Identification of Antimicrobial Compounds in Two Streptomyces sp. Strains Isolated From Beehives
Bibliographic record
Abstract
The World Health Organization warns that the alarming increase in antibiotic resistant bacteria will lead to 2.7 million deaths annually due to the lack of effective antibiotic therapies. Clearly, there is an urgent need for short-term alternatives that help to alleviate these alarming figures. In this respect, the scientific community is exploring neglected ecological niches from which the prototypical antibiotic-producing bacteria Streptomycetes are expected to be present. Recent studies have reported that honeybees and their products carry Streptomyces species that possess strong antibacterial activity. In this study, we have investigated the antibiotic profile of two Streptomycetes strains that were isolated from beehives. One of the isolates is the strain Streptomyces albus AN1, which derives from pollen, and shows potent antimicrobial activity against Candida albicans . The other isolate is the strain Streptomyces griseoaurantiacus AD2, which was isolated from honey, and displays a broad range of antimicrobial activity against different Gram-positive bacteria, including pathogens such as Staphylococcus aureus and Enterococus faecalis . Cultures of S. griseoaurantiacus AD2 have the capacity to produce the antibacterial compounds undecylprodigiosin and manumycin, while those of S. albus AN1 accumulate antifungal compounds such as candicidins and antimycins. Furthermore, genome and dereplication analyses suggest that the number of putative bioactive metabolites produced by AD2 and AN1 is considerably high, including compounds with anti-microbial and anti-cancer properties. Our results postulate that beehives are a promising source for the discovery of novel bioactive compounds that might be of interest to the agri-food sector and healthcare pharmaceuticals.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".