Identification and Application of Phocaeicola-Specific Conserved Signature DNA Markers for Human Fecal Source Tracking
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A major goal of fecal pollution monitoring in the environment is to identify point sources of fecal contamination that may pose potential health risks due to animal- and human-specific pathogens. Ideal source tracking markers should have high host specificity and can be employed for the unambiguous identification of the host/fecal point sources. Conserved signature proteins (CSPs) are a class of unique, phylogenetically coherent indicators that are specific to a given taxon (e.g., genus or species). In this study, we report the identification and characterization of a new CSP, whose gene (designated as CSP-DV) is present in a single copy, and for whom homologs showing a high degree of sequence similarity are found only in genomes of Phocaeicola dorei and Phocaeicola vulgatus, two commensal species commonly found in the human gut and feces. We developed a qPCR method targeting this CSP gene to explore its usefulness as a human source tracking marker. We confirmed that the CSP-DV marker showed an absolute human sensitivity (100%) but some cross-reactivities in chicken, cats, dogs, rabbits, and rodents. In recreational water, the CSP-DV marker gene levels were well correlated with those of HF183, a well-validated human marker that predominantly targets the 16S rRNA gene of P. dorei, suggesting that it can be a new potential source tracking tool for human fecal contamination in specific environmental waters. In summary, our CSP-DV marker targets Phocaeicola clade-specific microbes and can provide an additional approach independent of the 16S rRNA gene to detect human sources of fecal pollution.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it