The Wall Teichoic Acid Polymerase TagF Is Non-processive in Vitro and Amenable to Study Using Steady State Kinetic Analysis
Bibliographic record
Abstract
Wall teichoic acids are a chemically diverse group of anionic polymers that constitute up to 50% of the Gram-positive cell wall. These polymers play a pivotal role in virulence and have been implicated in a diverse range of physiological functions. The TagF-like family of enzymes has been shown to be responsible for wall teichoic acid priming and polymerization events. Although many such enzymes are well validated therapeutic targets, a mechanistic understanding of this enzyme family has remained elusive. TagF is the prototypical teichoic acid polymerase and uses CDP-glycerol to catalyze synthesis of the linear (1,3)-linked poly(glycerol phosphate) teichoic acid in Bacillus subtilis 168. Here we used a synthetic soluble analog of the natural substrate of the enzyme, Lipid , to conduct the first detailed mechanistic investigation of teichoic acid polymerization. Through the use of a new high pressure liquid chromatography-based assay to monitor single glycerol phosphate incorporations into the Lipid analog, we conducted a detailed analysis of reaction product formation patterns and unequivocally showed TagF to be non-processive in vitro. Furthermore by monitoring the kinetics of polymerization, we showed that Lipid analog species varying in size have the same K(m) value of 2.6 microm and validated use of Bi Bi velocity expressions to model the TagF enzyme system. Initial rate analysis showed that TagF catalyzes a sequential Bi Bi mechanism where both substrates are added to the enzyme prior to product release consistent with a single displacement chemical mechanism.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".