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Record W2110338827 · doi:10.1128/iai.01568-07

<scp>d</scp> -Alanylation of Lipoteichoic Acid Contributes to the Virulence of <i>Streptococcus suis</i>

2008· article· en· W2110338827 on OpenAlexafffund
Nahuel Fittipaldi, Tsutomu Sekizaki, Daisuke Takamatsu, Josée Harel, María de la Cruz Domínguez-Punaro, Sonja von Aulock, Christian Draing, Corinne Marois‐Créhan, Marylène Kobisch, Marcelo Gottschalk

Bibliographic record

VenueInfection and Immunity · 2008
Typearticle
Languageen
FieldMedicine
TopicStreptococcal Infections and Treatments
Canadian institutionsUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of CanadaBeijing Municipal Education CommissionFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsVirulenceStreptococcus suisBiologyMicrobiologyLipoteichoic acidVirulence factorMutantPathogenImmune systemStreptococcaceaeSerotypeBacteriocinVirologyBacteriaAntimicrobialStaphylococcus aureusImmunologyGeneAntibioticsGenetics

Abstract

fetched live from OpenAlex

We generated by allelic replacement a DeltadltA mutant of a virulent Streptococcus suis serotype 2 field strain and evaluated the contribution of lipoteichoic acid (LTA) d-alanylation to the virulence traits of this swine pathogen and zoonotic agent. The absence of LTA D-alanylation resulted in increased susceptibility to the action of cationic antimicrobial peptides. In addition, and in contrast to the wild-type strain, the DeltadltA mutant was efficiently killed by porcine neutrophils and showed diminished adherence to and invasion of porcine brain microvascular endothelial cells. Finally, the DeltadltA mutant was attenuated in both the CD1 mouse and porcine models of infection, probably reflecting a decreased ability to escape immune clearance mechanisms and an impaired capacity to move across host barriers. The results of this study suggest that LTA D-alanylation 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score0.294

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 head0.022
GPT teacher head0.274
Teacher spread0.251 · 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 designObservational
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

Citations110
Published2008
Admission routes2
Has abstractyes

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