Genomic Resource and Genome Guided Comparison of Twenty Type Strains of the Genus Methylobacterium
Bibliographic record
Abstract
Bacteria of the genus Methylobacterium are widespread in diverse habitats ranging from soil, water and plant (phyllosphere, rhizosphere and endosphere). In the present study, we in house generated genomic data resource of six type strains along with fourteen database genomes of the Methylobacterium genus to carry out phylogenomic, taxonomic, comparative and ecological studies of this genus. Overall, the genus shows high diversity and genetic variation primarily due to its ability to acquire genetic material from diverse sources through horizontal gene transfer. As majority of species identified in this study are plant associated with their genomes equipped with methylotrophy and photosynthesis related gene along with genes for plant probiotic traits. Most of the species genomes are equipped with genes for adaptation and defense for UV radiation, oxidative stress and desiccation. The genus has an open pan-genome and we predicted the role of gain/loss of prophages and CRISPR elements in diversity and evolution. Our genomic resource with annotation and analysis provides a platform for interspecies genomic comparisons in the genus Methylobacterium, and to unravel their natural genome diversity and to study how natural selection shapes their genome with the adaptive mechanisms which allow them to acquire diverse habitat lifestyles. This type strains genomic data display power of Next Generation Sequencing in rapidly creating resource paving the way for studies on phylogeny and taxonomy as well as for basic and applied research for this important genus.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".