Identifying essential genes in <i>Schaalia odontolytica</i> using a saturated transposon library
Bibliographic record
Abstract
ABSTRACT The unique epibiotic-parasitic relationship between Nanosynbacter lyticus type strain TM7x, a member of the newly identified candidate phyla radiation, now referred to as Patescibacteria , and its basibiont, Schaalia odontolytica strain XH001 (formerly Actinomyces odontolyticus ), requires more powerful genetic tools for a deeper understanding of the genetic underpinnings that mediate their obligate relationship. Previous studies have mainly characterized the genomic landscape of XH001 during or post-TM7x infection through comparative genomic or transcriptomic analyses, followed by phenotypic analysis. Comprehensive genetic dissection of the pair is currently cumbersome due to the lack of robust genetic tools in TM7x. However, basic genetic tools are available for XH001, and this study expands the current genetic toolset by developing high-throughput transposon insertion sequencing (Tn-seq). Tn-seq was employed to screen for essential genes in XH001 under laboratory conditions. A highly saturated Tn-seq library was generated with nearly 660,000 unique insertion mutations, averaging one insertion every two–three nucleotides. A total of 203 genes comprising 10.5% of the XH001 genome were identified as putatively essential. IMPORTANCE Schaalia odontolytica strain XH001, an early colonizer of the oral multispecies biofilm (dental plaque), forms a unique epibiotic-parasitic relationship with Nanosynbacter lyticus type strain TM7x, a member of the newly identified Patescibacteria (formerly candidate phyla radiation). Achieving a mechanistic understanding of their relationship requires practical genetic tools for dissecting the roles played by different genetic mediators and shedding light on how their interspecies interaction may affect dynamics in the oral microbiome. In this study, we developed a high-throughput mutagenesis technique, Tn-seq, in XH001. The constructed Tn-seq library enabled the identification of putatively essential genes in XH001, revealing growth requirements under laboratory conditions. This library can be leveraged in future studies to elucidate TM7x’s dependence on XH001 at the molecular level.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".