Antibiotic resistomes and microbial communities in biosolid fertilizers collected from two Canadian wastewater treatment plants in a 10-years interval-potential risks to food chains?
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
Dissemination of microorganisms with antimicrobial resistance genes (ARGs) through the food chain has been recognized as a growing public health concern worldwide. Biosolids, a product of wastewater treatment process, have been used as fertilizers in agriculture globally and have also been considered as a potential source of pathogens and ARGs for horizontal transfer across various environments. This study characterized antibiotic resistomes and microbiota in 24 biosolids samples collected from two Canadian waste water treatment plants in different cities in 2009 and 2019. The ARGs were detected using a qPCR array kit, and microbiota was analyzed using 16S ribosomal RNA gene amplicon sequencing. Furthermore, correlation analysis of ARG abundance and bacterial genera abundance was explored to predict potential hosts of ARGs. Seventy-one of 84 ARGs were detected in at least one or more samples with 12 ARGs being detected in all samples. Antibiotic resistomes did not show a statistically significant distinction between different collection years, sites, or year and site combined in principle coordinate analysis. The microbiota communities were significantly different between samples collected in different years, sites, or year and site combined. In total 34 phyla were detected with 13 genera among the top three phyla were typically related to the human gut microbiota and seven of them showing strong correlation with ARGs related to aminoglycoside and beta-lactam resistance. This study provides valuable baseline information and consistent trend on ARGs and bacterial communities in biosolid fertilizers in Canada, indicating that the biosolid fertilizer could potentially be a source of ARGs in the agricultural soils and may leading to potential contamination of plant-based food chains.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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