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Record W3172207088 · doi:10.1101/2021.06.16.448779

Bacterial factors drive the differential targeting of Guanylate Binding Proteins to <i>Francisella</i> and <i>Shigella</i>

2021· preprint· en· W3172207088 on OpenAlexaff
Stanimira Valeva, Fanny Michal, Manon Degabriel, John R. Rohde, Felix Randow, Robert K. Ernst, Brice Lagrange, Thomas Henry

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2021
Typepreprint
Languageen
FieldImmunology and Microbiology
TopicImmune Response and Inflammation
Canadian institutionsDalhousie University
Fundersnot available
KeywordsBiologyFrancisellaShigella flexneriShigellaFrancisella tularensisCell biologyMicrobiologyBacteriaGeneticsEscherichia coliSalmonella

Abstract

fetched live from OpenAlex

ABSTRACT Guanylate-Binding Proteins (GBPs) are interferon-inducible GTPases that play a key role in cell autonomous responses against intracellular pathogens. Seven GBPs are present in humans. Despite sharing high sequence similarity, subtle differences among GBPs translate into functional divergences that are still largely not understood. A key step for the antimicrobial activity of GBPs towards cytosolic bacteria is the formation of supramolecular GBP complexes on the bacterial surface. Such complexes are formed when GBP1 binds lipopolysaccharide (LPS) from Shigella and Salmonella and further recruits GBP2, 3, and 4. Here, we investigated GBPs recruitment on Francisella novicida , a professional cytosol-dwelling pathogen with an atypical tetra-acylated LPS. Co-infection experiments demonstrated that GBPs target preferentially S. flexneri compared to F. novicida . F. novicida was coated by GBP1 and GBP2 in human macrophages but escaped targeting by GBP3 and GBP4. GBP1 and GBP2 features that drive recruitment to F. novicida were investigated revealing that GBP1 GDPase activity is required to initiate GBP recruitment to F. novicida but facultative to target S. flexneri . Furthermore, analysis of chimeric GBP2/5 proteins identified a central domain in GBP2 necessary and sufficient to target F. novicida. Finally, a F. novicida Δ lpxF mutant with a penta-acylated lipid A was targeted by GBP3 suggesting that lipid A tetra-acylation contributes to escape from GBP3. Altogether our results indicate that GBPs have different affinity for different bacteria and that the repertoire of GBPs recruited onto cytosolic bacteria is dictated by GBP-intrinsic features and specific bacterial factors, including the structure of the lipid A. IMPORTANCE Few bacteria have adapted to thrive in the hostile environment of the cell cytosol. As a professional cytosol-dwelling pathogen, S. flexneri secretes several effectors to block cytosolic immune effectors, including GBPs. This study illustrates a different approach of adapting to the host cytosol: the stealth strategy developed by F. novicida . F. novicida bears an atypical hypoacylated LPS, which does not elicit neither TLR4 nor caspase-11 activation. Here, this atypical LPS was shown to promote escape from GBP3 targeting. Furthermore, the lower affinity of GBPs for F. novicida allowed to decipher the different domains that govern GBP recruitment to the bacterial surface. This study illustrates the importance of investigating different bacterial models to broaden our understanding of the intricacies of host-pathogen interactions.

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 score0.003

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)0.0010.000

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 head0.008
GPT teacher head0.195
Teacher spread0.187 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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