Characterization of Actinobacterial Communities from Arauca River Sediments (Colombia) Reveals Antimicrobial Potential Presented in Low Abundant Isolates
Bibliographic record
Abstract
Introduction: New strategies have been arisen to set a rapid and effective screening for selection of microorganism with bioactive potential. This study suggests that combination of physicochemical pretreatments and taxonomic dereplication of microbial collections through MALDI-TOF MS, facilitates the detection of low abundance actinobacteria with potential as a source of antimicrobial agents. Material and Methods: An unstudied microbial community from a tropical river sediment in Colombian Orinoquía is described, applying an extended cultivation strategy using physicochemical pretreatments, biological screenings and taxonomic dereplication through MALDI-TOF MS approach. Results: Actinobacteria-like isolates (790) were growth and their antimicrobial activity was assessed against methicillin-resistant Staphylococcus aureus , Vancomycin-resistant Enterococcus faecium , extended-spectrum β-lactamase Klebsiella pnumoniae , and clinical isolates of Cladosporium cladosporioides and Epicoccum nigrum. Seventy-eight isolates, belonging to the Streptomycetaceae family according to 16S rDNA analysis were found to have antimicrobial activity and were categorized as low abundance actinobacteria by MALDI-TOF MS. Conclusion: The results suggest that combination of physicochemical pretreatments and taxonomic dereplication of microbial collections through MALDI-TOF MS, facilitates the detection of low abundance actinobacteria with potential as a source of antimicrobial agents.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".