Molecular Characterization and Significance of Salt‐Tolerant Alkaliphilic Actinomycetes of the Saline Habitats of Mithapur, Coastal Gujarat, India
Bibliographic record
Abstract
Soil salinization and alkalinization threaten agriculture and microbial diversity, driving the need for salt-tolerant and alkaliphilic microorganisms in biotechnology. The present study aimed to isolate, characterize, and assess the molecular diversity of such actinomycetes from coastal Gujarat, India, to identify candidates for biotechnological applications. Eight salt-tolerant and alkaliphilic actinomycetes were isolated from Mithapur, Gujarat (India), and confirmed to grow at 5% salt and pH 9. Their colony characteristics, in situ growth, biochemical properties, and antibiotic susceptibility were examined. To extend the study further, the genomic DNA was extracted from the cell mass to assess the molecular diversity of the actinobacteria. The quality, purity, and yield of the extracted DNA were assessed by spectroscopic analysis and agarose gel electrophoresis. The 16S rRNA genes were then amplified using five different primer sets, including two universal (U1 and U2), two Streptomyces-specific (StrepB/StrepE and StrepB/StrepF), and one Nesterenkonia-specific (NF/R) primer set. The varying number of isolates yielded expected amplicons with U1 (1500 bp), U2 (1000 bp), StrepB/StrepE (500 bp), StrepB/StrepF (1170 bp), and NF/R (1120 bp) primer sets. DGGE with the amplified 16S rRNA gene was used as a fingerprinting tool to further differentiate the actinomycetes and assess their molecular diversity, highlighting their potential for bioremediation, agriculture, and biotechnology.
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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 | 0.000 | 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".