
==== Front
Poult Sci
Poult Sci
Poultry Science
0032-5791
1525-3171
Elsevier

S0032-5791(24)00762-4
10.1016/j.psj.2024.104183
104183
METABOLISM AND NUTRITION
Effects of dietary protein level on liver lipid deposition, bile acid profile and gut microbiota composition of growing pullets
Yuan Xi *
Fang Xiaoshuang †
Li Yongxia *
Yan Zixing *
Zhai Shuangshuang *
Yang Ye *
Song Jiao songjiao19881127@126.com
†1
⁎ College of Life Science, Yangtze University, Jingzhou, People's Republic of China
† College of Animal Science and Technology, Yangtze University, Jingzhou, People's Republic of China
1 Corresponding author: songjiao19881127@126.com
08 8 2024
11 2024
08 8 2024
103 11 1041836 3 2024
1 8 2024
© 2024 The Authors
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
The current study investigated the effects of dietary crude protein (CP) level on the liver lipid metabolism, gut microbiota, and bile acids (BA) profiles of growing pullets. Roman growing pullets (N = 180, 13-wk-old) were divided into 3 treatments groups with 6 replicates in each group and 10 hens in each replicate and provided 3 different dietary CP level diet treatments. The diet treatments included: a high-protein diet (15.5% CP, HP group), a medium-protein diet (14.5% CP, MP group), and a low-protein diet (13.5% CP, LP group). Compared with HP group, LP group significantly increased the lipid contents in the body (such as Breast intramuscular fat [BIMF], Leg intramuscular fat [LIMF], Percentage of abdominal fat [PAF], liver triglyceride [TG] and liver cholesterol [TC]), and the lipid metabolism-related parameters in serum (such as cholesterol (TC), high density lipoprotein cholesterol [HDL-C], low density lipoprotein cholesterol [LDL-C], very low density lipoprotein [VLDL]), and the mRNA expression of lipid metabolism-related genes (such as fatty acid synthase [FAS], CCAAT/enhancer binding protein β [C/EBPβ], and fatty acid translocase [FAT/CD6]) (P < 0.05). In addition, LP group significantly reduced the contents of lithocholic acid (LCA), isoLCA, and ursodesoxycholic acid (UDCA), and increased the deoxycholic acid (DCA) content compared with HP group (P < 0.05). The effects of LCA on lipid deposition were confirmed in chicken preadipocyte cell line (CPI), in which LCA supplementation significantly decreased the relative expression of PPARγ, FAS, acyl-CoA carboxylase (ACC) and SREBP-1c (P < 0.05). Correlation analysis further revealed a significant association between BA profiles and lipid metabolism-related parameters. Furthermore, 16S rRNA gene sequencing indicated that dietary protein level can significantly affect the richness, diversity, and composition of cecal microbiota in growing pullets. LP group significantly increased the abundance of Bacteroidetes and significantly decreased the abundance of Firmicutesa compared with the HP group. In summary, low protein diet in growing pullets influence the liver lipid metabolism through changing the gut microbiota and liver BA metabolism.

Key words

low protein diet
growing pullet
bile acid
gut microbiota
lipid metabolism
==== Body
pmcINTRODUCTION

In China, the high cost of protein sources and environmental concerns related to high nitrogen excretion have been 2 important limiting factors in the development of the poultry industry. And thus the strategy of using a low protein diet balanced with amino acids in poultry production has been widely accepted. It is reported that crude protein in laying hen diets can be reduced by 2% units if fortified with synthetic AA (Parenteau et al., 2020). Nonetheless, feeding low protein diet increased the contents of abdominal fat, liver fat and serum triglyceride, which increased the fatty liver rate (Xie et al., 2016; Heo et al., 2023). Especially in laying hens, excessive fat deposition damaged liver function and resulted in fatty liver hemorrhagic syndrome (FLHS), which led to a decline of laying performance and the death of laying hens (Shini et al., 2019; Gu et al, 2021; Wang et al., 2023).

Liver is the primary organ for de novo lipogenesis and bile acie (BA) metabolism in chickens. The disturbance of lipid metabolism and BA metabolism homeostasis induced by low protein diet have been associated with the development of fatty liver syndrome and fatty liver hemorrhagic syndrome (FLHS) in laying hens (Lefort and Cani, 2021; Gillard et al., 2022). Primary bile acids are synthesized from cholesterol in the liver, which have been implicated in the pathogenesis of FLHS disease. When BA metabolism is impaired, BAs (especially hydrophobic bile acid) accumulate in the liver at high concentrations, which may cause hepatic oxidative stress and induce hepatic lipid synthesis and accumulation (Ma et al., 2022). In addition, as a key regulator of BAs metabolism, the farnesoid X receptor (FXR) simultaneously plays an important regulatory role in lipid metabolism. BAs decreased the liver lipid deposition through the FXR-SHP-SREBP1 pathway (Lefort and Cani, 2021). FXR activation could reduce hepatic lipids levels through the positive regulation of peroxisome proliferator-activated receptor α (PPARα) (Rajani and Jia 2018; Feng et al., 2023). As FXR antagonist, LCA and HDCA were found to be decreased in serum or intestine of animals with hepatic steatosis (Tang et al., 2019; Ushiroda et al., 2019). Recent studies have also demonstrated that the activated FXR decreases hepatic triglycerides accumulation via lowing intestinal lipid absorption independently of SHP -SREBP1C pathway (Clifford et al., 2021).

A number of studies have provided that gut microbiota also contribute to the hepatic fat accumulation and the BA metabolism in poultry (Kong et al., 2020; Wang et al., 2021; Wang et al., 2023). The imbalance of the gut microbiota is also considered to be an important factor in the hepatic lipid metabolism disorder in chickens (Wang et al., 2021). The gut microbiota also affects the bile acids profiles through microbial processing, such as dehydrogenation, dihydroxylation, and epimerization, which results in a more hydrophobic bile acid pool and ultimately influence hepatic lipid metabolism and liver healthy through FXR signal (Schoeler and Caesar, 2019). The gut microbiota may affect host lipid metabolism and BA metabolism through interaction with the diet (Schoeler and Caesar, 2019). Multiple studies have investigated the effects of dietary protein on intestinal microbial composition and host health (Diether and Willin, 2019; Zhang et al., 2020). Many studies showed that excessive protein intake has been shown to stimulate the growth of potentially pathogenic species such as Clostridium perfringens, and to reduce fecal counts of beneficial bifidobacteria (Rist et al., 2013; De Cesare et al., 2019). The crude protein level in the diet also played an important effects on microbial richness and diversity which were important parameters in host–microbe symbiosis (Zhang et al., 2020).

Therefore, the hepatic lipid accumulation induced by low dietary protein may associate with gut microbiota and BA metabolism interaction. However, the information about the effect of a low protein diet on gut microbiota and BA metabolism are limited. The aim of the present study was to clarify the effects of interaction between gut microbiota and BA metabolism disturbance on liver lipid metabolism in growing pullets with low protein diet.

MATERIALS AND METHODS

Experimental protocols were performed in accordance with the guidelines of the Institutional Review Board (No. IRB14044) and the Ethics Committee of Yangtze University (No. DKYB20140302) in China for the humane care and use of animals in research.

Animal Feeding and Management

A total of 180 13-wk-old Roman growing laying hens with similar weight (Beijing Huadu Yukou Poultry Industry Co., Ltd, Beijing, China) were randomly assigned to 3 groups (6 replicates of 10 birds each), including a high-protein diet (15.5% crude protein, HP group), a medium-protein diet (14.5% crude protein, MP group), and a low-protein diet (13.5% crude protein, LP group). The medium-protein diet were formulated to meet the Roman laying hens's recommended standard (Leeson and Summers, 2008) as reported in Table 1. The four main animo acids (Lys, Met, Thr, and Try) were supplemented with crystalline amino acids at the levels sufficient to meet the recommendation their requirements (Leeson and Summers, 2008). Feeds were supplied ad libitum in mash form throughout the experiment. The experiment lasted 4 wk.Table 1 Composition and nutrient levels of basal diets (air-dry basis) (g/kg).

Table 1Item	Treatment	
HP group	MP group	LP group	
Ingredients				
 Corn	624.2	645.6	668.2	
 Soybean meal	210.3	185.8	160.0	
 Wheat bran	40.0	40.0	40.0	
 Rice bran	40.0	40.0	40.0	
 Limestone	15.0	16.0	16.0	
 CaHPO4	14.0	14.0	15.0	
 NaCl	3.50	3.50	3.50	
 Choline (50%)	2.00	2.00	2.00	
 DL-Methionine	1.00	1.40	1.60	
 Lysine		0.8	1.9	
 Threonine		0.9	1.6	
 Tryptophan			0.2	
 Zedite	40.0	40.0	40.0	
 premix feed1	10.0	10.0	10.0	
 Total	1000.0	1000.0	1000.0	
Nutrient composition (%) 2				
 Metabolic energy (MJ/kg)	11.75	11.75	11.75	
 Crude protein	155.0	145.0	135.0	
 Calcium	9.90	9.90	9.90	
 Available phosphorus	4.40	4.40	4.40	
 NaCl	3.80	3.80	3.80	
 Lysine	7.10	7.10	7.10	
 Methionine	3.50	3.50	3.50	
 Tryptophan	1.50	1.50	1.50	
 Threonine	5.20	5.20	5.20	
1 The premix provided the following per kg of diets: vitamin A, 15 000 IU; vitamin D3, 3 600 IU; vitamin E, 62.5 mg; vitamin B1, 3 mg; vitamin B2, 9 mg; vitamin B6, 6 mg; vitamin B12, 0.03 mg; nicotinic acid 60 mg; calcium pantothenate, 18 mg; folic acid, 1.5 mg; biotin, 0.36 mg; choline chloride, 500 mg; Fe, 47 mg; Zn, 75 mg; Cu, 6mg; Mn, 100mg; I, 0.46 mg; Se, 0.06 mg.

2 The composition of crude protein was measured value, while the others were calculated values.

Sample Collection

At the end of 17-wk ages, 2 chickens from each replicate was randomly selected and slaughtered for sample collection.

Blood was also sampled from one chicken chosen at random from each replicate, incubated at 37 °C for 10 min (GRP-9050; Shanghai Senxin Test Instrument Co., Ltd, Shanghai, China), and then serum were separated at 1,000 g/min for 15 min andstored at −20°C to analyse serum biochemical indexes.

The abdominal fat was stripped and weighed to determine the percentage of abdominal fat (PAF). Muscle (breast and leg) and liver were collected and stored at −20°C for determination of hepatic lipids contents.

The live samples were removed into in 1.5 mL Eppendorf tubes and immediately snap frozen in liquid nitrogen and then stored at −80°C till further analysis of liver mRNA expression and BAs contents.

The cecal contents were sampled from 1 chicken each replicate and squeezed out into frozen tubes and stored at -80°C for DNA extraction for 16S rRNA.

Biochemical Assay of Serum Samples

Serum triglyceride (TG), total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C) concentrations, very low density lipoprotein(VLDL), total protein (TP), glucose (GLU), and uric acid (UA) were measured using by a Hitachi 7,600 automated biochemical analyzer (Hitachi, Tokyo, Japan).

Measurement of Hepatic and Muscle Lipid Contents

The crude fat content of breast muscle and leg muscle were measured by Soxhlet extractor method. The abdominal fat was weighed and expressed as the percentage of body weight. Liver TC and TG were determined using commercial kits (Nanjing Jiancheng Bioengineering Institute, Nanjing, China) in accordance with manufacturer's instructions.

Targeted Metabolome Analysis of Liver BAs

The ultra-high performance liquid chromatography-mass spectrometry (UPLC/MS) method was modified to determine BAs contents in ileal digesta (Wang et al., 2020).

Briefly, approximately 50 mg of each sample was deproteinized by adding 1,000 µL of extract solvent (Vacetonitrile: Vmethanol: Vwater = 2: 2: 1, containing 0.1% formic acid and 50 nmol/L internal standard). The mixture was vortexed for 60 s, homogenized at 35 Hz for 4 min, and sonication for 5 min in ice-water bath. These steps were repeated for 3 times, followed by incubation at −20 °C for 1 h. After centrifugation at 12,000 × g for 10 min at 4°C, the supernatants were collected and diluted with methanol before UPLC/MS analysis. The BAs were quantified by Waters ACQUITY UHPLC System (Waters Technologies, Milford, MA) coupled with a AB SCIEX4000 MS (AB SCIEX, Framingham, MA). An ACQUITY UPLC BEH column (100 mm × 2.1 mm, 1.7 µm, Waters) heated to 45 °C was used for chromatographic separation. A gradient system consisted of the Solvent A (0.01% acetic acid) and the Solvent B (acetonitrile) at a flow rate of 0.25 mL/min. The auto-sampler temperature was set at 4°C and the injection volume was 3 µL. BA standards were obtained from Sigma-Aldrich, Co. Ltd. (St. Louis, MO). The mix reference standards were prepared by dissolving each BA reference standard respectively in methanol.

Cell Culture and Treatment

The chicken preadipocyte cell line (CPI) was obtained from Northeast Agricultural University (Harbin, China). CPI cells were cultured with growth media containing 85% DMEM/F12, 15% fetal bovine serum (FBS, GIBCO, Grand Island, NY), and penicillin 100 U/mL, streptomycin 100 U/mL, plated in a 6-well plate at 37°C in a humidified, 5% CO2 atmosphere. The medium was changed every 48 h. At 30% confluence, CPI cells were incubated in an adipogenic medium composed of 10% FBS/DMEM supplemented with insulin (10 µg/mL, Sigma), dexamethasone (1 µM, Sigma), 3-isobutyl-1-methylxanthine (IBMX, 115 ng/mL, Sigma) for 24 h. Then the cells were treated with 30 μmol/L lithocholic acid (LCA, Sigama), 30 μmol/L lithocholic acid and 5 μmol/L Z-guggulsterone (Z-g, Yuanye, Shanghai) and DMSO control group. After 7- to 10 d incubation, the cells were used for Oil Red O staining (Qu et al., 2015) and were collected for mRNA expression analysis respectively. The images of Oil Red O staining were analyzing by image-pro plus 6.0 software to show the percent (Per) of red lipid drop area.

RNA Isolation and Real-Time PCR

Quantitative real-time PCR was performed on samples of liver and CPI cells. Total RNA was isolated using TRIzol reagenta MiniBEST Universal RNA Extraction Kit (TaKaRa, Dalian, China) and cDNA samples were obtained by reverse transcription of total RNA using a High Capacity cDNA Reverse Transcription Kit (Thermo Fisher Scientific, Waltham, MA) and stored at –20 °C until analysis. Gene expression levels were measured by real-time PCR using SYBR1 Premix Ex Taq (Tli RNaseH Plus; Takara Biotechnology Inc., Osaka, Japan) and an ABI 7500 Real Time PCR Systems (Applied Biosystems, Foster City, CA). Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) expression levels were used as an internal control to normalise the amount of initial RNA for each sample. Primer sequences for the target and reference genes are shown in Table 2. The results of relative expression of genes were calculated using the the 2−ΔΔCt method (Livak and Schmittgen, 2001).Table 2 Primers used in PCR.

Table 2Target gene1	Primer sequences (5′—3′)	Accession number	
FAT/CD6	F: TAATCATCGCAGGTTCT	DQ323177.1	
R: GCTTATTTGGGTTATTCAGT	
FAS	F: CAATGGACTTCATGCCTCGGT	J04485	
R: GCTGGGTACTGGAAGACAAACA	
C/EBPβ	F: GCCCGACTACACCTACATCAGC	NM_205253	
R: GCTCCACTTTGGTCTCCACGAT	
LPL	F: GACAGCTTGGCACAGTGCAA	NM_205282	
R: CACCCATGGATCACCACAAA	
apoVLDL	F: CAGTTCTTGCTGGATGTTTCCCAGAC	S82591.1	
R: CAATGGCCAAGTCATTCAGGAGGA	
FXR	F: AGTAGAAGCCATGTTCCTCCGTT	AF492497	
F: GCAGTGCATATTCCTCCTGTGTC	
CYP7A1	F: GATCTTCCCAGCCCTTGTGG	AY700578	
F: AGCCTCTCCCAGCTTCTCAC	
PPARγ	F:CAGTGGATCTGTCTGCGATG	NM_001001460	
R:GCTCTTCCAAGAGGTATATC	
ACC	F:AATGGCAGCTTTGGAGGTGT	NM_205505	
R:TCTGTTTGGGTGGGAGGTG	
SREBP-1c	F:GAGACCATCTACAGCTCCGC	NM_204126	
R:ATCCGAAAAGCACCCCTCTC	
GAPDH	F: GGAGAAACCAGCCAAGTAT	NM_204305.1	
R: CCATTGAAGTCACAGGAGA	
1 FAT/CD36, fatty acid translocase (FAT/CD36); FAS, fatty acid synthase; C/EBPβ, CCAAT/enhancer binding protein β; LPL, Lipoprotein lipase; apoVLDL, apolipoprotein -very low density lipoprotein; FXR, farnesoid X receptor; CYP7A1, cholesterol-7α- hydroxylase; PPARγ, peroxisome proliferator-activated receptor γ; ACC, acetyl-CoA carboxylase; SREBP-1c, sterol regulatory element-binding protein-1c.

High-throughput Sequencing of the Microbial 16S rRNA Analysis

The cecal microbiota was determined with 16S rRNA sequencing analysis as described previously (Song et al., 2020). Briefly, bacterial DNA was extracted from 18 cecal digested samples using an E.Z.N.A.®digesta DNA Kit (Omega Bio-tek, Norcross, GA) according to the manufacturer's protocols. The DNA concentration and purification were determined using TBS-380 and a NanoDrop 2000 UV-vis spectrophotometer (Thermo Scientific, Wilmington, DE), respectively. DNA quality was examined by 1% agarose gel electrophoresis. The V3-V4 hypervariable regions of the bacterial 16S rRNA gene were amplified with primers 338F (5ʹ-ACTCCTACGGGAGGCAGCAG-3ʹ) and 806R (5ʹ-GGACTACHVGGGTWTCTAAT-3ʹ) using a thermocycler polymerase chain reaction (PCR) system (GeneAmp 9700, ABI, CA). The sequencing of the PCR products was performed on an Illumina MiSeq platform (Illumina, San Diego, CA) according to standard protocols, by Majorbio Bio-Pharm Technology Co. Ltd. (Shanghai, China).

Statistical Analyses

All statistical analyses were performed using SAS V8. Means were compared by one-way analysis of variance followed by Duncan's multiple tests. Relationships between liver bile acid profiles and lipid deposition-related indicators were analyzed based on Pearson's test, and between fecal microbiota and liver bile acid profiles were analyzed based on Spearman's test using R software (Version 3.5.0). Orthogonal polynomial contrasts were also used to evaluate the linear and quadratic effects of dietary protein levels. Statistical significance was considered at P < 0.05.

RESULTS

Growth Performance

The effects of dietary CP levels on growth performance are shown in Table 3, the dietary CP levels had no significant effect on final body weight, average daily body weight gain, and average daily feed intake (P > 0.05).Table 3 Effects of dietary crude protein level on growth performance of growing pullets.1

Table 3Items2	Treatment3	SEM	P-value	
HP group	MP group	LP group	Linear	Quadratic	
Initial body weight, g/hen	912	920	936	10.16	0.254	0.769	
Final body weight, g/hen	1608	1600	1640	13.35	0.208	0.658	
ADG, g/hen/d	35	34	35	2.61	0.593	0.719	
ADFI, g/hen/d	66	67	67	4.28	0.794	0.826	
1 Results are the mean of 6 replicate cages, 10 birds per cage.

2 ADG, average daily gain; ADFI, average daily feed intake.

3 HP group, high-protein diet group; MP group, medium-protein diet group; LP group, low-protein diet group.

Lipid Contents in the Body and Lipid Metabolism-Related Gene Expression in the Liver

The effects of dietary CP levels on lipid deposition are shown in Tables 4 and 5. Dietary protein level had significant effect (P < 0.05) on the lipid contents in the body. The contents of BIMF, LIMF, PAF, liver TG and liver TC in LP group were significantly higher than in HP group (P < 0.05). Decreasing CP levels in diets linearly and quadratically (P < 0.05) increased the contents of BIMF, LIMF, PAF, liver TG and liver TC in pullets. As showed in Table 5, the serum TC, HDL-c, LDL-c, VLDL contents were increased linearly (P < 0.05) with the decrease in dietary protein level.Table 4 Effects of dietary protein level on lipid deposition of growing pullets.1

Table 4Items2	Treatment3	SEM	P-value	
HP group	MP group	LP group	Linear	Quadratic	
BIMF (%)	1.25c	1.89b	2.01a	0.162	0.012	0.029	
LIMF (%)	1.64c	2.39b	3.79a	0.141	0.001	0.001	
PAF (%)	1.2b	1.8b	2.4a	0.331	0.009	0.006	
Liver TG content (mg/g)	9.39c	10.18b	12.25a	0.514	0.017	0.034	
Liver TC content (mg/g)	2.36b	3.08ab	3.27b	0.091	0.035	0.041	
a,b,c Means with different superscripts differ significantly (P < 0.05).

1 Results are the mean of 6 replicate cages, 1 birds per cage.

2 BIMF, Breast intramuscular fat; LIMF, Leg intramuscular fat; PAF, Percentage of abdominal fat; TG, Triglyceride; TC, Total cholesterol.

3 HP group, high-protein diet group; MP group, medium-protein diet group; LP group, low-protein diet group.

Table 5 Effects of dietary protein level on serum lipid metabolism-related parameters of growing pullets.1

Table 5Items2	Treatment3	SEM	P-value	
HP group	MP group	LP group	Linear	Quadratic	
TC (mmol/L)	2.85b	3.09ab	3.12a	0.047	0.038	0.079	
TG (mmol/L)	0.34	0.36	0.38	0.015	0.615	0.817	
HDL-c (mmol/L)	1.83b	2.17ab	2.28a	0.017	0.019	0.026	
LDL-c (mmol/L)	0.75b	0.89a	0.91a	0.006	0.036	0.063	
VLDL (mmol/L)	0.30a	0.25b	0.16c	0.011	0.002	0.015	
a,b,c Means with different superscripts differ significantly (P < 0.05).

1 Results are the mean of 6 replicate cages, 1 birds per cage.

2 TC: Total cholesterol; TG: Triglyceride; HDL-c: High-density lipoprotein cholesterol; LDL-c: low-density lipoprotein cholesterol; VLDL, very low-density lipoprotein cholesterol.

3 HP group, high-protein diet group; MP group, medium-protein diet group; LP group, low-protein diet group.

In terms of lipid metabolism-related genes (Figure 1), there were a significantly increased (P < 0.05) mRNA expression of FAS, C/EBPβ, and FAT/CD6 in LP group, and a significantly decreased (P < 0.05) mRNA expression of LPL and apoVLDL (P < 0.05).Figure 1 Effects of dietary protein level on lipid metabolism related gene mRNA expression in liver of growing pullets (n = 6). a,b,cDifferent superscripts above bar differ significantly between each other (P < 0.05). HP group, high-protein diet group; MP group, medium-protein diet group; LP group, low-protein diet group; FAT/CD36: fatty acid translocase (FAT/CD36); FAS: fatty acid synthase; C/EBPβ: CCAAT/enhancer binding protein β; LPL: lipoprotein lipase; apoVLDL: apolipoprotein -very low density lipoprotein.

Figure 1

Liver BA Profile and BA Metabolism-Related Gene Expression in the Liver

The effects of dietary CP levels on BA profile are showen in Table 6. Dietary protein level had significant effect (P < 0.05) on the secondary BAs, such as lithocholic acid (LCA), isoLCA, deoxycholic acid (DCA), ursodeoxycholic acid (UDCA), β-muricholic acid (β-MCA) contents in the liver, but had no significant effect (P > 0.05) on the primary BAs (Table 6). Low dietary protein level (LP group) significantly linearly and quadratically reduced (P < 0.05) the contents of LCA, isoLCA, and UDCA. There was a significant linearly and quadratically increased (P < 0.05) content of DCA and β-MCA with a decreasing dietary protein level. In terms of BAs metabolism-related genes (Figure 2), the mRNA expression of FXR and CYP7A1 were significantly reduced with the decreasing dietary protein level (P < 0.05).Table 6 Effects of dietary protein level on liver bile acids content of growing pullets1, mg/kg.

Table 6Items2	Treatment3	SEM	P-value	
HP group	MP group	LP group	Linear	Quadratic	
Secondary bile acids							
 LCA	5.28a	4.67b	3.63c	0.133	0.042	0.033	
 isoLCA	3.72a	3.61a	2.78b	0.118	0.016	0.039	
 DCA	1.64c	3.41b	4.48a	0.016	0.018	0.027	
 UDCA	14.09a	9.67b	9.51b	0.543	0.023	0.036	
 β-MCA	117.67b	127.74ab	132.80a	4.095	0.037	0.048	
 α-MCA	3.52	3.87	3.02	0.059	0.251	0.634	
 UCA	2.51	2.29	2.10	0.049	0.185	0.291	
 GUCA	130.20	140.00	138.22	4.361	0.095	0.196	
 GLCA	16.45	16.55	15.65	0.643	0.628	0.837	
 GHDCA	10.39	9.88	10.27	0.645	0.376	0.688	
 GUDCA	2.74	2.89	2.67	0.094	0.182	0.354	
 TLCA	0.51	0.44	0.46	0.015	0.247	0.516	
 TDCA	9.67	8.21	8.50	0.423	0.219	0.539	
Primary bile acids							
 CDCA	11.57	13.85	12.75	0.512	0.352	0.716	
 CA	2.58	2.40	2.43	0.061	0.357	0.638	
 GCDCA	1.15	1.09	0.94	0.082	0.521	0.619	
 GCA	3.50	2.96	3.26	0.099	0.364	0.729	
 TCDCA	4.84	4.27	4.42	0.223	0.368	0.658	
a,b,c Means with different superscripts differ significantly (P < 0.05).

1 Results are the mean of 6 replicate cages, 1 birds per cage..

2 LCA, lithocholic acid; isoLCA, isolithocholic acid; DCA, deoxycholic acid; UDCA, ursodeoxycholic acid; β-MCA, β-muricholic acid; α-MCA, alpha-muricholic acid; UCA, ursocholic acid; GUCA,glycoursocholic acid; GLCA, glycolithocholic acid; GHDCA, glycohyodeoxycholic acid; GUDCA, glycoursodeoxycholic acid; TLCA, taurolithocholic acid; TDCA, taurodeoxycholic acid; CDCA, chenodeoxycholic acid; CA, cholic acid; GCDCA, glycochenodeoxycholic acid; GCA, glycocholic acid; TCDCA, taurochenodeoxycholic acid.

3 HP group, high-protein diet group; MP group, medium-protein diet group; LP group, low-protein diet group.

Figure 2 Effects of dietary protein level on bile acid metabolism related gene mRNA expression of growing pullets in liver (n = 6). a,b,cDifferent superscripts above bar differ significantly between each other (P < 0.05). HP group, high-protein diet group; MP group, medium-protein diet group; LP group, low-protein diet group; FXR, farnesoid X receptor; CYP7A1, cholesterol-7α- hydroxylase.

Figure 2

Correlation Analysis of BAs Profiles and Lipid Metabolism Related-Parameters

The correlation analysis of BAs profiles and lipid metabolism are showed in Table 7. The results showed that LCA and UDCA were negatively correlated with PAF contents (P < 0.05), and isoCLA was negatively correlated with LIMF, PAF, Liver TG, and Liver TC contents (P < 0.05), while DCA was positively correlated with these lipid metabolism related-parameters, meanwhile DCA was positively correlated with serum HDL-C and LDLC (P < 0.05). The correlation analysis also showed that isoCLA was positively correlated with serum VLDL (P < 0.05), while DCA was negatively correlated with serum VLDL (P < 0.05).Table 7 Correlation analysis of BAs and lipid metabolism related-parameters.1

Table 7	LCA	isoLCA	DCA	UDCA	β-MCA	
Serum TC	−0.1775	−0.4434	0.5220	0.0780	0.2907	
Serum TG	−0.0206	−0.2301	0.3730	0.0456	0.2655	
HDL-C	−0.2253	−0.5397	0.6925*	0.0550	0.4036	
LDL-C	0.0572	−0.4621	0.7607*	0.2530	0.7008	
VLDL	0.4152	0.7390*	−0.7891*	0.2188	−0.4304	
BIMF	−0.0061	−0.7190	0.9664	0.27030	0.7349	
LIMF	−0.4473	−0.9294**	0.9350**	−0.2023	0.4414	
PAF	−0.8492*	−0.8893**	0.5822	−0.7242*	−0.0821	
Liver TG	−0.5009	−0.9576**	0.9110**	−0.2536	0.3974	
Liver TC	0.0764	−0.6526*	0.9470**	0.3615	0.7743	
*Means significant difference, P < 0.05. **Means significant difference, P < 0.01

1 Results are the mean of 6 replicate cages, 1 birds per cage.

LCA, lithocholic acid; isoLCA, isolithocholic acid; DCA, deoxycholic acid;

UDCA, ursodeoxycholic acid; β-MCA, β-muricholic acid; TC, total cholesterol; TG, triglyceride; HDL-c, high-density lipoprotein cholesterol; LDL-c, low-density lipoprotein cholesterol; VLDL, very low-density lipoprotein cholesterol; BIMF, breast intramuscular fat; LIMF, leg intramuscular fat; PAF, percentage of abdominal fat.

Effect of LCA on Lipid Metabolism in CPI Cells

The effects of LCA on lipid metabolism are shown in Figure 3. To examine the role of bile acids on lipid metabolism regulation, CPI cells were treated with LCA or LCA combination with Z-guggulsterone (Z-g) which was regarded as a FXR inhibitor. The results (Figure 3B) showed that compared with DMSO group, LCA administration significantly down-regulated the relative expression of PPARγ, FAS, ACC and SREBP-1c (P < 0.05). But LCA combination with Z-guggulsterone administration significantly up-regulated the relative expression of PPARγ, FAS, ACC, and SREBP-1c compared with LCA group (P < 0.05). The result of oil red O staining of CPI cells (Figure 3A) also shown that CPI cells treated with LCA reduced the percent area of red lipid drop compared with DMSO group, and CPI cells treated with LCA combination with Z-guggulsterone increased the percent area of red lipid drop compared with LCA group (Figure 3C), which indicated that LCA might reduce the lipid droplets.Figure 3 Effect of LCA on mRNA expression related to lipid metabolism of CPI cells. (A) Relative mRNA expression related to lipid metabolism of CPI cells. a,b,cDifferent superscripts above bar differ significantly between each other (P < 0.05). DMSO, dimethyl sulfoxide; LCA, lithocholic acid; Z-g, Z-guggulsterone; PPARγ, peroxisome proliferator-activated receptor γ; ACC, acetyl-CoA carboxylase; SREBP-1c, sterol regulatory element-binding protein-1c. DMSO, dimethyl sulfoxide; LCA, lithocholic acid; Z-g, Z-guggulsterone. (B) Oil red O staining of CPI cells (40X). (C) The lipid drop area percent.

Figure 3

The Alpha Diversity of Cecal Microbiota

The alpha diversity of cecal microbiota was shown in Table 8. Compared with HP group, both richness indices (Chao1 and ACE) and diversity index (Shannon) significantly reduced in the LP group (P < 0.05), meanwhile, the diversity index (Simpson) significantly increased in the LP group (P < 0.05).Table 8 Alpha diversity caecal microbial flora1

Table 8Items	Treatment2	SEM	P-value	
HP group	MP group	LP group	Linear	Quadratic	
Shannon	3.628a	3.431b	3.300b	0.218	0.013	0.037	
Simpson	0.055a	0.064a	0.108b	0.001	0.002	0.016	
Ace	415a	396ab	386b	22.3	0.005	0.013	
Chao1	433a	391b	388b	21.8	0.014	0.035	
a,b Means with different superscripts differ significantly (P < 0.05).

1 Results are the mean of 6 replicate cages, 1 birds per cage..

2 HP group, high-protein diet group; MP group, medium-protein diet group; LP group, low-protein diet group.

The Cecal Microbiota Composition at Phyla Level

The effects of dietary CP levels on cecal microbiota composition are shown in Figure 4. The most abundant phyla are presented in Figure 4A.The dominant phyla in the cecal microbiota across all the groups were Bacteroidetes (73.58-46.73%), Firmicutes (44.61-21.21%), Actinobacteria (4.57-1.52%), Proteobacteria (2.59-1.19%), which accounted for >97% of the total sequences (Figure 4A).Figure 4 Relative abundance of cecal microbiota at phylum level. (A) Relative abundance of cecal microbiota phylum for LP, MP, and HP group. (B) The microbiota differential abundant at phylum level among groups in the cecum by One-way ANOVA analysis. HP, high-protein diet group; MP, medium-protein diet group; LP, low-protein diet group.

Figure 4

Low dietary protein (LP group) significantly increased (P < 0.05) the abundance of Bacteroidetes and significantly decreased (P < 0.05) the abundance of Firmicutesa compared with the middle dietary protein (MP group) and high dietary protein (HP group) (Figure 4B).

Correlations Among Microbiota Genus and BA Metabolism

Spearman's correlation analysis was performed to determine the correlations between the abundance of top 30 microorganisms (genus level) and the significantly different hepatic BA profiles (Figure 5). Results revealed that the relative abundances of Alloprevotella was positively correlated with the hepatic LCA and isoLCA contents, and negatively correlated with the hepatic DCA contents. The relative abundances of Rikenellaceae_RC9_gut_group was negatively correlated with the hepatic DCA and β-MCA contents. It is worth noting that several bacterial genus, such as Odoribacter, Sellimonas, Lachnoclostridium, unclassified_f__Ruminococcaceae, and [Ruminococcus]_torques_group, were positively correlated with the hepatic DCA. In addition, UDCA contents was significantly positively correlated with norank_f__Muribaculaceae, and β-MCA contents was significantly positively correlated with Odoribacter, Phascolarctobacterium, Faecalibacterium. These correlations suggest that the liver BA profiles were closely related to host microbiota composition.Figure 5 Correlations among microbiota genus and BA metabolism. LCA, lithocholic acid; isoLCA, isolithocholic acid; DCA, deoxycholic acid; UDCA, ursodeoxycholic acid; β-MCA, β-muricholic acid.

Figure 5

DISCUSSION

Liver is the primary organ of lipid metabolism and bile acie metabolism in chickens. Dysregulation of lipid metabolism and BA metabolism homeostasis have been associated with the development of fatty liver, a common nutritional metabolic disease, which contribute to the increase in mortality and decrease in egg production in laying hens (Lefort and Cani, 2021;Gillard et al., 2022). The pathogenesis of fatty liver diseases in laying hens is accompanied by excessive lipid accumulation in livers. Diet is the main factor regulating hepatic fat metabolism. In chickens, high energy low protein diets induce fatty liver (Zhuang et al., 2019). Liver fat content is closely related to fat synthesis, TG secretion, absorption of free fatty acids (FFA) and fat oxidation in liver (Otani et al., 2020). This study shows that low crude protein diet can not only up-regulate the expression of genes related to liver fat synthesis such as FAS and C/EBPβ, but also increase the intramuscular fat content, PAF and liver TG content. High crude protein level would inhibit liver malate enzyme activity, thereby reducing lipid content in liver (Mohiti-Asli et al., 2012). The insufficiency of dietary protein and amino acid contribute to the increase of liver fat (Xie et al., 2016; Lin et al., 2021; Heo et al., 2023). The study showed that the imbalance of amino acids will increase the catabolism of amino acids, and the carbon skeleton may be converted into intermediate metabolites for the synthesis of carbohydrates and fats, thus increasing the capacity of fat synthesis (Xie et al., 2016). A large number of studies have shown that adding Met, Arg and Thr in low crude protein diet can reduce liver fat content. In this study, although Lys, Met, Thr and Trp were also added in low protein diet group, the fat deposition of that group was also significantly increased. It may be that dietary crude protein level has a greater influence on liver fat metabolism. Therefore, the mediate dietary protein levels have an important effect on hepatic fat deposition.

It was reported that bile acid (BA) metabolism disorder play an important role in lipid metabolism and the pathogenesis of fatty liver disease (Chen et al., 2021; Sun et al., 2023). The many evidence showed that secondary BAs (e.g., DCA, GDCA and TDCA) are closely related to liver fat content, which can regulate fat synthesis by activating FXR and SREBP-1c pathways or independently of SHP and SREBP1C pathway (Chen et al., 2020; Clifford et al., 2021). As BAs receptor, FXR plays an important role in the regulation of BAs homeostasis and fat metabolism. FXR activation can reduce liver fat level by promoting PPARα/γ expression (Zhao et al., 2020; Xu et al., 2022). BAs also activates SHP expression through FXR induction to inhibit the expression of SREBP-1c and reduce the synthesis of FA, TG and VLDL (Rajani & Jia, 2018). This study showed that low dietary protein reduced the contents of FXR agonists LCA and UDCA and increased FXR antagonist DCA and β-MCA, which were all closely related to the fatty liver (Tang et al., 2019; Marion et al., 2020; Wang et al., 2020). In this study, the results of CPI cells treating with FXR antagonist Z-g showed that the Z-g group increased LCA-relieved fat deposition in CPI cells, which indicated that LCA could down-regulate the expression of FAS, ACC, and SREBP-1c and reduce fat deposition in CPI cells, which was in agreement with previous study (Luu et al., 2018).

Many studies have revealed the role of gut microbiota in BA metabolism and fat deposition (Han et al., 2022). Microbial diversity and abundance have a significant impact on the formation of secondary BAs (Marion et al., 2020). The primary BAs are converted into secondary BA through microbial deconjugation, dehydrogenation, dihydroxylation, and epimerization with the action of microbial enzyme such as microbial bile saline hydrolyase (BSH) and steroid dehydrogenase (Han et al., 2022). Bile saline hydrolyase is expressed in large quantities by major microorganisms such as Lactobacillus, Bifidobacterium, Enterococcus, Bacteroides and Clostridium. Therefore, the species and abundance of these microbes in the gut affects the composition and levels of secondary BAs, which significantly affects the lipid metabolism. Previous studies have shown that dietary protein has an important effect on gut microbial composition (Rist et al., 2013; Diether and Willin, 2019). Decreased dietary protein level can lead to the growth of intestinal pathogens such as Clostridium Perfringens and Campylobacter, and inhibit the growth of Bifidobacterium (Rist et al., 2013). Reducing dietary protein can significantly increase the Lactobacillus level in cecum of poultry (De Cesare et al., 2019). This study also showed that Low dietary protein increased the abundance of Bacteroidetes and decreased the abundance of Firmicutesa at phyla level, which may implicate in the metabolism of BA and lipid.

CONCLUSIONS

In summary, although dietary CP levels did not affect growth performance of growing pullets, CP levels had an important effects on liver lipid deposition, bile acid profile and gut microbiota composition. Furthermore, low CP levels increased the hepatic fat depositon by regulating the gut microbiota and liver bile acid profile, which maybe increase the risk of fatty liver of growing pullets. Therefore, the mediate dietary protein levels have an important effect on liver health of growing pullets.

DISCLOSURES

The authors declare no conflicts of interest.

Appendix Supplementary materials

Image, image 1

Supplementary material associated with this article can be found in the online version at doi:10.1016/j.psj.2024.104183.
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