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Poultry is the main source of meat production worldwide. The respiratory microbiota of chickens plays a critical role in avian health and disease prevention. To better understand its composition and dynamics, we conducted a comprehensive meta-analysis focusing on factors such as age, breed, SPF status, and respiratory organs. We collected 16S rRNA data from 13 different studies available on NCBI’s PubMed and Scopus, including data on the nasal cavity, trachea, and lungs from healthy chickens. All the data were processed using QIIME2 and then analysed together. Metadata from each study was completed and standardized to ensure consistency. Our analysis revealed distinct spatial dynamics and composition gradients across the respiratory organs, with the nasal cavity exhibiting the highest bacterial diversity. Firmicutes and Proteobacteria dominated the respiratory tract, with age-related shifts in their relative abundance. These phyla exhibited competitive interactions. Firmicutes colonization started early in the nasal cavity, progressing to the trachea and lungs, while Proteobacteria followed an opposite pattern. Significant compositional changes occurred after four weeks of age, likely driven by immune system maturation, coinciding with a peak in alpha diversity. Both SPF status and breed influenced microbiota’s composition and diversity, with clear patterns observed across the respiratory organs. Overall, the chicken respiratory microbiota demonstrated spatial and temporal dynamics influenced by age, respiratory organ connectivity, breed and SPF status. Important changes occur in the composition and diversity of the chicken respiratory microbiota after four weeks of age, probably driven by immune system maturation. The existence of gradients between the different respiratory organs shapes the composition and beta diversity of the chicken respiratory microbiota. Firmicutes and Proteobacteria may have antagonistic or competitive interactions as they follow opposite patterns during chicken’s life. Understanding these dynamics is pivotal for developing effective respiratory disease management strategies.
Moreno-León et al. (Wed,) studied this question.