Chickens are a key food source for humans yet their microbiome contains bacteria that can be pathogenic to humans, and indeed potentially to chickens themselves. Campylobacter is present within the chicken gut and is the leading cause of bacterial foodborne gastroenteritis within humans worldwide. Infection can lead to secondary sequelae such as Guillain-Barré syndrome and stunted growth in children from low-resource areas. Despite the global health impact and economic burden of Campylobacter, how and when Campylobacter appears within chickens remains unclear. The lack of day to day microbiome data with replicates, relevant metadata, and a lack of natural infection studies have delayed our understanding of the chicken gut microbiome and Campylobacter. Here, we performed a comprehensive day to day microbiome analysis of the chicken cecum from day 3 to 35 (12 replicates each day; final n = 379). We combined metadata such as chicken weight and feed conversion rates to investigate what the driving forces are for the microbial changes within the chicken gut over time, and how this relates to Campylobacter appearance within a natural habitat setting. We found a rapidly increasing microbial diversity up to day 12 with variation observed both in terms of genera and abundance, before a stabilization of the microbial diversity after day 20. In particular, we identified a shift from competitive to environmental drivers of microbial community from days 12 to 20 creating a window of opportunity whereby Campylobacter can appear. Campylobacter was identified at day 16 which was 1 day after the most substantial changes in metabolic profiles observed. In addition, microbial variation over time is most likely influenced by the diet of the chickens whereby significant shifts in OTU abundances and beta dispersion of samples often corresponded with changes in feed. This study is unique in comparison to the most recent studies as neither sampling was sporadic nor Campylobacter was artificially introduced, thus the experiments were performed in a natural setting. We believe that our findings can be useful for future intervention strategies and help reduce the burden of Campylobacter within the food chain.

Slowing the growth of modern broiler chickens can have a positive effect on a number of welfare outcomes. However, relatively few studies have compared fast and slower growing broiler chickens reared under the same commercial conditions. The main aim of this study was to evaluate a slower growing breed and standard fast growing broilers on commercial farms. Ross 308 broilers and slower growing Hubbard Redbro broilers were housed on six farms for 17 production cycles. Production data were available for all cycles. Behaviour and environmental measures were taken over one cycle on each of two farms. The farms were visited during weeks 3–6 for both breeds and week 7 for Redbros. We found that breed had a significant effect on a number of measures, including gait score, latency to lie, feather cover, avoidance distances, perch use and play behaviour (p < 0.05). Gait scores were consistently lower among the Redbro flocks during weeks 4, 5, 6 and 7. Redbro broilers generally had longer latency to lie times, better feather cover, and were more reactive to approaching observers. They also showed higher levels of perch use and play. Despite these indications of improved locomotion and physical ability, we found little difference in their general behaviour. However, Redbro broilers did perform longer activity bouts in week 7 than Ross 308s in their final week. There was no effect of breed on dust levels, ammonia concentration or litter condition. Redbro broilers were slaughtered 5.5 days later than Ross 308 birds at a lower average weight (2.32 vs 2.52kg) and had lower mortality, fewer culls and fewer carcasses downgraded at the abattoir. Our results suggest that the slower growing strain was healthier throughout the cycle and more capable of displaying some natural behaviours.

Background The factors affecting host-pathogen ecology in terms of the microbiome remain poorly studied. Chickens are a key source of protein with gut health heavily dependent on the complex microbiome which has key roles in nutrient assimilation and vitamin and amino acid biosynthesis. The chicken gut microbiome may be influenced by extrinsic production system parameters such as Placement Birds/m2 (stocking density), feed type and additives. Such parameters, in addition to on-farm biosecurity may influence performance and also pathogenic bacterial numbers such as Campylobacter. In this study, three different production systems ‘Normal’ (N), ‘Higher Welfare’ (HW) and ‘Omega-3 Higher Welfare’ (O) were investigated in an industrial farm environment at day 7 and day 30 with a range of extrinsic parameters correlating performance with microbial dynamics and Campylobacter presence. Results Our data identified production system N as significantly dissimilar from production systems HW and O when comparing the prevalence of genera. An increase in Placement Birds/m2 density led to a decrease in environmental pressure influencing the microbial community structure. Prevalence of genera, such as Eisenbergiella within HW and O, and likewise Alistipes within N were representative. These genera have roles directly relating to energy metabolism, amino acid, nucleotide and short chain fatty acid (SCFA) utilisation. Thus, an association exists between consistent and differentiating parameters of the production systems that affect feed utilisation, leading to competitive exclusion of genera based on competition for nutrients and other factors. Campylobacter was identified within specific production system and presence was linked with the increased diversity and increased environmental pressure on microbial community structure. Addition of Omega-3 though did alter prevalence of specific genera, in our analysis did not differentiate itself from HW production system. However, Omega-3 was linked with a positive impact on weight gain. Conclusions Overall, our results show that microbial communities in different industrial production systems are deterministic in elucidating the underlying biological confounders, and these recommendations are transferable to farm practices and diet manipulation leading to improved performance and better intervention strategies against Campylobacter within the food chain.

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21Chickens are a key food source for humans yet their microbiome contains bacteria that can be pathogenic to 22 humans, and indeed potentially to chickens themselves. Campylobacter is present within the chicken gut and 23 is the leading cause of bacterial foodborne gastroenteritis within humans worldwide. Infection can lead to 24 secondary sequelae such as Guillain-Barré syndrome and stunted growth in children from low-resource 25 areas. Despite the global health impact and economic burden of Campylobacter, how and when 26 Campylobacter appears within chickens remains unclear. As such, there has been a motivation to decrease 27 the number of Campylobacter within chickens and thus reduce the risk of infection to humans. The lack of 28 2 day-to-day microbiome data with replicates, relevant metadata, and a lack of natural infection studies have 29 delayed our understanding of the chicken gut microbiome and Campylobacter. Here, we performed a 30 comprehensive day-to-day microbiome analysis of the chicken cecum from day 3 to 35 (12 replicates each 31 day; n=396) combining metadata such as chicken weight and feed conversion rates to investigate what the 32 driving forces are for the microbial changes within the chicken gut over time, and how this relates to 33 Campylobacter appearance within a natural habitat setting. We found a rapidly increasing microbial diversity 34 up to day 12 with variation observed both in terms of genera and abundance, before a stabilisation of the 35 microbial diversity after day 20. In particular, we identified a shift from competitive to environmental drivers 36 of microbial community from days 12 to 20 creating a window of opportunity whereby Campylobacter 37 appears. Campylobacter was identified at day 16 which was one day after the most substantial changes in 38 metabolic profiles observed. In addition, microbial variation over time is most likely influenced by the diet 39 of the chickens whereby significant shifts in OTU abundances and beta dispersion of samples often 40 corresponded with changes in feed. This study is unique in comparison to the most recent studies as neither 41 sampling was sporadic nor Campylobacter was artificially introduced, thus the experiments were performed 42 in a natural setting. We believe that our findings can be useful for future intervention strategies and can help 43 elucidate the mechanism through which Campylobacter within chickens can be reduced.