Lack of consistency in poultry dust microbial taxa associated with high and low-performing commercial broiler flocks

Abstract

The microbial communities of the gastrointestinal tract play an essential role in poultry health and productivity. Poultry dust has been used to investigate bacterial taxa associated with performance in commercial broiler farms. This study investigated the commonalities of poultry dust microbial taxa associated with performance in samples collected from three broiler integrator companies and their stability in a successive flock of the same companies using deep sequencing of the 16S rRNA gene. Poultry dust samples (n = 248) were collected on days 14 and 35 of the production cycle from 38 commercial broiler flocks (2 flocks from each of 19 farms). The farms were ranked as low or high performers based on the feed conversion ratio corrected for body weight. Permutational analysis of variance based on Bray-Curtis index using abundance data for bacterial community structure results showed that company explained the most variation in the bacterial community structure (7.5 %), followed by bird age (2 %) and the least variation was explained by performance (1.9 %), with significant interactions among these factors (P < 0.001). No bacterial taxa in high or low-performing farms overlapped in all three companies or successive flocks from the same company. Some taxa associated with high performance in a company were associated with low performance in another company (e.g., Bifidobacterium), corroborating other studies highlighting the lack of universal microbial markers of productivity. In conclusion, there were no consistent microbial taxa across companies and flocks within a company under the conditions of this study.

Keywords: 16S sequencing; Broiler; Environment; Microbiota; Population-level monitoring.

Fig. 1

Taxonomic assignment of the bacteria at genus level in dust stratified by bird age (A), company (B) and performance (C). The levels of the top 10 most abundant genera are shown. Genera not included under the top 10 most abundant ones were merged and presented as ‘Others’.

Fig. 2

Principal coordinate analysis based on the Bray-Curtis index of the bacteria community between companies. Company A (red), B (green) and C (blue).

Fig. 3

Alpha diversity using Chao1 and Shannon indices in dust samples stratified by company (A, B), bird age (C, D), and performance (E, F), respectively. The asterisk indicates statistical significance between groups connected by a line. *denotes a 0.01 < P < 0.05; and ** denotes P < 0.01.

Fig. 4

Taxonomic assignment of the top 10 most abundant bacteria at genus level in dust for companies A (A), B (B) and C (C) sampled at 14 and 35 days of age. The genera not included under the top 10 most abundant ones were merged and presented as ‘Others’.

Fig. 5

Linear discriminant analysis (LDA) plots displaying differences in dust microbiota at genus level between low and high performance in company A (A), B (B) and C (C), and UpSet plot displaying the number of distinct and shared genera among groups (D). A genus with a positive LDA score indicates more abundance in the low-performance compared to high-performance farms.

Fig. 6

Longitudinal changes in dust microbiota at genus level within farms of the same company in samples at 14 and 35 of the grow out period collected one year apart (cycle 1 and cycle 2) in company A (A) and company B (B), stratified by flock performance (low and high). Cycle 2 high-performance farms for company B is not depicted due to the low number of samples collected at this point.