Intestinal Microbiota and Species Diversity of <i>Campylobacter</i> and <i>Helicobacter</i> spp. in Migrating Shorebirds in Delaware Bay
Bibliographic record
Abstract
Using 16S rRNA gene sequencing analysis, we examined the bacterial diversity and the presence of opportunistic bacterial pathogens (i.e., Campylobacter and Helicobacter) in red knot (Calidris canutus; n = 40), ruddy turnstone (Arenaria interpres; n = 35), and semipalmated sandpiper (Calidris pusilla; n = 22) fecal samples collected during a migratory stopover in Delaware Bay. Additionally, we studied the occurrence of Campylobacter spp., enterococci, and waterfowl fecal source markers using quantitative PCR (qPCR) assays. Of 3,889 16S rRNA clone sequences analyzed, the bacterial community was mostly composed of Bacilli (63.5%), Fusobacteria (12.7%), Epsilonproteobacteria (6.5%), and Clostridia (5.8%). When epsilonproteobacterium-specific 23S rRNA gene clone libraries (i.e., 1,414 sequences) were analyzed, the sequences were identified as Campylobacter (82.3%) or Helicobacter (17.7%) spp. Specifically, 38.4%, 10.1%, and 26.0% of clone sequences were identified as C. lari (>99% sequence identity) in ruddy turnstone, red knot, and semipalmated sandpiper clone libraries, respectively. Other pathogenic species of Campylobacter, such as C. jejuni and C. coli, were not detected in excreta of any of the three bird species. Most Helicobacter-like sequences identified were closely related to H. pametensis (>99% sequence identity) and H. anseris (92% sequence identity). qPCR results showed that the occurrence and abundance of Campylobacter spp. was relatively high compared to those of fecal indicator bacteria, such as Enterococcus spp., E. faecalis, and Catellicoccus marimammalium. Overall, the results provide insights into the complexity of the shorebird gut microbial community and suggest that these migratory birds are important reservoirs of pathogenic Campylobacter species.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".