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A Tale about Shigella: Evolution, Plasmid, and Virulence

2023· review· en· W4382775188 on OpenAlexafffund
Nathaline Haidar-Ahmad, France Ourida Manigat, Navoun Silué, Stéphanie M. Pontier, François‐Xavier Campbell‐Valois

Bibliographic record

VenueMicroorganisms · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEscherichia coli research studies
Canadian institutionsCégep de l'OutaouaisUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchUniversity of Ottawa
KeywordsShigellaBiologyPlasmidVirulenceSecretionGeneGeneticsMicrobiologyType three secretion systemEscherichia coli

Abstract

fetched live from OpenAlex

Shigella spp. cause hundreds of millions of intestinal infections each year. They target the mucosa of the human colon and are an important model of intracellular bacterial pathogenesis. Shigella is a pathovar of Escherichia coli that is characterized by the presence of a large invasion plasmid, pINV, which encodes the characteristic type III secretion system and icsA used for cytosol invasion and cell-to-cell spread, respectively. First, we review recent advances in the genetic aspects of Shigella, shedding light on its evolutionary history within the E. coli lineage and its relationship to the acquisition of pINV. We then discuss recent insights into the processes that allow for the maintenance of pINV. Finally, we describe the role of the transcription activators VirF, VirB, and MxiE in the major virulence gene regulatory cascades that control the expression of the type III secretion system and icsA. This provides an opportunity to examine the interplay between these pINV-encoded transcriptional activators and numerous chromosome-encoded factors that modulate their activity. Finally, we discuss novel chromosomal genes icaR, icaT, and yccE that are regulated by MxiE. This review emphasizes the notion that Shigella and E. coli have walked the fine line between commensalism and pathogenesis for much of their history.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.880
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.030
GPT teacher head0.330
Teacher spread0.299 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations18
Published2023
Admission routes2
Has abstractyes

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