This document summarizes research on studying feed additives in experimental conditions. It describes various experimental infection models used to study Salmonella, E. coli, and Clostridium perfringens. It also discusses analyzing the gut microbiota using cloning, sequencing, and ion torrent analysis. Key findings include that the gut microbiota plays an essential role in digestive physiology and animal health, and can be modified by feed composition and additives, which can help reduce variance in productive parameters and improve farm economics.

1. Studies of feed additives in
experimental conditions
Dr. Ignacio Badiola
Head of the BACPAR SubProgram, IRTA-CReSA
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2. Introduction
Agence Française de Sécurité Sanitaire des Aliments (AFSSA), Maisons-Alfort
Departamento de Ciencia Animal, ETSI Agrónomos, UPV
Departamento de Producción Animal, ETSI Agrónomos, UPM
Department of Agronomy, Food, Natural Resources, Animal and Environment, Università de Padova
Department of Comparative Biomedicine and Food Science, Università de Padova
Department of Genetics and Microbiology, UAB
Faculty of Animal Sciences of the Agricultural University of Athens
Gut and Immunology Group, Rowett Institute of Nutrition and Health, University of Aberdeen
Institut National de la Recherche Agronomique, Toulouse
Institut National de la Recherche Agronomique, Tours
Instituto de Estudios Biofuncionales. Facultad de Farmacia. UCM
Instituto de Investigación en Recursos Cinegéticos, IREC (CSIC-UCLM-JCCM)
IRTA, Centre de Sant Carles de la Ràpita, Unitat de Cultius Aqüícoles
IRTA, Centre Mas de Bover, Nutrició de Monogàstrics
National Veterinary School, Toulouse
Research Institute for Animal Breeding and Nutrition, Godollo University
Royal Veterinary and Agricultural University (KVL), Frederiksberg
Statens Veterinärmedicinska Anstalt, Uppsala University
ADISSEO France S.A.S.
DSM Nutritional Products
Elanco Animal Science Research
Indukern, S.A.
Laboratorios Andrés Pintaluba, S.A.
Laboratorios Calier, S.A.
Laboratorios CENAVISA
Laboratorios Esteve Veterinaria, S.A.
Laboratorios Intervet, S.A.
Laboratorios Lamons, S.A.
Laboratorios Maymo S.A.
Laboratorios S.P. Veterinaria, S.A.
NANTA, S.A.
Novartis Animal Health
Novozymes Biologicals FR S.A.
ONDAX Scientific
Rubinum Animal Health
• Public projects with in vivo feed additive trials (9)
 EU: 5
 Nationals: 4
• Private company contracts with in vivo feed additive trials (26)
 International
 Antimicrobials: 3
 Prebiotics and probiotics: 10
 Nationals
 Antimicrobials: 12
 Prebiotics and probiotics: 1

3. Introduction
• Feed additives are used to supplement essential components in
the diet of farm animals (essential aminoacids, vitamins).
• Another important role of feed additives is to increase the
digestibility of raw materials (enzymes).
• After the ban of antimicrobials growth promoters, the interest
for feed additives with antimicrobial activity has been increased
(plant extracts, organic acids...)
• To reduce pathogenic and to increase saprophytic
microorganisms are fundamental aims for feed additives
(probiotics, prebiotics).
• To stimulate the immunologic system is another point of interest
for feed additives.
• To improve the knowledge of intestinal physiology, and specially
changes in the intestinal microbiota (components and
metabolism), is essential for the development of new feed
additives.

4. Experimental infection models
 Salmonella Enteritidis in chickens.
 Salmonella Enteritidis in hens.
 Salmonella Typhimurium in pigs.
 Escherichia coli in pigs.
 Escherichia coli in chickens.
 Clostridium perfringens in chickens.

6. The gut microbiota contributions to host physiology
Sekirov et al., Physiol. Rev. 2010;90:859-904
DC tolerization
Cellular immunity
Lymphoid organogenesis
Mucosal Immunity
↑Bacteroidetes
B. fragilis (PSA)
SCFAs
AMPs
Gm-PG
GM-LPS
↑IgA
↑Iap
activation
NFKB
inactivation
Lactobacillus spp. E.coli
Barrier
maintenance
B. thetaiotaomicron
Bifidobacterium spp.
Clostridium spp.
SCFA
metabolism
Conjugation of
linoleic acid
Nutrition
Xenobiotics metabolism
Drug disposition
↓Oxalate
excretion
Lipid
metabolism
Behavior O.formigenes
Normalization of
HPA stress response
B.infantis
Angiogenesis
Presistalsis
Glycosylation
GIT surface maturation
GIT functional maturation
Immunocompetence
Tolerance

7. The intestinal microbiota of productive animals is
composed by:
16-23% cultured bacteria.
77-84% uncultured bacteria.
To analyse the cultured and the uncultured intestinal
bacteria we initially used the Restriction Fragment
Length Polymorphism (RFLP) method

8. RFLP profiles
AGL2008-00627-GAN

9. 0
500
1000
1500
2000
2500
0 100 200 300 400 500 600 700 800
T1-D27-A1403-Ce
T3-D27-A1401-CeLactobacillus helveticus
Uncultured alpha proteobacterium
Uncultured gamma proteobacterium
Parabacteroides sp.
Prevotella nigrescens
No sequence homology No sequence homology
Uncultured bacterium
Uncultured Desulfovibrio
Uncultured Succinivibrio
Uncultured Veillonella
No sequence homology
Lactobacillus spp.
Rodobacter spp.
Uncultured Desulfovibrio
No sequence homology
Lactobacillus salivarius
No sequence homologyParabacteroides sp.
No sequence homology
Identification of Bacteria Species by Cloning and
Sequencing

10. Effect of strains L-92 and L-94 (Bacteroides spp.) on
mortality rate by ERE
0
10
20
30
40
50
L-94 Control -
Trial 1
23.33
46.66
Mortality by ERE
At weaning At the beginning of ERE
0
10
20
30
40
50
60
L-92 L-94 Control -
Trial 2
29.17 31.25
58.33
Mortality by ERE
OT00-040-C2-2

11. Effect of fiber source and enzyme supplementation on
digesta’s and mucosa’s biodiversity of ileum and caecum
C = Corn
WBR = Wheat+Barley+Rye
- = Without enzyme
+ = With enzyme

12. New molecular biology methods
RNA-Later
Etanol Etanol
0
2
4
6
0
5
10
15
20
C-C-C/L
C-C-L/L
L-C-C/L
L-C-L/L
C-C-C/L
C-C-L/L
L-C-C/L
L-C-L/L
1st period 2nd period
Q-PCR and 2-ΔΔCт
22d 30d
RNA-Later
Ion Torrent 316™ Chip Kit

13. Summary of Ion-Torrent analysis of Ileal Microbiota
First Period Second Period
C-C/GFC C-C/BFC L-C/GFC L-C/BFC C-C-C/GFC C-C-C/BFC C-C-L/GFC C-C-L/BFC L-C-C/GFC L-C-C/BFC L-C-L/GFC L-C-L/BFC
Number of sequences 345221 353196 382219 311926 125949 181309 173262 201476 197613 200657 166206 155863
% Lactobacillus 91.74 86.38 83.36 93.99 91.19 83.62 91.07 90.61 86.99 84.98 90.82 93.75
% Other bacteria 8.26 13.62 16.64 6.01 8.81 16.38 8.93 9.39 13.01 15.02 9.18 6.25
Biodiversity 78 60 89 57 84 93 71 50 86 135 101 68

14. Kruskal-Wallis rank sum test & Period P-value Kruskal-Wallis rank sum test & FCR P-value Kruskal-Wallis rank sum test & SD P-value Kruskal-Wallis rank sum test & FD P-value
Bacillus 0.001 Anaerostipes 0.027 Jeotgalicoccus 0.027 Butyricicoccus 0.006
unclas_Bacillales 0.001 Aerococcus 0.035 unclas_Bacteroidetes 0.044 unclas_Betaproteobacteria 0.011
unclas_Porphyromonadaceae 0.003 unclas_Burkholderiales 0.044 Catenibacterium 0.064 unclas_Clostridiales 0.016
Prevotella 0.003 unclas_Lactobacillaceae 0.059 Comamonas 0.064 unclas_Clostridia 0.019
unclas_Prevotellaceae 0.003 Brachybacterium 0.064 Deinococcus 0.064 Bacteroides 0.020
unclas_Bacillaceae.1 0.004 Curvibacter 0.064 Finegoldia 0.064 Clostridium.XI 0.021
unclas_Chitinophagaceae 0.004 Delftia 0.064 Peptoniphilus 0.064 unclas_Bacteria 0.021
Paracoccus 0.006 Parabacteroides 0.064 unclas_Bradyrhizobiaceae 0.064 unclas_Lachnospiraceae 0.021
Enterococcus 0.006 Erysipelotrichaceae_incerta_sedis 0.074 Methylobacterium 0.025
Dorea 0.008 Neisseria 0.097 Streptophyta 0.027
Lactococcus 0.011 unclas_Rhodobacteraceae 0.097 Cloacibacterium 0.027
Roseburia 0.011 Fusobacterium 0.027
Sarcina 0.011 Ruminococcus 0.027
unclas_Acidaminococcaceae 0.011 unclas_Peptostreptococcaceae 0.027
Selenomonas 0.011 Clostridium.IV 0.037
unclas_Bacilli 0.012 Sphingomonas 0.043
unclas_Erysipelotrichaceae 0.020 unclas_Firmicutes 0.046
unclas_Alphaproteobacteria 0.025 unclas_Ruminococcaceae 0.046
Aquabacterium 0.027 Barnesiella 0.046
Parasutterella 0.027 Alistipes 0.061
unclas_Planococcaceae 0.027 Brachybacterium 0.064
unclas_Clostridiaceae.1 0.033 Coprobacillus 0.064
Chryseobacterium 0.033 Coprococcus 0.064
Barnesiella 0.035 Gemella 0.064
unclas_Lactobacillales 0.036 Granulicatella 0.064
Flavonifractor 0.037 Megasphaera 0.064
Phenylobacterium 0.037 Peptoniphilus 0.064
unclas_Enterococcaceae 0.045 Clostridium.XlVb 0.073
Clostridium.XVIII 0.061 unclas_Bacteroidales 0.073
Comamonas 0.065 Sarcina 0.074
Coprobacillus 0.065 Pelomonas 0.074
Deinococcus 0.065 unclas_Comamonadaceae 0.093
Granulicatella 0.065 Actinomyces 0.097
Lysinibacillus 0.065
Megasphaera 0.065
Sphingobacterium 0.065
unclas_Cytophagaceae 0.065
unclas_Leptotrichiaceae 0.065
unclas_Veillonellaceae 0.065
Clostridium.XlVb 0.073
Sphingomonas 0.073
unclas_Ruminococcaceae 0.074
unclas_Bacteroidetes 0.081
Anaerococcus 0.083
Veillonella 0.083
Clostridium.sensu.stricto 0.091
Oscillibacter 0.092
unclas_Neisseriaceae 0.093
Clostridium.XI 0.093
Staphylococcus 0.093
Neisseria 0.097
Significant differences for Ileal Microbiota vs Trial Factors

15. Effect of feed supplemented with marine algae extract on some
immunological parameters of intestinal mucosa by RT-PCR
CENIT VIDA (CEN-20101026)

16. Importance of variance homogeneity as productive parameter
Clinical efficacy evaluation of the use of tylosin for the treatment and control of porcine
proliferative enteropathy (ileitis) associated with Lawsonia intracellularis
Mean Variance
Control Tylosin P-value1
Control Tylosin P-value2
Animal weight (kg/pig)
Day 0 28.42 29.20 0.77 25.40 15.10 0.16
Day 21 42.72 45.66 0.36 51.80 21.70 0.02
Day 31 50.90 53.98 0.35 76.10 23.00 0.002
Daily growth rate (kg/pig/day)
Day 0 to 21 0.681 0.773 0.036 0.022 0.009 0.02
Day 21 to 31 0.818 0.833 0.76 0.064 0.018 0.001
Daily feed consumption (kg/pig/day)
Days 0 to 21 1.471 1.569 0.21 0.005 0.008 0.65
Days 21 to 31 1.862 1.922 0.5 0.006 0.014 0.53
Feed conversion ratio
Days 0 to 21 2.160 2.030 0.050 0.535 0.073 <0.001
Days 21 to 31 2.280 2.300 0.770 0.550 0.137 <0.001
1
Anova test
2
Bartlett test

17. Importance of variance homogeneity as productive parameter
This batch will be punished
if all animals are sent
together to slaughterhouse
Troubles for the correct cleaning and disinfection of farm
facilities. Increasing the risk of maintenance of infectious agents.
Higher prevalence of respiratory and digestive disorders in the
next batch.

18. Conclusions
• It is important to normalise experimental infection
models.
• The intestinal microbiota is essential for animal health
and welfare.
• The gut microbiota plays an essential role on digestive
physiology.
• Some microbial components have direct effect on
intestinal mucosa (barrier effect and gut associated
lymphoid tissue).
• The intestinal microbiome can be modified by feed
composition (raw materials and feed additives).
• Feed additives can reduce the variance of productive
parameters, representing a significant improvement on
the economical balance of farm.

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