The phylogenetic and global distribution of bacterial polyhydroxyalkanoate bioplastic‐degrading genes
Bibliographic record
Abstract
Polyhydroxyalkanoates (PHAs) are a family of microbially made polyesters commercialized as biodegradable plastics. PHA production rates are predicted to increase as concerns around environmental plastic contamination and limited fossil fuel resources have increased the importance of biodegradable and bio-based plastic alternatives. Microbially produced PHA depolymerases are the key enzymes mediating PHA biodegradation, but only a few PHA depolymerases have been well-characterized and screens employing metagenomic sequence data are lacking. Here, we used 3078 metagenomes to analyse the distribution of PHA depolymerases in microbial communities from diverse aquatic, terrestrial and waste management systems. We significantly expand the recognized diversity of this protein family by screening 1914 Gb of sequence data and identifying 13 869 putative PHA depolymerases in 1295 metagenomes. Our results indicate that PHA depolymerases are unevenly distributed across environments. We predicted the highest frequency of PHA depolymerases in wastewater systems and the lowest in marine and thermal springs. In tandem, we screened 5290 metagenome-assembled genomes to describe the phylogenetic distribution of PHA depolymerases, which is substantially broader compared with current cultured representatives. The Proteobacteria and Bacteroidota are key lineages encoding PHA depolymerases, but PHA depolymerases were predicted from members of the Bdellovibrionota, Methylomirabilota, Actinobacteriota, Firmicutes, Spirochaetota, Desulfobacterota, Myxococcota and Planctomycetota.
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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".