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To address the need for sensitive high-throughput assays to analyse avian innate and adaptive immune responses, we developed and validated a highly multiplexed qPCR 96.96 Fluidigm Dynamic Array to analyse the transcription of chicken immune-related genes. This microfluidic system permits the simultaneous analysis of expression of 96 transcripts in 96 samples in 6 nanolitre reactions and the 9,216 reactions are ready for interpretation immediately. A panel of 89 genes was selected from an RNA-seq analysis of the transcriptional response of chicken macrophages, dendritic cells and heterophils to agonists of innate immunity and from published transcriptome data. Assays were confirmed to be highly specific by amplicon sequencing and melting curve analysis and the reverse transcription and preamplification steps were optimised. The array was applied to RNA of various tissues from a commercial line of broiler chickens housed at two different levels of biosecurity. Gut-associated lymphoid tissues, bursa, spleen and peripheral blood leukocytes were isolated and transcript levels for immune-related genes were defined. The results identified blood cells as a potentially reliable indicator of immune responses among all the tissues tested with the highest number of genes significantly differentially transcribed between birds housed under varying biosecurity levels. Conventional qPCR analysis of three differentially transcribed genes confirmed the results from the multiplex qPCR array. A highly multiplexed qPCR-based platform for evaluation of chicken immune responses has been optimised and validated using samples from commercial chickens. Apart from applications in selective breeding programmes, the array could be used to analyse the complex interplay between the avian immune system and pathogens by including pathogen-specific probes, to screen vaccine responses, and as a predictive tool for immune robustness.

In this era of next generation sequencing technologies it is now possible to characterise the chicken respiratory microbiota without the biases inherent to traditional culturing techniques. However, little research has been performed in this area. In this study we characterise and compare buccal, nasal and lung microbiota samples from chickens in three different age groups using 16S rRNA gene analysis. Buccal and nasal swabs were taken from birds aged 2 days (n = 5), 3 weeks (n = 5) and 30 months (n = 6). Bronchoalveolar lavage (BAL) samples were also collected alongside reagent only controls. DNA was extracted from these samples and the V2-V3 region of the 16S rRNA gene was amplified and sequenced. Quality control and OTU clustering were performed in mothur. Bacterial DNA was quantified using qPCR, amplifying the V3 region of the 16S rRNA gene. We found significant differences between the quantity and types of bacteria sampled at the three different respiratory sites. We also found significant differences in the composition, richness and diversity of the bacterial communities in buccal, nasal and BAL fluid samples between age groups. We identified several bacteria which had previously been isolated from the chicken respiratory tract in culture based studies, including lactobacilli and staphylococci. However, we also identified bacteria which have not previously been cultured from the respiratory tract of the healthy chicken. We conclude that our study can be used as a baseline that future chicken respiratory microbiota studies can build upon.

Current avian influenza surveillance in poultry primarily targets subtypes of interest for the veterinary sector (H5, H7). However, as virological and serological evidence suggest, surveillance of additional subtypes is important for public health as well as for the poultry industry. Therefore, we developed a protein microarray enabling simultaneous identification of antibodies directed against different HA-types of influenza A viruses in chickens. The assay successfully discriminated negative from experimentally and naturally infected, seropositive chickens. Sensitivity and specificity depended on the cut-off level used but ranged from 84.4% to 100% and 100%, respectively, for a cut off level of ≥ 1:40, showing minimal cross reactivity. As this testing platform is also validated for the use in humans, it constitutes a surveillance tool that can be applied in human-animal interface studies.

Avian influenza virus (AIV) infection is a continuing threat to both humans and poultry. Influenza virus specific CD8+ T cells are associated with protection against homologous and heterologous influenza strains. In contrast to what has been described for humans and mice, knowledge on epitope-specific CD8+ T cells in chickens is limited. Therefore, we set out to identify AIV-specific CD8+ T-cell epitopes. Epitope predictions based on anchor residues resulted in 33 candidate epitopes. MHC I inbred chickens were infected with a low pathogenic AIV strain and sacrificed at 5, 7, 10 and 14 days post infection (dpi). Lymphocytes isolated from lung, spleen and blood were stimulated ex vivo with AIV-specific pooled or individual peptides and the production of IFNγ was determined by ELIspot. This resulted in the identification of 12 MHC B12-restricted, 3 B4-restricted and 1 B19-restricted AIV- specific CD8+ T-cell epitopes. In conclusion, we have identified novel AIV-derived CD8+ T-cell epitopes for several inbred chicken strains. This knowledge can be used to study the role of CD8+ T cells against AIV infection in a natural host for influenza, and may be important for vaccine development.