Antibiotic resistance genes detected in lichens: insights from <i>Cladonia stellaris</i>
Bibliographic record
Abstract
BACKGROUND AND AIMS: Antibiotics are natural compounds produced by microorganisms that have long existed in ecosystems. However, the widespread clinical and agricultural use of antibiotics has intensified selective pressures on bacteria, leading to the proliferation of antibiotic resistance genes (ARGs). The increasing prevalence of these genetic elements in clinical and environmental settings now poses a major global health threat. While ARGs are well documented in anthropogenically influenced environments, their distribution and origins in remote ecosystems, such as boreal forests, remain poorly understood. Here, we investigate the occurrence, diversity and potential origins of ARGs in the boreal lichen Cladonia stellaris. METHODS: We conducted the first targeted assessment of ARGs in lichens by analysing 42 C. stellaris samples from northern and southern lichen woodlands in eastern Canada. Using high-throughput quantitative PCR, we screened for 33 ARGs and three mobile genetic elements (MGEs), quantifying their relative abundance. Bacterial community composition was characterized via 16S rRNA gene sequencing. Statistical analyses evaluated geographical patterns, co-occurrence between ARGs and bacterial taxa, and the influence of latitude on ARG distribution. KEY RESULTS: Ten ARGs conferring resistance to four antibiotic classes (aminoglycosides, beta-lactams, quinolones and sulfonamides), along with one MGE, were detected. The ARGs blaCTX-M-1, qnrB and qepA were highly prevalent, with qepA often surpassing 16S rRNA gene abundance. Only qnrB showed significantly higher abundance in southern samples. Latitude significantly influenced ARG profiles, whereas bacterial community composition did not. CONCLUSIONS: Our findings demonstrate that C. stellaris harbours diverse ARGs in remote boreal ecosystems with limited anthropogenic influence. Proposed explanations for ARG presence include long-distance dispersal via bioaerosols and endogenous development within lichen microbiomes, yet these remain speculative. Future work incorporating bacterial isolation, whole-genome sequencing, metatranscriptomics, air sampling and metabolomic profiling is necessary to unravel the ecology and evolution of ARGs in natural habitats.
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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) | 0.000 | 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 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".