.24, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.009), although the overall clustering pattern indicated a partial convergence between infected and control birds, suggesting a progressive recovery of microbial community structure. Even at 14 dpi, both analyses revealed significant differences between the microbiota composition of the infected groups and group C (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), as illustrated in the PCoA plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), indicating that microbial reorganization and strain-dependent dysbiosis persisted throughout the study period. However, the separation among infected groups became less distinct.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDifferential abundance analysis\u003c/p\u003e \u003cp\u003eANCOM-BC was used to identify significant taxonomic shifts at both genus and ASV levels across groups and time points (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e6\u003c/span\u003e). We focused on reporting those taxa with known relevance to gut health, fermentative function, or \u003cem\u003eCampylobacter\u003c/em\u003e-associated dysbiosis.\u003c/p\u003e \u003cp\u003eLongitudinally, the microbial changes were different among groups. Group C maintained a relatively stable microbial composition throughout the study, with few taxa showing significant changes. In contrast, infected groups (B, H and I) exhibited more pronounced and dynamic alterations, particularly at 7 dpi.\u003c/p\u003e \u003cp\u003eFocusing on the effect of the infection, we observed that \u003cem\u003eCampylobacter\u003c/em\u003e showed a marked and consistent pattern across infected groups, while it remained undetectable in group C throughout all study. At 2 dpi, the relative abundance of this genus was significantly higher in groups B and H, being also detected in group I, though at lower abundance. At 7 dpi, \u003cem\u003eCampylobacter\u003c/em\u003e persisted in all infected groups, maintaining its highest relative abundance in group B. By 14 dpi, reduced \u003cem\u003eCampylobacter\u003c/em\u003e levels were observed, compared to earlier time points in all infected groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe analyzed the differentially abundant genera among the different groups at each time point. Overall, infected groups showed reduced relative abundances of genera within Firmicutes such as \u003cem\u003eRuminococcus\u003c/em\u003e, \u003cem\u003eFaecalibacterium, Oscillospira\u003c/em\u003e and \u003cem\u003eCoprobacillus\u003c/em\u003e, compared to group C. At 2 dpi, an unclassified genus from \u003cem\u003eRikenellaceae\u003c/em\u003e family was undetectable in group C, nearly absent in group H, while being highly enriched in groups B and I. At 7 dpi, group-specific differences emerged: \u003cem\u003eEnterococcus\u003c/em\u003e was more abundant in groups C and H, with lower abundance in group I but absent in B; \u003cem\u003eBifidobacterium\u003c/em\u003e was more abundant in groups I and C; whereas \u003cem\u003eBacteroides\u003c/em\u003e showed a high relative abundance in groups B and H. At 14 dpi, several unclassified \u003cem\u003eClostridiales\u003c/em\u003e, such as an unclassified genus from \u003cem\u003eMogibacteriaceae\u003c/em\u003e family, together with \u003cem\u003eSubdoligranulum\u003c/em\u003e genus showed higher abundances in groups H and I. Additionally, \u003cem\u003eButyricicoccus\u003c/em\u003e showed higher relative abundances in the I group; \u003cem\u003eBilophila\u003c/em\u003e appeared exclusively in group H and \u003cem\u003eCoprobacillus\u003c/em\u003e showed a higher abundance in group H.\u003c/p\u003e \u003cp\u003eWe also performed the differential abundance analysis at ASV level. At 2 dpi, two specific ASVs classified as \u003cem\u003eLactobacillus\u003c/em\u003e were detected as differentially abundant, with the highest relative abundance observed in group B and in very low abundance in group C. At 7 dpi, a specific ASV classified as \u003cem\u003eOscillospira\u003c/em\u003e was detected in group B and C, with highest relative abundance in group C. Additionally, multiple ASVs classified as \u003cem\u003eBacteroides fragilis\u003c/em\u003e were differentially abundant across groups, with the most pronounced observed in group B, followed by C and H, being absent in group I. At 14 dpi, different ASVs, including \u003cem\u003eBacteroides, Ruminococcus, Faecalibacterium, Blautia and Bacteroides fragilis\u003c/em\u003e were identified. \u003cem\u003eFaecalibacterium prausnitzii\u003c/em\u003e was more abundant in group B, followed by H and C, while completely absent in group I. In contrast, \u003cem\u003eButyricicoccus pullicaecorum\u003c/em\u003e and \u003cem\u003eRuminococcus\u003c/em\u003e were predominantly detected in group I, with minimal representation in the others. Notably, \u003cem\u003eBacteroides fragilis\u003c/em\u003e remained absent in group I, but was consistently present in all other groups, most prominently in B. ASVs assigned to \u003cem\u003eBlautia\u003c/em\u003e and \u003cem\u003eAnaerofustis\u003c/em\u003e also appeared uniquely or more abundantly in group I, further supporting a strain-specific microbial signature that persists through late-stages of infection.\u003c/p\u003e\u003cp\u003eSCFA in cecal contents\u003c/p\u003e \u003cp\u003eThe concentrations of SCFA in cecal contents at days 2, 7 and 14 dpi were quantified in the four experimental groups. The mean results obtained (\u0026micro;mol/g) for each metabolite are presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e7\u003c/span\u003e only those SCFA which showed statistically significant differences between groups are presented.\u003c/p\u003e \u003cp\u003eThe cecal concentration of SCFAs varied over time post-infection, and the pattern differed for each fatty acid. At 2 dpi, formate levels were markedly higher in group C (911 \u0026micro;mol/g) compared to the infected groups (30.8\u0026ndash;143.5 \u0026micro;mol/g; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Isobutyrate was significantly higher in group C (p\u0026thinsp;=\u0026thinsp;0.017). Acetate showed numerically higher concentrations at group C and B compared to group H and I. Lactate and succinate accumulated in infected groups, particularly in the group H and I (lactate: 8\u0026ndash;9 \u0026micro;mol/g; succinate: 18.5\u0026ndash;32.6 \u0026micro;mol/g), while remaining low in C.\u003c/p\u003e \u003cp\u003eAt 7 dpi, formate increased in infected groups (245\u0026ndash;270 \u0026micro;mol/g) and dropped in group C (14.6 \u0026micro;mol/g). Acetate was lower in group I compared to group H. Propionate showed a numerically increase in infected groups. Butyrate remained similar across all groups except for group I, which showed the lowest level. Lactate and succinate decreased across H and I groups.\u003c/p\u003e \u003cp\u003eAt 14 dpi, SCFA levels largely stabilized. Group C retained higher acetate (60.5 \u0026micro;mol/g). Propionate increased in all groups compared to previous dpi. Succinate remained elevated only in group I (10.6 \u0026micro;mol/g; p\u0026thinsp;=\u0026thinsp;0.025), opposite to the other groups.\u003c/p\u003e \u003cp\u003eCorrelation between SCFA concentrations and microbiota composition\u003c/p\u003e \u003cp\u003eSpearman correlation analysis revealed no statistically significant associations after adjustment for multiple comparisons (q\u0026thinsp;\u0026gt;\u0026thinsp;0.10 for all correlations) at any timepoint. However, several moderate correlations with unadjusted p-values below 0.05 were observed and may reflect biologically relevant patterns between cecal SCFA concentrations and the relative abundance (log-transformed) of specific bacterial genera in the different infected groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn group C, \u003cem\u003eButyricicoccus\u003c/em\u003e was positively correlated with butyrate (ρ 0.65). \u003cem\u003eSphingomonas\u003c/em\u003e exhibited a positive association with lactate (ρ 0.65). On the contrary, a strong negative correlation was identified between \u003cem\u003eLactobacillus\u003c/em\u003e presence and lactate (ρ -0.73) showing that higher lactate accumulation was associated with lower abundance of \u003cem\u003eLactobacillus\u003c/em\u003e genus. For propionate, \u003cem\u003ePelomonas\u003c/em\u003e showed a moderate positive correlation (ρ 0.69), while \u003cem\u003eBlautia\u003c/em\u003e was negatively correlated (ρ -0.67).\u003c/p\u003e \u003cp\u003eIn group B, several taxa exhibited significant correlations with SCFAs. Some positive correlations were observed between \u003cem\u003eRikenellaceae\u003c/em\u003e and butyrate (ρ 0.65), \u003cem\u003eDorea\u003c/em\u003e and succinate (ρ 0.61), \u003cem\u003eMogibacteriaceae\u003c/em\u003e with propionate (ρ 0.53) and \u003cem\u003eFaecalibacterium\u003c/em\u003e and valerate (ρ 0.74). In contrast, negative correlations were also observed, particularly between \u003cem\u003eCampylobacter\u003c/em\u003e and isovalerate (ρ -0.56) and between \u003cem\u003eFaecalibacterium\u003c/em\u003e and succinate (ρ -0.57).\u003c/p\u003e \u003cp\u003eIn group H notably, positive correlations were observed between \u003cem\u003eClostridium\u003c/em\u003e and multiple SCFAs (e.g., propionate (ρ 0.72) and valerate (ρ 0.68)), as well as \u003cem\u003eBifidobacterium\u003c/em\u003e with lactate (ρ 0.65) and \u003cem\u003eSphingomonas\u003c/em\u003e with valerate (ρ 0.75). Negative associations were noted for \u003cem\u003eCampylobacter\u003c/em\u003e, particularly with acetate (ρ -0.67) and propionate (ρ -0.59).\u003c/p\u003e \u003cp\u003eFinally, in group I, positive correlations were observed between \u003cem\u003eBifidobacterium\u003c/em\u003e and formate (ρ 0.54), as well as \u003cem\u003eBacteroides\u003c/em\u003e and isobutyrate (ρ 0.65). Valerate was positively correlated with \u003cem\u003eSubdoligranulum\u003c/em\u003e (ρ 0.57). In contrast, negative correlations were identified for an unclassified \u003cem\u003eLachnospiraceae\u003c/em\u003e genus and \u003cem\u003eBacteroides\u003c/em\u003e with acetate (ρ -0.52, -0.53). \u003cem\u003eCampylobacter\u003c/em\u003e also showed a negative correlation with isovalerate (ρ -0.43). Additionally, \u003cem\u003eBacteroides\u003c/em\u003e also correlated negatively with butyrate (ρ -0.62), lactate (ρ -0.64) and succinate (ρ -0.74).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eConcentrations (\u0026micro;mol/g) of SCFA in cecal contents at days 2, 7 and 14 post infection (dpi) in each experimental group. Benign: infected group with the benign strain; Harmful: infected group with the harmful strain; Invasive: infected group with the liver strain. Means obtained for each experimental group and metabolite are shown. Different letters mean significant differences among groups for each SCFA and day.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"15\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003e2 dpi\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c10\" namest=\"c7\"\u003e \u003cp\u003e7 dpi\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c15\" namest=\"c12\"\u003e \u003cp\u003e14 dpi\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBenign\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHarmful\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eInvasive\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eBenign\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eHarmful\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eInvasive\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eBenign\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003eHarmful\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003eInvasive\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcetate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e51\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e47.2\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e58.5\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e41.9\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e60.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e46.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e55.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e43.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eButyrate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e14.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e8.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e11.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e12.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e13.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFormate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e911\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e143.5\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.4\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.8\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e245.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e270.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e261.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e23.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e38.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e18.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e19.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsobutyrate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.3\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.4\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.3\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.35\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.27\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.44\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.63\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsovalerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.54\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.21\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.59\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.19\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.15\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.21\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.31\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.15\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLactate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePropionate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e6.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSuccinate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.5\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.7\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.5\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32.6\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e2.1\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e2.6\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e2.6\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e10.6\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eValerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study provides a multidimensional view of the effects of \u003cem\u003eC. jejuni\u003c/em\u003e infection in broilers, evaluating the impact of three \u003cem\u003eC. jejuni\u003c/em\u003e strains with different pathogenic potential on performance, immune response, intestinal morphometry, cecal microbiota composition, and SCFA production.\u003c/p\u003e \u003cp\u003eThe three strains were selected from a subset of strains from our strain collection, after an initial grouping of these strains as benign, harmful or invasive. The benign strain was isolated from a flock with low FCR and overall good performance, suggesting commensal behavior. In contrast, the potentially harmful strain was recovered from a high-FCR flock showing poor productivity, supporting a possible adverse or negative implication for bird health. The invasive strain was isolated from the internal liver tissue, indicative of its capacity for translocation outside the gut. Genomic data of the subset of strains from each group (data not shown) were used for the final selection of the three strains used in the experimental infection, based on the presence or absence of virulence-associated genes and accessory genes. The harmful strain was the only one carrying the \u003cem\u003emaf4\u003c/em\u003e gene, which is thought to enhance persistence and immune evasion in poultry contexts (Van Alphen et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Both the harmful and invasive strains carried the \u003cem\u003eneuA1\u003c/em\u003e gene, involved in sialylation of surface structures, which may facilitate immune evasion and have been associated with post-infectious sequelae like Guillain-Barr\u0026eacute; syndrome (A. Karlyshev et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). They also shared the \u003cem\u003ehddC\u003c/em\u003e gene, crucial for heptose biosynthesis within the capsular polysaccharide (A. V. Karlyshev et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Accessory genome analysis further reinforced the functional divergence among the strains. The benign strain stood out for functions suggestive of metabolic adaptability and stable colonization, the harmful strain for elements linked to competitiveness and host impact, and the invasive isolate for genes potentially enhancing stress tolerance and extraintestinal survival.\u003c/p\u003e \u003cp\u003eAccording to the data published in the PubMLST database, all three \u003cem\u003eC. jejuni\u003c/em\u003e strains belong to ST and CC which have been predominantly isolated from human samples (ranging from 47% to 84% of records), followed by chicken-related sources (from 6% to 24% of records).\u003c/p\u003e \u003cp\u003e \u003cem\u003eC. jejuni\u003c/em\u003e established rapidly and persistently in the caeca in experimentally challenged birds and was recovered from all but one infected bird by 2 dpi and from all sampled birds at 7 and 14 dpi; occasional translocation to the liver occurred in up to three birds per group. These findings mirror earlier work demonstrating that oral challenge reliably induces consistent cecal carriage by 2 or 3 weeks of age (Awad et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Connerton et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), with sporadic extraintestinal spread under certain strain and host conditions.\u003c/p\u003e \u003cp\u003eBroilers infected with the harmful and invasive strains exhibited a FCR impairment at 14 dpi, whereas the benign strain had no measurable effect. This lower feed efficiency aligns with previous studies reporting that subclinical \u003cem\u003eC. jejuni\u003c/em\u003e infection can produce moderate performance deficits via compromised nutrient absorption secondary to mucosal damage (Awad et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Naseri et al., 2012).\u003c/p\u003e \u003cp\u003ePrevious studies showed the chicken immune system being inefficiently activated, allowing high-level, asymptomatic colonization, which contributed to the persistence of \u003cem\u003eCampylobacter\u003c/em\u003e colonization (Hermans et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Meade et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Our finding of a 8\u0026ndash;12‐fold surge in cecal IFN-γ expression at 7 dpi in birds infected with invasive and harmful strains indicates a strong T helper type 1 (Th1) response that likely contributes to an inflammatory response, epithelial disruption and to the mild FCR impairment similar to what was found in other studies (Chagneau et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Mortada et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Furthermore, marginal or downregulated IL-6 in those same groups at 7 dpi parallels Mortada et al., (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) observation that the expression of chicken IL-6 cytokine may be significantly downregulated. However, it contrasts with Al-Banna et al., (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) that proposed IL-6 as a key driver of early inflammatory signaling in human campylobacteriosis. The pronounced Th1-type bias, marked by this elevated IFN-γ and reduced IL-6 in the groups infected with the harmful and invasive strains likely contributes to epithelial barrier disruption (Mortada et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), whereas a more balanced Th1/Th2 profile may allow \u003cem\u003eC. jejuni\u003c/em\u003e cecal persistence without pathology as also suggested by Wigley (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The bile sIgA kinetics we observed, generally rising with age is similar to what Lacharme-Lora et al., (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) reported, other than peaking unusually in group B at 7 dpi. Moreover, the sIgA can be also variably induced by different colonization patterns as reported by Gloanec et al., (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Chagneau et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) further showed that systemic (IgY) and local (IgA) humoral responses coincide with the possibility of hepatic dissemination and Th1/Th2 shifts.\u003c/p\u003e \u003cp\u003eAt the structural level, \u003cem\u003eC. jejuni\u003c/em\u003e infection has been associated with intestinal morphological alterations, including decreased VH, and increased CD, reducing the absorptive area, compromising epithelial barrier integrity and the nutrient uptake (Awad et al., 2015). In our study, infection with the invasive and harmful strains induced a drop in VH:CD ratio in the ileum at 7 dpi. This transitory intestinal structure impairment at 7 dpi, followed by partial recovery at 14 dpi, parallels Awad et al., (2015) early-challenge model, in which mucosal injury peaks within the first week post‐infection but subsequently resolves. Previous studies emphasize that VH:CD measurements remain the gold-standard biomarker for poultry intestinal health, with lower ratios consistently associated with dysbiosis and epithelial dysfunction (Ducatelle et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eLongitudinal analysis of cecal microbiota diversity following \u003cem\u003eC. jejuni\u003c/em\u003e challenge reveals a rapid, strain-dependent dysbiosis that parallels and extends findings in the literature (Oakley \u0026amp; Kogut, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Valečkov\u0026aacute; et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The early and pronounced decline in α-diversity observed across all infected groups suggests that \u003cem\u003eC. jejuni\u003c/em\u003e infection disrupts microbial homeostasis during a critical window of intestinal maturation. This drop in species\u0026rsquo; richness and evenness reflects both a direct microbial displacement by \u003cem\u003eCampylobacter\u003c/em\u003e and an indirect effect through host immune activation. Given the known role of microbial diversity in maintaining colonization resistance, these patterns support the notion that \u003cem\u003eC. jejuni\u003c/em\u003e promotes dysbiosis that may facilitate its own persistence. These findings align with those of Valečkov\u0026aacute; et al. (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) reporting that \u003cem\u003eC. jejuni\u003c/em\u003e colonization in broilers precipitates an early collapse in α-diversity with partial recovery by the end of the period (slaughter age). The sharp reduction in α-diversity observed in all infected groups at 2 dpi, when compared to group C, strongly supports a direct impact of \u003cem\u003eC. jejuni\u003c/em\u003e infection rather than a natural fluctuation over time. While Qi et al., (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and Richards et al., (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) showed a consistent trajectory of increasing α-diversity in developing broilers; the early loss of richness and evenness in infected birds clearly deviates from this pattern, reinforcing the infection-driven nature of dysbiosis.\u003c/p\u003e \u003cp\u003eBoth quantitative (Bray\u0026ndash;Curtis) and qualitative (Jaccard) β-diversity metrics demonstrated that \u003cem\u003eC. jejuni\u003c/em\u003e challenge induces an immediate and strain-specific restructuring of the broiler cecal microbiota composition. Already at 2 dpi, all infected groups diverged from the control group, indicating that even at early stages of colonization by \u003cem\u003eC. jejuni\u003c/em\u003e, disruption of the composition of the microbiota occurs. Importantly, this effect was not limited to the strains with higher pathogenic potential, as group B also exhibited distinct community profiles. The alterations in cecal microbiota observed at early stages persisted over time. Bray\u0026ndash;Curtis analysis showed that groups I and B remained more distinct from the control by the end of the study. The persistent divergence of group I suggests a longer lasting or more profound disruption, which could be linked to reduced SCFA production and slower recovery of key beneficial taxa. These different trajectories illustrate that \u003cem\u003eC. jejuni\u003c/em\u003e infection does not simply lower microbial diversity but actively reorganizes microbial networks in ways that may affect host health and pathogen persistence.\u003c/p\u003e \u003cp\u003eSimilarly, Pang et al. (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), showed that \u003cem\u003eC. jejuni\u003c/em\u003e positive flocks develop stable, farm-specific β-diversity profiles clearly distinct from \u003cem\u003eCampylobacter\u003c/em\u003e-negative flocks, and Di Marcantonio et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) found enduring, flock-specific community shifts linked to pathogen carriage. Our experimental infections also demonstrate that each \u003cem\u003eC. jejuni\u003c/em\u003e strain imprints a strain-specific β-diversity signature in broiler caeca, which remains differentiated from group C across time points, although the magnitude and direction of these differences evolve throughout the infection course.\u003c/p\u003e \u003cp\u003eANCOM-BC analyses at both genus and ASV level revealed a dynamic, strain-dependent remodeling of the cecal microbiota composition, extending previous observations in poultry infection and gut-microbiome diversity.The concurrent bloom of \u003cem\u003eRikenellaceae\u003c/em\u003e and \u003cem\u003eCampylobacter\u003c/em\u003e in groups B and I at 2 dpi suggests a potential synergistic interaction, where pathogen-induced mucosal or metabolic changes facilitate \u003cem\u003eRikenellaceae\u003c/em\u003e expansion. Given the fermentative capacity of \u003cem\u003eRikenellaceae\u003c/em\u003e and their early increase post-challenge, these taxa could act either as opportunistic colonizers of a disrupted niche or as functional enablers of \u003cem\u003eCampylobacter\u003c/em\u003e persistence. Members of \u003cem\u003eRikenellaceae\u003c/em\u003e, belonging to \u003cem\u003eBacteroidetes\u003c/em\u003e, are core inhabitants of the chicken caecum, implicated in polysaccharide fermentation and propionate production (Rychlik, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Similarly, another experimental \u003cem\u003eC. jejuni\u003c/em\u003e challenge in broilers triggered an early bloom of Bacteroidetes, especially \u003cem\u003eBacteroides\u003c/em\u003e, at 3 dpi, suggesting these lineages exploit ecological niches vacated by pathogen‐driven community shifts (Valečkov\u0026aacute; et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eConcurrently, at 2 dpi, classical fermenters within Firmicutes, including \u003cem\u003eRuminococcus\u003c/em\u003e, \u003cem\u003eFaecalibacterium\u003c/em\u003e and \u003cem\u003eOscillospira\u003c/em\u003e (Rychlik, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Yang et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), were reduced in all infected groups compared to the group C. These genera are key butyrate producers and barrier-protective taxa in healthy broilers; their loss aligns with reports that shows how \u003cem\u003eC. jejuni\u003c/em\u003e dysbiosis suppresses SCFA-producing consortia, increasing inflammation and impairing nutrient uptake (Awad et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Fan et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Notably, group I, which showed the lowest cecal butyrate concentration, also exhibited the most pronounced reduction in VH:CD ratio at 7 dpi. While these measurements were taken from distinct intestinal segments, the observation supports a functional link between microbiota, SCFA reduction and epithelial atrophy, consistent with the role of butyrate as a major energy source for enterocytes and a driver of intestinal health. At 2 dpi all experimental groups showed higher levels of \u003cem\u003eBifidobacterium\u003c/em\u003e, known for its role in gut barrier integrity and mucosal health (Bindari \u0026amp; Gerber, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and by 7 dpi, was notably reduced in all groups and nearly absent in group B. This mirrors previous studies which showed that \u003cem\u003eBifidobacteriales\u003c/em\u003e act as early cecal colonizers in broilers (Mancabelli et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAt 7 dpi, in group B, \u003cem\u003eBacteroides\u003c/em\u003e heavily increased, probably taking advantage of empty niches left by reduced Firmicutes, whereas in other groups these niches remained occupied. Similar opportunistic blooms of \u003cem\u003eBacteroides\u003c/em\u003e following \u003cem\u003eC. jejuni\u003c/em\u003e challenge have been reported before by Hankel et al., (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and Valečkov\u0026aacute; et al., (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAt 14 dpi, changes became more strain specific. The results reflect biologically relevant patterns linked to infection dynamics and suggest that the cecal microbiota shows small but specific differences between infecting strains. The genera \u003cem\u003eFaecalibacterium\u003c/em\u003e, \u003cem\u003eRuminococcus\u003c/em\u003e and \u003cem\u003eBlautia\u003c/em\u003e all rebounded in I and H groups, suggesting that certain Clostridiales lineages more readily re-establish post-challenge, consistent with Rychlik, (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) which noted that cecal Clostridiales possess diverse carbohydrate-fermenting capabilities essential for community recovery.\u003c/p\u003e \u003cp\u003eASV-level ANCOM-BC uncovered strain-specific shifts masked at the genus level. These findings echo Lin \u0026amp; Peddada, (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) recommendations that high-resolution ASV analysis reveal small details in community shifts otherwise overlooked.\u003c/p\u003e \u003cp\u003eOur cecal SCFA data reveal a dynamic, again, strain-specific fermentative response to \u003cem\u003eC. jejuni\u003c/em\u003e challenge that closely mirrors shifts in community composition and aligns with findings from other studies in broiler chickens (Al Hakeem et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Awad et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Fan et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Although most correlations between bacterial genera and SCFA concentrations were group-specific, some consistent patterns emerged. Generally, SCFA-producing Firmicutes such as \u003cem\u003eFaecalibacterium\u003c/em\u003e, \u003cem\u003eRuminococcaceae\u003c/em\u003e, and \u003cem\u003eButyricicoccus\u003c/em\u003e exhibited positive correlations with key metabolites like butyrate and propionate in several groups, reinforcing their functional relevance in gut recovery and highlighting their potential as microbial biomarkers of resilience.\u003c/p\u003e \u003cp\u003eSpecifically, at 2 dpi, infected birds exhibited a dramatic decline in butyrate and formate alongside succinate accumulation, consistent with Awad et al., (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Early blooms of \u003cem\u003eBacteroides\u003c/em\u003e and lactate-producers suggest opportunistic expansion in niches vacated by fermenters (Valečkov\u0026aacute; et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). At 7 dpi, formate levels were markedly higher in all infected groups, potentially via blooms of \u003cem\u003eRikenellaceae\u003c/em\u003e and succinate‐to‐formate converters, indicating metabolic adaptation or restructuration of the microbiota. Butyrate remained relatively stable across groups except in group I, where it declined significantly, consistent with delayed recovery of butyrate-producing \u003cem\u003eFaecalibacterium\u003c/em\u003e, \u003cem\u003eRuminococcus\u003c/em\u003e and \u003cem\u003eBlautia\u003c/em\u003e. Meanwhile, succinate began to normalize in groups B and H, suggesting a possible functional recovery, but stayed elevated in group I, underscoring strain‐specific persistence of dysbiosis. At 14 dpi, a general trend towards stabilization of the fermentation profile was observed in most groups. Acetate and propionate reached values similar to group C in groups B and H, indicating a possible reactivation of healthy fermentation and reflecting re‐establishment of acetate‐producers (\u003cem\u003eRuminococcus\u003c/em\u003e, \u003cem\u003eOscillospira\u003c/em\u003e) as described by Rychlik, (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Butyrate also remained high in these groups, consistent with renewed growth of \u003cem\u003eFaecalibacterium\u003c/em\u003e which could produce butyrate by acetyl-CoA acetyl-transferase (Polansky et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). However, group I maintained the lowest butyrate and the highest succinate levels, suggesting persistent functional imbalance of the microbial ecosystem. The low lactate concentration in all infected groups indicates a partial recovery of microbial balance. Although none of the correlations between microbiota composition and SCFAs production were not significant after false discovery rate correction, several pointed to biologically relevant interactions deserving further investigations in larger sample sets.\u003c/p\u003e \u003cp\u003eTogether, these results reflect an early and marked alteration of cecal fermentative activity after infection, followed by differential recovery patterns among groups, with the group I showing the most limited recovery and a more dysbiotic metabolic profile.\u003c/p\u003e \u003cp\u003eThese strain-specific effects highlight both the heterogeneity in \u003cem\u003eC. jejuni\u003c/em\u003e pathogenic potential and the central role of gut microbiota in shaping infection outcomes. Our data suggest that beneficial taxa such as \u003cem\u003eFaecalibacterium\u003c/em\u003e, \u003cem\u003eRuminococcus\u003c/em\u003e and \u003cem\u003eButyricicoccus\u003c/em\u003e are linked to resilient, fermentatively balanced states, whereas \u003cem\u003eBacteroides\u003c/em\u003e bloom, loss of \u003cem\u003eFirmicutes\u003c/em\u003e fermenters, and succinate accumulation in group I point to a microbiome vulnerable to disruption. Importantly, the identification of specific microbial lineages linked to SCFA recovery and mucosal homeostasis provides a basis for targeted probiotic interventions. Enriching taxa that support butyrate and acetate production, could mitigate the dysbiosis caused by \u003cem\u003eC. jejuni\u003c/em\u003e colonization, improve poultry performance and welfare, and may help reduce intestinal loads of this zoonotic pathogen, thereby improving food safety.\u003c/p\u003e \u003cp\u003eIn conclusion, this study underscores the broad, strain-dependent impact of \u003cem\u003eC. jejuni\u003c/em\u003e infection in broilers, ranging from harmless or near-commensal colonization with minimal microbiota disruption to marked dysbiosis characterized by epithelial injury, proinflammatory responses, altered fermentation patterns, leading to performance impairment. Our results reinforce the microbiota as both a target and tool in combatting \u003cem\u003eCampylobacter\u003c/em\u003e infection and support future research into precision microbiota-based strategies to improve broiler resilience and reduce zoonotic risk in poultry production systems.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eA.M-P conducted farm and laboratory experiments, analyzed and interpreted the data and wrote the draft manuscript. F.C-F assisted with microbiota data analysis and interpretation. P.O-G assisted with microbiota data analysis. A.D assisted with immune response characterization. T.A conducted wet lab experiments. B.V assisted with analysis of SCFA production and with performance parameters data analysis and interpretation. M.N and M.C-C conceptualized and designed the study, assisted in farm and lab experiments, analyzed and interpreted the data, revised and checked the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThis study was supported by the Spanish Ministry of Science and Innovation (grant No. RTI2018-095081-B-I00) and the Spanish Ministry of Science, Innovation and Universities (grant No, PID2021-128079OB-I00). A. M. P. was supported by a pre-doctoral fellowship FPI 2019 from the Spanish Ministry of Science, Innovation and Universities (PRE2019-087435). Technical support of Ana P\u0026eacute;rez de Rozas, N\u0026uacute;ria Aloy and Judith Gonz\u0026aacute;lez is greatly appreciated; Diego P\u0026eacute;rez and Alcarr\u0026agrave;s IRTA farm staff support are also appreciated. CERCA from the Generalitat de Catalunya is acknowledged.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAll data supporting the findings of this study are available within the paper and its Supplementary Files.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAl Hakeem, W. G., Cason, E. E., Adams, D. A., Villanueva, K. Y. A., Shanmugasundaram, R., Lourenco, J., \u0026amp; Selvaraj, R. K. (2024). 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Oscillospira\u0026mdash;A candidate for the next-generation probiotics. \u003cem\u003eGut Microbes\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e(1), 1987783. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/19490976.2021.1987783\u003c/span\u003e\u003cspan address=\"10.1080/19490976.2021.1987783\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Campylobacter, immune response, intestinal health, gut microbiota, SCFA","lastPublishedDoi":"10.21203/rs.3.rs-8346657/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8346657/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003e \u003cem\u003eCampylobacter jejuni\u003c/em\u003e is the leading cause of foodborne enteritis. Although typically a commensal of the avian gut, it can induce pro-inflammatory responses, damage intestinal integrity and affect broilers\u0026rsquo; performance. To understand the host response to \u003cem\u003eCampylobacter\u003c/em\u003e infection, ROSS 308 male broiler chickens were experimentally infected at 21 days of age with three \u003cem\u003eC. jejuni\u003c/em\u003e strains of different pathogenic potential (potentially benign, potentially harmful and invasive). An unchallenged group served as control.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAfter infection, feed conversion rate was significantly impaired by 3% in groups infected with the harmful and invasive strains. At 2-, 7- and 14-days post-infection (dpi), 10 birds per group were euthanized for \u003cem\u003eCampylobacter\u003c/em\u003e isolation, evaluation of immune response, intestinal morphometry, microbiota composition and determination of short chain fatty acids. \u003cem\u003eC. jejuni\u003c/em\u003e was recovered from all caeca samples from all infected groups and timepoints except for one infected bird at 2 dpi. At 7 dpi significant increase was observed in interferon gamma gene expression in chickens infected with the harmful and invasive strains, while bile secretory immunoglobulin A levels were elevated in all challenged groups. At this timepoint, chickens infected with harmful and invasive strains showed a reduced villus height:crypt depth ratio. Microbiota analysis revealed reduced α-diversity in infected birds, especially at 2 dpi. β-diversity showed distinct microbial clustering between control and infected groups at early timepoints, confirming infection-driven dysbiosis. Several differentially abundant genera were identified at early timepoints including enrichment of \u003cem\u003eFaecalibacterium\u003c/em\u003e in controls, higher abundance of an unclassified \u003cem\u003eRikenellaceae\u003c/em\u003e genus in benign and invasive infected groups, and increased \u003cem\u003eClostridiales\u003c/em\u003e taxa at later timepoints in harmful and invasive infected groups. At early timepoints, infected chickens showed reduced butyrate and formate levels, along with increased lactate and succinate accumulation, particularly in chickens infected with the invasive strain. These metabolic changes reflect functional shifts in microbial activity associated with dysbiosis.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThese results underscore the strain-specific pathogenic potential of \u003cem\u003eC. jejuni\u003c/em\u003e in broilers, ranging from gut commensals to disruptors of intestinal integrity, highlighting the need for in-depth studies of \u003cem\u003eCampylobacter\u003c/em\u003e biology for targeted control strategies, to improve animal health and control its spread to humans.\u003c/p\u003e","manuscriptTitle":"Campylobacter jejuni strains with different pathogenic potential shapes host-pathogen interactions and gut microbiota dynamics","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-19 16:29:41","doi":"10.21203/rs.3.rs-8346657/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c86d7f2c-6516-4325-9bee-c4c4d4d5c0a9","owner":[],"postedDate":"January 19th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-10T15:12:06+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-19 16:29:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8346657","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8346657","identity":"rs-8346657","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}