Synthetic polyprenol-pyrophosphate linked oligosaccharides are efficient substrates for mycobacterial galactan biosynthetic enzymes
Bibliographic record
Abstract
Mycobacteria, including the human pathogen Mycobacterium tuberculosis, produce a complex cell wall that is critical for their survival. The largest structural component of the cell wall, the mycolyl-arabinogalactan-peptidoglycan complex, has at its core a galactan domain composed of d-galactofuranose residues. Mycobacterial galactan biosynthesis has been proposed to involve two glycosyltransferases, GlfT1 and GlfT2, which elongate polyprenol-pyrophosphate linked glycosyl acceptor substrates using UDP-galactofuranose as the donor substrate. We here report the first chemical synthesis of GlfT1 and GlfT2 acceptor substrates containing pyrophosphate and polyprenol moieties (compounds 3, 4, 22 and 23). The approach involves chemical synthesis of an oligosaccharide, subsequent phosphorylation at the reducing end and coupling to a polyprenol phosphate. These compounds were shown to be substrates for either GlfT1 (22 and 23) or GlfT2 (3 and 4) and all were substantially more active than the corresponding alkyl glycoside substrates reported previously. Mass spectrometric analysis of the products formed from the reaction of 3, 4, 22 and 23 with the respective cognate enzyme and UDP-galactofuranose provide additional evidence for the galactan biosynthetic model in which GlfT1 adds the first two galactofuranose residues with the remainder being installed via GlfT2. Overall, these results highlight the importance of the pyrophosphate motif in recognition of acceptor substrates by both enzymes and demonstrate a straightforward route for the preparation of such compounds. The work also provides additional support for the process by which this important glycan is biosynthesized using, for the first time, close structural analogs to the natural substrates.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".