Metagenomic analysis of isolation methods of a targeted microbe, Campylobacter jejuni, from chicken feces with high microbial contamination
Bibliographic record
Abstract
Originating from poultry, particularly chickens, Campylobacter jejuni is the leading foodborne pathogen worldwide and a major cause of campylobacteriosis. Isolating C. jejuni is difficult due to its specific growth requirements, the presence of viable but non-culturable bacteria, and because it is often masked by competing flora. Currently, there is no optimized method for isolating C. jejuni from chicken feces. Here, we evaluated the method for isolating C. jejuni from chicken feces using culture-independent sequence-based metagenomics and culture-dependent tools. Further, we assessed changes in microbial communities during microbe isolation to determine how the process can be improved. Fourteen different variations of C. jejuni isolation procedures were applied to all 35 chicken fecal samples. These variations included using different enrichment broths (without enrichment or enrichment in Bolton or Preston broth), different ratios of sample-to-enrichment broth (1:10 1 , 1:10 2 , and 1:10 3 ), and different selective agars (modified charcoal-cefoperazone-deoxycholate agar (mCCDA) or Preston agar). Enrichment during isolation of C. jejuni was evaluated on the basis of microbial diversity and taxonomic composition using metagenomics tools. The effect of selective media was evaluated using a combination of metagenomics and culture-dependent tools. Microbial diversity significantly decreased during the enrichment process, regardless of the type of enrichment broth, with the most significant decrease observed at a feces-to-broth ratio of 1:10 3 . Particularly, in 10 3 -Preston broth, the relative abundance of Campylobacter increased, while extended-spectrum beta-lactamase-producing Escherichia coli , which interfere with Campylobacter isolation, decreased. Metagenomics results were validated by quantitative PCR and culture-dependent analysis. Additionally, selective media affected the isolation results, although microbes with high relative abundance during enrichment were also frequently isolated using culture-dependent methods. Significantly more C. jejuni was isolated from mCCDA than from Preston agar enriched in 10 3 Preston broth. Enrichment in Preston broth at a ratio of 1:10 3 followed by spreading onto mCCDA was the most effective method for isolating C. jejuni . This is the first study to apply metagenomics to evaluate a method for isolating a targeted microbe, C. jejuni , from chicken feces, a source with high microbial contamination. Thus, metagenomics can be applied to improve methods for isolating bacteria that are difficult to separate.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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 teacher head, 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".