As mentioned in our previous post, we had the opportunity to work with a few Iowa farms to start to better understand the turkey microbiome. When we first started analyzing litter samples from these turkey houses, we weren't entirely sure what we would see. Would each farm be completely unique? Would bird age or location shape the microbiome more?
The microbiomes, thankfully, were just as talkative as the birds themselves (and if you’ve ever been to a turkey farm, that’s saying alot).
Defining a Healthy Baseline
We found that when turkeys are healthy, microbial ecosystem diversity (i.e., alpha diversity; as seen below in Figure 1) looks remarkably similar across different operations. The most dramatic shifts happen immediately after placement and during early development. Young poults are building their internal ecosystem from scratch, sampling from their environment and establishing the microbial communities that will help them digest feed, resist pathogens, and more.
As birds mature, we see week over week changes (ecosystem stability i.e., beta diversity) in the microbiome begin to lessen over time. Birds of the same age develop similar, consistent microbial communities.
Figure 1: Ecosystem or alpha diversity (calculated via the Simpon’s diversity index) is shown for healthy samples for each customer. Yellow points represent individual samples while the green shaded regions show the overall distribution within each customer. Values range from 0 to 1 with high values indicating high diversity.
When Ecosystems Destabilize
Throughout the course of the sampling certain adverse health events (typically disease challenges as expressed in mortality, symptoms, etc.) occurred, and we saw ecosystem diversity drop - sometimes sharply during these events (see below in Figure 2). In one operation, these drops corresponded with major shifts in non-pathogenic bacteria. The pathogens weren't taking over; the entire ecosystem was being reshuffled, likely from the health event itself or the required antimicrobial treatment. The microbiome tells the story of disturbance, and metagenomics allows us to track whether the microbiome recovers to a healthy place (or not!).
Figure 2: Ecosystem diversity is shown for samples where an adverse health reaction was reported (unhealthy) vs. not reported (healthy). Diversity drops during certain reported health events.
Distinct Microbiome Signatures
Even though there are similar patterns in turkey microbiome development, we also observe that each flock still maintains its own distinct microbiome fingerprint. Each barn has its own microbial personality - this has implications for things like potential management strategies, treatment decisions, and more. Each barn is unique, and deserves to be managed as such.
Figure 3: Average distribution of antimicrobial and disinfectant classes across all customers. Metagenomic data allows us to look beyond who is there to what they are capable of doing.
As part of understanding the unique facets of each barn, we are starting to detect antimicrobial resistance (AMR) genes and virulence factors in the microbiome (see Figure 3). These genes indicate potential capabilities of a microbial community, not active disease. We might detect tetracycline resistance or toxin genes when no birds are sick or being treated, but it tells us about the genetic reservoir on a farm: what capabilities exist if selection pressure shifts the community composition. There is still more work to do here, but this data shows a promising start.
What the Data Means
These patterns - ecosystem diversity in health, stability by age and house, unique barn microbial footprints, disturbance during disease events, and genetic potential in resistance and virulence factor genes - give us a baseline picture for understanding of the ‘normal’ state.
By establishing a normal baseline, we unlock the ability to spot abnormal early and offer insights on how to optimize performance.
We're still learning what the turkey microbiome can tell us, but the data from Iowa shows consistent patterns worth tracking and makes us excited about the future. More to come as we dig deeper into what these patterns mean for on-farm decision making.
