Rearing environment affects development of the immune system in neonates.

Early-life exposure to appropriate microbial flora drives expansion and development of an efficient immune system. Aberrant development results in increased likelihood of allergic disease or increased susceptibility to infection. Thus, factors affecting microbial colonization may also affect the direction of immune responses in later life. There is a need for a manipulable animal model of environmental influences on the development of microbiota and the immune system during early life. We assessed the effects of rearing under low- (farm, sow) and high-hygiene (isolator, milk formula) conditions on intestinal microbiota and immune development in neonatal piglets, because they can be removed from the mother in the first 24 h for rearing under controlled conditions and, due to placental structure, neither antibody nor antigen is transferred in utero. Microbiota in both groups was similar between 2 and 5 days. However, by 12-28 days, piglets reared on the mother had more diverse flora than siblings reared in isolators. Dendritic cells accumulated in the intestinal mucosa in both groups, but more rapidly in isolator piglets. Importantly, the minority of 2-5-day-old farm piglets whose microbiota resembled that of an older (12-28-day-old) pig also accumulated dendritic cells earlier than the other farm-reared piglets. Consistent with dendritic cell control of T cell function, the effects on T cells occurred at later time-points, and mucosal T cells from high-hygiene, isolator pigs made less interleukin (IL)-4 while systemic T cells made more IL-2. Neonatal piglets may be a valuable model for studies of the effects of interaction between microbiota and immune development on allergy.

Validation of computer-assisted, pixel-based analysis of multiple-colour immunofluorescence histology.

Developments in immunohistology allow the routine simultaneous use on tissue sections of three monoclonal antibodies, tagged with different fluorochromes. Such staining can identify seven different cell populations and the limiting factor is rapid, reliable and reproducible analysis. Future reliance on computer-assisted analysis of digitised images depends on validation against manual counting, often viewed as the 'gold standard'. In this study images were digitised from sections of normal porcine skin, inflamed skin and tonsil, simultaneously stained with three monoclonal antibodies. Combinations of staining were quantified by four manual counts and by pixel-based area measurement. On individual images, the correlation between automated and manual measurements was poor. Despite this, the concordance between manual and automated measurements in the means and variances of tissues was good, and both techniques identified the same changes in inflamed versus normal tissues. In addition, pixel-based counting permitted statistical analysis of co-localisation of cell types in tissue sections. We conclude that automated counting is acceptable for the assessment of tissues, is faster and provides less opportunity for observer variation than manual counting. We also demonstrate that the technique is applicable where more than three fluorochromes are used such that manual counting becomes essentially impossible.