Caecal Microbiome and Metabolites Associated With Different Growth Performances of Broilers
Caecal Microbiome and Metabolites Associated With Different Growth Performances of Broilers
Caecal Microbiome and Metabolites Associated With Different Growth Performances of Broilers
ABSTRACT
We investigated changes in the caecal microbial composition and metabolic compounds of broiler chickens weighing approximately
0.8-1.5 kg. Arbor Acres (AA) broilers (n =186) were divided into four groups (A-D) according to body weight on day 35. The results
showed that there were significant differences in the average daily feed intake (ADFI), average daily gain (ADG) and feed-to-gain ratio
(F:G) of chickens (P < 0.05). The abundance of 11 genera were found to be significantly different in the four groups (P < 0.05). The
broilers with poor performance had increased levels of D-mannose, hexadecanoic acid, cholesterol, L-valine, L-leucine, glutamic
acid, glucopyranose, α-D-allopyranose and phosphoric acid (P < 0.05) in the cecum. Microbial compositions were different in the ceca
of broilers with different growth performances and higher growth performance correlated with changes in metabolic pathways related
to energy, amino acids and others.
INTRODUCTION
College of Animal Science and Technology, JLAU-Borui Dairy
Broiler performance has been found to be influenced by a
Science and Technology R and D Centre, Key Laboratory of Animal
range of factors such as breed, sex, diet and growth
Nutrition and Feed Science of Jilin Province, Jilin Agricultural
environment (Korver, et al. 2004; Brake et al. 2003; Ali et al. University, Changchun-130118, P.R.China.
2018; Ghosh et al. 2012). However, even for broilers of the 1
Postdoctoral Scientific Research Workstation, Feed Engineering
same breed, sex and age that are raised in controlled Technology Research Center of Jilin Province, Changchun Borul
environments with the same diet and water, the growth Science and Technology Co., Ltd, Changchun-130118, P.R. China.
performance of individuals is different. Some studies have 2
College of Life Science, Jilin Agricultural University, Changchun-
investigated the effects of the environment (Butler et al. 130118, P.R. China.
2016), age, sex (Lumpkins et al. 2008), supplement addition 3
College of Agriculture and Environmental Science, Dilla University,
(Biswas et al. 2018) and differential feed conversion ration Ethiopia.
(Stanley et al. 2012) on the gut microbiota of chickens. In
Corresponding Author: Yu Guo Zhen, College of Animal Science
poultry, the cecum is the most studied gastrointestinal tract
and Technology, Jilin Agricultural University, No. 2888, Xincheng
because it is an ideal habitat for the microbiome and caecal Street, Nan guan District, Changchun-130118, P.R. China.
microbiota have the ability to digest feeds rich in cellulose, Email: 1179550561@qq.com; nickzhen@263.net
starch and resistant polysaccharides (Clench and Mathias
How to cite this article: Chen, X., Zhao, W., Liu, Y.Z., Aschalew,
1995).
N.D., Sun, Z., Zhang, X.F., Wang, T., Zhen, Y.G. and Qin, G.X.
In this study, we report changes in the cecal microbiome
(2021). Caecal microbiome and metabolites assoc iated with
and metabolites in broilers with different growth
different growth performances of broilers. Indian Journal of Animal
performances using high-throughput sequencing and gas
Research. 55(1): 109-114. DOI: 10.18805/ijar.B-1062.
chromatography mass spectrometry (GC/MS). Our findings
Submitted: 18-11-2018 Accepted: 18-03-2019 Online: 24-05-2019
may be applicable not only to the livestock industry but also
to human health.
MATERIALS AND METHODS 53, 76 and 11 broilers, respectively. Groups A and B had 6
A total of 200 one-day-old Arbor Acres broilers were obtained replicate pens with approximately equal to 8 to 9 broilers
from a local commercial hatchery (Jilin Deda Company, per pen and group C had 6 replicate pens with 12~13 broilers
Changchun, China). The broilers were placed on a plastic per pen and the replicates were placed in cages (1.5 m×1
net (6 m×10 m) and each broiler was weighed with the m×0.75 m). Group D had six replicates with 1 ~2 broilers
stomachs empty on day 35. One hundred eighty-six AA that were placed in small cages (0.3 m×0.3 m×0.75m). The
broilers were selected and divided into four groups according diet and water were offered ad libitum and the broilers were
to body weight, with the chickens of each group differing by fed a standard corn/soybean meal ration without
0.2 kg: group A (1.5~1.7 kg), group B (1.3~1.5 kg), group C antimicrobial additives which met the 1994 National
(1.0~1.3 kg) and group D (0.8~1.0 kg). Each group had 46, Research Council (NRC 1994, Table 1) standards.
During the experimental period from days 35 to 42, feed temperature of injection, quadrupole and ion source were
intake was recorded daily for each pen. On day 42, broilers 280, 230 and 150C, respectively. The mass spectra were
were weighed with the empty stomachs by the pen in the acquired from 20-800 m/z.
morning to detect the ADFI, ADG and F:G. Two broilers per Data of growth performance and cecal microbiota
replicate pen were sacrificed on day 42 and one side of the (at the genus level) were analyzed using the SPSS 17.0
caecum (digesta) was tied using string and stored at -20C and differences between means were assessed using
for DNA extraction and the remaining part was stored at - Duncan’s multiple-range test. The results are presented as
80C until GC/MS analysis. means ± standard deviation. The metabolic profile data were
DNA of the cecum was isolated using the Fast DNA processed by SIMCA 13.0 software and orthogonal partial
Spin Kit for Soil (MP Biotechnology, USA) in accordance least squares-discriminate analysis (OPLS-DA) and
with the manufacturer’s protocol. The DNA samples were principal component analysis (PCA) were employed to
sent to Biomarker Technologies Co, Ltd (China) for PCR process the cecum metabolomic data. Both the variable
amplification and high-throughput sequencing with the importance in the projection (VIP>1) values and Student’s
Illumina Hiseq method. t test (P<0.05) were compared to find the metabolites
The cecal digesta samples were dried by a freeze drier among the groups.
(MIKRO-22R, Germany) for 24 h and 0.05 g of dried samples
were mixed with 100 μl (20 mg/ml) methoxyamine hydrochloride RESULTS AND DISCUSSION
and pyridine and vigorously vortexed and mixed for 30 s in The ADFI of group D was significantly lower than those of
1.5 ml tubes. Then the samples were heated in a water bath groups A, B and C (P < 0.05, Table 2). The ADG of the groups
at 37C for 90 min, followed by 200 µl bis (trimethylsilyl)- A, B, C and D on day 42 increased with increasing weight
trifluoroacetamide (BSTFA) with 1% trimethylchlorosilane on day 35 and there were significant differences among the
(TMCS) being added and heated at 70C for 60 min. The groups (P < 0.05). Compared with group A, the F:G was
tubes were taken out and left to stand for 10 min at room significantly increased by 14.86%, 42.86% and 72.00% in
temperature and subsequently the samples were centrifuged groups B, C and D, respectively. It can be concluded that
at 13,000×g at 4C for 5 min. Then 50 μl of the supernatant the ADFI, ADG and feed conversion ratio were lowest in
of each sample was transferred to a GC vial. group D with the poorest growth performance.
Each sample (1 μl) was injected into an Agilent 7890/ In Table 2, there were big differences in the growth
5975C system equipped with a fused silica capillary column performances of broilers even though they were the same
(30.0 m×0.25 mm i.d.) with a 0.25-μm HP-5MS stationary breed and were fed the same diet under the same conditions.
phase (Agilent, Shanghai, China). Helium was used as the Broilers with high body weight showed higher feed
carrier at a constant flow rate of 1.0 mL/min. The temperature conversion ratios than those with lower body weights. Similar
of the column was maintained at 70C for 4 min, increased results were reported by Stanley et al. (2012), who
to 100C at a rate of 4C/min and maintained for 5 min, demonstrated that the composition or proportion of cecal
increased to 150C at a rate of 10C/min and maintained microbiota and metabolites are different among different
for 10 min, then increased to 240C at a rate of 5C/min growth performance broilers.
and maintained for 8 min and finally increased to 270C at All groups of different weight broilers harbored diverse
a rate of 10C/min and maintained for 5 min. The lineages of bacterial phyla. A total of 10 phyla were detected
Table 2: The difference of growth performance of broilers from day 35 to 42 in different groups.
Item A (1.5k~1.7kg ) B (1.3kg~1.5kg) C (1.0kg~1.3kg) D (0.8kg~1.0kg)
a a a
ADFI/g 154.75±21.31 151.99±15.50 158.56±18.20 126.89±8.38b
a b c
ADG/g 88.03±8.56 75.39±4.50 63.18±4.07 42.16±3.67d
a b c
F:G 1.75±0.09 2.01±0.09 2.50±0.17 3.01±0.44d
in all groups: Bacteroides , Firmicutes, Tenericutes, Bacteroidetes/Firmicutes ratio in the present study, even
Verrucomicrobia, Proteobacteria, Actinobacteria, Syner- though the broilers showed significantly different growth
gistetes, Cyanobacteria and Lentisphaerae (Fig 1). The performances. And there was no significant difference in
predominate phyla were Firmicutes and Bacteroidetes, abundances among groups at the phylum level, while the
followed by Proteobacteria and Tenericutes in groups A, B compositions of Bacteroidetes, Firmicutes, Proteobacteria,
and C. However, Verrucomicrobia was the third most and Actinobacteria at the genus level were altered in different
abundant phylum behind phyla Firmicutes and Bacteroidetes
in group D. The proportions of phyla Bacteroidetes in group
C and Firmicutes in group D were lower than those in other
groups. Only trace amounts of Fusobacteria were detected
in groups C and D.
At the genus level, a total of 89 genera were detected
among the four groups and the abundances of genera in
the top 10 are listed in Fig 2. Sequences that could not be
classified into any known genus were named as unknown.
The predominate genus was Alistipes followed by
Barensiella and Bacteroides. Significant relative abundances
of genera in the four groups of different weight broilers are
listed in Table 3. Genus Parabacteroides in groups B and D
was significantly higher than that in groups A and C. Genus
Coprobacter was higher in groups A and B; however, genus
Barnesiella was the most abundant when compared with
the other groups (P<0.05). The proportions of genera
Streptococcus and Blautia in group A were larger than in
groups B, C and D, respectively (P < 0.05). The abundances
of genera Incertae Sedis and Subdoligranulum in group C Fig 1: Relative abundance of microbial communities at phylum
were the highest and were significantly higher than those in level of broilers.
group A (P < 0.05) and genus Anaerofilum in group C was
higher than in the other groups. Genera Ruminococcus in
group A, Escherichia-Shigella in group D and Streptococcus
in group C were significantly higher than those in group B
(P < 0.05).
Bacteroidetes and Firmicutes were found to be the
predominate phyla among all the tested samples and made
up more than 90% of the cecal microbiota. Bacteroidetes
and Firmicutes are known to utilize complex carbohydrates
and produce short-chain fatty acids, which provide energy
and regulate metabolism (Benítez-Paez et al. 2016; Pieper
et al. 2012). In Fig 1, the abundances of phyla Bacteroidetes
in group C and Firmicutes in group D were the lowest when
compared with other groups. Fusobacteria were detected
in groups C and D and this phylum is widely pathogenic to
other vertebrates (Gupta and Sethy 2014). It is likely that
high concentrations of phyla Bacteroidetes and Firmicutes
in the cecum contributed to increased broiler weight, but
phylum Fusobacteria had the opposite effect. Human study
has shown that the ratio of Bacteroidetes to Firmicutes is
correlated with weight (Ley et al. 2005). However, there was Fig 2: Relative abundance of microbial community at genus level
no significant correlation between weight and the of broilers.
groups. Not all proportions of the same genus changed stands for a sample and the sample C-6 was removed since
consis- tently with increasing or decreasing of weights of it was outside of the 95% confidence interval. Based on the
broilers. PCA results and the OPLS-DA plots of the cecum
Principle component analysis (PCA) score plots of the metabolomic data, there were clear separations between
four groups of cecum samples are shown in Fig 3. Each dot groups A and C, groups A and D, groups B and C, groups B
Fig 3: PCA score plots of different groups and each dot stands for a cecal sample of four groups.
Table 3: Relative abundance of genera level that were significantly affected of the four groups.
phylum genus Group A Group B Group C Group D
a b a
Bacteroidetes Parabacteroides 0.55±0.18 1.39±0.29 0.25±0.14 1.95±0.81b
b b a
Coprobacter 0.94±0.28 1.10±0.40 0.28±0.07 0.92±0.42ab
a ab a
Barnesiella 8.61±3.23 12.50±2.59 7.00±1.84 17.30±2.91b
b a ab
Firmicutes Streptococcus 0.95±0.42 0.07±0.03 0.27±0.10 0.36±0.24ab
c bc a
Blautia 0.67±0.13 0.49±0.10 0.24±0.07 0.31±0.06b
a ab b
Incertae_Sedis 7.31±1.08 9.12±1.73 11.20±1.09 7.63±0.76ab
a a b
Anaerofilum 0.08±0.02 0.09±0.03 0.23±0.06 0.08±0.02a
b a ab
Ruminococcus 1.14±0.35 0.30±0.07 0.40±0.16 0.38±0.10ab
a ab b
Subdoligranulum 0.82±0.29 1.02±0.39 3.54±1.35 0.55±0.17ab
b a ab
Proteobacteria Escherichia-Shigella 0.12±0.05 0.01±0.01 0.12±0.08 0.28±0.15b
ab a b
Actinobacteria Eggerthella 0.19±0.04 0.14±0.03 0.30±0.08 0.16±0.05ab
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