Dried and cleaned AMP was obtained from Fuyang Fruit Wine Engineering Technology Center (Fuyang, China). FAMP was prepared according to the following procedure. A compound starter culture was prepared to ferment the raw material (AMP). The compound starter culture was composed of a microbial agent mixture, enzyme, medium 1, medium 2, and sucrose at a mass ratio of 1:1:1:1:1. Among them, the microbial agent mixture (Guangdong Microbial Culture Collection Center, Guangzhou, China) contained Bacillus subtilis GDMCC 1.372, Bacillus licheniensis GDMCC 1.182, Lactobacillus plantarum GDMCC 1.648, and Rhodotorula benthica GDMCC 2.215 at a mass ratio of 1:1:1:1. The active enzyme was a mixture of cellulase and papain at a mass ratio of 1:1. Medium 1 consisted of cultivated ginseng leaves, which were dried and crushed to a 40-mesh powder. Medium 2 was soybean flour. The above compound starter culture and AMP were blended at a mass ratio of 1:100. The fermentation conditions were as follows: fermentation temperature, 75°C; dissolved oxygen, 3–10%; moisture content, 30–80%; and fermentation method, solid fermentation. The measured nutrient levels (%; dry matter basis) of FAMP were as follows: ash, 5.20; crude protein, 10.63; ether extract, 4.80; crude fiber, 15.90; calcium, 0.55; total phosphorus, 0.28; and gross energy, 18.65 MJ/kg. Amino acid and fatty acid profiles of FAMP are presented in Supplementary Tables S1 and S2, respectively.

A total of 320 Yukou Jingfen No. 8 laying hens that were 345 days old with similar health conditions were selected and randomly allocated into one of the four treatment groups with eight replicates per treatment (ten birds/replicate). The four treatment groups were fed on a basal diet with the addition of 0 (control, CON), 0.25%, 0.5%, and 1.0% FAMP, respectively. The basal diet for laying hens was formulated based on the standard nutriment requirements (Supplementary Table S3). The trial continued for eight weeks and there was a 1-week pre-feeding trial. All laying hens were raised in a controlled environment at 18–24 °C, humidity of 45–60%, and 16 h/day of illumination. The other feeding management followed routine commercial feeding management protocols during the trial.

The weight and number of eggs and feed intake in each replicate were recorded during the whole trial. Then, average laying rate (ALR), average egg weight (AEW), average daily feed intake (ADFI), and feed-to-egg ratio (FER) were analyzed from weeks 1 to 2, 3 to 4, 5 to 6, 7 to 8, and 1 to 8 of the trial.

Three eggs per replicate were randomly collected for egg quality measurement every two weeks during the trial. The egg shape index was determined by a Vernier caliper and calculated using previous formulas described by Feng et al. (2021). The eggshell strength, egg weight, albumen height, Haugh unit, and yolk color (Roche colorimetric unit) were measured with an Egg Force Reader and an EggAnalyzer (ORKA Food Technology Ltd., Ramat HaSharon, Israel), respectively. Then, the eggshell, yolk, and albumen were separated, weighed, and their percentages calculated. The eggshell thickness was measured by a hand-held micrometer (Deli Group, Ningbo, China).

Three eggs from each replicate were collected to obtain the egg yolk and egg albumen for further nutritive value analyses after the 8-week animal trial. The plasma samples were obtained through wing vein-blood collection and centrifugation and kept at −80°C for plasma hormone, biochemical parameter, and antioxidant indicator analyses. Then, hens from each replicate were euthanized by jugular vein bleeding. The liver and ovary were dissected and kept at −80°C for mRNA extraction, and the ovary samples were also collected for hormone and antioxidant indicator analyses. The cecal contents were collected to determine the microbiota abundance and short-chain fatty acids (SCFA).

In hens' ovaries, numbers of large white (2–5 mm), small yellow (6–8 mm), and hierarchical (>9 mm) follicles were recorded based on previously described methods (Li et al., 2020; Huang et al., 2021).

The ether extract level of egg yolks was determined by a Soxhlet extraction with petroleum. The fatty acid composition was determined by employing the area normalization method (Hu et al., 2017). Briefly, total lipids were taken from egg yolks following the chloroform–methanol process. The fatty acid methyl ester was obtained with KOH/methanol and determined by a gas chromatograph (GC2030, Shimadzu Corporation, Kyoto, Japan).

According to the percentage of particular fatty acids of egg yolks, saturated fatty acids (SFA), polyunsaturated fatty acids (PUFA), monounsaturated fatty acids (MUFA), n-3 PUFA, and n-6 PUFA percentages were counted as follows: SFA = C14:0 + C16:0 + C17:0 + C18:0, MUFA = C16:1n-7 + C18:1n-9 + C20:1n-9, n-3 PUFA = C18:3n-3 + C22:6n-3, n-6 PUFA = C18:2n-6 + C18:3n-6 +C20:2n-6 + C20:3n-6 + C20:4n-6, and PUFA= n-3 PUFA + n-6 PUFA. Meanwhile, the health lipid indices related to fatty acids, such as atherogenicity index (AI), thrombogenic index (TI), hypocholesterolemic/hypercholesterolaemic ratio (H/H), health promotion index (HPI), and desirable fatty acids (DFA), were calculated as reported in our previous study (Li et al., 2024): AI = (C12:0 + 4 × C14:0 + C16:0)/UFA, TI = (C14:0 + C16:0 + C18:0)/(0.5 × MUFA + 0.5 × n-6 PUFA + 3 × n-3 PUFA + n-3/ n-6 PUFA), H/H ratio = (C18:1n-9 + C18:2n-6 + C20:4n-6 + C18:3n-3 + C20:5n-3 + C22:5n-3+C22:6n-3)/(C14:0 + C16:0), HPI = (MUFA + PUFA)/(C12:0 + 4 × C14:0 +C16:0), and DFA = C18:0 + MUFA + PUFA.

The crude protein content in egg albumen was evaluated by the Kjeldahl method. The content of amino acids in egg albumen was determined using a previously described method (Hu et al., 2017). Briefly, freeze-dried egg albumen samples were prepared using 6 mol/L hydrochloric acid at 110°C for 24 h. Then, the suspensions were filtered and detected by an ion-exchange AA analyzer (LA8080, Hitachi, Tokyo, Japan).

Ovary samples were placed in normal saline, vortexed, and then centrifuged at 4°C for supernatant collection. The protein content in ovary homogenate was measured with a bicinchoninic acid assay kit (Nanjing Jiancheng Bioengineering Institute, Nanjing, China).

The content of estrogen 2 (E₂), follicle-stimulating hormone (FSH), and luteinizing hormone (LH) in plasma and ovary homogenate was determined using the enzyme-linked immunosorbent assay (ELISA) kits (Hunan Richamp Biotechnology Co., Ltd., Changsha, China). The optical density (OD) values were obtained on a spectrophotometer (Tecan, Infinite M200 Pro, Basel, Switzerland).

The content of superoxide dismutase (SOD), glutathione peroxidase (GPX), total antioxidant capacity (T-AOC), glutathione (GSH), and malondialdehyde (MDA) in plasma and ovary homogenate was determined by colorimetry (Nanjing Jiancheng Bioengineering Institute, Nanjing, China) on a spectrophotometer (Tecan, Infinite M200 Pro, Basel, Switzerland). The protein content of each ovary homogenate sample was used to normalize the indexes mentioned above. The content of total cholesterol (TC) and triglyceride (TG), alanine aminotransferase (ALT), and aspartate aminotransferase (AST) in plasma was also determined by colorimetry (Nanjing Jiancheng Bioengineering Institute, Nanjing, China) on a spectrophotometer (Tecan, Infinite M200 Pro, Basel, Switzerland).

The total RNA in both liver and ovary samples was measured using the TransZol agent (TransGen Biotech, Beijing, China). The concentration and purity of extracted RNA samples were evaluated by a Nanophotometer N60 (Implen, GmbH, Germany). The total RNA was reverse transcribed into cDNA following instructions provided in the RT Kit (Accurate Biology, Changsha, China). Quantitative PCR amplification was carried out on the LightCycler R 480II Real-Time PCR System (Roche, Basel, Switzerland) using the qPCR Kit (Accurate Biology, Changsha, China) following the manufacturer's instructions. Characteristic primer sequences devised through the Primer 3 web (https://primer3.ut.ee/) are available in Supplementary Table S4. The relative gene expression was computed with the 2^−ΔΔCt method (Livak and Schmittgen, 2001).

The cecal microbiota composition analysis was performed by the Shanghai Personal Biotechnology Co., Ltd., Shanghai, China (Zhu et al., 2022). Briefly, the total microbial DNA of cecal contents was extracted and amplified with specific primers (forward primer: 5′-ACTCCTACGGGAGGCAGCA-3′ and reverse primer: 5′-GGACTACHVGGGTWTCTAAT-3′) to obtain bacterial V3-V4 sequences. After purification and amplification, the PCR products were paired-end sequenced on an Illumina NovaSeq platform (Illumina, San Diego, CA, USA). After quality control and chimera removal, amplified sequence variants (ASVs) were taxonomically aligned with species annotation using the Greengenes database. The α and β diversity indices were analyzed to detect the diversity, richness, and dissimilarity of the microbiota. Kruskal–Wallis test was performed to determine the differential phyla and genera. The linear discriminant analysis (LDA) effect size (LEfSe; LDA ≥ 2, P < 0.05) and random forest analysis were applied to identify and distinguish the microbiota in the four groups. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the microbiota was conducted with the Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt2) method. The correlation between cecal microbiota abundance (top 50 genera) and phenotypes was performed using Spearman correlation by the R package (|R| > 0.50, P < 0.05).

The concentrations of cecal SCFA were measured according to our previous study (Li et al., 2021) using Agilent 7890A gas chromatograph (Agilent Inc., Palo Alto, CA, USA).

All data analyses were performed using the SPSS 22.0 software (SPSS Inc., Chicago, IL, USA) package. The normality and homogeneity of variances of the data were assessed using the Shapiro–Wilk test and Levene's test, respectively. When applicable, the one-way analysis of variance (ANOVA) following Tukey's post-hoc test was performed to assess significant differences. Otherwise, Welch's ANOVA and Games-Howell tests were performed for the significant difference analyses. The results are expressed as means with standard error of the mean (SEM). P < 0.05 was considered statistically significant, whereas 0.05 ≤ P < 0.1 suggested a trend.

Table 1 showed no notable differences (P > 0.05) in the ALR, AEW, and FER among the four groups during 1 to 2, 3 to 4, 5 to 6, 7 to 8, and 1 to 8 weeks of the trial. The ADFI was elevated (P < 0.05) in the 0.25% and 0.5% FAMP groups relative to that in the CON group during 7–8 weeks. The ADFI in the 0.25% FAMP group was higher (P < 0.05) than that of the 1% FAMP group during 7 to 8 weeks, and showed an increasing trend (P = 0.082) during 1 to 8 weeks. As presented in Table 2, the addition of 0.25% FAMP decreased (P < 0.05) the egg shape index relative to that in the CON and 0.5% AMP groups at week 2. The eggshell thickness was higher (P < 0.05) in the 0.25% FAMP group than in the 1% FAMP group at week 6. No notable differences (P > 0.05) were found in the eggshell strength, Haugh unit, albumen height, yolk color, and percentages of eggshell, yolk, and albumen among the four groups throughout the trial.

As seen in Table 3, the C16:0 percentage was lower (P < 0.05) in the 0.5% FAMP group than that of the CON group. The C20:4n-6 percentage showed a decrease (P < 0.05) in the 0.25% FAMP group compared to the CON group. Moreover, FAMP supplementation exhibited a declining trend (P = 0.059) in the C20:3n-6 percentage compared to the CON group. Additionally, the SFA percentage and AI and TI indexes were reduced (P < 0.05), whereas H/H, HPI, and DFA indexes were elevated (P < 0.05) in the 0.5% FAMP group by comparison with the CON group. PUFA, PUFA/SFA, n-3 PUFA, and n-6 PUFA in the four groups showed no obvious distinctions (P > 0.05).

The valine content in egg albumen was reduced (P < 0.05) in the 0.25% FAMP group than in the CON group. The 0.25% and 0.5% FAMP groups exhibited a decreasing trend with regard to the content of histidine (P = 0.093), proline (P = 0.060), and branched-chain amino acid (BCAA, P = 0.089) of egg albumen relative to the CON group (Table 4).

The results of ovarian follicles are shown in Figure 1A. The number of large white follicles in the FAMP groups exhibited an increasing trend (P = 0.092) relative to the CON group. There were no significant changes (P > 0.05) in plasma FSH, LH, and E₂ contents among the four groups (Figure 1B). However, ovary FSH, LH, and E₂ levels were higher (P < 0.05) in the 0.25%, 0.5%, and 1.0% FAMP groups relative to the CON group (Figure 1C). The ovary HSD17B1 expression was upregulated (P < 0.05) in the 1.0% FAMP group relative to the CON group. The mRNA expression involved in hormonogenesis (including CYP11A1, HSD3B1, CYP17A1, and CYP19A1) and hormone receptors (including ESR1, ESR2, FSHR, and LHCGR) in ovarian tissues did not differ among the four groups (Figures 1D, E).

As shown in Figure 2A, plasma TC, TG, ALT, and AST levels of the four groups showed no significant differences (P > 0.05). The gene expression involved in the synthesis of yolk precursor (including ACC, FAS, and SCD1) and ESR2 in the liver was upregulated (P < 0.05) in the 1.0% FAMP group compared with the CON group (Figures 2B, E). The gene expressions of the liver-respecting egg yolk precursor transportation (including VTG II, ApoVLDL II, and APOB) were upregulated (P < 0.05) in the 0.5% FAMP group relative to the CON group (Figure 2C). As for the VLDR gene expression of the ovary, no difference (P > 0.05) was observed among the four groups (Figure 2D).

The levels of plasma redox status-related parameters, including T-AOC, GSH, GSH-PX, SOD, and MDA, were not changed (P > 0.05) by dietary FAMP supplementation (Figure 3A). In the ovary, T-AOC (P < 0.05) and SOD (P = 0.064) levels were increased in the 0.5% FAMP group in comparison to the CON group (Figure 3B). Furthermore, the Keapl expression of the 0.5% and 1.0% FAMP groups was decreased (P < 0.05) relative to the CON group. Moreover, the Nrf2 expression of the 0.5% FAMP group was higher (P < 0.05) than in the 1.0% FAMP group.

The results of the α-diversity are presented in Figure 4A. The Observed_species, Chao1, and Faith-pd indexes were higher, whereas the Goods coverage index was lower in the 0.25% FAMP group relative to the CON group (P < 0.05). The Pielou_e index of the 1.0% FAMP group was higher (P < 0.05) relative to the 0.5% FAMP group. The β-diversity analysis (non-metric multidimensional scaling ordination plot) indicated that cecal microbial communities were differentiated between the CON and the three FAMP groups (Figure 4B). Bacteroidetes, Firmicutes, and Proteobacteria predominated in the cecal phyla (Figure 4C). An increase (P < 0.05) in the relative abundance of Bacteroidetes was found in the 0.25% and 0.5% FAMP groups relative to the 1.0% FAMP group. The relative abundance of Firmicutes was increased (P < 0.05) in the 1.0% FAMP group relative to the other three groups. Especially, we found a decrease (P < 0.05) in the relative abundance of Proteobacteria in the FAMP groups in comparison to the CON group (Figure 4E). Furthermore, the top ten genera were Bacteroides, Lactobacillus, Megamonas, Faecalibacterium, Phascolarctobacterium, Prevotella, Oscillospira, [Ruminococcus], Desulfovibrio, and Subdoligranulum (Figure 4D). Notably, the relative abundance of Lactobacillus of the 1.0% FAMP group was the highest (P < 0.05) among all groups. The 0.5% and 1% FAMP groups exhibited a decrease in the relative abundances of Oscillospira and [Ruminococcus] (P < 0.05) relative to the 0.25% FAMP group. The relative abundance of [Ruminococcus] of the 0.5% FAMP group was decreased (P < 0.05) relative to the CON group (Figure 4F).

As presented in Figure 5A, the LEfSe analysis of taxa with LDA score ≥ 2 showed that Proteobacteria in the CON group; Armatimonadetes, Chloroflexi, GNO4, OD1, Planctomycetes, and WS3 in the 0.25% FAMP group, Bacteroidetes in the 0.5% FAMP, and Firmicutes in the 1.0% FAMP group were enriched. At the genus level, Streptomyces, Symbiobacterium, Methylobacterium, Massilia, Shigella, Acinetobacter, and Pseudomonas in the CON group, Alistipes, Candidatus_Brocadia, Nitrosomonas, and Psychrobacter in the 0.25% FAMP group, Weissella and Streptococcus in the 0.5% FAMP group, and Lactobacillus, Acetobacter, and Ralstonia in the 1.0% FAMP group were enriched. The random forest model was performed to further identify the biomarkers. As shown in Figure 5B, the top five marker genera among the four groups were Methylobacterium, Ralstonia, Alistipes, Olsenella, and Weissella at the genus level. Meanwhile, the 0.25% FAMP group had increased Alistipes, Olsenella, Oscillospira, and others. Furthermore, the pathways at level 3 were further identified (Figure 5C). The results showed that the CON, 0.25%, 0.5%, and 1.0% FAMP groups significantly enriched 5, 1, 3, and 31 pathways, respectively. There were five significantly enriched pathways in the CON group, namely, bacterial chemotaxis, metabolism of xenobiotics by cytochrome P450, geraniol degradation, biosynthesis of unsaturated fatty acids, and hypertrophic cardiomyopathy. The pathway enriched in the 0.25% FAMP group was valine, leucine, and isoleucine degradation. There were three significantly enriched pathways in the 0.5% FAMP group, namely polyketide sugar unit biosynthesis, biotin metabolism, and lipopolysaccharide biosynthesis. The 1.0% FAMP group enriched 31 pathways, and the top 10 pathways included D-alanine metabolism, D-glutamine and D-glutamate metabolism, aminoacy1-tRNA biosynthesis, mismatch repair, peptidoglycan biosynthesis, ribosome, pentose phosphate pathway, lysine biosynthesis, homologous recombination, and dioxin degradation.

As shown in Figure 5D, the positive correlations were obtained between Ruminococcaceae_Ruminococcus with SFA and TI, Methylobacterium with C16:0, SFA, AI, and TI, and Shigella with C20:4n-6 (|R| > 0.50, P < 0.05). The negative correlations (|R| > 0.50, P < 0.05) were obtained between Ruminococcaceae_Ruminococcus with HPI, and Methylobacterium with H/H, HPI, and DFA.

The levels of cecal SCFA of aged laying hens are presented in Figure 6. The levels of acetate, propionate, butyrate, and valerate were increased (P < 0.05) in the 1.0% FAMP group relative to the 0.25% FAMP group. Dietary 0.25%−1.0% FAMP did not (P > 0.05) affect the level of isobutyrate.