Improving feed efficiency by understanding the intestinal bacterial network in pigs and poultry Dr. Stefan G. Buzoianu Dr. Peadar G. Lawlor Ms. Ursula McCormack Moorepark Research Centre, Teagasc, Ireland Dr. Barbara Metzler-Zebeli Mr. Andor Molnar Ms. Janine Scholz University of Veterinary Medicine Vienna

Introduction

ECO-FCE overview Feb 2013 – Feb 2017 17 partners 7 WPs Overall objectives improve food security by optimising the feed efficiency in pigs and broilers without negatively affecting animal welfare and meat quality reduce the ecological footprint of the pig and broiler production systems WP 3 objective to examine the gut structure, function, microbiota and metagenomics in animals divergent for feed efficiency

RFI Work Package 3 Intestinal structure & function Intestinal health Intestinal microbiota Animal performance Genetics Genomics RFI Low Medium High Health & welfare Meat quality

Determination of feed efficiency Selection of high and low feed efficient animals - based on Residual Feed Intake Residual Feed Intake (RFI) = difference between observed and predicted feed intake, with lower RFI values indicating greater energy efficiency RFI = FI [a + b1 * BW0.75 + b2 * BWG] Where a is the intercept and b1 and b2 are partial regression coefficients of feed intake (FI) on BW0.75 and body weight gain (BWG), respectively. Other measures of feed efficiency Feed efficiency = gain (g) / feed intake (g) Feed conversion ratio (FCR) = feed intake (g) / gain (g) RG = BWG [a + b1 * BW0.75 + b2 * FI] RIG = (RG/SD RG) - (RFI/SD RFI)

Feed efficiency in monogastric livestock species Genetics Diet Rearing environment Age Gut commensal microbiota Substantial variation in feed efficiency between individual animals. Great variation in gut commensal microbiota between individuals.

Role of the intestinal microbiota Benefits to the host intestinal maturation inhibition of pathogen growth nutrient salvaging detoxification production of vitamins Costs to the host competition for nutrients immune activation production of toxins opportunistic toxin reabsorption mucolytic activity

Effect of host microbiota on host metabolism and hormone secretion Intestinal microbiota can redirect energy partitioning to adipose tissue and reduce fatty acid oxidation. Implications for feed use efficiency and carcass composition in livestock animals? Bäckhed (2011) Ann Nutr Metab 58(suppl 2):44

Effect of gut microbiota composition on body weight Obese humans & mice: Firmicutes  Bacteroidetes  Low-calorie diet Firmicutes  Bacteroidetes  wikipedia.org Actinobacteria  Bacteroidetes  no difference in Firmicutes Changes in Lactobacillus and Bifidobacterium species Methanogenic archaea  Requena et al. (2013) Trends Food Sci Tech 34:44 Meat-producing monogastric livestock species are young, fast growing and lean animals Are the key players the same as in human obesity models ?

Chickens

Diet-related cecal microbiota and performance in male chickens Caecal microbial communities by diet Caecal microbial communities identified as being from birds with improved performance or poorer performance Diet is the most influencing factor affecting feed efficiency. Torok et al. (2011) AEM 77: 5868

Batch to batch variation in caecal microbiota of chickens 3 different batches of chickens PCA plot of caecal microbiota. The plot is based on between groups (trials) analysis. Very different microbiota profiles across chicken batches Very different feed use efficiencies across chicken batches Stanley et al. (2013) PloS ONE 8(12): e84290 High variation in caecal microbiota partly due to lack of colonisation of the chickens by maternally derived bacteria High hygiene levels in modern commercial hatcheries remove natural bacteria Environmental microbiota from transport boxes, first feed and staff people

Fecal community of high and low feed efficient broiler chickens Singh et al. (2014) J Appl Genet 55: 145

Characterisation of differences in gut microbiota and gut function of chickens with good and poor feed efficiency Experimental design: 2 partner institutions (AFBI & Vetmeduni) performed identical chicken experiments with 3 batches of 50/64 chicks Similar chicken genetic: Cobb 500FF Similar maize-soybean meal diets (starter, grower, and finisher diets) No in-feed antibiotics and any other gut health-related additives Chickens were individually housed Best and worst feed efficient chickens were identified using Residual Feed Intake On day 42, samples were collected for: Ileal and caecal digesta for metagenomics and microbial metabolites Tissue of duodenum, jejunum, ileum, caeca for gut function and structure

Residual feed intake of good and poor feed efficient broiler chickens Great variation in residual feed intake and thus in feed use efficiency.

Microbial metagenome of good and poor feed efficient chickens Shotgun sequencing using MiSeq Technology (Illumina) Under construction

Influencing factors: Host genome or gut microbiota ? Jejunal electrophysiological characteristics of good and poor feed efficient broiler chickens Gut electrophysiology was performed using Ussing chamber technique. Tissue originated from the distal jejunum. Good feed efficient females showed lower tissue resistance, higher conductance and short-circuit current indicating a higher ion flux and permeability of the jejunal mucosa Influencing factors: Host genome or gut microbiota ?

Pigs

Literature Little data available in pigs ↓ Bacteroidetes & ↑ Firmicutes in obese pigs (Pedersen et al., 2013) ↑ Firmicutes & ↓ β-Proteobacteria in ERS-fed pigs (Haenen et al., 2013) Protein, CHO and lipid metabolic pathways affected by intestinal microbial profile mice (Antunes et al., 2011) pigs (Mulder et al., 2009)

Screening on feed efficiency in pigs Teagasc × 3 AFBI Vetmeduni 46 litters Common genetics Common & site-specific boars Common diets Common protocols Pigs divergent for RFI weaning d 42 d 84 d 112 F – faecal I – ileal digesta C – caecal digesta P – performance P P F F F I C

Compositional analysis Microbiota profiling d 0 (weaning) d 42 d 84 d 126 d 139 P P P P F F F F F I C Compositional analysis 16S rRNA gene sequencing Functionality Shotgun metagenomics Illumina F – faecal; I – ileal digesta; C – caecal digesta; P – performance

Progress on microbiota profiling Samples collected DNA extracted 16S rRNA gene sequencing – results being analysed Shotgun metagenomics samples being prepared results ~ Oct 2014

Manipulation of GIT microbial profile inoculation Nutrition Management Low RFI Additives

Inoculation with faecal inoculum from good feed converters Anaerobically processed diluted 1:6 strained centrifuged (6000 × G for 15 minutes) frozen at -80°C in 10% glycerol No inoculum Single inoculation Multiple inoculation Inoculum No inoculum Single inoculation Multiple inoculation Sows Offspring

Nutritional intervention Optimum strategy – inoculum Prebiotics – alone or in combination Monitoring and sampling of offspring through their lifetime performance health intestinal microbiota

Acknowledgements ECO-FCE has received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration (FP7 2007/2013) under grant agreement No. 311794 Teagasc Walsh Fellowship Programme

Thank you

ECO-FCE Gut structure, function, microbiota and metagenomics Hypothesis: It is assumed that the gut microbiome of pigs and broiler chickens with good and poor feed use efficiency differs in key members, thereby influencing the intestinal and metabolic host response, production efficiency and host health. Objectives: To enhance our understanding of the interactions between gut microbiome and host genome in pigs and chickens. This task will be achieved by employing cutting-edge 16S rRNA-specific and shotgun metagenomics. Using this improved understanding, strategies to improve feed conversion efficiency through gut microbiome manipulation in embryonic and subsequent developmental stages will be developed.

Nutrient digestibility Interactions between gut microbiome and host physiology and health Mucus secretion NF-kB Barrier function Mucosal immunity Commensal microbiota Growth & feed efficiency Gut morphology Nutrient digestibility Nutrient transporters Bäckhed (2011) Ann Nutr Metab 58(suppl 2): 44; Twarziok et al. (2014) Mol Inf 33: 171