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Record W3101459439 · doi:10.1101/648865

The <i>Salmonella</i> LysR family regulator, RipR, activates the SPI-13 encoded itaconate degradation cluster

2019· preprint· en· W3101459439 on OpenAlexaff
Steven J. Hersch, William Wiley Navarre

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2019
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVibrio bacteria research studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOperonIsocitrate lyasePhagosomeGlyoxylate cycleBiologyBacterialac operonSalmonellaMetaboliteImmune systemBiochemistryMicrobiologyGeneCell biologyGene expressionEnzymeEscherichia coliIntracellularGenetics

Abstract

fetched live from OpenAlex

Abstract Itaconate is a dicarboxylic acid that inhibits the isocitrate lyase enzyme of the bacterial glyoxylate shunt. Activated macrophages have been shown to produce itaconate, suggesting that these immune cells may employ this metabolite as a weapon against invading bacteria. Here we demonstrate that, in vitro , itaconate can exhibit bactericidal effects under acidic conditions similar to the pH of a macrophage phagosome. In parallel, successful pathogens including Salmonella have acquired a genetic operon encoding itaconate degradation proteins, which are induced heavily in macrophages. We characterize the regulation of this operon by the neighbouring gene, ripR , in specific response to itaconate. Moreover, we develop an itaconate biosensor based on the operon promoter that can detect itaconate in a semi-quantitative manner and, when combined with the ripR gene, is sufficient for itaconate-regulated expression in E. coli . Using this biosensor with fluorescence microscopy, we observe bacteria responding to itaconate in the phagosomes of macrophage and provide additional evidence that interferon-γ stimulates macrophage itaconate synthesis and that J774 mouse macrophages produce substantially more itaconate than the human THP-1 monocyte cell line. In summary, we examine the role of itaconate as an antibacterial metabolite in mouse and human macrophage, characterize the regulation of Salmonella ’s defense against it, and develop it as a convenient itaconate biosensor and inducible promoter system. Importance In response to invading bacteria, immune cells can produce a molecule called itaconate, which can inhibit microbial metabolism. Here we show that itaconate can also directly kill Salmonella when combined with moderate acidity, further supporting itaconate’s role as an antibacterial weapon. We also discover how Salmonella recognizes itaconate and activates a defense to degrade it, and we harness this response to make a biosensor that detects the presence of itaconate. This biosensor is versatile, working in Salmonella enterica or lab strains of Escherichia coli , and can detect itaconate quantitatively in the environment and in immune cells. By understanding how immune cells kill bacteria and how the microbes defend themselves, we can better develop novel antibiotics to inhibit pathogens such as Salmonella .

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 score0.002
Threshold uncertainty score0.006

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)0.0020.001

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 head0.012
GPT teacher head0.228
Teacher spread0.216 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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