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Amal Rouissi
PhD student
Gut Health Symposium
St-Louis
November 2018
TOWARDS THE REPLACEMENT OF ANTIBIOTICS GROWTH
PROMOTERS IN CHICKEN: META-ANALYSIS APPROACH
Amal Rouissi, Boulianne M , F Guay and M. P. Létourneau-Montminy
www.ulaval.ca
Antibiotic resistance
It is a natural phenomenon of defense of the bacteria with respect to the action exerted by the antibiotic
(Bywater, 2006 ; Sorum et Sunde, 2001 ; Perry et Wright, 2013)
Introduction
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• The impact of antimicrobial growth promoters on the development ofantimicrobial resistant bacteria has been the subject of several reportsand led to their ban in the European Union in 2006 (regulations [CE]1831/2003)
• In Canada, preventive use of antibiotics will be ban at the end of 2018
• Withdrawal of antibiotics from broiler flocks has been associated withthe resurgence of necrotic enteritis (Marie-Lou Gaucher, 2015)
Introduction
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• Antibiotic effects on animal growth efficiency is most likely derivedfrom effects on the intestinal microbiota, which in turn may
• Reduce opportunistic subclinical infections
• Reduce host response to the gut microflora
• Reduce competition for nutrients
• improve nutrient digestibility(Dibner and Richards, 2005)
Introduction
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Many antibiotic alternatives available are for poultry production (Gadde et al. 2017)
Introduction
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• Organic acids may reduced colonization of pathogens in the
intestine and in turns improve growth performance due to pH
modifications and bactericidal effects
(Peter Theobald, 2018)
Introduction
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• Prebiotics, defined as either
1. non-digestible food ingredients that beneficially affect the
host by selectively stimulating the growth and/or activity
of colonic bacteria
(Gibson and Roberfroid, 1995)
2. selectively fermented food ingredients that improve host
health by targeting indigenous components thought to
be positive
(Walton et al., 2013)
Introduction
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Design a database of publications aimed at studying the effects of
alternatives to antibiotics growth promoters in broiler chickens and study
it with meta-analysis tool
The specific objectives are:
1. Make an inventory of the alternatives studied, the measured criteria,
the most studied ages, etc.
2. Quantify the effect of the different alternatives on the criteria
commonly measured in the trials (e.g. growth performance, mortality,
digestive physiology, digestibility)
3. Highlighting factors that modulate the response of the alternatives
tested
Objectives
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Meta-analysis
• Statistical tool that gather data from multiple published studies and attempted to1. Increase the statistical power of an effect2. Raise a doubt about discordant results3. Test and increase the possibility of generalization4. Explain the variability of the results between tests5. Confront a test with others6. Answering a question not asked in the tests
• Each publication and experiment within publication receive a code that is included in the statistical model
Materials and Methods
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Meta-analysis steps
Databasedesign
Selection and coding of
experiments
Users
Post-analysisevaluation
Selection of statistical model
Study of the meta-design
Graphicalanalysis
Adjustments
From Sauvant et al. (2005)
Objective(s)
Literaturesearch
Materials and Methods
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Criteria of inclusion
1. Diet composition
2. Broiler genetic line
3. Feed conversion ratio data
Materials and Methods
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• Studies including the keywords “broilers", "poultry“, and “organic
acids“, “prebiotics"
• Publications and experiments were specifically coded
• Each observation represented the mean of one treatment group
• All dietary nutrient profile recalculated INRA-AFZ tables (Sauvant et
al., 2004)
Materials and Methods
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• Many publications included positive control with antibiotics (C+)
and negative control without (C-)
• The difference between C+ and C- have been calculated to have an
idea of the challenge imposed to the birds
• However, in the database only C- and C- with alternatives has
been included
Materials and Methods
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Nb publications = 17
Nb trials= 44Nb treatment
= 107
Nb publications = 11
Nb trials= 32Nb treatment
= 75
Organic Acids
Prebiotics
Materials and Methods
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Variables XFixed
• Metab. energy (% supply vs require)
• Crude protein (% supply vs require)
• Difference in performance C+ vs C-
• Alternative types
• Genetic line
• Presence of challenge
• Age class
Continuous
• Dose
Variables Y
• Average daily gain (ADG)
• Average daily feed intake
(ADFI)
• Feed conversion ratio
(FCR)
• ADG effect (% vs C-)
• ADFI effect (% vs C-)
• FCR effect (% vs C-)
Materials and Methods
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Data analysis
Graphical examination
a) Relationship X and X
b) Relationship Y and X
Statistical analysis
• Minitab 18.0 and SAS 9.4
• Experiment as random effect
• Dose as covariate
• Post-analysis tests
Materials and Methods
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Results and discussions
Consistency:
70% of OA treatment have
positive and significant effect
on the FCR
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Results and discussions
• No effect of age
• No effect of genetic
• No effect of challenge
• No effect of CP
• No effect of OA type
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+ 4%
Parameters Coefficient P-value
Intercept 186 0.88
%AMEnRequirement 1.87 0.67
Linear effect of OA 3.98 0.01
Quadratic effect of OA 9.80 0.13
Results and discussions
R2 = 99,72%
RMSE= 1,38466
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1,75
1,80
1,85
1,90
0,00 0,05 0,10 0,15 0,20 0,25 0,30 0,35
FC
R
Dose Organic Acids (%)
+ 3%
Parameters Coefficient P-value
Intercept 10.7 0.0018
%EnergyRequirement -0,0893 0.0001
Linear effect of OA -0.368 0.0016
Quadratic effect of OA 0.563 0.0385
Results and discussions
R2 = 99,2%
RMSE= 0,0330143
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Results and discussions
1,6
1,7
1,8
1,9
2,0
2,1
2,2
2,3
0 0,05 0,1 0,15 0,2 0,25 0,3 0,35
FCR
Dose Organic Acids (%)
%requirME =99 %requirME =95 %requirME =97
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Consistency:
60% of Prebiotic treatment have
positive significant effect on the
FCR
Results and discussions
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Results and discussions
• No effect of age
• No effect of genetic
• No effect of challenge
• No effect of CP
• No effect of prebiotic type
www.ulaval.ca
57
58
59
60
61
62
63
64
0 0,25 0,5 0,75 1 1,25 1,5 1,75 2 2,25 2,5 2,75 3
AD
G (
g)
Dose Prebiotics (g/kg)
Parameters Coefficient P-value
Intercept 208 0.003
%EnergyRequirement 10.8 0.224
Linear effect of Prebiotic -1.50 0.025
Quadratic effect of Prebiotic -0.485 < 0.001
Linear effect of Prebiotic* %_EnergyRequirement -0.0831 0.353
Results and discussions
the best dosage of prebiotic for
optimal growth is around 2 g /kg diet
(Tucker et al. 2003)
+ 6%
R2 = 99,77%
RMSE= 2,19618
www.ulaval.ca
1,60
1,62
1,64
1,66
1,68
1,70
1,72
1,74
0 0,25 0,5 0,75 1 1,25 1,5 1,75 2 2,25 2,5 2,75 3
FC
R
Dose Prebiotics (g/kg)
Parameters Coefficient P-value
Intercept 3.62 < 0.001
%EnergyRequirement -0.573 0.023
Linear effect of Prebiotic -0.0191 0.056
Quadratic effect of Prebiotic 0.009 0.017
Linear effect of Prebiotic* %_EnergyRequirement 0.005 0.039
Results and discussions
the best dosage of prebiotic for
optimal growth is around 2 g /kg diet
(Tucker et al. 2003)
+ 9%
R2 = 96,25%
RMSE= 0,0605137
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The current study shows
• Response of OA and prebiotics depends of the dose and level of
dietary energy supply in comparison to requirements
• The most studied alternatives are butyric acid for OA and MOS for
prebiotics
Next step
• Probiotics database
• Essential oil database
• Comparing the most studied alternatives together
• Testing the best alternative in the farm
To be continued…
Conclusions and perspectives
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Results and discussions
Consistency:
60% of Probiotic treatment
have positive and significant
effect on the FCR
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Results and discussions
• No effect of age
• No effect of genetic
• No effect of challenge
• No effect of CP
• No effect of ME
• No effect of Probiotic type
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+ 3%
Parameters Coefficient P-value
Intercept 186 0.8
%AMEnRequirement 0,689036 0.63
Linear effect of Pro -6,776955 0.005
Quadratic effect of Pro 0,015327 0.7
Results and discussions
R2 = 99,72%
RMSE= 1,38466
35
36
37
38
39
40
41
0 1,5 2 2,5 4 4,5 5 5,5 6 6,5 7 7,5 8
AD
G(g
)
Dose Probiotiques (Log cfu/g)
www.ulaval.ca
+ 6%
Parameters Coefficient P-value
Intercept-1,858924
0.08
%EnergyRequirement0,034598
0.46
Linear effect of Pro0,153277
0.04
Quadratic effect of Pro -0,002468 0.08
Results and discussions
R2 = 96,9%
RMSE= 0,055
1,3
1,35
1,4
1,45
1,5
1,55
1,6
0 1,5 2 2,5 4 4,5 5 5,5 6 6,5 7 7,5 8
FC
R
Dose Probiotiques (Log cfu/g)
www.ulaval.ca
Results and discussions
1,35
1,40
1,45
1,50
1,55
1,60
0 1 2 3 4 5 6 7 8 9 10
FC
R
Dose Probiotique( Log cfu/g)
%Ebesoin=99 % Requir ME=97 % Requir ME=95
www.ulaval.ca
http://monogastriques.fsaa.ulaval.ca/
Thank you for
your attention