Discovery of the Polyketide Lagriamide B by Integrated Genome Mining, Isotopic Labeling, and Untargeted Metabolomics
Bibliographic record
Abstract
Microorganisms from the order Burkholderiales have been the source of a number of important classes of natural products in recent years. For example, study of the beetle-associated symbiont Burkholderia gladioli led to the discovery of the antifungal polyketide lagriamide; an important molecule from the perspectives of both biotechnology and chemical ecology. As part of a wider project to sequence Burkholderiales genomes from our in-house Burkholderiales library we identified a strain containing a biosynthetic gene cluster (BGC) similar to the original lagriamide BGC. Structure prediction failed to identify any candidate masses for the products of this BGC from untargeted metabolomics mass spectrometry data. However, genome mining from publicly available databases identified fragments of this BGC from a culture collection strain of Paraburkholderia. Whole genome sequencing of this strain revealed the presence of a homologue of this BGC with very high sequence identity. Stable isotope feeding of the two strains in parallel using our newly developed IsoAnalyst platform identified the product of this lagriamide-like BGC directly from the crude fermentation extracts, affording a culturable supply of this important class of antifungal agents. Using a combination of bioinformatic, computational and spectroscopic methods we defined the absolute configurations for all 11 chiral centers in this new metabolite, which we named lagriamide B. Biological testing of lagriamide B against a panel of 21 bacterial and fungal pathogens revealed selective antifungal activity against the opportunistic human pathogen Aspergillus niger.
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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) | 0.001 | 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 | 0.001 |
| 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".