Intestinal Microbiota and Probiotic Characteristics of Two Indigenous Chicken Breeds (Hotan Black Chicken and Baicheng You Chicken) from the Tarim Basin

TL;DR

This study maps the gut bacteria of two desert-adapted chicken breeds and identifies potential probiotics that could help raise healthier poultry in dry regions.

Contribution

The study provides a high-resolution map of gut microbiota and isolates novel probiotic strains from two indigenous chicken breeds in the Tarim Basin.

Findings

Both chicken breeds share the Rikenellaceae RC9 gut group as the dominant microbe in the cecum.

Eight probiotic strains with in vitro attributes were isolated, including Lactobacillus and Enterococcus species.

The study reveals distinct microbial profiles in the duodenum, jejunum, and ileum between the two chicken breeds.

Abstract

We mapped the gut bacteria of two desert-adapted chicken breeds from China’s Tarim Basin—Baicheng You Chicken and Hotan Black Chicken—to hunt for beneficial microbes they naturally carry. After sampling four intestinal sites and culturing bacteria from the cecum, we found that both breeds share the same dominant microbe in this section. From their intestinal contents, we isolated eight promising probiotic strains. Already thriving in an extremely arid climate, these home-grown bacteria could become low-cost, water-saving probiotics for poultry in other dry regions, helping farmers raise healthier flocks with fewer antibiotics and chemicals.

Drawing on two indigenous chicken breeds that have adapted for centuries to the hyper-arid Tarim Basin, namely the Baicheng You Chicken and Hotan Black Chicken, this study provides a high-resolution map of their gut microbiota across the duodenum, jejunum, ileum and cecum and subsequently isolates putative probiotic strains from cecal contents using conventional culture techniques. In the duodenum, Lactobacillus dominated Hotan Black Chicken (43.16%), whereas Ligilactobacillus prevailed in Baicheng You Chicken (37.03%). This segregation persisted in the jejunum, with Lactobacillus accounting for 62.55% of Hotan Black Chicken reads and Ligilactobacillus accounting for 60.76% reads in Baicheng You Chicken. The ileal core of Hotan Black Chicken remained Lactobacillus (50.63%), while Baicheng You Chicken shifted to Enterococcus (32.37%). In the cecum, both breeds converged on the Rikenellaceae RC9 gut group as the single dominant lineage (Hotan Black Chicken, 46.87%; Baicheng You Chicken, 46.23%). At the genus level, Hotan Black Chicken was enriched in Lactobacillus and Ligilactobacillus, whereas Baicheng You Chicken harbored a greater proportion of Enterococcus. Concurrently, eight strains with in vitro probiotic attributes were isolated, four from each breed, identified as Ligilactobacillus salivarius, Limosilactobacillus reuteri, Lactobacillus gallinarum, Enterococcus lactis, Enterococcus faecium, Enterococcus faecalis, and Bacillus velezensis. This study deciphers the intestinal microbiome of two native Tarim Basin chicken breeds, Hotan Black Chicken and Baicheng You Chicken, and mines them for autochthonous probiotic strains. The obtained dataset has established a foundational resource for poultry-related probiotics adapted to extremely arid environments, providing theoretical insights and practical value for poultry nutritionists in water-scarce regions in the future.

Figures

Full text

1. Introduction

Inhabiting the gastrointestinal tracts of animals, intestinal lactic acid bacteria (LAB) constitute a complex microbial guild that is instrumental in maintaining gut homeostasis, profoundly influencing host health, nutrient assimilation, and overall well-being [1,2], while also modulating meat quality [3]. Of particular note, Weissella halotolerans with potential probiotic properties has been isolated from the feces of camels inhabiting arid environments, while Enterococcus italicus has been recovered from their milk [4,5]. This implies that specific microbial taxa play a pivotal role in host adaptation to drought conditions.

For poultry, this microbial ecosystem dictates feed conversion efficiency, immune competence, and disease resistance [6]. The spatially distinct physiology of the avian intestine offers a natural model for mapping the biogeography of gut microbes [7]. The duodenum mixes chyme with bile and digestive enzymes [8], and the jejunum and ileum propel digesta forward via peristalsis while intermittently delivering it retrogradely to the cecum; these pairs function as dedicated fermentation chambers whose development and motility are directly modulated by dietary fiber [9]. Notably, the cecal microbiota exhibits the highest diversity [10]. Consequently, profiling the microbiome along each intestinal segment is necessary.

Among the diverse microbial profiling technologies, 16S rRNA amplicon sequencing has emerged as the gold standard for high-resolution dissection of gut microbiota [11]. Previous investigations have been confined largely to single intestinal segments [12,13,14,15]. Conversely, several studies have systematically profiled microbial communities across multiple gut segments, providing a holistic view of spatial variation along the entire intestinal tract [16,17,18,19]. Nevertheless, most surveys have relied on short amplicons spanning the V1, V3, or V4 regions of the 16S rRNA gene [20,21,22,23]. Full-length 16S rRNA sequencing remains comparatively scarce, yet it delivers markedly higher taxonomic resolution at the genus and species levels [24]. Beyond merely cataloging microbial diversity, functional characterization of gut microbiota has garnered increasing attention, particularly regarding the isolation and screening of probiotic strains. Lactobacilli spp. are routinely isolated on de Man, Rogosa, and Sharpe (MRS) agar via serial dilution and spread-plating [25], whereas Bacillus spp. are typically cultured on Luria–Bertani (LB) medium [26]. Candidate probiotics must subsequently be evaluated for safety, functionality and practicality—encompassing hemolytic potential, tolerance to simulated gastric acid and bile salts, storage stability and scalability for industrial production.

Extreme habitats are crucibles for uniquely adapted microbial life. Recent work confirms that geography exerts a decisive influence on the cecal microbiota of chickens [27]. Although commercial breeds have been exhaustively studied, indigenous chickens worldwide remain invaluable reservoirs of genetic diversity and cultural heritage. The Tarim Basin, characterized by vast diurnal temperature swings and chronic aridity [28], has shaped two emblematic poultry populations: the Baicheng You Chicken and Hotan Black Chicken. These landraces are integral to local agriculture and serve as unparalleled models for investigating avian adaptation and evolution under extreme environmental pressures.

The Baicheng You chicken is a strong flier and has been extensively studied [29,30,31,32,33]. Its muscle and skin contain high total lipid levels. A continuous subcutaneous fat layer is deposited evenly across the body wall [34,35], and the intramuscular fat content is also elevated [36]. The name “You” therefore equates to “Oil”. This trait is interpreted as an adaptation to local aridity, conserving both energy and water. The Hotan Black chicken, also named the Niya Black chicken, was already widespread during the ancient Jingjue kingdom. No cross-breeding has since been recorded, so the line remains genetically intact [37,38]. The breed exhibits high stress tolerance and disease resistance, retaining a desert-specific green-ecotype profile. Its intramuscular fat content is likewise high [21].

This study profiles the gut microbiota of Baicheng You Chicken and Hotan Black Chicken along the entire intestinal tract using high-throughput sequencing, then selectively isolates lactic acid bacteria and Bacillus from the cecum for comprehensive probiotic characterization. The resulting data illuminates the microbial biogeography of poultry adapted to an extreme arid environment and enables the construction of a three-dimensional, geo-referenced map of the Baicheng You Chicken and Hotan Black Chicken gut microbiomes. Moreover, the newly acquired probiotic candidates provide a scientific basis for the conservation and sustainable exploitation of these two distinctive indigenous breeds.

2. Materials and Methods

2.1. Chickens and Sample Collection

Sampling was conducted in April 2024 on the margin of the Tarim Basin (Figure 1). Eighteen healthy, 1-year-old laying hens—nine Hotan Black Chickens and nine Baicheng You Chickens—were selected at random from a commercial flock (body weight 2.0 ± 0.5 kg). Chickens were reared under identical layer cage conditions with ad libitum access to feed and water. After a 12 h feed withdrawal period, hens were euthanized by cervical dislocation followed by exsanguination. The thoraco-abdominal cavity was opened aseptically, and the entire gastrointestinal tract was removed and placed in a sterile tray. The duodenum, jejunum, ileum and cecum were dissected and clamped. Luminal contents (0.5 g) were collected from a 1 cm section of each segment (same anatomical position), pooled, snap-frozen in liquid nitrogen, and stored at −80 °C.

2.2. Amplicon Sequencing of the 16S rRNA Gene for Intestinal Microbiota Analysis

For each breed, three biological replicates were established by randomly pooling intestinal contents from three chickens per replicate, resulting in one composite sample per segment. Total DNA was extracted using the QIAamp DNA Stool Mini Kit (Qiagen, Valencia, CA, USA) following the manufacturer’s instructions. Briefly, frozen aliquots were thawed, transferred to lysis buffer, and homogenized prior to bead-beating lysis. DNA was purified on QIAamp Mini spin columns to remove inhibitors and checked for concentration/purity with a NanoDrop 2000 spectrophotometer (Thermo Fisher, Waltham, MA, USA) and for integrity on 0.8% agarose gels.

Full-length 16S rRNA genes were amplified with primers 27F (5′-AGAGTTTGATCMTGGCTCAG-3′) and 1492R (5′-TACGGYTACCTTGTTACGACTT-3′). Triplicates of 20 µL of PCR were run in an ABI GeneAmp 9700 thermocycler using 2 × Pro Taq HS Premix (10 µL), 5 µM of forward and reverse primers, and 10 ng of template DNA. Cycling conditions were: 95 °C for 3 min; 30 cycles of 95 °C for 30 s, 60 °C for 30 s, and 72 °C for 45 s; and final extension at 72 °C for 10 min. Amplicons were visualized on 2% agarose gels, excised, and purified with the QIAquick Gel Extraction Kit (Qiagen). Purified amplicons were sent to Shanghai Majorbio Bio-Pharm Technology Co. for single-molecule real-time (SMRT) sequencing on a PacBio RS II platform (Pacific Biosciences, Menlo Park, CA, USA). Raw reads were processed through SMRT Link Analysis software 11.0: adapter sequences were trimmed, and reads < 1400 bp or Q-score < 0.8 were discarded to generate high-quality CCS (circular-consensus) sequences for downstream analysis.

Operational taxonomic units (OTUs) were clustered at a 97% sequence-identity threshold. Sequences with <10 copies in any single biological replicate were discarded, and the resulting OTU table was further filtered to remove low-abundance OTUs representing < 0.1% of the total reads per sample. The most frequent sequence within each OTU was selected as the representative and classified against SILVA 138.1 (https://www.arb-silva.de/, accessed on 4 July 2024). Statistical analyses were performed in R v3.3.1. Differences in genus-level abundance, microbial diversity, and predicted metabolic pathways were evaluated with the Wilcoxon rank-sum test; significance was declared at p < 0.05.

2.3. Isolation, Purification and Identification of Intestinal Probiotics

Two grams of cecal content from each Hotan Black Chicken and Baicheng You Chicken were serially diluted to 10^−4^ and 10^−5^; 100 µL aliquots were spread on MRS agar for LAB and on LB agar for Bacillus spp. Plates were inverted and incubated at 37 °C for 3 d. Single colonies were picked and re-streaked ≥ 3 times to ensure purity. Genomic DNA was extracted by the CTAB method. The 16S rRNA was amplified with primers 27F and 1492R in a 25 µL reaction containing 0.2 µL of EasyTaq, 2 µL of EasyTaq buffer, 1.5 µL of dNTPs, 1 µL of each primer, 50 ng of DNA, and 25 µL of ddH_2_O. Cycling was as follows: 94 °C for 5 min; 30 cycles of 94 °C for 30 s, 54 °C for 30 s, and 72 °C for 90 s; final extension at 72 °C for 10 min; and holding at 4 °C. Amplicons were checked by 1% (w/v) agarose gel electrophoresis, and positive products were bidirectionally sequenced by Sangon Biotech (Shanghai, China). Sequences were queried against the EzBioCloud database (https://www.ezbiocloud.net/, accessed on 8 August 2024) to infer taxonomic identity.

2.4. In Vitro Assessment of Probiotic Traits of Intestinal Isolates

Isolates were subjected to acid, bile salt, and simulated gastrointestinal tolerance assays. MRS broth was prepared at pH 2.0 and 3.0 for acid challenge or supplemented with 0.2% and 0.3% (w/v) ox bile for bile salt challenge. Artificial gastric juice (pH 2.0, 3 g/L pepsin) and intestinal fluid (pH 8.0, 1 g/L pancreatin, 0.3% bile) were also prepared for sequential GI exposure. Each isolate was inoculated at 2% (v/v) into the acid or bile-supplemented MRS broths and incubated at 37 °C for 24 h. For sequential GI challenge, cells were first exposed to artificial gastric juice for 2 h and then transferred to artificial intestinal fluid for 4 h. At set time points, appropriately diluted cultures were plated on MRS (or LB) agar and incubated at 37 °C for 24–48 h, and survival (%) was calculated as (Nt/N_0_) × 100.

The strains were subjected to antimicrobial susceptibility and hemolysis tests. The Kirby–Bauer disk diffusion method was used to determine the zone diameters of inhibition against antibiotics including penicillin, ampicillin, gentamicin, ceftriaxone, tetracycline, erythromycin, ciprofloxacin, clindamycin, trimethoprim-sulfamethoxazole, and chloramphenicol. After 1 day of incubation, the diameters of the inhibition zones were measured, and the tests were repeated three times. A 2 μL volume of bacterial suspension was spotted onto Columbia blood agar plates. After 1 day of incubation, the presence or absence of hemolysis zones around the colonies on the plates was recorded, with three biological replicates [26].

Detection of cellulase production by intestinal bacteria. The isolated bacteria were activated and the OD_600_ nm was adjusted to 0.60. A 2 μL volume of the bacterial suspension was spotted onto CMC-Na medium, with three biological replicates. After 1 day of incubation, the medium was stained with Congo red solution, and the presence or absence of a clear zone on the medium was used to determine whether the strains produced cellulase.

Detection of amylase production by intestinal bacteria. A 2 μL volume of the bacterial suspension was spotted onto MRS medium containing 1% soluble starch, with three biological replicates. The medium was stained with iodine-potassium iodide solution, and the presence or absence of a clear zone on the medium was used to determine whether the strains produced amylase.

Detection of BSH activity in intestinal bacteria [39]. The strains were cultured in MRS medium containing glycine/taurine deoxycholate for 8 h. The samples were freeze-dried synchronously with methanol standards containing glycine cholate, taurocholate, and cholic acid. The samples were dissolved in methanol and spotted onto a GF254 silica gel plate. The plate was developed with isoamyl acetate–propionic acid–n-propanol–water (4:3:2:1), baked at 110 °C for 3 min, and then sprayed with 10% phosphomolybdic acid–ethanol solution and baked for another 5 min. The presence of cholic acid spots indicated BSH activity.

3. Results

3.1. Gut Microbiota Distribution and Composition

In this study, we conducted a detailed analysis of the gut microbiota distribution in Hotan Black Chicken and Baicheng You Chicken (Figure S1). At the phylum level, the most abundant microbes in the intestines of both types of chickens were Firmicutes, Bacteroidota, and Proteobacteria. Notably, the abundance of Proteobacteria in the intestines of Hotan Black Chicken was significantly lower than that in Baicheng You Chicken (p < 0.05). Further analysis at the genus level revealed that the more abundant microbes in the intestines of Hotan Black Chicken were Lactobacillus (39.74%), Rikenellaceae RC9 gut group (12.91%), and Ligilactobacillus (12.30%). In contrast, the more abundant microbes in the intestines of Baicheng You Chicken were Ligilactobacillus (30.68%), the Rikenellaceae RC9 gut group (15.79%), and Enterococcus (9.43%). The abundance of Lactobacillus (p < 0.01) and Ligilactobacillus (p < 0.05) in the intestines of Hotan Black Chicken was significantly higher than that in Baicheng You Chicken, while Enterococcus (p < 0.05) was significantly lower. Additionally, there were significant differences in the microbial composition across different intestinal segments of the two types of chickens. Table 1 shows the most abundant microbes in different intestinal segments of Hotan Black Chicken and Baicheng You Chicken. These results provide an important basis for further studying the interactions between gut microbiota and the host.

3.2. Analysis of Diversity and Differences in Gut Microbiota Distribution

The α-diversity analysis based on full-length sequencing of the 16S rRNA gene revealed significant differences in the complexity of microbial communities across different intestinal segments of different chicken breeds (Tables S1 and S2). Using Welch’s T-test with Benjamini–Hochberg correction and two-tailed testing, it was found that in the intestines of Hotan Black Chicken, the cecum microbial community had significantly higher Sobs index (96.667 ± 1.1547 vs. 76.000 ± 3.6056), coverage index (1.000 ± 0.00007 vs. 0.998 ± 0.0005), and Shannon index (3.284 ± 0.4577 vs. 1.804 ± 0.4732) values than the ileum, and higher coverage index (1.000 ± 0.00007 vs. 0.999 ± 0.0003) and Shannon index (3.284 ± 0.4577 vs. 1.616 ± 0.6778) values than the jejunum. The coverage index of the duodenal microbial community (0.999 ± 0.0006 vs. 0.998 ± 0.0005) was significantly higher than that of the ileum (p < 0.05). When comparing the different chicken breeds (Figure 2A), it was found that the coverage index of the cecum microbiota in Baicheng You Chicken (0.9993 ± 0.00004 vs. 1.000 ± 0.00007) was significantly lower than that in Hotan Black Chicken, while the Chao1 index of the cecum microbiota (103.980 ± 0.8874 vs. 100.640 ± 0.8512) and the coverage index of the ileum microbiota (0.999 ± 0.0005 vs. 0.998 ± 0.0004) were significantly higher in Baicheng You Chicken than in Hotan Black Chicken (p < 0.05).

Principal component analysis (PCA) revealed a significant separation in the overall structure of the gut microbiota between the two types of chickens (permutational multivariate analysis of variance, R^2^ = 0.210, p = 0.003). Specifically, cecum and ileum samples showed significant differences along the principal component 1 (PC1) axis (explaining variances of 40.74% and 43.42%, respectively), while jejunum samples exhibited breed differences along the principal component 2 (PC2) axis (explaining a variance of 28.07%) (p < 0.05). Principal coordinate analysis (PCoA) further confirmed this trend, with a significant separation in the overall structure of the gut microbiota between the two types of chickens (permutational multivariate analysis of variance, R^2^ = 0.232, p = 0.008). In the jejunum, ileum, and cecum, the PC1 axis (Bray–Curtis distance, explaining variances of 73.71%, 51.86%, and 56.25%, respectively) showed significant differences between groups, and the duodenum PC2 (32.13%) also exhibited significant differences (p < 0.05) (Figure 2B). These results indicate that the spatial heterogeneity of gut microbial community structure is significantly associated with the host genetic background.

Differences in small intestine microbiota distribution. At the genus level (Figure 3A), significant differences in microbial species and abundance were observed in the small intestines of Baicheng You Chicken and Hotan Black Chicken. In Baicheng You Chicken, the abundance of Pelomonas in the duodenum and Escherichia-Shigella, Acinetobacter, and Fournierella in the jejunum were significantly higher than in Hotan Black Chicken (p < 0.05). In contrast, the abundance of Romboutsia in the ileum of Baicheng You Chicken was significantly lower than that in Hotan Black Chicken (p < 0.05).

At the species level (Figure 3B), significant differences were also observed. In Baicheng You Chicken, the abundance of Pelomonas in the duodenum and Escherichia coli g Escherichia Shigella, Acinetobacter guillouiae CIP 63.46, Acinetobacter johnsonii XBBI, and Fournierella massiliensis in the jejunum were significantly higher than in Hotan Black Chicken (p < 0.05). In contrast, the abundance of uncultured Peptostreptococcaceae bacterium g Romboutsia in the jejunum of Baicheng You Chicken was significantly lower than that in Hotan Black Chicken (p < 0.05).

Cecum microbiota distribution differences. At the genus level (Figure 3A), the abundance of Bacteroides and Parabacteroides in Baicheng You Chicken was significantly lower than that in Hotan Black Chicken, while the abundance of Escherichia-Shigella, Enterococcus, Pelomonas, and Pseudomonas was significantly higher in Baicheng You Chicken than in Hotan Black Chicken (p < 0.05). At the species level (Figure 3B), significant differences were observed in the cecum of Baicheng You Chicken and Hotan Black Chicken. In Baicheng You Chicken, the abundance of the Rikenellaceae RC9 gut group, E. coli g Escherichia-Shigella, Bacteroides sp. Marseille-P3166, Enterococcus cecorum, Lactobacillus ingluviei, Pelomonas, and Pseudomonas was significantly higher than in Hotan Black Chicken. In contrast, the abundance of Bacteroides baresiae, Bacteroides, and Parabacteroides in Baicheng You Chicken was significantly lower than that in Hotan Black Chicken (p < 0.05).

3.3. Functional Prediction by Tax4Fun

Cecal microbial metabolic pathway prediction. In this study, functional prediction analysis of the microbiota revealed marked differences in metabolic pathways between the cecum of Hotan Black Chicken (HC) and the cecum of Baicheng You Chicken (BC). Specifically, the HC group exhibited significantly higher relative abundances of fatty acid biosynthesis (0.55 vs. 0.47%, p = 0.03463), sphingolipid metabolism (1.23 ± 0.01% vs. 0.83 ± 0.01%, p = 0.03011), glycerolipid metabolism (0.41 ± 0.03% vs. 0.33 ± 0.02%, p = 0.04319), starch and sucrose metabolism, and glycosphingolipid biosynthesis-globo and isoglobo series (0.05 ± 0.005% vs. 0.02 ± 0.003%, p = 0.03011; 1.88 ± 0.10% vs. 1.43 ± 0.08%, p = 0.03011). Conversely, the BC group showed significantly greater representation in lipopolysaccharide biosynthesis (0.36 ± 0.04% vs. 0.16 ± 0.04%, p = 0.03011), fatty acid degradation (0.39 ± 0.02% vs. 0.30 ± 0.03%, p = 0.04514), α-linolenic acid metabolism (0.05 ± 0.004% vs. 0.03 ± 0.001%, p = 0.03463), Ubiquinone and other terpenoid quinone biosynthesis (0.27 ± 0.03% vs. 0.15 ± 0.03%, p = 0.03427), and pentose and glucuronate interconversions (0.43 ± 0.02% vs. 0.28 ± 0.04%, p = 0.03063). These results indicate that the HC and BC groups may adapt to distinct metabolic demands through functional divergence of the gut microbiota, particularly in pathways related to lipid synthesis versus degradation (Figure 4A).

Jejunal microbial metabolic pathway prediction. Further analyses revealed that the jejunum of the Hotan Black Chicken (HJ) group displayed significantly higher relative abundances than the jejunum of the Baicheng You Chicken (BJ) group across most metabolic pathways, including galactose metabolism (0.87 ± 0.05% vs. 0.56 ± 0.05%, p = 0.01125), prokaryotic carbon fixation pathways (1.01 ± 0.09% vs. 0.68 ± 0.07%, p = 0.02621), starch and sucrose metabolism (1.66 ± 0.02% vs. 1.09 ± 0.04%, p = 0.04157), glycerophospholipid metabolism (0.65 ± 0.05% vs. 0.46 ± 0.02%, p = 0.04535), glycerolipid metabolism (0.61 ± 0.19% vs. 0.37 ± 0.15%, p = 0.01468), and the folate-mediated one-carbon pool (0.47 ± 0.04% vs. 0.27 ± 0.01%, p = 0.02868). In contrast, the BJ group showed significantly greater representation in butyrate metabolism (0.81 ± 0.06% vs. 0.56 ± 0.02%, p = 0.02826); valine, leucine and isoleucine degradation (0.65 ± 0.016% vs. 0.38 ± 0.002%, p = 0.009349); 2-oxocarboxylic acid metabolism (0.43 ± 0.04% vs. 0.21 ± 0.03%, p = 0.01577); fatty acid degradation (0.56 ± 0.01% vs. 0.22 ± 0.04%, p = 0.0122); and β-alanine metabolism (0.34 ± 0.04% vs. 0.04 ± 0.02%, p = 0.009349). These differences likely reflect distinct adaptive strategies of the gut microbiota between the HJ and BJ groups, suggesting that they may play divergent roles in host metabolism (Figure 4B).

3.4. Isolation and Identification of Probiotics in the Gut

Using the dilution spread plate method, Enterococcus lactis TRM58087 (Genbank: PV383792), Ligilactobacillus salivarius TRM58234 (PV383916), Enterococcus faecium TRM58261 (PV383940), and Bacillus velezensis TRM89184 (PX138893) were isolated from the cecum of Hotan Black Chicken. Limosilactobacillus reuteri TRM59703 (PX149929), Enterococcus faecalis TRM59713 (PX149939), L. salivarius TRM59715 (PX149941), and Lactobacillus gallinarum TRM59728 (PX149954) were isolated from the cecum of Baicheng You Chicken.

3.5. In Vitro Evaluation of Probiotic Characteristics of Gut Probiotics

The strains obtained in Section 2.4 were subjected to acid and bile salt tolerance experiments. It was found that all strains could grow under pH levels of 2.0 and 3.0, as well as bile salt concentrations of 0.2% and 0.3%. They were also able to survive in gastric and intestinal juices (Table 2). Additionally, their sensitivity to antibiotics is shown in Table 3, where B. velezensis TRM89184 was found to be more sensitive to most antibiotics. Moreover, none of the strains exhibited hemolytic zones, indicating their safety.

Furthermore, the ability of the bacteria from Section 2.4 to produce cellulase was screened. B. velezensis TRM89184 was found to have a relatively distinct transparent zone, with a measured hydrolysis zone diameter (D)-to-colony diameter (d) ratio of 1.75. The ability to produce amylase was also screened, and E. lactis TRM58087, E. faecium TRM58261, and E. faecalis TRM59713 were identified as having this capability. The hydrolysis zone diameter (D)-to-colony diameter (d) ratios were measured as 2, 1.85, 2.53 and 1.25, respectively. Additionally, the ability to produce bile salt hydrolase was tested, and L. salivarius TRM58234 and L. gallinarum TRM59728 were found to hydrolyze conjugated bile salts, such as sodium taurocholate and sodium cholate, into cholic acid, indicating significant bile salt hydrolase activity.

4. Discussion

Studies have shown that different climates and altitudes can cause significant differences in the cecum microbiota of chickens [40], and there are significant differences in the relative abundance of fecal microbial genera among people in different geographical environments [41]. However, some studies have found that geographical location has no significant impact on the gut microbiota composition of chickens [42]. In high-altitude areas, the predominant genera in the gut microbiota of Tibetan chickens are Bacteroides and the RC9 gut group, and differences in gut microbiota composition between Tibetan chickens and LM/DH chickens are related to geographical conditions [43]. In the Jianghan Plain, there are significant differences in the cecal microbial composition of the same Jianghan chicken breed between Jingzhou, which is on flat terrain, and three other areas with different geographical features [44]. However, there are few studies on the gut microbiota of chickens living on the edge of deserts. The Tarim Basin contains the Taklamakan Desert, the largest desert in China, characterized by extreme environmental features such as aridity, high temperatures, and scarce rainfall [28]. Hotan Black Chicken and Baicheng You Chicken have been living in this desert–oasis transition zone for generations. Their gut microbiota has changed in the process of co-adapting to extreme environmental stress with the host.

The diversity index of the cecal microbiota in Hotan Black Chicken was significantly higher than that in the duodenum and jejunum, while the Chao1 richness index of the cecal microbiota in Baicheng You Chicken was significantly higher than that in the ileum. This indicates that there are significant differences in the microbial composition of the small intestine and cecum, abd the microbial diversity in the cecal region is at a high level in both types of chickens, further supporting the key role of the cecum in microbial metabolism [45]. This may imply that, despite inhabiting the extreme environment of the Tarim Basin, the chicken breeds in this study maintain a conserved, segment-specific distribution of gut microbial diversity characteristic of the species.

In terms of the geographical distribution and spatial characteristics of gut microbiota, the most abundant phyla are Firmicutes, Bacteroidota, and Proteobacteria, which is similar to previous studies [46]. The genus Lactobacillus is the dominant group in the duodenum and jejunum of both types of chickens, consistent with previous findings [17]. Lactobacillus exhibits strong adhesion to the intestinal wall and can also inhibit the proliferation of pathogenic bacteria [47]. However, the ileum of Baicheng You Chicken is dominated by the genus Enterococcus, which differs from earlier studies [48]. Prior investigations have revealed a positive correlation between the abundance of Enterococcus sp. and elevated BSH activity in broilers; this genus can potentiate fat emulsification and absorption [49], a metabolic process that may underpin the enhanced fat deposition in Baicheng You Chickens.

In contrast, the cecal microbiota showed a distinct environmental adaptation signature. Both chicken breeds were dominated by the Rikenellaceae RC9 gut group (>46%), and this microbial group was positively correlated with the genes involved in the absorption and metabolism of short-chain fatty acids (SCFAs) [50]. Conventional isolation methods further yielded indigenous strains with complementary functional characteristics, such as B. velezensis, E. lactis, E. faecalis, and L. reuteri. This is in contrast to the reported literature [51]. B. velezensis produces cellulase [52], Enterococcus sp. produces amylase [53], and L. salivarius is acid-tolerant and capable of generating BSH [54], which provides evidence that the cecal microbiota can utilize carbohydrates (cellulose and starch). Additionally, the probiotic potential of these strains has been verified in other studies [55,56,57,58,59]. The probiotic properties of these strains may work in conjunction with the RC9 gut group to exert a positive effect on the host’s adaptation to arid environments.

This stands in contrast to the cecal microbiota of broilers reared in Fuzhou (a southern Chinese city), where the class Clostridia is the dominant taxon [60]. Furthermore, this finding is inconsistent with previous reports, whereby Methanobrevibacter and Mucispirillum schaedleri in the cecum were positively correlated with fat deposition in broilers [61]. The cecal microbiota of chickens in the Tarim Basin are more unique, and they may help the host adapt to these environmental stresses through its metabolic functions [62]. The gut microbiota of chickens in the Tarim Basin differ from those in other environments. Under conditions of drought or high temperature, the host may require a more efficient energy utilization mechanism, which may imply that the special geographical environment of the Tarim Basin harbors unique gut microbiota.

The differences in metabolic pathways between the cecum and jejunum reveal distinct mechanisms of microbial tolerance to environmental stress. Hotan Black Chickens exhibit enrichment in fatty acid biosynthesis and sphingolipid metabolism, which may enhance energy reserves and strengthen intestinal barrier integrity [63], thereby resisting heat stress-induced intestinal permeability. Baicheng You Chickens demonstrate advantages in fatty acid degradation and butyrate metabolism, potentially supporting rapid ATP generation and anti-inflammatory signaling to cope with heat and nutritional stress [64]. These distinct strategies demonstrate that intestinal microbiota contribute to host adaptation to arid and extreme temperature environments through complementary mechanisms of metabolic specialization.

For a long time, people have tried to associate certain genera of gut microbiota with host phenotypes, especially in broilers [65]; for example, gut microbiota may regulate meat quality [66]. Meanwhile, studies have shown that fat deposition in chickens is more easily regulated by gut microbiota and has less association with host genetic factors [61]. Additionally, cecal microbiota are the main contributors to intramuscular fat in broilers [67]. The Rikenellaceae RC9 gut group may be associated with the host’s lipid metabolism [68]. Baicheng You Chicken shares the same characteristics with Beijing oil chicken [69], and compared with Hotan Black Chicken, Baicheng You Chicken has more fat accumulation [35]. This study found that the α-diversity of the ileum and cecum in Baicheng You Chicken was significantly higher than that in Hotan Black Chicken, which is similar to previous studies: compared with low-fat animals, high-fat animals have more diverse and abundant gut microbiota [70,71]. Compared with Baicheng You Chicken, the abundance of potential pathogens Escherichia-Shigella and Enterococcus in the gut of Hotan Black Chicken is lower, which is similar to previous studies showing that lean broilers exhibit a reduction in intestinal potential pathogens [72].

The Tarim Basin, as a region with significant geographical and climatic differences from other areas, is home to a rich variety of local chicken breeds. Therefore, conducting research on more local chicken breeds within the Tarim Basin is of great significance. This study has several limitations: the effects of rearing regimes and other environmental variables on the gut microbiotas of the two chicken lines were unaddressed, and the causal relationships between these microbiota features and host adaptation to extreme environments await validation through gnotobiotic animal models or fecal microbiota transplantation. The mechanistic basis of host–microbiota crosstalk awaits in-depth dissection via transcriptomic and metabolomic profiling.

5. Conclusions

Multi-site profiling (duodenum, jejunum, ileum, and cecum) revealed distinct gut microbiota structures between Baicheng You Chicken and Hotan Black Chicken. A three-dimensional map of breed-specific indicator taxa was constructed and functionally annotated. The cecum consistently showed the highest microbial diversity. Autochthonous strains isolated from the cecum exhibited in vitro probiotic traits. This dataset provides a baseline for future studies on both desert-adapted breeds.