Genomic Insights of Antibiotic-Resistant Escherichia coli Isolated from Intensive Pig Farming in South Africa Using ‘Farm-to-Fork’ Approach
Bibliographic record
Abstract
Background/Objectives: Intensive pig farming is a critical component of food security and economic activity in South Africa; however, it also presents a risk of amplifying antimicrobial resistance (AMR). This study provides genomic insights into antibiotic-resistant Escherichia coli (E. coli) circulating across the pork production chain, using a ‘farm-to-fork’ approach. Methods: A total of 417 samples were collected from various points along the production continuum, including the farm (n = 144), transport (n = 60), and abattoir (n = 213). E. coli isolates were identified using the Colilert-18 system, and their phenotypic resistance was tested against 20 antibiotics. Thirty-one isolates were selected for further characterization based on their resistance profiles and sampling sources, utilizing whole-genome sequencing and bioinformatic analysis. Results: The isolates exhibited varying resistance to critical antibiotics used in both human and animal health, including ampicillin (31/31, 100%), tetracycline (31/31, 100%), amoxicillin–clavulanate (29/31, 94%), chloramphenicol (25/31, 81%), and sulfamethoxazole–trimethoprim (10/31, 33%). Genetic analysis revealed the presence of resistance genes for β-lactams (blaEC, blaTEM), trimethoprim/sulfonamides (dfrA1, dfrA5, dfrA12, sul2, sul3), tetracyclines (tetA, tetB, tetR, tet34), aminoglycosides (aadA, strA, aph variants), and phenicols (catB4, floR, cmlA1), most of which were plasmid-borne. Virulome analysis identified 24 genes, including toxins and adhesion factors. Mobile genetic elements included 24 plasmid replicons, 43 prophages, 19 insertion sequence families, and 7 class 1 integrons. The E. coli isolates belonged to a diverse range of sequence types, demonstrating significant genetic variability. Further phylogenomic analysis revealed eight major clades, with isolate clustering by sequence type alongside South African environmental and clinical E. coli strains, regardless of their sampling source. Conclusions: The genetic complexity observed across the pork production continuum threatens food safety and may impact human health. These findings underscore the need for enhanced AMR monitoring in livestock systems and support the integration of AMR surveillance into food safety policy frameworks.
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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 | 0.002 |
| 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".