Structural analysis and immunostimulatory potency of lipoteichoic acids isolated from three Streptococcus suis serotype 2 strains
Bibliographic record
Abstract
Whitfield Streptococcus suis serotype 2 is an important porcine and human pathogen.Lipoteichoic acid (LTA) from S. suis has been suggested to contribute to its virulence, and absence of D-alany- lation from the S. suis LTA is associated with increased susceptibility to cationic antimicrobial peptides.Here, using high-resolution NMR spectroscopy and MS analyses, we characterized the LTA structures from three S. suis serotype 2 strains differing in virulence, sequence type (ST), and geographical origin.Our analyses revealed that these strains possess-in addition to the typical type I LTA present in other streptococci-a second, mixed-type series of LTA molecules of high complexity.We observed a ST-specific difference in the incorporation of glycosyl residues into these mixed-type LTAs.We found that strains P1/7 (ST1, high virulence) and SC84 (ST7, very high virulence) can attach a 1,2-linked ␣-D-Glcp residue as branching substituent to an ␣-D-Glcp that is 1,3-linked to glycerol phosphate moieties and that is not present in strain 89-1591 (ST25, intermediate virulence).In contrast, the latter strain could glycosylate its LTA at the glycerol O-2 position, which was not observed in the other two strains.Using LTA preparations from WT strains and from mutants with an inactivated prolipoprotein diacylglyceryl transferase, resulting in deficient lipoprotein acylation, we show that S. suis LTAs alone do not induce Toll-like receptor 2-dependent pro-inflammatory mediator production from dendritic cells.In summary, our study reveals an unexpected complexity of LTAs present in three S. suis serotype 2 strains differing in genetic background and virulence.The authors declare that they have no conflicts of interest with the contents of this article.This article contains Figs.S1-S9 and Tables S1-S9.
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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 | 0.000 | 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 | 0.000 |
| 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 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".