Cellular adaptation and the importance of the purine biosynthesis pathway during biofilm formation in Gram-positive pathogens
Bibliographic record
Abstract
Abstract Bacterial biofilms are involved in chronic infections and confer 10 to 1000 times more resistance to antibiotics, leading to treatment failure and complications. When transitioning from a planktonic lifestyle to biofilms, certain Gram-positive bacteria are likely to modulate several cellular pathways including central carbon metabolism, primary biosynthesis pathways and production of secondary metabolites. These metabolic adaptations might play a crucial role in biofilm formation by Gram-positive pathogens such as Staphylococcus aureus and Enterococcus faecalis . Here, we performed a transcriptomic approach to identify cellular pathways that might be similarly regulated during biofilm formation in these bacteria. Different strains and biofilm-inducing media were used to identify a set of regulated genes that are common and independent of the environment or accessory genomes analysed. The gene set enrichment analysis of the transcriptome of four different strains of Gram-positive bacteria identified biosynthesis of secondary metabolites, biosynthesis of antibiotics and purine biosynthesis as three commonly upregulated pathways in biofilm. Our approach did not highlight downregulated pathways during biofilm formation that were common to S. aureus and E. faecalis . Of the three upregulated pathways, the de novo IMP biosynthesis pathway constitutes a promising target of cellular adaptation during biofilm formation. Gene deletions in this pathway, particularly purN, purL, purQ, purH and purM significantly impaired biofilm formation of S. aureus . Importance Biofilms are often involved in nosocomial infections and can cause serious chronic infections if not treated properly. Current anti-biofilm strategies rely on antibiotic usage, but they have a limited impact because of the biofilm’s intrinsic resistance to drugs. Metabolism remodelling likely plays a central role during biofilm formation, but it is still unclear if these cellular adaptations are shared between strains and species. Using comparative transcriptomics of different strains of Staphylococcus aureus and Enterococcus faecalis , we identified a core of commonly regulated genes during biofilm formation. Interestingly, we observed that the de novo IMP biosynthesis was systematically upregulated during biofilm formation. This pathway could constitute an interesting new anti-biofilm target to increase the host spectrum, drug efficiency and prevent resistance evolution. These results are also relevant to a better understanding of biofilm physiology.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".