Characterization of Potential Virulence, Resistance to Antibiotics and Heavy Metals, and Biofilm-Forming Capabilities of Soil Lignocellulolytic Bacteria
Bibliographic record
Abstract
Soil bacteria participate in self-immobilization processes for survival, persistence, and production of virulence factors in some niches or hosts through their capacities for autoaggregation, cell surface hydrophobicity, biofilm formation, and antibiotic and heavy metal resistance. This study investigated potential virulence, antibiotic and heavy metal resistance, solvent adhesion, and biofilm-forming capabilities of six cellulolytic bacteria isolated from soil samples: Paenarthrobacter sp. MKAL1, Hymenobacter sp. MKAL2, Mycobacterium sp. MKAL3, Stenotrophomonas sp. MKAL4, Chryseobacterium sp. MKAL5, and Bacillus sp. MKAL6. Strains were subjected to phenotypic methods, including heavy metal and antibiotic susceptibility and virulence factors (protease, lipase, capsule production, autoaggregation, hydrophobicity, and biofilm formation). The effect of ciprofloxacin was also investigated on bacterial susceptibility over time, cell membrane, and biofilm formation. Strains MKAL2, MKAL5, and MKAL6 exhibited protease and lipase activities, while only MKAL6 produced capsules. All strains were capable of aggregating, forming biofilm, and adhering to solvents. Strains tolerated high amounts of chromium, lead, zinc, nickel, and manganese and were resistant to lincomycin. Ciprofloxacin exhibited bactericidal activity against these strains. Although the phenotypic evaluation of virulence factors of bacteria can indicate their pathogenic nature, an in-depth genetic study of virulence, antibiotic and heavy metal resistance genes is required.
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.
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 | 0.000 |
| 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 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".