Insights into Interactions of Mycobacteria with the Host Innate Immune System from a Novel Array of Synthetic Mycobacterial Glycans
Bibliographic record
Abstract
An array of homogeneous glycans representing all the major carbohydrate structures present in the cell wall of the human pathogen Mycobacterium tuberculosis and other mycobacteria has been probed with a panel of glycan-binding receptors expressed on cells of the mammalian innate immune system. The results provide an overview of interactions between mycobacterial glycans and receptors that mediate uptake and survival in macrophages, dendritic cells, and sinusoidal endothelial cells. A subset of the wide variety of glycan structures present on mycobacterial surfaces interact with cells of the innate immune system through the receptors tested. Endocytic receptors, including the mannose receptor, DC-SIGN, langerin, and DC-SIGNR (L-SIGN), interact predominantly with mannose-containing caps found on the mycobacterial polysaccharide lipoarabinomannan. Some of these receptors also interact with phosphatidyl-myo-inositol mannosides and mannose-containing phenolic glycolipids. Many glycans are ligands for overlapping sets of receptors, suggesting multiple, redundant routes by which mycobacteria can enter cells. Receptors with signaling capability interact with two distinct sets of mycobacterial glycans: targets for dectin-2 overlap with ligands for the mannose-binding endocytic receptors, while mincle binds exclusively to trehalose-containing structures such as trehalose dimycolate. None of the receptors surveyed bind furanose residues, which often form part of the epitopes recognized by antibodies to mycobacteria. Thus, the innate and adaptive immune systems can target different sets of mycobacterial glycans. This array, the first of its kind, represents an important new tool for probing, at a molecular level, biological roles of a broad range of mycobacterial glycans, a task that has not previously been possible.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".