The results showed that was significantly positively correlated with 6-hydroxy-5-methoxyindole glucuronide and negatively correlated with doxycycline and cinchonidine, while and had the opposite regulation pattern to and were negatively correlated with cinchonidine, and was also significantly positively correlated with 6-hydroxy-5-methoxyindole glucuronide. Open in a separate window FIGURE 8 Correlation analysis was conducted between the top focus metabolites and the signature microbiota to explore the key factors influencing organismal fitness by adding CE. and fertilization and hatching rates were also significantly increased ( 0.05) in the CE-fed group. 16S rRNA sequence analysis showed that CE strongly affected both JAK/HDAC-IN-1 – and -diversity of the ileal microbiota. LEfSe analysis revealed that the potentially beneficial genera were enriched as biomarkers in the CE-fed group. Microbial functional analysis revealed that the functional genes associated with harmful-substance biodegradation was significantly increased in the CE-fed group. Additionally, Spearman correlation analysis indicated that changes in microbial genera were correlated with differential metabolites. In summary, dietary multi-enzyme addition can improve egg quality, humoral immunity, and reproductive performance and regulate the intestinal microbiome and metabolome in breeders. Therefore, multi-enzymes could be used as feed additive to extend breeder service life. 0.05) based on the bootstrapping of 100 iterations were plotted. Untargeted Metabolomics by Liquid Chromatography-Mass Spectrometry The ileal chyme (30 mg) was precisely weighed and transferred to 1.5 mL microcentrifuge tubes (Eppendorf), to which two 3 mm stainless steel beads were added. Then, 20 L of L-2-chlorophenylalanine (0.3 mg/mL) and 17:0 Lyso PC (1-heptadecanoyl-sn-glycero-3-phosphocholine, 0.01 mg/mL) were used as the internal standard. Both were configured with methanol. An internal standard mixed with 400 L of methanol aqueous solution (CH3OH: H2O, V: V = 4:1) was added to each sample and pre-cooled at ?20C for 2 min. The sample was then ground in a fully automatic sample fast grinding machine (60 Hz, 2 min; Shanghai Jingxin Industrial Development Co., Ltd., Shanghai, China) and placed in an ultrasonic bath with ice water for 10 min. The sample was placed in a ?20C refrigerator for 20 min before centrifugation at 13,000 rpm at 4C for 10 min. The supernatant was removed with a syringe and filtered by passing through a 0.22 m-membrane filter to an LC-MS vial and stored at ?80C for subsequent analysis by raw data were collected by UNIFI (version 1.8.1) and then processed using Progenesis QI (version 2.3) with the following threshold parameters: precursor tolerance of 5 ppm, product tolerance of 10 ppm, and production threshold of 5%. Metabolites were identified by retention time, exact mass, and JAK/HDAC-IN-1 tandem MS JAK/HDAC-IN-1 data against the Human Metabolome Project,4 Lipidmaps (v2.3)5 and METLIN6 databases. All metabolites with a percentage of missing values 50% and quality scores 30 were discarded by qualitative screening. Metabolome Bioinformatics Analysis Metabolome data were subjected to bioinformatics analysis using the SIMCA software (version 14.0, Umetrics, Ume?, Sweden). Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) models and plots were constructed using SIMCA. Volcano plots were plotted using the R package ggplot2. The differential metabolites were converted from names to KEGG compound IDs using MetaboAnalyst software (version 5.0),7 CTS (Wohlgemuth et al., 2010), and MBRole software (version 2.0).8 These IDs were used as input files for metabolite set enrichment analysis using MetaboAnalyst 5.0 software [annotations: KEGG pathway; Organism: (human)] and MBRole 2.0 software [annotations: KEGG pathway; Organism: (chicken)]. We also applied the pathway topology analysis [annotations: KEGG pathway; Organism: (chicken)] to verify our findings using MetaboAnalyst with the IFNA17 default setting. Considering the relative lack of lipid information in the KEGG database, the differential metabolites that were annotated in the LipidMaps database were enriched by LIPEA9 [annotations: KEGG pathway; Organism: (chicken)]. Spearmans correlation between the differential microbial biomarkers and metabolites and the three identified metabolites and six microbial biomarkers were analyzed using R software. Only correlation coefficients with an absolute value of | r| 0.6 (Adj 0.05 were considered as significant and 0.05 0.1 was considered a trend. Results Production Performance and Egg Quality The laying performance of breeding hens fed the CE diet is presented in Table 2. Egg production, egg weight ratio, damaged JAK/HDAC-IN-1 egg ratio, abnormal egg ratio, FCR, mortality, and feed intake were not affected by CE administration at 55C59, 59C63, and 55C63 weeks JAK/HDAC-IN-1 ( 0.05). The egg quality results are presented in.
