A Consistent and Predictable Commercial Broiler Chicken Bacterial Microbiota in Antibiotic-Free Production Displays Strong Correlations with Performance

Abstract

Defining the baseline bacterial microbiome is critical to understanding its relationship with health and disease. In broiler chickens, the core microbiome and its possible relationships with health and disease have been difficult to define, due to high variability between birds and flocks. Presented here are data from a large, comprehensive microbiota-based study in commercial broilers. The primary goals of this study included understanding what constitutes the core bacterial microbiota in the broiler gastrointestinal, respiratory, and barn environments; how these core players change across age, geography, and time; and which bacterial taxa correlate with enhanced bird performance in antibiotic-free flocks. Using 2,309 samples from 37 different commercial flocks within a vertically integrated broiler system and metadata from these and an additional 512 flocks within that system, the baseline bacterial microbiota was defined using 16S rRNA gene sequencing. The effects of age, sample type, flock, and successive flock cycles were compared, and results indicate a consistent, predictable, age-dependent bacterial microbiota, irrespective of flock. The tracheal bacterial microbiota of broilers was comprehensively defined, and Lactobacillus was the dominant bacterial taxon in the trachea. Numerous bacterial taxa were identified, which were strongly correlated with broiler chicken performance across multiple tissues. While many positively correlated taxa were identified, negatively associated potential pathogens were also identified in the absence of clinical disease, indicating that subclinical dynamics occur that impact performance. Overall, this work provides necessary baseline data for the development of effective antibiotic alternatives, such as probiotics, for sustainable poultry production.IMPORTANCE Multidrug-resistant bacterial pathogens are perhaps the greatest medical challenge we will face in the 21st century and beyond. Antibiotics are necessary in animal production to treat disease. As such, animal production is a contributor to the problem of antibiotic resistance. Efforts are underway to reduce antibiotic use in animal production. However, we are also challenged to feed the world's increasing population, and sustainable meat production is paramount to providing a safe and quality protein source for human consumption. In the absence of antibiotics, alternative approaches are needed to maintain health and prevent disease, and probiotics have great promise as one such approach. This work paves the way for the development of alternative approaches to raising poultry by increasing our understandings of what defines the poultry microbiome and of how it can potentially be modulated to improve animal health and performance.

Keywords: antibiotic free; broilers; chickens; microbiome; performance; poultry.

FIG 1

Sampling strategy. A total of 29 barns carrying 37 flocks were sampled, and each icon represents a barn within a farm. A total of 12 flocks were sampled by following four barns longitudinally for three grow-out cycles, and 10 birds per flock and per time point were sampled (left). A total of 25 random flocks of different ages were sampled in a cross-sectional fashion using six birds per flock (right). Each flock sampled came from a geographically distinct farm within a single vertically integrated broiler company.

FIG 2

Principal-coordinate analysis of samples using unweighted UniFrac measures of beta diversity. Samples are colored by sample type.

FIG 3

Core OTUs of the broiler microbiota. Classification of OTUs identified as core (present in >90% of samples) was performed by sample type and bird age. Gold indicates core taxa, and maroon indicates noncore taxa. Names listed more than once (e.g., L. aviarius) represent multiple OTUs classified as that taxon.

FIG 4

Effects of successive flock cycles on the broiler microbiota. Principal-coordinate analysis of samples was performed using unweighted UniFrac measures of beta diversity. Samples are colored by flock cycle (C).

FIG 5

Correlations between broiler weight and its cecal microbiota. Principal-coordinate analysis of cecum samples from flock cycles 1 and 2 was performed. Samples are colored by total body weight and scaled to minimum and maximum weights for each sampling age. Sample shapes represent the four different flocks (F) sampled during each flock cycle.

FIG 6

Individual bird weights in flock cycles 1 and 2 by age. Weights are displayed in grams. Error bars depict standard deviations.

FIG 7

Genus-level taxa in the ileum and cecum correlated with broiler weight. Positively associated taxa (P < 0.05) are colored shades of yellow-green, with numbers indicating Spearman's correlation, while negatively associated taxa are colored shades of orange-red. Gray indicates a nonsignificant value.

FIG 8

Genus-level taxa in the trachea correlated with broiler weight. Positively associated taxa (P < 0.05) are colored shades of yellow-green with a number indicating Spearman's correlation, while negatively associated taxa are colored shades of orange-red. Gray indicates a nonsignificant value.

FIG 9

Cooccurring potential pathogens in the trachea of 7-day-old broilers. Each stacked bar depicts an individual bird, and bars are ordered by total bird weight.

FIG 10

Dominant bacterial taxa in the broiler chicken trachea. The top 50 most abundant genus-level taxa across all tracheal samples (top to bottom) are displayed in a log₂-normalized heat map. Classifications are displayed to the right, with colors indicating a bacterial class that occurs more than once. Gray indicates a bacterial class that occurs only once.

FIG 11

Ecology of lactobacilli differs in the broiler chicken ileum and trachea. Proportions of normalized counts of the top seven OTUs classified as Lactobacillus are displayed across day of age (D) and flock cycle (C).