K. OPHEL-KELLER1
R.J. HUGHES2
R. FORDER3
M. ALI4
R. MACALPINE4
1SARDI, Plant and Soil Health, Adelaide SA, Australia.
2SARDI, Pig and Poultry Production Institute, Roseworthy SA, Australia.
3University of Adelaide, Department of Animal Science, Roseworthy SA, Australia.
4Inghams Enterprises Pty Limited, Leppington NSW, Australia.
The gastro-intestinal tract contains a complex population of bacteria, which can have both negative and positive effects on their host. However, the complexity of these interactions is not yet fully understood. Changes in gut microflora immediately post hatch and modification to achieve lifelong benefit have not been investigated in great detail.
This report describes the application of T-RFLP, a microbial profiling technique for examining the chicken intestinal microflora. This DNA based technique is capable of providing a "snap-shot" of the complex bacterial population at any particular time and combined with multivariate statistical analysis has enabled relationships between gut microflora and bird performance to be investigated. These tools are being used to examine changes in the microbial community of the chicken gut associated with environment and age, hence contributing to an increased understanding of the chicken gut microbiota and its role in health.
I. Introduction
The microorganisms that colonise the gastrointestinal tract during the early post-hatch period form a synergistic relationship with their poultry host. Gastrointestinal microorganisms have a highly significant impact on uptake and utilisation of energy (Choct et al., 1996) and other nutrients (Smits et al., 1997; Steenfeldt et al., 1995), and on the response of poultry to anti-nutritional factors (such as non-starch polysaccharides), pre- and pro-biotic feed additives and feed enzymes (Bedford and Apajalahti, 2001). Microorganisms can also directly interact with the lining of the gastrointestinal tract (Van Leeuwen et al., 2004), which may alter the physiology of the tract and immunological status of the bird (Klasing et al., 1999). During the first week post-hatch, the chicken small intestine grows rapidly. In ovo and early post hatch feeding, as well as altering gut microflora development within the first two weeks post hatch, have been shown to modify gut development in chickens (Smirnov et al., 2006; Smirnov et al., 2005). Litter material has been shown to influence bird performance (Grimes et al., 2006) but information on the effect of litter material on gut microflora development is lacking.
Therefore, knowledge about the composition of the gut flora, microbial ecology of the gastrointestinal tract and factors affecting its development are still limited. Previous investigations have used culture-dependant approaches, which are limited by knowledge of particular bacterial growth requirements, and generation of sequence information, which is not appropriate for high throughput comparative studies. Alternatively, DNA-based molecular techniques have the advantages of being rapid, relatively inexpensive and capable of monitoring specific gene regions of complex populations. To this end, we have developed terminal restriction fragment length polymorphism (T-RFLP) to examine changes in gut microbial communities in response to a range of parameters. We have previously used this technique to show a correlation between particular gut microflora profiles and bird performance associated with diet change (Torok et al., 2006). We are presently using this technique to examine the effect of a variety of factors, including age, litter materials and different bacterial load environments, on the development of gut microflora.
II. Material and methods
Total nucleic acid was extracted from chicken gut samples by a modification of a SARDI proprietary extraction method. Tissue, including digesta content, was taken from the indicated gut section from each chicken and the microbial community analysed by T-RFLP. Bacterial ribosomal DNA was amplified with universal 16S bacterial primers, one of which was 5′-labelled with 6-carboxyfluorescein. Amplicons were cut with a four base pair recognition sequence restriction enzyme and separated on a capillary DNA sequencer (ABI 3730, Applied Biosystems). Data were analysed using GeneMapper (Applied Biosystems) to determine positions of terminal restriction fragments (TRF). Prior to statistical analysis the TRF profiles were analysed by a modified method of Dunbar et al. (2001) and resulting TRF treated as operational taxonomic units (OTU).
OTU were analysed using multivariate statistical models (Primer 5, Primer-E Ltd., Plymouth UK).
III. Results and discussion
a) Influence of environment on gut microflora immediately post-hatch
Gut microbial communities were analysed from the caeca of three broiler chicks each aged 2-7 days which were raised either in a low pathogen load isolator or under conventional poultry shed conditions post-hatch (Figure 1). Birds were hatched under identical conditions and fed identical diets. Significant differences in the overall microbial communities between environmental treatments were observed (P<0.05). No significant differences where detected in gut microbial community composition between birds of different ages in the same environment, although the small sample size (n=3) used may have prevented detection of a significant effect of age.
b) Influence of litter on gut microflora
Gut microbial communities were analysed from the caeca of 12 broiler chickens each raised on seven different litter materials including: softwood sawdust; softwood shavings; hardwood sawdust; shredded paper; chopped straw; rice hulls; and single-batch reused litter based on softwood shavings.
Birds were placed on litter materials at day one of age and fed identical diets. Gut samples were collected for microbial profiling at 14 and 28 days of age. Significant differences (P<0.001) in caecal microbial community composition were detected between birds aged 14 and 28 days, regardless of litter material used.
Significant differences were observed in caecal microbial community composition of day 14 old birds raised on re-used litter when compared with the six other litter materials used (P<0.001). There were also differences in caecal microbial community composition of day 14 old birds raised on rice hulls when compared with softwood sawdust, hardwood sawdust and shredded paper (P<0.05), and between hardwood sawdust when compared with softwood sawdust and shredded paper (P<0.05).
Significant differences were also observed in caecal microbial community composition of day 28 old birds raised on re-used litter when compared with softwood sawdust, hardwood sawdust, shredded paper, rice hulls and chopped straw (P<0.05), but not with softwood shavings. There were also differences in caecal microbial community composition of day 28 old birds raised on rice hulls when compared with shredded paper and chopped straw (P<0.05). No significant differences were detected in gut microbial community composition between birds on any of the other litter treatments.
Differences observed in gut microbial community composition between birds raised on re-used litter as opposed to non re-used litter materials may be partly due to re-used litter acting as a bacterial inoculum for gut microflora establishment, particularly in the younger birds.
c) Influence of age on gut microflora
Gut microbial communities were analysed from the caeca of birds from two flocks raised under commercial poultry conditions in South Australia. Over a single growing period samples from 12 birds each aged 1 to 6 weeks were analysed per flock (Figure 2). Significant differences in the overall gut microbial communities of birds aged 1, 2, 3-5 and 6 weeks were observed (P<0.05). No significant differences were detected in gut microbial community composition between ages 3-5 weeks. The same trend was observed on two commercial farms, even though overall chicken caecal microbial communities were significantly different between the two flocks (P<0.05).
IV. Conclusion
T-RFLP has been used to monitor shifts in the chicken gut microbial population associated with environmental and age changes. We have shown that gut microbial community composition changes greatly within the first 2-3 weeks of age before stabilising until age 5-6 weeks, when a final change in community composition was observed. Although previous studies have shown the composition of the gut microflora can vary with age (Knarreborg et al., 2002; Lu et al., 2003), this is the first report which follows the succession of gut microflora over a six week period within a commercial production setting, and is not dependant on generation of bacterial sequence information for identifying differences in microbial community composition.
Litter material has also been shown to influence development of gut microbial community composition and has confirmed age related changes when comparing birds aged 2 and 4 weeks old. Furthermore, environmental conditions have been shown to affect caecal microbial community development within the first week. This has previously been shown to be a crucial period for gut development and mucin production, which is linked to intestinal bacterial populations.
The results indicate that the T-RFLP tool has the potential to contribute significantly to an increased knowledge of the chicken gut microbiota, and hence, a better understanding in its role in chicken nutrition.
Acknowledgements
Dr Valeria Torok is supported by the Australian Poultry CRC. Ms Rebecca Forder and Ms Moreen Ali are Australian Poultry CRC supported postgraduate students.
References
Bedford, M.R. and Apajalahti, J. (2001). Enzymes in Farm Animal Nutrition. Eds M.R. Bedford and G.G. Partridge. CABI Publishing, Wallingford.
Choct, M., Hughes, R.J., Wang, J., Bedford, M.R., Morgan, A.J. and Annison, G. (1996). British Poultry Science, 37: 609-621.
Dunbar, J., Ticknor, L.O. and Kuske, C.R. (2001) Applied and Environmental Microbiology, 67: 190- 197.
Grimes, J.L., Carter, T.A., and Godwin, J.L. (2006). Poultry Science, 85:563-568.
Klasing, K.C., Johnstone, B.K. and Benson, B.N. (1999). Recent Developments in Poultry Nutrition.
2. Eds P.C. Garnsworthy and J. Wiseman. Nottingham University Press, Nottingham.
Knarreborg, A., Simon, M.A., Engberg, R.M., Jensen, B.B. and Tannock, G.W. (2002). Applied and environmental Microbiology, 68: 5918-5924.
Lu, J., Idris, U., Harmon, B., Hofacre, C., Maurer, J.J and Lee, M.D. (2003). Applied and environmental Microbiology, 69: 6816-6824.
Smits, H.M., Veldman, A. Verstegen, M.W.A. and Beynen, A.C. (1997). Journal of Nutrition, 127: 483-487.
Smirnov, A., Perez, R., Amit-Romach, E., Sklan, D., and Uni, Z. (2005). Journal of Nutrition, 135:187-192.
Smirnov, A., Tako, E., Ferket, P.R., and Uni, Z. (2006). Poultry Science, 85:669-673.
Steenfeldt, S., Knudsen, K.E.B. Borsting, C.F. and Eggum, B.O. (1995). Animal Feed Science and Technology, 54: 249-265.
Torok, V.A., Ophel-Keller, K. and Hughes, R.J. (2006). Australasian Poultry Science Symposium 2006 Abstract Book, pp 43-46.
Van Leeuwen, P., Mouwen, J.M.V.M., Van der Klis, J.D. and Verstegen, M.W.A. (2004). British Poultry Science, 45: 41-48.
From Proceedings of "19th Australian Poultry Science Symposium", New South Wales, Australia.
