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Significant contribution of the <i>pgdA</i> gene to the virulence of <i>Streptococcus suis</i>

2008· article· en· W2005563340 on OpenAlexaff
Nahuel Fittipaldi, Tsutomu Sekizaki, Daisuke Takamatsu, María de la Cruz Domínguez-Punaro, Josée Harel, Nhat Khai Bui, Waldemar Vollmer, Marcelo Gottschalk

Bibliographic record

VenueMolecular Microbiology · 2008
Typearticle
Languageen
FieldMedicine
TopicStreptococcal Infections and Treatments
Canadian institutionsUniversité de MontréalCegep de Saint Hyacinthe
FundersJoint Genome InstituteWellcome Trust
KeywordsStreptococcus suisBiologyVirulenceMicrobiologyMutantLysozymePathogenVirulence factorGeneIn vitroPeptidoglycanBacteriaGenetics

Abstract

fetched live from OpenAlex

Streptococcus suis is a major swine pathogen and emerging zoonotic agent. In this study we have determined the muropeptide composition of S. suis peptidoglycan (PG) and found, among other modifications, N-deacetylated compounds. Comparison with an isogenic mutant showed that the product of the pgdA gene is responsible for this specific modification which occurred in very low amounts. Low level of PG N-deacetylation correlated with absence of significant lysozyme resistance when wild-type S. suis was grown in vitro. On the other hand, expression of the pgdA gene was increased upon interaction of the bacterium with neutrophils in vitro as well as in vivo in experimentally inoculated mice, suggesting that S. suis may enhance PG N-deacetylation under these conditions. Evaluation of the DeltapgdA mutant in both the CD1 murine and the porcine models of infection revealed a significant contribution of the pgdA gene to the virulence traits of S. suis. Reflecting a severe impairment in its ability to persist in blood and decreased ability to escape immune clearance mechanisms mediated by neutrophils, the DeltapgdA mutant was highly attenuated in both models. The results of this study suggest that modification of PG by N-deacetylation is an important factor in S. suis virulence.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.253

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.235
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations120
Published2008
Admission routes1
Has abstractyes

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