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Microbial Diversity and Community Dynamics in the Intestines of Broiler Chicken Raised in an Open-Sided House

Written By

Waleed Al-Marzooqi

Submitted: October 29th, 2021 Reviewed: February 21st, 2022 Published: March 31st, 2022

DOI: 10.5772/intechopen.103815

IntechOpen
Animal Husbandry Edited by Sándor Kukovics

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Animal Husbandry [Working Title]

Prof. Sándor Kukovics

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Abstract

The intestinal microbiota of the chicken plays a central role in enhancing nutrient absorption and affecting both host performance, health and immunity. This study was conducted to assess the relative abundance of bacteria microflora in different segments of the gastrointestinal tract (duodenum, jejunum, ileum, and cecum) of broiler chicken raised in an open-sided house. One hundred fifty-one-day-old chicks of Cobb 500 broiler chickens were raised in an open-sided house fed a standard non-medicated corn-soybean meal diet from day 0–35 days of age. The study showed a distinctive difference in the bacterial community between each region of intestinal segments and the diversity of the bacterial community changed as the chicken aged. In addition, Lactobacillales were the dominant 16S rDNA sequences in the duodenum, jejunum, and ileum libraries, whereas Clostridiales were the dominant 16S rDNA sequences in the cecum libraries. The bacterial microbiota relative abundance differed significantly (p < 0.05) across different intestinal segments. In conclusion, each region developed its own bacterial community and the relative abundances of the bacterial community were quite different. Based on the composition of the microbial community, future gut modulation with beneficial bacteria, such as probiotics, may benefit the host.

Keywords

  • broiler chicken
  • 16S rDNA
  • intestine
  • gut microbiota
  • open-sided house

1. Introduction

Many studies have used sequencing technologies to characterize the microbial communities that colonies the gastrointestinal tracts of chickens and to characterize the development of these communities over time [1]. It is well known that the chicken gut microbiota influences the host gut development, growth performance, and overall health [2, 3]. Different factors, such as diet and bird age, have a strong influence on the diversity and composition of the intestinal microbiome in chickens, which has grown in complexity and richness as chickens have grown [3, 4]. Each region of the gastrointestinal tract (GIT) develops its own distinct bacterial community, and the structure of the microflora gets more complicated and varies as chickens age, position in the digestive system, feed, breed, and environment change [5, 6, 7, 8].

Several studies have shown the beneficial effect of gut microbiota on the physiological, metabolic, immunological, digestion, and nutrient absorption of the host [6]. Evaluation of the bacterial community and intestinal development of different genetic lines of chickens has become a recent point of interest [9]. A greater understanding of the chicken gut function and microbiology will provide a new opportunity for the improvement of broiler chicken health and production raised in an open-sided house.

The use of molecular approaches, which involve examining the structure of bacterial communities by detecting the distinguishing features of microbial DNA isolated from community samples, has solved the problems associated with microbe culture [10, 11]. Using these methods, researchers discovered that 90% of the bacteria in the chicken GIT belong to previously undiscovered species [12]. Furthermore, metagenomics (a nonculture-based technique) was established, allowing researchers to examine microbial communities in various habitats in-depth [13]. Metagenomic analysis has provided important information on microbial community alterations and succession [13].

Understanding the taxonomic composition of the bacterial community of the gastrointestinal tract, diversity and succession will permit detecting disruption in the microbiota. This information is crucial, as it may allow for the manipulation of intestinal flora to improve intestinal health and overall bird performance. The objective of this study was to use 16S rDNA-based analysis to analyze the relative abundance, diversity, and changes with age in the microbial community detected in different sections of the gut of broiler chickens.

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2. Materials and methods

All experimental work was carried out at the Agricultural Experiment Station’s Poultry Research Unit in compliance with the experimental unit’s animal welfare policy and the requirements of procedures involving animals/birds and their care. The Animal Research Ethics Board at Sultan Qaboos University approved the research project.

2.1 Birds management and diet

One-day-old chicks (Cobb 500) were obtained from a commercial hatchery and screened upon arrival to ensure that no abnormalities or symptoms of the disease were present. Throughout the experiment, standard operating procedures for broiler house management [14] were followed. Before the experiment, the Open-sided house unit, cages, feeders, and drinks were fumigated to clean and disinfect them. In addition, strong cleanliness and biosecurity measures were implemented. The open-sided house was constructed from a galvanized iron shed with profiled steel shed roofing that was naturally ventilated. On all sides, chicken mesh panels and a one-meter-high block work protection were installed. It included four sets of electric wall fans to help circulate the air. Shade cloths were used to screen direct sun rays during midday (Figure 1). Six birds were randomly assigned to each of 15 suspended wire cages (62 × 62 × 37 cm) such that all cages had nearly a similar average initial weight. Feed was available ad libitum and the composition of the experimental diet is presented in Table 1. The house temperature was maintained at 33°C on day 1 and reduced by 3°C each week to reach a constant 22°C. The lighting program was 23 L—1D. There were 15 replicates with each replicate cage containing six birds (a total of 90 birds). Birds per replicate combinations were randomly allocated.

Figure 1.

Photograph of an open-sided poultry house used in the current experiment.

Ingredients (%)Amount
Corn56.18
Soybean meal (48%)37.4
Vegetable Oil3
Monocalcium Phosphate1.751
Limestone0.853
Salt0.290
Vitamin and Mineral Premix10.325
DL-Methionine0.201
Total100
Calculated Analysis
ME (kcal/kg)3095
Crude Protein (%)
Available phosphorus (%)
22.5
0.45
Lysine (%)1.15
Calcium (%)0.9
Methionine (g)0.53

Table 1.

Composition of the conventional diet used in the experiment.

1 kg of premix used contains a blend of Vitamin and Mineral all balanced according to the breed recommendation.


2.2 Sample collection

One bird per cage was chosen at random at the ages of 5, 15, 25, and 35 days. The birds were chosen, marked, and maintained in their cages until they were euthanized, based on the weight of their bodies. Each cage’s birds with the closest body weight to the average were chosen, labeled, and euthanized accordingly. Then birds were injected intramuscularly with a xylazine-ketamine combination containing 5 mg xylazine (Ilium Xylazil-20-Xylazine 20 mg/mL, as hydrochloride) and 25 mg ketamine (Ketamine Injection-Ketamine 100 mg/mL as hydrochloride) to put the birds into a deep plan of sedation and anesthesia. Both xylazine–ketamine were supplied by Troy Laboratories Pty Limited, Glendenning, Australia. The bird was euthanized via cervical dislocation once it was totally immobilized. Then, at the bottom of the breastbone, an incision was made and a huge V shape was carved toward the head. The abdominal cavity was opened at the apex of the V form, taking care not to burst the intestine below. The small intestine was carefully pushed out of the abdominal cavity till the ileal-caecal-colonic junction was observed once a large enough opening had been formed. The duodenum (from the gizzard to the bile and pancreatic ducts), jejunum (from the ducts to the yolk stalk), ileum (from the yolk stalk to the ileocecal junction), and caecum (two horns) were distinguished, separated, and cleaned with 70% alcohol wipes.

The mid portions of the duodenum, jejunum, ileum, and ceca were cut into 4 cm long sections (including digesta). After each bird, the dissecting instruments were cleaned with 70% ethanol. The entire procedure of collecting intestinal contents took less than 30 minutes and was completed on a thoroughly cleaned workbench.

The contents of the four segments of the intestine were collected and placed in a sterile 15-mL conical tube with labels. The samples were immediately placed on ice and transferred to the laboratory, where they were kept in an 80°C freezer until they were analyzed. The analysis of all samples began 2 weeks after the trial ended on day 35. All of the samples were taken under identical conditions.

2.3 DNA extraction

Total DNA was extracted from the contents of each intestinal segment (duodenum, jejunum, ileum, and cecum) according to the manufacturer’s instructions using a QIAamp DNA Stool Mini Kit (QIAGEN, CA, Hamburg, Germany). The optical density of the 16 DNA samples was measured using a Nano-Drop 2000 (Thermo Electron Corporation, Waltham, MA, USA) at wavelengths of 260 and 280 nm to assess their integrity. Using 1.0% agarose gel electrophoresis (including ethidium bromide), the integrity of the DNA extracts was visually evaluated.

2.4 Polymerase chain reaction amplicon production and high-throughput sequencing

The variable regions V3-V4 of the 16S rDNA gene were amplified and sequenced. For the PCRs, 5 mM of each primer, 10 ng of DNA template, 4 liters of 1 FastPfu buffer, 2.5 mM dNTPs, and 0.4 liters of FastPfu polymerase in triplicate in a total volume of 20 liters were used (TransGen Biotech, Beijing, China). The PCR conditions were as follows: Denaturation at 95°C for 2 minutes, then 25 cycles of 30 seconds denaturation at 94°C, 30 seconds annealing at 55°C, and 30 seconds extension at 72°C, followed by a final extension at 72°C for 5 minutes. Amplicons produced from different intestinal luminal content samples were sent to a commercial company (BGI Genomic Lab, Tai Po Industrial Zone, New Territories, Hong Kong, China) for sequencing on the Illumina MiSequencing platform.

2.5 Sequencing analysis

To get operational sequences, all of the raw sequences obtained from Illumina Miseq were first filtered for quality control. The sequences were checked for quality and analyzed using the software Quantitative Insights into Microbial Ecology (QIIME, v1.8.0) [15]. FLASH [16] was used to combine the paired-end readings from the DNA fragments. Read trimming and identification of V3-V4 sequences were performed on the sequencing data, and a group of sequences with 97% identity was identified as an operational taxonomic unit (OTU). To cluster operational taxonomic units, the UCLUST [17] clustering approach was applied. At a cutoff of 97%, the determined OTUs were allocated to different taxonomic levels (phylum, class, genus, and families). Furthermore, the Shannon and Simpson diversity indices, abundance-based coverage estimators (ACE), Chao 1 richness, and coverage percentage were all calculated by Good’s method. Also, clustered OTUs were used to construct the rarefaction curves.

2.6 Data analyses and bioinformatics

The QIIME and R packages were used for bioinformatics and statistical studies (v3.1.1). To determine the relative abundance and diversity of the sequences, the alpha-diversity indices (ACE, Chaol, Shannon, and Simpson index) were calculated. To examine whether taxonomic categories were significantly different across groups of samples based on intestine segments and age period, Metastats and R package (v3.1.1) [18] were used. At p 0.05, the differences were considered significant. A Benjamini–Hochberg false discovery rate correction (Function “p. adjust” in the stats package of R (v3.1.1)) was used to alter the obtained p-value.

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3. Results

The diversity of bacterial populations detected in distinct intestinal segments was highlighted by data acquired by molecular detection and bioinformatics analysis. The 16S rDNA study produced a large amount of data that is beyond the scope of this article. As a result, the current study’s findings have been confined to the most quantitatively significant Classes/Orders of bacteria.

3.1 Sequencing overview

A total of 128 samples were obtained from a combination of four intestinal segments—(duodenum, jejunum, ileum, and caecum) and four age periods—(day 5, day 15, day 25, and day 35) with n = 8 per group and subsequently sequenced to generate V3-V4 of the 16S rDNA gene profiles A total of 1179,68 sequences were obtained with the number of sequences ranging from 58,498 to 112,785 and clustered into 14 to 133 OTUs for each sample, resulting in a total of 253 OTUs for all samples at the 97% sequence similarity value. The microbial complexity and microbial community composition and abundance of water are summarized in their respective sections below.

3.1.1 The microbial complexity

The alpha-diversity indices were used to evaluate the microbial complexity in the duodenum, jejunum, ileum, and cecum (ACE index, Chao1 index, Simpson index, and Shannon index) Table 2 The Chao1 was used to quantify species diversity, while Simpson’s and Shannon’s indexes were used to evaluate species richness. When comparing the means of the indices, there was a substantial difference across intestinal regions throughout age periods.

ACEChao1SimpsonShannon
Intestinal SegmentMeanSTDMeanSTDMeanSTDMeanSTD
Duodenum133.2014.12111.3621.420.3190.1831.951.03
Jejunum69.9229.5764.2828.400.3770.1621.550.535
Ileum74.4442.8570.1638.140.6140.3421.091.09
Cecum137.1435.00137.8434.110.2580.1482.250.605
P-value0.02520.05270.22850.1377

Table 2.

The average alpha-diversity indices (ACE, Chao1, Simpson, and Shannon indices) of the data distribution.

The differences were considered to be significant at P < 0.05. These results emanate from our own experiment.

3.2 Microbial composition of the duodenum

Bacteria classified according to their respective Class and Order, found in the duodenum of broiler chickens at different ages, are presented in Table 3. Sixteen bacterial microbiota at the Order level were found in the duodenum. Of the 30,173 reads, Lactobacillales were the most abundant Order, from the Class Bacilli, at 78.73% of the total number of sequences. Clostridiales, a representative Order from the Class Clostridia, was the second most common Order accounting for 17.32% of the total number of sequences. At the Class level, Actinobacteria, and Chloroplast accounted for 0.93% and 1.15%, of the total number of sequences, respectively, at the Class level. Lactobacillales were the most dominant group across all age groups, accounting for 93.37% at day 5, 98.80% at day 15, and 89.77% at day 25 to 5.77% at day 35 of the sequences. Clostridiales were the second most abundant, sequences fluctuated from 1.78% at day 5, 0.06% at day 15, 4.61% at day25, and 88.71% at day 35. Comparatively, Coriobacteriales, (member from Class Coriobacteriia), Bacteroidales, (Class, Bacteroidia), Bacillales, (member from Class Bacilli), Erysipelotrichales (Class, Erysipelotrichi), Rhizobiales (Class, Alphaproteobacteria), Rhodocyclales (Class, Betaproteobacteria), Enterobacteriales (Class, Gammaproteobacteria), and RF39 (member from Class Mollicutes) group-related sequences were detected at smaller percentages through all age periods.

Abundance of sequence (no. of sequence [%]) at day:
ClassOrderDay5Day15Day25Day35
ActinobacteriaActinomycetales191 (2.32)43 (0.53)46 (0.53)0 (0.00)
Bifidobacteriales0 (0.00)0 (0.00)0 (0.00)0 (0.00)
CoriobacteriiaCoriobacteriales3 (0.04)0 (0.00)0 (0.00)15 (0.28)
BacteroidiaBacteroidales0 (0.00)0 (0.00)0 (0.00)8 (0.15)
4C0d-2YS20 (0.00)0 (0.00)2 (0.02)175 (3.32)
ChloroplastStreptophyta20 (0.24)34 (0.42)293 (3.38)0 (0.00)
BacilliBacillales98 (1.19)5 (0.06)14 (0.16)3 (0.06)
Lactobacillales7679 (93.37)8000 (98.80)7771 (89.77)304 (5.77)
ClostridiaClostridiales146 (1.78)5 (0.06)399 (4.61)4675 (88.71)
ErysipelotrichiErysipelotrichales2 (0.02)0 (0.00)0 (0.00)42 (0.80)
AlphaproteobacteriaCaulobacterales11 (0.13)1 (0.01)3 (0.03)0 (0.00)
Rhizobiales21 (0.26)3 (0.04)11 (0.13)0 (0.00)
BetaproteobacteriaRhodocyclales5 (0.06)0 (0.00)2 (0.02)0 (0.00)
EpsilonproteobacteriaCampylobacterales11 (0.13)3 (0.04)84 (0.97)0 (0.00)
GammaproteobacteriaEnterobacteriales1 (0.01)0 (0.00)5 (0.06)0 (0.00)
MollicutesRF390 (0.00)0 (0.00)0 (0.00)32 (0.61)
UnclassifiedUnclassified0 (0.01)0 (0.00)0 (0.00)6 (0.11)
Others (<0.5%)Others (<0.5%)1 (0.43)0 (0.04)0 (0.31)0 (0.19)
Total8189809486305260

Table 3.

The abundance of bacterial 16S rDNA sequences (n = 30,173) identified from the duodenummicroflora of cobb 500 broiler chicken.

These results emanate from our own experiment.

3.3 Microbial composition of the jejunum

Bacteria classified according to their respective Class and Order, found in the jejunum of broiler chickens at different ages, are presented in Table 4. Sixteen bacterial microbiota at the Order level were found in the jejunum. Of the 28,646 reads, Lactobacillales were the most abundant Order, from the Class Bacilli, at 75.95% of the total sequences. Clostridiales, a representative Order from the Class Clostridia, was the most second Order accounted for 11.21% of the total sequences. At the Class level, only a few 4.46% Actinobacteria-related sequences were detected; these were related to Actinomycetales and Bifidobacteriales. Chloroplast, Erysipelotrichi, and Gammaproteobacteria at the Class level represented a small percentage of 2.32%, 1.55%, and 4.06%, respectively, of the total sequences. Across different age periods, Lactobacillales were the most dominant group, representing 93.09% at day 5, 86.01% at day15, 91.45% at day 25 to 23.46% at day 35 of the sequences. Clostridiales were the second most abundant, sequences fluctuated from 4.33% at day 5, 4.02% at day 15, 0.86% at day 25, and 40.07% at day 35. Relatively, Bifidobacteriales, (Class, Actinobacteria), Streptophyta (Class, Chloroplast), Bacillales (Class, Bacilli), Erysipelotrichales (Class, Erysipelotrichia), Rhizobiales (member from Class, Alphaproteobacteria), Rhodocylales (Class, Betaproteobacteria) and Enterobacteriales (member from Class, Gammaproteobacteria) group-related sequences were detected at lower levels across age periods.

Abundance of sequence (no. of sequence [%]) at day:
ClassOrderDay5Day15Day25Day35
ActinobacteriaActinomycetales23 (0.27)154 (2.33)8 (0.11)0 (0.00)
Bifidobacteriales4 (0.05)0 (0.00)0 (0.00)1090 (17.44)
CoriobacteriiaCoriobacteriales0 (0.00)0 (0.00)0 (0.00)0 (0.00)
BacteroidiaBacteroidales0 (0.00)0 (0.00)0 (0.00)0 (0.00)
4C0d-2YS20 (0.00)0 (0.00)0 (0.00)0 (0.00)
ChloroplastStreptophyta64 (0.75)427 (6.45)175 (2.39)0 (0.00)
BacilliBacillales14 (0.17)23 (0.35)2 (0.03)9 (9.99)
Lactobacillales7892 (93.09)5695 (86.01)6703 (91.45)1466 (23.46)
ClostridiaClostridiales367 (4.33)278 (4.20)63 (0.86)2504 (40.07)
ErysipelotrichiErysipelotrichales13 (0.15)0 (0.00)1 (0.01)429 (6.87)
AlphaproteobacteriaCaulobacterales4 (0.05)4 (0.06)2 (0.03)0 (0.00)
Rhizobiales29 (0.34)17 (0.26)12 (0.16)0 (0.00)
BetaproteobacteriaRhodocyclales6 (0.07)2 (0.03)0 (0.00)0 (0.00)
EpsilonproteobacteriaCampylobacterales0 (0.00)0 (0.00)0 (0.00)0 (0.00)
GammaproteobacteriaEnterobacteriales51 (0.60)1 (0.02)361 (4.92)751 (12.02)
MollicutesRF390 (0.00)0 (0.00)0 (0.00)0 (0.00)
UnclassifiedUnclassified0 (0.01)0 (0.02)0 (0.00)0 (0.00)
Others (<0.5%)Others (<0.5%)1 (0.12)1 (0.29)0 (0.04)0 (0.00)
Total8468660273276249

Table 4.

The abundance of bacterial 16S rDNA sequences (n = 28,646) identified from the jejunummicroflora of cobb 500 broiler chicken.

These results emanate from our own experiment.

3.4 Microbial composition of the ileum

Bacteria classified according to their respective Class and Order, found in the ileum of broiler chickens at different ages, are presented in Table 5. Sixteen bacterial microbiota at the Order level were found in the ileum. Of the 30,961 reads, Lactobacillales were the most abundant Order, from the Class Bacilli, at 51.36% of the total sequences. Clostridiales, a representative Order from the class Clostridia, was the most second Order accounted for 18.35% of the total sequences. At the Class level, only a few 0.90% Actinobacteria-related sequences were detected; these were related to Actinomycetales and Bifidobacteriales. At the Class level, Coriobacteriia, Bacteroidia, and Erysipelotrichi represented small percentages of 0.32%, 0.14%, and 0.44%, respectively, of the total sequences. Across different age periods, Lactobacillales were the most dominant group, representing 98.69% at day 5, 90.59% at day 15, 99.63% at day 25 to 0.05% at day 35 of the sequences. Clostridiales were the second most abundant, sequences fluctuated from 0.14% at day 5, 0.57% at day 15, 0.11% at day 25, and 95.17% at day 35. Relatively, Actinomycetales (Class, Actinobacteria), Coribacteriales, (member from Class Coriobacteria), Bacteroidales, (Class, Bacteroidia), Streptophyta (Class, Chloroplast), Bacillales (Class, Bacilli), Erysipelotrichales (Class, Erysipelotrichi) group-related sequences were detected at smaller percentages across all age periods.

Abundance of sequence (no. of sequence [%]) at day:
ClassOrderDay5Day15Day25Day35
ActinobacteriaActinomycetales54 (0.63)217 (2.40)1 (0.01)0 (0.00)
Bifidobacteriales2 (0.02)3 (0.03)0 (0.00)0 (0.00)
CoriobacteriiaCoriobacteriales0 (0.00)0 (0.00)0 (0.00)87 (1.46)
BacteroidiaBacteroidales2 (0.02)3 (0.03)0 (0.00)40 (0.67)
4C0d-2YS20 (0.00)0 (0.00)0 (0.00)7 (0.12)
ChloroplastStreptophyta7 (0.08)466 (5.16)17 (0.23)0 (0.00)
BacilliBacillales26 (0.30)48 (0.53)1 (0.01)0 (0.00)
Lactobacillales8432 (98.69)8174 (90.59)7466 (99.63)3 (0.05)
ClostridiaClostridiales12 (0.14)51 (0.57)8 (0.11)5659 (95.17)
ErysipelotrichiErysipelotrichales0 (0.00)1 (0.01)0 (0.00)137 (2.30)
AlphaproteobacteriaCaulobacterales1 (0.01)5 (0.06)0 (0.00)0 (0.00)
Rhizobiales2 (0.02)13 (0.14)0 (0.00)0 (0.00)
BetaproteobacteriaRhodocyclales1 (0.01)0 (0.00)0 (0.00)0 (0.00)
EpsilonproteobacteriaCampylobacterales0 (0.00)0 (0.00)0 (0.00)0 (0.00)
GammaproteobacteriaEnterobacteriales0 (0.00)0 (0.00)0 (0.00)2 (0.03)
MollicutesRF390 (0.00)0 (0.00)0 (0.00)11 (0.18)
UnclassifiedUnclassified0 (0.00)0 (0.02)0 (0.00)0 (0.00)
Others (<0.5%)Others (<0.5%)0 (0.06)2 (0.44)0 (0.01)0 (0.00)
Total8539898374935946

Table 5.

The abundance of bacterial 16S rDNA sequences (n = 30,961) identified from the ileummicroflora of cobb 500 broiler chicken.

These results emanate from our own experiment.

3.5 Microbial composition of the cecum

Bacteria classified according to their respective Class and Order, found in the Cecum of broiler chickens at different ages, are presented in Table 6. Sixteen bacterial microbiota at the Order level were found in the cecum. Of the 27,842 reads, Clostridiales, were the most abundant Order, a representative Order from the Class Clostridia, at 62.81% of the total sequences. Lactobacillales, which was the most second Order from the Class Bacilli, accounted for 12.75% of the total sequences. At the Class level, only a few 6.1% Actinobacteria-related sequences were detected; these were related to Actinomycetales and Bifidobacteriales. At the Class level, Bacteroidia and Alphaproteobacteria represented small percentages of 7.47% and 0.79%, respectively, of the total sequences. Across different age periods, Clostridiales were the most dominant group, representing 62.55% at day 5, 38% at day 15, 72.55% at day 25 to 71.87% at day 35 of the sequences, Lactobacillales were the second most abundant, sequences fluctuated from 25.99% at day 5, 16.49% at day 15, 13.05% at day 25 and 0.13% at day 35. Smaller percentage of sequences for Bacteroidales, (Class, Bacteroidia), were observed day 5: 0.56%, day 15: 0.51%, day 25: 0.03% and day 35: 24.57%. Relatively, Coriobacteriales (member from Class Coriobacteriia), Bacillales (member from Class Bacilli), Erysipelotrichales (member from Class, Erysipelotrichi), Rhizobiales (member from Class, Alphaproteobacteria), and Rhodocyclales (Class, Betaproteobacteria) group-related sequences were detected at lower levels across age periods.

Abundance of sequence (no. of sequence [%]) at day:
ClassOrderDay5Day15Day25Day35
ActinobacteriaActinomycetales53 (0.93)1505 (21.89)92 (1.30)0 (0.00)
Bifidobacteriales4 (0.07)30 (0.44)1 (0.01)0 (0.0)
CoriobacteriiaCoriobacteriales21 (0.37)25 (0.36)0 (0.00)114 (1.39)
BacteroidiaBacteroidales32 (0.56)35 (0.51)2 (0.03)2010 (24.57)
4C0d-2YS213 (0.23)9 (0.13)0 (0.00)27 (0.33)
ChloroplastStreptophyta92 (1.62)1101 (16.01)855 (12.06)0 (0.00)
BacilliBacillales33 (0.58)224 (3.26)22 (0.31)131 (1.61)
Lactobacillales1480 (25.99)1134 (16.49)925 (13.05)11 (0.13)
ClostridiaClostridiales3851 (62.55)2613 (38.00)5144 (72.55)5880 (71.87)
ErysipelotrichiErysipelotrichales24 (0.42)24 (0.35)2 (0.03)6 (0.07)
AlphaproteobacteriaCaulobacterales14 (0.25)45 (0.65)2 (0.03)0 (0.0)
Rhizobiales31 (0.54)86 (1.25)40 (0.56)0 (0.00)
BetaproteobacteriaRhodocyclales38 (0.67)42 (0.610)4 (0.06)0 (0.00)
EpsilonproteobacteriaCampylobacterales0 (0.00)0 (0.00)0 (0.00)0 (0.0()
GammaproteobacteriaEnterobacteriales8 (0.14)3 (0.04)1 (0.01)0 (0.00)
MollicutesRF391 (0.02)0 (0.00)0 (0.00)1 (0.01)
UnclassifiedUnclassified0 (0.00)0 (0.00)0 (0.00)0 (0.00)
Others (<0.5%)Others (<0.5%)0 (0.78)0 (1.31)0 (0.53)0 (0.00)
Total5695687670908181

Table 6.

The abundance of bacterial 16S rDNA sequences (n = 27,842) identified from the cecummicroflora of cobb 500 broiler chicken.

These results emanate from our own experiment.

3.6 Differences of microbial communities among samples from different intestinal segments of broiler chickens

Table 7 shows the p value distribution of 16S rDNA gene sequence libraries used to compare relative abundance differences of microbial communities between samples from different intestinal regions of broiler chickens. The composition of the bacterial microbiota in the duodenum-jejunum, duodenum-ileum, cecum-duodenum, cecum-ileum, and cecum-jejunum differed considerably (p0.05) in statistical comparisons of the libraries, implying that each region established its own bacterial community. The relative abundance of Actinomycetales at different intestinal segment differed significantly (p<0.05). In the duodenum, jejunum, and ileum libraries, Lactobacillales were the most common 16S rDNA sequences, while Clostridiales were the most common 16S rDNA sequences in the cecum libraries.

3.6.1 Differences of microbial communities among samples of different age groups

Table 8 presents the p value distribution of 16S rDNA gene sequence libraries used to compare quantitative differences in microbial communities between samples from broiler chickens of various age groups. Statistical analyses of the libraries revealed that the microbial composition at different age groups—day 5-day 15, day 5-day 25, day 5-day 35, day 15-day 25, day 15-day 35, and day 25-day 35 had no significant changes (p > 0.05).

P- Value
OrderDuodenum-JejunumDuodenum-IleumIleum-JejunumCaecum-DuodenumCaecum-IleumCaecum-Jejunum
Actinomycetales0.3400.3630.0110.0990.0930.030
Bifidobacteriales0.5330.0150.4970.2520.4950.485
Coriobacteriales0.9170.2550.0380.4060.0320.013
Bacteroidales0.8880.3920.3350.3150.3520.275
YS20.7820.5670.2160.7390.2040.214
Streptophyta0.0310.0920.0170.8160.0140.024
Bacillales0.6060.0510.9400.1000.8630.578
Lactobacillales0.5450.9260.0000.8080.0010.000
Clostridiales0.7810.8130.0010.9340.0000.001
Erysipelotrichales0.7150.1030.0700.6170.0430.040
Caulobacterales0.6320.0480.0090.2060.1220.002
Rhizobiales0.6450.8100.0020.7940.0470.019
Rhodocyclales0.3950.1880.1210.4060.4070.058
Campylobacterales0.5740.6010.3710.5470.2630.318
Enterobacteriales0.3250.5910.5720.3870.4460.804
RF391.0001.0000.1110.0560.104
Unclassified0.6800.5000.6350.1210.8210.318

Table 7.

P-value distribution of 16S rDNA gene sequence libraries compared the abundance differences of microbial communities among samples from the different segments for cobb 500 broiler chicken.

These results emanate from our own experiment.

P- Value
OrderDay5-Day15Day5-Day25Day5-Day35Day15-Day25Day15-Day35Day25-Day35
Actinomycetales0.8690.9080.9040.4580.4810.476
Bifidobacteriales0.3140.0690.2970.2250.5030.326
Coriobacteriales0.2180.6010.3060.1870.1440.714
Bacteroidales0.3320.5210.2510.3780.3190.373
YS20.2970.4580.3060.6430.0240.096
Streptophyta0.6520.8590.7150.1330.2800.185
Bacillales0.7180.7680.8300.1360.0380.064
Lactobacillales0.9340.9460.9370.4840.2870.513
Clostridiales0.8070.9500.7680.8570.3180.873
Erysipelotrichales0.5760.7270.6300.9610.5510.626
Caulobacterales0.8300.5260.5650.3260.2470.222
Rhizobiales0.5630.4840.0480.0890.2030.033
Rhodocyclales0.8920.2600.3060.0810.3870.049
Campylobacterales0.1760.2500.198
Enterobacteriales0.0850.7560.0880.5590.1230.239
RF390.3320.6770.3060.4600.2440.532
Unclassified0.5960.4871.0000.3000.5000.501

Table 8.

P-value distribution of 16S rDNA gene sequence libraries compared the abundance differences of microbial communities among samples at different age period for cobb 500 broiler chicken.

These results emanate from our own experiment.

3.7 The taxonomic composition distribution of the bacterial Community in Intestinal Segments at the order-level

The diversity of the bacterial population in the intestinal segments of broiler chickens shifted from one age period to the next, as shown in Figure 2. Species with an abundance of less than 0.5% across all samples were labeled “Unclassified.” The duodenum, jejunum, and ileum had a larger abundance of Lactobacillales, and the percentage of Lactobacillales declined as the birds aged, but the cecum had a higher abundance and the percentage of Clostridiales increased as the birds aged.

Figure 2.

Percentage of relative abundance of the bacterial community of cobb 500 broiler chicken determined from different intestinal segments at different age periods from 16S rDNA libraries. These results emanate from our own experiment.

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4. Discussion

The luminal content samples obtained from the duodenum, jejunum, ileum, and cecum of broiler chicks at four-time points from day 5 to day 35 of age were compared in this study. Understanding how the microbiota evolves over time at specific places in the small intestine could lead to a better understanding of the chicken gut’s microbial succession and dynamics. In this study, the dynamic of microbiota in the duodenum, jejunum, ileum, and cecum of broiler chickens raised in an open-sided house and supplied with a commercial diet was examined through 16S rDNA gene sequencing. The most significant finding in this work is that statistical comparisons of the compositions of distinct 16S rDNA libraries of microbial communities indicated that each region from separate intestine segments generated its own bacterial community, with very diverse relative abundances.

Our data showed that Lactobacillales were the dominant Order of bacteria in the duodenum, jejunum, and ileum through all age periods. In contrast, Clostridiales were the most abundant Order detected in the cecum at different ages. Our results agree with the previous studies [19, 20] who reported that nearly 70% of sequences from ileum were related to those of lactobacillus, whereas Clostridiaceae related sequences 65% were the most abundant group detected in the cecum. An interesting observation is that we found changes in community composition, diversity, and richness across all intestinal segments over time. More specifically, we observed an increase in the richness of microbial communities in all gut sections and a general increase in diversity.

However, the microbial community structure was moderately transient at an early age (day 5) and was replaced by a rather stable bacterial community during the period of rapid growth, according to our findings (15–35 days of age). Other research [7, 11, 19, 20] showed similar findings, indicating that different regions of the chicken gut harbor different microorganisms and that the microbial community structure varies with age.

The microbiome is known to be affected by developmental changes in the chicken GIT as the distinct segments of the GIT become differentiated [21]. The current study discovered that the microbial composition and abundance in the four intestinal segments vary, implying that diverse intestinal microbial compositions may influence intestinal function. The alpha-diversity indices (ACE index, Chao1 index, Simpson index, and Shannon index) revealed considerable differences in microbial abundance between different intestinal portions. Gut functional variations could be caused or exacerbated by changes in microbial makeup between the four intestinal segments/locations [9, 22, 23].

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5. Conclusion

Our study shows that each region of different intestinal segments developed its own bacterial community and the relative abundance was quite diverse. Further work should be directed to look in toward histological alterations related to intestinal function.

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Acknowledgments

This study was financially supported by the Sultan Qaboos University Research Fund [number: IG/AGR/ANVS/19/01].

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Written By

Waleed Al-Marzooqi

Submitted: October 29th, 2021 Reviewed: February 21st, 2022 Published: March 31st, 2022