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Surface-Expressed Mig Protein Protects<i>Streptococcus dysgalactiae</i>against Phagocytosis by Bovine Neutrophils

2001· article· en· W2141376616 on OpenAlexafffund
Xin-Ming Song, José Perez‐Casal, Alexandra Bolton, Andrew Potter

Bibliographic record

VenueInfection and Immunity · 2001
Typearticle
Languageen
FieldMedicine
TopicStreptococcal Infections and Treatments
Canadian institutionsCanadian Bio-Systems (Canada)
FundersNatural Sciences and Engineering Research Council of CanadaMinistry of Agriculture - Saskatchewan
KeywordsStreptococcus dysgalactiaeBiologyMicrobiologyPhagocytosisVirulenceMutantMolecular biologyEscherichia coliMutagenesisGeneStreptococcus agalactiaeBacteriaStreptococcusBiochemistryGenetics

Abstract

fetched live from OpenAlex

The mig gene of Streptococcus dysgalactiae, a major bovine mastitis pathogen, encodes two plasma protein-binding receptors, alpha2-macroglobulin (alpha2-M) and immunoglobulin G (IgG). In this study, the mig gene from one S. dysgalactiae isolate was cloned and expressed in Escherichia coli. The IgG receptor region encoded by mig was conserved in 16 S. dysgalactiae strains. An isogenic mig mutant was constructed by allele replacement mutagenesis of the wild-type gene in S. dysgalactiae. The IgG-binding activity was lost in the mig mutant strain, whereas the alpha2-M receptor activity was still expressed but was detected only in the culture supernatant. In flow cytometry phagocytosis and bacterial-colony-counting bactericidal assays, the wild-type strain was found to be significantly more resistant to phagocytosis and killing by bovine neutrophils (PMNs) than the mig mutant strain when bacteria were preincubated with bovine serum. We therefore speculate that the Mig protein of S. dysgalactiae plays a role in virulence of the bacteria by binding to the plasma protein alpha2-M or IgG and thus preventing phagocytosis by bovine PMNs.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 head0.020
GPT teacher head0.275
Teacher spread0.255 · 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 source (direct Gemma or distilled Codex), 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

Citations23
Published2001
Admission routes2
Has abstractyes

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