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

S0032-5791(24)00765-X
10.1016/j.psj.2024.104186
104186
MANAGEMENT AND PRODUCTION
Exploring the relationship between rearing system and carcass traits of Danzhou chicken: a microbial perspective
Yuan Bo ⁎1
Md. Ahsanul Kabir ⁎†1
Rong Li ⁎
Han Shaobo ⁎
Pan Yangming ⁎
Hou Guanyu guanyuhou@126.com
‡2
Li Shijun ⁎§#
⁎ Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Huazhong Agricultural University, Wuhan, Hubei Province 430070, China
† Biotechnology Division, Bangladesh Livestock Research Institute, Savar, Dhaka-1341, Bangladesh
‡ Tropical Crops Genetic Resources Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou, China
§ Key Laboratory of Smart Farming for Agricultural Animals, Ministry of Education, Huazhong Agricultural University, Wuhan, Hubei Province 430070, China
# Hubei Hongshan Laboratory, Wuhan, Hubei Province 430070, China
2 Corresponding author: guanyuhou@126.com
1 These authors should be considered the joint first author.

08 8 2024
11 2024
08 8 2024
103 11 10418611 6 2024
2 8 2024
© 2024 Published by Elsevier Inc. on behalf of Poultry Science Association Inc.
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/).
This study investigated the effects of free-range (FR) and cage-rearing (CR) systems on intestinal health, carcass traits, and microbial diversity in the Danzhou chicken breed. Two groups of 125 hens in each group, aged 42 wk, were reared under FR and CR systems. At 50 wk, 50 hens from each group were randomly selected for carcass analysis and 10 hens for intestinal morphology and microbiota profiling. Results indicated a significant increase in villus height (VH) in the duodenum (P < 0.05), jejunum (P < 0.01), and ileum (P < 0.001) of the CR group. Additionally, the ratio of VH to crypt depth (VR) significantly (P < 0.001) increased in the jejunum, while crypt depth (CD) decreased significantly (P < 0.001) in the same section in the CR group. Carcass traits, including dress weight (DW), eviscerated with giblet weight (EGW), eviscerated weight (EW), and leg muscle weight (LW) significantly improved (P < 0.05) in the CR group. Microbial diversity showed significant β-diversity differences, with Lactobacillus, Enterococcus, and Oxalobacteraceae as dominant biomarkers in the CR group. Conversely, Actinomycetaceae, Erysipelotrichaceae, Coriobacteriaceae, Eubacterium, Actinomyces, Scardovia, and Lachnospiraceae were dominant in the FG group. Correlation analysis showed duodenum Lactobacillus was positively correlated with VH (P < 0.05), EW (P < 0.05), and LW (P < 0.001). Jejunum Lactobacillus was positively correlated considerably with VH (P < 0.01), VR (P < 0.05), DW (P < 0.05), EGW (P < 0.01), and LW (P < 0.001). Ileum Lactobacillus was positively correlated with EGW (P < 0.01), EW (P < 0.05), and LW (P < 0.01). Aeriscardovia in duodenum was positively (P < 0.01) associated with EGW. Enterococcus in the duodenum was positively (P < 0.05) associated with EGW and in Jejunum positively correlated with VH (P < 0.05) and VR (P < 0.01). The study concludes that cage rearing improves intestinal health, carcass traits, and microbial diversity in Danzhou chickens, with Lactobacillus and Enterococcus playing key roles.

Key words

rearing system
carcass trait
intestinal health
microorganism
Danzhou chicken
==== Body
pmcINTRODUCTION

Danzhou chicken is a small breed native to Hainan, China. It was discovered in 2014 and has been found to have many beneficial traits, such as adaptability, disease resistance, tolerance to crude feeding conditions, low-fat meat, and a delightful taste profile (Peng et al., 2019). In China, people rear Danzhou chickens using both free and cage-rearing systems. Previous research suggests that the rearing system is closely linked to chickens' welfare, health, and productivity (Abo Ghanima et al., 2020). Moreover, much research was conducted to determine a suitable rearing system for the boiler and layer (Abo Ghanima et al., 2020; Chen et al., 2020; Wan et al., 2021; Song et al., 2022). Still, there is a lack of information on suitable rearing methods for native chickens like Danzhou.

The caged-rearing system has many benefits, such as reduced labor costs, enhanced uniformity, improved feed efficiency, and lower rates of coccidiosis (Sun et al., 2023). However, the free-range system is considered beneficial for improving chicken welfare. However, it can lead to a higher feed-to-gain ratio, increased feed costs, and reduced land use efficiency (Wang et al., 2021). Studies comparing indoor-floor, cage, and free-range systems have shown that free-rearing systems significantly reduce growth, abdominal fat, and carcass traits in boiler, slow, and medium-growing chickens (Wang et al., 2009; Li et al., 2017b; Abo Ghanima et al., 2020). However, studies investigating the meat tenderness, water-holding capacity, and protein content of free-range chickens have shown inconsistent findings, with some studies indicating superior results, others reporting inferior outcomes, and some showing no significant difference compared to alternative methods (Wang et al., 2021). In addition, a free-range rearing system increases energy requirements due to increased animal movement (Wiersema et al., 2021). This increase in movement may impact production, and other factors such as intestinal morphology, microbes, or other substances that could potentially affect production in different rearing systems are still not fully understood.

The development of microorganisms in chickens is associated with the rearing system and significantly impacts feed digestion, nutrient absorption, and metabolism of the birds (Chen et al., 2019; Wang et al., 2021; Stefanetti et al., 2023). A healthy balance of gastrointestinal bacteria is crucial for proper digestion and absorption of nutrients, helps enhance intestinal barrier function, fosters symbiotic relationships, and combats pathogens (Nochi et al., 2018; Li et al., 2022). Recent research has focused on microbial diversity in different rearing systems and the correlation between microbes, intestinal health, immune function, and meat production in different rearing systems for broiler chickens and reported that some impotent bacteria significantly correlated with immunity, intestinal health, and meat production (Shi et al., 2019; Wiersema et al., 2021; Lei et al., 2022; Song et al., 2022). Although native chicken meat is popular due to its unique taste and texture compared to broiler meat (Jayasena et al., 2013; Jaturasitha et al., 2017), there are limited studies on the microbial correlation between intestinal morphology and meat production. However, some studies reported that adding Lactobacillus spp. (Pan and Yu, 2013) and Bifidobacterium spp. (Fathima et al., 2022). Chicken diets have such types of microbes that significantly enhanced intestinal tissue health, nutrient absorption, and meat production (Li et al., 2018; Aruwa et al., 2021). Enterococcus spp., Candidatus Savagella, Ruminococcus, and Lachnospiraceae are potential microorganisms that promote good intestinal tissue health, absorption, and meat production (Maki et al., 2019; Ducatelle et al., 2023).

Native chicken breeds are predominantly raised in extensive systems and play a vital role in the economies of rural areas in most developing and underdeveloped countries (Padhi, 2016). However, the optimal rearing system for native chickens regarding production and microbial diversity is unclear due to limited research, especially for Danzhou chickens. It is suspected that the rearing system regulates microbial diversity, and increasing or decreasing some potential microbes may regulate intestinal health as well as carcass traits. To address this, we compared the microbial diversity, intestinal health, and carcass trait of Danzhou chickens raised in cage and free-rearing systems to determine the better rearing system regarding intestinal health and production. Moreover, we also correlate microbial diversity with intestinal health and meat production to identify some potential microbes influencing good health and production. Our findings will improve the understanding of the relationship.

MATERIALS AND METHODS

Ethics Statement

This research was conducted by the guidelines for the Care and Use of Laboratory Animals, as specified by the Standing Committee of the Hubei People's Congress (No. 5) issued on July 29, 2005. The Ethics Committee of Huazhong Agricultural University, PR China, approved it (Approval number: 202408020006).

Bird and Sample Collection

The experiment was conducted at the Danzhou Chickens Ancestral Generation Chicken Farm in Rekeyuan, Danzhou City, Hainan Province. Danzhou hens were selected based on similar average body weight (867.53 ± 56.98 g) and were raised on two different systems. Briefly, the experiment divided 250 healthy, 42-wk-old Danzhou hens into two groups. One group was reared in a cage (CR) system, which served as the control group, and the other group was reared in the free-rearing system (FR), the experimental group. Each group comprised 125 hens and was further divided into 5 replications, with 25 hens in each replication. This experiment was conducted according to completely randomized design (CRD). The sample size was determined based on previous research (Li et al., 2017a; Dong et al., 2020; Stefanetti et al., 2023).

In the CR system, each chicken was housed individually in a closed controlled housed cage environment with seven birds per square meter density. The average temperature was maintained at 21.73 ± 1.30 (ranges between 20° and 25°C), and the average relative humidity level was 64.12 ± 1.28 (ranges between 60% and 70%). The birds were exposed to 16 h of light and 8 h of darkness. White LED lights were used as a lighting source, and the lighting intensity was 15 lux. On the other hand, chickens in the FR system were kept in a confined open area with access to free daylight (from 6:00 to 18:00), a grass paddock with a density of 1 bird per square meter, and an indoor housing facility with a density of 6 birds per square meter at night (Wang et al., 2009; Li et al., 2017b). During the feeding trial, CR and FR chickens were given the same diet (Table 2S) according to the NRC feeding standard (NRC, 1994) and had unlimited access to water without antibiotics or probiotics. At 50 wk of age sample was collected from the experimental birds. Random sampling was conducted for carcass trait characteristics. For this purpose, 50 hens (10 hens from each replication) from each group were randomly selected for data recording for carcass traits. However, 10 hens (5 from each rearing system) were used for intestinal morphology and microbiota profiling.

Carcass Characteristics

Chickens were slaughtered in a processing plant using an electrical stunning procedure for carcass analysis. Before slaughtering, 12-hower fusting was provided. Several measurements, including dressing weight (DW), eviscerated with giblet weight (EGW), eviscerated weight (EW), leg muscle weight (LW), breast muscle weight (BW), leg muscle ratio (LR), breast muscle ratio (BR) were measured according to the "Terminology and Measurement Methods for Poultry Production Performance" (NY/T 823-2020) guideline (Chen et al., 2024). DW refers to the weight of the chicken after bleeding and plucking, but before the internal organs have been removed. Eviscerated weight indicates the weight of the chicken after the internal organs have been removed. Eviscerated with giblet weight describes the eviscerated weight, including the giblet (heart, liver, and gizzard). The LR and BR were calculated using specific equations:Legmuscleratio(%)=LegmuscleweightEvisceratedweight×100

Breastmuscleratio(%)=BreastmuscleweightEvisceratedweight×100

Intestinal Morphology Analysis

The duodenum, jejunum, and ileum segments were separated, washed with a physiological saline solution containing 0.9% sodium chloride, and then stored in formaldehyde solution at room temperature. After sample collection, collected samples were embedded in paraffin wax before being sliced and stained with hematoxylin and eosin (Ma et al., 2023). To accurately evaluate the structural properties of the intestine, the villus height (VH), crypt depth (CD) that can be defined as the distance between the villus-crypt axis and the tip of the muscular mucosa, and the ratio of villus height and crypt depth (VR) were determined using Image-Pro Plus 6.0 software and light microscopy (Eclipse Ci-L), following the method described by Zhao et al. (2023).

Microbiota Profiling of Intestinal Sample

Microbiota profiling was performed via 16S rRNA sequencing according to Zhao et al. (2023), with slight modifications from the sampled segments of the gastrointestinal tract, including the duodenum, ileum, jejunum, and cecum. In brief, total microbial DNA was extracted using an OMEGA Soil DNA kit (Omega Bio Tek, Norcross, GA), and the quality of isolated DNA was quantified using a NanoDrop spectrophotometer (NC2000, Thermo Fisher Scientific, Waltham, MA) and 0.8 % agarose gel electrophoresis (Li et al., 2024). The universal primers (338F: 5′ACTCCTACGGGAGGCAGCA-3′ and 5′-GACTACHVGGTWTTCTAAT-3′) were used to amplify the V3–V4 region of the bacterial 16S rRNA gene (Zhao et al., 2023; Li et al., 2024a). The PCR amplification was conducted according to an initial denaturation step at 98°C for 15 s, followed by 25 cycles of denaturation (98°C for 15 s), annealing (50°C for 30 s), and extension (72°C for 30 s), with a final extension at 72°C for 5 mi. Subsequently, the PCR products were purified and quantified using VAHTSTM DNA Clean Beads (Vazyme, Nanjing, China) and the Quant-iT PicoGreen dsDNA Assay Kit (Invitrogen, Carlsbad, CA), respectively. Finally, sequencing was conducted on the Illumina NovaSeq platform for paired-end reads of 250 base pairs using the NovaSeq 6000 SP Reagent Kit (500 cycles) at Bioprofile Co., Ltd., China and raw data was stored in FASTQ format. For sequence denoising or clustering DADA2 method was used (Callahan et al., 2016) and for bioinformatics analyses, QIIME2 2019.4 was used (Zhao et al., 2023). Alpha diversity (α-diversity) and beta diversity (β-diversity) were analyzed by applying QIIME2 software. During α-diversity analysis, three indices (Chao1, Simpson, and Shannon) were considered. Alpha diversity quantifies species variation within a single sample (Calle, 2019). Moreover, the structural diversity of microbial communities among samples was explored through beta diversity analysis, utilizing UniFrac distance metrics. Principal Coordinate Analysis (PCoA) was then employed to visualize the results. Significance testing for variations in microbiota structure across groups was conducted using Permutational Multivariate Analysis of Variance (PERMANOVA) with QIIME2. Moreover, to compare microbial diversity between two rearing systems, a particular statistical test called ANOSIM was conducted (Shi et al., 2019). Additionally, a combination of Linear Discriminant Analysis (LDA) with a score > 2.5 and Effect Size Measurements (LEfSe) was used to differentiate bacteria between groups further.

Statistical Analysis

A two-tail independent sample t-test was performed using IBM SPSS statistics (version 20) to compare the morphology of intestinal segments and carcass characteristics among two rearing systems. Before data analysis, the normality of data was checked by the Kolmogorov–Smirnov test, and the homogeneity of variance was examined by Levene's test. The differences were considered to be significant at P < 0.05, and data are presented as the mean ± Standard error of the mean (SEM). Moreover, correlation analysis was conducted using the correlation plot app in Origin2020, microbial OTU count, slaughter performance data, and intestinal tissue morphology data.

RESULTS

Impact of Rearing System on Histo-Morphology of the Intestinal Segment

The impact of the rearing system on the morphologies of different intestinal tissues was measured using VH, CD, and VR. Overall, VH and VR increased while CD decreased in the intestinal tissue of the cage-rearing group (Table 1). Specifically, VH showed a very significant increase in the Jejunum (P = 0.002) and ileum (P = 0.000) and a significant increase (P = 0.049) in the duodenum within the cage-rearing group compared to the free-rearing group. Moreover, VR significantly increased (P = 0.000) in the Jejunum within the cage-rearing group. Conversely, CD significantly decreased (P = 0.000) in the jejunum of the same group.Table 1 Measurement results of intestinal tissue morphology in each segment of the intestine.

Table 1Intestinal parts	CR (n = 5)	FR (n = 5)	P-value	
Duodenum	VH/μm	885.40 ± 18.38	833.30 ± 16.64	0.049	
CD/μm	222.66 ± 17.52	243.29 ± 16.82	0.406	
VR	4.14 ± 0.24	3.54 ± 0.20	0.081	
Jejunum	VH/μm	707.04 ± 25.83	589.50 ± 19.41	0.002	
CD/μm	137.22 ± 9.97	231.13 ± 15.49	0.000	
VR	5.46 ± 0.52	2.63 ± 0.15	0.000	
Ileum	VH/μm	802.62 ± 26.01	636.31 ± 24.76	0.000	
CD/μm	164.64 ± 18.46	177.92 ± 20.61	0.637	
VR	5.43 ± 0.60	4.04 ± 0.49	0.087	
Caecum	CD/μm	103.45 ± 2.81	101.53 ± 3.43	0.669	
VH/μm	252.19 ± 18.81	296.24 ± 15.72	0.893	
	VR	2.45 ± 0.18	2.93 ± 0.14	0.056	
Abbreviations: CR= cage rearing system; FR= free rearing system; VH =Villus height; CD= Crypt depth; VR= Ratio of villus height and crypt depth; n= Population number. All results are presented as the mean ± standard error of mean (SEM).

Impact of Rearing System on Meat Production

Compared to the free-rearing group, the cage-rearing group increased meat production. Moreover, the cage-rearing group's DW, EGW, EW, and LW increased significantly, and their significant levels were P = 0.044, P = 0.012, P = 0.017, and P = 0.029, respectively (Table 2). Farthermore, final body weight and body weight gain were significantly higher (P = 0.030 and P = 0.034, respectively) in the cage-rearing group (Table S3).Table 2 Impact of rearing system on meat production.

Table 2Indicators	FR (n=50)	CR(n = 50)	P – value	
Dress weight (g) (DW)	993.08 ± 8.60	1015.06 ± 6.46	0.044	
Eviscerated with giblets weight (g)(EGH)	974.82 ± 6.29	1004.08 ± 9.65	0.012	
Eviscerated weight (g)(EW)	900.92 ± 4.07	915.06 ± 4.18	0.017	
Leg muscle weight (g)(LW)	93.03 ± 2.15	100.8 ± 2.76	0.029	
Breast muscle weight (g)(BW)	57.54 ± 1.31	61.18 ± 1.61	0.082	
Leg muscle ratio (%)(LR)	10.34 ± 0.24	11.01 ± 0.30	0.078	
Breast muscle ratio (%)(BR)	6.39 ± 0.15	6.69 ± 0.17	0.201	
Abbreviations: CR= cage rearing system; FR= free rearing system; n= Population number; All results are presented as the mean ± Standard error of mean (SEM).

Impact of Rearing System on Microbial Diversity

Operational Taxonomic Unit Analysis of Intestinal Microbes

After sequencing, we obtained 3,155,772 high-quality reads from the duodenum, jejunum, ileum, and cecum samples. These reads were grouped into 24,759 Operational Taxonomic Units (OTU), and the distribution of OTUs varied across rearing conditions. Specifically, we observed 13,242 OTUs in the free-rearing system and 10,078 OTUs in the cage-rearing system, with 1,439 OTUs shared between both systems. When examining individual intestinal organs, the cecum had the highest number of OTUs, followed by the ileum, duodenum, and jejunum. Additionally, the rearing system influenced the distribution of OTUs, with higher percentages of OTUs observed in the duodenum and cecum in the free-rearing system and the jejunum and ileum in the cage-rearing system (Figure 1). Therefore, the rearing system significantly impacts the variation of OTUs in different intestinal tissues.Figure 1 Comparative OUT distribution in different rearing system where A, B, C, and D represents duodenum, jejunum, ileum and cecum OUT distribution respectively. Dd represents the duodenum of the free-rearing system; Cd represents the duodenum of the cage-rearing system; DJ represents the jejunum of the free-rearing system; CJ represents the jejunum of the cage-rearing system; CI represents the ileum of the cage-rearing system; DI represented the ileum of the free-rearing system; DD represented the cecum of the free-rearing system, and CD represented the cecum of the cage-rearing system.

Figure 1

Alpha and Beta Diversity Analysis

To analyze the differences in microbiota between different rearing systems, α and β diversity of gut microbes were performed. The α diversity result revealed no significant difference in the species abundance or diversity of the intestinal microbial community between different rearing systems (Table 1S). However, the β diversity was analyzed using the Bray-Curtis algorithm to calculate dissimilarities and to gauge the similarity among microbial communities (Shi et al., 2019; Wiersema et al., 2021). Notably, on the first principal coordinate axis (PCoA1) of the PCoA plot (Figures 2A–2D), distinct boundaries were observed between bacterial groups from cage rearing and free rearing. Moreover, the ANOSIM analysis revealed significant overall differences in the communities (Table 1S). The analysis showed significant variations (P < 0.01) in different intestinal microbes between the 2 rearing groups. In the duodenum, jejunum, ileum, and cecum, the significant levels were P = 0.004, P = 0.001, P = 0.013, and P = 0.004, respectively. Furthermore, the PCoA plot indicated that microbiota structure in different intestinal organs differed.Figure 2 Intestinal microbial beta diversity analysis. A. B, C, and D represent the intestinal microbial community PCoA analysis in the duodenum, jejunum, ileum, and cecum, respectively. Dd represents the duodenum of the free-rearing system; Cd represents the duodenum of the cage-rearing system; DJ represents the jejunum of the free-rearing system; CJ represents the jejunum of the cage-rearing system; CI represents the ileum of the cage-rearing system; DI represented the ileum of the free-rearing system; DD represented the cecum of the free-rearing system, and CD represented the cecum of the cage-rearing system.

Figure 2

Relative Abundance Analysis of Top 20 Phyla

After analysis of the small intestine at the phylum level, the top 20 phyla were compared between the two rearing systems and their proportion was represented by relative abundance (RA). It was observed that among 20 phyla, Bacteroidetes, Firmicutes, Proteobacteria, and Actinobacteria were dominating (Figure 3). However, the proportion of these bacteria phyla changed in different rearing systems. Both in the duodenum and jejunum, Firmicutes was dominating in the cage-rearing system (more than 90% RA); however, in the free-rearing system, Firmicutes and Actinobacteria were dominating, representing RA about 42.5% and 53.3%, respectively (Figures 3A and 3B). In the ileum of the cage-rearing system, the same train was observed, where Firmicutes dominated (more than 90% RA). In contrast, Firmicutes, Actinobacteria, and Bacteroidetes dominated the free-rearing system, representing RA at about 48, 32 and 18%, respectively (Figure 3C). In Cecum Bacteroidetes, Firmicutes, Proteobacteria, and Actinobacteria dominated, and no significant variations were observed considering the top 20 microbes between the cage and free-rearing system (Figure 3D).Figure 3 Relative abundance of gut microbiota in phylum and genus level. A, B, C and D represent the relative abundance map of microbiota at the phylum level in duodenum, jejunum, ileum, and cecum, respectively. E, F, G, and H represent the relative abundance map of microbiota at the genus level in duodenum, jejunum, ileum, and cecum, respectively. Dd represents the duodenum of the free-rearing system; Cd represents the duodenum of the cage-rearing system; DJ represents the jejunum of the free-rearing system; CJ represents the jejunum of the cage-rearing system; CI represented the ileum of the cage-rearing system; DI represented the ileum of the free-rearing system; DD represented the cecum of the free-rearing system, and CD represented the cecum of the cage-rearing system.

Figure 3

Comparing the top 20 genera between 2 rearing systems, it was observed that in the duodenum, jejunum, and ileum of the cage-rearing system, Lactobacillus and Enterococcus prevailed with more than 85% of total RA (Figure 3E, 3F, and 3G). However, in the free-rearing system, the RA of Lactobacillus was not more than 5%. Furthermore, the top 20 genera represented about 55 to 65% of total RA, with Enterococcus (Eubacterium) and Actinomyces (Actinomyces) were dominated. Among the two rearing systems, no significant variation in abundance was observed in Cecum, considering the top 20 microbes. (Figure 3H).

LEfSe Analysis of Microorganisms in Each Intestinal Segment

The LEfSe analysis was used to determine the significant biomarkers differentiating between free-range and cage-rearing chickens (Figure 4). The results showed that in the duodenum and jejunum of free-range chickens, Actinomycetaceae, Erysipelotrichaceae, Coriobacteriaceae, and Lachnospiraceae were the dominant biomarkers at the family level, while Actinomyces, Eubacterium, and Atopobium were the dominant biomarkers at the genus level. In the ileum, Erysipelotrichaceae, Coriobacteriaceae, Lachnospiraceae, Ruminococcaceae, and Oxalobacteraceae were the dominant biomarkers at the family level, and Eubacterium, Actinomyces, Scardovia were the dominant biomarkers at the genus level. On the other hand, in the cage-reared group, Lactobacillaceae was identified as a potential biomarker at the family level, while Lactobacillus and Pediococcus were identified at the genus level in the duodenum. In the jejunum, Lactobacillus and Oxalobacteraceae were identified as potential biomarkers at the family level, and Lactobacillus, Allobaculum, and Ralstonia were identified at the genus level. In the ileum, Lactobacillaceae and Enterococcaceae were the dominant biomarkers at the family level, while Lactobacillus, Enterococcus, and Aeriscardovia were the dominant biomarkers at the genus level. In the cecum, Desulfovibrionaceae and Synergistaceae were identified as the dominant biomarkers at the family level in the free-range group, with Desulfovibrio being the dominant biomarker at the genus level. However, in the cage-reared group, Bacteroidaceae, Veillonellaceae, and Lactobacillaceae were identified as the dominant biomarkers at the family level, with Bacteroides, Phascolarctobacterium, Faecalibacterium, and Lactobacillus being the dominant biomarkers at the genus level. The LDA value was used to determine the dominant biomarkers between the two groups. Biomarkers with an LDA value greater than 4 were considered dominant.Figure 4 Differential microorganisms in the jejunum of different feeding methods groups. (A, B) represented LEfSe analysis and LDA diagram of different microorganisms in the duodenum; (C, D) represented LEfSe analysis and LDA diagram of different microorganisms in the jejunum; (E, F) represented LEfSe analysis and LDA diagram of different microorganisms in the ileum; (G, H) represented LEfSe analysis and LDA diagram of different microorganisms in the cecum. Hollow dots represent insignificant differences between groups, while solid dots represent significant differences between groups; Dd represents the duodenum of the free-rearing system; Cd represents the duodenum of the cage-rearing system; DJ represents the jejunum of the free-rearing system; CJ represents the jejunum of the cage-rearing system; CI represented the ileum of the cage-rearing system; DI represented the ileum of the free-rearing system; DD represented the cecum of the free-rearing system, and CD represented the cecum of the cage-rearing system.

Figure 4

Microbial Correlation Analysis

Correlation With Intestinal Morphology

Microbial diversity was found between two rearing systems in the duodenum, jejunum, and ileum. To analyze the impact of microbiota on intestinal health, in this study, correlation analysis between microbiota and intestinal morphology of duodenum, jejunum, and ileum was conducted (Figure 5). After correlation analysis, it was reported that Lactobacillus showed a significant positive correlation (P = 0.042), and Peptostreptococcus showed a significant (P = 0.03) negative correlation with VH (Figure 5A). Lactobacillus and Enterococcus showed a significant positive correlation with VH and VR in the jejunum (P = 0.039 and P = 0.004 for VH; P = 0.001 and P = 0.028 for VR) (Figure 5B). However, unidentified Christensenellaceae, Clostridium, Peptostreptococcus, and Butyricicoccus showed a significant negative correlation (P = 0.003, P = 0.037, P = 0.009, P = 0.050, respectively) with VH. In the case of CD, Lactobacillus showed a significant negative correlation (P = 0.005). In the case of ileum, Rothia, Atopobium, Staphylococcus, and Peproniphilus represented a highly significant (P=0.004, P=0.003, P=0.006, P=0.009, respectively) negative correlation, and Actinomyces and Eubacterium represented a significant (P = 0.015 and P = 0.014 respectively) negative correlation with VH (Figure 5C). Moreover, Bacillus was positively (P = 0.035) correlated with CD.Figure 5 Microbial correlation with intestinal morphology, where A, B, C, and D represent duodenum, jejunum, ileum, and cecum intestinal microorganisms correlated with intestinal morphology.

Figure 5

Correlation With Meat Production

A correlation analysis examined the microbial communities associated with meat production. The analysis revealed positive and negative correlations among bacteria (Figure 6). The correlation analysis revealed a significant positive correlation between the presence of Duodenal Aeriscardovia and Enterococcus (P = 0.009 and P = 0.010, respectively) with EGW. On the other hand, duodenal Actinomyces demonstrated a statistically significant inverse correlation with EW and LW (P = 0.028 and 0.024, respectively), while jejunal Actinomyces exhibited a statistically significant (P = 0.050) inverse correlation EGW. Lactobacillus was significantly positively correlated with EW, and LW in the duodenum (P = 0.033, and P = 0.000, respectively), DW, EGW, and LW in the jejunum (P = 0.019, P = 0.005, and P = 0.000, respectively), and EGW, EW, and LW in the ileum (P = 0.006, P = 0.037 and P = 0.004, respectively). Additionally, Unidentified Christensenellaceae, Clostridium, Peptostreptococcus, and Butyrricicoccus, which were present in the jejunum, exhibited a significant negative correlation with DW and EW (P = 0.040, P = 0.002, P = 0.000, P = 0.007, respectively for DW and P = 0.026, P = 0.009, P = 0.004, P = 0.006, respectively for EW).Figure 6 The microbial correlation analyses with meat production were A, B, C, and D, representing duodenum, jejunum, ileum, and cecum intestinal microbial correlation with different meat production. Moreover, DW, EGW, EW, LW, and BW represent dressing weight, eviscerated with giblet weight, eviscerated weight, leg muscle weight, and breast muscle weight, respectively.

Figure 6

DISCUSSION

The manner in which chickens are raised significantly affects their overall well-being, productivity, and the quality, safety, and sustainability of poultry products. The influence of rearing systems on chicken production is multifaceted, involving numerous factors. Previous research has examined the effects of various rearing systems on production metrics, intestinal microbial diversity, intestinal health, and immune function in broiler and layer chickens (Shi et al., 2019; Wiersema et al., 2021; Lei et al., 2022; Song et al., 2022). However, the specific impacts of rearing systems on the production of native chicken breeds like the Danzhou chicken remain unclear. This study aims to elucidate these effects by comparing microbial diversity, intestinal health, and carcass traits between Danzhou chickens raised in cage and free-range systems. Additionally, we explore the correlations between microbial diversity, intestinal health, and meat production to identify key microorganisms that contribute to optimal intestinal health and productivity.

Intestinal health, also known as gut health, refers to the efficient functioning of the intestines within the digestive system. The gut microbiome, a diverse community of intestinal bacteria, contributes to optimal intestinal health, and maintaining a balanced and nutritious diet is crucial for sustaining intestinal well-being (Aziz et al., 2024). There are many biomarkers to determine intestinal health in poultry (Ducatelle et al., 2018); among them, measuring the intestinal wall (Villus height, crypt depth and villus crypt ratios) is widely used (Stefanetti et al., 2023). A well-developed gut morphology, characterized by long villi and shallow crypts, indicates good intestinal health, enhancing nutrient absorption and digestive enzyme activity (Ducatelle et al., 2018). Conversely, shallower crypts suggest reduced cellular turnover and proliferation, indicative of lower inflammation and improved intestinal health (Pan and Yu, 2013; Marchewka et al., 2021).

Our analysis of intestinal morphology data revealed increases in villus height (VH) and villus height-to-crypt depth ratio (VR), along with a decrease in crypt depth (CD) in the cage-reared group. Specifically, VH and VR increased in the duodenum; VH, VR, and CD increased in the jejunum; and VH significantly increased in the ileum of the cage-reared group. Microbial exposure and environmental stress are 2 important factors that regulate intestinal health (Baxter et al., 2018; Nguyen, 2021). In a cage-rearing system, exposure to harmful pathogens and environmental stress is less, which may ensure better intestinal health than the free-rearing group. These findings align with previous studies (Wiersema et al., 2021) and suggest that differences in intestinal morphology impact digestion and nutrient absorption, potentially influencing meat production.

The effects of free and cage-rearing systems on chicken performance are variable. Studies on Xueshan chickens have shown better performance in cage-reared chickens (Wang et al., 2021), while in slow and medium-growing chickens, the rearing system did not influence carcass, breast, thigh, and wing yields (Wang et al., 2009; Li et al., 2017b). Conversely, in meat-type chickens, the free-rearing system performed better than the cage-rearing system (Sun et al., 2023). Our data showed that the cage-rearing group represented significantly higher final body weight, body weight gain, dressing weight, eviscerated with giblets weight, eviscerated weight, and leg muscle weight than the free-rearing group. This may be due to better intestinal health. Good intestinal health ensures better nutrient absorption, feed efficiency, energy utilization, and reduced intensity of diseases, which may ensure consistent growth and meat production (Iqbal et al., 2021; Xu et al., 2021; Feng et al., 2022).

The enteric microbiota undergoes constant changes, influenced by environmental and dietary factors (Paoli et al., 2019). Previous research indicates that different rearing systems affect the intestinal microbial composition of chickens (Li et al., 2022). Our results demonstrated significant differences in β diversity of intestinal microbes between the two rearing systems in different intestinal parts, while α diversity was non-significant. There was a difference in managing mental practice, environmental exposure, physical activity, stress level, and flock density between the two rearing systems, which may have influenced the beta diversity of intestinal microbes. These findings are consistent with previous studies (Shi et al., 2019; Wiersema et al., 2021; Li et al., 2022), which indicate that the microbial composition within each rearing system remained relatively consistent, but there were notable differences in the overall structure or composition of microbial communities between the 2 systems.

Comparing the relative abundance of the top 20 phyla and genera between the two rearing systems, we observed that the rearing system altered the microbial populations of the duodenum, jejunum, and ileum but not the cecum. Higher bacterial diversity was observed in the free-rearing group, consistent with previous studies (Sun et al., 2018). In the cage-rearing system, Firmicutes dominated the duodenum, jejunum, and ileum, while Bacteroidetes, Proteobacteria, and Actinobacteria dominated in the free-rearing system. Free-range chickens got access to a much more diverse environment, including soil and all those fascinating outdoor microorganisms. This may give them a fantastic opportunity to experience a whole range of different bacteria, including Bacteroidetes, Proteobacteria, and Actinobacteria. On the other hand, cage-reared chickens have much more limited exposure to their environment, which may actually favor the growth of Firmicutes. This aligns with earlier findings (Shi et al., 2019; Wang et al., 2021). At the genus level, Lactobacillus and Enterococcus prevailed in the cage-rearing system, while Enterococcus (Eubacterium) and Actinomyces (Actinomyces) were dominant in the free-rearing system. Lactobacillus and Enterococcus are common gut bacteria for chickens (Aruwa et al., 2021), and due to the favorable environment in the cage-rearing system, this type of bacteria may be dominating. On the other hand, due to exposure to a broader range of environmental microbes and interaction among microbes and host Enterococcus (Eubacterium) and Actinomyces (Actinomyces) may be dominant in the free-rearing system. This result is consistent with the previous study (Wiersema et al., 2021), where Lactobacillus dominated the cage-rearing system and Aeriscardovia dominated the free-rearing system.

LEfSe analysis revealed that in duodenum, jejunum and ileum, Lactobacillus, Enterococcus, and Oxalobacteraceae were dominant biomarkers in the cage-reared group, whereas Actinomycetaceae, Erysipelotrichaceae, Coriobacteriaceae, Eubacterium, Actinomyces, Scardovia, and Lachnospiraceae were prevalent in the free-rearing group. Desulfovibrio was the dominant biomarker in the cecum of the free-rearing system, while Bacteroides, Phascolarctobacterium, Faecalibacterium, and Lactobacillus were dominant in the cage-rearing system. The differences in microbial diversity may be due to the free-rearing system exposing chickens to a broader array of microbes.

Microorganisms in the intestine are crucial in nutrient utilization, immune function, growth performance, and maintaining microbial diversity (Chen et al., 2022). Altering microbial diversity influences intestinal health and production (Wang et al., 2023). Our correlation analysis showed that Lactobacillus and Enterococcus were significantly positively correlated with duodenal and jejunal VH development, while other microbes such as unidentified Christensenellaceae, Clostridium, Peptostreptococcus, Butyricicoccus, Actinomyces, and Eubacterium were negatively correlated with VH development. Lactobacillus and Enterococcus also positively correlated with jejunum VR development. This finding is consistent with previous studies showing that Lactobacillus supplementation increases VH and VR in pigs (Zhu et al., 2022). Lactobacillus and Enterococcus are recognized probiotics that are vital for maintaining optimal gut health. They facilitate the maintenance of intestinal integrity and the modulation of the immune response which help to maintain good intestinal health (Wang et al., 2017; Vimon et al., 2023). Moreover, Lactobacillus produce short-chain fatty acids (SCFA) that promote the proliferation and differentiation of epithelial cells, leading to an increase in villus height (VH) (Vimon et al., 2023). On the other hand, Clostridium and Actinomyces are known as pathogen (Glendinning et al., 2019; Liao et al., 2020) may produce metabolites that inhibit the growth of VH and VR.

Good intestinal health is essential for optimal production performance. Our analysis showed that Lactobacillus was significantly positively correlated with EW, and LW in the duodenum, DW, EGW, and LW in the jejunum, and EGW, EW, and LW in the ileum. Additionally, Enterococcus and Aeriscardovia in the duodenum were significantly positively correlated with EGW, suggesting their role in improving growth performance and microbial diversity (Wang et al., 2020; Farooq et al., 2023). Actinomyces in the duodenum and jejunum negatively correlated EW, LW, and EGW. Clostridium, Peptostreptococcus, and Butyrricicoccus, present in the jejunum, negatively correlated with EW and DW, with high significance levels. Moreover, duodenal Peptostreptococcus was significantly negatively associated with LW. The relative abundance of Lactobacillus and Enterococcus in the cage-rearing group was higher, significantly increasing VH and VR in the duodenum and jejunum, leading to better intestinal health than the free-rearing system. Which may lead to better nutrition absorption and higher DW, EGW, EW, and LW compared to free rearing group. In contrast, the free-rearing group had a higher relative abundance of Actinomyces, which can act as a pathogen in the small intestine, causing inflammation and inhibiting the growth of beneficial bacteria (Li et al., 2018). This suggests that the free-rearing system's exposure to a broader microbial diversity may negatively impact chicken production by altering intestinal microbial diversity and health.

CONCLUSIONS

The study investigated the impact of rearing systems on intestinal health and meat production in native Danzhou chickens, along with the correlation between intestinal microbes and these parameters. Cage-rearing significantly enhanced intestinal health indicators such as the jejunum's villus height and height-to-crypt depth ratio. Furthermore, carcass traits metrics were notably improved in the cage-rearing group. Microbial diversity analysis highlighted distinct microbial profiles between the free-range and cage-rearing systems, with Lactobacillus, Enterococcus, and Oxalobacteraceae dominating the cage-rearing group. Correlation analyses identified positive associations between specific microbial taxa and intestinal health or meat production parameters, emphasizing the role of Lactobacillus and Enterococcus. Overall, the findings suggest that the cage-rearing system offers advantages over free-range rearing regarding intestinal health, carcass production, and microbial diversity, with Lactobacillus and Enterococcus potentially contributing to these benefits. These findings provide valuable insights for optimizing rearing systems and gut micro biome management to enhance the productivity and well-being of native chicken breeds. In this research, only female chicken aged 42-50 weeks was used. Sex and age are two important factors that influence microbial diversity. Future research needs to be conducted to explore the microbial diversity in male chickens and birds of different ages. Moreover, this research mainly focuses on the correlation of microbes with the rearing system and carcass traits. Hence, during the experiment, the feed intake of the bird and feed conversion ratio were not calculated, which may have an influence on meat production. It is suspected that due to improving intestinal health and beneficial microbes, the feed conversion ratio may improve in the cage-rearing group. However, further experiments are needed to verify this.

DISCLOSURES

The authors declare no conflicts of interest.

Appendix Supplementary materials

Image, application 1

ACKNOWLEDGMENTS

This work was supported by the earmarked fund for Hainan Agriculture Research System (HNARS), HNARS-06-G02 .

Supplementary material associated with this article can be found in the online version at doi:10.1016/j.psj.2024.104186.
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