Preventive Antibiotic Treatment Increases Suscepti bility of Neonatal chicks to Salmonella Infection via Disrupting Gut Microbiota and Linoleic Acid Metabol is

Background: Antibiotics are widely employed in animal husbandry to prevent and treat diseases. Increasing evidence suggests they may alter the animals’ natural microbiota and increase their susceptibility to pathogen. However, the mechanisms linking the gut microbiota and pathogen colonization in poultry have not yet been full elucidated. Herein, we used metagenomic and metabonomic approaches to investigate the effects of orfenicol (FFC) pre-treatment on Salmonella enterica serovar Enteritidis (S. Enteritidis) colonization in the intestines of neonatal chicks in terms of host response, microbiota composition and metabolism. Results: We determined that FFC pre-treatment signicantly alters the cecal microbiota and metabolome, and also increases the intestinal permeability and promotes a pro-inammatory gene expression prole in the host. Host physiological changes were concordant with signicantly increased susceptibility to S. Enteritidis infection in chicks with FFC pre-treatment relative to without pre-treatment chicks. Prior to Salmonella infection, FFC pre-treatment signicantly reduced the abundance of Lactobacillus, and signicantly affected linoleic acid metabolism, including signicantly reducing the levels of conjugated linoleic acid (CLA), and signicantly elevating the abundance of 12,13-EpOME and 12,13-diHOME in cecum. After infection with S. Enteritidis, the abundance of Proteobacteria were signicantly increased and host inammatory responses and intestinal permeability were signicantly aggravated relative to without FFC pre-treatment chicks, suggestive of a profound exacerbating of the host response inuenced by infection in the context of FFC pre-treatment. The linoleic acid metabolism was still signicantly different pathway after Salmonella infection, and we screened CLA and 12,13-diHOME as the target metabolites using a multi-omics technique. Supplementation with CLA maintained intestinal integrity, reduced intestinal inammation, and accelerated Salmonella clearance from the gut and remission of enteropathy. Whereas, treatment with 12,13-diHOME promoted intestinal inammation and disrupted the intestinal barrier function to sustain Salmonella infection. Therefore, orfenicol reduces production of CLA by inhibiting Lactobacillus growth, increases 12,13-diHOME level of intestine, thereby reducing colonization resistance of neonatal chicks to Salmonella infection. Conclusion: This study reveals the potential health impact of antibiotics on gut microbiota and linoleic acid metabolism and contributing factors inuencing Salmonella colonization in neonatal chicks, and provides mechanistic understanding into the role of the antibiotics promote the colonization of pathogens.

Furthermore, neonatal chicks exhibit high susceptibility to infections with Salmonella serovars because of their immature gut microbiota; the complexity of which gradually increases from day 1 to day 19 of life [24,25]. Nonetheless, chickens are coprophagic and the transfer of cecal microbiota from adult chickens to neonatal chicks increases resistance to Salmonella infection [26,27]. Unlike other farm animals, neonatal chicks are hatched in the clean environment of a hatchery, without any contact with adult chickens and their colonization resistance is only dependent on the environment [28]. If a pathogen is present in the environment, the immature gut microbiota of a newly hatched chick essentially enables its unrestricted multiplication. Therefore, large-scale intensive rearing systems typically depend on antibiotics to prevent and control disease outbreaks, which disrupt the gut microbiota of chicks and facilitate higher susceptibility to Salmonella infections.
We hypothesize that pre-treatment of newly hatched chicks with antibiotics is accompanied by changes in their gut microbiota and metabolic pro le, which result in increased susceptibility to Salmonella infections. Therefore, a greater understanding of how antibiotics affect the mechanism of colonization resistance is required. The objectives of the present study were to investigate the in uence of a 7-day treatment course of orfenicol, a commonly used broad-spectrum antibiotic in poultry in many countries [17,18,29], on the composition of the microbial community and metabolic pro le of neonatal chicks, and determine the potential factors that facilitate the growth of S. Enteritidis in the cecum.

Bacterial strains
Chicks were challenged with the S. Enteritidis (ATCC 13076) oR mutant strain. The S. Enteritidis oR mutant was constructed using a plasmid-based homologous recombination integration method as previously described [30]. Brie y, the oR gene (NG_047860.1) was synthesized and cloned into an E. coli cloning vector (pCVD442). The upstream and downstream homologous recombinant arms were ampli ed by PCR from the S. Enteritidis genome using ultra-delity DNA polymerase, and oR sequence was ampli ed by PCR from the template vector. The fragments were assembled by fusion PCR to construct the gene targeting fragment. The pCVD442 suicide plasmid was digested with restriction endonuclease (SmaI) to construct the gene targeting plasmid pCVD442-oR, which was transformed into E. coli SY327λpir. The plasmid pCVD442-oR was conjugated into S. Enteritidis using E. coli SY327λpir as a donor strain and plated on FFC-resistant chromogenic XLT4 agar for selection positive clones that integrated the suicide plasmid into their genome. Finally, FFC-resistant colonies were veri ed by PCR and gene sequencing. Prior to inoculation, S. Enteritidis was grown overnight in Luria-Bertani broth at 37 °C with shaking at 200 rpm.

Florfenicol intervention and S. Enteritidis infection
Leghorn layer chicks (1-day-old) were hatched from the same batch eggs of SPF birds (Beijing Boehringer Ingelheim Vital Biotechnology Co., Ltd., China), and each assigned group was reared in an individual GJ-1 SPF isolator (Suzhou Fengshi Laboratory Animal Equipment Co., Ltd., China). Animals received nonmedicated chick feed and water ad libitum; they were raised under controlled environmental conditions with a 16-h lighting cycle and a temperature of 32°C at day 1 which was gradually reduced and maintained at 24°C from day 10.
Animal protocol 1: effect of orfenicol pre-treatment on intestinal Salmonella colonization. Eighty-eight newly hatched chicks were assigned at random to four groups. Each group included 22 chicks for three time points (n = 7 to 8 chicks in each time point) and were treated with 30 mg/kg b. w. of FFC for 7 days or infected with approximately 10 8 CFU of the challenge strain S. Enteritidis by oral gavage. The groups were: (1) NT, control group neither FFC-treated nor S. Enteritidis-infected; (2) FT, FFC-treated group; (3) ST, S. Enteritidis-infected group; (4) and FST, FFC-pre-treated and S. Enteritidis-infected group. On days 11, 18, and 25, chicks were euthanized for analysis.
After chicks were euthanized, the cecal contents and internal organs were aseptically collected and homogenized in PBS. For enumerating Salmonella loads, an aliquot (100 μl) of appropriate dilutions was spread onto XLT4 agar plates (50 ug/ml orfenicol); Salmonella appeared as typical black colonies after incubation at 37 °C for 24 h.
Histopathology and microscopic analysis of the intestine Parts of ileal tissue were perfusion-xed with formalin for 24 h. After gradient dehydration with ethanol, specimens were embedded in para n. Subsequently, 5 μm sections were rehydrated and stained with Alcian blue. Representative images were obtained with a BA400 digital microscope (Motic Group CO., LTD., China). Mean staining densities were calculated from the integral optical densities and areas of positive Alcian blue staining using the Image-Pro ® Plus v6.0 analysis system (Media Cybernetics, USA). Statistical signi cance was determined by one-way ANOVA. A P-value of less than 0.05 was considered statistically signi cant. To determine the degree of lesion, the pathological score was monitored as previously described [32]. SEM (Inspect TM , FEI Ltd., USA) of the intestinal villi was performed as previously described [33].
DNA extraction, 16S rRNA gene sequencing, and data analysis Seven or eight chicks per treatment were randomly chosen at three time points: 11, 18, and 25 days of age, and euthanized by carotid artery bleeding. The cecal contents were collected within 5 min of euthanasia, immediately placed in pre-cooling cryogenic vials, and stored at −80 °C until DNA extraction.
Total genomic DNA was extracted from cecal contents using the QIAamp DNA Stool Mini Kit (Qiagen, Germany) according to the manufacturer's protocols, and stored at −20 °C until analysis. The concentration and quality of extracted DNA samples were measured by Nanodrop 2000 (Thermo Fisher Scienti c, Waltham, MA, United States) and agarose gel electrophoresis, respectively.
Using the isolated genomic DNA as template, the V3-V4 hypervariable regions of the bacterial 16S rRNA genes were PCR-ampli ed with primers 338F (5′-ACTCCTACGGGAGGCAGCA-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′) following previously described method [34]. Amplicons were then sequenced on the Illumina MiSeq platform (Illumina Inc., USA) using 2 × 250 bp cycles. These sequence data were deposited in the NCBI database (Bioproject PRJNA655362) under the accession number SRP277009. QIIME was employed to process the sequencing data. Briefly, raw sequencing reads with exact matches to the barcodes were assigned to respective samples and identified as valid sequences.
The low-quality sequences were ltered through the following criteria [35,36]: sequences that had a length of <150 bp, sequences with an average Phred scores of <20, sequences that contained ambiguous bases, and sequences that contained mononucleotide repeats of >8 bp. Paired-end reads were assembled using FLASH [37]. After chimera detection, the remaining high-quality sequences were clustered into operational taxonomic units (OTU) at 97% sequence identity by UCLUST [38]. A representative sequence was selected from each OTU using default parameters. OTU taxonomic classi cation was conducted by BLAST searches of the representative sequences set against the Greengenes Database [39] and the best hit was used for further analysis [40]. An OTU table was generated to record the abundance of each OTU in each sample and the taxonomy of these OTUs. OTUs containing less than 0.001% of total sequences across all samples were discarded. To minimize differences in sequencing depth across samples, an averaged, rounded rare ed OTU table was generated by averaging 100 evenly resampled OTU subsets under 90% of the minimum sequencing depth for further analysis.
Sequence data were analyzed using the QIIME and R software packages (v3.2.0) [41]. OTU-level alpha diversity indices, including Shannon indices, species abundance and Pielou indices were calculated using the OTU table in QIIME. Beta diversity analysis was performed to investigate the structural variation of microbial communities across samples using Bray-Curtis distances metrics and visualized via principal coordinate analysis (PCoA). Taxonomic compositions and relatives abundances were visualized using MEGAN [42] and GraPhlAn [43]. LEfSe was performed to detect differentially abundant taxa across groups using default parameters [44].
Quantitative PCR for microbiota analysis Bacterial composition of the microbiota was measured by qPCR as previously described [45][46][47][48]. All qPCR reactions were performed using the Bio-Rad real-time PCR detection system (Bio-Rad CFX Maestro 1.1, 3.0, USA) and SsoFast EvaGreen Supermix (Bio-Rad Inc., USA) according to the manufacturers' instructions. Genomic DNA from cecal samples was used as a template for qPCR using the main groupspeci c primers (Supplementary Table S1): all eubacteria, Lactobacillus, Bacteroidetes, Enterobacteriaceae, Clostridium butyricum and Faecalibacterium prausnitzii. Serial dilutions of plasmids containing the target gene cloned into the pMD-19 T cloning vector (TaKaRa, Dalian, China) were analyzed to generate standard curves and calculate absolute counts of target genes.

Metabolomics for chicken cecal content
Untargeted metabolomics. Chickens were sacri ced, and the cecum was resected. The cecal contents were obtained and stored at −80 °C until analysis. Sample preparation for LC/MS was performed as previously described [49]. Brie y, 50 mg freeze-dried sample, 800 μl methanol, and 5 μl DL-ochlorophenylalanine (internal standard) were added to a 1.5 mL Eppendorf tube. All samples were ground to ne powder using a grinding mill at 65 HZ for 90 s, vortexed for 30 s, and centrifuged at 12,000 rpm at 4°C for 15 min. Then, 200μL of supernatant was transferred to a new vial for LC-MS. A total of 10 μl of the sample solution at 4 °C was injected into the LC-MS system (Thermo, Ultimate 3000LC, Exactive Orbitrap) with an Agilent C18 column (Hypergod C18, 100 x 2.1 mm 1.9 μm) with the column temperature maintained at 40 °C. The mobile phase consisted of solutions A and B: A was 0.1% formic acid/5% acetonitrile/water (v/v/v) and B was 0.1% formic acid/acetonitrile (v/v). The ow rate was 350 μl/min. The gradient was set as: 0% B at 0 min, 20% B at 1.5 min, 100% B at 9.5 min to 14.5min, and 0% B at 14.6 min to 18min. Samples were analyzed in positive and negative ion modes using 300 °C heater temperature, 350 °C capillary temperature, and 3.0 KV spray voltage. The ow rates of sheath gas, auxiliary gas, and sweep gas were 45, 15, and 1 arb, respectively. Peaks were aligned according to m/z values and normalized migration time. Peak areas were calculated by normalizing against the internal standards. Metabolites were identi ed by searches against the database based on m/z values and normalized migration time. Compound Discoverer Software (Thermo) was used to process the Thermo RAW les. The data after editing were subjected to multivariate analysis using SIMCA-P 14.0 software (Umetrics AB, Umea, Sweden). Metabolites selected as biomarker candidates were identi ed on the basis of a VIP threshold of 1 from the sevenfold cross-validated OPLS-DA model, which was validated at a univariate level with adjusted P < 0.05. MetaboAnalyst (version 3.0) was used for the identi cation of metabolic pathways [50].
Targeted metabolomics. A 50 mg sample of dried cecal content and 800 μl methanol were added to a 1.5 mL Eppendorf tube. The sample was ground to a ne powder using a grinding mill at 65 HZ for 90 s followed by being vortexed for 30 sec, and centrifuged at 12,000 rpm at 4 °C for 15 min. Next, 200 μl of supernatant was used for detection.
For quantitative detection of linoleic acid and CLA, 1 μl of each sample was injected into a DB-5 column (60 m x 0.25 mm 0.25 μm) using a Thermo Trace 1300 GC (Thermo Fisher Scienti c, USA) system online with mass spectrometer (ISQ7000, Thermo Fisher Scienti c, USA) (GC-MS). The temperature program was as: initial oven temperature of 140 °C held for 5 min, increased at with 10 °C /min to 180 °C, at 4°C /min to 210 °C, and nally reached 260 °C at the rate of 10 °C /min, then held for 20 min. Helium (99.999% purity) was used as carrier gas with a ow rate of 1.5 ml/min. The MS inlet line and the ion source temperatures were maintained at 260 and 230 °C, respectively, and the MS ionization energy was 70 eV. A full scan mode set from 5 min to 20 min, monitoring m/z range from 33 to 550 Da, was used for the identi cation of possible interferences from the matrix extract.

RNA isolation and RT-qPCR
Total RNA from the ileum and liver tissue was extracted using Trizol reagent (Invitrogen Life Technologies, Carlsbad, CA) according to the manufacturer's instructions. The quality and concentration of RNA were measured using a Nanodrop 2000 spectrophotometer. One microgram of total RNA from each sample was reverse transcribed into cDNA using a SuperScript II kit (Invitrogen Life Technologies, Carlsbad, USA) using oligo (dT) primer and random hexamer primers. The qPCR reaction was performed with the SsoFast EvaGreen Supermix using a Bio-Rad CFX real-time PCR detection system following the manufacturer's protocols. Primers listed in Supplementary Table S1 [51,52]. Relative mRNA expression levels of each target gene were calculated using the log 2 of the fold change method. Triplicate parallel reactions were run for all samples.

Data and statistical analysis
The heatmap of the interrelationship between the differential ora and the metabolites was generated using the R (3.6.1) pheatmap package. The calculated correlation coe cient (R < 0.5) was used to exclude metabolites and ora with weak correlation and no correlation. Cytoscape (3.7.1) software was used to draw the correlation network diagram; the ora and metabolites were used to form points and line segments represent the correlation size. The distributions of bacterial communities and their potential correlations with differential metabolites were determined using CCA, using the R (3.6.1) vegan package. Statistical analyses were conducted with SPSS 20.0 (SPSS Inc., USA). Data collected are presented as geometric medians or means ± standard deviation. Statistical signi cance was determined by Mann-Whitney tests or one-way ANOVA. The Mann-Whitney test was used for comparing two groups. One-way ANOVA with a Dunnett's multiple comparison test was used for pair-wise comparison of means from more than two groups in relation to the control group. The p values of less than 0.05 were considered statistically signi cant (*p < 0.05; **p < 0.01; ***p < 0.001).

Florfenicol exposure increases susceptibility to S. Enteritidis infection
We established a study design (Fig. 1a) in which SPF chicks were divided into four groups: orally administered orfenicol (FT); S. Enteritidis-infected by oral gavage (ST); simultaneously of FFC-treated and S. Enteritidis infected (FST); and an untreated control group (NT). Under the SPF environment, all chicks cultured negative for Salmonella spp. until experimental infection with S. Enteritidis. The control group remained culture negative for Salmonella spp. throughout the study. The colonization and translocation of S. Enteritidis in the intestinal tract of chicks directly determines its survival and pathogenicity. Therefore, we quanti ed S. Enteritidis levels in the caecum, spleen, and liver. The number of S. Enteritidis (log10 CFU/g tissue) signi cantly increased by 25.49% (cecal contents, P < 0.01), 23.04% (spleen, P < 0.01) and 21.33% (liver, P < 0.01), respectively, in the FST group relative to that of in the ST group at 3 days post-infection (dpi). Similar results were observed at days 18 (10 dpi) and 25 (17 dpi), although the Salmonella loads were less than those observed at 3 dpi (Fig. 1b).

Florfenicol administration aggravates S. Enteritidis-induced intestinal morphology and barrier injury
As FFC intervention made the chicks more susceptible to Salmonella infection, it is possible that antibiotics disrupted the immature intestinal barrier homeostasis of chicks, altered intestinal permeability, and facilitated greater translocation of Salmonella to their internal organs. Therefore, we investigated the effects of FFC administration on S. Enteritidis-induced changes in intestinal morphology. Hematoxylin and eosin (H & E) staining showed that the chicks in the NT group exhibited an intact ileal mucosa, neat intestinal villi, deep crypts, and a clear and complete gland structure, similar to that observed for the FT group ( Fig. S1a and b). The ST group displayed an incomplete structure of the ileal mucosa, villi had a shorter length and sparse distribution, and crypts were shallow (Fig. S1c). However, the FST group morphology included loss of mucosal structures, atrophic crypts, and lamina propria bowel edema (Fig.  S1d). Histological injury (Fig. S1e) was scored based on H & E-stained images; the scores indicated tissue damage. The score for the ST group (7.13 ± 0.44) was signi cantly higher than control (0.63 ± 0.18). Relative to the ST group, FFC pre-administration signi cantly increased the ileum injury score (10.75 ± 0.45). Scanning electron microscopy (SEM) showed that the NT group had complete ileal villi, forming full and closely arranged structures (Fig. 2e), whereas the FT group also had intact ileal villi, but their arrangement was relatively loose (Fig. 2f). As expected, the ileal villi of the ST group were damaged (Fig.  2g) and those of the FST group showed more severe damage (Fig. 2h). These results suggested that although FFC has less effect on intestinal morphology, intestinal injury was aggravated by Salmonella invasion.
An effect of FFC on intestinal barrier function in the ileum after S. Enteritidis infection was also observed exacerbating. The FFC pre-treatment can exacerbate the S. Enteritidis-induced increase in permeability of the Ileum (Fig. 3a-d). The serum diamine oxidase (DAO) and lipopolysaccharide (LPS) levels of the FT group were signi cantly higher (P < 0.001 and 0.05 respectively) than those of the NT group ( Fig. 3c and d). In the case of Salmonella infection, serum D-lactate, DAO, and LPS levels in both the ST and FST groups were signi cantly increased (P < 0.001) relative to those of the NT group. However, FFC treatment signi cantly increased (P < 0.001) serum D-lactate, DAO, and LPS levels in chicks exposed to Salmonella (Fig. 3b-d). Alcian blue staining indicated that FFC signi cantly decreased (P < 0.05) the acidic mucin of ileum relative to the ileum of chicks in the NT group, as evident by the quantitative evaluation of positive Alcian blue staining ( Fig. 2a and b) using integral optical density measurement (Fig. 3a). Similarly, FFC treatment also signi cantly decreased (P < 0.01) the mean density of acidic mucin (Fig. 2d and Fig. 3A) after exposure to Salmonella. Transcriptional analysis of a range of relevant intestinal barrier genes (Fig.  5) showed that FFC treatment signi cantly altered the transcription of (Claudin 1, IL-17A, and IFN-α) in the FT group. However, in the presence of Salmonella, FFC signi cantly reduced the expression of ZO-1, Occludin, Claudin 1, MUC2, and TFF2, and signi cantly increased the expression of IL-17A, IL-22, and IFNα. Furthermore, treatment with FFC signi cantly decreased (P < 0.01) secretory immune globulin A (SIgA) secretion, but had no effect on serum IgG (Fig. 3e and f). Nevertheless, FFC treatment reduced SIgA secretion to a higher degree (P < 0.001) after Salmonella infection (Fig. 3f). Thus, FFC intervention, to some extent, increased the permeability of the intestinal mucosal of chicks, reduced mucosal immunity, and substantially increased the extent of damage to the intestinal mucosal barrier after Salmonella infection.

Florfenicol administration alters the gut microbiota
The composition and density of the gut microbiota play an important role in combating Salmonella invasion. Oral pretreatment with antibiotics decreases colonization resistance and leads to an posttreatment expansion of Salmonella loading in the gut [53]. Thus, we hypothesized that the higher Salmonella population observed in the chicks of the FFC-treated group may be linked to the disruption of microbiota composition and density. To this end, the microbiota compositions of the cecal content of chicks at 3, 10, and 17 dpi were determined by 16S rRNA gene sequencing. Fig. S2 illustrates microbiota diversity, represented as boxplots of measures of α-diversity, Shannon index, Observed Species and Pielou index. The α-diversity at 3 dpi was neither affected by FFC treatment nor by S. Enteritidis infection (Fig. S2a). However, a signi cant decrease in α-diversity was observed in the FST group at 10 dpi (Fig.  S2b). Fig. S2c shows that the Shannon and Pielou index of the cecal microbial communities were signi cantly increased in the FST group at 17 dpi. These results indicated that the α-diversity of gut microbiota from chicks is not signi cant affected by a single FFC treatment or Salmonella challenge. However, the combination of both treatments signi cantly disturbed cecal α-diversity.
Phylum and genus distributions of microbial compositions are shown in Fig. S3. Firmicutes (67.85 -99.62%) dominated the microbiota in all four groups at three different stages of infection (Fig. S3a). At 3, 10, and 17 dpi, the FST chicks had the highest relative abundance of Proteobacteria (2.68%, 1.30%, and 1.75%, respectively) relative to the other three groups (Fig. S3a). At 17 dpi, the FFC (9.23%) chicks had signi cantly reduced relative abundance of Bacteroidetes relative to the NT group (31.26%). Salmonella infection (23.87%) had negligible effect on Bacteroidetes abundance. However, infection with Salmonella after pretreatment with FFC almost eliminated the growth of Bacteroidetes (0.01%) (Fig. S3). We applied the LEfSe (linear discriminant analysis effect size) method to identify abundant bacterial taxa among these groups; only those taxa that obtained a log LDA (linear discriminant analysis) score > 3 were ultimately considered. A cladogram from phylum to genus level abundance is shown in Fig. 6. In total, 21, 21, and 28 differentially abundant taxa were identi ed at 3, 10, and 17 dpi, respectively (Fig. 6). In the untreated control chicks, LEfSe highlighted the greater differential abundance of Lactobacillus at 3 and 10 dpi, and Bacteroides at 17 dpi. Notably, the relative abundance of Enterobacteriaceae was signi cantly higher in the FST group than in the other three groups at all three time points. However, the other taxa were altered irregularly at different times in different groups. The relative abundance of these biomarkers is shown in Fig. S4, wherein consistent results were obtained. We also established taxonomic cladograms at 11 day (3 dpi), with the relative abundance of the taxa node of each group shown as a pie chart; only those taxa with relative abundance > 0.1% were considered (Fig. 7a). Similarly, the abundance ratio of Lactobacillus was considerably higher in the control group than in the other three groups. Additionally, the abundance ratio of Enterobacteriaceae in the FST group dominated among all four groups. Furthermore, Salmonella was only found in the challenged groups (ST and FST) at the genus level, with the abundance ratio of Salmonella in the FFC pretreatment group signi cantly higher than those of the untreated groups (Fig. 7a). We measured the cecal loads of these biomarkers and two intestinal protective bacteria by quantitative real-time PCR (qPCR) (Fig. 7b). At day 11 (3 dpi), FFC pre-treatment signi cantly reduced the densities of total bacteria, Lactobacillus, Clostridium butyricum and Faecalibacterium prausnitzii. Although Salmonella infection had no effect on cecal bacterial densities, chicks with Salmonella infection after pretreatment with FFC harbored much higher densities of Enterobacteriaceae, and lower densities of Lactobacillus, Bacteroides, C. butyricum and F. prausnitzii relative to the control group. At day 25 (17 dpi), C. butyricum and F. prausnitzii were present at equivalent densities in the cecal content of all four groups. However, signi cant differences in the bacterial densities of total bacteria, Lactobacillus, Bacteroides, and Enterobacteriaceae were still apparent between the NT and FST groups or between the ST and FST groups (Fig. 7b). Lactobacillus and Bacteroides are generally considered as bene cial bacteria that provide protection for the gut, whereas Enterobacteriaceae are potential pathogens in poultry and humans. These observations suggested that FFC exposure signi cantly decreased the abundance of Lactobacillus in chicks, and this inhibitory effect may provide a growth advantage for Enterobacteriaceae, especially Salmonella.
The similarity of microbial communities (β-diversity) between groups was visualized using principalcoordinate analysis (PCoA) of Bray-Curtis distances. PCoA plots for 3 dpi showed that microbial communities from Salmonella or FFC treated chicks are clearly different from those of the untreated chicks. The rst axis of the PCoA plot shows 19.0% of variation in bacterial diversity while the second axis shows 13.0% (Fig. 7c). The rst axis roughly distinguishes the antibiotic pre-treated chicks and nonpretreated chicks, and the second axis roughly distinguishes the infected and non-infected chicks. The PCoA at 10 dpi shows that the microbiota composition was very similar between the NT and FT groups, whereas the ST and FST groups are still obviously distinguish from the NT group (Fig. S5a). Intriguingly, at day 25 (17 dpi), the PCoA plot demonstrated that both the microbiota composition of ST and FT groups tends toward the NT group, whereas composition of the FST group is still strikingly divergent from the NT group (Fig. S5b). These ndings suggested that a single FFC or Salmonella treatment alters the microbiota composition, with recovery two weeks after infection. Whereas FFC pretreatment hindered the recovery of microbiota composition of chicks after Salmonella infection.

Florfenicol administration alters the metabolic pro ling
We hypothesized that differences in key metabolites may be crucial to the effect of Salmonella colonization on chicks. Therefore, we analyzed metabolomes by LC-MS to determine differential levels of metabolites on day 11 (3 dpi) in cecal contents. The PCA score plot shows that the metabolome of NT group and ST group was signi cantly separated among the four groups, whereas there was no clear distinction in cecal metabolites between the FT and FST groups (Fig. 8a). Orthogonal projections to latent structures discriminant analysis (OPLS-DA) and permutation test plot of OPLS-DA were performed. As shown in Fig. 8, cecal metabolites of the NT group were clearly distinguished from those of the FT group (Fig. 8b), ST group (Fig. 8d), and FST group (Fig. 8f). In addition, there was a clear separation between the FST group and ST group in cecal metabolites (Fig. 8h).
From the OPLS-DA models, we identi ed 72 differential metabolites between the NT and FT groups, 42 differential metabolites between the NT and ST groups, 69 differential metabolites between the NT and FST groups, and 57 differential metabolites between the FST and ST groups, using to the threshold VIP > 1 and p < 0.05 (Welch's t test). The differential metabolites are listed in Supplementary Table S2. Next, we performed pathway enrichment analysis based on these differential metabolites to better understand the effect of FFC on metabolism (Fig. 9). Linoleic acid metabolism, aminoacyl-tRNA biosynthesis, lysine biosynthesis, phenylalanine metabolism and lysine degradation were enriched after FFC treatment (Fig.  9a). Arginine and proline metabolism, lysine biosynthesis, lysine degradation and D-glutamine and Dglutamate metabolism were enriched by Salmonella infection (Fig. 9b). Linoleic acid metabolism, aminoacyl-tRNA biosynthesis, lysine biosynthesis, butanoate metabolism and phenylalanine metabolism were enriched in FFC pre-treated, Salmonella infected chicks (Fig. 9c). Linoleic acid metabolism was enriched between the FST and ST groups (Fig. 9d). These data indicated that linoleic acid metabolism is the most noteworthy metabolic pathway in the FFC-treated groups with or without Salmonella challenge. We mapped the metabolic pathway of linoleic acid based on the identi ed differential metabolites, as well as the relative amounts (means ± SD) of these metabolites in the four groups (Fig. 9e). The metabolites that affect the metabolic pathways of linoleic acid are primarily linoleic acid, 12,13-EpOME, and 12,13-diHOME; the relative amounts of these metabolites in the FT and FST groups were signi cantly higher than in the NT and ST groups. Notably, the relative levels of 12,13-EpOME and 12,13-diHOME were signi cantly higher in the FFC-pretreated group, but were negligible in the non-pretreated group (Fig. 9e).

Correlation between the differential gut microbiota and metabolites
After observing marked differences in metabolite content as well as the microbial composition after FFC pre-treatment, we tested for speci c correlations between the microbial taxa and key metabolites.
Spearman correlation analysis revealed an association between four bacterial genera and nine discriminant metabolites in FFC-pretreated chicks (Fig. 10a). Enterobacteriaceae was a taxon with strong correlation, particularly with linoleic acid, 12,13-EpOME, 12,13-diHOME and L-tyrosine (positive correlations), whereas only L-ascorbic acid was negatively correlated. Furthermore, Clostridium positively correlated with L-palmitoyl carnitine, linoleic acid, 12,13-diHOME and L-tyrosine, while the taxon negatively correlated with L-ascorbic acid, anandamide, and 4-pyridoxic acid. The genus Lactobacillus negatively correlated with L-palmitoyl carnitine, linoleic acid, 12,13-EpOME, 12,13-diHOME, and L-tyrosine, and positively correlated with L-ascorbic acid. Lastly, a weaker positive correlation was detected between Ruminococcus and metabolites 4-pyridoxic acid and gamma-aminobutyric acid. Canonical correspondence analysis (CCA) showed that Enterobacteriaceae was the most important bacterial taxon in uencing linoleic acid metabolism (including linoleic acid, 12,13-EpOME, and 12,13-diHOME) after FFC pre-treatment (Fig. 10b). The correlation network between differential bacterial taxa and metabolites consisted of 13 nodes and 22 edges. We found that the metabolic pathway of linoleic acid has a strong positive correlation with Enterobacteriaceae, whereas Lactobacillus has a negative correlation with it (Fig.  10c).
As linoleic acid can be converted into conjugated linoleic acid (CLA) by Lactobacillus [54], and a signi cantly negative correlation between linoleic acid and Lactobacillus was observed in our study, we hypothesized that the non-FFC pretreated chicks (more abundance of Lactobacillus) may have higher CLA levels. However, CLA is an isomer of linoleic acid, so the use of untargeted metabolomics cannot distinguish between these compounds. Therefore, we employed targeted LC-MS to detect compounds including linoleic acid, 9c,11t-CLA, 10t,11c-CLA, 12,13-EpOME, and 12,13-diHOME (Fig. 10d). In line with the results of metabolic pro ling, linoleic acid, 12,13-EpOME, and 12,13-diHOME levels were higher in the FFC-pretreated groups. Moreover, we observed a higher more CLAs concentrations in the cecal contents of non-FFC pretreated chicks, with the levels of 9c,11t-CLA signi cantly higher than that of10t,11c-CLA (Fig. 10d). Spearman correlation analysis showed a strong association between the abundance of Lactobacillus and CLA concentrations (Fig. S6). Collectively, these ndings suggested that 12,13-EpOME and 12,13-diHOME may be the key metabolites for the propagation of gut colonization of Salmonella, whereas CLA may limit the Salmonella growth during infection.
Contrasting effects of conjugated linoleic acid and 12,13-diHOME on S. Enteritidis colonization We pre-administered CLA and 12,13-diHOME to newly-hatched chicks before infecting them with S. Enteritidis (Fig. 11a). By 3 dpi, Salmonella loads in the caecum, spleen, and liver were signi cantly reduced in the chicks pretreated with CLA, whereas they were signi cantly increased by pre-treatment with 12,13-diHOME (Fig. 11b). Consistent with the fecal Salmonella loads, pre-treatment with CLA signi cantly reduced enteropathy at 3 dpi, whereas 12,13-diHOME signi cantly increased it (Fig. S8). Furthermore, CLA-pretreated chicks exhibited a decrease in intestinal permeability (serum D-lactate, DAO and LPS levels), and pro-in ammatory factors (IL-1β, IL-6, IL-8, TNF-α and IFN-γ), as well as a signi cant increase in IL-10 levels. Notably, 12,13-diHOME-pretreated chicks exhibited contrasting results (Fig. 12). We also compared the effect of these two metabolites on the expression of genes related to intestinal barrier function after Salmonella infection (Fig. 13). We found that CLA signi cantly increased the expression of ZO-1 and Occludin, whereas the 12,13-diHOME signi cantly reduced the expression ZO-1, Occludin, Claudin1, and MUC2. CLA also signi cantly increased the expression of IL-17A (Fig. 13). To evaluate whether orally administered CLA and 12,13-diHOME reach the gut lumen, we quanti ed their concentrations in the cecal contents, and observed a signi cant increase in CLA and 12,13-diHOME relative to non-treated chicks (data not shown). Together, these results demonstrated that pretreatment with CLA attenuates Salmonella colonization, whereas 12,13-diHOME promotes it (Fig. 14).

Discussion
Administration of antibiotics perturbs the gut bacterial community, resulting in weakened resistant to gut colonization by pathogens [22,45,53,55]. However, the mechanisms that promote Salmonella outgrowth after antibiotic pretreatment in chicks remain unclear. In this study, we investigated the effect of antibiotic (FFC) pre-administration on the intestinal Salmonella colonization of chicks and its mechanism through microbiome analysis and metabolomics. Consistent with reported studies [45,55], our results indicated that FFC signi cantly increased Salmonella load in the gut and prolonged gut colonization. The abundance of Salmonella also signi cantly increased in livers and spleens exposed to FFC pretreatment. Salmonella employs two type III secretion systems, encoded by Salmonella pathogenicity island 1 (SPI-1) and Salmonella pathogenicity island 2 (SPI-2) to enter the intestine and adhere to the surfaces of intestinal epithelial cells. It subsequently enters the subepithelial tissue via a series of invasive pathological pathways [56]. In the current study, we found that FFC pre-treatment exacerbated Salmonella-induced defects in morphology, decreased intestinal barrier function, and increased intestinal barrier permeability. Enzyme-linked immunosorbent assays (ELISA) revealed that FFC directly decreased SIgA concentration, and mucous layer density, and increased the concentration of serum DAO and LPS. FFC signi cantly decreased the expression of mRNA encoding claudin 1, and increased the expression of mRNAs IL-17A and IFN-α. SIgA re ects the state of intestinal immunity, and stabilizes intestinal colonization by symbiotic microorganisms and confers resistance to future invasion by exogenous pathogens [57][58][59]. Studies have shown that the gut microbiota is the most important source of microbial stimulation of the immune response. The use of antibiotics disrupts the delicate ecosystem of the neonatal microbiome, which may impair stimulation of SIgA and a low IgA response, in which in turn leads to decreased mucosal barrier function [60][61][62]. Furthermore, FFC aggravates Salmonella-induced in ammation in the ileum; the secretion of IL-1β, IL-6, IL-8, INF-γ, TNF-α is higher and IL-10 is lower. Previous studies have reported that intestinal in ammation provides a growth advantage for Salmonella [53,[63][64][65]. Taken together, these ndings imply that FFC pretreatment impaired intestinal immunity, increased intestinal permeability and in ammation, and aggravated Salmonella-induced intestinal barrier damage. These changes collectively promoted Salmonella colonization in neonatal chicks.
As the gut microbiota plays an important role in combating Salmonella invasion and maintaining intestinal immunity [53,66], we characterized the intestinal ora of neonatal chicks in the treated groups. The present study showed that Firmicutes dominated the gut microbiota of neonatal chicks at day 11 and 18, and the mature microbial communities of chickens (at day 25) were dominated by Firmicutes and Bacteroidetes. This nding was consistent with previous studies [67,68]; however, FFC administration signi cantly decreased the abundance of Lactobacillus at day 11 and 18 (4 and 11 days post-treatment), and that of Bacteroides at day 25 (18 days post-treatment). Lactobacillus spp. are considered probiotic in nature and have been used in livestock feed processing for decades because of their bene cial effects on immunity, growth, and intestinal colonization resistance [69][70][71]. For example, the L. rhamnosus reduces the colonization of pathogenic Salmonella, Clostridium, and E. coli strains in porcine intestinal mucus [72]. L. acidophilus binds to cultured human intestinal cell lines and inhibits cell invasion by enterovirulent bacteria including Salmonella Typhimurium [73]. Another study showed that L. plantarum exerts an antagonistic effect on pathogenic bacteria by increasing the content of SIgA [74]. In our study, FFC treatment signi cantly decreased the abundance of Lactobacillus in chicks, suggesting that this genus may be the main target bacteria of FFC. Similar observations have been found on intestinal microbiota upon FFC therapy in chickens [75]. This reduction may be responsible for the promotion of Salmonella colonization after FFC pre-treatment. Bacteroidetes is the dominant phylum in the mature microbiota of chickens [76], and may have some inhibitory effects on the gut colonization of Salmonella. Miki et al. reported that Bacteroides spp. accelerates the elimination of S. Typhimurium from the intestinal lumen of mice by producing vitamin B6 [45]. Another study demonstrated that Bacteroides species confer colonization resistance to S. Typhimurium infection by producing propionate, which directly limits Salmonella growth by disrupting intracellular pH homeostasis [77]. Our results showed that at day 25, FFC pretreatment signi cantly reduced the abundance of Bacteroidetes and the cecum contained higher Salmonella loads relative to non-pretreated controls, suggesting that FFC may have delayed the maturation of chicken intestinal ora and hindered the clearance of Salmonella. Furthermore, Salmonella infection after FFC pre-treatment chicks had the highest relative abundance of Proteobacteria, which is known to be potential pathogens of poultry and humans. A recent study showed that preventive treatment of calves with orfenicol resulted in a 10-fold increase in facultative anaerobic Escherichia spp, which is a signature of imbalanced microbiota [78]. Sáenz et al. reported that oral administration of orfenicol to sh resulted in a shift in the gut microbiome towards well-known putative pathogens such as Salmonella, Plesiomonas, and Citrobacter [79]. Combined with our results, we conclude that FFC administration changes the overall structure of gut microbiota and promotes the growth of Proteobacteria, especially Salmonella. Although the microbial community of chicken is complex and relatively stable, the restoration of microbiota after antibiotic withdrawal can be expected [80,81]. Our results indicated that antibiotic administration at an early age in chickens may have a profound effect on microbial composition that hindered its restoration (Fig. S4). And the study also demonstrated that the maturation of intestinal microbiota is signi cantly retarded and eventually delayed by antibiotic intervention at early ages of chicks [82].
Next, we used metabolomics to determine how FFC affects Salmonella gut colonization. Our data suggested that linoleic acid metabolism is the most notable pathway affected by FFC pre-treatment.
Linoleic acid, 12,13-EpOME and 12,13-diHOME are the most important compounds affected in the linoleic acid metabolic pathway, and concentrations of these metabolites are signi cantly higher after FFC pretreatment. Notably, the concentration of 12,13-EpOME and 12,13-diHOME were signi cantly high in the FFC-pretreated group, but negligible in the non-pretreated group. Linoleic acid is rstly metabolized to 12,13-EpOME by cytochrome P450 (CYP) epoxygenase, followed by hydrolysis catalyzed by soluble epoxide hydrolases (sEHs) to form the diols 12,13-diHOME [83]. DiHOME compounds have multiple pathological features, such as decreasing post-ischemic cardiac recovery, participating in vascular cognitive impairment, increasing skeletal muscle fatty acid uptake, and impeding immune tolerance in asthmatic children [31,[84][85][86]. The 12,13-diHOME produced by sEH hydrolysis of 12,13-EpOME showed stronger cytotoxicity [83,87]. Our analysis of metabolic enzymes in this pathway revealed that FFC signi cantly increases the expression of CYP1A2, whereas it had no signi cant effect on sEH (Fig. S7). Besides liver, a variety of gut bacteria also produce she [31]. Correlation analysis results showed that the concentration of 12,13-diHOME positively correlated with Enterobacteriaceae and Clostridium, so we suspected that sEH may be produced by these bacteria in the gut. A recent study showed that the sEH and sEH-derived lipid metabolites induce intestinal barrier dysfunction, bacterial translocation, and colonic in ammation in mice [88]. Therefore, we propose that 12,13-diHOME promotes the intestinal colonization of Salmonella. Subsequently, we pretreated neonatal chicks with 12,13-diHOME and observed a signi cantly higher Salmonella colonization. Our results also showed that 12,13-diHOME pretreatment signi cantly increases Salmonella-induced expression of intestinal proin ammatory cytokines, exacerbates morphology, intestinal barrier injury, and increases the intestinal barrier permeability.
Intestinal in ammation, particularly that due to proin ammatory cytokines, disrupts barrier function and lead to intestinal permeability, and promotes colonization by pathogens [63,89,90]. Previous studies showed that diHOMEs compounds exhibit pro-in ammatory effects on vascular endothelial cells [91], lung [31] and peripheral nervous tissue [92]. Our study indicated that 12,13-diHOME also exhibits a proin ammatory effect on intestinal epithelial cells. Moreover, the diHOMEs compounds also disrupt mitochondrial function, by altering mitochondrial permeability and inducing cellular apoptosis [93,94], and this may be why 12,13-diHOME exacerbates intestinal barrier damage. Therefore, we suggest that 12,13-diHOME contributes to Salmonella colonization of chick intestine, by promoting intestinal in ammation and disrupting the intestinal barrier function.
CLA is the second factor affecting Salmonella gut colonization in chicks pre-administered with FFC. Our correlation analysis combined with targeted metabolomics revealed that Lactobacillus and CLA showed a signi cant positive correlation, and FFC pretreatment reduced the abundance of both Lactobacillus and CLA in the gut lumen. CLA is formed from linoleic acid by Lactobacillus and can inhibit the growth of pathogenic bacteria [95]. Therefore, we assume that CLA may be additional factor affecting Salmonella colonization after FFC pretreatment. We pretreated neonatal chicks with CLA and observed that it effectively reduced Salmonella colonization, accompanied by an increased expression of tight junction proteins (ZO-1 and occludin). CLA also alleviated Salmonella-induced intestinal in ammation and intestinal barrier injury. We suggest that CLA reduces intestinal colonization by Salmonella by in uencing several processes. Firstly, CLA treatment considerably upregulated the concentration of tight junction proteins (ZO-1, occludin, E-cadherin 1 and claudin-3) and ameliorated epithelial apoptosis [96][97][98], which protects intestinal cells from the impairment caused by Salmonella infection. Secondly, CLA modulates gut in ammation by attenuating the expression of proin ammatory cytokines (TNF-α, INF-γ, IL-1β, and IL-Lactobacillus competitively excludes Salmonella in a mixed-culture condition [102]. Additionally, Tabashsum et al. also showed that CLA produced by Lactobacillus inhibits the growth and survival of Salmonella by altering the relative expression of genes related to Salmonella virulence [103]. Thus, our results suggest that CLA maintains intestinal integrity, reduces intestinal in ammation, and inhibits Salmonella growth to effectively reduce gut colonization by Salmonella in chicks. Therefore, FFC may reduce production of CLA by inhibiting Lactobacillus growth, thereby reducing colonization resistance of neonatal chicks to Salmonella infection.

Conclusions
In conclusion, our study indicates that FFC pre-treatment signi cantly increases gut susceptibility to S. Enteritidis, in addition to enhancing Salmonella-induced in ammatory responses and intestinal barrier damage in neonatal chicks. Our ndings suggest that FFC reduces production of CLA by inhibiting Lactobacillus growth, increases 12,13-diHOME level of intestine, thereby reducing colonization resistance of neonatal chicks to Salmonella infection. We provide a better understanding of the susceptibility of animal species to Salmonella after antibiotics intervention may help to elucidate infection mechanisms that are important in both animal and human health. And the observations also facilitate the more careful and rational use of antibiotics in poultry.