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Peer-reviewed

Research Commodity

Different antibiotic growth promoters induce specific changes in the cecal microbiota membership of broiler chicken

  • Marcio C. Costa,
  • Jose A. Bessegatto,
  • Amauri A. Alfieri,
  • J. Scott Weese,
  • JoĂŁo A. B. Filho,
  • Alexandre Oba

PLOS

x

  • Published: February 21, 2017
  • https://doi.org/10.1371/journal.pone.0171642

Abstract

Antimicrobials are sometimes given to food animals at low doses in order to promote faster growth. Withal, the mechanisms by which those drugs improve performance are not fully understood. This report aimed to investigate the affect of zinc bacitracin (55g/ton), enramycin (10g/ton); halquinol® (30g/ton); virginiamycin (16,5g/ton) and avilamycin (10g/ton) on the cecal microbiota of broiler chicken, compared to a control group. Six hundred and twenty four chicks (Cobb 500) arriving to an experimental unit were randomly assigned into each treatment with four repetitions per treatment. The cecal content of 16 animals per treatment (northward = 96) was used for DNA extraction and sequencing of the V4 region of the 16S rRNA gene using Illumina technology. The use of antimicrobials induced significant changes in membership merely not in structure of the cecal microbiota compared to the control group, suggesting a greater affect on the less abundant species of leaner present in that environment. Halquinol was the only drug that did not affect microbial membership. Firmicutes comprised the major bacterial phylum nowadays in the cecum of all groups. There was no statistical difference in relative abundances of the main phyla betwixt treated animals and the command grouping (all P>0.05). Handling with enramycin was associated with decreased richness and with lower relative abundance of unclassified Firmicutes, Clostridium XI, unclassified Peptostreptococcaceae (all P<0.001) and greater abundance of Clostridium XIVb (P = 0.004) and Anaerosporobacter spp. (P = 0.015), and treatment with bacitracin with greater relative abundance of Bilophila spp. (P = 0.004). Several bacterial genera were identified as representative of usage of each drug. This study used loftier throughput sequencing to characterize the impact of several antimicrobials in broiler chicken under controlled atmospheric condition and add new insights to the current knowledge on how AGPs affect the cecal microbiota of chicken.

Citation: Costa MC, Bessegatto JA, Alfieri AA, Weese JS, Filho JAB, Oba A (2017) Different antibiotic growth promoters induce specific changes in the cecal microbiota membership of broiler chicken. PLoS ONE 12(2): e0171642. https://doi.org/10.1371/journal.pone.0171642

Editor: Richard Due east. Isaacson, Academy of Minnesota, U.s.

Received: September 5, 2016; Accepted: Jan 24, 2017; Published: February 21, 2017

Copyright: © 2022 Costa et al. This is an open access article distributed under the terms of the Artistic Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: Data were made publicly bachelor at the NCBI Sequence Read Archive under accession number SUB1906187.

Funding: This work was funded by Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES), Brasil. The funders had no role in report design, information collection and analysis, conclusion to publish, or grooming of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Antibiotic growth promoters (AGPs) accept been widely used to amend functioning of food animals. Antimicrobials are given to broiler craven in society to command diseases such every bit necrotic enteritis acquired by Clostridium perfringens, and also to promote faster growth and ameliorate conversion rates [one–3]. The effects of those drugs are not fully understood, but the potential of the intestinal microbiota in increasing feed efficiency has been shown [iv–vii].

This practice has recently raised concerns regarding emergence of antibiotic resistant strains of bacteria that could potentially spread to humans [8]. Indeed, AGPs usage has been banned in the European Marriage and there is increasing pressure level for stricter regulations in North America [9].

The abdominal microbiota has been shown to accept a tremendous influence on host health and disturbances in its residuum (dysbiosis) have been associated with diverse diseases [10]. While several factors, such equally diet, surroundings and genetics can induce changes in the intestinal microbiota, the use of antimicrobials is one of the virtually important [xi]. The different spectrum of pick depending on the agile ingredients present in each compound should induce anticipated changes on the intestinal microbiota [12]. However, the in lodge to adequately address those changes, controlled ecology conditions should be used for the characterizations of changes induced by those drugs.

Changes in the cecal environment are of importance since cecal bacteria are responsible for nutrient fermentation and short concatenation fatty acids (SCFA) production in chickens [13–15]. Therefore, a amend label of how AGPs impact the cecal microbiota of chickens could exist the keystone for the evolution of alternative methods to improve growth efficacy in this species [16].

The effects of AGPs on the chicken microbiota have recently been investigated [3,17,18]. However, since several factors can touch the intestinal microbiota, comparing between studies is difficult and in order to fairly compare the consequence of different drugs molecules, it is essential to secure that experimental atmospheric condition are rigorously controlled. To date, most studies using high throughput sequencing have compared a limited number of drugs, with special emphasis given to virginiamycin and bacitracin [3,xix–21].

This study was designed to test the hypothesis that unlike antimicrobial drugs would differentially affect the cecal microbiota of broiler chicken.

Materials and methods

Report pattern

This study was approved by the University of Londrina'due south Animal Intendance and Employ Committee (process number: 10482014.57).

Half dozen hundred and xx four two day-old chicks (Cobb 500) arriving to the poultry subcontract of the experimental unit of the Londrina University (Londrina, Paraná State, Brazil) were allocated into cages of 1.45 x one.45 1000 (26 animals per cage). Cages were randomly assigned into six handling groups with four repetitions per treatment: control (no antibiotic), zinc bacitracin (55g/ton), enramycin (10g/ton); halquinol (30g/ton); virginiamycin (xvi,5g/ton) and avilamycin (10g/ton). All animals received a standard diet recommended for this brood from 1 to 21 days of life and some other from 22 to 42 days of life, constituted mainly of corn (63%), grinded soy (28%) and soy oil (five%) (S1 Table). Antimicrobials were given to animals during the whole period of the trial.

Chicks were vaccinated at the hatchery against Marek's disease and at the experimental unit of measurement when were 10 day-old confronting gumboro (Bursine ii, Zoetis, New Jersey USA). Litter consisted of woods shavings was added to the cages to a height of 6 cm. Approximately 300 grams of litter from a commercial farm were mixed to the clean litter in order to increment challenge with illness strains present in the field.

Weight gain and feed intake were recorded and feed conversion and viability calculated within each group. Four animals per cage (n = 16/grouping; 96 total) were randomly selected at the time of slaughter (43 days) and had their cecal contents collected into sterile plastic tubes that were promptly refrigerated (for a maximum of ane.5 60 minutes) and frozen at -lxxx°C until DNA extraction. Chickens were rendered unconscious past electrical stunning just before slaughtering past exsanguination.

Deoxyribonucleic acid extraction and sequencing

Deoxyribonucleic acid was extracted with a commercial kit (Due east.Z.N.A. Stool DNA Kit, Omega Bio-Tek) according to the manufacturer's instructions. The V4 region of the gene 16S rRNA was amplified past PCR using the forward S-D-Bact-0564-a-South-15 and the reverse primers S-D-Bact-0785-b-A-18 [22] containing an overlapping region of the Illumina sequencing primers. PCR was carried in 2 steps: first, 2.5ÎĽL of DNA were added to a mixture containing 9ÎĽL of water, 12.5ÎĽL of Kapa 2X ReadMix (Kapa Biosystems. MA) and 0.5ÎĽL of each 16S primer (10 pmol/ÎĽL). The reaction was carried co-ordinate to the PCR conditions: iii min at 94°C for denaturing, and 26 cycles of 45s at 94°C for denaturing, 60s at 53°C for annealing and 90s at 72°C for elongation followed by a final period of 10 min at 72°C and kept at four°C. PCR products were purified with 20 ÎĽL of Agencourt AMPure XP (Beckman Coulter) magnetic beads and eluted in 52.5 ÎĽl Tris buffer (10mM, pH 8.5). The 2nd PCR was carried past adding 4ÎĽL of the purified production to a mixture with 9.6ÎĽL of h2o, 20ÎĽL of 2X Ready Mix and three.2ÎĽL of each Illumina alphabetize primer (2.5pmol/ÎĽL), which was submitted to the post-obit PCR conditions: three min at 94°C, and seven cycles of 45s at 94°C, 60s at 50°C and 90s at 72°C and a terminal menses of ten min at 72°C and kept at 4°C. A second purification was performed by using 40ÎĽL of AMPure beads and eluting samples with 32ÎĽL of Tris buffer (10mM, pH eight.five). Sequencing was performed with an Illumina MiSeq platform with the V2 reagents kit for 250 cycles from each end at the Genomics Facility of the University of Guelph.

Data were made publicly bachelor at the NCBI Sequence Read Annal under accession number SRP096720.

Statistical analysis

Bioinformatic assay was performed using the software mothur (v.1.36.one) following the standard operational protocol recommended by Kozich et al. [23]. In brusque, after information clean upwards sequences were assigned into phylotypes at the genus level (94% similarity) with taxonomic classification obtained from the Ribosomal Database Classifier (March 2012) [24].

Relative abundances of the main phyla and genera (abundance >1%) and the Firmicutes:Bacteroidetes (F:B) and Firmicutes:Proteobacteria ratios (F:P) found in each handling were represented by column charts. The effect of treatment on each variable was investigated using the ANOVA on ranks with the Kruskal-Wallis non-parametric test and the Tukey test for multiple comparison correction considering a P<0.010 as statistically significant to decrease simulated discovery rate. The ANOVA with Tukey'southward test (considering a P<0.05 as pregnant) was used to investigate interactions between treatments and performance indexes.

In order to decrease bias caused by non-uniform sequence numbers, a subsample from the main dataset was used for alpha and beta diversity analyses and the Good´s coverage bootstrap was calculated in society to ensure that the cutoff adopted was representative of original samples. Richness was estimated by the Chao index and past the number of observed genera. The Shannon and the Simpson's indices were used to judge diversity. The effect of treatment on those variables was investigated using the ANOVA on ranks with the Kruskal-Wallis non-parametric test.

Community membership (that considers the different genera present in each sample) and structure (that considers the different genera and their evenness in each sample) were addressed respectively past the classic Jaccard and by the Yue and Clayton index [25]. The similarity betwixt community membership and structure present in each sample was represented past dendrograms visualized with FigTree (v1.4.2) (http://tree.bio.ed.ac.britain/software/figtree/), and past the Principal Coordinate Assay (PCoA) with two dimensions. The Parsimony test and the analysis of molecular variance (AMOVA) were used for statistical comparison of communities' membership and structure between the groups, and the Benjamini-Hochberg for multiple comparisons adjustment using a false discovery charge per unit of 0.twenty.

The "indicator analysis" implemented in mothur [26] was used with a cutoff of 0.01 in society to identify the about representative bacterial taxa present inside each grouping. In addition, the linear discriminant analysis (LDA) Effective Size (LefSe) was used to detect meaningful biological differences between treatments [27]. P values <0.05 and logarithmic LDA scores college than 2.0 were considered as significant.

Results

A total of 5,695,309 good quality reads were used for the analysis, from which 15,510 reads per sample were randomly subsampled to normalize sequence numbers. The subsampling yielded coverage of 99.9%, indicating that it was representative of the total population.

Alpha diversity

Boilerplate and standard divergence of alpha variety indices institute in each group are presented in Tabular array 1. The statistical analysis revealed that but enramycin was associated with decreased richness estimated past the number of observed genera (P = 0.007) and by the Chao index (P = 0.031) compared to controls. There was no statistical difference between the other treatment groups regarding the number of observed genera, estimated richness (Chao), or diversity (Simpson and Shannon indices).

thumbnail

Table 1. Average and standard deviation (in brackets) of the number of different genera and results of Chao, Simpson and Shannon indexes nowadays in the cecum of broiler chicken after treatment with different antibody growth promoters.

https://doi.org/x.1371/journal.pone.0171642.t001

Beta diversity

The similarity between bacterial communities nowadays in each sample is represented by dendrograms in Fig 1 and Principal Coordinate Analysis (PCoA) in Fig 2. Fig 2A represents microbial membership present in each sample and is indicative that each antimicrobial drug tended to have a specific issue on the choice of cecal species, evidenced past the germination of clusters according to the different treatments. Noteworthy is the overlapping between controls and animals treated with halquinol, indicating a express apparent impact of this drug on the microbiota. The lack of action on microbial customs structure is axiomatic from Fig 2B, with overlapping of samples from the different treatments.

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Fig 1. Dendrograms representing the similarity between membership (A) and structure (B) of bacterial communities institute in cecum of broiler chicken treated with zinc bacitracin (orange), enramycin (red); halquinol (dark-green); virginiamycin (bluish), avilamycin (purple) and in a control grouping (blackness).

CQH: Halquinol.

https://doi.org/10.1371/periodical.pone.0171642.g001

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Fig two. Principal Coordinate Analysis (PCoA) representing the similarity between membership (A) and structure (B) of bacterial communities establish in cecum of broiler craven treated with several antibody growth promoters.

https://doi.org/10.1371/journal.pone.0171642.g002

The effect of antimicrobials on microbial membership is farther evidenced by Parsimony and AMOVA results (Table 2). Halquinol was the only drug that did not impact microbial membership compared to the control group. Interestingly, treatment with antimicrobials did not affect microbial structure in the cecum of any of the studied groups. This, along with the changes acquired in membership, suggests that those drugs had a greater impact on rare species present in that environment.

Relative abundances

Relative abundances of the master phyla and genera are presented in Fig three and S1 Fig. Firmicutes comprised the major bacterial phylum nowadays in the cecum of all groups. Along with Bacteroidetes and Proteobacteria, these three phyla accounted for more than than xc% of all sequences. At that place was no statistical difference in the relative abundances betwixt treated animals and the command group (all P>0.05).

thumbnail

Fig 3. Relative abundances at the phylum (A) and genus (B) level of the main bacteria plant in the cecum of broiler chicken treated with zinc bacitracin, enramycin; halquinol; virginamycin, avilamycin and in a control grouping.

https://doi.org/10.1371/periodical.pone.0171642.g003

Compared to the control group, animals treated with enramycin had statistically lower relative abundance of unclassified Firmicutes, Clostridium XI, unclassified Peptostreptococcaceae (all P<0.001) and greater abundance of Clostridium XIVb (P = 0.004) and Anaerosporobacter (P = 0.015). In improver, animals treated with bacitracin had greater affluence of Bilophila (P = 0.004) compared to controls.

The Firmicutes:Bacteroidetes and Firmicutes:Proteobacteria ratios were calculated inside each treatment group and are presented in Fig 4. Firmicutes:Bacteroidetes ratio did non differ between groups (all P>0.05), but all groups treated with AGPs had numerically lower Firmicutes:Proteobacteria ratios compared to controls.

Specific taxa associated with each treatment

The taxa considered more likely to be representative of each group (P>0.001) equally per the indicator assay are presented in Table 3. No significantly discriminative features could be identified using the LefSe assay.

Table 4 contains data from the performance indexes calculated for each treatment. avilamycin was the only drug associated with higher weight gain and feed conversion.

Discussion

None of the antibiotics selected for this report caused significant changes in cecal community structure (related to the genera comprising a community and how they are distributed) compared to the control group, but did affect microbial membership (the different genera present in the cecum). Thus, while at that place were significant changes in the specific bacterial members that were nowadays (Jaccard index), the lack of an overall impact on the microbial construction (Yue and Clayton index) would suggest that changes affected rare members of the microbiota. This could be related to the fact that nearly axiomatic changes would exist expected to happen at earlier ages and in the almost proximal compartments of the intestinal tract [18]. Notwithstanding, these findings are particularly important for a better understanding of how AGPs bear on cecal bacterial populations and might be used in the hereafter for microbiota manipulation.

Although microbial membership was significantly different from controls regardless the statistical test applied (Table 2), clustering of samples co-ordinate to the different treatments was not as potent as it has been shown with the use of therapeutic doses [28]. Yet, some clustering can still be noticed in the principal coordinate analysis (Fig 2A).

Halquinol was the only drug that did not change significantly the membership of the cecal microbiota in whatsoever detectable style. The similarity between animals treated with the drug and controls is evidenced past the overlapping of samples observed in Fig 2A. Withal, at this signal, it is not clear whether this "lack of activity" is desirable or not. Guasti [26] reported lower weight gain in chicken receiving halquinol compared to groups that also received avilamycin and a prebiotic, which could indicate that this drug may not fairly select species associated with better efficiency for harvesting feed energy. In understanding with those results, weight gain from animals treated with halquinol in the present written report did not differ from the control group, simply farther studies are necessary earlier solid conclusions can be made.

The group treated with avilamycin was the only to have statistically greater weight gain and amend feed conversion compared to controls. Although no genera of biological significance could be identified using the LefSe analysis, but an unclassified Sutterellaceae was associated with the use of this drug pointed by the indicator assay and may be of importance for the evolution of new alternative approaches to subtract the use of antimicrobials for growth promotion, such as probiotics [3,29].

Enramycin was associated with decreased diversity and profoundly affected the relative abundance of several genera compared to controls. Pedroso et al. [xxx] also reported changes in composition of the abdominal microbiota of chicken treated with this drug, but the label of those changes was not possible since molecular fingerprinting was used in that written report.

Fasina et al. [three] showed that handling with bacitracin suppressed experimental infection with C. perfirngens, since treated animals presented lower affluence of the Clostridiaceae family. This drug has also been reported to deplete members of the Lactobacillaceae family unit [3,20,21], simply the same tendency could not be observed in the present written report.

Virginiamycin was associated with enrichment of Faecalibacterium and Lactobacillus spp. and with decreased diversity in the cecal microbiota [21]. Too, the use of this drug along with monensin was reported to crusade depletion of Firmicutes compared to a control group [31]. However, those findings could non exist confirmed by our results and that might be related to differences in diet, geographical location and methodological analyses.

Greater Firmicutes:Bacteroidetes ratios have been associated with bacterial profiles with higher chapters of free energy harvesting [7,32,33]. Firmicutes are as well reported to exist the primary phylum in commercial broilers, while complimentary range chicken seems to present with increased Bacteroidetes and Proteobacteria [34]. Interestingly, the group with the highest Firmicutes:Bacteroidetes ratio in this written report was the only ane to proceeds statistically more weight. Nonetheless, differences in ratios between groups were not significant, and further investigations are required before whatever assumption can be made.

Firmicutes, along with Bacteroidetes and Proteobacteria comprised the major bacterial phyla present in the cecum of all groups. Despite selection bias towards Verrucomicrobia detection normally observed with sequencing of the V4 region of the 16S gene, this phylum was non amid the well-nigh abundant in this study, which further supports the findings of other researchers [35,36]. While results of this study is in agreement with other reports that showed Clostridium, Lactobacillus and Ruminococcus spp. as the nearly arable genera in the chicken cecum [31,37], the high abundance of Megamonas spp. was not expected. This genus has been recently classified and is considered a commensal organism present in the intestinal tract of mammals and birds [38].

Since the 1940'south low doses of antimicrobials take been given to food animals to increment weight gain, but the mechanisms of how this drugs favor the increase in productivity are still nether investigation. The function that the abdominal microbiota plays in this procedure has been demonstrated [4] and further studies should focus on gut microbiota manipulation in order to improve productivity and beast health.

The results of this report add new insights to the current knowledge on how AGPs touch the cecal microbiota of chicken.

Conclusions

The use of several antimicrobials at growth promotion doses caused significant changes in the cecal microbial membership of broiler chicken, simply not in microbial structure, suggesting that those drugs accept a stronger impact on the rare species of bacteria nowadays in that environment.

Supporting information

S1 Fig. Individual representation of the relative abundances at the phylum (A) and genus (B) level of the chief leaner institute in the cecum of broiler craven treated with zinc bacitracin, enramycin; halquinol; virginamycin, avilamycin and in a control group.

https://doi.org/10.1371/periodical.pone.0171642.s002

(TIFF)

Author Contributions

  1. Conceptualization: MCC AAA JSW AO.
  2. Data curation: MCC JSW.
  3. Formal analysis: MCC JSW.
  4. Funding conquering: MCC AAA JSW AO.
  5. Investigation: MCC JAB JABF AO.
  6. Methodology: MCC AAA JSW AO.
  7. Project administration: MCC.
  8. Resources: AAA JSW AO.
  9. Supervision: MCC JSW AO.
  10. Writing – original draft: MCC JSW.
  11. Writing – review & editing: MCC JAB AAA JSW JABF AO.

References

  1. 1. Castanon JIR. History of the apply of antibiotic every bit growth promoters in European poultry feeds. Poult Sci. 2007;86: 2466–2471. pmid:17954599
    • View Commodity
    • PubMed/NCBI
    • Google Scholar
  2. ii. Stutz MW, Lawton GC. Effects of diet and antimicrobials on growth, feed efficiency, intestinal Clostridium perfringens, and ileal weight of broiler chicks. Poult Sci. 1984;63: 2036–2042. pmid:6093090
    • View Article
    • PubMed/NCBI
    • Google Scholar
  3. 3. Fasina YO, Newman MM, Stough JM, Liles MR. Effect of Clostridium perfringens infection and antibiotic administration on microbiota in the minor intestine of broiler chickens. Poult Sci. 2015.
    • View Article
    • Google Scholar
  4. iv. Cox LM, Yamanishi S, Sohn J, Alekseyenko AV, Leung JM, Cho I, et al. Altering the intestinal microbiota during a critical developmental window has lasting metabolic consequences. Cell. 2014;158: 705–721. pmid:25126780
    • View Article
    • PubMed/NCBI
    • Google Scholar
  5. 5. Han GG, Kim EB, Lee J, Lee J-Y, Jin K, Park J, et al. Relationship between the microbiota in dissimilar sections of the alimentary canal, and the body weight of broiler chickens. Springerplus. 2016;5: 911. pmid:27386355
    • View Article
    • PubMed/NCBI
    • Google Scholar
  6. 6. Latorre JD, Hernandez-Velasco X, Wolfenden RE, Vicente JL, Wolfenden Advertisement, Menconi A, et al. Evaluation and Selection of Bacillus Species Based on Enzyme Product, Antimicrobial Activeness, and Biofilm Synthesis every bit Directly-Fed Microbial Candidates for Poultry. Front Vet Sci. 2016;3: 95. pmid:27812526
    • View Commodity
    • PubMed/NCBI
    • Google Scholar
  7. 7. Singh KM, Shah T, Deshpande S, Jakhesara SJ, Koringa PG, Rank DN, et al. Loftier through put 16S rRNA gene-based pyrosequencing analysis of the fecal microbiota of loftier FCR and low FCR broiler growers. Mol Biol Rep. 2012;39: 10595–10602. pmid:23053958
    • View Article
    • PubMed/NCBI
    • Google Scholar
  8. 8. Maron DF, Smith TJS, Nachman KE. Restrictions on antimicrobial use in food animal production: an international regulatory and economic survey. Global Health. 2013;9: 48. pmid:24131666
    • View Article
    • PubMed/NCBI
    • Google Scholar
  9. nine. Miller M. The White House Forum on Antibiotic Stewardship impacts labs across the U.Due south. MLO Med Lab Obs. 2015;47: 28.
    • View Article
    • Google Scholar
  10. 10. Turnbaugh PJ, Ley RE, Mahowald MA, Magrini V, Mardis ER, Gordon JI. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature. 2006;444: 1027–1031. pmid:17183312
    • View Article
    • PubMed/NCBI
    • Google Scholar
  11. 11. Yegani G, Korver DR. Factors affecting intestinal health in poultry. Poult Sci. 2008;87: 2052–2063. pmid:18809868
    • View Article
    • PubMed/NCBI
    • Google Scholar
  12. 12. Costa MC, Stampfli HR, Arroyo LG, Allen-Vercoe East, Gomes RG, Weese JS. Changes in the equine fecal microbiota associated with the use of systemic antimicrobial drugs. BMC Veterinary Enquiry. 2015;11: nineteen. pmid:25644524
    • View Article
    • PubMed/NCBI
    • Google Scholar
  13. thirteen. Patterson JA, Burkholder KM. Application of prebiotics and probiotics in poultry production. Poult Sci. 2003;82: 627–631. pmid:12710484
    • View Commodity
    • PubMed/NCBI
    • Google Scholar
  14. fourteen. Rehman HU, Vahjen West, Awad WA, Zentek J. Indigenous bacteria and bacterial metabolic products in the gastrointestinal tract of broiler chickens. Arch Anim Nutr. 2007;61: 319–335. pmid:18030916
    • View Commodity
    • PubMed/NCBI
    • Google Scholar
  15. 15. Sergeant MJ, Constantinidou C, Cogan TA, Bedford MR, Penn CW, Pallen MJ. Extensive microbial and functional diversity within the chicken cecal microbiome. PLoS Ane. 2014;9: e91941. pmid:24657972
    • View Article
    • PubMed/NCBI
    • Google Scholar
  16. 16. Stanley D, Denman SE, Hughes RJ, Geier MS, Crowley TM, Chen H, et al. Intestinal microbiota associated with differential feed conversion efficiency in chickens. Appl Microbiol Biotechnol. 2012;96: 1361–1369. pmid:22249719
    • View Article
    • PubMed/NCBI
    • Google Scholar
  17. 17. Pourabedin Thou, Guan L, Zhao 10. Xylo-oligosaccharides and virginiamycin differentially modulate gut microbial composition in chickens. Microbiome. 2015;3: 15. pmid:25874109
    • View Article
    • PubMed/NCBI
    • Google Scholar
  18. 18. Dumonceaux TJ, Loma JE, Hemmingsen SM, Van Kessel AG. Characterization of intestinal microbiota and response to dietary virginiamycin supplementation in the broiler chicken. Applied and Environmental Microbiology. 2006;72: 2815–2823. pmid:16597987
    • View Article
    • PubMed/NCBI
    • Google Scholar
  19. 19. Lu J, Hofacre C, Smith F, Lee Dr.. Furnishings of feed additives on the development on the ileal bacterial community of the broiler craven. Animal. 2008;2: 669–676. pmid:22443592
    • View Article
    • PubMed/NCBI
    • Google Scholar
  20. 20. Wise MG, Siragusa GR. Quantitative analysis of the intestinal bacterial community in 1- to iii-week-old commercially reared broiler chickens fed conventional or antibiotic-free vegetable-based diets. Journal of Practical Microbiology. 2007;102: 1138–1149. pmid:17381758
    • View Article
    • PubMed/NCBI
    • Google Scholar
  21. 21. Neumann AP, Suen G. Differences in major bacterial populations in the intestines of mature broilers subsequently feeding virginiamycin or bacitracin methylene disalicylate. Journal of Practical Microbiology. 2015.
    • View Article
    • Google Scholar
  22. 22. Klindworth A, Pruesse Eastward, Schweer T, Peplies J, Quast C, Horn Yard, et al. Evaluation of full general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies. Nucleic Acids Inquiry. 2013;41: e1–e1. pmid:22933715
    • View Article
    • PubMed/NCBI
    • Google Scholar
  23. 23. Kozich JJ, Westcott SL, Baxter NT, Highlander SK, Schloss PD. Development of a Dual-Index Sequencing Strategy and Curation Pipeline for Analyzing Amplicon Sequence Data on the MiSeq Illumina Sequencing Platform. Applied and Environmental Microbiology. 2013;79: 5112–5120. pmid:23793624
    • View Article
    • PubMed/NCBI
    • Google Scholar
  24. 24. Cole JR, Wang Q, Fish JA, Chai B, McGarrell DM, Dominicus Y, et al. Ribosomal Database Projection: information and tools for high throughput rRNA analysis. Nucleic Acids Research. 2014;42: D633–42. pmid:24288368
    • View Article
    • PubMed/NCBI
    • Google Scholar
  25. 25. Costa MC, Arroyo LG, Allen-Vercoe East, Stampfli Hr, Kim PT, Sturgeon A, et al. Comparison of the fecal microbiota of healthy horses and horses with colitis by high throughput sequencing of the V3-V5 region of the 16S rRNA cistron. PLoS ONE. 2012;7: e41484. pmid:22859989
    • View Article
    • PubMed/NCBI
    • Google Scholar
  26. 26. Dufrene M, Legendre P. Species assemblages and indicator species: The demand for a flexible asymmetrical approach. Ecol Monogr 1997;67: 345–66.
    • View Commodity
    • Google Scholar
  27. 27. Segata Northward, Izard J, Waldron L, Gevers D, Miropolsky L, Garrett WS, et al. Metagenomic biomarker discovery and explanation. Genome Biol. 2011;12: R60. pmid:21702898
    • View Article
    • PubMed/NCBI
    • Google Scholar
  28. 28. Videnska P, Faldynova M, Juricova H, Babak 5, Sisak F, Havlickova H, et al. Chicken faecal microbiota and disturbances induced by unmarried or repeated therapy with tetracycline and streptomycin. BMC Veterinary Research. 2013;nine: 30. pmid:23406343
    • View Article
    • PubMed/NCBI
    • Google Scholar
  29. 29. Torok VA, Hughes RJ, Mikkelsen LL, Perez-Maldonado R, Balding M, MacAlpine R, et al. Identification and characterization of potential performance-related gut microbiotas in broiler chickens across various feeding trials. Applied and Environmental Microbiology. 2011;77: 5868–5878. pmid:21742925
    • View Article
    • PubMed/NCBI
    • Google Scholar
  30. thirty. Pedroso AA, Menten JFM, Lambais MR, Racanicci AMC, Longo FA, Sorbara Chore. Abdominal bacterial customs and growth functioning of chickens fed diets containing antibiotics. Poult Sci. 2006;85: 747–752. pmid:16615359
    • View Article
    • PubMed/NCBI
    • Google Scholar
  31. 31. Danzeisen JL, Kim HB, Isaacson RE, Tu ZJ, Johnson TJ. Modulations of the chicken cecal microbiome and metagenome in response to anticoccidial and growth promoter treatment. PLoS ONE. 2011;6: e27949. pmid:22114729
    • View Article
    • PubMed/NCBI
    • Google Scholar
  32. 32. Ley RE, Bäckhed F, Turnbaugh P, Lozupone CA, Knight RD, Gordon JI. Obesity alters gut microbial ecology. Proc Natl Acad Sci U S A. 2005;102: 11070–11075. pmid:16033867
    • View Article
    • PubMed/NCBI
    • Google Scholar
  33. 33. Jami Due east, White BA, Mizrahi I. Potential role of the bovine rumen microbiome in modulating milk limerick and feed efficiency. PLoS ONE. 2014;nine: e85423. pmid:24465556
    • View Article
    • PubMed/NCBI
    • Google Scholar
  34. 34. Mancabelli Fifty, Ferrario C, Milani C, Mangifesta M, Turroni F, Duranti S, et al. Insights into the biodiversity of the gut microbiota of broiler chickens. Environ Microbiol. 2016.
    • View Article
    • Google Scholar
  35. 35. Wei S, Morrison M, Yu Z. Bacterial census of poultry intestinal microbiome. Poult Sci. 2013;92: 671–683. pmid:23436518
    • View Article
    • PubMed/NCBI
    • Google Scholar
  36. 36. Reed S, Neuman H, Moscovich Southward, Glahn RP, Koren O, Tako Eastward. Chronic Zinc Deficiency Alters Chick Gut Microbiota Composition and Office. Nutrients. 2015;7: 9768–9784. pmid:26633470
    • View Commodity
    • PubMed/NCBI
    • Google Scholar
  37. 37. Gong J, Si W, Forster RJ, Huang R, Yu H, Yin Y, et al. 16S rRNA gene-based analysis of mucosa-associated bacterial community and phylogeny in the craven gastrointestinal tracts: from crops to ceca. FEMS Microbiol Ecol. 2007;59: 147–157. pmid:17233749
    • View Article
    • PubMed/NCBI
    • Google Scholar
  38. 38. Polansky O, Sekelova Z, Faldynova M, Sebkova A, Sisak F, Rychlik I. Of import Metabolic Pathways and Biological Processes Expressed by Craven Cecal Microbiota. Applied and Environmental Microbiology. 2015;82: 1569–1576. pmid:26712550
    • View Article
    • PubMed/NCBI
    • Google Scholar

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Source: https://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0171642

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