Bioplastic reservoir of diverse bacterial communities revealed along altitude gradient of Pangi-Chamba trans-Himalayan region
Bibliographic record
Abstract
Himalaya hosts a unique environment for microbial ecology. The present study aimed to explore the bioplastic producing bacterial communities along altitude gradient of Pangi-Chamba trans-Himalayan region. A total of 411 bacteria were isolated and 70 characterized at the molecular level for potential polyhydroxyalkanoates (PHA) producers. The most abundant phylum for PHA synthesis was Proteobacteria (73%), followed by Actinobacteria (11%), Firmicutes (10%) and Bacteroidetes (6%). However, at the genus level, Pseudomonas and Janthinobacterium were dominantly reported. Also, the ability to synthesize PHA was reported for the first time for few genera such as Collimonas, Pseudarthrobacter and Paenarthrobacter. Phylogenetic analysis of partial 16S rDNA and phaC genes revealed conservation in phaC and possibility of horizontal gene transfer among distant taxa. Furthermore, GC-MS also confirmed the ability of potential bacterial isolates to synthesize PHA. In fact, we found that PHA-positive bacteria are dominant in the high altitude of Himalaya, suggesting the vital role of PHA in bacterial adaptation and survival. Together, these findings had revealed the rich bacterial diversity and genetic machinery for PHA synthesis which does have potential for further utilization in the commercial applications.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".