Analysis of genetic variability within the Beijing lineage of «Mycobacterium tuberculosis»
Bibliographic record
Abstract
Previous research has demonstrated that the DosR/DosS two-component signaling system is constitutively overexpressed in modern Beijing strains of Mycobacterium tuberculosis (M. tb). It is hypothesized that constitutive overexpression of this regulatory system is related to the unique pathogenic properties reported for this important strain lineage. Within this thesis we attempted to determine the cause of this overexpression phenotype. We first compared known DosR signaling stimuli between different strains of M. tb, looking specifically at NO (nitric oxide) and redox (reduction-oxidation) balance. We demonstrated that there was no difference in endogenous NO production between strains, but we showed that there was a significantly more reductive NADH/NAD pool in modern Beijing strains. To determine the specific factor responsible, we transformed four independent strains of M. tb with a DosR-dependent XylE reporter and developed a novel colony-screening assay to determine DosR activity. We then performed whole-genome transposon mutagenesis to screen for genes that are potentially able to modify DosR expression and/or activity. After screening ~80,000 transductants, we identified 49 genes that appear to influence reporter activity. Surprisingly, when analyzed by qRT-PCR, we were not able to demonstrate a modulation in dosR expression for any of these putative candidates, which suggested that expression of our reporter was being modified in a DosR-independent manner. Further analysis has revealed that many candidate genes directly affect the activity of the reporter protein by modulating H2O2 levels within the bacteria. Intriguingly, this lead us to the observation that modern Beijing strains have elevated catalase activity compared to other strains of M. tb. This work further characterizes the unique properties of the Beijing lineage of M. tb and identifies a novel phenotype that may be associated with its pathogenesis.
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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 | 0.000 | 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".